Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-Term Hydrological Forecast Using Artificial Neural Network Models with Different Combinations and Spatial Representations of Hydrometeorological Inputs

In hydrological modelling, artificial neural network (ANN) models have been popular in the scientific community for at least two decades. The current paper focuses on short-term streamflow forecasting, 1 to 7 days ahead, using an ANN model in two northeastern American watersheds, the Androscoggin and Susquehanna. A virtual modelling environment is implemented, where data used to train and validate the ANN model were generated using a deterministic distributed model over 16 summers (2000–2015). To examine how input variables affect forecast accuracy, we compared streamflow forecasts from the ANN model using four different sets of inputs characterizing the watershed state—surface soil moisture, deep soil moisture, observed streamflow the day before the forecast, and surface soil moisture along with antecedent observed streamflow. We found that the best choice of inputs consists of combining surface soil moisture with observed streamflow for the two watersheds under study. Moreover, to examine how the spatial distribution of input variables affects forecast accuracy, we compared streamflow forecasts from the ANN using surface soil moisture at three spatial distributions—global, fully distributed, and single pixel-based—for the Androscoggin watershed. We show that model performance was similar for both the global and fully distributed representation of soil moisture; however, both models surpass the single pixel-based models. Future work includes evaluating the developed ANN model with real observations, quantified in situ or remotely sensed.
Meta-Analysis of Common and Differential Transcriptomic Responses to Biotic and Abiotic Stresses in Arabidopsis thaliana

Environmental stresses adversely affect crop growth and yield, resulting in major losses to plants. These stresses occur simultaneously in nature, and we therefore conducted a meta-analysis in this study to identify differential and shared genes, pathways, and transcriptomic mechanisms involved in Arabidopsis response to biotic and abiotic stresses. The results showed a total of 436/21 significant up-/downregulated differentially expressed genes (DEGs) in response to biotic stresses, while 476 and 71 significant DEGs were respectively up- and downregulated in response to abiotic stresses in Arabidopsis thaliana. In addition, 21 DEGs (2.09%) were commonly regulated in response to biotic and abiotic stresses. Except for WRKY45 and ATXTH22, which were respectively up-/down- and down-/upregulated in response to biotic and abiotic stresses, other common DEGs were upregulated in response to all biotic and abiotic treatments. Moreover, the transcription factors (TFs) bHLH, MYB, and WRKY were the common TFs in response to biotic and abiotic stresses. In addition, ath-miR414 and ath-miR5658 were identified to be commonly expressed in response to both biotic and abiotic stresses. The identified common genes and pathways during biotic and abiotic stresses may provide potential candidate targets for the development of stress resistance breeding programs and for the genetic manipulation of crop plants.
A Physiological Perspective on Treadmill and Sit-to-Stand Workstations

Active workstations, such as treadmill and sit-to-stand workstations, enable office employees to break prolonged sitting with bouts of light-intensity walking and/or standing. Compared with sitting, walking and/or standing accumulated during the workday using these workstations will increase muscle contractions, which may influence blood flow, energy expenditure, metabolism, musculoskeletal health, and brain function. Physiological responses when using treadmill and sit-to-stand workstations may vary due to differences in muscle contraction type (dynamic vs. static) and may thus affect cardio-metabolic and musculoskeletal health and brain function in different ways.
Selective Loss of MATR3 in Spinal Interneurons, Upper Motor Neurons and Hippocampal CA1 Neurons in a MATR3 S85C Knock-In Mouse Model of Amyotrophic Lateral Sclerosis

