Search results for: Humans.

Authors: Kihyon Kwon, Hyun T. Park, Gil Y. Chung, Sang-Hoon Lee

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This paper focuses on assessing sloshing-induced overflow of the seismically-isolated nuclear tanks based on Fluid-Structure Interaction (FSI) analysis. Typically, fluid motion in the seismically-isolated nuclear tank systems may be rather amplified and even overflowed under earthquake. Sloshing-induced overflow in those structures has to be reliably assessed and predicted since it can often cause critical damages to humans and environments. FSI analysis is herein performed to compute the total cumulative overflowed water volume more accurately, by coupling ANSYS with CFX for structural and fluid analyses, respectively. The approach is illustrated on a nuclear liquid storage tank, Spent Fuel Pool (SFP), forgiven conditions under consideration: different liquid levels, Peak Ground Accelerations (PGAs), and post earthquakes.

Keywords: FSI analysis, seismically-isolated nuclear tank system, sloshing-induced overflow

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Authors: Muhammad Usman Ghani

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Religious tolerance is essential for the establishment of peace in the world. In the system created by Almighty Allah where a lot of diversity is found, still, this world holds unity itself. In today's world, human beings have been divided into clashes of civilizations or divided on the basis of religions or lingual differences. A religious scholar of Indo- Pak subcontinent describes four ethics, on the basis of which all religions of the world can unite. He says in his philosophy of religion that, there is a number of elements common in all religions but four are very common and they are: cleanliness, nobel deeds, relation to Almighty (existence of Almighty) and justice. He says that this universe also holds its integrity in itself. All humans are different in their attributes but to be a human being is common in them. Similarly, all species of the universe are different in their nature, but to be the creature of God is commonly shared by all of them.

Keywords: inter-religious relation, peace and harmony, unity, four common ethics/virtues

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Authors: Nhabhat Chaimongkol

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Human capital is one of the factors that are vital for economic growth. This is especially true as humans will face increasingly more forms of disruptive technology in the near future. Therefore, there is a need to develop human capital in order to overcome the current uncertainty in the global economy and the future of jobs. In recent years, Thailand has increasingly devoted more attention to developing its human capital. The Thai government has raised this issue in its national agenda, which is part of its 20-year national strategy. Currently, there are multiple challenges and solutions regarding this issue. This study aims to find out what are the challenges and solutions to human capital development in Thailand. The research in this study uses mixed methods consisting of quantitative and qualitative research methods. The results show that while Thailand has many plans to develop human capital, it is still lacking the necessary actions and integrations that are required to achieve its goals. Finally, the challenges and solutions will be discussed in detail.

Keywords: challenges, human capital, solutions, Thailand

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Authors: Surachart Koyadun

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Introduction: Plasmodium knowlesi (P. knowlesi) malaria is a zoonotic disease that is classified as type 5 of human malaria. Commonly found in macaques (Macaca fascicularis) and (Macaca nemestrina), P. knowlesi is capable of resulting in both uncomplicated and severe malaria in humans. Situation of P. knowlesi malaria in Phang-Nga province for the past 3 years from 2020 – 2022 revealed no case report in 2020, however, a total of 14 cases had been reported in 2021 - 2022. This research aimed to 1) study the epidemiology of P. knowlesi, 2) examine the clinical manifestations of P. knowlesi patients, 3) analyze the ecology and entomology of P. knowlesi, and 4) analyze the diagnosis and treatment of P. knowlesi. Method: This research was a retrospective descriptive study/case report. The study was conducted in 14 patients with P. knowlesi malaria between 2021 and 2022 in 4 districts of Phang-Nga Province, Thailand including Thapput, Kapong, Takuapa and Khuraburi. Results: The study subjects of P. knowlesi malaria were all males. Most of them were working age groups as farmers and worked in forest or plantation areas. All had no history of blood transfusions. Most of the patients did not use mosquito nets and had a history of camping in the forest prior to the onset of fever. An analysis of all 14 sources of infection unveiled the area is home to macaques, and that area has detected Anopheles mosquito, which is the carrier of the disease. Majority of them got sick in the dry season of Thailand (December-April). The main symptoms brought to the hospital were fever, chills, headache, body aches. Laboratory findings on the first day of diagnosis were as follows: The white blood cell count was found within the normal range. In the proportion of white blood cells, eosinophils were found to be slightly higher than normal. Slight anemia was found on early examination. The platelet count was found to be below normal in all cases. Severely low platelet count (2,000 cells/mm3) was found in severe cases with multiple complications. No patient was found dead but 85.7% of complications were found, with acute renal failure being the most common. Patients with delayed diagnosis and treatment of malaria (inaccurate diagnosis or late access to the hospital) had the highest severity and complications than those who had seen the doctor since the first 3-4 days of illness or the screening of symptoms and risk history by the malaria clinic staff at vector-borne disease control unit. Conclusion and Recommendation: P. knowlesi malaria is an emerging infectious disease transmitted from animals to humans. There are challenges in epidemiology, entomology, ecology for effective surveillance, prevention and control. Early diagnosis and treatment would reduce complications and prevent death.

