Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogenetic Tree and Sequence Similarity of β-Lactamases

Abstract β-Lactamases are the main cause of β-lactam resistance in many pathogenic bacteria. These enzymes can be detected in a variety of pathogenic as well as non-pathogenic bacteria. The cyanobacteria are also known to produce a β-lactamase. Recently, the amino acid sequences and the three-dimensional structures of some of these β-lactamases have been clarified. On the basis of the amino acid sequences of 47 β-lactamases and the computer-aided analysis, a phylogenetic tree is proposed in this paper. According to the tree, β-lactamases are classified into six groups. Group 1 β-lactamases are mainly composed of plasmid-mediated enzymes from gram-negative bacteria. However, chromosome-derived β-lactamases from Klebsiella pneumoniae and Rhodopseudomonas capsulata take part in this group. Group 2 enzymes consist of a part of the chromosome-encoded β-lactamases from Streptomyces, and chromosome-mediated enzymes from Yersinia enterocolitica, Citrobacter diversus, and Klebsiella oxytoca. Chromosome-encoded β-lactamases from gram-negative bacteria form group 3. Group 4 is composed of metalloenzymes, whereas group 5 consists of OXA type β-lactamases. Chromosome-encoded β-lactamases from gram-positive bacteria form group 6. Comparison of the amino acid sequences among these groups confirmed the phylogenetic tree and the classification: the β-lactamases in each group have its particular conserved amino acid sequences. In addition, the tree provides more detailed classification and time-scale mutual relationships and predicts new types of β-lactamases that may be found. Furthermore, the classification deduced from the tree is generally in accord with the one based on the amino acid sequences reported previously. However, the class A β-lactamases are clearly divided into three groups: groups 1, 2, and 6. RDF2 analysis shows that some combinations between β-lactamases and β-lactam-interacting proteins as well as eukaryotic proteins have a low but significant evolutionary relatedness.
Response of growing Japanese quails to dietary concentration of L‐threonine

The influence of dietary levels of L-threonine (Thr) on growth and immune response was investigated in growing (0–5 weeks of age) Japanese quails (n = 288). Three dietary treatments were formulated using three levels of Thr [9.6, 10.2 and 11.2 kg−1 diet dry matter (DM)] at a fixed protein level of 233 g kg−1 and an energy level of 12.15 MJ (2900 kcal) metabolizable energy (ME) kg−1 feed dry matter. A metabolism trial with a 3-day collection period was conducted at the third week of age employing all the birds. The cell-mediated (using PHA-P) and humoral (SRBC response) immune responses were measured at the fourth week of age. Carcass traits were assessed at the end of fifth week of age. Body weight gain was lower (P 0.05) with Thr level. Carcass traits, relative weight of immune organs and cell-mediated (PHA-P) and humoral (SRBC response) immune responses did not differ significantly (P > 0.05) as a result of the dietary treatments. Copyright © 2006 Society of Chemical Industry
Influence of pine (Pinus sylvestris L.) growth rings width on the strength properties of structural sawn timber

Annual growth ring width was considered relative to the mechanical properties of timber from the Silesian Forestry Region in Poland. The timber was acquired from raw wood aged approximately 120 years old, with log quality A, B, and C. The study was conducted on 210 pieces of timber; 70 of them were from each part of the log: butt, middle, and top. The tested parameters, modulus of elasticity (MOE) and modulus of rupture (MOR), were measured on fully dimensional timber (40 × 138 × 3500 mm3) that had been dried and planed in industrial conditions. The density of wood (stereometric method) and annual rings width were calculated after MOR and MOE determination on samples including the entire cross-section cut near the failure zone. The tests revealed that the correlation between the width of growth rings and MOE or MOR depended on the log area: it was the highest for timber from butt logs and the lowest for timber from top logs. Moreover, the correlation between growth ring width and MOE or MOR depended also on the quality class of the logs from which the samples were obtained: it was the highest for timber from class A, and the lowest for class C.
Total lipid content and fatty acid composition of oilseed from lesser known sweet pomegranate clones

The oil content and fatty acid composition of the oilseed of seven lesser known Spanish sweet pomegranate (Punica granatum L) clones were determined by gas chromatography. The seeds contained oil in the range of about 63–122 g kg−1 dry matter, a notably lower content than that of some oriental pomegranate cultivars. Levels of lipid content probably could be considered insufficient for economic industrial exploitation compared with those of conventional oilseeds. The predominant fatty acid was the polyunsaturate (n − 3) linolenic acid (43.4–88.2%), followed by the diunsaturate linoleic (5.3–16.5%), the monounsaturate oleic (3.7–20.3%) and palmitoleic (traces to 2.9%) acids. To a lesser extent the saturates palmitic (2.6–14.9%) and stearic (1.2–9.0%) acids were also found in all clones. Lauric and arachidic acids were rarely detected. We have not confirmed the presence of behenic (C22:0) and lignoceric (C24:0) acids previously reported in edible and non-edible pomegranate cultivars. Intervarietal differences in fatty acid composition were shown and they could be useful to establish chemotaxonomic differences. In contrast with previous reports on sweet pomegranate cultivars, a very low (0.04–0.35) saturated/unsaturated fatty acid ratio was found. © 2000 Society of Chemical Industry
A rationale for dinosaurian taxonomy

