Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanoarchitectonic atomic switch networks for unconventional computing

Developments in computing hardware are constrained by the operating principles of complementary metal oxide semiconductor (CMOS) technology, fabrication limits of nanometer scaled features, and difficulties in effective utilization of high density interconnects. This set of obstacles has promulgated a search for alternative, energy efficient approaches to computing inspired by natural systems including the mammalian brain. Atomic switch network (ASN) devices are a unique platform specifically developed to overcome these current barriers to realize adaptive neuromorphic technology. ASNs are composed of a massively interconnected network of atomic switches with a density of ∼109 units/cm2 and are structurally reminiscent of the neocortex of the brain. ASNs possess both the intrinsic capabilities of individual memristive switches, such as memory capacity and multi-state switching, and the characteristics of large-scale complex systems, such as power-law dynamics and non-linear transformations of input signals. Here we describe the successful nanoarchitectonic fabrication of next-generation ASN devices using combined top-down and bottom-up processing and experimentally demonstrate their utility as reservoir computing hardware. Leveraging their intrinsic dynamics and transformative input/output (I/O) behavior enabled waveform regression of periodic signals in the absence of embedded algorithms, further supporting the potential utility of ASN technology as a platform for unconventional approaches to computing.
Who votes for virtue? Religion and party choice in Thailand’s 2019 election

Does religion shape political competition in Thailand? Despite the prominence of religiously inflected rhetoric of good and evil in contemporary political contestation, existing research suggests that it does not. This article challenges this conventional wisdom. Survey data collected in connection with Thailand’s 2019 general election, which marked a transition from direct military rule to a hybrid regime, allow us to examine the political relevance of religious belonging, belief, and behaviour. Our analysis finds evidence for the political salience of a secular/religious cleavage: voters who self-identified as more religious were more inclined to support the main pro-military party Palang Pracharath and its closest allies, whilst more secularised voters tended to support anti-military parties in general and the Future Forward Party in particular. We also find that Thailand’s religious minorities were politically divided: Muslims and Protestants backed the pro-military parties whilst Catholics opposed them. Our analysis underscores the need for more attention to the role of religious cleavages in Thai political contention.
From Weed to Fabric

The book from weed to fabric was written within the project: Revitalisation of textile production of Spartium junceum L. - Development of indigenous Croatian product: From weed to fabric, funded by the Development fund of the University of Zagreb. The main goal of the project was to develop original textile products made from Spartium junceum L. - as autochthon Croatian souvenir.
PySCP: A Multiple-Phase Optimal Control Software Using Sequential Convex Programming

Optimal control problems are common in aerospace engineering. A Python software program called PySCP is described for solving multiple-phase optimal control problems using sequential convex programming methods. By constructing a series of approximated second-order cone programming subproblems, PySCP approaches to the solution of the original optimal control problem in an iterative way. The key components of the software are described in detail, including convexification, discretization, and the adaptive trust region method. The convexification of the first-order differential dynamic equation is implemented using successive linearization. Six discretization methods, including zero-order hold, first-order hold, Runge-Kutta, and three hp pseudospectral collocation methods, are implemented so that different types of optimal control problems can be tackled efficiently. Adaptive trust region method is employed, and robust convergence is achieved. Both free-final-time problem and fixed-final-time problem can be solved by the software. The application of the software is demonstrated on three optimal control problems with varying complexity. PySCP provides researchers a useful toolkit to solve a wide variety of optimal control problems using sequential convex programming.
Computing One-Bit Compressive Sensing Via Zero-Norm Regularized Dc Loss Model and its Surrogate

One-bit compressed sensing is very popular in signal processing and communications due to its low storage costs and low hardware complexity, but it is a challenging task to recover the signal by using the one-bit information. In this paper, we propose a zero-norm regularized smooth difference of convexity (DC) loss model and derive a family of equivalent nonconvex surrogates covering the MCP and SCAD surrogates as special cases. Compared to the existing models, the new model and its SCAD surrogate have better robustness. To compute their $\tau$-stationary points, we develop a proximal gradient algorithm with extrapolation and establish the convergence of the whole iterate sequence. Also, the convergence is proved to have a linear rate under a mild condition by studying the KL property of exponent 0 of the models. Numerical comparisons with several state-of-art methods show that in terms of the quality of solution, the proposed model and its SCAD surrogate are remarkably superior to the $\ell_p$-norm regularized models, and are comparable even superior to those sparsity constrained models with the true sparsity and the sign flip ratio as inputs.
Curcumin Facilitates Aryl Hydrocarbon Receptor Activation to Ameliorate Inflammatory Astrogliosis

