Miracle-dz/UniFAR-FTUs huggingface dataset:
Electrolyte-gated transistors for neuromorphic applications

Von Neumann computers are currently failing to follow Moore’s law and are limited by the von Neumann bottleneck. To enhance computing performance, neuromorphic computing systems that can simulate the function of the human brain are being developed. Artificial synapses are essential electronic devices for neuromorphic architectures, which have the ability to perform signal processing and storage between neighboring artificial neurons. In recent years, electrolyte-gated transistors (EGTs) have been seen as promising devices in imitating synaptic dynamic plasticity and neuromorphic applications. Among the various electronic devices, EGT-based artificial synapses offer the benefits of good stability, ultra-high linearity and repeated cyclic symmetry, and can be constructed from a variety of materials. They also spatially separate “read” and “write” operations. In this article, we provide a review of the recent progress and major trends in the field of electrolyte-gated transistors for neuromorphic applications. We introduce the operation mechanisms of electric-double-layer and the structure of EGT-based artificial synapses. Then, we review different types of channels and electrolyte materials for EGT-based artificial synapses. Finally, we review the potential applications in biological functions.
Non‐governmental organisations and universities as transition intermediaries in sustainability transformations building on grassroots initiatives

While niche grassroots initiatives can push bottom-up sustainability transitions, they can face problems in forming a more global niche, and in scaling their innovative solutions to a regime level. A thorough literature review shows scholarly agreement on the assumption that universities and NGOs can support sustainability transition in the acceleration phase by intermediating within niches, and between niches and regimes. As indepth research and a reality check on successful intermediary strategies in this context are still lacking, this paper aims to contribute to a conceptual framework that integrates the of NGOs and universities expected activities in existing literature, and relates them to one another. We develop such a framework, and test it in three case studies from the plastic revaluation field, comparing and drawing on the perspectives of niche, intermediary and regime actors. Findings confirm the conceptual framework, and suggest changes and extensions. We enhance existing knowledge by providing detailed insights into successful intermediary activities in these innovation systems, and draw conclusions for policy-makers.
Investigating the P300 Response as a Marker of Working Memory in Virtual Training Environments

Conventional performance metrics fail to offer high-resolution evaluation of learning and memory during training tasks; the P300 component of the event-related potential (ERP) is a promising tool for enhancing the assessment of training quality in virtual environments, but this technique is yet to be investigated. A driver training simulator and scenario were developed to explore the capability of the P300 for this purpose. A user study was conducted with 32 participants divided into two groups objectively determined by driving performance scores, thus enabling observations of the P300 response to be equated to varying levels of learning and memory. Participant electroencephalogram data were recorded during the procedure, which was postprocessed to filter and extract ERPs to capture neural responses to specific events in the virtual training scenario. These were combined to produce a result for each participant, which was then grand averaged to create an overall ERP for each group. Across the eight electrode sites, statistically significant differences were found between the grand average waveforms of the two groups, with high memory retention producing significantly greater peak-to-peak amplitude (U = 9.00, p = 0.045), peak latency (U = 0.00, p $< $ 0.001), and positive area (U = 13.00, p = 0.05) of the waveform than low memory retention. The evidenced relationship between the P300 response and working memory in this context suggests that it has the potential for monitoring learning and memory in stimulus-driven virtual training systems.
The Effect of Individual’s Technological Belief and Usage on Their Absorptive Capacity towards Their Learning Behaviour in Learning Environment

Absorptive capacity is a common barrier to knowledge transfer at the individual level. However, technology absorptive capacity can enhance an individual’s learning behaviour. This study investigates that technology readiness, the tools for knowledge sources, social influences, and social networks influence an individual’s absorptive capacity on an adaptation of the individual learning behaviour. A quantitative approach is used to assess the presence of a causal relationship from the constructs mentioned above. Data were collected from university students in Australia to examine the hypotheses. With 199 responses, a partial least squares structural equation modelling (PLS-SEM) approach was used for the analysis. The results generated mixed findings. Individual’s technological belief in optimism and innovation and social influences had a significantly weaker effect on individual absorptive capacity, which in turn had a significantly weaker impact on their learning behaviour.
Deglacial Ventilation Changes in the Deep Southwest Pacific

Processes underlying changes in the oceanic carbon storage during the Last Glacial Maximum and the subsequent deglaciation are not fully understood. Here, we present a new high‐resolution radiocarbon reconstruction (expressed as δ14R) at the depth of the modern Lower Circumpolar Deep Water from the Pacific Sector of the Southern Ocean. Our record shows δ14R increases during Heinrich Stadial 1 and the Younger Dryas that agree with the deep‐to‐shallow transfer of old carbon in the Southern Ocean during these two periods. Our record also shows, for the first time, a clear ∼80‰ decline in δ14R during the Antarctic Cold Reversal (ACR), indicating the development of poorly ventilated conditions in the deep Southwest Pacific. These conditions are consistent with the increased Southern Ocean sea‐ice and associated stratification between Upper and Lower Circumpolar Deep Waters. This enhanced stratification in the deep South Pacific possibly facilitated greater carbon storage in the ocean interior during the ACR, effectively limiting oceanic CO2 release and contributing to the atmospheric CO2 plateau as observed in ice cores at that time.
Designing Meaningful and Relevant Activities to Enhance Students’ Motivation during Covid-19 Pandemic

