Search results for: community based rehabilitation

Authors: Clarence Dissanayake, Anishka A. Hettiarachchi

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Landscape architecture needs to encompass a placemaking process carefully composing and manipulating landscape elements to address perceptual needs of humans, especially aesthetic, psychological and spiritual. The objective of this qualitative investigation is to inquire the impact of elements of rock and water combination on landscape perception and related feelings, emotions, and behavior. The past empirical studies have assessed the impact of landscape elements in isolation on user preference, yet the combined effect of elements have been less considered. This research was conducted with reference to the verity of qualities of water and rock through a visual landscape quality assessment focusing on landscape qualities derived from five visual concepts (coherence, historicity imageability, naturalness, and ephemera). 'Kaludiya Pokuna' archeological site in Anuradhapura was investigated with a sample of University students (n=19, male 14, female 5, age 20-25) using a five-point Likert scale via a perception based questionnaire and a visitor employed photographic survey (VEP). Two hypothetical questions were taken into investigation concerning biophilic (naturalness) and topophilic (historicity) aspects of humans to prefer a landscape with rock and water. The findings revealed that this combination encourages both biophilic and topophilic aspects, but in varying degrees. The identified hierarchy of visual concepts based on visitor’s preference signify coherence (93%), historicity (89%), imageability (79%), naturalness (75%) and ephemera (70%) respectively. It was further revealed that this combination creates a scenery more coherent dominating information processing aspect of humans to perceive a landscape over the biophilic and topophilic aspects. Different characteristics and secondary landscape effects generated by rock and water combination were found to affect in transforming a space into a place, full filling the aesthetic and spiritual aspects of the visitors. These findings enhance a means of making places for people, resource management and historical landscape conservation. Equalization of gender based participation, taking diverse cases and increasing the sample size with more analytical photographic analysis are recommended to enhance the quality of further research.

Keywords: landscape perception, visitor’s preference, rock and water combination, visual concepts

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Authors: Maria Kazantzaki, Evangelos Tsakalos, Eleni Filippaki, Yannis Bassiakos

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Mediterranean areas are characterized by intense seismic and volcanic activity as well as eustatic changes, the result of which is the creation of particularly vulnerable coastal zones. The most vulnerable are low-lying coastal areas, the geomorphological evolution of which are highly affected by natural processes and anthropogenic interventions. Therefore, assessing changes that take place along coastal zones is of great importance in order to enable the development of integrated coastal management plans. A characteristic case is the gulf of Mirabello in N.E Crete, where intense coastal erosion, in combination with the tectonic subsidence of the area, threatens a large part of the coastal zone, resulting in direct socio-economic impacts. The present study assesses the temporal geomorphological changes that have taken place in the coastal zone of Mirabello gulf to provide a clear frame of the coastal zone evolution over time and performs a vulnerability assessment based on the coastal vulnerability index (CVI) methodology by Thieler and Hammar-Klose, considering geological features, coastal slope, relative sea-level change, shoreline erosion/accretion rates and mean significant wave height as well as mean tide range in the area. In light of this, an impact assessment, based on three different sea level rise scenarios, is also performed and presented.

Keywords: coastal vulnerability index, coastal erosion, GIS, sea level rise

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Authors: Alieu B. Sanneh

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In a country where there are minimal economic opportunities, with a declining living condition of the people, do electorates in Africa’s newest democracy reevaluate their support for a candidate based on issues or ethnicity. In the 2016 presidential election in The Gambia, the opposition coalition party had successfully managed to overthrow an authoritarian government, which has ruled the country for 22 years. The results of the election are not only surprising but also presented an interesting theoretical puzzle that raises important this paper is going to address. An important fact is that dictator had organized an election which he lost, and this paper will assess the voting decisions of Gambian electorates to determine whether they were more concerned with issues such as status of the economy, human rights abuses by the Jammeh administration or the ethnicities of the contestants who took part in the election. This study uses field survey data, conducted six months after this historic vote, to evaluate the opinion of the electorates. Contrary to the notion of the prevalence of ethnic voting in African elections, an argument made by many scholars, this study concluded that Gambian voters were more concerned with issues such as the economy and human rights under the Jammeh administration than they were for the ethnicities of the candidates. The election was issue-based, and that Jammeh lost the polls due to the concern the electorate had on human rights abuses by his government.

Keywords: election, issue, ethnicity, regime change

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Authors: Mohammad Aziz Shah Mohamed Arip, Aslina Ahmad, Fauziah Mohd Sa'ad, Samsiah Mohd Jais, Syed Sofian Syed Salim

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This experimental study evaluates the effect of using Cognitive-Behavioral Therapy (CBT) and Multidimensional Self-Concept Model (MSCM) in a drug prevention programme to increase resiliency and reduce aggression among at-risk youth in Malaysia. A number of 60 (N=60) university students who were at-risk of taking drugs were involved in this study. Participants were identified with self-rating scales, Adolescent Resilience Attitude Scale (ARAS) and Aggression Questionnaire. Based on the mean score of these instruments, the participants were divided into the treatment group, and the control group. Data were analyzed using t-test. The finding showed that the mean score of resiliency was increased in the treatment group compared to the control group. It also shows that the mean score of aggression was reduced in the treatment group compared to the control group. Drug Prevention Programme was found to help in enhancing resiliency and reducing aggression among participants in the treatment group compared to the controlled group. Implications were given regarding the preventive actions on drug abuse among youth in Malaysia.

