Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Primary Health Care Specialized Reference Clinics in Riyadh First Health Cluster: Outcome, Cost-Effectiveness and Patient Satisfaction

Purpose The objectives of the study are to assess the outcome and cost-effectiveness of specialized reference clinics (SRCs) in primary health care centers (PHCCs) of Riyadh First Health Cluster (RFHC), then to estimate the patient satisfaction among clients utilizing such SRCs. Patients and Methods This facility-based study was conducted in Riyadh city, Saudi Arabia among six PHCCs in RFHC that contain SRCs. Records of all patients utilizing SRCs and their referral information were studied along two years. An in-depth interview was conducted with health care providers in SRCs. Cost analysis was calculated by the financial support group within RFHC. Also, a randomly selected 400 subjects utilizing SRCs were asked to fill patient satisfaction questionnaire. Results Over two years, a total number of 55,084 patients utilized SRCs among different specialties. Most of these patients (86.7%) had full medical service within PHC-SRCs with no need for referral to hospitals. SRCs are significantly effective in decreasing the burden on hospitals in most specialties (p < 0.001). This effectiveness is significantly increased during the 2nd year of service. The time spent until appointment is significantly reduced from an average of six weeks in hospitals to an average of one week in SRCs. SRCs are very cost-effective as they reduced referrals to hospitals by 86.7% among 55,084 patients who utilized SRCs over two years, saving total costs of about 14.08 million Saudi Riyals (3.75 million US dollars). Most of the specialties are cost-effective except for urology and general surgery clinics, which are not cost-effective. Patient satisfaction is high regarding all service domains. The overall patient satisfaction score increased from 71.4% in the 1st year up to 73.2% in the second year. Conclusion PHC-SRCs are cost-effective health services and their creation is reasonable and beneficial in terms of reducing costs of health care delivery, reducing the burden on hospitals, and improving patient satisfaction.
An Empirical Study on the Relationship between American Stock Market and Exchange Rate under the COVID-19

From 2020, the COVID-19 pandemic spread globally and had a significant impact on the economies of most countries. This article analysed the impact of the COVID-19 pandemic in the United States and the dollar exchange rate on the US stock market. We found a significant statistical correlation between the COVID-19 pandemic and the return of the US stock market, but there was no economic significance. COVID-19 impacted the volatility of the US stock market in the short term, but in the long term, it did not have an impact on the volatility of the US stock market. However, the dollar's exchange rate did have a significant impact on the return and volatility of the US stock market.
Socioeconomic Status and Social Support: Social Support Reduces Inflammatory Reactivity for Individuals Whose Early-Life Socioeconomic Status Was Low.

Low socioeconomic status (SES) during childhood confers risk for adverse health in adulthood. Accumulating evidence suggests that this may be due, in part, to the association between lower childhood SES and higher levels of proinflammatory cytokines. Drawing from literature showing that low childhood SES predicts exaggerated physiological reactivity to stressors and that lower SES is associated with a more communal, socially attuned orientation, we hypothesized that inflammatory reactivity would be more greatly affected by cues of social support among individuals whose childhood SES was low than among those whose childhood SES was high. In two studies, we found that individuals with lower subjective childhood SES exhibited greater reductions in pro-inflammatory cytokine reactivity to a stressor in the presence of a supportive figure (relative to conditions with an unsupportive or neutral figure). These effects were independent of current SES. This work helps illuminate SES-based differences in inflammatory reactivity to stressors, particularly among individuals whose childhood SES was low.
OTT_A_284211 699..710

