Search results for: quality of health care

Authors: Szymon Kuczynski, Krystian Liszka, Mariusz Laciak, Andrii Oliinyk, Adam Szurlej

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The history of gaseous fuel use in the motive power of vehicles dates back to the second half of the nineteenth century, and thus the beginnings of the automotive industry. The engines were powered by coal gas and became the prototype for internal combustion engines built so far. It can thus be considered that this construction gave rise to the automotive industry. As the socio-economic development advances, so does the number of motor vehicles. Although, due to technological progress in recent decades, the emissions generated by internal combustion engines of cars have been reduced, a sharp increase in the number of cars and the rapidly growing traffic are an important source of air pollution and a major cause of acoustic threat, in particular in large urban agglomerations. One of the solutions, in terms of reducing exhaust emissions and improving air quality, is a more extensive use of alternative fuels: CNG, LNG, electricity and hydrogen. In the case of electricity use for transport, it should be noted that the environmental outcome depends on the structure of electricity generation. The paper shows selected regulations affecting the use of alternative fuels for transport (including Directive 2014/94/EU) and its dynamics between 2000 and 2015 in Poland and selected EU countries. The paper also gives a focus on the impact of alternative fuels on the environment by comparing the volume of individual emissions (compared to the emissions from conventional fuels: petrol and diesel oil). Bearing in mind that the extent of various alternative fuel use is determined in first place by economic conditions, the article describes the price relationships between alternative and conventional fuels in Poland and selected EU countries. It is pointed out that although Poland has a wealth of experience in using methane alternative fuels for transport, one of the main barriers to their development in Poland is the extensive use of LPG. In addition, a poorly developed network of CNG stations in Poland, which does not allow easy transport, especially in the northern part of the country, is a serious problem to a further development of CNG use as fuel for transport. An interesting solution to this problem seems to be the use of home CNG filling stations: Home Refuelling Appliance (HRA, refuelling time 8-10 hours) and Home Refuelling Station (HRS, refuelling time 8-10 minutes). The team is working on HRA and HRS technologies. The article also highlights the impact of alternative fuel use on energy security by reducing reliance on imports of crude oil and petroleum products.

Keywords: alternative fuels, CNG (Compressed Natural Gas), CNG stations, LNG (Liquefied Natural Gas), NGVs (Natural Gas Vehicles), pollutant emissions

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Authors: Reira Kinoshita, Shin'ichi Ishimaru

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Vapochromism is a type of chromism in which the color of a substance changes when it is exposed to the vapor of volatile materials, and has been investigated for the application of chemical sensors for volatile organic compounds causing sick building syndrome and health hazards in workspaces. We synthesized intercalation compounds of 3,3',5,5'-tetramethylbenzidine (TMB), and tetrasilisicfluormica (TSFM) by the commonly used cation-exchange method with the cation ratio TMB²⁺/CEC of TSFM = 1.0, 2.0, 2.7 and 5.4 to investigate the vapochromism of these materials. The obtained samples were characterized by powder XRD, XRF, TG-DTA, N₂ adsorption, and SEM. Vapochromism was measured for each sample under a controlled atmosphere by a handy reflectance spectrometer directly from the outside of the glass sample tubes. The color was yellow for all specimens vacuum-dried at 50 °C, but it turned green under H₂O vapor exposure for the samples with TMB²⁺/CEC = 2.0, 2.7, and 5.4 and blue under acetonitrile vapor for all cation ratios. Especially the sample TMB²⁺/CEC = 2.0 showed clear chromism both for water and acetonitrile. On the other hand, no clear color change was observed for vapors of alcohols, acetone, and non-polar solvents. From these results, this material can be expected to apply for easy detection of humidity and acetonitrile vapor in the environment.

Keywords: chemical sensor, intercalation compound, tetramethylbenzidine, tetrasilisicfluormica, vapochromism, volatile organic compounds

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Authors: Rangika Perera, Shyamani Hettiarachchi, Fran Hagstrom

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Dyslexia is the most common reading reading-related difficulty among the school school-aged population and currently, 5-10% are showing the features of dyslexia in Sri Lanka. As there is an insufficient number of speech and language pathologists in the country and few speech and language pathologists working in government mainstream school settings, these children who are at risk of dyslexia are not receiving enough quality early intervention services to develop their reading skills. As teachers are the key professionals who are directly working with these children, using them as the primary facilitators to improve their reading skills will be the most effective approach. This study aimed to identify the efficacy of a two and half a day of intensive training provided to fifteen mainstream government school teachers of grade two classes. The goal of the training was to enhance their knowledge of dyslexia and provide full classroom skills training that could be used to support the development of the students’ reading competencies. A closed closed-ended multiple choice questionnaire was given to these teachers pre and -post-training to measure teachers’ knowledge of dyslexia, the areas in which these children needed additional support, and the best strategies to facilitate reading competencies. The data revealed that the teachers’ knowledge in all areas was significantly poorer prior to the training and that there was a clear improvement in all areas after the training. The gain in target areas of teaching skills selected to improve the reading skills of children was evaluated through peer feedback. Teachers were assigned to three groups and expected to model how they were going to introduce the skills in recommended areas using researcher developed, validated and reliability reliability-tested materials and the strategies which were introduced during the training within the given tasks. Peers and the primary investigator rated teachers’ performances and gave feedback on organizational skills, presentation skills of materials, clarity of instruction, and appropriateness of vocabulary. After modifying their skills according to the feedback the teachers received, they were expected to modify and represent the same tasks to the group the following day. Their skills were re-evaluated by the peers and primary investigator using the same rubrics to measure the improvement. The findings revealed a significant improvement in their teaching skills development. The data analysis of both knowledge and skills gains of the teachers was carried out using quantitative descriptive data analysis. The overall findings of the study yielded promising results that support intensive training as a method for improving teachers’ knowledge and teaching skill development for use with children in a whole class intervention setting who are at risk of dyslexia.

