Miracle-dz/UniFAR-FTUs huggingface dataset:
Toward Performance Portability of Highly Parametrizable TRSM Algorithm Using SYCL

Presented in 1979, BLAS is, to this day, the de-facto standard for low-level linear algebra routines. BLAS provides essential linear algebra routines used in various domains such as numerical and scientific computing, weather simulation, computational fluid dynamics, machine learning and adopted for a broad range of hardware from HPC to embedded systems and AI specialized accelerators. While originally BLAS routines have been implemented for CPU, with the emergence of GPGPU, BLAS routines had to be re-written to exploit the provided extensive computational power. Machine learning is rapidly changing this landscape again by incentivizing the development of specialized hardware that can perform certain operations more efficiently. With a wide range of hardware available, each with a new kind of memory hierarchy, different cache line sizes, and various memory access patterns required for performance, with different number of registers and different type of memory connections, performance portability of BLAS routine across various platforms while avoiding rewrites of existing code is a major challenge of the heterogeneous programming world. Written in SYCL, SYCL-BLAS is an open-source BLAS library that provides performance portability across various SYCL-enabled platforms. This paper presents the implementation of a parametric tile-based TRSM routine for SYCL-BLAS by employing a formulation that leverages a highly optimized GEMM routine already provided in SYCL-BLAS. Our results shows that we can achieve up to 2.6x speedup on Intel GPU, 7x on AMD GPU and up to 3.4x speedup on ARM GPU compared with the highly optimized clBLAST and clBLAS libraries by tuning the tile size per-device without reimplementing the kernel.
Exploring the Career Engagement, Interests, and Goals of Pharmacy Students Identifying as Underrepresented Racial Minorities

Objective. To examine pharmacy career engagement, interest, and confidence in Doctor of Pharmacy (PharmD) students identifying as underrepresented racial minorities (URMs). Methods. A 15-item survey about career engagement, confidence, and goals was administered at a business session of a national conference. The survey included demographic items and items about career exposure prior to and during school, career aspirations after graduation, frequency of engagement in various settings, career factors, and career confidence. Cronbach alpha was used to examine survey reliability. Descriptive statistics and nonparametric statistical tests were used to analyze survey responses. Results. Sixty-nine URM students completed the survey. Most indicated frequent engagement with community pharmacy prior to and during school; no engagement with hospital pharmacy prior to school, yet occasional or frequent engagement during school; and no engagement with the pharmaceutical industry prior to and during school. Most selected hospital pharmacy as their career aspiration, followed by community pharmacy and industry. Approximately half indicated an interest in completing a postgraduate fellowship. Items selected as important to career choice included patient care, job security, and level of stress. Group differences were found by gender and year in school. Conclusion. Despite calls for diversity in pharmacy, there is a paucity of research in this area. This study provides a first glimpse into the career engagement, confidence, and goals of students identifying as URMs, raising a number of critical issues for pharmacy education. Moving forward, schools, employers, and researchers must work to better understand the career development of URM students, including barriers and facilitators to access and success.
DNA identification of a sailor from the 1845 Franklin northwest passage expedition

Abstract The 1845 British polar expedition in search of a northwest passage through the Canadian Arctic under the command of Sir John Franklin resulted in the greatest loss of life event in the history of polar exploration. The names of the 129 officers and crew who sailed and died on the catastrophic voyage are known, but the identification of their skeletons found scattered along the route of their attempted escape is problematic. Here, we report DNA analyses from skeletal remains from King William Island, where the majority of the expedition fatalities occurred, and from a paternal descendant of a member of the expedition. A match was found between an archaeological sample and a presumed descendant sample using Y-chromosome haplotyping. We conclude that DNA and genealogical evidence confirm the identity of the remains as those of Warrant Officer John Gregory, Engineer, HMS Erebus. This is the first member of the 1845 Franklin expedition whose identity has been confirmed through DNA and genealogical analyses.
Special issue on adaptive and learning agents 2018

