Search results for: maximum entropy modeling

Authors: Judith Stein, Elfriede Friedmann

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The injection of a drug into the vitreous body for the treatment of retinal diseases like wet aged-related macular degeneration (AMD) is the most common medical intervention worldwide. We develop mathematical models for drug transport in the vitreous body of a human eye to analyse the impact of different rheological models of the vitreous on drug distribution. In addition to the convection diffusion equation characterizing the drug spreading, we use porous media modeling for the healthy vitreous with a dense collagen network and include the steady permeating flow of the aqueous humor described by Darcy's law driven by a pressure drop. Additionally, the vitreous body in a healthy human eye behaves like a viscoelastic gel through the collagen fibers suspended in the network of hyaluronic acid and acts as a drug depot for the treatment of retinal diseases. In a completely liquefied vitreous, we couple the drug diffusion with the classical Navier-Stokes flow equations. We prove the global existence and uniqueness of the weak solution of the developed initial-boundary value problem describing the drug distribution in the healthy vitreous considering the permeating aqueous humor flow in the realistic three-dimensional setting. In particular, for the drug diffusion equation, results from the literature are extended from homogeneous Dirichlet boundary conditions to our mixed boundary conditions that describe the eye with the Galerkin's method using Cauchy-Schwarz inequality and trace theorem. Because there is only a small effective drug concentration range and higher concentrations may be toxic, the ability to model the drug transport could improve the therapy by considering patient individual differences and give a better understanding of the physiological and pathological processes in the vitreous.

Keywords: coupled PDE systems, drug diffusion, mixed boundary conditions, vitreous body

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Authors: Mohammed Saleh Rezk, Reza Kashani

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Auxiliary damping has gained popularity in recent years, especially in structures such as mid- and high-rise buildings. Distributed damping systems (typically viscous and viscoelastic) or reactive damping systems (such as tuned mass dampers) are the two types of damping choices for such structures. Distributed VE dampers are normally configured as braces or damping panels, which are engaged through relatively small movements between the structural members when the structure sways under wind or earthquake loading. In addition to being used as stand-alone dampers in distributed damping applications, VE dampers can also be incorporated into the suspension element of tuned mass dampers (TMDs). In this study, analytical and numerical tools for modeling and design of multilayer viscoelastic damping devices to be used in dampening the vibration of large structures are developed. Considering the limitations of analytical models for the synthesis and analysis of realistic, large, multilayer VE dampers, the emphasis of the study has been on numerical modeling using the finite element method. To verify the finite element models, a two-layer VE damper using ½ inch synthetic viscoelastic urethane polymer was built, tested, and the measured parameters were compared with the numerically predicted ones. The numerical model prediction and experimentally evaluated damping and stiffness of the test VE damper were in very good agreement. The effectiveness of VE dampers in adding auxiliary damping to larger structures is numerically demonstrated by chevron bracing one such damper numerically into the model of a massive frame subject to an abrupt lateral load. A comparison of the responses of the frame to the aforementioned load, without and with the VE damper, clearly shows the efficacy of the damper in lowering the extent of frame vibration.

Keywords: viscoelastic, damper, distributed damping, tuned mass damper

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Authors: Mohammad Azam

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This work is an endeavor to empirically investigate the Gross Domestic Product-Growth as mediating variable between various factors and portfolio returns using a broad sample of 522 financial and non-financial firms enlisted on Pakistan Stock Exchange between January-1993 and June-2022. The study employs the Structural Equation modeling and Ordinary Least Square regression to determine the findings before and during the Covid-19 epidemiological situation, which has not received due attention by researchers. The analysis reveals that market and investment factors are redundant, whereas size and value show significant results, whereas Gross Domestic Product-Growth performs significant mediating impact for the whole time frame. Using before Covid-19 period, the results reveal that market, value, and investment are redundant, but size, profitability, and Gross Domestic Product-Growth are significant. During the Covid-19, the statistics indicate that market and investment are redundant, though size and Gross Domestic Product-Growth are highly significant, but value and profitability are moderately significant. The Ordinary Least Square regression shows that market and investment are statistically insignificant, whereas size is highly significant but value and profitability are marginally significant. Using the Gross Domestic Product-Growth augmented model, a slight growth in R-square is observed. The size, value and profitability factors are recommended to the investors for Pakistan Stock Exchange. Conclusively, in the Pakistani market, the Gross Domestic Product-Growth indicates a feeble moderating effect between risk-premia and portfolio returns.

Keywords: asset pricing puzzle, mediating role of GDP-growth, structural equation modeling, COVID-19 pandemic, Pakistan stock exchange

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Authors: Shreyas S. Hegde, Anindya Deb, Suresh Nagesh

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Computational bio-mechanics is developing rapidly as a non-invasive tool to assist the medical fraternity to help in both diagnosis and prognosis of human body related issues such as injuries, cardio-vascular dysfunction, atherosclerotic plaque etc. Any system that would help either properly diagnose such problems or assist prognosis would be a boon to the doctors and medical society in general. Recently a lot of work is being focused in this direction which includes but not limited to various finite element analysis related to dental implants, skull injuries, orthopedic problems involving bones and joints etc. Such numerical solutions are helping medical practitioners to come up with alternate solutions for such problems and in most cases have also reduced the trauma on the patients. Some work also has been done in the area related to the use of computational fluid mechanics to understand the flow of blood through the human body, an area of hemodynamics. Since cardio-vascular diseases are one of the main causes of loss of human life, understanding of the blood flow with and without constraints (such as blockages), providing alternate methods of prognosis and further solutions to take care of issues related to blood flow would help save valuable life of such patients. This project is an attempt to use computational fluid dynamics (CFD) to solve specific problems related to hemodynamics. The hemodynamics simulation is used to gain a better understanding of functional, diagnostic and theoretical aspects of the blood flow. Due to the fact that many fundamental issues of the blood flow, like phenomena associated with pressure and viscous forces fields, are still not fully understood or entirely described through mathematical formulations the characterization of blood flow is still a challenging task. The computational modeling of the blood flow and mechanical interactions that strongly affect the blood flow patterns, based on medical data and imaging represent the most accurate analysis of the blood flow complex behavior. In this project the mathematical modeling of the blood flow in the arteries in the presence of successive blockages has been analyzed using CFD technique. Different cases of blockages in terms of percentages have been modeled using commercial software CATIA V5R20 and simulated using commercial software ANSYS 15.0 to study the effect of varying wall shear stress (WSS) values and also other parameters like the effect of increase in Reynolds number. The concept of fluid structure interaction (FSI) has been used to solve such problems. The model simulation results were validated using in vivo measurement data from existing literature