Keywords: malaria, plasmodium knowlesi, epidemiology, ecology, entomology, diagnosis, treatment

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Authors: Vahid Bairami Rad

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Due to the tremendous progress in computer technology in the last decades, the capabilities of computers increased enormously and working with a computer became a normal activity for nearly everybody. With all the possibilities a computer can offer, humans and their interaction with computers are now a limiting factor. This gave rise to a lot of research in the field of HCI (human computer interaction) aiming to make interaction easier, more intuitive, and more efficient. To research eye gaze based interfaces it is necessary to understand both sides of the interaction–the human eye and the eye tracker. The first section gives an overview on the anatomy of the eye. The second section accuracy and calibration issue. The subsequent section presents data from a user study where eye movements have been recorded while watching a video and while surfing the Internet. Statistics on the eye movement during these tasks for several individuals provide typical values and ranges for fixation times and saccade lengths and are the foundation for discussions in later chapters. The data also reveal typical limitations of eye trackers.

Keywords: human computer interaction, gaze tracking, calibration, eye movement

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Authors: Igor Faulmann, Arnaud Saj, Roland Maurer

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Spatial cognition consists in a plethora of high level cognitive abilities: among them, the ability to learn and to navigate in large scale environments is probably one of the most complex skills. Navigation is thought to rely on the ability to read a cognitive map, defined as an allocentric representation of ones environment. Those representations are of course intimately related to the two geometrical primitives of the environment: distance and direction. Also, many recent studies point to a predominant hippocampal and para-hippocampal role in spatial cognition, as well as in the more specific cluster of navigational skills. In a previous study in humans, we used a newly validated test assessing cognitive map processing by evaluating the ability to judge relative distances and directions: the CMRT (Cognitive Map Recall Test). This study identified in topographically disorientated patients (1) behavioral differences between the evaluation of distances and of directions, and (2) distinct causality patterns assessed via VLSM (i.e., distinct cerebral lesions cause distinct response patterns depending on the modality (distance vs direction questions). Thus, we hypothesized that: (1) if the CMRT really taps into the same resources as real navigation, there would be hippocampal, parahippocampal, and parietal activation, and (2) there exists underlying neuroanatomical and functional differences between the processing of this two modalities. Aiming toward a better understanding of the neuroanatomical correlates of the CMRT in humans, and more generally toward a better understanding of how the brain processes the cognitive map, we adapted the CMRT as an fMRI procedure. 23 healthy subjects (11 women, 12 men), all living in Geneva for at least 2 years, underwent the CMRT in fMRI. Results show, for distance and direction taken together, than the most active brain regions are the parietal, frontal and cerebellar parts. Additionally, and as expected, patterns of brain activation differ when comparing the two modalities. Furthermore, distance processing seems to rely more on parietal regions (compared to other brain regions in the same modality and also to direction). It is interesting to notice that no significant activity was observed in the hippocampal or parahippocampal areas. Direction processing seems to tap more into frontal and cerebellar brain regions (compared to other brain regions in the same modality and also to distance). Significant hippocampal and parahippocampal activity has been shown only in this modality. This results demonstrated a complex interaction of structures which are compatible with response patterns observed in other navigational tasks, thus showing that the CMRT taps at least partially into the same brain resources as real navigation. Additionally, differences between the processing of distances and directions leads to the conclusion that the human brain processes each modality distinctly. Further research should focus on the dynamics of this processing, allowing a clearer understanding between the two sub-processes.

