Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fast Multi-Scale Generative Adversarial Network for Image Compressed Sensing

Recently, deep neural network-based image compressed sensing methods have achieved impressive success in reconstruction quality. However, these methods (1) have limitations in sampling pattern and (2) usually have the disadvantage of high computational complexity. To this end, a fast multi-scale generative adversarial network (FMSGAN) is implemented in this paper. Specifically, (1) an effective multi-scale sampling structure is proposed. It contains four different kernels with varying sizes so that decompose, and sample images effectively, which is capable of capturing different levels of spatial features at multiple scales. (2) An efficient lightweight multi-scale residual structure for deep image reconstruction is proposed to balance receptive field size and computational complexity. The key idea is to apply smaller convolution kernel sizes in the multi-scale residual structure to reduce the number of operations while maintaining the receptive field. Meanwhile, the channel attention structure is employed for enriching useful information. Moreover, perceptual loss is combined with MSE loss and adversarial loss as the optimization function to recover a finer image. Numerous experiments show that our FMSGAN achieves state-of-the-art image reconstruction quality with low computational complexity.
The Importance of Social Influencer-Generated Contents for User Cognition and Emotional Attachment: An Information Relevance Perspective

It has become a marketing trend for marketers to use influencers to advertise and sell products because influencers can affect the attitudes and decision-making of other social media users. Most previous research on influencer marketing has concentrated on its effectiveness as a promotional tool. In contrast, there have been limited studies on the influencer-social media user relationship. The relationship that influencers have with other social media users is the foundation for the success of influencer marketing. Therefore, it is critical to investigate the factors that affect the influencers’ relationships with other users. In accordance with the concept of information relevance, this study presents a model relating the various attributes of influencer-generated content with emotional attachment and information quality to examine the relationship between influencers and other social media users. The findings of a survey of 280 respondents indicate that the interestingness, novelty, reliability, and understandability of influencer-generated content can effectively increase users’ emotional attachment to influencers. Reliability and understandability can also have a significant positive impact on information quality. This eventually inclines social media users to follow or recommend influencers to others, which can increase the popularity of influencers. This study helps researchers and marketers advance their understanding of influencers’ relationships with other social media users and offers management-related recommendations for influencers and marketers.
Evolution of Cool-Roof Standards in the US

Abstract Roofs that have high solar reflectance and high thermal emittance stay cool in the sun. A roof with lower thermal emittance but exceptionally high solar reflectance can also stay cool in the sun. Substituting a cool roof for a non-cool roof decreases cooling electricity use, cooling power demand and cooling equipment capacity requirements, while slightly increasing heating energy consumption. Cool roofs can also lower the citywide ambient air temperature in summer, slowing ozone formation and increasing human comfort. Provisions for cool roofs in energy efficiency standards can promote the building and climate-appropriate use of cool roofing technologies. Cool-roof requirements are designed to reduce building energy use, while energy-neutral cool-roof credits permit the use of less energy-efficient components (e.g. larger windows) in a building that has energy-saving cool roofs. Both types of measures can reduce the life-cycle cost of a building (initial cost plus lifetime energy cost). Since 1999, several widely used building energy efficiency standards, including ASHRAE 90.1, ASHRAE 90.2, the International Energy Conservation Code and California's Title 24 have adopted cool-roof credits or requirements. This chapter reviews the technical development of cool-roof provisions in the ASHRAE 90.1, ASHRAE 90.2 and California Title 24 Standards, and discusses the treatment of cool roofs in other standards and energy efficiency programmes. The techniques used to develop the ASHRAE and Title 24 cool-roof provisions can be used as models to address cool roofs in building energy efficiency standards worldwide.
Estudo de alguns parâmetros básicos da soldagem GMAW com transferência por curto-circuito (Evaluation of Basic Parameters of Short-Circuit GMA Welding)

GMA welding is characterized by a strong dependence between its operational parameters and a high sensitivity to small variations of those. These characteristics tend to make it harder to replicate welding conditions. It is also a barrier to welding automation and makes it necessary to perform a number of real welding tests before determining operational conditions for a given application. In order to contribute to reduce these limitations of GMA welding, the authors of the present work have been working on the development of a mathematical model to simulate the variation of operational and electrical parameters during welding. This paper aims to evaluate methodologies to determine two key variables of this model (the electrode electrical resistivity and the sum of the voltage drops in the arc anode and cathode regions)in short-circuit welding. Experimental trials were performed in a mechanized jig by depositing bead-on- plate welds on low-carbon steel bars. Methodologies to evaluate those variables were developed based in proposals from the literature. Experimental details of these methodologies are analyzed and their results are compared to results from the literature. These procedures are evaluated, compared with data from the literature and new procedures are proposed to estimate those parameters and the contact resistance between the contact tip and the electrode. Results suggest values between 6 and 9 W for this last parameter.
Fabrication of CdS/C3N5 photocatalyst for enhanced H2 production