Keywords: computational fluid dynamics, hemodynamics, blood flow, results validation, arteries

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Authors: Abiola A. Ojesanmi, Eric O. Amonsou

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The formation of soluble complexes is usually within a narrow pH range characterized by weak interactions. Moreover, the rigid conformation of globular proteins restricts the number of charged groups capable of interacting with polysaccharides, thereby limiting food applications. Hence, this study investigated the impact of tryptic-limited hydrolysis on the formation of Bambara protein-gum arabic soluble complexes formation. The electrostatic interactions were monitored through turbidimetry analysis. The Bambara protein hydrolysates at a specified degree of hydrolysis, and DHs (2, 5, and 7.5) were characterized using size exclusion chromatography, zeta potential, surface hydrophobicity, and intrinsic fluorescence. The stability of the complexes was investigated using differential scanning calorimetry and rheometry. The limited tryptic hydrolysis significantly widened the pH range of the formation of soluble complexes, with DH 5 having a wider range (pH 7.0 - 4.3) compared to DH 2 and DH 7.5, while there was no notable difference in the optimum complexation pH of the insoluble complexes. Larger peptides (140, 118 kDa) were detected in DH 2 relative to 144, 70, and 61 kDa in DH 5, which were larger than 140, 118, 48, and 32 kDa in DH 7. 5. An increase in net negative charge (- 30 Mv for DH 7.5) and a slight shift in the net neutrality (from pH 4.9 to 4.3) of the hydrolysates were observed which consequently impacted the electrostatic interaction with gum arabic. There was exposure of the hydrophobic amino acids up to 4-fold in comparison with the isolate and a red shift in maximum fluorescence wavelength in DH dependent manner following the hydrolysis. The denaturation temperature of the soluble complex from the hydrolysates shifted to higher values, having DH 5 with the maximum temperature (94.24 °C). A highly interconnected gel-like soluble complex network was formed having DH 5 with a better structure relative to DH 2 and 7.5. The study showed the use of limited tryptic hydrolysis at DH 5 as an effective approach to modify Bambara protein and provided a more stable and wider pH range of formation for soluble complex, thereby enhancing the food application.

Keywords: Bambara groundnut, gum arabic, interaction, soluble complex

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Authors: Eng Rima Al-Awadhi, Abdul Jaleel Tharayil

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In a project-centric organization like KOC, managing the knowledge of the project is of critical importance to the success of the project and the organization. However, due to the very nature and complexity involved, each project engagement generates a lot of 'learnings' that need to be factored into while new projects are initiated and thus avoid repeating the same mistake. But, many a time these learnings are localized and remains as ‘tacit knowledge’ leading to scope re-work, schedule overrun, adjustment orders, concession requests and claims. While KOC follows an asset based organization structure, with a multi-cultural and multi-ethnic workforce and larger chunk of the work is carried out through complex, long term project engagement, diffusion of ‘learnings’ across assets while dealing with the natural entropy of the organization is of great significance. Considering the relatively higher number of mega projects, it's important that the issues raised during the project life cycle are centrally harvested, analyzed and the ‘learnings’ from these issues are shared, absorbed and are in-turn utilized to enhance and refine the existing process and practices, leading to improve the project performance. One of the many factors contributing to the successful completion of a project on time is the reduction in the number of variations or concessions triggered during the project life cycle. The project process integrated knowledge sharing framework discusses the knowledge harvesting methodology adopted, the challenges faced, learnings acquired and its impact on project performance. The framework facilitates the proactive identification of issues that may have an impact on the overall quality of the project and improve performance.

Keywords: knowledge harvesting, project integrated knowledge sharing, performance improvement, knowledge management, lessons learn

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Authors: Farah Ali, Tehreem Fayyaz, Musadiq Idris

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The present work was undertaken to investigate effects of various extracts of withania somnifera for anti-diabetic activity in alloxan induced diabetic rabbits. Rabbits were acclimatized for a week to standard laboratory temperature. Animals were fed according to a strict schedule (8 am, 3 pm and 10 pm) with green fodder (Medicago sativa) and tap water ad libitum. Animals were divided into nine groups of six rabbits each in a random manner. Body weights and physical activities of all rabbits were recorded before start of experiments. The animals of group 1 and 2 were given lactose (250 mg/kg, p.o) and Withania somniferaroot powder (100 mg/kg, p.o) respectively daily from day 1-20. Animals of group 3 were given alloxan (100 mg/kg, i.v) as a single dose on day 1. Powdered root of Withania somnifera in the doses of 100, 150, 200 mg/kg and its aqueous and ethanol extracts (equivalent to 200 mg/kg of crude drug) were given to the treated animals (groups 4-8), respectively by oral route for three weeks (day 1-20o.d), along with alloxan (100 mg/kg, i.v) as a single dose on day 1. Group 9 was treated with metformin (200 mg/kg, p.o) daily from day 1-20, along with a single dose of alloxan (100 mg/ kg, i.v) on day 1. Fasting serum glucose concentration in groups 3-9 was increased significantly (p<0.05) on day 3, with a maximum increase (215.3 mg/dl) in animals of toxic control (TC) group (3) on day 21 of the experiment as compared to normal control (NC) group (1). Effects of different doses (100, 150, 200 mg/kg, p.o) of W. somnifera root powder (WS) decreased the fasting serum glucose concentration as compared to toxic control group, with a maximum decrease (88.3 mg/dl) in group 2 (treated control) on day 21 of the experiment. Metformin (200 mg/kg, p.o) (reference control), aqueous extract (AWS) and ethanol extract (EWS) of W. somnifera (equivalent to 100 mg/kg W.somnifera root, p.o) antagonized the effects of alloxan as compared to toxic control group. These results indicate that the W. somnifera possess significant anti–diabetic activity.

