Search results for: sustainability performance assessment

Authors: Dawei Cai, Yuya Tokuda

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

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

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Authors: Yosra Ben Mhamed

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Most previous research that investigates the importance of earnings volatility for a firm’s value has focused on the effects of earnings volatility on the cost of capital. Many study illustrate that earnings volatility can reduce the firm’s value by enhancing the cost of capital. However, a few recent studies directly examine the relation between earnings volatility and subsequent earnings levels. In our study, we further explore the role of volatility in forecasting. Our study makes two primary contributions to the literature. First, taking into account the level of current firm’s performance, we provide causal theory to the link between volatility and earnings predictability. Nevertheless, previous studies testing the linearity of this relationship have not mentioned any underlying theory. Secondly, our study contributes to the vast body of fundamental analysis research that identifies a set of variables that improve valuation, by showing that earnings volatility affects the estimation of future earnings. Projections of earnings are used by valuation research and practice to derive estimates of firm value. Since we want to examine the impact of volatility on earnings predictability, we sort the sample into three portfolios according to the level of their earnings volatility in ascending order. For each quintile, we present the predictability coefficient. In a second test, each of these portfolios is, then, sorted into three further quintiles based on their level of current earnings. These yield nine quintiles. So we can observe whether volatility strongly predicts decreases on earnings predictability only for highest quintile of earnings. In general, we find that earnings volatility has an inverse relationship with earnings predictability. Our results also show that the sensibility of earnings predictability to ex-ante volatility is more pronounced among profitability firms. The findings are most consistent with overinvestment and persistence explanations.

Keywords: earnings volatility, earnings predictability, earnings persistence, current profitability

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Authors: Amarachukwu B. Isiaka, Vivian N. Anakwenze, Chinyere C. Ezemba, Chiamaka R. Ilodinso, Chikodili G. Anaukwu, Chukwuebuka M. Ezeokoli, Ugonna H. Uzoka

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Infectious diseases continue to pose significant threats to global public health, necessitating advanced and timely detection methods for effective outbreak management. This study explores the integration of artificial intelligence (AI) in the early detection and management of infectious disease outbreaks. Leveraging vast datasets from diverse sources, including electronic health records, social media, and environmental monitoring, AI-driven algorithms are employed to analyze patterns and anomalies indicative of potential outbreaks. Machine learning models, trained on historical data and continuously updated with real-time information, contribute to the identification of emerging threats. The implementation of AI extends beyond detection, encompassing predictive analytics for disease spread and severity assessment. Furthermore, the paper discusses the role of AI in predictive modeling, enabling public health officials to anticipate the spread of infectious diseases and allocate resources proactively. Machine learning algorithms can analyze historical data, climatic conditions, and human mobility patterns to predict potential hotspots and optimize intervention strategies. The study evaluates the current landscape of AI applications in infectious disease surveillance and proposes a comprehensive framework for their integration into existing public health infrastructures. The implementation of an AI-driven early detection system requires collaboration between public health agencies, healthcare providers, and technology experts. Ethical considerations, privacy protection, and data security are paramount in developing a framework that balances the benefits of AI with the protection of individual rights. The synergistic collaboration between AI technologies and traditional epidemiological methods is emphasized, highlighting the potential to enhance a nation's ability to detect, respond to, and manage infectious disease outbreaks in a proactive and data-driven manner. The findings of this research underscore the transformative impact of harnessing AI for early detection and management, offering a promising avenue for strengthening the resilience of public health systems in the face of evolving infectious disease challenges. This paper advocates for the integration of artificial intelligence into the existing public health infrastructure for early detection and management of infectious disease outbreaks. The proposed AI-driven system has the potential to revolutionize the way we approach infectious disease surveillance, providing a more proactive and effective response to safeguard public health.

Keywords: artificial intelligence, early detection, disease surveillance, infectious diseases, outbreak management

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Authors: Izian Abd. Karim, Kachalla Mohammed, Nora Farah Abd Aznieta Aziz, Law Teik Hua

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The economic use and ease of construction of profiled deck composite slab is marred with the complex and un-economic strength verification required for the serviceability and general safety considerations. Beside these, albeit factors such as shear span length, deck geometries and mechanical frictions greatly influence the longitudinal shear strength, that determines the ultimate strength of profiled deck composite slab, and number of methods available for its determination; partial shear and slope-intercept are the two methods according to Euro-code 4 provision. However, the complexity associated with shear behavior of profiled deck composite slab, the use of these methods in determining the load carrying capacities of such slab yields different and conflicting values. This couple with the time and cost constraint associated with the strength verification is a source of concern that draws more attentions nowadays, the issue is critical. Treating some of these known shear strength influencing factors as random variables, the load carrying capacity violation of profiled deck composite slab from the use of the two-methods defined according to Euro-code 4 are determined using reliability approach, and comparatively studied. The study reveals safety values from the use of m-k method shows good standing compared with that from the partial shear method.

