Search results for: performance budgeting

Authors: M. B. Ricardo De Oliveira, A. Borghi-Silva, E. Paravizo, F. Lizarelli, L. Di Thomazzo, D. Braatz

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Prototypes are a critical feature in the product development process, as they help the project team visualize early concept flaws, communicate ideas and introduce an initial product testing. Involving stakeholders, such as consumers and users, in prototype tests allows the gathering of valuable feedback, contributing for a better product and making the design process more participatory. Even though recent studies have shown that user evaluation of prototypes is valuable, few articles provide a method or protocol on how designers should conduct it. This multidisciplinary study (involving the areas of physiotherapy, engineering and computer science) aims to develop an evaluation protocol, using an ergometric step prototype as the product prototype to be assessed. The protocol consisted of performing two tests (the 2 Minute Step Test and the Portability Test) to allow users (patients) and consumers (physiotherapists) to have an experience with the prototype. Furthermore, the protocol contained four Likert-Scale questionnaires (one for users and three for consumers), that inquired participants about how they perceived the design characteristics of the product (performance, safety, materials, maintenance, portability, usability and ergonomics), in their use of the prototype. Additionally, the protocol indicated the need to conduct interviews with the product designers, in order to link their feedback to the ones from the consumers and users. Both tests and interviews were recorded for further analysis. The participation criteria for the study was gender and age for patients, gender and experience with 2 Minute Step Test for physiotherapists and involvement level in the product development project for designers. The questionnaire's reliability was validated using Cronbach's Alpha and the quantitative data of the questionnaires were analyzed using non-parametric hypothesis tests with a significance level of 0.05 (p <0.05) and descriptive statistics. As a result, this study provides a concise evaluation protocol which can assist designers in their development process, collecting quantitative feedback from consumer and users, and qualitative feedback from designers.

Keywords: Product Design, Product Evaluation, Prototypes, Step

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Authors: Bong Jae Lee, Jeong Il Lee, Hyo Su Kim

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Both developed and developing countries have adopted the decision to join the Paris agreement to reduce greenhouse gas (GHG) emissions at the Conference of the Parties (COP) 21 meeting in Paris. As a result, the developed and developing countries have to submit the Intended Nationally Determined Contributions (INDC) by 2020, and each country will be assessed for their performance in reducing GHG. After that, they shall propose a reduction target which is higher than the previous target every five years. Therefore, an accurate method for calculating greenhouse gas emissions is essential to be presented as a rational for implementing GHG reduction measures based on the reduction targets. Non-CO2 GHGs (CF4, NF3, N2O, SF6 and so on) are being widely used in fabrication process of semiconductor manufacturing, and etching/deposition process of display manufacturing process. The Global Warming Potential (GWP) value of Non-CO2 is much higher than CO2, which means it will have greater effect on a global warming than CO2. Therefore, GHG calculation methods of the electronics industry are provided by Intergovernmental Panel on climate change (IPCC) and U.S. Environmental Protection Agency (EPA), and it will be discussed at ISO/TC 146 meeting. As discussed earlier, being precise and accurate in calculating Non-CO2 GHG is becoming more important. Thus this study aims to discuss the implications of the calculating methods through comparing the methods of IPCC and EPA. As a conclusion, after analyzing the methods of IPCC & EPA, the method of EPA is more detailed and it also provides the calculation for N2O. In case of the default emission factor (by IPCC & EPA), IPCC provides more conservative results compared to that of EPA; The factor of IPCC was developed for calculating a national GHG emission, while the factor of EPA was specifically developed for the U.S. which means it must have been developed to address the environmental issue of the US. The semiconductor factory ‘A’ measured F gas according to the EPA Destruction and Removal Efficiency (DRE) protocol and estimated their own DRE, and it was observed that their emission factor shows higher DRE compared to default DRE factor of IPCC and EPA Therefore, each country can improve their GHG emission calculation by developing its own emission factor (if possible) at the time of reporting Nationally Determined Contributions (NDC). Acknowledgements: This work was supported by the Korea Evaluation Institute of Industrial Technology (No. 10053589).

Keywords: non-CO2 GHG, GHG emission, electronics industry, measuring method

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Authors: Yelba Maria Carrillo

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The focus of this research study was to explore barriers, if any, faced by parents or legal guardians who are of Latinx background and speak Spanish as a primary language or are bilingual speakers of Spanish and English; barriers that limit their understanding of and involvement in their gifted child’s academic life. This study was guided by a qualitative case study design. The primary investigator hosted focus group interviews at a Magnet Middle School in Southern California. The groups consisted of 25 parents, or legal guardians of bilingual (English/Spanish) or former English learner students enrolled in a school serving 6th-8th grades. The primary investigator interviewed Latinx Spanish-speaking parents or legal guardians of gifted students regarding their perception of their child’s giftedness, parental involvement in schools, and fostering their child’s exceptional abilities. Parents and legal guardians described children as creative, intellectual, and highly intelligent. Key themes such as student performance, language proficiency, socio-emotional, and general intellectual ability were strong indicators of giftedness. Barriers such as language and education inhibited parent and legal guardian ability to understand their child’s giftedness, which resulted in their inability to adequately contribute to the development of their children’s talents and advocate for the appropriate services for their children. However, they recognized the importance of being involved in their child’s academic life and the importance of nurturing their ‘dón’ or ‘gift.’ La Familia is the foundation and core of Latinx culture; and, without a strong foundation, children lack guidance, confidence, and awareness to tap into their gifted abilities. Providing Latinx parents with the proper tools and resources to appropriately identify gifted characteristics and traits could lead to early identification and intervention for students in schools and at home.

