Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of field margins and other uncultivated fields on Orthoptera assemblages in the mountainous paddy field area of northeast Japan

To understand how farmlands help maintain biodiversity, we investigated the relationship between habitat heterogeneity and Orthoptera community composition on multiple spatial scales. First, we determined the impact of 12 environmental variables on the Orthoptera community diversity by sampling 37 quadrats in uncultivated fields over a broad spatial scale. Canonical correspondence analysis (CCA) demonstrated that environmental parameters influenced species composition. The first two canonical axes were associated with forest cover, grass (including harvested dried grass in some cases), bare or paddy fields, and plants with tall stems. Secondly, we conducted a local-scale survey of Orthoptera assemblages in an operational farm unit consisting of paddy fields, fallow fields, marginal grass fields, and secondary forests. Eleven Orthoptera species (46%) were found exclusively on specific vegetation types. Thirdly, we carried out a habitat-scale survey to elucidate the correspondence between consecutive spatial changes in vegetation and Orthoptera community composition in a paddy field and surrounding marginal fields. Even within narrower ranges, the compositional habitat heterogeneity induced changes in the dominant Orthoptera species composition. These results indicate that a high degree of habitat segregation occurs among Orthoptera species in field margins and in uncultivated fields, and that farmland management significantly affects spatial distribution of Orthoptera.
Playing the post 9/11 on game service platforms: Premediation in The Division via Twitch.tv and Steam

This article focuses on the relation between post 9/11 imaginary and digital entertainment’s audiences. Its aim is to enlighten potential players’ perception of such an influence by exploring game service platforms – that is, online spaces with peculiar functions that are getting a foothold in the sector. By following the leading concepts of ‘premediation’ (Grusin, 2010) and ‘platform’ (Gillespie, 2010), an empirical investigation was directed about the game The Division, which glaringly exploits references to 9/11, in relation with Twitch.tv (live streaming) and Steam (multi-hub with several features, from user-generated content upload to discussion) environments. For the first 20 days from the release, multiple data were gathered daily (e.g. streaming chats, threads and artworks) and framed with a discourse/visual analysis (e.g. Gee, 2010). Results show that connections to 9/11 were perceived in experiencing game mechanics (e.g. multiplayer mode) rather than in discussing setting or plot. A preventive attitude against other players emerged as winning strategy and potential bridge to an ‘interactive premediation’ in media consumption.
IDA-based definition of damage states for rc silo subjected to seismic excitations

Extensive damages or collapse observed for silos subjected to earthquake excitations can lead to significant monetary and environmental losses while human life may also be set at high risk. Therefore, the design of earthquake-resistant silos is essential to safeguard silos’ integrity and functionality over their lifetime. In case of adopting the performance-based design approach, well-defined damage limit states are required to quantify the expected seismic failures of silos. Nevertheless, to the authors’ best knowledge, only marginal research effort has been already spent to quantify appropriate damage limit states for silos. To this end, the current study is dedicated to determine damage states for a typical cylindrical reinforced concrete silo, containing granular material with the use of a multi-record, non-linear incremental dynamic analysis (IDA). The numerical model of the silo was developed in ABAQUS. The advanced hypoplastic constitutive model, extended with the intergranular strain approach, was adopted to simulate the dynamic performance of the granular material while the silo wall was modelled by using the concrete damaged plasticity model. Additionally, granular materialstructure interaction was considered through a Coulomb friction interface. Both static and dynamic (i.e., time history) analyses were performed to validate both the granular material-structure interaction and the silo’s dynamic response. Furthermore, IDA curves, in terms of base shear over top displacement, were calculated with the use of an appropriately selected and scaled set of earthquake strong ground motions. The IDA curves were eventually used to quantify five damage limit states according to maximum top displacement criterion.
Turbulent diffusion modelling of sediment in turbidity currents: An experimental validation of the Rouse approach

The margins of submarine channels are characterized by deposits that fine away from the channel thalweg. This grain‐size trend is thought to reflect upward fining trends in the currents that formed the channels. This assumption enables reconstruction of turbidity currents from the geologic record, thereby providing insights into the overall sediment load of the system. It is common to assume that the density structure of a turbidity current can be modelled with simple diffusion models, such as the Rouse equation. Yet the Rouse equation was developed to describe how particles should be distributed through the water column in open‐channel flows, which fundamentally differ from turbidity currents in terms of their flow structure. Consequently, a rigorous appraisal of the Rouse model in deep‐marine settings is needed to validate the aforementioned flow reconstructions. The present study addresses this gap in the literature by providing a robust evaluation of the Rouse model's predictions of vertical particle segregation in two experimental turbidity currents that differ only in terms of their initial bed slopes (4° versus 8°). The concentration profiles of the coarsest sediment, which is suspended predominantly in the lower part of the flow, is accurately reproduced by the Rouse equation. Significant mismatches appear, however, in the concentration of finer grained sediment, especially towards the top of the flow. This problem is caused by the mixing with clear water at the top of turbidity currents. Caution is therefore advised in applying a Rouse model to levee overspill and levee‐crest deposits. Nonetheless, the Rouse model shows good agreement with laboratory measurements in the lower regions of the flow and for the coarser grains that are predominantly transported in the lower sections of submarine channels.
Efforts for aligning the Brazilian Height System to the International Height Reference System

