Search results for: quick fix GPS

Authors: Neil Fourati

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Collaboration between public and private stakeholders for agricultural development are today lacking in Tunisia. The last dictatorship witnessed by the country has deteriorated the necessary trust between the state and small farmers for the realization of development projects, in particular in the interior, disadvantaged regions of the country. These regions, where the youth unemployment rate is above 30%, have been the heart of the uprising that preceded the revolution. The transitional period that the country is going through since 2011 is an opportunity for the emergence of new governance systems in the context of the decentralization. The latter is recognized in the 2nd Tunisian Republic constitution as the basis of regional management. Civil society participation to the decision-making process is considered as a mean to identify measures that are more coherent with local populations’ needs. The development of agriculture and food value chains in rural areas is relevant within the framework of the implementation of new decisions systems that require public-private collaborations. These new systems can lead to actions in favor of improving living conditions of rural populations. The diverisification of activities around agriculture can be a solution for job creation and local value creation. The project for the promotion of sustainable agriculture and rural development in Tunisia has designed and implemented a multi-stakeholder dialogue process for the development of local value chains platforms in disadvantaged areas of the country. The platforms gather public and private organizations ; as well civil society organizations ; that intervene in a locality in relation to the production transformation or product’s commercialization. The role of these platforms is to formulate realize and evaluate collaborative actions or projects for the promotion of the concerned product and territory. The dialogue process steps allow to create the necessary collaboration conditions in order to promote viable collectivities, dynamic economies and healthy environments. Effectively, the dialogue process steps allow to identify the local leaders. These leaders recognize the development constraints and opportunities. They deal with key and gathering subjects around the collaborative projects or actions. They take common decisions in order to create effective coalitions for the implementation of common actions. The plateforms realize quick success so as to build trust. The project has supported the formulation of 22 collaborative projects. Seven priority collaborative projects have been realized. Each collaborative project includes 3 parts : the signature of the collaboration conventions between public and private organizations, investment in the relevant material in order to increase productivity and the quality of local and products and finally management and technical training in favour of producers’ organizations for the promotion of local products. The implementation of this process has enabled to enhance the capacities of collaboration between local actors : producers, traders, processors and support structures from public sector and civil society. It also allowed to improve the efficiency and relevance of actions and measures for agriculture and rural development programs. Thus, the process for the development of local value chain platform is a basis for sustainable development of agriculture.

Keywords: governance, public private collaboration, rural development, value chains

Procedia PDF Downloads 245

Authors: Lauren G. Coggins

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Catheter-associated urinary tract infections (CAUTI) and central line-associated bloodstream infections (CLABSI) are among the most common healthcare-associated infections (HAI), contributing to prolonged lengths of stay, greater costs of patient care, and increased patient mortality. Evidence-based preventative care bundles exist to establish consistent, safe patient-care practices throughout an entire organization, helping to ensure the collective application of care strategies that aim to improve patient outcomes and minimize complications. The cardiac intensive care unit at a nationally ranked teaching and research hospital in the United States exceeded its annual CAUTI and CLABSI targets in the fiscal year 2019, prompting examination into the unit’s infection prevention efforts that included preventative care bundles for both HAIs. Adherence to the CAUTI and CLABSI preventative care bundles was evaluated through frequent audits conducted over three months, using standards and resources from The Joint Commission, a globally recognized leader in quality improvement in healthcare and patient care safety. The bundle elements with the lowest scores were identified as the most commonly missed elements. Three elements from both bundles, six elements in total, served as key content areas for the educational interventions targeted to bedside nurses. The CAUTI elements included appropriate urinary catheter order, appropriate continuation criteria, and urinary catheter care. The CLABSI elements included primary tubing compliance, needleless connector compliance, and dressing change compliance. An integrated, multi-platform education campaign featured content on each CAUTI and CLABSI preventative care bundle in its entirety, with additional reinforcement focused on the lowest scoring elements. One-on-one educational materials included an informational pamphlet, badge buddy, a presentation to reinforce nursing care standards, and real-time application through case studies and electronic health record demonstrations. A digital hub was developed on the hospital’s Intranet for quick access to unit resources, and a bulletin board helped track the number of days since the last CAUTI and CLABSI incident. Audits continued to be conducted throughout the education campaign, and staff were given real-time feedback to address any gaps in adherence. Nearly every nurse in the cardiac intensive care unit received all educational materials, and adherence to all six key bundle elements increased after the implementation of educational interventions. Recommendations from this implementation include providing consistent, comprehensive education across multiple teaching tools and regular audits to track adherence. The multi-platform education campaign brought focus to the evidence-based CAUTI and CLABSI bundles, which in turn will help to reduce CAUTI and CLABSI rates in clinical practice.

Keywords: education, healthcare-associated infections, infection, nursing, prevention

Procedia PDF Downloads 84

Authors: Fei Jia, Xingjian Bai, Xiaowei Zhang, Wenjie Yan, Ruitong Dai, Xingmin Li, Jozef Kokini

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Pseudomonas aeruginosa is a Gram-negative, aerobic, opportunistic human pathogen that is present in the soil, water, and food. This microbe has been recognized as a representative food-borne spoilage bacterium that can lead to many types of infections. Considering the casualties and property loss caused by P. aeruginosa, the development of a rapid and reliable technique for the detection of P. aeruginosa is crucial. The whole-cell aptasensor, an emerging biosensor using aptamer as a capture probe to bind to the whole cell, for food-borne pathogens detection has attracted much attention due to its convenience and high sensitivity. Here, a low-field magnetic resonance imaging (LF-MRI) aptasensor for the rapid detection of P. aeruginosa was developed. The basic detection principle of the magnetic relaxation switch (MRSw) nanosensor lies on the ‘T₂-shortening’ effect of magnetic nanoparticles in NMR measurements. Briefly speaking, the transverse relaxation time (T₂) of neighboring water protons get shortened when magnetic nanoparticles are clustered due to the cross-linking upon the recognition and binding of biological targets, or simply when the concentration of the magnetic nanoparticles increased. Such shortening is related to both the state change (aggregation or dissociation) and the concentration change of magnetic nanoparticles and can be detected using NMR relaxometry or MRI scanners. In this work, two different sizes of magnetic nanoparticles, which are 10 nm (MN₁₀) and 400 nm (MN₄₀₀) in diameter, were first immobilized with anti- P. aeruginosa aptamer through 1-Ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC)/N-hydroxysuccinimide (NHS) chemistry separately, to capture and enrich the P. aeruginosa cells. When incubating with the target, a ‘sandwich’ (MN₁₀-bacteria-MN₄₀₀) complex are formed driven by the bonding of MN400 with P. aeruginosa through aptamer recognition, as well as the conjugate aggregation of MN₁₀ on the surface of P. aeruginosa. Due to the different magnetic performance of the MN₁₀ and MN₄₀₀ in the magnetic field caused by their different saturation magnetization, the MN₁₀-bacteria-MN₄₀₀ complex, as well as the unreacted MN₄₀₀ in the solution, can be quickly removed by magnetic separation, and as a result, only unreacted MN₁₀ remain in the solution. The remaining MN₁₀, which are superparamagnetic and stable in low field magnetic field, work as a signal readout for T₂ measurement. Under the optimum condition, the LF-MRI platform provides both image analysis and quantitative detection of P. aeruginosa, with the detection limit as low as 100 cfu/mL. The feasibility and specificity of the aptasensor are demonstrated in detecting real food samples and validated by using plate counting methods. Only two steps and less than 2 hours needed for the detection procedure, this robust aptasensor can detect P. aeruginosa with a wide linear range from 3.1 ×10² cfu/mL to 3.1 ×10⁷ cfu/mL, which is superior to conventional plate counting method and other molecular biology testing assay. Moreover, the aptasensor has a potential to detect other bacteria or toxins by changing suitable aptamers. Considering the excellent accuracy, feasibility, and practicality, the whole-cell aptasensor provides a promising platform for a quick, direct and accurate determination of food-borne pathogens at cell-level.

