Miracle-dz/UniFAR-FTUs huggingface dataset:
VoAD: A Sub-μW Multiscene Voice Activity Detector Deploying Analog-Frontend Digital-Backend Circuits

This brief proposes a multi-scene low power voice activity detector deploying both analog and digital circuit, named VoAD. For the speech feature extractor as frontend, the analog circuit is integrated with an extra channel for noise prediction under a wide SNR range. For the voice classifier as backend, a hybrid neural network (HNN) accelerator with precision-aware approximate computing and reconfigurable work modes is proposed to achieve high accuracy and low power. The approximate computing techniques are used to accelerate the neural network layers, the batch-normalization and activation layers. Fabricated with an industrial 22-nm CMOS process, experimental results show that the HNN inspired VoAD can achieve accuracy upto 97.2%, with 508nW power consumption in clean scenes, and over 91.4% accuracy with 578nW in noisy scenes with −5dB SNR, respectively. Compared to the state-of-the-art silicon-based works, the proposed VoAD realizes sub- $\mu \text{W}$ power consumption and enhanced recognition accuracy under multi-scenes in a wide SNR range.
Utilization of Olive Pomace in Green Synthesis of Selenium Nanoparticles: Physico-Chemical Characterization, Bioaccessibility and Biocompatibility

Olive pomace extract (OPE) was investigated as a potential surface modifier for the development of the green synthesis process of selenium nanoparticles (SeNPs). In order to evaluate them as potential nutraceuticals, the obtained nanosystems were characterized in terms of size distribution, shape, zeta potential, stability in different media, gastrointestinal bioaccessibility and biocompatibility. Systems with a unimodal size distribution of spherical particles were obtained, with average diameters ranging from 53.3 nm to 181.7 nm, depending on the type of coating agent used and the presence of OPE in the reaction mixture. The nanosystems were significantly affected by the gastrointestinal conditions. Bioaccessibility ranged from 33.57% to 56.93% and it was significantly increased by functionalization of with OPE. Biocompatibility was investigated in the HepG2 and Caco2 cell models, proving that they had significantly lower toxicity in comparison to sodium selenite. Significant differences were observed in cellular responses depending on the type of cells used, indicating differences in the mechanisms of toxicity induced by SeNPs. The obtained results provide new insight into the possibilities for the utilization of valuable food-waste extracts in the sustainable development of nanonutraceuticals.
Application of Machine Learning in Hospitalized Patients with Severe COVID-19 Treated with Tocilizumab

Among the IL-6 inhibitors, tocilizumab is the most widely used therapeutic option in patients with SARS-CoV-2-associated severe respiratory failure (SRF). The aim of our study was to provide evidence on predictors of poor outcome in patients with COVID-19 treated with tocilizumab, using machine learning (ML) techniques. We conducted a retrospective study, analyzing the clinical, laboratory and sociodemographic data of patients admitted for severe COVID-19 with SRF, treated with tocilizumab. The extreme gradient boost (XGB) method had the highest balanced accuracy (93.16%). The factors associated with a worse outcome of tocilizumab use in terms of mortality were: baseline situation at the start of tocilizumab treatment requiring invasive mechanical ventilation (IMV), elevated ferritin, lactate dehydrogenase (LDH) and glutamate-pyruvate transaminase (GPT), lymphopenia, and low PaFi [ratio between arterial oxygen pressure and inspired oxygen fraction (PaO2/FiO2)] values. The factors associated with a worse outcome of tocilizumab use in terms of hospital stay were: baseline situation at the start of tocilizumab treatment requiring IMV or supplemental oxygen, elevated levels of ferritin, glutamate-oxaloacetate transaminase (GOT), GPT, C-reactive protein (CRP), LDH, lymphopenia, and low PaFi values. In our study focused on patients with severe COVID-19 treated with tocilizumab, the factors that were weighted most strongly in predicting worse clinical outcome were baseline status at the start of tocilizumab treatment requiring IMV and hyperferritinemia.
ICSpot: A High-Interaction Honeypot for Industrial Control Systems

