Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network

Background Microbes have dense linkages with human diseases. Balanced microorganisms protect human body against physiological disorders while unbalanced ones may cause diseases. Thus, identification of potential associations between microbes and diseases can contribute to the diagnosis and therapy of various complex diseases. Biological experiments for microbe–disease association (MDA) prediction are expensive, time-consuming, and labor-intensive. Methods We developed a computational MDA prediction method called GPUDMDA by combining graph attention autoencoder, positive-unlabeled learning, and deep neural network. First, GPUDMDA computes disease similarity and microbe similarity matrices by integrating their functional similarity and Gaussian association profile kernel similarity, respectively. Next, it learns the feature representation of each microbe–disease pair using graph attention autoencoder based on the obtained disease similarity and microbe similarity matrices. Third, it selects a few reliable negative MDAs based on positive-unlabeled learning. Finally, it takes the learned MDA features and the selected negative MDAs as inputs and designed a deep neural network to predict potential MDAs. Results GPUDMDA was compared with four state-of-the-art MDA identification models (i.e., MNNMDA, GATMDA, LRLSHMDA, and NTSHMDA) on the HMDAD and Disbiome databases under five-fold cross validations on microbes, diseases, and microbe-disease pairs. Under the three five-fold cross validations, GPUDMDA computed the best AUCs of 0.7121, 0.9454, and 0.9501 on the HMDAD database and 0.8372, 0.8908, and 0.8948 on the Disbiome database, respectively, outperforming the other four MDA prediction methods. Asthma is the most common chronic respiratory condition and affects ~339 million people worldwide. Inflammatory bowel disease is a class of globally chronic intestinal disease widely existed in the gut and gastrointestinal tract and extraintestinal organs of patients. Particularly, inflammatory bowel disease severely affects the growth and development of children. We used the proposed GPUDMDA method and found that Enterobacter hormaechei had potential associations with both asthma and inflammatory bowel disease and need further biological experimental validation. Conclusion The proposed GPUDMDA demonstrated the powerful MDA prediction ability. We anticipate that GPUDMDA helps screen the therapeutic clues for microbe-related diseases.
Multiaxial Fatigue Analysis of Connecting Bolt at High-Speed Train Axle Box under Structural Subharmonic Resonance

Based on the dynamic characteristics of the axle box front cover of high-speed trains in the subharmonic resonance state, the nonlinear single-degree-of-freedom (SDOF) model was proved to be reasonable, and reasons for the ineffectiveness of the common prevention methods for preventing bolt failure were analyzed firstly. Then, dynamic stress of the bolt was simulated by innovatively adopting the linear method based on frequency response analysis. The stress simulation method was verified to be practical under the subharmonic resonance state by analyzing and comparing the experimental and numerical results of the bolted front cover. It was proved that the linear method was accurate enough to simulate the dynamic stress of bolts, which is of great engineering significance. In addition to the transverse resonance stress of bolts caused by drastic vertical vibration of the front cover, the tensile resonance stress at the root of the first engaged thread was too large to be neglected on account of the first-order bending modes of bolts. Next, equivalent stress amplitude of the multiaxial stresses was obtained by means of the octahedral shear stress criterion. Finally, fatigue life of bolts was predicted in terms of S-N curve suitable for bolt fatigue life analysis. It argued that the bolts were prone to multiaxial fatigue failure when the front cover was in subharmonic resonance for more than 26.8 h, and the fatigue life of bolts could be greatly improved when the wheel polygonization was eliminated by shortening the wheel reprofiling interval.
Human Health Risk Assessment of Arsenic and Other Metals in Herbal Products Containing St. John’s Wort in the Metropolitan Area of Mexico City