Keywords: magnetic resonance imaging, meat spoilage, P. aeruginosa, transverse relaxation time

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Authors: Ashish Kumar Dwivedi

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Uttar Pradesh is largest part of Indian Federal system encapsulating twenty two million populations and has huge cultural, economic and religious diversity. The newly elected 18 months old state leadership of Uttar Pradesh has envisaged and initiated various proactive strides for the public grievance redressal and inclusive development schemes for all the sections of population from its very day of assumption of the office by Hon’ble Chief Minster Shri Yogi Adtiyanath. These initiatives also include Departmental responses via social media handles as Twitter, Facebook Page, and Web interaction. In the same course, every department of state government has been guided for the correct usage of verified social media handle separately and in co-ordination with other departments. These guidelines included making new WhatsApp groups to connect technocrats and politicians to communicate on common platform. Minister for Department of Infrastructure and Industrial Development, Shri Satish Mahana is a very popular leader and very intuitive statesman, has thousands of followers on social media and his accounts receive almost three hundred individually mentioned notifications from the various parts of Uttar Pradesh. These notifications primarily include problems related to livelihood and grievances concerned to department. To address these communications, a body of five experts has been set who are actively responding on various levels and increase bureaucratic engagements with marginalized sections of society. With reference to above background, this piece of research was conducted to analyze, categorize and derive effective implementation of public policies via social media platforms. This act of responsiveness has brought positive change in the mindset of population for the government, which was missed earlier. Department of Industrial Development in the Government is also inclined to attract investors aiming to become first trillion-dollar economy of India henceforth department also organized two major successful events in last one year. These events were also frame worked on social media platform to update 2.5 million population of state who is actively using social media in many ways. To analyze change scientifically, this study has been conducted and big data has been collected from October 2017 to September 2018 from the departmental social media handles as Twitter, Facebook, and emails. For this data, a statistical study has been conducted to analyze sentiments and expectations, specific and common requirement of communities, nature of grievances and their effective elucidation fitted into government policies. The control sample has also been taken from previous government activities to analyze the change. The statistical study used tools such as correlation study and principal component analysis. Also in this research communication, the modus operandi of grievance redressal, proliferation of government policies, connections to their beneficiaries and quick response procedure will be discussed.

Keywords: correlation study, principal component analysis, bureaucratic engagements, social media

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Authors: Heitor Oliveira, Gabriele De-Waal, Juergen Schmenger, Lynsey Godfrey, Tibor Kovacs

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Rheolaser MASTER™ makes use of multiple scattering of light, caused by scattering objects in a continuous medium (such as droplets and particles in colloids), to characterize the viscoelasticity of soft materials. It offers an alternative to conventional rheometers to characterize viscoelasticity of products such as hair cosmetics. Up to six simultaneous measurements at controlled temperature can be carried out simultaneously (10-15 min), and the method requires only minor sample preparation work. Conversely to conventional rheometer based methods, no mechanical stress is applied to the material during the measurements. Therefore, the properties of the exact same sample can be monitored over time, like in aging and stability studies. We determined the elastic index (EI) of water/emulsion mixtures (1 ≤ fat alcohols (FA) ≤ 5 wt%) and emulsion/gel-network mixtures (8 ≤ FA ≤ 17 wt%) and compared with the elastic/sorage mudulus (G’) for the respective samples using a TA conventional rheometer with flat plates geometry. As expected, it was found that log(EI) vs log(G’) presents a linear behavior. Moreover, log(EI) increased in a linear fashion with solids level in the entire range of compositions (1 ≤ FA ≤ 17 wt%), while rheometer measurements were limited to samples down to 4 wt% solids level. Alternatively, a concentric cilinder geometry would be required for more diluted samples (FA > 4 wt%) and rheometer results from different sample holder geometries are not comparable. The plot of the rheolaser output parameters solid-liquid balance (SLB) vs EI were suitable to monitor product aging processes. These data could quantitatively describe some observations such as formation of lumps over aging time. Moreover, this method allowed to identify that the different specifications of a key raw material (RM < 0.4 wt%) in the respective gel-network (GN) product has minor impact on product viscoelastic properties and it is not consumer perceivable after a short aging time. Broadening of a RM spec range typically has a positive impact on cost savings. Last but not least, the photon path length (λ*)—proportional to droplet size and inversely proportional to volume fraction of scattering objects, accordingly to the Mie theory—and the EI were suitable to characterize product destabilization processes (e.g., coalescence and creaming) and to predict product stability about eight times faster than our standard methods. Using these parameters we could successfully identify formulation and process parameters that resulted in unstable products. In conclusion, Rheolaser allows quick and reliable characterization of viscoelastic properties of hair cosmetics that are related to their performance and stability. It operates in a broad range of product compositions and has applications spanning from the formulation of our hair cosmetics to fast release criteria in our production sites. Last but not least, this powerful tool has positive impact on R&D development time—faster delivery of new products to the market—and consequently on cost savings.

Keywords: colloids, hair cosmetics, light scattering, performance and stability, soft materials, viscoelastic properties

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Authors: Dan Kanmegne

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Africa will become the most populated continent by the end of the century, with around 4 billion inhabitants. Food security and climate changes will become continental issues since agricultural practices depend on climate but also contribute to global emissions and land degradation. Agroforestry has been identified as a cost-efficient and reliable strategy to address these two issues. It is defined as the integrated management of trees and crops/animals in the same land unit. Agroforestry provides benefits in terms of goods (fruits, medicine, wood, etc.) and services (windbreaks, fertility, etc.), and is acknowledged to have a great potential for carbon sequestration; therefore it can be integrated into reduction mechanisms of carbon emissions. Particularly in sub-Saharan Africa, the constraint stands in the lack of information about both areas under agroforestry and the characterization (composition, structure, and management) of each agroforestry system at the country level. This study describes and quantifies “what is where?”, earliest to the quantification of carbon stock in different systems. Remote sensing (RS) is the most efficient approach to map such a dynamic technology as agroforestry since it gives relatively adequate and consistent information over a large area at nearly no cost. RS data fulfill the good practice guidelines of the Intergovernmental Panel On Climate Change (IPCC) that is to be used in carbon estimation. Satellite data are getting more and more accessible, and the archives are growing exponentially. To retrieve useful information to support decision-making out of this large amount of data, satellite data needs to be organized so to ensure fast processing, quick accessibility, and ease of use. A new solution is a data cube, which can be understood as a multi-dimensional stack (space, time, data type) of spatially aligned pixels and used for efficient access and analysis. A data cube for Burkina Faso has been set up from the cooperation project between the international service provider WASCAL and Germany, which provides an accessible exploitation architecture of multi-temporal satellite data. The aim of this study is to map and characterize agroforestry systems using the Burkina Faso earth observation data cube. The approach in its initial stage is based on an unsupervised image classification of a normalized difference vegetation index (NDVI) time series from 2010 to 2018, to stratify the country based on the vegetation. Fifteen strata were identified, and four samples per location were randomly assigned to define the sampling units. For safety reasons, the northern part will not be part of the fieldwork. A total of 52 locations will be visited by the end of the dry season in February-March 2020. The field campaigns will consist of identifying and describing different agroforestry systems and qualitative interviews. A multi-temporal supervised image classification will be done with a random forest algorithm, and the field data will be used for both training the algorithm and accuracy assessment. The expected outputs are (i) map(s) of agroforestry dynamics, (ii) characteristics of different systems (main species, management, area, etc.); (iii) assessment report of Burkina Faso data cube.

Keywords: agroforestry systems, Burkina Faso, earth observation data cube, multi-temporal image classification

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Authors: Khlood F. Salman, Richard Zoucha, Hani Nawafleh

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Introduction: Jordan ranks the fourth highest breast cancer prevalence after Lebanon, Bahrain, and Kuwait. Considerable evidence showed that cultural, ethnic, and economic differences influence a woman’s practice to early detection and prevention of breast cancer. Objectives: To understand women’s health beliefs and values in relation to early detection of breast cancer; and to explore the impact of these beliefs on their decisions regarding reluctance or acceptance of early detection measures such as mammogram screening. Design: A qualitative focused ethnography was used to collect data for this study. Settings: The study was conducted in the second largest city surrounded by a large rural area in Ma’an- Jordan. Participants: A total of twenty seven women, with no history of breast cancer, between the ages of 18 and older, who had prior health experience with health providers, and were willing to share elements of personal health beliefs related to breast health within the larger cultural context. The participants were recruited using the snowball method and words of mouth. Data collection and analysis: A short questionnaire was designed to collect data related to socio demographic status (SDQ) from all participants. A Semi-structured interviews guide was used to elicit data through interviews with the informants. Nvivo10 a data manager was utilized to assist with data analysis. Leininger’s four phases of qualitative data analysis was used as a guide for the data analysis. The phases used to analyze the data included: 1) Collecting and documenting raw data, 2) Identifying of descriptors and categories according to the domains of inquiry and research questions. Emic and etic data is coded for similarities and differences, 3) Identifying patterns and contextual analysis, discover saturation of ideas and recurrent patterns, and 4) Identifying themes and theoretical formulations and recommendations. Findings: Three major themes were emerged within the cultural and religious context; 1. Fear, denial, embarrassment and lack of knowledge were common perceptions of Ma’anis’ women regarding breast health and screening mammography, 2. Health care professionals in Jordan were not quick to offer information and education about breast cancer and screening, and 3. Willingness to learn about breast health and cancer prevention. Conclusion: The study indicated the disparities between the infrastructure and resourcing in rural and urban areas of Jordan, knowledge deficit related to breast cancer, and lack of education about breast health may impact women’s decision to go for a mammogram screening. Cultural beliefs, fear, embarrassments as well as providers lack of focus on breast health were significant contributors against practicing breast health. Health providers and policy makers should provide resources for the establishment health education programs regarding breast cancer early detection and mammography screening. Nurses should play a major role in delivering health education about breast health in general and breast cancer in particular. A culturally appropriate health awareness messages can be used in creating educational programs which can be employed at the national levels.

