Search results for: validation of ontology mapping

Authors: Eliska Smidova, Petr Kabele

Abstract:

This paper describes non-linear finite element simulation of laminated veneer lumber (LVL) under tensile and shear loads that induce cracking along fibers. For this purpose, we use 2D homogeneous orthotropic constitutive model of tensile and shear fracture in timber that has been recently developed and implemented into ATENA® finite element software by the authors. The model captures (i) material orthotropy for small deformations in both linear and non-linear range, (ii) elastic behavior until anisotropic failure criterion is fulfilled, (iii) inelastic behavior after failure criterion is satisfied, (iv) different post-failure response for cracks along and across the grain, (v) unloading/reloading behavior. The post-cracking response is treated by fixed smeared crack model where Reinhardt-Hordijk function is used. The model requires in total 14 input parameters that can be obtained from standard tests, off-axis test results and iterative numerical simulation of compact tension (CT) or compact tension-shear (CTS) test. New engineered timber composites, such as laminated veneer lumber (LVL), offer improved structural parameters compared to sawn timber. LVL is manufactured by laminating 3 mm thick wood veneers aligned in one direction using water-resistant adhesives (e.g. polyurethane). Thus, 3 main grain directions, namely longitudinal (L), tangential (T), and radial (R), are observed within the layered LVL product. The core of this work consists in 3 numerical simulations of experiments where Radiata Pine LVL and Yellow Poplar LVL were involved. The first analysis deals with calibration and validation of the proposed model through off-axis tensile test (at a load-grain angle of 0°, 10°, 45°, and 90°) and CTS test (at a load-grain angle of 30°, 60°, and 90°), both of which were conducted for Radiata Pine LVL. The second finite element simulation reproduces load-CMOD curve of compact tension (CT) test of Yellow Poplar with the aim of obtaining cohesive law parameters to be used as an input in the third finite element analysis. That is four point bending test of small-size arch of 780 mm span that is made of Yellow Poplar LVL. The arch is designed with a through crack between two middle layers in the crown. Curved laminated beams are exposed to high radial tensile stress compared to timber strength in radial tension in the crown area. Let us note that in this case the latter parameter stands for tensile strength in perpendicular direction with respect to the grain. Standard tests deliver most of the relevant input data whereas traction-separation law for crack along the grain can be obtained partly by inverse analysis of compact tension (CT) test or compact tension-shear test (CTS). The initial crack was modeled as a narrow gap separating two layers in the middle the arch crown. Calculated load-deflection curve is in good agreement with the experimental ones. Furthermore, crack pattern given by numerical simulation coincides with the most important observed crack paths.

Keywords: compact tension (CT) test, compact tension shear (CTS) test, fixed smeared crack model, four point bending test, laminated arch, laminated veneer lumber LVL, off-axis test, orthotropic elasticity, orthotropic fracture criterion, Radiata Pine LVL, traction-separation law, yellow poplar LVL, 2D constitutive model

Procedia PDF Downloads 255

Authors: Kavitha Madhu, Karthik K. Srinivasan, R. Sivanandan

Abstract:

Indian traffic can be considered as mixed and heterogeneous due to the presence of various types of vehicles that operate with weak lane discipline. Consequently, vehicles can position themselves anywhere in the traffic stream depending on availability of gaps. The choice of lateral positioning is an important component in representing and characterizing mixed traffic. The field data provides evidence that the trajectory of vehicles in Indian urban roads have significantly varying longitudinal and lateral components. Further, the notion of headway which is widely used for homogeneous traffic simulation is not well defined in conditions lacking lane discipline. From field data it is clear that following is not strict as in homogeneous and lane disciplined conditions and neighbouring vehicles ahead of a given vehicle and those adjacent to it could also influence the subject vehicles choice of position, speed and acceleration. Given these empirical features, the suitability of using headway distributions to characterize mixed traffic in Indian cities is questionable, and needs to be modified appropriately. To address these issues, this paper attempts to analyze the time gap distribution between consecutive vehicles (in a time-sense) crossing a section of roadway. More specifically, to characterize the complex interactions noted above, the influence of composition, manoeuvre types, and lateral placement characteristics on time gap distribution is quantified in this paper. The developed model is used for evaluating various performance measures such as link speed, midblock delay and intersection delay which further helps to characterise the vehicular fuel consumption and emission on urban roads of India. Identifying and analyzing exact interactions between various classes of vehicles in the traffic stream is essential for increasing the accuracy and realism of microscopic traffic flow modelling. In this regard, this study aims to develop and analyze time gap distribution models and quantify it by lead lag pair, manoeuvre type and lateral position characteristics in heterogeneous non-lane based traffic. Once the modelling scheme is developed, this can be used for estimating the vehicle kilometres travelled for the entire traffic system which helps to determine the vehicular fuel consumption and emission. The approach to this objective involves: data collection, statistical modelling and parameter estimation, simulation using calibrated time-gap distribution and its validation, empirical analysis of simulation result and associated traffic flow parameters, and application to analyze illustrative traffic policies. In particular, video graphic methods are used for data extraction from urban mid-block sections in Chennai, where the data comprises of vehicle type, vehicle position (both longitudinal and lateral), speed and time gap. Statistical tests are carried out to compare the simulated data with the actual data and the model performance is evaluated. The effect of integration of above mentioned factors in vehicle generation is studied by comparing the performance measures like density, speed, flow, capacity, area occupancy etc under various traffic conditions and policies. The implications of the quantified distributions and simulation model for estimating the PCU (Passenger Car Units), capacity and level of service of the system are also discussed.

Keywords: lateral movement, mixed traffic condition, simulation modeling, vehicle following models

Procedia PDF Downloads 318

Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

Abstract:

Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of variety of bacterial infection. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. In present study, analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F, and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin.According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Plasmaviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients.

Keywords: acinetobacter baumannii, extremely drug- resistant, phage therapy, surgery wound

Procedia PDF Downloads 55

Authors: K. Ghosh, S. N. Tripathi, Manish Joshi, Y. S. Mayya, Arshad Khan, B. K. Sapra

Abstract:

We have developed a CFD coupled aerosol microphysics model in the context of aerosol generation from a glowing wire. The governing equations can be solved implicitly for mass, momentum, energy transfer along with aerosol dynamics. The computationally efficient framework can simulate temporal behavior of total number concentration and number size distribution. This formulation uniquely couples standard K-Epsilon scheme with boundary layer model with detailed aerosol dynamics through residence time. This model uses measured temperatures (wire surface and axial/radial surroundings) and wire compositional data apart from other usual inputs for simulations. The model predictions show that bulk fluid motion and local heat distribution can significantly affect the aerosol behavior when the buoyancy effect in momentum transfer is considered. Buoyancy generated turbulence was found to be affecting parameters related to aerosol dynamics and transport as well. The model was validated by comparing simulated predictions with results obtained from six controlled experiments performed with a laboratory-made hot wire nanoparticle generator. Condensation particle counter (CPC) and scanning mobility particle sizer (SMPS) were used for measurement of total number concentration and number size distribution at the outlet of reactor cell during these experiments. Our model-predicted results were found to be in reasonable agreement with observed values. The developed model is fast (fully implicit) and numerically stable. It can be used specifically for applications in the context of the behavior of aerosol particles generated from glowing wire technique and in general for other similar large scale domains. Incorporation of CFD in aerosol microphysics framework provides a realistic platform to study natural convection driven systems/ applications. Aerosol dynamics sub-modules (nucleation, coagulation, wall deposition) have been coupled with Navier Stokes equations modified to include buoyancy coupled K-Epsilon turbulence model. Coupled flow-aerosol dynamics equation was solved numerically and in the implicit scheme. Wire composition and temperature (wire surface and cell domain) were obtained/measured, to be used as input for the model simulations. Model simulations showed a significant effect of fluid properties on the dynamics of aerosol particles. The role of buoyancy was highlighted by observation and interpretation of nucleation zones in the planes above the wire axis. The model was validated against measured temporal evolution, total number concentration and size distribution at the outlet of hot wire generator cell. Experimentally averaged and simulated total number concentrations were found to match closely, barring values at initial times. Steady-state number size distribution matched very well for sub 10 nm particle diameters while reasonable differences were noticed for higher size ranges. Although tuned specifically for the present context (i.e., aerosol generation from hotwire generator), the model can also be used for diverse applications, e.g., emission of particles from hot zones (chimneys, exhaust), fires and atmospheric cloud dynamics.

