Search results for: Moshe Farhi

Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Lu Zhao, Nadir Farhi, Yeltsin Valero, Zoi Christoforou, Nadia Haddadou

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In this paper, a long short-term memory (LSTM) neural network model is proposed to replicate simultaneously car-following and lane-changing behaviors in road networks. By combining two kinds of LSTM layers and three input designs of the neural network, six variants of the LSTM model have been created. These models were trained and tested on the NGSIM 101 dataset, and the results were evaluated in terms of longitudinal speed and lateral position, respectively. Then, we compared the LSTM model with a classical car-following model (the intelligent driving model (IDM)) in the part of speed decision. In addition, the LSTM model is compared with a model using classical neural networks. After the comparison, the LSTM model demonstrates higher accuracy than the physical model IDM in terms of car-following behavior and displays better performance with regard to both car-following and lane-changing behavior compared to the classical neural network model.

Keywords: traffic modeling, neural networks, LSTM, car-following, lane-change

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Authors: Katherine Carl Payne, Moshe Dror

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The problem of minimum cost routing has been extensively explored in a variety of contexts. While there is a prevalence of routing applications based on least distance, time, and related attributes, exertion-based routing has remained relatively unexplored. In particular, the network structures traditionally used to construct minimum cost paths are not suited to representing exertion or finding paths of least exertion based on road gradient. In this paper, we introduce a topographical network or “topograph” that enables minimum cost routing based on the exertion metric on each arc in a given road network as it is related to changes in road gradient. We describe an algorithm for topograph construction and present the implementation of the topograph on a road network of the state of California with ~22 million nodes.

Keywords: topograph, RPE, routing, GIS

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Authors: Lu Zhao, Nadir Farhi, Zoi Christoforou, Nadia Haddadou

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The safety test of deploying intelligent connected vehicles (ICVs) on the road network is a critical challenge. Road traffic network simulation can be used to test the functionality of ICVs, which is not only time-saving and less energy-consuming but also can create scenarios with car collisions. However, the relationship between different human driver behaviors and the car-collision occurrences has been not understood clearly; meanwhile, the procedure of car-collisions generation in the traffic numerical simulators is not fully integrated. In this paper, we propose an approach to identify specific driver profiles from real driven data; then, we replicate them in numerical traffic simulations with the purpose of generating inter-vehicular collisions. We proposed three profiles: (i) 'aggressive': short time-headway, (ii) 'inattentive': long reaction time, and (iii) 'normal' with intermediate values of reaction time and time-headway. These three driver profiles are extracted from the NGSIM dataset and simulated using the intelligent driver model (IDM), with an extension of reaction time. At last, the generation of inter-vehicular collisions is performed by varying the percentages of different profiles.

Keywords: vehicular collisions, human driving behavior, traffic modeling, car-following models, microscopic traffic simulation

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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Tires are extremely challenging to recycle due to the available chemically cross-linked polymer which constitutes their nature and therefore, they are neither fusible nor soluble and consequently, cannot be remoulded into other shapes without serious degradation. Pyrolysis of tires produces four valuable products namely; char, steel, tire pyrolytic oil (TPO) and non-condensable gases. TPO has been reported to have similar properties to commercial diesel fuel (CDF). In this study, distillation of TPO was carried out in a batch distillation column and biodiesel was produced from waste cooking oil. FTIR analysis proved that TPO can be used as a fuel due to the available compounds detected and GC analysis displayed 94% biodiesel concentration from waste cooking oil. Different blends of TPO/biodiesel, TPO/CDF and biodiesel/CDF were prepared at different ratios. Fuel properties such as viscosity, density, flash point, and calorific value were studied. Viscosity and density models were also studied to measure the quality of different blends.

Keywords: biodiesel, distillation, pyrolysis, tire

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The adsorptive ability of different carbon materials, tire char (TC), demineralized tire char (DTC), activated tire char (ATC) and Aldrich supplied commercial activated carbon (CAC) was studied for desulfurization of tire pyrolytic oil (TPO). TPO with an initial sulfur content of 7767.7 ppmw was used in this present study. Preparation of ATC was achieved by chemical treatment of raw TC using a potassium hydroxide (KOH) solution and subsequent activation at 800°C in the presence of nitrogen. The thermal behavior of TC, surface microstructure, and the surface functional groups of the carbon materials was investigated using TGA, SEM, and FTIR, respectively. Adsorptive desulfurization of TPO using the carbon materials was performed and they performed in the order of CAC>ATC>DTC>TC. Adsorption kinetics were studied, and pseudo-first order kinetic model displayed a better fit compared to pseudo-second order model. For isotherm studies, the Freundlich isotherm model fitted to the equilibrium data better than the Langmuir isotherm model.