Keywords: gifted education, gifted Latino students, Latino parent involvement, high ability students

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Authors: Maciej Jedrzejczyk, Karolina Marzantowicz

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Traditional utility value chain is being transformed during last few years into unbundled markets. Increased distributed generation of energy is one of considerable challenges faced by Smart Grid networks. New sources of energy introduce volatile demand response which has a considerable impact on traditional middlemen in E&U market. The purpose of this research is to search for ways to allow near-real-time electricity markets to transact with surplus energy based on accurate time synchronous measurements. A proposed framework evaluates the use of secure peer-2-peer (P2P) communication and distributed transaction ledgers to provide flat hierarchy, and allow real-time insights into present and forecasted grid operations, as well as state and health of the network. An objective is to achieve dynamic grid operations with more efficient resource usage, higher security of supply and longer grid infrastructure life cycle. Methods used for this study are based on comparative analysis of different distributed ledger technologies in terms of scalability, transaction performance, pluggability with external data sources, data transparency, privacy, end-to-end security and adaptability to various market topologies. An intended output of this research is a design of a framework for safer, more efficient and scalable Smart Grid network which is bridging a gap between traditional components of the energy network and individual energy producers. Results of this study are ready for detailed measurement testing, a likely follow-up in separate studies. New platforms for Smart Grid achieving measurable efficiencies will allow for development of new types of Grid KPI, multi-smart grid branches, markets, and businesses.

Keywords: autonomous agents, Distributed computing, distributed ledger technologies, large scale systems, micro grids, peer-to-peer networks, Self-organization, self-stabilization, smart grids

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Authors: Francesca Nicolosi, Teresa Cosola

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Climate changes in Mediterranean areas, such as the increase of average seasonal temperatures, the urban heat island phenomenon, the intensification of solar radiation and the extreme weather threats, cause disruption events, so that climate adaptation has become a pressing issue. Due to the strategic role that the built heritage holds in terms of environmental impact and energy waste and its potentiality, it is necessary to assess the vulnerability and the adaptive capacity of the existing building to climate change, in order to define different mitigation scenarios. The aim of this research work is to define an optimized and integrated methodology for the assessment of resilience levels and adaptation scenarios for existing buildings in Mediterranean urban areas. Moreover, the study of resilience indicators allows us to define building environmental and energy performance in order to identify the design and technological solutions for the improvement of the building and its urban area potentialities. The methodology identifies step-by-step different phases, starting from the detailed study of characteristic elements of urban system: climatic, natural, human, typological and functional components are analyzed in their critical factors and their potential. Through the individuation of the main perturbing factors and the vulnerability degree of the system to the risks linked to climate change, it is possible to define mitigation and adaptation scenarios. They can be different, according to the typological, functional and constructive features of the analyzed system, divided into categories of intervention, and characterized by different analysis levels (from the single building to the urban area). The use of software simulations allows obtaining information on the overall behavior of the building and the urban system, to generate predictive models in the medium and long-term environmental and energy retrofit and to make a comparative study of the mitigation scenarios identified. The studied methodology is validated on a case study.

Keywords: climate impact mitigation, energy efficiency, existing building heritage, resilience

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Authors: Muhammad Naveed Ali, Hamad Bin Rashid, Muhammad Arif Khan, Abdul Basit, Hafiz Muhammad Arshad

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Abdominal defects are very common in pigeons. A new technique is known as intraabdominal mesh transplant that give better protection for herniorrhaphy. The aim of this study was to determine the performance of hernia mesh. In this study, an efficacy of two synthetic hernia mesh implants viz. conventional Prolene and a lightweight mesh monofilament polyester were assessed for the abdominal wall repair in pigeons. Twenty four healthy pigeons were selected and randomly distributed into three groups, A, B and C (n=8). In all groups, experimental laparotomy was performed; thereafter, abdominal muscles and peritoneum were sutured together, while, a 2 x 2 cm defect was created in the abdominal muscles. For onlay hernioplasty, the hernia mesh (Prolene mesh: group A; Polyester mesh: group B) was implanted over the external oblique muscles of the abdomen. In group C (control), the mesh was not implanted; instead, the laparotomy incision was closed after a herniorrhaphy. Post-operative pain wound healing, adhesion formation, histopathological findings and formation of hematoma, abscess and seroma were assessed as short-term complications. Post-operatively, pain at surgical site was significantly less (P < 0.001) in group B (Polyester mesh); wound healing was also significantly better and rapid in group B (P < 0.05) than in group A (Prolene mesh). Group B (Polyester mesh) also depicted less than 25% adhesions when assessed on the basis of a Quantitative Modified Diamond scale; a Qualitative Adhesion Tenacity scale also depicted either no adhesions or flimsy adhesions (n=2) in group B (Polyester mesh), in contrast to group A (Prolene), which manifested greater adhesion formation and presence of dense adhesions requiring blunt dissection. There were observed hematoma, seroma and abscess formations in birds treated by Prolene mesh only. Conclusively, the polyester mesh proved superior to the Prolene mesh regarding lesser adhesion, better in wound healing, and no short-term follow-up complications.