Keywords: cognitive map, navigation, fMRI, spatial cognition

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Authors: Aysan Esgandanian, Sabalan Daneshvar

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The study is done to determine the comparison between proportional-integral-derivative controller (PID controller) and tilt-integral-derivative (TID controller) for cardiac pacemaker systems, which can automatically control the heart rate to accurately track a desired preset profile. The controller offers good adaption of heart to the physiological needs of the patient. The parameters of the both controllers are tuned by particle swarm optimization (PSO) algorithm which uses the integral of time square error as a fitness function to be minimized. Simulation results are performed on the developed cardiovascular system of humans and results demonstrate that the TID controller produces superior control performance than PID controllers. In this paper, all simulations were performed in Matlab.

Keywords: integral of time square error, pacemaker systems, proportional-integral-derivative controller, PSO algorithm, tilt-integral-derivative controller

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Authors: Mohamad Reza Asariha

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Crises are an integral part of social life, and their diversity is increasing day by day. Every aspect of life for humans involves a crisis, and these crises are becoming more varied over time. In times of crisis, the media has a special responsibility to inform the public and raise awareness of the situation. The public can be calmed by the media and inspired to take positive action or vice versa; the media can terrorize the public and cause mayhem. Media are regarded as one of the most significant forms of communication in the information age. Media plays an important role in different stages of crises. Before a crisis occurs, they can prevent the spread of the crisis and reduce its losses by warning about the consequences. At the time of the crisis, they can minimize the crisis by creating a scientific and rational atmosphere, or as mediators between the crisis agents and the interest groups, they can minimize the political clashes and be effective in attracting and participating the audience in crisis management. There is widespread access to the media, so it has a significant role in moderating and changing public opinion.

Keywords: media, crisis, crisis communication, crisis management, emergency situations

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Authors: Julia Ive, Lucia Specia

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Understanding and detecting toxicity is an important problem to support safer human interactions online. Our work focuses on the important problem of contextual toxicity detection, where automated classifiers are tasked with determining whether a short textual segment (usually a sentence) is toxic within its conversational context. We use “toxicity” as an umbrella term to denote a number of variants commonly named in the literature, including hate, abuse, offence, among others. Detecting toxicity in context is a non-trivial problem and has been addressed by very few previous studies. These previous studies have analysed the influence of conversational context in human perception of toxicity in controlled experiments and concluded that humans rarely change their judgements in the presence of context. They have also evaluated contextual detection models based on state-of-the-art Deep Learning and Natural Language Processing (NLP) techniques. Counterintuitively, they reached the general conclusion that computational models tend to suffer performance degradation in the presence of context. We challenge these empirical observations by devising better contextual predictive models that also rely on NLP data augmentation techniques to create larger and better data. In our study, we start by further analysing the human perception of toxicity in conversational data (i.e., tweets), in the absence versus presence of context, in this case, previous tweets in the same conversational thread. We observed that the conclusions of previous work on human perception are mainly due to data issues: The contextual data available does not provide sufficient evidence that context is indeed important (even for humans). The data problem is common in current toxicity datasets: cases labelled as toxic are either obviously toxic (i.e., overt toxicity with swear, racist, etc. words), and thus context does is not needed for a decision, or are ambiguous, vague or unclear even in the presence of context; in addition, the data contains labeling inconsistencies. To address this problem, we propose to automatically generate contextual samples where toxicity is not obvious (i.e., covert cases) without context or where different contexts can lead to different toxicity judgements for the same tweet. We generate toxic and non-toxic utterances conditioned on the context or on target tweets using a range of techniques for controlled text generation(e.g., Generative Adversarial Networks and steering techniques). On the contextual detection models, we posit that their poor performance is due to limitations on both of the data they are trained on (same problems stated above) and the architectures they use, which are not able to leverage context in effective ways. To improve on that, we propose text classification architectures that take the hierarchy of conversational utterances into account. In experiments benchmarking ours against previous models on existing and automatically generated data, we show that both data and architectural choices are very important. Our model achieves substantial performance improvements as compared to the baselines that are non-contextual or contextual but agnostic of the conversation structure.