Keywords: ATC, desulfurization, pyrolysis, tire, TPO

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng, Itumeleng Kohitlhetse

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The accelerating requirement to reach 0% sulfur content in liquid fuels demand researchers to seek efficient alternative technologies to challenge the predicament. In this current study, the adsorption capabilities of modified Cu(I)-Y zeolite were tested for the removal of organosulfur compounds (OSC) present in tire pyrolytic oil (TPO). The π-complexation-based adsorbent was obtained by ion exchanging Y-zeolite with Cu+ cation using liquid phase ion exchange (LPIE). Preparation of the adsorbent involved firstly ion exchange between Na-Y zeolite with a Cu(NO₃)₂ aqueous solution of 0.5M for 48 hours followed by reduction of Cu²⁺ to Cu+. Fixed-bed breakthrough studies for TPO in comparison with model diesel comprising of sulfur compounds such as thiophene, benzothiophenes (BT), and dibenzothiophenes (DBT) showed that modified Cu(I)-Y zeolite is an effective adsorbent for removal of OSC in liquid fuels. The effect of operating conditions such as adsorbent dosage and reaction time were studied to optimize the adsorptive desulfurization process. For model diesel fuel, the selectivity for adsorption of sulfur compounds followed the order DBT> BT> Thiophene. The Cu(I)-Y zeolite is fully regeneratable and this is achieved by a simple procedure of blowing the adsorbent with air at 350 °C, followed by reactivation at 450 °C in a rich helium surrounding.

Keywords: adsorption, desulfurization, TPO, zeolite

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Authors: Manikandakumar Shunmugavel, Ashwin Polishetty, Moshe Goldberg, Junior Nomani, Guy Littlefair

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Selective laser melting (SLM), a promising additive manufacturing (AM) technology, has a huge potential in the fabrication of Ti-6Al-4V near-net shape components. However, poor surface finish of the components fabricated from this technology requires secondary machining to achieve the desired accuracy and tolerance. Therefore, a systematic understanding of the machinability of SLM fabricated Ti-6Al-4V components is paramount to improve the productivity and product quality. Considering the significance of machining in SLM fabricated Ti-6Al-4V components, this research aim is to study the influence of build orientation on machinability characteristics by performing low speed orthogonal cutting tests. In addition, the machinability of SLM fabricated Ti-6Al-4V is compared with conventionally produced wrought Ti-6Al-4V to understand the influence of SLM technology on machining. This paper is an attempt to provide evidence to the hypothesis associated that build orientation influences cutting forces, chip formation and surface integrity during orthogonal cutting of SLM Ti-6Al-4V samples. Results obtained from the low speed orthogonal cutting tests highlight the practical importance of microstructure and build orientation on machinability of SLM Ti-6Al-4V.

Keywords: additive manufacturing, build orientation, machinability, titanium alloys (Ti-6Al-4V)

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The accelerating requirement to reach 0% sulfur content in liquid fuels demands researchers to seek efficient alternative technologies to challenge the predicament. In this current study, the adsorption capabilities of modified Cu(I)-Y zeolite were tested for removal of organosulfur compounds (OSC) present in TPO. The π-complexation-based adsorbent was obtained by ion exchanging Y-zeolite with Cu+ cation using liquid phase ion exchange (LPIE). Preparation of the adsorbent involved firstly ion-exchange between Na-Y zeolite with a Cu(NO3)2 aqueous solution of 0.5M for 48 hours followed by reduction of Cu2+ to Cu+. Batch studies for TPO in comparison with model diesel comprising of sulfur compounds such as thiophene (TH), benzothiophene (BTH), dibenzothiophene (DBT) and 4,6-dimethyldibenzothiophe (4,6-DMDBT) showed that modified Cu(I)-Y zeolite is an effective adsorbent for removal of OSC in liquid fuels. The effect of multiple operating conditions such as adsorbent dosage, reaction time and temperature were studied to optimize the process. For model diesel fuel, the selectivity for adsorption of sulfur compounds followed the order 4,6-DMDBT> DBT> BTH> TH. Interpretation of the results was justified using the molecular orbital theory and calculations. Langmuir and Freundlich isotherms were used to predict adsorption of the reaction mixture. The Cu(I)-Y zeolite is fully regeneratable and this is achieved by a simple procedure of blowing the adsorbent with air at 350 °C, followed by reactivation at 450 °C in a rich helium surrounding.