Teachers and students all over the world are now facing the biggest shift in their lives, from studying in the school to studying at home, from meeting their teachers and friends face to face to meeting them via technology, and from depending on teachers to give them knowledge to depend on themselves. This change is not easy to cope with, both teachers and students are at their wit’s end. They are confused what to do and if this continues, they will be frustrated and lose their motivation for learning. Many parents complain that their children have to do a lot of assignments that overwhelm them. As a result, they lose motivation. To remedy this situation, teacher needs to design activities which are relevant and meaningful to their students.
Design and Analysis of Dual-Band Circular Patch Antenna for X-Band Applications with Enhanced Bandwidth

An antenna is a crucial component in the wireless communication system which converts electrical waves to EM waves and vice-versa which leads to revaluation in wireless communication technology. Due to this reason the experiment was performed on a simple circular patch antenna for better radiation along with wide transmission bandwidth. In this paper, a simple circular microstrip antenna structure is designed to operate at dual bands. The proposed antenna consists of a circular radiating patch, a 50-ohm feedline line, a quarter-wave impedance matching transmission line, and a ground plane. It meets significant requirements for large bandwidth, optimized gain, minimum reflections, and small size with high directivity and efficiency. This antenna contains FR4 Epoxy substrate material with permittivity 4.4 and size 36mm x 36mm x 1.67mm. ANSOFT HFSS simulator is used to analyze various parameters like return loss, VSWR, Impedance, and gain. The Resonant Frequency of the designed antenna is 8.77 GHz and 10.6 GHz. with minimum Return Loss of -52 dB and -21.66 dB respectively. It was also observed that 1.005 and 1.2 VSWR at 8.77 GHz and 10.6 GHz respectively.
A Comparison Study on Multilayered Barrier Oxide Structure in Charge Trap Flash for Synaptic Operation

A synaptic device that contains weight information between two neurons is one of the essential components in a neuromorphic system, which needs highly linear and symmetric characteristics of weight update. In this study, a charge trap flash (CTF) memory device with a multilayered high-κ barrier oxide structure on the MoS2 channel is proposed. The fabricated device was oxide-engineered on the barrier oxide layers to achieve improved synaptic functions. A comparison study between two fabricated devices with different barrier oxide materials (Al2O3 and SiO2) suggests that a high-κ barrier oxide structure improves the synaptic operations by demonstrating the increased on/off ratio and symmetry of synaptic weight updates due to a better coupling ratio. Lastly, the fabricated device has demonstrated reliable potentiation and depression behaviors and spike-timing-dependent plasticity (STDP) for use in a spiking neural network (SNN) neuromorphic system.
A two-nation investigation of leadership self-perceptions and motivation to lead in early adulthood: the moderating role of gender and socio-economic status

PurposeDrawing on the social-cognitive and motivational literature of leadership, the present study examines the influence of young adults' self-perceptions of leadership on their leadership self-efficacy (LSE) and motivation to lead (MTL) in their future career. The authors further examine gender and socio-economic status (SES) as important moderators of the proposed relationships.Design/methodology/approachThe present investigation consists of a two-study research design, based on data collected from young adult samples across two culturally different countries, namely the UK (N = 267) and Japan (N = 127). FindingsThe study presents evidence of self-perceptions of leadership influencing LSE and MTL. The results further support the mediating role of leader self-efficacy. Regarding the moderating role of gender, results in both samples showed that the effects of leader self-efficacy on MTL were stronger for males. SES was found to moderate the effects of leadership self-perceptions of negative implicit leadership theories (ILTs) on LSE in the UK sample and the effects of leadership self-perceptions of positive ILTs on LSE in the Japanese sample.Originality/valueThis study fills the gap of empirical research focused on early adulthood influences on leadership development. In particular, this study has a three-fold contribution, by, firstly, developing a conceptual model that examines the role of young adults' self-perceptions of leadership on their self-efficacy as leaders and MTL; secondly examining contingencies of the proposed relationships; and thirdly testing the conceptual model in two countries.
A Sparse Nonstationary Trigonometric Gaussian Process Regression and Its Application on Nitrogen Oxide Prediction of the Diesel Engine

Gaussian process regression (GPR) has shown superiority in terms of state estimation for its nonparametric characteristic and uncertainty prediction ability. Due to its heavy computational complexity, GPR is generally used for small datasets. To efficiently deal with the big data, the sparse spectrum approximation method has been successfully applied to GPR to decrease the computational complexity. However, the stationarity of this method is a strict assumption for data and usually mismatches the industrial processes. In this article, we proposed a sparse nonstationary GPR, which can deal with the nonstationary relationship among samples and make the model more flexible, to settle the aforementioned problems. Furthermore, the performance of the proposed method is evaluated using three public datasets and a sampled diesel engine dataset, and the results show the superiority of our proposed method in terms of accuracy.
Optimization of Crude Inulin Extraction from Garlic (Allium sativum L.) Agro-industrial Waste using the Response Surface Methodology.