Keywords: diabetes, serum, glucose, blood, sugar, rabbits

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Authors: Ammar S. M. Moohialdin, Bambang T. Suhariadi, Mohsin Siddiqui

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This paper addresses the application of physiological status monitoring (PSM) for assessing the impact of harsh weather conditions on sports activities in universities in Saudi Arabia. Real sports measurement was conducted during sports activities such that the physiological status (HR and BR) of five students were continuously monitored by using Zephyr BioHarness^TM 3.0 sensors in order to identify the physiological bonds and zones. These bonds and zones were employed as indicators of the associated physiological risks of the performed sports activities. Furthermore, a short yes/no questionnaire was applied to collect information on participants’ health conditions and opinions of the applied PSM sensors. The results show the absence of a warning system as a protective aid for the hazardous levels of extremely hot and humid weather conditions that may cause dangerous and fatal circumstances. The applied formulas for estimating maximum HR provides accurate estimations for Maximum Heart Rate (HR_max). The physiological results reveal that the performed activities by the participants are considered the highest category (90–100%) in terms of activity intensity. This category is associated with higher HR, BR and physiological risks including losing the ability to control human body behaviors. Therefore, there is a need for immediate intervention actions to reduce the intensity of the performed activities to safer zones. The outcomes of this study assist the safety improvement of sports activities inside universities and athletes performing their sports activities. To the best of our knowledge, this is the first paper to represent a special case of the application of PSM technology for assessing sports activities in universities considering the impacts of harsh weather conditions on students’ health and safety.

Keywords: physiological status monitoring (PSM), heart rate (HR), breathing rate (BR), Arabian Gulf

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Authors: Jinan Fiaidhi, Hashmath Shaik

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Breaking the barrier for practicing evidence-based medicine relies on effective methods for rapidly identifying relevant evidence from the body of biomedical literature. An important challenge confronted by medical practitioners is the long time needed to browse, filter, summarize and compile information from different medical resources. Deep learning can help in solving this based on automatic question answering (Q&A) and transformers. However, Q&A and transformer technologies are not trained to answer clinical queries that can be used for evidence-based practice, nor can they respond to structured clinical questioning protocols like PICO (Patient/Problem, Intervention, Comparison and Outcome). This article describes the use of deep learning techniques for Q&A that are based on transformer models like BERT and GPT to answer PICO clinical questions that can be used for evidence-based practice extracted from sound medical research resources like PubMed. We are reporting acceptable clinical answers that are supported by findings from PubMed. Our transformer methods are reaching an acceptable state-of-the-art performance based on two staged bootstrapping processes involving filtering relevant articles followed by identifying articles that support the requested outcome expressed by the PICO question. Moreover, we are also reporting experimentations to empower our bootstrapping techniques with patch attention to the most important keywords in the clinical case and the PICO questions. Our bootstrapped patched with attention is showing relevancy of the evidence collected based on entropy metrics.

Keywords: automatic question answering, PICO questions, evidence-based medicine, generative models, LLM transformers

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Authors: Malla Vijayeta, Y. Vijaya Kumar, N. Ramakrishna Raju, K. Satyanarayana

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Global AEC (architecture, engineering, and construction) industry has been coined as one of the most resistive domains in embracing technology. Although this digital era has been inundated with software tools like CAD, STADD, CANDY, Microsoft Project, Primavera etc. the key stakeholders have been working in siloes and processes remain fragmented. Unlike the yesteryears’ simpler project delivery methods, the current projects are of fast-track, complex, risky, multidisciplinary, stakeholder’s influential, statutorily regulative etc. pose extensive bottlenecks in preventing timely completion of projects. At this juncture, a paradigm shift surfaced in construction industry, and Building Information Modeling, aka BIM, has been a panacea to bolster the multidisciplinary teams’ cooperative and collaborative work leading to productive, sustainable and leaner project outcome. Building information modeling has been integrative, stakeholder engaging and centralized approach in providing a common platform of communication. A common misconception that BIM can be used for building/high rise projects in Indian Construction Industry, while this paper discusses of the implementation of BIM processes/methodologies in water and waste water industry. It elucidates about BIM 4D planning and constructability reviews of a Sewage Treatment Plant in India. Conventional construction planning and logistics management involves a blend of experience coupled with imagination. Even though the excerpts or judgments or lessons learnt gained from veterans might be predictive and helpful, but the uncertainty factor persists. This paper shall delve about the case study of real time implementation of BIM 4D planning protocols for one of the Sewage Treatment Plant of Dravyavati River Rejuvenation Project in India and develops a Time Liner to identify logistics planning and clash detection. With this BIM processes, we shall find that there will be significant reduction of duplication of tasks and reworks. Also another benefit achieved will be better visualization and workarounds during conception stage and enables for early involvement of the stakeholders in the Project Life cycle of Sewage Treatment Plant construction. Moreover, we have also taken an opinion poll of the benefits accrued utilizing BIM processes versus traditional paper based communication like 2D and 3D CAD tools. Thus this paper concludes with BIM framework for Sewage Treatment Plant construction which will achieve optimal construction co-ordination advantages like 4D construction sequencing, interference checking, clash detection checking and resolutions by primary engagement of all key stakeholders thereby identifying potential risks and subsequent creation of risk response strategies. However, certain hiccups like hesitancy in adoption of BIM technology by naïve users and availability of proficient BIM trainers in India poses a phenomenal impediment. Hence the nurture of BIM processes from conception, construction and till commissioning, operation and maintenance along with deconstruction of a project’s life cycle is highly essential for Indian Construction Industry in this digital era.

Keywords: integrated BIM workflow, 4D planning with BIM, building information modeling, clash detection and visualization, constructability reviews, project life cycle

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Authors: Lin Dong, Fei Shi

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Based on the railway network and the principles of space syntax, the study attempts to reconstruct the spatial relationship of the passenger network connections from space and time perspective. According to the travel time data of main stations in the Yangtze River Delta urban agglomeration obtained by the Internet, the topological drawing of railway network under different time sections is constructed. With the comprehensive index composed of connection and integration, the accessibility and network operation efficiency of the railway network in different time periods is calculated, while the fairness of the network is analyzed by the fairness indicators constructed with the integration and location entropy from the perspective of horizontal and vertical fairness respectively. From the analysis of the efficiency and fairness of the railway passenger transport network, the study finds: (1) There is a strong regularity in regional system accessibility change; (2) The problems of efficiency and fairness are different in different time periods; (3) The improvement of efficiency will lead to the decline of horizontal fairness to a certain extent, while from the perspective of vertical fairness, the supply-demand situation has changed smoothly with time; (4) The network connection efficiency of Shanghai, Jiangsu and Zhejiang regions is higher than that of the western regions such as Anqing and Chizhou; (5) The marginalization of Nantong, Yancheng, Yangzhou, Taizhou is obvious. The study explores the application of spatial syntactic theory in regional traffic analysis, in order to provide a reference for the development of urban agglomeration transportation network.

