Search results for: long memory

Authors: Alexander Rosenblatt

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The musical culture of the city of Los Angeles, as it is seen today, developed not without the influence of outstanding musicians who came from Europe during the period between the world wars. The combination of European modernist ideas with American musical culture, which differed in many ways from European musical culture, led to unique results. During the 1920s and even more so in the 1930s, members of the Austrian-German artistic intelligentsia, particularly those of Jewish origin who felt insecure in their homeland, began to look for a safer place. The United States has become such a place for many, and many of them chose the second largest metropolis—Los Angeles. The most notable figure in this group was the modernist composer Arnold Schoenberg. Other famous musicians were conductors Otto Klemperer and Bruno Walter. The study focused on how these people acclimated to a city whose culture and business revolved around film production; what place the conductors Klemperer and Walter occupied in the city, state, and country; how Schoenberg, whose musical style was little understood by the American public, was able to realize himself; what path he took when he was accepted to two universities as a professor of counterpoint and composition; and whether he revised his own views on the development of Western music. Another aspect was the study of how the composer’s memory was preserved in the universities where he taught. The study is based primarily on materials found in four libraries of two universities located in Los Angeles, UCLA and USC, during my tenure as a visiting scholar at USC Thornton School of Music (August 2023), to be completed during my upcoming visit there in August-September 2024, as well as on interviews with people active in efforts to keep Schoenberg’s memory alive on the USC Campus.

Keywords: los angeles, filmmaking, immigrant musicians, arnold schoenberg, otto klemperer, bruno walter

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Authors: Yuyun Sri Wahyuni, Fathih Misbahuddin Islam

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Nanggroe Aceh Darussalam is the special district with its long conflict history. The long conflict history started from The Free Aceh Movement’s intentions to implement Islamic principles in Aceh Province, it was actually contradicted with the principles of state. This long conflict was finally ended on 2005. Then, since 2005 Aceh had special authority to administer its local government affairs by applying Islamic principles (syariah), included criminal law matters. To administer it, Aceh Government enacted Law Number 6 of 2014 on the Jinayah. This law consists the criminal act (jarimah) and the punishment (uqubat). Khamr, maisir, khalwat, ikhtilath, zina, sexual harrasment, rape, qadzaf, liwath, and musahaqah are the kinds of the criminal act which are ruled within. Meanwhile, Hudud and Takdzir as the kinds of punishment (uqubat). After 2 years of the issuance of this law inflicting controversy from any sides and being discussed not only locally but also globally. The objectives of this paper are to analyze the fundamental value of the flagellation punishment within this law and Aceh Government review in formulating the law.

Keywords: Aceh province, flagellation punishment, Islamic Principle, Qanun Jinayah

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Authors: Vivian Wu

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During the mating season, honeybee drones make mating fights to congregation areas where they face fierce competition to mate with a queen. Drones have developed distinct anatomical and functional features in order to optimize their chances of success. Flight activities of western honeybee (Apis mellifera) drones and foragers were monitored using radio frequency identification (RFID) to test if drones have also developed distinct flight behaviors. Drone flight durations showed a bimodal distribution dividing the flights into short flights and long flights while forager flight durations showed a left-skewed unimodal distribution. Interestingly, the short trips occurred prior to the long trips on a daily basis. The first trips of the day the drones made were primarily short trips, and the distribution significantly shifted to long trips as the drones made more trips. In contrast, forager trips showed no such shift of distribution. In addition, drones made short trips but no long mating trips on days associated with a significant drop in temperature and increase of clouds compared to the previous day. These findings suggest that drones may have developed a unique flight behavior making short trips first to survey the weather conditions before flying out to the congregation area to pursue a successful mating.

Keywords: apis mellifera, drone, flight behavior, weather, RFID

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Authors: José Eduardo García-Mendiola