Keywords: composite slab, first order reliability method, longitudinal shear, partial shear connection, slope-intercept

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Authors: Salima Djehaichia, Rachid Lassoued

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Reinforced concrete structural walls are very efficient elements for protecting buildings against excessive early damage and against collapse under earthquake actions. It is therefore of interest to develop a numerical model which simulates the typical behavior of these units, this paper presents and describes different modeling techniques that have been used by researchers and their advantages and limitations mentioned. The earthquake of Boumerdes in 2003 has demonstrated the fragility of structures and total neglect of sismique design rules in the realization of old buildings. Significant damage and destruction of buildings caused by this earthquake are not due to the choice of type of material, but the design and the study does not congruent with seismic code requirements and bad quality of materials. For idealizing the failure of rules, a parametric study focuses on: low rate of reinforcements, type of reinforcement, resistance moderate of concrete. As an application the modeling strategy based on finite elements combined with a discretization of wall more solicited by successive thin layers. The estimated performance level achieved during a seismic action is obtained from capacity curves under incrementally increasing loads. Using a pushover analysis, a characteristic non linear force-displacement relationship can be determined. The results of numeric model are confronted with those of Algerian Para seismic Rules (RPA) in force have allowed the determination of profits in terms of displacement, shearing action, ductility.

Keywords: modeling, old building, pushover analysis, structural walls

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Authors: Lina Yang, Mao Wen, Jianhong Chen, Kan Zhang

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Molybdenum disulfide (MoS₂) represents a highly sought lubricant for reducing friction based on intrinsic layered structure, but for this reason, practical applications have been greatly restricted due to the fact that its low hardness would cause severe wear. Here, a novel TiMoN/MoSₓ composite coatings with TiMoN solid solution grains embedded into MoSₓ-based amorphous matrix has been successfully designed and synthesized, through magnetron co-sputtering technology. Desirably, in virtue of such special microstructure, superhardness and excellent toughness can be well achieved, along with an ultra-low wear rate at ~2×10⁻¹¹ mm³/Nm in the air environment, simultaneously, low friction at ~0.1 is maintained. It should be noted that this wear level is almost two orders of magnitude lower than that of pure TiN coating, and is, as we know, the lowest wear rate in dry sliding. Investigations of tribofilm reveal that it is amorphous MoS₂ in nature, and its formation arises directly from the MoSₓ amorphous matrix. Which contributes to effective lubrication behavior, coupled with excellent mechanical performances of such composite coating, exceptionally low wear can be guaranteed. The findings in this work suggest that the special composite structure makes it possible for the synthesis of super-hard and super-durable lubricative coating, offering guidance to synthesize ultrahigh performance protective coating for industrial application.

Keywords: hardness, MoS₂-containing composite coatings, toughness, tribological properties

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

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The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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Authors: Akash Verma, Sujit Kumar Samanta

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This study examines a discrete-time Geo/G/1 queueing-inventory system attached with (s, Q) inventory policy. Assume that the customers follow the Bernoulli process on arrival. Each customer demands a single item with arbitrarily distributed service time. The inventory is replenished by an outside supplier, and the lead time for the replenishment is determined by a geometric distribution. There is a single server and infinite waiting space in this facility. Demands must wait in the specified waiting area during a stock-out period. The customers are served on a first-come-first-served basis. With the help of the embedded Markov chain technique, we determine the joint probability distributions of the number of customers in the system and the number of items in stock at the post-departure epoch using the Matrix Analytic approach. We relate the system length distribution at post-departure and outside observer's epochs to determine the joint probability distribution at the outside observer's epoch. We use probability distributions at random epochs to determine the waiting time distribution. We obtain the performance measures to construct the cost function. The optimum values of the order quantity and reordering point are found numerically for the variety of model parameters.

Keywords: discrete-time queueing inventory model, matrix analytic method, waiting-time analysis, cost optimization

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Authors: Abdullah Mukhtar, Shehroz Mukhtar, Amina Mukhtar, Choudhry Shahid, Hafiz Raza Razzaq, Saif Ur Rahman

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The aim of this study is to find out the negative and positive impacts of social media platforms on the attitude of learning and educational environment of student’s community. Social Media platforms have become a source of collaboration with one another throughout the globe making it a small world. This study performs focalized investigation of the adverse and constructive factors that have a strong impact not only on the psychological adjustments but also on the academic performance of peers. This study is a quantitative research adopting random sampling method in which the participants were the students of university. Researcher distributed 1000 questionnaires among the university students from different departments and asked them to fill the data on Lickert Scale. The participants are from the age group of 18-24 years. Study applies user and gratification theory in order to examine behavior of students practicing social media in their academic and personal life. Findings of the study reveal that the use of social media platforms in Pakistani context has less positive impact as compared to negative impacts on the behavior of students towards learning. The research suggests that usage of online social media platforms should be taught to students; awareness must the created among the users of social media by the means of seminars, workshops and by media itself to overcome the negative impacts of social media leading towards sustainable education in Pakistan.

