Miracle-dz/UniFAR-FTUs huggingface dataset:
AIS Electronic

Enterprise systems (ES) are a priority in China. The main literature on ES is dominated by survey-based research on large Western firms, which typically focuses on the user firm only and before-and-after effects of implementation. Analyses using critical success factors and technology adoption theories feature widely. China-based research on ES is relatively limited and significantly influenced by Western-based approaches. In contrast, this research examines ES adoption and implementation in Chinese SMEs, from a process perspective, through four case studies. It argues that ES adoption and implementation is a complex process that involves multiple stakeholders, and exploring the interplay among them explains why and how an ES is adopted and implemented. Actor-network theory informs the main analysis. Importantly, the unit of analysis (UOA) is the user-SME and the technology provider combined. The findings challenge the dominant user-centred adoption theories, and the importance of the technology provider in the sociotechnical role
Calorie Estimation From Pictures of Food: Crowdsourcing Study

Background Software designed to accurately estimate food calories from still images could help users and health professionals identify dietary patterns and food choices associated with health and health risks more effectively. However, calorie estimation from images is difficult, and no publicly available software can do so accurately while minimizing the burden associated with data collection and analysis. Objective The aim of this study was to determine the accuracy of crowdsourced annotations of calorie content in food images and to identify and quantify sources of bias and noise as a function of respondent characteristics and food qualities (eg, energy density). Methods We invited adult social media users to provide calorie estimates for 20 food images (for which ground truth calorie data were known) using a custom-built webpage that administers an online quiz. The images were selected to provide a range of food types and energy density. Participants optionally provided age range, gender, and their height and weight. In addition, 5 nutrition experts provided annotations for the same data to form a basis of comparison. We examined estimated accuracy on the basis of expertise, demographic data, and food qualities using linear mixed-effects models with participant and image index as random variables. We also analyzed the advantage of aggregating nonexpert estimates. Results A total of 2028 respondents agreed to participate in the study (males: 770/2028, 37.97%, mean body mass index: 27.5 kg/m2). Average accuracy was 5 out of 20 correct guesses, where “correct” was defined as a number within 20% of the ground truth. Even a small crowd of 10 individuals achieved an accuracy of 7, exceeding the average individual and expert annotator’s accuracy of 5. Women were more accurate than men (P<.001), and younger people were more accurate than older people (P<.001). The calorie content of energy-dense foods was overestimated (P=.02). Participants performed worse when images contained reference objects, such as credit cards, for scale (P=.01). Conclusions Our findings provide new information about how calories are estimated from food images, which can inform the design of related software and analyses.
High Current Tests over Conductive Fabrics

Lightning, as a powerful natural phenomenon, is dangerous for living beings, equipment, structures, and buildings. The protection principle against lightning currents is to divert and conduct them safely into ground. Therefore, materials and components of lightning protection systems (LPS) must be able to bear lightning currents on the order of tens of kiloamperes. On the search of light materials for LPS, we performed several laboratory tests with high-current lightning-type impulses over some different types of commercial conductive fabrics. The samples used as object under test (OUT) were pieces of 10 cm × 10 cm from four different types of conductive fabrics, including rip-stop, plain-weave and non-woven commercial ones. The OUTs were subject to four 4/10 μs impulsive currents up to 20 kA generated by an Impulse Current Generator. Were taken images of before and after tests and both current and voltage on the OUTs were recorded. Moreover, Scanning Electron Microscope inspections were performed after the tests, to understand some particular patterns presented on the fabric surfaces. A rip-stop type of conductive textile looks that withstands better the four impulses applied. The results of carried out tests suggest that is possible to use some conductive fabrics as part of a LPS, particularly in lightweight and portable applications required in outdoor conditions, such as in the cases of mobile shelters and tents.
Assessment of Soil Moisture Information Content in Level-1 Data from Low-Frequency Active and Passive Microwave Sensors

Low-frequency microwave brightness temperature and backscatter observations are sensitive to surface soil moisture, a key variable for applications like numerical weather prediction, drought monitoring and climate modeling. With ESA's Soil Moisture and Ocean Salinity (SMOS) mission and NASA's Soil Moisture Active Passive (SMAP) mission, two L-band radiometers dedicated to soil moisture monitoring are currently in orbit. In addition, operational soil moisture products exist based on EUMETSAT MetOp C-band advanced scatterometer (ASCAT) and JAXA GCOM-W multifrequency radiometer (AMSR2) data. This study aims to assess the information content of Level-l data from active and passive microwave sensors for soil moisture estimation. Specific focus lies on the comparison between frequencies (L-band, C-band, X-band) and sensor types (active and passive) as well as the added value of multi-angular brightness temperature observations (e.g. from SMOS) with respect to fixed incidence angle observations. The study will provide insights into the suitability of different sensor types for soil moisture estimation irrespective of the individual Level-2 retrieval algorithm specifics. The results shall assist the definition of new observation concepts and the identification of synergies between planned or existing satellite missions.
Occlusion-Aware Unsupervised Learning of Monocular Depth, Optical Flow and Camera Pose with Geometric Constraints

