Search results for: tightly coupled memory

Authors: T. M. L. Hoang, G. Tan, S. D. Bhowmik, B. Williams, A. Johnson, M. R. Karbaschi, Y. Cheng, H. Long, S. G. Mundree

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Iron deficiency is a worldwide problem affecting both developed and developing countries. Currently, two major approaches namely iron supplementation and food fortification have been used to combat this issue. These measures, however, are limited by the economic status of the targeted demographics. Iron biofortification through genetic modification to enhance the inherent iron content and bioavailability of crops has been employed recently. Several important crops such as rice, wheat, and banana were reported successfully improved iron content via this method, but there is no known study in legumes. Chickpea (Cicer arietinum) is an important leguminous crop that is widely consumed, particularly in India where iron deficiency anaemia is prevalent. Chickpea is also an ideal pulse in the formulation of complementary food between pulses and cereals to improve micronutrient contents. This project aims at generating enhanced ion accumulation and bioavailability chickpea through the exogenous expression of genes related to iron transport and iron homeostasis in chickpea plants. Iron-Regulated Transport (IRT) and Ferritin genes in combination were transformed into chickpea half-embryonic axis by agrobacterium–mediated transformation. Transgenic independent event was confirmed by Southern Blot analysis. T3 leaves and seeds of transgenic chickpea were assessed for iron contents using LA-ICP-MS (Laser Ablation – Inductively Coupled Plasma Mass Spectrometry) and ICP-OES (Inductively Coupled Plasma Optical Emission Spectrometry). The correlation between transgene expression levels and iron content in T3 plants and seeds was assessed using qPCR. Results show that iron content in transgenic chickpea expressing the above genes significantly increased compared to that in non-transgenic controls.

Keywords: iron biofortification, chickpea, IRT, ferritin, Agrobacterium-mediated transformation, LA-ICP-MS, ICP-OES

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Authors: Akanksha Bhatnagar, Sandhya Kortegare, Felice Elefant

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

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

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Authors: Kamal Ameis

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This study aims to further improve our understanding of the underlying mechanism of local injury that occurs after manual acupuncture needle manipulation, and that initiates the muscle regeneration process, which is essential for muscle maintenance and adaptation. Skeletal muscle is maintained by resident stem cells called muscle satellite cells. These cells are normally in quiescent state, but following muscle injury, they re-enter the cell cycle and execute a myogenic program resulting in muscle fiber regeneration. Our previous work in young rats demonstrated that acupuncture treatment induced injury that activated resident satellite (stem) cells, which leads to muscle regeneration. Skeletal muscle regeneration is an adaptive response to injury that requires a tightly orchestrated event between signaling pathways activated by growth factor and intrinsic regulatory program controlled by myogenic transcription factor. We identified several gene expressions uniquely important for muscle regeneration in response to acupuncture treatment at different time course using different biological techniques, including Immunocytochemistry, western blotting, and Real Time PCR. This study uses a novel but non-invasive model of injury induced by manual acupuncture to further our current understanding of regenerative mechanism of muscle stem cells. From a clinical perspective, this model of injury induced by manual acupuncture may be easily translatable into a clinical tool that can be used as an alternative to physical exercise for patients challenged by bed rest or forced inactivity. Finally, the knowledge gained from this research could be useful for studies of the local effects of various modalities of induced injury, such as the traditional method of healing by cupping (hijamah), which may enhanced muscle stem cells and muscle fiber regeneration.

Keywords: acupuncture, injury, regeneration, muscle stem cells

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Authors: Maiko Kiyohara, Toshiki Ito

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In this study, we used a psychotherapy process for patient with dissociative disorder and the graphic Rorschach (Digital version) (GRD). A dissociative disorder is a type of dissociation characterized by multiple alternating personalities (also called alternate identity or another identity). "dissociation" is a state in which consciousness, memory, thinking, emotion, perception, behavior, body image, and so on are divided and experienced. Dissociation symptoms, such as lack of memory, are seen, and the repetition of blanks in daily events causes serious problems in life. Although the pathological mechanism of dissociation has not yet been fully elucidated, it is said that it is caused by childhood abuse or shocking trauma. In case of Japan, no reliable data has been reported on the number of patients and prevalence of dissociative disorders, no drug is compatible with dissociation symptoms, and no clear treatment has been established. GRD is a method that the author revised in 2017 to a Graphic Rorschach, which is a special technique for subjects to draw language responses when enforce Rorschach. GRD reduces the burden on both the subject and the examiner, reduces the complexity of organizing data, improves the simplicity of organizing data, and improves the accuracy of interpretation by introducing a tablet computer during the drawing reaction. We are conducting research for the purpose. The patient in this case is a woman in her 50s, and has multiple personalities since childhood. At present, there are about 10 personalities whose main personality is just grasped. The patients is raising her junior high school sons as single parent, but personal changes often occur at home, which makes the home environment inferior and economically oppressive, and has severely hindered daily life. In psychotherapy, while a personality different from the main personality has appeared, I have also conducted psychotherapy with her son. In this case, the psychotherapy process and the GRD were performed to understand the personality characteristics, and the possibility of therapeutic significance to personality integration is reported.

Keywords: GRD, dissociative disorder, a case study of psychotherapy process, dissociation

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Authors: Ebipatei Victoria Tunyan, T. A. Cao, Cheol Young Ock

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Detecting subjectively biased statements is a vital task. This is because this kind of bias, when present in the text or other forms of information dissemination media such as news, social media, scientific texts, and encyclopedias, can weaken trust in the information and stir conflicts amongst consumers. Subjective bias detection is also critical for many Natural Language Processing (NLP) tasks like sentiment analysis, opinion identification, and bias neutralization. Having a system that can adequately detect subjectivity in text will boost research in the above-mentioned areas significantly. It can also come in handy for platforms like Wikipedia, where the use of neutral language is of importance. The goal of this work is to identify the subjectively biased language in text on a sentence level. With machine learning, we can solve complex AI problems, making it a good fit for the problem of subjective bias detection. A key step in this approach is to train a classifier based on BERT (Bidirectional Encoder Representations from Transformers) as upstream model. BERT by itself can be used as a classifier; however, in this study, we use BERT as data preprocessor as well as an embedding generator for a Bi-LSTM (Bidirectional Long Short-Term Memory) network incorporated with attention mechanism. This approach produces a deeper and better classifier. We evaluate the effectiveness of our model using the Wiki Neutrality Corpus (WNC), which was compiled from Wikipedia edits that removed various biased instances from sentences as a benchmark dataset, with which we also compare our model to existing approaches. Experimental analysis indicates an improved performance, as our model achieved state-of-the-art accuracy in detecting subjective bias. This study focuses on the English language, but the model can be fine-tuned to accommodate other languages.

