Miracle-dz/UniFAR-FTUs huggingface dataset:
Issues in Information Systems

Coined by Gross (1964) and popularized by Toffler (1970) and Carr (2010), information overload represents an overwhelming bombardment of digital information that often substantiates underpinnings of continuous mental stress, anxiety, and distraction caused by a combination of queued info glut and incessant interruptions. But it was the advent of the World Wide Web in 1989 (Berners-Lee, 2000) and the onset of ubiquitous connectivity that turned information overload into a daunting and even debilitating phenomenon. Informationists have written extensively about the corporate manifestation of info glut in the workplace requiring agile mitigation strategies to retain knowledge workers and managers. And a new Pew Report (Dec. 2016) disclosed positive results that users are discovering their own ways to ameliorate the tensions of today’s information-saturated-world when organizations place high demands on employees. However, this research represents a pragmatic approach to understanding the present environment of organizational information overload. The professional employees and managers of a large US global corporation were studied for coping strategy feedback regarding an infinite and unwieldy information glut; results were analyzed for successful or failed remedies set-forth by employers; and then findings were compared to the Pew Report results to assess the current state of infomania (Ferrarini, 1984) in the workplace.
verifiable and multi-keyword searchable attribute-based encryption scheme for cloud storage

The success of the cloud computing paradigm is due to its on-demand, self-service, and pay-by-use nature. Public key encryption with keyword search applies only to the certain circumstances that keyword cipher text can only be retrieved by a specific user and only supports single-keyword matching. In the existing searchable encryption schemes, either the communication mode is one-to-one, or only single-keyword search is supported. This paper proposes a searchable encryption that is based on attributes and supports multi-keyword search. Searchable encryption is a primitive, which not only protects data privacy of data owners but also enables data users to search over the encrypted data. Most existing searchable encryption schemes are in the single-user setting. There are only few schemes in the multiple data users setting, i.e., encrypted data sharing. Among these schemes, most of the early techniques depend on a trusted third party with interactive search protocols or need cumbersome key management. To remedy the defects, the most recent approaches borrow ideas from attribute-based encryption to enable attribute-based keyword search (ABKS).
Recent advances in the development of legumain-selective chemical probes and peptide prodrugs

Abstract Legumain, which is also known as vacuolar processing enzyme (VPE) or asparaginyl endopeptidase (AEP), is a cysteine protease that was first discovered and characterized in the leguminous seeds of the moth bean in the early 1990s. Later, this enzyme was also detected in higher organisms, including eukaryotes. This pH-dependent protease displays the highest activity in acidic endolysosomal compartments; however, legumain also displays nuclear, cytosolic and extracellular activity when stabilized by other proteins or intramolecular complexes. Based on the results from over 25 years of research, this protease is involved in multiple cellular events, including protein degradation and antigen presentation. Moreover, when dysregulated, this protease contributes to the progression of several diseases, with cancer being the well-studied example. Research on legumain biology was undoubtedly facilitated by the use of small molecule chemical tools. Therefore, in this review, I present the historical perspectives and most current strategies for the development of small molecule substrates, inhibitors and activity-based probes for legumain. These tools are of paramount importance in elucidating the roles of legumain in multiple biological processes. Finally, as this enzyme appears to be a promising molecular target for anticancer therapies, the development of legumain-activated prodrugs is also described.
A Symphytum officinale Root Extract Exerts Anti-inflammatory Properties by Affecting Two Distinct Steps of NF-κB Signaling

Symphytum officinale, commonly known as comfrey, constitutes a traditional medicinal plant with a long-standing therapeutic history, and preparations thereof have been widely used for the treatment of painful muscle and joint complaints, wound and bone healing, and inflammation. Today, its topical use is based on its analgesic and anti-inflammatory effects, which have been substantiated by modern clinical trials. However, the molecular basis of its action remained elusive. Here, we show that a hydroalcoholic extract of comfrey root impairs the development of a pro-inflammatory scenario in primary human endothelial cells in a dose-dependent manner. The extract, and especially its mucilage-depleted fraction, impair the interleukin-1 (IL-1) induced expression of pro-inflammatory markers including E-selectin, VCAM1, ICAM1, and COX-2. Both preparations inhibit the activation of NF-κB, a transcription factor of central importance for the expression of these and other pro-inflammatory genes. Furthermore, our biochemical studies provide evidence that comfrey inhibits NF-κB signaling at two stages: it dampens not only the activation of IKK1/2 and the subsequent IκBα degradation, but also interferes with NF-κB p65 nucleo-cytoplasmatic shuttling and transactivation. These results provide a first mechanistic insight into the mode of action of a century-old popular herbal medicine.
Precision Nutrition and the Microbiome, Part I: Current State of the Science

