Search results for: random direction embedding (RDE)

Authors: Emre Kara, Ali Kurşun, Halil Aykul

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The lightweight sandwiches obtained with the use of various core materials such as foams, honeycomb, lattice structures etc., which have high energy absorbing capacity and high strength to weight ratio, are suitable for several applications in transport industry (automotive, aerospace, shipbuilding industry) where saving of fuel consumption, load carrying capacity increase, safety of vehicles and decrease of emission of harmful gases are very important aspects. While the sandwich structures with foams and honeycombs have been applied for many years, there is a growing interest on a new generation sandwiches with micro lattice cores. In order to produce these core structures, various production methods were created with the development of the technology. One of these production technologies is an additive manufacturing technique called selective laser sintering/melting (SLS/SLM) which is very popular nowadays because of saving of production time and achieving the production of complex topologies. The static bending and the dynamic low velocity impact tests of the sandwiches with carbon fiber/epoxy skins and the micro lattice cores produced via SLS/SLM were already reported in just a few studies. The goal of this investigation was the analysis of the flexural response of the sandwiches consisting of glass fiber reinforced plastic (GFRP) skins and the micro lattice cores manufactured via SLS under thermo-mechanical loads in order to compare the results in terms of peak load and absorbed energy values respect to the effect of core cell size, temperature and support span length. The micro lattice cores were manufactured using SLS technology that creates the product drawn by a 3D computer aided design (CAD) software. The lattice cores which were designed as body centered cubic (BCC) model having two different cell sizes (d= 2 and 2.5 mm) with the strut diameter of 0.3 mm were produced using titanium alloy (Ti6Al4V) powder. During the production of all the core materials, the same production parameters such as laser power, laser beam diameter, building direction etc. were kept constant. Vacuum Infusion (VI) method was used to produce skin materials, made of [0°/90°] woven S-Glass prepreg laminates. The combination of the core and skins were implemented under VI. Three point bending tests were carried out by a servo-hydraulic test machine with different values of support span distances (L = 30, 45, and 60 mm) under various temperature values (T = 23, 40 and 60 °C) in order to analyze the influences of support span and temperature values. The failure mode of the collapsed sandwiches has been investigated using 3D computed tomography (CT) that allows a three-dimensional reconstruction of the analyzed object. The main results of the bending tests are: load-deflection curves, peak force and absorbed energy values. The results were compared according to the effect of cell size, support span and temperature values. The obtained results have particular importance for applications that require lightweight structures with a high capacity of energy dissipation, such as the transport industry, where problems of collision and crash have increased in the last years.

Keywords: light-weight sandwich structures, micro lattice cores, selective laser sintering, transport application

Procedia PDF Downloads 339

Authors: S. Nishat Fatima Rizvi, Tulika Chandra, Abbas Ali Mahdi, Devisha Agarwal

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Introduction: Blood components are an unexplored area prone to numerous discoveries which influence patient’s care. Experiments at different levels will further change the present concept of blood banking. Hyperlipidemia is a condition of elevated plasma level of low-density lipoprotein (LDL) as well as decreased plasma level of high-density lipoprotein (HDL). Studies show that platelets play a vital role in the progression of atherosclerosis and thrombosis, a major cause of death worldwide. They are activated by many triggers like elevated LDL in the blood resulting in aggregation and formation of plaques. Hyperlipidemic platelets are frequently transfused to patients with various disorders. Screening the random donor platelets for hyperlipidemia and correlating the condition with other donor criteria such as lipid rich diet, oral contraceptive pills intake, weight, alcohol intake, smoking, sedentary lifestyle, family history of heart diseases will lead to further deciding the exclusion criteria for donor selection. This will help in making the patients safe as well as the donor deferral criteria more stringent to improve the quality of blood supply. Technical evaluation and assessment will enable blood bankers to supply safe blood and improve the guidelines for blood safety. Thus, we try to study the correlation between hyperlipidemic platelets with platelets parameters, weight, and specific history of the donors. Methodology: This case control study included 100 blood samples of Blood donors, out of 100 only 30 samples were found to be hyperlipidemic and were included as cases, while rest were taken as controls. Lipid Profile were measured by fully automated analyzer (TRIGL:triglycerides),(LDL-C:LDL –Cholesterol plus 2nd generation),CHOL 2: Cholesterol Gen 2), HDL C 3: HDL-Cholesterol plus 3rdgeneration)-(Cobas C311-Roche Diagnostic).And Platelets parameters were analyzed by the Sysmex KX21 automated hematology analyzer. Results: A significant correlation was found amongst hyperlipidemic level in single time donor. In which 80% donors have history of heart disease, 66.66% donors have sedentary life style, 83.3% donors were smokers, 50% donors were alcoholic, and 63.33% donors had taken lipid rich diet. Active physical activity was found amongst 40% donors. We divided donors sample in two groups based on their body weight. In group 1, hyperlipidemic samples: Platelet Parameters were 75% in normal 25% abnormal in >70Kg weight while in 50-70Kg weight 90% were normal 10% were abnormal. In-group 2, Non Hyperlipidemic samples: platelet Parameters were 95% normal and 5% abnormal in >70Kg weight, while in 50-70Kg Weight, 66.66% normal and 33.33% abnormal. Conclusion: The findings indicate that Hyperlipidemic status of donors may affect the platelet parameters and can be distinguished on history by their weight, Smoking, Alcoholic intake, Sedentary lifestyle, Active physical activity, Lipid rich diet, Oral contraceptive pills intake, and Family history of heart disease. However further studies on a large sample size will affirm this finding.

Keywords: blood donors, hyperlipidemia, platelet, weight

Procedia PDF Downloads 313

Authors: Puzanova Zhanna Vasilyevna, Larina Tatiana Igorevna, Tertyshnikova Anastasia Gennadyevna

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In this day and age, extremism in various forms of its manifestation is a real threat to the world community, the national security of a state and its territorial integrity, as well as to the constitutional rights and freedoms of citizens. Extremism, as it is known, in general terms described as a commitment to extreme views and actions, radically denying the existing social norms and rules. Supporters of extremism in the ideological and political struggles often adopt methods and means of psychological warfare, appeal not to reason and logical arguments, but to emotions and instincts of the people, to prejudices, biases, and a variety of mythological designs. They are dissatisfied with the established order and aim at increasing this dissatisfaction among the masses. Youth extremism holds a specific place among the existing forms and types of extremism. In this context in 2015, we conducted a survey among Moscow college and high school students. The aim of this study was to determine how great or small is the difference in understanding and attitudes towards extremism manifestations, inclination and readiness to take part in extremist activities and what causes this predisposition, if it exists. We performed multivariate analysis and found the Russian college and high school students' opinion about the extremism and terrorism situation in our country and also their cognition on these topics. Among other things, we showed, that the level of aggressiveness of young people were not above the average for the whole population. The survey was conducted using the questionnaire method. The sample included college and high school students in Moscow (642 and 382, respectively) by method of random selection. The questionnaire was developed by specialists of RUDN University Sociological Laboratory and included both original questions (projective questions, the technique of incomplete sentences), and the standard test Dayhoff S. to determine the level of internal aggressiveness. It is also used as an experiment, the technique of study option using of FACS and SPAFF to determine the psychotypes and determination of non-verbal manifestations of emotions. The study confirmed the hypothesis that in respondents’ opinion, the level of aggression is higher today than a few years ago. Differences were found in the understanding of and respect for such social phenomena as extremism, terrorism, and their danger and appeal for the two age groups of young people. Theory of psychotypes, SPAFF (specific affect cording system) and FACS (facial action cording system) are considered as additional techniques for the diagnosis of a tendency to extreme views. Thus, it is established that diagnostics of acceptance of extreme views among young people is possible thanks to simultaneous use of knowledge from the different fields of socio-humanistic sciences. The results of the research can be used in a comparative context with other countries and as a starting point for further research in the field, taking into account its extreme relevance.