We present an occlusion-aware unsupervised neural network for jointly learning three low-level vision tasks from monocular videos: depth, optical flow, and camera motion. The system consists of three different predicting sub-networks simultaneously coupled by combined loss terms and is capable of computing each task independently on test samples. Geometric constraints extracted from scene geometry which have traditionally been used in bundle adjustment or pose-graph optimization are formed as various self-supervisory signals during our end-to-end learning approach. Different from prior works, our image reconstruction loss also takes account of optical flow. Moreover, we impose novel 3D flow consistency constraints over the predictions of all the three tasks. By explicitly modeling occlusion and taking utilization of both 2D and 3D geometry relationships, abundant geometric constraints are formed over estimated outputs, enabling the system to capture both low-level representations and high-level cues to infer thinner scene structures. Empirical evaluation on the KITTI dataset demonstrates the effectiveness and improvement of our approach: (1) monocular depth estimation outperforms state-of-the-art unsupervised methods and is comparable to stereo supervised ones; (2) optical flow prediction ranks top among prior works and even beats supervised and traditional ones especially in non-occluded regions; (3) pose estimation outperforms established SLAM systems under comparable input settings with a reasonable margin.
Complementary Feeding Practices for South Asian Young Children Living in High-Income Countries: A Systematic Review

Sub-optimal nutrition among South Asian (SA) children living in high-income countries is a significant problem. High rates of obesity have been observed in this population, and differential complementary feeding practices (CFP) have been highlighted as a key influence. Our aim was to undertake a systematic review of studies assessing CFP in children under two years of age from SA communities living in high-income countries, including dietary diversity, timing, frequency and promotors/barriers. Searches covered January 1990–July 2018 using MEDLINE, EMBASE, Global Health, Web of Science, BanglaJOL, OVID Maternity and Infant Care, CINAHL, Cochrane Library, POPLINE and World Health Organisation (WHO) Global Health Library. Eligible studies were primary research on CFP in SA children aged 0–2 years. Search terms were “children”, “feeding” and “South Asian”, and derivatives. Quality appraisal used the Evidence for Policy and Practice Information (EPPI) Weight of Evidence scoring. From 50,713 studies, 13 were extracted with ten from the UK, and one each from the USA, Canada and Singapore. Sub-optimal CFP were found in all studies. All ten studies investigating timing reported complementary feeding (CF) being commenced before six months. Promoters/barriers influencing CFP included income, lack of knowledge, and incorrect advice. This is the first systematic review to evaluate CFP in SA children living in high-income countries and these findings should inform the development of effective interventions for SA infants in these settings.
Desnet: Deep Residual Networks for Descalloping of Scansar Images

Scalloping is one of the critical problems in ScanSAR images. It not only affects image visualization, but also influences the quantitative applications such as surface wind and wave retrievals in the ocean area. The existing method of descalloping needs artificial parameter setting and lacks generality in the image domain. A novel deep neural network based on residual learning for descalloping of ScanSAR images is proposed in this paper. The proposed method can eliminate scalloping patterns and has strong adaptive ability, which can handle inhomogeneous scalloping patterns and different scenarios. Experiments on GF-3 ScanSAR images verify the good performance of this method. The code for our models is available online.1
Genomewide SNP markers breathe new life into phylogeography and species delimitation for the problematic short‐necked turtles (Chelidae: Emydura) of eastern Australia

Understanding the evolutionary history of diversifying lineages and the delineation of evolutionarily significant units and species remains major challenges for evolutionary biology. Low‐cost representational sampling of the genome for single nucleotide polymorphisms shows great potential at the temporal scales that are typically the focus of species delimitation and phylogeography. We apply these markers to a case study of a freshwater turtle, Emydura macquarii, whose systematics has so far defied resolution, to bring to light a dynamic system of substantive allopatric lineages diverging on independent evolutionary trajectories, but held back in the process of speciation by low level and episodic exchange of alleles across drainage divides on various timescales. In the context of low‐level episodic gene flow, speciation is often reticulate, rather than a bifurcating process. We argue that species delimitation needs to take into account the pattern of ancestry and descent of diverging lineages in allopatry together with the recent and contemporary processes of dispersal and gene flow that retard and obscure that divergence. Underpinned by a strong focus on lineage diagnosability, this combined approach provides a means for addressing the challenges of incompletely isolated populations with uncommon, but recurrent gene flow in studies of species delimitation, a situation likely to be frequently encountered. Taxonomic decisions in cases of allopatry often require subjective judgements. Our strategy, which adds an additional level of objectivity before that subjectivity is applied, reduces the risk of taxonomic inflation that can accompany lineage approaches to species delimitation.
Adaptive neurogenesis in the cerebral cortex and contralateral subventricular zone induced by unilateral cortical devascularization: Possible modulation by dopamine neurotransmission