The gut microbiota is a highly complex community which evolves and adapts to its host over a lifetime. It has been described as a virtual organ owing to the myriad of functions it performs, including the production of bioactive metabolites, regulation of immunity, energy homeostasis and protection against pathogens. These activities are dependent on the quantity and quality of the microbiota alongside its metabolic potential, which are dictated by a number of factors, including diet and host genetics. In this regard, the gut microbiome is malleable and varies significantly from host to host. These two features render the gut microbiome a candidate ‘organ’ for the possibility of precision microbiomics—the use of the gut microbiome as a biomarker to predict responsiveness to specific dietary constituents to generate precision diets and interventions for optimal health. With this in mind, this two-part review investigates the current state of the science in terms of the influence of diet and specific dietary components on the gut microbiota and subsequent consequences for health status, along with opportunities to modulate the microbiota for improved health and the potential of the microbiome as a biomarker to predict responsiveness to dietary components. In particular, in Part I, we examine the development of the microbiota from birth and its role in health. We investigate the consequences of poor-quality diet in relation to infection and inflammation and discuss diet-derived microbial metabolites which negatively impact health. We look at the role of diet in shaping the microbiome and the influence of specific dietary components, namely protein, fat and carbohydrates, on gut microbiota composition.
Low genetic heterogeneity of copy number variations (CNVs) in the genes encoding the human deoxyribonucleases 1-like 3 and II potentially relevant to autoimmunity

Deoxyribonucleases (DNases) might play a role in prevention of autoimmune conditions such as systemic lupus erythematosus through clearance of cell debris resulting from apoptosis and/or necrosis. Previous studies have suggested that variations in the in vivo activities of DNases I-like 3(1L3) and II have an impact on autoimmune-related conditions. The genes for these DNases are known to show copy number variations (CNVs) whereby copy loss leads to a reduction of the in vivo activities of the enzymes, thereby possibly affecting the pathophysiological background of autoimmune diseases. Using a simple newly developed quantitative real-time PCR method, we investigated the distributions of the CNVs for DNASE1L3 and DNASE2 in Japanese and German populations. It was found that only 2 diploid copy numbers for all of these DNASE CNVs was distributed in both of the study populations; no copy loss or gain was evident for any of the autoimmune-related DNase genes. Therefore, it was demonstrated that these human autoimmune-related DNase genes show low genetic diversity of CNVs resulting in alterations of the in vivo levels of DNase activity.
CAViaR : Conditional Autoregressive Value at Risk by Regression Quantiles

Value at Risk (VaR) has become the standard measure of market risk employed by financial institutions for both internal and regulatory purposes. VaR is defined as the value that a portfolio will lose with a given probability, over a certain time horizon (usually one or ten days). Interpreting the VaR as the quantile of future portfolio values conditional on current information, we propose a new approach to quantile estimation that does not require any of the extreme assumptions invoked by existing methodologies (such as normality or i.i.d. returns). The Conditional Autoregressive Value at Risk or CAViaR model moves the focus of attention from the distribution of returns directly to the behavior of the quantile. We specify the evolution of the quantile over time using an autoregressive process and use the regression quantile framework introduced by Koenker and Bassett to determine the unknown parameters. Utilizing the criterion that each period the probability of exceeding the VaR must be independent of all the past information, we introduce a new test of model adequacy, the Dynamic Quantile (DQ) test. Applications to real data provide empirical support to this methodology.
Haematological evaluation of Wistar rats exposed to chronic doses of cadmium, mercury and combined cadmium and mercury

1 Interfaculty Centre of Training and Research in Environment for Sustainable Development (CIFRED), University of Abomey-Calavi, 03 BP 1463, Cotonou, Benin. 2 Departement of Biochemistry and Cellular Biology, University of Abomey-Calavi, 01BP 526 Cotonou, Benin. 3 Department of Cell Biology and Genetics, Faculty of Science, University of Lagos, Nigeria 4 Polytechnic School of Abomey-Calavi, Research Laboratory in Applied Biology, University of Abomey-Calavi, 01 BP 2009 Cotonou, Benin. 5 Laboratory of Hydrobiology, Ecotoxicology and Cleansing, Department of Biology, Faculty of Science Semlalia, University Cadi Ayyad, BP 2390, Marrakech, Morocco. 6 Laboratory of Toxicology and Applied Hygiene/UFR of Pharmaceutical Sciences, 146, Road Leo Saignat, 33076 Bordeaux Cedex, France.
A narrative review of the evidence regarding the use of telemedicine to deliver video‐interpreting during dementia assessments for older people

As Australia's aging population increases and diversifies, there will be a growing need to address the burden of dementia among culturally and linguistically diverse (CALD) communities. Due to a lack of CALD‐appropriate services and bilingual health professionals, older people from CALD backgrounds often receive a delayed diagnosis of dementia. The use of telemedicine (TM) to deliver video‐interpreting services may overcome the barriers of interpreter availability when diagnosing and assessing dementia in older people from CALD backgrounds.
Comprehensive Analysis of Housing Price Prediction in Pune Using Multi-Featured Random Forest Approach