Keywords: adhesion, mesh, polyester, prolene

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Authors: Matthew P. Mancini, Vincent Ribiere

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Today’s workers face more numerous and complex challenges and are required to be increasingly interdependent and faster learners. Knowledge sharing activities between people have been understood as a significant element affecting organizational innovation performance. While they do have the potential to spark cognitive conflict, disagreement is important from an organizational perspective because it can stimulate the development of new ideas and perhaps pave the way for creativity, innovation, and competitive advantage. How teams cope with the cognitive conflict dimension of knowledge sharing and the associated interpersonal risk is what captures our attention. Specifically, assertive conflict management strategies have a positive influence on knowledge sharing behaviors, and team psychological safety has a positive influence on knowledge sharing intention. This paper focuses on explaining the impact that these factors have on the shaping of an individual’s decision to engage or not in knowledge sharing activities. To accomplish this, we performed an empirical analysis on the results of our questionnaire about knowledge-sharing related conflict management and team psychological safety in pharmaceutical enterprises located in North America, Europe, and Asia. First, univariate analysis is used to characterize behavior regarding conflict management strategy into two groups. Group 1 presents assertive conflict management strategies and group 2 shows unassertive ones. Then, by using SEM methodology, we evaluated the relationships between them and the team psychological safety construct with the knowledge sharing process. The results of the SEM analysis show that assertive conflict management strategies affect the knowledge sharing process the most with a small, but significant effect from team psychological safety. The findings suggest that assertive conflict management strategies are just as important as knowledge sharing intentions for encouraging knowledge sharing behavior. This paper provides clear insights into how employees manage the sharing of their knowledge in the face of conflict and interpersonal risk and the relative importance of these factors in sustaining productive knowledge sharing activities.

Keywords: cognitive dissonance, conflict management, knowledge sharing, organizational behavior, psychological safety

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Authors: Venuka Kuruwita Arachchige Don, Mohamed Shaheen, Chris Goodier

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Aerated autoclaved concrete (AAC) is known for its lightweight, easy handling, high thermal insulation, and extremely porous structure. Investigation of pore behavior in AAC is crucial for characterizing the material, standardizing design and production techniques, enhancing the mechanical, durability, and thermal performance, studying the effectiveness of protective measures, and analyzing the effects of weather conditions. The significant details of pores are complicated to observe with acknowledged accuracy. The High-resolution Field Emission Scanning Electron Microscope (FESEM) image analysis is a promising technique for investigating the pore behavior and density of AAC, which is adopted in this study. Mercury intrusion porosimeter and gas pycnometer were employed to characterize porosity distribution and density parameters. The analysis considered three different densities of AAC blocks and three layers in the altitude direction within each block. A set of understandings was presented to extract and analyze the details of pore shape, pore size, pore connectivity, and pore percentages from FESEM images of AAC. Average pore behavior outcomes per unit area were presented. Comparison of porosity distribution and density parameters revealed significant variations. FESEM imaging offered unparalleled insights into porosity behavior, surpassing the capabilities of other techniques. The analysis conducted from a multi-staged approach provides porosity percentage occupied by various pore categories, total porosity, variation of pore distribution compared to AAC densities and layers, number of two-dimensional and three-dimensional pores, variation of apparent and matrix densities concerning pore behaviors, variation of pore behavior with respect to aluminum content, and relationship among shape, diameter, connectivity, and percentage in each pore classification.

Keywords: autoclaved aerated concrete, density, imaging technique, microstructure, porosity behavior

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Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

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Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

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Authors: Afolabi Comfort Yemisi

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Gender-based violence remains a serious threat to the growth, health, and safety of women and girls globally, including Nigeria. The rising violence of various shades of violence, especially against women and girls in the guise of cultural preservation, raised serious concerns. The challenge of this harmful gender narrative is more critical in attaining the Sustainable Development Goals and Goal 4 (Quality Education) in Nigeria. The study investigated the perception and effects of gender-based violence on sustainable development and education of the girl-child in Southwestern Nigeria. Primary and Secondary data were used for the study. Primary data were obtained using a structured questionnaire administered to young females in tertiary institutions, secondary schools, non-governmental organizations, and government institutions dealing with gender-based violence in the study area, while the secondary data were sourced from journals, books and dailies. A multistage random sampling technique was employed to select a sample of 360 respondents who completed the questionnaire for the study. Descriptive statistics and regression analysis were applied to the data collected. The result revealed a high prevalence of gender-based violence, and it was perceived to be culturally motivated. Sexual violence, sexual harassment and psychological violence were the significant forms of gender-based violence that adversely affected the Sustainable Development Goal 4. The result further revealed that loss of concentration, shame and depression, school drop-out, poor academic performance and inferiority complex were the major effects of gender-based violence on the education of girl-child in the study area. The study recommended that to avert catastrophic damages and adverse effects of gender-based violence on the girl-child, there is a need for thorough awareness and sensitization programmes to build their resilience. Also, enforcement of established laws against gender-based violence by both government and non-governmental institutions is sacrosanct.

Keywords: perception, effects, gender-based violence, sustainable development, education, girl-child, sensitisation

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Authors: Abbas Ali Husseini, Ali Mohammad Yazdani, Fatemeh Ghadiri, Alper Şişman

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We developed a microchip device that uses surface acoustic waves for rapid lysis of low level of cell samples. The device incorporates sharp-edge glass microparticles for improved performance. We optimized the lysis conditions for high efficiency and evaluated the device's feasibility for point-of-care applications. The microchip contains a 13-finger pair interdigital transducer with a 30-degree focused angle. It generates high-intensity acoustic beams that converge 6 mm away. The microchip operates at a frequency of 16 MHz, exciting Rayleigh waves with a 250 µm wavelength on the LiNbO3 substrate. Cell lysis occurs when Candida albicans cells and glass particles are placed within the focal area. The high-intensity surface acoustic waves induce centrifugal forces on the cells and glass particles, resulting in cell lysis through lateral forces from the sharp-edge glass particles. We conducted 42 pilot cell lysis experiments to optimize the surface acoustic wave-induced streaming. We varied electrical power, droplet volume, glass particle size, concentration, and lysis time. A regression machine-learning model determined the impact of each parameter on lysis efficiency. Based on these findings, we predicted optimal conditions: electrical signal of 2.5 W, sample volume of 20 µl, glass particle size below 10 µm, concentration of 0.2 µg, and a 5-minute lysis period. Downstream analysis successfully amplified a DNA target fragment directly from the lysate. The study presents an efficient microchip-based cell lysis method employing acoustic streaming and microparticle collisions within microdroplets. Integration of a surface acoustic wave-based lysis chip with an isothermal amplification method enables swift point-of-care applications.

