Miracle-dz/UniFAR-FTUs huggingface dataset:
OMIP‐91: A 27‐color flow cytometry panel to evaluate the phenotype and function of human conventional and unconventional T‐cells

This 27‐color panel was developed to simultaneously measure different T‐cell populations (CD4, CD8, γδ T‐cells, and MAIT cells) and their subsets (Memory, Th1, Th2, Th17, Tfh, and Treg) along with functional markers associated with their activation status, cytokine production and cytotoxicity. This panel will be useful for both in vivo and in vitro studies evaluating T‐cells in the context of human health and disease. This panel is valuable in settings where samples are limited as a large amount of data will be generated using small volumes of blood.
Validation of resonance Raman spectroscopy-measured skin carotenoid status as a biomarker for fruit and vegetable intake in Korean adults

Abstract Blood carotenoid concentration measurement is considered the gold standard for fruit and vegetable (F&V) intake estimation; however, this method is invasive and expensive. Recently, skin carotenoid status (SCS) measured by optical sensors has been evaluated as a promising parameter for F&V intake estimation. In this cross-sectional study, we aimed to validate the utility of resonance Raman spectroscopy (RRS)-assessed SCS as a biomarker of F&V intake in Korean adults. We used data from 108 participants aged 20–69 years who completed SCS measurements, blood collection and 3-d dietary recordings. Serum carotenoid concentrations were quantified using HPLC, and dietary carotenoid and F&V intakes were estimated via 3-d dietary records using a carotenoid database for common Korean foods. The correlations of the SCS with serum carotenoid concentrations, dietary carotenoid intake and F&V intake were examined to assess SCS validity. SCS was positively correlated with total serum carotenoid concentration (r = 0·52, 95 % CI = 0·36, 0·64, P < 0·001), serum β-carotene concentration (r = 0·60, 95 % CI = 0·47, 0·71, P < 0·001), total carotenoid intake (r = 0·20, 95 % CI = 0·01, 0·37, P = 0·04), β-carotene intake (r = 0·30, 95 % CI = 0·11, 0·46, P = 0·002) and F&V intake (r = 0·40, 95 % CI = 0·23, 0·55, P < 0·001). These results suggest that SCS can be a valid biomarker of F&V intake in Korean adults.
Mixed Feedings and Necrotizing Enterocolitis: The Proportion of Human Milk Matters

Objectives: Impact of the proportion of human milk (HM) in mixed feeding on necrotizing enterocolitis (NEC) remains unknown. This study explores the influence of different proportions of HM on the risk of NEC. Materials and Methods: A retrospective cohort study was performed in infants with very low birth weight (VLBW). A spline smoothing curve was used to evaluate the dose-dependent association between HM and the risk of NEC. Univariate and multivariate analyses were performed to detect the association between the proportion of HM and NEC. Results: Twenty-four infants developed NEC, with 4 (1.9%) in the high HM group, 18 (28.1%) in the low HM group, and 2 (8.0%) in the exclusive formula group (p < 0.001). After adjusting for the relevant confounders, low HM (proportion of HM ≤54%) (OR 33.526, 95% confidential interval [CI] 7.183–156.475, p < 0.001) and exclusive formula feeding (OR 8.493, 95% CI 1.107–65.187, p = 0.040) significantly increased the incidence of NEC, compared with the high HM feeding (proportion of HM >54%). Similarly, low HM was independently associated with an increased risk of feeding intolerance compared with high HM feeding (OR 4.383, 95% CI 2.243–8.564, p < 0.001). Conclusion: A low ratio of HM (≤54%) significantly increased the risk of intestinal complications in VLBW infants. Mixed feeding should relate to the proportion of HM in premature infants.
An edges detecting scheme for rocket based on B- spline function

In this paper,a method of detecting rocket image edges based on B spline function is presented.First the rocket surface is fit by B spline function.Then the second order derivates is obtained for the smoothing surface.Finally the edge points are found through zero- crossing of the second order derivates.By experiments,using B spline function for detecting rocket image edges is shown to be superior to the current algorithms in terms of resolving the contradiction between the detection precision of the rocket image edges and the restraining ability of an image noise.The image edge derived from this scheme is more explicit and hence,a perfect result for splitting image is achieved.The scheme is simple and useful in real- time operation and is therefore an attractive scheme for practical systems.
The progress and trend of research on bifurcation and chaos in H-bridge converter

