Miracle-dz/UniFAR-FTUs huggingface dataset:
ANFIS-Inspired Smart Framework for Education Quality Assessment

In the education sector, the Internet of Things (IoT) technology, integrated with fog-cloud computing, has offered productive services. Motivated by this, the smart recommender system offers the facility to the students to opt for the course and college based on the education quality. This research provides an IoT-fog-cloud paradigm for evaluating the academic environment with a perspective to enhance quality education. Specifically, IoT technology is incorporated to gather data about the academic environment that directly and indirectly influence the quality of education. Using the Bayesian Modeling Technique, the data collected is analyzed utilizing a fog-cloud computing framework to quantify the measure of the probability of education quality (PoEQ). Moreover, the Education Quality Assurance Index (EQAI) is calculated to analyze the quality assessment over a temporal scale. Furthermore, predictive decision-making is performed for quality estimation using the Adaptive Neuro-Fuzzy Inference System (ANFIS). The experimental simulation on 4 challenging datasets namely C1 (2124 instances), C2 (2112), C3 (2139), and C4 (2109) shows the effectiveness of the proposed framework. Simulation findings are compared with state-of-the-art techniques to measure the overall performance enhancement of the proposed system. Also, the mathematical analysis was carried out to assess the analytical performance of the proposed framework.
Understanding exploration in humans and machines by formalizing the function of curiosity

Recent work in machine learning has demonstrated the benefits of providing artificial agents with a sense of curiosity – a form of intrinsic reward that supports exploration. Two strategies have emerged for defining these rewards: favoring novelty and pursuing prediction errors. Psychological theories of curiosity have also emphasized these two factors. We show how these two literatures can be connected by understanding the function of curiosity, which requires thinking about the abstract computational problem that bothhumans and machines face as they explore their world
Manufacturing in the Time of COVID-19: An Assessment of Barriers and Enablers

Pandemics and other forms of epidemic outbreaks are a unique case of manufacturing risk typified by high uncertainty, increasing propagation, and long-term disruption to manufacturers, supply chain actors as well as the end-users and consumers. For manufacturing the COVID-19 disruption scope has been largely twofold; an endogenous disruption of manufacturing processes and systems as well as extreme shifts in demand and supply caused by exogenous supply chain disruption. Existing literature on disruptions in manufacturing suggests that pandemics are qualitatively different from typical disruptions. There is no literature available to manufacturing practitioners that identify the barriers and enablers of manufacturing resilience, especially with regards to pivoting of the manufacturing sector in response to a pandemic. This article draws on an extensive survey collected during the COVID-19 pandemic. The respondents were employees of manufacturing firms in all regions of the world who had engaged in manufacturing during the pandemic or had opted out from manufacturing due to various identified reasons. By collating their responses, we offer to practitioners and policymakers an analysis for identifying a best-practice framework for pivoting successfully as a response to major manufacturing disruptions.
Teachers’ online teaching expectations and experiences during the Covid19-pandemic in the Netherlands

ABSTRACT The COVID19-Pandemic has forced educators to transform their lessons into online versions in a short period of time. This study compares teachers’ perception regarding their online teaching expectations (prior to the transition to remote teaching) and experiences (after a month of online teaching). Two surveys were completed by 200 Dutch teachers. Results demonstrated a significant change in the perception of teachers regarding their resolutions to implement technology in their lessons in a post-corona era. In this regard, teachers’ gender and prior experiences with the use of ICT seem to play a small role. Findings of this study provide implications for the professionalisation of teachers, such as characteristics of teachers and intentions to implement technology in teaching, as well as experienced positive and negative aspects of online teaching. Future research should focus on constructing and testing educational design principles for effective professionalisation of teachers in adopting technology in their educational practices.
Hypertension prevalence and control among community‐dwelling lebanese older adults

There is a high prevalence of hypertension among Lebanese adults, but no evidence is available on its prevalence and control exclusively among older adults (65 + years). This study provides the first evidence on a representative sample of 502 community elderly and presents the basis for future research and policy implications. Results show an overall prevalence of 52% with a significantly higher female‐to‐male ratio. Factors independently associated with hypertension were older age, body mass index, and dementia. More than a third of those with a positive history of hypertension had uncontrolled blood levels. Uncontrolled hypertension was higher among women. Increasing awareness about medication adherence and controlling multi‐morbidities constitute promising measures to lowering the burden of hypertension among Lebanese older adults, especially women.
Physical and Aerodynamic Characterization of Particle Clusters at Sakurajima Volcano (Japan)