Keywords: extremism, youth extremism, diagnostics of extremist manifestations, forecast of behavior, sociological polls, theory of psychotypes, FACS, SPAFF

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Authors: Sarah Fitzpatrick, Hossein Zare-Behtash, Konstantinos Kontis

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Traditionally, the focus of horizontal axis wind turbine (HAWT) blade aerodynamic optimisation studies has been the outer working region of the blade. However, recent works seek to better understand, and thus improve upon, the performance of the inboard blade region to enhance power production, maximise load reduction and better control the wake behaviour. This paper presents the design considerations and characterisation of a wind turbine wind tunnel model devised to further the understanding and fundamental definition of horizontal axis wind turbine root vortex shedding and interactions. Additionally, the application of passive and active flow control mechanisms – vortex generators and plasma actuators – to allow for the manipulation and mitigation of unsteady aerodynamic behaviour at the blade inboard section is investigated. A static, modular blade wind turbine model has been developed for use in the University of Glasgow’s de Havilland closed return, low-speed wind tunnel. The model components - which comprise of a half span blade, hub, nacelle and tower - are scaled using the equivalent full span radius, R, for appropriate Mach and Strouhal numbers, and to achieve a Reynolds number in the range of 1.7x105 to 5.1x105 for operational speeds up to 55m/s. The half blade is constructed to be modular and fully dielectric, allowing for the integration of flow control mechanisms with a focus on plasma actuators. Investigations of root vortex shedding and the subsequent wake characteristics using qualitative – smoke visualisation, tufts and china clay flow – and quantitative methods – including particle image velocimetry (PIV), hot wire anemometry (HWA), and laser Doppler anemometry (LDA) – were conducted over a range of blade pitch angles 0 to 15 degrees, and Reynolds numbers. This allowed for the identification of shed vortical structures from the maximum chord position, the transitional region where the blade aerofoil blends into a cylindrical joint, and the blade nacelle connection. Analysis of the trailing vorticity interactions between the wake core and freestream shows the vortex meander and diffusion is notably affected by the Reynold’s number. It is hypothesized that the shed vorticity from the blade root region directly influences and exacerbates the nacelle wake expansion in the downstream direction. As the design of inboard blade region form is, by necessity, driven by function rather than aerodynamic optimisation, a study is undertaken for the application of flow control mechanisms to manipulate the observed vortex phenomenon. The designed model allows for the effective investigation of shed vorticity and wake interactions with a focus on the accurate geometry of a root region which is representative of small to medium power commercial HAWTs. The studies undertaken allow for an enhanced understanding of the interplay of shed vortices and their subsequent effect in the near and far wake. This highlights areas of interest within the inboard blade area for the potential use of passive and active flow control devices which contrive to produce a more desirable wake quality in this region.

Keywords: vortex shedding, wake interactions, wind tunnel model, wind turbine

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Authors: Shazi Farooqui, Anupam Sharma

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The Mahi River (~600km long) is an important west flowing the river of Central India. It originates in Madhya Pradesh and starts flowing in NW direction and enters into the state of Rajasthan. It flows across southern Rajasthan and then enters into Gujarat and finally debouches in the Gulf of Cambay. In Gujarat state, it flows through all four geomorphic zones i.e. eastern upland zone, shallow buried piedmont zone, alluvial zone and coastal zone. In lower reaches and particularly when it is flowing under the coastal regime, it provides an opportunity to study – 1. Land–Sea interaction and role of relative sea level changes, 2. Coastal/estuarine geological process, 3. Landscape evolution in marginal areas and so on. The Late Quaternary deposits of Mainland Gujarat is appreciably studied by Chamyal and his group of MS University of Baroda, and they have established that the 30-35m thick sediment package of the Mainland Gujarat is comprised of marine, fluvial and aeolian sediments. It is also established that in the estuarine zone, the upper few meter thick sediments package is of marine nature. However, its thickness, characters and the depositional environment including the role of climate and tectonics is still not clearly defined. To understand few aspects of the above mentioned, in the present study, a 17m subsurface sediment core has been retrieved from the estuarine zone of Mahi river basin. The Multiproxy studies which include the textural analysis (grain size), Loss on ignition (LOI), Bulk and clay mineralogy and geochemical studies have been carried out. In the entire sedimentary sequence, the grain size largely varies from coarse sand to clay; however, a solitary gravel bed is also noticed. The lower part (depth 9-17m), is mainly comprised of sub equal proportion of sand and silt. The sediments mainly have bimodal and leptokurtic distribution and deposited in alternate sand-silt package, probably indicating flood deposits. Relatively low moisture (1.8%) and organic carbon (2.4%) with increased carbonate values (12%) indicate that conditions must have to remain oxidizing. The middle part (depth 9–6m) has a 1m thick gravel bed at the bottom and overlain by coarse sand to very fine sand showing fining upward sequence. The presence of gravel bed suggests some kind of tectonic activity resulting into change in base level or enhanced precipitation in the catchment region. The upper part (depth 6–0m; top part of sequence) mainly comprised of fine sand to silt size grains (with appreciable clay content). The sediment of this part is Unimodal and very leptokurtic in nature suggesting wave and winnowing process and deposited in low energy suspension environment. This part has relatively high moisture (2.1%) and organic carbon (2.7%) with decreased carbonate content (4.2%) indicating change in the depositional environment probably under estuarine conditions. The presence of chlorite along with smectite clay mineral further supports the significant marine contribution in the formation of upper part of the sequence.

Keywords: grain size, statistical analysis, clay minerals, late quaternary, LOI

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Authors: Grzegorz Raniszewski, Zbigniew Kolacinski, Lukasz Szymanski, Slawomir Wiak, Lukasz Pietrzak, Dariusz Koza

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One of the most promising area for carbon nanotubes (CNTs) application is medicine. One of the most devastating diseases is cancer. Carbon nanotubes may be used as carriers of a slowly released drug. It is possible to use of electromagnetic waves to destroy cancer cells by the carbon nanotubes (CNTs). In our research we focused on thermal ablation by ferromagnetic carbon nanotubes (Fe-CNTs). In the cancer cell hyperthermia functionalized carbon nanotubes are exposed to radio frequency electromagnetic field. Properly functionalized Fe-CNTs join the cancer cells. Heat generated in nanoparticles connected to nanotubes warm up nanotubes and then the target tissue. When the temperature in tumor tissue exceeds 316 K the necrosis of cancer cells may be observed. Several techniques can be used for Fe-CNTs synthesis. In our work, we use high-temperature methods where arc-discharge is applied. Low-temperature systems are microwave plasma with assisted chemical vapor deposition (MPCVD) and hybrid physical-chemical vapor deposition (HPCVD). In the arc discharge system, the plasma reactor works with a pressure of He up to 0,5 atm. The electric arc burns between two graphite rods. Vapors of carbon move from the anode, through a short arc column and forms CNTs which can be collected either from the reactor walls or cathode deposit. This method is suitable for the production of multi-wall and single-wall CNTs. A disadvantage of high-temperature methods is a low purification, short length, random size and multi-directional distribution. In MPCVD system plasma is generated in waveguide connected to the microwave generator. Then containing carbon and ferromagnetic elements plasma flux go to the quartz tube. The additional resistance heating can be applied to increase the reaction effectiveness and efficiency. CNTs nucleation occurs on the quartz tube walls. It is also possible to use substrates to improve carbon nanotubes growth. HPCVD system involves both chemical decomposition of carbon containing gases and vaporization of a solid or liquid source of catalyst. In this system, a tube furnace is applied. A mixture of working and carbon-containing gases go through the quartz tube placed inside the furnace. As a catalyst ferrocene vapors can be used. Fe-CNTs may be collected then either from the quartz tube walls or on the substrates. Low-temperature methods are characterized by higher purity product. Moreover, carbon nanotubes from tested CVD systems were partially filled with the iron. Regardless of the method of Fe-CNTs synthesis the final product always needs to be purified for applications in medicine. The simplest method of purification is an oxidation of the amorphous carbon. Carbon nanotubes dedicated for cancer cell thermal ablation need to be additionally treated by acids for defects amplification on the CNTs surface what facilitates biofunctionalization. Application of ferromagnetic nanotubes for cancer treatment is a promising method of fighting with cancer for the next decade. Acknowledgment: The research work has been financed from the budget of science as a research project No. PBS2/A5/31/2013

Keywords: arc discharge, cancer, carbon nanotubes, CVD, thermal ablation

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Authors: Jonas De Kerf, Rein De Cooman, Sara De Gieter

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For many decades, scholars have aimed to understand how work can become more meaningful by maximizing both potential and enhancing feelings of satisfaction. One of the largest contributions towards such positive psychology was made with the introduction of the concept of ‘flow,’ which refers to a condition in which people feel intense engagement and effortless action. Since then, valuable research on work-related flow has indicated that this state of mind is related to positive outcomes for both organizations (e.g., social, supportive climates) and workers (e.g., job satisfaction). Yet, scholars still do not fully comprehend how such deep involvement at work is obtained, given the notion that flow is considered a short-term, complex, and dynamic experience. Most research neglects that people who experience flow ought to be optimally challenged so that intense concentration is required. Because attention is at the core of this enjoyable state of mind, this study aims to comprehend how elements that affect workers’ cognitive functioning impact flow at work. Research on cognitive performance suggests that working on mentally demanding tasks (e.g., information processing tasks) requires workers to concentrate deeply, as a result leading to flow experiences. Based on social facilitation theory, working on such tasks in an isolated environment eases concentration. Prior research has indicated that working at home (instead of working at the office) or in a closed office (rather than in an open-plan office) impacts employees’ overall functioning in terms of concentration and productivity. Consequently, we advance such knowledge and propose an interaction by combining cognitive task characteristics and work environments among part-time teleworkers. Hence, we not only aim to shed light on the relation between cognitive tasks and flow but also provide empirical evidence that workers performing such tasks achieve the highest states of flow while working either at home or in closed offices. In July 2022, an experience-sampling study will be conducted that uses a semi-random signal schedule to understand how task and environment predictors together impact part-time teleworkers’ flow. More precisely, about 150 knowledge workers will fill in multiple surveys a day for two consecutive workweeks to report their flow experiences, cognitive tasks, and work environments. Preliminary results from a pilot study indicate that on a between level, tasks high in information processing go along with high self-reported fluent productivity (i.e., making progress). As expected, evidence was found for higher fluency in productivity for workers performing information processing tasks both at home and in a closed office, compared to those performing the same tasks at the office or in open-plan offices. This study expands the current knowledge on work-related flow by looking at a task and environmental predictors that enable workers to obtain such a peak state. While doing so, our findings suggest that practitioners should strive for ideal alignments between tasks and work locations to work with both deep involvement and gratification.

