Miracle-dz/UniFAR-FTUs huggingface dataset:
Influences of the timing of extreme precipitation on floods in Poyang Lake, China

Changes in the timing of extreme precipitation have important ramifications for public safety and storm water management, but it has not received much attention in relation to flooding. This study analyzed the changes in the timing of extreme precipitation in the Poyang Lake basin and projected its future changes for the period 2020–2099. The study also quantified the influences of changes in the timing of peak flows on lake floods based on a hydrodynamic model. The results showed that peak rainfall in the Poyang Lake basin had occurred on later dates during the period 1960–2012, and it is this change that caused a delay in peak streamflows from five rivers in the lake basin. Moreover, the effects of these changes are expected to be more prominent during 2020–2099; for example, the rate of delay will be about 2.0 days per 10 years both for peak rainfall and for streamflow in the Poyang Lake basin. The hydrodynamic simulation further showed that a delay of peak streamflows from five rivers would significantly increase the flood level and outflow of the lake and also prolong the duration of floods. These results indicate that the risk of floods in Poyang Lake is likely to increase in the future, therefore making flood control in this region more challenging.
A Flexible Reference-Insensitive Spatiotemporal Fusion Model for Remote Sensing Images Using Conditional Generative Adversarial Network

Due to the tradeoff between spatial and temporal resolutions of remote sensing images, spatiotemporal fusion models were proposed to synthesize the high spatiotemporal image series. Currently, spatiotemporal fusion models usually employ one coarse-resolution image acquired on a prediction date and at least another pair of coarse–fine resolution images close to the prediction time as references to derive the fine-resolution image on the prediction date. After years of development, the model accuracy has gained a certain improvement, but nearly, all the models require at least three image inputs and rigid time constraints must be applied to the references to guarantee the fusion accuracy. However, it is not always that easy to collect adequate data pairs for fine-resolution image series simulation in practice because of the bad weather condition or the time inconsistency between the coarse–fine resolution data sources, which causes some difficulties in the actual application. This article introduces the conditional generative adversarial network (CGAN) and switchable normalization technique into the spatiotemporal fusion problem and proposes a flexible deep network named the GAN-based SpatioTemporal Fusion Model (GAN-STFM) to reduce the number of model inputs and broke the time restriction on reference image selection. The GAN-STFM just needs a coarse-resolution image on the prediction date and another fine-resolution reference image at an arbitrary time in the same area for model inputs. As far as we know, this is the first spatiotemporal fusion model that requires only two images as model inputs and puts no restriction on the acquisition time of references. Even so, the GAN-STFM performs on par or better than other classical fusion models in the experiments. With this improvement, the data preparation for spatiotemporal fusion tends to be much easier than before, showing a promising perspective for practical applications.
Scaling and Disseminating Brief Bullying Prevention Programming: Strengths, Challenges, and Considerations

Abstract Peer bullying occurs frequently among middle school youth, negatively impacting students and the broader school climate. However, during these years there is a gap in translating empirically supported prevention science into school-based practices. This paper describes how the evidence-based Free2B bullying prevention multimedia assembly was disseminated by a team of educators, researchers, and technologists to over 14,000 students in 40 middle schools across the state. This dissemination and scaling effort was conducted in partnership with the state’s government officials and Office of Safe Schools in order to ensure that each school and district across the state had equal access in applying for the programming. Over half of participating students expressed concerns about school bullying, with 36% reporting victimization and 17% reporting perpetration of bullying in the past month. Significant improvements were found in problem-solving knowledge, confidence in being a positive bystander, and sympathy for peer victims. We discuss gender and community setting differences (urban, suburban, rural) in the findings, implications for dissemination and implementation science, and school psychologists’ role in disseminating bullying prevention practices. Impact Statement Bullying in schools is a crucial impediment for children learning and achieving their full potential. Although effective evidence-based bullying prevention programming exist, when these same programs are disseminated and scaled, they often are less successful. The current study illustrates how researchers utilized principles of the Diffusion of Innovation theory to partner with state influencers to successfully disseminate and scale the Free2B program with strong results to over 14,000 students from 40 schools across the state.
The effects of brand equity and failure severity on remedy choice after a product recall