Keywords: breast health, beliefs, cultural context, ethnography, mammogram screening

Procedia PDF Downloads 272

Authors: Dorian Audot, Isobel Margaret Thompson, Dominic Hudson, Joseph Banks, Martin Warner

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In competitive swimming, after dives and turns, athletes perform underwater undulatory swimming (UUS), copying marine mammals’ method of locomotion. The body, performing this wave-like motion, accelerates the fluid downstream in its vicinity, generating propulsion with minimal resistance. Through this technique, swimmers can maintain greater speeds than surface swimming and take advantage of the overspeed granted by the dive (or push-off). Almost all previous work has considered UUS when performed at maximum effort. Critical parameters to maximize UUS speed are frequently discussed; however, this does not apply to most races. In only 3 out of the 16 individual competitive swimming events are athletes likely to attempt to perform UUS with the greatest speed, without thinking of the cost of locomotion. In the other cases, athletes will want to control the speed of their underwater swimming, attempting to maximise speed whilst considering energy expenditure appropriate to the duration of the event. Hence, there is a need to understand how swimmers adapt their underwater strategies to optimize the speed within the allocated energetic cost. This paper develops a consistent methodology that enables different sets of UUS kinematics to be investigated. These may have different propulsive efficiencies and force generation mechanisms (e.g.: force distribution along with the body and force magnitude). The developed methodology, therefore, needs to: (i) provide an understanding of the UUS propulsive mechanisms at different speeds, (ii) investigate the key performance parameters when UUS is not performed solely for maximizing speed; (iii) consistently determine the propulsive efficiency of a UUS technique. The methodology is separated into two distinct parts: kinematic data acquisition and computational fluid dynamics (CFD) analysis. For the kinematic acquisition, the position of several joints along the body and their sequencing were either obtained by video digitization or by underwater motion capture (Qualisys system). During data acquisition, the swimmers were asked to perform UUS at a constant depth in a prone position (facing the bottom of the pool) at different speeds: maximum effort, 100m pace, 200m pace and 400m pace. The kinematic data were input to a CFD algorithm employing a two-dimensional Large Eddy Simulation (LES). The algorithm adopted was specifically developed in order to perform quick unsteady simulations of deforming bodies and is therefore suitable for swimmers performing UUS. Despite its approximations, the algorithm is applied such that simulations are performed with the inflow velocity updated at every time step. It also enables calculations of the resistive forces (total and applied to each segment) and the power input of the modeled swimmer. Validation of the methodology is achieved by comparing the data obtained from the computations with the original data (e.g.: sustained swimming speed). This method is applied to the different kinematic datasets and provides data on swimmers’ natural responses to pacing instructions. The results show how kinematics affect force generation mechanisms and hence how the propulsive efficiency of UUS varies for different race strategies.

Keywords: CFD, efficiency, human swimming, hydrodynamics, underwater undulatory swimming

Procedia PDF Downloads 187

Authors: Anantha S. Babbili

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This paper analyzes the current media practices dominant in global journalistic practices within the framework of world press theories of Libertarian, Authoritarian, Communist, and Social Responsibility to evaluate their efficacy in addressing their role in the coverage of the coronavirus, also known as COVID-19. The global media flows, determinants of news coverage, and international awareness and the Western view of the world will be critically analyzed within the context of the prevalent news values that underpin free press and media coverage of the world. While evaluating the global discourse paramount to a sustained and dispassionate understanding of world events, this paper proposes an ethical framework that brings clarity devoid of sensationalism, partisanship, right-wing and left-wing interpretations to a breaking and dangerous development of a pandemic. As the world struggles to contain the coronavirus pandemic with death climbing close to 6,000 from late January to mid-March, 2020, the populations of the developed as well as the developing nations are beset with news media renditions of the crisis that are contradictory, confusing and evoking anxiety, fear and hysteria. How are we to understand differing news standards and news values? What lessons do we as journalism and mass media educators, researchers, and academics learn in order to construct a better news model and structure of media practice that addresses science, health, and media literacy among media practitioners, journalists, and news consumers? As traditional media struggles to cover the pandemic to its audience and consumers, social media from which an increasing number of consumers get their news have exerted their influence both in a positive way and in a negative manner. Even as the world struggles to grasp the full significance of the pandemic, the World Health Organization (WHO) has been feverishly battling an additional challenge related to the pandemic in what it termed an 'infodemic'—'an overabundance of information, some accurate and some not, that makes it hard for people to find trustworthy sources and reliable guidance when they need it.' There is, indeed, a need for journalism and news coverage in times of pandemics that reflect social responsibility and ethos of public service journalism. Social media and high-tech information corporations, collectively termed GAMAF—Google, Apple, Microsoft, Amazon, and Facebook – can team up with reliable traditional media—newspapers, magazines, book publishers, radio and television corporates—to ease public emotions and be helpful in times of a pandemic outbreak. GAMAF can, conceivably, weed out sensational and non-credible sources of coronavirus information, exotic cures offered for sale on a quick fix, and demonetize videos that exploit peoples’ vulnerabilities at the lowest ebb. Credible news of utility delivered in a sustained, calm, and reliable manner serves people in a meaningful and helpful way. The world’s consumers of news and information, indeed, deserve a healthy and trustworthy news media – at least in the time of pandemic COVID-19. Towards this end, the paper will propose a practical model for news media and journalistic coverage during times of a pandemic.

Keywords: COVID-19, international news flow, social media, social responsibility

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Authors: Emily Moore, Andrew Gaukroger, Matthew Solan, Lucy Bailey, Alexandra Boxall, Andrew Carne, Chintu Gadamsetty, Charlotte Morley, Katy Western, Iwona Kolodziejczyk

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Introduction: Rupture of the Achilles tendon is common and has a long recovery period. Most cases are managed non-operatively. Foot and Ankle Surgeons advise an ultrasound scan to check the gap between the torn ends. A large gap (with the ankle in equinus) is a relative indication for surgery. The definitive decision regarding surgical versus non-operative management can only be made once an ultrasound scan is undertaken and the patient is subsequently reviewed by a Foot and Ankle surgeon. To get to this point, the patient journey involves several hospital departments. In nearby trusts, patients reattend for a scan and go to the plaster room both before and after the ultrasound for removal and re-application of the cast. At a third visit to the hospital, the surgeon and patient discuss options for definitive treatment. It may take 2-3 weeks from the initial Emergency Department visit before the final treatment decision is made. This “wasted time” is ultimately added to the recovery period for the patient. In this hospital, Achilles rupture patients are seen in a weekly multidisciplinary OneStop Heel Pain clinic. This pathway was already efficient but subject to occasional frustrating delays if a key staff member was absent. A new pathway was introduced with the goal to reduce delays to a definitive treatment plan. Method: A retrospective series of Achilles tendon ruptures managed according to the 2019 protocol was identified. Time taken from the Emergency Department to have both an ultrasound scan and specialist Foot and Ankle surgical review were calculated. 30 consecutive patients were treated with our new pathway and prospectively followed. The time taken for a scan and for specialist review were compared to the 30 consecutive cases from the 2019 (pre-COVID) cohort. The new pathway includes 1. A new contoured splint applied to the front of the injured limb held with a bandage. This can be removed and replaced (unlike a plaster cast) in the ultrasound department, removing the need for plaster room visits. 2. Urgent triage to a Foot and Ankle specialist. 3. Ultrasound scan for assessment of rupture gap and deep vein thrombosis check. 4. Early decision regarding surgery. Transfer to weight bearing in a prosthetic boot in equinuswithout waiting for the once-a-week clinic. 5. Extended oral VTE prophylaxis. Results: The time taken for a patient to have both an ultrasound scan and specialist review fell > 50%. All patients in the new pathway reached a definitive treatment decision within one week. There were no significant differences in patient demographics or rates of surgical vs non-operative treatment. The mean time from Emergency Department visit to specialist review and ultrasound scan fell from 8.7 days (old protocol) to 2.9 days (new pathway). The maximum time for this fell from 23 days (old protocol) to 6 days (new pathway). Conclusion: Teamwork and innovation have improved the experience for patients with an Achilles tendon rupture. The new pathway brings many advantages - reduced time in the Emergency Department, fewer hospital visits, less time using crutches and reduced overall recovery time.