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In this work, a phenomenological approach to computational modeling of analogy processing is carried out. The paper goes through the consideration of the structure of the analogy, based on the possibility of sustaining the genesis of its elements regarding Husserl's genetic theory of association. Among particular processes which take place in order to get analogical inferences, there is one which arises crucial for enabling efficient base cases retrieval through long-term memory, namely analogical transference grounded on familiarity. In general, it has been argued that analogical reasoning is a way by which a conscious agent tries to determine or define a certain scope of objects and relationships between them using previous knowledge of other familiar domain of objects and relations. However, looking for a complete description of analogy process, a deeper consideration of phenomenological nature is required in so far, its simulation by computational programs is aimed. Also, one would get an idea of how complex it would be to have a fully computational account of the analogy elements. In fact, familiarity is not a result of a mere chain of repetitions of objects or events but generated insofar as the object/attribute or event in question is integrable inside a certain context that is taking shape as functionalities and functional approaches or perspectives of the object are being defined. Its familiarity is generated not by the identification of its parts or objective determinations as if they were isolated from those functionalities and approaches. Rather, at the core of such a familiarity between entities of different kinds lays the way they are functionally encoded. So, and hoping to make deeper inroads towards these topics, this essay allows us to consider that cognitive-computational perspectives can visualize, from the phenomenological projection of the analogy process reviewing achievements already obtained as well as exploration of new theoretical-experimental configurations towards implementation of analogy models in specific as well as in general purpose machines.

Keywords: analogy, association, encoding, retrieval

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Authors: Mohammad Maruf Hasan

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Foreign Direct Investment (FDI) has been increased at a remarkable position around the globe in which emerging economies are getting more FDI compared to industrialized economies. This study aims to examine the determinants of inward FDI flows in Bangladesh. To estimate the long and short-run impact of the FDI determinants for 1996-2020, we employed the Autoregressive-Distributed Lag (ARDL) model. Results show that: (1) macroeconomic determinants, such as economic growth, infrastructure, and market size, have a significant and strong positive effect.(2) Inflation exchange rate shows insignificant effects, while trade openness has mixed (short-run negative, long-run positive) effects on FDI inflows in both the long and short run. (3) Current institutional determinants rule of law has a positive effect on FDI inflows but is statistically insignificant, political stability has a negative, and the rule of law has a considerable beneficial impact on inflows of FDI. (4) The macroeconomic factors have been determined to impact Bangladesh's FDI inflows. Finally, a stable macroeconomic climate is more effective at luring FDI, as this study confirms. From a policy perspective, this study will help the government and policymakers to make a new investment policy.

Keywords: determinants, FDI, ARDL, Bangladesh

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Authors: Garima Joshi, Pratap Sharan, V. Sreenivas, Nand Kumar, Kameshwar Prasad, Ashima N. Wadhawan

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Schizophrenia is a debilitating disorder and is marked by cognitive impairment, which deleteriously impacts the social and professional functioning along with the quality of life of the patients and the caregivers. Often the cognitive symptoms are in their prodromal state and worsen as the illness progresses; they have proven to have a good predictive value for the prognosis of the illness. It has been shown that intensive cognitive rehabilitation (CR) leads to improvements in the healthy as well as cognitively-impaired subjects. As the majority of population in India falls in the lower to middle socio-economic status and have low education levels, using the existing packages, a majority of which are developed in the West, for cognitive rehabilitation becomes difficult. The use of technology is also restricted due to the high costs involved and the limited availability and familiarity with computers and other devices, which pose as an impedance for continued therapy. Cognitive rehabilitation in India uses a plethora of retraining methods for the patients with schizophrenia targeting the functions of attention, information processing, executive functions, learning and memory, and comprehension along with Social Cognition. Psychologists often have to follow an integrative therapy approach involving social skills training, family therapy and psychoeducation in order to maintain the gains from the cognitive rehabilitation in the long run. This paper reviews the methodologies and cognitive retaining programs used in India. It attempts to elucidate the evolution and development of methodologies used, from traditional paper-pencil based retraining to more sophisticated neuroscience-informed techniques in cognitive rehabilitation of deficits in schizophrenia as home-based or supervised and guided programs for cognitive rehabilitation.

Keywords: schizophrenia, cognitive rehabilitation, neuropsychological interventions, integrated approached to rehabilitation

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Authors: Soheila Sadeghi

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Accurate forecasting of project performance metrics is crucial for successfully managing and delivering urban road reconstruction projects. Traditional methods often rely on static baseline plans and fail to consider the dynamic nature of project progress and external factors. This research proposes a machine learning-based approach to forecast project performance metrics, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category in an urban road reconstruction project. The proposed model utilizes time series forecasting techniques, including Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance based on historical data and project progress. The model also incorporates external factors, such as weather patterns and resource availability, as features to enhance the accuracy of forecasts. By applying the predictive power of machine learning, the performance forecasting model enables proactive identification of potential deviations from the baseline plan, which allows project managers to take timely corrective actions. The research aims to validate the effectiveness of the proposed approach using a case study of an urban road reconstruction project, comparing the model's forecasts with actual project performance data. The findings of this research contribute to the advancement of project management practices in the construction industry, offering a data-driven solution for improving project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, earned value management

