Miracle-dz/UniFAR-FTUs huggingface dataset:
An ensemble learning model for asphalt pavement performance prediction based on gradient boosting decision tree

ABSTRACT This paper proposes an ensemble learning model that deploys a Gradient Boosting Decision Tree (GBDT) to predict two relevant functional indices, the International roughness index (IRI) and the rut depth (RD), considering multiple influence factors. To train and validate the proposed models, more than 1600 different records were extracted from Long-Term Pavement Performance database. The most suitable hyper parameters for the GBDT model are determined through a grid search and 5-fold cross-validation. Then, a sensitivity analysis is performed to determine the final input variables among the initial considered factors. Further, the optimized models utilise SHAP (Shapley Additive explanation) to interpret the results and analyse the importance of influencing factors. Finally, a comparison experiment with reference artificial intelligence approaches demonstrates that, the GBDT model can outperform the artificial neural network (ANN) and the random forest regression (RFR) methods in terms of quality of prediction results, reaching a coefficient of determination (R2) equal to 0.9. The proposed model can provide more precise pavement performance values and may be useful for providing accurate reference for pavement maintenance and optimising the available budget for road administrations.
Salesforce Compensation and Two‐Sided Ambiguity: Robust Moral Hazard with Moment Information

We analyze a salesforce principal‐agent model where both the firm and sales agent have limited information on the effort‐dependent demand distribution, creating two‐sided ambiguity. Under the max–min decision criteria, the firm offers a contract to the agent who exerts unobservable effort to influence the demand distribution. We formulate the problem as a semi‐infinite program and use the agent's shadow prices to construct the least expensive contract. Next, we use the least expensive contract to create a non‐linear optimization model, which provides the firm's optimal robust contract. Due to the problem's complexity, we focus our attention on the class of distribution‐free contracts. We show that using a distribution‐free contract is a necessary condition for achieving the first‐best outcome. Our analysis reveals that the index of dispersion determines whether the optimal distribution‐free contract is linear or quadratic. Finally, we extend our model to incorporate quota‐bonus contracts and inventory considerations. Overall, our results demonstrate that variance information plays a critical role in designing contracts under distributional ambiguity and provides justification for the application of quadratic contracts in practice.
Pandemic Fear and Weight Gain: Effects on Overweight and Obese Adults’ Purchasing Exercise Apparel Online

The purpose of this study was to investigate the interactive effect of pandemic fear and weight gain on overweight and obese consumers’ decisions to purchase exercise apparel online based on the theory of planned behavior and body-related self-discrepancy theory. A sample of 515 male and female adults with BMIs of 25 and higher participated in this study. The effect of pandemic fear on the attitudes toward purchasing exercise apparel online was only positive for overweight and obese consumers who did not gain weight during pandemic. However, for those who gained weight during the pandemic, there was no significant effect of pandemic fear on the attitudes toward purchasing exercise apparel online. Attitudes, subjective norm, and perceived behavioral control were all significant predictors of intent to purchase exercise apparel online. This study extends the theory of planned behavior by adding the pandemic-related factors and provides practical implications for online retailers.
Taxonomy and paleobiogeography of the Maastrichtian cephalopods from the Abu Monqar-west Dakhla stretch, Western Desert, Egypt

ABSTRACT The Maastrichtian sedimentary succession in the Abu Monqar-west Dakhla stretch yields rare cephalopod content. Six cephalopods, including three nautiloids and three ammonoids, are described in detail and identified. Two new species of nautiloids are erected from the study area; these are Angulithes monqarensis nov. sp. and Anglonautilus hewaidyi nov. sp. The ammonoid Sphenodiscus lobatus (Tuomey) is firstly recorded from the Maastrichtian rocks of Egypt. Paleobiogeographically, Pachydiscus (P.) neubergicus has a wide geographic distribution within the Tethyan and Boreal realms. Sphenodiscus lobatus appeared earlier in the late Campanian of North America and then migrated through shallow environments to the Southern Tethys. The Anglonautilus appeared earlier in the Hauterivian age in the Northern Tethys and then migrated into Southern Tethys, Northern America, and Asia. The distribution of Baculites ovatus at the Southern Tethyan Province is chiefly controlled by the prevailed palaeoecological factors.
Vitamin B6 Effects on Breast Pain in Women of Reproductive Age: A Systematic Review