Honeypots represent one of the most common solutions to study the adversaries’ movements and develop ad-hoc protection strategies. An effective honeypot can mimic a real system behavior and can be used to deceive the attacker and collect data related to his actions. However, current honeypots for Industrial Control Systems (ICSs) still lack realistic physical process simulation of the industrial network. Simulating an industrial process accurately while also enabling interaction with it is a complicated task. In this paper, we present ICSpot, the first ICS honeypot that addresses the current state-of-the-art limitations by integrating a physical process interaction. We developed our honeypot by leveraging different ad-hoc ICS tools resulting in a more completed and realistic solution. Then, we installed our honeypot on a local Internet Exchange Point and an AWS server, and we collected the interaction for 30 days. Finally, we report the finding related to the interaction collection and compare the results on the two installation points. Our results show that the physical process port we implemented is highly attractive to attackers.
RELIGIOSITY, BIOLOGICAL MARKERS AND HEALTH-RELATED QUALITY OF LIFE IN PATIENTS WITH HYPERTENSION

Motivation/Background: the adoption of a healthy lifestyle has a positive influence on the control of hypertension. Objective: The objective of this study was to analyze the effect of Spirituality and Health Workshops on biological markers and Health-Related Quality of Life of hypertensive patients. Method: This is a randomized controlled trial study in which an educational intervention was carried out and the religiosity and Quality of Life indices as well as the blood pressure and, Cortisol, C-Reactive Protein (CRP) and cholesterol were evaluated. Results: The intervention group experienced a lower diastolic pressure (p <0.05). There were no differences between intervention and control groups on systolic blood pressure, quality of life, somatic manifestations, mental state, CRP, and cholesterol levels. Conclusions: It was concluded that the intervention positively influenced the results, at least in one of the biological markers and the quality of life of this group.
Selenium-Enriched Spirulina (SeE-SP) Enhance Antioxidant Response, Immunity, and Disease Resistance in Juvenile Asian Seabass, Lates calcarifer

The present study examined the efficacy of dietary selenium-enriched spirulina (SeE-SP) on growth performance, antioxidant response, liver and intestinal health, immunity and disease resistance of Asian seabass, Lates calcarifer. A total of 480 seabass juveniles with an initial weight of 9.22 ± 0.09 g/fish were randomly assigned to four dietary groups. The fish were fed a fishmeal protein replacement diets with SeE-SP at 5%, 10%, and 20%, namely SeE-SP5, SeE-SP10, and SeE-SP20, and a fishmeal-based diet as control for 8 weeks. The results indicated that seabass juveniles fed SeE-SP5 and SeE-SP10 diets grew at the same rate as the fish fed a fishmeal-based control diet after 8 weeks of feeding, while SeE-SP20 grew at a significantly lower rate than the control (p < 0.05). Although most of the measured biochemical parameters were not influenced by the Se-SP diets, serum antioxidant-enzyme glutathione peroxidase (GPx) and immunological indices, such as lysozyme activity and immunoglobulin-M, were found significantly higher in the SeE-SP5 and SeE-SP10 diets compared to control. In addition, the fish fed the SeE-SP5 diet showed significantly lower mortalities after the 14-day of bacterial challenge with V. harveyi. These outcomes indicated that up to 10% inclusion of SeE-SP in the diet of juvenile Asian seabass does not compromise growth, while SeE-SP5 enhanced disease resistance in juvenile seabass.
Sustainable Synthesis and Characterization of Zinc Oxide Nanoparticles Using Raphanus sativus Extract and Its Biomedical Applications