The research actuality of the bifurcation and chaos phenomena in the H-bridge converter is summarized.Two discrete models of the typical H-bridge converter are introduced in detail,and their applicability is also analyzed and assessed.The existing stability analysis approaches and the numerical simulation methods used in the nonlinear study of H-bridge converter are analyzed concretely,and the merits and demerits are also summarized.With the method of Lyapunov exponent,those two discrete models are verified,and the difference between them,which are changeable according to the switching frequency,is analyzed and explained in detail.The application of time-delayed feedback control(TDFC)method and extended time-delayed feedback control method(ETDFC),which are used to control the chaos in H-bridge converter,is introduced,and their superiorities and deficiencies are evaluated.Finally,several future researches on the bifurcation and chaos phenomena of H-bridge converter are proposed,which provides some instructions for follow-up study.
Influence d'un échantillonnage irrégulier sur les performances de la reconstruction

This paper studies the problem of band-limited random signal reconstruction in the case of periodic and irregular sampling. Various methods (spline interpolation, matrix method, iterative algorithms, modified Lagrange formula) are considered in the case of irregular sampling. The reconstruction is performed using the Shannon formula in the case of periodic sampling. Periodic and random sampling are compared in terms of reconstruction error. When the Shannon condition holds, the modified Lagrange formula applied to jitter shows similar performance to the Shannon formula applied to regular sampling. Otherwise, an irregular sampling allows to spread the out-of-band interference. The influence of a spectral component outside the Nyquist band is studied: in this case, the perioding sampling may occur misleading interpretation of the spectral containt.
Empowering the Voter: A Mathematical Analysis of Borda Count Elections with Non-Linear Preferences

This project explores the application of non linearly-ordered sets to the field of voting theory. In particular, a specific voting system known as Borda Count is studied. In order to analyze the mathematical properties associated with different voting systems the alternatives on a ballot are represented as elements of an ordered set. Traditional voting theory analysis has studied many properties of Borda Count that hold when voters’ ballots are limited to linearly ordered sets. This project expands the Borda Count election method to allow the use of bucket ordered and partially ordered sets as ballots instead of only linearly ordered sets. The different mathematical properties associated with traditional Borda Count are then analyzed in order to see if they still hold for these expanded Borda Count voting systems.
Convex Polygons That Cannot Tile the Plane

The seemingly straightforward task of assigning seats to states according to population runs into several politically unacceptable complications. It is shown that this is a serious problem in the sense that these complications will occur for most population densities. The mathematical reasons for these complications are discussed, and one of them is related to flows on a higher dimensional torus. Finally, a simple apportionment method is suggested.
Incorporating Signal Awareness in Source Code Modeling: An Application to Vulnerability Detection

AI models of code have made significant progress over the past few years. However, many models are actually not learning task-relevant source code features. Instead, they often fit non-relevant but correlated data, leading to a lack of robustness and generalizability, and limiting the subsequent practical use of such models. In this work, we focus on improving the model quality through signal awareness, i.e., learning the relevant signals in the input for making predictions. We do so by leveraging the heterogeneity of code samples in terms of their signal-to-noise content. We perform an end-to-end exploration of model signal awareness, comprising: (i) uncovering the reliance of AI models of code on task-irrelevant signals, via prediction-preserving input minimization; (ii) improving models’ signal awareness by incorporating the notion of code complexity during model training, via curriculum learning; (iii) improving models’ signal awareness by generating simplified signal-preserving programs and augmenting them to the training dataset; and (iv) presenting a novel interpretation of the model learning behavior from the perspective of the dataset, using its code complexity distribution. We propose a new metric to measure model signal awareness, Signal-aware Recall, which captures how much of the model’s performance is attributable to task-relevant signal learning. Using a software vulnerability detection use-case, our model probing approach uncovers a significant lack of signal awareness in the models, across three different neural network architectures and three datasets. Signal-aware Recall is observed to be in the sub-50s for models with traditional Recall in the high 90s, suggesting that the models are presumably picking up a lot of noise or dataset nuances while learning their logic. With our code-complexity-aware model learning enhancement techniques, we are able to assist the models toward more task-relevant learning, recording up-to 4.8× improvement in model signal awareness. Finally, we employ our model learning introspection approach to uncover the aspects of source code where the model is facing difficulty, and we analyze how our learning enhancement techniques alleviate it.
Distributed Task Offloading and Resource Purchasing in NOMA-enabled Mobile Edge Computing: Hierarchical Game Theoretical Approaches