Consumption of St. John’s wort plant is high worldwide due to its various medicinal properties. However, herbal products containing St. John’s wort may be contaminated with toxic metals. This is often related to contamination of both water and the atmosphere, lack of proper cultivation methods, and inadequate plant storage conditions, as well as a lack of stricter sanitary supervision. A safety assessment of copper (Cu), lead (Pb), cadmium (Cd) and arsenic (As) content in 23 products containing St. John’s wort (pharmaceutical herbal products, food supplements and traditional herbal remedies) sold in the metropolitan area of Mexico City was conducted. The analysis of metals was determined using a graphite-furnace atomic absorption spectrometer. All herbal products were contaminated with Cu, Pb, Cd and As. The pharmaceutical herbal items showed less contamination by metals. The daily human intake (DHI) values for Pb exceeded the permissible limits in the group of traditional herbal remedies. The DHI calculation for As exceeded the permitted intake values for all items in the group of traditional herbal remedies, five food supplements and one pharmaceutical herbal product. The hazard indicator calculation of the non-carcinogenic cumulative risk values for traditional herbal remedies was greater than 1, suggesting a risk to human health.
Working environment of health care professionals - focus on occupational stress.

INTRODUCTION AND OBJECTIVE Healthcare professionals most often encounter occupational stress. The aim of the study was to investigate the working environment of health care professionals with the focus on expression of occupational stress, and oversee the possibilities of stress management and prevention. MATERIAL AND METHODS 326 representatives from five different healthcare institutions were surveyed in Siauliai city, Lithuania. The validated questionnaires HSE Management Standards Indicator Tool and the SF-36 questionnaire were used. RESULTS The study revealed that the most important organizational factors were lack of communication, inappropriate relations with authorities and colleagues, big workload and long working hours, quick decision-making, and manifestations of mobbing. Financial support was reported as one of the main motivators in stress management. The most frequent individual factors were emotional relations with patients and their relatives. The healthcare professionals who experienced stress at work more often felt aches that disturbed their work routine, and their health interfered more their ordinary social activities. The main stress prevention measures are involvement of employees in decision-making, annual interviews with authorities, education, assurance of a safe work environment, and elimination of manifestations of mobbing. CONCLUSIONS More attention must be paid to occupational stress management. It appeared that there is a lack of knowledge by institutions about the models of occupational stress management and internal stress management policy of organization. Therefore, this stimulates the search for measures that could help to change the situation.
Silencing of Glutamine: Fructose-6-Phosphate Aminotransferase Impairs Growth and Development in Sogatella furcifera (Hemiptera: Delphacidae)

Glutamine: fructose-6-phosphate aminotransferase (GFAT), the fourth enzyme in the chitin synthesis pathway, exerts wide-ranging effects on the growth and development of organisms. However, the role of GFAT in Sogatella furcifera remains unknown. In this study, the functional significance of the GFAT gene of S. furcifera was analyzed using a reverse transcription-polymerase chain reaction and RNA interference (RNAi) analyses. The complementary DNA sequence of SfGFAT was 3162 bp in length and contained a 2067 bp open reading frame encoding 688 amino acid residues. Structural domain analysis indicated that the SfGFAT protein consisted of one glutamine aminotransferase class 2 domain and two sugar isomerase domains. Expression profile analysis revealed that SfGFAT was expressed throughout the egg, nymph, and adult phases and was strongly expressed on the first day of each nymph stage and in the integuments of five tissues. RNAi results revealed that SfGFAT gene silencing significantly inhibited the mRNA expression of the target gene and resulted in severe mortality among S. furcifera. In summary, these findings demonstrate that SfGFAT plays a critical role in the development of S. furcifera. Moreover, these results may aid in the development of methods to control the spread of S. furcifera.
Perceived stress and secondary traumatization in social workers during coronavirus disease 2019: The moderating effect of psychological capital and social work supervision

Summary Social workers have had a pivotal role in handling the challenges faced by people dealing with the coronavirus disease 2019 (COVID-19) pandemic. Supporting clients who have undergone traumatic experiences during a global pandemic may increase the risk of experiencing secondary traumatic stress. This study examined two protective factors that may be key in the association between stress and social workers’ secondary traumatic stress: Psychological capital (internal protective factor) and satisfaction with supervision (external factor). The study sample included 104 Israeli social workers who worked in their profession during the first year of the COVID-19 pandemic. A regression-based path analysis was conducted to test the moderation model with the PROCESS software. Findings Self-efficacy significantly moderated the association between perceived stress and intrusion; increasing self-efficacy decreases perceived stress's effect on intrusion. Although no significant moderating effect was found for the existence of supervision, the interaction between perceived stress and satisfaction with supervision was significant in predicting secondary trauma. Applications Social workers’ unions must work to improve the quality of supervision and raise awareness of the importance of supervision in general and particularly during times of crisis. Manageable workloads, a reasonable balance between work and home, and verbal and financial encouragement to seek professional psychological assistance would all be to the advantage of social workers at risk for secondary trauma.
Cell-type expression and activation by light of neuropsins in the developing and mature Xenopus retina