Keywords: Dyslexia, knowledge, teaching skills, training program

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Authors: Habtamu Abera Goshu, Ping Yan

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Copy number variation (CNV) is a significant marker of the genetic and phenotypic diversity among individuals that accounts for complex quantitative traits of phenotype and diseases via modulating gene dosage, position effects, alteration of downstream pathways, modification of chromosome structure, and position within the nucleus and disrupting coding regions in the genome. Associating copy number variations (CNVs) with growth and gene expression are a powerful approach for identifying genomic characteristics that contribute to phenotypic and genotypic variation. A previous study using next-generation sequencing illustrated that the choline kinase beta (CHKB), Krüpple-like factor 6 (KLF6), glypican 1(GPC1), and cholinergic receptor muscarinic 3 (CHRM3) genes reside within copy number variable regions (CNVRs) of yak populations that overlap with quantitative trait loci (QTLs) of meat quality and growth. As a result, this research aimed to determine the association of CNVs of the KLF6, CHKB, GPC1, and CHRM3 genes with growth traits in the Datong yak breed. The association between the CNV types of the KLF6, CHKB, GPC1, and CHRM3 genes and the growth traits in the Datong yak breed was determined by one-way analysis of variance (ANOVA) using SPSS software. The CNV types were classified as a loss (a copy number of 0 or 1), gain (a copy number >2), and normal (a copy number of 2) relative to the reference gene, BTF3 in the 387 individuals of Datong yak. These results indicated that the normal CNV types of the CHKB and GPC1 genes were significantly (P<0.05) associated with high body length, height and weight, and chest girth in six-month-old and five-year-old Datong yaks. On the other hand, the loss CNV types of the KLF6 gene is significantly (P<0.05) associated with body weight and length and chest girth at six-month-old and five-year-old Datong yaks. In the contrary, the gain CNV type of the CHRM3 gene is highly (P<0.05) associated with body weight, length, height, and chest girth in six-month-old and five-year-old. This work provides the first observation of the biological role of CNVs of the CHKB, KLF6, GPC1, and CHRM3 genes in the Datong yak breed and might, therefore, provide a novel opportunity to utilize data on CNVs in designing molecular markers for the selection of animal breeding programs for larger populations of various yak breeds. Therefore, we hypothesized that this study provided inclusive information on the application of CNVs of the CHKB, KLF6, GPC1, and CHRM3 genes in growth traits in Datong yaks and its possible function in bovine species.

Keywords: Copy number variation, growth traits, yak, genes

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Authors: Steven Hidalgo, Patricio Neumann

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The growth of societies has increased the consumption of raw materials and food obtained from nature. This has influenced the services offered by ecosystems to humans, mainly supply and regulation services. One of the indicators used to evaluate these services is Net Primary Productivity (NPP), which is understood as the energy stored in the form of biomass by primary organisms through the process of photosynthesis and respiration. The variation of NPP by defined area produces changes in the properties of terrestrial and aquatic ecosystems, which alter factors such as biodiversity, nutrient cycling, carbon storage and water quality. The analysis of NPP to evaluate variations in ecosystem services includes harvested NPP (understood as provisioning services), which is the raw material from agricultural systems used by humans as a source of energy and food, and the remaining NPP (expressed as a regulating service) or the amount of biomass that remains in ecosystems after the harvesting process, which is mainly related to factors such as biodiversity. Given that agriculture is a fundamental pillar of Chile's integral development, the purpose of this study is to evaluate provisioning and regulating ecosystem services in the agricultural sector, specifically in cereal production, in the communes of the central-southern regions of Chile through a conceptual framework based on the quantification of the fraction of Human Appropriation of Net Primary Productivity (HANPP) and the fraction remaining in the ecosystems (NPP remaining). A total of 161 communes were analyzed in the regions of O'Higgins, Maule, Ñuble, Bio-Bío, La Araucanía and Los Lagos, which are characterized by having the largest areas planted with cereals. It was observed that the region of La Araucanía produces the greatest amount of dry matter, understood as provisioning service, where Victoria is the commune with the highest cereal production in the country. In addition, the maximum value of HANPP was in the O'Higgins region, highlighting the communes of Coltauco, Quinta de Tilcoco, Placilla and Rengo. On the other hand, the communes of Futrono, Pinto, Lago Ranco and Pemuco, whose cereal production was important during the study, had the highest values of remaining NPP as a regulating service. Finally, an inverse correlation was observed between the provisioning and regulating ecosystem services, i.e., the higher the cereal or dry matter production in a defined area, the lower the net primary production remaining in the ecosystems. Based on this study, future research will focus on the evaluation of ecosystem services associated with other crops, such as forestry plantations, whose activity is an important part of the country's productive sector.

Keywords: provisioning services, regulating services, net primary productivity, agriculture

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Authors: Apinya Mungaomklang, Natakamol Lookkham

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The purpose of this research is to study the characteristics of the graduates based on Thailand Qualification Framework (TQF) of the Faculty of Industrial Technology, Suan Sunandha Rajabhat University. The population of the research was employers/entrepreneurs/supervisors of students who were doing Professional Experiences course in their respective organizations during semester 1/2012. Data were collected during the month of September 2012 from the total number of 100 people. The tool used in this research was a questionnaire developed by the research team. Data were analyzed using percentage, mean and standard deviation using a computer program. The results showed that most of the surveyed organizations were private companies. The program with most students doing Professional Experiences course was Safety Technology and Occupational Health. The nature of work that most students did was associated with the document. Employers/ entrepreneurs/employers’ opinions on the characteristics of the graduates based on TQF received high scores. Cognitive skills received the highest score, followed by interpersonal relationships and responsibilities, ethics and moral, numerical analysis skills, communication and information technology skills, and knowledge, respectively.

Keywords: graduates characteristics, Thailand Qualification Framework, employers, entrepreneurs

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Authors: Adel Fatima Zohra, Guendouz Abdelkader

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The solitary sector seems to appear nowadays as a third sector along the private and public ones, because of their ineptitude to take in charge the social exigency of the society regarding the lack in their local assets and the weakness of their financial institutions. The role of this sector is promoting a set of activities in the field of the charity, without aiming neither the individual profit nor a power practice. With the rise in the need of domestic resources, it is possible to count on the Zakat funding to realize some investment projects in order to develop the local society in many sectors as health, agriculture … etc. In the Islamic financial system, the Zakat is likely one of the most important instruments in financing the local development with the respect of the “Charia” rules: the amount of the Zakat is 2.5% of a wealth equivalent of each 85 gr of gold possessed since one year at least. In Algeria a fund of Zakat, was created since 2003 as an alternative to the public finding of development. This fund is a religious and social institution under the supervision of the ministry of religious affairs. This supervision covers two tasks: the first is traditional witch concern the distribution and the forwarding of the zakat to the poor people, and the second is modern concerning the financing of microcredits in the aim to enhance social and economic development. In this paper, we try to highlight the main role of the Zakat fund and its impact on the both social and economic development in Algeria.