Curcumin is an anti-inflammatory and neuroprotective compound in turmeric. It is a potential ligand of the aryl hydrocarbon receptor (AhR) that mediates anti-inflammatory signaling. However, the AhR-mediated anti-inflammatory effect of curcumin within the brain remains unclear. We investigated the role of AhR on the curcumin effect in inflammatory astrogliosis. Curcumin attenuated lipopolysaccharide (LPS)-induced proinflammatory IL-6 and TNF-α gene expression in primary cultured rat astrocytes. When AhR was knocked down, LPS-induced IL-6 and TNF-α were increased and curcumin-decreased activation of the inflammation mediator NF-κB p65 by LPS was abolished. Although LPS increased AhR and its target gene CYP1B1, curcumin further enhanced LPS-induced CYP1B1 and indoleamine 2,3-dioxygenase (IDO), which metabolizes tryptophan to AhR ligands kynurenine (KYN) and kynurenic acid (KYNA). Potential interactions between curcumin and human AhR analyzed by molecular modeling of ligand–receptor docking. We identified a new ligand binding site on AhR different from the classical 2,3,7,8-tetrachlorodibenzo-p-dioxin site. Curcumin docked onto the classical binding site, whereas KYN and KYNA occupied the novel one. Moreover, curcumin and KYNA collaboratively bound onto AhR during molecular docking, potentially resulting in synergistic effects influencing AhR activation. Curcumin may enhance the inflammation-induced IDO/KYN axis and allosterically regulate endogenous ligand binding to AhR, facilitating AhR activation to regulate inflammatory astrogliosis.
Anisakicidal Effects of R (+) Limonene: An Alternative to Freezing Treatment in the Industrial Anchovy Marinating Process

Anisakiasis is a fish-borne zoonotic disease caused by the ingestion of raw/undercooked fishes or cephalopods parasitized by members of the genus Anisakis. Freezing ensures the inactivation of viable Anisakis larvae; however, since it affects the organoleptic properties of food, essential oils and their compounds were proposed as an alternative. In this study, fresh anchovy fillets were experimentally parasitized with L3 Anisakis larvae to test the anisakicidal efficacy of R (+) limonene (LMN) in marinated fishery products. The anisakicidal effectiveness and organoleptic influence of several LMN concentrations (0.5%, 1%, and 5%) were tested during the marinating process (MS) and storage in sunflower seed oil (SO) of marinated anchovy fillets. Double treatment (DT) with 1% LMN was also performed both during marination and subsequent storage in oil. MS treatment resulted only in a reduction in larvae viability after 48 h, while a complete inactivation was observed in SO after 8, 10, and 20 days of treatment with 5%, 1%, and 0.5% LMN, respectively. DT was the most effective with complete larval inactivation after 7 days. Only 5% LMN influenced the sensory characteristics of the fillets, resulting, however, in a pleasant lemon-like odor and taste. Considering the results obtained, LMN might be a suitable natural alternative to manage Anisakis risk in the fishery industry.
The Association between Medical Utilization and Chronic Obstructive Pulmonary Disease Severity: A Comparison of the 2007 and 2011 Guideline Staging Systems

(1) Background: This study aimed to investigate the associations between the Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging systems, medical costs, and mortality among patients with chronic obstructive lung disease (COPD). Predictions of the effectiveness of the two versions of the staging systems were also compared. (2) Purpose: this study investigated the associations between the Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging systems, medical costs, and mortality among patients with COPD. Predicting effectiveness between the two versions of the staging systems was also compared. (3) Procedure: This study used a secondary clinical database of a medical center in central Taiwan to examine records between 2011 and 2017. A total of 613 patients with COPD were identified. The independent variables comprised the COPD GOLD Guideline staging of the 2007 and 2011 versions, demographic characteristics, health status, and physician seniority. The dependent variables included total medical cost, average length of hospital stay, and mortality. The statistical methods included binomial logistic regression and the general linear model (GLM). (4) Discussion: The total medical cost during the observation period for patients with COPD averaged TWD 292,455.6. The average length of hospital stay was 9.7 days. The mortality rate was 9.6%, compared with that of patients in Grade 1 of the 2007 version; patients in Grade 4 of the 2007 version had significantly higher odds of death (OR = 4.07, p = 0.02). The accuracy of mortality prediction for both the 2007 and 2011 versions of the staging was equal, at 90.4%. The adjusted GLM analysis revealed that patients in Group D of the 2011 version had a significantly longer length of hospital stay than those in Group A of the 2011 version (p = 0.04). No difference between the 2007 and 2011 versions was found regarding the total medical cost. Complications were significantly associated with the total medical cost and average length of hospital stay. (5) Conclusions: The COPD staging 2011 version was associated with an average length of hospital stay, whereas the COPD staging 2007 version was related to mortality risk. Therefore, the 2011 version can estimate the length of hospital stay. However, in predicting prognosis and mortality, the 2007 version is recommended.
Deep Learning for Vulnerability and Attack Detection on Web Applications: A Systematic Literature Review

