Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of gut microflora of donkeys in high and low altitude areas

Donkeys’ gut microbe is critical for their health and adaptation to the environment. Little research has been conducted on the donkey gut microbiome compared with other domestic animals. The Tibetan Plateau is an extreme environment. In this study, 6 Qinghai donkeys (QH) from the Tibetan Plateau and 6 Dezhou donkeys (DZ) were investigated, and the contents of 4 parts—stomach, small intestine, cecum, and rectum—were collected. 16S rRNA sequencing and metagenomic sequencing were used to analyze the composition and diversity of gut microbial communities in donkeys. The results showed that the flora diversity and richness of the hindgut were significantly higher than those of the foregut (p < 0.01), with no sex differences, and the community structure and composition of the same or adjacent regions (stomach, small intestine, cecum, and rectum) were similar. Besides, the flora diversity and richness of QH on the Tibetan Plateau were significantly higher than those of DZ (p < 0.05). The major pathways associated with QH were signal transduction mechanisms and carbohydrate transport and metabolism, and Bacteroidales were the major contributors to these functions. Our study provides novel insights into the contribution of microbiomes to the adaptive evolution of donkeys.
The impact of using different ancestral reference populations in assessing crossbred population admixture and influence on performance

Crossbreeding is a process in which animals from different breeds are mated together. The animals produced will exhibit a combination of both additive and non-additive genetic improvement from parental breeds that increase heterozygosity and negate inbreeding depression. However, crossbreeding may also break up the unique and often beneficial gene combinations in parental breeds, possibly reducing performance potential as the benefits of heterosis depends on the type of crossbreeding systems used and heritability of the traits. This effect of crossbreeding, especially on the genome architecture, is still poorly understood with respect to 3-breed crossbreeding systems. Thus, this study examined variation in genomic ancestry estimations relative to pedigree-based estimations and correlated breed composition to key production and health traits. Two rotational crossbred populations, referenced as ProCROSS and Grazecross were assessed and totaled 607 crossbred cattle. ProCROSS is a product of rotational crossbreeding of Viking Red (VKR), Holstein (HOL), and Montbeliarde (MON). In contrast, Grazecross consists of Viking Red (VKR), Normande (NOR), and Jersey (JER). Both breeding programs were aimed at capitalizing on the positive effect of heterosis. The VKR is a marketing term for Swedish Red, Danish Red, and Finnish Ayrshire breed which complicated breed determination. Therefore, genomic breed composition estimates were compared using two different representations of VKR, one of which was based on parents used in the crossing system and a second based on genotypes from the ancestral breeds that comprise VKR. Variation of breed composition estimates were assessed between pedigree and genome-based predictions. Lastly, Genomic estimations were correlated with production and health traits by comparing extreme performance groups to identify the relationship between breed ancestry and performance. With the exception of the JER breed composition in Grazecross, all other estimates of the purebred contribution to the ProCROSS and Grazecross showed a significant difference in their genomic breed estimation when using the VKR ancestral versus the VKR parental reference populations for admixture analysis. These observations were expected given the different relationship of each VKR representation to the crossbred cattle. Further analysis showed that regardless of which VKR reference population was used, the degree of MON and HOL breed composition plays a significant role in milk and fat production in ProCROSS, while the degree of VKR and NOR ancestry were related to improved health performance in Grazecross. In all, identifying the most appropriate and informative animals to use as reference animals in admixture analysis is an important factor when interpreting results of relationship and population structure, but some degree of uncertainty exists when assessing the relationship of breed composition to phenotypic performance.
Luminal epithelial cells integrate variable responses to aging into stereotypical changes that underlie breast cancer susceptibility