Keywords: orthopaedics, achilles rupture, ultrasound, innovation

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Authors: Yashas Bedre Raghavendra, Pim Vullers

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This study presents the design and implementation of an abstract cryptographic coprocessor, leveraging AMBA(Advanced Microcontroller Bus Architecture) protocols - APB (Advanced Peripheral Bus) and AHB (Advanced High-performance Bus), to enable seamless integration with the main CPU(Central processing unit) and enhance the coprocessor’s algorithm flexibility. The primary objective is to create a versatile coprocessor that can execute various cryptographic algorithms, including ECC(Elliptic-curve cryptography), RSA(Rivest–Shamir–Adleman), and AES (Advanced Encryption Standard) while providing a robust and secure solution for modern secure embedded systems. To achieve this goal, the coprocessor is equipped with a tightly coupled memory (TCM) for rapid data access during cryptographic operations. The TCM is placed within the coprocessor, ensuring quick retrieval of critical data and optimizing overall performance. Additionally, the program memory is positioned outside the coprocessor, allowing for easy updates and reconfiguration, which enhances adaptability to future algorithm implementations. Direct links are employed instead of DMA(Direct memory access) for data transfer, ensuring faster communication and reducing complexity. The AMBA-based communication architecture facilitates seamless interaction between the coprocessor and the main CPU, streamlining data flow and ensuring efficient utilization of system resources. The abstract nature of the coprocessor allows for easy integration of new cryptographic algorithms in the future. As the security landscape continues to evolve, the coprocessor can adapt and incorporate emerging algorithms, making it a future-proof solution for cryptographic processing. Furthermore, this study explores the addition of custom instructions into RISC-V ISE (Instruction Set Extension) to enhance cryptographic operations. By incorporating custom instructions specifically tailored for cryptographic algorithms, the coprocessor achieves higher efficiency and reduced cycles per instruction (CPI) compared to traditional instruction sets. The adoption of RISC-V 128-bit architecture significantly reduces the total number of instructions required for complex cryptographic tasks, leading to faster execution times and improved overall performance. Comparisons are made with 32-bit and 64-bit architectures, highlighting the advantages of the 128-bit architecture in terms of reduced instruction count and CPI. In conclusion, the abstract cryptographic coprocessor presented in this study offers significant advantages in terms of algorithm flexibility, security, and integration with the main CPU. By leveraging AMBA protocols and employing direct links for data transfer, the coprocessor achieves high-performance cryptographic operations without compromising system efficiency. With its TCM and external program memory, the coprocessor is capable of securely executing a wide range of cryptographic algorithms. This versatility and adaptability, coupled with the benefits of custom instructions and the 128-bit architecture, make it an invaluable asset for secure embedded systems, meeting the demands of modern cryptographic applications.

Keywords: abstract cryptographic coprocessor, AMBA protocols, ECC, RSA, AES, tightly coupled memory, secure embedded systems, RISC-V ISE, custom instructions, instruction count, cycles per instruction

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Authors: M. D. Haneef, R. B. Randall, Z. Peng

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Journal bearings used in IC engines are prone to premature failures and are likely to fail earlier than the rated life due to highly impulsive and unstable operating conditions and frequent starts/stops. Vibration signature extraction and wear debris analysis techniques are prevalent in the industry for condition monitoring of rotary machinery. However, both techniques involve a great deal of technical expertise, time and cost. Limited literature is available on the application of these techniques for fault detection in reciprocating machinery, due to the complex nature of impact forces that confounds the extraction of fault signals for vibration based analysis and wear prediction. This work is an extension of a previous study, in which an engine simulation model was developed using a MATLAB/SIMULINK program, whereby the engine parameters used in the simulation were obtained experimentally from a Toyota 3SFE 2.0 litre petrol engines. Simulated hydrodynamic bearing forces were used to estimate vibrations signals and envelope analysis was carried out to analyze the effect of speed, load and clearance on the vibration response. Three different loads 50/80/110 N-m, three different speeds 1500/2000/3000 rpm, and three different clearances, i.e., normal, 2 times and 4 times the normal clearance were simulated to examine the effect of wear on bearing forces. The magnitude of the squared envelope of the generated vibration signals though not affected by load, but was observed to rise significantly with increasing speed and clearance indicating the likelihood of augmented wear. In the present study, the simulation model was extended further to investigate the bearing wear behavior, resulting as a consequence of different operating conditions, to complement the vibration analysis. In the current simulation, the dynamics of the engine was established first, based on which the hydrodynamic journal bearing forces were evaluated by numerical solution of the Reynold’s equation. Also, the essential outputs of interest in this study, critical to determine wear rates are the tangential velocity and oil film thickness between the journal and bearing sleeve, which if not maintained appropriately, have a detrimental effect on the bearing performance. Archard’s wear prediction model was used in the simulation to calculate the wear rate of bearings with specific location information as all determinative parameters were obtained with reference to crank rotation. Oil film thickness obtained from the model was used as a criterion to determine if the lubrication is sufficient to prevent contact between the journal and bearing thus causing accelerated wear. A limiting value of 1 µm was used as the minimum oil film thickness needed to prevent contact. The increased wear rate with growing severity of operating conditions is analogous and comparable to the rise in amplitude of the squared envelope of the referenced vibration signals. Thus on one hand, the developed model demonstrated its capability to explain wear behavior and on the other hand it also helps to establish a correlation between wear based and vibration based analysis. Therefore, the model provides a cost-effective and quick approach to predict the impending wear in IC engine bearings under various operating conditions.

Keywords: condition monitoring, IC engine, journal bearings, vibration analysis, wear prediction

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Authors: David F. Nettleton, Elodie Bugnicourt, Christian Wasiak, Alejandro Rosales

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In this presentation, preliminary results are given for the modeling and calibration of two different industrial winding MIMO (Multiple Input Multiple Output) processes using machine learning techniques. In contrast to previous approaches which have typically used ‘black-box’ linear statistical methods together with a definition of the mechanical behavior of the process, we use non-linear machine learning algorithms together with a ‘white-box’ rule induction technique to create a supervised model of the fitting error between the expected and real force measures. The final objective is to build a precise model of the winding process in order to control de-tension of the material being wound in the first case, and the friction of the material passing through the die, in the second case. Case 1, Tension Control of a Winding Process. A plastic web is unwound from a first reel, goes over a traction reel and is rewound on a third reel. The objectives are: (i) to train a model to predict the web tension and (ii) calibration to find the input values which result in a given tension. Case 2, Friction Force Control of a Micro-Pullwinding Process. A core+resin passes through a first die, then two winding units wind an outer layer around the core, and a final pass through a second die. The objectives are: (i) to train a model to predict the friction on die2; (ii) calibration to find the input values which result in a given friction on die2. Different machine learning approaches are tested to build models, Kernel Ridge Regression, Support Vector Regression (with a Radial Basis Function Kernel) and MPART (Rule Induction with continuous value as output). As a previous step, the MPART rule induction algorithm was used to build an explicative model of the error (the difference between expected and real friction on die2). The modeling of the error behavior using explicative rules is used to help improve the overall process model. Once the models are built, the inputs are calibrated by generating Gaussian random numbers for each input (taking into account its mean and standard deviation) and comparing the output to a target (desired) output until a closest fit is found. The results of empirical testing show that a high precision is obtained for the trained models and for the calibration process. The learning step is the slowest part of the process (max. 5 minutes for this data), but this can be done offline just once. The calibration step is much faster and in under one minute obtained a precision error of less than 1x10-3 for both outputs. To summarize, in the present work two processes have been modeled and calibrated. A fast processing time and high precision has been achieved, which can be further improved by using heuristics to guide the Gaussian calibration. Error behavior has been modeled to help improve the overall process understanding. This has relevance for the quick optimal set up of many different industrial processes which use a pull-winding type process to manufacture fibre reinforced plastic parts. Acknowledgements to the Openmind project which is funded by Horizon 2020 European Union funding for Research & Innovation, Grant Agreement number 680820

