Search results for: memory stimulation

Authors: Achiron Anat, Mathilda Mandel, Mayust Sue, Achiron Reuven, Gurevich Michael

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Introduction: As coronavirus disease 2019 (COVID-19) vaccination is currently spreading around the world, it is of importance to assess the ability of multiple sclerosis (MS) patients to mount an appropriate immune response to the vaccine in the context of disease-modifying treatments (DMT’s). Objectives: Evaluate immunity generated following COVID-19 vaccination in MS patients, and assess factors contributing to protective humoral and cellular immune responses in MS patients vaccinated against severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) virus infection. Methods: Review our recent data related to (1) the safety of PfizerBNT162b2 COVID-19 mRNA vaccine in adult MS patients; (2) the humoral post-vaccination SARS-CoV2 IgG response in MS vaccinees using anti-spike protein-based serology; and (3) the cellular immune response of memory B-cells specific for SARS-CoV-2 receptor-binding domain (RBD) and memory T-cells secreting IFN-g and/or IL-2 in response to SARS-CoV2 peptides using ELISpot/Fluorospot assays in MS patients either untreated or under treatment with fingolimod, cladribine, or ocrelizumab; (4) covariate parameters related to mounting protective immune responses. Results: COVID-19 vaccine proved safe in MS patients, and the adverse event profile was mainly characterised by pain at the injection site, fatigue, and headache. Not any increased risk of relapse activity was noted and the rate of patients with acute relapse was comparable to the relapse rate in non-vaccinated patients during the corresponding follow-up period. A mild increase in the rate of adverse events was noted in younger MS patients, among patients with lower disability, and in patients treated with DMTs. Following COVID-19 vaccination protective humoral immune response was significantly decreased in fingolimod- and ocrelizumab- treated MS patients. SARS-CoV2 specific B-cell and T-cell cellular responses were respectively decreased. Untreated MS patients and patients treated with cladribine demonstrated protective humoral and cellular immune responses, similar to healthy vaccinated subjects. Conclusions: COVID-19 BNT162b2 vaccine proved as safe for MS patients. No increased risk of relapse activity was noted post-vaccination. Although COVID-19 vaccination is new, accumulated data demonstrate differences in immune responses under various DMT’s. This knowledge can help to construct appropriate COVID-19 vaccine guidelines to ensure proper immune responses for MS patients.

Keywords: covid-19, vaccination, multiple sclerosis, IgG

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Authors: James Newman

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Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

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Authors: Tery Nehemia Nugraha Joseph, J. D. P. Wisnubroto

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Thyroid cancer is a healthcare problem with high morbidity and mortality. Follicular adenoma and follicular carcinoma are thyroid tumors from the thyroid follicular cells differentiation with a microfollicular pattern that consists of follicular cuboidal cells. vascular endothelial growth factor (VEGF) is a potent and powerful mitogen for endothelial cells and increases vascular permeability. Therefore, due to an increase in thyroid-stimulating hormone (TSH), VEGF production is activated in the thyroid that leads to the end of mitogenic TSH stimulation and initiation of angiogenesis. The differences in VEGF levels in the follicular carcinoma of thyroid tissue with follicular adenoma thyroid can be used as a basis in differentiating the two types of neoplasms. This study aims to analyze VEGF in the serum so that it can be used to differentiate the types of thyroid carcinoma before surgery. This study uses a cross-sectional research design. Samples were carried out by taking serum samples, and the VEGF levels were calculated. Data were analyzed using the Mann-Whitney test. The results found a significant difference between VEGF levels in the follicular carcinoma thyroid group and VEGF levels in the follicular adenoma thyroid group with a value of p = 0.007 (p < 0.05). The results obtained are 560,427 ± 160,506 ng/mL in the type of follicular carcinoma thyroid and 320.943 ± 134.573 ng/mL in the type of follicular adenoma thyroid. VEGF levels between follicular adenoma and follicular carcinoma are different. VEGF levels are higher in follicular carcinoma thyroid than follicular adenoma thyroid.