Keywords: dogmatic instrument, solidary sector, zakat fund, micro project

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Authors: Dongping Fang, Lian Duan, Xiaojing Yuan, Mike Xu, Allyn Klunder, Kevin Tan, Suiting Cao, Yeqing Ji

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Accurate prediction of a medical condition with straight clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still, to a certain degree, suspicious about the model's accuracy and interpretability. This paper presents an innovative hierarchical attention deep learning model to achieve good prediction and clear interpretability that can be easily understood by medical professionals. This deep learning model uses a hierarchical attention structure that matches naturally with the medical history data structure and reflects the member’s encounter (date of service) sequence. The model attention structure consists of 3 levels: (1) attention on the medical code types (diagnosis codes, procedure codes, lab test results, and prescription drugs), (2) attention on the sequential medical encounters within a type, (3) attention on the medical codes within an encounter and type. This model is applied to predict the occurrence of stage 3 chronic kidney disease (CKD3), using three years’ medical history of Medicare Advantage (MA) members from a top health insurance company. The model takes members’ medical events, both claims and electronic medical record (EMR) data, as input, makes a prediction of CKD3 and calculates the contribution from individual events to the predicted outcome. The model outcome can be easily explained with the clinical evidence identified by the model algorithm. Here are examples: Member A had 36 medical encounters in the past three years: multiple office visits, lab tests and medications. The model predicts member A has a high risk of CKD3 with the following well-contributed clinical events - multiple high ‘Creatinine in Serum or Plasma’ tests and multiple low kidneys functioning ‘Glomerular filtration rate’ tests. Among the abnormal lab tests, more recent results contributed more to the prediction. The model also indicates regular office visits, no abnormal findings of medical examinations, and taking proper medications decreased the CKD3 risk. Member B had 104 medical encounters in the past 3 years and was predicted to have a low risk of CKD3, because the model didn’t identify diagnoses, procedures, or medications related to kidney disease, and many lab test results, including ‘Glomerular filtration rate’ were within the normal range. The model accurately predicts members A and B and provides interpretable clinical evidence that is validated by clinicians. Without extra effort, the interpretation is generated directly from the model and presented together with the occurrence date. Our model uses the medical data in its most raw format without any further data aggregation, transformation, or mapping. This greatly simplifies the data preparation process, mitigates the chance for error and eliminates post-modeling work needed for traditional model explanation. To our knowledge, this is the first paper on an interpretable deep-learning model using a 3-level attention structure, sourcing both EMR and claim data, including all 4 types of medical data, on the entire Medicare population of a big insurance company, and more importantly, directly generating model interpretation to support user decision. In the future, we plan to enrich the model input by adding patients’ demographics and information from free-texted physician notes.

Keywords: deep learning, interpretability, attention, big data, medical conditions

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Authors: Johannes Günther

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Time Sensitive Networking (TSN), standardized in the IEEE 802.1 standard, has been lent increasing attention in the context of mission critical systems. Such mission critical systems, e.g., in the automotive domain, aviation, industrial, and smart factory domain, are responsible for coordinating complex functionalities in real time. In many of these contexts, a reliable data exchange fulfilling hard time constraints and quality of service (QoS) conditions is of critical importance. TSN standards are able to provide guarantees for deterministic communication behaviour, which is in contrast to common best-effort approaches. Therefore, the superior QoS guarantees of TSN may aid in the development of new technologies, which rely on low latencies and specific bandwidth demands being fulfilled. TSN extends existing Ethernet protocols with numerous standards, providing means for synchronization, management, and overall real-time focussed capabilities. These additional QoS guarantees, as well as management mechanisms, lead to an increased attack surface for potential malicious attackers. As TSN guarantees certain deadlines for priority traffic, an attacker may degrade the QoS by delaying a packet beyond its deadline or even execute a denial of service (DoS) attack if the delays lead to packets being dropped. However, thus far, security concerns have not played a major role in the design of such standards. Thus, while TSN does provide valuable additional characteristics to existing common Ethernet protocols, it leads to new attack vectors on networks and allows for a range of potential attacks. One answer to these security risks is to deploy defense mechanisms according to a moving target defense (MTD) strategy. The core idea relies on the reduction of the attackers' knowledge about the network. Typically, mission-critical systems suffer from an asymmetric disadvantage. DoS or QoS-degradation attacks may be preceded by long periods of reconnaissance, during which the attacker may learn about the network topology, its characteristics, traffic patterns, priorities, bandwidth demands, periodic characteristics on links and switches, and so on. Here, we implemented and tested several MTD-like defense strategies against different attacker models of varying capabilities and budgets, as well as collaborative attacks of multiple attackers within a network, all within the context of TSN networks. We modelled the networks and tested our defense strategies on an OMNET++ testbench, with networks of different sizes and topologies, ranging from a couple dozen hosts and switches to significantly larger set-ups.

Keywords: network security, time sensitive networking, moving target defense, cyber security

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Authors: Chandragouda R. Patil, K. S. Jagadeesh, S. D. Kalolgi

