Miracle-dz/UniFAR-FTUs huggingface dataset:
THE RELATIONSHIP BETWEEN CONVENIENCE MOTIVATION, ATTITUDE, AND BEHAVIORAL INTENTION OF FOOD DELIVERY APPLICATIONS’ USERS

This study aims to analyze the impact of convenience motivation on behavioral intention of food delivery apps’ users with the mediating role of attitude. The research object is three major Food Delivery Apps (FDA) in Indonesia namely GoFood, GrabFood, and ShopeeFood. Primary data was collected through online questionnaire to 195 samples of FDA users. Data was then analyzed with path analysis with three hypothesis. Findings show that user first assess the ease of use in operating FDA above anything else, in which driving in adopting FDA, as well as emerging the intention to purchase food through FDA. However, attitude was found mediate the relationship between convenience motivation and user’s behavioral intention. The impact of convenience motivation on behavioral intention of FDA users is mediated by attitude. It means that users’ intention to order food through FDA at first emerges because there is a positive attitude, where that attitude is formed when users feel that using FDA is easy. FDA are expected to prioritize ease of use from the application from its design, writing style, symbol, map, and process sequences. Small food enterprises might consider placing their products in existing FDA as consumer prefer to order from the application that familiar with.
Adoption and Cost-benefit Analysis of Drip Irrigation for Production of High-Value Crops in Pakistan

Drip irrigation is regarded as one of the highly efficient methods that allow limited water resources to be properly utilized. The study has been conducted to perform the economic analysis of low and high head drip irrigation systems throughout the country based on data from 100 adopters of drip irrigation through a research & development project funded by the International Center for Agricultural Research in the Dry Areas (ICARDA-Pakistan)/United States Department of Agriculture (USDA). A field survey for the study was conducted in the year 2018 in all the provinces of Pakistan. The study revealed that technology is generally adopted by the farmers having diversified income sources and medium-sized land holdings i.e. ranging from 12.5 to 25 acres. System installation cost-shared 11 percent in low-head drip system of the annual production cost of fruits. While, it shared 29, 32, and 27 percent in case of a high-head system for grapes orchards, vegetables in tunnels, and open fields, respectively. Low-head drip irrigation is profitable for dates/ lemon orchards in Khyber Pakhtunkhwa with a benefit-cost ratio (BCR) of 1.27:1.00. It results in considerable profitability for grapes orchards with BCR of 1.73:1.00 and 1.32:100 in Punjab and Balochistan provinces, respectively. The low-head system is also beneficial for mixed fruit orchards in rain-fed Punjab with a BCR of 1.24:1.00. Similarly, for high-head systems, the benefit-cost ratio was the highest for grapes produced in rain-fed Punjab (2.62:1.00), followed by squash-gourd in irrigated Sindh (2.17:1.00) bitter-gourd in rain-fed Punjab (1.50:1.00) and okra in Sindh (1.22:1.00). However, low and high-head systems could not result in considerable returns for farmers in the case of mixed fruits in Balochistan and cucumber production in tunnels in Punjab province during the study year.
Social Media and Sexual Behaviour: A Study of Undergraduate Students in a Public University in Imo State, South East Nigeria

Objective: To determine the effect of social media use on sexual behaviors among undergraduate students in public universities in Imo State, Nigeria. Materials and Methods: This descriptive cross-sectional study employed multistage sampling technique in selecting 300 undergraduates. Data on social media use and sexual behaviors were collected with self- administered semi-structured questionnaire and analysed using statistical package for social sciences version 22.0. Chi-square test was used to identify statistically significant associations between variables. A p value of < 0.05 was considered significant. Results: The mean age of respondents was 22.13+ 4.26 years, while 252(84%) were youths (ages 15 to 25 years). The mean age at sexual initiation was 18.25+ 3.67 years. There was 100% awareness of social media, 170 (56.67%) heard about it from friends, while the commonest reasons cited for its use is 213 (71.0%) solving school assignments, while the favorite platforms cited was 102 (91.9%) Facebook. There were statistically significant associations between ever had sex and gender and between use of social media and [the sexually active (p=0.001); type of sexual acts practiced (p=0.000) and number of sexual partners (p=0.000)] respectively. Conclusions: This study found an association between ever had sex and gender, as well as between use of social media for sexually explicit content and some risky sexual behavior. We recommend that measures such as correct sexuality education should be instituted for these students to help in curbing such use of social media and so minimize risky sexual behaviors and their attendant consequences.
SFNet-N: An Improved SFNet Algorithm for Semantic Segmentation of Low-Light Autonomous Driving Road Scenes

