Miracle-dz/UniFAR-FTUs huggingface dataset:
The influence of mesoscale land–sea breeze circulation on local wind climatology in the Svalbard fjords of Kongsfjorden and Hornsund

We analyse data series (1992–2013) of wind measurements from meteorological stations in Ny‐Ålesund and Hornsund on Svalbard and then have them compared to surface layer winds from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis. We find significant discrepancies between the local wind direction and directions of wind compatible with the analysis of large‐scale pressure fields. We argue that one of the most important factors controlling wind directions in the Svalbard fjords is the difference in temperature between the neighbouring glaciers and surface sea temperatures of open waters warmed by the west Spitsbergen current. This creates atmospheric circulation patterns similar to the land breeze in temperate climates. We show that the frequency of simultaneous breeze‐type circulation events on the northern and southern fjords of Spitsbergen is highly correlated with sea–land temperature difference on monthly timescales. A Monte Carlo analysis of breeze probabilities rejects the null hypothesis of independent breeze events in both fjords. This result shows that breeze events are not independent where two fjords placed at opposite ends of Spitsbergen's west coast are concerned, and we also posit that the breeze occurrence is largely controlled by the synoptic situation. Such large‐scale wind phenomena should have an impact on air–sea heat fluxes to the east of Spitsbergen.
Impact of perceived social norms on farmers’ behavior of cultivated land protection: an empirical analysis based on mediating effect model

In this study, the impact of social norms on farmers’ behavior of cultivated land protection and the related mechanism was investigated in terms of direct effect and mediating effect and further verified by logistic and mediation effect estimation of different organic fertilizer application behaviors. An empirical analysis of the data collected from Xiajin County of Shandong, China, revealed that (1) perceived social norms can exert significant and positive effects on the behavior of farmers in cultivated land protection; (2) social norms can stimulate farmers to adopt cultivated land protection behaviors by affecting their related value cognition, risk confidence and skills; and (3) the mediating mechanisms varied in the impact of perceived social norms on different cultivated land protection behaviors, with farmyard manure application being significantly moderated by value cognition, risk confidence and skills, in contrast to a major impact of social network on the application of commercial organic fertilizers. This study enriched the theoretical interpretation of the impact of social norms on farmers’ behavior of cultivated land protection and provided useful information on activation of farmers’ cultivated land protection behavior to promote the sustainable development of agriculture.
Rotationally Inelastic Collisions of CN− with He: Computing Cross Sections and Rates in the Interstellar Medium

A newly calculated ab initio potential energy surface is used to compute collision-driven state-changing cross sections and rate coefficients over a range from 5 to 100 K for CN−(1Σ), the smallest anion detected in the interstellar medium, interacting with He, an abundant species in this environment. We compare our presently computed rate coefficients with those previously published for the similar and important systems CN–He, CN-H2, and CN−–H2 to illustrate the broader network of inelastic, state-changing processes for these four systems. We also discuss the size-scaling effects that occur when changing partners from He to H2. We further analyze the differences in size between collision-driven rate coefficients when going from neutral CN to its anion. All the present results are discussed in detail, to provide accurate and realistic data for chemical networks that wish to include the CN− anion in their modeling of astrochemical environments.
Effects of Approximation in Computation on the Accuracy and Performance of Deep Neural Network Inference

Recently, deep learning is at the forefront of the state-of-the-art machine learning algorithms and has shown excellent results in a variety of applications such as medical field, consumer as well as autonomous vehicles. Convolutional Neural Network (CNN) – is the leading deep learning architecture that is mostly applied. However, huge dataset is needed to train with complex architecture to achieve precise learning. Inference can be performed when given a ready CNN model and its weight file to another user. Inference takes time with precise weights and huge dataset. To overcome this problem, and enhance the inference system, approximation computation will be applying in terms of weight for changed of decimal place. The smaller size of the dataset is used in the inference process to reduce the inference time. MobileNetV2 architecture is used with the new weight for inference. Also, open source libraries such as TensorFlow, Keras and python is used. GPU (NVIDIA GeForce GTX 1060 6GB 64 Bit) is used as training and inference platform. Inference time is shortened, and the accuracy of performance for new weights compare with the precise weight only has a small gap which still has a great performance for classification. This work has proved that with 4 decimal places is able to obtain the same accuracy for inference when compared to benchmark with 9 decimal places. Inference time for 4 decimal places is also less than benchmark time.
The complete chloroplast genome of Ilex ‘Emily Bruner’, Ilex cornuta ‘Burfordii’ × Ilex latifolia (Aquifoliaceae)