Keywords: drug prevention programme, cognitive-behavioral therapy (CBT), multidimensional self concept model (MSCM), resiliency, aggression, at-risk youth

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Authors: Monika Konieczyńska, Joanna Fajfer, Olga Lipińska

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In Poland works related to the exploration and prospection of unconventional hydrocarbons (natural gas accumulated in the Silurian shale formations) started in 2007, based on the experience of the other countries that have created new possibilities for the use of existing hydrocarbons resources. The highly water-consuming process of hydraulic fracturing is required for the exploitation of shale gas which implies a need to ensure large volume of water available. As a result considerable amount of mining waste is generated, particularly liquid waste, i.e. flowback fluid with variable chemical composition. The chemical composition of the flowback fluid depends on the composition of the fracturing fluid and the chemistry of the fractured geological formations. Typically, flowback fluid is highly salinated, can be enriched in heavy metals, including rare earth elements, naturally occurring radioactive materials and organic compounds. The generated fluids considered as the extractive waste should be properly managed in the recovery or disposal facility. Problematic issue is both high hydration of waste as well as their variable chemical composition. Also the limited capacity of currently operating facilities is a growing problem. Based on the estimates, currently operating facilities will not be sufficient for the need of waste disposal when extraction of unconventional hydrocarbons starts. Further more, the content of metals in flowback fluids including rare earth elements is a considerable incentive to develop technology of metals recovery. Also recycling is a key factor in terms of selection of treatment process, which should provide that the thresholds required for reuse are met. The paper will present the study of the flowback fluids chemical composition, based on samples from hydraulic fracturing processes performed in Poland. The scheme of flowback fluid cleaning and recovering technology will be reviewed along with a discussion of the results and an assessment of environmental impact, including all generated by-products. The presented technology is innovative due to the metal recovery, as well as purified water supply for hydraulic fracturing process, which is significant contribution to reducing water consumption.

Keywords: environmental impact, flowback fluid, management of special waste streams, metals recovery, shale gas

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Authors: Varun Dongre, Stefan Pirker, Stefan Heinrich

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Over the last decades, the numerical modelling of fluidized bed processes has become feasible even for industrial processes. Commonly, continuous two-fluid models are applied to describe large-scale fluidization. In order to allow for coarse grids novel two-fluid models account for unresolved sub-grid heterogeneities. However, computational efforts remain high – in the order of several hours of compute-time for a few seconds of real-time – thus preventing the representation of long-term phenomena such as heating or particle conversion processes. In order to overcome this limitation, data-based recurrence computational fluid dynamics (rCFD) has been put forward in recent years. rCFD can be regarded as a data-based method that relies on the numerical predictions of a conventional short-term simulation. This data is stored in a database and then used by rCFD to efficiently time-extrapolate the flow behavior in high spatial resolution. This study will compare the numerical predictions of rCFD simulations with those of corresponding full CFD reference simulations for lab-scale and pilot-scale fluidized beds. In assessing the predictive capabilities of rCFD simulations, we focus on solid mixing and secondary gas holdup. We observed that predictions made by rCFD simulations are highly sensitive to numerical parameters such as diffusivity associated with face swaps. We achieved a computational speed-up of four orders of magnitude (10,000 time faster than classical TFM simulation) eventually allowing for real-time simulations of fluidized beds. In the next step, we apply the checkerboarding technique by introducing gas tracers subjected to convection and diffusion. We then analyze the concentration profiles by observing mixing, transport of gas tracers, insights about the convective and diffusive pattern of the gas tracers, and further towards heat and mass transfer methods. Finally, we run rCFD simulations and calibrate them with numerical and physical parameters compared with convectional Two-fluid model (full CFD) simulation. As a result, this study gives a clear indication of the applicability, predictive capabilities, and existing limitations of rCFD in the realm of fluidization modelling.

Keywords: multiphase flow, recurrence CFD, two-fluid model, industrial processes

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Authors: Raghunandan Gurumurthy, Aricson Pereira, Sandeep Patil

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The escalating adoption of electric vehicles (EVs) across the globe has underscored the critical importance of advancing battery system technologies. This has catalyzed a shift towards the design and development of battery systems that not only exhibit higher energy efficiency but also boast enhanced thermal performance and sophisticated multi-material enclosures. A significant leap in this domain has been the incorporation of simulation-based design optimization for battery packs and Battery Management Systems (BMS), a move further enriched by integrating artificial intelligence/machine learning (AI/ML) approaches. These strategies are pivotal in refining the design, manufacturing, and operational processes for electric vehicles and energy storage systems. By leveraging AI/ML, stakeholders can now predict battery performance metrics—such as State of Health, State of Charge, and State of Power—with unprecedented accuracy. Furthermore, as Li-ion batteries (LIBs) become more prevalent in urban settings, the imperative for bolstering thermal and fire resilience has intensified. This has propelled Battery Thermal Management Systems (BTMs) to the forefront of energy storage research, highlighting the role of machine learning and AI not just as tools for enhanced safety management through accurate temperature forecasts and diagnostics but also as indispensable allies in the early detection and warning of potential battery fires.

Keywords: electric vehicles, battery thermal management, industrial engineering, machine learning, artificial intelligence, manufacturing

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Authors: Nabil Hameed Al-Farsi

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This study’s main goal is to develop a model and a maintenance strategy for a cement factory called Arabian Cement Company, Rabigh Plant. The proposed work here depends on Reliability centric maintenance approach to develop a strategy and maintenance schedule that ensures increasing the reliability of the production system components, thus ensuring continuous productivity. The cost-effective maintenance of the plant’s dependability performance is the key goal of durability-based maintenance is. The cement plant consists of 7 important steps, so, developing a maintenance plan based on Reliability centric maintenance (RCM) method is made up of 10 steps accordingly starting from selecting units and data until performing and updating the model. The processing unit chosen for the analysis of this case is the calcinatory unit regarding model’s validation and the Travancore Titanium Products Ltd (TTP) using the claimed data history acquired from the maintenance department maintenance from the mentioned company. After applying the proposed model, the results of the maintenance simulation justified the plant's existing scheduled maintenance policy being reconsidered. Results represent the need for preventive maintenance for all Class A criticality equipment instead of the planned maintenance and the breakdown one for all other equipment depends on its criticality and an FMEA report. Consequently, the additional cost of preventive maintenance would be offset by the cost savings from breakdown maintenance for the remaining equipment.

