Miracle-dz/UniFAR-FTUs huggingface dataset:
Nutritional Profiling, Phytochemical Composition and Antidiabetic Potential of Taraxacum officinale, an Underutilized Herb

Taraxacum officinale (T. officinale), a wild vegetable with a number of health claims, has been mostly ignored and unexplored. The study aims to compare the nutritional, phytochemical as well as antidiabetic potential of fresh as well as shade-dried leaves of T. officinale, in order to recommend its best form as a dietary antidiabetic product. The results revealed that as compared to fresh leaves, the shade-dried leaves, in addition to possessing higher levels of carbohydrates, crude protein, crude fat, crude fiber, etc., also contain appreciable amounts of total phenols (5833.12 ± 4.222 mg/100), total flavonoids (188.84 ± 0.019 mg/100 g), ascorbic acid (34.70 ± 0.026 mg/100 g), β-carotene (3.88 ± 1.473 mg/100 g) and total chlorophyll (239.51 ± 0.015 mg/100 g) antioxidants. The study revealed the presence of medicinally important antidiabetic flavonoid quercetin present in T. officinale leaves. Among the three solvent systems used, the aqueous extract of shade-dried T. officinale leaves comparatively demonstrated potent antidiabetic activity under in vitro conditions in a dose-dependent manner via targeting α-amylase and α-glucosidase, the two potent enzymes of carbohydrate metabolism. Therefore, in addition to being a nutritious herb, the shade-dried leaves of T. officinale have great potential to suppress post-prandial glucose rise and can be better exploited through clinical trials to be used as a dietary intervention for better management of diabetes.
The predictive relation of maternal sensitivity over time and child characteristics on early attachment

ABSTRACT Hierarchical linear modelling was used to explore the effect of changes in maternal sensitivity on attachment over time. Child characteristics of gender, temperament, and developmental status were used as moderating factors. Data from 1,249 mothers and their children from the NICHD Study of Early Child Care and Youth Development when the children were 15, 24, and 36 months of age. Results indicated that maternal sensitivity at 15 months was not predictive of attachment when conditioned on maternal sensitivity at 24 and 36 months. Mothers who were more sensitive on average were more likely to have children with secure attachments; fluctuations in individual mothers’ sensitivity did not predict her child’s attachment. Male children were more strongly affected by their mothers’ sensitivity than female children. The higher a child’s developmental status in infancy, the lower the likelihood for later insecure attachment. Implications regarding the importance of parental behaviour in toddlerhood is discussed.
Efektivitas Model Connected Mathematics Project Terhadap Kemampuan Penalaran Matematis dan Kecemasan Matematika

Kemampuan penalaran matematis adalah salah satu aspek terpenting dan mendasar dalam matematika. Kemampuan ini dapat dikembangkan melalui model pembelajaran yang dapat menstimulus siswa untuk membangun pengetahuan penalarannya sendiri. Salah satu model pembelajaran dengan karakteristik tersebut adalah Connected Mathematics Project (CMP). Maka dari itu, penelitian ini bertujuan untuk menganalisis efektivitas model pembelajaran CMP terhadap kemampuan penalaran matematis dan kecemasan matematika. Penelitian ini merupakan penelitian kuantitatif dengan metode eksperimen dengan desain kuasi eksperimen. Desain kuasi eksperimen yang digunakan dalam penelitian ini adalah the nonequivalent posttest-only control group design. Penelitian dilakukan di salah satu SMK di Karawang. Pengambilan sampel dilakukan dengan menggunakan teknik cluster random sampling. Dengan jumlah sampel sebanyak 18 siswa kelas eksperimen dan 18 siswa kelas kontrol. Instrumen yang digunakan adalah tes kemampuan penalaran matematis yang terdiri atas tiga soal tes uraian dan angket kecemasan matematika. Hasil penelitian ini menunjukkan bahwa: 1) kemampuan penalaran matematis siswa pada model pembelajaran CMP lebih tinggi daripada siswa pada pembelajaran konvensional. 2) persentase rata-rata sikap kecemasan siswa pada model pembelajaran CMP lebih rendah daripada siswa pada pembelajaran konvensional, dan 3) Efektifitas pembelajaran CMP terhadap kemampuan penalaran matematis dan kecemasan matematika tergolong tinggi.
Manufacture of High-Efficiency and Stable Lead-Free Solar Cells through Antisolvent Quenching Engineering