As the computing resources and the battery capacity of mobile devices are usually limited, it is a feasible solution to offload the computation-intensive tasks generated by mobile devices to edge servers in mobile edge computing (MEC). In this paper, we study the multi-user multi-server task offloading problem in mobile edge computing systems, where all the users compete for the limited communication resources and computing resources. We formulate the offloading problem with the goal of minimizing the cost of the users and maximizing the profits of the edge servers. We propose a hierarchical Economic and Efficient Task Offloading and Resource Purchasing (EETORP) framework that includes a two-stage joint optimization process. Then, we prove that the problem is NP-complete. For the first stage, we formulate the offloading problem as a multi-channel access game (MCA-Game) and prove theoretically the existence of at least one Nash equilibrium strategy in the MCA-Game. Next, we propose a game-based multi-channel access (GMCA) algorithm to obtain the Nash equilibrium strategy and analyze the performance guarantee of the obtained offloading strategy in the worst case. For the second stage, we model the computing resource allocation between the users and edge servers by Stackelberg game theory, and reformulate the problem as a resource pricing and purchasing game (PAP-Game). We prove theoretically the property of incentive compatibility and the existence of Stackelberg equilibrium. A game-based pricing and purchasing (GPAP) algorithm is proposed. Finally, a series of both parameter experiments and comparison experiments are carried out, which validate the convergence and effectiveness of the GMCA and GPAP algorithms.
Trends in glycemic, blood pressure, and lipid control in adults with diabetes in Switzerland: the CoLaus|PsyCoLaus Study

Aim To assess the 15-year trends in the level of glycemic, blood pressure, and cholesterol control in adults with diabetes in a Swiss population-based cohort. Research design and methods CoLaus|PsyCoLaus is a prospective cohort study of 6733 adults aged 35–75 years in Lausanne, Switzerland. Baseline recruitment was conducted in 2003–6 and was followed by three subsequent follow-ups in 2009–12, 2014–17 and 2018–21. In adults with diabetes, glycemic control was defined as fasting plasma glucose <7 mmol/L, blood pressure control as systolic and diastolic pressures of <140/90 mm Hg, and lipid control as non-high-density lipoprotein (non-HDL) cholesterol control <3.4 mmol/L. Results Rates of glycemic control improved from 23.2% (95% CI 19.5 to 27.3) in 2003–6 to 32.8% (95% CI 28.1 to 37.8) in 2018–21. Blood pressure control also improved, from 51.5% at baseline (95% CI 46.8 to 56.2) to 63.3% (95% CI 58.2 to 68.1) 15 years later. The largest improvement was in cholesterol control, from 29.1% (95% CI 25.1 to 33.6) in 2003–6 to 56.3% (95% CI 51.1 to 61.4) in 2018–21. Overall, simultaneous control of all three improved from 5.5% (95% CI 3.7 to 8.1) at baseline to 17.2% (95% CI 13.7 to 21.5) 15 years later. Improvements in risk factor control tallied with an increase in the use of glucose-lowering agents, blood pressure-lowering medication, and statins. Men were less likely to achieve blood pressure control but presented with a better control of non-HDL cholesterol. Caucasians were less likely to achieve simultaneous control than non-Caucasians. Conclusion Cardiovascular risk factor control in adults with diabetes in Switzerland has increased in the last 15 years, but there remains a margin for improvement.
Drivers of Digital Transformation and their Impact on Organizational Management