Effects from aging in single cells are unpredictable, whereas aging phenotypes at the organ- and tissue-levels tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages, the luminal epithelial and myoepithelial cells. Mammary epithelia exhibit substantial stereotypical changes with age that merits attention because they are putative breast cancer-cells-of-origin. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increases susceptibility to cancer initiation. We identified two models of age-dependent changes in gene expression, directional changes and increased variance, which contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and implicated downregulation of chromatin and genome organizers such as SATB1. Epithelial expression of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal detectable in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue and that their emergent aging phenotype both endows cells with the ability to become cancer-cells-of-origin and embodies a biosensor that presages cancer susceptibility.
AUTO REGRESSION BASED RESNET METHODOLOGY FOR AIR POLLUTION DETECTION

: The health effects of air pollution endanger human lives, especially among the at-risk population and those who suffer from respiratory illnesses. Hence the detection and monitoring of air pollution becomes necessarily important. Given the exorbitant cost of putting highly precise air pollution monitors throughout a city is quiet expensive. In contrast to previous machine learning studies that primarily focus on pollutant estimation based on single day-time images, our proposed deep learning model integrates ResNet with Long Short-Term Memory , extracting spatial-temporal features of sequential images taken from smartphones instead for estimating air pollution using high equipped sensors and other sophisticated euipments. In this study, logistic regression is used to determine whether or not a data sample is polluted. Based on prior PM2.5 data, auto regression and other extracted features, ResNet is used to predict PM2.5 levels. Knowing the level of PM2.5 in the coming years, months, or weeks allows us to reduce it to a safe level. This proposed work aims to determine air quality level based on data set of camera images taken from a specific city in various time intervals.
Visualizing Prediction Provenance in Regression Random Forests

Random forest models are widely used in many application domains due to their performance and the fact that their constituent decision trees carry clear decision rules. Yet, the provenance of the predictions made by an entire forest is complex to grasp, which motivates application domain experts to adopt black-box testing strategies. We propose in this paper a coordinated multiple view system allowing to shed more light on prediction provenance, uncertainty and error in terms of bias and variance at the global model scale or at the local scale of decision paths and individual instances
Performance Analysis of Two-Hop Systems Over α − η − κ − µ Channel

: The increasing demand for new services, ubiquitous coverage and device/thing-oriented communications have been the main driving force to the development of a new, advanced generation relaying communication technology. Current technologies, such as 3G and even 4G, will not be able to meet the data requirements required for necessary connectivity. The wide diversity of scenarios for 5G with relay system opens the possibility for development of different solutions to meet the future demands. However recently developed α−η-κ-μ channel model can be used to model the behaviour of mm-Wave for aforesaid fading environment. This paper investigates performance matrices of fading model for two-hop communication system in closed-form formulas. More specifically, Amount of Fading, Average Bit Error Rate (ABER) and Average Channel Capacity.
Stop, DROP, and ROA: effectiveness of defenses through the lens of DROP

We analyze the properties of 712 prefixes that appeared in Spamhaus' Don't Route Or Peer (DROP) list over a nearly three-year period from June 2019 to March 2022. We show that attackers are subverting multiple defenses against malicious use of address space, including creating fraudulent Internet Routing Registry records for prefixes shortly before using them. Other attackers disguised their activities by announcing routes with spoofed origin ASes consistent with historic route announcements, and in one case, with the ASN in a Route Origin Authorization. We quantify the substantial and actively-exploited attack surface in unrouted address space, which warrants reconsideration of RPKI eligibility restrictions by RIRs, and reconsideration of AS0 policies by both operators and RIRs.
Sentiment Clustering of Movie Review Data UsingUnsupervised Machine Learning Algorithm

: It is observed that consumer often share their opinion, views or feeling about any term used on social networkthrough reviews, comments. These reviews are often writtenin natural language and mostly unstructured. Thus, to obtainany meaningful information from these reviews, it needs to beprocessed. The reviews obtained are mostly not tagged as whetherit is of positive or negative in nature. so, in order to processit unsupervised machine learning techniques are implemented.Clustering method are applied to analyse the reviews by makingcluster of reviews. In this paper, four different unsupervisedclustering techniques i.e., K-Means, mini batch K-Means, AffinityPropagation and DBSCAN are applied to analyse the moviereviews. Different performance evaluation parameters are usedto evaluate the performance of these techniques.
Growth and characterization of Bi2Sr2Ca2Cu3O10 and (Bi,Pb)2Sr2Ca2Cu3O10−δ single crystals

