Miracle-dz/UniFAR-FTUs huggingface dataset:
The Computational Challenges of Means Selection Problems: Network Structure of Goal Systems Predicts Human Performance

We study human performance in two classical NP-hard optimization problems: Set Cover and Maximum Coverage. We suggest that Set Cover and Max Coverage are related to means selection problems that arise in human problem-solving and in pursuing multiple goals: The relationship between goals and means is expressed as a bipartite graph where edges between means and goals indicate which means can be used to achieve which goals. While these problems are believed to be computationally intractable in general, they become more tractable when the structure of the network resembles a tree. Thus, our main prediction is that people should perform better with goal systems that are more tree-like. We report three behavioral experiments which confirm this prediction. Our results suggest that combinatorial parameters that are instrumental to algorithm design can also be useful for understanding when and why people struggle to choose between multiple means to achieve multiple goals.
Symptoms of Depression in the Postpartum Period: Targeting Maternal Mental Health in the Perinatal Period

Abstract This cross-sectional study aimed to examine the relationship between postpartum depression symptoms, anxiety, and stress during the postpartum period. A total of 101 women were assessed using the Depression, Anxiety and Stress Scale (DASS-21) and the Edinburgh Postnatal Depression Scale (EPDS) within 14 days after delivery. Multivariate regression analysis revealed that paid work, tobacco use, and stress symptoms were significantly associated with a higher incidence of postpartum depression symptoms. These results underscore the importance of comprehensive prenatal care and effective postpartum follow-up to address maternal mental health and prevent adverse outcomes for both mothers and children.
Integrated network pharmacology to investigate the mechanism of Salvia miltiorrhiza Bunge in the treatment of myocardial infarction

Salvia miltiorrhiza Bunge is a natural drug for treating myocardial infarction (MI). However, the targets and mechanisms of S. miltiorrhiza Bunge in the treatment of MI are yet to be elucidated. Traditional Chinese medicine systems pharmacology (TCMSP) data were used to screen out chemical constituents, and UniProt was used to predict relevant targets. Disease targets were obtained from the Online Mendelian Inheritance in Man and GeneCards databases. We used the STRING platform to build a protein–protein interaction network and used Cytoscape_v3. 8.1 software to make a Drug–Ingredients–Gene Symbols–Disease network map. The Metascape database was used to perform gene ontology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses for drug–disease overlapping gene symbols. The targets identified by network pharmacology were further verified by in vitro and in vivo experiments. Seventy‐five active components of S. miltiorrhiza Bunge were obtained from the TCMSP database, while 370 disease targets and 29 cross‐targets were obtained from the Genecards database. The KEGG pathway enrichment results suggested that the mechanism of S. miltiorrhiza Bunge in the treatment of MI was significantly related to the VEGF signalling pathway. In vitro and in vivo experiments were used to evaluate the reliability of some important active ingredients and targets. S. miltiorrhiza Bunge alleviated the damage to cardiac function, attenuated myocardial fibrosis and protected endothelial cell function by increasing the expression of TGF‐β and VEGFA. S. miltiorrhiza Bunge showed the therapeutic effect of MI by promoting the expression of VEGFA signalling pathway, providing a reliable basis for exploring herbal treatment of MI.
Unique activities of two overlapping PAX6 retinal enhancers

A unique combination of high-resolution imaging and single-cell RNA sequencing in zebrafish reveals cell type-specific activities of developmental eye enhancers. Enhancers play a critical role in development by precisely modulating spatial, temporal, and cell type-specific gene expression. Sequence variants in enhancers have been implicated in diseases; however, establishing the functional consequences of these variants is challenging because of a lack of understanding of precise cell types and developmental stages where the enhancers are normally active. PAX6 is the master regulator of eye development, with a regulatory landscape containing multiple enhancers driving the expression in the eye. Whether these enhancers perform additive, redundant or distinct functions is unknown. Here, we describe the precise cell types and regulatory activity of two PAX6 retinal enhancers, HS5 and NRE. Using a unique combination of live imaging and single-cell RNA sequencing in dual enhancer–reporter zebrafish embryos, we uncover differences in the spatiotemporal activity of these enhancers. Our results show that although overlapping, these enhancers have distinct activities in different cell types and therefore likely nonredundant functions. This work demonstrates that unique cell type-specific activities can be uncovered for apparently similar enhancers when investigated at high resolution in vivo.
Sellithyridinae, terebratulidae du crétacé d'Europe occidentale : dynamique des populations, systématique et évolution

