Miracle-dz/UniFAR-FTUs huggingface dataset:
Byte-Select Compression

Cache-block compression is a highly effective technique for both reducing accesses to lower levels in the memory hierarchy (cache compression) and minimizing data transfers (link compression). While many effective cache-block compression algorithms have been proposed, the design of these algorithms is largely ad hoc and manual and relies on human recognition of patterns. In this article, we take an entirely different approach. We introduce a class of “byte-select” compression algorithms, as well as an automated methodology for generating compression algorithms in this class. We argue that, based on upper bounds within the class, the study of this class of byte-select algorithms has potential to yield algorithms with better performance than existing cache-block compression algorithms. The upper bound we establish on the compression ratio is 2X that of any existing algorithm. We then offer a generalized representation of a subset of byte-select compression algorithms and search through the resulting space guided by a set of training data traces. Using this automated process, we find efficient and effective algorithms for various hardware applications. We find that the resulting algorithms exploit novel patterns that can inform future algorithm designs. The generated byte-select algorithms are evaluated against a separate set of traces and evaluations show that Byte-Select has a 23% higher compression ratio on average. While no previous algorithm performs best for all our data sets which include CPU and GPU applications, our generated algorithms do. Using an automated hardware generator for these algorithms, we show that their decompression and compression latency is one and two cycles respectively, much lower than any existing algorithm with a competitive compression ratio.
Algorithm 1018: FaVeST—Fast Vector Spherical Harmonic Transforms

Vector spherical harmonics on the unit sphere of ℝ3 have broad applications in geophysics, quantum mechanics, and astrophysics. In the representation of a tangent vector field, one needs to evaluate the expansion and the Fourier coefficients of vector spherical harmonics. In this article, we develop fast algorithms (FaVeST) for vector spherical harmonic transforms on these evaluations. The forward FaVeST evaluates the Fourier coefficients and has a computational cost proportional to N log √N for N number of evaluation points. The adjoint FaVeST, which evaluates a linear combination of vector spherical harmonics with a degree up to ⊡M for M evaluation points, has cost proportional to M log √M. Numerical examples of simulated tangent fields illustrate the accuracy, efficiency, and stability of FaVeST.
Changes in Amino Acids, Anti-Nutrients and Functional Properties of African Yam Bean Flour Caused by Variation in Steeping Time Prior to Autoclaving

Background and Aim: Legume seeds are usually steeped in water or bicarbonate solution before further processing and this has some effect on the constituents and functional properties of the flour. The present study was to evaluate the effect of steeping time in 0.50% solution of unripe plantain peel ash prior to autoclaving on the amino acids, anti-nutrients and functional properties of African yam bean flour. Study Design: Analysis of variance (ANOVA) was carried out. Place and Duration: Department of Food Science and Technology, University of Uyo, Akwa Ibom State, Nigeria, from November 2016 to May 2017. Methodology: African yam bean seeds were sorted, washed and divided into four portions of 500g each. Portion I was not steeped and served as control sample while portions 2, 3 and 4 were Original Research Article Inyang et al.; AJB2T, 3(1): 1-10, 2018; Article no.AJB2T. 39747 2 steeped in 0.50% solution of unripe plantain peel ash (1:5w/v) at ambient temperature (27±2oC) for 24, 48 and 72h respectively. Both the unsteeped and steeped portions were separately autoclaved, dehulled, oven dried, milled and sieved to obtain the flours used for analysis. Results: The result revealed that all the parameters varied with steeping time. The total amino acids and total essential amino acids increased from 75.52g/100g and 30.07g/100g in the flour from unsteeped seeds to 80.29g/100g and 32.87g/100g respectively in the flour from the seeds that were steeped for 72h. Phytate, tannin, trypsin inhibitor, raffinose, stachyose, bulk density, water absorption capacity and swelling index decreased while oil absorption and foaming capacities increased with steeping time. Percentage reduction of phytate, tannin, trypsin inhibitor, raffinose and stachyose after 72h steeping were 80, 86, 98, 97 and 94%, respectively. Conclusion: The treatment caused significant (p<0.05) reduction in anti-nutrients and flatulence causing factors and enhanced amino acid profile of the flour.
Surface Defect Detection of Aluminum Material Based on HRNet Feature Extraction