Keywords: social media, positive impact, negative impact, learning behaviour

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Authors: Abul Hassan

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Present socio-economic context and women wellbeing in Bangladesh imposes lots of constraints on women’s involvement in income generating activities. Different studies showed that the implementation of World Bank structural adjustment policies have had mixed impacts on women and their wellbeing. By involving poor people specially women in Islamic microfinance programmes in Bangladesh are used as a tool to combat poverty. Women are specifically targeted by Islamic microfinance under the rural development scheme of Islami Bank Bangladesh that provide interest free loan to the women groups. The programme has a multiplier effect since women invest largely in their households. The aim of this research is twofold: firstly, it wanted to confirm or refute a positive link between Islamic microfinance and the socio-economic wellbeing of women in Bangladesh and secondly, to explore the context in which Islamic microfinance programs function in Bangladesh and the way their performance can be improved. Based on structured questionnaires’ survey, this study addressed two research questions: (1) What can be expected from the offer of Islamic microfinance on the welfare of recipients and (2) Under what conditions would such an offer be more beneficial. The main result of this study shows that increase in women’s income and assets played a very important role in enhancing women’s economic independence and sense of self-confidence. An important policy recommendation is that it is necessary to redirect Islamic microfinance towards diversified developmental activities that will contribute to the improvement, in the long run, of the wellbeing of the recipients.

Keywords: business model, Islamic microfinance, women’s wellbeing

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Authors: Han Xiao

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The development of nanomedicines has recently achieved several breakthroughs in the field of cancer treatment; however, the biocompatibility and targeted burst release of these medications remain a limitation, which leads to serious side effects and significantly narrows the scope of their applications. The self-assembly of intermediate filament protein (IFP) peptides was triggered by a hydrophobic cation drug 7-amino actinomycin D (7-AAD) to synthesize pH-activatable nanoparticles (NPs) that could simultaneously locate tumors and produce antitumor effects. The designed IFP peptide included a target peptide (arginine–glycine–aspartate), a negatively charged region, and an α-helix sequence. It also possessed the ability to encapsulate 7-AAD molecules through the formation of hydrogen bonds and hydrophobic interactions by a one-step method. 7-AAD molecules with excellent near-infrared fluorescence properties could be target delivered into tumor cells by NPs and released immediately in the acidic environments of tumors and endosome/lysosomes, ultimately inducing cytotoxicity by arresting the tumor cell cycle with inserted DNA. It is noteworthy that the IFP/7-AAD NPs tail vein injection approach demonstrated not only high tumor-targeted imaging potential, but also strong antitumor therapeutic effects in vivo. The proposed strategy may be used in the delivery of cationic antitumor drugs for precise imaging and cancer therapy.

Keywords: 7-amino actinomycin D, intermediate filament protein, nanoparticle, tumor image

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Authors: Vijaya Kumar, Vidayasagar Pagilla, Abraham Joshua, Rakshith Kedambadi, Prasanna Mithra

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Background: Post stroke rehabilitation are aimed to accelerate for optimal sensorimotor recovery, functional gain and to reduce long-term dependency. Intensive physical therapy interventions can enhance this recovery as experience-dependent neural plastic changes either directly act at cortical neural networks or at distal peripheral level (muscular components). Neuromuscular Electrical Stimulation (NMES), a traditional bottom-up approach, mirror therapy (MT), a relatively new top down approach have found to be an effective adjuvant treatment methods for lower extremity motor and functional recovery in stroke rehabilitation. However there is a scarcity of evidence to compare their therapeutic gain in stroke recovery.Aim: To compare the efficacy of neuromuscular electrical stimulation (NMES) and mirror therapy (MT) in very early phase of post stroke rehabilitation addressed to lower extremity motor recovery and balance. Design: observer blinded Randomized Clinical Trial. Setting: Neurorehabilitation Unit, Department of Physical Therapy, Tertiary Care Hospitals. Subjects: 32 acute stroke subjects with first episode of unilateral stroke with hemiparesis, referred for rehabilitation (onset < 3 weeks), Brunnstorm lower extremity recovery stages ≥3 and MMSE score more than 24 were randomized into two group [Group A-NMES and Group B-MT]. Interventions: Both the groups received eclectic approach to remediate lower extremity recovery which includes treatment components of Roods, Bobath and Motor learning approaches for 30 minutes a day for 6 days. Following which Group A (N=16) received 30 minutes of surface NMES training for six major paretic muscle groups (gluteus maximus and medius,quadriceps, hamstrings, tibialis anterior and gastrocnemius). Group B (N=16) was administered with 30 minutes of mirror therapy sessions to facilitate lower extremity motor recovery. Outcome measures: Lower extremity motor recovery, balance and activities of daily life (ADLs) were measured by Fugyl Meyer Assessment (FMA-LE), Berg Balance Scale (BBS), Barthel Index (BI) before and after intervention. Results: Pre Post analysis of either group across the time revealed statistically significant improvement (p < 0.001) for all the outcome variables for the either group. All parameters of NMES had greater change scores compared to MT group as follows: FMA-LE (25.12±3.01 vs. 23.31±2.38), BBS (35.12±4.61 vs. 34.68±5.42) and BI (40.00±10.32 vs. 37.18±7.73). Between the groups comparison of pre post values showed no significance with FMA-LE (p=0.09), BBS (p=0.80) and BI (p=0.39) respectively. Conclusion: Though either groups had significant improvement (pre to post intervention), none of them were superior to other in lower extremity motor recovery and balance among acute stroke subjects. We conclude that eclectic approach is an effective treatment irrespective of NMES or MT as an adjunct.