The International Height Reference System (IHRS) consolidated the idea of a world height system (WHS) according to the IAG Resolution 1/2015. Since 2000, the majority of activities related to the modernization of the Brazilian Height System (BHS) has referred to a physical meaning for the heights and have linked two existing vertical datums in the country to a same equipotential surface. Today, these activities relate to the BHS and its realization by the Brazilian Vertical Reference Network (BVRN) agrees with the IHRS precepts. In this context, the main developed activities related to BHS/BVRN and achieved goals are described in this work.
Transcriptomic analysis of isolated and pooled human postmortem cerebellar Purkinje cells in autism spectrum disorders

At present, the neuronal mechanisms underlying the diagnosis of autism spectrum disorder (ASD) have not been established. However, studies from human postmortem ASD brains have consistently revealed disruptions in cerebellar circuitry, specifically reductions in Purkinje cell (PC) number and size. Alterations in cerebellar circuitry would have important implications for information processing within the cerebellum and affect a wide range of human motor and non-motor behaviors. Laser capture microdissection was performed to obtain pure PC populations from a cohort of postmortem control and ASD cases and transcriptional profiles were compared. The 427 differentially expressed genes were enriched for gene ontology biological processes related to developmental organization/connectivity, extracellular matrix organization, calcium ion response, immune function and PC signaling alterations. Given the complexity of PCs and their far-ranging roles in response to sensory stimuli and motor function regulation, understanding transcriptional differences in this subset of cerebellar cells in ASD may inform on convergent pathways that impact neuronal function.
Transcriptome analysis of gonads and brain of giant freshwater prawn (Macrobrachium rosenbergii): screening and validation of genes related to germ cell development

Macrobrachium rosenbergii is an important cultured shrimp worldwide, and its precocious puberty has led to serious economic losses. Although reproductive sterilization can avoid this problem, little is known about the molecular mechanisms underlying gonadal development and gametogenesis in M. rosenbergii. Here, we conducted transcriptome analysis of the ovaries, testes, and male/female brain tissues of M. rosenbergii to discover germ cell development-related genes. A total of 60,607 unigenes were identified, of which 20,963 unigenes could be functionally annotated. Eighteen candidate genes were identified by Venn diagram analysis, keyword, and known marker search, followed by elimination of low-expression and repetitive genes. Subsequent real-time quantitative reverse transcription polymerase chain reaction and in situ hybridization identified five genes (RAD51, vasa, SPDS, MRR, and Fem-1C) associated with germ cell development—RAD51, vasa, and SPDS were expressed in both male and female gonads, whereas Fem-1C was specifically expressed in the ovary and MRR in the testis. In the ovary, vasa, SPDS, and Fem-1C were mainly expressed in stage 1–3 oocytes, while RAD51 was expressed in stage 2–3 oocytes. In testis, vasa were significantly expressed in spermatogonia and primary spermatocytes, whereas RAD51 and SPDS were only enriched in spermatogonia and MRR in vas deferens. Our research indicates that these five genes are important germ cell development-related genes, of which RAD51, SPDS, and Fem-1C were proven to function in germ cells of this species for the first time. The discovery of these genes could help develop molecular breeding techniques to overcome precocious puberty in M. rosenbergii.
Time series model selection with a meta-learning approach; evidence from a pool of forecasting algorithms

One of the challenging questions in time series forecasting is how to find the best algorithm. In recent years, a recommender system scheme has been developed for time series analysis using a meta-learning approach. This system selects the best forecasting method with consideration of the time series characteristics. In this paper, we propose a novel approach to focusing on some of the unanswered questions resulting from the use of meta-learning in time series forecasting. Therefore, three main gaps in previous works are addressed including, analyzing various subsets of top forecasters as inputs for meta-learners; evaluating the effect of forecasting error measures; and assessing the role of the dimensionality of the feature space on the forecasting errors of meta-learners. All of these objectives are achieved with the help of a diverse state-of-the-art pool of forecasters and meta-learners. For this purpose, first, a pool of forecasting algorithms is implemented on the NN5 competition dataset and ranked based on the two error measures. Then, six machine-learning classifiers known as meta-learners, are trained on the extracted features of the time series in order to assign the most suitable forecasting method for the various subsets of the pool of forecasters. Furthermore, two-dimensionality reduction methods are implemented in order to investigate the role of feature space dimension on the performance of meta-learners. In general, it was found that meta-learners were able to defeat all of the individual benchmark forecasters; this performance was improved even after applying the feature selection method.
Modeling the kinetics of heteromeric potassium channels