The process of particle aggregation significantly affects ash settling dynamics associated with volcanic explosive eruptions. Several experiments have been carried out to investigate the physics of ash aggregation and dedicated numerical schemes have been developed to produce more accurate forecasting of ash dispersal and sedimentation. However, numerical description of particle aggregation is complicated by the lack of complete datasets on natural samples required for model validation and calibration. Here we present a first comprehensive dataset for the internal structure, aerodynamical properties (e.g., size, density, terminal velocity) and grain size of constituting particles of a variety of aggregate types collected in the natural laboratory of Sakurajima Volcano (Japan). Even though the described particle clusters represent the most common types of aggregates associated with ash-rich fallouts, they are of difficult characterization due to the very low potential of preservation in tephra-fallout deposits. Properties were, therefore, derived based on a combination of high-resolution-high-speed videos of tephra fallout, scanning electron microscope analysis of aggregates collected on adhesive paper and analysis of tephra samples collected in dedicated trays. Three main types of particle clusters were recognized and quantitively characterized: cored clusters (PC3), coated particles (PC2), and ash clusters (PC1) (in order of abundance). A wide range of terminal velocities (0.5–4 m/s) has been observed for these aggregates, with most values varying between 1 and 2 m/s, while aggregate size varies between 200 and 1,200 µm. PC1, PC2, and PC3 have densities between 250 and 500, 1,500 and 2,000, and 500 and 1,500 kg/m3, respectively. The size of the aggregate core, where present, varies between 200 and 750 µm and increases with aggregate size. Grain size of tephra samples was deconvoluted into a fine and a coarse Gaussian subpopulation, well correlated with the grain size of shells and of the internal cores of aggregates, respectively. This aspect, together with the revealed abundance of PC3 aggregates, reconciles the presence of a large amount of fine ash (aggregate shells) with coarse ash (aggregate cores) and better explains the grain size distribution bimodality, the high settling velocity with respect to typical PC1 velocities and the low settling velocities of large aggregates with respect to typical PC2 velocity. Furthermore, ash forming the aggregates was shown to be always finer than 45 µm, confirming the key role played by aggregation processes in fine ash deposition at Sakurajima.
Building Semantic Metadata for Historical Archives through an Ontology-driven User Interface

Historical archives represent an immense wealth, the potential of which is endangered by the lack of effective management and access tools. We believe that this issue can be faced by providing archive catalogs with a semantic layer, containing rich semantic metadata, representing the content of documents in a full-fledged formal machine-readable format. In this article, we present the contribution offered in this direction by the PRiSMHA project, in which the conceptual vocabulary of the semantic layer is represented by computational ontologies. However, acquiring semantic knowledge represents a well-known bottleneck for knowledge-based systems; to solve this problem, PRiSMHA relies on a crowdsourcing collaborative model, i.e., an online community of users who collaborate in building semantic representations of the content of archival documents. In this perspective, this article aims at answering the following research question: Starting from the axioms characterizing concepts in the computational ontology underlying the system, how can we derive a user interface enabling users to formally represent the content of archival documents by exploiting the conceptual vocabulary provided by the ontology? Our solution includes the following steps: (a) a manually defined configuration, acting as a pre-filter, to hide “unsuited” classes, properties, and relations; (b) an algorithm, combining heuristics and reasoning, which extracts from the ontology all and only the “compatible” properties and relations, given an entity (event) type; and (c) a set of strategies to rank, group, and present the entity (event) properties and relations, based on the results of a study with users. This integrated solution enabled us to design an ontology-driven user interface enabling users to characterize entities, and in particular (historical) events, on the basis of the vocabulary provided by the ontology.
Surface Modification of Monolayer MoS2 by Baking for Biomedical Applications

Molybdenum disulfide (MoS2), a transition metal dichalcogenide material, possesses great potential in biomedical applications such as chemical/biological sensing, drug/gene delivery, bioimaging, phototherapy, and so on. In particular, monolayer MoS2 has more extensive applications because of its superior physical and chemical properties; for example, it has an ultra-high surface area, is easily modified, and has high biodegradability. It is important to prepare advanced monolayer MoS2 with enhanced energy exchange efficiency (EEE) for the development of MoS2-based nanodevices and therapeutic strategies. In this work, a monolayer MoS2 film was first synthesized through a chemical vapor deposition method, and the surface of MoS2 was further modified via a baking process to develop p-type doping of monolayer MoS2 with high EEE, followed by confirmation by X-ray photoelectron spectroscopy and Raman spectroscopy analysis. The morphology, surface roughness, and layer thickness of monolayer MoS2 before and after baking were thoroughly investigated using atomic force microscopy. The results showed that the surface roughness and layer thickness of monolayer MoS2 modified by baking were obviously increased in comparison with MoS2 without baking, indicating that the surface topography of the monolayer MoS2 film was obviously influenced. Moreover, a photoluminescence spectrum study revealed that p-type doping of monolayer MoS2 displayed much greater photoluminescence ability, which was taken as evidence of higher photothermal conversion efficiency. This study not only developed a novel MoS2 with high EEE for future biomedical applications but also demonstrated that a baking process is a promising way to modify the surface of monolayer MoS2.
A Kinetic Monte Carlo Study of Retention Time in a POM Molecule-Based Flash Memory