∗ Existing algorithms for surface defect detection of aluminum materials have problems such as insufficient features, different types and sizes of surface defects on aluminum materials, and low robustness. This paper proposes a surface defect detection method for aluminum materials based on HRNet feature extraction. The method uses Faster R-CNN as the basic framework and uses HRNet as the backbone network for feature extraction. Features at different levels are exchanged in parallel subnets so that the acquired feature images are more refined through deformable convolution, the limitation of the traditional convolution receptive field is broken, and the extraction accuracy of irregular shape defects is improved. The experimental results show that compared with the detection method using ResNet as the backbone network, the method in this paper improves mAP by 2.8%, and the accuracy of defect types with various shapes such as jets is also significantly improved. The detection rate of this method meets the requirements of real-time detection and has practical feasibility of real-time inspection of the quality of aluminum materials in production.
Towards an automatic interior design system using GAN

Since its first introduction in 2014, GAN has achieved a lot of attention and success. Nevertheless, GAN has been used mostly in academia or in some toy problems. As the matter of fact, it is difficult to control GAN, hence it is not trivial to apply the outcome of GAN in the industry. However, due to the unpredictable property of GAN, we believe that GAN has a lot of potential in the fields that require creativity such as design. In this paper, we discuss the usage of GAN in the field of interior and house design. We show that GAN can be used to generate near-realistic but still creative living spaces.
Summarizing internal dynamics boosts differential analysis and functional interpretation of super enhancers

Super enhancers (SEs) are broad enhancer domains usually containing multiple constituent enhancers that hold elevated activities in gene regulation. Disruption in one or more constituent enhancers causes aberrant SE activities that lead to gene dysregulation in diseases. To quantify SE aberrations, differential analysis is performed to compare SE activities between cell conditions. The state-of-art strategy in estimating differential SEs relies on overall activities and neglect the changes in length and structure of SEs. Here, we propose a novel computational method to identify differential SEs by weighting the combinatorial effects of constituent-enhancer activities and locations (i.e., internal dynamics). In addition to overall activity changes, our method identified four novel classes of differential SEs with distinct enhancer structural alterations. We demonstrate that these structure alterations hold distinct regulatory impact, such as regulating different number of genes and modulating gene expression with different strengths, highlighting the differentiated regulatory roles of these unexplored SE features. When compared to the existing method, our method showed improved identification of differential SEs that were linked to better discernment of cell-type-specific SE activity and functional interpretation. We implement an R package, DASE, to facilitate the use of our method.
Preparation of CdS@C Photocatalyst Using Phytoaccumulation Cd Recycled From Contaminated Wastewater

Cadmium is one of the most toxic heavy metal contaminants in soils and water bodies and poses a serious threat to ecosystems and humans. However, cadmium is also an important resource widely used in many industries. The recovery of cadmium in the form of high-value products is considered as an ideal disposal strategy for Cd-contaminated environments. In this work, Pistia stratiotes was used to recycle cadmium from wastewaters through phytoaccumulation and then transformed into carbon-supported cadmium sulfide photocatalyst (CdS@C) through carbonization and hydrothermal reaction. The CdS@C photocatalyst contained a mixture of cubic and hexagonal CdS with lower band gap energy (2.14 eV) and high electron-hole separation efficiency, suggesting an excellent photoresponse ability and photocatalytic efficiency. The impressive stability and photocatalytic performance of CdS@C were demonstrated in efficient photodegradation of organic pollutants. •OH and O2•- were confirmed as the major active species for organic pollutants degradation during CdS@C photocatalysis. This work provides new insights into addressing Cd contaminated water bodies and upcycling in the form of photocatalyst.
Design Implications for Explanations: A Case Study on Supporting Reflective Assessment of Potentially Misleading Videos