Abstract Ilex ‘Emily Bruner’ is an important economic plant with ornamental and ecological functions in southeastern China. In this study, we characterized the complete chloroplast (cp) genome sequence of ‘Emily Bruner’ to investigate its phylogenetic relationship. The entire cp genome of ‘Emily Bruner’ was 157,216 bp in length with 37.68% overall GC content, including a large single-copy (LSC) region of 86,721 bp and a small single-copy (SSC) region of 18,427 bp, which were separated by a pair of inverted repeats (IRs) of 52,068 bp. The cp genome contained 135 genes, including 90 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Phylogenetic analysis based on whole cp genome sequences showed that ‘Emily Bruner’ is closest to I. cornuta species.
The complete chloroplast genome sequence of Ormosia formosana

Abstract Ormosia formosana is an important hardwood species and its seeds are popular as decorative jewelry. Currently, this species is threatened in the natural forests due to habitat destruction. Here, we first report the chloroplast genome of O. formosana for future studies in ecology, phylogeny, and conservation. The chloroplast genome of O. formosana is 173,587 bp in length with a GC content of 35.80%. It includes a large single-copy region of 73,550 bp, a small single-copy region of 18,683 bp, and two inverted repeat regions of 40,696 bp and 40,658 bp, respectively. The genome was totally annotated with 135 genes, including 90 protein-coding genes, eight ribosomal RNA genes, and 37 transfer RNA genes. Phylogenetic analysis indicated that O. formosana is most genetically similar to O. boluoensis.
Menopause and frailty: a scoping review

Supplemental Digital Content is available in the text Abstract Importance and Objective: Frailty refers to the decline in physiological reserve capacity caused by the deterioration of multiple physiological systems (brain, endocrine system, immune system, and skeletal muscle), leading to increased vulnerability and decreased stress capacity. Women have a higher prevalence of frailty than men, although the epidemiological factors underlying this phenomenon are not fully understood. Menopause and menopause-related characteristics may be among the contributing factors. Hence, the purpose of this scoping review was to explore the relationship between menopause and frailty. We attempted to summarize information such as the age that menopause occurs, years since menopause, types of menopause, and hormones and inflammatory markers of frailty among postmenopausal women. Methods: PubMed, EMBASE, The Cochrane Library, the Cumulative Index to Nursing and Allied Health Literature and Web of Science, the China National Knowledge Infrastructure, the China Biomedical Literature Service System, Wanfang Database and the WeiPu (VIP) Database were searched from inception until April 3, 2019. Supplementary searches of the references, cited documents, and similar documents of the included literature were also carried out. Discussion and Conclusions: Of 762 papers identified, 15 articles matching the criteria were included. The prevalence of frailty among postmenopausal women ranged from 5.9% to 57.3%. Existing studies suggest that menopause is associated with frailty. Early menopause, hysterectomy, low-free testosterone levels, and high C-reactive protein levels may increase the likelihood of frailty among postmenopausal women. Few original studies have explored the relationship between estrogen and frailty and the results of these studies are conflicting. Changes in hormone and inflammatory cytokine levels may mediate frailty among postmenopausal women. More in-depth research would be required to better understand the physiological and etiological mechanisms of the occurrence of frailty among postmenopausal women.
Application of System-Dynamic Modeling to Improve Distribution Logistics Processes in the Supply Chain

