Miracle-dz/UniFAR-FTUs huggingface dataset:
Grain yields and soil properties on loam soil after three decades with conservation tillage in southeast Norway

Four tillage trials have been performed on moderately well-drained loam soil in southeast Norway for 30–37 years (mean 34), comparing reduced tillage (8–10 cm in spring) with autumn ploughing (25 cm). In some years, additional stubble harrowing in autumn (10–12 cm) was compared with harrowing only in spring. Weeds were controlled with herbicides. Straw residues were retained after around 1990 and no fungicides were used. Grain yields are reported for the last nine years, and compared with earlier years. Results are presented for a number of soil properties measured in recent years. Autumn harrowing gave no consistent yield benefit over harrowing only in spring. There was little difference between ploughed and unploughed treatments in mean grain yields over the whole trial period, and the variability between years was similar in both tillage systems. Relative grain yields, calculated as yields obtained without ploughing in percentage of those obtained with ploughing, appeared to be normally distributed around 100%. Responses were often positive in dry years, and negative in wet years. Reduced tillage gave higher P and K concentrations near the soil surface and slightly lower concentrations in deeper layers. There was little change in their levels, relative to earlier findings. Changes in bulk density and total porosity were mostly attributable to changes in the stratification of organic matter. Reduced tillage increased porosity at 4–8 cm depth and decreased it slightly at 24–28 cm, but there was no change in the intermediate layer. The moisture-holding capacity of the soil was altered little by reduced tillage, and soil aeration properties were satisfactory at all three depths measured. There was no change in the total amount of organic matter stored within the topsoil, despite marked changes in its distribution. Reduced tillage gave significant increases in aggregate stability and an indication of greater earthworm activity.
Stearoyl-CoA Desaturase-Mediated Monounsaturated Fatty Acid Availability Supports Humoral Immunity

Immune cells can metabolize glucose, amino acids, and fatty acids (FAs) to generate energy. The role of different FA species, and their impacts on humoral immunity remains poorly understood. Here we report that proliferating B cells require monounsaturated FAs (MUFA) to maintain mitochondrial metabolism and mTOR activity, and to prevent excessive autophagy and endoplasmic reticulum (ER) stress. Furthermore, B cell extrinsic Stearoyl-CoA desaturase (SCD) activity generates MUFA to support early B cell development and germinal center (GC) formation in vivo during immunization and influenza infection. Thus, SCD-mediated MUFA production is critical for humoral immunity.
Cognitive regulation of multimodal food perception in the human brain

The ability to regulate appetite is essential to avoid food over-consumption. The desire for a particular food can be triggered by its odor before it is even seen. Using fMRI, we identify the neural systems modulated by cognitive regulation when experiencing appetizing food stimuli presented in both olfactory and visual modalities, while being hungry. Regulatory instruction modulated bids for food items and inhalation patterns. Distinct brain regions were observed for up and down appetite-regulation, respectively the dorsomedial prefrontal cortex (dmPFC) and dorsolateral PFC. Food valuation engaged the ventromedial PFC and bilateral striatum while the amygdala was modulated by individual food preferences, indexed by rank-ordered bids. Furthermore, we identified a neurobiological marker for up-regulating success: individuals with higher blood levels of ghrelin were better at exercising up-regulation, and engaged more the dmPFC. This characterizes the neural circuitry regulating food consumption and suggests potential hormonal and neurofunctional targets for preventing eating disorders.
A Review of Image Denoising Algorithms, with a New One

The search for efficient image denoising methods is still a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods, most algorithms have not yet attained a desirable level of applicability. All show an outstanding performance when the image model corresponds to the algorithm assumptions but fail in general and create artifacts or remove image fine structures. The main focus of this paper is, first, to define a general mathematical and experimental methodology to compare and classify classical image denoising algorithms and, second, to propose a nonlocal means (NL-means) algorithm addressing the preservation of structure in a digital image. The mathematical analysis is based on the analysis of the "method noise," defined as the difference between a digital image and its denoised version. The NL-means algorithm is proven to be asymptotically optimal under a generic statistical image model. The denoising performance of all consid.
Genetic dissection of glutamatergic neuron subpopulations and developmental trajectories in the cerebral cortex