Keywords: balance, motor recovery, mirror therapy, neuromuscular electrical stimulation, stroke

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Authors: Tareq Nikzad

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Since the first bank was established in 1933, Afghanistan's banking sector has seen a number of variations but hasn't been able to grow to its full potential because of the civil war. The implementation of dual banks in Afghanistan is investigated in this study in relation to the effects of inflation and interest rates. This research took data from World Bank Data (WBD) over a period of nineteen years. For the banking sector, inflation, which is the general rise in prices of goods and services over time, presents considerable difficulties. The objectives of this research are to analyze the effect of inflation and interest rates on conventional and Islamic banks in Afghanistan, identify potential differences between these two banking models, and provide insights for policymakers and practitioners. A mixed-methods approach is used in the research to analyze quantitative data and qualitatively examine the unique difficulties that banks in Afghanistan's economic atmosphere encounter. The findings contribute to the understanding of the relationship between interest rate, inflation rate, and the performance of both banking systems in Afghanistan. The paper concludes with recommendations for policymakers and banking institutions to enhance the stability and growth of the banking sector in Afghanistan. Interest is described as "a prefixed rate for use or borrowing of money" from an Islamic perspective. This "prefixed rate," known in Islamic economics as "riba," has been described as "something undesirable." Furthermore, by using the time series regression data technique on the annual data from 2003 to 2021, this research examines the effect of CPI inflation rate and interest rate of Banking in Afghanistan.

Keywords: inflation, Islamic banking, conventional banking, interest, Afghanistan, impact

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Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

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The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems does not scale well on multi-CPU/multi-GPUs clusters. For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration instead of two for standard CG. The standard and pipelined CG methods need the vector entries generated by the current GPU and other GPUs for matrix-vector products. So the communication between GPUs becomes a major performance bottleneck on multi GPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using the pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP, and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: conjugate gradient, GPU, parallel programming, pipelined algorithm

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

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Authors: Einat Waizbard, Emilio Ferrer, Meghan Miller, Brianna Heath, Derek S. Andrews, Sally J. Rogers, Christine Wu Nordahl, Marjorie Solomon, David G. Amaral

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Background: Autism symptoms are comprised of social-communication deficits and restricted/repetitive behaviors (RRB). The severity of these symptoms can change during childhood, with differences between boys and girls. From the literature, it was found that young autistic girls show a stronger tendency to decrease and a weaker tendency to increase their overall autism symptom severity levels compared to young autistic boys. It is not clear, however, which symptoms are driving these sex differences across childhood. In the current study, we evaluated the trajectories of independent autism symptoms across childhood and compared the patterns of change in such symptoms between boys and girls. Method: The study included 183 children diagnosed with autism (55 girls) evaluated three times across childhood, at ages 3, 6 and 11. We analyzed 22 independent items from the Autism Diagnostic Observation Scheudule-2 (ADOS-2), the gold-standard assessment tool for autism symptoms, each item representing a specific autism symptom. First, we used latent growth curve models to estimate the trajectories for the 22 ADOS-2 items for each child in the study. Second, we extracted the factor scores representing the individual slopes for each ADOS-2 item (i.e., slope representing that child’s change in that specific item). Third, we used factor analysis to identify common patterns of change among the ADOS-2 items, separately for boys and girls, i.e., which autism symptoms tend to change together and which change independently across childhood. Results: The best-emerging patterns for both boys and girls identified four common factors: three factors representative of changes in social-communication symptoms and one factor describing changes in RRB. Boys and girls showed the same pattern of change in RRB, with four items (e.g., speech abnormalities) changing together across childhood and three items (e.g., mannerisms) changing independently of other items. For social-communication deficits in boys, three factors were identified: the first factor included six items representing initiating and engaging in social-communication (e.g., quality of social overtures, conversation), the second factor included five items describing responsive social-communication (e.g., response to name) and the third factor included three items related to different aspects of social-communication (e.g., level of language). Girls’ social-communications deficits also loaded onto three factors: the first factor included five items (e.g., unusual eye contact), the second factor included six items (e.g., quality of social response), and the third factor included four items (e.g., showing). Some items showed similar patterns of change for both sexes (e.g., responsive joint attention), while other items showed differences (e.g., shared enjoyment). Conclusions: Girls and boys had different patterns of change in autism symptom severity across childhood. For RRB, both sexes showed similar patterns. For social-communication symptoms, however, there were both similarities and differences between boys and girls in the way symptoms changed over time. The strongest patterns of change were identified for initiating and engaging in social communication for boys and responsive social communication for girls.