Purpose There is limited insight concerning a firm’s remedy choice after a product recall. This study aims to propose that failure severity and brand equity are key antecedents of remedy choice and provides empirical evidence for a non-linear relationship between pre-recall brand equity and the firm’s remedy offer that is moderated by severity. Design/methodology/approach This study uses field data for 159 product recalls from 60 brands between January 2008 to February 2020 to estimate a probit model of the effects of failure severity, pre-recall brand equity and remedy choice. Findings Firms with higher and lower pre-recall brand equity are less likely to offer full (vs partial) remedy compared to medium level pre-recall brand equity firms. Failure severity moderates this relationship positively, i.e. firms with low and high brand equity are more sensitive to failure severity and then select full instead of partial remedy. Research limitations/implications This research reconciles contradictory arguments and research results about failure severity as an antecedent of remedy choice by introducing brand equity as another key variable. Future research could examine the psychological process of managerial decision-making through experiments. Practical implications This study increases the awareness of the importance of remedy choice during product-harm crises and can help firms and regulators to better understand managerial decision-making mechanisms (and fallacies) during a product-harm crisis. Originality/value This study theoretically and empirically advances the limited literature on managerial decision-making in response to product recalls.
Semantic role labelling using transfer learning model

Semantic role labelling plays a major role in determining the main predicate and related arguments and its relationship to the predicate. These arguments identify the semantic roles in a sentence such as agent, goal, result, etc. Many approaches have been made to perform the task of semantic role labelling. Many recent works incorporated neural networks making use of syntactic features of the given text such as part of speech tags, POS tagged dependency tree, etc. Other works included the use of BERT along with LSTM and MLP to create semantic role labeling models. In this work, BERT model has been fine tuned to be used as a classifier to detect the main predicate, arguments of the predicate and also the relationship arguments maintain with the predicate in the sentence. Using BERT to build a simple classifier creates an efficient semantic role labelling model. Model performance was assessed using metric accuracy, precision, recall and F1 score. This is achieved by comparing the output of each word with the predicted word and labels as well as the arguments in the prediction of the output.
Nutritional Research and Fetal Programming: Parental Nutrition Influences the Structure and Function of the Organs

nutrition the structure and function of the organs. SUMMARY: Rodents are animals extensively used in biomedical and nutrition research, a necessary step before the research in humans. The composition and type of administration of the experimental diets are relevant and should be thought, considering each type of animal used in the research. It is particularly important to consider, among others, the metabolic differences between species and food needs in macro- and micronutrients to avoid possible bias. The American Institute of Nutrition (AIN) made recommendations for rodents, adapted to the period of growth (AIN-93G), which are pivotal in fetal programming studies. The experiments can be compared among different studies and better translated into humans, considering these limitations in the nutrition of parents and offspring. The review addresses different compositions of experimental food for rodents during development with the ability to induce fetal programming in the offspring and chronic diseases in adulthood due to the nutrition of the mother and father. The 'developmental origins of health and disease' (DOHaD) concept due to maternal nutrition is commented considering the protein restriction, vitamin D restriction, obesity, and intake of fructose or fish-oil. The 'paternal origins of health and disease transmission' (POHaD), because of the nutritional state of the father, were also analyzed in the review, primarily considering the obesity of the father. The review proposes some diet compositions to experimental research considering varied nutritional situations, hoping to assist young researchers or researches not familiar with experimental diet manipulations in the elaboration of the projects.
Biological Bleaching of Kraft Pulp with Lignin-Degrading Enzymes

An unbleached hardwood kraft pulp was bleached in vitro with partially purified manganese peroxidase (MnP) from the fungus Phanerochaete sordida YK-624 without the addition of MnSO in the presence of oxalate, malonate or gluconate known as manganese chelator, When the pulp was treated without the addition of MnSO, the pulp brightness increased by about 10 points in the presence of 2 mM oxalate, but the brightness did not significantly increase in the presence of 50 mM malonate. Residual MnP activity decreased faster during the bleaching with MnP without MnSO in the presence of malonate than in the presence of oxalate. Oxalate reduced MnO which already existed in the pulp or was produced from by oxidation with MnP and thus supplied to the MnP system. Thus, bleaching of hardwood kraft pulp with MnP, using manganese originally existing in the pulp, became possible in the presence of oxalate, a good manganese chelator and reducing reagent. Properties of partially purified MnPs from liquid cultures of white rot fungi, Ganoderma sp. YK-505, Phanerochaete sordida YK-624 and Phanerochaete chrysosporium were compared. MnP from Ganoderma sp. YK-505 was superior to MnPs from P. sordida YK-624 and P. chrysosporium in stabilities against high temperature and high concentration of . The MnP from Ganoderma sp. YK-505 differed in pH-activity profile from other MnPs. These data suggest that MnP from Ganoderma sp. YK-505 has different structure from those of other fungi. Bleaching of hardwood kraft pulp using the MnP from ganoderma sp. YK-505 is now in progress.
Functional diversity and trait composition of vascular plant and Sphagnum moss communities during peatland succession across land uplift regions