Abstract Digital transformation has become a critical topic for organizations that want to stay competitive in today’s digital age. The widespread use of digital technologies has brought significant changes to the way organizations exist, operate and interact with customers. They are going through a process of reshaping and reorganizing processes and operations, as well as rethinking and redefining the human role in the value creation process. However, digital technologies and their diffusion are not the only driver of digital transformation, as the success of such change initiatives depends on many other factors, the definition of which is crucial to the success of digital transformation. The objective of this paper is to explore the drivers of digital transformation and their impact on management. The work presents a comprehensive review of the literature on digital transformation, identifying the main drivers that influence the success of digital transformation initiatives. It also defines the impact of these drivers on the management of organizations, identifying how the role of the executive is being redefined in today’s digital age.
Primary Biliary Cirrhosis and Scleroderma Occuring in a Man

SUMMARY A man found to have primary biliary cirrhosis and extensive scleroderma is reported. This appears to be the first such association described in a man, and further strengthens the suggestion that there is some underlying link between these two obscure conditions. On reviewing 26 patients with primary biliary cirrhosis; 3 had the Sicca syndrome, 11 had Raynaud's phenomenon and 6 had detectable antinuclear factor.
The 1/f-like behavior of neural field spectra are a natural consequence of noise driven brain dynamics

Consistent observations across recording modalities, experiments, and neural systems find neural field spectra with 1/f-like scaling, eliciting many alternative theories to explain this universal phenomenon. We show that a general dynamical system with stochastic drive and minimal assumptions generates 1/f-like spectra consistent with the range of values observed in vivo, without requiring a specific biological mechanism or collective critical behavior.
Erythromycin resistance of clinical Campylobacter jejuni and Campylobacter coli in Shanghai, China

Campylobacter species are zoonotic pathogens, as well as the prevalent cause of foodborne bacterial gastroenteritis. The spread of antimicrobial-resistant strains poses a serious threat to global public health and attracts attention worldwide, but information about clinical Campylobacter is relatively limited compared to isolates from food and animals. The current study illustrated the prevalence and antimicrobial resistance profiles of Campylobacter jejuni and Campylobacter coli isolates collected from a consecutive surveillance program between 2012 and 2019 in Shanghai, China, using antimicrobial susceptibility testing and whole-genome sequencing. Among the 891 Campylobacter strains (761 C. jejuni and 130 C. coli) isolates collected, high portions above 90% of resistance to ciprofloxacin, nalidixic acid, and tetracycline were observed for both C. jejuni and C. coli. The most common MDR profiles represented by C. jejuni and C. coli were combination of ciprofloxacin, tetracycline, florfenicol and nalidixic acid (5.39%), and azithromycin, ciprofloxacin, erythromycin, gentamicin, tetracycline, clindamycin, nalidixic acid (28.46%), respectively. The erythromycin resistance of C. coli (59.23%) is higher than C. jejuni (2.50%). A total of 76 erythromycin resistant isolates (16 C. jejuni and 60 C. coli) were sequenced using Illumina platform for determining the genotypes, antimicrobial resistance patterns and phylogeny analysis. Multilocus sequence typing (MLST) analysis showed a high genetic diversity with 47 sequence types (STs), including 4 novel alleles and 12 new STs. The most abundant clonal complexes (CCs) were CC-403 (31.25%) and CC-828 (88.33%) for C. jejuni and C. coli, respectively. Among the 76 erythromycin-resistant isolates, mutation A2075G in 23S rRNA and erm(B) gene were detected in 53.95 and 39.47%, respectively. The erm(B) gene was identified exclusively in 30 C. coli isolates. All these erm(B) positive isolates were multi-drug resistant. Furthermore, comparison of the erm(B)-carrying isolates of multiple sources worldwide demonstrated the possibility of zoonotic transmission of erm(B) in Campylobacter. These findings highlight the importance of continuous surveillance of erythromycin resistance dissemination in Campylobacter which may compromise the effectiveness of antimicrobial therapy.
Molecular transition of SARS-CoV-2 from critical patients during the first year of the COVID-19 pandemic in Mexico City