Keywords: autism spectrum disorder, autism symptom severity, symptom trajectories, sex differences

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Authors: Mennatallah M. Hussein, Olivier de Weck

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The advancement of space exploration demands a robust space launch services program capable of reliably propelling payloads into orbit. Despite rigorous testing and quality assurance, launch failures still occur, leading to significant financial losses and jeopardizing mission objectives. Traditional failure prediction methods often lack the sophistication to account for multi-mode failure scenarios, as well as the predictive capability in complex dynamic systems. Traditional approaches also rely on expert judgment, leading to variability in risk prioritization and mitigation strategies. Hence, there is a pressing need for robust approaches that enhance launch vehicle reliability from lift-off until it reaches its parking orbit through comprehensive simulation techniques. In this study, the developed model proposes a multi-mode launch vehicle simulation framework for predicting failure scenarios when incorporating new technologies, such as new propulsion systems or advanced staging separation mechanisms in the launch system. To this end, the model combined a 6-DOF system dynamics with comprehensive data analysis to simulate multiple failure modes impacting launch performance. The simulator utilizes high-fidelity physics-based simulations to capture the complex interactions between different subsystems and environmental conditions.

Keywords: launch vehicle, failure prediction, propulsion anomalies, rocket launch simulation, rocket dynamics

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Authors: Manganyi Patricia Siphiwe

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Work environments are characterised by performance pressure and mechanisation, which lead to job stress and the dehumanisation of work spaces. The personnel’s competence to accomplish job responsibilities and high job demands lead to a substantial load of health. Therefore, providing employees with conducive working environments is essential. In order to attain it, the employer should ensure that responsive and institutional safe systems are in place. The employer’s responses to employees’ needs are of significance to a healthy and developmental work environment. Denying employees a developmental and flourishing workplace is to deprive a workplace of being humane. Stressors coming from various aspects in the workplace can yield undue pressure and undesired responses for the workforces. Against the profiled background, this paper examines the causes and consequences of workplace stress within the Emergency Medical sector. The paper utilised a qualitative methodology and in-depth interviews for data collection with the purposively sampled emergency medical personnel. The findings showed that workplace stress has been associated with high demands and lack of support which has an adverse effect on biopsychosocial wellbeing of employees. This paper, therefore, recommends an engaged involvement of social workers through work organisational initiatives, such as Employee Assistance Programmes (EAP) and related labour relations policy activities to promote positive and developmental working environments.

Keywords: stress, employee, workplace, wellbeing

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Authors: Ali Akbar Heydari

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Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values.

Keywords: control chart, markov chain approach, statistical design, synthetic, variable parameter

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Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Sara R. Knigge, Sugat R. Tuladhar, Alexander Becker, Tobias Schilling, Birgit Glasmacher

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Commercially available mechanical or biological heart valve prostheses both tend to fail long-term due to thrombosis, calcific degeneration, infection, or immunogenic rejection. Moreover, these prostheses are non-viable and do not grow with the patients, which is a problem for young patients. As a result, patients often need to undergo redo-operations. Tissue-engineered (TE) heart valves based on degradable electrospun fiber scaffolds represent a promising approach to overcome these limitations. Such scaffolds need sufficient mechanical properties to withstand the hydrodynamic stress of intracardiac hemodynamics. Additionally, the scaffolds should be colonized by autologous or homologous cells to facilitate the in vivo remodeling of the scaffolds to a viable structure. This study investigates how process parameters of electrospinning and degradation affect the mechanical properties of electrospun scaffolds made of FDA-approved, biodegradable polymer polycaprolactone (PCL). Fiber mats were produced from a PCL/tetrafluoroethylene solution by electrospinning. The e-spinning process was varied in terms of scaffold thickness, fiber diameter, fiber orientation, and fiber interconnectivity. The morphology of the fiber mats was characterized with a scanning electron microscope (SEM). The mats were degraded in different solutions (cell culture media, SBF, PBS and 10 M NaOH-Solution). At different time points of degradation (2, 4 and 6 weeks), tensile and cyclic loading tests were performed. Fresh porcine pericardium and heart valves served as a control for the mechanical assessment. The progression of polymer degradation was quantified by SEM and differential scanning calorimetry (DSC). Primary Human aortic endothelial cells (HAECs) and Human induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) were seeded on the fiber mats to investigate the cell colonization potential. The results showed that both the electrospinning parameters and the degradation significantly influenced the mechanical properties. Especially the fiber orientation has a considerable impact and leads to a pronounced anisotropic behavior of the scaffold. Preliminary results showed that the polymer became strongly more brittle over time. However, the embrittlement can initially only be detected in the mechanical test. In the SEM and DSC investigations, neither morphological nor thermodynamic changes are significantly detectable. Live/Dead staining and SEM imaging of the cell-seeded scaffolds showed that HAECs and iPSC-ECs were able to grow on the surface of the polymer. In summary, this study's results indicate a promising approach to the development of a TE aortic heart valve based on an electrospun scaffold.