Keywords: follicular adenoma thyroid, follicular carcinoma thyroid, thyroid, VEGF

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Authors: Peng Guo

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Objective: This study investigates the clinical characteristics of sleep disorders (SD) in patients with Alzheimer's disease (AD) and their relationship with cognitive impairment. Methods: According to the inclusion and exclusion criteria of AD, 460 AD patients were consecutively included in Beijing Tiantan Hospital from January 2016 to April 2022. Demographic data, including gender, age, age of onset, course of disease, years of education and body mass index, were collected. The Pittsburgh sleep quality index (PSQI) scale was used to evaluate the overall sleep status. AD patients with PSQI ≥7 was divided into AD with SD (AD-SD) group, and those with PSQI < 7 were divided into AD with no SD (AD-nSD) group. The overall cognitive function of AD patients was evaluated by the scales of Mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA), memory was evaluated by the AVLT-immediate recall, AVLT-delayed recall and CFT-delayed memory scales, the language was evaluated by BNT scale, visuospatial ability was evaluated by CFT-imitation, executive function was evaluated by Stroop-A, Stroop-B and Stroop-C scales, attention was evaluated by TMT-A, TMT-B, and SDMT scales. The correlation between cognitive function and PSQI score in AD-SD group was analyzed. Results: Among the 460 AD patients, 173 cases (37.61%) had SD. There was no significant difference in gender, age, age of onset, course of disease, years of education and body mass index between AD-SD and AD-nSD groups (P>0.05). The factors with significant difference in PSQI scale between AD-SD and AD-nSD groups include sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbance, use of sleeping medication and daytime dysfunction (P<0.05). Compared with AD-nSD group, the total scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales in AD-SD group were significantly lower（P＜0.01，P＜0.01，P＜0.01，P＜0.05）. In AD-SD group, subjective sleep quality was significantly and negatively correlated with the scores of MMSE, MoCA, AVLT-immediate recall and CFT-imitation scales (r=-0.277，P=0.000; r=-0.216，P=0.004; r=-0.253，P=0.001; r=-0.239, P=0.004), daytime dysfunction was significantly and negatively correlated with the score of AVLT-immediate recall scale (r=-0.160，P=0.043). Conclusion The incidence of AD-SD is 37.61%. AD-SD patients have worse subjective sleep quality, longer time to fall asleep, shorter sleep time, lower sleep efficiency, severer nighttime SD, more use of sleep medicine, and severer daytime dysfunction. The overall cognitive function, immediate recall and visuospatial ability of AD-SD patients are significantly impaired and are closely correlated with the decline of subjective sleep quality. The impairment of immediate recall is highly correlated with daytime dysfunction in AD-SD patients.

Keywords: Alzheimer's disease, sleep disorders, cognitive impairment, correlation

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Authors: María Eugenia Peltzer, María Estela Rodríguez

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This work presents an approach to the cultural aspects of the Immigrants as part of the Cultural Intangible Heritage of Argentina. The intangible cultural heritage consists of the manifestations, practices, uses, representations, expressions, knowledge, techniques and cultural spaces that communities and groups recognize as an integral part of their cultural heritage. This heritage generates feelings of identity and establishes links with the collective memory, as well as being transmitted and recreated over time according to its environment, its interaction with nature and its history contributing to promote respect for cultural diversity and Human creativity. The Immigrants brings together those who came from other lands and their descendants, thus maintaining their traditions through time and linking the members of each cultural group with a strong sense of belonging through a communicative and effective process.

Keywords: cultural, immigration, memories, social

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Authors: Paul Stonaha, Mariia Romashchenko, Xaio Xu

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Magnetic shape memory alloys (MSMAs) are promising technological materials for a range of fields, from biomaterials to energy harvesting. We have performed inelastic neutron scattering on two powder samples of cobalt-based high-entropy MSMAs across a range of temperatures in an effort to compare calculations of thermodynamic properties (entropy, specific heat, etc.) to the measured ones. The measurements were correct for multiphonon scattering and multiple scattering contributions. We present herein the neutron-weighted vibrational density of states. Future work will utilize DFT calculations of the disordered lattice to correct for the neutron weighting and retrieve the true thermodynamical properties.