Keywords: subjective bias detection, machine learning, BERT–BiLSTM–Attention, text classification, natural language processing

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Authors: Victor N. Anisimov, Igor E. Serov, Ksenia M. Kolkova, Natalia V. Galkina

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The problem of memorability of the advertising content is closely connected with the key issues of neuromarketing. The memorability of the advertising content contributes to the marketing effectiveness of the promoted product. Significant directions of studying the phenomenon of memorability are the memorability of the brand (detected through the memorability of the logo) and the memorability of the product offer (detected through the memorization of dynamic audiovisual advertising content - commercial). The aim of this work is to reveal the predictors of memorization of static and dynamic audiovisual stimuli (logos and commercials). An important direction of the research was revealing differences in psychophysiological correlates of memorability between static and dynamic audiovisual stimuli. We assumed that static and dynamic images are perceived in different ways and may have a difference in the memorization process. Objective methods of recording psychophysiological parameters while watching static and dynamic audiovisual materials are well suited to achieve the aim. The electroencephalography (EEG) method was performed with the aim of identifying correlates of the memorability of various stimuli in the electrical activity of the cerebral cortex. All stimuli (in the groups of statics and dynamics separately) were divided into 2 groups – remembered and not remembered based on the results of the questioning method. The questionnaires were filled out by survey participants after viewing the stimuli not immediately, but after a time interval (for detecting stimuli recorded through long-term memorization). Using statistical method, we developed the classifier (statistical model) that predicts which group (remembered or not remembered) stimuli gets, based on psychophysiological perception. The result of the statistical model was compared with the results of the questionnaire. Conclusions: Predictors of the memorability of static and dynamic stimuli have been identified, which allows prediction of which stimuli will have a higher probability of remembering. Further developments of this study will be the creation of stimulus memory model with the possibility of recognizing the stimulus as previously seen or new. Thus, in the process of remembering the stimulus, it is planned to take into account the stimulus recognition factor, which is one of the most important tasks for neuromarketing.

Keywords: memory, commercials, neuromarketing, EEG, branding

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Authors: Samaneh Nabavi, Hadi Shirzad, Somayeh Khanjani, Shirin Jalili

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Quantum dots (QDs) are semiconductor nanocrystals that exhibit intrinsic optical and electrical properties that are size dependent due to the quantum confinement effect. Quantum confinement is brought about by the fact that in bulk semiconductor material the electronic structure consists of continuous bands, and that as the size of the semiconductor material decreases its radius becomes less than the Bohr exciton radius (the distance between the electron and electron-hole) and discrete energy levels result. As a result QDs have a broad absorption range and a narrow emission which correlates to the band gap energy (E), and hence QD size. QDs can thus be tuned to give the desired wavelength of fluorescence emission.Due to their unique properties, QDs have attracted considerable attention in different scientific areas. Also, they have been considered for forensic applications in recent years. The ability of QDs to fluoresce up to 20 times brighter than available fluorescent dyes makes them an attractive nanomaterial for enhancing the visualization of latent fingermarks, or poorly developed fingermarks. Furthermore, the potential applications of QDs in the detection of nitroaromatic explosives, such as TNT, based on directive fluorescence quenching of QDs, electron transfer quenching process or fluorescence resonance energy transfer have been paid to attention. DNA analysis is associated tightly with forensic applications in molecular diagnostics. The amount of DNA acquired at a criminal site is inherently limited. This limited amount of human DNA has to be quantified accurately after the process of DNA extraction. Accordingly, highly sensitive detection of human genomic DNA is an essential issue for forensic study. QDs have also a variety of advantages as an emission probe in forensic DNA quantification.

Keywords: forensic science, quantum dots, DNA typing, explosive sensor, fingermark analysis

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Authors: F. V. Matta, C. M. Donnelly, M. B. Jaafar, N. I. Ward

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‘Yerba Mate’ (Ilex paraguariensis) is a native plant from South America with the main producers being Argentina and Brazil. ‘Mate’ is widely consumed in Argentina, Brazil, Uruguay and Paraguay. The most popular format is as an infusion made from dried leaves of a traditional cup, roasted material in tea bags or iced tea infusions. There are many alleged health benefits resulted from mate consumption, even though there is a lack of conclusive research published in the international literature. The main objective of this study was to develop and evaluate the sample preparation and instrumental analysis stages involved in the determination of trace elements in yerba mate using inductively coupled plasma mass spectrometry (ICP-MS). Specific details on the methods of sample digestion, validation of the ICP-MS analysis especially for polyatomic ion correction and matrix effects associated with the complex medium of mate will be presented. More importantly, mate produced in Brazil and Argentina, is subject to different soil conditions, methods of cultivation and production, especially for loose leaves and tea bags. The highest concentrations for loose mate leaf were for (mg/kg, dry weight): aluminium (253.6 – 506.9 for Brazil (Bra), 230.0 – 541.8 for Argentina (Arg), respectively), manganese (378.3 – 762.6 Bra; 440.8 – 879.9 Arg), iron (32.5 – 85.7 Bra; 28.2 – 132.9 Arg), zinc (28.2 – 91.1 Bra; 39.1 – 92.3 Arg), nickel (2.2 – 4.3 Bra; 2.9 – 10.8 Arg) and copper (4.8 – 9.1 Bra; 4.3 – 9.2 Arg), with lower levels of chromium, cobalt, selenium, molybdenum, cadmium, lead and arsenic. Elemental levels of mate leaf consumed in tea bags were found to be higher, mainly due to only using leaf material (as opposed to leaf and twig for loose packed product). Further implications of the way of consuming yerba mate will be presented, including different infusion methods in Brazil and Argentina. This research provides for the first time an extensive evaluation of mate products from both countries and the possible implications of specific trace elements, especially Mn, Fe, Se, Cu and Zn and the various health claims of consuming yerba mate.