This article presents an approach of improve logistics processes with the system dynamics modeling of two different processes scenarios. System dynamics is used, not only as a causal loop diagram, but calculated measures of end-user satisfaction indicators were provided by experts, as well. Literature review of fundamental definitions and recent ideas in subject of supply chain management (SCM), system dynamics (SD), business processes model and notation (BPMN) and distribution logistics for dozens of major sources, has been made. In the work, methods of expert interviews, content analysis of recent publications, system-dynamic modeling and business process modeling, were used. Developed BPMN-models of distribution logistics business processes are given in Appendices #1 and #2.
Study on equivalent circuit model of lithium titanate battery for rail transit

Recently, lithium titanate batteries have been widely used in energy storage systems, because of their attractive performance and environmentally friendly characteristics. Regarding the state estimation of lithium titanate batteries used in the new energy rail transit vehicles, the research work accomplished in our study mainly includes model-driven state estimation method on short time scale, and ageing mechanisms analysis based on state estimation result on long time scale. The experiments were conducted under constant current and UDDS dynamic conditions using three types of lithium titanate batteries. The results indicate that the maximum voltage error of our new battery model and estimation method is less than 2%.
Critical Disability Studies and ‘Inclusive’ Early Childhood Education: The Ongoing Divide

Critical Disability Studies (cds) provokes the field of early childhood ‘inclusion’ to reflect on its own complex history in order to identify how ableism has played a central role in the field’s development. However, the fields of early childhood ‘inclusive’ education and cds remain largely distinct. This paper explores the ongoing separation between these fields in the context of the United States. I begin by providing a brief overview of the history of cds and early childhood ‘inclusive’ education as distinct fields. Then, I discuss the divide between these two fields, analyzing their contemporary states, and describing the factors that facilitate the distance between them.
Feature selection for malicious android applications using Symmetrical Uncert Attribute Eval method

The fast growth of tablets, smartphones has led to increase the usage of mobile applications. The Android apps have more popularity, however, the applications downloaded from third-party markets could be malware that may threaten the users’ privacy. Several works used techniques to detect normal apps from malicious apps based on mining requested permissions. However, there are some set of permissions that can occur in benign and malignant applications. Redundant features could reduce the detection rate and increase the false positive rate. In this paper, we have proposed feature selection methods to identify clean and malicious applications based on selecting a set combination of permission patterns using different classification algorithms such as sequential minimal optimization (SMO), decision Tree (J48) and Naive Bayes. The experimental results show that sequential minimal optimization (SMO) combining with SymmetricalUncertAttributeEval method achieved the highest accuracy rate of 0.88, with lowest false positive rate of 0.085 and highest precision of 0.910. And the findings prove that feature selection methods enhanced the result of classification.
Development of Indicator of Data Sufficiency for Feature-based Early Time Series Classification with Applications of Bearing Fault Diagnosis

Diagnosis of bearing faults is crucial in various industries. Time series classification (TSC) assigns each time series to one of a set of pre-defined classes, such as normal and fault, and has been regarded as an appropriate approach for bearing fault diagnosis. Considering late and inaccurate fault diagnosis may have a significant impact on maintenance costs, it is important to classify bearing signals as early and accurately as possible. TSC, however, has a major limitation, which is that a time series cannot be classified until the entire series is collected, implying that a fault cannot be diagnosed using TSC in advance. Therefore, it is important to classify a partially collected time series for early time series classification (ESTC), which is a TSC that considers both accuracy and earliness. Feature-based TSCs can handle this, but the problem is to determine whether a partially collected time series is enough for a decision that is still unsolved. Motivated by this, we propose an indicator of data sufficiency to determine whether a feature-based fault detection classifier can start classifying partially collected signals in order to diagnose bearing faults as early and accurately as possible. The indicator is trained based on the cosine similarity between signals that were collected fully and partially as input to the classifier. In addition, a parameter setting method for efficiently training the indicator is also proposed. The results of experiments using four benchmark datasets verified that the proposed indicator increased both accuracy and earliness compared with the previous time series classification method and general time series classification.
A Simple Sample Processing Protocol and Multiplex PCR for Direct Detection of MRSA from Uncultured Clinical Samples—A Pilot Study