Keywords: neutron scattering, vibrational dynamics, computational physics, material science

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Authors: Pin-Ling Yin, Dung-Ying Lin

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Satellites play an important role in our daily lives, from monitoring the Earth's environment and providing real-time disaster imagery to predicting extreme weather events. As technology advances and demands increase, the tasks undertaken by satellites have become increasingly complex, with more stringent resource management requirements. A common challenge in satellite mission scheduling is the limited availability of resources, including onboard memory, ground station accessibility, and satellite power. In this context, efficiently scheduling and managing the increasingly complex satellite missions under constrained resources has become a critical issue that needs to be addressed. The core of Satellite Onboard Activity Planning (SOAP) lies in optimizing the scheduling of the received tasks, arranging them on a timeline to form an executable onboard mission plan. This study aims to develop an optimization model that considers the various constraints involved in satellite mission scheduling, such as the non-overlapping execution periods for certain types of tasks, the requirement that tasks must fall within the contact range of specified types of ground stations during their execution, onboard memory capacity limits, and the collaborative constraints between different types of tasks. Specifically, this research constructs a mixed-integer programming mathematical model and solves it with a commercial optimization package. Simultaneously, as the problem size increases, the problem becomes more difficult to solve. Therefore, in this study, a heuristic algorithm has been developed to address the challenges of using commercial optimization package as the scale increases. The goal is to effectively plan satellite missions, maximizing the total number of executable tasks while considering task priorities and ensuring that tasks can be completed as early as possible without violating feasibility constraints. To verify the feasibility and effectiveness of the algorithm, test instances of various sizes were generated, and the results were validated through feedback from on-site users and compared against solutions obtained from a commercial optimization package. Numerical results show that the algorithm performs well under various scenarios, consistently meeting user requirements. The satellite mission scheduling algorithm proposed in this study can be flexibly extended to different types of satellite mission demands, achieving optimal resource allocation and enhancing the efficiency and effectiveness of satellite mission execution.

Keywords: mixed-integer programming, meta-heuristics, optimization, resource management, satellite mission scheduling

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Authors: Păcurar Diana Istina

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Structured in three chapters, the article attempts an X-ray of the theatrical aesthetics, correctly understood through the emotions generated in the intimate structure of the spectator that precedes the triggering of the viewer’s perception and not through the superposition, unfortunately common, of the notion of aesthetics with the style in which a theater show is built. The first chapter contains a brief history of the appearance of the word aesthetic, the formulation of definitions for this new term, as well as its connections with the notions of semiotics, in particular with the perception of the message transmitted. Starting with Aristotle and Plato, and reaching Magritte, their interventions should not be interpreted in the sense that the two scientific concepts can merge into one discipline. The perception that is the object of everyone’s analysis, the understanding of meaning, the decoding of the messages sent, and the triggering of feelings that culminate in pleasure, shaping the aesthetic vision, are some elements that keep semiotics and aesthetics distinct, even though they share many methods of analysis. The compositional processes of aesthetic representation and symbolic formation are analyzed in the second part of the paper from perspectives that include or do not include historical, cultural, social, and political processes. Aesthetics and the organization of its symbolic process are treated, taking into account expressive activity. The last part of the article explores the notion of aesthetics in applied theater, more specifically in the theater show. Taking the postmodern approach that aesthetics applies to the creation of an artifact and the reception of that artifact, the intervention of these elements in the theatrical system must be emphasized –that is, the analysis of the problems arising in the stages of the creation, presentation, and reception, by the public, of the theater performance. The aesthetic process is triggered involuntarily, simultaneously, or before the moment when people perceive the meaning of the messages transmitted by the work of art. The finding of this fact makes the mental process of aesthetics similar or related to that of semiotics. No matter how perceived individually, beauty, the mechanism of production can be reduced to two. The first step presents similarities to Peirce’s model, but the process between signified and signified additionally stimulates the related memory of the evaluation of beauty, adding to the meanings related to the signification itself. Then, the second step, a process of comparison, is followed, in which one examines whether the object being looked at matches the accumulated memory of beauty. Therefore, even though aesthetics is derived from the conceptual part, the judgment of beauty and, more than that, moral judgment come to be so important to the social activities of human beings that it evolves as a visible process independent of other conceptual contents.