Zinc Oxide Nanoparticles (ZnONPs) are one of the most widely used metal oxide nanoparticles in biological applications because of their outstanding biocompatibility, affordability, and low toxicity. In biomedicine, ZnONPs have shown promise, particularly in the disciplines of anticancer and antibacterial fields. In comparison to other standard synthesis methods, the environmentally-friendly synthesis of metallic nanoparticles utilizing various plant extracts is a good option. The current research focuses on the synthesis of zinc oxide nanoparticles (ZnONPs) from R. sativus leaf extract under various physical conditions (Precipitation method). Analytical methods were used to confirm and characterize the produced ZnONPs. The spherical nature of the produced nanoparticles was established by SEM analysis. The generation of very pure ZnONPs was confirmed by EDS data. The crystalline nature of the produced nanoparticles, with a particle size of 66.47 nm, was confirmed by XRD. The XRD graphs’ presence of the (100), (002), and (101) planes strongly suggest the production of wurtzite ZnO. The visual and infrared area exhibits transmissions of 84 percent in the pH 10 nanoparticles. The band gap of the nanoparticles increases from 3.34 to 3.38 eV when the pH increases. These nanoparticles were effective against both Gram-positive and Gram-negative bacteria. The effect of several process parameters such as pH and temperature were investigated, and the best conditions were discovered to be pH 12 and 80 °C, respectively. The effect of ZnONPs was tested with human breast cancer cells (MCF-7), and they showed significant cytotoxic results. Collectively, our data suggest that ZnONPs of R. sativus leaf extract inhibit breast cancer cell lines. The ZnONPs are, therefore, a prospective source of chemopreventive drugs that merit additional exploration in order to uncover lead compounds with cancer chemotherapeutic potential.
Multi-Object Detection in Traffic Scenes Based on Improved SSD

In order to solve the problem that, in complex and wide traffic scenes, the accuracy and speed of multi-object detection can hardly be balanced by the existing object detection algorithms that are based on deep learning and big data, we improve the object detection framework SSD (Single Shot Multi-box Detector) and propose a new detection framework AP-SSD (Adaptive Perceive). We design a feature extraction convolution kernel library composed of multi-shape Gabor and color Gabor and then we train and screen the optimal feature extraction convolution kernel to replace the low-level convolution kernel of the original network to improve the detection accuracy. After that, we combine the single image detection framework with convolution long-term and short-term memory networks and by using the Bottle Neck-LSTM memory layer to refine and propagate the feature mapping between frames, we realize the temporal association of network frame-level information, reduce the calculation cost, succeed in tracking and identifying the targets affected by strong interference in video and reduce the missed alarm rate and false alarm rate by adding an adaptive threshold strategy. Moreover, we design a dynamic region amplification network framework to improve the detection and recognition accuracy of low-resolution small objects. Therefore, experiments on the improved AP-SSD show that this new algorithm can achieve better detection results when small objects, multiple objects, cluttered background and large-area occlusion are involved, thus ensuring this algorithm a good engineering application prospect.
The Influence of the Stratospheric Quasi‐Biennial Oscillation on the Tropical Easterly Jet Over the Maritime Continent

This study investigated the influence of the stratospheric quasi‐biennial oscillation (QBO) on the tropical easterly jet (TEJ), using the ERA5 and QBO series of Singapore and Freie Universität Berlin. Since the 1980s, the easterlies of the TEJ over the Maritime Continent are weaker during easterly QBO (EQBO) than westerly QBO. QBO influences TEJ by affecting convection on the east and west sides of the Maritime Continent. The climatological rising movement on the west side of the Maritime Continent can reach a higher altitude than that on the east side, which implies the convections on the west side are likely to be more effectively promoted by the reduced stability near the tropopause during EQBO. The zonal asymmetry in the stability near the tropopause is also a possible cause for QBO modulating convection. QBO has a significant influence on the Asian summer monsoon and tropical/subtropical precipitation through modulating the TEJ.
Therapeutic Potential of the Combination of Pentoxifylline and Vitamin-E in Inflammatory Bowel Disease: Inhibition of Intestinal Fibrosis