Context: Vitamin B6, which is known as pyridoxine, is used as a nutritional supplement for many therapeutic purposes in medical centers. Women's health is important because they are assumed as the guarantors of health in societies. Breast pain is a common complaint in women of reproductive age and one of the most common reasons for women’s referral to health centers. The present study reviewed the impact of vitamin B6 on breast pain. Evidence Acquisition: In order to gather relevant articles, the databases of IRCT, Iran Doc, SID, MagIran, Medline, Cochrane, Embase, PubMed, Scopus, Science Direct, and Web of Knowledge were searched from 1980 up to July 2019. Keywords were extracted from MeSH, which included "Pyridoxol", "Rodex”, "PLP", "Pyridoxal-5-Phosphate", "Pyridoxine Hydrochloride", "Pyridoxine", "Vitamin B6", "Mastodynia", "Mammalgia", "Breast Pain", (Pain AND Breast), "Mastalgia", "Cycle Mastalgia", and "Non-Cycle Mastalgia". The same keywords were also searched in Persian databases. All selected studies had control and intervention groups and compared the pain-relieving effects of vitamin B6 with that of other therapies or placebo. Results: Among 338 examined articles, seven fulfilled our inclusion criteria and were included in the review. The results showed that vitamin B6 was more effective than placebo in improving breast pain even at low doses. Conclusions: Vitamin B6 is effective in relieving breast pain. However, there are also other supplements and medications to treat breast pain, so some factors like cost-effectiveness, availability, and side effects should be considered to choose a suitable agent.
Allele frequency of promoter region -1082A>G interleukinl0 gene and risk of prostate tumors in Iraqi patients

Number of studies has demonstrated the relationship of interleukin 10 gene polymorphism with risk of prostate cancer. This research aimed to evaluate the effect of single nucleotide polymorphism in the promoter region rs1800896 of IL-10 -1082A >G on the incidence of benign prostate hyperplasia and prostate cancer in Iraqi patients. In this study, we studied IL-10 gene polymorphism in two groups of patients, thirty of whom have benign prostate hyperplasia and thirty have prostate cancer, as well as in thirty healthy subjects who were the control group. Relevant primers were used for the amplification by the polymerase chain reaction of the promoter region IL-10 rs1800896. Restriction fragment length polymorphism has been used to determine the frequencies of the alleles associated with each group of subjects studied. The amplified products of PCR were sequenced using the forward primer. The result of restriction fragment length polymorphism showed that AG, AA alleles were not found and GG allele was detected in all of the controls and patients, leading to a conclusion that AA, GG homozygotes and AG heterozygote alleles were not associated with both benign prostate hyperplasia and prostate cancer.
Antioxidant effect of Hymenaea courbaril L (Jatob) sap on the healing of wounds on mice

The use of natural products with curative action is a common cultural practice in the Brazilian Amazon, but little explored scientifically. The effect of Hymenaea courbaril L sap extract and its contribution to wound healing in mice was evaluated. The antioxidant potential of the extract was studied using the radical 1,1-diphenyl-2-picrilhidrazil and 2,2'-azino-bis (3-ethyl benzothiazoline-6-sulfonic) acid radical, anion superoxide (O2-) radical tests, phenol and flavonoid content, proliferation assay, cell viability and migration. In vivo tests were performed on adult Swiss mice, submitted to back injury and treated with a formulation containing 2% sap extract, extracted with ethyl acetate. The animals were treated topically for 14 days, it was observed that the sap extract has antioxidant activity, inhibiting the production of reactive oxygen species, presented potential for the proliferation of fibroblasts and promoted cell migration. Morphometric analysis of wound closure on the 3rd day suggested that animals treated with Jatoba sap had a reduced area of injury when compared with the control group on the 3rd post-injury day for the treated group. On the 14th day, there was no difference between groups. The total closure of the wounds did not occur during the 14-day experiment, but through histological evaluation, it was found that there was re-epithelialization. The results suggest that Jatoba sap extract has the potential to induce the healing of skin wounds due to its antioxidant activity. Key words: Hymenaea courbaril L extract, cytotoxicity, antioxidant activity, wound.
Integrated Thermal Insulation Packing and Vehicle Routing for Perishable Products in Community Group Purchase