Background The SARS-CoV-2 virus has caused unprecedented mortality since its emergence in late 2019. The continuous evolution of the viral genome through the concerted action of mutational forces has produced distinct variants that became dominant, challenging human immunity and vaccine development. Aim and methods In this work, through an integrative genomic approach, we describe the molecular transition of SARS-CoV-2 by analyzing the viral whole genome sequences from 50 critical COVID-19 patients recruited during the first year of the pandemic in Mexico City. Results Our results revealed differential levels of the evolutionary forces across the genome and specific mutational processes that have shaped the first two epidemiological waves of the pandemic in Mexico. Through phylogenetic analyses, we observed a genomic transition in the circulating SARS-CoV-2 genomes from several lineages prevalent in the first wave to a dominance of the B.1. 1.519 variant (defined by T478K, P681H, and T732A mutations in the spike protein) in the second wave. Conclusion This work contributes to a better understanding of the evolutionary dynamics and selective pressures that act at the genomic level, the prediction of more accurate variants of clinical significance, and a better comprehension of the molecular mechanisms driving the evolution of SARS-CoV-2 to improve vaccine and drug development.
Complete genome analysis of Tequatrovirus ufvareg1, a Tequatrovirus species inhibiting Escherichia coli O157:H7

Introduction Bacteriophages infecting human pathogens have been considered potential biocontrol agents, and studying their genetic content is essential to their safe use in the food industry. Tequatrovirus ufvareg1 is a bacteriophage named UFV-AREG1, isolated from cowshed wastewater and previously tested for its ability to inhibit Escherichia coli O157:H7. Methods T. ufvareg1 was previously isolated using E. coli O157:H7 (ATCC 43895) as a bacterial host. The same strain was used for bacteriophage propagation and the one-step growth curve. The genome of the T. ufvareg1 was sequenced using 305 Illumina HiSeq, and the genome comparison was calculated by VIRIDIC and VIPTree. Results Here, we characterize its genome and compare it to other Tequatrovirus. T. ufvareg1 virions have an icosahedral head (114 x 86 nm) and a contracted tail (117 x 23 nm), with a latent period of 25 min, and an average burst size was 18 phage particles per infected E. coli cell. The genome of the bacteriophage T. ufvareg1 contains 268 coding DNA sequences (CDS) and ten tRNA genes distributed in both negative and positive strains. T. ufvareg1 genome also contains 40 promoters on its regulatory regions and two rho-independent terminators. T. ufvareg1 shares an average intergenomic similarity (VIRIDC) of 88.77% and an average genomic similarity score (VipTree) of 88.91% with eight four reference genomes for Tequatrovirus available in the NCBI RefSeq database. The pan-genomic analysis confirmed the high conservation of Tequatrovirus genomes. Among all CDS annotated in the T. ufvareg1 genome, there are 123 core genes, 38 softcore genes, 94 shell genes, and 13 cloud genes. None of 268 CDS was classified as being exclusive of T. ufvareg1. Conclusion The results in this paper, combined with other previously published findings, indicate that T. ufvareg1 bacteriophage is a potential candidate for food protection against E. coli O157:H7 in foods.
How the Brain and Memory Grow Up Together

We forget a lot about events that happen early in our lives. Why does this happen? To answer this question, we looked at how memory changes as children grow. We know the brain is important for memory, but we wanted to understand whether it was the changes in the brain that help kids to remember or if it was the ability to remember that changes the brain. We gave kids memory tests and looked at their brain activity across 3 years. Then we asked which changed first—kids’ memories or kids’ brains? We found that there was an interactive relationship: in younger kids, memory shaped the brain; but in older kids, memory and the brain shaped each other. These results help us understand why memory gets better as kids grow up and how using our brains helps us to remember.
Editorial: The notch signaling pathway in lymphoid malignancies

COPYRIGHT © 2023 Fais and Efremov. This is an openaccess article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 16 May 2023 DOI 10.3389/fonc.2023. 1216398