Keywords: beverage analysis, ICP-MS, trace elements, yerba mate

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Authors: Azza A. Ali, Abeer I. Abd El-Fattah, Shaimaa S. Hussein, Hanan A. Abd El-Samea, Karema Abu-Elfotuh

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Background: Aluminium (Al) represents an environmental risk factor. Exposure to high levels of Al causes neurotoxic effects and different diseases. Vinpocetine is widely used to improve cognitive functions, it possesses memory-protective and memory-enhancing properties and has the ability to increase cerebral blood flow and glucose uptake. Cocoa bean represents a rich source of iron as well as a potent antioxidant. It can protect from the impact of free radicals, reduces stress as well as depression and promotes better memory and concentration. Wheatgrass is primarily used as a concentrated source of nutrients. It contains vitamins, minerals, carbohydrates, amino acids and possesses antioxidant and anti-inflammatory activities. Coenzyme Q10 (CoQ10) is an intracellular antioxidant and mitochondrial membrane stabilizer. It is effective in improving cognitive disorders and has been used as anti-aging. Zinc is a structural element of many proteins and signaling messenger that is released by neural activity at many central excitatory synapses. Objective: To study the role of some nutrients and drugs as Vinpocetine, Cocoa, Wheatgrass, CoQ10 and Zinc against neurotoxicity induced by Al in rats as well as to compare between their potency in providing protection. Methods: Seven groups of rats were used and received daily for three weeks AlCl3 (70 mg/kg, IP) for Al-toxicity model groups except for the control group which received saline. All groups of Al-toxicity model except one group (non-treated) were co-administered orally together with AlCl3 the following treatments; Vinpocetine (20mg/kg), Cocoa powder (24mg/kg), Wheat grass (100mg/kg), CoQ10 (200mg/kg) or Zinc (32mg/kg). Biochemical changes in the rat brain as acetyl cholinesterase (ACHE), Aβ, brain derived neurotrophic factor (BDNF), inflammatory mediators (TNF-α, IL-1β), oxidative parameters (MDA, SOD, TAC) were estimated for all groups besides histopathological examinations in different brain regions. Results: Neurotoxicity and neurodegenerations in the rat brain after three weeks of Al exposure were indicated by the significant increase in Aβ, ACHE, MDA, TNF-α, IL-1β, DNA fragmentation together with the significant decrease in SOD, TAC, BDNF and confirmed by the histopathological changes in the brain. On the other hand, co-administration of each of Vinpocetine, Cocoa, Wheatgrass, CoQ10 or Zinc together with AlCl3 provided protection against hazards of neurotoxicity and neurodegenerations induced by Al, their protection were indicated by the decrease in Aβ, ACHE, MDA, TNF-α, IL-1β, DNA fragmentation together with the increase in SOD, TAC, BDNF and confirmed by the histopathological examinations of different brain regions. Vinpocetine and Cocoa showed the most pronounced protection while Zinc provided the least protective effects than the other used nutrients and drugs. Conclusion: Different degrees of protection from neurotoxicity and neuronal degenerations induced by Al could be achieved through the co-administration of some nutrients and drugs during its exposure. Vinpocetine and Cocoa provided the most protection than Wheat grass, CoQ10 or Zinc which showed the least protective effects.

Keywords: aluminum, neurotoxicity, vinpocetine, cocoa, wheat grass, coenzyme Q10, Zinc, rats

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Authors: Sun fang, Zhang Wenxin

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This paper establishes an evaluation index system for spatio-temporal patterns of urbanization, with the county as research unit. We use the Entropy Weight method, coefficient variance, the Theil index and ESDA-GIS to analyze spatial patterns and evolutionary characteristics of New-Type Urbanization in the Central Plains Economic Region (CPER) between 2000 and 2011. Results show that economic benefit, non-agricultural employment level and level of market development are the most important factors influencing the level of New-Type Urbanization in the CPER; overall regional differences in New-Type Urbanization have declined while spatial correlations have increased from 2000 to 2011. The overall spatial pattern has changed little, however; differences between the western and eastern areas of the CPER are clear, and the pattern of a strong west and weak east did not change significantly over the study period. Areas with high levels of New-Type Urbanization were mostly distributed along the Beijing-Guangzhou and LongHai Railways on both sides, a new influx of urbanization was tightly clustered around ZhengZhou in the Central Henan Urban Agglomeration, but this trend was found to be weakening slightly. The level of New-Type Urbanization in municipal districts was found to be much higher than it was in the county generally. Provincial borders experienced a lower rate of growth and a lower level of New-Type Urbanization than did any other areas, consistently forming clusters of cold spots and sub-cold spots. The analysis confirms that historical development, location, and diffusion effects of urban agglomeration are the main drivers of changes in New-Type Urbanization patterns in CPER.

Keywords: new-type urbanization, spatial pattern, central plains economic region, spatial evolution

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Authors: Manasa Kalla, Narasimha Raju Chebrolu, Ashok Chatterjee

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We have studied the quantum transport properties of a single molecular transistor in the presence of an external magnetic field using the Keldysh Green function technique. We also used the Anderson-Holstein-Caldeira-Leggett Model to describe the single molecular transistor that consists of a molecular quantum dot (QD) coupled to two metallic leads and placed on a substrate that acts as a heat bath. The phonons are eliminated by the Lang-Firsov transformation and the effective Hamiltonian is used to study the effect of an external magnetic field on the spectral density function, Tunneling Current, Differential Conductance and Spin polarization. A peak in the spectral function corresponds to a possible excitation. In the presence of a magnetic field, the spin-up and spin-down states are degenerate and this degeneracy is lifted by the magnetic field leading to the splitting of the central peak of the spectral function. The tunneling current decreases with increasing magnetic field. We have observed that even the differential conductance peak in the zero magnetic field curve is split in the presence electron-phonon interaction. As the magnetic field is increased, each peak splits into two peaks. And each peak indicates the existence of an energy level. Thus the number of energy levels for transport in the bias window increases with the magnetic field. In the presence of the electron-phonon interaction, Differential Conductance in general gets reduced and decreases faster with the magnetic field. As magnetic field strength increases, the spin polarization of the current is increasing. Our results show that a strongly interacting QD coupled to metallic leads in the presence of external magnetic field parallel to the plane of QD acts as a spin filter at zero temperature.