Phenotypic tests have limited discrimatory power to identify closely related members of genus Staphylococcus and particularly for identification of S. aureus. 157 isolates of S. aureus obtained from different clinical specimens were included in our study. To present a demonstration of our method’s sensitivity and ability to correctly detect S. aureus from uncultured clinical specimen, 30 known S. aureus positive but leftover uncultured clinical specimens from clinical microbiology laboratory were processed by our protocol and analyzed. All the 30 clinical specimens were confirmed as S. aureus among which 26 specimen were identified as MRSA and the remaining 4 as MSSA. These 30 clinical specimens used in the study showed 100% correlation with coagulase test and Cefoxitin disc diffusion method. Though commercial molecular diagnostic kits are available for detecting MRSA from swabs, this is probably the first time that multiplex PCR is being demonstrated directly on a variety of uncultured clinical specimens.
The Costs of Conflict and Support for the Use of Force: Accounting for Information Equivalence in Survey Experiments

Abstract How do the costs of conflict influence public support for the use of force? Existing research finds that weapons that eliminate the possibility of military casualties, such as drones, increase popular support for engaging in conflict. We argue that this effect may be overstated because the choice of weapons technology is endogenous to conflict. Leaders may select to use drones in conflicts where the risk of harm to ground forces is especially high. To address this, we replicate and extend the research design of Walsh and Schulzke across three survey experiments. The key innovation in our experiments is that subjects are led to believe that the choice of attack type – drones or ground troops – is determined by weather conditions rather than strategic considerations. We find that support for military action does not differ across treatments in which subjects are told that the attack involves drone strikes or ground troops.
Feature identification and extraction of urban built-up surfaces and materials in AVIRIS-NG hyperspectral imagery

Abstract Regular monitoring and precise mapping of urban environment is required by various applications. In this paper, a new method is proposed, in which different combinations of feature bands have been utilized for extraction of built-up surfaces, sub-surfaces and materials in different levels (Level-1, 2 and 3) using AVIRIS-NG hyperspectral imagery of Jodhpur, Rajasthan region of India. Features identified in this study are based on spectral indices, major principal components and fractional abundances, in which first combination is developed using spectral indices and fractional abundances while second is made using spectral indices and major principal components and finally third using combination of all the aforesaid features. It is observed that the combined form of all the aforementioned features produces better extraction results than the other two while combination of spectral indices and fractional abundances may be more useful than the combined form of spectral indices and major principal components.
Remediation of Artificially Hydrocarbon Polluted Vadose Zone Soil in Glass Column through Percolation with Solution of Nutrient, Nutrient-Surfactant or Surfactant

Remediation of hydrocarbon polluted vadose zone (HPVZ) through percolation with solution of nutrient, nutrient-surfactant, or surfactant in glass columns was investigated in this study using standard methods. Percolated liquids from the columns and soils retrieved at the end of the experiment were analyzed for nitrate, phosphate, sulphate, total-petroleum hydrocarbon, and selected microbial groups. Results obtained showed that there were nitrate, phosphate, and sulphate in the percolated liquids. Cumulative hydrocarbon in the percolated liquids was 5.35 – 7.59 % of cumulative hydrocarbon start-up concentration in the columns. Cumulative hydrocarbon attenuation across soil layers in column flooded with solution of nutrients (column NT), nutrient-surfactant (column NTS), and surfactant (column SF) were 89.29, 95.27, and 66.92 % respectively. There was more phosphate reduction in column NTS, and more sulphate reduction in column NT. Hydrocarbon-utilizing fungi in columns NT and NTSincreased from 3.5 Log10 CFU.g-1 to between 4.0 – 5.0 Log10 CFU.g-1, whereas a decrease was observed for column SF. Hydrocarbon-utilizing bacteria in all the columns increased from between 1.0 – 2.5 Log10 CFU.g-1 to between 2.0 - 3.5 Log10 CFU.g-1. Emergence of hydrocarbon utilization among anaerobic bacteria population was also observed in all the columns. It is concludedthat percolation with nutrient-surfactant solution will be more effective in remediation of HPVZ, and that consequential migration of nutrients alongside hydrocarbons into groundwater canaid in enhancing biodegradation of the infiltrated hydrocarbons. Keywords: Biodegradation; petroleum hydrocarbons; vadose zone; inorganic nutrients; surfactant
Development of a visible marker trait based on leaf sheath–specific anthocyanin pigmentation applicable to various genotypes in rice