Keywords: aesthetics, semiotics, symbolic composition, subjective joints, signifying, signified

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Authors: Annu Panghal, Bimla Dhanda

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This research paper aims to determine the genetic-environment influences on the cognitive abilities of twins. Using the 100 pairs of twins from two districts, namely: Bhiwani (N = 90) and Hisar (N = 110) of Haryana State, genetic and environmental influences were assessed in twin study design. The cognitive abilities of twins were measured using the Wechsler Intelligence Scale for Children (WISC-R). Home Observation for Measurement of the Environment (HOME) Inventory was taken to examine the home environment of twins. Heritability estimate was used to analyze the genes contributing to shape the cognitive abilities of twins. The heritability estimates for cognitive abilities of 6-7 years old twins in Hisar district were 74% and in Bhiwani District 76%. Further the heritability estimates were 64% in the twins of Hisar district and 60 in Bhiwani district % in the age group of 7-8 years. The remaining variations in the cognitive abilities of twins were due to environmental factors namely: provision for Active Stimulation, paternal involvement, safe physical environment. The findings provide robust evidence that the cognitive abilities were more influenced by genes than the environmental factors and also revealed that the influence of genetic was more in the age group 6-7 years than the age group 7-8 years. The conclusion of the heritability estimates indicates that the genetic influence was more in the age group of 6-7 years than the age group of 7-8 years. As the age increases the genetic influence decreases and environment influence increases. Mother education was strongly associated with the cognitive abilities of twins.

Keywords: genetics, heritability, twins, environment, cognitive abilities

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Ghorab Sara, Meziani Lila, Rubin Harvey Stuart

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The rapid growth of deep learning has led to intricate and resource-intensive deep neural networks widely used in computer vision tasks. However, their complexity results in high computational demands and memory usage, hindering real-time application. To address this, research focuses on model compression techniques. The paper provides an overview of recent advancements in compressing neural networks and categorizes the various methods into four main approaches: network pruning, quantization, network decomposition, and knowledge distillation. This paper aims to provide a comprehensive outline of both the advantages and limitations of each method.

Keywords: model compression, deep neural network, pruning, knowledge distillation, quantization, low-rank decomposition

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Authors: Ji Eun Shin, Byung Ho Jung, Dong Hoon Lim

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It is almost impossible to store or analyze big data increasing exponentially with traditional technologies. Hadoop is a new technology to make that possible. R programming language is by far the most popular statistical tool for big data analysis based on distributed processing with Hadoop technology. With RHadoop that integrates R and Hadoop environment, we implemented parallel multiple regression analysis with different sizes of actual data. Experimental results showed our RHadoop system was much faster as the number of data nodes increases. We also compared the performance of our RHadoop with lm function and big lm packages available on big memory. The results showed that our RHadoop was faster than other packages owing to paralleling processing with increasing the number of map tasks as the size of data increases.

Keywords: big data, Hadoop, parallel regression analysis, R, RHadoop

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Authors: Cheba Ben Amar

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Bacillus and Paenibacillus are Gram-positive aerobic endospore-forming bacteria (AEFB) and most abundant in the rhizosphere, they mediated plant growth promotion and disease protection by several complex and interrelated processes involving direct and indirect mechanisms that include nitrogen fixation, phosphate solubilization, siderophores production, phytohormones production and plant diseases control. In addition to their multiple PGPR properties, high secretory capacity, spore forming ability and spore resistance to unfavorable conditions enabling their extended commercial applications for long shelf-life. Due to these unique advantages, Bacillus species were the most an ideal candidate for developing efficient PGPR products such as biopesticides, fungicides and fertilizers. This review list all studied and reported plant growth promoting Bacillus species and strains, discuss their capacities to enhance plant growth and protection with special focusing on the most frequent species Bacillus subtilis, B. pumilus ,B. megaterium, B. amyloliquefaciens , B. licheniformis and B. sphaericus, furthermore we recapitulate the beneficial activities and mechanisms of several species and strains of the genus Paenibacillus involved in plant growth stimulation and plant disease control.