Keywords: Anderson-Holstein model, Caldeira-Leggett model, spin-polarization, quantum dots

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Meenu S. Babu, K. Jayasankara Reddy

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Depression is a serious mental health concern that leads to significant distress and dysfunction in an individual. Due to the high physical, psychological, social, and economic burden it causes, it is important to study various bio-psycho-social factors that influence the onset, course, duration, intensity of depressive symptoms. The study aims to explore relationship between autobiographical memory (AM) functions, perceived control over stressful events and depressive symptoms. AM functions and perceived control were both found to be protective factors for individuals against depression and were both modifiable to predict better behavioral and affective outcomes. An extensive review of literatur, with a systematic search on Google Scholar, JSTOR, Science Direct and Springer Journals database, was conducted for the purpose of this review paper. These were used for all the aforementioned databases. The time frame used for the search was 2010-2021. An additional search was conducted with no time bar to map the development of the theoretical concepts. The relevant studies with quantitative, qualitative, experimental, and quasi- experimental research designs were included for the review. Studies including a sample with a DSM- 5 or ICD-10 diagnosis of depressive disorders were excluded from the study to focus on the behavioral patterns in a non-clinical population. The synthesis of the findings that were obtained from the review indicates there is a significant relationship between cognitive variables of AM functions and perceived control and depressive symptoms. AM functions were found to be have significant effects on once sense of self, interpersonal relationships, decision making, self- continuity and were related to better emotion regulation and lower depressive symptoms. Not all the components of AM function were equally significant in their relationships with various depressive symptoms. While self and directive functions were more related to emotion regulation, anhedonia, motivation and hence mood and affect, the social function was related to perceived social support and social engagement. Perceived control was found to be another protective cognitive factor that provides individuals a sense of agency and control over one’s life outcomes which was found to be low in individuals with depression. This was also associated to the locus of control, competency beliefs, contingency beliefs and subjective well being in individuals and acted as protective factors against depressive symptoms. AM and perceived control over stressful events serve adaptive functions, hence it is imperative to study these variables more extensively. They can be imperative in planning and implementing therapeutic interventions to foster these cognitive protective factors to mitigate or alleviate depressive symptoms. Exploring AM as a determining factor in depressive symptoms along with perceived control over stress creates a bridge between biological and cognitive factors underlying depression and increases the scope of developing a more eclectic and effective treatment plan for individuals. As culture plays a crucial role in AM functions as well as certain aspects of control such as locus of control, it is necessary to study these variables keeping in mind the cultural context to tailor culture/community specific interventions for depression.

Keywords: autobiographical memories, autobiographical memory functions, perceived control, depressive symptoms, depression, young adults

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Authors: D. Amaranatha Reddy

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Highly efficient and stable co-catalysts materials is of great important for boosting photo charge carrier’s separation, transportation efficiency, and accelerating the catalytic reactive sites of semiconductor photocatalysts. As a result, it is of decisive importance to fabricate low price noble metal free co-catalysts with high catalytic reactivity, but it remains very challenging. Considering this challenge here, dual metal organic frame work derived N-Doped Fe3C nanocages have been rationally designed and decorated with ultrathin ZnIn2S4 nanosheets for efficient photocatalytic hydrogen generation. The fabrication strategy precisely integrates co-catalyst nanocages with ultrathin two-dimensional (2D) semiconductor nanosheets by providing tightly interconnected nano-junctions and helps to suppress the charge carrier’s recombination rate. Furthermore, constructed highly porous hybrid structures expose ample active sites for catalytic reduction reactions and harvest visible light more effectively by light scattering. As a result, fabricated nanostructures exhibit superior solar driven hydrogen evolution rate (9600 µmol/g/h) with an apparent quantum efficiency of 3.6 %, which is relatively higher than the Pt noble metal co-catalyst systems and earlier reported ZnIn2S4 based nanohybrids. We believe that the present work promotes the application of sulfide based nanostructures in solar driven hydrogen production.

Keywords: photocatalysis, water splitting, hydrogen fuel production, solar-driven hydrogen

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Authors: Daniel Martin Fellows, Sean P. Walton, Jennifer Thompson, Oubay Hassan, Ella Quigley, Kevin Tinkham

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Fire performance is a crucial aspect to consider when designing cladding products, and testing this performance is extremely expensive. Appropriate use of numerical simulation of fire performance has the potential to reduce the total number of fire tests required when designing a product by eliminating poor-performing design ideas early in the design phase. Due to the complexity of fire and the large spectrum of failures it can cause, multi-disciplinary models are needed to capture the complex fire behavior and its structural effects on its surroundings. Working alongside Tata Steel U.K., the authors have focused on completing a coupled CFD-FEA simulation model suited to test Polyisocyanurate (PIR) based sandwich panel products to gain confidence before costly experimental standards testing. The sandwich panels are part of a thermally insulating façade system primarily for large non-domestic buildings. The work presented in this paper compares two coupling methodologies of a replicated physical experimental standards test LPS 1181-1, carried out by Tata Steel U.K. The two coupling methodologies that are considered within this research are; one-way and two-way. A one-way coupled analysis consists of importing thermal data from the CFD solver into the FEA solver. A two-way coupling analysis consists of continuously importing the updated changes in thermal data, due to the fire's behavior, to the FEA solver throughout the simulation. Likewise, the mechanical changes will also be updated back to the CFD solver to include geometric changes within the solution. For CFD calculations, a solver called Fire Dynamic Simulator (FDS) has been chosen due to its adapted numerical scheme to focus solely on fire problems. Validation of FDS applicability has been achieved in past benchmark cases. In addition, an FEA solver called ABAQUS has been chosen to model the structural response to the fire due to its crushable foam plasticity model, which can accurately model the compressibility of PIR foam. An open-source code called FDS-2-ABAQUS is used to couple the two solvers together, using several python modules to complete the process, including failure checks. The coupling methodologies and experimental data acquired from Tata Steel U.K are compared using several variables. The comparison data includes; gas temperatures, surface temperatures, and mechanical deformation of the panels. Conclusions are drawn, noting improvements to be made on the current coupling open-source code FDS-2-ABAQUS to make it more applicable to Tata Steel U.K sandwich panel products. Future directions for reducing the computational cost of the simulation are also considered.