*These authors contributed equally to this work Introduction: Colorectal cancer (CRC) is a major cause of cancer-related mortality worldwide. Copines-1 (CPNE1) has been shown to be overexpressed in various cancers; however, the role of CPNE1 in CRC remains unknown. Therefore, it is of great importance to elucidate the role of CPNE1 in CRC and its underlying mechanism of action. Methods: CPNE1 expression in CRC tissues was measured by quantitative real-time PCR and immunohistochemical (IHC) staining. CPNE1 was knocked down (KD) or overexpressed using small inferring RNAs or lentiviral transduction in CRC cells. The proliferation, apoptosis, glycolysis, and mitochondrial respiration of CRC cells were assessed by cell counting kit-8, flow cytometry, and Xfe24 extracellular flux analyzer assays, respectively. The role of CPNE1 in tumor growth and chemoresistance was further confirmed in xenograft and patient-derived tumor xenograft models, respectively. Results: CPNE1 mRNA and protein were upregulated in CRC tissues. CPNE1 promoted proliferation, inhibited apoptosis, increased mitochondrial respiration, enhanced aerobic glycolysis by activating AKT signaling, upregulated glucose transporter 1 (GLUT1) and hexokinase 2 (HK2), and downregulated the production of cleaved Caspase-3 (c-Caspase 3). CPNE1 also contributed to chemoresistance in CRC cells. CPNE1 KD inhibited tumor growth and increased the sensitivity of tumors to oxaliplatin in vivo. Conclusion: CPNE1 promotes CRC progression by activating the AKT-GLUT1/HK2 cascade and enhances chemoresistance.
GraphFuzz: Library API Fuzzing with Lifetime-aware Dataflow Graphs

We present the design and implementation of GraphFuzz, a new structure-, coverage- and object lifetime-aware fuzzer capable of automatically testing low-level Library APIs. Unlike other fuzzers, GraphFuzz models sequences of executed functions as a dataflow graph, thus enabling it to perform graph-based mutations both at the data and at the execution trace level. GraphFuzz comes with an automated specification generator to minimize the developer integration effort. We use GraphFuzz to analyze Skia-the rigorously tested Google Chrome graphics library-and benchmark GraphFuzz-generated fuzzing harnesses against hand-optimized, painstakingly written libFuzzer harnesses. We find that GraphFuzz generates test cases that achieve 2-3x more code coverage on average with minimal development effort, and also uncovered previous unknown defects in the process. We demonstrate GraphFuzz's applicability on low-level APIs by analyzing four additional open-source libraries and finding dozens of previously unknown defects. All security relevant findings have already been reported and fixed by the developers. Last, we open-source GraphFuzz under a permissive license and provide code to reproduce all results in this paper.
Analysing the uncertainty of modelling hydrologic states of AWRA-L – understanding impacts from parameter uncertainty for the National Hydrological Projections

Title: Analysing the uncertainty of modelling hydrologic states of AWRA-L – understanding impacts from parameter Projections to and precision of the in show regions with lower number of calibrated catchments, ephemerality, flashiness, and high contributions of to baseflow are associated with higher levels of uncertainty, e.g., as observed for the Rangelands and Southern and South-Western Flatlands regions. The lowest performing region, Rangelands has only nine AWRA-L evaluation catchments and its dominant flow is non-perennial. To improve the certainty in this area, both runoff rate and needs to be captured. Although the amount of runoff in non-perennial are across all regions, a large part of depends on baseflow contributions. Since in non-perennial catchments, during the wet seasons, typically water-tables typically rise, and subsurface flow and surface runoff contribute to runoff generation. Groundwater storage and baseflow therefore play key roles in increasing flow during the wet season. Thus, other components of water must be simulated precisely in regions with non-perennial flow to provide accurate and reliable simulations, and groundwater storage (TWS) and ET were also simulated with high uncertainty in these areas. For the Southern and South-Western Flatlands region, the key issue is the poorer performance of AWRA-L across flat areas within this region.
Vul4J: A Dataset of Reproducible Java Vulnerabilities Geared Towards the Study of Program Repair Techniques