Antisolvent quenching has shown to significantly enhance several perovskite films used in solar cells; however, no studies have been conducted on its impact on MASnI3. Here, we investigated the role that different antisolvents, i.e., diethyl ether, toluene, and chlorobenzene, have on the growth of MASnI3 films. The crystallinity, morphology, topography, and optical properties of the obtained thin films were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence (PL) measurements, and UV–visible spectroscopy. The impact of the different antisolvent treatments was evaluated based on the surface homogeneity as well as the structure of the MASnI3 thin films. In addition, thermal annealing was optimized to control the crystallization process. The applied antisolvent was modified to better manage the supersaturation process. The obtained results support the use of chlorobenzene and toluene to reduce pinholes and increase the grain size. Toluene was found to further improve the morphology and stability of thin films, as it showed less degradation after four weeks under dark with 60% humidity. Furthermore, we performed a simulation using SCAPS-1D software to observe the effect of these antisolvents on the performance of MASnI3-based solar cells. We also produced the device FTO/TiO2/MASnI3/Spiro-OMeTAD/Au, obtaining a remarkable photoconversion efficiency (PCE) improvement of 5.11% when using the MASnI3 device treated with chlorobenzene. A PCE improvement of 9.44% was obtained for the MASnI3 device treated with toluene, which also showed better stability. Our results support antisolvent quenching as a reproducible method to improve perovskite devices under ambient conditions.
Multiple-Input Multiple-Output Multiple-Mode OFDM With Index Modulation

Multiple-mode orthogonal frequency division multiplexing with index modulation (MM-OFDM-IM) has been proposed as a novel IM technique, which conveys information via the permutation of multiple distinguishable constellations. In this paper, we propose a novel multiple-input multiple-output MM-OFDM-IM (MIMO-MM-OFDM-IM) scheme by combining MM-OFDM-IM and MIMO to take advantage of both techniques collectively. The low complexity detections, such as minimum mean square error (MMSE) Viterbi-like and MMSE subcarrier-wise log-likelihood ratio (MMSE-LLR), are proposed to largely reduce the receiver detection complexity. Besides, the theoretical analyses on bit error rate (BER) is also derived in closed-form to evaluate the performance of MIMO-MM-OFDM-IM. Considering different system configurations, it is shown via Monte Carlo simulations that the proposed MIMO-MM-OFDM-IM scheme not only achieves higher SE but also provides better error performance than the conventional schemes.
Modeling the distribution of the endangered Jemez Mountains salamander (Plethodon neomexicanus) in relation to geology, topography, and climate

Abstract The Jemez Mountains salamander (Plethodon neomexicanus; hereafter JMS) is an endangered salamander restricted to the Jemez Mountains in north‐central New Mexico, United States. This strictly terrestrial and lungless species requires moist surface conditions for activities such as mating and foraging. Threats to its current habitat include fire suppression and ensuing severe fires, changes in forest composition, habitat fragmentation, and climate change. Forest composition changes resulting from reduced fire frequency and increased tree density suggest that its current aboveground habitat does not mirror its historically successful habitat regime. However, because of its limited habitat area and underground behavior, we hypothesized that geology and topography might play a significant role in the current distribution of the salamander. We modeled the distribution of the JMS using a machine learning algorithm to assess how geology, topography, and climate variables influence its distribution. The best habitat suitability model indicates that geology type and maximum winter temperature (November to March) were most important in predicting the distribution of the salamander (23.5% and 50.3% permutation importance, respectively). Minimum winter temperature was also an important variable (21.4%), suggesting this also plays a role in salamander habitat. Our habitat suitability map reveals low uncertainty in model predictions, and we found slight discrepancies between the designated critical habitat and the most suitable areas for the JMS. Because geological features are important to its distribution, we recommend that geological and topographical data are considered, both during survey design and in the description of localities of JMS records once detected.
Self-Medication Patterns during a Pandemic: A Qualitative Study on Romanian Mothers’ Beliefs toward Self-Treatment of Their Children