Keywords: nanoparticles, k-epsilon model, buoyancy, CFD, hot wire generator, aerosol dynamics

Procedia PDF Downloads 112

Authors: Ririh Rahma Ratinghayu, Jayu Pramudya, Nur Aini Masruroh, Shi-Woei Lin

Abstract:

This research studies pricing strategy in cooperative setting of hotel duopoly selling perishable product under fixed capacity constraint by using the perspective of managers. In hotel revenue management, competitor’s average room rate and occupancy rate should be taken into manager’s consideration in determining pricing strategy to generate optimum revenue. This information is not provided by business intelligence or available in competitor’s website. Thus, Information Sharing (IS) among players might result in improved performance of pricing strategy. IS is widely adopted in the logistics industry, but IS within hospitality industry has not been well-studied. This research put IS as one of cooperative game schemes, besides Mutual Price Setting (MPS) scheme. In off-peak season, hotel manager arranges pricing strategy to offer promotion package and various kinds of discounts up to 60% of full-price to attract customers. Competitor selling homogenous product will react the same, then triggers a price war. Price war which generates lower revenue may be avoided by creating collaboration in pricing strategy to optimize payoff for both players. In MPS cooperative game, players collaborate to set a room rate applied for both players. Cooperative game may avoid unfavorable players’ payoff caused by price war. Researches on horizontal cooperative game in logistics show better performance and payoff for the players, however, horizontal cooperative game in hotel revenue management has not been demonstrated. This paper aims to develop hotel revenue management models under duopoly cooperative schemes (IS & MPS), which are compared to models under non-cooperative scheme too. Each scheme has five models, Capacity Allocation Model; Demand Model; Revenue Model; Optimal Price Model; and Equilibrium Price Model. Capacity Allocation Model and Demand Model employs self-hotel and competitor’s full and discount price as predictors under non-linear relation. Optimal price is obtained by assuming revenue maximization motive. Equilibrium price is observed by interacting self-hotel’s and competitor’s optimal price under reaction equation. Equilibrium is analyzed using game theory approach. The sequence applies for three schemes. MPS Scheme differently aims to optimize total players’ payoff. The case study in which theoretical models are applied observes two hotels offering homogenous product in Indonesia during a year. The Capacity Allocation, Demand, and Revenue Models are built using multiple regression and statistically tested for validation. Case study data confirms that price behaves within demand model in a non-linear manner. IS Models can represent the actual demand and revenue data better than Non-IS Models. Furthermore, IS enables hotels to earn significantly higher revenue. Thus, duopoly hotel players in general, might have reasonable incentives to share information horizontally. During off-peak season, MPS Models are able to predict the optimal equal price for both hotels. However, Nash equilibrium may not always exist depending on actual payoff of adhering or betraying mutual agreement. To optimize performance, horizontal cooperative game may be chosen over non-cooperative game. Mathematical models can be used to detect collusion among business players. Empirical testing can be used as policy input for market regulator in preventing unethical business practices potentially harming society welfare.

Keywords: horizontal cooperative game theory, hotel revenue management, information sharing, mutual price setting

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Authors: Sylvie Michel, François Cocula

Abstract:

Digital agriculture is an approach that exploits information and communication technologies. These encompass data acquisition tools like mobile applications, satellites, sensors, connected devices, and smartphones. Additionally, it involves transfer and storage technologies such as 3G/4G coverage, low-bandwidth terrestrial or satellite networks, and cloud-based systems. Furthermore, embedded or remote processing technologies, including drones and robots for process automation, along with high-speed communication networks accessible through supercomputers, are integral components of this approach. While farm-level adoption studies regarding digital agricultural technologies have emerged in recent years, they remain relatively limited in comparison to other agricultural practices. To bridge this gap, this study delves into understanding farmers' intention to adopt digital tools, employing the technology, organization, environment framework. A qualitative research design encompassed semi-structured interviews, totaling fifteen in number, conducted with key stakeholders both prior to and following the 2020-2021 COVID-19 lockdowns in France. Subsequently, the interview transcripts underwent thorough thematic content analysis, and the data and verbatim were triangulated for validation. A coding process aimed to systematically organize the data, ensuring an orderly and structured classification. Our research extends its contribution by delineating sub-dimensions within each primary dimension. A total of nine sub-dimensions were identified, categorized as follows: perceived usefulness for communication, perceived usefulness for productivity, and perceived ease of use constitute the first dimension; technological resources, financial resources, and human capabilities constitute the second dimension, while market pressure, institutional pressure, and the COVID-19 situation constitute the third dimension. Furthermore, this analysis enriches the TOE framework by incorporating entrepreneurial orientation as a moderating variable. Managerial orientation emerges as a pivotal factor influencing adoption intention, with producers acknowledging the significance of utilizing digital sales support tools to combat "greenwashing" and elevate their overall brand image. Specifically, it illustrates that producers recognize the potential of digital tools in time-saving and streamlining sales processes, leading to heightened productivity. Moreover, it highlights that the intent to adopt digital sales support tools is influenced by a market mimicry effect. Additionally, it demonstrates a negative association between the intent to adopt these tools and the pressure exerted by institutional partners. Finally, this research establishes a positive link between the intent to adopt digital sales support tools and economic fluctuations, notably during the COVID-19 pandemic. The adoption of sales support tools in agriculture is a multifaceted challenge encompassing three dimensions and nine sub-dimensions. The research delves into the adoption of digital farming technologies at the farm level through the TOE framework. This analysis provides significant insights beneficial for policymakers, stakeholders, and farmers. These insights are instrumental in making informed decisions to facilitate a successful digital transition in agriculture, effectively addressing sector-specific challenges.

Keywords: adoption, digital agriculture, e-commerce, TOE framework

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Authors: Carolyn Hatch, Laurent Simon

Abstract:

Urban mobility and the transportation industry are undergoing a transformation, shifting from an auto production-consumption model that has dominated since the early 20th century towards new forms of personal and shared multi-modality [1]. This is shaped by key forces such as climate change, which has induced a shift in production and consumption patterns and efforts to decarbonize and improve transport services through, for instance, the integration of vehicle automation, electrification and mobility sharing [2]. Advanced innovation practices and platforms for experimentation and validation of new mobility products and services that are increasingly complex and multi-stakeholder-oriented are shaping this new world of mobility. Transportation hubs – such as airports - are emblematic of these disruptive forces playing out in the mobility industry. Airports are emerging as the core of innovation ecosystems on and around contemporary mobility issues, and increasingly recognized as complex public/private nodes operating in many societal dimensions [3,4]. These include urban development, sustainability transitions, digital experimentation, customer experience, infrastructure development and data exploitation (for instance, airports generate massive and often untapped data flows, with significant potential for use, commercialization and social benefit). Yet airport innovation practices have not been well documented in the innovation literature. This paper addresses this gap by proposing a model of airport innovation that aims to equip airport stakeholders to respond to these new and complex innovation needs in practice. The methodology involves: 1 – a literature review bringing together key research and theory on airport innovation management, open innovation and innovation ecosystems in order to evaluate airport practices through an innovation lens; 2 – an international benchmarking of leading airports and their innovation practices, including such examples as Aéroports de Paris, Schipol in Amsterdam, Changi in Singapore, and others; and 3 – semi-structured interviews with airport managers on key aspects of organizational practice, facilitated through a close partnership with the Airport Council International (ACI), a major stakeholder in this research project. Preliminary results find that the most successful airports are those that have shifted to a multi-stakeholder, platform ecosystem model of innovation. The recent entrance of new actors in airports (Google, Amazon, Accor, Vinci, Airbnb and others) have forced the opening of organizational boundaries to share and exchange knowledge with a broader set of ecosystem players. This has also led to new forms of governance and intermediation by airport actors to connect complex, highly distributed knowledge, along with new kinds of inter-organizational collaboration, co-creation and collective ideation processes. Leading airports in the case study have demonstrated a unique capacity to force traditionally siloed activities to “think together”, “explore together” and “act together”, to share data, contribute expertise and pioneer new governance approaches and collaborative practices. In so doing, they have successfully integrated these many disruptive change pathways and forced their implementation and coordination towards innovative mobility outcomes, with positive societal, environmental and economic impacts. This research has implications for: 1 - innovation theory, 2 - urban and transport policy, and 3 - organizational practice - within the mobility industry and across the economy.