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Biofertilizers containing live microbial cells can mobilize one or more nutrients to plants when applied to either seed or rhizosphere. They form an integral part of nutrient management strategies for sustainable production of agricultural crops. Annually, about 22 tons of lignite-based biofertilizers are being produced and supplied to farmers at the Institute of Organic Farming, University of Agricultural Sciences, Dharwad, Karnataka state India. Although carrier based biofertilizers are common, they have shorter shelf life, poor quality, high contamination, unpredictable field performance and high cost of solid carriers. Hence, liquid formulations are being developed to increase their efficacy and broaden field applicability. An attempt was made to develop liquid formulation of strains of Rhizobium NC-92 (Groundnut), Azospirillum ACD15 both nitrogen-fixing biofertilizers and Pseudomonas striata an efficient P-solubilizing bacteria (PSB). Different concentration of amendments such as additives (glycerol and polyethylene glycol), adjuvants (carboxyl methyl cellulose), gum arabica (GA), surfactant (polysorbate) and trehalose specifically for Azospirillum were found essential. Combinations of formulations of Rhizobium and PSB for groundnut and Azospirillum and PSB for maize were evaluated under field conditions to determine the optimum level of inoculum required. Each biofertilizer strain was inoculated at the rate of 2, 4, 8 ml per kg of seeds and the efficacy of each formulation both individually and in combinations was evaluated against the lignite-based formulation at the rate of 20 g each per kg seeds and a un-inoculated set was included to compare the inoculation effect. The field experiment had 17 treatments in three replicates and the best level of inoculum was decided based on net returns and cost: benefit ratio. In peanut, the combination of 4 ml of Rhizobium and 2 ml of PSB resulted in the highest net returns and higher cost to benefit ratio of 1:2.98 followed by treatment with a combination of 2 ml per kg each of Rhizobium and PSB with a B;C ratio of 1:2.84. The benefits in terms of net returns were to the extent of 16 percent due to inoculation with lignite based formulations while it was up to 48 percent due to the best combination of liquid biofertilizers. In maize combination of liquid formulations consisting of 4 ml of Azospirillum and 2 ml of PSB resulted in the highest net returns; about 53 percent higher than the un-inoculated control and 20 percent higher than the treatment with lignite based formulation. In both the crops inoculation with lignite based formulations significantly increased the net returns over un-inoculated control while levels higher or lesser than 4 ml of Rhizobium and Azospirillum and higher or lesser than 2 ml of PSB were not economical and hence not optimal for these two crops.

Keywords: Rhizobium, Azospirillum, phosphate solubilizing bacteria, liquid formulation, benefit-cost ratio

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Authors: Rawan K. Al-Duaij, Salem A. Al-Salem

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Projects, the unique and temporary process of achieving a set of requirements have always been challenging; Planning the schedule and budget, managing the resources and risks are mostly driven by a similar past experience or the technical consultations of experts in the matter. With that complexity of Projects in Scope, Time, and execution environment, Adjustment Orders are tools to reflect changes to the original project parameters after Contract signature. Adjustment Orders are the official/legal amendments to the terms and conditions of a live Contract. Reasons for issuing Adjustment Orders arise from changes in Contract scope, technical requirement and specification resulting in scope addition, deletion, or alteration. It can be as well a combination of most of these parameters resulting in an increase or decrease in time and/or cost. Most business leaders (handling projects in the interest of the owner) refrain from using Adjustment Orders considering their main objectives of staying within budget and on schedule. Success in managing the changes results in uninterrupted execution and agreed project costs as well as schedule. Nevertheless, this is not always practically achievable. In this paper, a detailed study through utilizing Industrial Engineering & Systems Management tools such as Six Sigma, Data Analysis, and Quality Control were implemented on the organization’s five years records of the issued Adjustment Orders in order to investigate their prevalence, and time and cost impact. The analysis outcome revealed and helped to identify and categorize the predominant causations with the highest impacts, which were considered most in recommending the corrective measures to reach the objective of minimizing the Adjustment Orders impacts. Data analysis demonstrated no specific trend in the AO frequency in past five years; however, time impact is more than the cost impact. Although Adjustment Orders might never be avoidable; this analysis offers’ some insight to the procedural gaps, and where it is highly impacting the organization. Possible solutions are concluded such as improving project handling team’s coordination and communication, utilizing a blanket service contract, and modifying the projects gate system procedures to minimize the possibility of having similar struggles in future. Projects in the Oil and Gas sector are always evolving and demand a certain amount of flexibility to sustain the goals of the field. As it will be demonstrated, the uncertainty of project parameters, in adequate project definition, operational constraints and stringent procedures are main factors resulting in the need for Adjustment Orders and accordingly the recommendation will be to address that challenge.

Keywords: adjustment orders, data analysis, oil and gas sector, systems management

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Authors: Yong Zhao, Jian He, Cheng Zhang

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Cardiovascular diseases caused by hypertension are extremely threatening to human health, and early diagnosis of hypertension can save a large number of lives. Traditional hypertension detection methods require special equipment and are difficult to detect continuous blood pressure changes. In this regard, this paper first analyzes the principle of heart rate variability (HRV) and introduces sliding window and power spectral density (PSD) to analyze the time domain features and frequency domain features of HRV, and secondly, designs an HRV-based hypertension prediction network by combining Resnet, attention mechanism, and multilayer perceptron, which extracts the frequency domain through the improved ResNet18 features through a modified ResNet18, its fusion with time-domain features through an attention mechanism, and the auxiliary prediction of hypertension through a multilayer perceptron. Finally, the network was trained and tested using the publicly available SHAREE dataset on PhysioNet, and the test results showed that this network achieved 92.06% prediction accuracy for hypertension and outperformed K Near Neighbor(KNN), Bayes, Logistic, and traditional Convolutional Neural Network(CNN) models in prediction performance.

Keywords: feature extraction, heart rate variability, hypertension, residual networks

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Authors: Karl Peltzer, Supa Pengpid

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Introduction: The aim of this study was to assess suicidal ideation and associated factors in school-going adolescents in the Association of Southeast Asian Nations (ASEAN) Member States. Methods: The analysis included 30284 school children aged 13-15 years from seven ASEAN that participated in the cross-sectional Global School-based Student Health Survey (GSHS) between 2007 and 2013. Results: The overall prevalence of suicidal ideation across seven ASEAN countries (excluding Brunei) was 12.3%, significantly higher in girls (15.1%) than boys (9.3%). Among eight ASEAN countries with the highest prevalence of suicidal ideation was in the Philippines (17.0%) and Vietnam (16.9%) and the lowest in Myanmar (1.1%) and Indonesia (4.2%). In multivariate logistic regression analysis, female gender, older age (14 or 15 years), living in a low income or lower middle income country, having no friends, loneliness, bullying victimization, having been in a physical fight in the past 12 months, lack of parental or guardian support, tobacco use and having a history of ever got drunk were associated with suicidal ideatiion. Conclusion: Different rates of suicidal ideation were observed in ASEAN member states. Several risk factors for suicidal ideation were identified which can help guide preventive efforts.