ABSTRACT In this work, we explored way to improve the photocatalytic hydrogen production activity of C3N5. A spot of CdS precursor was doped into the prepared porous C3N5 precursor, and CdS/C3N5 compounds were synthesized by hydrothermal method. Compared with C3N5, the absorption range of the CdS/C3N5 materials decreased slightly (1.765 eV), but the charge carrier mobility increased. And the electron-hole recombination rate greatly decreased via heterojunction Type-I, which resulted in the better photocatalytic performance. Experimental results show that the optimal CdS/C3N5 can produce hydrogen more than 4 times than pure C3N5, and the stability is far better than that of single photocatalytic material. GraphicalAbstract
Effects of an Amino Acid-Based Formula Supplemented with Two Human Milk Oligosaccharides on Growth, Tolerability, Safety, and Gut Microbiome in Infants with Cow’s Milk Protein Allergy

This open-label, non-randomized, multicenter trial (Registration: NCT 03661736) aimed to assess if an amino acid-based formula (AAF) supplemented with two human milk oligosaccharides (HMO) supports normal growth and is well tolerated in infants with a cow’s milk protein allergy (CMPA). Term infants aged 1–8 months with moderate-to-severe CMPA were enrolled. The study formula was an AAF supplemented with 2′-fucosyllactose (2′-FL) and lacto-N-neotetraose (LNnT). Infants were fed the study formula for 4 months and were offered to remain on the formula until 12 months of age. Tolerance and safety were assessed throughout the trial. Out of 32 infants (mean age 18.6 weeks; 20 (62.5%) male), 29 completed the trial. During the 4-month principal study period, the mean weight-for-age Z score (WAZ) increased from –0.31 at the baseline to +0.28 at the 4-months’ follow-up. Linear and head growth also progressed along the WHO child growth reference, with a similar small upward trend. The formula was well tolerated and had an excellent safety profile. When comparing the microbiome at the baseline to the subsequent visits, there was a significant on-treatment enrichment in HMO-utilizing bifidobacteria, which was associated with a significant increase in fecal short-chain fatty acids. In addition, we observed a significant reduction in the abundance of fecal Proteobacteria, suggesting that the HMO-supplemented study formula partially corrected the gut microbial dysbiosis in infants with CMPA.
Comprehensive Study of the Current-Induced Spin–Orbit Torque Perpendicular Effective Field in Asymmetric Multilayers

The spin–orbit torques (SOTs) in the heavy metal (HM)/ferromagnetic metal (FM) structure hold promise for next-generation low-power and high-density spintronic memory and logic applications. For the SOT switching of a perpendicular magnetization, an external magnetic field is inevitable for breaking the mirror symmetry, which is not practical for high-density nanoelectronics applications. In this work, we study the current-induced field-free SOT switching and SOT perpendicular effective field (Hzeff) in a variety of laterally asymmetric multilayers, where the asymmetry is introduced by growing the FM layer in a wedge shape. We show that the design of structural asymmetry by wedging the FM layer is a universal scheme for realizing field-free SOT switching. Moreover, by comparing the FM layer thickness dependence of (Hzeff) in different samples, we show that the efficiency (β = Hzeff/J, J is the current density) is sensitive to the HM/FM interface and the FM layer thickness. The sign of β for thin FM thicknesses is related to the spin Hall angle (θSH) of the HM layer attached to the FM layer. β changes its sign with the thickness of the FM layer increasing, which may be caused by the thickness dependence of the work function of FM. These results show the possibility of engineering the deterministic field-free switching by combining the symmetry breaking and the materials design of the HM/FM interface.
Comparative Studies on Antioxidant Activity of Ten Medicinal Plants Collected From the Ilam District of Nepal

Methanol extracts of ten medicinal plants collected from Ilam district were prepared and a preliminary phytochemical screening was performed. Phytochemical test revealed that selected plant samples contain alkaloids, flavonoids, terpenoids, glycosides, quinones, reducing sugars, coumarin, polyphenols, and saponins. The antioxidant properties of ten samples were evaluated by using DPPH free radical scavenging assay and their inhibitory concentration for 50% inhibition (IC50 values) for antioxidant properties were calculated. Among all ten studied samples, IC50 values of extracts of barks of Atrocarpus lakoocha (41.42±3.1 µg/mL) and flowers of Woodfordia fructicosa (41.89±2.5 µg/ mL) were very close to that of standard ascorbic acid (38.74±2.5 µg/mL). Similarly, flowers of Rhododendron arboreum (45.55±2.2 µg/mL), roots of Vetiveria zizanoids (46.22±2.0 µg/mL) and rhizomes of Mirabilis jalapa (48.99±3.0 µg/mL) also showed strong activity against DPPH free radicals. These results showed that these plants could be the potential sources of natural antioxidants in the food and/or pharmaceutical industry
A New Approach to FPGA-Implementation of DWT Applied to Real Time Denoising of Vibration Signals Related to Bearing Defects