Keywords: adsorption, desulfurization, TPO, zeolite

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Authors: Amir Mahyar Khorasani, Ian Gibson, Moshe Goldberg, Mohammad Masoud Movahedi, Guy Littlefair

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One of the important factors in manufacturing processes especially machining operations is surface quality. Improving this parameter results in improving fatigue strength, corrosion resistance, creep life and surface friction. The reliability and clearance of removable joints such as thread and nuts are highly related to the surface roughness. In this work, the effect of different cutting parameters such as cutting fluid pressure, feed rate and cutting speed on the surface quality of the crest of thread in the high-speed milling of Brass C3600 have been determined. Two popular neural networks containing MLP and RBF coupling with Taguchi L32 have been used to model surface roughness which was shown to be highly adept for such tasks. The contribution of this work is modelling surface roughness on the crest of the thread by using precise profilometer with nanoscale resolution. Experimental tests have been carried out for validation and approved suitable accuracy of the proposed model. Also analysing the interaction of parameters two by two showed that the most effective cutting parameter on the surface value is feed rate followed by cutting speed and cutting fluid pressure.

Keywords: artificial neural networks, cutting conditions, high-speed machining, surface roughness, thread milling

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Authors: Moshe Davidian, Shlomo Mark, Yotam Lurie

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With the rapid development of technology and the concomitant growth in the capability of Artificial Intelligence (AI) systems and their power, the ethical challenges involved in these systems are also evolving and increasing. In recent years, various organizations, including governments, international institutions, professional societies, civic organizations, and commercial companies, have been choosing to address these various challenges by publishing ethical codes for AI systems. However, despite the apparent agreement that AI should be “ethical,” there is debate about the definition of “ethical artificial intelligence.” This study investigates the various AI ethical codes and their key ethical values. From the vast collection of codes that exist, it analyzes and compares 25 ethical codes that were found to be representative of different types of organizations. In addition, as part of its literature review, the study overviews data collected in three recent reviews of AI codes. The results of the analyses demonstrate a convergence around seven key ethical values. However, the key finding is that the different AI ethical codes eventually reflect the type of organization that designed the code; i.e., the organizations’ role as regulator, user, or developer affects the view of what ethical AI is. The results show a relationship between the organization’s role and the dominant values in its code. The main contribution of this study is the development of a list of the key values for all AI systems and specific values that need to impact the development and design of AI systems, but also allowing for differences according to the organization for which the system is being developed. This will allow an analysis of AI values in relation to stakeholders.

Keywords: artificial intelligence, ethical codes, principles, values

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Authors: Ayal Siegel, Moshe Inbar, Amatzya Peled

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This study examined the characteristic runoff coefficient in different urban areas. The main area studied is located in the city of Haifa, northern Israel. Haifa spreads out eastward from the Mediterranean seacoast to the top of the Carmel Mountain range with an elevation of 300 m. above sea level. For this research project, four watersheds were chosen, each characterizing a different part of the city; 1) Upper Hadar, a spacious suburb on the upper mountain side; 2) Qiryat Eliezer, a crowded suburb on a level plane of the watershed; 3) Technion, a large technical research university which is located halfway between the top of the mountain range and the coast line. 4) Keret, a remote suburb, on the southwestern outskirts of Haifa. In all of the watersheds found suitable, instruments were installed to continuously measure the water level flowing in the channels. Three rainfall gauges scattered in the study area complete the hydrological requirements for this research project. The runoff coefficient C in peak discharge events was determined by the Rational Formula. The main research finding is the significant relationship between the intensity of rainfall, and the impervious area which is connected to the drainage system of the watershed. For less intense rainfall, the full potential of the connected impervious area will not be exploited. As a result, the runoff coefficient value decreases as do the peak discharge rate and the runoff yield from the storm event. The research results will enable application to other areas by means of hydrological model to be be set up on GIS software that will make it possible to estimate the runoff coefficient of any given city watershed.

Keywords: runoff coefficient, rational method, time of concentration, connected impervious area.

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Authors: Gali Pesin, Yuliya Lipshits-Braziler, Sima Amram-Vaknin, Moshe Tatar