Keywords: adolesents, ASEAN, correlates, suicidal behaviour

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Authors: Malinda Sabrina, Khoerul Anwar

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Railway noise generated by pass-by train has been described as a form of environmental pollutants especially for the residential area near the railway. Many studies have shown, that environmental noise particularly transportation noise has negative effects on people which resulting in annoyance and specific health problems such as cardiovascular disease, cognitive impairment and sleep disturbance. Therefore, various attempts are made to reduce the noise. One method of reducing such noise to acceptable noise levels is to build acoustically barrier walls. The objective of this study was to review the method of reducing railway noise and obtain the preliminary design of the acoustics barrier on the edge of railway tracks close to the residential area. The design of this barrier is using the Maekawa's method. Measurements have been performed in residential areas around the railroads in the Karawang - Indonesia with the absence of an acoustical barrier. From the observation, it was found that the railway was passed by five trains within thirty minutes. With the limited distance between the railway tracks and the location of the residential area as well as the street of residents, then it was obtained that a reduction in sound pressure level is 25 dBA. Maximum sound pressure level obtained is 86.9 dBA then by setting the barrier as high as 4 m at a distance, 2.5 m from the railway, the noise level received by residents in the settlement around the railway line becomes 61.9 dBA.

Keywords: acoustics barrier, Maekawa's method, noise attenuation, railway noise

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Authors: Wendi Dunham, Kimberly Floyd

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The constructivist approach to learning is a theoretical orientation that posits that individuals create their own understanding and knowledge of the world through their experiences and interactions. This approach emphasizes that learning is an active process and that individuals are not passive recipients when constructing their understanding of their world. When used concurrently with trauma-informed practices, a constructivist approach can inform the development of a framework for students and teachers that supports their social, emotional, and mental health in addition to enabling academic success. This framework can be applied to teachers and students. When applied to teachers, it can be used to achieve purposeful coping mechanisms through restorative justice and dispositional mindfulness. When applied to students, the framework can implement proactive, student-based practices such as Response to Intervention (RtI) and the 4 Rs to connect resiliency and intervention to academic learning. Using a constructivist, trauma-informed framework can provide students with a greater sense of control and agency over their trauma experiences and impart confidence in achieving school success.

Keywords: trauma, trauma informed practices in education, constructivist theory framework, school responses to trauma, trauma informed supports for teachers, trauma informed strategies for students, restorative justice, mindfulness, response to intervention, the 4 R's, resiliency

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Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

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Authors: Roberta Martino, Viviana Ventre

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From a theoretical point of view, the relationship between the risk associated with an investment and the expected value are directly proportional, in the sense that the market allows a greater result to those who are willing to take a greater risk. However, empirical evidence proves that this relationship is distorted in the minds of investors and is perceived exactly the opposite. To deepen and understand the discrepancy between the actual actions of the investor and the theoretical predictions, this paper analyzes the essential parameters used for the valuation of financial assets with greater attention to two elements: probability and the passage of time. Although these may seem at first glance to be two distinct elements, they are closely related. In particular, the error in the theoretical description of the relationship between risk and return lies in the failure to consider the impatience that is generated in the decision-maker when events that have not yet happened occur in the decision-making context. In this context, probability loses its objective meaning and in relation to the psychological aspects of the investor, it can only be understood as the degree of confidence that the investor has in the occurrence or non-occurrence of an event. Moreover, the concept of objective probability does not consider the inter-temporality that characterizes financial activities and does not consider the condition of limited cognitive capacity of the decision maker. Cognitive psychology has made it possible to understand that the mind acts with a compromise between quality and effort when faced with very complex choices. To evaluate an event that has not yet happened, it is necessary to imagine that it happens in your head. This projection into the future requires a cognitive effort and is what differentiates choices under conditions of risk and choices under conditions of uncertainty. In fact, since the receipt of the outcome in choices under risk conditions is imminent, the mechanism of self-projection into the future is not necessary to imagine the consequence of the choice and the decision makers dwell on the objective analysis of possibilities. Financial activities, on the other hand, develop over time and the objective probability is too static to consider the anticipatory emotions that the self-projection mechanism generates in the investor. Assuming that uncertainty is inherent in valuations of events that have not yet occurred, the focus must shift from risk management to uncertainty management. Only in this way the intertemporal dimension of the decision-making environment and the haste generated by the financial market can be cautioned and considered. The work considers an extension of the prospectus theory with the temporal component with the aim of providing a description of the attitude towards risk with respect to the passage of time.

Keywords: impatience, risk aversion, subjective probability, uncertainty

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Authors: Jennifer Natalya Fink

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Since the racial reckoning of 2020, almost every major educational institution has incorporated diversity, equity, and inclusion (DEI) principles into its administrative, hiring, and pedagogical practices. Yet these DEI principles rarely incorporate explicit language or critical thinking about disability. Despite the fact that according to the World Health Organization, one in five people worldwide is disabled, making disabled people the larger minority group in the world, disability remains the neglected stepchild of DEI. Drawing on disability studies and crip theory frameworks, the underlying causes of this exclusion of disability from DEI, such as stigma, shame, invisible disabilities, institutionalization/segregation/delineation from family, and competing models and definitions of disability are examined. This paper explores both the ideological and practical shifts necessary to include disability in university DEI initiatives. It offers positive examples as well as conceptual frameworks such as 'divers ability' for so doing. Using Georgetown University’s 2020-2022 DEI initiatives as a case study, this paper describes how curricular infusion, accessibility, identity, community, and diversity administration infused one university’s DEI initiatives with concrete disability-inclusive measures. It concludes with a consideration of how the very framework of DEI itself might be challenged and transformed if disability were to be included.