Background: Although intestinal fibrosis is a consequence of recurrent inflammation in Inflammatory bowel disease (IBD), alleviating inflammation alone does not prevent the progression of fibrosis, suggesting that the development of direct anti-fibrotic agents is necessary. This study aimed to evaluate the anti-fibrotic properties of combination treatment with pentoxifylline (PTX) and vitamin E (Vit-E) on human primary intestinal myofibroblasts (HIMFs) and the therapeutic potential of the combination therapy in murine models of IBD. Methods: HIMFs were pretreated with PTX, Vit-E, or both, and incubated with TGF-β1. We performed Western blot, qPCR, collagen staining, and immunofluorescence to estimate the anti-fibrotic effects of PTX and Vit-E. The cytotoxicity of these was investigated through MTT assay. To induce murine models of IBD for in vivo study, C57BL/6 mice were treated with repeated cycles of dextran sulfate sodium (DSS), developing chronic colitis. We examined whether the combined PTX and Vit-E treatment would effectively ameliorate colonic fibrosis in vivo. Results: We found that the co-treatment with PTX and Vit-E suppressed TGF-β1-induced expression of fibrogenic markers, with decreased expression of pERK, pSmad2, and pJNK, more than either treatment alone in HIMFs. Neither PTX nor Vit-E showed any significant cytotoxicity in given concentrations. Consistently with the in vitro results, the co-administration with PTX and Vit-E effectively attenuated colonic fibrosis with recovery from thickening and shortening of colon in murine models of IBD. Conclusions: These findings demonstrated that the combination of PTX and Vit-E exhibits significant anti-fibrotic effects in both HIMFs and in vivo IBD models, providing a promising therapy for IBD.
On-policy learning-based deep reinforcement learning assessment for building control efficiency and stability

Deep reinforcement learning (DRL) has been considered as a potential solution to efficiently control and manage building systems. However, broad assessment of DRL-based building control is still required to characterize their pros and cons in comparison with conventional rule-based feedback controls. In this paper, we assessed DRL-based controls with on-policy learning-based algorithms and continuous control actions for cooling control of large office buildings in the summer season to minimize whole-building energy use and occupant discomfort. We compared DRL-based control methods with two baseline control methods: (1) a pre-determined schedule with supply temperature and static pressure setpoints, and (2) advanced reset method that adjusts setpoints based on heuristic rules, i.e., ASHRAE Guideline 36. We also tested the DRL algorithms to evaluate their performances in multiple climate locations. We found that DRL-based control methods outperformed the baseline control methods in terms of energy savings while maintaining a thermal comfort. DRL reduced energy use between ∼4%–22% on average compared to the baseline methods, depending on climate location. We also evaluated DRL-based control in terms of control stability and showed that DRL-based methods should consider hardware lifetimes in practical operations.
Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias

Plankton metabarcoding is increasingly implemented in marine ecosystem assessments and is more cost-efficient and less time-consuming than monitoring based on microscopy (morphological). 18S rRNA gene is the most widely used marker for groups’ and species’ detection and classification within marine eukaryotic microorganisms. These datasets have commonly relied on the acquisition of organismal abundances directly from the number of DNA sequences (i.e. reads). Besides the inherent technical biases in metabarcoding, the largely varying 18S rRNA gene copy numbers (GCN) among marine protists (ranging from tens to thousands) is one of the most important biological biases for species quantification. In this work, we present a gene copy number correction factor (CF) for four marine planktonic groups: Bacillariophyta, Dinoflagellata, Ciliophora miscellaneous and flagellated cells. On the basis of the theoretical assumption that ‘1 read’ is equivalent to ‘1 GCN’, we used the GCN median values per plankton group to calculate the corrected cell number and biomass relative abundances. The species-specific absolute GCN per cell were obtained from various studies published in the literature. We contributed to the development of a species-specific 18S rRNA GCN database proposed by previous authors. To assess the efficiency of the correction factor we compared the metabarcoding, morphological and corrected relative abundances (in cell number and biomass) of 15 surface water samples collected in the Belgian Coastal Zone. Results showed that the application of the correction factor over metabarcoding results enables us to significantly improve the estimates of cell abundances for Dinoflagellata, Ciliophora and flagellated cells, but not for Bacillariophyta. This is likely to due to large biovolume plasticity in diatoms not corresponding to genome size and gene copy numbers. C-biomass relative abundance estimations directly from amplicon reads were only improved for Dinoflagellata and Ciliophora. The method is still facing biases related to the low number of species GCN assessed. Nevertheless, the increase of species in the GCN database may lead to the refinement of the proposed correction factor.
Effect of Bayah natural zeolite for purification of waste cooking oil as feedstock of alkyd resin