Keywords: data model, machine learning, industrial winding, calibration

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Authors: Atin Adhikari, Sushma Kurella, Pratik Banerjee, Nabanita Mukherjee, Yamini M. Chandana Gollapudi, Bushra Shah

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Different sharp instruments, drilling machines, and high speed rotary instruments are routinely used in dental clinics during dental cleaning. Therefore, these cleaning procedures release a lot of oral microorganisms including bacteria in clinic air and may cause significant occupational bioaerosol exposure risks for dentists, dental hygienists, patients, and dental clinic employees. Two major goals of this study were to quantify volumetric airborne concentrations of bacteria and to assess overall microbial activity in this type of occupational environment. The study was conducted in several dental clinics of southern Georgia and 15 dental cleaning procedures were targeted for sampling of airborne bacteria and testing of overall microbial activity in settled dusts over clinic floors. For air sampling, a Biostage viable cascade impactor was utilized, which comprises an inlet cone, precision-drilled 400-hole impactor stage, and a base that holds an agar plate (Tryptic soy agar). A high-flow Quick-Take-30 pump connected to this impactor pulls microorganisms in air at 28.3 L/min flow rate through the holes (jets) where they are collected on the agar surface for approx. five minutes. After sampling, agar plates containing the samples were placed in an ice chest with blue ice and plates were incubated at 30±2°C for 24 to 72 h. Colonies were counted and converted to airborne concentrations (CFU/m3) followed by positive hole corrections. Most abundant bacterial colonies (selected by visual screening) were identified by PCR amplicon sequencing of 16S rRNA genes. For understanding overall microbial activity in clinic floors and estimating a general cleanliness of the clinic surfaces during or after dental cleaning procedures, ATP levels were determined in swabbed dust samples collected from 10 cm2 floor surfaces. Concentration of ATP may indicate both the cell viability and the metabolic status of settled microorganisms in this situation. An ATP measuring kit was used, which utilized standard luciferin-luciferase fluorescence reaction and a luminometer, which quantified ATP levels as relative light units (RLU). Three air and dust samples were collected during each cleaning procedure (at the beginning, during cleaning, and immediately after the procedure was completed (n = 45). Concentrations at the beginning, during, and after dental cleaning procedures were 671±525, 917±1203, and 899±823 CFU/m3, respectively for airborne bacteria and 91±101, 243±129, and 139±77 RLU/sample, respectively for ATP levels. The concentrations of bacteria were significantly higher than typical indoor residential environments. Although an increasing trend for airborne bacteria was observed during cleaning, the data collected at three different time points were not significantly different (ANOVA: p = 0.38) probably due to high standard deviations of data. The ATP levels, however, demonstrated a significant difference (ANOVA: p <0.05) in this scenario indicating significant change in microbial activity on floor surfaces during dental cleaning. The most common bacterial genera identified were: Neisseria sp., Streptococcus sp., Chryseobacterium sp., Paenisporosarcina sp., and Vibrio sp. in terms of frequencies of occurrences, respectively. The study concluded that bacterial exposure in dental clinics could be a notable occupational biohazard, and appropriate respiratory protections for the employees are urgently needed.

Keywords: bioaerosols, hospital hygiene, indoor air quality, occupational biohazards

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Authors: Paola Montenegro, Maria de los Angeles Balaguera Villa

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In February 2022 Colombia achieved a historic milestone in ensuring universal access to abortion rights with ruling C-055 of 2022 decriminalising abortion up to 24 weeks of gestation. In the context of this triumph and the expansion of telemedicine services in the wake of the COVID-19 pandemic, this research studied the acceptability of self-care abortion in young people (13 - 28 years) through a telemedicine service and also explored the primary needs that should be the focus of such care. The results shine light on a more comprehensive understanding of opportunities and challenges of teleabortion practices in a context that combines overall higher access to technology and low access to reliable information of safe abortion, stigma, and scarcity especially felt by transnational migrants, racialised people, trans men and non-binary people. Through a mixed methods approach, this study collected 5.736 responses to a virtual survey disseminated nationwide in Colombia and 47 in-person interviews (24 of them with people who were assigned female at birth and 21 with local key stakeholders in the abortion ecosystem). Quantitative data was analyzed using Stata SE Version 16.0 and qualitative analysis was completed through NVivo using thematic analysis. Key findings of the research suggest that self-care abortion is practice with growing acceptability among young people, but important adjustments must be made to meet quality of care expectations of users. Elements like quick responses from providers, lower costs, and accessible information were defined by users as decisive factors to choose over the abortion service provider. In general, the narratives in participants about quality care were centred on the promotion of autonomy and the provision of accompaniment and care practices, also perceived as transformative and currently absent of most health care services. The most staggering findings from the investigation are related to current barriers faced by young people in abortion contexts even when the legal barriers have: high rates of scepticism and distrust associated with pitfalls of telehealth and structural challenges associated with lacking communications infrastructure, among a few of them. Other important barriers to safe self-care abortion identified by participants surfaced like lack of privacy and confidentiality (especially in rural areas of the country), difficulties accessing reliable information, high costs of procedures and expenses related to travel costs or having to cease economic activities, waiting times, and stigma are among the primary barriers to abortion identified by participants. Especially in a scenario marked by unprecedented social, political and economic disruptions due to the COVID-19 pandemic, the commitment to design better care services that can be adapted to the identities, experiences, social contexts and possibilities of the user population is more necessary than ever. In this sense, the possibility of expanding access to services through telemedicine brings us closer to the opportunity to rethink the role of health care models in transforming the role of individuals and communities to make autonomous, safe and informed decisions about their own health and well-being.

Keywords: contraception, family planning, premarital fertility, unplanned pregnancy

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Authors: Anitha Kandasamy, Thirumurugan Ramaiah

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Interestingly, organic materials exhibit large optical nonlinearity with quick responses and having the flexibility of molecular tailoring using computational modelling and favourable synthetic methodologies. Pyridine based organic compounds and carboxylic acid contained aromatic compounds play a crucial role in crystal engineering of NCS complexes that displays admirable optical nonlinearity with fast response and favourable physicochemical properties such as low dielectric constant, wide optical transparency and large laser damage threshold value requires for optoelectronics device applications. Based on these facts, it was projected to form an acentric molecule of π-conjugated system interaction with appropriately replaced electron donor and acceptor groups for achieving higher SHG activity in which quinoline-2-carboyxlic acid is chosen as an electron acceptor and capable of acting as an acid as well as a base molecule, while 2-amino-4-methylpyridine is used as an electron donor and previously employed in numerous proton transfer complexes for synthesis of NLO materials for optoelectronic applications. 2-amino-4-mehtylpyridinium quinoline-2-carboxylate molecular complex (2AQ) is having π-donor-acceptor groups in which 2-amino-4-methylpyridine donates one of its electron to quinoline -2-carboxylic acid thereby forming a protonated 2-amino-4-methyl pyridinium moiety and mono ionized quinoline-2-carboxylate moiety which are connected via N-H…O intermolecular interactions with non-centrosymmetric crystal packing arrangement at microscopic scale is accountable to the enhancement of macroscopic second order NLO activity. The 2AQ crystal was successfully grown by a slow evaporation solution growth technique and its structure was determined in orthorhombic crystal system with acentric, P212121, space group. Hirshfeld surface analysis reveals that O…H intermolecular interactions primarily contributed with 31.0 % to the structural stabilization of 2AQ. The molecular structure of title compound has been confirmed by 1H and 13C NMR spectral studies. The vibrational modes of functional groups present in 2AQ have been assigned by using FTIR and FT-Raman spectroscopy. The grown 2AQ crystal exhibits high optical transparency with lower cut-off wavelength (275 nm) within the region of 275-1500 nm. The laser study confirmed that 2AQ exhibits high SHG efficiency of 12.6 times greater than that of KDP. TGA-DTA analysis revealed that 2AQ crystal had a thermal stability of 223 °C. The low dielectric constant and low dielectric loss at higher frequencies confirmed good crystalline nature with fewer defects of grown 2AQ crystal. The grown crystal exhibits soft material and positive photoconduction behaviour. Mulliken atomic distribution and FMOs analysis suggested that the strong intermolecular hydrogen bonding which lead to the enhancement of NLO activity. These properties suggest that 2AQ crystal is a suitable material for optoelectronic and laser frequency conversion applications.