The modelling of conventional and novel memory devices has gained significant traction in recent years. This is primarily because the need to store an increasingly larger amount of data demands a better understanding of the working of the novel memory devices, to enable faster development of the future technology generations. Furthermore, in-memory computing is also of great interest from the computational perspectives, to overcome the data transfer bottleneck that is prevalent in the von-Neumann architecture. These important factors necessitate the development of comprehensive TCAD simulation tools that can be used for modeling carrier dynamics in the gate oxides of the flash memory cells. In this work, we introduce the kinetic Monte Carlo module that we have developed and integrated within the Nano Electronic Simulation Software (NESS) – to model electronic charge transport in Flash memory type structures. Using the developed module, we perform retention time analysis for a polyoxometalate (POM) molecule-based charge trap flash memory. Our simulation study highlights that retention characteristics for the POM molecules have a unique feature that depends on the properties of the tunneling oxide.
Learning Social Skills and Acquiring Social Capital through Pervasive Gaming

There are several implicit benefits to formal school education One the most important is the learning of social skills i e how to behave, interact meaningfully and form social bonds with other people However, there are multiple situations where the learning of social skills can be disrupted, e g bullying or the recent COVID-19 pandemic that forced schools to transition into distance education In this work, we investigate the potential of pervasive games (PGs) to teach social skills and help acquire social capital Using the theoretical viewpoints of affordance lens and Pierre Bourdieu's theory of capital, we argue that PGs are able create meaningful activities that not only help learn social skills, but can scaffold social bonding and increase social capital We identify six social affordances in the PG Pokemon GO and show the game teaches a wide variety of social skills ranging from negotiation and bartering to group interaction Our findings have implications on designing educational pervasive games that teach social skills and accrue social capital Copyright © 2020 for this paper by its authors Use permitted under Creative Commons License Attribution 4 0 International (CC BY 4 0)
Interferon-Induced Protein 44 Correlated With Immune Infiltration Serves as a Potential Prognostic Indicator in Head and Neck Squamous Cell Carcinoma

Interferon-induced protein 44 (IFI44) containing a guanosine-5′-triphosphate (GTP) binding domain was reported to play a significant role in the immune response to autoimmune disease. However, its roles involved in cancers remain unclear. Here, we detected the expression of IFI44 in The Cancer Genome Atlas (TCGA) Pan-cancer and generally explored the effect of IFI44 on immune infiltration in the tumor microenvironment (TME). The results displayed that IFI44 was mainly located in the cytoplasm and overexpressed in head and neck squamous cell carcinoma (HNSC) samples compared with normal tissues. Survival analysis exhibited that IFI44 was remarkably associated with the clinical outcomes, particularly in lymph node-positive and locally advanced HNSC patients. Biological analysis showed that IFI44 was correlated with such immune biological processes as antigen-presenting and nuclear factor (NF)-kappa B signaling pathways. Immune signature analysis demonstrated that the expression of IFI44 was positively correlated with the infiltration of CD4+ cells and macrophages as well as neutrophils in HNSC. Taken together, these data suggested that IFI44 was abnormally expressed in cancer tissues and indicated the potential impact of IFI44 on the tumor immune infiltration in HNSC.
Delta-Modulator-Based Quantised Output Feedback Controller for Linear Networked Control Systems

This article proposes a <inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>-Modulator (<inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>-M) based quantised output feedback controller for linear networked systems. The proposed <inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>-M is essentially a 2-level quantiser, in contrast to some of the existing quantisers such as <inline-formula> <tex-math notation="LaTeX">$2^{p}$ </tex-math></inline-formula> level (<inline-formula> <tex-math notation="LaTeX">$p \geq 1$ </tex-math></inline-formula>) uniform-interval-nearest-neighbour quantiser, and offers various advantages which include lower design complexity, less noisy and lower cost. The three key components of the control system: the <italic>controller</italic>, the <italic>filter</italic> and the <italic>quantiser</italic> are designed to achieve the desired performance. The stability conditions of the <inline-formula> <tex-math notation="LaTeX">$\Delta $ </tex-math></inline-formula>-M are derived and conditions for the existence of <italic>zig-zag</italic> behaviour in steady-state are determined. The performance of the proposed controller is illustrated through simulations considering practical communication network based on ZigBee protocol. The results of the simulation demonstrate that the proposed controller could effectively achieve desired performance under various imperfections of the practical communication network.
Abundance Trends, Distribution, and Habitat Associations of the Invasive Mississippi Silverside (Menidia audens) in the Sacramento–San Joaquin Delta, California, USA