Etude des terebratules biplissees du cretace d'Europe de l'Ouest. Apres avoir aborde le probleme de la definition de l'espece en paleontologie, on s'interesse a la variabilite specifique dans le temps et dans l'espace. Pour cela, on etudie la morphologie de la coquille des sellithyridinae selon une optique populationniste visant a cerner les modifications ontogenetiques et aussi la variabilite au sein de chaque population. Des comparaisons entre populations sont realisees grâce aux outils statistiques tels que analyse factorielle et analyse discriminante. Pour une meilleure definition des especes, on prend en compte des aspects microstructuraux de la coquille. Enfin on presente une revision systematique des sellithyridinae
Expression, activity, and consequences of biochemical inhibition of α- and β-glucosidases in different life stages of Culex quinquefasciatus

Mosquitoes have a wide range of digestive enzymes that enable them to utilize requisite blood and sugar meals for survival and reproduction. Sugar meals, typically derived from plant sources, are critical to maintain energy in both male and female mosquitoes, whereas blood meals are taken only by females to complete oogenesis. Enzymes involved in sugar digestion have been the subject of study for decades but have been limited to a relatively narrow range of mosquito species. The southern house mosquito, Culex quinquefasciatus, is of public health importance and seldom considered in these types of studies outside of topics related to Bacillus sphaericus, a biocontrol agent that requires interaction with a specific gut-associated α-glucosidase. Here we sought to describe the nature of α-glucosidases and unexplored β-glucosidases that may aid Cx. quinquefasciatus larvae in acquiring nutrients from cellulosic sources in their aquatic habitats. Consistent with our hypothesis, we found both α- and β-glucosidase activity in larvae. Interestingly, β-glucosidase activity all but disappeared at the pupal stage and remained low in adults, while α-glucosidase activity remained in the pupal stage and then exceeded larval activity by approximately 1.5-fold. The expression patterns of the putative α- and β-glucosidase genes chosen did not consistently align with observed enzyme activities. When the α-glucosidase inhibitor acarbose was administered to adults, mortality was seen especially in males but also in females after two days of exposure and key energetic storage molecules, glycogen and lipids, were significantly lower than controls. In contrast, administering the β-glucosidase inhibitor conduritol β-epoxide to larvae did not produce mortality even at the highest soluble concentration. Here we provide insights into the importance of α- and β-glucosidases on the survival of Cx. quinquefasciatus in their three mobile life stages.
The use of breast milk iodine concentration in the first week of lactation as a biomarker of iodine status in breast-feeding women

Abstract Breast milk iodine concentration (BMIC) is a promising indicator of iodine status in lactating women. However, there are limited data on its usefulness to reflect maternal iodine deficiency. Therefore, the aim of our study was to assess iodine concentration in breast milk and urine samples in exclusively breast-feeding women. Eligible pregnant women undergoing routine antenatal care in a large hospital in Shaanxi Province, China, were followed up from the third trimester of pregnancy until the first week of lactation. Urine samples (20 ml) were collected during pregnancy and lactation. Iodine concentration in samples was measured based on Sandell–Kolthoff reaction. Breast milk samples (5 ml) were provided during lactation. A receiver operating curve (ROC) was constructed to determine the diagnostic performance of BMIC. An iodine-specific FFQ was completed twice during pregnancy and lactation. A total of 200 women completed the study. The overall median BMIC was 89 μg/l, indicating iodine sufficiency (i.e. BMIC reference range between 60 and 465 μg/l). Women reported similar median urinary iodine concentration (UIC) during pregnancy and lactation (112 and 113 μg/l, respectively), but their iodine status differed – mild-to-moderate iodine deficiency during pregnancy and iodine sufficiency during lactation. The ROC for BMIC using UIC as a reference standard was 0·755 (95 % CI: 0·644, 0·866). In conclusion, this study demonstrated that women were iodine sufficient in the first week of lactation as assessed by UIC, which was consistent with BMIC. These findings suggested that BMIC is a useful biomarker to assess iodine status in lactating women.
X-RAY DIFFRACTION (XRD) ANALYSES OF THAR, SONDA AND METING-JHIMPIR COALFIELDS, SINDH