Keywords: contextual toxicity detection, data augmentation, hierarchical text classification models, natural language processing

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Authors: Nisha Budhwar, Sunita Daniel

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In this paper, we analyse the stability of the SEIR model of malaria with infective immigrants which was recently formulated by the authors. The model consists of an SEIR model for the human population and SI Model for the mosquitoes. Susceptible humans become infected after they are bitten by infectious mosquitoes and move on to the Exposed, Infected and Recovered classes respectively. The susceptible mosquito becomes infected after biting an infected person and remains infected till death. We calculate the reproduction number R0 using the next generation method and then discuss about the stability of the equilibrium points. We use the Lyapunov function to show the global stability of the equilibrium points.

Keywords: equilibrium points, exposed, global stability, infective immigrants, Lyapunov function, recovered, reproduction number, susceptible

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Authors: Amin Padash, Mehran Khodaparast, Saadat Khodaparast

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Climate change is a significant and lasting change in the statistical distribution of weather patterns over periods ranging from decades to millions of years. Climate change is caused by factors such as biotic processes, variations in solar radiation received by Earth, plate tectonics, and volcanic eruptions. Certain human activities have also been identified as significant causes of recent climate change, often referred to as “Global Warming”. The ultimate goal of this paper is to determine how climate change affects the style of life and all of our activities. The paper focuses on what the effects of humans are on climate change and how communities can achieve sustainable development and use resources in a way that is good for the ecosystem and public. We opine Climate Change is a vital issue that can be called “Wicked Problem”. This paper attempts to address this wicked problem by COMPRAM Methodology as one of the possible solutions.

Keywords: climate change, COMPRAM, human influences, sustainable development, wicked problems

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Authors: Cathrine Scharning Cornwall-Nyquist, David Rafael Vaz Fernandes

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Since its origins, mankind has been dreaming of communicating directly with other animals. Past civilizations interacted on different levels with other species and recognized them in their rituals and daily activities. However, recent scientific developments have limited the ability of humans to consider deeper levels of interaction beyond observation and/or physical behavior. In recent years, animal caretakers and facilities such as sanctuaries or rescue centers have been introducing new techniques based on intuition. Most of those initiatives are related to specific cases, such as the incapacity to understand an animal’s behavior. Respected organizations also include intuitive animal communication (IAC) sessions to follow up on past interventions with their animals. Despite the lack of credibility of this discipline, some animal caring structures have opted to integrate IAC into their daily routines and approaches to animal welfare. At this stage, animal communication will be generally defined as the ability of humans to communicate with animals on an intuitive level. The trend in the field remains to be explored. The lack of theory and previous research urges the scientific community to improve the description of the phenomenon and its consequences. Considering the current scenario, qualitative approaches may become a suitable pathway to explore this topic. The purpose of this case study is to explore the beliefs behind and the consequences of an approach based on intuitive animal communication techniques for Panthera Africa (PA), an ethical sanctuary located in South Africa. Due to their personal experience, the Sanctuary’s founders have developed a philosophy based on IAC while respecting the world's highest standards for big cat welfare. Their dual approach is reflected in their rescues, daily activities, and healing animals’ trauma. The case study's main research questions will be: (i) Why do they choose to apply IAC in their work? (ii) What consequences to their activities do IAC bring? (iii) What effects do IAC techniques bring in their interactions with the outside world? Data collection will be gathered on-site via: (i) Complete participation (field notes); (ii) Semi-structured interviews (audio transcriptions); (iii) Document analysis (internal procedures and policies); (iv) Audio-visual material (communication with third parties). The main researcher shall become an active member of the Sanctuary during a 30-day period and have full access to the site. Access to documents and audio-visual materials will be granted on a request basis. Interviews are expected to be held with PA founders and staff members and with IAC practitioners related to the facility. The information gathered shall enable the researcher to provide an extended description of the phenomenon and explore its internal and external consequences for Panthera Africa.

Keywords: animal welfare, intuitive animal communication, Panthera Africa, rescue

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Authors: Denis Özdemir, Max Senges

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There are many examples of AI-supported apps for better health and wellbeing. Generally, these applications help people to achieve their goals based on scientific research and input data. Still, they do not always explain how those three are related, e.g. by making implicit assumptions about goals that hold for many but not for all. We present a seven-step method for designing health and wellbeing AIs considering goal setting, measurable results, real-time indicators, analytics, visual representations, communication, and feedback. It can help engineers as guidance in developing apps, recommendation algorithms, and interfaces that support humans in their decision-making without patronization. To illustrate the method, we create a recommender AI for tiny wellbeing habits and run a small case study, including a survey. From the results, we infer how people perceive the relationship between them and the AI and to what extent it helps them to achieve their goals. We review our seven-step engineering method and suggest modifications for the next iteration.