Simple Summary Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease affecting the motor neurons in the brain and spinal cord. Mutations in the gene Matr3 have been linked to ALS, including the autosomal dominant missense mutation S85C. We previously created a mouse model containing the S85C mutation in the Matr3 gene to understand how it causes ALS. The S85C mice exhibited MATR3 staining loss in selective populations of degenerating neurons, such as Purkinje cells in the cerebellum and α-motor neurons in the lumbar spinal cord. However, studies have shown that neurons other than motor neurons may be involved in contributing to ALS; therefore, we investigated additional neuronal cell types in the spinal cord and brain. Here, we found that MATR3 staining is selectively reduced in interneurons and α-motor neurons of the cervical and thoracic regions of the spinal cord, as well as in subsets of upper motor neurons and hippocampal neurons. These neurons did not exhibit cell body loss; however, how the MATR3 loss affects neuronal function remains to be determined. Overall, these findings demonstrate that the MATR3 S85C mutation affects other neuronal types of the brain and spinal cord in addition to motor neurons, suggesting that these additional neuronal types are involved in ALS pathogenesis. Abstract The neuropathological hallmark of amyotrophic lateral sclerosis (ALS) is motor neuron degeneration in the spinal cord and cortex. Accumulating studies report that other neurons in the central nervous system (CNS) are also affected in ALS. Mutations in Matr3, which encodes a nuclear matrix protein involved in RNA splicing, have been linked to ALS. Previously, we generated a MATR3 S85C knock-in (KI) mouse model that recapitulates early-stage features of ALS. We reported that MATR3 S85C KI mice exhibit defects in lumbar spinal cord motor neurons and in cerebellar Purkinje cells, which are associated with reduced MATR3 immunoreactivity. Here, we show that neurons in various other regions of the CNS are affected in MATR3 S85C KI mice. Using histological analyses, we found selective loss of MATR3 staining in α-motor neurons, but not γ-motor neurons in the cervical and thoracic spinal cord. Loss of MATR3 was also found in parvalbumin-positive interneurons in the cervical, thoracic and lumbar spinal cord. In addition, we found the loss of MATR3 in subsets of upper motor neurons and hippocampal CA1 neurons. Collectively, our findings suggest that these additional neuronal types may contribute to the disease process in MATR3 S85C KI mice.
Precipitable Water Vapor Retrieval Over Land From GCOM-W/AMSR2 Based on a New Integrated Method

Precipitable water vapor (PWV) is an important parameter reflecting atmospheric water vapor, which plays an important role in the global hydrological cycle. At present, brightness temperatures (Tbs) at frequencies of 18 and 23 GHz from the Advanced Microwave Scanning Radiometer 2 (AMSR2) are commonly applied in PWV data retrieval. Two tools are usually employed to perform the retrieval: physical models and neural networks. In this article, we creatively deduced a more universal physical equation and verified the consistency between theoretical and experimental equations both theoretically and numerically. Then, we fully considered the defects of these two tools and proposed a new integrated method that combines the physical model with a neural network. The Tbs in horizontal and vertical polarizations from AMSR2 and GNSS-derived PWV (GNSS-PWV) data from the SuomiNet global network were used to build the physical model. In the construction of the neural network, we also introduced the related surface parameters from GNSS stations as inputs. Validation results obtained with GNSS-PWV data showed that the accuracy of the test set can reach 2.38 and 2.37 mm in the ascending and descending orbit cases, respectively. Compared with the traditional physical model and neural network model, the improvements of the test set were 24.4% and 17.4% in the ascending orbit and 26.4% and 19.4% in the descending orbit. Radiosonde observation (RAOB) data were applied to carry out another external independent verification, and the accuracy of the test set reached 2.70 and 3.54 mm based on the RAOB data.
The Impact of Estrogens and Their Receptors on Immunity and Inflammation during Infection