Keywords: airport management, ecosystem, innovation, mobility, platform, transport hubs

Procedia PDF Downloads 153

Authors: Chung-Ming Lo, Chung-Chien Lee

Abstract:

In many countries, the lifetime prevalence of shoulder pain is up to 70%. In America, the health care system spends 7 billion per year about the healthy issues of shoulder pain. With respect to the origin, up to 70% of shoulder pain is attributed to rotator cuff lesions This study proposed a computer-aided diagnosis (CAD) system to assist radiologists classifying rotator cuff lesions with less operator dependence. Quantitative features were extracted from the shoulder ultrasound images acquired using an ALOKA alpha-6 US scanner (Hitachi-Aloka Medical, Tokyo, Japan) with linear array probe (scan width: 36mm) ranging from 5 to 13 MHz. During examination, the postures of the examined patients are standard sitting position and are followed by the regular routine. After acquisition, the shoulder US images were drawn out from the scanner and stored as 8-bit images with pixel value ranging from 0 to 255. Upon the sonographic appearance, the boundary of each lesion was delineated by a physician to indicate the specific pattern for analysis. The three lesion categories for classification were composed of 20 cases of tendon inflammation, 18 cases of calcific tendonitis, and 18 cases of supraspinatus tear. For each lesion, second-order statistics were quantified in the feature extraction. The second-order statistics were the texture features describing the correlations between adjacent pixels in a lesion. Because echogenicity patterns were expressed via grey-scale. The grey-scale co-occurrence matrixes with four angles of adjacent pixels were used. The texture metrics included the mean and standard deviation of energy, entropy, correlation, inverse different moment, inertia, cluster shade, cluster prominence, and Haralick correlation. Then, the quantitative features were combined in a multinomial logistic regression classifier to generate a prediction model of rotator cuff lesions. Multinomial logistic regression classifier is widely used in the classification of more than two categories such as the three lesion types used in this study. In the classifier, backward elimination was used to select a feature subset which is the most relevant. They were selected from the trained classifier with the lowest error rate. Leave-one-out cross-validation was used to evaluate the performance of the classifier. Each case was left out of the total cases and used to test the trained result by the remaining cases. According to the physician’s assessment, the performance of the proposed CAD system was shown by the accuracy. As a result, the proposed system achieved an accuracy of 86%. A CAD system based on the statistical texture features to interpret echogenicity values in shoulder musculoskeletal ultrasound was established to generate a prediction model for rotator cuff lesions. Clinically, it is difficult to distinguish some kinds of rotator cuff lesions, especially partial-thickness tear of rotator cuff. The shoulder orthopaedic surgeon and musculoskeletal radiologist reported greater diagnostic test accuracy than general radiologist or ultrasonographers based on the available literature. Consequently, the proposed CAD system which was developed according to the experiment of the shoulder orthopaedic surgeon can provide reliable suggestions to general radiologists or ultrasonographers. More quantitative features related to the specific patterns of different lesion types would be investigated in the further study to improve the prediction.

Keywords: shoulder ultrasound, rotator cuff lesions, texture, computer-aided diagnosis

Procedia PDF Downloads 254

Authors: Zdravko Trivic, Kelvin E. Y. Low, Darko Radovic, Raymond Lucas

Abstract:

Our understanding and experience of the built environment are primarily shaped by multi‐sensory, emotional and symbolic modes of exchange with spaces. Associated sensory and cognitive declines that come with ageing substantially affect the overall quality of life of the elderly citizens and the ways they perceive and use urban environment. Reduced mobility and increased risk of falls, problems with spatial orientation and communication, lower confidence and independence levels, decreased willingness to go out and social withdrawal are some of the major consequences of sensory declines that challenge almost all segments of the seniors’ everyday living. However, contemporary urban environments are often either sensory overwhelming or depleting, resulting in physical, mental and emotional stress. Moreover, the design and planning of housing neighbourhoods hardly go beyond the passive 'do-no-harm' and universal design principles, and the limited provision of often non-integrated eldercare and inter-generational facilities. This paper explores and discusses the largely neglected relationships between the 'hard' and 'soft' aspects of housing neighbourhoods and urban experience, focusing on seniors’ perception and multi-sensory experience as vehicles for design and planning of high-density housing neighbourhoods that are inclusive and empathetic yet build senior residents’ physical and mental abilities at different stages of ageing. The paper outlines methods and key findings from research conducted in two high-density housing neighbourhoods in Singapore with aims to capture and evaluate multi-sensorial qualities of two neighbourhoods from the perspective of senior residents. Research methods employed included: on-site sensory recordings of 'objective' quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, spatial mapping of patterns of elderly users’ transient and stationary activity, socio-sensory perception surveys and sensorial journeys with local residents using eye-tracking glasses, and supplemented by walk-along or post-walk interviews. The paper develops a multi-sensory framework to synthetize, cross-reference, and visualise the activity and spatio-sensory rhythms and patterns and distill key issues pertinent to ageing-friendly and health-supportive neighbourhood design. Key findings show senior residents’ concerns with walkability, safety, and wayfinding, overall aesthetic qualities, cleanliness, smell, noise, and crowdedness in their neighbourhoods, as well as the lack of design support for all-day use in the context of Singaporean tropical climate and for inter-generational social interaction. The (ongoing) analysis of eye-tracking data reveals the spatial elements of senior residents’ look at and interact with the most frequently, with the visual range often directed towards the ground. With capacities to meaningfully combine quantitative and qualitative, measured and experienced sensory data, multi-sensory framework shows to be fruitful for distilling key design opportunities based on often ignored aspects of subjective and often taken-for-granted interactions with the familiar outdoor environment. It offers an alternative way of leveraging the potentials of housing neighbourhoods to take a more active role in enabling healthful living at all stages of ageing.

Keywords: ageing-friendly neighbourhoods, eye-tracking, high-density environment, multi-sensory approach, perception

Procedia PDF Downloads 107

Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

Abstract:

Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

Procedia PDF Downloads 62

Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

Abstract:

Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of a variety of bacterial infections. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi-drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. The present study analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, the range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin. According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Podoviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients. The findings of our research indicated that isolated phages could be an effective antimicrobial and an appreciate candidate for prophylaxis against pressure ulcers.

Keywords: acinetobacter baumannii, extremely drug-resistant, phage therapy, surgery wound

Procedia PDF Downloads 54

Authors: Clara Tramuta, Lucia Decastelli, Elisa Barcucci, Sandra Fragassi, Samantha Lupi, Enrico Arletti, Melissa Bizzarri, Daniela Manila Bianchi

Abstract:

Introdution: Food allergies occurs, in the Western World, 2% of adults and up to 8% of children. The protection of allergic consumers is guaranted, in Eurrope, by Regulation (EU) No 1169/2011 of the European Parliament which governs the consumer's right to information and identifies 14 food allergens to be mandatory indicated on the label. Among these, mustard is a popular spice added to enhance the flavour and taste of foods. It is frequently present as an ingredient in spice blends, marinades, salad dressings, sausages, and other products. Hypersensitivity to mustard is a public health problem since the ingestion of even low amounts can trigger severe allergic reactions. In order to protect the allergic consumer, high performance methods are required for the detection of allergenic ingredients. Food safety laboratories rely on validated methods that detect hidden allergens in food to ensure the safety and health of allergic consumers. Here we present the test results for the validation and accreditation of a Real time PCR assay (RT-PCR: SPECIALfinder MC Mustard, Generon), for the detection of mustard traces in food. Materials and Methods. The method was tested on five classes of food matrices: bakery and pastry products (chocolate cookies), meats (ragù), ready-to-eat (mixed salad), dairy products (yogurt), grains, and milling products (rice and barley flour). Blank samples were spiked starting with the mustard samples (Sinapis Alba), lyophilized and stored at -18 °C, at a concentration of 1000 ppm. Serial dilutions were then prepared to a final concentration of 0.5 ppm, using the DNA extracted by ION Force FAST (Generon) from the blank samples. The Real Time PCR reaction was performed by RT-PCR SPECIALfinder MC Mustard (Generon), using CFX96 System (BioRad). Results. Real Time PCR showed a limit of detection (LOD) of 0.5 ppm in grains and milling products, ready-to-eat, meats, bakery, pastry products, and dairy products (range Ct 25-34). To determine the exclusivity parameter of the method, the ragù matrix was contaminated with Prunus dulcis (almonds), peanut (Arachis hypogaea), Glycine max (soy), Apium graveolens (celery), Allium cepa (onion), Pisum sativum (peas), Daucus carota (carrots), and Theobroma cacao (cocoa) and no cross-reactions were observed. Discussion. In terms of sensitivity, the Real Time PCR confirmed, even in complex matrix, a LOD of 0.5 ppm in five classes of food matrices tested; these values are compatible with the current regulatory situation that does not consider, at international level, to establish a quantitative criterion for the allergen considered in this study. The Real Time PCR SPECIALfinder kit for the detection of mustard proved to be easy to use and particularly appreciated for the rapid response times considering that the amplification and detection phase has a duration of less than 50 minutes. Method accuracy was rated satisfactory for sensitivity (100%) and specificity (100%) and was fully validated and accreditated. It was found adequate for the needs of the laboratory as it met the purpose for which it was applied. This study was funded in part within a project of the Italian Ministry of Health (IZS PLV 02/19 RC).

