Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the high energy frontiers of the Milky Way with ground-based gamma-ray astronomy: PeVatrons and the quest for the origin of Galactic cosmic-rays

Cosmic rays (CRs) are charged particles that arrive at Earth isotropically from all directions and interact with the atmosphere. The presence of a spectral knee feature seen in the CR spectrum at $\sim$3 PeV energies is an evidence that astrophysical objects within our Galaxy, which are known as 'Galactic PeVatrons', are capable of accelerating particles to PeV energies. Scientists have been trying to identify the origin of Galactic CRs and have been looking for signatures of Galactic PeVatrons through neutral messengers. Recent advancements in ground-based $\gamma$-ray astronomy have led to the discovery of 12 Galactic sources emitting above 100 TeV energies, and even the first time detection of PeV photons from the direction of the Crab Nebula and the Cygnus region. These groundbreaking discoveries have opened up the field of ultra-high energy (UHE, E$>$100 TeV) $\gamma$-ray astronomy, which can help us explore the high energy frontiers of our Galaxy, hunt for PeVatron sources, and shed light on the century-old problem of the origin of CRs. This review article provides an overview of the current state of the art and potential future directions for the search for Galactic PeVatrons using ground-based $\gamma$-ray observations.
Generalized Supervised Contrastive Learning

With the recent promising results of contrastive learning in the self-supervised learning paradigm, supervised contrastive learning has successfully extended these contrastive approaches to supervised contexts, outperforming cross-entropy on various datasets. However, supervised contrastive learning inherently employs label information in a binary form--either positive or negative--using a one-hot target vector. This structure struggles to adapt to methods that exploit label information as a probability distribution, such as CutMix and knowledge distillation. In this paper, we introduce a generalized supervised contrastive loss, which measures cross-entropy between label similarity and latent similarity. This concept enhances the capabilities of supervised contrastive loss by fully utilizing the label distribution and enabling the adaptation of various existing techniques for training modern neural networks. Leveraging this generalized supervised contrastive loss, we construct a tailored framework: the Generalized Supervised Contrastive Learning (GenSCL). Compared to existing contrastive learning frameworks, GenSCL incorporates additional enhancements, including advanced image-based regularization techniques and an arbitrary teacher classifier. When applied to ResNet50 with the Momentum Contrast technique, GenSCL achieves a top-1 accuracy of 77.3% on ImageNet, a 4.1% relative improvement over traditional supervised contrastive learning. Moreover, our method establishes new state-of-the-art accuracies of 98.2% and 87.0% on CIFAR10 and CIFAR100 respectively when applied to ResNet50, marking the highest reported figures for this architecture.
Nutrient Deficiency Diagnosis of Plants Based on Transfer Learning and Lightweight Convolutional Neural Networks MobileNetV3-Large

Nutrient Deficiency Diagnosis of Plants is an important application in precision agriculture. At present, nutrient deficiency diagnosis of plants mainly depends on manual identification, which makes it difficult to ensure efficiency and accuracy. Therefore, based on deep learning and focusing on the problems of difficult convergence and poor real-time performance of the existing deep convolution neural network in the detection of plant nutrient deficiency, this study proposes a lightweight model—UMNet (Nutrient-MobileNetV3-Network) for plant nutrient deficiency detection. This model enhances the collected rice leaf images to expand the dataset, then migrates the knowledge learned by the MobilenetV3-Large network on the ImageNet dataset to UMNet, redesigns a new full connection layer, and uses a new activation function. The experimental results show that: (1) Transfer learning solves the problem of insufficient training data. Compared with learning without transfer learning, the accuracy increases by 7.22% ∼ 9.63%, which greatly improves the convergence speed and recognition accuracy of the model. (2) Compared with complex convolutional neural networks(CNN), such as InceptionV3, InceptionResnetV2 and VGG16, the lightweight network UMNet has lower storage requirements and shorter training time. At the same time, it can still ensure high accuracy, and the recognition accuracy is better than other lightweight networks with the same complexity: ShuffleNetV2, EfficientNetB0 and Xception. The identification accuracy of the plant nutrient deficiency detection model UMNet constructed in this paper can reach 97.80%, and the training time of a single epoch is about 46.4s. It only takes 1.45s to predict the nutrient deficiency of a single object, which realizes the intelligent detection in the field of plant nutrient deficiency, and it will promote academic exploration of deep learning in plant phenotype research.
LEPD-Net: A Lightweight Efficient Network with Pyramid Dilated Convolution for Seed Sorting