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The present study introduces four different patterns of seeking and providing help online among adolescents: (I) ‘Transceivers’ - adolescents who both seek as well as provide help online; (II) ‘Receivers’ - adolescents who seek help online, yet don’t provide it; (III) ‘Transmitters’ - adolescents who provide help online, yet don’t seek it; and (IV) ‘Idles’ - adolescents who refrain from seeking and providing help online. The study examined differences in seeking and providing help online between possible combinations of the four patterns, as well as gender differences within each pattern. Data was collected from 528 adolescents in Israel (59% were girls). Findings revealed that Transceivers are the largest group (45%) in this study, with higher representation of girls (65%). These adolescents seek help mainly around social difficulties, and they turn to peers who are both known and unknown to them. In addition, their preferred way to seek and provide help is through social network sites. Moreover, they often accept and give others emotional support. Receivers are the smallest group (5%) in this study. They turn to both known and unknown professionals more often than to friends and family. In addition, they seek help mostly around health and nutrition issues, and they usually receive instrumental support. For Receivers, the most important factor for seeking help online is anonymity, and the least important factor is familiarity with the help giver. Transmitters represent 16% of the adolescents in this study, with a greater representation of boys (52%). Their main reason to refrain from seeking help online is self-reliance. Nevertheless, these adolescents provide help to others online, mainly to those known to them through posting or responding to posts on social network sites. Idles represent 34% of the adolescents in this study. They refrain from seeking help online mainly due to their preference to seek help face to face, and due to their lack of trust in the internet or those using it. Idles and Transmitters are willing to seek help online mostly from friends and family. In addition, they are willing seek help online mainly regarding questions concerning military or civil service. They consider the most important facilitators for seeking help online as confidentiality and reliability. The present study’s main contribution is exploring the role of providing online help in understanding the adolescent behavior of seeking help online. In addition, the results of the present study have practical implications for the work of mental health providers, such as counseling psychologists and online mental health support.

Keywords: adolescents, counseling, online help-seeking, online help-providing

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Authors: Moshe Wasserblat, Jonathan Mamou, Oren Pereg

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Natural Language Processing (NLP) has made a major leap in the last few years, in practical integration into medical solutions; for example, extracting clinical concepts from medical texts such as medical condition, medication, treatment, and symptoms. However, training and deploying those models in real environments still demands a large amount of annotated data and NLP/Machine Learning (ML) expertise, which makes this process costly and time-consuming. We present a practical and efficient method for clinical concept extraction that does not require costly labeled data nor ML expertise. The method includes three steps: Step 1- the user injects a large in-domain text corpus (e.g., PubMed). Then, the system builds a contextual model containing vector representations of concepts in the corpus, in an unsupervised manner (e.g., Phrase2Vec). Step 2- the user provides a seed set of terms representing a specific medical concept (e.g., for the concept of the symptoms, the user may provide: ‘dry mouth,’ ‘itchy skin,’ and ‘blurred vision’). Then, the system matches the seed set against the contextual model and extracts the most semantically similar terms (e.g., additional symptoms). The result is a complete set of terms related to the medical concept. Step 3 –in production, there is a need to extract medical concepts from the unseen medical text. The system extracts key-phrases from the new text, then matches them against the complete set of terms from step 2, and the most semantically similar will be annotated with the same medical concept category. As an example, the seed symptom concepts would result in the following annotation: “The patient complaints on fatigue [symptom], dry skin [symptom], and Weight loss [symptom], which can be an early sign for Diabetes.” Our evaluations show promising results for extracting concepts from medical corpora. The method allows medical analysts to easily and efficiently build taxonomies (in step 2) representing their domain-specific concepts, and automatically annotate a large number of texts (in step 3) for classification/summarization of medical reports.

Keywords: clinical concepts, concept expansion, medical records annotation, medical records summarization

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Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The nature of tires makes them extremely challenging to recycle due to the available chemically cross-linked polymer and, therefore, they are neither fusible nor soluble and, consequently, cannot be remolded into other shapes without serious degradation. Open dumping of tires pollutes the soil, contaminates underground water and provides ideal breeding grounds for disease carrying vermins. The thermal decomposition of tires by pyrolysis produce char, gases and oil. The composition of oils derived from waste tires has common properties to commercial diesel fuel. The problem associated with the light oil derived from pyrolysis of waste tires is that it has a high sulfur content (> 1.0 wt.%) and therefore emits harmful sulfur oxide (SOx) gases to the atmosphere when combusted in diesel engines. Desulphurization of TPO is necessary due to the increasing stringent environmental regulations worldwide. Hydrodesulphurization (HDS) is the commonly practiced technique for the removal of sulfur species in liquid hydrocarbons. However, the HDS technique fails in the presence of complex sulfur species such as Dibenzothiopene (DBT) present in TPO. This study aims to investigate the viability of photodegradation (Photocatalytic oxidative desulphurization) and adsorptive desulphurization technologies for efficient removal of complex and non-complex sulfur species in TPO. This study focuses on optimizing the cleaning (removal of impurities and asphaltenes) process by varying process parameters; temperature, stirring speed, acid/oil ratio and time. The treated TPO will then be sent for vacuum distillation to attain the desired diesel like fuel. The effect of temperature, pressure and time will be determined for vacuum distillation of both raw TPO and the acid treated oil for comparison purposes. Polycyclic sulfides present in the distilled (diesel like) light oil will be oxidized dominantly to the corresponding sulfoxides and sulfone via a photo-catalyzed system using TiO2 as a catalyst and hydrogen peroxide as an oxidizing agent and finally acetonitrile will be used as an extraction solvent. Adsorptive desulphurization will be used to adsorb traces of sulfurous compounds which remained during photocatalytic desulphurization step. This desulphurization convoy is expected to give high desulphurization efficiency with reasonable oil recovery.