Keywords: fire engineering, numerical coupling, sandwich panels, thermo fluids

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Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

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Authors: Moser Stephan, Lukasser Gerald, Weitlaner Robert

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Urban structures will be used more intensively in the future through redensification or new planned districts with high building densities. Especially, to achieve positive energy balances like requested for Positive Energy Districts (PED) the single use of roofs is not sufficient for dense urban areas. However, the increasing share of window significantly reduces the facade area available for use in PV generation. Through the use of PV technology at other building components, such as external venetian blinds, onsite generation can be maximized and standard functionalities of this product can be positively extended. While offering advantages in terms of infrastructure, sustainability in the use of resources and efficiency, these systems require an increased optimization in planning and control strategies of buildings. External venetian blinds with PV technology require an intelligent control concept to meet the required demands such as maximum power generation, glare prevention, high daylight autonomy, avoidance of summer overheating but also use of passive solar gains in wintertime. Today, geometric representation of outdoor spaces and at the building level, three-dimensional geometric information is available for planning with Building Information Modeling (BIM). In a research project, a web application which is called HELLA DECART was developed to provide this data structure to extract the data required for the simulation from the BIM models and to make it usable for the calculations and coupled simulations. The investigated object is uploaded as an IFC file to this web application and includes the object as well as the neighboring buildings and possible remote shading. This tool uses a ray tracing method to determine possible glare from solar reflections of a neighboring building as well as near and far shadows per window on the object. Subsequently, an annual estimate of the sunlight per window is calculated by taking weather data into account. This optimized daylight assessment per window provides the ability to calculate an estimation of the potential power generation at the integrated PV on the venetian blind but also for the daylight and solar entry. As a next step, these results of the calculations as well as all necessary parameters for the thermal simulation can be provided. The overall aim of this workflow is to advance the coordination between the BIM model and coupled building simulation with the resulting shading and daylighting system with the artificial lighting system and maximum power generation in a control system. In the research project Powershade, an AI based control concept for PV integrated façade elements with coupled simulation results is investigated. The developed automated workflow concept in this paper is tested by using an office living lab at the HELLA company.

Keywords: BIPV, building simulation, optimized control strategy, planning tool

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Authors: Bahatti̇n Ki̇mençe, Uğur Ki̇mençe

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In this study, the purpose of obtaining the influence functions of the displacement discontinuity in an anisotropic elastic medium is to produce the boundary element equations. A Displacement Discontinuous Method formulation (DDM) is presented with the aim of modeling two-dimensional elastic fracture problems. This formulation is found by analytical integration of the fundamental solution along a straight-line crack. With this purpose, Kelvin's fundamental solutions for anisotropic media on an infinite plane are used to form dipoles from singular loads, and the various combinations of the said dipoles are used to obtain the influence functions of displacement discontinuity. This study introduces a technique for coupling Fictitious Stress Method (FSM) and DDM; the reason for applying this technique to some examples is to demonstrate the effectiveness of the proposed coupling method. In this study, displacement discontinuity equations are obtained by using dipole solutions calculated with known singular force solutions in an anisotropic medium. The displacement discontinuities method obtained from the solutions of these equations and the fictitious stress methods is combined and compared with various examples. In this study, one or more crack problems with various geometries in rectangular plates in finite and infinite regions, under the effect of tensile stress with coupled FSM and DDM in the anisotropic environment, were examined, and the effectiveness of the coupled method was demonstrated. Since crack problems can be modeled more easily with DDM, it has been observed that the use of DDM has increased recently. In obtaining the displacement discontinuity equations, Papkovitch functions were used in Crouch, and harmonic functions were chosen to satisfy various boundary conditions. A comparison is made between two indirect boundary element formulations, DDM, and an extension of FSM, for solving problems involving cracks. Several numerical examples are presented, and the outcomes are contrasted to existing analytical or reference outs.

Keywords: displacement discontinuity method, fictitious stress method, crack problems, anisotropic material

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Authors: Iliuta Cumpanasu, Veronica Oana Cumpanasu

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This paper focuses on studying the conjunction between the new emerged theory of “Memory Effect” in Irregular Migration and Related Criminality and the notion of securitization, and its impact on border management, bringing about a scientific advancement in the field by identifying the patterns corresponding to the linkage of the two concepts, for the first time, and developing a theoretical explanation, with respect to the effects of the non-military threats on border security. Over recent years, irregular migration has experienced a significant increase worldwide. The U.N.'s refugee agency reports that the number of displaced people is at its highest ever - surpassing even post-World War II numbers when the world was struggling to come to terms with the most devastating event in history. This is also the fresh reality within the core studied coordinate, the Balkan Route of Irregular Migration, which starts from Asia and Africa and continues to Turkey, Greece, North Macedonia or Bulgaria, Serbia, and ends in Romania, where thousands of migrants find themselves in an irregular situation concerning their entry to the European Union, with its important consequences concerning the related criminality. The data from the past six years was collected by making use of semi-structured interviews with experts in the field of migration and desk research within some organisations involved in border security, pursuing the gathering of genuine insights from the aforementioned field, which was constantly addressed the existing literature and subsequently subjected to the mixed methods of analysis, including the use of the Vector Auto-Regression estimates model. Thereafter, the analysis of the data followed the processes and outcomes in Grounded Theory, and a new Substantive Theory emerged, explaining how the phenomena of irregular migration and cross-border criminality are the decisive impetus for implementing the concept of securitization in border management by using the proposed pattern. The findings of the study are therefore able to capture an area that has not yet benefitted from a comprehensive approach in the scientific community, such as the seasonality, stationarity, dynamics, predictions, or the pull and push factors in Irregular Migration, also highlighting how the recent ‘Pandemic’ interfered with border security. Therefore, the research uses an inductive revelatory theoretical approach which aims at offering a new theory in order to explain a phenomenon, triggering a practically handy contribution for the scientific community, research institutes or Academia and also usefulness to organizational practitioners in the field, among which UN, IOM, UNHCR, Frontex, Interpol, Europol, or national agencies specialized in border security. The scientific outcomes of this study were validated on June 30, 2021, when the author defended his dissertation for the European Joint Master’s in Strategic Border Management, a two years prestigious program supported by the European Commission and Frontex Agency and a Consortium of six European Universities and is currently one of the research objectives of his pending PhD research at the West University Timisoara.