Online videos have become a prevalent means for people to acquire information. Videos, however, are often polarized, misleading, or contain topics on which people have different, contradictory views. In this work, we introduce natural language explanations to stimulate more deliberate reasoning about videos and raise users’ awareness of potentially deceiving or biased information. With these explanations, we aim to support users in actively deciding and reflecting on the usefulness of the videos. We generate the explanations through an end-to-end pipeline that extracts reflection triggers so users receive additional information to the video based on its source, covered topics, communicated emotions, and sentiment. In a between-subjects user study, we examine the effect of showing the explanations for videos on three controversial topics. Besides, we assess the users’ alignment with the video’s message and how strong their belief is about the topic. Our results indicate that respondents’ alignment with the video’s message is critical to evaluate the video’s usefulness. Overall, the explanations were found to be useful and of high quality. While the explanations do not influence the perceived usefulness of the videos compared to only seeing the video, people with an extreme negative alignment with a video’s message perceived it as less useful (with or without explanations) and felt more confident in their assessment. We relate our findings to cognitive dissonance since users seem to be less receptive to explanations when the video’s message strongly challenges their beliefs. Given these findings, we provide a set of design implications for explanations grounded in theories on reducing cognitive dissonance in light of raising awareness about online deception.
A Multi-Disciplinary Review on the Aerobiology of COVID-19 in Dental Settings

The COVID-19 pandemic pushed dental health officials around the world to reassess and adjust their existing healthcare practices. As studies on controlled COVID-19 transmission remain challenging, this review focuses on particles that can carry the virus and relevant approaches to mitigate the risk of pathogen transmission in dental offices. This review gives an overview of particles generated in clinical settings and how size influences their distribution, concentration, and generation route. A wide array of pertinent particle characterization and counting methods are reviewed, along with their working range, reliability, and limitations. This is followed by a focus on the effectiveness of personal protective equipment (PPE) and face shields in protecting patients and dentists from aerosols. Direct studies on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still limited, but the literature supports the use of masks as an important and effective non-pharmaceutical preventive measure that could reduce the risk of contracting a respiratory infection by up to 20%. In addition to discussing about PPE used by most dental care professionals, this review describes other ways by which dental offices can protect patients and dental office personnel, which includes modification of the existing room design, dental equipment, and heating, ventilation, and air conditioning (HVAC) system. More affordable modifications include positioning a high-efficiency particulate air (HEPA) unit within proximity of the patient's chair or using ultraviolet germicidal irradiation in conjunction with ventilation. Additionally, portable fans could be used to direct airflow in one direction, first through the staff working areas and then through the patient treatment areas, which could decrease the number of airborne particles in dental offices. This review concludes that there is a need for greater awareness amongst dental practitioners about the relationship between particle dynamics and clinical dentistry, and additional research is needed to fill the broad gaps of knowledge in this field.
Predominance of Heart Failure With Preserved Ejection Fraction in Postmenopausal Women: Intra- and Extra-Cardiomyocyte Maladaptive Alterations Scaffolded by Estrogen Deficiency

Heart failure (HF) remains a public health concern as it is associated with high morbidity and death rates. In particular, heart failure with preserved ejection fraction (HFpEF) represents the dominant (>50%) form of HF and mostly occurring among postmenopausal women. Hence, the initiation and progression of the left ventricular diastolic dysfunctions (LVDD) (a typically clinical manifestation of HFpEF) in postmenopausal women have been attributed to estrogen deficiency and the loss of its residue cardioprotective effects. In this review, from a pathophysiological and immunological standpoint, we discuss the probable multiple pathomechanisms resulting in HFpEF, which are facilitated by estrogen deficiency. The initial discussions recap estrogen and estrogen receptors (ERs) and β-adrenergic receptors (βARs) signaling under physiological/pathological states to facilitate cardiac function/dysfunction, respectively. By reconciling these prior discussions, attempts were made to explain how the loss of estrogen facilitates the disruptions both ERs and βARs-mediated signaling responsible for; the modulation of intra-cardiomyocyte calcium homeostasis, maintenance of cardiomyocyte cytoskeletal and extracellular matrix, the adaptive regulation of coronary microvascular endothelial functions and myocardial inflammatory responses. By scaffolding the disruption of these crucial intra- and extra-cardiomyocyte physiological functions, estrogen deficiency has been demonstrated to cause LVDD and increase the incidence of HFpEF in postmenopausal women. Finally, updates on the advancements in treatment interventions for the prevention of HFpEF were highlighted.
Predicting Trustworthiness Across Cultures: An Experiment