Keywords: bacillus, paenibacillus, PGPR, beneficial activities, mechanisms, growth promotion, disease control, agrobiotechnology

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Authors: Paula Andrea Segura Delgado, Martha Helena Ramírez-Bahena

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Research on how the brain learns has a transcendental application in the educational context. It is crucial for teacher training to understand the nature of brain changes and their direct influence on learning processes. This communication is based on a literature review focused on neuroscience, neuroeducation, and the impact of digital technology on the human brain. Information was gathered from both English and Spanish language sources, using online journals, books and reports. The general objective was to analyze the role of neuroscience knowledge in enriching our understanding of the learning process. In fact, the authors have focused on the impact of digital technology on the human brain as well as its influence in the field of education..Neuroscience knowledge can contribute significantly to improving the training of educators and therefore educational practices. Education as an instrument of change and school as an agent of socialization, it is necessary to understand what it aims to transform: the human brain. Understanding the functioning of the human brain has important repercussions on education: this elucidates cognitive skills, psychological processes and elements that influence the learning process (memory, executive functions, emotions and the circadian cycle); helps identify psychological and neurological deficits that can impede learning processes (dyslexia, autism, hyperactivity); It allows creating environments that promote brain development and contribute to the advancement of brain capabilities in alignment with the stages of neurobiological development. The digital age presents diverse opportunities to every social environment. The frequent use of digital technology (DT) has had a significant and abrupt impact on both the cognitive abilities and physico-chemical properties of the brain, significantly influencing educational processes. Hence, educational community, with the insights from advances in neuroscience, aspire to identify the positive and negative effects of digital technology on the human brain. This knowledge helps ensure the alignment of teacher training and practices with these findings. The knowledge of neuroscience enables teachers to develop teaching methods that are aligned with the way the brain works. For example, neuroscience research has shown that digital technology is having a significant impact on the human brain (addition, anxiety, high levels of dopamine, circadian cycle disorder, decrease in attention, memory, concentration, problems with their social relationships). Therefore, it is important to understand the nature of these changes, their impact on the learning process, and how educators should effectively adapt their approaches based on these brain's changes.

Keywords: digital technology, learn process, neuroscience knowledge, neuroeducation, training proffesors

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Authors: Mohammad H. Fattahi

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Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. The noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: chaotic behavior, wavelet, noise reduction, river flow

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Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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Authors: Ashis Pradhan, Mohan P. Pradhan

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Pattern Matching is useful for recognizing character in a digital image. OCR is one such technique which reads character from a digital image and recognizes them. Line segmentation is initially used for identifying character in an image and later refined by morphological operations like binarization, erosion, thinning, etc. The work discusses a recognition technique that defines a set of morphological operators based on its orientation in a character. These operators are further categorized into groups having similar shape but different orientation for efficient utilization of memory. Finally the characters are recognized in accordance with the occurrence of frequency in hierarchy of significant pattern of those morphological operators and by comparing them with the existing database of each character.

Keywords: binary image, morphological patterns, frequency count, priority, reduction data set and recognition

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Authors: A. Mech

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Repetitive transcranial magnetic stimulation has proven to be a valuable treatment option for patients who have failed to respond to multiple courses of antidepressant medication. In fact, the American Psychiatric Association recommends TMS after one failed treatment course of antidepressant medication. Genetic testing has proven valuable for pharmacokinetic variables, which, if understood, could lead to more efficient dosing of psychotropic medications to improve outcomes. Pharmacodynamic testing can identify biomarkers, which, if addressed, can improve patients' outcomes in antidepressant therapy. Monotherapy treatment of major depressive disorder with methylated B vitamin treatment has been shown to be safe and effective in patients with MTHFR polymorphisms without waiting for multiple trials of failed medication treatment for depression. Such treatment has demonstrated remission rates similar to antidepressant clinical trials. Combining pharmacodynamics testing with repetitive TMS treatment with NeuroStar has shown promising potential for enhancing remission rates and durability of treatment. In this study, a retrospective chart review (ongoing) of patients who obtained repetitive TMS treatment enhanced by dietary supplementation guided by Pharmacodynamic testing, displayed a greater remission rate (90%) than patients treated with only NeuroStar TMS (62%).