Photosensitive opsins detect light and perform image- or nonimage-forming tasks. Opsins such as the “classical” visual opsins and melanopsin are well studied. However, the retinal expression and functions of a novel family of neuropsins are poorly understood. We explored the developmental time-course and cell-type specificity of neuropsin (opn5, 6a, 6b, and 8) expression in Xenopus laevis by in situ hybridization and immunohistochemistry. We compared the Xenopus results with publicly available single cell RNA sequencing (scRNA-seq) data from zebrafish, chicken, and mouse. Additionally, we analyzed light-activation of neuropsin-expressing cells through induction of c-fos mRNA. opn5 and opn8 expression begins at stage 37/38 when the retinal circuits begin to be activated. Once retinal circuits connect to the brain, opn5 mRNA is distributed across multiple retinal cell types, including bipolar (~70%–75%), amacrine (~10%), and retinal ganglion (~20%) cells, with opn8 present in amacrine (~70%) and retinal ganglion (~30%) cells. opn6a and opn6b mRNAs emerge in newborn-photoreceptors (stage 35), and are colocalized in rods and cones by stage 37/38. Interestingly, in the mature larval retina (stage 43/44), opn6a and opn6b mRNAs become preferentially localized to rods and cones, respectively, while newborn photoreceptors bordering the proliferative ciliary marginal zone express both genes. In zebrafish, opn6a and opn6b are also expressed in photoreceptors, while Müller glia and amacrine cells express opn8c. Most neuropsin-expressing retinal ganglion cells display c-fos expression in response to light, as do over half of the neuropsin-expressing interneurons. This study gave a better understanding of retinal neuropsin-expressing cells, their developmental onset, and light activation.
Calibration and adaptation of the NDICEA model to reduced tillage systems: Final-report of the Tilman CORE Organic II project. Work package 5.2.

The NDICEA model was used to simulate and evaluate field trials, designed to improve organic cropping system by using reduced tillage and green manures. The model can help to assess whether nitrogen shortages are likely to occur, and to evaluate the effect of green manure and reduced tillage conditions on nitrogen dynamics and soil organic matter pools. To investigate the effects of tillage and nutrient management on N cycling and soil organic matter pools using the model NDICEA for different experimental sites across Europe. In addition adaptations to the NDICEA model are proposed to cover the effects of reduced tillage in these computer simulations.
Perceptional and actional enrichment for metaphor detection with sensorimotor norms

Understanding the nature of meaning and its extensions (with metaphor as one typical kind) has been one core issue in figurative language study since Aristotle’s time. This research takes a computational cognitive perspective to model metaphor based on the assumption that meaning is perceptual, embodied, and encyclopedic. We model word meaning representation for metaphor detection with embodiment information obtained from behavioral experiments. Our work is the first attempt to incorporate sensorimotor knowledge into neural networks for metaphor detection, and demonstrates superiority, consistency, and interpretability compared to peer systems based on two general datasets. In addition, with cross-sectional analysis of different feature schemas, our results suggest that metaphor, as a device of cognitive conceptualization, can be ‘learned’ from the perceptual and actional information independent of several more explicit levels of linguistic representation. The access to such knowledge allows us to probe further into word meaning mapping tendencies relevant to our conceptualization and reaction to the physical world.
Efficient N:M Sparse DNN Training Using Algorithm, Architecture, and Dataflow Co-Design