X-ray powder diffraction (XRD) is an instrumental technique used to identify unknown /various minerals. Rigaku X-ray diffractometer was used to record X-ray intensities scatters of the coal samples, collected from various coalfields of Sindh. Cu (K-alpha) radiations were used as X-ray source. These scatters shows that minerlogically the Sindh coals contain quartz and kaolinite as the dominant mineral phases with subordinate amount of calcite, dolomite, muscovite and illite. These minerals may have significance influence on the boiler of the power plant may also cause environmental degradation by producing emission of SO2, CO2.
Zinc for Infection Prevention in Sickle Cell Anemia (ZIPS): Study Protocol for a Randomized Placebo-Controlled Trial in Ugandan children with Sickle Cell Anemia

Background Sickle cell anemia (SCA) is the most common inherited hemoglobinopathy worldwide. Infection is a major cause of illness and death in children with SCA, especially in sub Saharan Africa where an estimated 50-90% of affected children die before their �fth birthday. Interventions to reduce the incidence and severity of infections are needed urgently. A high proportion of adults and children with SCA are zinc-de�cient, and zinc de�ciency leads to impaired immunity and an increased risk of infection. Zinc supplementation has been shown to decrease the risk of infection in adolescents and adults, but there is no data on the effectiveness of zinc for prevention of infection in children <5 years of age with SCA. Methods/Design The study will be a randomized, placebo-controlled, double-blind clinical trial in which 250 Ugandan children 1.00-4.99 years of age with SCA will receive daily zinc supplementation (10 mg oral dispersible tablet) or identical placebo for 12 months. Discussion If this trial shows a reduction in severe or invasive infection incidence, it would be the basis for a multi-site, multi-country clinical trial to assess real-world safety and e�cacy of zinc in African children with SCA. Since zinc is safe, inexpensive, and easy to administer, this trial has the potential to improve the health of hundreds of thousands of African children with SCA through reduction of infection-related morbidity and mortality. Trial Registration
Risk factors for Clostridioides difficile infection and colonization among patients admitted to an intensive care unit in Shanghai, China

Background: Clostridioides difficile is considered the main pathogen responsible for hospital-acquired infections. This prospective study determined the prevalence, molecular epidemiological characteristics, and risk factors for C. difficile infection (CDI) and C. difficile colonization (CDC) among patients in the intensive care unit (ICU) of a large-scale tertiary hospital in China, with the aim of providing strategies for efficient CDI and CDC prevention and control. Methods: Stool samples were collected and anaerobically cultured for C. difficile detection. The identified isolates were examined for toxin genes and subjected to multilocus sequence typing. Patients were classified into CDI, CDC, and control groups, and their medical records were analyzed to determine the risk factors for CDI and CDC. Results: Of the 800 patients included in the study, 33 (4.12%) and 25 (3.12%) were identified to have CDI and CDC, respectively. Associations with CDI were found for fever (OR=13.993), metabolic disorder (OR=7.972), and treatment with fluoroquinolone (OR=42.696) or combined antibiotics (OR=2.856). CDC patients were characterized by prolonged hospital stay (OR=1.137), increased number of comorbidities (OR=36.509), respiratory diseases (OR=0.043), and treatment with vancomycin (OR=18.168). Notably, treatment with metronidazole was found to be a protective factor in both groups (CDI: OR=0.042; CDC: OR=0.013). Eighteen sequence types (STs) were identified. In the CDI group, the isolated strains were predominantly toxin A and toxin B positive (A+B+) and the epidemic clone was genotype ST2. In the CDC group, the dominant strains were A+B+ and the epidemic clone was ST81. Conclusions: The prevalences of CDC and CDI in our ICU were relatively high, suggesting the importance of routine screening for acquisition of C. difficile . Future prevention and treatment strategies for CDC and CDI should consider hospital stay, enteral nutrition, underlying comorbidities, and use
Molecular determinants of metazoan tricRNA biogenesis