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Knowledge, attitude, and practice regarding COVID-19 outbreak in Bangladeshi people: An online-based cross-sectional study

Objectives: In Bangladesh, remarkable measures have been adopted to control the rapid spread of the ongoing COVID-19 epidemic. Adherence to control measures in general populations significantly influences on their perception, knowledge, attitudes, and practices (KAP) towards COVID-19. This study aimed to investigate KAP towards COVID-19 immediately after the locked down and during the rapid rise period of the outbreak. Study design: Cross-sectional study. Methods: This online-based cross-sectional study was conducted from March 29 to April 19, 2020, involving 2017 Bangladeshi residents aged (12-64) years. The sample was successfully recruited via the social media. After consenting, participants completed an online survey assessing socio-demographic variables, perception, and KAP towards COVD-19. Results: Of the 2017 survey participants, 59.8% and 40.2% were male and female, respectively. A majority of the participants were students (71.2%), aged 21-30 years (57.9%), having a bachelor's degree (61.0%), having family income >30000 in BDT (50.0%), and living urban area (69.8). The findings revealed that 48.3% of participants had more accurate knowledge, 62.3% had more positive attitudes, and 55.1% had more frequent practices for COVID-19 prevention. Majority (96.7%) of the participants agreed COVID-19 is a dangerous disease and almost all (98.7%) of the participants wore a face mask in the crowded place, (98.8%) agreed to report a suspected case to health authorities, and (93.8%) good practicing of washing hands with soap and water. In multiple logistic regression analyses, the COVID-19 more accurate knowledge was associated with age, and residence. Whereas, the results reported that sociodemographic factors such as being older, having higher education, being unemployment, having a joint family, having monthly family income >30,000 BDT, and having more frequent prevention practices were the more positive attitudes factors; and the more frequent prevention practices factors were associated to being female, being older, having higher education, having monthly family income more than 30,000 BDT, urban area and having more positive attitudes. Conclusion: To improve the knowledge, attitudes, and practices of general populations are crucial during the rapid rise period of the COVID-19 outbreak. Therefore, an effective health education program must be initiated.
Geographic distribution and spatial differentiation in the color pattern of abdominal stripes of the Neotropical stingless bee Melipona quadrifasciata (Hymenoptera: Apidae)

Melipona quadrifasciata Lepeletier, 1836, regionally known as "mandacaia", has been traditionally divided in two distinct subspecies: M. quadrifasciata anthidioides and M. quadrifasciata quadrifasciata. The main difference between the subspecies refers to the yellow metasomal stripes which are continuous in M. q. quadrifasciata and discontinuous in M. q. anthidioides. This study investigated the geographic differentiation in the metasomal stripes and characterized the restriction sites in the mtDNA of both chromatic types. Specimens from 198 localities were examined, and the variation observed in the pattern of stripes was grouped into distinct classes. The distribution pattern found in the present work agrees with the previously reported pattern: M. q. quadrifasciata inhabits the southern portion of the distribution, from Misiones, Argentina, southeastern Paraguay and Rio Grande do Sul to southern Sao Paulo, and M. q. anthidioides ranges from northeastern Sao Paulo to the northern Diamantina Plateau, Bahia, and westwards to the central portion of the Goias state. It is documented for the first time the occurrence of two populations with continuous stripes inhabiting disjunct areas in relation to M. q. quadrifasciata - one in northern Minas Gerais and another in northeastern Bahia and Sergipe. The data of RFLP showed two restriction patterns, one present in M. q. quadrifasciata, and another in M. q. anthidioides and in populations with continuous metasomal stripes from northern Minas Gerais and northeastern Bahia and Sergipe. The observed patterns of geographic differentiation of M. quadrifasciata suggests the occurrence of repeated events of geographical isolation, followed by range expansion, that occurred probably during the cycles of climatic changes in the Pleistocene.
Unconventional Majorana fermions on the surface of topological superconductors protected by rotational symmetry