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Authors: Harry G. Segal

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The idea of the “self” has been essential ever since the early modern period in western culture, especially since the development of psychotherapy, but advances in neuroscience and cognitive theory challenge traditional notions of the self. More specifically, neuroanatomists have found no location of “the self” in the brain; instead, consciousness has been posited to be a rapid combination of perception, memory, anticipation of future events, and judgment. In this paper, a theoretical model is presented to address these neuroanatomical findings and to revise the historical understanding of “selfhood” in the practice of psychotherapy.

Keywords: the self, psychotherapy, the self and the brain

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Authors: Verónica Muñoz-Rivero

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The historically marginalized indigenous communities in the Atacama Desert continue to experience and struggle curricular hegemony in a prevalent monocultural educational context that denies heritage, culture and epistemologies in a documented attempted knowledge negation by the educational policies, the national curriculum and educational culture. The ancestral indigenous community of Toconce demands a territorial-based intercultural education and a school in their ancestral land to prevent the progressive cultural loss as they reclaim their memory and identity negated. This case study makes use of the intercultural theoretical framework and open qualitative methodology to analyze local socio-educational reality integrating aspects related to the educational experience, education demands for future generations and importance given to formal education. The interlocutors: elders, parents, caretakers and former teachers raised the educational experience for the indigenous childhood as an intergenerational voice that experienced discrimination, exclusion and racism on their K-12 trajectories. By center, the indigenous epistemologies, geography and memory, this research proposes a project-based learning approach anchored to the Limpia de Canales ceremony to develop a situated territorial intercultural curriculum unpacking from the local epistemology and structure thinking. The work on terraces gives students the opportunity to co-create a real-life application with practical purpose and present the importance of reinforcing notions related to the relevance of a situated intercultural curriculum for social justice in the formative development of prospective teachers.

Keywords: cultural studies, decolonial education, epistemic symmetry, intercultural curriculum, multidimensional curriculum

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Authors: Sunil Kumar, Vinay Kumar, Mamta Bulla, Rita Dahiya

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Supercapacitors have emerged as a leading energy storage technology, gaining popularity in applications like digital telecommunications, memory backup, and hybrid electric vehicles. Their appeal lies in a long cycle life, high power density, and rapid recharge capabilities. These exceptional traits attract researchers aiming to develop advanced, cost-effective, and high-energy-density electrode materials for next-generation energy storage solutions. Two-dimensional (2D) nanostructures are highly attractive for fabricating nanodevices due to their high surface-to-volume ratio and good compatibility with device design. In the current study, a composite was synthesized by combining MoS2 with reduced graphene oxide (rGO) under optimal conditions and characterized using various techniques, including XRD, FTIR, SEM and XPS. The electrochemical properties of the composite material were assessed through cyclic voltammetry, galvanostatic charging-discharging and electrochemical impedance spectroscopy. The supercapacitor device demonstrated a specific capacitance of 153 F g-1 at a current density of 1 Ag-1, achieving an excellent energy density of 30.5 Wh kg-1 and a power density of 600 W kg-1. Additionally, it maintained excellent cyclic stability over 5000 cycles, establishing it as a promising candidate for efficient and durable energy storage solutions. These findings highlight the dynamic relationship between electrode materials and offer valuable insights for the development and enhancement of high-performance symmetric devices.

Keywords: 2D material, energy density, galvanostatic charge-discharge, hydrothermal reactor, specific capacitance

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Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Nikolaos Konstantopoulos, Aristeidis Samitas, Vasileiou Evangelos

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The purpose of this study is to examine if the financial trends influence not only the stock markets’ returns, but also their anomalies. We choose to study the day of the week effect (DOW) for the Greek stock market during the Euro period (2002-12), because during the specific period there are not significant structural changes and there are long term financial trends. Moreover, in order to avoid possible methodological counterarguments that usually arise in the literature, we apply several linear (OLS) and nonlinear (GARCH family) models to our sample until we reach to the conclusion that the TGARCH model fits better to our sample than any other. Our results suggest that in the Greek stock market there is a long term predisposition for positive/negative returns depending on the weekday. However, the statistical significance is influenced from the financial trend. This influence may be the reason why there are conflict findings in the literature through the time. Finally, we combine the DOW’s empirical findings from 1985-2012 and we may assume that in the Greek case there is a tendency for long lived turn of the week effect.