Keywords: adsorption, asphaltenes, photocatalytic oxidation, pyrolysis

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Authors: Yori Gidron, Maartje Mol, Norbert Foudraine, Frits Van Osch, Joop Van Den Bergh, Moshe Farchi, Maud Straus

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Background: The worldwide pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-COV2), which began in 2019, also known as Covid-19, has infected over 136 million people and tragically took the lives of over 2.9 million people worldwide. Many of the complications and deaths are predicted by the inflammatory “cytokine storm.” One way to progress in the prevention of death is by finding a predictive and protective factor that inhibits inflammation, on the one hand, and which also increases anti-viral immunity on the other hand. The vagal nerve does precisely both actions. This study examined whether vagal nerve activity, indexed by heart-rate variability (HRV), predicts survival in patients with Covid-19. Method: We performed a pseudo-prospective study, where we retroactively obtained ECGs of 271 Covid-19 patients arriving at a large regional hospital in The Netherlands. HRV was indexed by the standard deviation of the intervals between normal heartbeats (SDNN). We examined patients’ survival at 3 weeks and took into account multiple confounders and known prognostic factors (e.g., age, heart disease, diabetes, hypertension). Results: Patients’ mean age was 68 (range: 25-95) and nearly 22% of the patients had died by 3 weeks. Their mean SDNN (17.47msec) was far below the norm (50msec). Importantly, relatively higher HRV significantly predicted a higher chance of survival, after statistically controlling for patients’ age, cardiac diseases, hypertension and diabetes (relative risk, H.R, and 95% confidence interval (95%CI): H.R = 0.49, 95%CI: 0.26 – 0.95, p < 0.05). However, since HRV declines rapidly with age and since age is a profound predictor in Covid-19, we split the sample by median age (40). Subsequently, we found that higher HRV significantly predicted greater survival in patients older than 70 (H.R = 0.35, 95%CI: 0.16 – 0.78, p = 0.01), but HRV did not predict survival in patients below age 70 years (H.R = 1.11, 95%CI: 0.37 – 3.28, p > 0.05). Conclusions: To the best of our knowledge, this is the first study showing that higher vagal nerve activity, as indexed by HRV, is an independent predictor of higher chances for survival in Covid-19. The results are in line with the protective role of the vagal nerve in diseases and extend this to a severe infectious illness. Studies should replicate these findings and then test in controlled trials whether activating the vagus nerve may prevent mortality in Covid-19.

Keywords: Covid-19, heart-rate Variability, prognosis, survival, vagal nerve

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Authors: Moshe Leiba, Doron Zohar

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Computer Science (CS) and programming is still considered a boy’s club and is a male-dominated profession. This is also the case in high schools and higher education. In Israel, not different from the rest of the world, there are less than 35% of female students in CS studies that take the matriculation exams. The Israeli matriculation exams are written in a masculine form language. Gender-fair language (GFL) aims at reducing gender stereotyping and discrimination. There are several strategies that can be employed to make languages gender-fair and to treat women and men symmetrically (especially in languages with grammatical gender, among them neutralization and using the plural form. This research aims at exploring computer science teachers’ beliefs regarding the use of gender-fair language in exams. An exploratory quantitative research methodology was employed to collect the data. A questionnaire was administered to 353 computer science teachers. 58% female and 42% male. 86% are teaching for at least 3 years, with 59% of them have a teaching experience of 7 years. 71% of the teachers teach in high school, and 82% of them are preparing students for the matriculation exam in computer science. The questionnaire contained 2 matriculation exam questions from previous years and open-ended questions. Teachers were asked which form they think is more suited: (a) the existing form (mescaline), (b) using both gender full forms (e.g., he/she), (c) using both gender short forms, (d) plural form, (e) natural form, and (f) female form. 84% of the teachers recognized the need to change the existing mescaline form in the matriculation exams. About 50% of them thought that using the plural form was the best-suited option. When examining the teachers who are pro-change and those who are against, no gender differences or teaching experience were found. The teachers who are pro gender-fair language justified it as making it more personal and motivating for the female students. Those who thought that the mescaline form should remain argued that the female students do not complain and the change in form will not influence or affect the female students to choose to study computer science. Some even argued that the change will not affect the students but can only improve their sense of identity or feeling toward the profession (which seems like a misconception). This research suggests that the teachers are pro-change and believe that re-formulating the matriculation exams is the right step towards encouraging more female students to choose to study computer science as their major study track and to bridge the gap for gender equality. This should indicate a bottom-up approach, as not long after this research was conducted, the Israeli ministry of education decided to change the matriculation exams to gender-fair language using the plural form. In the coming years, with the transition to web-based examination, it is suggested to use personalization and adjust the language form in accordance with the student's gender.