In this work we present Vul4j, a Java vulnerability dataset where each vulnerability is associated to a patch and, most importantly, to a Proof of Vulnerability (PoV) test case. We analyzed 1803 fix commits from 912 real-world vulnerabilities in the Project KB knowledge base to extract the reproducible vulnerabilities, i.e., vulnerabilities that can be triggered by one or more PoV test cases. To this aim, we ran the test suite of the application in both, the vulnerable and secure versions, to identify the corresponding PoVs. Furthermore, if no PoV test case was spotted, then we wrote it ourselves. As a result, Vul4j includes 79 reproducible vulnerabilities from 51 open-source projects, spanning 25 different Common Weakness Enumeration (CWE) types. To the extent of our knowledge, this is the first dataset of its kind created for Java. Particularly, it targets the study of Automated Program Repair (APR) tools, where PoVs are often necessary in order to identify plausible patches. We made our dataset and related tools publically available on GitHub.
Design and Implementation of Digital Media Technology Experimental System Based on Machine Learning

: Digital media technology is an open platform, which mainly includes scene design, role image design, game programming, multimedia post-processing and human-computer interaction technology. In this paper, machine learning is used to study the recognition and Simulation of human motion by humanoid robots, so as to enhance human-computer interaction experience. Four tasks have been done, including moving object detection and tracking, motion feature representation, motion recognition and robot imitation, with emphasis on the use of machine learning methods, extraction of human body features, and research and implementation of motion recognition and simulation.
A Preliminary Study on Third Tone Sandhi in Malaysian Mandarin

Malaysian Mandarin Third Tone Sandhi Tonal Realisation Chinese Prosody Global Chinese Mandarin Chinese language has increased in importance among the Chinese community in Malaysia. At present, the Mandarin language is the only medium of instruction in Chinese schools, but it has also become a lingua franca of local Chinese Malaysians of various dialect groups. With the expansion of the Global Chinese concept, numerous studies have been carried out on the Mandarin language used in Malaysia (henceforth, Malaysian Mandarin). These studies have mainly focused on lexical and syntactic aspects rather than on the phonetic system of Malaysian Mandarin. This could be because many researchers consider the standard spoken form of Malaysian Mandarin similar to Standard Mandarin, although they are different. To better understand the development of the sound systems in regional Mandarin varieties, this paper investigates Malaysian Mandarin, specifically the standard spoken variety, by examining the acoustic realisation of third tone sandhi, a well-known Mandarin language tonal variation phenomenon. Forty-four Malaysian Chinese undergraduate students have been selected as speakers of the standard spoken variety. A nursery rhyme consisting of nineteen third tone (T3) syllables was used as the reading material to analyse the effect of different prosodic and syntactic structures on T3 realisation. The findings indicated that generally, the T3 sandhi phenomena in Malaysian Mandarin match Standard Chinese's sandhi rule. However, the acoustic realisation of T3 in terms of pitch contour and voice quality showed some differences. The implementation of T3 sandhi is also affected by the syntactic and rhythmic structure if a disyllabic or trisyllabic T3 sequence occurs across two feet. The findings suggest that the prosodic structure in the standard spoken form of Malaysian Mandarin may be developing differently from Standard Mandarin.
Calibration of Dissipative Particle Dynamics Method to Study Rheology of Dense Suspensions

Dissipative Particle Dynamics method is employed to model the particulate suspensions. The system input parameters are calibrated to capture the experimental relative viscosity versus volume fraction in dilute (φ≤ 0.2), semidilute (0.2<φ≤ 0.3) and dense regimes 0.3<φ≤ 0.45. Statistical uncertainties and system bulk and overall temperatures are monitored to guarantee that equilibrium has been quantitatively reached. It was found that increment of solvent drag coefficient or the dissipation rate (1≤γs≤200) between like solvent particles linearly increases the solvent and suspension viscosity. Solvent number density (ρs) changing from 2 to 20 in sync with the repulsion coefficient renders a parabolic variation for suspension and solvent viscosities. Two sets of calibrated simulation settings are ultimately proposed to reasonably capture the rheological behaviour of dilute to dense suspensions according to experiment and empirical relations for relative viscosity.
Comparison of Effect of Dressing with Bilva Herbal Ointment and Silver Sulfadiazine on Healing Process, Pain and Itching of Burn Wounds: A Randomized Clinical Trial