doi: http://dx.doi. org/10.15447/sfews.2016v14iss1art2 Although many alien fish species have colonized the Sacramento–San Joaquin Delta (Delta), few are as pervasive and abundant as Mississippi Silversides (Menidia audens). Moreover, Mississippi Silversides are hypothesized to be an intra-guild predator of the endangered Delta Smelt (Hypomesus transpacificus). Because of their prevalence in the Delta and poten-tial predation on Delta Smelt, Mississippi Silversides may have far-reaching effects on both the aquatic ecosystem and conservation management policies of the region. Yet little is known about how Mississippi Silverside abundance and distribution have changed within the Delta, or how they respond to various habitat attributes such as temperature, turbidity, and flow. We examined 19 years of beach seine survey data to evaluate how the abundance and distribution of Mississippi Silversides has changed over the years, characterize their habitat associations, and determine the environmental factors that predict their annual cohort strength. Concurrent with the decline of sev-eral pelagic fish species in the San Francisco Estuary in the early 2000s, we observed a significant increase in Mississippi Silverside catch that was accompanied by a moderate distributional shift in which densi-ties increased in the western Delta region. We also found that the occurrence of this highly prolific alien species was associated with higher water tempera-ture, higher turbidity, relatively low conductivity, and moderate to high levels of dissolved oxygen. Lastly, we demonstrated that freshwater input to the Sacramento–San Joaquin Delta during the summer and water exports during the spring months were both negatively correlated with the annual cohort size of Mississippi Silversides in the region. Our study identified the environmental variables deserv-ing additional attention in future studies involving Mississippi Silverside and suggests that the species favors habitat conditions that are likely to be detri-mental for pelagic species such as Delta Smelt.
Compact Macro-Cell With OR Pulse Combining for Low Power Digital-SiPM

High-density digital-Silicon Photomultipliers call for high-performance Single Photon Avalanche Diodes (SPAD) front-ends. Power consumption and fill factor are significant concerns in this kind of sensors. This paper presents a compact and power-efficient macro-cell where several SPADs share the active recharge circuitry for increased fill factor. Integrated with 110nm technology for image sensors, the array of macro-cells has 30% fill factor. Also, following the first firing of any SPAD during the same macro-pixel dead-time, the other SPADs are disabled for power saving. Of course, subsequent triggers are lost. However, they would have been masked by the OR pulse combining scheme. Besides this event-driven disabling feature, the macro-cell includes circuitry to disable noisy devices – similar to other SiPM cells. Also, the macro-cell features control of the dead-time. This paper describes the macro-cell concept, its associated analysis and design equations. Key parameters of the design are discussed to optimize power consumption. Design scalability is contemplated as well. Experimental results proved that the power efficiency of the proposed scheme depends on the illumination power. Also, power efficiency is linked to the pulse overlapping probability. For example, power saving up to 30% is obtained with 4 sub-cells per macro-cell, when pulse overlapping is about 11% for correlated light or the pulse rate per sub-cell is about 100kHz for uncorrelated light.
The Influence of Knowledge Management Process on Job Satisfaction: A Case Study of detikNetwork Product Management Division

As a part of creative businesses, online news company requires innovations to stay ahead in the competition. Company capability to innovate relies on the employee's competency. Product Management division in detikNetwork adopts knowledge management processes to increase their employee's innovation capability. However, they still suffered 20% rate of employee resignation from November 2018 until November 2019. On the other hand, knowledge management is believed to have an impact on job satisfaction. Therefore, this research purpose is to investigate which KM process has an impact on job satisfaction. The KM process can be represented in a SECI model. The SECI model consists of socialization, externalization, combination, and internalization process. This research used online questionnaires for collecting data, and the participant was employees of Product Management division in detikNetwork. From 69 target participants, only 43 sent valid replies. The response of questionnaires realized the participants were in early stage of their career. This research used SmartPLS software for quantitative analysis. The result of this research showed that only the internalization process had an impact on job satisfaction. It reflects a process that facilitates knowledge improvement influences job satisfaction positively. Hence, it is important for management to maintain internalization in their KM Process. Since the other processes did not bring a significant impact on job satisfaction, management needs to adopt another KM process which is more suitable to company characteristics.