Wavelet based denoising excels in extracting hidden diagnostic information and enhancing non-stationary signals. Implementing this technique for denoising sensed vibrations before their transmission allows reducing the size of monitoring and diagnosis applications and increasing transmission capacity, processing speed, and results accuracy. This paper presents a new approach for hardware implementation of real time Discrete Wavelet Transform for signal denoising. The first step of this approach is the choice of the wavelet bases and coefficients shrinkage settings in order to meet the requirements of vibration signal related to bearings defects in an electrical machine. Then, hardware optimization is obtained by using only two FIR filters based on a single LUT and controlled by a finite state machine. Hence, the resulting Field Programmable Gate Arrays design complexity is greatly reduced providing a huge economy of used resources while maintaining a very satisfactory execution rate.
A COMPARISON BETWEEN UWB AND LASER-BASED PEDESTRIAN TRACKING

Abstract. Despite the availability of GNSS on consumer devices enabled personal navigation for most of the World population in most of the outdoor conditions, the problem of precise pedestrian positioning is still quite challenging when indoors or, more in general, in GNSS-challenging working conditions. Furthermore, the covid-19 pandemic also raised of pedestrian tracking, in any environment, but in particular indoors, where GNSS typically does not ensure sufficient accuracy for checking people distance. Motivated by the mentioned needs, this paper investigates the potential of UWB and LiDAR for pedestrian positioning and tracking. The two methods are compared in an outdoor case study, nevertheless, both are usable indoors as well. The obtained results show that the positioning performance of the LiDAR-based approach overcomes the UWB one, when the pedestrians are not obstructed by other objects in the LiDAR view. Nevertheless, the presence of obstructions causes gaps in the LiDAR-based tracking: instead, the combination of LiDAR and UWB can be used in order to reduce outages in the LiDAR-based solution, whereas the latter, when available, usually improves the UWB-based results.
Study and Numerical Simulation of Negative and Positive Corona Discharge: A Review

Two models to describe the phenomenon of corona discharge are presented: the first is known as the plasma model which with plasma chemistry defines the volumetric and surface reactions among charge carriers such as electrons, positive, and negative ions. This model uses Poisson's equation and a formulation of the space-charge density to calculate the electric field necessary to solve the species transport equations. Besides, only the plasma model determines the density of the charge carriers. The second is a simplified model which describes the corona discharge in terms of current conservation coupled with Poisson's equation. This model does not have any connection with the attributes of plasma chemistry. Both models propose solutions for the electric potential and space charge density distribution from the corona electrode to the ground electrode.
HIV Antiretroviral Medication Neuropenetrance and Neurocognitive Outcomes in HIV+ Adults: A Review of the Literature Examining the Central Nervous System Penetration Effectiveness Score

This literature review summarizes the existing research examining the CNS penetration effectiveness (CPE) score and neurocognitive outcomes (i.e., neuropsychological assessment and neurocognitive screening) in HIV+ individuals. Despite the effectiveness of Combined Antiretroviral Therapy (CART) in reducing mortality and morbidity in HIV and controlling viral replication, HIV often persists in the Central Nervous System (CNS), and rates of neurocognitive impairment remain higher than predicted in the post-CART era. The CPE score was developed to rank antiretroviral regimens on their ability to penetrate the CNS and potency in inhibiting the virus, and it has been examined in relation to neurocognitive functioning for over a decade. Based on the results of 23 studies, we conclude that CPE is not as strongly associated with neurocognitive outcomes as initially hypothesized, although higher CPE ARV regimens may be associated with modest, improved outcomes in global neurocognitive functioning, and to a lesser extent attention/working memory and learning/memory. Conclusions, however, are limited by the heterogeneity in study design and methods, and the lack of a more recent CPE metric update. It is recommended that future research in this area employ comprehensive, standardized neuropsychological test batteries and examine domain-level performance, and use the newer 2010 CPE metric, although an updated CPE ranking is urgently needed.
Network Traffic Measurements, Applications to Internet Services and Security