Keywords: engineering, reliability, strategy, maintenance, failure modes, effects and criticality analysis (FMEA)

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Authors: Jianfang Wang, Xianzhe Chen, Zhuoliang Liu, Cheng-An Tao, Yujiao Li

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Organophosphorus (OPs) pesticide used as insecticides are widely used in agricultural pest control, household and storage deworming. The detection of pesticides needs more simple and efficient methods. One of the best ways is to make electrochemical biosensors. In this paper, an electrochemical enzyme biosensor based on acetylcholine esterase (AChE) was constructed, and its sensing properties and sensing mechanisms were studied. Reduced graphene oxide-polydopamine complexes (RGO-PDA), gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were prepared firstly and composited with AChE and chitosan (CS), then fixed on the glassy carbon electrode (GCE) surface to construct the biosensor GCE/RGO-PDA-AuNPs-AgNPs-AChE-CS by one-pot method. The results show that graphene oxide (GO) can be reduced by dopamine (DA) and dispersed well in RGO-PDA complexes. And the composites have a synergistic catalysis effect and can improve the surface resistance of GCE. The biosensor selectively can detect acetylcholine (ACh) and OPs pesticide with good linear range and high sensitivity. The performance of the biosensor is affected by the ratio and adding ways of AChE and the adding of AuNPs and AChE. And the biosensor can achieve a detection limit of 2.4 ng/L for methyl parathion and a wide linear detection range of 0.02 ng/L ~ 80 ng/L, and has excellent stability, good anti-interference ability, and excellent preservation performance, indicating that the sensor has practical value.

Keywords: acetylcholine esterase, electrochemical biosensor, nanoparticles, organophosphates, reduced graphene oxide

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Authors: Lu Anne A. Godinez, May Claudine I. Gador, Preacious G. Gumolon, Louiechi Von R. Mendoza, Neil Bryan N. Moninio

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Gender equality and women empowerment is the third of eight Millennium Development Goals. Understanding corruption’s linkages to gender equality issues and how it impacts women’s empowerment is part of the broader process of advancing women’s rights and understanding the gender dimensions of democratic governance. Taking a long view of political (corruption index) and the social (women empowerment) dimension — a view from 2015 to 2030, a context based forecast was conducted to forecast the ASEAN corruption index in the next 15 years, answering the question: “Does women political involvement decrease corruption rate index of ASEAN countries in the next 15 years?” The study have established that there will be an increase women political involvement in the ASEAN countries in the next 15 years that will cause a drop on corruption rate index. There will be a significant decline on corruption rate index in 2030. This change entails reform not only in the political aspect of progress, but to the social aspect as well. Finally, the political aspect is increasing at a constant rate however a double or triple increase of the social aspect is seen to be the key solution for corruption.

Keywords: women, women political involvement, corruption, gender equity index, economic participation, educational attainment, political empowerment, control of corruption, regulatory quality, rule of law, voice and accountability government effectiveness, political stability and corruption perception index

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Authors: Elham Koohikerade, Silvio Jose Gumiere

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In this research, irrigation is highlighted as crucial for improving both the yield and quality of ‎potatoes due to their high sensitivity to soil moisture changes. The study presents a hybrid Long ‎Short-Term Memory (LSTM) model aimed at optimizing irrigation scheduling in potato fields in ‎Quebec City, Canada. This model integrates model-based and satellite-derived datasets to simulate ‎soil moisture content, addressing the limitations of field data. Developed under the guidance of the ‎Food and Agriculture Organization (FAO), the simulation approach compensates for the lack of direct ‎soil sensor data, enhancing the LSTM model's predictions. The model was calibrated using indices ‎like Surface Soil Moisture (SSM), Normalized Vegetation Difference Index (NDVI), Enhanced ‎Vegetation Index (EVI), and Normalized Multi-band Drought Index (NMDI) to effectively forecast ‎soil moisture reductions. Understanding soil moisture and plant development is crucial for assessing ‎drought conditions and determining irrigation needs. This study validated the spectral characteristics ‎of vegetation and soil using ECMWF Reanalysis v5 (ERA5) and Moderate Resolution Imaging ‎Spectrometer (MODIS) data from 2019 to 2023, collected from agricultural areas in Dolbeau and ‎Peribonka, Quebec. Parameters such as surface volumetric soil moisture (0-7 cm), NDVI, EVI, and ‎NMDI were extracted from these images. A regional four-year dataset of soil and vegetation moisture ‎was developed using a machine learning approach combining model-based and satellite-based ‎datasets. The LSTM model predicts soil moisture dynamics hourly across different locations and ‎times, with its accuracy verified through cross-validation and comparison with existing soil moisture ‎datasets. The model effectively captures temporal dynamics, making it valuable for applications ‎requiring soil moisture monitoring over time, such as anomaly detection and memory analysis. By ‎identifying typical peak soil moisture values and observing distribution shapes, irrigation can be ‎scheduled to maintain soil moisture within Volumetric Soil Moisture (VSM) values of 0.25 to 0.30 ‎m²/m², avoiding under and over-watering. The strong correlations between parcels suggest that a ‎uniform irrigation strategy might be effective across multiple parcels, with adjustments based on ‎specific parcel characteristics and historical data trends. The application of the LSTM model to ‎predict soil moisture and vegetation indices yielded mixed results. While the model effectively ‎captures the central tendency and temporal dynamics of soil moisture, it struggles with accurately ‎predicting EVI, NDVI, and NMDI.‎

Keywords: irrigation scheduling, LSTM neural network, remotely sensed indices, soil and vegetation ‎monitoring

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Authors: Kirsi Laurén, Tiina Seppä