1 School of Computer Science, National University of Ireland Galway, University Road, Galway H91 TK33, Ireland e-mail: patrick.mannion@nuigalway.ie 2 DeepMind, 6 Pancras Square, London N1C 4AG, UK e-mail: harutyunyan@google.com 3 Department of Computer Science, University of Oxford, Parks Road, Oxford OX1 3QD, UK e-mail: bei.peng@cs.ox. ac.uk 4 College of Computing, Georgia Institute of Technology, 801 Atlantic Drive, Atlanta, GA 30332, USA e-mail: ksubrama@cc.gatech. edu
Imbalance deep multi‐instance learning for predicting isoform–isoform interactions

Multi‐instance learning (MIL) can model complex bags (samples) that are further made of diverse instances (subsamples). In typical MIL, the labels of bags are known while those of individual instances are unknown and to be specified. In this paper we propose an imbalanced deep multi‐instance learning approach (IDMIL‐III) and apply it to predict genome‐wide isoform–isoform interactions (IIIs). This prediction task is crucial for precisely understanding the interactome between proteoforms and to reveal their functional diversity. The current solutions typically formulate the prediction of IIIs as a MIL problem by pairing two genes as a “bag” and any two isoforms spliced from these two genes as “instances. ” The key instances (interacting isoform pairs) trigger the label of the positive (interacting) gene bags, which is important for identifying the IIIs. Furthermore, the prediction task was simplified as a balanced classification problem, which in practice is a rather imbalanced one. To address these issues, IDMIL‐III fuses RNA‐seq, nucleotide sequence, amino acid sequence and exon array data, and further introduces a novel loss function to separately model the loss of positive pairs and of negative pairs, and thus to avoid the expected loss dominated by majority negative pairs. In addition, it includes an attention strategy to identify positive isoform pairs from a positive gene bag. Extensive experimental results prove the effectiveness of IDMIL‐III on predicting IIIs. Particularly, IDMIL‐III achieves an F1 value as 95.4%, at least 3.8% higher than those of competitive methods at the gene‐level; and obtains an F1 as 29.8%, at least 2.4% higher than the state‐of‐the‐art methods at the isoform‐level. The code of IDMIL‐III is available at http://mlda.swu. edu.cn/codes.php? name=IDMIL-III.
Model‐free attitude synchronization for multiple heterogeneous quadrotors via reinforcement learning

In this paper, a model‐free optimal synchronization controller is designed to achieve the aggressive attitude synchronization for multiple heterogeneous quadrotor systems with highly nonlinear and coupled dynamics by using a reinforcement learning (RL) approach. A distributed observer is first designed for each following quadrotor to estimate the states of a virtual leader. A performance function is then utilized for each quadrotor to penalize the observed synchronization error and the control effort. An RL approach is finally employed to learn the optimal control law without any knowledge of the dynamic model information of the followers. The control law depends on the quadrotor states and the observer states, and guarantees that the attitude synchronization error converges to zero for all quadrotors, under aggressive maneuvers. Simulation results are provided to verify the effectiveness of the proposed controller.
EntraPT: An online platform for elastic geothermobarometry

Abstract EntraPT is a web-based application for elastic geobarometry freely accessible at the “Fiorenzo Mazzi” experimental mineralogy lab website (http://www.mineralogylab.com/software/). It provides an easy-to-use tool to calculate the entrapment conditions of inclusions, with error propagation, from the residual strain measured in mineral inclusions. EntraPT establishes a method and a workflow to import and analyze the measured residual strains, correctly calculates the mean stress in the inclusions, computes the entrapment isomekes with uncertainty estimation, and visualizes all the results in relevant graphs. It enables the user to avoid the many possible errors that can arise from manual handling of the data and from the numerous steps required in geobarometry calculations. All of the data, parameters, and settings are stored in a consistent format and can be exported as project files and spreadsheets, and imported back to EntraPT for further analysis. This allows researchers to store and/or share their data easily, making the checking and the comparison of data and results reliable. EntraPT is an online tool that does not require any download and/or installation, and it will be updated in the future with new functionalities made available from advances in the development of elastic geobarometry.
Enrichment of common carp (Cyprinus carpio) diet with Malic acid: Effects on skin mucosal immunity, antioxidant defecne and growth performance