Keywords: cell lysis, surface acoustic wave, micro-glass particle, droplet

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Authors: Kana Matsuyanagi

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Anorexia Nervosa (AN) is a psychiatric disorder characterized by a relentless pursuit of thinness and strict restriction of food. The current therapeutic approaches for AN predominantly revolve around outpatient psychotherapies, which create significant financial barriers for the majority of affected patients, hindering their access to treatment. Nonetheless, AN exhibit one of the highest mortality and relapse rates among psychological disorders, underscoring the urgent need to provide patients with an affordable self-treatment tool, enabling those unable to access conventional medical intervention to address their condition autonomously. To this end, a neurofeedback software, termed RelaxNeuron, was developed with the objective of providing an economical and portable means to aid individuals in self-managing AN. Electroencephalography (EEG) was chosen as the preferred modality for RelaxNeuron, as it aligns with the study's goal of supplying a cost-effective and convenient solution for addressing AN. The primary aim of the software is to ameliorate the negative emotional responses towards food stimuli and the accompanying aberrant eye-tracking patterns observed in AN patient, ultimately alleviating the profound fear towards food an elemental symptom and, conceivably, the fundamental etiology of AN. The core functionality of RelaxNeuron hinges on the acquisition and analysis of EEG signals, alongside an electrocardiogram (ECG) signal, to infer the user's emotional state while viewing dynamic food-related imagery on the screen. Moreover, the software quantifies the user's performance in accurately tracking the moving food image. Subsequently, these two parameters undergo further processing in the subsequent algorithm, informing the delivery of either negative or positive feedback to the user. Preliminary test results have exhibited promising outcomes, suggesting the potential advantages of employing RelaxNeuron in the treatment of AN, as evidenced by its capacity to enhance emotional regulation and attentional processing through repetitive and persistent therapeutic interventions.

Keywords: Anorexia Nervosa, fear conditioning, neurofeedback, BCI

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

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Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: A. Kourou, M. Panoutsopoulou

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Nowadays, disaster risk reduction requires innovative ways of working collaboratively, monitoring tools, management methods, risk communication, and knowledge, as key factors for decision-making actors. Experience has shown that the assessment of seismic risk and its effective management is still an important challenge. In Greece, Ionian Islands region is characterized as the most seismic area of the country and one of the most active worldwide. It is well known that in case of a disastrous earthquake the local authorities need to assess the situation in the affected area and coordinate the disaster response. In particular, the main outcomes of 'Telemachus' project are the development of an innovative operational system that hosts the needed data of seismic risk management in the Ionian Islands and the implementation of educational actions for the involved target groups. This project is funded in the Priority Axis 'Environmental Protection and Sustainable Development' of Operational Plan 'Ionian Islands 2014-2020'. EPPO is one of the partners of the project and it is responsible, among others, for the development of proper training material. This paper presents the training material of 'Telemachus' and its usage as a helpful, managerial tool in case of earthquake emergency. This material is addressed to different target groups, such as civil protection staff, people that involved with the tourism industry, educators of disabled people, etc. Very positive aspect of the project is the involvement of end-users that should evaluate the training products; test standards; clarify the personnel’s roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement. It is worth mentioning that even though the abovementioned material developed is useful for the training of specific target groups on emergency management issues within Ionian Islands Region, it could be used throughout Greece and other countries too.

Keywords: education of civil protection staff, Ionian Islands Region of Greece, seismic risk, training material

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Authors: O. Elkana, O Heyman, S. Hamdan, M. Franko, J. Vatine

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Objective: To investigate whether a direct link exists between perceived pain (PP) and executive functions (EF), above and beyond the influence of depression symptoms, in the context of medical rehabilitation. Design: Cross-sectional study. Setting: Rehabilitation Hospital. Participants: 125 medical records of hospitalized patients were screened for matching to our inclusion criteria. Only 60 patients were found fit and were asked to participate. 19 decline to participate on personal basis. The 41 neurologically intact patients (mean age 46, SD 14.96) that participated in this study were in their sub-acute stage of recovery, with fluent Hebrew, with intact upper limb (to neutralize influence on psychomotor performances) and without an organic brain damage. Main Outcome Measures: EF were assessed using the Wisconsin Card Sorting Test (WCST) and the Stop-Signal Test (SST). PP was measured using 3 well-known pain questionnaires: Pain Disability Index (PDI), The Short-Form McGill Questionnaire (SF-MPQ) and the Pain Catastrophizing Scale (PCS). Perceived pain index (PPI) was calculated by the mean score composite from the 3 pain questionnaires. Depression symptoms were assessed using the Patient Health Questionnaire (PHQ-9). Results: The results indicate that irrespective of the presence of depression symptoms, PP is directly correlated with response inhibition (SST partial correlation: r=0.5; p=0.001) and mental flexibility (WSCT partial correlation: r=-0.37; p=0.021), suggesting decreased performance in EF as PP severity increases. High correlations were found between the 3 pain measurements: SF-MPQ with PDI (r=0.62, p<0.001), SF-MPQ with PCS (r=0.58, p<0.001) and PDI with PCS (r=0.38, p=0.016) and each questionnaire alone was also significantly associated with EF; thus, no specific questionnaires ‘pulled’ the results obtained by the general index (PPI). Conclusion: Examining the direct association between PP and EF, beyond the contribution of depression symptoms, provides further clinical evidence suggesting that EF and PP share underlying mediating neuronal mechanisms. Clinically, the importance of assessing patients' EF abilities as well as PP severity during rehabilitation is underscored.