Sparse training is one of the promising techniques to reduce the computational cost of deep neural networks (DNNs) while retaining high accuracy. In particular, N:M fine-grained structured sparsity, where only <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> out of consecutive <inline-formula> <tex-math notation="LaTeX">${M}$ </tex-math></inline-formula> elements can be nonzero, has attracted attention due to its hardware-friendly pattern and capability of achieving a high sparse ratio. However, the potential to accelerate N:M sparse DNN training has not been fully exploited, and there is a lack of efficient hardware supporting N:M sparse training. To tackle these challenges, this article presents a computation-efficient training scheme for N:M sparse DNNs using algorithm, architecture, and dataflow co-design. At the algorithm level, a bidirectional weight pruning method, dubbed BDWP, is proposed to leverage the N:M sparsity of weights during both forward and backward passes of DNN training, which can significantly reduce the computational cost while maintaining model accuracy. At the architecture level, a sparse accelerator for DNN training, namely, SAT, is developed to neatly support both the regular dense operations and the computation-efficient N:M sparse operations. At the dataflow level, multiple optimization methods ranging from interleave mapping, pregeneration of N:M sparse weights, and offline scheduling, are proposed to boost the computational efficiency of SAT. Finally, the effectiveness of our training scheme is evaluated on a Xilinx VCU1525 FPGA card using various DNN models (ResNet9, ViT, VGG19, ResNet18, and ResNet50) and datasets (CIFAR-10, CIFAR-100, Tiny ImageNet, and ImageNet). Experimental results show the SAT accelerator with the BDWP sparse training method under 2:8 sparse ratio achieves an average speedup of <inline-formula> <tex-math notation="LaTeX">$1.75\times $ </tex-math></inline-formula> over that with the dense training, accompanied by a negligible accuracy loss of 0.56% on average. Furthermore, our proposed training scheme significantly improves the training throughput by <inline-formula> <tex-math notation="LaTeX">$2.97\times $ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$25.22\times $ </tex-math></inline-formula> and the energy efficiency by <inline-formula> <tex-math notation="LaTeX">$1.36\times $ </tex-math></inline-formula>–<inline-formula> <tex-math notation="LaTeX">$3.58\times $ </tex-math></inline-formula> over prior FPGA-based accelerators.
Controlled g-frames and their dual in Hilbert $C^{\ast}-$modules

In this paper we give some new results for controlled g-frames and controlled dual g-frames in Hilbert $C^*$-modules. First, we talk about controlled g-frame characterisation and find certain conditions that are equal to them.Then, we explain the purpose controlled dual g-frames and controlled dual g-frames operator and discuss some of their characteristics.
Inequalities in the home learning environment during the pandemic: a closer look at Syrian refugee children’s home learning environment in Türkiye prior to COVID-19

ABSTRACT The home learning environment of children became critical during the COVID-19 school closures, and already-existing deprivations of children increased inequalities in access to education during the COVID crisis. This study documents the home learning environment for the Turkish host community and Syrian refugee children in the pre-pandemic year. In order to ac hieve this end, a composite home learning environment (HLEQI) is calculated using the Demographic Health Survey (DHS) in Türkiye, which includes a sample of Syrian children. This study reveals that Syrian children were already burdened with disadvantages regarding their home learning environment quality, with the average HLEQI calculated for Turkish children as 61.7% and Syrian children at 36.5%. Moreover, when examining the individual components of this composite index, our study reveals substantial gaps in the supportive home learning environment for both Turkish and Syrian children, with the latter facing even greater challenges. These gaps span across various dimensions of the composite index, encompassing aspects such as access to remote learning infrastructure, adequate study space at home, and quality interaction with adults. The study underscores the need for targeted interventions to address these disparities and ensure an equitable learning environment for all children, regardless of their background or circumstances.
Increased Heat Pain Tolerance but Hyperalgesia to Tonic Inflammatory Pain in the CRND8 Mouse Model of Alzheimer’s Disease