Abstract The present study investigated possible effects of dietary malic acid on the expression of immunity, antioxidant and growth related genes expression as well as skin mucus immune parameters in common carp. Common carp (Cyprinus carpio) fingerlings were fed diets supplemented with different levels (0 [control], 0.5%, 1%, 2%) of malic acid (MA) for 60 days. The results revealed highest expression levels of immune-related genes (tnf-alpha, il1b, il8 and lyz) in skin of common carp fed 2% MA (P < 0.05). Regarding 1% MA treatment comparison with control group, significant difference was noticed just in case of lyz (P < 0.05). Evaluation of growth related genes expression revealed no significant difference between treatments (P > 0.05). The study of antioxidant related genes (gsta and gpx) in common carp skin fed with MA, showed significant difference between treated groups and control (P < 0.05). Carps fed with 2% MA had highest alkaline phosphatase activity in skin mucus compared other treated groups and control (P < 0.05). There were no significant difference between 0.5% and 1% and control (P > 0.05). The study of total protein and total immunoglobulin (Ig) in common carp skin musus revealed no alteration following MA treatment (P > 0.05). The present data demonstrated that feeding with MA altered immune and antioxidant genes expression in skin mucus of common carp.
Assessment of the mercury contamination of landfilled and recovered foundry waste – a case study

Abstract Environmental pollution by mercury is a local problem in Poland and concerns mainly industrial sites. Foundry waste are usually characterized by low mercury content compared to other heavy metals. Spent foundry sands with low content of Hg are the main component of foundry waste. However, Hg may be present in foundry dust, which may also be landfilled. Due to Hg toxicity, even a minimal content may have a negative impact on biota. This study focuses on assessing the mercury content of landfilled foundry waste (LFW), to assess its toxicity. Currently tested waste is recovered and reused as a road aggregate. The results were compared with the mercury content of local soils as the reference level. Waste samples were taken from foundry landfill. The mercury content, fractional composition, organic matter (OM) and total organic carbon content, pH and elementary composition of waste were analysed. It was found that the mercury content in LFW was very low, at the level of natural content in soils and did not pose a threat to the environment. The statistical analysis shows that mercury was not associated with OM of the waste, in contrast to soils, probably due to different types of OM in both materials.
Recent advances on the fabrication methods of nanocomposite yarn-based strain sensor

Abstract Yarn-based strain sensor is an emerging candidate for the fabrication of wearable electronic devices. The intrinsic properties of yarn, such as excellent lightweight, flexibility, stitchability, and especially its highly stretchable performance, stand out the yarn-based strain sensor from conventional rigid sensors in detection of human body motions. Recent advances in conductive materials and fabrication methods of yarn-based strain sensors are well reviewed and discussed in this work. Coating techniques including dip-coating, layer by layer assemble, and chemical deposition for deposition of conductive layer on elastic filament were first introduced, and fabrication technology to incorporate conductive components into elastic matrix via melt extrusion or wet spinning was reviewed afterwards. Especially, the recent advances of core–sheath/wrapping yarn strain sensor as-fabricated by traditional spinning technique were well summarized. Finally, promising perspectives and challenges together with key points in the development of yarn strain sensors were presented for future endeavor.
Differentially expressed genes in resistant and susceptible Pistacia vera L. Cultivars in response to Pseudomonas fluorescens and Phytophthora parsiana