Keywords: spatial syntax, the Yangtze River Delta, railway passenger time, efficiency and fairness

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Authors: Ali Masria , Abdelazim Negm, Moheb Iskander, Oliver C. Saavedra

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Estuaries play an important role in exchanging water and providing a navigational pathway for ships. These zones are very sensitive and vulnerable to any interventions in coastal dynamics. Almost major of these inlets experience coastal problems such as severe erosion, and accretion. Rosetta promontory, Egypt is an example of this environment. It suffers from many coastal problems as erosion problem along the coastline and siltation problem inside the inlet. It is due to lack of water and sediment resources as a side effect of constructing the Aswan High dam. The shoaling of the inlet leads to hindering the navigation process of fishing boats, negative impacts to estuarine and salt marsh habitat and decrease the efficiency of the cross section to transfer the flow during emergencies to the sea. This paper aims to reach a new condition of stability of Rosetta Promontory by using coastal measures to control the sediment entering, and causes shoaling inside the inlet. These coastal measures include modifying the inlet cross section by using centered jetties, eliminate the coastal dynamic in the entrance using boundary jetties. This target is achieved by using a hydrodynamic model Coastal Modeling System (CMS). Extensive field data collection (hydrographic surveys, wave data, tide data, and bed morphology) is used to build and calibrate the model. About 20 scenarios were tested to reach a suitable solution that mitigate the coastal problems at the inlet. The results show that 360 m jetty in the eastern bank with system of sand bypass from the leeside of the jetty can stabilize the estuary.

Keywords: Rosetta promontory, erosion, sedimentation, inlet stability

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Authors: Bouanati Sidi Mohammed, N. E. Chabane Sari, Mostefa Kara Selma

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It is well-known that Organic light emitting diodes (OLEDs) are attracting great interest in the display technology industry due to their many advantages, such as low price of manufacturing, large-area of electroluminescent display, various colors of emission included white light. Recently, there has been much progress in understanding the device physics of OLEDs and their basic operating principles. In OLEDs, Light emitting is the result of the recombination of electron and hole in light emitting layer, which are injected from cathode and anode. For improve luminescence efficiency, it is needed that hole and electron pairs exist affluently and equally and recombine swiftly in the emitting layer. The aim of this paper is to modeling polymer LED and OLED made with small molecules for studying the electrical and optical characteristics. The first simulation structures used in this paper is a mono layer device; typically consisting of the poly (2-methoxy-5(2’-ethyl) hexoxy-phenylenevinylene) (MEH-PPV) polymer sandwiched between an anode usually an indium tin oxide (ITO) substrate, and a cathode, such as Al. In the second structure we replace MEH-PPV by tris (8-hydroxyquinolinato) aluminum (Alq3). We choose MEH-PPV because of it's solubility in common organic solvents, in conjunction with a low operating voltage for light emission and relatively high conversion efficiency and Alq3 because it is one of the most important host materials used in OLEDs. In this simulation, the Poole-Frenkel- like mobility model and the Langevin bimolecular recombination model have been used as the transport and recombination mechanism. These models are enabled in ATLAS -SILVACO software. The influence of doping and thickness on I(V) characteristics and luminescence, are reported.

Keywords: organic light emitting diode, polymer lignt emitting diode, organic materials, hexoxy-phenylenevinylene

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Authors: Isaac K. E. Ampomah, Seong-Bae Park, Sang-Jo Lee

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Over the past decade, there have been promising developments in Natural Language Processing (NLP) with several investigations of approaches focusing on Recognizing Textual Entailment (RTE). These models include models based on lexical similarities, models based on formal reasoning, and most recently deep neural models. In this paper, we present a sentence encoding model that exploits the sentence-to-sentence relation information for RTE. In terms of sentence modeling, Convolutional neural network (CNN) and recurrent neural networks (RNNs) adopt different approaches. RNNs are known to be well suited for sequence modeling, whilst CNN is suited for the extraction of n-gram features through the filters and can learn ranges of relations via the pooling mechanism. We combine the strength of RNN and CNN as stated above to present a unified model for the RTE task. Our model basically combines relation vectors computed from the phrasal representation of each sentence and final encoded sentence representations. Firstly, we pass each sentence through a convolutional layer to extract a sequence of higher-level phrase representation for each sentence from which the first relation vector is computed. Secondly, the phrasal representation of each sentence from the convolutional layer is fed into a Bidirectional Long Short Term Memory (Bi-LSTM) to obtain the final sentence representations from which a second relation vector is computed. The relations vectors are combined and then used in then used in the same fashion as attention mechanism over the Bi-LSTM outputs to yield the final sentence representations for the classification. Experiment on the Stanford Natural Language Inference (SNLI) corpus suggests that this is a promising technique for RTE.

Keywords: deep neural models, natural language inference, recognizing textual entailment (RTE), sentence-to-sentence relation

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Authors: Mamidi Ramakrishna Rao

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Doubly-fed induction generator (DFIG) is currently the choice for many wind turbines. These generators, when connected to the grid through a converter, is subjected to varied power system conditions like voltage variation, frequency variation, short circuit fault conditions, etc. Further, many countries like Canada, Germany, UK, Scotland, etc. have distinct grid codes relating to wind turbines. Accordingly, following the network faults, wind turbines have to supply a definite reactive current. To satisfy the requirements including reactive current capability, an optimum electrical design becomes a mandate for DFIG to function. This paper intends to optimize the equivalent circuit parameters of an electrical design for satisfactory DFIG performance. Direct search method has been used for optimization of the parameters. The variables selected include electromagnetic core dimensions (diameters and stack length), slot dimensions, radial air gap between stator and rotor and winding copper cross section area. Optimization for 2 MW DFIG has been executed separately for three objective functions - maximum reactive power capability (Case I), maximum efficiency (Case II) and minimum weight (Case III). In the optimization analysis program, voltage variations (10%), power factor- leading and lagging (0.95), speeds for corresponding to slips (-0.3 to +0.3) have been considered. The optimum designs obtained for objective functions were compared. It can be concluded that direct search method of optimization helps in determining an optimum electrical design for each objective function like efficiency or reactive power capability or weight minimization.