Inulin is a polysaccharide with several applications within the chemical, pharmaceutical, and food industry. It is considered a dietary fibre that provides multiple health benefits. In this work, the yield of raw inulin obtained from garlic agro-industrial useless waste was maximized, by applying the response surface methodology in a central composite design (CCD), in which different distilled-water (DW)-to-garlic-agro-industrial-waste (GAIW) ratios (3 and 5 mL/g) and different temperatures (60 and 80 °C) were evaluated. Optimal condition was obtained with a DW/GAIW ratio of 4.3 mL/g and a temperature of 80.2 °C. Under this condition, the quadratic model showed a maximum yield of crude inulin of 8.17 ± 0.89 g/100 g. Further, the CCD model obtained was validated with three additional experiments at the same optimal condition. The FTIR spectra of inulin obtained from garlic agro-industrial residues and chicory inulin showed similarities and differences, presumably related to the different degrees of polymerization of the fructans present.
Death Anxiety, Religiosity and Culture: Implications for Therapeutic Process and Future Research

Death anxiety is a common phenomenon that humans experience. It is multidimensional. There has been an upsurged interest around the discussion on death anxiety across the globe, however, much of the literature focuses on the concept of death anxiety, religiosity, and its role in mental health conditions. Further, studies on death anxiety are scattered and at times disconnected. It is important to review existing literature to get an overview of the current direction in research and understand its relevance to facilitate therapeutic processes. In this scoping review, literature was searched in databases such as PubMed, Scopus, and PsychINFO using key words such as “death anxiety”, “fear of death”, religion”, “culture”, and “psychopathology” combined with Boolean operators to narrow down the search results. The initial search yielded 614 records, of which 546 records were removed based on title review (363), abstract review (94), and full-text review (89). Finally, 68 articles were appraised, narratively synthesized, and thematically presented. Major themes revealed in the literature were theoretical frameworks of death anxiety, religiosity, universality, psychological effects of death anxiety, psychopathology, and religious coping strategies. There is a need to assess client’s death anxiety and address them using religious rituals and coping mechanisms.
Chaos Based Secure Medical Image Transmission Model for IoT- Powered Healthcare Systems

Due to the extensive development of Internet of Things (IoT) in e-healthcare environment, security and integrity of the medical data especially medical images became a big issue. This paper proposes a chaotic security architecture for ensuring the security of the medical images during transmission and storage. The proposed model is built by comprising of three main stages. At first, message digest 5 algorithm is applied to the plain image for generating the seed key of Lorenz chaotic map. Subsequently Lorenz map is iterated to generate the chaotic key series utilized for further process. In second stage, dual confusion such as row-by-row and column-by-column confusion is executed on the plain image. At last, dual diffusion process is performed by applying binary reverse and compliment operation, in addition to that XOR operation is executed between diffused image and Lorenz chaotic key image. Simulation results and analysis of security level by applying different attacks indicates that the developed cryptosystem has the potential of satisfying the security requirements of IoT healthcare applications.
Adaptive Named Entity Recognition Using Distant Supervision for Contemporary Written Texts

Named entity recognition (NER) is the process of categorizing named entities in a given text that suffers from the lack of labeled corpora, which is a long-standing issue. Deep neural networks have been successfully applied to NER tasks. However, they require a large number of annotated data. Regardless of the number of data made available, annotation requires significant human effort, which is expensive and time-consuming. Moreover, collecting labeled data that reflect contemporary surrounding statuses requires exhaustive follow-up and incurs correspondingly higher costs. Current NERs typically focus on the supervised learning of hand-crafted data. The most well-known dataset for NER shared tasks, which was released at the 2003 Conference on Natural Language Learning, is used for basic training and evaluation. Although the data are qualified, the database has low coverage of timely material. In this paper, we illustrate methods for swiftly labeling up-to-date data via distant supervision. To tackle the difficulty of annotating contemporary written texts, we generate labeled data articles that reflect the latest issues. We evaluated the proposed methods with bidirectional long short-term memory conditional random-field architecture using static and contextualized embedding methods. Our proposed models perform higher than state-of-the-art methods with average F1-scores 3.09% better with weakly labeled Wikipedia data and 3.47% better with Cable News Network data. When using the NER model with Flair embedding, our method shows 1.50 and 3.26% higher F1-scores with weakly labeled Wikipedia and news data, respectively. Qualitatively, the proposed model also performs better when extracting contemporary keywords.
Studies on Variability, Heritability, Correlation and Path Analysis in Segregating Population of Black Gram [Vigna mungo (L.) Hepper]