ABSTRACT Gummosis (Phytophthora root and crown rot) is an important and destructive disease that affects fruit trees like pistachio (Pistacia vera L.). Although many studies have been performed on the possibility of biological control of gummosis, up to now few studies have been done on transcriptionally induced resistance genes in pistachio against Phytophthora disease. In the present research, the cDNA-AFLP method was used to analyze the transcriptionally regulated genes during the interaction between susceptible (Sarakhs) and resistant (Badami-Rize Zarandi) pistachio cultivars with Pseudomonas fluorescens and/or Phytophthora parsiana. Using 12 AFLP primer combinations, approximately 740 different cDNA-AFLP fragments with sizes ranged from 50 to 700 bp were generated for susceptible and resistant pistachio cultivars. Forty six TDFs (transcript derived fragments) were then selected for susceptible cultivar and 24 TDFs for resistant cultivar. Accordingly, each one of these TDFs was recognized by similarity search using the BlastX program against the NCBI GenBank nucleotide database. Notably, 18.5% of TDFs were hypothetical or uncharacterized proteins and 1.4% of them indicated no significant similarity to the known genes. Among the TDFs with known function, disease resistance proteins were identified, which were newly regulated in response to pathogen or rhizobacterium. Furthermore, we found that the expression level of different growth-regulatory or defense-related genes was higher after the exposure to Pseudomonas fluorescens and/or Phytophthora parsiana. To better understand the defense mechanism of pistachio plants and recognition of P. fluorescens-activated genes, which induce resistance against P. parsiana, would significantly assist in the development of new resistant pistachio cultivars.
Adsorption of syn−propanethial S−oxide on the Zn12O12 cluster: insights from ab-initio modelling

The sensitivity and reactivity of a Zn12O12 nanocluster are investigated to a syn−Propanethial−S−oxide (PSO) agent using B3LYP level of theory. In the gas phase, the Gibbs free energy change (ΔG) was calculated to be approximately −20.5 kcal/mol. We found that the Zn12O12 nanocluster is meaningfully sensitive to the PSO and it may be a possible sensor which can be used for the detection of PSO. At low PSO concentrations, the change of the HOMO–LUMO gap indicates a suitable index for the detection of PSO detection, while at high concentrations, the work function change indicates a much more appropriate index. A short recovery time of 0.10 s was predicted for the desorption of PSO from the surface of the Zn12O12 nanocluster using vacuum ultra-violet light at room temperature. The adsorption of PSO onto the Zn12O12 nanocluster is decreased after moving from the water to benzene solvent. GRAPHICAL ABSTRACT
The prediction of the ZnNi thickness and Ni % of ZnNi alloy electroplating using a machine learning method

ABSTRACT ZnNi alloy coating is commonly used to enhance the corrosion resistance of steel. The percentage of Ni should be maintained between 12% and 14% in the coating for best corrosion performance. The response surface design (RSD), polynomial regression (PR), support vector regression (SVR), XGBoost regression (XGB), K-nearest neighbours regression and Gaussian process regression (GP) algorithms have been used to predict the ZnNi alloy coating thickness and Ni % amount in the coating. As statistical indices mean square error (MSE) and correlation coefficient (R 2) were used to compare the models. The results of the analysis show that the XGB algorithm gives the best estimation for both ZnNi thickness and Ni%. A high correlation was observed between the predicted values and experimental results. R 2 values of 0.87 and 0.81 were acquired for ZnNi thickness and Ni %, respectively, using the XGB algorithm. This study has proved that the machine learning algorithm is a promising method to predict the ZnNi coating thickness and Ni % in the alloy based on the composition of the ZnNi electroplating bath.
Exploring the experiences of recently arrived Latin American migrant parents regarding their children’s education

ABSTRACT This study explored the experiences of recently arrived Latin American parents to the UK related to their children’s education, to highlight how these experiences can inform educational practice. A small-scale qualitative design employed semi-structured interviews to give voice to five parents who had each arrived in London after time spent living in Spain. Thematic analysis led to four key themes: ambition, sacrifice and the high value placed on education; language difficulties; feelings of powerlessness; and cultural adaptation. The implications emerging from this study centre on how educational psychologists (EPs) can act as a bridge between schools and a local migrant community by drawing on their knowledge of both second language development and the psychological experience of migration. There is also a role for EPs in advocating for the practical needs of recently arrived parents and responding to power imbalances to ensure their inclusion within the school community.
Sliding mode control of SEPIC converter based photovoltaic system