Diverse types of glutamatergic pyramidal neurons (PyNs) mediate the myriad processing streams and output channels of the cerebral cortex, yet all derive from neural progenitors of the embryonic dorsal telencephalon. Here, we establish genetic strategies and tools for dissecting and fate mapping PyN subpopulations based on their developmental and molecular programs. We leverage key transcription factors and effector genes to systematically target the temporal patterning programs in progenitors and differentiation programs in postmitotic neurons. We generated over a dozen temporally inducible mouse Cre and Flp knock-in driver lines to enable combinatorial targeting of major progenitor types and projection classes. Intersectional converter lines confer viral access to specific subsets defined by developmental origin, marker expression, anatomical location and projection targets. These strategies establish an experimental framework for understanding the hierarchical organization and developmental trajectory of PyN subpopulations that assemble cortical processing networks and output channels.
The Impact of Information Technology and Analytics on the Performance of a Hospital: Scale Development in Indian Context

Today, in the era of analytics and Information Technology, analysing every form of data is possible. Be it manufacturing, Supply Chain, Retail, Service, Product, Sales Marketing or be it Pharmaceuticals and Healthcare. In recent times hospitals are facing the issue of over-crowding and medical staff is not able to deliver the healthcare properly. With the help of the Information Technology System used in hospitals for routine work, high quality and high amount of data can be generated. With the capabilities to analyse the data accurately for the internal operations, planning, and forecasting for the benefits of the patients in deciding the nature of the treatment, medicines used or the probable adverse drug reaction pharmacologically, the performance of the healthcare organization increases. The study concentrates on the scale development for the constructs which can improve the operational performance by using the information technology and the care analytics.
StackRAM: a cross-species method for identifying RNA N6-methyladenosine sites based on stacked ensemble

N6-methyladenosine is a prevalent RNA methylation modification, which plays an important role in various biological processes. Accurate identification of the m6A sites is fundamental to deeply understand the biological functions and mechanisms of the modification. However, the experimental methods for detecting m6A sites are usually time-consuming and expensive, and various computational methods have been developed to identify m6A sites in RNA. This paper proposes a novel cross-species computational method StackRAM using machine learning algorithms to identify the m6A sites in S. cerevisiae、H. sapiens and A. thaliana. First, the RNA sequences features are extracted through binary encoding, chemical property, nucleotide frequency, k-mer nucleotide frequency, pseudo dinucleotide composition, and position-specific trinucleotide propensity, and the initial feature set is obtained by feature fusion. Secondly, the Elastic Net is used for the first time to filter redundant and noisy information and retain important features for m6A sites classification. Finally, the base-classifiers output probabilities are combined with the optimal feature subset corresponding to the Elastic Net, and the combination feature input the second-stage meta-classifier SVM. The jackknife test on training dataset S. cerevisiae indicates that the prediction performance of StackRAM is superior to the current state-of-the-art methods. StackRAM prediction accuracy for independent test datasets H. sapiens and A. thaliana reach 92.30% and 87.06%, respectively. Therefore, StackRAM has development potential in cross-species prediction and can be a useful method for identifying m6A sites. The source code and all datasets are available at https://github.com/QUST-AIBBDRC/StackRAM/.
Wharton’s Jelly-derived mesenchymal stromal cells retain their immunophenotype and immunomodulating characteristics after transfection with polyethylenimine