Keywords: cognitive work, office lay-out, work location, work-related flow

Procedia PDF Downloads 100

Authors: S. Candamano, A. Iorfida, L. Pagnotta, F. Crea

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Basalt fabric reinforced cementitious composites (FRCM) have attracted great attention because they result in being effective in structural strengthening and eco-efficient. In this study, authors investigate their mechanical behavior when an alkali-activated binder, with tuned properties and containing high amounts of industrial by-products, such as ground granulated blast furnace slag, is used. Reinforcement is made up of a balanced, coated bidirectional fabric made out of basalt fibres and stainless steel micro-wire, with a mesh size of 8x8 mm and an equivalent design thickness equal to 0.064 mm. Mortars mixes have been prepared by maintaining constant the water/(reactive powders) and sand/(reactive powders) ratios at 0.53 and 2.7 respectively. Tensile tests were carried out on composite specimens of nominal dimensions equal to 500 mm x 50 mm x 10 mm, with 6 embedded rovings in the loading direction. Direct shear tests (DST), aimed to the stress-transfer mechanism and failure modes of basalt-FRCM composites, were carried out on brickwork substrate using an externally bonded basalt-FRCM composite strip 10 mm thick, 50 mm wide and a bonded length of 300 mm. Mortars exhibit, after 28 days of curing, a compressive strength of 32 MPa and a flexural strength of 5.5 MPa. Main hydration product is a poorly crystalline CASH gel. The constitutive behavior of the composite has been identified by means of direct tensile tests, with response curves showing a tri-linear behavior. The first linear phase represents the uncracked (I) stage, the second (II) is identified by crack development and the third (III) corresponds to cracked stage, completely developed up to failure. All specimens exhibit a crack pattern throughout the gauge length and failure occurred as a result of sequential tensile failure of the fibre bundles, after reaching the ultimate tensile strength. The behavior is mainly governed by cracks development (II) and widening (III) up to failure. The main average values related to the stages are σI= 173 MPa and εI= 0.026% that are the stress and strain of the transition point between stages I and II, corresponding to the first mortar cracking; σu = 456 MPa and εu= 2.20% that are the ultimate tensile strength and strain, respectively. The tensile modulus of elasticity in stage III is EIII= 41 GPa. All single-lap shear test specimens failed due to composite debonding. It occurred at the internal fabric-to-matrix interface, and it was the result of fracture of the matrix between the fibre bundles. For all specimens, transversal cracks were visible on the external surface of the composite and involved only the external matrix layer. This cracking appears when the interfacial shear stresses increase and slippage of the fabric at the internal matrix layer interface occurs. Since the external matrix layer is bonded to the reinforcement fabric, it translates with the slipped fabric. Average peak load around 945 N, peak stress around 308 MPa, and global slip around 6 mm were measured. The preliminary test results allow affirming that Alkali Activated Binders can be considered a potentially valid alternative to traditional mortars in designing FRCM composites.

Keywords: alkali activated binders, basalt-FRCM composites, direct shear tests, structural strengthening

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Authors: S. Candamano, A. Iorfida, F. Crea, A. Macario

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Recently, basalt fabric reinforced cementitious composites (FRCM) have attracted great attention because they result to be effective in structural strengthening and cost/environment efficient. In this study, authors investigate their mechanical behavior when an inorganic matrix, belonging to the family of alkali-activated binders, is used. In particular, the matrix has been designed to contain high amounts of industrial by-products and waste, such as Ground Granulated Blast Furnace Slag (GGBFS) and Fly Ash. Fresh state properties, such as workability, mechanical properties and shrinkage behavior of the matrix have been measured, while microstructures and reaction products were analyzed by Scanning Electron Microscopy and X-Ray Diffractometry. Reinforcement is made up of a balanced, coated bidirectional fabric made out of basalt fibres and stainless steel micro-wire, with a mesh size of 8x8 mm and an equivalent design thickness equal to 0.064 mm. Mortars mixes have been prepared by maintaining constant the water/(reactive powders) and sand/(reactive powders) ratios at 0.53 and 2.7 respectively. An appropriate experimental campaign based on direct tensile tests on composite specimens and single-lap shear bond test on brickwork substrate has been thus carried out to investigate their mechanical behavior under tension, the stress-transfer mechanism and failure modes. Tensile tests were carried out on composite specimens of nominal dimensions equal to 500 mm x 50 mm x 10 mm, with 6 embedded rovings in the loading direction. Direct shear tests (DST) were carried out on brickwork substrate using an externally bonded basalt-FRCM composite strip 10 mm thick, 50 mm wide and a bonded length of 300 mm. Mortars exhibit, after 28 days of curing, an average compressive strength of 32 MPa and flexural strength of 5.5 MPa. Main hydration product is a poorly crystalline aluminium-modified calcium silicate hydrate (C-A-S-H) gel. The constitutive behavior of the composite has been identified by means of direct tensile tests, with response curves showing a tri-linear behavior. Test results indicate that the behavior is mainly governed by cracks development (II) and widening (III) up to failure. The ultimate tensile strength and strain were respectively σᵤ = 456 MPa and ɛᵤ= 2.20%. The tensile modulus of elasticity in stage III was EIII= 41 GPa. All single-lap shear test specimens failed due to composite debonding. It occurred at the internal fabric-to-matrix interface, and it was the result of a fracture of the matrix between the fibre bundles. For all specimens, transversal cracks were visible on the external surface of the composite and involved only the external matrix layer. This cracking appears when the interfacial shear stresses increase and slippage of the fabric at the internal matrix layer interface occurs. Since the external matrix layer is bonded to the reinforcement fabric, it translates with the slipped fabric. Average peak load around 945 N, peak stress around 308 MPa and global slip around 6 mm were measured. The preliminary test results allow affirming that Alkali-Activated Materials can be considered a potentially valid alternative to traditional mortars in designing FRCM composites.

Keywords: Alkali-activated binders, Basalt-FRCM composites, direct shear tests, structural strengthening

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Authors: Esmael Makarian, Ayub Elyasi, Fatemeh Saberi, Olusegun Stanley Tomomewo

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Rock mechanical investigation is one of the most crucial activities in underground operations, especially in surveys related to hydrocarbon exploration and production, geothermal reservoirs, energy storage, mining, and geotechnics. There is a wide range of traditional methods for driving, collecting, and analyzing rock mechanics data. However, these approaches may not be suitable or work perfectly in some situations, such as fractured zones. Cutting-edge technologies have been provided to solve and optimize the mentioned issues. Internet of Things (IoT), Edge, and Cloud Computing technologies (ECt & CCt, respectively) are among the most widely used and new artificial intelligence methods employed for geomechanical studies. IoT devices act as sensors and cameras for real-time monitoring and mechanical-geological data collection of rocks, such as temperature, movement, pressure, or stress levels. Structural integrity, especially for cap rocks within hydrocarbon systems, and rock mass behavior assessment, to further activities such as enhanced oil recovery (EOR) and underground gas storage (UGS), or to improve safety risk management (SRM) and potential hazards identification (P.H.I), are other benefits from IoT technologies. EC techniques can process, aggregate, and analyze data immediately collected by IoT on a real-time scale, providing detailed insights into the behavior of rocks in various situations (e.g., stress, temperature, and pressure), establishing patterns quickly, and detecting trends. Therefore, this state-of-the-art and useful technology can adopt autonomous systems in rock mechanical surveys, such as drilling and production (in hydrocarbon wells) or excavation (in mining and geotechnics industries). Besides, ECt allows all rock-related operations to be controlled remotely and enables operators to apply changes or make adjustments. It must be mentioned that this feature is very important in environmental goals. More often than not, rock mechanical studies consist of different data, such as laboratory tests, field operations, and indirect information like seismic or well-logging data. CCt provides a useful platform for storing and managing a great deal of volume and different information, which can be very useful in fractured zones. Additionally, CCt supplies powerful tools for predicting, modeling, and simulating rock mechanical information, especially in fractured zones within vast areas. Also, it is a suitable source for sharing extensive information on rock mechanics, such as the direction and size of fractures in a large oil field or mine. The comprehensive review findings demonstrate that digital transformation through integrated IoT, Edge, and Cloud solutions is revolutionizing traditional rock mechanical investigation. These advanced technologies have empowered real-time monitoring, predictive analysis, and data-driven decision-making, culminating in noteworthy enhancements in safety, efficiency, and sustainability. Therefore, by employing IoT, CCt, and ECt, underground operations have experienced a significant boost, allowing for timely and informed actions using real-time data insights. The successful implementation of IoT, CCt, and ECt has led to optimized and safer operations, optimized processes, and environmentally conscious approaches in underground geological endeavors.