In recent years, considerable progress has been made in semantic segmentation of images with favorable environments. However, the environmental perception of autonomous driving under adverse weather conditions is still very challenging. In particular, the low visibility at nighttime greatly affects driving safety. In this paper, we aim to explore image segmentation in low-light scenarios, thereby expanding the application range of autonomous vehicles. The segmentation algorithms for road scenes based on deep learning are highly dependent on the volume of images with pixel-level annotations. Considering the scarcity of labeled large-scale nighttime data, we performed synthetic data collection and data style transfer using images acquired in daytime based on the autonomous driving simulation platform and generative adversarial network, respectively. In addition, we also proposed a novel nighttime segmentation framework (SFNET-N) to effectively recognize objects in dark environments, aiming at the boundary blurring caused by low semantic contrast in low-illumination images. Specifically, the framework comprises a light enhancement network which introduces semantic information for the first time and a segmentation network with strong feature extraction capability. Extensive experiments with Dark Zurich-test and Nighttime Driving-test datasets show the effectiveness of our method compared with existing state-of-the art approaches, with 56.9% and 57.4% mIoU (mean of category-wise intersection-over-union) respectively. Finally, we also performed real-vehicle verification of the proposed models in road scenes of Zhenjiang city with poor lighting. The datasets are available at https://github.com/pupu-chenyanyan/semantic-segmentation-on-nightime.
Financial Big Data Management and Control and Artificial Intelligence Analysis Method Based on Data Mining Technology

Driven by capital and Internet information (IT) technology, the operating scale and capital scale of modern industrial and commercial enterprises and various organizations have increased exponentially. At present, the manual-based financial work model has been unable to adapt to the changing speed of the modern business environment and the business rhythm of enterprises. All kinds of enterprises and organizations, especially large enterprises, urgently need to improve the operational efficiency of financial systems. By enhancing the integrity, timeliness, and synergy of financial information, it improves the comprehensiveness and ability of analyzing complex problems in financial analysis. It can cope with such rapid changes and help improve the financial management capabilities of enterprises. It provides more valuable decision-making guidance for business operations and reduces business risks. In recent years, the vigorous development of artificial intelligence technology has provided a feasible solution to meet the urgent needs of enterprises. Combining data mining, deep learning, image recognition, natural language processing, knowledge graph, human-computer interaction, intelligent decision-making, and other artificial intelligence technologies with IT technology to transform financial processes, it can significantly reduce the processing time of repetitive basic financial processes, reduce the dependence on manual accounting processing, and improve the work efficiency of the financial department. Through the autonomous analysis and decision-making of artificial intelligence, the intelligentization of financial management is realized, and more accurate and effective financial decision-making support is provided for enterprises. This paper studies the company’s intelligent financial reengineering process, so as to provide reference and reference for other enterprises to upgrade similar financial systems. The results of the analysis showed that at the level of α = 0.05 , there was a significant difference in the mean between the two populations. When the r value is in the range of -1 and 1, the linear relationship between the x and y variables is more obvious. This paper proposes decision-making suggestions and risk control early warning to the group decision-making body, or evaluates the financial impact of the group’s decision-making, and opens the road to financial intelligence.
Analysis of the Positive Feelings of Caregivers in Children with Type 1 Diabetes Mellitus and Its Influencing Factors