Large and high-quality single crystals of both Pb-free and Pb-doped high-temperature superconducting compounds (Bi1−xPbx)2Sr2Ca2Cu3O10−y (x = 0 and 0.3) were grown by means of a newly developed 'vapour-assisted travelling solvent floating zone' technique (VA-TSFZ). This modified zone-melting technique was performed in an image furnace and allowed for the first time the growth of large Pb-doped crystals, by compensating for the Pb losses that occur at high temperature. Crystals up to 3 × 2 × 0.1 mm3 were successfully grown. Post-annealing under high pressure of O2 (up to 10 MPa at T = 500 °C) was applied to enhance Tc and improve the homogeneity of the crystals. Structural characterization was performed by single-crystal x-ray diffraction (XRD). Structure refinement confirmed a commensurate modulated superlattice in the Pb-free crystals. The space group is orthorhombic, A2aa, with cell parameters a = 21.829(4) A, b = 5.4222(9) A and c = 37.19(1) A. Superconducting studies were carried out by ac and dc magnetic measurements. Very sharp superconducting transitions were obtained in both kinds of crystals (ΔTc ≤ 1 K). In optimally doped Pb-free crystals, critical temperatures up to 111 K were measured. Magnetic critical current densities of 2 × 105 A cm−2 were measured at T = 30 K and μ0H = 0 T. A weak second peak in the magnetization loops was observed in the temperature range 40–50 K, above which the critical current density was found to rapidly decrease as a function of T and H. A comparison between the pinning properties in Pb-free and Pb-doped crystals is reported and discussed.
Supercritical N = 2 string theory

The N=2 string is examined in dimensions above the critical dimension (D=4) in a linear dilaton background. We demonstrate that string states in this background propagate in a single physical time dimension, as opposed to two such dimensions present when the dilaton gradient vanishes in D=4. We also find exact solutions describing dynamical dimensional reduction and transitions from N=2 string theory to bosonic string theory via closed-string tachyon condensation.
ADJUSTMENT OF ADOLESCENTS ABOUT THEIR EMOTIONAL MATURITY

Education is the inevitable base for the socio-economic development of any country. In the present circumstances, children, youth, and adults are facing many problems in life and work. The present investigation aimed at finding the adjustment of adolescents about their emotional maturity in senior secondary school. A survey method was adopted in the present study to find out the emotional maturity and adjustment of adolescent males and females in senior secondary school. The sample of the study consisted of 100 students of XI and XII grades from a private school in the Patiala District. The findings of the study revealed that adolescent boys and girls in private senior secondary schools have similar levels of adjustment. Adolescent boys and girls in private senior secondary schools have an equal level of emotional maturity. There is no significant relationship between adjustment and the emotional maturity of adolescents.
Data-driven method of pile-up correction for the substructure of massive jets

We describe a method to measure and subtract the incoherent component of energy flow arising from multiple interactions from jet shape/substructure observables of ultra-massive jets. The amount subtracted is a function of the jet shape variable of interest and not a universal property. Such a correction is expected to significantly reduce any bias in the corresponding distributions generated by the presence of multiple interactions, and to improve measurement resolution. Since in our method the correction is obtained from the data, it is not subject to uncertainties coming from the use of theoretical calculations and/or Monte Carlo event generators. We derive our correction method for the jet mass, angularity and planar flow. We find these corrections to be in good agreement with data on massive jets observed by the CDF collaboration. Finally, we comment on the linkage with the concept of jet area and jet mass area.
KNOW YOUR NEIGHBORHOOD: A DETAILED MODEL ATMOSPHERE ANALYSIS OF NEARBY WHITE DWARFS