Keywords: rock mechanical studies, internet of things, edge computing, cloud computing, underground surveys, geological operations

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Authors: Muna Mitchell, Akshay Parchure, Krishna Singaraju

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There is an increasing need for medium- to long-span steel bridges with complex geometry due to site restrictions in developed areas. One of the solutions to grade separations in congested areas is to use longer spans on skewed supports that avoid at-grade obstructions limiting impacts to the foundation. Where vertical clearances are also a constraint, continuous steel girders can be used to reduce superstructure depths. Combining continuous long steel spans on severe skews can resolve the constraints at a cost. The behavior of skewed girders is challenging to analyze and design with subsequent complexity during fabrication and construction. As a part of a corridor improvement project, Walter P Moore designed two 1700-foot side-by-side bridges carrying four lanes of traffic in each direction over a railroad track. The bridges consist of prestressed concrete girder approach spans and three-span continuous steel plate girder units. The roadway design added complex geometry to the bridge with horizontal and vertical curves combined with superelevation transitions within the plate girder units. The substructure at the steel units was skewed approximately 56 degrees to satisfy the existing railroad right-of-way requirements. A horizontal point of curvature (PC) near the end of the steel units required the use flared girders and chorded slab edges. Due to the flared girder geometry, the cross-frame spacing in each bay is unique. Staggered cross frames were provided based on AASHTO LRFD and NCHRP guidelines for high skew steel bridges. Skewed steel bridges develop significant forces in the cross frames and rotation in the girder websdue to differential displacements along the girders under dead and live loads. In addition, under thermal loads, skewed steel bridges expand and contract not along the alignment parallel to the girders but along the diagonal connecting the acute corners, resulting in horizontal displacement both along and perpendicular to the girders. AASHTO LRFD recommends a 95 degree Fahrenheit temperature differential for the design of joints and bearings. The live load and the thermal loads resulted in significant horizontal forces and rotations in the bearings that necessitated the use of HLMR bearings. A unique bearing layout was selected to minimize the effect of thermal forces. The span length, width, skew, and roadway geometry at the bridges also required modular bridge joint systems (MBJS) with inverted-T bent caps to accommodate movement in the steel units. 2D and 3D finite element analysis models were developed to accurately determine the forces and rotations in the girders, cross frames, and bearings and to estimate thermal displacements at the joints. This paper covers the decision-making process for developing the framing plan, bearing configurations, joint type, and analysis models involved in the design of the high-skew three-span continuous steel plate girder bridges.

Keywords: complex geometry, continuous steel plate girders, finite element structural analysis, high skew, HLMR bearings, modular joint

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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: Hakimeh Masoudigavgani

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Since manufacturing firms deplete non-renewable resources and pollute air, soil, and water in greatly unsustainable manner, industrial activities or production of products are considered to be a key contributor to adverse environmental impacts. Hence, management strategies and approaches that involve an effective supply chain decision process in a manufacturing sector could be extremely significant to the application of environmental initiatives. Green manufacturing (GM) is one of these strategies which minimises negative effects on the environment through reducing greenhouse gas emissions, waste, and the consumption of energy and natural resources. This paper aims to explore what greening methods and mechanisms could be applied in the manufacturing supply chain and what are the outcomes of adopting these methods in terms of abating environmental burdens? The study is an interpretive research with an exploratory approach, using thematic analysis by coding text, breaking down and grouping the content of collected literature into various themes and categories. It is found that green supply chain could be attained through execution of some pre-production strategies including green building, eco-design, and green procurement as well as a number of in-production and post-production strategies involving green manufacturing and green logistics. To achieve an effective GM, the pre-production strategies are suggested to be employed. This paper defines GM as (1) the analysis of the ecological impacts generated by practices, products, production processes, and operational functions, and (2) the implementation of greening methods to reduce damaging influences of them on the natural environment. Analysis means assessing, monitoring, and auditing of practices in order to measure and pinpoint their harmful impacts. Moreover, greening methods involved within GM (arranged in order from the least to the most level of environmental compliance and techniques) consist of: •product stewardship (e.g. less use of toxic, non-renewable, and hazardous materials in the manufacture of the product; and stewardship of the environmental problems with regard to the product in all production, use, and end-of-life stages); •process stewardship (e.g. controlling carbon emission, energy and resources usage, transportation method, and disposal; reengineering polluting processes; recycling waste materials generated in production); •lean and clean production practices (e.g. elimination of waste, materials replacement, materials reduction, resource-efficient consumption, energy-efficient usage, emission reduction, managerial assessment, waste re-use); •use of eco-industrial parks (e.g. a shared warehouse, shared logistics management system, energy co-generation plant, effluent treatment). However, the focus of this paper is only on methods related to the in-production phase and needs further research on both pre-production and post-production environmental innovations. The outlined methods in this investigation may possibly be taken into account by policy/decision makers. Additionally, the proposed future research direction and identified gaps can be filled by scholars and researchers. The paper compares and contrasts a variety of viewpoints and enhances the body of knowledge by building a definition for GM through synthesising literature and categorising the strategic concept of greening methods, drivers, barriers, and successful implementing tactics.

Keywords: green manufacturing (GM), product stewardship, process stewardship, clean production, eco-industrial parks (EIPs)

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Authors: Lia Mania, Ketevan Nanobashvili

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Background: The coronavirus disease COVID-19 has become the cause of a global health crisis during the current pandemic. This study aims to fill the paucity of epidemiological studies on the impact of COVID-19 on the oral health of pediatric populations. Methods: It was conducted an observational, cross-sectional study in Georgia, in Tbilisi (capital of Georgia), among 7 to 12-year-old PCR or rapid test-confirmed post-Covid populations in all districts of Tbilisi (10 districts in total). 332 beneficiaries who were infected with Covid within one year were included in the study. The population was selected in schools of Tbilisi according to the principle of cluster selection. A simple random selection took place in the selected clusters. According to this principle, an equal number of beneficiaries were selected in all districts of Tbilisi. By July 1, 2022, according to National Center for Disease Control and Public Health data (NCDC.Ge), the number of test-confirmed cases in the population aged 0-18 in Tbilisi was 115137 children (17.7% of all confirmed cases). The number of patients to be examined was determined by the sample size. Oral screening, microbiological examination of saliva, and administration of oral health questionnaires to guardians were performed. Statistical processing of data was done with SPSS-23. Risk factors were estimated by odds ratio and logistic regression with 95% confidence interval. Results: Statistically reliable differences between the averages of oral health indicators in asymptomatic and symptomatic covid-infected groups are: for caries intensity (DMF+def) t=4.468 and p=0.000, for modified gingival index (MGI) t=3.048, p=0.002, for simplified oral hygiene index (S-OHI) t=4.853; p=0.000. Symptomatic covid-infection has a reliable effect on the oral microbiome (Staphylococcus aureus, Candida albicans, Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus epidermalis); (n=332; 77.3% vs n=332; 58.0%; OR=2.46, 95%CI: 1.318-4.617). According to the logistic regression, it was found that the severity of the covid infection has a significant effect on the frequency of pathogenic and conditionally pathogenic bacteria in the oral cavity B=0.903 AOR=2.467 (CL 1.318-4.617). Symptomatic covid-infection affects oral health indicators, regardless of the presence of other risk factors, such as parental employment status, tooth brushing behaviors, carbohydrate meal, fruit consumption. (p<0.05). Conclusion: Risk factors (parental employment status, tooth brushing behaviors, carbohydrate consumption) were associated with poorer oral health status in a post-Covid population of 7- to 12-year-old children. However, such a risk factor as symptomatic ongoing covid-infection affected the oral microbiome in terms of the abundant growth of pathogenic and conditionally pathogenic bacteria (Staphylococcus aureus, Candida albicans, Pseudomonas aeruginosa, Streptococcus pneumoniae, Staphylococcus epidermalis) and further worsened oral health indicators. Thus, a close association was established between symptomatic covid-infection and microbiome changes in the post-covid period; also - between the variables of oral health indicators and the symptomatic course of covid-infection.

