Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolutionary Analysis of the Steroidogenic Acute Regulatory Protein-Related Lipid Transfer Domain and Its Response to Salt Stress In Vitis Vinifera

This study aimed to enhance the understanding of the steroidogenic acute regulatory protein-related lipid transfer (START) domain in Vitis vinifera. A total of 23 members of the VvSTARD gene family were found, which could be divided into five groups. The analyses of the gene codon preference, selective pressure, and tandem replication events of the VvSTARD, AtSTARD, and OsSTARD genomes indicated that tandem replication events occured in grapes, Arabidopsis, and rice genomes. Eight lipid transporter proteins were found in the tertiary structure of the STARD gene family in grapes. The analysis of the expression profiles of the three species microarrays showed that the expression sites of the STARD gene and the response to abiotic stress in the same subgroup had similar characteristics. In addition, quantitative real-time polymerase chain reaction (qRT-PCR) was used to analyze the expression of the STARD gene family in grape leaves in response to different hormones and abiotic stresses, and the obtained results were the same as those predicted by the cis-elements and the expression profiles. Furthermore, 35S:STARD5:EGFP was successfully constructed to verify the subcellular prediction results, and the results showed that STARD5 was located in the nucleus. Through the identification of salt tolerance of transgenic tomato, STARD5 was found to regulate the salt stress of plants. Collectively, these data indicated that the VvSTARD gene family plays an important role in response to salt stress.
Global, High-Resolution, Reduced-Complexity Air Quality Modeling Using InMAP(Intervention Model for Air Pollution)

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many policy scenarios at high spatial resolution. However, air quality modeling typically has high requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with 4 km horizontal grid cell widths in cities. We evaluate Global InMAP performance both against measurements and a state-of-the-science chemical transport model, GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%. Global InMAP can be run on a desktop computer; simulations here took 2.6–4.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate air pollution policy assessment worldwide, providing a tool for reducing the deaths where they occur most.
Prediction of Synoptic-Scale Sea Level Pressure Over the Indian Monsoon Region Using Deep Learning

The synoptic-scale (3–7 days) variability is a dominant contributor to the Indian summer monsoon (ISM) seasonal precipitation. An accurate prediction of ISM precipitation by dynamical or statistical model remains a challenge. Here, we show that the sea level pressure (SLP) can be used as a proxy to predict the active-break cycle as well as the genesis of low-pressure systems (LPSs), using a deep learning model, namely convolutional long short-term memory (ConvLSTM) networks. The deep learning model is able to reliably predict the daily SLP anomalies over central India and the Bay of Bengal at a lead time of 7 days. As the fluctuations in SLP drive the changes in the strength of the atmospheric circulation, the prediction of SLP anomalies is useful in predicting the intensity of ISM. A comparison of the ConvLSTM predicted SLP with the forecast of a conventional numerical weather prediction model indicates that the deep learning model possesses better skill in capturing the synoptic-scale SLP fluctuations over central India and Bay of Bengal.
Analysis on Characteristics of Vegetation and Soil Bacterial Community under 20 Years’ Restoration of Different Tree Species: A Case Study of the Qinling Mountains

Afforestation with different tree species formed different vegetation patterns, and altered soil properties and the composition and diversity of the soil bacterial community. In order to analyze the difference characteristics of vegetation, soil and bacterial community after 20 years’ restoration of different tree species, we investigated changes in vegetation (tree, shrubs, and herbs), soil properties and the soil bacterial community composition in the topsoil (0–10 cm) following afforestation of P. asperata Mast. and L. kaempferi (Lamb.) Carr.on the southern slope of the Qinling mountains. The results showed that, within a 20-year recovery period, the restorative effect of L. kaempferi was better than that of P. asperata, for alpha diversity and biomass of vegetation, composition and diversity of soil bacterial community were all preferable under nearly same environmental conditions if just taking these indices into consideration. Additionally, biodiversity of L. kaempfer was much richer than that of P. asperata. Our observations suggest that soil physicochemical properties, soil bacterial community composition and diversity following afforestation were mainly affected by tree species. The results could explain our hypothesis to some extent that a planted forest with quick growth speed and sparse canopy has higher biomass productivity and alpha diversity of ecosystem.
Recovery of samarium (III) from aqueous solutions by poly(sodium 4‐styrenesulfonate) assisted‐ultrafiltration