We present improved atmospheric parameters of nearby white dwarfs lying within 20 pc of the Sun. The aim of the current study is to obtain the best statistical model of the least-biased sample of the white dwarf population. A homogeneous analysis of the local population is performed combining detailed spectroscopic and photometric analyses based on improved model atmosphere calculations for various spectral types including DA, DB, DC, DQ, and DZ stars. The spectroscopic technique is applied to all stars in our sample for which optical spectra are available. Photometric energy distributions, when available, are also combined to trigonometric parallax measurements to derive effective temperatures, stellar radii, as well as atmospheric compositions. A revised catalog of white dwarfs in the solar neighborhood is presented. We provide, for the first time, a comprehensive analysis of the mass distribution and the chemical distribution of white dwarf stars in a volume-limited sample.
A Study on the Prediction of House Price Index in First-Tier Cities in China Based on Heterogeneous Integrated Learning Model

To address the difficulty of low prediction accuracy, insufficient model stability, and certain lag associated with a single machine learning model in the prediction of house price, this paper proposes a multimodel fusion house price prediction model based on stacking integrated learning. Firstly, web search data affecting house prices were collected by web crawler technology, and Spearman correlation analysis was performed on the attribute set to reduce its complexity and establish a prediction index system for four first-tier cities in China. Secondly, with the goal of improving accuracy, diversity, and generalization ability, the types of base learners as well as metalearners are determined, and the parameters of the base learners are optimized using the grey wolf optimization algorithm to produce the GWO-stacking model, and the experimental results from four datasets demonstrate that the model has high prediction accuracy. Finally, to solve the issue of unintelligible black boxes in machine learning models, we have used the state-of-the-art interpretation method SHAP combined with the LightGBM algorithm to interpret the model, and the result can be used as a basis for real estate policy planning and adjustment and even guide the demand of home buyers, thus improving the efficiency and effectiveness of government policy making.
Reverse Line Graph Construction: The Matrix Relabeling Algorithm MARINLINGA Versus Roussopoulos's Algorithm

We propose a new algorithm MARINLINGA for reverse line graph computation, i.e., constructing the original graph from a given line graph. Based on the completely new and simpler principle of link relabeling and endnode recognition, MARINLINGA does not rely on Whitney's theorem while all previous algorithms do. MARINLINGA has a worst case complexity of O(N^2), where N denotes the number of nodes of the line graph. We demonstrate that MARINLINGA is more time-efficient compared to Roussopoulos's algorithm, which is well-known for its efficiency.
Cytotoxic and antimicrobial effects of selected Egyptian Asteraceae species as well as GC-MS metabolite profiling of Senecio cruentus lipophilic fraction

The ethanol extracts of three ornamental Asteraceae species; Senecio cruentus DC. , Dimorphotheca ecklonis DC. and Arctotis aurantiaca L. were studied for their cytotoxicity against Panc1 and antimicrobial activities against selected microbial strains. Lipophilic fraction of S. cruentus showed the most active cytotoxic extract (IC 50 = 7.63±0.46 µg/ml) and was subjected to metabolite profiling by using GC-MS. Seventeen compounds of different categories were identified. The detection of phytol as well as unsaturated fatty acids/esters; cis-vaccenic acid (C18:1), glycidyl oleate (C21:1), 9,12-Octadecadienoic acid (Z,Z)- methyl ester (C19:2), 9,12,15-(Z,Z,Z)- Octadecatrienoic acid, 2,3-dihydroxypropyl ester, (C21:3) and Z,Z-3,15-Octadecadien-1-ol acetate (C20:2) are suggesting its cytotoxicity. The S. cruentus lipophilic fraction exhibited potent cytotoxic activity against A549 (lung) cancer cells (IC 50 = 1.919±0.1 µg/ml) through inhibition of cell growth at G1/S stage. All the species displayed moderate antimicrobial activities against certain types of selected strains. The LD 50 of S. cruentus ethanol extract was determined as 1.5 g/kg.
Generic Side-channel Distinguisher Based on Kolmogorov-Smirnov Test: Explicit Construction and Practical Evaluation *