Keywords: oral microbiome, COVID-19, population based research, oral health indicators

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Authors: Irina Deputat, Anatoly Gribanov, Yuliya Dzhos, Alexandra Nekhoroshkova, Tatyana Yemelianova, Irina Bolshevidtseva, Irina Deryabina, Yana Kereush, Larisa Startseva, Tatyana Bagretsova, Irina Ikonnikova

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In the modern world the number of elderly people increases. Preservation of functionality of an organism in the elderly becomes very important now. During aging the higher cortical functions such as feelings, perception, attention, memory, and ideation are gradual decrease. It is expressed in the rate of information processing reduction, volume of random access memory loss, ability to training and storing of new information decrease. Perspective directions in studying of aging neurophysiological parameters are brain imaging: computer electroencephalography, neuroenergy mapping of a brain, and also methods of studying of a neurodynamic brain processes. Research aim – to study features of a brain aging in elderly people by electroencephalogram (EEG) and the DC-potential level. We examined 130 people aged 55 - 74 years that did not have psychiatric disorders and chronic states in a decompensation stage. EEG was recorded with a 128-channel GES-300 system (USA). EEG recordings are collected while the participant sits at rest with their eyes closed for 3 minutes. For a quantitative assessment of EEG we used the spectral analysis. The range was analyzed on delta (0,5–3,5 Hz), a theta - (3,5–7,0 Hz), an alpha 1-(7,0–11,0 Hz) an alpha 2-(11–13,0 Hz), beta1-(13–16,5 Hz) and beta2-(16,5–20 Hz) ranges. In each frequency range spectral power was estimated. The 12-channel hardware-software diagnostic ‘Neuroenergometr-KM’ complex was applied for registration, processing and the analysis of a brain constant potentials level. The DC-potential level registered in monopolar leads. It is revealed that the EEG of elderly people differ in higher rates of spectral power in the range delta (р < 0,01) and a theta - (р < 0,05) rhythms, especially in frontal areas in aging. By results of the comparative analysis it is noted that elderly people 60-64 aged differ in higher values of spectral power alfa-2 range in the left frontal and central areas (р < 0,05) and also higher values beta-1 range in frontal and parieto-occipital areas (р < 0,05). Study of a brain constant potential level distribution revealed increase of total energy consumption on the main areas of a brain. In frontal leads we registered the lowest values of constant potential level. Perhaps it indicates decrease in an energy metabolism in this area and difficulties of executive functions. The comparative analysis of a potential difference on the main assignments testifies to unevenness of a lateralization of a brain functions at elderly people. The results of a potential difference between right and left hemispheres testify to prevalence of the left hemisphere activity. Thus, higher rates of functional activity of a cerebral cortex are peculiar to people of early advanced age (60-64 years) that points to higher reserve opportunities of central nervous system. By 70 years there are age changes of a cerebral power exchange and level of electrogenesis of a brain which reflect deterioration of a condition of homeostatic mechanisms of self-control and the program of processing of the perceptual data current flow.

Keywords: brain, DC-potential level, EEG, elderly people

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Authors: Z. Gharaee

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Recognizing actions performed by others is important in our daily lives since it is necessary for communicating with others in a proper way. We perceive an action by observing the kinematics of motions involved in the performance. We use our experience and concepts to make a correct recognition of the actions. Although building the action concepts is a life-long process, which is repeated throughout life, we are very efficient in applying our learned concepts in analyzing motions and recognizing actions. Experiments on the subjects observing the actions performed by an actor show that an action is recognized after only about two hundred milliseconds of observation. In this study, hierarchical action recognition architecture is proposed by using growing grid layers. The first-layer growing grid receives the pre-processed data of consecutive 3D postures of joint positions and applies some heuristics during the growth phase to allocate areas of the map by inserting new neurons. As a result of training the first-layer growing grid, action pattern vectors are generated by connecting the elicited activations of the learned map. The ordered vector representation layer receives action pattern vectors to create time-invariant vectors of key elicited activations. Time-invariant vectors are sent to second-layer growing grid for categorization. This grid creates the clusters representing the actions. Finally, one-layer neural network developed by a delta rule labels the action categories in the last layer. System performance has been evaluated in an experiment with the publicly available MSR-Action3D dataset. There are actions performed by using different parts of human body: Hand Clap, Two Hands Wave, Side Boxing, Bend, Forward Kick, Side Kick, Jogging, Tennis Serve, Golf Swing, Pick Up and Throw. The growing grid architecture was trained by applying several random selections of generalization test data fed to the system during on average 100 epochs for each training of the first-layer growing grid and around 75 epochs for each training of the second-layer growing grid. The average generalization test accuracy is 92.6%. A comparison analysis between the performance of growing grid architecture and self-organizing map (SOM) architecture in terms of accuracy and learning speed show that the growing grid architecture is superior to the SOM architecture in action recognition task. The SOM architecture completes learning the same dataset of actions in around 150 epochs for each training of the first-layer SOM while it takes 1200 epochs for each training of the second-layer SOM and it achieves the average recognition accuracy of 90% for generalization test data. In summary, using the growing grid network preserves the fundamental features of SOMs, such as topographic organization of neurons, lateral interactions, the abilities of unsupervised learning and representing high dimensional input space in the lower dimensional maps. The architecture also benefits from an automatic size setting mechanism resulting in higher flexibility and robustness. Moreover, by utilizing growing grids the system automatically obtains a prior knowledge of input space during the growth phase and applies this information to expand the map by inserting new neurons wherever there is high representational demand.

Keywords: action recognition, growing grid, hierarchical architecture, neural networks, system performance

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Authors: Utkarsh Tripathi, Bikalp C. Mandal, Ravi Kumar Umrao, Sirsha Das, M. K. Bhowmic, Joyesh Bagchi, Hemant Kumar

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The Central India Diamond Province (CIDP) is known for the occurrences of primary and secondary sources for diamonds from the Vindhyan platformal sediments, which host several kimberlites, with one operating mine. The known kimberlites are Neo-Proterozoic in age and intrude into the Kaimur Group of rocks. Based on the interpretation of areo-geomagnetic data, three potential zones were demarcated in parts of Chitrakoot and Banda districts, Uttar Pradesh, and Satna district, Madhya Pradesh, India. To validate the aero-geomagnetic interpretation, ground magnetic coupled with a gravity survey was conducted to validate the anomaly and explore the possibility of some pipes concealed beneath the Vindhyan sedimentary cover. Geologically the area exposes the milky white to buff-colored arkosic and arenitic sandstone belonging to the Dhandraul Formation of the Kaimur Group, which are undeformed and unmetamorphosed providing almost transparent media for geophysical exploration. There is neither surface nor any geophysical indication of intersections of linear structures, but the joint patterns depict three principal joints along NNE-SSW, ENE-WSW, and NW-SE directions with vertical to sub-vertical dips. Aeromagnetic data interpretation brings out three promising zones with the bi-polar magnetic anomaly (69-602nT) that represent potential kimberlite intrusive concealed below at an approximate depth of 150-170m. The ground magnetic survey has brought out the above-mentioned anomalies in zone-I, which is congruent with the available aero-geophysical data. The magnetic anomaly map shows a total variation of 741 nT over the area. Two very high magnetic zones (H1 and H2) have been observed with around 500 nT and 400 nT magnitudes, respectively. Anomaly zone H1 is located in the west-central part of the area, south of Madulihai village, while anomaly zone H2 is located 2km apart in the north-eastern direction. The Euler 3D solution map indicates the possible existence of the ultramafic body in both the magnetic highs (H1 and H2). The H2 high shows the shallow depth, and H1 shows a deeper depth solution. In the reduced-to-pole (RTP) method, the bipolar anomaly disappears and indicates the existence of one causative source for both anomalies, which is, in all probabilities, an ultramafic suite of rock. The H1 magnetic high represents the main body, which persists up to depths of ~500m, as depicted through the upward continuation derivative map. Radially Averaged Power Spectrum (RAPS) shows the thickness of loose sediments up to 25m with a cumulative depth of 154m for sandstone overlying the ultramafic body. The average depth range of the shallower body (H2) is 60.5-86 meters, as estimated through the Peters half slope method. Magnetic (TF) anomaly with BA contour also shows high BA value around the high zones of magnetic anomaly (H1 and H2), which suggests that the causative body is with higher density and susceptibility for the surrounding host rock. The ground magnetic survey coupled with the gravity confirms a potential target for further exploration as the findings are co-relatable with the presence of the known diamondiferous kimberlites in this region, which post-date the rocks of the Kaimur Group.

Keywords: Kaimur, kimberlite, Euler 3D solution, magnetic

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Authors: Sofia Quaglia, Carmine Di Martino, Brendan Tierney

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Artificial Intelligence (A.I.) constitutes various aspects of modern life, from the Machine Learning algorithms predicting the stocks on Wall streets to the killing of belligerents and innocents alike on the battlefield. Moreover, the end goal is to create autonomous A.I.; this means that the presence of humans in the decision-making process will be absent. The question comes naturally: when an A.I. does something wrong when its behavior is harmful to the community and its actions go against the law, which is to be held responsible? This research’s subject matter in A.I. and Robot Ethics focuses mainly on Robot Rights and its ultimate objective is to answer the questions: (i) What is the function of rights? (ii) Who is a right holder, what is personhood and the requirements needed to be a moral agent (therefore, accountable for responsibility)? (iii) Can an A.I. be a moral agent? (ontological requirements) and finally (iv) if it ought to be one (ethical implications). With the direction to answer this question, this research project was done via a collaboration between the School of Computer Science in the Technical University of Dublin that oversaw the technical aspects of this work, as well as the Department of Philosophy in the University of Milan, who supervised the philosophical framework and argumentation of the project. Firstly, it was found that all rights are positive and based on consensus; they change with time based on circumstances. Their function is to protect the social fabric and avoid dangerous situations. The same goes for the requirements considered necessary to be a moral agent: those are not absolute; in fact, they are constantly redesigned. Hence, the next logical step was to identify what requirements are regarded as fundamental in real-world judicial systems, comparing them to that of ones used in philosophy. Autonomy, free will, intentionality, consciousness and responsibility were identified as the requirements to be considered a moral agent. The work went on to build a symmetrical system between personhood and A.I. to enable the emergence of the ontological differences between the two. Each requirement is introduced, explained in the most relevant theories of contemporary philosophy, and observed in its manifestation in A.I. Finally, after completing the philosophical and technical analysis, conclusions were drawn. As underlined in the research questions, there are two issues regarding the assignment of moral agency to artificial agent: the first being that all the ontological requirements must be present and secondly being present or not, whether an A.I. ought to be considered as an artificial moral agent. From an ontological point of view, it is very hard to prove that an A.I. could be autonomous, free, intentional, conscious, and responsible. The philosophical accounts are often very theoretical and inconclusive, making it difficult to fully detect these requirements on an experimental level of demonstration. However, from an ethical point of view it makes sense to consider some A.I. as artificial moral agents, hence responsible for their own actions. When considering artificial agents as responsible, there can be applied already existing norms in our judicial system such as removing them from society, and re-educating them, in order to re-introduced them to society. This is in line with how the highest profile correctional facilities ought to work. Noticeably, this is a provisional conclusion and research must continue further. Nevertheless, the strength of the presented argument lies in its immediate applicability to real world scenarios. To refer to the aforementioned incidents, involving the murderer of innocents, when this thesis is applied it is possible to hold an A.I. accountable and responsible for its actions. This infers removing it from society by virtue of its un-usability, re-programming it and, only when properly functioning, re-introducing it successfully