Keywords: electrospun scaffolds, long-term polymer degradation, mechanical behavior of electrospun PCL, tissue engineered aortic heart valve

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Authors: M. Al Huwayz, A. Salhi, S. Alhassan, S. Alotaibi, A. Almalki, M.Almunyif, A. Alhassni, M. Henini

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Recently, there has been much research carried out to investigate quantum dots (QDs) lasers with the aim to increase the gain of quantum well lasers. However, one of the difficulties with these structures is that electrically active defects can lead to serious issues in the performance of these devices. It is therefore essential to fully understand the types of defects introduced during the growth and/or the fabrication process. In this study, the effects of Gamma radiation on the electrically active defects in p-i-n InAs/InGaAsQDs laser structures grown by Molecular Beam Epitaxy (MBE) technique on GaAs substrates were investigated. Deep Level Transient Spectroscopy (DLTS), current-voltage (I-V), and capacitance-voltage (C-V) measurements were performed to explore these effects on the electrical properties of these QDs lasers. I-V measurements showed that as-grown sample had better electrical properties than the irradiated sample. However, DLTS and Laplace DLTS measurements at different reverse biases revealed that the defects in the-region of the p-i-n structures were decreased in the irradiated sample. In both samples, a trap with an activation energy of ~ 0.21 eV was assigned to the well-known defect M1 in GaAs layers

Keywords: quantum dots laser structures, gamma radiation, DLTS, defects, nAs/IngaAs

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Authors: Sanjeev Gupta, Ankit Prabhakar, K. Rajkumar Singh

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Sunni Dam Hydroelectric Project (382 MW) is a run of river type development with an underground powerhouse, proposed to harness the hydel potential of river Satluj in Himachal Pradesh, India. The project is located in the inner lesser Himalaya between Dhauladhar Range in the south and the higher Himalaya in the north. The project comprises two large underground caverns, a Powerhouse cavern (171m long, 22.5m wide and 51.2m high) and another transformer hall cavern (175m long, 18.7m wide and 27m high) and the rock pillar between the two caverns is 50m. The highly jointed, fractured, anisotropic rock mass is a key challenge in Himalayan geology for an underground structure. The concern for the stability of rock mass increases when weak/shear zones are encountered in the underground structure. In the Sunni Dam project, 1.7m to 2m thick weak/shear zone comprising of deformed, weak material with gauge has been encountered in powerhouse cavern at 70m having dip direction 325 degree and dip amount 38 degree which also intersects transformer hall at initial reach. The rock encountered in the powerhouse area is moderate to highly jointed, pink quartz arenite belonging to the Khaira Formation, a transition zone comprising of alternate grey, pink & white quartz arenite and shale sequence and dolomite at higher reaches. The rock mass is intersected by mainly 3 joint sets excluding bedding joints and a few random joints. The rock class in powerhouse mainly varies from poor class (class IV) to lower order fair class (class III) and in some reaches, very poor rock mass has also been encountered. To study the stability of the underground structure in weak/shear rock mass, a 3D numerical model analysis has been carried out using RS3 software. Field studies have been interpreted and analysed to derive Bieniawski’s RMR, Barton’s “Q” class and Geological Strength Index (GSI). The various material parameters, in-situ characteristics have been determined based on tests conducted by Central Soil and Materials Research Station, New Delhi. The behaviour of the cavern has been studied by assessing the displacement contours, major and minor principal stresses and plastic zones for different stage excavation sequences. For optimisation of the support system, the stability of the powerhouse cavern with different powerhouse orientations has also been studied. The numerical modeling results indicate that cavern will not likely face stress governed by structural instability with the support system to be applied to the crown and side walls.