Keywords: improved remission rate, major depressive disorder, pharmacodynamic testing, rTMS outcomes

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Authors: R. Sudhesh Solomon, P. Y. K. L. Srinivas, Abhay Narayan, Amitava Das

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Users in social networks either unicast or broadcast their messages. At mention is the popular way of unicasting for Twitter whereas general tweeting could be considered as broadcasting method. Understanding the information flow and dynamics within a Social Network and modeling the same is a promising and an open research area called Information Diffusion. This paper seeks an answer to a fundamental question - understanding if the at-mention network or the unicasting pattern in social media is purely random in nature or is there any user specific selectional preference? To answer the question we present an empirical analysis to understand the sociological aspects of Twitter mentions network within a social network community. To understand the sociological behavior we analyze the values (Schwartz model: Achievement, Benevolence, Conformity, Hedonism, Power, Security, Self-Direction, Stimulation, Traditional and Universalism) of all the users. Empirical results suggest that values traits are indeed salient cue to understand how the mention-based communication network functions. For example, we notice that individuals possessing similar values unicast among themselves more often than with other value type people. We also observe that traditional and self-directed people do not maintain very close relationship in the network with the people of different values traits.

Keywords: information diffusion, personality and values, social network analysis, twitter mentions network

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Authors: Yifan Fan, Xudong Luo, Pingping Lin

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Nowadays, dialogue systems increasingly become the way for humans to access many computer systems. So, humans can interact with computers in natural language. A dialogue system consists of three parts: understanding what humans say in natural language, managing dialogue, and generating responses in natural language. In this paper, we survey deep learning based methods for dialogue management, response generation and dialogue evaluation. Specifically, these methods are based on neural network, long short-term memory network, deep reinforcement learning, pre-training and generative adversarial network. We compare these methods and point out the further research directions.

Keywords: dialogue management, response generation, deep learning, evaluation

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Authors: Roudabeh Vakil Monfared, Farhad Mashayekhi

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Breast cancer is the most common malignancy type among women with about 1 million new cases each year. The immune system plays an important role in the breast cancer development. OX40L (also known as TNFSF4), a membrane protein, which is a member of the tumor necrosis factor super family binds to its receptor OX40 and this co-stimulation has a crucial role in T-cell proliferation, survival and cytokine release. Due to the importance of the T-cells in anti-tumor activities of OX40L we studied the association of rs3850641 (T→C) polymorphism of OX40L gene with breast cancer. The study included 123 women with breast cancer and 126 healthy volunteers with no signs of cancer. Genomic DNA was extracted from blood leucocytes. Genotype and allele frequencies were determined in patients and control cases with the method of polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and the analysis was performed by Med Calc. The prevalence of genotype frequencies of TT, CT and CC were 60.9%, 30.08% and 8.9 % in patients with breast cancer and 74.6 %, 18.25 % and 7.14 % in healthy volunteers while the T and C allelic frequency was 76.01% and 23.98 % in patients and 83.73% and 16.26% in healthy controls. Respectively Statistical analysis has shown no significant difference from the comparison of either genotype (P=0.06). According to these results, the rs3850641 SNP has no association with the susceptibility of breast cancer in a population in northern Iran. However, further studies in larger populations including other genetic and environmental factors are required to achieve conclusion.

Keywords: OX40L, gene, polymorphism, breast cancer

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Authors: Mohammed Belloufi, Rachid Benzine, Badreddine Sellami

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Conjugate gradient methods is useful for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. It is well known that the search direction plays a main role in the line search method. In this paper, we propose a search direction with the Wolfe line search technique for solving unconstrained optimization problems. Under the above line searches and some assumptions, the global convergence properties of the given methods are discussed. Numerical results and comparisons with other CG methods are given.