Keywords: crystal growth, NLO activity, proton transfer complex, quantum chemical investigation

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Authors: Catherine S. Fichten, Tali Heiman, Mary Jorgensen, Mai Nhu Nguyen, Rhonda Amsel, Dorit Olenik-Shemesh

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The study examined Canadian and Israeli students' perceptions related to their intention to graduate from their program of studies. Canada and Israel are dissimilar in many ways that affect education, including language and alphabet. In addition, the postsecondary education systems differ. For example, in some parts of Canada (e.g., in Quebec, Canada’s 2nd largest province), students matriculate after 11 years of high school; in Israel, this typically occurs after 12 years. In addition, Quebec students attend two compulsory years of junior college before enrolling in a three-year university Bachelor program; in Israel students enroll in a three-year Bachelor program directly after matriculation. In addition, Israeli students typically enroll in the army shortly after high school graduation; in Canada, this is not the case. What the two countries do have in common is concern about the success of postsecondary students with disabilities. The present study was based on Ajzen’s Theory of Planned Behavior (TPB); the model suggests that behavior is influenced by Intention to carry it out. This, in turn, is predicted by the following correlated variables: Perceived Behavioral Control (i.e., ease or difficulty enacting the behavior - in this case graduation), Subjective Norms (i.e., perceived social/peer pressure from individuals important in the student’s life), and Attitude (i.e., positive or negative evaluation of graduation). A questionnaire was developed to test the TPB in previous Canadian studies and administered to 845 Canadian college students (755 nondisabled, 90 with LD/ADHD) who had completed at least one semester of studies) and to 660 Israeli university students enrolled in a Bachelor’s program (537 nondisabled, 123 with LD/ADHD). Because Israeli students were older than Canadian students we covaried age in SPSS-based ANOVA comparisons and included it in regression equations. Because females typically have better academic outcomes than males, gender was included in all analyses. ANOVA results indicate only a significant gender effect for Intention to graduate, with females having higher scores. Four stepwise regressions were conducted, with Intention to graduate as the predicted variable, and Gender and the three TPB predictors as independent variables (separate analyses for Israeli and Canadian samples with and without LD/ADHD). Results show that for samples with LD/ADHD, although Gender and Age were not significant predictors, the TPB predictors were, with all three TPB predictors being significant for the Canadian sample (i.e., Perceived Behavioral Control, Subjective Norms, Attitude, R2=.595), and two of the three (i.e., Perceived Behavioral Control, Subjective Norms) for the Israeli sample (R2=.528). For nondisabled students, the results for both countries show that all three TPB predictors were significant along with Gender: R2=.443 for Canada and R2=.332 for Israel; age was not significant. Our findings show that despite vast differences between our Canadian and Israeli samples, Intention to graduate was related to the three TPB predictors. This suggests that our TPB measure is valid for diverse samples and countries that it can be used as a quick, inexpensive way to predict graduation rates, and that strengthening the three predictor variables may result in higher graduation rates.

Keywords: disability, higher education, students, theory of planned behavior

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Authors: Arjun Kumar Rath, Titus Dhanasingh

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Embedded product development requires software to test hardware functionality during development and finding issues during manufacturing in larger quantities. As the components are getting integrated, the devices are tested for their full functionality using advanced software tools. Benchmarking tools are used to measure and compare the performance of product features. At present, these tests are based on a variety of methods involving varying hardware and software platforms. Typically, these tests are custom built for every product and remain unusable for other variants. A majority of the tests goes undocumented, not updated, unusable when the product is released. To bridge this gap, a solution accelerator in the form of a framework can address these issues for running all these tests from one place, using an off-the-shelf tests library in a continuous integration environment. There are many open-source test frameworks or tools (fuego. LAVA, AutoTest, KernelCI, etc.) designed for testing embedded system devices, with each one having several unique good features, but one single tool and framework may not satisfy all of the testing needs for embedded systems, thus an extensible framework with the multitude of tools. Embedded product testing includes board bring-up testing, test during manufacturing, firmware testing, application testing, and assembly testing. Traditional test methods include developing test libraries and support components for every new hardware platform that belongs to the same domain with identical hardware architecture. This approach will have drawbacks like non-reusability where platform-specific libraries cannot be reused, need to maintain source infrastructure for individual hardware platforms, and most importantly, time is taken to re-develop test cases for new hardware platforms. These limitations create challenges like environment set up for testing, scalability, and maintenance. A desirable strategy is certainly one that is focused on maximizing reusability, continuous integration, and leveraging artifacts across the complete development cycle during phases of testing and across family of products. To get over the stated challenges with the conventional method and offers benefits of embedded testing, an embedded test framework (ETF), a solution accelerator, is designed, which can be deployed in embedded system-related products with minimal customizations and maintenance to accelerate the hardware testing. Embedded test framework supports testing different hardwares including microprocessor and microcontroller. It offers benefits such as (1) Time-to-Market: Accelerates board brings up time with prepacked test suites supporting all necessary peripherals which can speed up the design and development stage(board bring up, manufacturing and device driver) (2) Reusability-framework components isolated from the platform-specific HW initialization and configuration makes the adaptability of test cases across various platform quick and simple (3) Effective build and test infrastructure with multiple test interface options and preintegrated with FUEGO framework (4) Continuos integration - pre-integrated with Jenkins which enabled continuous testing and automated software update feature. Applying the embedded test framework accelerator throughout the design and development phase enables to development of the well-tested systems before functional verification and improves time to market to a large extent.

Keywords: board diagnostics software, embedded system, hardware testing, test frameworks

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Authors: Kiran Datta, Daniella Holland-Hart, Anthony Byrne

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Introduction: Oesophago-gastric (OG) cancers are the fifth commonest in the UK, accounting for over 12,000 deaths each year. Most patients will present at later stages of the disease, with only 21% of patients with stage 4 disease surviving longer than a year. As a result, many patients are unsuitable for curative surgery and instead receive palliative treatment to improve prognosis and symptom burden. However, palliative chemotherapy can result in significant toxicity: almost half of the patients are unable to complete their chemotherapy regimen, with this proportion rising significantly in older and frailer patients. In addition, clinical trials often exclude older and frailer patients due to strict inclusion criteria, meaning there is limited evidence to guide which patients are most likely to benefit from palliative chemotherapy. Inappropriate chemotherapy administration is at odds with the goals of palliative treatment and care, which are to improve quality of life, and this also represents a significant resource expenditure. This literature review aimed to examine and appraise evidence regarding treatment resilience in order to guide clinicians in identifying the most suitable candidates for palliative chemotherapy. Factors influencing treatment resilience were assessed, as measured by completion rates, dose reductions, and toxicities. Methods: This literature review was conducted using rapid review methodology, utilising modified systematic methods. A literature search was performed across the MEDLINE, EMBASE, and Cochrane Library databases, with results limited to papers within the last 15 years and available in English. Key inclusion criteria included: 1) participants with either oesophageal, gastro-oesophageal junction, or gastric cancers; 2) patients treated with palliative chemotherapy; 3) available data evaluating the association between baseline participant characteristics and treatment resilience. Results: Of the 2326 papers returned, 11 reports of 10 studies were included in this review after excluding duplicates and irrelevant papers. Treatment resilience factors that were assessed included: age, performance status, frailty, inflammatory markers, and sarcopenia. Age was generally a poor predictor for how well patients would tolerate chemotherapy, while poor performance status was a better indicator of the need for dose reduction and treatment non-completion. Frailty was assessed across one cohort using multiple screening tools and was an effective marker of the risk of toxicity and the requirement for dose reduction. Inflammatory markers included lymphopenia and the Glasgow Prognostic Score, which assessed inflammation and hypoalbuminaemia. Although quick to obtain and interpret, these findings appeared less reliable due to the inclusion of patients treated with palliative radiotherapy. Sarcopenia and body composition were often associated with chemotherapy toxicity but not the rate of regimen completion. Conclusion: This review demonstrates that there are numerous measures that can estimate the ability of patients with oesophago-gastric cancer to tolerate palliative chemotherapy, and these should be incorporated into clinical assessments to promote personalised decision-making around treatment. Age should not be a barrier to receiving chemotherapy and older and frailer patients should be included in future clinical trials to better represent typical patients with oesophago-gastric cancers. Decisions regarding palliative treatment should be guided by these factors identified as well as patient preference.