The Internet has become along the years a pervasive network interconnecting billions of users and is now playing the role of collector for a multitude of tasks, ranging from professional activities to personal interactions. From a technical standpoint, novel architectures, e.g., cloud-based services and content delivery networks, innovative devices, e.g., smartphones and connected wearables, and security threats, e.g., DDoS attacks, are posing new challenges in understanding network dynamics. In such complex scenario, network measurements play a central role to guide traffic management, improve network design, and evaluate application requirements. In addition, increasing importance is devoted to the quality of experience provided to final users, which requires thorough investigations on both the transport network and the design of Internet services. In this thesis, we stress the importance of users' centrality by focusing on the traffic they exchange with the network. To do so, we design methodologies complementing passive and active measurements, as well as post-processing techniques belonging to the machine learning and statistics domains. Traffic exchanged by Internet users can be classified in three macro-groups: (i) Outbound, produced by users' devices and pushed to the network; (ii) unsolicited, part of malicious attacks threatening users' security; and (iii) inbound, directed to users' devices and retrieved from remote servers. For each of the above categories, we address specific research topics consisting in the benchmarking of personal cloud storage services, the automatic identification of Internet threats, and the assessment of quality of experience in the Web domain, respectively. Results comprise several contributions in the scope of each research topic. In short, they shed light on (i) the interplay among design choices of cloud storage services, which severely impact the performance provided to end users; (ii) the feasibility of designing a general purpose classifier to detect malicious attacks, without chasing threat specificities; and (iii) the relevance of appropriate means to evaluate the perceived quality of Web pages delivery, strengthening the need of users' feedbacks for a factual assessment.
Does Exposure to School Violence Predispose Adolescents to Engage in Sex While Under the Influence of Alcohol/Drugs?

ABSTRACT The study’s aim was to determine the association between school-based violence and being under the influence of drugs/alcohol during the last sexual intercourse among US high-school adolescents. A total of 3136 students from the 2019 Youth Risk Behavior survey were included. Multivariate logistic regression models were conducted to examine associations of exposure to school-based violence and being under the influence of drugs/alcohol during the last sexual intercourse, adjusting for demographics, early initiation of risky behaviors, mental health indicators, and good school performance. Adolescents who had been threatened/injured with a weapon on school property showed higher odds of engagement in being under the influence of drugs/alcohol during their last sexual intercourse (aOR = 1.49(1.05, 2.11)). Study findings highlight the substantial need for addressing associated factors for RSBs. Future research should explore the longitudinal association between school-based violence and risky sexual behaviors.
Effect of Operating Conditions and Fructans Size Distribution on Tight Ultrafiltration Process for Agave Fructans Fractionation: Optimization and Modeling

The objective of this work was to evaluate the effect of operating conditions and fructans size distribution on the tight Ultrafiltration process for agave fructans fractionation. A mathematical model of limiting mass flux transfer was used to represent the profile of concentrations over time at the outlet of a pilot scale ultrafiltration system. First, a Box-Behnken experimental design was performed for the optimization of the parameters that determine the operating conditions in their respective ranges: temperature, 30–60 °C; transmembrane pressure (TMP), 1–5 bar and feed concentration, 50–150 kg∙m−3, on the separation factor (SF) and permeate flux. Then, the validation of the model for different fructans size distribution was carried out. The results showed that for SF, the quadratic terms of temperature, TMP and feed concentration were the most significant factors. Statistical analysis revealed that the temperature-concentration interaction has a significant effect (p < 0.005) and that the optimal conditions were: 46.81 °C, 3.27 bar and 85.70 kg∙m−3. The optimized parameters were used to validate the hydrodynamic model; the adjustments conclude that the model, although simplified, is capable of correctly reproducing the experimental data of agave fructans fractionation by a tight ultrafiltration pilot unit. The fractionation process is favored at higher proportions of FOS:Fc in native agave fructans.
ESTIMATION OF NDVI FOR CLOUDY PIXELS USING MACHINE LEARNING

Abstract. The Normalized Difference Vegetation Index (NDVI) is a useful index for vegetation monitoring. However, due to cloud cover the observations of NDVI are discrete and vary in the intensity. Therefore, there is a need to estimate the NDVI during cloud cover using alternative sources of satellite observations. The main objective of this study is to estimate NDVI during cloudy conditions using moderate resolution multi-spectral and synthetic aperture radar (SAR) observations. Two approaches were identified: 1) pixel replacement and 2) machine learning based regression analysis to estimate cloud free NDVI. Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day NDVI composite, Sentinel-1 SAR and cloud masked Sentinel-2 multi-spectral observations were collected for entire cropping season. The satellite observations were selected only for agricultural areas by applying the agriculture, non-agriculture land use land cover mask. Machine learning algorithms such as Linear Regression (LR), Random Forest Regression (RFR), and Support Vector Regression (SVR) were used for NDVI estimation. Regression analysis was performed using Sentinel-2 NDVI as an independent variable and VV, VH, Cross Ratio (i.e., VV/VH), and MODIS NDVI as dependent variables. NDVI of the cloudy pixel was estimated using the trained regression models over the agriculture areas. A regression model was trained and applied to each Sentinel-2 tile that covers an area of 100 km × 100 km. The RFR and SVR showed the highest R2 of 0.73 and a RMSE of 0.12. A visual comparison of time series graphs showed good alignment between actual (Sentinel-2) and predicted NDVI and usual crop growth trend.