Background Wharton’s Jelly-derived mesenchymal stromal cells (WJ-MSCs) present several advantages over other sources of multipotent stem cells, not only because they are obtained from neonatal umbilical cord, which is considered a biological waste, but also display higher proliferation rate and low senescence at later passages compared to stromal cells obtained from other sources. In the field of tissue engineering, WJ-MSCs have a wide therapeutic potential, due to their multipotential capacity, which can be reinforced if cells are genetically modified to direct their differentiation towards a specific lineage; unfortunately, as primary cells, WJ-MSC are difficult to transfect. Therefore, the objective of the present work was to standardize a protocol for the transfection of WJ-MSCs using a cationic polymer. Such protocol is important for future developments that contemplate the genetic modification of WJ-MSCs for therapeutic purposes. Methods In this work, WJ-MSCs were genetically modified using polyethylenimine (PEI) and a lentiviral plasmid that encodes for green fluorescent protein (pGFP). To achieve WJ-MSCs transfection, complexes between PEI and pGFP, varying its composition (N/P ratio), were evaluated and characterized by size, zeta potential and cytotoxicity. At the N/P ratio condition where the highest transfection efficiencies were obtained, immunophenotype, immunomodulation properties and multipotential capacity of WJ-MSCs were evaluated. Results Here, we present the standardization of the transfection conditions of the WJ-MSCs in a monolayer culture with PEI. The concentrations of plasmid and PEI that have the best transfection efficiencies were established Conclusions Transfection with PEI doesn’t affect immunophenotype, immunomodulatory properties and differentiation capacity of WJ-MSCs.
341-436 Tourism 2014 04EN.indd

Following the theoretical discussion on changes in the development paradigm of cities in the post-industrial society, on the strategic implications of urban regeneration and the interrelations of culture and tourism in those processes, the paper presents a conceptual model which provided a basis for the empirical verifi cation of assumed links and relations between the concepts under scrutiny. Th e possibility of relating cultural and tourism strategies in the process of regeneration of Croatian cities was analysed by application of structural equations modelling. Th e assumption that cultural strategy based on fl agship cultural projects cannot be related to tourism development strategies in Croatian cities has been verifi ed. Furthermore, the estimated parameter have pointed at the existence of a direct positive correlations between the strategies promoting the development of cultural districts and similar projects, which are integrated into the general city development strategies and the tourism development strategies relying mostly on the small and medium-sized entrepreneurship. Apart from the empirical research an analysis of the cities' strategic development documents showed the growing prevalence of the approach in which culture is considered to be a powerful entrepreneurial resource for the development of small entrepreneurship, especially through tourism and related industries. In the light of detected problems, recommendations on further research have been proposed in the area of urban planning and urban management.
The Effects of Environmental Uncertainty on Young and Small Businesses

Entrepreneurs face a wide variety of uncertainties in managing new or small businesses. Uncertainty can potentially magnify the liability of newness faced by younger businesses, as well as the challenges that smaller businesses face in having adequate resources to maintain performance. Here we present a model of environmental uncertainty tied to industry, geographic and macro-level effects. We hypothesize a moderating effect of uncertainty upon both new and small business performance, and present a pilot test of the model using NFIB data that supports one of our two hypotheses.
Network attack detection and visual payload labeling technology based on Seq2Seq architecture with attention mechanism

In recent years, Internet of things (IoT) devices are playing an important role in business, education, medical as well as in other fields. Devices connected to the Internet is much more than the number of world population. However, it may face all kinds of attacks from the Internet easily for its accessibility. As we all know, most attacks against IoT devices are based on Web applications. So protecting the security of Web services can effectively improve the situation of IoT ecosystem. Conventional Web attack detection methods highly rely on samples, and artificial intelligence detection results are uninterpretable. Hence, this article introduced a supervised detection algorithm based on benign samples. Seq2Seq algorithm is been chosen and applied to detect malicious web requests. Meanwhile, the attention mechanism is introduced to label the attack payload and highlight labeling abnormal characters. The results of experiments show that on the premise of training a benign sample, the precision of proposed model is 97.02%, and the recall is 97.60%. It explains that the model can detect Web attack requests effectively. Simultaneously, the model can label attack payload visually and make the model “interpretable. ”
Chromosome-level and haplotype-resolved genome assembly enabled by high-throughput single-cell sequencing of gamete genomes