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This study focuses on human-mire relations in the context of digital aestheticization and the long-standing tradition of folklore concerning mires. The study concentrates on the Patvinsuo mire in Eastern Finland and the Viiankiaapa mire in Finnish Lapland. Patvinsuo is a national park, and Viiankiaapa is a protected mire area with hiking trails and other recreational infrastructure. Perceiving the environment through digital technology can help to notice aesthetic details in nature. In addition, sharing images and texts digitally through social media adds a sense of community to the relationship with nature and, at the same time, creates a different kind of living heritage where old and new traditions meet and mingle. People visiting and camping in these areas 'self-care' themselves through recreation in nature. However, these practices and digital aestheticization can sometimes lead to the erosion of fragile mires. The research focuses on understanding the impact of digital aestheticization, such as taking digital photos, on the relationship with nature for individuals moving and working in mires. Additionally, the study aims to explore the contemporary perception of the water environment in mires and its cultural heritage, including mythical and folkloric elements. The research material consists of senso-digital walking interviews and digital recordings (audio recordings, photographs, videos) made during the mire walks, as well as archival material from the Finnish Literature Society’s Archives on mire folklore. The analysis of the material relies centrally on theories from sensory anthropology on the relationship between sensory perception and culture. The modern-day interviewees include outdoor enthusiasts spending their leisure time in mires, artists treating mires in their art, and nature experts (scientists, civil servants, and nature guides). The senso-digital walking interviews were conducted in Patvinsuo and Viiankiaapa mires on a trail chosen by the interviewees themselves. The material selected from the archive consists mainly of folk beliefs and folk poetry from the 19th and 20th centuries that express the relationship of the narrator to the mires. The interview and archival materials date from different periods and are different in character, which has to be taken into account in the analysis. However, in the analysis of both materials, particular attention is paid to the descriptions of sensations that appear in them. Analyzing the materials in parallel is limited by the fact that they date from different periods, but on the other hand, it is their different ages that make it possible to perceive the changes in the cultural heritage of mires.

Keywords: mires, living heritage, digital aestheticization, folklore, sensory anthropology

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Authors: Pingping Zhang, Yanpeng Cai, Jianlong Wang

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Stormwater storage tank (SST) is a popular low impact development technology for reducing stormwater runoff in the construction of sponge city. At present, it is difficult to perform the automatic control of SST for reducing peak flow. In this paper, fuzzy control was introduced into the peak control of SST to improve the efficiency of reducing stormwater runoff. Firstly, the design of SST was investigated. A catchment area and a return period were assumed, a SST model was manufactured, and then the storage capacity of the SST was verified. Secondly, the control parameters of the SST based on reducing stormwater runoff were analyzed, and a schematic diagram of real-time control (RTC) system based on peak control SST was established. Finally, fuzzy control system of a double input (flow and water level) and double output (inlet and outlet valve) was designed. The results showed that 1) under the different return periods (one year, three years, five years), the SST had the effect of delayed peak control and storage by increasing the detention time, 2) rainfall, pipeline flow, the influent time and the water level in the SST could be used as RTC parameters, and 3) the response curves of flow velocity and water level fluctuated very little and reached equilibrium in a short time. The combination of online monitoring and fuzzy control was feasible to control the SST automatically. This paper provides a theoretical reference for reducing stormwater runoff and improving the operation efficiency of SST.

Keywords: stormwater runoff, stormwater storage tank, real-time control, fuzzy control

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Authors: Mohamed H. El-Newehy, Badr M. Thamer, Nasser A. M. Barakat, Mohammad A.Abdelkareem, Salem S. Al-Deyab, Hak Y. Kim

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In this study, the influence of nitrogen doping on the electrocatalytic activity of carbon nanofibers with nickel nanoparticles toward methanol oxidation is introduced. The modified carbon nanofibers have been synthesized from calcination of electrospun nanofiber mats composed of nickel acetate tetrahydrate, poly(vinyl alcohol) and urea in argon atmosphere at 750oC. The utilized physicochemical characterizations indicated that the proposed strategy leads to form carbon nanofibers having nickel nanoparticles and doped by nitrogen. Moreover, due to the high-applied voltage during the electrospinning process, the utilized urea chemically bonds with the polymer matrix, which leads to form nitrogen-doped CNFs after the calcination process. Investigation of the electrocatalytic activity indicated that nitrogen doping NiCNFs strongly enhances the oxidation process of methanol as the current density increases from 52.5 to 198.5 mA/cm2 when the urea content in the original electrospun solution was 4 wt% urea. Moreover, the nanofibrous morphology exhibits distinct impact on the electrocatalytic activity. Also, nitrogen-doping enhanced the stability of the introduced Ni-based electrocatalyst. Overall, the present study introduces effective and simple strategy to modify the electrocatalytic activity of the nickel-based materials.

Keywords: electrospinning, methanol electrooxidation, fuel cells, nitrogen-doping, nickel

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Authors: Zeina Bou Diab, Arij Daou

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The neural mechanisms of sequential behaviors are intensively studied, with songbirds a focus for learned vocal production. We are studying the premotor nucleus HVC at a nexus of multiple pathways contributing to song learning and production. The HVC consists of multiple classes of neuronal populations, each has its own cellular, electrophysiological and functional properties. During singing, a large subset of motor cortex analog-projecting HVCRA neurons emit a single 6-10 ms burst of spikes at the same time during each rendition of song, a large subset of basal ganglia-projecting HVCX neurons fire 1 to 4 bursts that are similarly time locked to vocalizations, while HVCINT neurons fire tonically at average high frequency throughout song with prominent modulations whose timing in relation to song remains unresolved. This opens the opportunity to define models relating explicit HVC circuitry to how these neurons work cooperatively to control learning and singing. We developed conductance-based Hodgkin-Huxley models for the three classes of HVC neurons (based on the ion channels previously identified from in vitro recordings) and connected them in several physiologically realistic networks (based on the known synaptic connectivity and specific glutaminergic and gabaergic pharmacology) via different architecture patterning scenarios with the aim to replicate the in vivo firing patterning behaviors. We are able, through these networks, to reproduce the in vivo behavior of each class of HVC neurons, as shown by the experimental recordings. The different network architectures developed highlight different mechanisms that might be contributing to the propagation of sequential neural activity (continuous or punctate) in the HVC and to the distinctive firing patterns that each class exhibits during singing. Examples of such possible mechanisms include: 1) post-inhibitory rebound in HVCX and their population patterns during singing, 2) different subclasses of HVCINT interacting via inhibitory-inhibitory loops, 3) mono-synaptic HVCX to HVCRA excitatory connectivity, and 4) structured many-to-one inhibitory synapses from interneurons to projection neurons, and others. Replication is only a preliminary step that must be followed by model prediction and testing.