Mature tRNAs are generated by multiple post-transcriptional processing steps, which can include intron removal. Recently, our laboratory discovered a new class of metazoan circular RNAs formed by ligation of excised tRNA introns; we termed these molecules tRNA intronic circular (tric)RNAs. To investigate the mechanism of tricRNA biogenesis, we generated constructs that replace the native introns of two Drosophila tRNA genes with the Broccoli fluorescent RNA aptamer. Using these reporters, we identified cis-acting elements required for tricRNA formation in both human and fly cells. We observed that disrupting the conserved anticodon-intron base pair dramatically reduces tricRNA levels. Although the integrity of this base pair is necessary for proper splicing, it is not sufficient. Furthermore, we found that strengthening weak base pairs in the pre-tRNA also impairs tricRNA production. We also used the reporters to identify trans-acting tricRNA processing factors. We found that several known tRNA processing factors, such as RtcB ligase and components of the TSEN endonuclease complex, are involved in tricRNA biogenesis. Depletion of these factors inhibits tRNA intron circularization. Furthermore, we observed that depletion of Clipper endonuclease results in increased tricRNA levels. In summary, our work characterizes the major players in Drosophila tricRNA biogenesis.
Improving homology‐directed repair by small molecule agents for genetic engineering in unconventional yeast?—Learning from the engineering of mammalian systems

Abstract The ability to precisely edit genomes by deleting or adding genetic information enables the study of biological functions and the building of efficient cell factories. In many unconventional yeasts, such as those promising new hosts for cell factory design but also human pathogenic yeasts and food spoilers, this progress has been limited by the fact that most yeasts favour non‐homologous end joining (NHEJ) over homologous recombination (HR) as a DNA repair mechanism, impairing genetic access to these hosts. In mammalian cells, small molecules that either inhibit proteins involved in NHEJ, enhance protein function in HR, or arrest the cell cycle in HR‐dominant phases are regarded as promising agents for the simple and transient increase of HR‐mediated genome editing without the need for a priori host engineering. Only a few of these chemicals have been applied to the engineering of yeast, although the targeted proteins are mostly conserved, making chemical agents a yet‐underexplored area for enhancing yeast engineering. Here, we consolidate knowledge of the available small molecules that have been used to improve HR efficiency in mammalian cells and the few ones that have been used in yeast. We include available high‐throughput‐compatible NHEJ/HR quantification assays that could be used to screen for and isolate yeast‐specific inhibitors.
Adaversarial Issue of Machine Learning Approaches Applied in Smart Grid: A Survey

—The machine learning (ML) sees an increasing prevalence of being used in the internet-of-things enabled smart grid. However, the trustworthiness of ML is a severe issue that must be addressed to accommodate the trend of ML-based smart grid applications (MLsgAPPs). The adversarial distortion injected into the power signal will greatly affect the system’s normal control and operation. Therefore, it is imperative to conduct vulnerability assessment for MLsgAPPs applied in the context of safety-critical power systems. In this paper, we provide a comprehensive review of the recent progress in designing attack and defense methods for MLsgAPPs. Unlike the traditional survey about ML security, this is the ﬁrst review work about the security of MLsgAPPs that focuses on the characteristics of power systems. The survey is organized from the aspects of adversarial assumptions, targeted applications, evaluation metrics, defending approaches, physics-related constraints, and applied datasets. We also highlight future directions on this topic to encourage more researchers to conduct further research on adversarial attacks and defending approaches for MLsgAPPs.
Physics-Informed DeepMRI: Bridging the Gap from Heat Diffusion to k-Space Interpolation