Keywords: diversity, equity, inclusion, disability, crip theory, accessibility

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Authors: Ana Julia C. Kfouri

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A prerequisite of any building design is to provide security to the users, taking the climate and its physical and physical-geometrical variables into account. It is also important to highlight the relevance of the right material elements, which arise between the person and the agent, and must provide improved thermal comfort conditions and low environmental impact. Furthermore, technology is constantly advancing, as well as computational simulations for projects, and they should be used to develop sustainable building and to provide higher quality of life for its users. In relation to comfort, the more satisfied the building users are, the better their intellectual performance will be. Based on that, the study of thermal comfort in educational buildings is of relative relevance, since the thermal characteristics in these environments are of vital importance to all users. Moreover, educational buildings are large constructions and when they are poorly planned and executed they have negative impacts to the surrounding environment, as well as to the user satisfaction, throughout its whole life cycle. In this line of thought, to evaluate university classroom conditions, it was accomplished a detailed case study on the thermal comfort situation at Federal University of Parana (UFPR). The main goal of the study is to perform a thermal analysis in three classrooms at UFPR, in order to address the subjective and physical variables that influence thermal comfort inside the classroom. For the assessment of the subjective components, a questionnaire was applied in order to evaluate the reference for the local thermal conditions. Regarding the physical variables, it was carried out on-site measurements, which consist of performing measurements of air temperature and air humidity, both inside and outside the building, as well as meteorological variables, such as wind speed and direction, solar radiation and rainfall, collected from a weather station. Then, a computer simulation based on results from the EnergyPlus software to reproduce air temperature and air humidity values of the three classrooms studied was conducted. The EnergyPlus outputs were analyzed and compared with the on-site measurement results to be possible to come out with a conclusion related to the local thermal conditions. The methodological approach included in the study allowed a distinct perspective in an educational building to better understand the classroom thermal performance, as well as the reason of such behavior. Finally, the study induces a reflection about the importance of thermal comfort for educational buildings and propose thermal alternatives for future projects, as well as a discussion about the significant impact of using computer simulation on engineering solutions, in order to improve the thermal performance of UFPR’s buildings.

Keywords: computer simulation, educational buildings, EnergyPlus, humidity, temperature, thermal comfort

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Authors: Silvia Zanazzi

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Artificial intelligence (AI) has become an integral part of our world, transitioning from scientific exploration to practical applications that impact daily life. The emergence of generative AI is reshaping education, prompting new questions about the role of teachers, the nature of learning, and the overall purpose of schooling. While AI offers the potential for optimizing teaching and learning processes, concerns about discrimination and bias arising from training data and algorithmic decisions persist. There is a risk of a disconnect between the rapid development of AI and the goals of building inclusive educational environments. The prevailing discourse on AI in education often prioritizes efficiency and individual skill acquisition. This narrow focus can undermine the importance of collaborative learning and shared experiences. A growing body of research challenges this perspective, advocating for AI that enhances, rather than replaces, human interaction in education. This study aims to examine the relationship between AI and education critically. Reviewing existing research will identify both AI implementation’s potential benefits and risks. The goal is to develop a framework that supports the ethical and effective integration of AI into education, ensuring it serves the needs of all learners. The theoretical reflection will be developed based on a review of national and international scientific literature on artificial intelligence in education. The primary objective is to curate a selection of critical contributions from diverse disciplinary perspectives and/or an inter- and transdisciplinary viewpoint, providing a state-of-the-art overview and a critical analysis of potential future developments. Subsequently, the thematic analysis of these contributions will enable the creation of a framework for understanding and critically analyzing the role of artificial intelligence in schools and education, highlighting promising directions and potential pitfalls. The expected results are (1) a classification of the cognitive biases present in representations of AI in education and the associated risks and (2) a categorization of potentially beneficial interactions between AI applications and teaching and learning processes, including those already in use or under development. While not exhaustive, the proposed framework will serve as a guide for critically exploring the complexity of AI in education. It will help to reframe dystopian visions often associated with technology and facilitate discussions on fostering synergies that balance the ‘dream’ of quality education for all with the realities of AI implementation. The discourse on artificial intelligence in education, highlighting reductionist models rooted in fragmented and utilitarian views of knowledge, has the merit of stimulating the construction of alternative perspectives that can ‘return’ teaching and learning to education, human growth, and the well-being of individuals and communities.

Keywords: education, artificial intelligence, teaching, learning

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Authors: Kim Nolte, Ben J. M. Steyn, Pieter E. Krüger, Lizelle Fletcher

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Objective: The primary aim of this research was to determine the attitudes, beliefs and knowledge of talented young South African athletes regarding prohibited performance-enhancing drugs (PEDs) and anti-doping rules and regulations. Methods: This was a survey study and a quantitative research approach was used. South African TuksSport academy athletes at the High Performance Centre, University of Pretoria and competitive high school athletes at four private high schools in Gauteng completed the survey. A self-determined structured questionnaire was used to establish the attitudes, beliefs and knowledge of the athletes. Results: A total of 346 (208 males, 138 females) athletes, age (mean ± SD) 16.9 ±1.41 years participated in the survey. According to this survey, 3.9% of the athletes in this survey admitted to be using a prohibited PED and more than 14% of the athletes said they would consider using a prohibited PED if they knew they would not get caught out. Ambition (46%) and emotional pressure (22.5%) was the primary reasons why the athletes would consider using prohibited PEDs. Even though coaches appear to be the main source of information (PEDs and anti-doping rules), only 42.1% of the athletes felt they were well informed. Conclusion: Controlling doping by means of testing is important. However, it is not sufficient and interventions should include psychosocial programmes planned and developed focusing on changing attitudes towards doping and doping culture, as well as the appropriate education specifically on the health risks of using PEDs.

Keywords: doping, anti-doping, attitudes, athletes and sport

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Authors: Shu-Hui Wen, Wei-Chuan Chang, Hsien-Chang Wu

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Background: Little is known about the benefits and risks of use of Chinese herbal medicine (CHM) in conditions related to hormone therapy (HT) use on the risk of ischemic stroke (IS). The aim of this study is to explore the risk of IS in menopausal women treated with HT and CHM. Materials and methods: A total of 32,441 menopausal women without surgical menopause aged 40- 65 years were selected from 2003 to 2010 using the 2-million random samples of the National Health Insurance Research Database in Taiwan. According to the medication usage of HT and CHM, we divided the current and recent users into two groups: an HT use-only group (n = 4,989) and an HT/CHM group (n = 9,265). Propensity-score matching samples (4,079 pairs) were further created to deal with confounding by indication. The adjusted hazard ratios (HR) of IS during HT or CHM treatment were estimated by the robust Cox proportional hazards model. Results: The incidence rate of IS in the HT/CHM group was significantly lower than in the HT group (4.5 vs. 12.8 per 1000 person-year, p < 0.001). Multivariate analysis results indicated that additional CHM use was significant with a lower risk of IS (HR = 0.3; 95% confidence interval, 0.21-0.43). Further subgroup analyses and sensitivity analyses had similar findings. Conclusion: We found that combined use of HT and CHM was associated with a lower risk for IS than HT use only. Further study is needed to examine possible mechanism underlying this association.