Self-medication represents a significant healthcare and health policy issue worldwide, both in developed and underdeveloped countries. Currently, the COVID-19 pandemic is considered a relevant context that could subtly trigger self-medication behavior because of limited access to health care services and the threat of infection with the SARS-CoV-2 virus. While the previous research conducted with quantitative methodologies reported a dramatically increased rate of self-medication around the world, qualitative inquiries on the subjective experience with self-medicine remain scarce in medical and related fields of study. For this purpose, a qualitative study with semi-structured interviews was undertaken to better understand how Romanian mothers (n = 18) applied self-treatment with their children by avoiding medical advice during the COVID-19 pandemic. The results showed that the COVID-19 pandemic did not affect the prevalence of self-medicine among the pediatric population as parents achieved a degree of awareness of self-treatment of their children due to the general context of the outbreak of the COVID-19 pandemic.
Fast code recommendation via approximate sub-tree matching

Software developers often write code that has similar functionality to existing code segments. A code recommendation tool that helps developers reuse these code fragments can significantly improve their efficiency. Several methods have been proposed in recent years. Some use sequence matching algorithms to find the related recommendations. Most of these methods are time-consuming and can leverage only low-level textual information from code. Others extract features from code and obtain similarity using numerical feature vectors. However, the similarity of feature vectors is often not equivalent to the original code’s similarity. Structural information is lost during the process of transforming abstract syntax trees into vectors. We propose an approximate sub-tree matching based method to solve this problem. Unlike existing tree-based approaches that match feature vectors, it retains the tree structure of the query code in the matching process to find code fragments that best match the current query. It uses a fast approximation sub-tree matching algorithm by transforming the sub-tree matching problem into the match between the tree and the list. In this way, the structural information can be used for code recommendation tasks that have high time requirements. We have constructed several real-world code databases covering different languages and granularities to evaluate the effectiveness of our method. The results show that our method outperforms two compared methods, SENSORY and Aroma, in terms of the recall value on all the datasets, and can be applied to large datasets.
Distinct response of near surface air temperature to clouds in North China

Using the daily 2 m maximum temperature (Tmax), 2 m minimum temperature (Tmin) and cloud cover data measured at ground sites of the China Meteorological Administration in North China from 2000 to 2017, this study investigates the influence of clouds on the daily temperature range (DTR) defined as the difference between Tmax and Tmin. As expected, the cloud cover shows the similar averaged spatial distribution and monthly variation with Tmin. Surprisingly, it also shows the similar average spatial distribution and monthly variation with Tmax, suggesting the more important roles of regions (latitude) and seasons associated with the variations of land surface temperature, which is further related to solar radiation absorbed and surface heat capacity. By comparing monthly variations of temperature between cloudy and clear skies, we find that clouds can weaken Tmax and increase Tmin, and thus decrease DTR. As a result, the spatial distribution of DTR is opposite to the cloud cover. The clouds have relatively stronger impact on Tmin and DTR over mountain region, which is most likely caused by the stronger longwave cloud radiative forcing associated with higher cloud tops over the mountain region.
Lifestyle Factors Associated with Metabolic Syndrome in Urban Cambodia