Topological superconductors are exotic gapped phases of matter hosting Majorana mid-gap states on their boundary. In conventional topological superconductors, Majorana in-gap states appear in the form of either localized zero-dimensional modes or propagating spin-1/2 fermions with a quasi-relativistic dispersion relation. Here we show that unconventional propagating Majorana states can emerge on the surface of three-dimensional topological superconductors protected by rotational symmetry. The unconventional Majorana surface states fall into three different categories: a spin-$S$ Majorana fermion with $(2S+1)$-fold degeneracy $(S\geq3/2)$, a Majorana Fermi line carrying two distinct topological charges, and a quartet of spin-1/2 Majorana fermions related by fourfold rotational symmetry. The spectral properties of the first two kinds, which go beyond the conventional spin-1/2 fermions, are unique to topological superconductors and have no counterpart in topological insulators. We show that the unconventional Majorana surface states can be obtained in the superconducting phase of doped $Z_2$ topological insulators or Dirac semimetals with rotational symmetry.
Análise de crescimento em plantas de soja tratadas com substâncias reguladoras

Growth analysis of soybean plants treated with plant growth regulators. This work aimed to verify the effect of plant growth regulators on soybean plant growth and chlorophyll content. In an experiment carried out in a greenhouse, soybean plants were cultivated (Glycine max (L.) Merrill cv. BRS-184) in 10-liter pots containing soil from the arable layer, corrected and fertilized according to the soil analysis. The treatments used were: control; GA3 100mg.L-1; BAP 100mg.L-1; IBA 100mg.L-1; Stimulate® (IBA, GA3 and kinetin) 20mL.L-1; mepiquat chloride 100mg.L-1 and mepiquat chloride 100mg.L-1 + BAP 100mg.L-1 + IBA 100mg.L-1. Treatments were applied three times at 30-day intervals. Six samplings were taken at 13-day intervals. The results indicated that the highest total dry weight value resulted from the application of IBA and Stimulate®, and that the application of mepiquat chloride in association with IBA and BAP reduced total dry matter production. The leaf area was smaller than the control in most treatments. The chlorophyll content and growth rate were slightly infl uenced by the treatments. The cytokinin treatment alone or in association with other plant growth regulators retained the chlorophyll content. RGR and NAR decreased from 99 days after sowing with the application of mepiquat chloride.
Scaling equations for mode-coupling theories with multiple decay channels

Multiple relaxation channels often arise in the dynamics of liquids where the momentum current associated to the particle-conservation law splits into distinct contributions. Examples are strongly confined liquids for which the currents in lateral and longitudinal direction to the walls are very different, or fluids of nonspherical particles with distinct relaxation patterns for translational and rotational degrees of freedom. Here, we perform an asymptotic analysis of the slow structural relaxation close to kinetic arrest as described by mode-coupling theory (MCT) with several relaxation channels. Compared to standard MCT, the presence of multiple relaxation channels significantly changes the structure of the underlying equations of motion and leads to additional, non-trivial terms in the asymptotic solution. We show that the solution can be rescaled, and thus prove that the well-known β-scaling equation of MCT remains valid even in the presence of multiple relaxation channels. The asymptotic treatment is validated using a novel schematic model. We demonstrate that the numerical solution of this schematic model can indeed be described by the derived asymptotic scaling laws close to kinetic arrest. Additionally, clear traces of the existence of two distinct decay channels are found in the low-frequency susceptibility spectrum, suggesting that clear footprints of the additional relaxation channels can in principle be detected in simulations or experiments of confined or molecular liquids.
STOLARSKY'S INVARIANCE PRINCIPLE FOR FINITE METRIC SPACES

Stolarsky's invariance principle quantifies the deviation of a subset of a metric space from the uniform distribution. Classically derived for spherical sets, it has been recently studied in a number of other situations, revealing a general structure behind various forms of the main identity. In this work we consider the case of finite metric spaces, relating the quadratic discrepancy of a subset to a certain function of the distribution of distances in it. Our main results are related to a concrete form of the invariance principle for the Hamming space. We derive several equivalent versions of the expression for the discrepancy of a code, including expansions of the discrepancy and associated kernels in the Krawtchouk basis. Codes that have the smallest possible quadratic discrepancy among all subsets of the same cardinality can be naturally viewed as energy‐minimizing subsets in the space. Using linear programming, we find several bounds on the minimal discrepancy and give examples of minimizing configurations. In particular, we show that all binary perfect codes have the smallest possible discrepancy.
Probability of consensus in the multivariate Deffuant model on finite connected graphs