Keywords: allergens, food, mustard, real time PCR

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Authors: Pierre-Andre Mudry, Jean Decaix, Jeremy Schmid, Cesar Papilloud, Cecile Munch-Alligne

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In most of the Swiss Alpine regions, the availability of water resources is usually adequate even in times of drought, as evidenced by the 2003 and 2018 summers. Indeed, important natural stocks are for the moment available in the form of snow and ice, but the situation is likely to change in the future due to global and regional climate change. In addition, alpine mountain regions are areas where climate change will be felt very rapidly and with high intensity. For instance, the ice regime of these regions has already been affected in recent years with a modification of the monthly availability and extreme events of precipitations. The current research, focusing on the municipality of Val de Bagnes, located in the canton of Valais, Switzerland, is part of a project led by the Altis company and achieved in collaboration with WSL, BlueArk Entremont, and HES-SO Valais-Wallis. In this region, water occupies a key position notably for winter and summer tourism. Thus, multiple actors want to apprehend the future needs and availabilities of water, on both the 2050 and 2100 horizons, in order to plan the modifications to the water supply and distribution networks. For those changes to be salient and efficient, a good knowledge of the current water distribution networks is of most importance. In the current case, the water drinking network is well documented, but this is not the case for the irrigation one. Since the water consumption for irrigation is ten times higher than for drinking water, data acquisition on the irrigation network is a major point to determine future scenarios. This paper first presents the instrumentation and simulation of the irrigation network using custom-designed IoT devices, which are coupled with a digital clone simulated to reduce the number of measuring locations. The developed IoT ad-hoc devices are energy-autonomous and can measure flows and pressures using industrial sensors such as calorimetric water flow meters. Measurements are periodically transmitted using the LoRaWAN protocol over a dedicated infrastructure deployed in the municipality. The gathered values can then be visualized in real-time on a dashboard, which also provides historical data for analysis. In a second phase, a digital clone of the irrigation network was modeled using EPANET, a software for water distribution systems that performs extended-period simulations of flows and pressures in pressurized networks composed of reservoirs, pipes, junctions, and sinks. As a preliminary work, only a part of the irrigation network was modelled and validated by comparisons with the measurements. The simulations are carried out by imposing the consumption of water at several locations. The validation is performed by comparing the simulated pressures are different nodes with the measured ones. An accuracy of +/- 15% is observed on most of the nodes, which is acceptable for the operator of the network and demonstrates the validity of the approach. Future steps will focus on the deployment of the measurement devices on the whole network and the complete modelling of the network. Then, scenarios of future consumption will be investigated. Acknowledgment— The authors would like to thank the Swiss Federal Office for Environment (FOEN), the Swiss Federal Office for Agriculture (OFAG) for their financial supports, and ALTIS for the technical support, this project being part of the Swiss Pilot program 'Adaptation aux changements climatiques'.

Keywords: hydraulic digital clone, IoT water monitoring, LoRaWAN water measurements, EPANET, irrigation network

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Authors: Eduardo Rodrigues, Gisela Mendes, José M. Torres, José E. Sousa

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In the sequence of the liberalisation of the electricity sector a progressive engagement of consumers has been considered and targeted by sector regulatory policies. With the objective of promoting market competition while protecting consumers interests, by transferring some of the upstream benefits to the end users while reaching a fair distribution of system costs, different market models to value consumers’ demand flexibility at the energy community level are envisioned. Local Energy and Flexibility Markets (LEFM) involve stakeholders interested in providing or procure local flexibility for community, services and markets’ value. Under the scope of DOMINOES, a European research project supported by Horizon 2020, the local market concept developed is expected to: • Enable consumers/prosumers empowerment, by allowing them to value their demand flexibility and Distributed Energy Resources (DER); • Value local liquid flexibility to support innovative distribution grid management, e.g., local balancing and congestion management, voltage control and grid restoration; • Ease the wholesale market uptake of DER, namely small-scale flexible loads aggregation as Virtual Power Plants (VPPs), facilitating Demand Response (DR) service provision; • Optimise the management and local sharing of Renewable Energy Sources (RES) in Medium Voltage (MV) and Low Voltage (LV) grids, trough energy transactions within an energy community; • Enhance the development of energy markets through innovative business models, compatible with ongoing policy developments, that promote the easy access of retailers and other service providers to the local markets, allowing them to take advantage of communities’ flexibility to optimise their portfolio and subsequently their participation in external markets. The general concept proposed foresees a flow of market actions, technical validations, subsequent deliveries of energy and/or flexibility and balance settlements. Since the market operation should be dynamic and capable of addressing different requests, either prioritising balancing and prosumer services or system’s operation, direct procurement of flexibility within the local market must also be considered. This paper aims to highlight the research on the definition of suitable DR models to be used by the Distribution System Operator (DSO), in case of technical needs, and by the retailer, mainly for portfolio optimisation and solve unbalances. The models to be proposed and implemented within relevant smart distribution grid and microgrid validation environments, are focused on day-ahead and intraday operation scenarios, for predictive management and near-real-time control respectively under the DSO’s perspective. At local level, the DSO will be able to procure flexibility in advance to tackle different grid constrains (e.g., demand peaks, forecasted voltage and current problems and maintenance works), or during the operating day-to-day, to answer unpredictable constraints (e.g., outages, frequency deviations and voltage problems). Due to the inherent risks of their active market participation retailers may resort to DR models to manage their portfolio, by optimising their market actions and solve unbalances. The interaction among the market actors involved in the DR activation and in flexibility exchange is explained by a set of sequence diagrams for the DR modes of use from the DSO and the energy provider perspectives. • DR for DSO’s predictive management – before the operating day; • DR for DSO’s real-time control – during the operating day; • DR for retailer’s day-ahead operation; • DR for retailer’s intraday operation.

Keywords: demand response, energy communities, flexible demand, local energy and flexibility markets

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Authors: Julien Caudeville, Muriel Ismert

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Analyzing the relationship between environment and health has become a major preoccupation for public health as evidenced by the emergence of the French national plans for health and environment. These plans have identified the following two priorities: (1) to identify and manage geographic areas, where hotspot exposures are suspected to generate a potential hazard to human health; (2) to reduce exposure inequalities. At a regional scale and fine resolution of exposure outcome prerequisite, environmental monitoring networks are not sufficient to characterize the multidimensionality of the exposure concept. In an attempt to increase representativeness of spatial exposure assessment approaches, risk composite indicators could be built using additional available databases and theoretical framework approaches to combine factor risks. To achieve those objectives, combining data process and transfer modeling with a spatial approach is a fundamental prerequisite that implies the need to first overcome different scientific limitations: to define interest variables and indicators that could be built to associate and describe the global source-effect chain; to link and process data from different sources and different spatial supports; to develop adapted methods in order to improve spatial data representativeness and resolution. A GIS-based modeling platform for quantifying human exposure to chemical substances (PLAINE: environmental inequalities analysis platform) was used to build health risk indicators within the Lorraine region (France). Those indicators combined chemical substances (in soil, air and water) and noise risk factors. Tools have been developed using modeling, spatial analysis and geostatistic methods to build and discretize interest variables from different supports and resolutions on a 1 km2 regular grid within the Lorraine region. By example, surface soil concentrations have been estimated by developing a Kriging method able to integrate surface and point spatial supports. Then, an exposure model developed by INERIS was used to assess the transfer from soil to individual exposure through ingestion pathways. We used distance from polluted soil site to build a proxy for contaminated site. Air indicator combined modeled concentrations and estimated emissions to take in account 30 polluants in the analysis. For water, drinking water concentrations were compared to drinking water standards to build a score spatialized using a distribution unit serve map. The Lden (day-evening-night) indicator was used to map noise around road infrastructures. Aggregation of the different factor risks was made using different methodologies to discuss weighting and aggregation procedures impact on the effectiveness of risk maps to take decisions for safeguarding citizen health. Results permit to identify pollutant sources, determinants of exposure, and potential hotspots areas. A diagnostic tool was developed for stakeholders to visualize and analyze the composite indicators in an operational and accurate manner. The designed support system will be used in many applications and contexts: (1) mapping environmental disparities throughout the Lorraine region; (2) identifying vulnerable population and determinants of exposure to set priorities and target for pollution prevention, regulation and remediation; (3) providing exposure database to quantify relationships between environmental indicators and cancer mortality data provided by French Regional Health Observatories.