Back ground: Pulses are an important source of protein in the human diet and black gram is a popular pulse crop in India. The black gram breeding program faces various drawbacks due to narrow genetic diversity accompanied by biotic and abiotic diseases which seriously affect the yield potential of the crop. Hence it is important to understand the gene action and to frame the efficient breeding program in black gram for yield improvement.Methods: The present experiment was conducted during 2018-2019. Sixty-nine F2 plants of the cross ADT3 x KKB14-052 were raised and nine biometrical traits were recorded. Genetic variability and association analysis were carried out.Result: High PCV and GCV were obtained for the traits viz., number of primary branches/ plant, number of clusters/plant, number of pods/plant and single plant yield. High heritability and high GAM were obtained for the traits viz., plant height, number of primary branches/plant, number of clusters/plant, number of pods/plant, hundred seed weight, pod length and single plant yield. All the characters under the study were significantly positive correlation with yield except days to 50% flowering. Number of pods/plant showed a high positive, direct effect on single plant yield. Hence, these characters would be mainly focused in black gram breeding programs for yield improvement.
Hospital digitalization in the era of industry 4.0 based on GHRM and service quality

Article history: Received: September 20, 2020 Received in revised format: January 15, 2021 Accepted: January 16, 2021 Available online: January 16, 2021 Health services, especially hospitals, are facing significant changes in the industrial era 4.0. Hospital digitization is responsible for building green hospitals and improving service quality in the era of modern technology. Green Human Resources Management (GHRM) is becoming known as the HRM concept that encourages employee commitment and environmental aspects. GHRM is an HR management system suitable for organizations, including hospitals that have a significant environmental impact. Hospitals are very dependent on the quality of service provided to their customers. GHRM as a management model in hospitals is very important to encourage hospital digitization and service quality. This research was conducted to answer the gap in hospital research in seeing the effect of GHRM on service quality in digitizing hospitals in the industrial era 4.0. GHRM and Service Quality is used in the healthcare industry to test its application in hospitals in Indonesia. They are using the SEM PLS method, a variant-based structural equation analysis that focuses on predictive models, to look for predictive linear relationships between variables to process data for 1004 respondents from 19 State-Owned Enterprises' hospitals throughout Indonesia. This research can answer research gaps related to the effect of GHRM on Service Quality and Hospital Digitalization in Indonesia. Based on Hospital Digitalization, GHRM affects Service Quality, which is closely related to environmental problems. © 2021 by the authors; licensee Growing Science, Canada.
Territorial development process based on the circular economy: a systematic literature review

ABSTRACT Our purpose is to examine the link between circular economy (CE) and territorial development in the literature. Works on CE most often deal with its integration within firms’ strategies. The link between CE and the territorial development process (TDP) is more rarely studied. We define the TDP through the interaction between three key dimensions: coordination modalities between the stakeholders, institutional factors, and the resources generated in the process. Using a systematic literature review our aim is to understand, through the occurrences of those dimensions in the 265 papers selected, whether or not and how the issue of the TDP is addressed. Our first result is that a part of the literature on CE often focuses on one or two of the three key dimensions identified. The second result is to highlight several forms of interactions between the key dimensions, illustrating that CE can imply different types of TDPs.
The Elimination Effect of Take-Back Regulation on Backward Production Capacity Remanufacturing Supply Chains

With more and more end-of-life products in daily life, many companies are engaging in remanufacturing, including backward production capacity (BPC) enterprises. Meanwhile, take-back regulation always asks the manufacturer to take back end-of-life products to reduce pollution. However, the effect of take-back regulation on remanufacturers remains unclear. In this paper, we first analyzed the take-back regulation threshold with the elimination effect. We then discussed the impact on stakeholders, such as the manufacturer, the remanufacturer, consumers, and the government. A two-stage dynamic market model is proposed, which considers the market with/without BPC remanufacturer. Take-back regulation’s elimination effect is studied, and the results show that when the collection target reaches the elimination threshold, the manufacturer’s profit declines, the BPC remanufacturer is eliminated, consumer surplus decreases, and social welfare is improved. Besides, to cope with a high take-back regulation target, the manufacturer will reduce new product output, which leads to BPC remanufacturer’s benefits decline. A numerical study is given with a different collecting strategy of the BPC remanufacturer, the incentive interval, the inhibition interval, and the elimination interval of the take-back regulation for stakeholders which are described. At last, some managerial insights are given to help the regulator implement take-back regulation.