Keywords: direct search, DFIG, equivalent circuit parameters, optimization

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Authors: Wen-Chung Wang, Xue-Lan Qiu

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Ipsative tests have been widely used in vocational and career counseling (e.g., the Jackson Vocational Interest Survey). Pairwise-comparison items are a typical item format of ipsative tests. When the two statements in a pairwise-comparison item measure two different constructs, the item is referred to as a multidimensional pairwise-comparison (MPC) item. A typical MPC item would be: Which activity do you prefer? (A) playing with young children, or (B) working with tools and machines. These two statements aim at the constructs of social interest and investigative interest, respectively. Recently, new item response theory (IRT) models for ipsative tests with MPC items have been developed. Among them, the Rasch ipsative model (RIM) deserves special attention because it has good measurement properties, in which the log-odds of preferring statement A to statement B are defined as a competition between two parts: the sum of a person’s latent trait to which statement A is measuring and statement A’s utility, and the sum of a person’s latent trait to which statement B is measuring and statement B’s utility. The RIM has been extended to polytomous responses, such as preferring statement A strongly, preferring statement A, preferring statement B, and preferring statement B strongly. To promote the new initiatives, in this study we developed computerized adaptive testing algorithms for MFC items and evaluated their performance using simulations and two real tests. Both the RIM and its polytomous extension are multidimensional, which calls for multidimensional computerized adaptive testing (MCAT). A particular issue in MCAT for MPC items is the within-person statement exposure (WPSE); that is, a respondent may keep seeing the same statement (e.g., my life is empty) for many times, which is certainly annoying. In this study, we implemented two methods to control the WPSE rate. In the first control method, items would be frozen when their statements had been administered more than a prespecified times. In the second control method, a random component was added to control the contribution of the information at different stages of MCAT. The second control method was found to outperform the first control method in our simulation studies. In addition, we investigated four item selection methods: (a) random selection (as a baseline), (b) maximum Fisher information method without WPSE control, (c) maximum Fisher information method with the first control method, and (d) maximum Fisher information method with the second control method. These four methods were applied to two real tests: one was a work survey with dichotomous MPC items and the other is a career interests survey with polytomous MPC items. There were three dependent variables: the bias and root mean square error across person measures, and measurement efficiency which was defined as the number of items needed to achieve the same degree of test reliability. Both applications indicated that the proposed MCAT algorithms were successful and there was no loss in measurement proficiency when the control methods were implemented, and among the four methods, the last method performed the best.

Keywords: computerized adaptive testing, ipsative tests, item response theory, pairwise comparison

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Authors: Shayla He

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Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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Authors: Gunjan Srivastava, Shamila Kalia

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Dalbergia sissoo Roxb., (Family- Leguminosae; Subfamily- Papilionoideae), is an economically and ecologically important tree species having medicinal value. Of the rich complex of insect fauna, ten have been recognized as potential pests of nurseries and plantations. Present study was conducted to explore an effective ecofriendly control of Dichomeris eridantis Meyrick, an important defoliator pest of D. sissoo. Health and environmental concerns demanded devising a bio-intensive pest management strategy and employing ecofriendly measures. In the present laboratory bioassay two entomopathogenic fungi Acremonium perscinum and Beauveria bassiana were tested and compared for evaluating the efficacy of their seven different concentrations (besides control) against the 3rd, 4th and 5th instar larvae of D. eridantis, on the basis of mean percent mortality data recorded and tabulated for seven days after treatment application. Analysis showed that both treatments vary significantly among themselves. Also, variations amongst instars and duration with respect to their mortality were highly significant (p < .001). All their interactions were found to vary significantly. B. bassiana at 0.25x107 spores / ml spore concentration caused maximum mean percent mortality (62.38%) followed by mean percent mortality at its 0.25x106 spores / ml concentration (56.67%). Mean percent mortality at maximum spore concentration (0.054x107 spores / ml) and next highest spore concentration (0.054 x106 spores / ml) due to A. perscinum treatment were far less effective (mean percent mortality of 45.40% and 31.29%, respectively). At 168 hours mean percent mortality of larval instars due to both fungal treatment applications reached its maximum (52.99%) whereas, at 24 hours mean percent mortality remained least (5.70%). In both cases, treatments were most effective against 3rd instar larvae and least effective against 5th instar larvae. A comparative acccount of efficacy of B. bassiana and A. perscinum on the 3rd, 4th and 5th instar larvae of D. eridantis on 5th, 6th and 7th post treatment observation days after their application, on the basis of their median lethal concentrations (LC50) proved B. bassiana to be more potential microbial pathogen of the two fungal microbes, for all the three instars (3rd, 4th and 5th) of D. eridantis, on all the three days (5th, 6th and 7th post observation days after application of both treatments). Percent mortality of D. eridantis increased in a dose dependent manner. Koch’s Postulates tested positive, thus confirming the pathogenicity of B. bassiana against the larval instars of D. eridantis. LC90 values of 0.280x1011 spores/ml, 0.301x108 spores/ml and 0.262x108 spores/ml concentrations of B. bassiana were standardized which can effectively cause mortality of all the larval instars of D. eridantis in the field after 5th, 6th and 7th day of their application, respectively. Therefore, these concentrations can be safely used in nurseries as well as plantations of D. sissoo for effective control of D. eridantis larvae.

Keywords: Acremonium perscinum, Beauveria bassiana, Dalbergia sissoo, Dichomeris eridantis

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Authors: M. A. Hernández-Ceballos, E. G. San Miguel, C. Galán, J. P. Bolívar

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The evolution of 7Be and 210Pb activity concentrations in surface air along the Guadalquivir valley (southern Iberian Peninsula) is presented in this study. Samples collected for 48 h, every fifteen days, from September 2012 to November 2013 at two sampling sites (Huelva city in the mouth and Cordoba city in the middle (located 250 km far away)), are used to 1) analysing the spatial variability and 2) understanding the influence of wind conditions on 7Be and 210Pb. Similar average concentrations were registered along the valley. The mean 7Be activity concentration was 4.46 ± 0.21 mBq/m3 at Huelva and 4.33 ± 0.20 mBq/m3 at Cordoba, although registering higher maximum and minimum values at Cordoba (9.44 mBq/m3 and 1.80 mBq/m3) than at Huelva (7.95 mBq/m3 and 1.04 mBq/m3). No significant differences were observed in the 210Pb mean activity concentrations between Cordoba (0.40 ± 0.04 mBq/m3) and Huelva (0.35 ± 0.04 mBq/m3), although the maximum (1.10 mBq/m3 and 0.87 mBq/m3) and minimum (0.02 mBq/m3 and 0.04 mBq/m3) values were recorded in Cordoba. Although similar average concentrations were obtained in both sites, the temporal evolution of both natural radionuclides presents differences between them. The meteorological analysis of two sampling periods, in which large differences on 7Be and 210Pb concentrations are observed, indicates the different impact of surface and upper wind dynamics. The analysis reveals the different impact of the two sea-land breeze patterns usually observed along the valley (pure and non-pure) and the corresponding air masses at higher layers associated with each one. The pure, with short development (around 30 km inland) and increasing accumulation process, favours high concentrations of both radionuclides in Huelva (coastal site), while the non-pure, with winds sweeping the valley until arrive to Cordoba (250 km far away), causes high activity values at this site. These results reveal the impact of mesoscale conditions on these two natural radionuclides, and the importance of these circulations on its spatial and temporal variability.