The housing sector in India has been predicted to grow at 30-35% over the next decade. In terms of employment provided, it is second only to the agricultural sector. Housing is one of the major domain of real estate. Pune is emerging as one of the major metropolitan cities of India and has many prestigious Educational institutions and IT parks. This makes it an ideal place to buy homes. Vagueness among the prices of houses makes it challenging for the buyer to select their dream house. The interests of both buyer and seller should be satisfied so that they do not overestimate or underestimate price. This housing price prediction model acts as a helping hand for buyer and seller or a real estate agent to make a better-informed decision. To achieve this, diverse features are selected as input from feature set and various algorithms are applied such as Random Forest and Decision Tree.
A Multi-Beam Direction- and Polarization-Agile mm-Wave Front-End for 5G Communications

A millimeter wave multi-beam direction- and polarization-agile front-end for 5th generation of wireless communications at 30 GHz is presented. Active voltage summing was used for the lossless electronic rotation of polarization, thus enhancing the envisaged flexibility of 5G air interfaces. The front-end core comprises a low-temperature co-fired ceramic multilayer module, hybrid-integrated monolithic microwave integrated circuits, and an incorporated dual-polarized 4-element array antenna, altogether at a compact size of 74 mm × 74 mm. Antenna feed phases and polarization angles and states are electronically programmable. The front-end, completed by control circuit boards and a heatsink, exhibits an over-the-air gain of 50 dB and a noise figure of 4.1 dB. Measurement results comprising the polarization control and beamformer blocks are presented.
Improved Time-Frequency Features and Electrode Placement for EEG-Based Biometric Person Recognition

This paper introduces a novel feature extraction method for biometric recognition using EEG data and provides an analysis of the impact of electrode placements on performance. The feature extraction method is based on the wavelet transform of the raw EEG signal. Furthermore, the logarithms of wavelet coefficients are processed using the discrete cosine transform (DCT). The DCT coefficients from each wavelet band are used to form the feature vectors for classification. As an application in the biometrics scenario, the effectiveness of the electrode locations on person recognition is also investigated, and suggestions are made for electrode positioning to improve performance. The effectiveness of the proposed feature was investigated in both identification and verification scenarios. The identification results of 98.24% and 93.28% were obtained using the EEG Motor movement/imagery dataset (MM/I) and the UCI EEG database dataset, respectively, which compares favorably with other published reports while using a significantly smaller number of electrodes. The performance of the proposed system also showed substantial improvements in the verification scenario, when compared with some similar systems from the published literature. A multi-session analysis is simulated using with eyes open and eyes closed recordings from the MM/I database. It is found that the proposed feature is less influenced by time separation between training and testing compared with a conventional feature based on power spectral analysis.
Multiple Residual Learning Network for Single Image Super-Resolution

Deep residual convolutional neural network (CNN) has recently achieved great success in image super-resolution (SR). Because residual learning accelerates convergence rate and eases the difficulty for reconstructing high-resolution (HR) image, these CNN models can achieve higher peak signal to noise ratio (PSNR) values with lower training cost. However, residual image used in present residual network still contains much high frequency information, which increases learning burden and limits learning ability of residual network. Moreover, training a very deep network faces many obstacles and costs too much time. In this paper, we propose a multiple residual learning network (MRLN), which not only further simplifies information complexity of residual image and improves the accuracy of residual network, but also obviously reduces time cost for training a very deep CNN. In MRLN, we use a shallow network formed by 30-layer convolutional layers as basic model and train it for multiple times. The output of previous basic model is used as the HR input of the next one. In this way, an extremely large CNN is converted into a series connection of shallow networks. Fig. 1 shows PSNR of recent state-of-the-art CNN models for scale factor 2 on Set5, our method performs better than other methods and set a new level for SR.
$L_gV$-Type Adaptive Controllers for Uncertain Non-Affine Systems and Application to a DC-Microgrid with PV and Battery

Adaptive control of general nonlinear systems with nonlinear parameterization is studied in this paper. Under the assumptions that the system has stable free dynamics and satisfies controllability-like conditions characterized by the Lie brackets of affine vector fields, it is proved that there exist <inline-formula><tex-math notation="LaTeX">$L_gV$</tex-math></inline-formula>-type adaptive controllers that not only asymptotically regulate the state of the nonlinearly parameterized system but also guarantee global stability of the closed-loop system. The design of <inline-formula><tex-math notation="LaTeX">$L_gV$</tex-math></inline-formula>-type adaptive controllers is also included. Applications of the proposed adaptive control scheme are presented, including an interesting case of a dc-microgrid with photovoltaic (PV) and battery system.
Cotton WATs Modulate SA Biosynthesis and Local Lignin Deposition Participating in Plant Resistance Against Verticillium dahliae