Two transportation modes have been used to solve the “last kilometer” delivery problem of perishable products in China. One mode involves the use of refrigerated vehicles, and the other involves transportation with nonrefrigerated vehicles but with thermal insulation packaging and phase-change refrigerants. In this paper, we studied the distribution of fresh products using nonrefrigerated vehicles under the community group purchase model. A new integrated model that can simultaneously select insulation packaging methods and vehicle paths was developed. We designed a heuristic algorithm based on genetic algorithm to solve larger-scale problems. We found that nonrefrigerated vehicle delivery was better than refrigerated vehicle delivery when neither the cost of the phase-change refrigerant nor the cost of packaging accounts for more than 50% of the total cost. There was an optimal balance between insulation packaging cost and shipping cost. The combination of thin and light packaging materials and high-efficiency cold storage materials could achieve the goals of ensuring the quality of fresh products and reducing transportation costs simultaneously.
Production and Quality Evaluation of Green and Black Herbal Teas from Moringa oleifera Leaf

Freshly plucked Moringa oleifera leaves were processed into green and black herbal teas, due to its nutritional, pharmacological and medicinal properties. The unit operations were plucking, destalking and steaming for green tea or withering, grinding, fermentation for black tea prior to drying, milling, grading and packing. The tea samples were subjected to chemical and microbial load analyses, using standard methods. The results revealed the following ranges: proximate parameters; crude protein (7.25-26.62%), moisture content (10.37-70.48%), crude fat (1.82-2.74%), crude fibre (1.09-19.37%), ash content (0.94-9.75%), carbohydrate (15.31-44.93%); phytochemicals; saponins (2.25-5.50%), flavonoid (6.0-16.50%), steroid (1.05-5.05%) and terpenoid (0.70-1.23%) and anti-nutritional factors; tannin (0.23-1.32%), phytate (5.5-18.75%), cyanide (2.55-12.00%) and alkaloid (0.65-2.20%). The ranges of vitamins detected were; vitamins A (7-35-20.37 mg), B 1 (0.11-2.85 mg), B 2 (0.07-21.46 mg) and C (8.25-213 mg), while minerals included calcium (465.5-2057.5 mg), phosphorus (74.80-225.00 mg) and iron (8.23-32.15 mg). The microbial profile of green tea revealed 8.34×10 2 CFU gG 1 total viable count, whereas no mould growth was observed in both green and black Moringa tea leaves.
Does Behavioral Dysregulation Moderate the Links Between Contextual Factors and Substance Use Among Detained Youth?

Abstract This study examined whether behavioral dysregulation moderated associations between individual contextual factors (i.e. psychological control, peer delinquency, peer victimization, and negative life events) and the past 30-day frequency of specific substance use (i.e. tobacco, alcohol, marijuana, e-cigarettes, and prescription drugs) in a sample of recently detained youth. Patterns of associations varied among substances, with peer delinquency being the contextual risk factor most robustly associated with the frequency of various substances. Behavioral dysregulation did not moderate these associations, with the exception of psychological control; psychological control was only positively associated with prescription drug use when levels of behavioral dysregulation were low.
Examining Lived Experiences of Infertility and Perceptions Toward the Adoption of Children in Urban India