To achieve long-term economic growth, competitiveness, and sustainability, speed and accuracy are the key requirements when it comes to seed purity sorting. However, current seed sorting methods suffer from large number of model parameters and computational complexity, make it a great challenge to deploy them in real-time applications, especially on devices with limited resources. To issue above problems, in this paper, a lightweight efficient network with pyramid dilated convolution, namely LEPD-Net, is proposed for seed sorting. First, a residual spatial pyramid module (RSPM) is elaborately designed, which uses dilated convolution with different dilation rates to enlarge the structural characteristics of the receptive field and effectively extracts multi-scale features. Then the depth-wise separable convolution to reduce the amount of model parameters and the computational complexity. In addition, to further improve the performance, a novel lightweight coordinate attention module is introduced, which uses the local cross-channel interaction to obtain the attention value of each channel and strengthen the network's ability to learn seed key features. Finally, the seed sorting task is completed through the learned features. Experimental results show that our proposed method achieves an accuracy of 96.00% and 97.25% on the Maize dataset and Red Kidney Bean dataset, respectively. The number of parameters is only 0.26M, which is far less than state-of-the-art networks (e.g., MobileNetv2, Shufflenetv2, and PPLC-Net).
Minimizing Cache Usage for Real-time Systems

Cache partitioning is a technique to reduce interference among tasks accessing the shared caches. To make this technique effective, cache segments must be given to the tasks that can benefit most from having their data and instructions cached for faster execution. The existing partitioning schemes for real-time systems divide the available cache among the tasks to guarantee their schedulability which is the sole optimization criterion. However, it is also preferable, especially in systems with power constraints or mixed criticalities, to reduce the total cache usage for real-time tasks. In this paper, we develop optimization algorithms for cache partitioning that, besides ensuring schedulability, also minimize cache usage. We consider both preemptive and non-preemptive scheduling policies on single-processor systems. For preemptive scheduling, we formulate the problem as an integer quadratically constrained program and propose an efficient heuristic achieving near-optimal solutions. For non-preemptive scheduling, we combine linear and binary search techniques with different schedulability tests. Our experiments based on synthetic task sets with parameters from real-world embedded applications show that the proposed heuristic: (i) achieves an average optimality gap of 0.79% within 0.1x run time of a mathematical programming solver and (ii) reduces average cache usage by 39.15% compared to existing cache partitioning approaches. Besides, we find that for large task sets with high utilization, non-preemptive scheduling can use less cache than preemptive to guarantee schedulability.
On the Validity of Credit-Based Shaper Delay Guarantees in Decentralized Reservation Protocols

Resource reservation is a fundamental mechanism for ensuring quality of service in time-sensitive networks, which can be decentralized by using reservation protocols. In the Ethernet technology Time-Sensitive Networking, this has been proposed in conjunction with the Credit-Based Shaper. For the reservation, the standards assume a maximum worst-case latency bound at each hop. However, we will show through formal analysis and simulation that these worst-case latency bounds are not safe. To face this, we propose an extension to the current standards to allow the reservation of time-sensitive traffic with reliable latency guarantees. The effectiveness of our approach is demonstrated through simulations of both synthetic and industrial networks. Finally, by providing additional information about neighboring devices, we could further increase the maximum reservable traffic by up to 20% in our test cases.
Collagen changes in rabbit conjunctiva after conjunctival crosslinking