Keywords: recommender systems, natural language processing, health apps, engineering methods

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Authors: N. Kotabin, Y. Tahara, K. Issakul, O. Chunhachart

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Cadmium (II) (Cd) is one of the major toxic elemental pollutants which is hazardous for humans, animals and plants. γ-Polyglutamic acid (γ-PGA) is an extracellular biopolymer produced by several species of Bacillus which has been reported to be an effective biosorbent for metal ions. The effect of γ-PGA on growth of rice grown under laboratory conditions was investigated. Rice seeds were germinated and then grown at 30±1°C on filter paper soaked with Cd solution and γ-PGA for 7 days. The result showed that Cd significantly inhibited the growth of roots and shoots by reducing root and shoot lengths. Fresh and dry weights also decreased compared with control; however, the addition of 500 mg•L-1 γ-PGA alleviated rice seedlings from the adverse effects of Cd. The analysis of physiological traits revealed that Cd caused a decrease in the total chlorophyll and soluble protein contents and amylase activities in all treatments. The Cd content in seedling tissues increased for the Cd 250 μM treatment (P < 0.05) but the addition of 500 mg•L-1 γ-PGA resulted in a noticeable decrease in Cd (P < 0.05).

Keywords: polyglutamic acid, cadmium, rice, bacillus subtilis

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Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

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Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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Authors: Jasem Al-Safran

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Nowadays Oil and Gas industry considered as one of the biggest industries around the world although it caused a lot of pollution to the world and it caused many damages to the mankind and the other creatures around the globe it still one of the biggest industries, it create millions of careers around the globe which reduced the poorness level and make the mankind life’s much more comfortable you may compare the humans life before the exploration of the oil and after the oil industries development. Construction project’s consist of 3 major sections also we call them EPC projects the first section is the detailed engineering, the second section is the procurements section and finally is the Construction section, each section required a specialized work force with a different skills in order to handle the work load for example in the oil sector and depending on the nature of the project and the project size the Construction team required mechanical engineer, civil engineer, electrical engineer and instrumentation engineer, also a work site supervisor for each disciplines also a huge number of labors, technicians and many equipment’s.

Keywords: Construction, EPC, Project, Work force

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Authors: Ksheeraj Sai Vepuri, Nada Attar

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We as humans use words with accompanying visual and facial cues to communicate effectively. Classifying facial emotion using computer vision methodologies has been an active research area in the computer vision field. In this paper, we propose a simple method for facial expression recognition that enhances accuracy. We tested our method on the FER-2013 dataset that contains static images. Instead of using Histogram equalization to preprocess the dataset, we used Unsharp Mask to emphasize texture and details and sharpened the edges. We also used ImageDataGenerator from Keras library for data augmentation. Then we used Convolutional Neural Networks (CNN) model to classify the images into 7 different facial expressions, yielding an accuracy of 69.46% on the test set. Our results show that using image preprocessing such as the sharpening technique for a CNN model can improve the performance, even when the CNN model is relatively simple.

Keywords: facial expression recognittion, image preprocessing, deep learning, CNN

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Authors: Sahil Anand, John Luetke, Nikhil Venkatesh, Dorothy Wong

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Trust plays an important role in building and sustaining long-term relationships between people. In this paper, we present a robot that communicates using nonverbal behaviors such as facial expressions and body movements. Our study reports on an experiment in which participants were asked to team up with the robot to perform specific tasks. We varied the expressivity of the robot and measured the effects on trust, quality of interactions as well as on the praising and punishing behavior of the participant towards the robot. We found that participants developed a stronger affinity towards the expressive robot, but did not show any significant differences in the level of trust. When the same robot made mistakes, participants unconsciously punished it with lesser intensity compared to the neutral robot. The results emphasize the role of expressive behaviors on participant’s perception of the robot and also on the quality of interactions between humans and robots.