Keywords: depression, executive functions, mental-flexibility, neuropsychology, pain perception, perceived pain, response inhibition

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Authors: Teng Li, Kamran Mohseni

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This paper presents an inviscid regularization technique that is capable of regularizing the shocks and sharp interfaces simultaneously in the shock-interface interaction simulations. The direct numerical simulation of flows involving shocks has been investigated for many years and a lot of numerical methods were developed to capture the shocks. However, most of these methods rely on the numerical dissipation to regularize the shocks. Moreover, in high Reynolds number flows, the nonlinear terms in hyperbolic Partial Differential Equations (PDE) dominates, constantly generating small scale features. This makes direct numerical simulation of shocks even harder. The same difficulty happens in two-phase flow with sharp interfaces where the nonlinear terms in the governing equations keep sharpening the interfaces to discontinuities. The main idea of the proposed technique is to average out the small scales that is below the resolution (observable scale) of the computational grid by filtering the convective velocity in the nonlinear terms in the governing PDE. This technique is named “observable method” and it results in a set of hyperbolic equations called observable equations, namely, observable Navier-Stokes or Euler equations. The observable method has been applied to the flow simulations involving shocks, turbulence, and two-phase flows, and the results are promising. In the current paper, the observable method is examined on the performance of regularizing shocks and interfaces at the same time in shock-interface interaction problems. Bubble-shock interactions and Richtmyer-Meshkov instability are particularly chosen to be studied. Observable Euler equations will be numerically solved with pseudo-spectral discretization in space and third order Total Variation Diminishing (TVD) Runge Kutta method in time. Results are presented and compared with existing publications. The interface acceleration and deformation and shock reflection are particularly examined.

Keywords: compressible flow simulation, inviscid regularization, Richtmyer-Meshkov instability, shock-bubble interactions.

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Authors: Kailas L. Wasewar

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Biobutanol has been considered as a potential and alternative biofuel relative to the most popular biodiesel and bioethanol. End product toxicity is the major problems in commercialization of fermentation based process which can be reduce to some possible extent by removing biobutanol simultaneously. Several techniques have been investigated for removing butanol from fermentation broth such as stripping, adsorption, liquid–liquid extraction, pervaporation, and membrane solvent extraction. Liquid–liquid extraction can be performed with high selectivity and is possible to carry out inside the fermenter. Conventional solvents have few drawbacks including toxicity, loss of solvent, high cost etc. Hence alternative solvents must be explored for the same. Room temperature ionic liquids (RTILs) composed entirely of ions are liquid at room temperature having negligible vapor pressure, non-flammability, and tunable physiochemical properties for a particular application which term them as “designer solvents”. Ionic liquids (ILs) have recently gained much attention as alternatives for organic solvents in many processes. In particular, ILs have been used as alternative solvents for liquid–liquid extraction. Their negligible vapor pressure allows the extracted products to be separated from ILs by conventional low pressure distillation with the potential for saving energy. Morpholinium, imidazolium, ammonium, phosphonium etc. based ionic liquids have been employed for the separation biobutanol. In present chapter, basic concepts of ionic liquids and application in separation have been presented. Further, type of ionic liquids including, conventional, functionalized, polymeric, supported membrane, and other ionic liquids have been explored. Also the effect of various performance parameters on separation of biobutanol by ionic liquids have been discussed and compared for different cation and anion based ionic liquids. The typical methodology for investigation have been adopted such as contacting the equal amount of biobutanol and ionic liquids for a specific time say, 30 minutes to confirm the equilibrium. Further, biobutanol phase were analyzed using GC to know the concentration of biobutanol and material balance were used to find the concentration in ionic liquid.

Keywords: biobutanol, separation, ionic liquids, sustainability, biorefinery, waste biomass

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Authors: Selamat Muliadi

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This study aimed to explain conceptual the role of Zakat on sustainable economic development by Rumah Zakat. Rumah Zakat is a philanthropic institution that manages zakat and other social funds through community empowerment programs. In running the program, including economic empowerment and socio health services are designed for these recipients. Rumah Zakat's connection with the establisment of Sustainable Development Goals (SDGs) which is to help impoverished recipients economically and socially. It’s an important agenda that the government input into national development, even the region. The primary goal of Zakat on sustainable economic development, not only limited to economic variables but based on Islamic principles, has comprehensive characteristics. The characteristics include moral, material, spiritual, and social aspects. In other words, sustainable economic development is closely related to improving people’s living standard (Mustahiq). The findings provide empiricial evidence regarding the positive contribution and effectiveness of zakat targeting in reducing poverty and improve the welfare of people related with the management of zakat. The purpose of this study was to identify the role of Zakat on sustainable economic development, which was applied by Rumah Zakat. This study used descriptive method and qualitative analysis. The data source was secondary data collected from documents and texts related to the research topic, be it books, articles, newspapers, journals, or others. The results showed that the role of zakat on sustainable economic development by Rumah Zakat has been quite good and in accordance with the principle of Islamic economics. Rumah Zakat programs are adapted to support intended development. The contribution of the productive program implementation has been aligned with four goals in the Sustainable Development Goals, i.e., Senyum Juara (Quality Education), Senyum Lestari (Clean Water and Sanitation), Senyum Mandiri (Entrepreneur Program) and Senyum Sehat (Free Maternity Clinic). The performance of zakat in the sustainable economic empowerment community at Rumah Zakat is taking into account dimensions such as input, process, output, and outcome.