Web applications are the best Internet-based solution to provide online web services, but they also bring serious security challenges. Thus, enhancing web applications security against hacking attempts is of paramount importance. Traditional Web Application Firewalls based on manual rules and traditional Machine Learning need a lot of domain expertise and human intervention and have limited detection results faced with the increasing number of unknown web attacks. To this end, more research work has recently been devoted to employing Deep Learning (DL) approaches for web attacks detection. We performed a Systematic Literature Review (SLR) and quality analysis of 63 Primary Studies (PS) on DL-based web applications security published between 2010 and September 2021. We investigated the PS from different perspectives and synthesized the results of the analyses. To the best of our knowledge, this study is the first of its kind on SLR in this field. The key findings of our study include the following. (i) It is fundamental to generate standard real-world web attacks datasets to encourage effective contribution in this field and to reduce the gap between research and industry. (ii) It is interesting to explore some advanced DL models, such as Generative Adversarial Networks and variants of Encoders–Decoders, in the context of web attacks detection as they have been successful in similar domains such as networks intrusion detection. (iii) It is fundamental to bridge expertise in web applications security and expertise in Machine Learning to build theoretical Machine Learning models tailored for web attacks detection. (iv) It is important to create a corpus for web attacks detection in order to take full advantage of text mining in DL-based web attacks detection models construction. (v) It is essential to define a common framework for developing and comparing DL-based web attacks detection models. This SLR is intended to improve research work in the domain of DL-based web attacks detection, as it covers a significant number of research papers and identifies the key points that need to be addressed in this research field. Such a contribution is helpful as it allows researchers to compare existing approaches and to exploit the proposed future work opportunities.
Spotted Hyena Optimization Method for Harvesting Maximum PV Power under Uniform and Partial-Shade Conditions

Maximum power-point-tracking techniques applied for partially shaded photovoltaic array yield maximum power output via operating the panel at its most efficient voltage. Considering the noticeable issues existing with the available methods, including steady-state oscillations, poor tracking capability and complex procedures, a new bioinspired Spotted-Hyena Optimizer (SHO) is proposed. It follows simple implementation steps, and does not require additional controller-parameter tuning to track the optimal power point. To validate the versatility of the proposed method, the SHO algorithm is applied to track the maximum power of different string arrangements under six partial-shade conditions. Further, to authenticate SHO’s methods, its results are compared with perturb-and-observe (P&O), and particle-swarm-optimization (PSO) methods. As a result of its implementation, it is observed that the tracking speed of SHO towards the global convergence for four patterns under 4S2P are 0.34 s, 0.24 s, 0.2 s, and 0.3 s, which is far less than the PSO and P&O methods. Further, to demonstrate its suitability, a hardware prototype is built and tested for various operating conditions. The experimental results are in good agreement with the simulated values.
Social vulnerability and disasters: development and evaluation of a CONVERGE training module for researchers and practitioners

PurposeSocial vulnerability in the context of disaster management refers to the sociodemographic characteristics of a population and the physical, social, economic, and environmental factors that increase their susceptibility to adverse disaster outcomes and capacity to anticipate, cope with, resist, and recover from disaster events. Because disasters do not impact people equally, researchers, public health practitioners, and emergency managers need training to meet the complex needs of vulnerable populations.Design/methodology/approachTo address gaps in current education, the CONVERGE initiative, headquartered at the Natural Hazards Center at the University of Colorado Boulder, developed the Social Vulnerability and Disasters Training Module. This free online course draws on decades of research to examine the factors that influence social vulnerability to disasters. Examples of studies and evidence-based programs are included to illuminate common methods for studying social vulnerability and ways that research can guide practice. To evaluate the module, all trainees completed a pre- and post-training questionnaire.FindingsBetween July 2019 and September 2021, 1,089 people completed the module. Wilcoxon signed rank tests demonstrated a significant perceived increase in self-rated knowledge, skills, and attitudes (KSA). Students, members of historically underrepresented populations, and those new to or less experienced in the field, had the greatest perceived increase.Practical implicationsThis training module can help participants understand the specific needs of socially vulnerable populations to help reduce human suffering from disasters.Originality/valueThis article describes a novel web-based training and offers evaluation data showing how it can help educate a broad hazards and disaster workforce on an important topic for disaster management.
Hybrid photometric redshifts for sources in the COSMOS and XMM-LSS fields