Keywords: compter science, gender-fair language, teachers, national exams

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Authors: Felicia Orah Rein Moshe

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Soil erosion has become a priority global concern, impairing water quality and degrading ecosystem services. In Mediterranean climates, following a long dry period, the onset of rain occurs when agricultural soils are often bare and most vulnerable to erosion. Early storms transport sediments and sediment-bound pollutants into streams, along with dissolved chemicals. This results in loss of valuable topsoil, water quality degradation, and potentially expensive dredged-material disposal costs. Information on the provenance of fine sediment and priority sources of adsorbed pollutants represents a critical need for developing effective control strategies aimed at source reduction. Modifying sediment traps designed for marine systems, this study tested a cost-effective method to collect suspended sediments on a catchment scale to characterize stream water quality during first-flush storm events in a flashy Eastern Mediterranean coastal perennial stream. This study investigated the Kishon Basin, deploying sediment traps in 23 locations, including 4 in the mainstream and one downstream in each of 19 tributaries, enabling the characterization of sediment as a vehicle for transporting chemicals. Further, it enabled direct comparison of sediment-bound pollutants transported during the first-flush winter storms of 2020 from each of 19 tributaries, allowing subsequent ecotoxicity ranking. Sediment samples were successfully captured in 22 locations. Pesticides, pharmaceuticals, nutrients, and metal concentrations were quantified, identifying a total of 50 pesticides, 15 pharmaceuticals, and 22 metals, with 16 pesticides and 3 pharmaceuticals found in all 23 locations, demonstrating the importance of this transport pathway. Heavy metals were detected in only one tributary, identifying an important watershed pollution source with immediate potential influence on long-term dredging costs. Simultaneous sediment sampling at first flush storms enabled clear identification of priority tributaries and their chemical contributions, advancing a new national watershed monitoring approach, facilitating strategic plan development based on source reduction, and advancing the goal of improving the farm-stream interface, conserving soil resources, and protecting water quality.

Keywords: adsorbed pollution, dredged material, heavy metals, suspended sediment, water quality monitoring

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Authors: Noa Nelson, Meitar Moshe, Dana Cohen

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Work-family conflict (WFC) is a significant source of stress for contemporary employees, with research indicating its heightened severity for women. The conservation of resources theory argues that individuals experience stress when their resources fall short of demands, and attempt to reach balance by obtaining resources. Presumably then, to achieve work-family balance women would need to negotiate for resources such as spouse support, employer support and work flexibility. The current research tested the hypotheses that competent negotiation at home and at work associated with increased family and job resources and with decreased WFC, as well as with higher work, marital and life satisfaction. In the first study, 113 employed mothers, married or cohabiting, reported to what extent they conducted satisfactory negotiation with spouse over division of housework, and their actual housework load compared to spouse. They answered a WFC questionnaire, measuring how much work interferes with family (WIF) and how much family interferes with work (FIW), and finally, measurements of satisfaction. In the second study, 94 employed mothers, married or cohabiting reported to what extent they conducted satisfactory negotiation with their boss over balancing work demands with family needs. They reported the levels of three job resources: flexibility, control and family-friendly organizational culture. Finally, they answered the same WFC and satisfaction measurements from study 1. Statistical analyses –t-tests, correlations, and hierarchical linear regressions- showed that in both studies, women reported higher WIF than FIW. Negotiations associated with increased resources: support from spouse, work flexibility and control and a family-friendly culture; negotiation with spouse associated also with satisfaction measurements. However, negotiations or resources (except family-friendly culture) did not associate with reduced conflict. The studies demonstrate the role of negotiation in obtaining family and job resources. Causation cannot be determined, but the fact is that employed mothers who enjoyed more support (at both home and work), flexibility and control, were more likely to keep active interactions to increase them. This finding has theoretical and practical implications, especially in view of research on female avoidance of negotiation. It is intriguing that negotiations and resources generally did not associate with reduced WFC. This finding might reflect the severity of the conflict, especially of work interfering with family, which characterizes many contemporary jobs. It might also suggest that employed mothers have high expectations from themselves, and even under supportive circumstances, experience the challenge of balancing two significant and demanding roles. The research contributes to the fields of negotiation, gender, and work-life balance. It calls for further studies, to test its model in additional populations and validate the role employees have in actively negotiating for the balance that they need. It also calls for further research to understand the contributions of job and family resources to reducing work-family conflict, and the circumstances under which they contribute.