Keywords: migration, border, security, memory effect

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Authors: Farzaneh Shayeganfar, Ali Ramazani

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Exciton (strong electronic interaction of electron-hole) and hot carriers created by surface plasmon polaritons has been demonstrated in nanoscale optoelectronic devices, enhancing the photoresponse of the system. Herein, we employ a quantum framework to consider coupled exciton- hot carriers effects on photovoltaiv energy distribution, scattering process, polarizability and light emission of 2D-semicnductor. We use density functional theory (DFT) to design computationally a semi-functionalized 2D honeycomb silicon boride (SiB) monolayer with H atoms, suitable for photovoltaics. The dynamical stability, electronic and optical properties of SiB and semi-hydrogenated SiB structures were investigated utilizing the Tran-Blaha modified Becke-Johnson (TB-mBJ) potential. The calculated phonon dispersion shows that while an unhydrogenated SiB monolayer is dynamically unstable, surface semi-hydrogenation improves the stability of the structure and leads to a transition from metallic to semiconducting conductivity with a direct band gap of about 1.57 eV, appropriate for photovoltaic applications. The optical conductivity of this H-SiB structure, determined using the random phase approximation (RPA), shows that light adsorption should begin at the boundary of the visible range of light. Additionally, due to hydrogenation, the reflectivity spectrum declines sharply with respect to the unhydrogenated reflectivity spectrum in the IR and visible ranges of light. The energy band gap remains direct, increasing from 0.9 to 1.8 eV, upon increasing the strain from -6% (compressive) to +6% (tensile). Additionally, compressive and tensile strains lead, respectively, to red and blue shifts of optical the conductivity threshold around the visible range of light. Overall, this study suggests that H-SiB monolayers are suitable as two-dimensional solar cell materials.

Keywords: surface plasmon, hot carrier, strain engineering, valley polariton

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Authors: Keltoum Bouherine, Olivier Leroy

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The present work is dedicated to study a three–dimensional (3D) self-consistent fluid simulation of microwave discharges of argon plasma in PECVD reactor. The model solves the Maxwell’s equations, continuity equations for charged species and the electron energy balance equation, coupled with Poisson’s equation, and Navier-Stokes equations by finite element method, using COMSOL Multiphysics software. In this study, the simulations yield the profiles of plasma components as well as the charge densities and electron temperature, the electric field, the gas velocity, and gas temperature. The results show that the microwave plasma reactor is outside of local thermodynamic equilibrium.The present work is dedicated to study a three–dimensional (3D) self-consistent fluid simulation of microwave discharges of argon plasma in PECVD reactor. The model solves the Maxwell’s equations, continuity equations for charged species and the electron energy balance equation, coupled with Poisson’s equation, and Navier-Stokes equations by finite element method, using COMSOL Multiphysics software. In this study, the simulations yield the profiles of plasma components as well as the charge densities and electron temperature, the electric field, the gas velocity, and gas temperature. The results show that the microwave plasma reactor is outside of local thermodynamic equilibrium.

Keywords: electron density, electric field, microwave plasma reactor, gas velocity, non-equilibrium plasma

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Authors: Hoorieh Darvishi, Rezaei

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Introduction: This study investigates the efficacy of computer-based interventions for children with Autism Spectrum Disorder , specifically targeting communication deficits and repetitive behaviors. The research evaluates novel software applications designed to enhance narrative capabilities and sensory integration through structured, progressive intervention protocols Method: The study evaluated two intervention software programs designed for children with autism, focusing on narrative speech and sensory integration. Twelve children aged 5-11 participated in the two-month intervention, attending three 45-minute weekly sessions, with pre- and post-tests measuring speech, communication, and behavioral outcomes. The narrative speech software incorporated 14 stories using the Cohen model. It progressively reduced software assistance as children improved their storytelling abilities, ultimately enabling independent narration. The process involved story comprehension questions and guided story completion exercises. The sensory integration software featured approximately 100 exercises progressing from basic classification to complex cognitive tasks. The program included attention exercises, auditory memory training (advancing from single to four-syllable words), problem-solving, decision-making, reasoning, working memory, and emotion recognition activities. Each module was accompanied by frequency and pitch-adjusted music that child enjoys it to enhance learning through multiple sensory channels (visual, auditory, and tactile). Conclusion: The results indicated that the use of these software programs significantly improved communication and narrative speech scores in children, while also reducing scores related to repetitive behaviors. Findings: These findings highlight the positive impact of computer-based interventions on enhancing communication skills and reducing repetitive behaviors in children with autism.

Keywords: autism, communication_skills, repetitive_behaviors, sensory_integration

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Authors: Hoorieh Darvishi, Rezaei

Abstract:

Introduction: This study investigates the efficacy of computer-based interventions for children with Autism Spectrum Disorder , specifically targeting communication deficits and repetitive behaviors. The research evaluates novel software applications designed to enhance narrative capabilities and sensory integration through structured, progressive intervention protocols Method: The study evaluated two intervention software programs designed for children with autism, focusing on narrative speech and sensory integration. Twelve children aged 5-11 participated in the two-month intervention, attending three 45-minute weekly sessions, with pre- and post-tests measuring speech, communication, and behavioral outcomes. The narrative speech software incorporated 14 stories using the Cohen model. It progressively reduced software assistance as children improved their storytelling abilities, ultimately enabling independent narration. The process involved story comprehension questions and guided story completion exercises. The sensory integration software featured approximately 100 exercises progressing from basic classification to complex cognitive tasks. The program included attention exercises, auditory memory training (advancing from single to four-syllable words), problem-solving, decision-making, reasoning, working memory, and emotion recognition activities. Each module was accompanied by frequency and pitch-adjusted music that child enjoys it to enhance learning through multiple sensory channels (visual, auditory, and tactile). Conclusion: The results indicated that the use of these software programs significantly improved communication and narrative speech scores in children, while also reducing scores related to repetitive behaviors. Findings: These findings highlight the positive impact of computer-based interventions on enhancing communication skills and reducing repetitive behaviors in children with autism.