Photovoltaic (PV) energy can be considered to be as highly efficient energy source since it is ecofriendly, harmless and available endlessly. In order to improve the output power of photovoltaic cells, the maximum power point tracking technology is used in PV systems. This paper designs a sliding mode controller based on SEPIC converter to implement MPPT. The difference from other methods is that the proposed method uses the circuit output voltage U 0 in the closed-loop system, so that the controller has better control effect. The buck-boost feature of the SEPIC widens the applicable PV voltage and thus increases the adopted PV module flexibility. First, the photovoltaic array is modeled and the simulation results are analyzed in this paper. Then model and analyze the SEPIC circuit and derive a sliding mode control strategy based on this circuit. Finally, the results obtained in MATLAB/Simulink were compared with the conventional P&O algorithm and INC algorithm. The results show that the sliding mode controller proposed in this paper has faster speed and less oscillation when tracking the maximum power point (MPP).
Analytical validation of an automated assay for the measurement of adenosine deaminase (ADA) and its isoenzymes in saliva and a pilot evaluation of their changes in patients with SARS-CoV-2 infection

Abstract Objectives The aim of the present study was to validate a commercially available automated assay for the measurement of total adenosine deaminase (tADA) and its isoenzymes (ADA1 and ADA2) in saliva in a fast and accurate way, and evaluate the possible changes of these analytes in individuals with SARS-CoV-2 infection. Methods The validation, in addition to the evaluation of precision and accuracy, included the analysis of the effects of the main procedures that are currently being used for SARS-CoV-2 inactivation in saliva and a pilot study to evaluate the possible changes in salivary tADA and isoenzymes in individuals infected with SARS-CoV-2. Results The automated assay proved to be accurate and precise, with intra- and inter-assay coefficients of variation below 8.2%, linearity under dilution linear regression with R2 close to 1, and recovery percentage between 80 and 120% in all cases. This assay was affected when the sample is treated with heat or SDS for virus inactivation but tolerated Triton X-100 and NP-40. Individuals with SARS-CoV-2 infection (n=71) and who recovered from infection (n=11) had higher mean values of activity of tADA and its isoenzymes than healthy individuals (n=35). Conclusions tADA and its isoenzymes ADA1 and ADA2 can be measured accurately and precisely in saliva samples in a rapid, economical, and reproducible way and can be analyzed after chemical inactivation with Triton X-100 and NP-40. Besides, the changes observed in tADA and isoenzymes in individuals with COVID-19 open the possibility of their potential use as non-invasive biomarkers in this disease.
Adsorption of an Organic Dye with Cellulose Nanocrystals

In developing countries many industries use dyes to colour their products, such as textiles, rubber, paper, cosmetics, leather, plastics, and food industries. Such a wide range of using dyes in many industries increases the demand of dye, and currently 100,000 dyes are commercially available with a rough estimated production of 10 tones/year. Without proper treatment, dye effluent can be mixed with surface and ground water system and it may finally enter the drinking water system. Therefore, the treatment of dye effluents before discharge to the environment has become an global challenge due to the stability and adverse effects of dyes. Among the present methods, adsorption has been preferred to other conventional techniques due to the simple design and operation, low initial investment, effectiveness and insensitivity to toxic substances. The high surface area and the presence of permanent negative charge on the surface makes cellulose nanocrystal (CNC) an excellent candidate for the adsorption of basic (cationic) dyes.The objective of this project is to evaluate the adsorption properties of CNC for the removal of methylene blue from aqueous solution by changing the parameters such as adsorbent dosage, initial dye concentration, pH, temperature and salt concentration. It was found that the adsorption is independent of pH, however increase in temperature and ionic strength decreased the removal percentage slightly. The Langmuir and Freundlich isotherms were used to evaluate the feasibility of the adsorption process. The adsorption capacity of CNC was determined using the linearized form of Langmuir model. It possessed a value of 118 mg/g at pH 9 and 25 ◦C. To enhance the adsorption, CNC was oxidized with TEMPO reagent to convert primary hydroxyl groups to carboxyl groups that provides more negative charge. After the oxidation, the adsorption capacity increased from 118 to 769 mg/g.