Keywords: artificial agency, correctional system, ethics, natural agency, responsibility

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Authors: Gashaw Sisay Zenebe

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Northern-Ethiopian conflict that broke out on 04 November 2020 between the central government and TPLF caused destruction beyond imagination in all aspects; millions of people have been killed, including civilians, mainly women, and children. Civilians have been indiscriminately attacked simply because of their ethnic or religious identity. Warrying parties committed serious crimes of international concern opposite to International Humanitarian Law (IHL). A House of People Representatives (HPR) declared that the terrorist Tigrean Defense Force (TDF), encompassing all segments of its people, waged war against North Gondar through human flooding. On Aug 30, 2021, after midnight, TDF launched a surprise attack against Chena People who had been drunk and deep slept due to the annual festivity. Unlike the lowlands, however, ENDF conjoined the local people to fight TDF in these Highland areas. This research examines identity politics and the consequential genocidal massacre of Chena, including its human and physical destructions that occurred as a result of the armed conflict. As such, the study could benefit international entities by helping them develop a better understanding of what happened in Chena and trigger interest in engaging in ensuring the accountability and enforcement of IHL in the future. Preserving fresh evidence will also serve as a starting point on the road to achieving justice either nationally or internationally. To study the Chena case evaluated against IHL rules, a combination of qualitative and doctrinal research methodology has been employed. The study basically follows a unique sampling case study which has used primary data tools such as observation, interview, key-informant interview, FGD, and battle-field notes. To supplement, however, secondary sources, including books, journal articles, domestic laws, international conventions, reports, and media broadcasts, were used to give meaning to what happened on the ground in light of international law. The study proved that the war was taking place to separate Tigray from Ethiopia. While undertaking military operations to achieve this goal, mass killings, genocidal acts, and war crimes were committed over Chena and approximate sites in the Dabat district of North Gondar. Thus, hundreds of people lost their lives to the brutalities of mass killings, hundreds of people were subjected to a forcible disappearance, and tens of thousands of people were forced into displacement. Furthermore, harsh beatings, forced labor, slavery, torture, rape, and gang rape have been reported, and generally, people are subjected to pass cruel, inhuman, and degrading treatment and punishment. Also, what is so unique is that animals were indiscriminately killed completely, making the environment unsafe for human survival because of pollution and bad smells and the consequent diseases such as Cholera, Flu, and Diarrhea. In addition to TDF, ENDF’s shelling has caused destruction to farmers’ houses & claimed lives. According to humanitarian principles, acts that can establish MACs and war crimes were perpetrated. Generally, the war in this direction has shown an absolute disrespect for international law norms.

Keywords: genocide, war crimes, Tigray Defense Force, Chena, IHL

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Authors: Raptis Sotirios

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Health and social care (HSc) services planning and scheduling are facing unprecedented challenges due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven can help to improve policies, plan and design services provision schedules using algorithms assist healthcare managers’ to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as CART, random forests (RF), and logistic regression (LGR). The significance tests Chi-Squared test and Student test are used on data over a 39 years span for which HSc services data exist for services delivered in Scotland. The demands are probabilistically associated through statistical hypotheses that assume that the target service’s demands are statistically dependent on other demands as a NULL hypothesis. This linkage can be confirmed or not by the data. Complementarily, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus groups of services. Statistical tests confirm ML couplings making the prediction also statistically meaningful and prove that a target service can be matched reliably to other services, and ML shows these indicated relationships can also be linear ones. Zero paddings were used for missing years records and illustrated better such relationships both for limited years and in the entire span offering long term data visualizations while limited years groups explained how well patients numbers can be related in short periods or can change over time as opposed to behaviors across more years. The prediction performance of the associations is measured using Receiver Operating Characteristic(ROC) AUC and ACC metrics as well as the statistical tests, Chi-Squared and Student. Co-plots and comparison tables for RF, CART, and LGR as well as p-values and Information Exchange(IE), are provided showing the specific behavior of the ML and of the statistical tests and the behavior using different learning ratios. The impact of k-NN and cross-correlation and C-Means first groupings is also studied over limited years and the entire span. It was found that CART was generally behind RF and LGR, but in some interesting cases, LGR reached an AUC=0 falling below CART, while the ACC was as high as 0.912, showing that ML methods can be confused padding or by data irregularities or outliers. On average, 3 linear predictors were sufficient, LGR was found competing RF well, and CART followed with the same performance at higher learning ratios. Services were packed only if when significance level(p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, birth weights, alcoholism, drug abuse, and emergency admissions. The work found that different HSc services can be well packed as plans of limited years, across various services sectors, learning configurations, as confirmed using statistical hypotheses.

Keywords: class, cohorts, data frames, grouping, prediction, prob-ability, services

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Authors: T. Heiman, D. Olenik-Shemesh

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Over the past decade, with the rapid growth of electronic communication, the internet and, in particular, social networking has become an inseparable part of people's daily lives. Along with its benefits, a new type of online aggression has emerged, defined as cyber bullying, a form of interpersonal aggressive behavior that takes place through electronic means. Cyber-bullying is characterized by repetitive behavior over time of maladaptive authority and power usage using computers and cell phones via sending insulting messages and hurtful pictures. Preliminary findings suggest that the prevalence of involvement in cyber-bullying among higher education students varies between 10 and 35%. As to date, universities are facing an uphill effort in trying to restrain online misbehavior. As no studies examined the relationships between cyber-bullying involvement with personal aspects, and its impacts on academic achievement and work functioning, this present study examined the nature of cyber-bullying involvement among 1,052 undergraduate students (mean age = 27.25, S.D = 4.81; 66.2% female), coping with, as well as the effects of social support, perceived self-efficacy, well-being, and body-perception, in relation to cyber-victimization. We assume that students in higher education are a vulnerable population and at high risk of being cyber-victims. We hypothesize that social support might serve as a protective factor and will moderate the relationships between the socio-emotional variables and the occurrence of cyber- victimization. The findings of this study will present the relationships between cyber-victimization and the social-emotional aspects, which constitute risk and protective factors. After receiving approval from the Ethics Committee of the University, a Google Drive questionnaire was sent to a random sample of students, studying in the various University study centers. Students' participation was voluntary, and they completed the five questionnaires anonymously: Cyber-bullying, perceived self-efficacy, subjective well-being, social support and body perception. Results revealed that 11.6% of the students reported being cyber-victims during last year. Examining the emotional and behavioral reactions to cyber-victimization revealed that female emotional and behavioral reactions were significantly greater than the male reactions (p < .001). Moreover, females reported on a significant higher social support compared to men; male reported significantly on a lower social capability than female; and men's body perception was significantly more positive than women's scores. No gender differences were observed for subjective well-being scale. Significant positive correlations were found between cyber-victimization and fewer friends, lower grades, and work ineffectiveness (r = 0.37- .40, p < 0 .001). The results of the Hierarchical regression indicated significantly that cyber-victimization can be predicted by lower social support, lower body perception, and gender (female), that explained 5.6% of the variance (R2 = 0.056, F(5,1047) = 12.47, p < 0.001). The findings deepen our understanding of the students' involvement in cyber-bullying, and present the relationships of the social-emotional and academic aspects on cyber-victim students. In view of our findings, higher education policy could help facilitate coping with cyber-bullying incidents, and student support units could develop intervention programs aimed at reducing cyber-bullying and its impacts.