Keywords: autism, narrative speech, persian, SI, repetitive behaviors, communication

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Authors: M. Gomaa Abdoelatef, Robert M. Field, Lee, Yong-Kwan

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Growing human populations have placed increased demands on water supplies and a heightened interest in desalination infrastructure. Key elements of the economics of desalination projects are thermal and electrical inputs. With growing concerns over the use of fossil fuels to (indirectly) supply these inputs, coupling of desalination with nuclear power production represents a significant opportunity. Individually, nuclear and desalination technologies have a long history and are relatively mature. For desalination, Reverse Osmosis (RO) has the lowest energy inputs. However, the economically driven output quality of the water produced using RO, which uses only electrical inputs, is lower than the output water quality from thermal desalination plants. Therefore, modern desalination projects consider that RO should be coupled with thermal desalination technologies (MSF, MED, or MED-TVC) with attendant steam inputs to permit blending to produce various qualities of water. A large nuclear facility is well positioned to dispatch large quantities of both electrical and thermal power. This paper considers the supply of thermal energy to a large desalination facility to examine heat balance impact on the nuclear steam cycle. The APR1400 nuclear plant is selected as prototypical from both a capacity and turbine cycle heat balance perspective to examine steam supply and the impact on electrical output. Extraction points and quantities of steam are considered parametrically along with various types of thermal desalination technologies to form the basis for further evaluations of economically optimal approaches to the interface of nuclear power production with desalination projects. In our study, the thermodynamic evaluation will be executed by DE-TOP which is the IAEA desalination program, it is approved to be capable of analyzing power generation systems coupled to desalination systems through various steam extraction positions, taking into consideration the isolation loop between the APR-1400 and the thermal desalination plant for safety concern.

Keywords: APR-1400, desalination, DE-TOP, IAEA, MSF, MED, MED-TVC, RO

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Authors: Linqing Ma, Huiling Feng, Jihong Liang, Yi Qian

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In China, some villages have survived in the long history of changes and remain until today with their unique styles and featured culture developed in the past. Those ancient villages, usually aged for hundreds or thousands of years, are the mirror for traditional Chinese culture, especially the farming-studying culture represented by the Confucianism. Gaoqian, an ancient village with a population of 3,000 in Zhejiang province, is such a case. With a history dating back to Yuan Dynasty, Gaoqian Village has 13 well-preserved traditional Chinese houses with a courtyard, which were built in the Ming and Qing Dynasty. It is a fine specimen to study traditional rural China. In China, some villages have survived in the long history of changes and remain until today with their unique styles and featured culture developed in the past. Those ancient villages, usually aged for hundreds or thousands of years, are the mirror for traditional Chinese culture, especially the farming-studying culture represented by the Confucianism. Gaoqian, an ancient village with a population of 3,000 in Zhejiang province, is such a case. With a history dating back to Yuan Dynasty, Gaoqian Village has 13 well-preserved traditional Chinese houses with a courtyard, which were built in the Ming and Qing Dynasty. It is a fine specimen to study traditional rural China. Then a repository for the memory of the Village will be completed by doing arrangement and description for those multimedia resources such as texts, photos, videos and so on. Production of Creative products with digital technologies is also possible based a thorough understanding of the culture feature of Gaoqian Village using research tools for literature and history studies and a method of comparative study. Finally, the project will construct an exhibition platform for the Village and its culture by telling its stories with completed structures and treads.

Keywords: ancient villages, digital exhibition, multimedia, traditional culture

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Authors: Sudip Kumar Kundu, Charu Singh

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As a great physiographic divide, the Himalayas affecting a large system of water and air circulation which helps to determine the climatic condition in the Indian subcontinent to the south and mid-Asian highlands to the north. It creates obstacles by defending chill continental air from north side into India in winter and also defends rain-bearing southwesterly monsoon to give up maximum precipitation in that area in monsoon season. Nowadays extreme weather conditions such as heavy precipitation, cloudburst, flash flood, landslide and extreme avalanches are the regular happening incidents in the region of North Western Himalayan (NWH). The present study has been planned to investigate the suitable model(s) to find out the rainfall pattern over that region. For this investigation, selected models from Coordinated Regional Climate Downscaling Experiment (CORDEX) and Coupled Model Intercomparison Project Phase 5 (CMIP5) has been utilized in a consistent framework for the period of 1976 to 2000 (historical). The ability of these driving models from CORDEX domain and CMIP5 has been examined according to their capability of the spatial distribution as well as time series plot of rainfall over NWH in the rainy season and compared with the ground-based Indian Meteorological Department (IMD) gridded rainfall data set. It is noted from the analysis that the models like MIROC5 and MPI-ESM-LR from the both CORDEX and CMIP5 provide the best spatial distribution of rainfall over NWH region. But the driving models from CORDEX underestimates the daily rainfall amount as compared to CMIP5 driving models as it is unable to capture daily rainfall data properly when it has been plotted for time series (TS) individually for the state of Uttarakhand (UK) and Himachal Pradesh (HP). So finally it can be said that the driving models from CMIP5 are better than CORDEX domain models to investigate the rainfall pattern over NWH region.