Keywords: day of the week effect, GARCH family models, Athens stock exchange, economic growth, crisis

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Authors: Tamal Roy, Anuradha Bhat

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Cognitive abilities aid fishes in foraging, avoiding predators & locating mates. Factors like predation pressure & habitat complexity govern learning & memory in fishes. This study aims to compare spatial learning & memory across four natural populations of zebrafish. Zebrafish, a small cyprinid inhabits a diverse range of freshwater habitats & this makes it amenable to studies investigating role of native environment in spatial cognitive abilities. Four populations were collected across India from waterbodies with contrasting ecological conditions. Habitat complexity of the water-bodies was evaluated as a combination of channel substrate diversity and diversity of vegetation. Experiments were conducted on populations under controlled laboratory conditions. A square shaped spatial testing arena (maze) was constructed for testing the performance of adult zebrafish. The square tank consisted of an inner square shaped layer with the edges connected to the diagonal ends of the tank-walls by connections thereby forming four separate chambers. Each of the four chambers had a main door in the centre. Each chamber had three sections separated by two windows. A removable coloured window-pane (red, yellow, green or blue) identified each main door. A food reward associated with an artificial plant was always placed inside the left-hand section of the red-door chamber. The position of food-reward and plant within the red-door chamber was fixed. A test fish would have to explore the maze by taking turns and locate the food inside the right-side section of the red-door chamber. Fishes were sorted from each population stock and kept individually in separate containers for identification. At a time, a test fish was released into the arena and allowed 20 minutes to explore in order to find the food-reward. In this way, individual fishes were trained through the maze to locate the food reward for eight consecutive days. The position of red door, with the plant and the reward, was shuffled every day. Following training, an intermission of four days was given during which the fishes were not subjected to trials. Post-intermission, the fishes were re-tested on the 13th day following the same protocol for their ability to remember the learnt task. Exploratory tendencies and latency of individuals to explore on 1st day of training, performance time across trials, and number of mistakes made each day were recorded. Additionally, mechanism used by individuals to solve the maze each day was analyzed across populations. Fishes could be expected to use algorithm (sequence of turns) or associative cues in locating the food reward. Individuals of populations did not differ significantly in latencies and tendencies to explore. No relationship was found between exploration and learning across populations. High habitat-complexity populations had higher rates of learning & stronger memory while low habitat-complexity populations had lower rates of learning and much reduced abilities to remember. High habitat-complexity populations used associative cues more than algorithm for learning and remembering while low habitat-complexity populations used both equally. The study, therefore, helped understand the role of natural ecology in explaining variations in spatial learning abilities across populations.

Keywords: algorithm, associative cue, habitat complexity, population, spatial learning

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Authors: Euphrasia Susy Suhendra, Lies Handrijaningsih

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The banking sector as an intermediary party or intermediaries occupies a very important position in bridging the needs of working capital investment in the real sector with funds owner. This will certainly make money more effectively to improve the economic value added. As an intermediary, Islamic banks raise funds from the public and then distribute in the form of financing. In practice, the distribution of funding that is run by Islamic Banking is not as easy as, in theory, because, in fact, there are many financing problems; some are caused by lacking the assessment and supervision of banks to customers. This study aims to analyze the influence of the Third Party Funds, Return on Assets (ROA), Non Performing Financing (NPF), and Financing Deposit Ratio (FDR) to Total Financing provided to the Community by Islamic Banks in Indonesia. The data used is monthly data released by Bank of Indonesia in Islamic Banking Statistics in the time period of January 2009 - December 2013. This study uses cointegration test to see the long-term relationship, and use error correction models to examine the relationship of short-term. The results of this study indicate that the Third Party Fund has a short-term effect on total funding, Return on Assets has a long term effect on the total financing, Non Performing Financing has long-term effects of total financing, and Financing deposit ratio has the effect of short-term and long-term of the total financing provided by Islamic Banks in Indonesia.