Polyelectrolyte‐assisted ultrafiltration (PAUF) was investigated for the removal of samarium (III) from aqueous solutions by using poly(sodium 4‐styrenesulfonate) (PSS) as a complexing agent. The ultrafiltration studies were carried out using a tangential cell system, equipped with a polyethersulfone membrane. Factors affecting the samarium ions retention, such as applied pressure, polyelectrolyte concentration, pH, and ionic strength, were investigated. After optimization, the best operating conditions can be obtained in order to achieve high levels of recovery. Experimental results indicate that the retention of samarium ions increases respectively with applied pressure and polyelectrolyte concentration. A maximum retention was obtained at 2 × 10−4 mol L−1 PSS concentration and 3 bars transmembrane pressure. Samarium retention by PSS assisted ultrafiltration was influenced by the pH varying from 5 to 9. The study of the ionic strength effect has shown a retention decrease with the salt concentration increase. © 2016 American Institute of Chemical Engineers Environ Prog, 35: 1091–1097, 2016
Estimating Causal Effects When the Treatment Affects All Subjects Simultaneously: An Application

Several important questions cannot be answered with the standard toolkit of causal inference since all subjects are treated for a given period and thus there is no control group. One example of this type of questions is the impact of carbon dioxide emissions on global warming. In this paper, we address this question using a machine learning method, which allows estimating causal impacts in settings when a randomized experiment is not feasible. We discuss the conditions under which this method can identify a causal impact, and we find that carbon dioxide emissions are responsible for an increase in average global temperature of about 0.3 degrees Celsius between 1961 and 2011. We offer two main contributions. First, we provide one additional application of Machine Learning to answer causal questions of policy relevance. Second, by applying a methodology that relies on few directly testable assumptions and is easy to replicate, we provide robust evidence of the man-made nature of global warming, which could reduce incentives to turn to biased sources of information that fuels climate change skepticism.
Selected ‘Starter Kit’ energy system modelling data for Gambia (#CCG)

Energy system modelling can be used to assess the implications of different scenarios and support improved policymaking. However, access to data is often a barrier to starting energy system modelling in developing countries, thereby causing delays. Therefore, this article provides data that can be used to create a simple zero order energy system model for Gambia, which can act as a starting point for further model development and scenario analysis. The data are collected entirely from publicly available and accessible sources, including the websites and databases of international organizations, journal articles, and existing modelling studies. This means that the dataset can be easily updated based on the latest available information or more detailed and accurate local data. These data were also used to calibrate a simple energy system model using the Open Source Energy Modelling System (OSeMOSYS) and two stylized scenarios (Fossil Future and Least Cost) for 2020–2050. The assumptions used and results of these scenarios are presented in the appendix as an illustrative example of what can be done with these data. This simple model can be adapted and further developed by in-country analysts and academics, providing a platform for future work.
Implementation and Evaluation of Mobile Shopping Services Based on RFID Sensing Technology

We have developed a new shopping model that integrates modern sensing technologies. A combined technology acceptance model and theory of planned behavior (C-TAM-TPB) model was also employed to examine the acceptance of this mobile service among seniors. As the sensing technology, we proposed a radio frequency identification (RFID) sensing technology based on the Internet of Things (IoT) to construct a platform for a mobile shopping service. In addition, a merchandise search, shopping guide, advertising, and mobile payment were also equipped as elements within the system. The acceptance of a mobile service by seniors may depend on whether its interface is easy to learn and whether its functions are easily understandable. These are key factors affecting seniors’ attitude toward the mobile service. The results of our study indicate that seniors’ perceptions of the mobile service (perceived usefulness and ease of use of RFID sensing) positively affect their attitude toward using the mobile service, which will further affect their purchase intention. The results also offer an insight into the needs of seniors and highlight some social issues about elderly care.
Consumers’ Behavioral Intention Towards Smartwatch Adoption in Malaysia: A Concept Paper

The wide-ranging features of a smartwatch have driven the rapid growth of the smartwatch market as they pique the users’ interests by offering interactive technology that simultaneously promotes fitness and tracks health. Nevertheless, the factors influencing smartwatch adoption among individuals are yet to be comprehended despite the ever-growing popularity of smartwatch usage. Hence, to understand the possible factors in detail, a research model is proposed to indicate the influential underlying factors relative to smartwatch adoption in the Malaysian populace. This study will examine the four proposed dimensions of perceived benefits, healthology, IT innovation, and smartwatch as luxury products. Online questionnaires will be used to collect the research data, while SPSS will be used to run both preliminary research and descriptive analyses, PLS-SEM will be used to further analyze the model.
Preparation of red and grey elemental selenium for food fortification

In recent years, the importance of nanomaterials in food science, medicine, etc. has been increasing quickly. Herein, organic and inorganic red selenium nanoparticles synthesised by the reduction of sodium selenite with chemical and biological reducing agents. Grey hexagonal form in aqueous and powder was assembled at a high temperature of 85 °C for 10 min. Also, selenium enriched yogurt powder was made that contained about 2,000 mg kg−1 selenium, 93.8% of which is in nano form with a size of 50–500 nm. The synthesised nanoparticles were characterised by Dynamic Light Scattering Particle Size Analyzer (DLS), X-ray Diffraction Analysis (XRD), Scanning Electron Microscope (SEM) and Transmission Electron Microscope (TEM). The prepared SeNPs could be promising additive for a wide range of applications.
Beneficiation and Physiochemical Characterization of Coal Deposits in Achibo-Sombo Area, South-Western Ethiopia