Keywords: frailty, oesophago-gastric cancer, palliative chemotherapy, treatment resilience

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Bidzina Matsaberidze, Anna Sikharulidze, Gia Sirbiladze, Bezhan Ghvaberidze

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In the modern world emergency management decision support systems are actively used by state organizations, which are interested in extreme and abnormal processes and provide optimal and safe management of supply needed for the civil and military facilities in geographical areas, affected by disasters, earthquakes, fires and other accidents, weapons of mass destruction, terrorist attacks, etc. Obviously, these kinds of extreme events cause significant losses and damages to the infrastructure. In such cases, usage of intelligent support technologies is very important for quick and optimal location-transportation of emergency service in order to avoid new losses caused by these events. Timely servicing from emergency service centers to the affected disaster regions (response phase) is a key task of the emergency management system. Scientific research of this field takes the important place in decision-making problems. Our goal was to create an expert knowledge-based intelligent support system, which will serve as an assistant tool to provide optimal solutions for the above-mentioned problem. The inputs to the mathematical model of the system are objective data, as well as expert evaluations. The outputs of the system are solutions for Fuzzy Multi-Objective Emergency Location-Transportation Problem (FMOELTP) for disasters’ regions. The development and testing of the Intelligent Support System were done on the example of an experimental disaster region (for some geographical zone of Georgia) which was generated using a simulation modeling. Four objectives are considered in our model. The first objective is to minimize an expectation of total transportation duration of needed products. The second objective is to minimize the total selection unreliability index of opened humanitarian aid distribution centers (HADCs). The third objective minimizes the number of agents needed to operate the opened HADCs. The fourth objective minimizes the non-covered demand for all demand points. Possibility chance constraints and objective constraints were constructed based on objective-subjective data. The FMOELTP was constructed in a static and fuzzy environment since the decisions to be made are taken immediately after the disaster (during few hours) with the information available at that moment. It is assumed that the requests for products are estimated by homeland security organizations, or their experts, based upon their experience and their evaluation of the disaster’s seriousness. Estimated transportation times are considered to take into account routing access difficulty of the region and the infrastructure conditions. We propose an epsilon-constraint method for finding the exact solutions for the problem. It is proved that this approach generates the exact Pareto front of the multi-objective location-transportation problem addressed. Sometimes for large dimensions of the problem, the exact method requires long computing times. Thus, we propose an approximate method that imposes a number of stopping criteria on the exact method. For large dimensions of the FMOELTP the Estimation of Distribution Algorithm’s (EDA) approach is developed.

Keywords: epsilon-constraint method, estimation of distribution algorithm, fuzzy multi-objective combinatorial programming problem, fuzzy multi-objective emergency location/transportation problem

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Elena Parmentier, Henrik Endeman

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Introduction: Large mediastinal masses often present with diagnostic and clinical challenges due to compression of the respiratory and hemodynamic system. We present a case of a mediastinal mass with symptomatic mechanical compression of the trachea, resulting in challenging airway management. Methods: We present a case of 66-year-old male, complaining of progressive dysphagia. Initial esophagogastroscopy revealed a stenosis secondary to external compression, biopsies were inconclusive. Additional CT scan showed a large mediastinal mass of unknown origin, situated between the vertebrae and esophagus. Symptoms progressed and patient developed dyspnea and stridor. A new CT showed quick growth of the mass with compression of the trachea, subglottic to just above the carina. A tracheal covered stent was successfully placed. Endobronchial ultrasound revealed a large irregular mass without tracheal invasion, biopsies were taken. 4 days after stent placement, the patients’ condition deteriorated with worsening of stridor, dyspnea and desaturation. Migration of the tracheal stent into the right main bronchus was seen on chest X ray, with obstruction of the left main bronchus and secondary atelectasis. Different methods have been described in the literature for tracheobronchial stent removal (surgical, endoscopic, fluoroscopyguided), our first choice in this case was flexible bronchoscopy. However, this revealed tracheal compression above the migrated stent and passage of the scope occurred impossible. Patient was admitted to the ICU, high-flow nasal oxygen therapy was started and the situation stabilized, giving time for extensive assessment and preparation of the airway management approach. Close cooperation between the intensivist, pulmonologist, anesthesiologist and otorhinolaryngologist was essential. Results: In case of sudden deterioration, a protocol for emergency situations was made. Given the increased risk of additional tracheal compression after administration of neuromuscular blocking agents, an approach with awake fiberoptic intubation maintaining spontaneous ventilation was proposed. However, intubation without retrieval of the tracheal stent was found undesirable due to expected massive shunting over the left atelectatic lung. As rescue option, assistance of extracorporeal circulation was considered and perfusionist was kept on standby. The patient stayed stable and was transferred to the operating theatre. High frequency jet ventilation under general anesthesia resulted in desaturations up to 50%, making rigid bronchoscopy impossible. Subsequently an endotracheal tube size 8 could be placed successfully and the stent could be retrieved via bronchoscopy over (and with) the tube, after which the patient was reintubated. Finally, a tracheostomy (Shiley™ Tracheostomy Tube With Cuff, size 8) was placed, fiberoptic control showed a patent airway. Patient was readmitted to the ICU and could be quickly weaned of the ventilator. Pathology was positive for rhabdomyosarcoma, without indication for systemic therapy. Extensive surgery (laryngectomy, esophagectomy) was suggested, but patient refused and palliative care was started. Conclusion: Due to meticulous planning in an interdisciplinary team, we showed a successful airway management approach in this complicated case of critical airway compression secondary to a rare rhabdomyosarcoma, complicated by tracheal stent migration. Besides presenting our thoughts and considerations, we support exploring other possible approaches of this specific clinical problem.

Keywords: airway management, rhabdomyosarcoma, stent displacement, tracheal stenosis

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Authors: Bailey Houghtaling, Sarah Misyak

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Food access; the availability, affordability, convenience, and desirability of food and beverage products within communities, is influential on consumers’ purchasing and consumption decisions. These variables may contribute to lower dietary quality scores and a higher obesity prevalence documented among rural and disadvantaged populations in the United States (U.S.). Current research assessing linkages between food access and obesity outcomes has primarily focused on distance to a traditional grocery/supermarket store as a measure of optimality. However, low-income consumers especially, including U.S. Department of Agriculture’s Supplemental Nutrition Assistance Program (SNAP) participants, seem to utilize non-traditional food store formats with greater frequency for household dietary needs. Non-traditional formats have been associated with less nutritious food and beverage options and consumer purchases that are high in saturated fats, added sugars, and sodium. Authors’ formative research indicated differences by U.S. region and rurality in the distribution of traditional and non-traditional SNAP-authorized food store formats. Therefore, using Virginia as a case study, the purpose of this research was to determine if a relationship between store format, rurality, and obesity exists. This research applied SNAP-authorized food store data (food access points for SNAP as well as non-SNAP consumers) and obesity prevalence data by Virginia county using publicly available databases: (1) SNAP Retailer Locator, and; (2) U.S. County Health Rankings. The alpha level was set a priori at 0.05. All Virginia SNAP-authorized stores (n=6,461) were coded by format – grocery, drug, mass merchandiser, club, convenience, dollar, supercenter, specialty, farmers market, independent grocer, and non-food store. Simple linear regression was applied primarily to assess the relationship between store format and obesity. Thereafter, multiple variables were added to the regression to account for potential moderating relationships (e.g., county income, rurality). Convenience, dollar, non-food or restaurant, mass merchandiser, farmers market, and independent grocer formats were significantly, positively related to obesity prevalence. Upon controlling for urban-rural status and income, results indicated the following formats to be significantly related to county obesity prevalence with a small, positive effect: convenience (p=0.010), accounting for 0.3% of the variance in obesity prevalence; dollar (p=0.005; 0.5% of the variance), and; non-food (p=0.030; 1.3% of the variance) formats. These results align with current literature on consumer behavior at non-traditional formats. For example, consumers’ food and beverage purchases at convenience and dollar stores are documented to be high in saturated fats, added sugars, and sodium. Further, non-food stores (i.e., quick-serve restaurants) often contribute to a large portion of U.S. consumers’ dietary intake and thus poor dietary quality scores. Current food access research investigates grocery/supermarket access and obesity outcomes. These results suggest more research is needed that focuses on non-traditional food store formats. Nutrition interventions within convenience, dollar, and non-food stores, for example, that aim to enhance not only healthy food access but the affordability, convenience, and desirability of nutritious food and beverage options may impact obesity rates in Virginia. More research is warranted utilizing the presented investigative framework in other U.S. and global regions to explore the role and the potential of non-traditional food store formats to prevent and reduce obesity.