Mechanistic mathematical modeling has long been used as a tool for answering questions in cellular physiology. To mathematically describe cellular processes such as cell excitability, volume regulation, neurotransmitter release, and hormone secretion requires accurate descriptions of ion channel kinetics. One class of ion channels currently lacking a physiological model framework is the class of channels built with multiple different potassium protein subunits called heteromeric voltage gated potassium channels. Here we present a novel mathematical model for heteromeric potassium channels that captures both the number and type of protein subunits present in each channel. Key model assumptions are validated by showing our model is the reduction of a Markov model and through observations about voltage clamp data. We then show our model's success in replicating kinetic properties of concatemeric channels with different numbers of Kv1.1 and Kv1.2 subunits. Finally, through comparisons with multiple expression experiments across multiple voltage gated potassium families, we use the model to make predictions about the importance and effect of genetic mutations in heteromeric channel formation.
Does ambient air quality standard contribute to green innovation of enterprises in China? Implications for environmental protection and public health

In the post-COVID-19 era, environmental pollution has been a serious threat to public health. Enterprises are in urgent need of enhancing green technology innovation as the main source of pollutant emissions, and it is necessary for governments to support green innovation of enterprises to reduce pollutant emissions and promote public health. In this context, this paper investigates whether the Ambient Air Quality Standard (AAQS) implemented in 2012 in China contributes to green innovation of enterprises, to provide implications for environmental protection and public health. By using panel data of Chinese A-share listed companies from 2008 to 2020, this study adopts the difference-in-difference model to analyze the policy impact of environmental regulation on green innovation of enterprises and its internal mechanism. The results show that AAQS has significantly improved the green innovation of enterprises. Furthermore, AAQS affects the green innovation of enterprises by virtue of two mechanism paths: compliance cost effect and innovation offset effect. On the one hand, AAQS leads to an increase in production costs of enterprises, thus inhibiting green innovation activities of enterprises. On the other hand, AAQS encourages enterprises to increase R&D investment in green technology, thus enhancing their green innovation. In addition, the impact of AAQS on firms' green innovation has heterogeneous characteristics. Our findings not only enrich the studies of environmental regulation and green innovation of enterprises but also provide policymakers in China and other developing countries with implications for environmental protection and public health improvement.
Effects of combined training during the COVID-19 pandemic on metabolic health and quality of life in sedentary workers: A randomized controlled study

This study aimed to analyze the effects of a combined training (CT) program performed during the first national lockdown due to the COVID-19 pandemic on body composition, metabolic profile, quality of life and stress in sedentary workers, and examines whether changes in the metabolic profile are associated with changes in health-related outcomes which are modifiable by exercise. We evaluated 31 sedentary workers (48.26 ± 7.89 years old). Participants were randomly assigned to a CT group (i.e., performed 16 weeks of exercise) or to a non-exercise control group. The CT program consisted of 16-week of resistance and aerobic exercise. Body composition, glycemic and lipidic profiles, cardiorespiratory fitness (CRF), health-related quality of life and stress levels were assessed pre- and post-intervention. After the intervention period, the CT group demonstrated significantly lower waist and hip circumference (p < 0.05) values than the control group. The control group significantly increased the fasting glucose and HOMA-IR after 16 weeks follow-up (+4.74 mg/dL, p = 0.029; and +0.41 units, p = 0.010, respectively), whiles no significant changes were observed in the CT group in the same parameters (+3.33 mg/dL, p = 0.176; and +0.04 units, p = 0.628, respectively). No changes were observed in the lipid profile for either group (p > 0.05). A significant positive relationship was detected between the change in BMI with the changes in insulin and HOMA-IR (r = 0.643, p = 0.024; and r = 0.605, p = 0.037, respectively). In addition, the changes in CRF were negatively associated with the changes in total cholesterol (r = −0.578, p = 0.049). We observed differences between groups on perceived stress levels and physical, psychological, and environmental domains of quality of life, with the CT group showing better results. Moreover, the CT group improved perceived life satisfaction (+3.17 points, p = 0.038). The findings of the present study suggest that the participants who remained physically active during the first pandemic-related lockdown were able to mitigate the deleterious effects associated with a sedentary lifestyle.
Biorefineries: Achievements and challenges for a bio-based economy