Keywords: Islamic banking, third party fund, return on asset, non-performing financing, financing deposit ratio

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Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

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This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, web service, XML

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Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

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Authors: Hasan Basri Jumin

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The swamp land contains high iron, aluminum, and low pH. Calcium and magnesium in the rice husk ash can reduce plant poisoning so that plant growth increases in fertility. The first factor was the doze of rice husk, and the second factor was 0.0 g rhizobium inoculant /kg seed, 4.0 g rhizobium inoculant/kg seed, 8 g rhizobium inoculant /kg seed, and 12 g l rhizobium inoculant /kg seed. The plants were maintained under light conditions with a + 11.45 – 12.15 hour photoperiod. The combination between rhizobium inoculant and rice husk ash has been an interacting effect on the production of long bean pod fresh weight. The mean relative growth rate, net assimilation rate, and pod fresh weight are increased by a combination of husk rice ash and rhizobium inoculant. Rice husk ash affected increases the availability of nitrogen in the land, albeit in poor condition of nutrition. Rhizobium is active in creating a fixation of nitrogen in the atmosphere because rhizobium increases the abilities of intercellular and symbiotic nitrogen in the long beans. The combination of rice husk ash and rhizobium could be effected to create a thriving in the land.

Keywords: aluminium, calcium, fixation, iron, nitrogen

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Authors: Woo-Tai Jung, Sung-Yong Choi, Young-Hwan Park

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The composite pavement system considered in this paper is composed of a functional surface layer, a fiber reinforced asphalt middle layer and a fiber reinforced lean concrete base layer. The mix design of the fiber reinforced lean concrete corresponds to the mix composition of conventional lean concrete but reinforced by fibers. The quasi-absence of research on the durability or long-term performances (fatigue, creep, etc.) of such mix design stresses the necessity to evaluate experimentally the long-term characteristics of this layer composition. This study tests the creep characteristics as one of the long-term characteristics of the fiber reinforced lean concrete layer for composite pavement using a new creep device. The test results reveal that the lean concrete mixed with fiber reinforcement and fly ash develops smaller creep than the conventional lean concrete. The results of the application of the CEB-FIP prediction equation indicate that a modified creep prediction equation should be developed to fit with the new mix design of the layer.

Keywords: creep, lean concrete, pavement, fiber reinforced concrete, base

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Authors: Olga C. Rodrigue

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Long-term care and skilled nursing facilities experience ebbs and flows of nursing staffing, a problem compounded by the perception of the facilities as undesirable workplaces and competition for staff from other healthcare entities. Travel nurses are contracted to fill staffing needs due to increased admissions, increased and unexpected attrition of nurses, or facility expansion of services. Prior to beginning the contracted assignment, the travel nurse must meet industry, company, and regulatory requirements (The Joint Commission and CMS) for skills and knowledge. Travel nurses, however, inconsistently receive the pre-assignment orientation needed to work at the contracted facility, if any information is given at all. When performance expectations are not met, travel nurses may subsequently choose to leave the position without completing the terms of the contract, and some facilities may choose to terminate the contract prior to the expected end date. The overarching goal of the Doctor of Nursing Practice evidence-based practice improvement project is to provide travel nurses with the basic and necessary information to prepare them to begin a long-term and skilled nursing assignment. The project involves the identification of travel nurse learning needs through a survey and the development and provision of web-based learning modules to address those needs prior to arrival for a long-term and skilled nursing assignment.

Keywords: nurse staffing, travel nurse, travel staff, contract staff, contracted assignment, long-term care, skilled nursing, onboarding, orientation, staff development, supplemental staff

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Authors: Maher Ali Rusho, Sudipta Halder

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The purpose of the study is to develop optimal solutions for models of parallel computing systems using the Java language. During the study, programmes were written for the examined models of parallel computing systems. The result of the parallel sorting code is the output of a sorted array of random numbers. When processing data in parallel, the time spent on processing and the first elements of the list of squared numbers are displayed. When processing requests asynchronously, processing completion messages are displayed for each task with a slight delay. The main results include the development of optimisation methods for algorithms and processes, such as the division of tasks into subtasks, the use of non-blocking algorithms, effective memory management, and load balancing, as well as the construction of diagrams and comparison of these methods by characteristics, including descriptions, implementation examples, and advantages. In addition, various specialised libraries were analysed to improve the performance and scalability of the models. The results of the work performed showed a substantial improvement in response time, bandwidth, and resource efficiency in parallel computing systems. Scalability and load analysis assessments were conducted, demonstrating how the system responds to an increase in data volume or the number of threads. Profiling tools were used to analyse performance in detail and identify bottlenecks in models, which improved the architecture and implementation of parallel computing systems. The obtained results emphasise the importance of choosing the right methods and tools for optimising parallel computing systems, which can substantially improve their performance and efficiency.