Keywords: 3D analysis, Himalayan geology, shear zone, underground power house

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

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In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

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Authors: A. Vinod Kumar, G. Sunny Deol, Rakesh Kumar, B. Chandra

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Application of fiber reinforcement in road construction is gaining some interest in enhancing soil strength. In this paper, the natural geotextile material obtained from gunny bags was used due to its vast local availability. Construction of flexible pavement on weaker soil such as clay soils is a significant problem in construction as well as in design due to its expansive characteristics. Jute geotextile (JGT) was used on a foundation layer of flexible pavement on rural roads. This problem will be conquered by increasing the subgrade strength by decreasing sub-base layer thickness by improving their overall pavement strength characteristics which ultimately reduces the cost of construction and leads to an economical design. California Bearing Ratio (CBR), unconfined compressive strength (UCS) and triaxial laboratory tests were conducted on two different soil samples, CI and MI. Weaker soil is reinforced with JGT, JGT+Bitumen. JGT+polythene sheet was varied with heights while performing the laboratory tests. Subgrade strength evaluation was investigated by conducting soak CBR test in the laboratory for clayey and silt soils. Laboratory results reveal that reinforced soak CBR value of clayey soil (CI) observed was 10.35%, and silty soil (MI) was 15.6%. This study intends to develop new technique for reinforcing weaker soil with JGT varying parameters for the need of low volume flexible pavements. It was observed that the performance of JGT is inferior when used with bitumen and polyethylene sheets.

Keywords: CBR, jute geotextile, low volume road, weaker soil

Procedia PDF Downloads 438

Authors: Stephanie Giordano, Eric Lam, Rosa Plasencia

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An important piece of active aging is ensuring people have the right support to meet individual needs. Using NCI-AD data, we will look at measures of satisfaction with community access and needed services among people with physical disabilities receiving LTSS in the US. National Core Indicators—Aging and Disabilities (NCI-AD) is a voluntary effort by State Medicaid, aging, and disability agencies across the US to measure and track their own performance. NCI-AD uses a standardized survey – the Adult Consumer Survey (ACS), to hear directly from people receiving services about the quality of services and supports they receive. Data from the 2018-19 ACS found that compared to people without a physical disability, those with a physical disability were more likely to make choices about the services they receive, including when and how often they receive those services. Yet people with a physical disability were less likely to report they get enough assistance with everyday activities (e.g., shopping, housework, and taking medications) and self-care (e.g., dressing or bathing) and more likely to report that services and supports do not fully meet their needs and goals. A further breakdown by age shows that people 40-65 years old with a physical disability experienced even greater barriers to being as active in the community as they would like to be, indicating a need to better support people as they age with or into a disability. We will explore how these and other outcomes were affected by COVID-19, take a closer look at outcomes by demographics (e.g., race/ethnicity, gender, and mental health diagnoses) and discuss implications on the future needs of service systems.

Keywords: quality-of-life, long-term services and supports, person-centered, community

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Authors: Timothy Fwa Yerima

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This paper evaluates the development of human rights jurisprudence in Africa by the ECOWAS Court of Justice. It traces that though ECOWAS was not established with the aim of promoting and protecting human rights as the African Court of Human and Peoples’ Rights, no doubt, the 1991 ECOWAS Court Protocol and the 1993 ECOWAS Revised Treaty give the ECOWAS Court its human rights mandate. The paper, however, points out that despite the availability of these two Laws, the ECOWAS Court had difficulty in its human rights mandate, in view of the twin problems of lack of access to the Court by private parties and personal jurisdiction of the Court to entertain cases filed by private parties. The paper considers the 2005 Supplementary Protocol, not only as an effective legal framework in West African Sub-Region that tackles these problems in human rights cases but also a strong foundation upon which the Court has been developing human rights jurisprudence in Africa through the interpretation and application of this Law and other sources of Law of the Court. After a thorough analysis of some principles laid down by the ECOWAS Court so far, the paper observes that human rights jurisprudence in Africa is growing rapidly; depicting that though the ECOWAS Court initially had difficulty in its human rights mandate, today it has a bright and visionary landing. The paper concludes that West African Sub-Region will witness a more effective performance of the ECOWAS Court if some of its challenges are tackled.

Keywords: access, African human rights, ECOWAS court of justice, jurisprudence, personal jurisdiction

Procedia PDF Downloads 345

Authors: Mehdi Boukri, Mohammed Naboussi Farsi, Mounir Naili, Omar Amellal, Mohamed Belazougui, Ahmed Mebarki, Nabila Guessoum, Brahim Mezazigh, Mounir Ait-Belkacem, Nacim Yousfi, Mohamed Bouaoud, Ikram Boukal, Aboubakr Fettar, Asma Souki

Abstract:

The seismic risk to which the urban centres are more and more exposed became a world concern. A co-operation on an international scale is necessary for an exchange of information and experiments for the prevention and the installation of action plans in the countries prone to this phenomenon. For that, the 1990s was designated as 'International Decade for Natural Disaster Reduction (IDNDR)' by the United Nations, whose interest was to promote the capacity to resist the various natural, industrial and environmental disasters. Within this framework, it was launched in 1996, the RADIUS project (Risk Assessment Tools for Diagnosis of Urban Areas Against Seismic Disaster), whose the main objective is to mitigate seismic risk in developing countries, through the development of a simple and fast methodological and operational approach, allowing to evaluate the vulnerability as well as the socio-economic losses, by probable earthquake scenarios in the exposed urban areas. In this paper, we will present the adaptation and application of this methodology to the Algerian context for the seismic risk evaluation in urban areas potentially exposed to earthquakes. This application consists to perform an earthquake scenario in the urban centre of Constantine city, located at the North-East of Algeria, which will allow the building seismic damage estimation of this city. For that, an inventory of 30706 building units was carried out by the National Earthquake Engineering Research Centre (CGS). These buildings were digitized in a data base which comprises their technical information by using a Geographical Information system (GIS), and then they were classified according to the RADIUS methodology. The study area was subdivided into 228 meshes of 500m on side and Ten (10) sectors of which each one contains a group of meshes. The results of this earthquake scenario highlights that the ratio of likely damage is about 23%. This severe damage results from the high concentration of old buildings and unfavourable soil conditions. This simulation of the probable seismic damage of the building and the GIS damage maps generated provide a predictive evaluation of the damage which can occur by a potential earthquake near to Constantine city. These theoretical forecasts are important for decision makers in order to take the adequate preventive measures and to develop suitable strategies, prevention and emergency management plans to reduce these losses. They can also help to take the adequate emergency measures in the most impacted areas in the early hours and days after an earthquake occurrence.

Keywords: seismic risk, mitigation, RADIUS, urban areas, Algeria, earthquake scenario, Constantine

Procedia PDF Downloads 258

Authors: C. A. Roberts, S. L. Mascaro, J. R. Gerrish, J. L. Horner

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Management-intensive Grazing (MiG) is a practice that rotates livestock through paddocks in a way that best matches the nutrient requirements of the animal to the yield and quality of the pasture. In the USA, MiG has been taught to livestock producers throughout the state of Missouri in 2- and 3-day workshops called “Missouri Grazing Schools.” The economic impact of these schools was quantified using IMPLAN software. The model included hectares of adoption, animal performance, carrying capacity, and input costs. To date, MiG, as taught in the Missouri Grazing Schools, has been implemented on more than 70,000 hectares in Missouri. The economic impact of these schools is presently $125 million USD per year added to the state economy. This magnitude of impact is the result not only of widespread adoption but also because of increased livestock carrying capacity; in Missouri, a capacity increase of 25 to 30% has been well documented. Additional impacts have been MiG improving forage quality and reducing the cost of feed and fertilizer. The environmental impact of MiG in the state of Missouri is currently being estimated. Environmental impact takes into account the reduction in the application of commercial fertilizers; in MiG systems, nitrogen is supplied by N fixation from legumes, and much of the P and K is recycled naturally by well-distributed manure. The environmental impact also estimates carbon sequestration and methane production; MiG can increase carbon sequestration and reduce methane production in comparison to default grazing practices and feedlot operations in the USA.

Keywords: agricultural education, forage quality, management-intensive grazing, nutrient cycling, stock density, sustainable agriculture

Procedia PDF Downloads 199

Authors: Ahmed Raza Khan

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Local-strain engineering is an exciting approach to tune the optoelectronic properties of materials and enhance the performance of devices. Two dimensional (2D) materials such as 2D transition metal dichalcogenides (TMDCs) are particularly well-suited for this purpose because they have high flexibility and can withstand high deformations before rupture. Wrinkles on thick TMDC layers have been reported to show the interesting photoluminescence enhancement due to bandgap modulation and funneling effect. However, the wrinkles in ultrathin TMDCs have not been investigated, because the wrinkles can easily fall down to form folds in these ultrathin layers of TMDCs. Here, we have achieved both wrinkle and fold nano-structures simultaneously on 1-3L WS₂ using a new fabrication technique. The comparable layer dependent reduction in surface potential is observed for both folded layers and corresponding perfect pack layers due to the dominant interlayer screening effect. The strains produced from the wrinkle nanostructures considerably vary semi conductive junction properties. Thermo-ionic modelling suggests that the strained (1.6%) wrinkles can lower the Schottky barrier height (SBH) by 20%. The photo-generated carriers would further significantly lower the SBH. These results present an important advance towards controlling the optoelectronic properties of atomically thin WS₂ using strain engineering, with important implications for practical device applications.

Keywords: strain engineering, folding, WS₂, Kelvin probe force microscopy, KPFM, surface potential, photo current, layer dependence

Procedia PDF Downloads 104