Introduction: The most common method for burn wound dressing is silver sulfadiazine (SSD); however, its side effects on wound healing and the need for repeated use for healing are often painful. This study aimed to compare two different dressings, namely Bilva and SSD ointments, on wound healing, pain, itching, and scarring of the burn wounds. Methods: This clinical trial study was performed on 35 patients with superficial second-degree burns hospitalized in the Burn Ward of Sina Hospital in Tabriz, Iran, from 2019 to 20. After irrigation of the wound, Bilva ointment was applied randomly on one side and SSD ointment on the other side to repair patients' burns. Patients were followed up on days 1, 7, 14, 21, and the first, second, and third months after burns; data related to the wound healing process, pain, itching, and scar status of patients were collected with a checklist. Results: There was no statistically significant difference between the two groups of variables related to the wound healing process on all days. The amount of burn wound scar did not differ between the two groups on day 21 and the first, second, and third months. Patients' pain and itching were significantly better in the Bilva group on the 7th (p<0.01), 14th (p<0.01), 21st day (p<0.01), and the first month (p<0.01) after burns relative to the SSD group. Conclusion: Bilva ointment had a similar effect in healing the burn wounds of patients compared to SSD, and it was more effective in controlling pain and itching of burn wounds than SSD. Further studies are needed to evaluate the cost-effectiveness of this dressing method on superficial burn wounds.
Evaluation of three state-of-the-art metabolite prediction software packages (Meteor, MetaSite, and StarDrop) through independent and synergistic use

The aim of this study was to evaluate three different metabolite prediction software packages (Meteor, MetaSite, and StarDrop) with respect to their ability to predict loci of metabolism and suggest relative proportions of metabolites. A chemically diverse test set of 22 compounds for which in vivo human mass balance studies and metabolic schemes were available, was used as basis for the evaluation. Each software package was provided with structures of the parent compounds, and predicted metabolites were compared with experimentally determined human metabolites. The evaluation consisted of two parts: firstly, different settings within each software package were investigated and the software was evaluated using those settings determined to give the best prediction. Secondly, the three different packages were combined using the optimized settings to see whether a synergistic effect concerning the overall metabolism prediction could be established. The performance of the software was scored for both sensitivity and precision, taking into account the capabilities/limitations of the particular software. Varying results were obtained for the individual packages. Meteor showed a general tendency towards overprediction and this led to a relatively low precision (~35%) but high sensitivity (~70%). MetaSite and StarDrop both exhibited a sensitivity and precision of ~50%. By combining predictions obtained with the different packages, we found that increased precision can be obtained. We conclude that the state-of-the-art individual metabolite prediction software has many advantageous features but needs refinement to obtain acceptable prediction profiles. Synergistic use of different software packages could prove useful.
An Exploratory Study of Mobile-Based Scenarios for Foreign Language Teaching in Early Childhood

: In today’s world, the ability to communicate in a foreign language is more highly prized than ever by prospective employers, which results in more options and possibilities for students, both academically and professionally. As a result of this tendency and the need for new communication methods, language instructors are driven to include cutting-edge language teaching approaches, resources, and materials in their classroom instruction, such as using ICT, or information, communication and ubiquitous technologies. In this paper, we introduce learning scenarios based on two mobile learning apps that facilitate language learning through interesting, interactive settings in a more personalized way based on children’s age. The writers’ emphasis will be on demonstrating interactive activities devised in their classrooms and on providing examples of student work in two languages, English and Spanish. Through this paper, we examine a range of educational tools and determine that Mondly Kids and Language Drops-Kahoot are the best acceptable teaching materials. On the basis of this assumption, we created three distinct groups of students, and the outcomes from the assessment technique show that mobile language learning enhances children’s experiences and increases their willingness to learn a new language. Additionally, students can use mobile applications to improve their speaking abilities and critical thinking skills throughout a language learning session.
Public Awareness and Acceptance of Telemedicine in Japan