Keywords: algorithm optimisation, memory management, load balancing, performance profiling, asynchronous programming.

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Authors: N. Uaphongsathorn, C. Worawong, S. Thaewpia

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Background and significance: The population is aging in Thai society, the elderly dependent is at great risk of various functional, psychological, and socio-economic problems as well as less access to health care. They may require long term care at home to maximize their functional abilities and activities of daily living and to improve their quality of life during their own age. Therefore, there is a need to develop a home-based long term care to meet the long term care needs of elders dependent. Methods: The research purpose was to develop long term care model among the elderly dependent in Chaiyaphum province in Northeast region of Thailand. Action Research which is composing of planning, action, observation, and reflection phases was used. Research was carried out for 12 months in all sub-districts of 6 districts in Chaiyaphum province. Participants (N = 1,010) participating in the processes of model development were comprised of 3 groups: a) a total of 110 health care professionals, b) a total of 600 health volunteers and family caregivers and c) a total of 300 the elderly dependent with chronically medical illnesses or disabilities. Descriptive statistics and content analysis were used to analyze data. Findings: Results have shown that the most common health problems among elders dependent with physical disabilities to function independently were cardiovascular disease, dementia, and traffic injuries. The development of home-based long term care model among elders dependent in Chaiyaphum province was composed of six key steps. They are: a) initiating policies supporting formal and informal caregivers for the elder dependent in all sub-districts, b) building network and multidisciplinary team, c) developing 3-day care manager training program and 3-day care provider training program d) training case managers and care providers for the elderly dependent through team and action learning, e) assessing, planning and providing care based on care individual’s needs of the elderly dependent, and f) sharing experiences for good practice and innovation for long term care at homes in district urban and rural areas. Among all care managers and care providers, the satisfaction level for training programs was high with a mean score of 3.98 out of 5. The elders dependent and family caregivers addressed that long term care at home could contribute to improving life’s daily activities, family relationship, health status, and quality of life. Family caregivers and volunteers have feeling a sense of personal satisfaction and experiencing providing meaningful care and support for elders dependent. Conclusion: In conclusion, a home-based long term care is important to Thai elders dependent. Care managers and care providers play a large role and responsibility to provide appropriate care to meet the elders’ needs in both urban and rural areas in Thai society. Further research could be rigorously studied with a larger group of populations in similar socio-economic and cultural contexts.

Keywords: elderly people, care manager, care provider, long term care

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Authors: Xinyi Xu

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This study conducts a detailed examination of Asian stock markets over the period from 2008 to 2023, with a focus on the dynamics of cointegration and their relevance for long-term investment strategies. Specifically, we assess the co-movement and potential for pairs trading—a strategy where investors take opposing positions on two stocks, indices, or financial instruments that historically move together. For example, we explore the relationship between the Nikkei 225 (N225), Japan’s benchmark stock index, and the Straits Times Index (STI) of Singapore, as well as the relationship between the Korea Composite Stock Price Index (KS11) and the STI. The methodology includes tests for normality, stationarity, cointegration, and the application of Vector Error Correction Modeling (VECM). Our findings reveal significant long-term relationships between these pairs, indicating opportunities for pairs trading strategies. Furthermore, the research underscores the challenges posed by model instability and the influence of major global incidents, which are identified as structural breaks. These findings pave the way for further exploration into the intricacies of financial market dynamics.

Keywords: normality tests, stationarity, cointegration, VECM, pairs trading

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Authors: Matthias Nnadi

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This paper investigates the relationship between premiums and returns in the short and long terms in European merger and acquisition (M&A) deals. The study employs Calendar Time Portfolio (CTP) model and find strong evidence that in the long run, premiums have a positive impact on performance, and we also establish evidence of a significant difference between the abnormal returns of the high premium paying portfolio and the low premium paying ones. Even in cases where all sub-portfolios show negative abnormal returns, the high premium category still outperforms the low premium category. Our findings have implications for companies engaging in acquisitions.

Keywords: mergers, premium, performance, returns, acquisitions

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Authors: Noga Bregman

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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.

Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves

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Authors: Saida Haider, Syeda Madiha

Abstract:

Parkinson’s disease (PD) is a common neurological disorder characterized by motor deficits and loss of dopaminergic neurons. Oxidative stress is said to play a pivotal role in the pathophysiology of the disease. In the present study, PD was induced by injection of rotenone (1.5 mg/kg/day, s.c.) for eight days. Pistachio (800 mg/kg/day, p.o.) was given for two weeks. At the end of treatment brains were dissected out and striatum was isolated for biochemical and neurochemical analysis. Morris water maze (MWM) test and novel object recognition (NOR) task was used to test the memory function while motor behavior was determined by open field test (OFT), Kondziela inverted screen test (KIST), pole test (PT), beam walking test (BWT), inclined plane test (IPT) and footprint (FP) test. Several dietary components have been evaluated as potential therapeutic compounds in many neurodegenerative diseases. Increasing evidence shows that nuts have protective effects against various diseases by improving the oxidative status and reducing lipid peroxidation. Pistachio is the only nut that contains anthocyanin, a potent antioxidant having neuroprotective properties. Results showed that pistachio supplementation significantly restored the rotenone-induced motor deficits and improved the memory performance. Moreover, rats treated with pistachio also exhibited enhanced oxidative status and increased dopamine (DA) and 5-hydroxytryptamine (5-HT) concentration in striatum. In conclusion, to our best knowledge, we have for the first time shown that pistachio nut possesses neuroprotective effects against rotenone-induced motor and cognitive deficits. These beneficial effects of pistachio may be attributed to its high content of natural antioxidant and phenolic compounds. Hence, consumption of pistachio regularly as part of a daily diet can be beneficial in the prevention and treatment of PD.

Keywords: rotenone, pistachio, oxidative stress, Parkinson’s disease

Procedia PDF Downloads 105

Authors: Haruo Okabayashi

Abstract:

Human biological signals (pulse wave and brain wave, etc.) have a rhythm which shows fluctuations. This study investigates the relationship between fluctuations of biological signals which are shown by a finger plethysmogram (i.e., finger pulse wave) in conversation and anthropophobic tendency, and identifies whether the fluctuation could be an index of mental health. 32 college students participated in the experiment. The finger plethysmogram of each subject was measured in the following conversation situations: Fun memory talking/listening situation and regrettable memory talking/ listening situation for three minutes each. Lyspect 3.5 was used to collect the data of the finger plethysmogram. Since Lyspect calculates the Lyapunov spectrum, it is possible to obtain the largest Lyapunov exponent (LLE). LLE is an indicator of the fluctuation and shows the degree to which a measure is going away from close proximity to the track in a dynamical system. Before the finger plethysmogram experiment, each participant took the psychological test questionnaire “Anthropophobic Scale.” The scale measures the social phobia trend close to the consciousness of social phobia. It is revealed that there is a remarkable relationship between the fluctuation of the finger plethysmography and anthropophobic tendency scale in talking about a regrettable story in conversation: The participants (N=15) who have a low anthropophobic tendency show significantly more fluctuation of finger pulse waves than the participants (N=17) who have a high anthropophobic tendency (F (1, 31) =5.66, p<0.05). That is, the participants who have a low anthropophobic tendency make conversation flexibly using large fluctuation of biological signal; on the other hand, the participants who have a high anthropophobic tendency constrain a conversation because of small fluctuation. Therefore, fluctuation is not an error but an important drive to make better relationships with others and go towards the development of interaction. In considering mental health, the fluctuation of biological signals would be an important indicator.

Keywords: anthropophobic tendency, finger plethymogram, fluctuation of biological signal, LLE

Procedia PDF Downloads 237

Authors: Elie Awwad, Bilal Hamad, Mounir Mabsout, Helmi Khatib

Abstract:

The paper reports test results on the long-term behavior of sustainable hemp-concrete material prepared in research work conducted at the American University of Beirut. The tests results are in terms of compressive and splitting tensile tests conducted on standard 150x300 mm cylinders. A control mix without fibers, one polypropylene-concrete mix, and ten hemp-concrete mixes were prepared with different percentages of industrial hemp fibers and reduced coarse aggregate contents. The objective was to investigate the strength properties of hemp-reinforced concrete at 1.5 years age as compared with control mixes. The results indicated that both the compressive strength and the splitting tensile strength results of all tested cylinders increased as compared with the 28-days values. Also, the difference between the hemp-concrete samples and the control samples at 28 days was maintained at 1.5 years age indicating that hemp fibers did not exhibit any negative effect on the long-term strength properties of concrete.