Keywords: human-robot interaction, nonverbal communication, relationships, social robot, trust

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Authors: Mazo Kone, Rachida Salah, Harir Noria

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Background and objectives: c-Cbl and Cbl-b are two members of the Cbl family proteins, with a crucial role of downregulation of tyrosine kinase receptors. They act as E3 ubiquitin ligases and are multivalent adaptor proteins, making them important in maintaining homeostasis in the body. This study investigated the expression level in thymus and testis in normal conditions. Methods: The expression level was assessed by immunochemistry of tissue microarrays of normal thymus and testis biopsies. Results: Cbl-b and c-Cbl proteins were found to be highly expressed in normal testis and thymus, indicated as yellowish brown granules in the cytomembrane and cytoplasm compared to controls. The c-Cbl appears to be more highly expressed than the Cbl-b in the thymus, while c-Cbl appears slightly stronger than Cbl-b in the testis. The thymus was found with a higher grade compared to the testis. Conclusion: In this work we concluded, that in normal condition, thymus tissue expresses more Cbl family proteins(c-Cbl and Cbl-b) than the testis tissue in humans.

Keywords: Human C-Cbl proteins, Human Cbl-b protein, Testis, Thymus

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Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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Authors: Tonderai Muchenje, Mkhatshwa Phethile

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Humans living in this current situation know that communication with one another is necessary for themselves. There are many ways to communicate with each other; during unexpected natural disasters and outbreak of epidemics and pandemics, the need for online meeting platforms are considered most important. Apparently, the development in the telecommunication sector also played an important role. Therefore, the epidemic of the Covid-19 Pandemic and the new normal situation resulted in the overwhelming production of online meeting platforms to prevent the situation. This software is commonly used in business communications in the beginning. Rapidly the COVID-19 pandemic changed the situation. At present-day, these virtual meeting applications are not only used to have informal meetings with friends and relatives but also to be used to have formal meetings in the business and education (universities) sector. In this article, an attempt has been made to list out the useful secured ways for using online meeting platforms.

Keywords: virtual background, zoom, secure online algorithm, RingCentral, Pexip Pexip, TeamViewer, microsoft teams

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Mohammed Alkahtani, Ali Ahmad, Saber Darmoul, Shatha Samman, Ayoub Al-zabidi, Khaled Ba Matraf

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Education systems are complex and involve interactions between humans (teachers and students); media based technologies, lectures, classrooms, etc. to provide educational services. The education system performance is characterized by how well students learn, which is measured using student grades on exams and quizzes, achievements on standardized tests, among others. Advances in portable communications technologies, such as mobile phones, tablets, and laptops, created a different type of classroom, where students seem to engage in more than just the intended learning activities. The performance of more than one task in parallel or in rapid transition is commonly known as multitasking. Several operations in educational systems are performed simultaneously, resulting in a multitasking education environment. This paper surveys existing research on multitasking in educational settings, summarizes literature findings, provides a synthesis of the impact of multitasking on performance, and identifies directions of future research.

Keywords: multitasking, education, education environment, impact

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Authors: Gleda Kutrolli, Maksi Kutrolli, Etjon Meco

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SARS-CoV-2 virus is currently one of the most infectious pathogens for humans. It started in China at the end of 2019 and now it is spread in all over the world. The origin and diffusion of the SARS-CoV-2 epidemic, is analysed based on the discussion of viral phylogeny theory. With the aim of understanding the spread of infection in the affected countries, it is crucial to modelize the spread of the virus and simulate its activity. In this paper, the prediction of coronavirus outbreak is done by using SIR model without vital dynamics, applying different numerical technique solving ordinary differential equations (ODEs). We find out that ABM and MRT methods perform better than other techniques and that the activity of the virus will decrease in April but it never cease (for some time the activity will remain low) and the next cycle will start in the middle July 2020 for Norway and Denmark, and October 2020 for Sweden, and September for Finland.

Keywords: forecasting, ordinary differential equations, SARS-COV-2 epidemic, SIR model

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Authors: Pallavi N., Gayatri Jadhav

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Good quality water is of prime importance for a healthy living. Fluoride is one such mineral present in water which causes many health problems in humans and specially children. Fluoride is said to be a double edge sword because lesser and higher concentration of fluoride in drinking water can cause both dental and skeletal fluorosis. Fluoride is one of the important mineral usually present at a higher concentration in ground water. There are many researches being carried out for defluoridation method. In the present research, fluoride removal is demonstrated using banana peel which is a biowaste as a biocoagulant. Response Surface Methodology (RSM) is a statistical design tool which is used to design the experiment. Central Composite Design (CCD) was used to determine the influence of the pH and dosage of the coagulant on the optimal removal of fluoride from a simulated water sample. 895 of fluoride removal were obtained in a acidic pH range of 4 – 9 and bio coagulant dosage of dosage of 18 – 20mg/L.