Understanding endogenous neurogenesis and neuronal replacement to mature circuits is a topic of discussion as a therapeutic alternative under acute and chronic neurodegenerative disorders. Adaptive neurogenic response may result as a result of ischemia which could support long‐term recovery of behavioral functions. Endogenous sources of neural progenitors may be stimulated by changes in blood flow or neuromodulation. Using a mouse model of unilateral cortical devascularization, we have observed reactive neurogenesis in the perilesional cortex and subventricular zone neurogenic niche. C57BL/6L 4 weeks old male mice were craneotomized at 1 mm caudal from frontal suture and 1 mm lateral from midline to generate a window of 3 mm side. Brain injury was produced by removal of the meninges and superficial vasculature of dorsal parietal cortex. BrdU agent (50 mg/kg, ip) was injected to lesioned and sham animals, during days 0 and 1 after surgery. Sagittal sections were analyzed at 1, 4, 7, and 10 days post‐injury. A time‐dependent increase in BrdU+ cells in the perilesional parietal cortex was accompanied by augmented BrdU+ cells in the sub ventricular and rostral migratory stream of ipsilateral and contralateral hemispheres. Neural progenitors and neuroblasts proliferated in the lesioned and non‐lesioned subventricular zone and rostral migratory stream on day 4 after injury. Augmented contralateral neurogenesis was associated with an increase in vesicular monoamine transporter 2 protein in the striosomal sub ventricular neurogenic niche of non‐lesioned hemisphere.
Effectiveness of a Program Intervention with Reduced-Iron Multiple Micronutrient Powders on Iron Status, Morbidity and Growth in Young Children in Ethiopia

Despite the potential for improving iron status and child growth in low- and middle-income settings, concerns on the safety of high iron dosages of Micronutrient Powders (MNP currently limit their applicability in programs. We examined the effectiveness and risks of an integrated complementary feeding program with low iron dose (6 mg/serving) MNP among 6–23-month-old Ethiopian children using a quasi-experimental study design comparing children from five intervention districts (n = 1172) to those from four matched non-intervention districts (n = 1137). Haemoglobin concentrations increased in intervention and decreased in non-intervention children (group-difference +3.17 g/L), but without improvement in iron stores. Intervention children were 2.31 times more likely to have diarrhoea and 2.08 times more likely to have common cold and flu, but these differences decreased towards the end of the intervention. At end line, intervention children had higher mean Height-for-Age Zscore (HAZ) and a 51% reduced odds of being stunted compared to non-intervention children. MNP with low iron dose, when provided combined with other Infant and Young Child Feeding (IYCF) interventions, marginally improved haemoglobin status and resulted in a remarkable improvement in linear growth in 6–23-month-old children. These benefits likely outweigh the relatively small increase in the risk of diarrhoea.
The Role of Vitamin D Oral Supplementation in Insulin Resistance in Women with Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Objective: To evaluate the effect of vitamin D supplementation (alone or with co-supplementation) on insulin resistance in patients with polycystic ovary syndrome (PCOS). Methods: We performed a literature search of databases (Medline, Scopus, Web of Knowledge, Cochrane Library) and identified all reports of randomized controlled trials (RCTs) published prior to April 2018. We compared the effects of supplementation with vitamin D alone (dose from 1000 IU/d to 60,000 IU/week) or with co-supplements to the administration of placebos in women diagnosed with PCOS. The systematic review and meta-analysis protocol was registered in the International Prospective Register of Systematic Reviews (Prospero) as number CRD42018090572. Main results: Eleven of 345 identified studies were included in the analysis; these involved 601women diagnosed with PCOS. Vitamin D as a co-supplement was found to significantly decrease fasting glucose concentrations and the HOMA-IR value. HOMA-IR also declined significantly when vitamin D was supplemented with a dose lower than 4000 IU/d. Conclusions: Evidence from RCTs suggests that the supplementation of PCOS patients with continuous low doses of vitamin D (<4000 IU/d) or supplementation with vitamin D as a co-supplement may improve insulin sensitivity in terms of the fasting glucose concentration (supplementation with vitamin D in combination with other micronutrients) and HOMA-IR (supplementation with vitamin D in continuous low daily doses or as co-supplement).
Online Off-policy Prediction