Abstract Infertility is emerging to be a key health concern in urban India. As a result, infertile couples in urban India tend to rely on assisted reproductive technologies (ARTs) for a child. Several media reports have highlighted that infertile couples in urban India intend to adopt a child only when all possibilities of becoming biological parents have been exhausted. Several studies have examined the relationship between infertility and assisted reproductive technologies in urban India. However, there is limited academic scholarship on the attitudes of infertile couples toward the adoption of children in India. Adopting a qualitative lens and using the functionalist theoretical framework the present study examines the different factors that shape the perceptions toward child adoption among infertile couples in urban Goa, India. In the process, the study also reflects on the intersections between infertility and gender role fulfillment among these couples to understand the lived experience of infertility on a regular basis.
Modified three-dimensional percolation simulation of char fragmentation and particulate formation

The current numerical calculation of particulate formation during char combustion mainly adopts the two-dimensional model. In this paper, based on the introduction of the concept of diffusion depth, the char combustion is simulated with a three-dimensional model. The modified model can simulate the actual situation that the reactant gas dose not diffuse into the char completely. The approach to realize the combustion process of char in chemical controlled zone (zone I) and transitional controlled zone (zone II) is given, and the results are compared with those in the diffusion controlled zone (zone III). The characteristic impact of initial porosity and mineral content on particulate formation in different zones is analyzed through the simulation and comparison. It can be seen from the results that the diffusion depth do put some limits on char fragmentation and mass distribution of ash particulates, which provides theoretical basis for the further study of particulate formation during char combustion and.
They’re Comparing Me to Her: Social Comparison Perceptions Reduce Belonging and STEM Engagement Among Women With Token Status

Belonging and academic engagement are important predictors of women’s retention in STEM. To better understand the processes influencing these outcomes, we investigate how numerical underrepresentation (i.e., token status) triggers social comparison perceptions—concerns that others are comparing oneself to another person—that can undermine women’s STEM outcomes. Across four experiments, female college students recruited via subject pool (Study 1a) and MTurk (Studies 1b–3) read a hypothetical scenario in which another female (Studies 1a–3) or male (Study 2) student performed well or poorly in an engineering course. Findings showed that having token (vs. non-token) status in the course increased social comparison perceptions (i.e., perceptions about being compared to an ingroup peer), which subsequently reduced course belonging (Studies 1a and 1b). Study 2 found that (a) token status increased social comparison perceptions in response to the ingroup (vs. outgroup) peer and (b) social comparison perceptions decreased belonging through stereotype threat concerns, particularly when the peer performed poorly. Study 3 directly manipulated social comparison perceptions to further establish their causal role on negative outcomes and demonstrated that these perceived direct comparisons predicted additional consequences signaling STEM disengagement. Collectively, findings identify a novel process that can diminish belonging and academic engagement for women in STEM. Additional online materials for this article are available on PWQ’s website at http://journals.sagepub. com/doi/suppl/10.1177/03616843211005447
A Deep Learning Streaming Methodology for Trajectory Classification

Due to the vast amount of available tracking sensors in recent years, high-frequency and high-volume streams of data are generated every day. The maritime domain is no different as all larger vessels are obliged to be equipped with a vessel tracking system that transmits their location periodically. Consequently, automated methodologies able to extract meaningful information from high-frequency, large volumes of vessel tracking data need to be developed. The automatic identification of vessel mobility patterns from such data in real time is of utmost importance since it can reveal abnormal or illegal vessel activities in due time. Therefore, in this work, we present a novel approach that transforms streaming vessel trajectory patterns into images and employs deep learning algorithms to accurately classify vessel activities in near real time tackling the Big Data challenges of volume and velocity. Two real-world data sets collected from terrestrial, vessel-tracking receivers were used to evaluate the proposed methodology in terms of both classification and streaming execution performance. Experimental results demonstrated that the vessel activity classification performance can reach an accuracy of over 96% while achieving sub-second latencies in streaming execution performance.
Ensemble machine learning based driving range estimation for real‐world electric city buses by considering battery degradation levels