— Telemedicine seeks to improve the quality, efficiency and cost of healthcare by a variety of electronic means. It is originally designed to serve patients in remote areas. The service involves the use of technologies to support the connection between doctors and their patients without the need for in- person meetings. Nowadays, the COVID-19 outbreak could put a spotlight on Telemedicine as an important tool to avoid the community from infection. This study aims to examine public awareness and acceptability of telemedicine in Japan. Furthermore, it determines the main reasons which hinder the growth of the service in the COVID-19 era from the public’s views. To achieve our goals, 84 participants in the age ranging from 20 to 64 years were randomly selected, and data were collected from them using a questionnaire survey. The survey reveals that all participants are not telemedicine users. Fifty-nine (70%) participants are somewhat aware of telemedicine service, and 51% of them are very much interested in telemedicine. Only 3 (4%) participants are quite satisfied with the amount of information available on telemedicine. This is obvious as 50% of them have no detailed information about the service. Fifty-two (37%) participants state that online telemedicine education program is an effective way to raise awareness of telemedicine. The survey results also identify the major reasons for not using telemedicine service in the COVID-19 era. At present, there are various issues for a slow growth of telemedicine in Japan. Recommendations to increase awareness of telemedicine service have been made.
Anticancer Activities of Green Synthesized Copper Oxide Nanoparticles: Recent Review

Nanotechnology and Nanoscience is a multidisciplinary field to exploit the wide spectrum of the emerging area from fundamental sciences with novel techniques. Nanoparticles have greater surface area to volume ratios. Up to now, nu merous biological organisms are described to have their po tentiality for the synthesis of metallic nanoparticles. Green synthesis is a gradually evolving research area that used to extract nanoparticles from plants. Natural products have a long history of use in the treatment of cancer. Cancer is a group of diseases involving abnormal cell growth with the ability to spread the other parts of the body. Cancer is of ten treated with some combination of radiation therapy, surgery, chemotherapy, and targeted CuO-NPs made of the plants, which have anticancereous properties, which can counteract the symptoms as against the cancerous cells. Dif ferent chemical and physical methods have been proposed to synthesize CuO-NPs. Among those methods, the green synthesized NPs have significance in safety and eco-friendly nature. The green synthesized CuO-NPs showed promising anticancer activity against different cancer cell lines. In fact, green synthesized CuO-NPs are an effective candidate for pharmaceutical, biomedical, and environmental applica -tions. To explore the anticancer potential of the CuO-NPs plants extracts for isolation and characterization of the ac tive anticancer principles so that better, safer and cost effec tive drugs can be developed for treating cancer.
SHIP DETECTION AND CLASSIFICATION USING TYPE OF CONVOLUTION NEURAL NETWORKS

Ship classification and detection systems are used in many areas that may cause problems such as national and local defense in countries with intense coastal and strait crossings, ship traffic control, illegal fishing, pirate, human traffickers and the global trade chain. In order to meet these kinds of needs easily, solutions with many different methods have been developed related to ship classification and detection. Research on these methods is divided into two groups intensely. These are the methods in used in Satellite and SAR images. Although the number of studies on these sources is high, the images that are come are not public. In addition, their resolution is not enough for ship classification and detection. As an alternative solution to these methods, CNNs with deep learning technology, have become quite popular. One of the reasons why thesis is number of classes can be easily expanded according to the scenarios in the classification and detection problems of CNN models. In this thesis, the most popular deep learning CNN architectures in the literature such as VGG16, VGG 19, DenseNet121 and Xception are used for ship classification. Also, CNN architecture YOLOv3 with high performance is preferred for ship detection. The results of these models are compared in this thesis. Our data set of 6 different ship types, created by us, is used for training and testing. Since CNN models require a large number of training data sets, the transfer learning technology is applied in these models in order to eliminate the problem of lack of data. The contribution of our thesis to literature can be listed as comparing CNN model architectures for ship classification problems, investigating the effects of layer numbers in CNN model architecture and choosing the appropriate hyper parameter for this problem. For ship detection, we can evaluate the number of labeled data as an impact on performance.