Most of the carbon accumulated into peatlands is derived from Sphagnum mosses. During peatland development, the relative share of vascular plants and Sphagnum mosses in the plant community changes, which impacts ecosystem functions. Little is known on the successional development of functional plant traits or functional diversity in peatlands, although this could be a key for understanding the mechanisms behind peatland resistance to climate change. Here we aim to assess how functionality of successive plant communities change along the autogenic peatland development and the associated environmental gradients, namely peat thickness and pH, and to determine whether trait trade‐offs during peatland succession are analogous between vascular plant and moss communities. We collected plant community and trait data on successional peatland gradients from post‐glacial rebound areas in coastal Finland, Sweden and Russia, altogether from 47 peatlands. This allowed us to analyse the changes in community‐weighted mean trait values and functional diversity (diversity of traits) during peatland development. Our results show comparative trait trade‐offs from acquisitive species to conservative species in both vascular plant and Sphagnum moss communities during peatland development. However, mosses had higher resistance to environmental change than vascular plant communities. This was seen in the larger proportion of intraspecific trait variation than species turnover in moss traits, while the proportions were opposite for vascular plants. Similarly, the functional diversity of Sphagnum communities increased during the peatland development, while the opposite occurred for vascular plants. Most of the measured traits showed a phylogenetic signal. More so, the species common to old successional stages, namely Ericacae and Sphagna from subgroup Acutifolia were detected as most similar to their phylogenetic neighbours. Synthesis. During peatland development, vegetation succession leads to the dominance of conservative plant species accustomed to high stress. At the same time, the autogenic succession and ecological engineering of Sphagna leads to higher functional diversity and intraspecific variability, which together indicate higher resistance towards environmental perturbations.
Cloud platform for smart product-service systems

The paper deals with the problem of decision-making support for digital production planning. The analysis of the stages of organization and production planning currently is poorly represented in existing software solutions. Main stages of digital production planning are identified such as optimization of manufacturing placement; optimization of suppliers selection of resources and its delivery to the place of manufacturing. Taking into account the conditions of the modern stage of development of technologies for the digital production, we can identify the key requirements for the functionality and use of the software platform. The formalization (ontology) based on the approach of production and operational management and the architecture of a digital cloud platform and its functional modules has been developed for the digital production planning process. It is a decentralized platform as a public network consisting of independent software modules (cloud services), connected into a tool with expandable number of modules. The software tool consists of production-planning unit and production-management support unit. Currently, a number of modules of the system have been developed and experimentally tested; now we are developing the full-featured tool.
Distributed Fiber Deformation Measurement by High-Accuracy Phase Detection in OFDR Scheme

Fiber deformation measurement is crucial in the structure health monitor, which reflects the stress, strain or deformation of the structure where the fiber is laid. The principle of the fiber deformation measurement by the optical phase tracking in OFDR scheme is described and the data processing algorithm is demonstrated in details to receive accurate results. The differential phase is acquired by making a difference between the phase spectrum of the reference and measurement states. A robust phase unwrapping method based on the density distribution is proposed to get the whole unwrapped low-noise phase of the fiber. Additionally, the phase decoherence caused by the scatter unit misalignment induced by the fiber deformation is analyzed and the phase correction method is proposed to improve the phase coherence. The fiber deformation can be tracked along the fiber with a resolution of tens of microns, depending on the set parameters of the OFDR system. Moreover, the strain distribution is also derived from the differential phase. In the experiments, the measurements of the standard single-mode fiber with uniform and non-uniform deformation have been accomplished in a spatial resolution of 40 μm. The noise is about 0.1 μm in a stretching range of about 40 μm. Simultaneously, hundreds of microstrain are obtained and show a high accuracy with a resolution of the level of millimeter.
Modularity in Production and Firm Relative Positional Advantage: Evidence from the Global Automobile Industry in China

Abstract This study investigates modularization and its impact on cost, speed to market and product quality (firm relative positional advantage) in the world’s largest car market. The research findings support the view that modularization is an important factor in the Chinese auto industry. It has a positive impact on these variables that constitute firm relative positional advantage. The study also shows that knowledge sharing and physical proximity partially moderate the relationship between the degree of modularization and firm relative positional advantage variables: cost, speed to market and product quality. The study contributes to the literature by showing modularization as an important competitive strategy.
Impact of Dose and Route of administration on Antibody Responses of Chickens Inoculated with inactivated Avian Influenza H5 Vaccine.