Keywords: Zakat, social welfare, sustainable economic development, charity

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Authors: Fariba Dortaj, Reza Asadinejad, Akram Dortaj, Atena Baziyar

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The aim of this study was to determine the effect of distance education (based on MOOC) on the components of academic engagement of Kerman PNU. The research was quasi-experimental method that cluster sampling with an appropriate volume was used in this study (one class in experimental group and one class in controlling group). Sampling method is single-stage cluster sampling. The statistical society is students of Kerman Payam Noor University, which) were selected 40 of them as sample (20 students in the control group and 20 students in experimental group). To test the hypothesis, it was used the analysis of univariate and Co-covariance to offset the initial difference (difference of control) in the experimental group and the control group. The instrument used in this study is academic engagement questionnaire of Zerang (2012) that contains component of cognitive, behavioral and motivational engagement. The results showed that there is no significant difference between mean scores of academic components of academic engagement in experimental group and the control group on the post-test, after elimination of the pre-test. The adjusted mean scores of components of academic engagement in the experimental group were higher than the adjusted average of scores after the test in the control group. The use of technology-based education in distance education has been effective in increasing cognitive engagement, motivational engagement and behavioral engagement among students. Experimental variable with the effect size 0.26, predicted 26% of cognitive engagement component variance. Experimental variable with the effect size 0.47, predicted 47% of the motivational engagement component variance. Experimental variable with the effect size 0.40, predicted 40% of behavioral engagement component variance. So teaching with technology (MOOC) has a positive impact on increasing academic engagement and academic performance of students in educational technology. The results suggest that technology (MOOC) is used to enrich the teaching of other lessons of PNU.

Keywords: educational technology, distance education, components of academic engagement, mooc technology

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Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

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Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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Authors: Muhammad Umar Mushtaq, Muhammad Bilal Khan Niazi, Nouman Ahmad, Dooa Arif

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Apart from organic dyes, heavy metals such as Pb, Ni, Cr, and Cu are present in textile effluent and pose a threat to humans and the environment. Many studies on removing heavy metallic ions from textile wastewater have been conducted in recent decades using metal-organic frameworks (MOFs). In this study new polyether sulfone ultrafiltration membrane, modified with Cu/Co and Cu/Zn-based bimetal-organic frameworks (MOFs), was produced. Phase inversion was used to produce the membrane, and atomic force microscopy (AFM), scanning electron microscopy (SEM) were used to characterize it. The bimetallic MOFs-based membrane structure is complex and can be comprehended using characterization techniques. The bimetallic MOF-based filtration membranes are designed to selectively adsorb specific contaminants while allowing the passage of water molecules, improving the ultrafiltration efficiency. MOFs' adsorption capacity and selectivity are enhanced by functionalizing them with particular chemical groups or incorporating them into composite membranes with other materials, such as polymers. The morphology and performance of the bimetallic MOF-based membrane were investigated regarding pure water flux and metal ion rejection. The advantages of developed bimetallic MOFs based membranes for wastewater treatment include enhanced adsorption capacity because of the presence of two metals in their structure, which provides additional binding sites for contaminants, leading to a higher adsorption capacity and more efficient removal of pollutants from wastewater. Based on the experimental findings, bimetallic MOF-based membranes are more capable of rejecting metal ions from industrial wastewater than conventional membranes that have already been developed. Furthermore, the difficulties associated with operational parameters, including pressure gradients and velocity profiles, are simulated using Ansys Fluent software. The simulation results obtained for the operating parameters are in complete agreement with the experimental results.

Keywords: bimetallic MOFs, heavy metal ions, industrial wastewater treatment, ultrafiltration.

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Authors: Nuri Onat, Omer Tatari, Gokhan Egilmez

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The U.S. buildings consume significant amount of energy and natural resources and they are responsible for approximately 40 % of the greenhouse gases emitted in the United States. Awareness of these environmental impacts paved the way for the adoption of green building movement. The green building movement is a rapidly increasing trend. Green Construction market has generated $173 billion dollars in GDP, supported over 2.4 million jobs, and provided $123 billion dollars in labor earnings. The number of LEED certified buildings is projected to be almost half of the all new, nonresidential buildings by 2015. National Science and Technology Council (NSTC) aims to increase number of net-zero energy buildings (NZB). The ultimate goal is to have all commercial NZB by 2050 in the US (NSTC 2008). Green Building Initiative (GBI) became the first green building organization that is accredited by American National Standards Institute (ANSI), which will also boost number of green buildings certified by Green Globes. However, there is much less focus on greening the residential buildings, although the environmental impacts of existing residential buildings are more than that of commercial buildings. In this regard, current research aims to model the residential green building movement with a dynamic model approach and assess the possible strategies to stabilize the carbon footprint of the U.S. residential building stock. Three aspects of sustainable development are considered in policy making, namely: high performance green building (HPGB) construction, NZB construction and building retrofitting. 19 different policy options are proposed and analyzed. Results of this study explored that increasing the construction rate of HPGBs or NZBs is not a sufficient policy to stabilize the carbon footprint of the residential buildings. Energy efficient building retrofitting options are found to be more effective strategies then increasing HPGBs and NZBs construction. Also, significance of shifting to renewable energy sources for electricity generation is stressed.

Keywords: green building movement, residential buildings, carbon footprint, system dynamics

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Authors: Roengchai Tansuchat, Woraphon Yamaka, Paravee Maneejuk

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From the past recent, the global financial crisis, economic instability, and large fluctuation in agricultural commodity price have led to increased concerns about the volatility transmission among them. The problem is further exacerbated by commodities volatility caused by other commodity price fluctuations, hence the decision on hedging strategy has become both costly and useless. Thus, this paper is conducted to analysis the volatility spillover effect among major agriculture including corn, soybeans, wheat and rice, to help the commodity suppliers hedge their portfolios, and manage the risk and co-volatility of them. We provide a switching regime approach to analyzing the issue of volatility spillovers in different economic conditions, namely upturn and downturn economic. In particular, we investigate relationships and volatility transmissions between these commodities in different economic conditions. We purposed a Copula-based multivariate Markov Switching GARCH model with two regimes that depend on an economic conditions and perform simulation study to check the accuracy of our proposed model. In this study, the correlation term in the cross-hedge ratio is obtained from six copula families – two elliptical copulas (Gaussian and Student-t) and four Archimedean copulas (Clayton, Gumbel, Frank, and Joe). We use one-step maximum likelihood estimation techniques to estimate our models and compare the performance of these copula using Akaike information criterion (AIC) and Bayesian information criteria (BIC). In the application study of agriculture commodities, the weekly data used are conducted from 4 January 2005 to 1 September 2016, covering 612 observations. The empirical results indicate that the volatility spillover effects among cereal futures are different, as response of different economic condition. In addition, the results of hedge effectiveness will also suggest the optimal cross hedge strategies in different economic condition especially upturn and downturn economic.