Simple Summary Human health is significantly affected by microbial infections. One of the largest determinants of the outcomes of such infections is the host immune response. Too weak of a response can lead to enhanced spread by the pathogen, while an overstimulated response can lead to immune-induced tissue damage. Thus, to effectively treat infected individuals, it is critical to understand the regulators that control inflammatory responses. Recently, it has become widely accepted that estrogens, a class of sex hormones, are capable of dramatically altering the responses of host cells to microbes. In this review, we discuss how estrogens change the host immune response, as well as how these changes can alter the outcome of the infection for the individual. Abstract Sex hormones, such as estrogen and testosterone, are steroid compounds with well-characterized effects on the coordination and development of vertebrate reproductive systems. Since their discovery, however, it has become clear that these “sex hormones” also regulate/influence a broad range of biological functions. In this review, we will summarize some current findings on how estrogens interact with and regulate inflammation and immunity. Specifically, we will focus on describing the mechanisms by which estrogens alter immune pathway activation, the impact of these changes during infection and the development of long-term immunity, and how different types of estrogens and their respective concentrations mediate these outcomes.
The Negative Effects of High Rates of Biochar on Violas Can Be Counteracted with Fertilizer

Increasing costs and environmental issues regarding excessive use of peat moss is impacting the horticultural industry. Biochar is a valuable substrate additive that has the potential to reduce the use of peatmoss in greenhouse production. However, its varying effects on ornamentals requires that individual species and cultivars of crops must be evaluated to determine the threshold for benefits. Viola cornuta is a high value ornamental crop; however, information on how different rates of biochar rates affect productivity and physiology of Viola cultivars in container production is not known. To determine if biochar rates could increase the productivity of Viola, we mixed a peat-based substrate with 10, 25, and 50% (w:w) hardwood biochar in two studies on four cultivars. Without fertilizers, 10 and 25% biochar improved plant biomass, growth, root length, and flowering, but 50% biochar was found to have negative effects on plant growth and flowering. Cultivars varied in their response to biochar rates. When fertilizer was applied in the second experiment, biochar rates did not impact growth parameters or flowering. These results suggest that up to 25% biochar can be used in Viola production without detrimental impacts. However, 50% biochar can be used with the addition of fertilizer without negatively affecting plant growth. Biochar can have a short-term impact on the growth characteristics of Viola plants in container production, but fertilization and growing period of Viola may influence these effects. These results indicate that biochar could be the suitable replacement for peat moss, with up to 50% biochar rate in Viola production reducing the environmental and economic burden for peat moss.
p140Cap Controls Female Fertility in Mice Acting via Glutamatergic Afference on Hypothalamic Gonadotropin-Releasing Hormone Neurons

p140Cap, encoded by the gene SRCIN1 (SRC kinase signaling inhibitor 1), is an adaptor/scaffold protein highly expressed in the mouse brain, participating in several pre- and post-synaptic mechanisms. p140Cap knock-out (KO) female mice show severe hypofertility, delayed puberty onset, altered estrus cycle, reduced ovulation, and defective production of luteinizing hormone and estradiol during proestrus. We investigated the role of p140Cap in the development and maturation of the hypothalamic gonadotropic system. During embryonic development, migration of Gonadotropin-Releasing Hormone (GnRH) neurons from the nasal placode to the forebrain in p140Cap KO mice appeared normal, and young p140Cap KO animals showed a normal number of GnRH-immunoreactive (-ir) neurons. In contrast, adult p140Cap KO mice showed a significant loss of GnRH-ir neurons and a decreased density of GnRH-ir projections in the median eminence, accompanied by reduced levels of GnRH and LH mRNAs in the hypothalamus and pituitary gland, respectively. We examined the number of kisspeptin (KP) neurons in the rostral periventricular region of the third ventricle, the number of KP-ir fibers in the arcuate nucleus, and the number of KP-ir punctae on GnRH neurons but we found no significant changes. Consistently, the responsiveness to exogenous KP in vivo was unchanged, excluding a cell-autonomous defect on the GnRH neurons at the level of KP receptor or its signal transduction. Since glutamatergic signaling in the hypothalamus is critical for both puberty onset and modulation of GnRH secretion, we examined the density of glutamatergic synapses in p140Cap KO mice and observed a significant reduction in the density of VGLUT-ir punctae both in the preoptic area and on GnRH neurons. Our data suggest that the glutamatergic circuitry in the hypothalamus is altered in the absence of p140Cap and is required for female fertility.
Research on the Algorithm to Measure the Pantographic Slipper Abrasion