Abstract This study aims to determine the ultrastructural changes in collagen fibrils in rabbit conjunctiva after conjunctival crosslinking using riboflavin and ultraviolet A (UVA) light at an irradiation intensity of 45 mW/cm2. Conjunctival crosslinking may increase conjunctival stiffness. The supertemporal quadrants of the right eyes of 24 adult rabbits were treated with a topical riboflavin solution (0.25%) before irradiation with UVA light at 45 mW/cm2 for 4 min. After 3 weeks, the collagen fibrils in fibril bundles were examined by electron microscopy. Immunohistochemical staining was used to detect the expression levels of collagen I and collagen III in the rabbits’ conjunctiva. The diameter of the collagen fibrils in the fibril bundles varied slightly, ranging from 30 to 60 nm in the conjunctival stroma of the control group. In the treatment group, the diameter of collagen fibrils ranged from 60 to 90 nm. The thickest collagen fibrils were observed in the treatment group (up to 90 nm in diameter). In contrast, those in the conjunctival stroma of the control group were considerably smaller (up to 60 nm in diameter). However, thicknesses of collagen fibrils displayed a unimodal distribution. Both collagen I and collagen III increased after treatment with riboflavin and UVA light irradiation at 45 mW/cm2. The data indicate that in rabbits, conjunctival crosslinking with riboflavin and UVA light at 45 mW/cm2 for 4 min is safe and does not induce ultrastructural alterations of the conjunctival cells. The conjunctival crosslinking with riboflavin and UVA light at 45 mW/cm2 can increase the diameter of collagen fibrils, but the average densities of collagen I and collagen III have no statistical significance.
Does Early Educational Tracking Contribute to Gender Gaps in Test Achievement? A Cross-Country Assessment

Abstract On average, boys score higher on math achievement tests and girls score higher in reading; these gaps increase between primary and secondary school. Using PISA, PIRLS, and TIMSS data, we investigate the role of early educational tracking (sorting students into different types of secondary schools at an early age) on gender gaps in test achievement in a cross-country difference-in-differences framework. We find strong evidence that early tracking increases gender differences in reading. For math test scores, we do not find consistent evidence that early tracking contributes to the gender gap.
TaqMan real-time PCR for detection of pathogenic Leptospira spp. in canine clinical samples

Abstract Introduction Canine leptospirosis has always been a differential diagnosis in dogs presenting with clinical signs and blood profiles associated with kidney and/or liver disease. The conventional polymerase chain reaction (PCR) provides diagnoses, but real-time PCR-based tests provide earlier confirmation and determine the severity of infection, especially in the acute stage, allowing early detection for immediate treatment decisions. To our knowledge, real-time PCR has not been routinely adopted for clinical investigation in Malaysia. This study evaluated TaqMan real-time PCR (qPCR) assays diagnosing leptospirosis and compared their applicability to clinical samples from dogs with kidney and/or liver disease against a conventional PCR reference. Material and Methods The qPCR assays were validated using existing leptospiral isolates. Whole blood and urine samples were analysed using a conventional PCR, LipL32(1) and LipL32(2) qPCRs and a microscopic agglutination test. The sensitivity and specificity of the qPCRs were determined. Results The LipL32(1) qPCR assay had more diagnostic value than the LipL32(2) qPCR assay. Further evaluation of this assay revealed that it could detect as low as five DNA copies per reaction with high specificity for the tested leptospiral strains. No cross-amplification was observed with other organisms. Analysing the clinical samples, the LipL32(1) qPCR assay had 100.0% sensitivity and >75.0% specificity. Conclusion The LipL32(1) qPCR assay is sensitive, specific and has the potential to be applied in future studies.
Effects of Punica granatum L. peel extract supplementation on body weight, cardiac function, and haematological and biochemical parameters in an animal model of metabolic syndrome