Generating chromosome-level, haplotype-resolved assemblies of heterozygous genomes remains challenging. To address this, we developed gamete binning, a method based on single-cell sequencing of haploid gametes enabling separation of the whole-genome sequencing reads into haplotype-specific reads sets. After assembling the reads of each haplotype, the contigs are scaffolded to chromosome-level using a genetic map derived from the gametes. As a proof-of-concept, we assembled the two genomes of a diploid apricot tree based on whole-genome sequencing of 445 individual pollen grains. The two haplotype assemblies (N50: 25.5 and 25.8 Mb) featured a haplotyping precision of >99% and were accurately scaffolded to chromosome-level.
Repetitive transcranial magnetic stimulation activates glial cells and inhibits neurogenesis after pneumococcal meningitis

Pneumococcal meningitis (PM) causes damage to the hippocampus, a brain structure critically involved in learning and memory. Hippocampal injury – which compromises neurofunctional outcome – occurs as apoptosis of progenitor cells and immature neurons of the hippocampal dentate granule cell layer thereby impairing the regenerative capacity of the hippocampal stem cell niche. Repetitive transcranial magnetic stimulation (rTMS) harbours the potential to modulate the proliferative activity of this neuronal stem cell niche. In this study, specific rTMS protocols – namely continuous and intermittent theta burst stimulation (cTBS and iTBS) – were applied on infant rats microbiologically cured from PM by five days of antibiotic treatment. Following two days of exposure to TBS, differential gene expression was analysed by whole transcriptome analysis using RNAseq. cTBS provoked a prominent effect in inducing differential gene expression in the cortex and the hippocampus, whereas iTBS only affect gene expression in the cortex. TBS induced polarisation of microglia and astrocytes towards an inflammatory phenotype, while reducing neurogenesis, neuroplasticity and regeneration. cTBS was further found to induce the release of pro-inflammatory cytokines in vitro. We conclude that cTBS intensified neuroinflammation after PM, which translated into increased release of pro-inflammatory mediators thereby inhibiting neuroregeneration.
Individual variation in susceptibility or exposure to SARS-CoV-2 lowers the herd immunity threshold

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spreads, the susceptible subpopulation is depleted causing the rate at which new cases occur to decline. Variation in individual susceptibility or exposure to infection exacerbates this effect. Individuals that are frailer, and therefore more susceptible or more exposed, have higher probabilities of being infected, depleting the susceptible subpopulation of those who are at higher risk of infection, and thus intensifying the deceleration in occurrence of new cases. Eventually, susceptible numbers become low enough to prevent epidemic growth or, in other words, herd immunity is attained. Although estimates vary, it is currently believed that herd immunity to SARS-CoV-2 requires 60-70% of the population to be immune. Here we show that variation in susceptibility or exposure to infection can reduce these estimates. Achieving accurate estimates of heterogeneity for SARS-CoV-2 is therefore of paramount importance in controlling the COVID-19 pandemic.
The ancient fusogen EnvP(b)1 is expressed in human tissues and its structure informs the evolution of gammaretrovirus envelope proteins