In order to explore the positive feelings of caregivers of children with type 1 diabetes mellitus and its influencing factors. The general data questionnaire, caregiver positive feeling scale, caregiver care ability of type 1 diabetes patients and Zarit care burden scale were used to investigate 193 caregivers of type 1 diabetes in Qingdao. The results of multiple stepwise regression analysis showed that caregivers’ educational level, care ability and care burden were important influencing factors of caregivers’ positive feelings. These factors could predict 95.6% of the variation of caregivers’ positive feelings. Medical staff should provide targeted support and help according to the specific situation of children and caregivers, cultivate caregivers’ care ability, reduce caregivers’ burden, help to improve T1DM caregivers’ positive feelings, and improve caregivers’ well-being and physical and mental health.
Serum Nardilysin as a Prognostic Biomarker in Pancreatic Ductal Adenocarcinoma

Background: Nardilysin, (N-arginine dibasic convertase, NRDC) has been reported to play an important role in cancer progression, and is associated with tumor proliferation signals and inflammatory signals, such as tumor necrosis factor-a (TNF-a) and heparin-binding epidermal growth factor-like growth factor (HB-EGF), through the activation of disintegrin and metalloproteinase (ADAM) proteases. NRDC has recently been revealed to be involved in the tumorigenesis of various types of cancer, including intrahepatic cholangiocarcinoma, malignant cerebral infarction, esophageal squamous cell carcinoma, and gastric cancer. However, the expression profiles and biological relevance of NRDC in pancreatic ductal adenocarcinoma have rarely been reported. Methods: We analyzed the NRDC expression profile in pancreatic ductal adenocarcinoma by enzyme-linked immunosorbent assay (ELISA) and identified NRDC as a circulating biomarker in the serum of 112 pancreatic ductal adenocarcinoma patients. The diagnostic value of NRDC was analyzed by the area under the curve (AUC) and the receiver operating characteristic (ROC) test. Results: Our results demonstrated that the clinical prognosis significance of NRDC with the clinical characteristics in pancreatic ductal adenocarcinoma (PDAC). NRDC was notably decreased in PDAC patient serum compared with the control group (p < 0.001). Furthermore, the present study found that the NRDC expression level was correlated with T grade (p < 0.001), metastasis(p < 0.001), differentiation(p < 0.001), and TNM stage (p = 0.011). Further bioinformatics analysis revealed that NRDC correlated with proliferation and migration pathways; in particular, it mediated cell-matrix adhesion-dependent activation in pancreatic ductal adenocarcinoma. Conclusions: Serum NRDC may play a useful diagnostic biomarker to evaluate the aggressive clinical features in PAAD patients.
Machinability of Polymeric Composites and Future Reinforcements—A Review

This paper reviews the machinability and mechanical properties of natural fiber-reinforced composites. Coupling agents, operating parameters, as well as chemical treatment effects on natural fiber-reinforced composites’ machinability are also reviewed. Moreover, the impacts of fibers’ physical properties on the machinability of the composite are mentioned. Fiber volume fraction (Vf), fiber orientation as well as chemical treatment effects on mechanical properties are also defined. Conclusively, the effect of fibers’ physical properties as well as mechanical properties is described. It was discovered that chemical treatment of natural fibers improved their compatibility with the matrix by removing their surface tissues, increasing the roughness average (Ra), and reducing moisture absorption. Also, the Orientation of the fiber plays an important role in controlling the mechanical properties of the composite. Moreover, some physical properties of the fibers, including quality of fiber distributed in the matrix; fiber size, length, and diameter; moisture absorption; porosity and the way fibers break during compounding with the matrix, were found to affect the mechanical properties of the composites formed.
Deep Learning‐Based H‐κ Method (HkNet) for Estimating Crustal Thickness and Vp/Vs Ratio From Receiver Functions