This paper investigates the problem of online prediction learning, where learning proceeds continuously as the agent interacts with an environment. The predictions made by the agent are contingent on a particular way of behaving, represented as a value function. However, the behavior used to select actions and generate the behavior data might be different from the one used to define the predictions, and thus the samples are generated off-policy. The ability to learn behavior-contingent predictions online and off-policy has long been advocated as a key capability of predictive-knowledge learning systems but remained an open algorithmic challenge for decades. The issue lies with the temporal difference (TD) learning update at the heart of most prediction algorithms: combining bootstrapping, off-policy sampling and function approximation may cause the value estimate to diverge. A breakthrough came with the development of a new objective function that admitted stochastic gradient descent variants of TD. Since then, many sound online off-policy prediction algorithms have been developed, but there has been limited empirical work investigating the relative merits of all the variants. This paper aims to fill these empirical gaps and provide clarity on the key ideas behind each method. We summarize the large body of literature on off-policy learning, focusing on 1- methods that use computation linear in the number of features and are convergent under off-policy sampling, and 2- other methods which have proven useful with non-fixed, nonlinear function approximation. We provide an empirical study of off-policy prediction methods in two challenging microworlds. We report each method's parameter sensitivity, empirical convergence rate, and final performance, providing new insights that should enable practitioners to successfully extend these new methods to large-scale applications. [Abridged abstract]
Alteration Minerals Mapping Using MTMF and CEM Based on ASTER in Zedang Orefield of Tibet, China

Zedang copper polymetallic ore field, including several middle and large skarn-porphyry deposits for large metallogenic scale and special mineralized combination, locates in south rim of Eastern of Gangdise mountains in Tibet. Using the ASTER imagery and MTMF and CEM methods and field sample spectra, the alteration minerals of the Zedang ore field were mapped. From measuring the spectral of rock and mineral using SVC portable spectrograph, it derived consequence of exists some main alteration minerals. According to alteration minerals spectral feature, distribution map of alteration minerals is displayed using MTMF and CEM algorithm. Through compare analysis, it is considered that the CEM approach can suppress the background and extract more accuracy minerals than MTMF method in the high topographic relief area. The result is very important meaning for mineral prospecting.
Modification of Growth, Yield, and the Nutraceutical and Antioxidative Potential of Soybean Through the Use of Synthetic Biostimulants

Improvement of crop cultivation technologies is focused on increasing crop productivity and improving yield quality, and at the same time on minimizing risks posed to the natural environment. The use of biostimulants contributes to the increase in the productivity of plants, especially under their exposure to stress induced by negative environmental stimuli. A field experiment was conducted in three growing seasons (2014–2016). Seeds of soybean of the Atlanta cultivar were sown in the third decade of April. Two synthetic biostimulants were used in the growing period in the form of single (stage BBCH 13-15) or double (stage BBCH 13-15, BBCH 61) spraying: Atonik (in concentrations of 0.1 and 0.2%) and Tytanit (in concentrations of 0.07 and 0.13%). Atonik, the first tested biostimulant, contained three phenolic compounds: sodium p-nitrophenolate, sodium o-nitrophenolate, and sodium 5-nitroguaiacolate. The Tytanit preparation contained a titanium complex, magnesium oxide, and sulfur (VI) oxide. This work presents a complex study addressing the action of the biostimulants Atonik and Tytanit and demonstrates their effect on the physiological traits, plant productivity, and seed yield quality of Glycine max L. The conducted experiment proved that the biostimulant type, as well as the number of its applications and its concentration, modified the biometric traits, crop productivity, as well as yield quality and the nutraceutical and antioxidative potential of soybean seeds. It was also found that by positively affecting plant growth and seed yield, the Atonik and Tytanit also resulted biostimulants decreased the protein and lipid contents in seeds. A double application of these preparations in their higher concentrations had a more positive impact on soybean seed number and soybean seed yield. The use of both Atonik and Tytanit resulted also in an increased antioxidative activity of soybean seeds. The greatest increase in this activity was observed after the application of the Tytanit preparation. Dietary fiber fraction analysis demonstrated an increase in the acid-detergent fiber, lignin, and cellulose contents in soybean seeds as a result of biostimulant application; however, the increase was greater upon the use of Tytanit. In contrast, the neutral-detergent fiber, cellulose, and hemicellulose contents were observed to decrease in all analyzed combinations of crops treated with the tested preparations.