Keywords: 7Be, 210Pb, air masses, mesoscale process

Procedia PDF Downloads 396

Authors: Shu-Hui Jan, Hui-Ping Tserng, Shih-Ping Ho

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Construction project control attempts to obtain real-time as-built schedule information and to eliminate project delays by effectively enhancing dynamic schedule control and management. Suitable platforms for enhancing an as-built schedule visually during the construction phase are necessary and important for general contractors. As the application of building information modeling (BIM) becomes more common, schedule management integrated with the BIM approach becomes essential to enhance visual construction management implementation for the general contractor during the construction phase. To enhance visualization of the updated as-built schedule for the general contractor, this study presents a novel system called the Construction BIM-assisted Schedule Management (ConBIM-SM) system for general contractors in Taiwan. The primary purpose of this study is to develop a web ConBIM-SM system for the general contractor to enhance visual as-built schedule information sharing and efficiency in tracking construction as-built schedule. Finally, the ConBIM-SM system is applied to a case study of a commerce building project in Taiwan to verify its efficacy and demonstrate its effectiveness during the construction phase. The advantages of the ConBIM-SM system lie in improved project control and management efficiency for general contractors, and in providing BIM-assisted as-built schedule tracking and management, to access the most current as-built schedule information through a web browser. The case study results show that the ConBIM-SM system is an effective visual as-built schedule management platform integrated with the BIM approach for general contractors in a construction project.

Keywords: building information modeling (BIM), construction schedule management, as-built schedule management, BIM schedule updating mechanism

Procedia PDF Downloads 357

Authors: Gajanan M. Sonwane

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Nowadays, the entire pharmaceutical industry is facing the challenge of increasing efficiency and innovation. The major hurdles are the growing cost of research and development and a concurrent stagnating number of new chemical entities (NCEs). Hence, the challenge is to select the most druggable targets and to search the equivalent drug-like compounds, which also possess specific pharmacokinetic and toxicological properties that allow them to be developed as drugs. The present research work includes the studies of developing new anticancer heterocycles by using molecular modeling techniques. The heterocycles synthesized through such methodology are much effective as various physicochemical parameters have been already studied and the structure has been optimized for its best fit in the receptor. Hence, on the basis of the literature survey and considering the need to develop newer anticancer agents, new phenazinamine derivatives were designed by subjecting the nucleus to molecular modeling, viz., GQSAR analysis and docking studies. Simultaneously, these designed derivatives were subjected to in silico prediction of biological activity through PASS studies and then in silico toxicity risk assessment studies. In PASS studies, it was found that all the derivatives exhibited a good spectrum of biological activities confirming its anticancer potential. The toxicity risk assessment studies revealed that all the derivatives obey Lipinski’s rule. Amongst these series, compounds 4c, 5b and 6c were found to possess logP and drug-likeness values comparable with the standard Imatinib (used for anticancer activity studies) and also with the standard drug methotrexate (used for antimitotic activity studies). One of the most notable mutations is the threonine to isoleucine mutation at codon 315 (T315I), which is known to be resistant to all currently available TKI. Enzyme assay planned for confirmation of target selective activity.

Keywords: drug design, tyrosine kinases, anticancer, Phenazinamine

Procedia PDF Downloads 97

Authors: Anuj Pathare, Aleksandra Birn-Jeffery

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Background: The Anterior Cruciate Ligament(ACL) helps stabilize the knee joint minimizing tibial anterior translation. Anterior Cruciate Ligament (ACL) injury is common in racquet sports and often occurs due to sudden acceleration, deceleration or changes of direction. This mechanism in badminton most commonly occurs during landing after an overhead stroke. Knee biomechanics during dynamic movements such as walking, running and stair negotiation, do not return to normal for more than a year after an ACL reconstruction. This change in the biomechanics may lead to re-injury whilst performing non-steady movements during sports, where these injuries are most prevalent. Aims: To compare if the knee kinetics and kinematics in ACL injury recovered athletes return to the same level as those from an uninjured cohort during standard movements used for clinical assessment and badminton shots. Objectives: The objectives of the study were to determine: Knee valgus during the single leg squat, vertical drop jump, net shot and drop shot; Degree of internal or external rotation during the single leg squat, vertical drop jump, net shot and drop shot; Maximum knee flexion during the single leg squat, vertical drop jump and net shot. Methods: This case-control study included 14 participants with three ACL injury recovered athletes and 11 uninjured participants. The participants performed various functional tasks including vertical drop jump, single leg squat; the forehand net shot and the forehand drop shot. The data was analysed using the two-way ANOVA test, and the reliability of the data was evaluated using the Intra Class Coefficient. Results: The data showed a significant decrease in the range of knee rotation in ACL injured participants as compared to the uninjured cohort (F₇,₅₅₆=2.37; p=0.021). There was also a decrease in the maximum knee flexion angles and an increase in knee valgus angles in ACL injured participants although they were not statistically significant. Conclusion: There was a significant decrease in the knee rotation angles in the ACL injured participants which could be a potential cause for re-injury in these athletes in the future. Although the results for decrease in maximum knee flexion angles and increase in knee valgus angles were not significant, this may be due to a limited sample of ACL injured participants; there is potential for it to be identified as a variable of interest in the rehabilitation of ACL injuries. These changes in the knee biomechanics could be vital in the rehabilitation of ACL injured athletes in the future, and an inclusion of sports based tasks, e.g., Net shot along with standard protocol movements for ACL assessment would provide a better measure of the rehabilitation of the athlete.