Keywords: computational modeling, neural networks, temporal neural sequences, ionic currents, songbird

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Authors: Haiyan Wang, Dongyun Wang, Yongyong Yan, Richard T. Jaspers, Gang Wu

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Mesenchymal stem cell and 3D printing-based bone tissue engineering present a promising technique to repair large-volume bone defects. Its success is highly dependent on cell attachment, spreading, osteogenic differentiation, and in vivo survival of stem cells on 3D-printed scaffolds. In this study, human salivary histatin-1 (Hst1) was utilized to enhance the interactions between human adipose-derived stem cells (hASCs) and 3D-printed β-tricalcium phosphate (β-TCP) bioceramic scaffolds. Fluorescent images showed that Hst1 significantly enhanced the adhesion of hASCs to both bioinert glass and 3D-printed β-TCP scaffold. In addition, Hst1 was associated with significantly higher proliferation and osteogenic differentiation of hASCs on 3D-printed β-TCP scaffolds. Moreover, coating 3D-printed β-TCP scaffolds with histatin significantly promotes the survival of hASCs in vivo. The ERK and p38 but not JNK signaling was found to be involved in the superior adhesion of hASCs to β-TCP scaffolds with the aid of Hst1. In conclusion, Hst1 could significantly promote the adhesion, spreading, osteogenic differentiation, and in vivo survival of hASCs on 3D-printed β-TCP scaffolds, bearing a promising application in stem cell/3D printing-based constructs for bone tissue engineering.

Keywords: 3d printing, adipose-derived stem cells, bone tissue engineering, histatin-1, osteogenesis

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Authors: Qian Li, Zhaoping Zhong

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Sewage sludge, a typical solid waste, has inevitably been produced in enormous quantities in China. Still worse, the amount of sewage sludge produced has been increasing due to rapid economic development and urbanization. Compared to the conventional method to treat sewage sludge, pyrolysis has been considered an economic and ecological technology because it can significantly reduce the sludge volume, completely kill pathogens, and produce valuable solid, gas, and liquid products. However, the large-scale utilization of sludge biochar has been limited due to the considerable risk posed by heavy metals in the sludge. Heavy metals enriched in pyrolytic biochar could be divided into exchangeable, reducible, oxidizable, and residual forms. The residual form of heavy metals is the most stable and cannot be used by organisms. Kaolin and zeolite are environmentally friendly inorganic minerals with a high surface area and heat resistance characteristics. So, they exhibit the enormous potential to immobilize heavy metals. In order to reduce the risk of leaching heavy metals in the pyrolysis biochar, this study pyrolyzed sewage sludge mixed with kaolin/zeolite in a small rotary kiln. The influences of additives and pyrolysis temperature on the leaching concentration and morphological transformation of heavy metals in pyrolysis biochar were investigated. The potential mechanism of stabilizing heavy metals in the co-pyrolysis of sludge blended with kaolin/zeolite was explained by scanning electron microscopy, X-ray diffraction, and specific surface area and porosity analysis. The European Community Bureau of Reference sequential extraction procedure has been applied to analyze the forms of heavy metals in sludge and pyrolysis biochar. All the concentrations of heavy metals were examined by flame atomic absorption spectrophotometry. Compared with the proportions of heavy metals associated with the F4 fraction in pyrolytic carbon prepared without additional agents, those in carbon obtained by co-pyrolysis of sludge and kaolin/zeolite increased. Increasing the additive dosage could improve the proportions of the stable fraction of various heavy metals in biochar. Kaolin exhibited a better effect on stabilizing heavy metals than zeolite. Aluminosilicate additives with excellent adsorption performance could capture more released heavy metals during sludge pyrolysis. Then heavy metal ions would react with the oxygen ions of additives to form silicate and aluminate, causing the conversion of heavy metals from unstable fractions (sulfate, chloride, etc.) to stable fractions (silicate, aluminate, etc.). This study reveals that the efficiency of stabilizing heavy metals depends on the formation of stable mineral compounds containing heavy metals in pyrolysis biochar.

Keywords: co-pyrolysis, heavy metals, immobilization mechanism, sewage sludge

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Authors: Liubov Magerramova, Eugene Kratt, Pavel Presniakov

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A detailed analysis has been performed for several schemes of Gas Turbine Wheels production based on additive and powder technologies including metal, ceramic, and stereolithography 3-D printing. During the process of development and debugging of gas turbine engine components, different versions of these components must be manufactured and tested. Cooled blades of the turbine are among of these components. They are usually produced by traditional casting methods. This method requires long and costly design and manufacture of casting molds. Moreover, traditional manufacturing methods limit the design possibilities of complex critical parts of engine, so capabilities of Powder Metallurgy Techniques (PMT) were analyzed to manufacture the turbine wheel with air-cooled blades. PMT dramatically reduce time needed for such production and allow creating new complex design solutions aimed at improving the technical characteristics of the engine: improving fuel efficiency and environmental performance, increasing reliability, and reducing weight. To accelerate and simplify the blades manufacturing process, several options based on additive technologies were used. The options were implemented in the form of various casting equipment for the manufacturing of blades. Methods of powder metallurgy were applied for connecting the blades with the disc. The optimal production scheme and a set of technologies for the manufacturing of blades and turbine wheel and other parts of the engine can be selected on the basis of the options considered.