The Deffuant model is a spatial stochastic model for the dynamics of opinions in which individuals are located on a connected graph representing a social network and characterized by a number in the unit interval representing their opinion. The system evolves according to the following averaging procedure: pairs of neighbors interact independently at rate one if and only if the distance between their opinions does not exceed a certain confidence threshold, with each interaction resulting in the neighbors' opinions getting closer to each other. All the mathematical results collected so far about this model assume that the individuals are located on the integers. In contrast, we study the more realistic case where the social network can be any finite connected graph. In addition, we extend the opinion space to any bounded convex subset of a normed vector space where the norm is used to measure the level of disagreement or distance between the opinions. Our main result gives a lower bound for the probability of consensus. Interestingly, our proof leads to a universal lower bound that depends on the confidence threshold, the opinion space~(convex subset and norm) and the initial distribution, but not on the size or the topology of the social network.
Survey of Transient Execution Attacks

Transient execution attacks, also called speculative execution attacks, have drawn much interest as they exploit the transient execution of instructions, e.g., during branch prediction, to leak data. Transient execution is fundamental to modern computer architectures, yet poses a security risk as has been demonstrated. Since the first disclosure of Spectre and Meltdown attacks in January 2018, a number of new attack types or variants of the attacks have been presented. These attacks have motivated computer architects to rethink the design of processors and propose hardware defenses. This paper summarizes the components and the phases of the transient execution attacks. Each of the components is further discussed and categorized. A set of metrics is proposed for each component to evaluate the feasibility of an attack. Moreover, the data that can be leaked in the attacks are summarized. Further, the existing attacks are compared, and the limitations of these attacks are discussed based on the proposed metrics. In the end, existing mitigations at the micro-architecture level from literature are discussed.
Reconstructing the lengths of juvenile Atlantic salmon from atlas bones: estimating the parr to smolt ratio from regression analyses revisited

Analyses of regressions of atlas bone width against fish length (mixed regressions) of Atlantic salmon Salmo salar can be used to infer the parr:smolt ratio of the source populations. Analyses of mixed regressions have been used to infer that, contrary to previous reports, sawbill ducks Mergus spp. eat only a few smolts. Here a Monte Carlo simulation model is presented which quantifies the effect of variation in the smolt:parr ratio on the form of the mixed regression. Based on published mixed regressions, the model predicts 95% CI of 1-36% and 1-42% smolts in diets of sawbill ducks, which are broadly consistent with results of earlier studies. However, other large inconsistencies still exist between results of previous studies and these are briefly discussed.
Syntactic Structure Distillation Pretraining for Bidirectional Encoders

Abstract Textual representation learners trained on large amounts of data have achieved notable success on downstream tasks; intriguingly, they have also performed well on challenging tests of syntactic competence. Hence, it remains an open question whether scalable learners like BERT can become fully proficient in the syntax of natural language by virtue of data scale alone, or whether they still benefit from more explicit syntactic biases. To answer this question, we introduce a knowledge distillation strategy for injecting syntactic biases into BERT pretraining, by distilling the syntactically informative predictions of a hierarchical—albeit harder to scale—syntactic language model. Since BERT models masked words in bidirectional context, we propose to distill the approximate marginal distribution over words in context from the syntactic LM. Our approach reduces relative error by 2–21% on a diverse set of structured prediction tasks, although we obtain mixed results on the GLUE benchmark. Our findings demonstrate the benefits of syntactic biases, even for representation learners that exploit large amounts of data, and contribute to a better understanding of where syntactic biases are helpful in benchmarks of natural language understanding.
Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy.

OBJECTIVE Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based method to synthesize DECT images from SECT image for proton radiotherapy. METHODS The proposed method uses a residual attention generative adversarial network. Residual blocks with attention gates were used to force the model to focus on the difference between DECT images and SECT images. To evaluate the accuracy of the method, we retrospectively investigated 70 head-and-neck cancer patients whose DECT and SECT scans were acquired simultaneously. The model was trained to generate both a high and low energy DECT image based on a SECT image. The generated synthetic low and high DECT images were evaluated against the true DECT images using leave-one-out cross-validation. To evaluate our method in the context of a practical application, we generated SPR maps from synthetic DECT (sDECT) using a dual-energy based stoichiometric method and compared the SPR maps to those generated from DECT. A dosimetric comparison for dose obtained from DECT was performed against that derived from sDECT. RESULTS The mean of mean absolute error, peak signal-to-noise ratio and normalized cross-correlation for the synthetic high and low energy CT images was 36.9 HU, 29.3 dB, 0.96 and 35.8 HU, 29.2 dB, and 0.96, respectively. The corresponding SPR maps generated from synthetic DECT showed an average normalized mean square deviation of about 1% with reduced noise level and artifacts than those from original DECT. Dose-volume histogram (DVH) metrics for the clinical target volume agree within 1% between the DECT and sDECT calculated dose. CONCLUSION Our method synthesized accurate DECT images and showed a potential feasibility for proton SPR map generation. ADVANCES IN KNOWLEDGE This study investigated a learning-based method to synthesize DECT images from SECT image for proton radiotherapy.