Keywords: sork-family conflict, work-life balance, negotiation, gender, job resources, family resources

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Authors: Haji Mohammad Zulfan Farhi Bin Haji Sulaini, Mohammad Azeezudde’en Bin Mohd Ismaon

Abstract:

The demands placed on military athletes extend beyond physical prowess to encompass cognitive resilience in high-stress environments. This study investigates the effects of resilience training on the cognitive performance of military athletes, shedding light on the potential benefits and implications for optimizing their overall readiness. In a rapidly evolving global landscape, armed forces worldwide are recognizing the importance of cognitive resilience alongside physical fitness. The study employs a mixed-methods approach, incorporating quantitative cognitive assessments and qualitative data from military athletes undergoing resilience training programs. Cognitive performance is evaluated through a battery of tests, including measures of memory, attention, decision-making, and reaction time. The participants, drawn from various branches of the military, are divided into experimental and control groups. The experimental group undergoes a comprehensive resilience training program, while the control group receives traditional physical training without a specific focus on resilience. The initial findings indicate a substantial improvement in cognitive performance among military athletes who have undergone resilience training. These improvements are particularly evident in domains such as attention and decision-making. The experimental group demonstrated enhanced situational awareness, quicker problem-solving abilities, and increased adaptability in high-stress scenarios. These results suggest that resilience training not only bolsters mental toughness but also positively impacts cognitive skills critical to military operations. In addition to quantitative assessments, qualitative data is collected through interviews and surveys to gain insights into the subjective experiences of military athletes. Preliminary analysis of these narratives reveals that participants in the resilience training program report higher levels of self-confidence, emotional regulation, and an improved ability to manage stress. These psychological attributes contribute to their enhanced cognitive performance and overall readiness. Moreover, this study explores the potential long-term benefits of resilience training. By tracking participants over an extended period, we aim to assess the durability of cognitive improvements and their effects on overall mission success. Early results suggest that resilience training may serve as a protective factor against the detrimental effects of prolonged exposure to stressors, potentially reducing the risk of burnout and psychological trauma among military athletes. This research has significant implications for military organizations seeking to optimize the performance and well-being of their personnel. The findings suggest that integrating resilience training into the training regimen of military athletes can lead to a more resilient and cognitively capable force. This, in turn, may enhance mission success, reduce the risk of injuries, and improve the overall effectiveness of military operations. In conclusion, this study provides compelling evidence that resilience training positively impacts the cognitive performance of military athletes. The preliminary results indicate improvements in attention, decision-making, and adaptability, as well as increased psychological resilience. As the study progresses and incorporates long-term follow-ups, it is expected to provide valuable insights into the enduring effects of resilience training on the cognitive readiness of military athletes, contributing to the ongoing efforts to optimize military personnel's physical and mental capabilities in the face of ever-evolving challenges.

Keywords: military athletes, cognitive performance, resilience training, cognitive enhancement program

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Authors: Lilah Inzelberg, David Rand, Stanislav Steinberg, Moshe David Pur, Yael Hanein

Abstract:

Human facial expressions carry important psychological and neurological information. Facial expressions involve the co-activation of diverse muscles. They depend strongly on personal affective interpretation and on social context and vary between spontaneous and voluntary activations. Smiling, as a special case, is among the most complex facial emotional expressions, involving no fewer than 7 different unilateral muscles. Despite their ubiquitous nature, smiles remain an elusive and debated topic. Smiles are associated with happiness and greeting on one hand and anger or disgust-masking on the other. Accordingly, while high-resolution recording of muscle activation patterns, in a non-interfering setting, offers exciting opportunities, it remains an unmet challenge, as contemporary surface facial electromyography (EMG) methodologies are cumbersome, restricted to the laboratory settings, and are limited in time and resolution. Here we present a wearable and non-invasive method for objective mapping of facial muscle activation and demonstrate its application in a natural setting. The technology is based on a recently developed dry and soft electrode array, specially designed for surface facial EMG technique. Eighteen healthy volunteers (31.58 ± 3.41 years, 13 females), participated in the study. Surface EMG arrays were adhered to participant left and right cheeks. Participants were instructed to imitate three facial expressions: closing the eyes, wrinkling the nose and smiling voluntary and to watch a funny video while their EMG signal is recorded. We focused on muscles associated with 'enjoyment', 'social' and 'masked' smiles; three categories with distinct social meanings. We developed a customized independent component analysis algorithm to construct the desired facial musculature mapping. First, identification of the Orbicularis oculi and the Levator labii superioris muscles was demonstrated from voluntary expressions. Second, recordings of voluntary and spontaneous smiles were used to locate the Zygomaticus major muscle activated in Duchenne and non-Duchenne smiles. Finally, recording with a wireless device in an unmodified natural work setting revealed expressions of neutral, positive and negative emotions in face-to-face interaction. The algorithm outlined here identifies the activation sources in a subject-specific manner, insensitive to electrode placement and anatomical diversity. Our high-resolution and cross-talk free mapping performances, along with excellent user convenience, open new opportunities for affective processing and objective evaluation of facial expressivity, objective psychological and neurological assessment as well as gaming, virtual reality, bio-feedback and brain-machine interface applications.