This study aimed to identify lifestyle factors associated with metabolic syndrome (MetS) in urban Cambodia. In this cross-sectional study, we used existing health checkup data from a private hospital in Phnom Penh, Cambodia. The participants comprised 5459 Cambodians aged ≥20 years who underwent health checkups between 2017 and 2019. The harmonized diagnostic definition was used as the MetS criteria. The prevalence of MetS was 56.6% overall, 60.4% in men and 52.6% in women. The lifestyle factor significantly associated with MetS in both sexes were “eating quicker than others”, (men: odds ratio [OR]= 2.25, 95% confidence interval [CI] = 1.68–3.03, women: OR = 1.92, 95%CI = 1.41–2.60), “walking faster than others”, (men: OR = 0.78, 95% CI = 0.67–0.92, women: OR = 0.75, 95% CI = 0.62–0.89) and “drinking alcohol” (men: OR = 1.33, 95% CI = 1.10–1.61, women: OR = 1.33, 95% CI = 1.09–1.62). Other significant associations with MetS for men was “eating speed is normal”, (OR = 1.73, 95%CI = 1.30–2.31), and, for women, “eating food after dinner at least 3 days a week”, (OR = 1.25, 95%CI = 1.01–1.55), “skipping breakfast at least 3 days a week”, (OR = 0.83, 95%CI = 0.69–0.99) and “getting enough rest from sleep” (OR = 1.19, 95% CI = 1.01–1.42) were significantly associated with MetS. Lifestyle interventions through health education and guidance may be effective in preventing MetS in Cambodia.
An Inverse, Decision-Based Design Method for Integrated Design Exploration of Materials, Products, and Manufacturing Processes

A material's design revolution is underway with a focus to design the material microstructure and processing paths to achieve certain performance requirements of products. A host of manufacturing processes are involved in producing a product. The processing carried out in each process influences its final properties. To couple the material processing-structure-property-performance (PSPP) spaces, models of specific manufacturing processes must be enhanced and integrated using multiscale modeling techniques (vertical integration) and then the input and output of the various manufacturing processes must be integrated to facilitate the flow of information from one process to another (horizontal integration). Together vertical and horizontal integration allows for the decision-based design exploration of the manufacturing process chain in an inverse manner to realize the end product. In this paper, we present an inverse method to achieve the integrated design exploration of materials, products, and manufacturing processes through the vertical and horizontal integration of models. The method is supported by the concept exploration framework (CEF) to systematically explore design alternatives and generate satisficing design solutions. The efficacy of the method is illustrated for a hot rod rolling (HRR) and cooling process chain problem by exploring the processing paths and microstructure in an inverse manner to produce a rod with specific mechanical properties. The proposed method and the exploration framework are generic and support the integrated decision-based design exploration of a process chain to realize an end product by tailoring material microstructures and processing paths.
How fast is it to city centers? The average travel speed as an indicator of road traffic accessibility potential

Transportation is the lifeblood of a modern metropolis. Accessibility generally refers to the interconnection between nodes in a regional traffic network. The purpose of the paper is to obtain more realistic and accurate measures of travel speed and to study the road traffic accessibility potential in cities. This study proposes a method for analyzing road traffic accessibility potential which is based on the average travel speed to city centers in off-peak times and which ranks 80 cities around the world. Based on the Suomi National Polar-Orbiting Partnership satellite’s visible-infrared imaging radiometer suite (NPP-VIIRS) night-time light data, urban built-up areas and city centers were extracted. Further, with the aid of the Google Maps application programming interface (API) network crawling technique, travel times and travel distances for several optimal routes to city centers by car were obtained. Feasible proposals for improving road traffic accessibility and planning urban transportation in different cities are presented. The proposed method offers a new possibility of analyzing traffic accessibility using internet data and geo-spatial methods.
An Improved YOLOX Algorithm for Forest Insect Pest Detection

A large number of insect pests in the forest will seriously affect the construction of forest resources and agriculture in China. In this regard, in order to deeply understand and analyze the existing forest pest detection technology, it is found that it cannot meet practical needs. In order to prevent the harm caused by forest pests, it is necessary to correctly identify the types of pests and take targeted control measures. Therefore, this paper proposes a forest pest detection algorithm based on improved YOLOX. Firstly, aiming at the problem that there are few image data of real deep forest pests in the wild, we use Mosaic, Mixup, and random erasure data enhancement to preprocess the images. Secondly, in order to extract fine-grained features, shallow information is introduced into the existing network architecture, and a two-way cross-scale feature fusion mechanism is adopted. Finally, the improved YOLOX algorithm proposed in this paper has achieved the best results on the public forest pest dataset IP102.
Face detection using Min-Max features enhanced with Locally Linear Embedding