Keywords: hemp-reinforced concrete, natural fibers, compressive strength, splitting tensile strength

Procedia PDF Downloads 361

Authors: Alexander Rych

Abstract:

Piql Preservation Services (“Piql”) is a turnkey solution designed for secure, migration-free long- term preservation of digital data. Piql sets an open standard for long- term preservation for the future. It consists of equipment and processes needed for writing and retrieving digital data. Exponentially growing amounts of data demand for logistically effective and cost effective processes. Digital storage media (hard disks, magnetic tape) exhibit limited lifetime. Repetitive data migration to overcome rapid obsolescence of hardware and software bears accelerated risk of data loss, data corruption or even manipulation and adds significant repetitive costs for hardware and software investments. Piql stores any kind of data in its digital as well as analog form securely for 500 years. The medium that provides this is a film reel. Using photosensitive film polyester base, a very stable material that is known for its immutability over hundreds of years, secure and cost-effective long- term preservation can be provided. The film reel itself is stored in a packaging capable of protecting the optical storage medium. These components have undergone extensive testing to ensure longevity of up to 500 years. In addition to its durability, film is a true WORM (write once- read many) medium. It therefore is resistant to editing or manipulation. Being able to store any form of data onto the film makes Piql a superior solution for long-term preservation. Paper documents, images, video or audio sequences – all of those file formats and documents can be preserved in its native file structure. In order to restore the encoded digital data, only a film scanner, a digital camera or any appropriate optical reading device will be needed in the future. Every film reel includes an index section describing the data saved on the film. It also contains a content section carrying meta-data, enabling users in the future to rebuild software in order to read and decode the digital information.

Keywords: digital data, long-term preservation, migration-free, photosensitive film

Procedia PDF Downloads 390

Authors: Doaa Hashad, Amany Elbanna, Abeer Ibrahim, Gihan Khedr

Abstract:

Background: H19 is one of the long non coding RNAs (LncRNA) that is related to the progression of many diseases including cancers. This work was carried out to study the level of the long non-coding RNA; H119, in plasma of patients with gastric cancer (GC) and to assess its significance in their clinical management. Methods: A total of sixty-two participants were enrolled in the present study. The first group included thirty-two GC patients, while the second group was formed of thirty age and sex matched healthy volunteers serving as a control group. Plasma samples were used to assess H19 gene expression using real time quantitative PCR technique. Results: H19 expression was up-regulated in GC patients with positive correlation to TNM cancer stages. Conclusions: Up-regulation of H19 is closely associated with gastric cancer and correlates well with tumor staging. Convenient, efficient quantification of H19 in plasma using real time PCR technique implements its role as a potential noninvasive prognostic biomarker in gastric cancer, that predicts patient’s outcome and most importantly as a novel target in gastric cancer treatment with better performance achieved on using both CEA and H19 simultaneously.

Keywords: biomarker, gastric, cancer, LncRNA

Procedia PDF Downloads 317

Authors: G. S. Ayyappan, Srinivas Kota, Jaffer R. C. Sheriff, C. Prakash Chandra Joshua

Abstract:

In the present scenario of energy crises, energy conservation in the electrical machines is very important in the industries. In order to conserve energy, one needs to monitor the performance of an induction motor on-site and in-situ. The instruments available for this purpose are very meager and very expensive. This paper deals with the design and development of induction motor performance analyser on-line, on-site, and in-situ. The system measures only few electrical input parameters like input voltage, line current, power factor, frequency, powers, and motor shaft speed. These measured data are coupled to name plate details and compute the operating efficiency of induction motor. This system employs the method of computing motor losses with the help of equivalent circuit parameters. The equivalent circuit parameters of the concerned motor are estimated using the developed algorithm at any load conditions and stored in the system memory. The developed instrument is a reliable, accurate, compact, rugged, and cost-effective one. This portable instrument could be used as a handy tool to study the performance of both slip ring and cage induction motors. During the analysis, the data can be stored in SD Memory card and one can perform various analyses like load vs. efficiency, torque vs. speed characteristics, etc. With the help of the developed instrument, one can operate the motor around its Best Operating Point (BOP). Continuous monitoring of the motor efficiency could lead to Life Cycle Assessment (LCA) of motors. LCA helps in taking decisions on motor replacement or retaining or refurbishment.

Keywords: energy conservation, equivalent circuit parameters, induction motor efficiency, life cycle assessment, motor performance analysis

Procedia PDF Downloads 379