Keywords: Chinese herbal medicine, hormone therapy, ischemic stroke, menopause

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Authors: Rahul Warmoota, Aditya Bhardwaj, Steffy Angural, Monika Rana, Sunena Jassal, Neena Puri, Naveen Gupta

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Seafood processing generates large volumes of waste products such as skin, heads, tails, shells, scales, backbones, etc. Pollution due to conventional methods of seafood waste disposal causes negative implications on the environment, aquatic life, and human health. Moreover, these waste products can be used for the production of high-value products which are still untapped due to inappropriate management. Paenibacillus sp. AD is known to act on chitinolytic and proteinaceous waste and was explored for its potential to degrade various types of seafood waste in solid-state fermentation. Effective degradation of seafood waste generated from a variety of sources such as fish scales, crab shells, prawn shells, and a mixture of such wastes was observed. 30 to 40 percent degradation in terms of decrease in the mass was achieved. Along with the degradation, chitinolytic and proteolytic enzymes were produced, which can have various biotechnological applications. Apart from this, value-added products such as chitin oligosaccharides and peptides of various degrees of polymerization were also produced, which can be used for various therapeutic purposes. Results indicated that Paenibacillus sp. AD can be used for the development of a process for the infield degradation of seafood waste.

Keywords: chitin, chitin-oligosaccharides, chitinase, protease, biodegradation, crab shells, prawn shells, fish scales

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Authors: Davoud Maleki

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Today, education and investment in human capital is a long-term investment without which the economy will be stagnant Stayed. Higher education represents a type of investment in human resources by providing and improving knowledge, skills and Attitudes help economic development. Providing efficient human resources by increasing the efficiency and productivity of people and on the other hand with Expanding the boundaries of knowledge and technology and promoting technology such as the responsibility of training human resources and increasing productivity and efficiency in High specialized levels are the responsibility of universities. Therefore, the university plays an infrastructural role in economic development and growth because education by creating skills and expertise in people and improving their ability.In recent decades, Iran's higher education system has been faced with many problems, therefore, scholars have looked for it is to identify and validate the causal factors affecting the responsiveness and productivity of non-governmental universities. The data in the qualitative part is the result of semi-structured interviews with 25 senior and middle managers working in the units It was Islamic Azad University of Tehran province, which was selected by theoretical sampling method. In data analysis, stepwise method and Analytical techniques of Strauss and Corbin (1992) were used. After determining the central category (answering for the sake of the beneficiaries) and using it in order to bring the categories, expressions and ideas that express the relationships between the main categories and In the end, six main categories were identified as causal factors affecting the university's responsiveness and productivity.They are: 1- Scientism 2- Human resources 3- Creating motivation in the university 4- Development based on needs assessment 5- Teaching process and Learning 6- University quality evaluation. In order to validate the response model obtained from the qualitative stage, a questionnaire The questionnaire was prepared and the answers of 146 students of Master's degree and Doctorate of Islamic Azad University located in Tehran province were received. Quantitative data in the form of descriptive data analysis, first and second stage factor analysis using SPSS and Amos23 software were analyzed. The findings of the research indicated the relationship between the central category and the causal factors affecting the response The results of the model test in the quantitative stage confirmed the generality of the conceptual model.

Keywords: accountability, productivity, non-governmental, universities, foundation data theory

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Authors: Karel Šebesta, Jiří Žáček, Matuš Salva, Mohammad Housam

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Drivers of agricultural vehicles are exposed to continuous vibration caused by driving over rough terrain. The long-term effects of these vibrations could start with a decreased level of vigilance at work and could reach the level of several health problems. Therefore, eliminating the vibration to maximize the comfort of the driver is essential for better/longer performance. One of the modern damping systems, which can deal with this problem is the Semi-active (S/A) suspension system featuring a Magnetorheological (MR) damper. With this damper, the damping level can be adjusted using varying currents through the coil. Adjustments of the damping force can be carried out continuously based on the evaluated data (position and acceleration of seat) by the control algorithm. The advantage of this system is the wide dynamic range and the high speed of force response time. Compared to other S/A or active systems, the MR damper does not need as much electrical power, and the system is much simpler. This paper aims to prove the effectiveness of this damping system used in the tractor seat. The vibration testing stand was designed and manufactured specifically for this type of research, which is used to simulate vibrations with constant amplitude at variable frequency.

Keywords: magnetorheological damper, semi-active suspension, seat scissor mechanism, sky-hook

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Authors: Pellecchia M. T., Savarese G., Carpinelli L., Calabrese M.

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Introduction: Parkinson's disease (PD) is characterized by a progressive loss of autonomy which undoubtedly has a significant impact on the quality of life of caregivers, and parents are the main informal caregivers. Caring for a person with PD is associated with an increased risk of psychiatric morbidity and persistent anxiety-depressive distress. The aim of the study is to investigate the burden on caregivers of patients with PD, through the use of multidimensional scales and to identify their personological and environmental determinants. Methods: The study has been approved by the Ethic Committee of the University of Salerno and informed consent for participation to the study was obtained from patients and their caregivers. The study was conducted at the Neurology Department of the A.O.U. "San Giovanni di Dio and Ruggi D’Aragona" of Salerno between September 2020 and May 2021. Materials: The questionnaires used were: a) Caregiver Burden Inventory - CBI a questionnaire of 24 items that allow identifying five sub-categories of burden (objective, psychological, physical, social, emotional); b) Depression Anxiety Stress Scales Short Version - DASS-21 questionnaire consisting of 21 items and valid in examining three distinct but interrelated areas (depression, anxiety and stress); c) Family Strain Questionnaire Short Form - FSQ-SF is a questionnaire of 30 items grouped in areas of increasing psychological risk (OK, R, SR, U); d) Zarit Caregiver Burden Inventory - ZBI, consisting of 22 items based on the analysis of two main factors: personal stress and pressure related to his role; e) Life Satisfaction, a single item that aims to evaluate the degree of life satisfaction in a global way using a 0-100 Likert scale. Findings: N ° 29 caregivers (M age = 55.14, SD = 9.859; 69% F) participated in the study. 20.6% of the sample had severe and severe burden (CBI score = M = 26.31; SD = 22.43) and 13.8% of participants had moderate to severe burden (ZBI). The FSQ-SF highlighted a minority of caregivers who need psychological support, in some cases urgent (Area SR and Area U). The DASS-21 results show a prevalence of stress-related symptoms (M = 10.90, SD = 10.712) compared to anxiety (M = 7.52, SD = 10.752) and depression (M = 8, SD = 10.876). There are significant correlations between some specific variables and mean test scores: retired caregivers report higher ZBI scores (p = 0.423) and lower Life Satisfaction levels (p = -0.460) than working caregivers; years of schooling show a negative linear correlation with the ZBI score (p = -0.491). The T-Test indicates that caregivers of patients with cognitive impairment are at greater risk than those of patients without cognitive impairment. Conclusions: It knows the factors that affect the burden the most would allow for early recognition of risky situations and caregivers who would need adequate support.