Keywords: Fluoride, Response Surface Methodology, Dosage, banana peel

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Authors: Akanksha Bhatnagar, Sandhya Kortegare, Felice Elefant

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Context: Alzheimer's disease (AD) is a neurodegenerative disorder that is characterized by progressive cognitive decline and memory loss. The cause of AD is not fully understood, but it is thought to be caused by a combination of genetic, environmental, and lifestyle factors. One of the hallmarks of AD is the loss of neurons in the hippocampus, a brain region that is important for memory and learning. This loss of neurons is thought to be caused by a decrease in histone acetylation, which is a process that regulates gene expression. Research Aim: The research aim of the study was to develop mall molecule compounds that can enhance the activity of Tip60, a histone acetyltransferase that is important for memory and learning. Methodology/Analysis: The researchers used in silico structural modeling and a pharmacophore-based virtual screening approach to design and synthesize small molecule compounds strongly predicted to target and enhance Tip60’s HAT activity. The compounds were then tested in vitro and in vivo to assess their ability to enhance Tip60 activity and rescue cognitive deficits in AD models. Findings: The researchers found that several of the compounds were able to enhance Tip60 activity and rescue cognitive deficits in AD models. The compounds were also developed to cross the blood-brain barrier, which is an important factor for the development of potential AD therapeutics. Theoretical Importance: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Data Collection: The study collected data from a variety of sources, including in vitro assays and animal models. The in vitro assays assessed the ability of compounds to enhance Tip60 activity using histone acetyltransferase (HAT) enzyme assays and chromatin immunoprecipitation assays. Animal models were used to assess the ability of the compounds to rescue cognitive deficits in AD models using a variety of behavioral tests, including locomotor ability, sensory learning, and recognition tasks. The human clinical trials will be used to assess the safety and efficacy of the compounds in humans. Questions: The question addressed by this study was whether Tip60 HAT activators could be developed as therapeutic agents for AD. Conclusions: The findings of this study suggest that Tip60 HAT activators have the potential to be developed as therapeutic agents for AD. The compounds are specific to Tip60, which suggests that they may have fewer side effects than other HDAC inhibitors. Additionally, the compounds are able to cross the blood-brain barrier, which is a major hurdle for the development of AD therapeutics. Further research is needed to confirm the safety and efficacy of these compounds in humans.

Keywords: Alzheimer's disease, cognition, neuroepigenetics, drug discovery

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Authors: Eduardo Antonio Lozano Hernandez, Nancy Ramirez Alvarez, Lorena Margarita Rios Mendoza, Jose Vinicio Macias Zamora, Felix Augusto Hernandez Guzman, Jose Luis Sanchez Osorio

Abstract:

Microplastics (MPs) are one of the most numerous reported wastes found in the marine ecosystem, representing one of the greatest risks for organisms that inhabit that environment due to their bioavailability. Such is the case of bivalve mollusks, since they are capable of filtering large volumes of water, which increases the risk of contamination by microplastics through the continuous exposure to these materials. This study aims to determine, quantify and characterize microplastics found in the cultured oyster Crassostrea gigas. We also analyzed if there are spatio-temporal differences in the microplastic concentration of organisms grown in two bays having quite different human population. In addition, we wanted to have an idea of the possible impact on humans via consumption of these organisms. Commercial size organisms (>6cm length; n = 15) were collected by triplicate from eight oyster farming sites in Baja California, Mexico during winter and summer. Two sites are located in Todos Santos Bay (TSB), while the other six are located in San Quintin Bay (SQB). Site selection was based on commercial concessions for oyster farming in each bay. The organisms were chemically digested with 30% KOH (w/v) and 30% H₂O₂ (v/v) to remove the organic matter and subsequently filtered using a GF/D filter. All particles considered as possible MPs were quantified according to their physical characteristics using a stereoscopic microscope. The type of synthetic polymer was determined using a FTIR-ATR microscope and using a user as well as a commercial reference library (Nicolet iN10 Thermo Scientific, Inc.) of IR spectra of plastic polymers (with a certainty ≥70% for polymers pure; ≥50% for composite polymers). Plastic microfibers were found in all the samples analyzed. However, a low incidence of MP fragments was observed in our study (approximately 9%). The synthetic polymers identified were mainly polyester and polyacrylonitrile. In addition, polyethylene, polypropylene, polystyrene, nylon, and T. elastomer. On average, the content of microplastics in organisms were higher in TSB (0.05 ± 0.01 plastic particles (pp)/g of wet weight) than found in SQB (0.02 ± 0.004 pp/g of wet weight) in the winter period. The highest concentration of MPs found in TSB coincides with the rainy season in the region, which increases the runoff from streams and wastewater discharges to the bay, as well as the larger population pressure (> 500,000 inhabitants). Otherwise, SQB is a mainly rural location, where surface runoff from streams is minimal and in addition, does not have a wastewater discharge into the bay. During the summer, no significant differences (Manne-Whitney U test; P=0.484) were observed in the concentration of MPs found in the cultured oysters of TSB and SQB, (average: 0.01 ± 0.003 pp/g and 0.01 ± 0.002 pp/g, respectively). Finally, we concluded that the consumption of oyster does not represent a risk for humans due to the low concentrations of MPs found. The concentration of MPs is influenced by the variables such as temporality, circulations dynamics of the bay and existing demographic pressure.