In the field of parallel imaging (PI), alongside image-domain regularization methods, substantial research has been dedicated to exploring $k$-space interpolation. However, the interpretability of these methods remains an unresolved issue. Furthermore, these approaches currently face acceleration limitations that are comparable to those experienced by image-domain methods. In order to enhance interpretability and overcome the acceleration limitations, this paper introduces an interpretable framework that unifies both $k$-space interpolation techniques and image-domain methods, grounded in the physical principles of heat diffusion equations. Building upon this foundational framework, a novel $k$-space interpolation method is proposed. Specifically, we model the process of high-frequency information attenuation in $k$-space as a heat diffusion equation, while the effort to reconstruct high-frequency information from low-frequency regions can be conceptualized as a reverse heat equation. However, solving the reverse heat equation poses a challenging inverse problem. To tackle this challenge, we modify the heat equation to align with the principles of magnetic resonance PI physics and employ the score-based generative method to precisely execute the modified reverse heat diffusion. Finally, experimental validation conducted on publicly available datasets demonstrates the superiority of the proposed approach over traditional $k$-space interpolation methods, deep learning-based $k$-space interpolation methods, and conventional diffusion models in terms of reconstruction accuracy, particularly in high-frequency regions.
Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data

Multi-centre colonoscopy images from various medical centres exhibit distinct complicating factors and overlays that impact the image content, contingent on the specific acquisition centre. Existing Deep Segmentation networks struggle to achieve adequate generalizability in such data sets, and the currently available data augmentation methods do not effectively address these sources of data variability. As a solution, we introduce an innovative data augmentation approach centred on interpretability saliency maps, aimed at enhancing the generalizability of Deep Learning models within the realm of multi-centre colonoscopy image segmentation. The proposed augmentation technique demonstrates increased robustness across different segmentation models and domains. Thorough testing on a publicly available multi-centre dataset for polyp detection demonstrates the effectiveness and versatility of our approach, which is observed both in quantitative and qualitative results. The code is publicly available at: https://github.com/nki-radiology/interpretability_augmentation
Spherical actions on locally factorial Fano varieties of dimension $\leq 4$ and rank $\leq 2$

We obtain the exhaustive list of 337 faithful spherical actions of rank two or less on locally factorial Fano manifolds of dimension four or less. As a preliminary step, we determine the explicit list of spherical homogeneous spaces of dimension four or less, together with their combinatorial data. Then we classify the possible locally factorial $G/H$-reflexive polytopes for each such spherical homogeneous space $G/H$. From the combinatorial data gathered in this article, one can easily read off the Picard rank (even the Picard group), Fano index, anticanonical volume of the underlying locally factorial Fano variety, etc.
High Performance Networking Layer for Simulation Applications

Autonomous vehicles are one of the most popular and also fast-growing technologies in the world. As we go further, there are still a lot of challenges that are unsolved and may cause problems in the future when it comes to testing in real world. Simulations on the other hand have always had a huge impact in the fields of science, technology, physics, etc. The simulation also powers real-world Autonomous Vehicles nowadays. Therefore, We have built an Autonomous Vehicle Simulation Software - called AVIS Engine - that provides tools and features that help develop autonomous vehicles in various environments. AVIS Engine features an advanced input and output system for the vehicle and includes a traffic system and vehicle sensor system which can be communicated using the fast networking system and ROS Bridge.
Gigahertz modulation of a fully dielectric nonlocal metasurface

Nonlocal metasurfaces are currently emerging as advanced tools for the manipulation of electromagnetic radiation, going beyond the widely explored Huygens metasurface concept. Nonetheless, the lack of an unified approach for their fast and efficient tunability still represents a serious challenge to overcome. In this article we report on gigahertz modulation of a dielectric slab-based, nonlocal (i.e. angle-dispersive) metasurface, whose operation relies on the optomechanical coupling with a mechanical wave excited piezoelectrically by a transducer integrated on the same chip. Importantly, the metasurface region is free from any conductive material, thus eliminating optical losses, and making our device of potential interest for delicate environments such as high-power apparatuses or quantum optical systems.