Keywords: additive technologies, gas turbine engine, powder technology, turbine wheel

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Authors: Gurbanova J., Majidova N., Ali-Zade S., Hasanova A., Mikailzade P.

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Currently, the problem of oncogynecological diseases is widespread and remains relevant in terms of quantitative growth. It is known that due to the increase in the number of benign diseases of the cervix, the development of precancerous conditions occurs. Benign diseases of the cervix represent the most common gynecological problem, which are often precursors of malignant neoplasms, especially cervical cancer. According to statistics, benign diseases of the cervix cover 25-45% of all gynecological diseases. Among women's oncogynecological diseases, cervical cancer ranks second in the world after breast cancer and ranks first in the mortality rate among oncological diseases in economically underdeveloped countries. We performed a comprehensive clinical and laboratory examination of 130 women aged 18 to 73 with benign cervical diseases. 59 (38.5%) women of reproductive age, as well as 39 (30%) premenopausal and 41 (31.5%) menopausal patients, participated in the study. Detailed anamnesis was collected from all patients, objective and gynecological examination was performed, laboratory and instrumental examinations (USM, IPV DNA, smear microscopy, and PCR bacteriological examination of sexually transmitted infections), simple and extended colposcopy, liquid-based РАР-smear smear and РАР-classic smear examinations were conducted. As a result of the research, the following nosological forms were found in women with benign diseases of the cervix: non-specific vaginitis in 10 (7.7%) cases; ectopia, endocervicitis - 60(46.2%); cervical ectropion - 7(5.4%); cervical polyp - 9(6.9%); cervical leukoplakia - 15(11.5%); atrophic vaginitis - 7(5.4%); condyloma - 12(9.2%); cervical stenosis - 2(1.5%); endometriosis of the cervix - was noted in 8 (6.2%) cases (p<0.001), respectively. Characteristics of the menstrual cycle among the examined women: normal cycle in 97 (74.6%) cases; oligomenorrhea – 23 (17.7%); polymenorrhea – 4(3.1%); algomenorrhea – noted in 6 (4.6%) cases (p<0.001). Cytological examination showed that: the specificity of liquid-based cytology was 76.2%, and the traditional PAP test was set at 70.6%. The overall diagnostic value was calculated to be 86% in liquid-based cytology and 78.5% in conventional PAP tests. Treatment of women with benign diseases of the cervix was carried out by diathermocoagulation method and "FOTEK EA 141M" device. It should be noted that 6 months after the treatment, after treatment with the "FOTEK EA 141M" device, there was no relapse in any patient. Recurrence was found in 23.7% of patients after diathermoelectrocoagulation. Thus, it is clear from the above that the study of cervical pathologies, the determination of optimal examinations, and effective treatment methods is one of the urgent problems facing obstetrics and gynecology.

Keywords: cervical cancer, cytological examination, PAP-smear, non-specific vaginitis

Procedia PDF Downloads 88

Authors: Ping Bo, Meng Yunshan

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Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

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Authors: Magdalena Smoktunowicz, Renata Wawrzyniak, Malgorzata Waleron, Krzysztof Waleron

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Pectobacterium spp. were previously classified into the Erwinia genus founded in 1917 to unite at that time all Gram-negative, fermentative, nonsporulating and peritrichous flagellated plant pathogenic bacteria. After work of Waldee (1945), on Approved Lists of Bacterial Names and bacteriology manuals in 1980, they were described either under the species named Erwinia or Pectobacterium. The Pectobacterium genus was formally described in 1998 of 265 Pectobacterium strains. Currently, there are 21 species of Pectobacterium bacteria, including Pectobacterium betavasculorum since 2003, which caused soft rot on sugar beet tubers. Based on the biochemical experiments carried out for this, it is known that these bacteria are gram-negative, catalase-positive, oxidase-negative, facultatively anaerobic, using gelatin and causing symptoms of soft rot on potato and sugar beet tubers. The mere fact of growing on sugar beet may indicate a metabolism characteristic only for this species. Metabolomics, broadly defined as the biology of the metabolic systems, which allows to make comprehensive measurements of metabolites. Metabolomics, in combination with genomics, are complementary tools for the identification of metabolites and their reactions, and thus for the reconstruction of metabolic networks. The aim of this study was to apply the GC-MS-based untargeted metabolomics to study the metabolism of P. betavasculorum in different growing conditions. The metabolomic profiles of biomass and biomass media were determined. For sample preparation the following protocol was used: extraction with 900 µl of methanol: chloroform: water mixture (10: 3: 1, v: v) were added to 900 µl of biomass from the bottom of the tube and up to 900 µl of nutrient medium from the bacterial biomass. After centrifugation (13,000 x g, 15 min, 4oC), 300µL of the obtained supernatants were concentrated by rotary vacuum and evaporated to dryness. Afterwards, two-step derivatization procedure was performed before GC-MS analyses. The obtained results were subjected to statistical calculations with the use of both uni- and multivariate tests. The obtained results were evaluated using KEGG database, to asses which metabolic pathways are activated and which genes are responsible for it, during the metabolism of given substrates contained in the growing environment. The observed metabolic changes, combined with biochemical and physiological tests, may enable pathway discovery, regulatory inference and understanding of the homeostatic abilities of P. betavasculorum.