We contribute to the ongoing debate in the psychological literature on the role of “thin slices” of observable information in predicting others' social behavior, and its generalizability to cross-cultural interactions. We experimentally assess the degree to which subjects, drawn from culturally different populations (France and Japan), are able to predict strangers' trustworthiness based on a set of visual stimuli (mugshot pictures, neutral videos, loaded videos, all recorded in an additional French sample) under varying cultural distance to the target agent in the recording. Our main finding is that cultural distance is not detrimental for predicting trustworthiness in strangers, but that it may affect the perception of different components of communication in social interactions.
Long-Term Global Solar Radiation Prediction in 25 Cities in Morocco Using the FFNN-BP Method

This article presents different combinations of input parameters based on an intelligent technique, using neural networks to predict daily global solar radiation (GSR) for twenty-five Moroccan cities. The collected measured data are available for 365 days and 25 stations around Morocco. Different input parameters are used, such as clearness index KT, day number, the length of the day, minimal temperature T min , maximal temperature T max , average temperature T average , difference temperature Δ T , ratio temperature T-Ratio, average relative humidity RH, solar radiation at the top outside atmosphere TOA, average wind speed Ws, altitude, longitude, latitude, and solar declination. A different combination was employed to predict daily GSR for the considered locations in order to find the most adequate input parameter that can be used in the prediction procedure. Several statistical metrics are applied to evaluate the performance of the obtained results, such as coefficients of determination (R 2), mean absolute percentage error (MAPE), root mean square error (RMSE), normalized root mean square error (NRMSE), mean bias error (MBE), test statistic (TS), linear regression coefficients (the slope “a” and the constant “b”), and standard deviation (σ). It is found that the usage of input parameters gives highly accurate results in the artificial neural network (FFNN-BP) model, obtaining the lowest value of the statistical metrics. The results showed the best input of 25 locations, 12 inputs for Er-Rachidia, Marrakech, Medilt, Taza, Oujda, Nador, Tetouan, Tanger, Al-Auin, Dakhla, Settat, and Safi, seven inputs for Fes, Ifrane, Beni-Mellal, and Meknes, six inputs for Agadir and Rabat, five inputs for Sidi Ifni, Essaouira, Casablanca and Kenitra, four inputs for Ouarzazate, Lareche, and Al-Hoceima. In terms of accuracy, R 2 of the selected best inputs parameters varies between 0.9860% and 0.9920%, the range value of MBE (%) being from −0.1076% to −0.5931%, the RMSE between 0.1990 and 0.4580%, the range value of the NRMSE between 0.0355 and 0.8938, and the lowest value MAPE between 0.0019 and 0.0060%. This technique could be used to predict other parameters for locations where measurement instrumentation is unavailable or costly to obtain.
Seroepidemiology of Chlamydia trachomatis Infection in the General Population of Northern China: The Jidong Community Cohort Study