Keywords: affective expressions, affective processing, facial EMG, high-resolution electromyography, independent component analysis, wireless electrodes

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Authors: Claire Harrison, Raajit K. Rampal, Vikas Gupta, Srdan Verstovsek, Moshe Talpaz, Jean-Jacques Kiladjian, Ruben Mesa, Andrew Kuykendall, Alessandro Vannucchi, Francesca Palandri, Sebastian Grosicki, Timothy Devos, Eric Jourdan, Marielle J. Wondergem, Haifa Kathrin Al-Ali, Veronika Buxhofer-Ausch, Alberto Alvarez-Larrán, Sanjay Akhani, Rafael Muñoz-Carerras, Yury Sheykin, Gozde Colak, Morgan Harris, John Mascarenhas

Abstract:

Myelofibrosis (MF) is characterized by bone marrow fibrosis, anemia, splenomegaly and constitutional symptoms. Progressive bone marrow fibrosis results from aberrant megakaryopoeisis and expression of proinflammatory cytokines, both of which are heavily influenced by bromodomain and extraterminal domain (BET)-mediated gene regulation and lead to myeloproliferation and cytopenias. Pelabresib (CPI-0610) is an oral small-molecule investigational inhibitor of BET protein bromodomains currently being developed for the treatment of patients with MF. It is designed to downregulate BET target genes and modify nuclear factor kappa B (NF-κB) signaling. MANIFEST-2 was initiated based on data from Arm 3 of the ongoing Phase 2 MANIFEST study (NCT02158858), which is evaluating the combination of pelabresib and ruxolitinib in Janus kinase inhibitor (JAKi) treatment-naïve patients with MF. Primary endpoint analyses showed splenic and symptom responses in 68% and 56% of 84 enrolled patients, respectively. MANIFEST-2 (NCT04603495) is a global, Phase 3, randomized, double-blind, active-control study of pelabresib and ruxolitinib versus placebo and ruxolitinib in JAKi treatment-naïve patients with primary MF, post-polycythemia vera MF or post-essential thrombocythemia MF. The aim of this study is to evaluate the efficacy and safety of pelabresib in combination with ruxolitinib. Here we report updates from a recent protocol amendment. The MANIFEST-2 study schema is shown in Figure 1. Key eligibility criteria include a Dynamic International Prognostic Scoring System (DIPSS) score of Intermediate-1 or higher, platelet count ≥100 × 10^9/L, spleen volume ≥450 cc by computerized tomography or magnetic resonance imaging, ≥2 symptoms with an average score ≥3 or a Total Symptom Score (TSS) of ≥10 using the Myelofibrosis Symptom Assessment Form v4.0, peripheral blast count <5% and Eastern Cooperative Oncology Group performance status ≤2. Patient randomization will be stratified by DIPSS risk category (Intermediate-1 vs Intermediate-2 vs High), platelet count (>200 × 10^9/L vs 100–200 × 10^9/L) and spleen volume (≥1800 cm^3 vs <1800 cm^3). Double-blind treatment (pelabresib or matching placebo) will be administered once daily for 14 consecutive days, followed by a 7 day break, which is considered one cycle of treatment. Ruxolitinib will be administered twice daily for all 21 days of the cycle. The primary endpoint is SVR35 response (≥35% reduction in spleen volume from baseline) at Week 24, and the key secondary endpoint is TSS50 response (≥50% reduction in TSS from baseline) at Week 24. Other secondary endpoints include safety, pharmacokinetics, changes in bone marrow fibrosis, duration of SVR35 response, duration of TSS50 response, progression-free survival, overall survival, conversion from transfusion dependence to independence and rate of red blood cell transfusion for the first 24 weeks. Study recruitment is ongoing; 400 patients (200 per arm) from North America, Europe, Asia and Australia will be enrolled. The study opened for enrollment in November 2020. MANIFEST-2 was initiated based on data from the ongoing Phase 2 MANIFEST study with the aim of assessing the efficacy and safety of pelabresib and ruxolitinib in JAKi treatment-naïve patients with MF. MANIFEST-2 is currently open for enrollment.

Keywords: CPI-0610, JAKi treatment-naïve, MANIFEST-2, myelofibrosis, pelabresib

Procedia PDF Downloads 201