Host genomes have acquired diversity from viruses through the capture of viral elements, often from endogenous retroviruses (ERVs). These viral elements contribute new transcriptional control elements and new protein encoding genes, and their refinement through evolution can generate novel physiological functions for the host. EnvP(b)1 is an endogenous retroviral envelope gene found in human and other primate genomes. We show that EnvP(b)1 arose very early in the evolution of primates, i.e. at least 40-47 million years ago, but has nevertheless retained its ability to fuse primate cells. We have detected similar sequences in the genome of a lemur species, suggesting that a progenitor virus may have circulated 55+ million years ago. We demonstrate that EnvP(b)1 protein is expressed in multiple human tissues and is fully processed, rendering it competent to fuse cells. This activated fusogen is expressed in multiple healthy human tissues and is under purifying selection, suggesting that its expression is selectively advantageous. We determined a structure of the inferred receptor binding domain of human EnvP(b)1, revealing close structural similarities between this Env protein and those of currently circulating leukemia viruses, despite poor sequence conservation. This observation highlights a common scaffold from which novel receptor binding specificities have evolved. The evolutionary plasticity of this domain may underlie the diversity of related Envs in circulating viruses and coopted elements alike. The function of EnvP(b)1 in primates remains unknown. SIGNIFICANCE STATEMENT Organisms can access genetic and functional novelty by capturing viral elements within their genomes, where they can evolve to drive new cellular or organismal processes. We demonstrate that a retrovirus envelope gene, EnvP(b)1, has been maintained as a functional protein for 40 to ≥55 million years and is expressed as a protein in multiple healthy human tissues. We believe it has an unknown function in primates. We determined the structure of its inferred receptor binding domain and compared it with the same domain in modern viruses. We find a common conserved architecture that underlies the varied receptor binding activity of divergent Env genes. The modularity and versatility of this domain may underpin the evolutionary success of this clade of fusogens.
Tonic GABAergic activity facilitates dendritic calcium signaling and short-term plasticity

Brain activity is highly regulated by GABAergic activity, which acts via GABAARs to suppress somatic spike generation as well as dendritic synaptic integration and calcium signaling. Tonic GABAergic conductances mediated by distinct receptor subtypes can also inhibit neuronal excitability and spike output, though the consequences for dendritic calcium signaling are unclear. Here, we use 2-photon calcium imaging in cortical pyramidal neurons and computational modeling to show that low affinity GABAARs containing an α5 subunit mediate a tonic hyperpolarization of the dendritic membrane potential, resulting in deinactivation of voltage-gated calcium channels and a paradoxical boosting of action potential-evoked calcium influx. We also find that GABAergic enhancement of calcium signaling modulates short-term synaptic plasticity, augmenting depolarization-induced suppression of inhibition. These results demonstrate a novel role for GABA in the control of dendritic activity and suggest a mechanism for differential modulation of electrical and biochemical signaling.
Coupled cascade regression from real and synthesized faces for simultaneous landmark detection and head pose estimation

Abstract The existing approaches usually perform facial landmark detection and head pose estimation independently and sequentially, ignoring their coupled relations. We introduce a unified framework, named coupled cascade regression (CCR), for simultaneous facial landmark detection and head pose estimation. Based on the cascade regression framework, we propose to learn two separate regressors to update the landmark locations and three-dimensional (3D) face model parameters at each cascade level. To capture the coupled relations of the landmark locations and head pose, we further apply the 3D face projection model to refine the prediction results in each cascade iteration and make them consistent. CCR can leverage both the learning methods and the projection model to simultaneously perform facial landmark detection and pose estimation to enhance the performances of both tasks. We also propose to learn the cascade regressors from the combination of real and synthesized face images to solve the problem of limited variations in head pose for training. Experimental results on Helen, labeled face parts in the wild, 300-W, and Boston University datasets show that our proposed CCR method outperforms other conventional methods both for landmark detection and head pose estimation.
The fish populations in inshore waters of the west coast of Scotland. The food and feeding of the whiting (Merlangius merlangus L

The food and feeding of the whiting (Merlangius merlangus) of the inshore waters and sea lochs of the west of Scotland were studied from 1969–1973. Fish and Crustacea were the main food items and their occurrence in the stomachs was clearly related to the size of the whiting and also to their seasonal abundance. The diurnal changes in feeding were also investigated and the results indicated that the size of fish was again an important factor which could affect the interpretation of the seasonal data.