Keywords: ACL, biomechanics, knee injury, racquet sport

Procedia PDF Downloads 160

Authors: Pius Marthin, Nihal Ata Tutkun

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Survival analysis has become one of the paramount procedures in the modeling of time-to-event data. When we encounter complex survival problems, the traditional approach remains limited in accounting for the complex correlational structure between the covariates and the outcome due to the strong assumptions that limit the inference and prediction ability of the resulting models. Several studies exist on the deep learning approach to survival modeling; moreover, the application for the case of complex survival problems still needs to be improved. In addition, the existing models need to address the data structure's complexity fully and are subject to noise and redundant information. In this study, we design a deep learning technique (CmpXRnnSurv_AE) that obliterates the limitations imposed by traditional approaches and addresses the above issues to jointly predict the risk-specific probabilities and survival function for recurrent events with competing risks. We introduce the component termed Risks Information Weights (RIW) as an attention mechanism to compute the weighted cumulative incidence function (WCIF) and an external auto-encoder (ExternalAE) as a feature selector to extract complex characteristics among the set of covariates responsible for the cause-specific events. We train our model using synthetic and real data sets and employ the appropriate metrics for complex survival models for evaluation. As benchmarks, we selected both traditional and machine learning models and our model demonstrates better performance across all datasets.

Keywords: cumulative incidence function (CIF), risk information weight (RIW), autoencoders (AE), survival analysis, recurrent events with competing risks, recurrent neural networks (RNN), long short-term memory (LSTM), self-attention, multilayers perceptrons (MLPs)

Procedia PDF Downloads 72

Authors: Şeyma Saliha Fidan, Ozgur Serin, Ata Mugan

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While performing verification analyses under static and dynamic loads that composite structures used in aviation are exposed to, it is necessary to obtain the bearing strength limit value for mechanically connected composite structures. For this purpose, various tests are carried out in accordance with aviation standards. There are many companies in the world that perform these tests in accordance with aviation standards, but the test costs are very high. In addition, due to the necessity of producing coupons, the high cost of coupon materials, and the long test times, it is necessary to simulate these tests on the computer. For this purpose, various test coupons were produced by using reinforcement and alignment angles of the composite radomes, which were integrated into the aircraft. Glass fiber reinforced and Quartz prepreg is used in the production of the coupons. The simulations of the tests performed according to the American Society for Testing and Materials (ASTM) D5961 Procedure C standard were performed on the computer. The analysis model was created in three dimensions for the purpose of modeling the bolt-hole contact surface realistically and obtaining the exact bearing strength value. The finite element model was carried out with the Analysis System (ANSYS). Since a physical break cannot be made in the analysis studies carried out in the virtual environment, a hypothetical break is realized by reducing the material properties. The material properties reduction coefficient was determined as 10%, which is stated to give the most realistic approach in the literature. There are various theories in this method, which is called progressive failure analysis. Because the hashin theory does not match our experimental results, the puck progressive damage method was used in all coupon analyses. When the experimental and numerical results are compared, the initial damage and the resulting force drop points, the maximum damage load values ​​, and the bearing strength value are very close. Furthermore, low error rates and similar damage patterns were obtained in both test and simulation models. In addition, the effects of various parameters such as pre-stress, use of bushing, the ratio of the distance between the bolt hole center and the plate edge to the hole diameter (E/D), the ratio of plate width to hole diameter (W/D), hot-wet environment conditions were investigated on the bearing strength of the composite structure.

Keywords: puck, finite element, bolted joint, composite

Procedia PDF Downloads 82

Authors: Joel Podgorski, Manouchehr Amini, Annette Johnson, Michael Berg

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One-third of the world’s population relies on groundwater for its drinking water. Natural geogenic arsenic and fluoride contaminate ~10% of wells. Prolonged exposure to high levels of arsenic can result in various internal cancers, while high levels of fluoride are responsible for the development of dental and crippling skeletal fluorosis. In poor urban and rural settings, the provision of drinking water free of geogenic contamination can be a major challenge. In order to efficiently apply limited resources in the testing of wells, water resource managers need to know where geogenically contaminated groundwater is likely to occur. The Groundwater Assessment Platform (GAP) fulfills this need by providing state-of-the-art global arsenic and fluoride contamination hazard maps as well as enabling users to create their own groundwater quality models. The global risk models were produced by logistic regression of arsenic and fluoride measurements using predictor variables of various soil, geological and climate parameters. The maps display the probability of encountering concentrations of arsenic or fluoride exceeding the World Health Organization’s (WHO) stipulated concentration limits of 10 µg/L or 1.5 mg/L, respectively. In addition to a reconsideration of the relevant geochemical settings, these second-generation maps represent a great improvement over the previous risk maps due to a significant increase in data quantity and resolution. For example, there is a 10-fold increase in the number of measured data points, and the resolution of predictor variables is generally 60 times greater. These same predictor variable datasets are available on the GAP platform for visualization as well as for use with a modeling tool. The latter requires that users upload their own concentration measurements and select the predictor variables that they wish to incorporate in their models. In addition, users can upload additional predictor variable datasets either as features or coverages. Such models can represent an improvement over the global models already supplied, since (a) users may be able to use their own, more detailed datasets of measured concentrations and (b) the various processes leading to arsenic and fluoride groundwater contamination can be isolated more effectively on a smaller scale, thereby resulting in a more accurate model. All maps, including user-created risk models, can be downloaded as PDFs. There is also the option to share data in a secure environment as well as the possibility to collaborate in a secure environment through the creation of communities. In summary, GAP provides users with the means to reliably and efficiently produce models specific to their region of interest by making available the latest datasets of predictor variables along with the necessary modeling infrastructure.

Keywords: arsenic, fluoride, groundwater contamination, logistic regression

Procedia PDF Downloads 328

Authors: Umer Ayyaz Aslam Sheikh

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Non Apis bee like the bumblebees are important due to their utilization of diverse floral plants and belong to the richest and most conspicuous flower visitors in alpine, temperate and arctic environments for pollination in both natural and managed cropping systems. These bees generally construct underground nests and habitat devastation and crumbling are major causes for their decline in nature. The present study was conducted in the Himalayan range of Azad Jammu, and Kashmir, Pakistan, surveys were conducted during the early spring season to observe maximum Bombus haemorrhoidalis queens (emerged after winter diapauses) searching for a nesting place. Whole study area was grouped into four types of landscape (open field, relatively open , relatively wooded and wooded), five habitat types (field, field boundary, pasture forest boundary and forest) and these habitat further grouped into four different patch types including withered grass, new grass, tussocks and stones and moss. Maximum nest seeking bumblebee queens preferred relatively open field landscape followed by open fields and forest boundaries. Field boundaries were recorded as most proffered habitat along with withered grasses for nesting sites of B. haemorrhoidalis queens. A wooded landscape with stone and moss type of patches were found least preferred nesting sites. This study will be helpful in the future for conservation program this for declining bumblebee species in this region. It will also provide the baseline for the conservation of other bumblebee species of the world.