Keywords: agricultural commodity futures, cereal, cross-hedge, spillover effect, switching regime approach

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Authors: Monika Simkute-Bukante

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Teachers significantly influence student achievements, personal development, and academic success. Consequently, they are subject to heightened expectations and scrutiny from governments, school administrations, parents, and even students. Increasing responsibilities and pressures impact teachers’ professional well-being, contributing to a global trend of increased teacher turnover and shortages due to stress and heavy workloads. Given the critical role of teachers in educating young people, it is essential to implement strategies to retain them. School administrations are pivotal in creating an environment conducive to optimal performance. However, there remains a gap in understanding how school administration leadership impacts teachers' professional well-being and its potential for improvement. This research aims to define teacher professional well-being, identify its attributes, and explore the factors influencing it, with a particular focus on the role of school administration. Employing the concept analysis method, this study reviews scholarly publications from 2019 to 2024 to articulate the components of teacher professional well-being. The findings highlight key attributes of teacher well-being, including self-efficacy, work engagement, job satisfaction, relationships with colleagues and students, support from administration, work autonomy, school climate, time pressure, workload, resilience, stress, burnout, and turnover intentions. The analysis demonstrates that school administration leadership directly affects these aspects by providing support in challenging situations, empowering teachers, offering recognition, facilitating open communication, and ensuring autonomy at work. In conclusion, the research shows that teachers' professional well-being is heavily dependent on relationships with school administration, colleagues, and students, as well as the overall school climate. It suggests that by enhancing these elements, school leaders can significantly improve teacher professional well-being. Recommendations are made for developing strategies to support these relationships, thereby fostering an environment that enhances teacher retention and effectiveness.

Keywords: concept analysis, teacher professional well-being, school administration leadership, well-being factors

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Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

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Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

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Authors: George B. Abaka-Wood, Massimiliano Zanin, Jonas Addai-Mensah, William Skinner

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The versatility of froth flotation has made it vital in the beneficiation of rare earth elements minerals from either high or low-grade ores. There has been a significant increase in the quantity of iron oxide silicate-rich tailings generated from the extraction of primary commodities such as copper and gold in Australia, which have been identified to contain very low-grade rare earth oxides (≤ 1%). There is a vast knowledge gap in the beneficiation of rare earth oxides from such tailings. The aim of this research is to investigate the feasibility of using fatty acids as collectors for the flotation recovery and upgrade of rare earth oxides from selected iron-oxide silicate-rich tailings. Two forms of fatty acid collectors (oleic acid and sodium oleate) were tested in this investigation. Flotation tests were carried out using a 1.2 L Denver D-12 cell. The effects of pulp pH, fatty acid dosage, particle size distribution (-150 +75 µm, -75 +38 µm and -38 µm) and conventional depressants (sodium silicate and starch) dosage on flotation recovery of rare earth oxides were investigated. A comparison of the flotation results indicated that sodium oleate was the more efficient fatty acid for rare earth oxides flotation at all the pulp pH investigated. The flotation performance was found to be particle size-dependent. Both sodium silicate and starch were unselective in decreasing the recovery of iron oxides and silicate minerals, respectively with the corresponding decrease in rare earth oxides recovery. Generally, iron oxides and silicate minerals formed the substantial fraction of the flotation concentrates obtained, both in the absence and presence of depressants, resulting in a generally low rare earth oxides upgrade, even though rare earth oxides recoveries were high. The flotation tests carried out on the tailings sample suggest the feasibility of rare earth oxides recovery using fatty acids, although particle size distribution and minerals liberation are key limiting factors in achieving selective rare earth oxides upgrade.

Keywords: depressants, flotation, oleic acid, sodium oleate

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Authors: Elahe Kamari

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Research on translation process has been conducted for more than 20 years, investigating various issues and using different research methodologies. Most recently, researchers have started to use eye tracking to study translation processes. They believed that the observable, measurable data that can be gained from eye tracking are indicators of unobservable cognitive processes happening in the translators’ mind during translation tasks. The aim of this study was to investigate directionality in translation processes through using eye tracking. The following hypotheses were tested: 1) processing the target text requires more cognitive effort than processing the source text, in both directions of translation; 2) L2 translation tasks on the whole require more cognitive effort than L1 tasks; 3) cognitive resources allocated to the processing of the source text is higher in L1 translation than in L2 translation; 4) cognitive resources allocated to the processing of the target text is higher in L2 translation than in L1 translation; and 5) in both directions non-professional translators invest more cognitive effort in translation tasks than do professional translators. The performance of a group of 30 male professional translators was compared with that of a group of 30 male non-professional translators. All the participants translated two comparable texts one into their L1 (Persian) and the other into their L2 (English). The eye tracker measured gaze time, average fixation duration, total task length and pupil dilation. These variables are assumed to measure the cognitive effort allocated to the translation task. The data derived from eye tracking only confirmed the first hypothesis. This hypothesis was confirmed by all the relevant indicators: gaze time, average fixation duration and pupil dilation. The second hypothesis that L2 translation tasks requires allocation of more cognitive resources than L1 translation tasks has not been confirmed by all four indicators. The third hypothesis that source text processing requires more cognitive resources in L1 translation than in L2 translation and the fourth hypothesis that target text processing requires more cognitive effort in L2 translation than L1 translation were not confirmed. It seems that source text processing in L2 translation can be just as demanding as in L1 translation. The final hypothesis that non-professional translators allocate more cognitive resources for the same translation tasks than do the professionals was partially confirmed. One of the indicators, average fixation duration, indicated higher cognitive effort-related values for professionals.