Keywords: health risk, environment, composite indicator, hotspot areas

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Authors: Christiane H. Kellner, Sarah Reker

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The UN-Convention on the Rights of Persons with Disabilities, which Germany also ratified, postulates the necessity of user-centred design, especially when it comes to evaluating the individual needs and wishes of all citizens. Therefore, a multidimensional approach is required. Based on this insight, the structure of the town-like centre in Schönbrunn - a large residential complex and service provider for persons with disabilities in the outskirts of Munich - will be remodelled to open up the community to all people as well as transform social space. This strategy should lead to more equal opportunities and open the way for a much more diverse community. The research project “Index for participation development and quality of life for persons with disabilities” (TeLe-Index, 2014-2016), which is anchored at the Technische Universität München in Munich and at the Franziskuswerk Schönbrunn supports this transformation process called “Vision 2030”. In this context, we have provided academic supervision and support for three projects (the construction of a new school, inclusive housing for children and teenagers with disabilities and the professionalization of employees using person-centred planning). Since we cannot present all the issues of the umbrella-project within the conference framework, we will be focusing on one sub-project more in-depth, namely “The Person-Centred Think Tank” [Arbeitskreis Personenzentriertes Denken; PZD]. In the context of person-centred thinking (PCT), persons with disabilities are encouraged to (re)gain or retain control of their lives through the development of new choice options and the validation of individual lifestyles. PCT should thus foster and support both participation and quality of life. The project aims to establish PCT as a fundamental approach for both employees and persons with disabilities in the institution through in-house training for the staff and, subsequently, training for users. Hence, for the academic support and supervision team, the questions arising from this venture can be summed up as follows: (1) has PCT already gained a foothold at the Franziskuswerk Schönbrunn? And (2) how does it affect the interaction with persons with disabilities and how does it influence the latter’s everyday life? According to the holistic approach described above, the target groups for this study are both the staff and the users of the institution. Initially, we planned to implement the group discussion method for both target-groups. However, in the course of a pretest with persons with intellectual disabilities, it became clear that this type of interview, with hardly any external structuring, provided only limited feedback. In contrast, when the discussions were moderated, there was more interaction and dialogue between the interlocutors. Therefore, for this target-group, we introduced structured group interviews. The insights we have obtained until now will enable us to present the intermediary results of our evaluation. We analysed and evaluated the group interviews and discussions with the help of qualitative content analysis according to Mayring in order to obtain information about users’ quality of life. We sorted out the statements relating to quality of life obtained during the group interviews into three dimensions: subjective wellbeing, self-determination and participation. Nevertheless, the majority of statements were related to subjective wellbeing and self-determination. Thus, especially the limited feedback on participation clearly demonstrates that the lives of most users do not take place beyond the confines of the institution. A number of statements highlighted the fact that PCT is anchored in the everyday interactions within the groups. However, the implementation and fostering of PCT on a broader level could not be detected and thus remain further aims of the project. The additional interviews we have planned should validate the results obtained until now and open up new perspectives.

Keywords: person-centered thinking, research with persons with disabilities, residential complex and service provider, participation, self-determination.

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Authors: Danyi Wang, Andrew Schriefer, Dennis O'Rourke, Brajendra Kumar, Yang Liu, Fei Zhong, Juergen Scheuenpflug, Zheng Feng

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Purpose: It has been recognized that the microbiome plays critical roles in disease pathogenesis, including cancer, autoimmune disease, and multiple sclerosis. To develop a clinical-grade assay for exploring microbiome-derived clinical biomarkers across disease areas, a two-phase approach is implemented. 1) Identification of the optimal sample preparation reagents using pre-mixed bacteria and healthy donor stool samples coupled with proprietary Sigma-Aldrich® bioinformatics solution. 2) Exploratory analysis of patient samples for enabling precision medicine. Study Procedure: In phase 1 study, we first compared the 16S sequencing results of two ATCC® microbiome standards (MSA 2002 and MSA 2003) across five different extraction kits (Kit A, B, C, D & E). Both microbiome standards samples were extracted in triplicate across all extraction kits. Following isolation, DNA quantity was determined by Qubit assay. DNA quality was assessed to determine purity and to confirm extracted DNA is of high molecular weight. Bacterial 16S ribosomal ribonucleic acid (rRNA) amplicons were generated via amplification of the V3/V4 hypervariable region of the 16S rRNA. Sequencing was performed using a 2x300 bp paired-end configuration on the Illumina MiSeq. Fastq files were analyzed using the Sigma-Aldrich® Microbiome Platform. The Microbiome Platform is a cloud-based service that offers best-in-class 16S-seq and WGS analysis pipelines and databases. The Platform and its methods have been extensively benchmarked using microbiome standards generated internally by MilliporeSigma and other external providers. Data Summary: The DNA yield using the extraction kit D and E is below the limit of detection (100 pg/µl) of Qubit assay as both extraction kits are intended for samples with low bacterial counts. The pre-mixed bacterial pellets at high concentrations with an input of 2 x106 cells for MSA-2002 and 1 x106 cells from MSA-2003 were not compatible with the kits. Among the remaining 3 extraction kits, kit A produced the greatest yield whereas kit B provided the least yield (Kit-A/MSA-2002: 174.25 ± 34.98; Kit-A/MSA-2003: 179.89 ± 30.18; Kit-B/MSA-2002: 27.86 ± 9.35; Kit-B/MSA-2003: 23.14 ± 6.39; Kit-C/MSA-2002: 55.19 ± 10.18; Kit-C/MSA-2003: 35.80 ± 11.41 (Mean ± SD)). Also, kit A produced the greatest yield, whereas kit B provided the least yield. The PCoA 3D visualization of the Weighted Unifrac beta diversity shows that kits A and C cluster closely together while kit B appears as an outlier. The kit A sequencing samples cluster more closely together than both the other kits. The taxonomic profiles of kit B have lower recall when compared to the known mixture profiles indicating that kit B was inefficient at detecting some of the bacteria. Conclusion: Our data demonstrated that the DNA extraction method impacts DNA concentration, purity, and microbial communities detected by next-generation sequencing analysis. Further microbiome analysis performance comparison of using healthy stool samples is underway; also, colorectal cancer patients' samples will be acquired for further explore the clinical utilities. Collectively, our comprehensive qualification approach, including the evaluation of optimal DNA extraction conditions, the inclusion of positive controls, and the implementation of a robust qualified bioinformatics pipeline, assures accurate characterization of the microbiota in a complex matrix for deciphering the deep biology and enabling precision medicine.

Keywords: 16S rRNA sequencing, analytical validation, bioinformatics pipeline, metagenomics

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Authors: David Shengelia, Giorgi Chichinadze, Tamara Tsutsunava, Giorgi Beridze, Irakli Javakhishvili