Keywords: food access, food store format, non-traditional food stores, obesity prevalence

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Authors: Agboka Komi Mensah, John Odindi, Elfatih M. Abdel-Rahman, Onisimo Mutanga, Henri Ez Tonnang

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Ecosystems are networks of organisms and populations that form a community of various species interacting within their habitats. Such habitats are defined by abiotic and biotic conditions that establish the initial limits to a population's growth, development, and reproduction. The habitat’s conditions explain the context in which species interact to access resources such as food, water, space, shelter, and mates, allowing for feeding, dispersal, and reproduction. Dispersal is an essential life-history strategy that affects gene flow, resource competition, population dynamics, and species distributions. Despite the importance of dispersal in population dynamics and survival, understanding the mechanism underpinning the dispersal of organisms remains challenging. For instance, when an organism moves into an ecosystem for survival and resource competition, its progression is highly influenced by extrinsic factors such as its physiological state, climatic variables and ability to evade predation. Therefore, greater spatial detail is necessary to understand organism dispersal dynamics. Understanding organisms dispersal can be addressed using empirical and mechanistic modelling approaches, with the adopted approach depending on the study's purpose Cellular automata (CA) is an example of these approaches that have been successfully used in biological studies to analyze the dispersal of living organisms. Cellular automata can be briefly described as occupied cells by an individual that evolves based on proper decisions based on a set of neighbours' rules. However, in the ambit of modelling individual organisms dispersal at the landscape scale, we lack user friendly tools that do not require expertise in mathematical models and computing ability; such as a visual analytics framework for tracking and forecasting the dispersal behaviour of organisms. The term "visual analytics" (VA) describes a semiautomated approach to electronic data processing that is guided by users who can interact with data via an interface. Essentially, VA converts large amounts of quantitative or qualitative data into graphical formats that can be customized based on the operator's needs. Additionally, this approach can be used to enhance the ability of users from various backgrounds to understand data, communicate results, and disseminate information across a wide range of disciplines. To support effective analysis of the dispersal of organisms at the landscape scale, we therefore designed Pydisp which is a free visual data analytics tool for spatiotemporal dispersal modeling built in Python. Its user interface allows users to perform a quick and interactive spatiotemporal analysis of species dispersal using bioecological and climatic data. Pydisp enables reuse and upgrade through the use of simple principles such as Fuzzy cellular automata algorithms. The potential of dispersal modeling is demonstrated in a case study by predicting the dispersal of Fopius arisanus (Sonan), endoparasitoids to control Bactrocera dorsalis (Hendel) (Diptera: Tephritidae) in Kenya. The results obtained from our example clearly illustrate the parasitoid's dispersal process at the landscape level and confirm that dynamic processes in an agroecosystem are better understood when designed using mechanistic modelling approaches. Furthermore, as demonstrated in the example, the built software is highly effective in portraying the dispersal of organisms despite the unavailability of detailed data on the species dispersal mechanisms.

Keywords: cellular automata, fuzzy logic, landscape, spatiotemporal

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Authors: Rajkumar Ghosh, Ananya Mukhopadhyay

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India has seen enormous urbanization in recent years, resulting in increased energy consumption and water demand in its metropolitan regions. Adoption of grid-connected solar rooftop systems and rainwater collection has gained significant popularity in urban areas to address these challenges while also boosting sustainability and environmental consciousness. Grid-connected solar rooftop systems offer a long-term solution to India's growing energy needs. Solar panels are erected on the rooftops of residential and commercial buildings to generate power by utilizing the abundant solar energy available across the country. Solar rooftop systems generate clean, renewable electricity, reducing reliance on fossil fuels and lowering greenhouse gas emissions. This is compatible with India's goal of reducing its carbon footprint. Urban residents and companies can save money on electricity by generating their own and possibly selling excess power back to the grid through net metering arrangements. India gives several financial incentives (subsidies 40% for system capacity 1 kW to 3 kW) to stimulate the building of solar rooftop systems, making them an economically viable option for city dwellers. India provides subsidies up to 70% to special states such as Uttarakhand, Sikkim, Himachal Pradesh, Jammu & Kashmir, and Lakshadweep. Incorporating solar rooftops into urban infrastructure contributes to sustainable urban expansion by alleviating pressure on traditional energy sources and improving air quality. Incorporating solar rooftops into urban infrastructure contributes to sustainable urban expansion by alleviating demand on existing energy sources and improving power supply reliability. Rainwater harvesting is another key component of India's sustainable urban development. It comprises collecting and storing rainwater for use in non-potable water applications such as irrigation, toilet flushing, and groundwater recharge. Rainwater gathering 2 helps to conserve water resources by lowering the demand for freshwater sources. This technology is crucial in water-stressed areas to ensure a sustainable water supply. Excessive rainwater runoff in metropolitan areas can lead to Urban flooding. Solar PV system with Rooftop Rainwater harvesting systems absorb and channel excess rainwater, which helps to reduce flooding and waterlogging in Smart cities. Rainwater harvesting systems are inexpensive and quick to set up, making them a tempting option for city dwellers and businesses looking to save money on water. Rainwater harvesting systems are now compulsory in several Indian states for specified types of buildings (bye law, Rooftop space ≥ 300 sq. m.), ensuring widespread adoption. Finally, grid-connected solar rooftop systems and rainwater collection are important to India's long-term urban development. They not only reduce the environmental impact of urbanization, but also empower individuals and businesses to control their energy and water requirements. The G20 summit will focus on green financing, fossil fuel phaseout, and renewable energy transition. The G20 Summit in New Delhi reaffirmed India's commitment to battle climate change by doubling renewable energy capacity. To address climate change and mitigate global warming, India intends to attain 280 GW of solar renewable energy by 2030 and Net Zero carbon emissions by 2070. With continued government support and increased awareness, these strategies will help India develop a more resilient and sustainable urban future.

Keywords: grid-connected solar PV system, rooftop rainwater harvesting, urban flood, groundwater, urban flooding, net zero carbon emission

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Authors: Tianqiao Zhang, Ye Tian, Yanliang Yin, Yichao Tian, Suzhai Tian, Weige Sun, Shuhui Gong, Limei Tang, Ruoliang Tang

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Introduction: Healthcare workers, especially the nurses all over the world, are highly vulnerable to work-related musculoskeletal disorders (WMSDs), experiencing high rates of neck, shoulder, and low back injuries, due to the unfavorable working conditions. To reduce WMSDs among nursing personnel, many workplace interventions have been developed and implemented. Unfortunately, the ongoing Covid-19 (SARS-CoV-2) pandemic has posed great challenges to the ergonomic practices and interventions in healthcare facilities, particularly the hospitals, since current Covid-19 mitigation measures, such as social distancing and working remotely, has substantially minimized in-person gatherings and trainings. On the other hand, hospitals throughout the world have been short-staffed, resulting in disturbance of shift scheduling and more importantly, the increased job demand among the available caregivers, particularly the doctors and nurses. With the latest development in communication technology, remote intervention measures have been developed as an alternative, without the necessity of in-person meetings. The Omaha System (OS) is a standardized classification system for nursing practices, including a problem classification system, an intervention system, and an outcome evaluation system. This paper describes the development of an OS-based ergonomic intervention program. Methods: First, a comprehensive literature search was performed among worldwide electronic databases, including PubMed, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), between journal inception to May 2020, resulting in a total of 1,418 scientific articles. After two independent screening processes, the final knowledge pool included eleven randomized controlled trial studies to develop the draft of the intervention program with Omaha intervention subsystem as the framework. After the determination of sample size needed for statistical power and the potential loss to follow-up, a total of 94 nurses from eight clinical departments agreed to provide written, informed consent to participate in the study, which were subsequently assigned into two random groups (i.e., intervention vs. control). A subgroup of twelve nurses were randomly selected to participate in a semi-structured interview, during which their general understanding and awareness of musculoskeletal disorders and potential interventions was assessed. Then, the first draft was modified to reflect the findings from these interviews. Meanwhile, the tentative program schedule was also assessed. Next, two rounds of consultation were conducted among experts in nursing management, occupational health, psychology, and rehabilitation, to further adjust and finalize the intervention program. The control group had access to all the information and exercise modules at baseline, while an interdisciplinary research team was formed and supervised the implementation of the on-line intervention program through multiple social media groups. Outcome measures of this comparative study included biomechanical load assessed by the Quick Exposure Check and stresses due to awkward body postures. Results and Discussion: Modification to the draft included (1) supplementing traditional Chinese medicine practices, (2) adding the use of assistive patient handling equipment, and (3) revising the on-line training method. Information module should be once a week, lasting about 20 to 30 minutes, for a total of 6 weeks, while the exercise module should be 5 times a week, each lasting about 15 to 20 minutes, for a total of 6 weeks.

Keywords: ergonomic interventions, musculoskeletal disorders (MSDs), omaha system, nurses, Covid-19

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