The teleseismic receiver function (RF) is commonly used to determine major interfaces of the Earth. If the crustal Vp is known approximately, the Moho converted Ps phase and crustal multiple reverberations can be used to determine the thickness (H) and average Vp/Vs ratio (κ) of the crust. A widely used method for this is H‐κ stacking (Zhu & Kanamori, 2000, https://doi.org/10.1029/1999JB900322), which uses grid search and superposition to find the maximum coherent energy of the Moho Ps and its reverberated multiples phases. However, this method assumes a homogeneous isotropic crust and a flat Moho. Furthermore, it is affected by the reference crustal Vp. Improved methods, such as the H‐κ‐c method for anisotropic media and inclined interfaces (J. Li et al., 2019, https://doi.org/10.1029/2018JB016356), help alleviate the problem. In this paper, we propose a new method that uses deep learning to estimate H and κ. Our method is divided into two steps. The first step employs a denoise architecture (the DenoiseNet) to reduce the noise level of the RFs and restore missing back‐azimuthal information. In the second step, our new deep learning network (the HkNet) is used to estimate H and κ. Deep learning has the inherent ability to automatically extract complex features from RFs, which allows us to estimate the parameters in complex media with different crustal Vp. Synthetic data tests show that the proposed method achieves better accuracy than the H‐κ and H‐κ‐c methods. Applications to real data show that the proposed method is robust and reliable in a wide range of geological settings.
Land Use, Productivity, and Profitability of Traditional Rice–Wheat System Could be Improved by Conservation Agriculture

Power tiller-driven plow tillage and crop residue exclusionary Traditional Agriculture practices are expensive, labor demanding, soil damaging, and eco-unfriendly. Over the last several years, pursuits of crop production through sustaining the productive capacity of soils, and environmental quality, have raised concern to adopt Conservation Agriculture worldwide. Single tillage combined with herbicides and crop residue retention principles of Conservation Agriculture are being developed. Between 2016–2017 and 2017–2018, a two-year on-farm experiment was done in Bangladesh. We practiced two crop establishment methods; Traditional Agriculture: Plow tillage followed by three manual weeding without residue preservation of previous crop and Conservation Agriculture: Pre-plant herbicide + single tillage + pre-emergence herbicide + post-emergence herbicide; under rice–wheat and rice–wheat–mungbean systems. Data reveal that the Conservation Agriculture was more cost-effective crop establishment technique than Traditional Agriculture in rice, wheat, and mungbean by increasing the ratio of benefit to costs by 24.3%, 35.7% and 48.8%, respectively, with a savings in tillage operations (66.3%, 58.1%, and 57.6%, respectively), weeding expenditures (59.2%, 24.5%, and 42.2%, respectively), and manpower requirements (25.1%, 27.2%, and 31.3%, respectively). This has resulted in an increase of 32% productivity of rice–wheat–mungbean systems with the yield advantage of 16%, 31% and 37% in rice, wheat and mungbean, respectively. When mungbean was added, the rice–wheat system’s productivity rose by 43%. The rice–wheat–mungbean system under Traditional Agriculture had the highest land utilization efficiency (99.45%), followed by Conservation Agriculture (92.05%), which expanded the scope to include additional crops into rice–wheat–mungbean system. Moreover, the Conservation Agriculture had a 59.7% greater production efficiency than Traditional Agriculture, where the rice–wheat–mungbean system having the highest production efficiency (53.00 kg–1 ha–1 day–1), followed by the rice–wheat system (45.57 kg–1 ha–1 day–1).
Investigating the Ovarian Microstructure in the Genera Helicolenus and Scorpaena (Teleostei, Sub-Order Scorpaenoidei) with Implications for Ovarian Dynamics and Spawning