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The Loki pre-Alpine crystalline massif crops out within the Caucasus region. The massif basement is represented by the Upper Devonian gneissose quartz-diorites, the Lower-Middle Paleozoic metamorphic allochthonous complex, and different magmatites. Earlier, the metamorphic complex was considered as indivisible set represented by the series of different temperature metamorphits. The degree of metamorphism of separate parts of the complex is due to different formation conditions. This fact according to authors of the abstract was explained by the allochthonous-flaky structure of the complex. It was stated that the complex thrust over the gneissose quartz diorites before the intrusion of Sudetic granites. During the detailed mapping, the authors turned out that the metamorphism issues need to be reviewed and additional researches to be carried out. Investigations were accomplished by using the following methodologies: finding of key sections, a sampling of rocks, microscopic description of the material, analytical determination of elements in the rocks, microprobe analysis of minerals and new interpretation of obtained data. According to the author’s recent data within the massif four tectonic plates: Lower Gorastskali, Sapharlo-Lok-Jandari, Moshevani and “mélange” overthrust sheets have been mapped. They differ from each other by composition, the degree of metamorphism and internal structure. It is confirmed that the initial rocks of the tectonic plates formed in different geodynamic conditions during overthrusting due to tectonic compression form a thick tectonic sheet. Based on the detailed laboratory investigations additional mineral assemblages were established, temperature limits were specified, and a renewed trend of metamorphism facies and subfacies was elaborated. The results are the following: 1. The Lower Gorastskali overthrust sheet is a fragment of ophiolitic association corresponding to the Paleotethys oceanic crust. The main rock-forming minerals are carbonate, chlorite, spinel, epidote, clinoptilolite, plagioclase, hornblende, actinolite, hornblende, albite, serpentine, tremolite, talc, garnet, and prehnite. Regional metamorphism of rocks corresponds to the greenschist facies lowest stage. 2. The Sapharlo-Lok-Jandari overthrust sheet metapelites are represented by chloritoid, chlorite, phengite, muscovite, biotite, garnet, ankerite, carbonate, and quartz. Metabasites containing actinolite, chlorite, plagioclase, calcite, epidote, albite, actinolitic hornblende and hornblende are also present. The degree of metamorphism corresponds to the greenschist high-temperature chlorite, biotite, and low-temperature garnet subfacies. Later the rocks underwent the contact influence of Late Variscan granites. 3. The Moshevani overthrust sheet is represented mainly by metapelites and rarely by metabasites. Main rock-forming minerals of metapelites are muscovite, biotite, chlorite, quartz, andalusite, plagioclase, garnet and cordierite and of metabasites - plagioclase, green and blue-green hornblende, chlorite, epidote, actinolite, albite, and carbonate. Metamorphism level corresponds to staurolite-andalusite subfacies of staurolite facies and partially to facies of biotite muscovite gneisses and hornfelse facies as well. 4. The “mélange” overthrust sheet is built of different size rock fragments and blocks of Moshevani and Lower Gorastskali overthrust sheets. The degree of regional metamorphism of first and second overthrust sheets of the Loki massif corresponds to chlorite, biotite, and low-temperature garnet subfacies, but of the third overthrust sheet – to staurolite-andalusite subfacies of staurolite facies and partially to facies of biotite muscovite gneisses and hornfelse facies.

Keywords: regional metamorphism, crystalline massif, mineral assemblages, the Caucasus

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Authors: Claire Williams

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Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Diogo José Morgado Rebelo, Francisco António Carneiro Pacheco de Andrade, Paulo Jorge Freitas de Oliveira Novais

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Not everything in AI-power consumer credit scoring turns out to be a wonder. When using AI in Creditworthiness Assessment (CWA), opacity and unfairness ‘sins’ must be considered to the task be deemed Responsible. AI software is not always 100% accurate, which can lead to misclassification. Discrimination of some groups can be exponentiated. A hetero personalized identity can be imposed on the individual(s) affected. Also, autonomous CWA sometimes lacks transparency when using black box models. However, for this intended purpose, human analysts ‘on-the-loop’ might not be the best remedy consumers are looking for in credit. This study seeks to explore the legality of implementing a Multi-Agent System (MAS) framework in consumer CWA to ensure compliance with the regulation outlined in Article 14(4) of the Proposal for an Artificial Intelligence Act (AIA), dated 21 April 2021 (as per the last corrigendum by the European Parliament on 19 April 2024), Especially with the adoption of Art. 18(8)(9) of the EU Directive 2023/2225, of 18 October, which will go into effect on 20 November 2026, there should be more emphasis on the need for hybrid oversight in AI-driven scoring to ensure fairness and transparency. In fact, the range of EU regulations on AI-based consumer credit will soon impact the AI lending industry locally and globally, as shown by the broad territorial scope of AIA’s Art. 2. Consequently, engineering the law of consumer’s CWA is imperative. Generally, the proposed MAS framework consists of several layers arranged in a specific sequence, as follows: firstly, the Data Layer gathers legitimate predictor sets from traditional sources; then, the Decision Support System Layer, whose Neural Network model is trained using k-fold Cross Validation, provides recommendations based on the feeder data; the eXplainability (XAI) multi-structure comprises Three-Step-Agents; and, lastly, the Oversight Layer has a 'Bottom Stop' for analysts to intervene in a timely manner. From the analysis, one can assure a vital component of this software is the XAY layer. It appears as a transparent curtain covering the AI’s decision-making process, enabling comprehension, reflection, and further feasible oversight. Local Interpretable Model-agnostic Explanations (LIME) might act as a pillar by offering counterfactual insights. SHapley Additive exPlanation (SHAP), another agent in the XAI layer, could address potential discrimination issues, identifying the contribution of each feature to the prediction. Alternatively, for thin or no file consumers, the Suggestion Agent can promote financial inclusion. It uses lawful alternative sources such as the share of wallet, among others, to search for more advantageous solutions to incomplete evaluation appraisals based on genetic programming. Overall, this research aspires to bring the concept of Machine-Centered Anthropocentrism to the table of EU policymaking. It acknowledges that, when put into service, credit analysts no longer exert full control over the data-driven entities programmers have given ‘birth’ to. With similar explanatory agents under supervision, AI itself can become self-accountable, prioritizing human concerns and values. AI decisions should not be vilified inherently. The issue lies in how they are integrated into decision-making and whether they align with non-discrimination principles and transparency rules.

Keywords: creditworthiness assessment, hybrid oversight, machine-centered anthropocentrism, EU policymaking

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Authors: Oluwaseun Adeleke, Samuel O. Ikani, Fidelis Edet, Anthony Nwala, Mopelola Raji, Simeon Christian Chukwu

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Background: The DISC project collaborated with partners to implement demand creation and service delivery interventions, including the MoT (Moment of Truth) innovation, in over 500 health facilities across 15 states. This has increased the voluntary conversion rate to self-injection among women who opt for injectable contraception. While some facilities recorded an increasing trend in key performance indicators, few others persistently performed sub-optimally due to provider and system-related barriers. Methodology: Twenty-two facilities performing sub-optimally were selected purposively from three Nigerian states. Low productivity was appraised using low reporting rates and poor SI conversion rates as indicators. Interviews were conducted with health providers across these health facilities using a rapid diagnosis tool. The project also conducted a data quality assessment that evaluated the veracity of data elements reported across the three major sources of family planning data in the facility. Findings: The inability and sometimes refusal of providers to support clients to self-inject effectively was associated with the misunderstanding of its value to their work experience. It was also observed that providers still held a strong influence over clients’ method choices. Furthermore, providers held biases and misconceptions about DMPA-SC that restricted the access of obese clients and new acceptors to services – a clear departure from the recommendations of the national guidelines. Additionally, quality of care standards was compromised because job aids were not used to inform service delivery. Facilities performing sub-optimally often under-reported DMPA-SC utilization data, and there were multiple uncoordinated responsibilities for recording and reporting. Additionally, data validation meetings were not regularly convened, and these meetings were ineffective in authenticating data received from health facilities. Other reasons for sub-optimal performance included poor documentation and tracking of stock inventory resulting in commodity stockouts, low client flow because of poor positioning of health facilities, and ineffective messaging. Some facilities lacked adequate human and material resources to provide services effectively and received very few supportive supervision visits. Supportive supervision visits and Data Quality Audits have been useful to address the aforementioned performance barriers. The project has deployed digital DMPA-SC self-injection checklists that have been aligned with nationally approved templates. During visits, each provider and community mobilizer is accorded special attention by the supervisor until he/she can perform procedures in line with best practice (protocol). Conclusion: This narrative provides a summary of a range of factors that identify health facilities performing sub-optimally in their provision of DMPA-SC services. Findings from this assessment will be useful during project design to inform effective strategies. As the project enters its final stages of implementation, it is transitioning high-impact activities to state institutions in the quest to sustain the quality of service beyond the tenure of the project. The project has flagged activities, as well as created protocols and tools aimed at placing state-level stakeholders at the forefront of improving productivity in health facilities.