Keywords: translation processes, eye tracking, cognitive resources, directionality

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Authors: Chithra A. V., Somoshree Datta, Sandeep Nithyanandan

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Sign Language Recognition (SLR) is the process of interpreting and translating sign language into spoken or written language using technological systems. It involves recognizing hand gestures, facial expressions, and body movements that makeup sign language communication. The primary goal of SLR is to facilitate communication between hearing- and speech-impaired communities and those who do not understand sign language. Due to the increased awareness and greater recognition of the rights and needs of the hearing- and speech-impaired community, sign language recognition has gained significant importance over the past 10 years. Technological advancements in the fields of Artificial Intelligence and Machine Learning have made it more practical and feasible to create accurate SLR systems. This paper presents a distinct approach to SLR by framing it as a video classification problem using Deep Learning (DL), whereby a combination of Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) has been used. This research targets the integration of sign language recognition into healthcare settings, aiming to improve communication between medical professionals and patients with hearing impairments. The spatial features from each video frame are extracted using a CNN, which captures essential elements such as hand shapes, movements, and facial expressions. These features are then fed into an RNN network that learns the temporal dependencies and patterns inherent in sign language sequences. The INCLUDE dataset has been enhanced with more videos from the healthcare domain and the model is evaluated on the same. Our model achieves 91% accuracy, representing state-of-the-art performance in this domain. The results highlight the effectiveness of treating SLR as a video classification task with the CNN-RNN architecture. This approach not only improves recognition accuracy but also offers a scalable solution for real-time SLR applications, significantly advancing the field of accessible communication technologies.

Keywords: sign language recognition, deep learning, convolution neural network, recurrent neural network

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Authors: Ese Urhie, Bosede Olopade, Muyiwa Oladosun, Henry Okodua

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In the past three and half decades, aside from the fact that the contribution of the industrial sector to gross domestic product in Nigeria has nose-dived, its performance has also been highly unstable. Investment funds needed to develop the industrial sector usually come from both internal and external sources. The internal sources include surplus generated within the industrial sector and surplus diverted from other sectors of the economy. It has been observed that due to the small size of the industrial sector in developing countries, very limited funds could be raised for further investment. External sources of funds which many currently industrialized and some ‘newly industrializing countries’ have benefited from including direct and indirect investment by foreign capitalists; foreign aid and loans; and investments by nationals living abroad. Foreign direct investment inflow in Nigeria has been declining since 2009 in both absolute and relative terms. High level of human capital has been identified as one of the crucial factors that explain the miraculous growth of the ‘Asian Tigers’. Its low level has also been identified as the major cause for the low level of FDI flow to Nigeria in particular and Africa in general. There has been positive, but slow improvement in human capital indicators in Nigeria in the past three decades. In spite of this, foreign direct investment inflow has not only been low; it has declined drastically in recent years. i) Why has the improvement in human capital in Nigeria failed to attract more FDI inflow? ii) To what extent does the level of human capital influence FDI inflow in Nigeria? iii) Is there a threshold of human capital stock that guarantees sustained inflow of FDI? iv) Does the quality of human capital matter? v) Does the influence of other (negative) factors outweigh the benefits of human capital? Using time series secondary data, a system of equations is employed to evaluate the effect of human capital on FDI inflow in Nigeria on one hand and the effect of FDI on the level of industrialization on the other. A weak relationship between human capital and FDI is expected, while a strong relationship between FDI and industrial growth is expected from the result.

Keywords: human capital, foreign direct investment, industrialization, gross domestic product

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Authors: Gift Chidi-Onwuta, Iwe Nkem Nkechinyere, Chikamadu Christabelle Chinyere

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The teaching of English is a resource-driven activity that requires rich resource-classroom settings for the delivery of effective lessons and the acquisition of interpersonal skills for integration in a target-language environment. However, throughout the world, English is often taught in low-resource classrooms. This paper is aimed to reveal the common problems associated with teaching English in low-resource environments and the prospects for teachers who found themselves in such undefined teaching settings. Self-structured and validated questionnaire in a closed-ended format, open question format and scaling format was administered to teachers across five countries: Nigeria, Cameroun, Iraq, Turkey, and Sudan. The study adopts situational language teaching theory (SLTT), which emphasizes a performance improvement imperative. This study inclines to this model because it maintains that learning must be fun and enjoyable like playing a favorite sport, just as in real life. Since teaching resources make learning engaging, we found this model apt for the current study. The perceptions of teachers about accessibility and functionality of teaching material resources, the nature of teaching outcomes in resource-less environments, their levels of involvement in improvisation and the prospects associated with resource limitations were sourced. Data were analysed using percentages and presented in frequency tables. Results: showed that a greater number of teachers across these nations do not have access to sufficient productive resource materials that can aid effective English language teaching. Teaching outcomes, from the findings, are affected by low material resources; however, results show certain advantages to teaching English with limited resources: flexibility and autonomy with students and creativity and innovation amongst teachers. Results further revealed group work, story, critical thinking strategy, flex, cardboards and flashcards, dictation and dramatization as common teaching strategies, as well as materials adopted by teachers to overcome low resource-related challenges in classrooms.

Keywords: teaching materials, low-resource environments, English language teaching, situational language theory

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