Avian influenza viruses (AIV) poses significant threats to human and animal lives globally, and in spite of availability of vaccines, only few studies have established the role of passively acquired antibodies in the protection of chickens in sub Saharan Africa. The present study evaluated the influence of dose and route of administration of AI H5 inactivated vaccine on the humoral immune response of ISA brown chickens. Ninety “one-day-old” chickens were purchased from three major commercial hatcheries A, B and C (n = 30 chicks per hatchery), respectively. Results showed significant differences (P < 0.001) in the mean antibody titre levels at day 21 of age between chicks from hatcheries C (2,205.0 ± 409.1) and A (57.7 ± 49.9) at 21 days of age when either 0.2 ml or 0.5 ml of the vaccine was administered IM or SC. In addition, there were intra- and inter dose significant differences (P < 0.001) between the chicks at 21, 28, 35 and 42 days of age. Furthermore, intra- and inter route significant differences (P < 0.001) were detected between the chicks at 21 and 35 days of age. Overall, the AI H5 vaccine studied had variable outcomes and poorly immunogenic. Further studies should be conducted to characterize the T- and B-lymphocytes in chickens post AI H5 vaccines administration, and evaluate the sequence homologies between imported AI H5 vaccines and circulating AIV strains in Nigeria.
Hysteresis and moisture buffering of wood

Hysteresis of oak is analysed using the empirical model of Pedersen (1990) and a new hysteresis model based on the model of Mualem (1974). Pedersen’s model necessitates the experimental determination of the main adsorption and desorption curves as well as the primary adsorption and desorption loops. The fitted parameters seem to lack physical background and the capacity follows a highly varying tendency. The new model is based on the well-known ink-bottle theory and has the potential to predict scanning curves only based on the knowledge of the main adsorption and desorption curve. In an analysis of the moisture balance of a room, hysteresis was shown to play a minor role, while the vapour permeability is of high importance.
Core Hopping of Bis-indole Derivatives to Identify an Effective Inhibitor for the Treatment of Bipolar Disorder

Bipolar disorder is found to be one of the crucial mental disorders with severe side effects. The suicide rate among patients with bipolar disorder is likely greater than with patients of major depression and up to 17%-19% of patients die by suicide. Various proofs identify that family of protein kinase C (PKC) can act as target in the treatment of BPD. Different medications for treating bipolar disorder may cause different side effects. Due to its higher severity of side effects there is a need for the development of novel drugs. In the present study, core hopping technique is employed to obtain a new compound with higher activity. X-ray crystal structure of PKC-ε protein was downloaded from Protein Data Bank (PDB ID: 1GMI). The target protein was obtained preprocessed for docking analysis. By using core-hopping method 21 novel structures were developed from bis-indole derivative. All the obtained compounds were subjected to molecular docking and molecular dynamics simulations. From the docking analysis a novel protocore 2-(3a,7a-dihydro-1Hindol-3-yl)-3-(1H-indol-3-yl)-1,2,3,3a,4,6a-hexahydropyrazolo[3,4-d] [1,2,3]triazol-6-amine showed significantly higher binding energy (-12.8 kcal/mol) than the normal bis-indole derivative (-4.5 kcal/mol). From the molecular dynamics study, the protein-ligand complex were found to be highly stable and the structure of protein remains intact and undergoes no deformation after binding with the ligand. Thus, the novel compound obtained from core hopping technique can be used for the development of effective drugs for the treatment of bipolar disorder with lesser side effects.
Quantitatively accurate calculations of conductance and thermopower of molecular junctions

Thermopower measurements of molecular junctions have recently gained interest as a characterization technique that supplements the more traditional conductance measurements. Here we investigate the electronic conductance and thermopower of benzenediamine (BDA) and benzenedicarbonitrile (BDCN) connected to gold electrodes using first‐principles calculations. We find excellent agreement with experiments for both molecules when exchange–correlation effects are described by the many‐body GW approximation. In contrast, results from standard density functional theory (DFT) deviate from experiments by up to two orders of magnitude. The failure of DFT is particularly pronounced for the n‐type BDCN junction due to the severe underestimation of the lowest unoccupied molecular orbital (LUMO). The quality of the DFT results can be improved by correcting the molecular energy levels for self‐interaction errors and image charge effects. Finally, we show that the conductance and thermopower of the considered junctions are relatively insensitive to the metal–molecule bonding geometry. Our results demonstrate that electronic and thermoelectric properties of molecular junctions can be predicted from first‐principles calculations when exchange–correlation effects are taken properly into account.