In this paper we present photometric redshifts for 2.7 million galaxies in the XMM-LSS and COSMOS fields, both with rich optical and near-infrared data from VISTA and HyperSuprimeCam. Both template fitting (using galaxy and Active Galactic Nuclei templates within LePhare) and machine learning (using GPz) methods are run on the aperture photometry of sources selected in the Ks-band. The resulting predictions are then combined using a Hierarchical Bayesian model, to produce consensus photometric redshift point estimates and probability distribution functions that outperform each method individually. Our point estimates have a root mean square error of ∼0.08 − 0.09, and an outlier fraction of ∼3 − 4 percent when compared to spectroscopic redshifts. We also compare our results to the COSMOS2020 photometric redshifts, which contains fewer sources, but had access to a larger number of bands and greater wavelength coverage, finding that comparable photo-z quality can be achieved (for bright and intermediate luminosity sources where a direct comparison can be made). Our resulting redshifts represent the most accurate set of photometric redshifts (for a catalogue this large) for these deep multi-square degree multi-wavelength fields to date.
Exploring the Impact of Chitosan Composites as Artificial Organs

Chitosan and its allies have in multiple ways expanded into the medical, food, chemical, and biological industries and is still expanding. With its humble beginnings from marine shell wastes, the deacetylated form of chitin has come a long way in clinical practices. The biomedical applications of chitosan are truly a feather on its cap, with rarer aspects being chitosan’s role in tissue regeneration and artificial organs. Tissue regeneration is a highly advanced and sensitive biomedical application, and the very fact that chitosan is premiering here is an authentication of its ability to deliver. In this review, the various biomedical applications of chitosan are touched on briefly. The synthesis methodologies that are specific for tissue engineering and biomedical applications have been listed. What has been achieved using chitosan and chitosan composites in artificial organ research as well as tissue regeneration has been surveyed and presented. The lack of enthusiasm, as demonstrated by the very few reports online with respect to chitosan composites and artificial organs, is highlighted, and the reasons for this lapse speculated. What more needs be done to expand chitosan and its allies for a better utilization and exploitation to best benefit the construction of artificial organs and building of tissue analogs has been discussed.
Interleukin-10 Mitigates Doxorubicin-Induced Endoplasmic Reticulum Stress as Well as Cardiomyopathy

The use of doxorubicin (Dox) in cancer patients carries the risk of cardiotoxicity via an increase in oxidative stress, mitochondrial dysfunction, and disturbed endoplasmic reticulum (ER) homeostasis in cardiomyocytes. The present study explores which of the ER transmembrane sensors is involved in Dox-induced apoptosis and whether interleukin-10 (IL-10) has any mitigating effect. There was a time-related increase in apoptosis in cardiomyocytes exposed to 5.43 µg/mL Dox for 0 to 48 h. Dox treatment for 24 h significantly upregulated glucose-regulated proteins 78 and 94, protein disulfide isomerase, cleavage of activating transcription factor 6α, and X-box binding protein 1. These Dox-induced changes in ER stress proteins as well as apoptosis were blunted by IL-10 (10 ng/mL). In Dox-exposed cardiomyocytes, IL-10 also promoted expression of protein kinase-like endoplasmic reticulum kinase and inositol-requiring kinase 1α, which helped in maintaining ER homeostasis. Additionally, under Dox-treatment, IL-10 downregulated caspase-12 activation as well as phosphorylation of c-JUN NH2-terminal kinase, thereby promoting cardiomyocyte survival. IL-10 was able to reduce the overexpression of mitochondrial apoptotic proteins caspase-3 as well as Bax, which were upregulated upon Dox treatment. Thus, a reduction in Dox-induced ER stress as well as apoptosis through IL-10 may provide a significant benefit in improving cardiac function.
Rapid Repair Technique to Improve Plastic Dissipation of Existing Chinese RC Bridges

A rapid repair and retrofitting technique for reinforced concrete (rc) Chinese existing bridges damaged by a strong earthquake, is proposed and tested. These bridges were designed according to Chinese codes [1] [2] [3] but with insufficient transversal steel reinforcement. The damaged rebar and concrete parts were replaced by new bar systems and concrete cast respectively. Finally, a C-FRP wrapping was applied to increase the insufficient shear strength and to guarantee the necessary ductility in plastic hinge. This repair technique is an upgrade of the one tested with very good results during a previous experimental research [4] on bridge designed according to old Italian code [5] without proper seismic details. A new bar system assures that plastic dissipation is distributed in plastic hinge only. Some pier specimens (in scale 1:6) were built with and without the new bar systems. These specimens were tested by cyclic tests at Fuzhou University lab (China) to evaluate the effectiveness of the intervention.
Astaxanthin as a Potential Antioxidant to Improve Health and Production Performance of Broiler Chicken

Recent interest in carotenoids has increased due to their antioxidant and production performance. Astaxanthin (AST) is a xanthophyll carotenoid abundantly distributed in microalgae, which is described as a highly potent antioxidant. Therefore, recent studies have tended to investigate the role of antioxidants in improving metabolic processes and physiological functioning of the body. It is now evident that AST could significantly reduce free radicals and oxidative stress and help to maintain a healthy state. Moreover, AST also could improve the performance of broiler chicken by increasing the daily feed intake, followed by improvement in the food conversion rate.