Keywords: family planning, contraception, DMPA-SC, self-care, self-injection, barriers, opportunities, performance

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Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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Authors: Artur Tyliszczak, Ewa Szymanek, Maciej Marek

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Flow through granular materials is important to a vast array of industries, for instance in construction industry where granular layers are used for bulkheads and isolators, in chemical engineering and catalytic reactors where large surfaces of packed granular beds intensify chemical reactions, or in energy production systems, where granulates are promising materials for heat storage and heat transfer media. Despite the common usage of granulates and extensive research performed in this field, phenomena occurring between granular solid elements or between solids and fluid are still not fully understood. In the present work we analyze the heat exchange process between the flowing medium (gas, liquid) and solid material inside the granular layers. We consider them as a composite of isolated solid elements and inter-granular spaces in which a gas or liquid can flow. The structure of the layer is controlled by shapes of particular granular elements (e.g., spheres, cylinders, cubes, Raschig rings), its spatial distribution or effective characteristic dimension (total volume or surface area). We will analyze to what extent alteration of these parameters influences on flow characteristics (turbulent intensity, mixing efficiency, heat transfer) inside the layer and behind it. Analysis of flow inside granular layers is very complicated because the use of classical experimental techniques (LDA, PIV, fibber probes) inside the layers is practically impossible, whereas the use of probes (e.g. thermocouples, Pitot tubes) requires drilling of holes inside the solid material. Hence, measurements of the flow inside granular layers are usually performed using for instance advanced X-ray tomography. In this respect, theoretical or numerical analyses of flow inside granulates seem crucial. Application of discrete element methods in combination with the classical finite volume/finite difference approaches is problematic as a mesh generation process for complex granular material can be very arduous. A good alternative for simulation of flow in complex domains is an immersed boundary-volume penalization (IB-VP) in which the computational meshes have simple Cartesian structure and impact of solid objects on the fluid is mimicked by source terms added to the Navier-Stokes and energy equations. The present paper focuses on application of the IB-VP method combined with large eddy simulation (LES). The flow solver used in this work is a high-order code (SAILOR), which was used previously in various studies, including laminar/turbulent transition in free flows and also for flows in wavy channels, wavy pipes and over various shape obstacles. In these cases a formal order of approximation turned out to be in between 1 and 2, depending on the test case. The current research concentrates on analyses of the flows in dense granular layers with elements distributed in a deterministic regular manner and validation of the results obtained using LES-IB method and body-fitted approach. The comparisons are very promising and show very good agreement. It is found that the size, number of elements and their distribution have huge impact on the obtained results. Ordering of the granular elements (or lack of it) affects both the pressure drop and efficiency of the heat transfer as it significantly changes mixing process.

Keywords: granular layers, heat transfer, immersed boundary method, numerical simulations

Procedia PDF Downloads 101

Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

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Authors: Keivan Davami, Michael Munther, Lloyd Hackel

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The control of properties and material behavior by implementing thermal-mechanical processes is based on mechanical deformation and annealing according to a precise schedule that will produce a unique and stable combination of grain structure, dislocation substructure, texture, and dispersion of precipitated phases. The authors recently developed a thermal-mechanical technique to stabilize the microstructure of additively manufactured nickel-based superalloys even after exposure to high temperatures. However, the mechanism(s) that controls this stability is still under investigation. Laser peening (LP), also called laser shock peening (LSP), is a shock based (50 ns duration) post-processing technique used for extending performance levels and improving service life of critical components by developing deep levels of plastic deformation, thereby generating high density of dislocations and inducing compressive residual stresses in the surface and deep subsurface of components. These compressive residual stresses are usually accompanied with an increase in hardness and enhance the material’s resistance to surface-related failures such as creep, fatigue, contact damage, and stress corrosion cracking. While the LP process enhances the life span and durability of the material, the induced compressive residual stresses relax at high temperatures (>0.5Tm, where Tm is the absolute melting temperature), limiting the applicability of the technology. At temperatures above 0.5Tm, the compressive residual stresses relax, and yield strength begins to drop dramatically. The principal reason is the increasing rate of solid-state diffusion, which affects both the dislocations and the microstructural barriers. Dislocation configurations commonly recover by mechanisms such as climbing and recombining rapidly at high temperatures. Furthermore, precipitates coarsen, and grains grow; virtually all of the available microstructural barriers become ineffective.Our results indicate that by using “cyclic” treatments with sequential LP and annealing steps, the compressive stresses survive, and the microstructure is stable after exposure to temperatures exceeding 0.5Tm for a long period of time. When the laser peening process is combined with annealing, dislocations formed as a result of LPand precipitates formed during annealing have a complex interaction that provides further stability at high temperatures. From a scientific point of view, this research lays the groundwork for studying a variety of physical, materials science, and mechanical engineering concepts. This research could lead to metals operating at higher sustained temperatures enabling improved system efficiencies. The strengthening of metals by a variety of means (alloying, work hardening, and other processes) has been of interest for a wide range of applications. However, the mechanistic understanding of the often complex processes of interactionsbetween dislocations with solute atoms and with precipitates during plastic deformation have largely remained scattered in the literature. In this research, the elucidation of the actual mechanisms involved in the novel cyclic LP/annealing processes as a scientific pursuit is investigated through parallel studies of dislocation theory and the implementation of advanced experimental tools. The results of this research help with the validation of a novel laser processing technique for high temperature applications. This will greatly expand the applications of the laser peening technology originally devised only for temperatures lower than half of the melting temperature.

Keywords: laser shock peening, mechanical properties, indentation, high temperature stability

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Authors: Mohamed Gazzeh, Bradley Null, Fethi Tlili, Hichem Besbes

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The burgeoning global ownership of personal vehicles has posed a significant strain on urban infrastructure, notably parking facilities, leading to traffic congestion and environmental concerns. Effective parking management systems (PMS) are indispensable for optimizing urban traffic flow and reducing emissions. The most commonly deployed systems nowadays rely on computer vision technology. This paper explores the integration of radar sensors and simulation in the context of smart parking management. We concentrate on radar sensors due to their versatility and utility in automotive applications, which extends to PMS. Additionally, radar sensors play a crucial role in driver assistance systems and autonomous vehicle development. However, the resource-intensive nature of radar data collection for algorithm development and testing necessitates innovative solutions. Simulation, particularly the monoDrive simulator, an internal development tool used by NI the Test and Measurement division of Emerson, offers a practical means to overcome this challenge. The primary objectives of this study encompass simulating radar sensors to generate a substantial dataset for algorithm development, testing, and, critically, assessing the transferability of models between simulated and real radar data. We focus on occupancy detection in parking as a practical use case, categorizing each parking space as vacant or occupied. The simulation approach using monoDrive enables algorithm validation and reliability assessment for virtual radar sensors. It meticulously designed various parking scenarios, involving manual measurements of parking spot coordinates, orientations, and the utilization of TI AWR1843 radar. To create a diverse dataset, we generated 4950 scenarios, comprising a total of 455,400 parking spots. This extensive dataset encompasses radar configuration details, ground truth occupancy information, radar detections, and associated object attributes such as range, azimuth, elevation, radar cross-section, and velocity data. The paper also addresses the intricacies and challenges of real-world radar data collection, highlighting the advantages of simulation in producing radar data for parking lot applications. We developed classification models based on Support Vector Machines (SVM) and Density-Based Spatial Clustering of Applications with Noise (DBSCAN), exclusively trained and evaluated on simulated data. Subsequently, we applied these models to real-world data, comparing their performance against the monoDrive dataset. The study demonstrates the feasibility of transferring models from a simulated environment to real-world applications, achieving an impressive accuracy score of 92% using only one radar sensor. This finding underscores the potential of radar sensors and simulation in the development of smart parking management systems, offering significant benefits for improving urban mobility and reducing environmental impact. The integration of radar sensors and simulation represents a promising avenue for enhancing smart parking management systems, addressing the challenges posed by the exponential growth in personal vehicle ownership. This research contributes valuable insights into the practicality of using simulated radar data in real-world applications and underscores the role of radar technology in advancing urban sustainability.

Keywords: autonomous vehicle simulator, FMCW radar sensors, occupancy detection, smart parking management, transferability of models

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Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

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Authors: Savvas Rogotis, Nikolaos Kalatzis, Stergios Dimou-Sakellariou, Nikolaos Marianos