Keywords: GC-MS chromatograpfy, metabolomics, metabolism, pectobacterium strains, pectobacterium betavasculorum

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Authors: Zia Amjad, Salem Safar Alghamdi

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This experiment was carried out at student educational farm College of Food and Agriculture, KSU, kingdom of Saudi Arabia; in order to characterize 154 Vicia faba, characterization, PCA, ago-morphological diversity. Icia faba L. accessions were based on ipove and ibpgr descriptors. 24 agro-morphological characters including 11 quantitative and 13 qualitative were observed for genetic variation. All the results were analyzed using multivariate analysis i.e. principle component analysis. First 6 principle components with eigenvalue greater than one; accounted for 72% of available Vicia faba genetic diversity. However, first three components revealed more than 10% of genetic diversity each i.e. 22.36%, 15.86%, and 10.89% respectively. PCA distributed the V. faba accessions into different groups based on their performance for the characters under observation. PC-1 which represented 22.36% of the genetic diversity was positively associated with stipule spot pigmentation, intensity of streaks, pod degree of curvature and to some extent with 100 seed weight. PC-2 covered 15.86 of the genetic diversity and showed positive association for average seed weight per plant, pod length, number of seeds per plant, 100 seed weight, stipule spot pigmentation, intensity of streaks (same as in PC-1), and to some extent for pod degree of curvature and number of pods per plant. PC-3 revealed 10.89% of genetic diversity and expressed positive association for number of pods per plant and number of leaflets per plant.

Keywords: Vicia faba, characterization, PCA, ago-morphological diversity

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Authors: Ju Peng Poh, Jun Yu Charles Lee, Jonathan Chew Hoe Khoo

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The emergence of digital twin technology, a digital replica of physical world, has improved the real-time access to data from sensors about the performance of buildings. This digital transformation has opened up many opportunities to improve the management of the building by using the data collected to help monitor consumption patterns and energy leakages. One example is the integration of predictive models for anomaly detection. In this paper, we use the GAM (Generalised Additive Model) for the anomaly detection of Air Handling Units (AHU) power consumption pattern. There is ample research work on the use of GAM for the prediction of power consumption at the office building and nation-wide level. However, there is limited illustration of its anomaly detection capabilities, prescriptive analytics case study, and its integration with the latest development of digital twin technology. In this paper, we applied the general GAM modelling framework on the historical data of the AHU power consumption and cooling load of the building between Jan 2018 to Aug 2019 from an education campus in Singapore to train prediction models that, in turn, yield predicted values and ranges. The historical data are seamlessly extracted from the digital twin for modelling purposes. We enhanced the utility of the GAM model by using it to power a real-time anomaly detection system based on the forward predicted ranges. The magnitude of deviation from the upper and lower bounds of the uncertainty intervals is used to inform and identify anomalous data points, all based on historical data, without explicit intervention from domain experts. Notwithstanding, the domain expert fits in through an optional feedback loop through which iterative data cleansing is performed. After an anomalously high or low level of power consumption detected, a set of rule-based conditions are evaluated in real-time to help determine the next course of action for the facilities manager. The performance of GAM is then compared with other approaches to evaluate its effectiveness. Lastly, we discuss the successfully deployment of this approach for the detection of anomalous power consumption pattern and illustrated with real-world use cases.

Keywords: anomaly detection, digital twin, generalised additive model, GAM, power consumption, supervised learning

Procedia PDF Downloads 137

Authors: Aaron Herve Mbwe Mbissik, Lotfi Khiari, Otmane Raji, Abdellatif Elghali, Abdelkarim Lajili, Muhammad Ouabid, Martin Jemo, Jean-Louis Bodinier

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Potassium (K) is an essential macronutrient for plant growth, helping to regulate several physiological and metabolic processes. Evaporite-related potash salts, mainly sylvite minerals (K chloride or KCl), are the principal source of K for the fertilizer industry. However, due to the high potash-supply risk associated with its considerable price fluctuations and uneven geographic distribution for most agriculture-based developing countries, the development of alternative sources of fertilizer K is imperative to maintain adequate crop yield, reduce yield gaps, and food security. Alkaline Igneous rocks containing significant K-rich silicate minerals such as K feldspar are increasingly seen as the best alternative available. However, these rocks may require to be hydrothermally treatment to enhance the release of potassium. In this study, we evaluate the fertilizing capacity of raw and hydrothermally treated K-bearing silicate rocks from different areas in Morocco. The effectiveness of rock powders was tested in a greenhouse experiment using ryegrass (Lolium multiflorum) by comparing them to a control (no K added) and to a conventional fertilizer (muriate of potash: MOP or KCl). The trial was conducted in a randomized complete block design with three replications, and plants were grown on K-depleted soils for three growing cycles. To achieve our objective, in addition to the analysis of the muriate response curve and the different biomasses, we also examined three necessary coefficients, namely: the K uptake, then apparent K recovery (AKR), and the relative K efficiency (RKE). The results showed that based on the optimum economic rate of MOP (230 kg.K.ha⁻¹) and the optimum yield (44 000 kg.K.ha⁻¹), the efficiency of K silicate rocks was as high as that of MOP. Although the plants took up only half of the K supplied by the powdered rock, the hydrothermal material was found to be satisfactory, with a biomass value reaching the optimum economic limit until the second crop cycle. In comparison, the AKR of the MOP (98.6%) and its RKE in the 1st cycle were higher than our materials: 39% and 38%, respectively. Therefore, the raw and hydrothermal materials mixture could be an appropriate solution for long-term agronomic use based on the obtained results.

Keywords: K-uptake, AKR, RKE, K-bearing silicate rock, MOP

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Authors: Lukumba Phiri, Simon Tembo, Kumbuso Joshua Nyoni

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In Zambia recent initiatives by various power operators like ZESCO, CEC, and consumers like the mines to upgrade power systems into smart grids target an even tighter integration with information technologies to enable the integration of renewable energy sources, local and bulk generation, and demand response. Thus, for the reliable operation of smart grids, its information infrastructure must be secure and reliable in the face of both failures and cyberattacks. Due to the nature of the systems, ICS/SCADA cybersecurity and governance face additional challenges compared to the corporate networks, and critical systems may be left exposed. There exist control frameworks internationally such as the NIST framework, however, there are generic and do not meet the domain-specific needs of the SCADA systems. Zambia is also lagging in cybersecurity awareness and adoption, therefore there is a concern about securing ICS controlling key infrastructure critical to the Zambian economy as there are few known facts about the true posture. In this paper, we introduce a stochastic Edged-based Anomaly Detection for SCADA systems (SEADS) framework for threat modeling and risk assessment. SEADS enables the calculation of steady-steady probabilities that are further applied to establish metrics like system availability, maintainability, and reliability.