Abstract Introduction Metabolic syndrome (MetS) is a cluster of pathological conditions well described in humans but still investigated insufficiently in animals. A novel approach in its management is the utilisation of nutrients from natural sources. Recent studies suggested that phenolic compounds from pomegranate peel could be a promising dietary intervention for MetS. This study evaluated the potency of polyphenol-rich pomegranate peel extract (EPP) in mitigating some MetS components in an animal model. Material and Methods Zucker diabetic fatty rats (with an fa/fa missense mutation in the Lepr leptin receptor gene) and their healthy counterparts (fa/+) as controls were fed a high-calorie diet to induce MetS and supplemented with EPP at two doses: 100 mg/kg body weight (b.w.) and 200 mg/kg b.w. The extract was administered for eight weeks. The rats’ body weights were monitored twice per week, and blood samples were taken before EPP administration after four weeks and eight weeks of study. Echocardiography measurement was performed at the beginning and at the end of the study. Results The extract restrained the dynamic of weight gain. A cardioprotective effect of the highest dose of EPP supplementation was manifested in a relative decrease in heart rate and improved mid-fractional shortening, representing myocardial contractility. No improvement in fasting blood glucose or lipid profile was observed. Conclusion Pomegranate peel extract possesses beneficial health properties that could be useful in dietary intervention in MetS. However, its bioavailability still requires further investigation in clinical trials in humans and animals suffering from endocrine and metabolic disorders.
Prevalence of the blaCTX-M and blaTEM genes among extended-spectrum beta lactamase–producing Escherichia coli isolated from broiler chickens in Indonesia

Abstract Introduction Infections of humans and animals by multidrug resistant bacteria are increasing because of the inappropriate use of antibiotics. Disease management may be more challenging if Escherichia coli produce extended-spectrum beta-lactamase (ESBL), which could cause resistance to aztreonam and third-generation cephalosporins. This study was aimed at determining the prevalence of the blaCTX-M and blaTEM genes among ESBL-producing E. coli isolated from broiler chickens in Indonesia. Material and Methods A total of 115 broiler cloacal swab samples were obtained from 22 farms and studied for the presence of E. coli. The isolates were identified using approved standard methods and were purified on eosin methylene blue agar media. The E. coli isolates were subjected to sensitivity testing using beta-lactam antibiotics, and ESBL production was confirmed by a double-disc synergy test. The presence of the blaCTX-M and blaTEM genes was identified using a PCR. Results It was found that 99/115 (86.1%) of the isolated E. coli were resistant to beta-lactam antibiotics and 34/115 (29.6%) of them were phenotypically detected to be ESBL producers. Of the 34 isolates that were confirmed ESBL producers, 32/34 (94.1%) of them harboured the blaCTX-M and 13/34 (38.2%) the blaTEM genes. The blaCTX-M and blaTEM genes were detected together in 12/34 (35.3%) isolates. Conclusion This study discovered that broiler chickens are possible reservoirs of ESBL-producing E. coli that may infect humans. Thus, a committed public health education campaign is recommended in order to mitigate the potential threat to human health.
Comment

This insightful paper by Eisfeldt, Falato, and Xiaolan introduces the concept of “human capitalists,” employees below the C-suite who receive a significant share of their pay as equity-based compensation. By collecting data on reserved shares across firms, this study documents the importance of this phenomenon in the corporate manufacturing sector. It then develops a theoretical equilibrium model to organize the correct income and value-added accounting. Finally, it argues that acknowledging the existence human capitalists can change our view on two key macroeconomic questions: (i) the recent decline in the aggregate labor share is smaller than previously estimated and (ii) the degree of capital-skill complementarity in aggregate technology is stronger than we thought. This is a paper of general interest because its findings are relevant for a number of diverse literatures in economics: the measurement of workers’ compensation, beyond wages; the prevalence of incentive-based pay and the design optimal labor contracts; the dynamics of the aggregate labor share; patterns of capital-labor substitution in the aggregate economy; intangible capital; and the nature of idiosyncratic labor market (or, as it is called in finance, background) risk. The paper provides new data, new facts, and new insights that affect all these research areas where an accurate measurement of worker compensation, and how it relates to the marginal product of labor, is crucial. I will organize my comments in five parts: (i) quick model recap, (ii) measurement of the skilled labor share of income, (iii) model identification,
Retinoblastoma protein activity revealed by CRISPRi study of divergent Rbf1 and Rbf2 paralogs