Construction and evaluation of efficient distinguishers with broad generality is one fundamental problem in the area of side-channel cryptanalysis. Due to their capabilities to deal with general correlations, MIA-like distinguishers have received wide attention from academia. In this paper, we conduct a comprehensive comparison investigation of existing MIA-like distinguishers, and then propose a new generic side-channel distinguisher based on partial Kolmogorov-Smirnov test, namely PKS distinguisher. Theoretical analysis and experimental attacks unanimously justify that PKS distinguisher works remarkably well with both linear and non-linear leakage models. Specifically, PKS distin- guisher has obvious advantages over existing MIA-like distinguishers in terms of both success rate and guessing entropy. Additionally, lower computational complexity of PKS distinguisher further shows its better applicability than MIA-like distinguishers.
Anisotropic magnetothermal transport and spin Seebeck effect

The angular dependence of the thermal transport in insulating or conducting ferromagnets is derived on the basis of the Onsager reciprocity relations applied to a magnetic system. It is shown that the angular dependence of the temperature gradient takes the same form as that of the anisotropic magnetoresistance, including anomalous and planar Hall contributions. The measured thermocouple generated between the extremities of the non-magnetic electrode in thermal contact to the ferromagnet follows this same angular dependence. The sign and amplitude of the magneto-voltaic signal is controlled by the difference of the Seebeck coefficients of the thermocouple.
Impact of a High-Resolution Anoscopy Clinic on Management of Anal Dysplasia in Women Living With HIV

Background The rate of anal squamous cell cancer (aSCC) is increasing among women living with HIV. Treatment of precursor high grade squamous intraepithelial lesions (HSIL) may reduce the risk of progression to aSCC. The objective of this study was to examine effects of a dedicated high-resolution anoscopy (HRA) clinic on management of HSIL in women with HIV. Methods Women living with HIV who underwent anal dysplasia screening at a single institution between 2006 and 2020 were reviewed. Those who underwent screening before (Group A) and after (Group B) the implementation of an HRA program in 2017 were compared. The primary outcome of interest was the successful detection and treatment of HSIL. Results A total of 201 women living with HIV underwent anal dysplasia screening between 2006 and 2020. Seventy-seven patients were found to have abnormal anal cytology requiring further treatment: 43 (55.8%) in Group A and 34 (44.2%) patients in Group B. Of the patients with abnormal anal cytology, 76.7% of patients in Group A received further biopsy and treatment, whereas 79.4% of Group B patients underwent subsequent biopsy and treatment. In propensity score weighting logistic regression analysis, the Group B was 4.6 times as likely to diagnosis HSIL on biopsy compared to Group A (OR = 4.60, 95% CI: 1.15 to 18.38, P = .03). Conclusions Anal dysplasia is common among women living with HIV. The establishment of a HRA program was associated with increased identification and treatment of HSIL among women living with HIV, which may prevent the progression to aSCC.
Controlling the self-doping of YBa2C3O7-d polar surfaces: From Fermi surface to nodal Fermi arcs by ARPES

The discovery of quantum oscillations in the normal-state electrical resistivity of YBa2Cu3O6.5 provides the first evidence for the existence of Fermi surface (FS) pockets in an underdoped cuprate. However, the pockets' electron vs. hole character, and the very interpretation in terms of closed FS contours, are the subject of considerable debate. Angle-resolved photoemission spectroscopy (ARPES), with its ability to probe electronic dispersion as well as the FS, is ideally suited to address this issue. Unfortunately, the ARPES study of YBa2C3O7-d (YBCO) has been hampered by the technique's surface sensitivity. Here we show that this stems from the polarity and corresponding self-doping of the YBCO surface. By in-situ deposition of potassium atoms on the cleaved surface, we are able to continuously tune the doping of a single sample from the heavily overdoped to the underdoped regime. This reveals the progressive collapse of the normal-metal-like FS into four disconnected nodal FS arcs, or perhaps into hole but not electron pockets, in underdoped YBCO6.5.