Battery electric buses (BEBs) have been regarded as effective options to address the congestion and pollution problems in the ﬁeld of urban transportation. However, since the limited driving range of BEBs brings challenges for their promotion, the accurate estimation of the driving range with limited available information has become a critical issue for public transport operators. The real-world data collected from 50 BEBs operated in two different cities is used to develop the driving range estimation method by considering the battery degradation effects. Firstly, the incremental capacity analysis method is introduced to characterize the battery performance, and the battery degradation levels under different charging modes are recognized. Afterward, four types of ensemble machine learning (EML) methods are adopted to model the driving range estimation. The BEB driving data, weather condition data and battery degradation levels are used to train and test the models with consideration of 17 impact factors together with two different charging modes. The results indicate that the ensemble machine learning methods have good performance over-all, of which the random forest has the highest accuracy. Furthermore, the importance of inﬂuencing factors is analysed, and the relevant insights
Evidence of Phosphate Mining and Agriculture Influence on Concentrations, Forms, and Ratios of Nitrogen and Phosphorus in a Florida River

Florida has a long history of phosphate-mining, but less is known about how mining affects nutrient exports to coastal waters. Here, we investigated the transport of inorganic and organic forms of nitrogen (N) and phosphorus (P) over 23 sampling events during a wet season (June–September) in primary tributaries and mainstem of Alafia River that drains into the Tampa Bay Estuary. Results showed that a tributary draining the largest phosphate-mining area (South Prong) had less flashy peaks, and nutrients were more evenly exported relative to an adjacent tributary (North Prong), highlighting the effectiveness of the mining reclamation on stream hydrology. Tributaries draining > 10% phosphate-mining area had significantly higher specific conductance (SC), pH, dissolved reactive P (DRP), and total P (TP) than tributaries without phosphate-mining. Further, mean SC, pH, and particulate reactive P were positively correlated with the percent phosphate-mining area. As phosphate-mining occurred in the upper part of the watershed, the SC, pH, DRP, and TP concentrations increased downstream along the mainstem. For example, the upper watershed contributed 91% of TP compared to 59% water discharge to the Alafia River. In contrast to P, the highest concentrations of total N (TN), especially nitrate + nitrite (NOx–N) occurred in agricultural tributaries, where the mean NOx–N was positively correlated with the percent agricultural land. Dissolved organic N was dominant in all streamwaters and showed minor variability across sites. As a result of N depletion and P enrichment, the phosphate-mining tributaries had significantly lower molar ratios of TN:TP and NOx–N:DRP than other tributaries. Bi-weekly monitoring data showed consistent increases in SC and DRP and a decrease in NOx–N at the South Prong tributary (highest phosphate-mining area) throughout the wet season, and different responses of dissolved inorganic nutrients (negative) and particulate nutrients (positive) to water discharge. We conclude that (1) watersheds with active and reclaimed phosphate-mining and agriculture lands are important sources of streamwater P and N, respectively, and (2) elevated P inputs from the phosphate-mining areas altered the N:P ratios in streamwaters of the Alafia River.
A Global LIS/OTD Climatology of Lightning Flash Extent Density

Previous lightning climatologies derived from Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) total lightning measurements have quantified lightning frequency as a Flash Rate Density (FRD). This approach assumes that lightning flashes can be represented as points and quantifies the frequency of lightning centered in each grid cell. However, lightning has a finite extent that can reach hundreds of kilometers. A new climatology based on Flash Extent Density (FED) is constructed for LIS (including ISS‐LIS) and OTD that accounts for the horizontal dimension of lightning. The FED climatology documents the frequency that an observer can expect lightning to be visible overhead—regardless of where the flash began or ended. This new FED climatology confirms and elaborates on the previous global LIS/OTD FRD and Americas‐only Geostationary Lightning Mapper (GLM) findings. The FED climatology maintains Lake Maracaibo as the global lightning hotspot with an average of 389 flashes/day but designates Karabre in the Democratic Republic of the Congo as the global thunderstorm duty (percent of the total viewtime where lightning is observed) hotspot at 7.29%. Meanwhile, Kuala Lumpur is the national capital city with the most lightning, and its airport (KUL) is the top major airport affected by lightning (in terms of duty). The FED seasonal cycle and month‐to‐month changes in the “center of lightning” for the three continental chimney regions are also discussed.