– Face detection is critical function in many embedded applications such as computer vision and security as it is widely used as preprocessor for face recognition systems. As a preprocessor, the face detection system needs to extract features from a region of interest and classify them quickly as either face or non-face. In our previous works, we have devised a feature representation method called Min-Max (MMX) feature that allows representation of a region of interest using a few data points based on the unique characteristics of vertical and horizontal summation of face regions. In this paper, we attempt to improve the classification accuracy of MMX by integrating a technique called Locally Linear Embedding (LLE), a powerful dimensionality and feature enhancement algorithm that has been used successfully in many pattern recognition tasks. To test the performance of the proposed enhancement, the LLE-treated features were compared with non-treated features using a Multi-Layer Perceptron (MLP) neural network classifier. The results indicate an increase (+1.2%) in classification accuracy of the MLPs, demonstrating the ability of LLE to enhance the representation of MMX features.
Drinking during social isolation: investigating associations between stress, inhibitory control, boredom, drinking motives, and alcohol use

Abstract Background: We aimed to assess whether stress, boredom, drinking motives, and/or inhibitory control were related to alcohol use during a period of social isolation. Method: Analyses were carried out on questionnaire data (N = 337) collected during the first wave of the COVID-19 pandemic (7 April–3 May 2020). We first assessed changes in drinking behavior, stress and boredom. We then regressed drinking behavior on drinking motives, inhibitory control, stress, and boredom. We also investigated interactions between change in stress/boredom and inhibitory control. Results: A minority of respondents reported increased alcohol use (units = 23.52%, drinking days = 20.73%, heavy days = 7.06%), alcohol-related problems (9.67%), and stress (36.63%). Meanwhile, most respondents reported increased boredom (67.42%). Similarly, boredom significantly increased (B = 21.22, p < .001), on average, while alcohol-related problems decreased (B = −1.43 p < .001). Regarding drinking motives, decreased alcohol-related problems were associated with social drinking motives (B = −0.09, p = .005). Surprisingly, risk-taking was associated with decreased alcohol-related problems (B = −0.02, p = .008) and neither stress nor boredom independently predicted changes in alcohol use. Finally, several significant interactions suggested that those who were more impulsive and less bored were more likely to report increased alcohol use and vice versa. Conclusions: These data provide a nuanced overview of changes in drinking-related behavior during the COVID-19-induced period of social isolation. While most people reduced their drinking, there was evidence of complex interactions between impulsivity and boredom that may be explored in future studies.
Decreased TSPAN14 Expression Contributes to NSCLC Progression

Tspan14 is a transmembrane protein of the tetraspanin (Tspan) protein family. Different members of the Tspan family can promote or suppress tumor progression. The exact role of Tspan14 in tumor cells is unknown. Earlier, mutational inactivation of the TSPAN14 gene has been proposed to coincide with a low survival rate in NSCLC patients. This study aimed to investigate the correlation of TSPAN14 lack of function with clinicopathological features of NSCLC patients, and to elucidate the role TSPAN14 might have in NSCLC progression. TSPAN14 expression was lower in tumor cells than non-tumor cells in NSCLC patients’ samples. The decreased gene expression was correlated with a low survival rate of patients and was more frequent in patients with aggressive, invasive tumor types. Additionally, the role of decreased TSPAN14 expression in the metastatic potential of cancer cells was confirmed in NSCLC cell lines. The highly invasive NSCLC cell line (NCI-H661) had the lowest TSPAN14 gene and protein expression, whereas the NSCLC cell line with the highest TSPAN14 expression (NCI-H460) had no significant metastatic potential. Finally, silencing of TSPAN14 in these non-metastatic cancer cells caused an increased expression of matrix-degrading enzymes MMP-2 and MMP-9, followed by an elevated capacity of cancer cells to degrade gelatin. The results of this study propose TSPAN14 expression as an indicator of NSCLC metastatic potential and progression.