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As precision holds the key for the introduction of distinct benefits in agriculture (e.g., energy savings, reduced labor costs, optimal application of inputs, improved products, and yields), it steadily becomes evident that new initiatives should focus on rendering Precision Agriculture (PA) more accessible to the average farmer. PA leverages on technologies such as the Internet of Things (IoT), earth observation, robotics and positioning systems (e.g., the Global Navigation Satellite System – GNSS - as well as individual positioning systems like GPS, Glonass, Galileo) that allow: from simple data georeferencing to optimal navigation of agricultural machinery to even more complex tasks like Variable Rate Applications. An identified customer pain point is that, from one hand, typical triangulation-based positioning systems are not accurate enough (with errors up to several meters), while on the other hand, high precision positioning systems reaching centimeter-level accuracy, are very costly (up to thousands of euros). Within this paper, a Ground-Based Augmentation System (GBAS) is introduced, that can be adapted to any existing IoT field-sensing station infrastructure. The latter should cover a minimum set of requirements, and in particular, each station should operate as a fixed, obstruction-free towards the sky, energy supplying unit. Station augmentation will allow them to function in pairs with GNSS rovers following the differential GNSS base-rover paradigm. This constitutes a key innovation element for the proposed solution that encompasses differential GNSS capabilities into an IoT field-sensing infrastructure. Integrating this kind of information supports the provision of several additional PA beneficial services such as spatial mapping, route planning, and automatic field navigation of unmanned vehicles (UVs). Right at the heart of the designed system, there is a high-end GNSS toolkit with base-rover variants and Real-Time Kinematic (RTK) capabilities. The GNSS toolkit had to tackle all availability, performance, interfacing, and energy-related challenges that are faced for a real-time, low-power, and reliable in the field operation. Specifically, in terms of performance, preliminary findings exhibit a high rover positioning precision that can even reach less than 10-centimeters. As this precision is propagated to the full dataset collection, it enables tractors, UVs, Android-powered devices, and measuring units to deal with challenging real-world scenarios. The system is validated with the help of Gaiatrons, a mature network of agro-climatic telemetry stations with presence all over Greece and beyond ( > 60.000ha of agricultural land covered) that constitutes part of “gaiasense” (www.gaiasense.gr) smart farming (SF) solution. Gaiatrons constantly monitor atmospheric and soil parameters, thus, providing exact fit to operational requirements asked from modern SF infrastructures. Gaiatrons are ultra-low-cost, compact, and energy-autonomous stations with a modular design that enables the integration of advanced GNSS base station capabilities on top of them. A set of demanding pilot demonstrations has been initiated in Stimagka, Greece, an area with a diverse geomorphological landscape where grape cultivation is particularly popular. Pilot demonstrations are in the course of validating the preliminary system findings in its intended environment, tackle all technical challenges, and effectively highlight the added-value offered by the system in action.

Keywords: GNSS, GBAS, precision agriculture, RTK, smart farming

Procedia PDF Downloads 85

Authors: Mireille Elhajj, Washington Ochieng, Deeph Chana

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The challenges of the rapid growth in the demand for transport has traditionally been seen within the context of the problems of congestion, air quality, climate change, safety, and affordability. However, there are increasing threats including those related to crime such as cyber-attacks that threaten the security of the transport of people and goods. To the best of the authors’ knowledge, this paper presents for the first time, a comprehensive framework for the assessment of the current and future security issues of multi-modal transport systems. The approach or method proposed is based on a structured framework starting with a detailed specification of the transport asset map (transport system architecture), followed by the identification of vulnerabilities. The asset map and vulnerabilities are used to identify the various approaches for exploitation of the vulnerabilities, leading to the creation of a set of threat scenarios. The threat scenarios are then transformed into risks and their categories, and include insights for their mitigation. The consideration of the mitigation space is holistic and includes the formulation of appropriate policies and tactics and/or technical interventions. The quality of the framework is ensured through a structured and logical process that identifies the stakeholders, reviews the relevant documents including policies and identifies gaps, incorporates targeted surveys to augment the reviews, and uses subject matter experts for validation. The approach to categorising security risks is an extension of the current methods that are typically employed. Specifically, the partitioning of risks into either physical or cyber categories is too limited for developing mitigation policies and tactics/interventions for transport systems where an interplay between physical and cyber processes is very often the norm. This interplay is rapidly taking on increasing significance for security as the emergence of cyber-physical technologies, are shaping the future of all transport modes. Examples include: Connected Autonomous Vehicles (CAVs) in road transport; the European Rail Traffic Management System (ERTMS) in rail transport; Automatic Identification System (AIS) in maritime transport; advanced Communications, Navigation and Surveillance (CNS) technologies in air transport; and the Internet of Things (IoT). The framework adopts a risk categorisation scheme that considers risks as falling within the following threat→impact relationships: Physical→Physical, Cyber→Cyber, Cyber→Physical, and Physical→Cyber). Thus the framework enables a more complete risk picture to be developed for today’s transport systems and, more importantly, is readily extendable to account for emerging trends in the sector that will define future transport systems. The framework facilitates the audit and retro-fitting of mitigations in current transport operations and the analysis of security management options for the next generation of Transport enabling strategic aspirations such as systems with security-by-design and co-design of safety and security to be achieved. An initial application of the framework to transport systems has shown that intra-modal consideration of security measures is sub-optimal and that a holistic and multi-modal approach that also addresses the intersections/transition points of such networks is required as their vulnerability is high. This is in-line with traveler-centric transport service provision, widely accepted as the future of mobility services. In summary, a risk-based framework is proposed for use by the stakeholders to comprehensively and holistically assess the security of transport systems. It requires a detailed understanding of the transport architecture to enable a detailed vulnerabilities analysis to be undertaken, creates threat scenarios and transforms them into risks which form the basis for the formulation of interventions.

Keywords: mitigations, risk, transport, security, vulnerabilities

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Authors: Faranak Felfeliyan, Parvaneh Shokrani, Maryam Atarod

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Introduction Using electron beam is widespread in radiotherapy. The main criteria in radiation therapy is to irradiate the tumor volume with maximum prescribed dose and minimum dose to vital organs around it. Using abutting fields is common in radiotherapy. The main problem in using abutting fields is dose inhomogeneity in the junction region. Electron beam divergence and lateral scattering may lead to hot and cold spots in the junction region. One solution for this problem is using of a spoiler to broaden the penumbra and uniform dose in the junction region. The goal of this research was to compare titanium and aluminum effects as a spoiler for dose uniformity achievement in the junction region of oblique electron fields with Monte Carlo simulation. Dose uniformity in the junction region depends on density, scattering power, thickness of the spoiler and the angle between two fields. Materials and Methods In this study, Monte Carlo model of Siemens Primus linear accelerator was simulated for a 5 MeV nominal energy electron beam using manufacture provided specifications. BEAMnrc and EGSnrc user code were used to simulate the treatment head in electron mode (simulation of beam model). The resulting phase space file was used as a source for dose calculations for 10×10 cm2 field size at SSD=100 cm in a 30×30×45 cm3 water phantom using DOSXYZnrc user code (dose calculations). An automatic MP3-M water phantom tank, MEPHYSTO mc2 software platform and a Semi-Flex Chamber-31010 with sensitive vol­ume of 0.125 cm3 (PTW, Freiburg, Germany) were used for dose distribution measurements. Moreover, the electron field size was 10×10 cm2 and SSD=100 cm. Validation of devel­oped beam model was done by comparing the measured and calculated depth and lateral dose distributions (verification of electron beam model). Simulation of spoilers (using SLAB compo­nent module) placed at the end of the electron applicator, was done using previously vali­dated phase space file for a 5 MeV nominal energy and 10×10 cm2 field size (simulation of spoiler). An in-house routine was developed in order to calculate the combined isodose curves re­sulting from the two simulated abutting fields (calculation of dose distribution in abutting electron fields). Results Verification of the developed 5.9 MeV elec­tron beam model was done by comparing the calculated and measured dose distributions. The maximum percentage difference between calculated and measured PDD was 1%, except for the build-up region in which the difference was 2%. The difference between calculated and measured profile was 2% at the edges of the field and less than 1% in other regions. The effect of PMMA, aluminum, titanium and chromium in dose uniformity achievement in abutting normal electron fields with equivalent thicknesses to 5mm PMMA was evaluated. Comparing R90 and uniformity index of different materials, aluminum was chosen as the optimum spoiler. Titanium has the maximum surface dose. Thus, aluminum and titanium had been chosen to use for dose uniformity achievement in oblique electron fields. Using the optimum beam spoiler, junction dose decreased from 160% to 110% for 15 degrees, from 180% to 120% for 30 degrees, from 160% to 120% for 45 degrees and from 180% to 100% for 60 degrees oblique abutting fields. Using Titanium spoiler, junction dose decreased from 160% to 120% for 15 degrees, 180% to 120% for 30 degrees, 160% to 120% for 45 degrees and 180% to 110% for 60 degrees. In addition, penumbra width for 15 degrees, without spoiler in the surface was 10 mm and was increased to 15.5 mm with titanium spoiler. For 30 degrees, from 9 mm to 15 mm, for 45 degrees from 4 mm to 6 mm and for 60 degrees, from 5 mm to 8 mm. Conclusion Using spoilers, penumbra width at the surface increased, size and depth of hot spots was decreased and dose homogeneity improved at the junc­tion of abutting electron fields. Dose at the junction region of abutting oblique fields was improved significantly by using spoiler. Maximum dose at the junction region for 15⁰, 30⁰, 45⁰ and 60⁰ was decreased about 40%, 60%, 40% and 70% respectively for Titanium and about 50%, 60%, 40% and 80% for Aluminum. Considering significantly decrease in maximum dose using titanium spoiler, unfortunately, dose distribution in the junction region was not decreased less than 110%.

Keywords: abutting fields, electron beam, radiation therapy, spoilers

Procedia PDF Downloads 142