This study was conducted to upgrade the quality of Achibo-Sombo coal deposits by physiochemical beneficiation methods particularly by using froth floatation technique to minimize the ash and sulfur content from coal particles. During the floatation test, proximate, ultimate, calorific value, functional groups, surface morphology and crystal structure analysis of Achibo-Sombo coal was carried out through different methods. The moisture content of a raw sample and treated sample is found in the range of 11.81 to 20.27% and 8.12 to 14.02 % respectively. The volatile matter is ranging from 22.74 to 34.85 % for raw coal and 21.92 to 30.64 % for treated coal samples. The ash content of the raw coal sample is ranging from 22.47 to 36.58 % which became in the range 7.49 to 13.62 % after treatment. The fixed carbon is also changed from 23.85 -38.31% of raw sample to 44.47 55.87 % for treated coal samples. The calorific value of a raw sample is found in the ranges of 5838.46 Btu/lb. to 9531.29 Btu/lb. whereas for treated coal samples it is found in the ranges of 9438.12 Btu/lb. to 11756.63 Btu/lb. The sulfur and nitrogen contents of the raw coal sample which were ranged from 0.57 to 1.9 % 1.22 to 1.44 % are reduced to 0.25 to 0.41% -0.52 to 0.92% respectively after treatment. Generally, the Achibo-Sombo raw coal is falling under the coal grade of lignite B to sub-bituminous B whereas the treated coal sample is grouped under sub-bituminous C to high volatile bituminous C. Accordingly, the results obtained indicate that the Achibo coal streams are upgraded relatively with better calorific value and fixed carbon and with lowest ash contents as compared to samples collected from other sites.
Study of serum ceruloplasmin and zinc in type 2 diabetes mellitus

Background and objective: Ceruloplasmin is the major copper-carrying protein in the blood and plays a role in iron metabolism. Zinc is an essential trace element for human health, which activates about 200 enzymes. This study aimed to evaluate the serum ceruloplasmin and zinc and the factor affecting them in type 2 diabetes. Methods: A case-control study was carried out from November 2018 to June 2019 in collaboration between the biochemistry unit at the College of Medicine and the biochemistry unit at the College of Nursing, Hawler Medical University. The study included 100 type 2 diabetic patients (group 1) and 100 healthy individuals (group 2) to evaluate the serum ceruloplasmin and zinc in both groups. Results: The mean value of serum ceruloplasmin was significantly (P <0.001) higher in type 2 diabetic patients (55.9 ± 1.26 mg/dL) than that of healthy individuals (36.65 ± 0.71 mg/dL). The mean value of serum zinc was significantly (P <0.001) lower in type 2 diabetic patients (39.19 ± 0.46 ug/dL) compared with controls (65.27 ± 2.5 ug/dL). There was a significant positive correlation between serum ceruloplasmin and the age of diabetic patients (P <0.001). There was a significant negative correlation between serum ceruloplasmin and serum zinc of diabetic patients (P <001). There was no significant correlation between serum ceruloplasmin and body mass index of diabetic patients (P = 0.928). Conclusion: Based on the findings of the present study, we concluded that high serum ceruloplasmin and low zinc were associated with type 2 diabetics. Keywords: Serum ceruloplasmin; Age; BMI; Zinc; Type 2 diabetes mellitus.
Response of Surface Erosion to Crustal Shortening and its Influence on Tectonic Evolution in Fold‐and‐Thrust Belts: Implications From Sandbox Modeling on Tectonic Geomorphology

Structural deformation affects surface processes and the consequent distribution of tectonic stress and structural deformation patterns via crustal isostasy. The associated processes and mechanisms are widely concerned topics in tectonic geomorphology. In this study, we discuss the interaction between tectonic deformation and surface processes in fold‐and‐thrust belts by sandbox experimental modeling. The tectonic deformation patterns under different conditions are studied, including the occurrence of detachment and the different crustal shortening rates. Furthermore, we discussed the influence of surface erosion and sedimentation on the spatial distribution, morphology, amplitude, and process of tectonic deformation. The results show that the occurrence of plastic detachment links the interaction of surface erosion and tectonics such as deformation patterns. Thin‐skinned structures develop when plastic detachment occurs, thus amplifying surface processes. In turn, the erosion and deposition affect the position and morphology of new structures as well as the lateral propagation and connection of isolated structures. Different shortening rates lead to different propagation distances and structure arrangements. These different tectonic conditions result in diverse drainage evolution and the specific processes of surface erosion and deposition. In general, structural development is controlled by both endogenic forces and surface erosion and deposition processes. The physical properties of detachments and crustal shortening rates play an important role in linking deep tectonic activity and surface processes. These results are comparable to natural examples, such as the fold‐and‐thrust belts along the Tianshan Mountains, thus providing new clues for understanding the mechanism of the interaction between endogenic tectonic activity and surface processes.
I scratched your back; should you not scratch mine? The expectation of reciprocity in 4- to 6-year-old children following a prosocial investment