The digital image processing technique is used in pantographic slipper abrasion measurement.An algorithm is proposed to measure pantographic slipper abrasion.Combing with edge detection,morphologic image processing,Hough transform and clustering,the slipper obrasion thickness is measured from digital images.This algorithm is composed of start points orientation,edge tracking and thickness calculation.The start points coordinates of the upper and lower edges of the slipper are determined by start points orientation.The information of the edges of the abrasive surface of the slipper is got by edge tracking which combines the advantages of the Sobel operator and Canny operator.And the slipper abrasion thickness is computed by thickness calculation which is completed by use of the fixed object-image ratio.The measurement precision is improved with the mean-method.
Expanding the Biological Role of Lipo-Chitooligosaccharides and Chitooligosaccharides in Laccaria bicolor Growth and Development

The role of lipo-chitooligosaccharides (LCOs) as signaling molecules that mediate the establishment of symbiotic relationships between fungi and plants is being redefined. New evidence suggests that the production of these molecular signals may be more of a common trait in fungi than what was previously thought. LCOs affect different aspects of growth and development in fungi. For the ectomycorrhizal forming fungi, Laccaria bicolor, the production and effects of LCOs have always been studied with a symbiotic plant partner; however, there is still no scientific evidence describing the effects that these molecules have on this organism. Here, we explored the physiological, molecular, and metabolomic changes in L. bicolor when grown in the presence of exogenous sulfated and non-sulfated LCOs, as well as the chitooligomers, chitotetraose (CO4), and chitooctaose (CO8). Physiological data from 21 days post-induction showed reduced fungal growth in response to CO and LCO treatments compared to solvent controls. The underlying molecular changes were interrogated by proteomics, which revealed substantial alterations to biological processes related to growth and development. Moreover, metabolite data showed that LCOs and COs caused a downregulation of organic acids, sugars, and fatty acids. At the same time, exposure to LCOs resulted in the overproduction of lactic acid in L. bicolor. Altogether, these results suggest that these signals might be fungistatic compounds and contribute to current research efforts investigating the emerging impacts of these molecules on fungal growth and development.
Risks, Accountability and Technology Thematic Working Paper

Aid agencies, governments, and donors are expanding investment in digitisation of their beneficiary identification and registration systems, and remote and algorithmic control of humanitarian and social protection programmes. They are doing so in ways that may facilitate the move from humanitarian assistance to government provision, and facilitate the delivery of shock-responsive social protection. This paper looks at evidence on the role of digital technologies in the nexus between humanitarian and social assistance, assessing their benefits and risks. We conclude with an exploration of emergent research themes, recommendations for future research in this area, and links with the broader Better Assistance in Crises (BASIC) Research programme themes.
Niedrigauflösende NMR-Spektroskopie zur Bestimmung textiler Parameter / Low resolution NMR-spectroscopy in textile analysis

Es wird gezeigt, daß es mit Hilfe der niedrigauflösenden NMR-Spektroskopie möglich ist, eine Vielzahl von auf naßchemischen Verfahren beruhende Textilanalysen zu ersetzen. So läßt sich die Analyse von Faserstoffzusammensetzungen gegenüber den herkömmlichen Methoden mit der NMR-Spektroskopie auf wenige Minuten verkürzen. Neben dem geringen Zeitaufwand ist von besonderem Vorteil, daß diese Meßmethode gegenüber bestehenden Analysenverfahren ohne Chemikalien auskommt und abgesehen von den Proben selbst keine Abfälle produziert. Erste Versuche zeigen, daß zwischen der Effektivtemperatur von thermisch unterschiedlich behandelten Fasermaterialien und der Kernresonanz ein Zusammenhang besteht.
The First Horse Gut Microbiome Gene Catalog Reveals That Rare Microbiome Ensures Better Cardiovascular Fitness During Endurance Racing