Keywords: FTIR-ATR, Human risk, Microplastic, Oyster

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Authors: Surajbhan Sevda

Abstract:

Metal containing wastewater is generated in large quintiles due to rapid industrialization. Generally, the metal present in wastewater is not biodegradable and can be accumulated in living animals, humans and plant tissue, causing disorder and diseases. The conventional metal recovery methods include chemical, physical and biological methods, but these are chemical and energy intensive. The recent development in microbial fuel cell (MFC) technology provides a new approach for metal recovery; this technology offers a flexible platform for both reduction and oxidation reaction oriented process. The use of MFCs will be a new platform for more efficient and low energy approach for metal recovery from the wastewater. So far metal recover was extensively studied using chemical, physical and biological methods. The MFCs present a new and efficient approach for removing and recovering metals from different wastewater, suggesting the use of different electrode for metal recovery can be a new efficient and effective approach.

Keywords: metal recovery, microbial fuel cell, wastewater, bioelectricity

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Authors: Osagiede Efosa Kelvin

Abstract:

The Ebola virus disease (EVD); also Ebola hemorrhagic fever, is a disease of humans and other primates caused by Ebola viruses. Signs and symptoms typically start between two days and three weeks after contracting the virus as a fever, sore throat, muscle pain, and headaches. Then, vomiting, diarrhoea and rash usually follow, along with decreased function of the liver and kidneys. At this time, some people begin to bleed both internally and externally. The first death in Nigeria was reported on 25 July 2014: a Liberian-American with Ebola flew from Liberia to Nigeria and died in Lagos soon after arrival. As part of the effort to contain the disease, possible contacts were monitored –353 in Lagos and 451 in Port Harcourt On 22 September, the World Health Organisation reported a total of 20 cases, including eight deaths. The WHO's representative in Nigeria officially declared Nigeria Ebola-free on 20 October after no new active cases were reported in the follow-up contact. This paper looks at the Ebola Virus in general and the measures taken by Nigeria to combat its spread.

Keywords: Ebola virus, hemorrhagic fever, Nigeria, outbreak

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Authors: Fatimazahrae Elbakri, Azeddine Ibrahimi, Meryem Lemrani, Dris Belghyti

Abstract:

Leishmaniasis represents a major public health problem because of the number of cases recorded each year and the wide distribution of the disease. It is a parasitic disease of flagellated protozoa transmitted by the bite of certain species of sandfly, causing a spectrum of clinical pathology in humans ranging from disfiguring skin lesions to fatal visceral leishmaniasis. Cutaneous leishmaniasis due to Leishmania major is a polymorphic disease; in fact, the infection can be asymptomatic, localized, or disseminated. The objective of this work is to determine the genomic diversity that contributes to clinical variability by trying to identify the variation in chromosome number and to extract SNPs and SNPs and InDels; it is based on four sequences (WGS) of Leishmania major available on NCBI in Fastq form, from three countries: Tunisia, Algeria, and Israel, the analysis is set up from a pipeline to facilitate the discovery of genetic diversity, in particular SNP and chromosomal somy.

Keywords: Leshmania major, cutaneous Leishmania, NGS, genomic, somy, variant calling

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