Keywords: academic and personal factors, cyber-victimization, social support, higher education

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Authors: Daniela Stephanie Kuenstle

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Complex industries such as banking or insurance experience slow growth in mobile sales. While today’s mobile applications are sophisticated and enable location based and personalized services, consumers prefer online or even face-to-face services to complete complex transactions. A possible reason for this reluctance is that the provided service within transactional mobile applications (apps) does not adequately correspond to users’ needs. Therefore, this paper examines the impact of the user context on mobile service (m-service) in m-commerce. Motivated by the potential which context-sensitive m-services hold for the future, the impact of temporal variations as a dimension of user context, on m-service design is examined. In particular, the research question asks: Does consumer urgency function as a determinant of m-service composition in transactional apps by moderating the relation between m-service type and m-service success? Thus, the aim is to explore the moderating influence of urgency on m-service types, which includes Technology Mediated Service and Technology Generated Service. While mobile applications generally comprise features of both service types, this thesis discusses whether unexpected urgency changes customer preferences for m-service types and how this consequently impacts the overall m-service success, represented by purchase intention, loyalty intention and service quality. An online experiment with a random sample of N=1311 participants was conducted. Participants were divided into four treatment groups varying in m-service types and urgency level. They were exposed to two different urgency scenarios (high/ low) and two different app versions conveying either technology mediated or technology generated service. Subsequently, participants completed a questionnaire to measure the effectiveness of the manipulation as well as the dependent variables. The research model was tested for direct and moderating effects of m-service type and urgency on m-service success. Three two-way analyses of variance confirmed the significance of main effects, but demonstrated no significant moderation of urgency on m-service types. The analysis of the gathered data did not confirm a moderating effect of urgency between m-service type and service success. Yet, the findings propose an additive effects model with the highest purchase and loyalty intention for Technology Generated Service and high urgency, while Technology Mediated Service and low urgency demonstrate the strongest effect for service quality. The results also indicate an antagonistic relation between service quality and purchase intention depending on the level of urgency. Although a confirmation of the significance of this finding is required, it suggests that only service convenience, as one dimension of mobile service quality, delivers conditional value under high urgency. This suggests a curvilinear pattern of service quality in e-commerce. Overall, the paper illustrates the complex interplay of technology, user variables, and service design. With this, it contributes to a finer-grained understanding of the relation between m-service design and situation dependency. Moreover, the importance of delivering situational value with apps depending on user context is emphasized. Finally, the present study raises the demand to continue researching the impact of situational variables on m-service design in order to develop more sophisticated m-services.

Keywords: mobile consumer behavior, mobile service design, mobile service success, self-service technology, situation dependency, user-context sensitivity

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Authors: Amandeep Kaur

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Farming is one of the most influential traditions which started around 10000 BC and has revolutionized human civilization. It is believed that farming originated at a separate location. Thus it has a great impact on local culture, which in turn gave rise to diversified farming practices. Farming activities are influenced by the culture of a particular region or community as local people have their own knowledge and belief system about soil and crops. With the inception of the Green Revolution, 'a high tech machinery model' in Punjab, various traditional farming methods and techniques changed. The present research concentrates on the local knowledge of farmers and local farming systems from an anthropological perspective. In view of the prevailing agrarian crisis in Punjab, this research is focused on farmer’s experiences and their perception regarding farming practices. Thus an attempt has to be made to focus on the local knowledge, perception, and experience of farmers for eco-friendly and sustainable agricultural development. Farmers voices are used to understand the relationship between farming practices and socio-cultural life of farmers in Faridkot district, Punjab. The research aims to comprehend the nature of changes taking place in the socio-cultural life of people with the development of capitalism and agricultural modernization. The study is based on qualitative methods of ethnography in Sarawan village of Faridkot District. Inferences drawn from in-depth case studies collected from 60 agricultural households lead to the concept of the process of diffusion, innovation, and adoption of farming technology, a variety of crops and the dissemination of agricultural skills regarding various cultural farming practices. The data is based on random sampling; the respondents were both males and females above the age of 18 years to attain a holistic understanding across the generations. A Quasi-participant observation related to lifestyle, the standard of living, and various farming practices performed by them were done. Narratives derived from the fieldwork depicts that farmers usually oppose the restrictions imposed by the government on certain farming practices, especially ban on stubble burning. This paper presents the narratives of farmers regarding the dissemination of awareness about the use of new varieties of seeds, technology, fertilizers, pesticides, etc. The study reveals that farming systems have developed in ways reflecting the activities and choices of farmers influenced by environmental, socio-cultural, economic, and political situations. Modern farming practices have forced small farmers into debt as farmers feel pride in buying new machinery. It has also led to the loss of work culture and excessive use of drugs among youngsters. Even laborers did not want to work on the land with cultivating farmers primarily for social and political reasons. Due to lack of proper marketing of crops, there is a continuum of the wheat-rice cycle instead of crop diversification in Punjab. Change in the farming system also affects the social structure of society. Agricultural modernization has commercialized the socio-cultural relations in Punjab and is slowly urbanizing the rural landscape revolutionizing the traditional social relations to capitalistic relations.

Keywords: agricultural modernization, capitalism, farming practices, narratives

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Ousmane Sarr

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The Senegalese coasts have high productivity of fishery resources due to the frequency of intense up-welling system that occurs along its coast, caused by the maritime trade winds making its waters nutrients rich. Fishing plays a primordial role in Senegal's socioeconomic plans and food security. However, a global diagnosis of the Senegalese maritime fishing sector has highlighted the challenges this sector encounters. Among these concerns, some significant stocks, a priority target for artisanal fishing, need further assessment. If no efforts are made in this direction, most stock will be overexploited or even in decline. It is in this context that this research was initiated. This investigation aimed to apply a multi-modal approach (LBB, Catch-only-based CMSY model and its most recent version (CMSY++); JABBA, and JABBA-Select) to assess the stock of Atlantic bonito, Sarda sarda (Bloch, 1793) in the Senegalese Exclusive Economic Zone (SEEZ). Available catch, effort, and size data from Atlantic bonito over 15 years (2004-2018) were used to calculate the nominal and standardized CPUE, size-frequency distribution, and length at retentions (50 % and 95 % selectivity) of the species. These relevant results were employed as input parameters for stock assessment models mentioned above to define the stock status of this species in this region of the Atlantic Ocean. The LBB model indicated an Atlantic bonito healthy stock status with B/BMSY values ranging from 1.3 to 1.6 and B/B0 values varying from 0.47 to 0.61 of the main scenarios performed (BON_AFG_CL, BON_GN_Length, and BON_PS_Length). The results estimated by LBB are consistent with those obtained by CMSY. The CMSY model results demonstrate that the SEEZ Atlantic bonito stock is in a sound condition in the final year of the main scenarios analyzed (BON, BON-bt, BON-GN-bt, and BON-PS-bt) with sustainable relative stock biomass (B2018/BMSY = 1.13 to 1.3) and fishing pressure levels (F2018/FMSY= 0.52 to 1.43). The B/BMSY and F/FMSY results for the JABBA model ranged between 2.01 to 2.14 and 0.47 to 0.33, respectively. In contrast, The estimated B/BMSY and F/FMSY for JABBA-Select ranged from 1.91 to 1.92 and 0.52 to 0.54. The Kobe plots results of the base case scenarios ranged from 75% to 89% probability in the green area, indicating sustainable fishing pressure and an Atlantic bonito healthy stock size capable of producing high yields close to the MSY. Based on the stock assessment results, this study highlighted scientific advice for temporary management measures. This study suggests an improvement of the selectivity parameters of longlines and purse seines and a temporary prohibition of the use of sleeping nets in the fishery for the Atlantic bonito stock in the SEEZ based on the results of the length-base models. Although these actions are temporary, they can be essential to reduce or avoid intense pressure on the Atlantic bonito stock in the SEEZ. However, it is necessary to establish harvest control rules to provide coherent and solid scientific information that leads to appropriate decision-making for rational and sustainable exploitation of Atlantic bonito in the SEEZ and the Eastern Atlantic Ocean.

Keywords: multi-model approach, stock assessment, atlantic bonito, healthy stock, sustainable, SEEZ, temporary management measures

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Authors: Liuhui Zhu, Peng Zeng

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With the rapid development in China, the urbanization has entered the transformation and promotion stage, and its direction of development has shifted to overall regional synergy. China has a large number of towns and villages, with comparative small scale and scattered distribution, which always support and provide resources to cities leading to urban-rural opposition, so it is difficult to achieve common development in a single town or village. In this context, the regional development should focus more on towns and villages to form a synergetic system, joining the regional association with cities. Thus, the paper raises the question about how to effectively organize towns and villages system to regulate the resource allocation and improve the comprehensive value of the regional area. To answer the question, it is necessary to find a suitable research unit and analysis of its present situation of towns and villages system for optimal development. By combing relevant researches and theoretical models, the county is the most basic administrative unit in China, which can directly guide and regulate the development of towns and villages, so the paper takes county as the research unit. Following the theoretical concept of ‘three structures and one network’, the paper concludes the research framework to analyse the present situation of towns and villages system, including scale structure, functional structure, spatial structure, and organization network. The analytical methods refer to the fractal theory and gravity model, using statistics and spatial data. The scale structure analyzes rank-size dimensions and uses the principal component method to calculate the comprehensive scale of towns and villages. The functional structure analyzes the functional types and industrial development of towns and villages. The spatial structure analyzes the aggregation dimension, network dimension, and correlation dimension of spatial elements to represent the overall spatial relationships. In terms of organization network, from the perspective of entity and ono-entity, the paper analyzes the transportation network and gravitational network. Based on the present situation analysis, the optimization strategies are proposed in order to achieve a synergetic relationship between towns and villages in the county area. The paper uses Suning county in the Beijing-Tianjin-Hebei region as a case study to apply the research framework and methods and then proposes the optimization orientations. The analysis results indicate that: (1) The Suning county is lack of medium-scale towns to transfer effect from towns to villages. (2) The distribution of gravitational centers is uneven, and the effect of gravity is limited only for nearby towns and villages. The gravitational network is not complete, leading to economic activities scattered and isolated. (3) The overall development of towns and villages system is immature, staying at ‘single heart and multi-core’ stage, and some specific optimization strategies are proposed. This study provides a regional view for the development of towns and villages and concludes the research framework and methods of towns and villages system for forming an effective synergetic relationship between them, contributing to organize resources and stimulate endogenous motivation, and form counter magnets to join the urban-rural integration.