Keywords: unconstrained optimization, conjugate gradient method, strong Wolfe line search, global convergence

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Authors: Neeraj Malhotra

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Background: Bioreactors in tissue engineering are used as devices that apply mechanical means to influence biological processes. They are commonly employed for stem cell culturing, growth and expansion as well as in 3D tissue culture. Contemporarily there use is well established and is tested extensively in the medical sciences, for tissue-regeneration and tissue engineering of organs like bone, cartilage, blood vessels, skin grafts, cardiac muscle etc. Methodology: Literature search, both electronic and hand search, was done using the following MeSH and keywords: bioreactors, bioreactors and dentistry, bioreactors & dental tissue engineering, bioreactors and regenerative dentistry. Articles published only in English language were included for review. Results: Bioreactors like, spinner flask-, rotating wall-, flow perfusion-, and micro-bioreactors and in-vivo bioreactor have been employed and tested for the regeneration of dental and like-tissues. These include gingival tissue, periodontal ligament, alveolar bone, mucosa, cementum and blood vessels. Based on their working dynamics they can be customized in future for regeneration of pulp tissue and whole tooth regeneration. Apart from this, they have been successfully used in testing the clinical efficacy and biological safety of dental biomaterials. Conclusion: Bioreactors have potential use in testing dental biomaterials and tissue engineering approaches aimed at regenerative dentistry.

Keywords: bioreactors, biological process, mechanical stimulation, regenerative dentistry, stem cells

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Authors: Eiko Takaoka, Yoshiyuki Fukushima, Koichiro Hirose, Tadashi Hasegawa

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Although all high school students in Japan are required to learn informatics, many of them do not learn this topic sufficiently. In response to this situation, we propose a support package for high school informatics classes. To examine what students learned and if they sufficiently understood the context of the lessons, a questionnaire survey was distributed to 186 students. We analyzed the results of the questionnaire and determined the weakest units, which were “basic computer configuration” and “memory and secondary storage”. We then developed a package for teaching these units. We propose that our package be applied in high school classrooms.

Keywords: computer science unplugged, computer science outreach, high school curriculum, experimental evaluation

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Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

Abstract:

Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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Authors: Zhan Chen, Wenquan Bi

Abstract:

This paper focuses on examining the strength of Midori against impossible differential attack. The Midori family of light weight block cipher orienting to energy-efficiency is proposed in ASIACRYPT2015. Using a 6-round property, the authors implement an 11-round impossible differential attack on Midori64 by extending two rounds on the top and three rounds on the bottom. There is enough key space to consider pre-whitening keys in this attack. An impossible differential path that minimises the key bits involved is used to reduce computational complexity. Several additional observations such as partial abort technique are used to further reduce data and time complexities. This attack has data complexity of 2 ⁶⁹·² chosen plaintexts, requires 2 ¹⁴·⁵⁸ blocks of memory and 2 ⁹⁴·⁷ 11- round Midori64 encryptions.

Keywords: cryptanalysis, impossible differential, light weight block cipher, Midori

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Authors: Ravid Inbar

Abstract:

CaMKII (calcium-calmodulin dependent protein kinase II) makes up 2% of the protein in our brain and has a critical role in memory formation and long-term potentiation of neurons. Despite this, research has yet to uncover the role of one of the domains on the activation of this kinase. The following proposes to express the protein without the hub domain in E. coli, leaving only the kinase and regulatory segment of the protein. Next, a series of kinase assays will be conducted to elucidate the role the hub domain plays on CaMKII sensitivity to calcium/calmodulin activation. The hub domain may be important for activation; however, it may also be a variety of domains working together to influence protein activation and not the hub alone. Characterization of a protein is critical to the future understanding of the protein's function, as well as for producing pharmacological targets in cases of patients with diseases.

Keywords: CaMKII, hub domain, kinase assays, kinase + reg seg

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Authors: Philip Robert Alldritt

Abstract:

The continuing increase in human migration is at crisis levels in all areas of the planet. The causes are varied, and the risks are high for the migrants. Migration has been ongoing since the beginning of human emergence on the planet, but for the first time in our historic memory has the, migration reached this level of critical mass. The causes are many. Climate collapse, economic opportunity, drug cartel activity, political upheaval, and gang wars. Many locations are seemingly “within reach” of the migrants, and the push factors are so loaded with hopelessness that almost anyone would be willing to risk anything to improve their conditions. There is no argument about that mass migrations are occurring and will increase in the future. The solutions to this increase are complex. This paper will examine the causes of migration and attempt to provide some reasonable solutions to mitigate the migrations with equitable outcomes that may guide immigration policy in impacted areas.