A longitudinal serological study to investigate the seropositive frequency, incidence, and antibody dynamics of Chlamydia trachomatis infection in the general population of China is urgently needed in order to optimize the strategies for surveillance and precise prevention of C. trachomatis infection. This longitudinal study enrolled 744 subjects aged 18–65 years from Jidong Community of Northern China from 2014 to 2018. Seropositive frequency, incidence, and reinfection of C. trachomatis were determined by detecting antibody against C. trachomatis Pgp3 using “in-house” luciferase immunosorbent assay (LISA). The dynamic of anti-Pgp3 antibody was analyzed using the Generalized Estimating Equation (GEE) model. The overall Pgp3 seropositive frequency among the 18–65-year-old population was 28.1% (95% CI 24.9–31.5), and significantly increased from 12.0% in those aged 18–29 years to 48.6% in the 60–65 years old. The seropositive frequency was slightly higher in women than in men (31.3% vs. 25.4%) without statistical significance. The C. trachomatis incidence and reinfection rate were 11 and 14 per 1,000 person-years, respectively, and showed no significant difference with respect to age, gender, ethnicity, marital status, and education levels. Furthermore, anti-Pgp3 antibody remained detectable in 93.3% (195/209) of the seropositive subjects during the 5 years of follow-up. The overall decay rate for anti-Pgp3 antibody for CT-infected persons was −0.123 Log2 RLU/year, which was dramatically slower than in CT new infection (−3.34 Log2 RLU/year) or reinfection (−1.1 Log2 RLU/year). In conclusion, at least one quarter of the people aged 18–65 years have been infected with C. trachomatis over their lifetime while all age groups are susceptible to C. trachomatis infection in the community of Northern China. Therefore, comprehensive prevention strategies are urgently needed.
Utilization of a Wheat Sidestream for 5-Aminovalerate Production in Corynebacterium glutamicum

Production of plastics from petroleum-based raw materials extensively contributes to global pollution and CO2 emissions. Biotechnological production of functionalized monomers can reduce the environmental impact, in particular when using industrial sidestreams as feedstocks. Corynebacterium glutamicum, which is used in the million-ton-scale amino acid production, has been engineered for sustainable production of polyamide monomers. In this study, wheat sidestream concentrate (WSC) from industrial starch production was utilized for production of l-lysine–derived bifunctional monomers using metabolically engineered C. glutamicum strains. Growth of C. glutamicum on WSC was observed and could be improved by hydrolysis of WSC. By heterologous expression of the genes xylA Xc B Cg (xylA from Xanthomonas campestris) and araBAD Ec from E. coli, xylose, and arabinose in WSC hydrolysate (WSCH), in addition to glucose, could be consumed, and production of l-lysine could be increased. WSCH-based production of cadaverine and 5-aminovalerate (5AVA) was enabled. To this end, the lysine decarboxylase gene ldcC Ec from E. coli was expressed alone or for conversion to 5AVA cascaded either with putrescine transaminase and dehydrogenase genes patDA Ec from E. coli or with putrescine oxidase gene puo Rq from Rhodococcus qingshengii and patD Ec . Deletion of the l-glutamate dehydrogenase–encoding gene gdh reduced formation of l-glutamate as a side product for strains with either of the cascades. Since the former cascade (ldcC Ec -patDA Ec ) yields l-glutamate, 5AVA production is coupled to growth by flux enforcement resulting in the highest 5AVA titer obtained with WSCH-based media.
Distinct Identity of GLP-1R, GLP-2R, and GIPR Expressing Cells and Signaling Circuits Within the Gastrointestinal Tract

Enteroendocrine cells directly integrate signals of nutrient content within the gut lumen with distant hormonal responses and nutrient disposal via the production and secretion of peptides, including glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide 1 (GLP-1) and glucagon-like peptide 2 (GLP-2). Given their direct and indirect control of post-prandial nutrient uptake and demonstrated translational relevance for the treatment of type 2 diabetes, malabsorption and cardiometabolic disease, there is significant interest in the locally engaged circuits mediating these metabolic effects. Although several specific populations of cells in the intestine have been identified to express endocrine receptors, including intraepithelial lymphocytes (IELs) and αβ and γδ T-cells (Glp1r+) and smooth muscle cells (Glp2r+), the definitive cellular localization and co-expression, particularly in regards to the Gipr remain elusive. Here we review the current state of the literature and evaluate the identity of Glp1r, Glp2r, and Gipr expressing cells within preclinical and clinical models. Further elaboration of our understanding of the initiating G-protein coupled receptor (GPCR) circuits engaged locally within the intestine and how they become altered with high-fat diet feeding can offer insight into the dysregulation observed in obesity and diabetes.