Simple Summary The diversity of reproductive mechanism in bony fishes is greater than in any other group of vertebrates. It ranges from oviparous, to several stages of viviparous forms. In this context, scorpaenoid fishes belonging to the families Scorpaenidae and Sebastidae are of particular interest, since they show extremely varied reproductive modes connected with ovarian structures. We describe here the ovarian morphology of five rockfish species showing different reproductive modalities, using histology. Specialized microscopic features were found during gametogenesis, strictly related to the production of gelatinous mass surrounding the eggs, typical of these species. Based on microscopic maturity stages here analyzed, we found that all species shed eggs more than once through the spawning season, and were characterized by continuous oogenesis with multiple oocyte deposition. Further ovarian dynamic observations supported the hypothesis that all species had an indeterminate fecundity. Abstract The sub-order Scorpenoidei appears to be particularly interesting due to the presence of intermediate stages between oviparity and viviparity in several species. The present study aims to describe the ovarian morphology, using a histological and histochemical approach, in four ovuliparous species belonging to Scorpaena genus compared with a zygoparous species, H. dactylopterus, focusing also on the assessment of the ovarian dynamics in the populations of such species in Sardinia waters (central–western Mediterranean). Ovarian sections of all species were examined using light microscopy. All species showed a specialized ovary, cystovarian type II-3, strictly related to the production of gelatinous matrices surrounding the eggs. Some microscopic peculiarities in the oogenesis process were found: thin zona pellucida, small and low cortical alveoli, and a specialized ovarian wall during the spawning period. All species analyzed were batch-spawners with an asynchronous ovarian organization. A continuous recruitment of oocytes and the occurrence of de novo vitellogenesis was also observed. During the spawning period, low atresia intensity was detected, while a marked increase in this intensity found in the ovaries at the end of spawning season. Our observations may support an indeterminate fecundity type for these species.
Functionalized Mesoporous Silica as Doxorubicin Carriers and Cytotoxicity Boosters

Mesoporous silica nanoparticles (MSNs) bearing methyl, thiol or glucose groups were synthesized, and their encapsulation and release behaviors for the anticancer drug Doxorubicin (Dox) were investigated in comparison with nonporous homologous materials. The chemical modification of thiol-functional silica with a double bond glucoside was completed for the first time, by green thiol-ene photoaddition. The MSNs were characterized in terms of structure (FT-IR, Raman), morphology (TEM), porosity (nitrogen sorption–desorption) and Zeta potential measurements. The physical interactions responsible for the Dox encapsulation were investigated by analytic methods and MD simulations, and were correlated with the high loading efficiency of MSNs with thiol and glucose groups. High release at pH 5 was observed in most cases, with thiol-MSN exhibiting 98.25% cumulative release in sustained profile. At pH 7.4, the glucose-MSN showed 75.4% cumulative release, while the methyl-MSN exhibited a sustained release trend. The in vitro cytotoxicity was evaluated on NDHF, MeWo and HeLa cell lines by CellTiter-Glo assay, revealing strong cytotoxic effects in all of the loaded silica at low equivalent Dox concentration and selectivity for cancer cells. Atypical applications of each MSN as intravaginal, topical or oral Dox administration route could be proposed.
An Empirical Analysis of Efficiency of English Premier League (EPL) Football clubs (2005-2015) Using a Data Envelopment Analysis (DEA) Approach

The aims of this study are in two folds; first to examine if any EPL club could maintain efficiency over the period (2005 – 2015) and second, to identify the most efficient club(s) within the same period using Data Envelopment Analysis (DEA). There are limited studies on this type of investigation. Contrary to [2] the result shows that there is a high degree of inefficiency among EPL clubs and that only one club (Aston Villa) could maintain efficiency over the research period. The results further confirm that efficiency is not an absolute privilege of national league champions or big clubs, which motivated the study in the first place. However, inefficiency is largely due to waste of productive resources among EPL clubs.
Improved Patient Experience and Outcomes: Is Patient–Provider Concordance the Key?

Health disparities remain ubiquitous in the United States despite initiatives by the federal government and other organizations. A long-term solution for health inequity is needed in order to help improve patient outcomes for all. The purpose of this review is to examine if racial, gender, or multifactorial concordance (eg, race, age, gender, education, language) between patient and provider leads to a better patient experience and improved health outcomes. A PubMed search for articles published between 2016 and 2021 resulted in 23 separate studies that met inclusion criteria. The results from these studies were inconclusive in determining an association between patient–provider concordance and patient outcomes. Further research is needed to evaluate the positive, neutral, and sometimes negative impact of patient–provider concordance. By diversifying healthcare professions and improving cultural competency and communication training programs, providers may be better prepared to care for diverse populations in both concordant and discordant patient relationships.