Background: The effects of Alzheimer’s disease (AD) pathology on the experience of pain are poorly understood. Objective: To understand the pathophysiological mechanisms underlying pain sensory transmission in the transgenic mouse model of AD, CRND8. Methods: We explored AD-related pathology in the spinal cord and dorsal root ganglia of 18-week-old female CRND8 mice. We assessed nociceptive responses to both acute heat stimuli and persistent inflammatory pain in CRND8 mice and non-transgenic (non-Tg) littermates. In addition, we searched for differences in biochemical correlates of inflammatory pain between CRND8 and non-Tg mice. Finally, we investigated the excitability of dorsal horn noc iceptive neurons in spinal cord slices from CRND8 and non-Tg mice. Results: We demonstrated the presence of intracellular AD-like pathology in the spinal cord and in the dorsal root ganglia nociceptive sensory neurons of CRND8 mice. We found that CRND8 mice had a reduced susceptibility to acute noxious heat stimuli and an increased sensitivity to tonic inflammatory pain. Tonic inflammatory pain correlated with a lack of induction of pro-opiomelanocortin in the spinal cord of CRND8 mice as compared to non-Tg mice. Electrophysiological recording in acute spinal cord slice preparations indicated an increased probability of glutamate release at the membrane of dorsal horn nociceptive neurons in CRND8 mice. Conclusion: This study suggests that an increased thermal tolerance and a facilitation of nociception by peripheral inflammation can coexist in AD.
Correlation between Microvessel Density Based on CD31 Immunohistochemical Expression and Clinicopathology of Invasive Breast Carcinoma

Background Breast carcinoma is the most common malignancy in women worldwide. Tumor size, metastases, lymph node involvement (KGB), stage and histopathological grade are significant prognostic factors in invasive breast carcinoma. Microvessel density (MVD) assessment is used to measure angiogenesis which helps predict tumor behavior and the effect of antiangiogenic therapy. MVD is a quantitative calculation of intratumoral capillary blood vessels which reflects the results of the process of angiogenesis. The aim of this study was to analyze the relationship between MVD based on CD31 immunohistochemical expression and the clinicopathology of invasive breast carcinoma. Method Cross sectional analytic study with 42 samples diagnosed with invasive breast carcinoma at H. Adam Malik General Hospital Medan. MVD is the number of small blood vessels in terms of size and diameter (arterioles and venules) with a round lumen that is positively stained with CD31 at 10 large visual fields, categorized as low if <45 blood vessels/10 LPB and high if ≥45 blood vessels/10 LPB. The relationship between MVD and several clinicopathological parameters was analyzed using the Chi-Square, Fisher's Exact and Mann-Whitney tests. Results There was a significant relationship between tumor size (p=0.029), metastasis (p=0.014), stage (p=0.002), histopathological grade (p=0.0043), LVI (p=0.002), TILs (p=0.007). Large tumor size, metastases, high histopathological stage and grade, positive LVI and high TILs were significantly associated with MVD. However, there was no significant relationship between KGB involvement (p=0.570) and MVD. Conclusion MVD is significantly related to tumor size, metastases, stage, histopathological grade, LVI and TILs, and not significantly related to lymph node involvement. MVD plays a role in the angiogenesis of invasive breast carcinoma clinicopathology.
Efficient Personal-Health-Records Sharing in Internet of Medical Things Using Searchable Symmetric Encryption, Blockchain, and IPFS

Secure storage and sharing of Personal Health Records (PHRs) in Internet of Medical Things (IoMT) is one of the significant challenges in the healthcare ecosystem. Due to the high value of personal health information, PHRs are one of the favourite targets of cyber attackers worldwide. Over the years, many solutions have been proposed; however, most solutions are inefficient for practical applications. For instance, several existing schemes rely on the bilinear pairings, which incur high computational costs. To mitigate these issues, we propose a novel PHR-sharing scheme that is dynamic, efficient, and practical. Specifically, we combine searchable symmetric encryption, blockchain technology and a decentralized storage system, known as Inter-Planetary File System (IPFS) to guarantee confidentiality of PHRs, verifiability of search results, and forward security. Moreover, we provide formal security proofs for the proposed scheme. Finally, we have conducted extensive test-bed experiments and the results demonstrate that the proposed scheme can be used in practical scenarios related to IoMT environment.