Climate change, socioeconomical pressures, and new policy and legislation are driving a decarbonization process across industries, with a critical shift from a fossil-based economy toward a biomass-based one. This new paradigm implies not only a gradual phasing out of fossil fuels as a source of energy but also a move away from crude oil as a source of platform chemicals, polymers, drugs, solvents and many other critical materials, and consumer goods that are ubiquitous in our everyday life. If we are to achieve the United Nations’ Sustainable Development Goals, crude oil must be substituted by renewable sources, and in this evolution, biorefineries arise as the critical alternative to traditional refineries for producing fuels, chemical building blocks, and materials out of non-edible biomass and biomass waste. State-of-the-art biorefineries already produce cost-competitive chemicals and materials, but other products remain challenging from the economic point of view, or their scaled-up production processes are still not sufficiently developed. In particular, lignin’s depolymerization is a required milestone for the success of integrated biorefineries, and better catalysts and processes must be improved to prepare bio-based aromatic simple molecules. This review summarizes current challenges in biorefinery systems, while it suggests possible directions and goals for sustainable development in the years to come.
Capturing key energy and emission trends in CGE models: Assessment of Status and Remaining Challenges

Limiting global warming in line with the goals in the Paris Agreement will require substantial technological and behavioural transformations. This challenge drives many of the current modelling trends. This article undertakes a review of 17 state-of-the-art recursive-dynamic computable general equilibrium (CGE) models and assesses the key methodologies and applied modules they use for representing sectoral energy and emission characteristics and dynamics. The purpose is to provide technical insight into recent advances in the modelling of current and future energy and abatement technologies and how they can be used to make baseline projections and scenarios 20-80 years ahead. Numerical illustrations are provided. In order to represent likely energy system transitions in the decades to come, modern CGE tools have learned from bottom-up studies. Three different approaches to baseline quantification can be distinguished: (a) exploiting bottom-up model characteristics to endogenize responses of technological investment and utilization, (b) relying on external information sources to feed the exogenous parameters and variables of the model, and (c) linking the model with more technology-rich, partial models to obtain bottom-up- and pathway-consistent parameters.
Review on Nowcasting using Least Absolute Shrinkage Selector Operator (LASSO) to Predict Dengue Occurrence in San Juan and Iquitos as Part of Disease Surveillance System

Dengue which was first detected mainly in South East Asia during 1940s is now a serious public health concern across the subtropical and temperate regions of Americas, Europe and China due to the change in global climate and international travel. Hence, 3.9 billion people in 128 countries are exposed to the danger of potentially fatal dengue infection. This is a review paper of various dengue forecasting methodology to identify suitable models for predicting the disease occurrence in San Juan, Puerto Rico and Iquitos, Peru. Least Absolute Shrinkage Selector Operator (LASSO) model using climatic variables and Google Trends search terms as predictors was proposed to forecast dengue cases four weeks in advance. LASSO’s flexibility in incorporating a variety of predictors and its ease of interpretation present LASSO as a compelling case against the general predictive models. Public health regulators could make use of such nowcasting model to facilitate the timing of vector control and public health campaigns along with the medical resource allocation to cope with potential dengue outbreaks.
Crosslinking of membrane CD13 in human neutrophils mediates phagocytosis and production of reactive oxygen species, neutrophil extracellular traps and proinflammatory cytokines

Aminopeptidase N, or CD13, is a cell membrane ectopeptidase highly expressed in myeloid cells. Through its enzymatic activity, CD13 regulates the activity of several bioactive peptides, such as endorphins and enkephalins, chemotactic peptides like MCP-1 and IL-8, angiotensin III, bradikinin, etc. In recent years, it has been appreciated that independently of its peptidase activity, CD13 can activate signal transduction pathways and mediate effector functions such as phagocytosis and cytokine secretion in monocytes and macrophages. Although neutrophils are known to express CD13 on its membrane, it is currently unknown if CD13 can mediate effector functions in these cells. Here, we show that in human neutrophils CD13 can mediate phagocytosis, which is dependent on a signaling pathway that involves Syk, and PI3-K. Phagocytosis mediated by CD13 is associated with production of reactive oxygen species (ROS). The level of phagocytosis and ROS production mediated by CD13 are similar to those through FcγRIII (CD16b), a widely studied receptor of human neutrophils. Also, CD13 ligation induces the release of neutrophil extracellular traps (NETs) as well as cytokine secretion from neutrophils. These results support the hypothesis that CD13 is a membrane receptor able to activate effector functions in human neutrophils.