Keywords: towns and villages system, organization structure, county area, fractal theory, gravity model

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Authors: Prashant Gupta

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Throughout India, temples have served as cultural centers, commerce hubs, art galleries, educational institutions, and social centers in addition to being places of worship since centuries. Across the country, there are over two million temples, which are crucial economic hubs, attracting devotees and tourists worldwide. In India, we have 53 temples per each 100,000 Indians. As per NSSO survey, the temple economy is worth about $40 billion and 2.32 per cent of GDP based on major temple’s survey, which only includes formal sector. It could be much larger as an actual estimation has not been done yet. In India, 43.1% of total economy represents informal sector. Over 10 billion domestic tourists visit to new destinations every year within India. Even 20 per cent of the 90 million foreign tourists visited Madurai and Mahabalipuram temples which became the most visited tourist spot in 2022. Recently the current central government in power have started revitalizing the ancient Indian civilization by reconstructing and beautifying the major temples of India i.e., Kashi Vishwanath Corridor, Mahakaleshwara Temple, Kedarnath, Ayodhya etc. The reason researcher chose Kashi as a case study because it is known as a Spiritual Capital of India, which is also the abode for the spread of Hinduism, Buddhism, Jainism and Sikkism, which are core Sanatan Dharmic practices. 17,800 Million INR Amount was spend to redevelop Kashi Vishwanath Corridor since 2019. RESEARCH OBJECTIVES 1. To assess historical contribution of temples in socio economic development and revival of Indic Civilization. 2. To examine the role of temples redevelopment for informal sector businesses. 3. To identify the sub-sectors of informal sector businesses 4. To identify products and services of informal businesses for investigation of marketing strategies and business development. PROPOSED METHODS AND PROCEDURES This study will follow a mixed approach, employing both qualitative and quantitative methods of research. To conduct the study, data will be collected from 500 informal business owners through structured questionnaire and interview instruments. The informal business owners will be selected using a systematic random sampling technique. In addition, documents from government offices of the last 10 years of tax collection will be reviewed to substantiate the study. To analyze the study, descriptive and econometric analysis techniques will be employed. EXPECTED CONTRIBUTION OF THE PROPOSED STUDY By studying the contribution of temple re-development on informal business creation and growth, the study will be beneficial to the informal business owners and the government. For the government, scientific and empirical evidence on the contribution of temple re-development for informal business creation and growth to give evidence the study will give based infrastructural development and boosting tax collection. For informal businesses, the study will give them a detailed insight on the nature of their business and the possible future growth potential of their business, and the alternative products and services supplying to their customers in the future. Studying informal businesses will help to identify the key products and services which are majorly profitable and possess potential to multiply and grow through correct product marketing strategies and business development.

Keywords: business development, informal sector businesses, services and products marketing, temple economics

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Authors: Vittorio Astarita, Giuseppe Guido, Vincenzo Pasquale Giofre, Alessandro Vitale

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Traffic microsimulation has been used extensively to evaluate consequences of different traffic planning and control policies in terms of travel time delays, queues, pollutant emissions, and every other common measured performance while at the same time traffic safety has not been considered in common traffic microsimulation packages as a measure of performance for different traffic scenarios. Vehicle conflict techniques that were introduced at intersections in the early traffic researches carried out at the General Motor laboratory in the USA and in the Swedish traffic conflict manual have been applied to vehicles trajectories simulated in microscopic traffic simulators. The concept is that microsimulation can be used as a base for calculating the number of conflicts that will define the safety level of a traffic scenario. This allows engineers to identify unsafe road traffic maneuvers and helps in finding the right countermeasures that can improve safety. Unfortunately, most commonly used indicators do not consider conflicts between single vehicles and roadside obstacles and barriers. A great number of vehicle crashes take place with roadside objects or obstacles. Only some recent proposed indicators have been trying to address this issue. This paper introduces a new procedure based on the simulation of potential crash events for the evaluation of safety levels in microsimulation traffic scenarios, which takes into account also potential crashes with roadside objects and barriers. The procedure can be used to define new conflict indicators. The proposed simulation procedure generates with the random perturbation of vehicle trajectories a set of potential crashes which can be evaluated accurately in terms of DeltaV, the energy of the impact, and/or expected number of injuries or casualties. The procedure can also be applied to real trajectories giving birth to new surrogate safety performance indicators, which can be considered as “simulation-based”. The methodology and a specific safety performance indicator are described and applied to a simulated test traffic scenario. Results indicate that the procedure is able to evaluate safety levels both at the intersection level and in the presence of roadside obstacles. The procedure produces results that are expressed in the same unity of measure for both vehicle to vehicle and vehicle to roadside object conflicts. The total energy for a square meter of all generated crash can be used and is shown on the map, for the test network, after the application of a threshold to evidence the most dangerous points. Without any detailed calibration of the microsimulation model and without any calibration of the parameters of the procedure (standard values have been used), it is possible to identify dangerous points. A preliminary sensitivity analysis has shown that results are not dependent on the different energy thresholds and different parameters of the procedure. This paper introduces a specific new procedure and the implementation in the form of a software package that is able to assess road safety, also considering potential conflicts with roadside objects. Some of the principles that are at the base of this specific model are discussed. The procedure can be applied on common microsimulation packages once vehicle trajectories and the positions of roadside barriers and obstacles are known. The procedure has many calibration parameters and research efforts will have to be devoted to make confrontations with real crash data in order to obtain the best parameters that have the potential of giving an accurate evaluation of the risk of any traffic scenario.

Keywords: road safety, traffic, traffic safety, traffic simulation

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Elisa Menardo, Margherita Pasini, Margherita Brondino

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A growing body of empirical research from different areas of inquiry suggests that brief contact with natural environment restore mental resources. The Attention Restoration Theory (ART) is the widespread used and empirical founded theory developed to explain why exposure to nature helps people to recovery cognitive resources. It assumes that contact with nature allows people to free (and then recovery) voluntary attention resources and thus allows them to recover from a cognitive fatigue situation. However, it was suggested that some people could have more cognitive benefit after exposure to urban environment. The objective of this study is to report the results of a meta-analysis on studies (peer-reviewed articles) comparing the restorativeness (the quality to be restorative) perceived in natural environments than those perceived in urban environments. This meta-analysis intended to estimate how much nature environments (forests, parks, boulevards) are perceived to be more restorativeness than urban ones (i.e., the magnitude of the perceived restorativeness’ difference). Moreover, given the methodological difference between study, it studied the potential role of moderator variables as participants (student or other), instrument used (Perceived Restorativeness Scale or other), and procedure (in laboratory or in situ). PsycINFO, PsycARTICLES, Scopus, SpringerLINK, Web of Science online database were used to identify all peer-review articles on restorativeness published to date (k = 167). Reference sections of obtained papers were examined for additional studies. Only 22 independent studies (with a total of 1371 participants) met inclusion criteria (direct exposure to environment, comparison between one outdoor environment with natural element and one without natural element, and restorativeness measured by self-report scale) and were included in meta-analysis. To estimate the average effect size, a random effect model (Restricted Maximum-likelihood estimator) was used because the studies included in the meta-analysis were conducted independently and using different methods in different populations, so no common effect-size was expected. The presence of publication bias was checked using trim and fill approach. Univariate moderator analysis (mixed effect model) were run to determine whether the variable coded moderated the perceived restorativeness difference. Results show that natural environments are perceived to be more restorativeness than urban environments, confirming from an empirical point of view what is now considered a knowledge gained in environmental psychology. The relevant information emerging from this study is the magnitude of the estimated average effect size, which is particularly high (d = 1.99) compared to those that are commonly observed in psychology. Significant heterogeneity between study was found (Q(19) = 503.16, p < 0.001;) and studies’ variability was very high (I2[C.I.] = 96.97% [94.61 - 98.62]). Subsequent univariate moderator analyses were not significant. Methodological difference (participants, instrument, and procedure) did not explain variability between study. Other methodological difference (e.g., research design, environment’s characteristics, light’s condition) could explain this variability between study. In the mine while, studies’ variability could be not due to methodological difference but to individual difference (age, gender, education level) and characteristics (connection to nature, environmental attitude). Furthers moderator analysis are working in progress.

Keywords: meta-analysis, natural environments, perceived restorativeness, urban environments

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