Keywords: anxious-depressive axis, caregivers’ burden, Parkinson’ disease, psychological risks

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Authors: Vibha Devi, Shabina Khanam

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Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

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Authors: Praniil Nagaraj

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This paper proposes a method to collect homeless data using crowdsourcing and presents an approach to analyze the data, demonstrating its potential to strengthen existing and future policies aimed at promoting socio-economic equilibrium. This paper's contributions can be categorized into three main areas. Firstly, a unique method for collecting homeless data is introduced, utilizing a user-friendly smartphone app (currently available for Android). The app enables the general public to quickly record information about homeless individuals, including the number of people and details about their living conditions. The collected data, including date, time, and location, is anonymized and securely transmitted to the cloud. It is anticipated that an increasing number of users motivated to contribute to society will adopt the app, thus expanding the data collection efforts. Duplicate data is addressed through simple classification methods, and historical data is utilized to fill in missing information. The second contribution of this paper is the description of data analysis techniques applied to the collected data. By combining this new data with existing information, statistical regression analysis is employed to gain insights into various aspects, such as distinguishing between unsheltered and sheltered homeless populations, as well as examining their correlation with factors like unemployment rates, housing affordability, and labor demand. Initial data is collected in San Francisco, while pre-existing information is drawn from three cities: San Francisco, New York City, and Washington D.C., facilitating the conduction of simulations. The third contribution focuses on demonstrating the practical implications of the data processing results. The challenges faced by key stakeholders, including charitable organizations and local city governments, are taken into consideration. Two case studies are presented as examples. The first case study explores improving the efficiency of food and necessities distribution, as well as medical assistance, driven by charitable organizations. The second case study examines the correlation between micro-geographic budget expenditure by local city governments and homeless information to justify budget allocation and expenditures. The ultimate objective of this endeavor is to enable the continuous enhancement of the quality of life for the underprivileged. It is hoped that through increased crowdsourcing of data from the public, the Generosity Curve and the Need Curve will intersect, leading to a better world for all.

Keywords: crowdsourcing, homelessness, socio-economic policies, statistical analysis

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Authors: Juan-Pedro Rica-Peromingo

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Nowadays, corpus linguistics has become a key research methodology for Translation Studies, which broadens the scope of cross-linguistic studies. In the case of the study presented here, the approach used focuses on learners with little or no experience to study, at an early stage, general mistakes and errors, the correct or incorrect use of translation strategies, and to improve the translational competence of the students. Led by Sylviane Granger and Marie-Aude Lefer of the Centre for English Corpus Linguistics of the University of Louvain, the MUST corpus (MUltilingual Student Translation Corpus) is an international project which brings together partners from Europe and worldwide universities and connects Learner Corpus Research (LCR) and Translation Studies (TS). It aims to build a corpus of translations carried out by students including both direct (L2 > L1) an indirect (L1 > L2) translations, from a great variety of text types, genres, and registers in a wide variety of languages: audiovisual translations (including dubbing, subtitling for hearing population and for deaf population), scientific, humanistic, literary, economic and legal translation texts. This paper focuses on the work carried out by the Spanish team from the Complutense University (UCMA), which is part of the MUST project, and it describes the specific features of the corpus built by its members. All the texts used by UCMA are either direct or indirect translations between English and Spanish. Students’ profiles comprise translation trainees, foreign language students with a major in English, engineers studying EFL and MA students, all of them with different English levels (from B1 to C1); for some of the students, this would be their first experience with translation. The MUST corpus is searchable via Hypal4MUST, a web-based interface developed by Adam Obrusnik from Masaryk University (Czech Republic), which includes a translation-oriented annotation system (TAS). A distinctive feature of the interface is that it allows source texts and target texts to be aligned, so we can be able to observe and compare in detail both language structures and study translation strategies used by students. The initial data obtained point out the kind of difficulties encountered by the students and reveal the most frequent strategies implemented by the learners according to their level of English, their translation experience and the text genres. We have also found common errors in the graduate and postgraduate university students’ translations: transfer errors, lexical errors, grammatical errors, text-specific translation errors, and cultural-related errors have been identified. Analyzing all these parameters will provide more material to bring better solutions to improve the quality of teaching and the translations produced by the students.

Keywords: corpus studies, students’ corpus, the MUST corpus, translation studies

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Authors: M. Dabirinezhad, M. Bayat Pour, A. Dabirinejad

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In 2020, the technology was introduced to solve some of the deficiencies of direct digital radiology. SDDR is an invention that is capable of capturing dental images without human intervention, and it was invented by the authors of this paper. Adjusting the radiology wave dose is a part of the dentists, radiologists, and dental nurses’ tasks during the radiology photography process. In this paper, an improvement will be added to enable SDDR to set the suitable radiology wave dose according to the density and age of the patients automatically. The separate sensors will be included in the sensors’ package to use the ultrasonic wave to detect the density of the teeth and change the wave dose. It facilitates the process of dental photography in terms of time and enhances the accuracy of choosing the correct wave dose for each patient separately. Since the radiology waves are well known to trigger off other diseases such as cancer, choosing the most suitable wave dose can be helpful to decrease the side effect of that for human health. In other words, it decreases the exposure time for the patients. On the other hand, due to saving time, less energy will be consumed, and saving energy can be beneficial to decrease the environmental impact as well.

Keywords: dental direct digital imaging, environmental impacts, SDDR technology, wave dose

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