Keywords: immigration, crisis, climate, cartels

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Authors: Sania Ashraf

Abstract:

The paper focuses on the prevalence of informational efficiency and integration of GCC Shariah Equity market for the period of 01st January 2010 to 31st June 2015 with daily equity returns of Kuwait, Oman, Qatar, Bahrain, Saudi Arabia and United Arab Emirates. The study employs traditional as well as the modern approach of tracing out the efficiency and integration in the return series. From the results of efficiency it was observed that the market lacked efficiency in terms of its past information. The results of integration test clearly indicates that there was a long memory in the returns of GCC Shariah during the study period. Hence it was concluded and proved that the returns of all GCC Equity Shariah were not informationally efficient but fractionally integrated during the study period.

Keywords: efficiency, Fama, GCC shariah, hurst exponent, integration, serial correlation

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Authors: Medina Kadiri

Abstract:

Nigeria has an extensive coastline of 853 km long between latitude 4°10′ to 6°20′ N and longitude 2°45′ to 8°35′ E and situated in the Gulf of Guinea within the Guinea Current Large Marine Ecosystem. There is a substantial coastal community relying on this region for their livelihood of fishing, aquaculture, mariculture for various sea foods either for consumption or economic sustenance or both. Socio-economic study was conducted, using questionnaires and interview, to investigate the health symptoms of harmful algae experienced by these communities on consumption of sea foods. Eighteen symptoms were recorded. Of the respondents who experienced symptoms after consumption of sea foods, overall, more people (33.5%) experienced vomiting as a symptom, followed by nausea (14.03%) and then diarrhea (13.57%). Others were headache (9.95%), mouth tingling (8.6%) and tiredness (7.24%).The least were muscle pain, rashes, confusion, chills, burning sensation, breathing difficulty and balance difficulty which represented 0.45% each and the rest (dizziness, digestive tract tumors, itching, memory loss, & stomach pain) were less than 3% each. In terms of frequency, the most frequent symptom was diarrhea with 87.5% occurrence, closely followed by vomiting with 81.3%. Tiredness was 75% while nausea was 62.5% and headache 50%. Others such as dizziness, itching, memory loss, mouth tingling and stomach pain had about 40% occurrence or less. The least occurring symptoms were muscle pain, rashes, confusion, chills and balance difficulty and burning sensation occurring only once i.e 6.3%. Breathing difficulty was last but one with 12.5%. Visible symptom from seafood and the particular seafood consumed that prompted the visible symptoms, shows that 3.5% of the entire respondents who ate crab experienced various symptoms ranging from vomiting (2.4%), itching (0.5%) and headache (0.4%). For periwinkle, vomiting had 1.7%, while 1.2% represented diarrhea and nausea symptom comprised 0.8% of all the respondents who ate periwinkle. Some respondents who consumed fish shows that 0.4% of the respondents had Itching. From the respondents who preferred to consume shrimps/crayfish and crab, shrimps/crayfish, crab and periwinkle, the most common illness was tiredness (1.2%), while 0.5% had experienced diarrhea and many others. However, for most respondents who claimed to have no preference for any seafood, with 55.7% affirming this with vomiting being the highest (6.1%), followed closely by mouth tingling/ burning sensation (5.8%). Examining the seasonal influence on visible symptoms revealed that vomiting occurred more in the month of January with 5.5%, while headache and itching were predominant in October with (2.8%). Nausea has 3.1% in January than any season of the year, 2.6% of the entire respondents opined to have experience diarrhea in October than in any other season of the year. Regular evaluation of harmful algal poisoning symptoms is recommended for coastal communities.

Keywords: coastal, harmful algae, human poisoning symptoms, Nigeria, phycotoxins

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