ABSTRACT Prosocial behaviours appear very early in a child’s development, suggesting that they are the basis for building social relationships. Previous studies have shown that two main factors influence decisions about pro-social behaviour: in-group membership and reciprocity. The main aim of this study was to investigate which of these motives children consider more important in making decisions about who to ask for help, resources, cooperation, or comfort. Children were given a choice to ask for those favours from either a friend or an out-group child who was recently a recipient of the child’s prosocial behaviour. In a study on children aged 4 to 6 years old with two research samples (sample 1: n = 60, sample 2: n = 71), we showed that reciprocity of recent prosocial behaviour is a stronger predictor than friendship when choosing a character in a helping need, resource sharing or cooperation related need, but not for a comforting need. Furthermore, this effect seems to be limited to reciprocating only the same type of pro-social behaviour.
Global Energy Production Computation of a Solar-Powered Smart Home Automation System Using Reliability-Oriented Metrics

This paper presents a modified global energy production computation formula that replaces the traditional Performance Ratio (PR) with a novel Solar Reliability Factor (SRF) for mobile solar tracking systems. The SRF parameter describes the reliability and availability of a dual-axis solar tracker, which powers a smart home automation system entirely by using clean energy. By applying the SRF in the global energy production formula of solar tracking systems, we can predict the energy generation in real time, allowing proper energy management of the entire smart home automation system. Regarding static deployed Photovoltaic (PV) systems, the PR factor is preserved to compute the power generation of these devices accurately. Experimental results show that the energy production computation constantly fluctuates over several days due to the SRF parameter variation, showing a 26.11% reduction when the dual-axis solar tracker’s availability is affected by system errors and maximum power generation when the solar tracking device is operating in optimal conditions.
Investigating the Impact of Root-Lesion Nematodes (Pratylenchus thornei) and Crown Rot (Fusarium pseudograminearum) on Diverse Cereal Cultivars in a Conservation Farming System

In two experiments on a farm practicing conservation agriculture, the grain yield of a range of wheat cultivars was significantly (p < 0.001) negatively related to the post-harvest population densities of Pratylenchus thornei in the soil profile to 45 cm depth. In a third and fourth experiment with different rotations, methyl bromide fumigation significantly (p < 0.05) decreased (a) a low initial population density of P. thornei in the soil profile to 90 cm depth and (b) a high initial population of P. thornei to 45 cm depth, and a medium level of the crown rot fungus, Fusarium pseudograminearum, at 0–15 cm depth to a low level. For a range of wheat and durum cultivars, grain yield and response to fumigation were highly significantly (p < 0.001) related to (a) the P. thornei tolerance index of the cultivars in the third experiment, and (b) to both the P. thornei tolerance index and the crown rot resistance index in the fourth experiment. In the latter, grain yield was significantly (p < 0.001) positively related to biomass at anthesis and negatively related to percentage whiteheads at grain fill growth stage. One barley cultivar was more tolerant to both diseases than the wheat and durum cultivars. Crop rotation, utilizing crop cultivars resistant and tolerant to both P. thornei and F. pseudograminearum, is key to success for conservation farming in this region.
Relationships between humus chemical composition and soil factors in typical tobacco growing regions in China

Relationships between humus chemical composition and soil factors in typical tobacco-growing regions were analyzed.Results showed that:(1) carbon content(TC) of soil humus ranged from10 g/kg to 20 g/kg,with average of 15.25 g/kg.Proportions of humic acid(HA),fulvic acid(FA) and humin(HM) in humus carbon content were distributed in 11.05%-32.15%,12.00%-36.28% and 38.43%-68.23%,respectively.Most of HA/FA ratios ranged from 0.7 to 1.3;(2) TC in tobacco growing regions in southeast China was significantly higher than in other regions,with Huanghuai region was the lowest.The HA/FA ratio of tobacco growing regions in southeast China was significantly higher than in others,with an average value of 1.14,while in other regions it was less than 1;(3) Carbon levels of TC and humus composition in paddy soil were the highest followed by purple,red,and brown soils.The humification degree of paddy soil was also much higher than others;(4) soil pH values were significantly negatively correlated with humus composition.Alkali-hydrolyzable nitrogen content increased with decreasing soil FA/TC,or increasing HA/FA.