Keywords: global warming, rainfall, CMIP5, CORDEX, NWH

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Authors: M. Testa, L. Peotta, S. Giusiano, B. Lazzolino, U. Manera, A. Canosa, M. Grassano, F. Palumbo, A. Bombaci, S. Cabras, F. Di Pede, L. Solero, E. Matteoni, C. Moglia, A. Calvo, A. Chio

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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease of adulthood, which primarily affects the central nervous system and is characterized by progressive bilateral degeneration of motor neurons. The degeneration processes in ALS extend far beyond the neurons of the motor system, and affects cognition, behaviour and language. To outline the prevalence of language deficits in an ALS cohort and explore their profile along with demographic and neuropsychological data. A full neuropsychological battery and language assessment was administered to 56 ALS patients. Neuropsychological assessment included tests of executive functioning, verbal fluency, social cognition and memory. Language was assessed using tests for verbal comprehension, production and pragmatics. Patients were cognitively classified following the Revised Consensus Criteria and divided in three groups showing different levels of language deficits: group 1 - no language deficit; group 2 - one language deficit; group 3 - two or more language deficits. Chi-square for independence and non-parametric measures to compare groups were applied. Nearly half of ALS-CN patients (48%) reported one language test under the clinical cut-off, and only 13% of patents classified as ALS-CI showed no language deficits, while the rest 87% of ALS-CI reported two or more language deficits. ALS-BI and ALS-CBI cases all reported two or more language deficits. Deficits in production and in comprehension appeared more frequent in ALS-CI patients (p=0.011, p=0.003 respectively), with a higher percentage of comprehension deficits (83%). Nearly all ALS-CI reported at least one deficit in pragmatic abilities (96%) and all ALS-BI and ALS-CBI patients showed pragmatic deficits. Males showed higher percentage of pragmatic deficits (97%, p=0.007). No significant differences in language deficits have been found between bulbar and spinal onset. Months from onset and level of impairment at testing (ALS-FRS total score) were not significantly different between levels and type of language impairment. Age and education were significantly higher for cases showing no deficits in comprehension and pragmatics and in the group showing no language deficits. Comparing performances at neuropsychological tests among the three levels of language deficits, no significant differences in neuropsychological performances were found between group 1 and 2; compared to group 1, group 3 appeared to decay specifically on executive testing, verbal/visuospatial learning, and social cognition. Compared to group 2, group 3 showed worse performances specifically in tests of working memory and attention. Language deficits have found to be spread in our sample, encompassing verbal comprehension, production and pragmatics. Our study reveals that also cognitive intact patients (ALS-CN) showed at least one language deficit in 48% of cases. Pragmatic domain is the most compromised (84% of the total sample), present in nearly all ALS-CI (96%), likely due to the influence of executive impairment. Lower age and higher education seem to preserve comprehension, pragmatics and presence of language deficits. Finally, executive functions, verbal/visuospatial learning and social cognition differentiate the group with no language deficits from the group with a clinical language impairment (group 3), while attention and working memory differentiate the group with one language deficit from the clinical impaired group.

Keywords: amyotrophic lateral sclerosis, language assessment, neuropsychological assessment, language deficit

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Authors: Ahmad Alhawarat, Mustafa Mamat, Mohd Rivaie, Ismail Mohd

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Conjugate gradient method has been enormously used to solve large scale unconstrained optimization problems due to the number of iteration, memory, CPU time, and convergence property, in this paper we find a new class of nonlinear conjugate gradient coefficient with global convergence properties proved by exact line search. The numerical results for our new βK give a good result when it compared with well-known formulas.

Keywords: conjugate gradient method, conjugate gradient coefficient, global convergence

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Authors: Radek Richtr, Petr Pauš

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Social media nowadays connects people more tightly and intensively than ever, but simultaneously, some sort of social distance, incomprehension, lost of social integrity appears. People can be strongly connected to the person on the other side of the world but unaware of neighbours in the same district or street. The Stoa is a type of application from the ”serious games” genre- it is research augmented reality experiment masked as a gaming environment. In the Stoa environment, the player can plant and grow virtual (organic) structure, a Pillar, that represent the whole suburb. Everybody has their own idea of what is an acceptable, admirable or harmful visual intervention in the area they live in; the purpose of this research experiment is to find and/or define residents shared subconscious spirit, genius loci of the Pillars vicinity, where residents live in. The appearance and evolution of Stoa’s Pillars reflect the real world as perceived by not only the creator but also by other residents/players, who, with their actions, refine the environment. Squares, parks, patios and streets get their living avatar depictions; investors and urban planners obtain information on the occurrence and level of motivation for reshaping the public space. As the project is in product conceptual design phase, the function is one of its most important factors. Function-based modelling makes design problem modular and structured and thus decompose it into sub-functions or function-cells. Paper discuss the current conceptual model for Stoa project, the using of different organic structure textures and models, user interface design, UX study and project’s developing to the final state.

Keywords: augmented reality, urban computing, interaction design, mixed reality, social engineering

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Authors: Shilu Deepa Thomas, P. Jayaprakash, Dorota Łazewska, Katarzyna Kieć-Kononowicz, B. Sadek

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A large body of evidence suggests the involvement of cognitive impairment, increased levels of inflammation and oxidative stress in the pathogenesis of autism spectrum disorder (ASD). ASD commonly coexists with psychiatric conditions like anxiety and cognitive challenges, and individuals with ASD exhibit significant levels of inflammation and immune system dysregulation. Previous Studies have identified elevated levels of pro-inflammatory markers such as IL-1β, IL-6, IL-2 and TNF-α, particularly in young children with ASD. The current therapeutic options for ASD show limited effectiveness, signifying the importance of exploring an efficient drugs to address the core symptoms. The role of histamine H3 receptors (H3Rs) in memory and the prospective role of H3R antagonists in pharmacological control of neurodegenerative disorders, e.g., ASD, is well-accepted. Hence, the effects of chronic systemic administration of H3R antagonist E159 on autistic-like repetitive behaviors, social deficits, memory and anxiety parameters, as well as neuroinflammation in Black and Tan BRachyury (BTBR) mice, were evaluated using Y maze, Barnes maze, self-grooming, open field and three chamber social test. E159 (2.5, 5 and 10 mg/kg, i.p.) dose-dependently ameliorated repetitive and compulsive behaviors by reducing the increased time spent in self-grooming and improved reduced spontaneous alternation in BTBR mice. Moreover, treatment with E159 attenuated disturbed anxiety levels and social deficits in tested male BTBR mice. Furthermore, E159 attenuated oxidative stress by significantly increasing GSH, CAT, and SOD and decreasing the increased levels of MDA in the cerebellum as well as the hippocampus. In addition, E159 decreased the elevated levels of proinflammatory cytokines (tumor necrosis factor (TNF-α), interleukin-1β (IL-1β), and IL-6). The observed results show that H3R antagonists like E159 may represent a promising novel pharmacological strategy for the future treatment of ASD.

Keywords: histamine H3 receptors, antagonist E159, autism, behaviors, mice

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