Retinoblastoma tumor suppressor proteins regulate the key transition from G1 to S phase of the cell cycle. The mammalian Rb family comprises Rb, p107, and p130, with overlapping and unique roles in gene regulation. Drosophila experienced an independent gene duplication event, leading to the Rbf1 and Rbf2 paralogs. To uncover the significance of paralogy in the Rb family, we used CRISPRi. We engineered dCas9 fusions to Rbf1 and Rbf2, and deployed them to gene promoters in developing Drosophila tissue to study their relative impacts on gene expression. On some genes, both Rbf1 and Rbf2 mediate potent repression, in a highly distance-dependent manner. In other cases, the two proteins have different effects on phenotype and gene expression, indicating different functional potential. In a direct comparison of Rb activity on endogenous genes and transiently transfected reporters, we found that only qualitative, but not key quantitative aspects of repression were conserved, indicating that the native chromatin environment generates context-specific effects of Rb activity. Our study uncovers the complexity of Rb-mediated transcriptional regulation in a living organism, which is clearly impacted by the different promoter landscapes and the evolution of the Rb proteins themselves.
TREM2 promotes glioma progression and angiogenesis mediated by microglia/brain macrophages

TREM2, a myeloid cell-specific signaling molecule, controls essential functions of microglia and impacts on the pathogenesis of Alzheimer’s disease and other neurodegenerative disorders. TREM2 is also highly expressed in tumor-associated macrophages and plays detrimental roles in an experimental mouse sarcoma model. Here we studied whether TREM2 influences glioma progression. We found a sex- dependent effect of TREM2: the glioma volume is significantly attenuated in TREM2- deficient male but not female mice injected with GL261-EGFP glioma cells. The accumulation of glioma-associated microglia/macrophages (GAMs) and vascularization is reduced in male TREM2-deficient mice. A transcriptomic analysis of glioma tissue revealed that TREM2 deficiency suppresses angiogenic genes and MHC clusters. In an organotypic slice model devoid of functional vascularization, the tumor size was not affected by TREM2-deficiency. In human resection samples from glioblastoma, TREM2 is upregulated in GAMs. Based on the TCGA and CGGA databases, the TREM2 expression levels are negatively correlated with survival. Thus, the TREM2-dependent crosstalk between GAMs and the vasculature formation promotes glioma growth. Graphic abstract TREM2-dependent crosstalk between glioma-associated microglia/macrophages and the vasculature formation promotes glioma growth in male glioma mouse model. Created with BioRender.com
De novo assembly of the whole genome of Moth bean (Vigna aconitifolia), an underutilized Vigna species of India

As a fast-growing legume species, moth bean (Vigna aconitifolia) has a unique habit of sustaining in conditions of higher temperatures and drought. This grain legume is also valued for it seeds which have one of the highest contents of proteins amongst all grain legumes. This plant can be a rich source of genomic resources, which can be applied to improve abiotic stress response in allied grain legumes and also help understand the biological processes governing their overall development. Here we generate a de novo genome assembly of Vigna aconitifolia using PacBio High-Fidelity reads and Hi-C sequencing data, with a total size of 409 Mb and contig N50 of more than 30Mb. We also annotated the genome for repeat sequences, found that the moth bean genome comprises of about 54% of repetitive sequences, and predicted 36950 protein-coding genes. Using the available RNA-Seq data for moth bean, we have developed a differential expression profile for various tissues of moth bean using the whole genome as a reference and identified simple sequence repeats that could be developed into viable molecular markers. This nascent study will provide insight into the identification of agronomically important genes and accelerate the genetic improvement of moth bean as well as other legume crops.