The waste of cooking oil was increased due to the cooking oil consumption increases. Waste cooking oil can reuse for raw material after the adsorption process with Bayah's natural zeolite, such as feedstock of alkyd resins. This paper studied the effect of the mass of Bayah natural zeolite (w/w %) on the characteristics of waste cooking oil. The Bayah natural Zeolite as adsorbent to reduce the value of free fatty acids and peroxide numbers The first stage is the preparation of waste cooking oil and Bayah natural zeolite, and then activation of Bayah natural zeolite, and the adsorption process of waste cooking oil with 15 and 30% w/w of zeolite. The results show the characteristics of waste cooking oil which before being adsorbed had an acid The can react with alkaline bases. The concentration of ethanol is 95-96%. The method of determining free fatty acids using direct acid-base titration with phenolphthalein (PP) indicator. The reaction was showed as follow.
Plasma Levels of Proprotein Convertase Subtilisin/Kexin Type 9 Are Inversely Associated with N-Terminal Pro B-Type Natriuretic Peptide in Older Men and Women

Background and Aims: Cardiac natriuretic peptides (NPs) exert several metabolic effects, including some on lipid metabolism. Higher NPs levels are likely to be associated with a favorable lipid profile. In in vitro studies, NPs have been found to modulate low-density lipoprotein receptor (LDLR) trafficking by preventing proprotein convertase subtilisin/kexin type 9 (PCSK9) overexpression. The aim of our study is to investigate a possible association between plasma levels of PCSK9 and N-terminal pro B-type natriuretic peptide (NT-proBNP) in vivo. Methods: We performed a cross-sectional study on 160 consecutive older male and female patients hospitalized for medical conditions. Patients taking lipid-lowering drugs and patients with an admission diagnosis of acute heart failure were excluded. Fasting blood samples were collected after clinical stabilization of the acute illness, the day before discharge. Results: The mean age was 87.8 ± 6.4 years with a female prevalence (62.5%). The median NT-proBNP was 2340 (814–5397) pg/mL. The mean plasma PCSK9 was 275.2 ± 113.2 ng/mL. We found an inverse correlation between plasma PCSK9 and NT-proBNP (r = −0.280; p = 0.001). This association was confirmed after taking into account NT-proBNP tertiles (plasma PCSK9 levels: 317.4 ± 123.6 ng/mL in the first tertile, 283.3 ± 101.8 ng/mL in the second tertile, 231.3 ± 99.0 ng/mL in the third tertile, p = 0.001) and even after an adjustment for confounding factors (beta = −0.361, p = 0.001 for ln(NT-proBNP); beta = −0.330, p = 0.001 for NT-proBNP tertiles). The strength of the correlation between plasma PCSK9 and NT-proBNP was likely greater in patients affected by type 2 diabetes mellitus (r = −0.483; p = 0.006) and in male patients (r = −0.431, p = 0.001). Conclusion: The inverse association found between PCSK9 and NT-proBNP plasma levels in our real-life clinical study supports the hypothesis that NPs may play a role in cholesterol metabolism, possibly through an inhibitory action on circulating PCSK9 concentrations, thus increasing the availability of LDLR.
A homological criterion for the failure of containment of the symbolic cube in the square of some ideals of points in $\mathbb{P}^2$

We establish a criterion for the failure of the containment $I^{(3)}\subset I^2$ for 3-generated ideals $I$ defining reduced sets of points in $\mathbb{P}^2$. Our criterion arises from studying the minimal free resolutions of the powers of $I$, specifically the minimal free resolutions for $I^2$ and $I^3$. We apply this criterion to two point configurations that have recently arisen as counterexamples to a question of B. Harbourne and C. Huneke: the Fermat configuration and the Klein configuration.
Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task

From smoothly pursuing moving objects to rapidly shifting gazes during visual search, humans employ a wide variety of eye movement strategies in different contexts. While eye movements provide a rich window into mental processes, building generative models of eye movements is notoriously difficult, and to date the computational objectives guiding eye movements remain largely a mystery. In this work, we tackled these problems in the context of a canonical spatial planning task, maze-solving. We collected eye movement data from human subjects and built deep generative models of eye movements using a novel differentiable architecture for gaze fixations and gaze shifts. We found that human eye movements are best predicted by a model that is optimized not to perform the task as efficiently as possible but instead to run an internal simulation of an object traversing the maze. This not only provides a generative model of eye movements in this task but also suggests a computational theory for how humans solve the task, namely that humans use mental simulation.