Verticillium wilt, caused by Verticillium dahliae, seriously limits cotton production. It is difficult to control this pathogen damage mainly due to the complexity of the molecular mechanism of plant resistance to V. dahliae. Here, we identified three homologous cotton Walls Are Thin (WAT) genes, which were designated as GhWAT1, GhWAT2, and GhWAT3. The GhWATs were predominantly expressed in the roots, internodes, and hypocotyls and induced by infection with V. dahliae and treatment with indole-3-acetic acid (IAA) and salicylic acid (SA). GhWAT1-, GhWAT2-, or GhWAT3-silenced plants showed a comparable phenotype and level of resistance with control plants, but simultaneously silenced three GhWATs (GhWAT123-silenced), inhibited plant growth and increased plant resistance to V. dahliae, indicating that these genes were functionally redundant. In the GhWAT123-silenced plants, the expression of SA related genes was significantly upregulated compared with the control, resulting in an increase of SA level. Moreover, the histochemical analysis showed that xylem development was inhibited in GhWAT123-silenced plants compared with the control. However, lignin deposition increased in the xylem of the GhWAT123-silenced plants compared to the control, and there were higher expression levels of lignin synthesis- and lignifications-related genes in the GhWAT123-silenced plants. Collectively, the results showed that GhWATs in triple-silenced plants acts as negative regulators of plant resistance against V. dahliae. The potential mechanism of the WATs functioning in the plant defence can modulate the SA biosynthesis and lignin deposition in the xylem.
WNK1 promotes renal tumor progression by activating TRPC6‐NFAT pathway

Deregulation of Ca2+ signaling has been regarded as one of the key features of cancer progression. Lysine‐deficient protein kinase 1 (WNK1), a major regulator of renal ion transport, regulates Ca2+ signaling through stimulating the phosphatidylinositol 4‐kinase IIIα (PI4KIIIα) to activate Gαq‐coupled receptor/PLC‐β signaling. However, the contribution of WNK1‐mediated Ca2+ signaling in the development of clear‐cell renal‐cell carcinoma (ccRCC) is yet unknown. We found that the canonical transient receptor potential channel (TRPC)6 was widely expressed in ccRCC tissues and functioned as a primary Ca2+ influx mechanism. We further identified that the expressions of WNK1, PI4KIIIcα, TRPC6, and the nuclear factor of activated T cells cytoplasmic 1 (NFATc1) were elevated in the tumor tissues compared with the adjacent normal tissues. WNK1 expression was directly associated with the nuclear grade of ccRCC tissues. Functional experiments showed that WNK1 activated TRPC6‐mediated Ca2+ influx and current by stimulating PI4KIIIα. Notably, the inhibition of WNK1‐mediated TRPC6 activation and its downstream substrate calcineurin attenuated NFATc1 activation and the subsequent migration and proliferation of ccRCC. These findings revealed a novel perspective of WNK1 signaling in targeting the TRPC6‐NFATc1 pathway as a therapeutic potential for renal‐cell carcinoma. —Kim, J.‐H. , Hwang, K. ‐H. , Eom, M. , Kim, M. , Park, E. Y. , Jeong, Y. , Park, K. ‐S. , Cha, S. ‐K. WNK1 promotes renal tumor progression by activating TRPC6‐NFAT pathway. FASEB J. 33, 8588–8599 (2019). www.fasebj. org
miR393s regulate salt stress response pathway in Arabidopsis thaliana through scaffold protein RACK1A mediated ABA signaling pathways

ABSTRACT Scaffold protein Receptor for Activated C Kinase 1 (RACK1) is a negative regulator of plant stress hormone – abscisic acid (ABA) mediated pathways. RACK1 has been reported to regulate global miRNA biogenesis pathway in C. elegans, humans, and in Arabidopsis. RACK1 regulates different steps of miRNA biogenesis and stability in response to different stimuli in plants. miR393s is implicated in salt stress response pathway through an antagonistic response between the stress hormone ABA-mediated salt stress and growth hormone auxin. Specifically, the known auxin receptor clade transcripts TIR1/AFB2 are the target for the miR393s. By down-regulating the auxin signaling pathways, the miR393s inhibit the regulation of salt tolerance by auxin. Here we show that genetic loss of RACK1A- the predominant member of the three genes family of RACK1 in Arabidopsis, results in the inhibition of miR393 level causing the same salt sensitivities as the individual mir393a or mir393b or the double mutant mir393ab phenotypes. We propose that down-regulation of auxin signaling through RACK1A induced miR393 biogenesis potentially regulates the Arabidopsis acclimation to salinity. Our findings fill up a molecular gap in our understanding of the role of miR393 mediated ABA and auxin-regulated salt stress responses.