Emerging evidence indicates that the gut microbiome contributes to endurance exercise performance, but the extent of their functional and metabolic potential remains unknown. Using elite endurance horses as a model system for exercise responsiveness, we built the first equine gut microbial gene catalog comprising more than 25 million non-redundant genes representing 4,696 genera spanning 95 phyla. The unprecedented resolution unrevealed functional pathways relevant for both the structure of the microbiome and the host health and recovered 369 novel metagenome-assembled bacterial genomes, providing useful reference for future studies. Integration of microbial and host omic datasets suggested that microbiomes harboring rare species were functionally dissimilar from those enriched in Lachnospiraceae taxa. Moreover, they offered expanded metabolic pathways to fine-tune the cardiovascular capacity through mitochondria-mediated mechanisms. The results identify an associative link between horse endurance capability and its microbiome gene function, laying the basis for nutritional interventions that could benefit endurance athletes.
Design and Implementation of Voltage Source Converter Excitation System to Improve Power System Stability

This paper presents the design of the voltage source converter (VSC) excitation system and an integrated prototype using digital signal processor (DSP) as the core of the excitation controller is developed. Compared with the static excitation systems with thyristor, the VSC excitation system owns one more channel offering positive damping to power system by controlling reactive power of VSC on its ac side, and this approach is approved much faster than field voltage regulation. To design the prototype, the VSC excitation system has to meet the practical condition of the selected synchronous generator (SG) set such as generator capacity, terminal voltage, field voltage and field current. The designed VSC excitation system consists of converters containing a front-end three-phase VSC and a back-end H-bridge chopper, a step-down transformer, and a coordinate excitation controller. Through a series of experiments, it is demonstrated that the VSC excitation system is able to improve both transient stability and steady-state stability limit of power systems. It is a prospective substitute to the conventional thyristor-based static excitation system and an attractive solution to strengthen power system stability as well as increase the capability of long-distance transmission systems.
Oro-dental lesions in paediatric patients with coeliac disease: an observational retrospective clinical study.

BACKGROUND AND AIM OF THE STUDY investigating the correlation between coeliac disease and specific oral lesions. METHODS 114 paediatric patients were enrolled and divided into three groups: diagnosed celiac patients (CD group), patients with malabsorption without coeliac disease (non-CD group), and healthy patients as control. Lesions of oral hard and soft tissues were detected and analysed by Fisher's test and odds ratio calculations. MAJOR RESULTS a non-random correlation between the three groups and the rate of enamel defects was detected. The CD group showed more and more severe enamel defects compared to the non-CD group. Instead, a non-random association between the three groups and the number of mucous lesions was not observed. Furthermore, malabsorption patterns not related to the coeliac disease involved a relatively modest risk of specific enamel defects when compared to control. CONCLUSIONS hypoplastic enamel defects of the permanent teeth could represent reliable indicators for the coeliac disease. The etiology of specific hypoplastic enamel lesions has to be mainly sought in the autoimmune response triggered by gluten, while the malabsorption would play only a minor role. Lesions of the oral mucous membranes should not be considered as specific risk indicators, however representing a non-specific marker of malabsorption.
Applying Center Loss to Multidimensional Feature Space in Deep Neural Networks for Open-set Recognition

With the advent of deep learning, significant improvements in image recognition performance have been achieved. In image recognition, it is generally assumed that all the test data are composed of known classes. This approach is termed as closed-set recognition. In closed-set recognition, when an untrained, unknown class is input, it is recognized as one of the trained classes. The method whereby an unknown image is recognized as unknown when it is input is termed as open-set recognition. Although several open-set recognition methods have been proposed, none of these previous methods excel in terms of all three evaluation items: learning cost, recognition performance, and scalability from closed-set recognition models. To address this, we propose an open-set recognition method using the distance between features in the multidimensional feature space of neural networks. By applying center loss to the feature space, we aim to maintain the classification accuracy of closed-set recognition and improve the unknown detection performance. In our experiments, we achieved state-of-the-art performance on the MNIST, SVHN, and CIFAR-10 datasets. In addition, the proposed approach shows excellent performance in terms of the three evaluation items.