Keywords: anomaly, availability, detection, edge, maintainability, reliability, stochastic

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Authors: Ming-Yang Guo, Cheng-Xian Wu, Wei-Xiang Chen, Chun-Yuan Lin, Yen-Jen Lin, Ann-Shyn Chiang

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With more and more Drosophila Driver and Neuron images, it is an important work to find the similarity relationships among them as the functional inference. There is a general problem that how to find a Drosophila Driver image, which can cover a set of Drosophila Driver/Neuron images. In order to solve this problem, the intersection/union region for a set of images should be computed at first, then a comparison work is used to calculate the similarities between the region and other images. In this paper, three encoding schemes, namely Integer, Boolean, Decimal, are proposed to encode each image as a one-dimensional structure. Then, the intersection/union region from these images can be computed by using the compare operations, Boolean operators and lookup table method. Finally, the comparison work is done as the union region computation, and the similarity score can be calculated by the definition of Tanimoto coefficient. The above methods for the region computation are also implemented in the multi-core CPUs environment with the OpenMP. From the experimental results, in the encoding phase, the performance by the Boolean scheme is the best than that by others; in the region computation phase, the performance by Decimal is the best when the number of images is large. The speedup ratio can achieve 12 based on 16 CPUs. This work was supported by the Ministry of Science and Technology under the grant MOST 106-2221-E-182-070.

Keywords: Drosophila driver image, Drosophila neuron images, intersection/union computation, parallel processing, OpenMP

Procedia PDF Downloads 222

Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

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Authors: Dawei Cai, Yuya Tokuda

Abstract:

The market of localization based service (LBS) is expanding. The acquisition of physical location is the fundamental basis for LBS. GPS, the de facto standard for outdoor localization, does not work well in indoor environment due to the blocking of signals by walls and ceiling. To acquire high accurate localization in an indoor environment, many techniques have been developed. Triangulation approach is often used for identifying the location, but a heavy and complex computation is necessary to calculate the location of the distances between the object and several source points. This computation is also time and power consumption, and not favorable to a mobile device that needs a long action life with battery. To provide a low power consumption approach for a mobile device, this paper presents a fast calculation approach to identify the location of the object without online solving solutions to simultaneous quadratic equations. In our approach, we divide the location identification into two parts, one is offline, and other is online. In offline mode, we make a mapping process that maps the location area to distance space and find a simple formula that can be used to identify the location of the object online with very light computation. The characteristic of the approach is a good tradeoff between the accuracy and computational amount. Therefore, this approach can be used in smartphone and other mobile devices that need a long work time. To show the performance, some simulation experimental results are provided also in the paper.

Keywords: indoor localization, location based service, triangulation, fast calculation, mobile device

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Authors: Hossain A., Miah S., Ray P. K.

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Introduction: Single channel and tri-channel applicators are used in the traditional treatment of cervical cancer. Total reference air kerma (TRAK) and treatment outcomes in high-dose-rate brachytherapy for cervical cancer using single-channel and tri-channel applicators were the main objectives of this retrospective study. Material and Methods: Patients in the radiotherapy division who received brachytherapy, chemotherapy, and external radiotherapy (EBRT) using single and tri-channel applicators were the subjects of a retrospective cohort study from 2016 to 2020. All brachytherapy parameters, including TRAK, were calculated in accordance with the international protocol. The Kaplan Meier method was used to analyze survival rates using a log-rank test. Results and Discussions: Based on treatment times of 15.34 (10-20) days and 21.35 (6.5-28) days, the TRAK for the tri-channel applicator was 0.52 cGy.m² and for the single-channel applicator was 0.34 cGy.m². Based on TRAK, the rectum, bladder, and tumor had respective Pearson correlations of 0.082, 0.009, and 0.032. The 1-specificity and sensitivity were 0.70 and 0.30, respectively. At that time, AUC was 0.71. The log-rank test showed that tri-channel applicators had a survival rate of 95% and single-channel applicators had a survival rate of 85% (p=0.565). Conclusions: The relationship between TRAK and treatment duration and Pearson correlation for the tumor, rectum, and bladder suggests that TRAK should be taken into account for the proper operation of single channel and tri-channel applicators.

Keywords: single-channel, tri-channel, high dose rate brachytherapy, cervical cancer

Procedia PDF Downloads 88

Authors: Siti Aishah Hasbullah

Abstract:

Studies on identification of pork content in food have grown rapidly to meet the Halal food standard in Malaysia. The used mitochondria DNA (mtDNA) approaches for the identification of pig species is thought to be the most precise marker due to the mtDNA genes are present in thousands of copies per cell, the large variability of mtDNA. The standard method commonly used for DNA detection is based on polymerase chain reaction (PCR) method combined with gel electrophoresis but has major drawback. Its major drawbacks are laborious, need longer time and toxic to handle. Therefore, the need for simplicity and fast assay of DNA is vital and has triggered us to develop DNA biosensors for porcine DNA detection. Therefore, the aim of this project is to develop electrochemical DNA biosensor based on ruthenium (II) complex, [Ru(bpy)2(p-PIP)]2+ as DNA hybridization label. The interaction of DNA and [Ru(bpy)2(p-HPIP)]2+ will be studied by electrochemical transduction using Gold Screen-Printed Electrode (GSPE) modified with gold nanoparticles (AuNPs) and succinimide acrylic microspheres. The electrochemical detection by redox active ruthenium (II) complex was measured by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). The results indicate that the interaction of [Ru(bpy)2(PIP)]2+ with hybridization complementary DNA has higher response compared to single-stranded and mismatch complementary DNA. Under optimized condition, this porcine DNA biosensor incorporated modified GSPE shows good linear range towards porcine DNA.

Keywords: gold, screen printed electrode, ruthenium, porcine DNA

Procedia PDF Downloads 295