Keywords: bumblebee, Bombus haemorrhoidalis, habitat, nest seeking preference, Pakistan

Procedia PDF Downloads 120

Authors: Joohyun Park, Jin Baek

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The purpose of this study is to Analyze the role and effect arise from Diagonal Plane Control by Street Width (DPCSW) in Architecture in Seoul, and to predict the aspect of transition about the relationship among buildings and Urban morphology After the abolition. To find the tendency of building shape regulation, This study review Building Acts concerned with form making (the building to land Ratio, building designated line, wall designated line, building height limit (DPCSW) and etc.) and simulate the shape of urban blocks made by Acts in drawings. The review results show DPCSW is not only limitation about height, but also making the building setback from road and make the Road broader. And it makes the typical shape of the urban block that buildings are moving away from surrounding road After the Abolition of DPCSW; it is expected by the legislature that domestic real estate’s market would be promoted by increased total floor areas in each building. Some substitution from the legislature is announced, but it just deals with Building Maximum unit by Block unit except the regulation about arrangement in urban Figure and Ground. In conclusion, refrain from the uncontrolled development of city, It is important to make regulation about not only height factors but limitation line in land. Furthermore, through revising District Unit Plan, It is positively necessary to reset the relationship between buildings for the making the city space better.

Keywords: diagonal plane control by street width, building maximum height, district unit plan, building acts, urban block type, morphology, building shape

Procedia PDF Downloads 295

Authors: Ghulam Hussain, Herrington Lee, Comfort Paul, Jones Richard

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Background: To determine the functional limitations of the lower limbs or readiness to return to sport, most rehabilitation programs use some form of testing; however, it is still unknown what the pass criteria is. This study aims to investigate the differences between the dominant and non-dominant leg performances across several lower limb tasks, which are hop tests, two-dimensional (2D) frontal plane projection angle (FPPA) tests, and isokinetic muscle tests. This study also provides the reference values for the limb symmetry index (LSI) for the hop and isokinetic muscle strength tests. Twenty recreationally active participants were recruited, 11 males and 9 females (age 23.65±2.79 years; height 169.9±3.74 cm; and body mass 74.72±5.81 kg. All tests were undertaken on the dominant and non-dominant legs. These tests are (1) Hop tests, which include horizontal hop for distance and crossover hop tests, (2) Frontal plane projection angle (FPPA): 2D capturing from two different tasks, which are forward hop landing and squatting, and (3) Isokinetic muscle strength tests: four different muscles were tested: quadriceps, hamstring, ankle plantar flexor, and hip extensor muscles. The main outcome measurements were, for the (1) hop tests: maximum distance was taken when undertaking single/crossover hop for distance using a standard tape measure, (2) for the FPPA: the knee valgus angle was measured from the maximum knee flexion position using a single 2D camera, and (3) for the isokinetic muscle strength tests: three different variables were measured: peak torque, peak torque to body weight, and the total work to body weight. All the muscle strength tests have been applied in both concentric and eccentric muscle actions at a speed of 60°/sec. This study revealed no differences between the dominant and non-dominant leg performance, and 85% of LSI was achieved by the majority of the subjects in both hop and isokinetic muscle tests, and; therefore, one leg’s hop performance can define the other.

Keywords: 2D FPPA, hop tests, isokinetic testing, LSI

Procedia PDF Downloads 48

Authors: Pedro Mota Veiga

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This study comprehensively evaluates the repercussions of innovation, digital advancements, and technological capabilities on the operational performance of companies across fifteen European Union countries following the initial wave of the COVID-19 pandemic. Drawing insights from longitudinal data sourced from the 2019 World Bank business surveys and subsequent 2020 World Bank COVID-19 follow-up business surveys, our extensive examination involves a diverse sample of 5763 family businesses. In exploring the relationships between these variables, we adopt a nuanced approach to assess the impact of innovation and digital and technological capabilities on performance. This analysis unfolds along two distinct perspectives: one rooted in necessity and the other insufficiency. The methodological framework employed integrates partial least squares structural equation modeling (PLS-SEM) with condition analysis (NCA), providing a robust foundation for drawing meaningful conclusions. The findings of the study underscore a positive influence on the performance of family firms stemming from both technological capabilities and digital advancements. Furthermore, it is pertinent to highlight the indirect contribution of innovation to enhanced performance, operating through its impact on digital capabilities. This research contributes valuable insights to the broader understanding of how innovation, coupled with digital and technological capabilities, can serve as pivotal factors in shaping the post-COVID-19 landscape for businesses across the European Union. The intricate analysis of family businesses, in particular adds depth to the comprehension of the dynamics at play in diverse economic contexts within the European Union.

Keywords: digital capabilities, technological capabilities, family firms performance, innovation, NCA, PLS-SEM

Procedia PDF Downloads 53

Authors: M. T. Islam, S. H. Shakif, R. Hasan, S. H. Kobi

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Investigation of rainfall trends is crucial considering climate change, food security, and the economy of a particular region. This research aims to study seasonal and annual precipitation trends and their abrupt changes over time in the south-central climatic zone of Bangladesh using monthly time series data of 50 years (1970-2019). A trend-free pre-whitening method has been employed to make necessary adjustments for autocorrelations in the rainfall data. Trends in rainfall and their intensity have been observed using the non-parametric Mann-Kendall test and Theil-Sen estimator. Significant changes and fluctuation points in the data series have been detected using the sequential Mann-Kendall test at the 95% confidence limit. The study findings show that most of the rainfall stations in the study area have a decreasing precipitation pattern throughout all seasons. The maximum decline in the rainfall intensity has been found for the Tangail station (-8.24 mm/year) during monsoon. Madaripur and Chandpur stations have shown slight positive trends in post-monsoon rainfall. In terms of annual precipitation, a negative rainfall pattern has been identified in each station, with a maximum decrement (-) of 14.48 mm/year at Chandpur. However, all the trends are statistically non-significant within the 95% confidence interval, and their monotonic association with time ranges from very weak to weak. From the sequential Mann-Kendall test, the year of changing points for annual and seasonal downward precipitation trends occur mostly after the 90s for Dhaka and Barishal stations. For Chandpur, the fluctuation points arrive after the mid-70s in most cases.

Keywords: trend analysis, Mann-Kendall test, Theil-Sen estimator, sequential Mann-Kendall test, rainfall trend

Procedia PDF Downloads 65