To overcome a limitation to the breeding of autogamous crops, recurrent selection using transgenic male sterility (RSUTMS) has been proposed. In this system, negatively or positively selectable marker traits are required along with dominant transgenic male sterility. Anthocyanin pigmentation is an excellent marker trait. Two regulatory genes for MYB and bHLH and a structural gene for DFR are required for anthocyanin pigmentation in rice. Therefore, to apply anthocyanin pigmentation as a marker trait in various rice genotypes, coordinated expression of the three genes is required. In this study, we developed a leaf sheath–specific promoter and introduced three genes—DFR and C1/Myb, driven by the 35S promoter, and OsB2/bHLH, driven by the leaf sheath–specific promoter—into the rice genome. Leaf sheath–specific pigmentation was confirmed in all seven genotypes tested, which included japonica and indica cultivars. Analysis of genome sequence data from 25 cultivars showed that the strategy of conferring leaf sheath–specific anthocyanin pigmentation by introduction of these three genes would be effective for a wide range of genotypes and will be applicable to RSUTMS.
Ambivalent sexism in adolescence: The relationship between family socialization styles and ambivalent sexism in adolescence

The aims of the present study are to identify the role that family socialisation styles play in ambivalent sexism and whether differences in sexism can be attributed to gender. We used a sample of 207 adolescents (56.5% girls), all of whom attended state schools and were aged between 14 and 18 years old, with an average age of 16.2 (SD = 1.7). The instruments used were the Ambivalent Sexism Inventory (ASI) consisting of two factors – hostile sexism and benevolent sexism – and the Family Socialization Scale (SOC-30) made up of four subscales: support, punishment/coercion, overprotection/control, and reprobation. The results show that boys presented higher levels of ambivalent sexism than girls and the reprobation of adolescents was the family socialization type that had the strongest associations with ambivalent sexism scales in both genders. The data suggest that family socialisation dynamics play an important role in the acquisition and retention of sexist attitudes.
Intestinal Bowel Wall Thickening Analysis on MDCT: A Retrospective Study

Background: The aim of this study was to determine the causes and establish the significance of bowel wall thickening on abdominal computed tomography. Subjects and Methods: Consecutive abdominal CT’s between January 2019 and December 2019 with findings of duodenal, jejunal, ileal and colonic ‘bowel wall thickening ‘on the formal report was reviewed retrospectively. The patients history, inpatient course & subsequent colonoscopy and /or operative findings were also reviewed. Results: Of the 88 consecutive CT abdomen’s identified, infection (26.1%) and new cancer (22.7%) were the most common causes. Bowel obstruction (12.5%) and Inflammatory Bowel Disease (10.2%) were relatively uncommon causes. Overall 40/88 (45%) & 14/88 (15%) patients underwent subsequent colonoscopy and progressed directly to surgery respectively; of these 36/40 (90%) of the former and 14/14 (100%) of the latter showed findings similar to CT. Conclusion: When thickening of the bowel is detected with CT; pattern of the thickening, accompanying findings, history of the patient and clinical features must be evaluated together to reach prompt and correct diagnosis. All cases detected with bowel wall thickening on CT abdomen should warrant a subsequent colonoscopy.