Miracle-dz/UniFAR-FTUs huggingface dataset:
Budget Impact Analysis of Pharmacist-Led Medication Management in Cardiovascular and Type 2 Diabetic Patients

The paper aims to identify and measure the costs and savings associated with the delivery of Comprehensive Medication Management (CMM) services in Croatia in patients diagnosed with hypertension accompanied by at least one additional established cardiovascular disease (CVD) and/or type 2 diabetes mellitus (DMT2) who use five or more medicines daily. The budget impact analysis (BIA) employed in this study compares the total costs of CMM to the cost reductions expected from CMM. The cost reductions (or savings) are based on the reduced incidence of unwanted clinical events and healthcare service utilisation rates due to CMM. The BIA model is populated by data on medication therapy costs, labour, and training from the pilot CMM intervention introduced in Zagreb’s main Health Centre, while relevant international published sources were used to estimate the utilisation, incidence, and unwanted clinical events rates. Total direct costs, including pharmacists’ labour and training (EUR 2,667,098) and the increase in the cost of prescribed medication (EUR 5,182,864) amounted to EUR 7,849,962 for 3 years, rendering the cost per treated patient per year EUR 57. CMM is expected to reduce the utilisation rates of healthcare services and the incidence of unwanted clinical events, leading to a total 3-year reduction in healthcare costs of EUR 7,787,765. Given the total CMM costs of EUR 7,849,962, CMM’s 3-year budget impact equals EUR 92,869, rendering per treated patient an incremental cost of CMM EUR 0.67. Hence, CMM appears to be an affordable intervention for addressing medication mismanagement and irrational drug use.
On the Security of an ECC-Based Authentication Scheme for Internet of Drones

We demonstrate that the ECC-based authentication scheme for internet of drones (short for IoD-AS, published in IEEE Systems Journal, Hussain et al., 2021) Amassing the security: An ECC-based authentication scheme for Internet of Drones) fails to prevent an adversary from launching drone impersonation attacks. We also demonstrate that an adversary can compromise the session key of a target user and her/his employed drone.
Non-Invasive Physical Plasma Generated by a Medical Argon Plasma Device Induces the Expression of Regenerative Factors in Human Gingival Keratinocytes, Fibroblasts, and Tissue Biopsies

After oral surgery, intraoral wound healing and tissue regeneration is an important factor for the success of the entire therapy. In recent years, non-invasive medical plasma (NIPP) has been shown to accelerate wound healing, which would be particularly beneficial for patients with wound healing disorders. Since the application of NIPP in dentistry has not been sufficiently understood, the aim of the present study was to investigate the effect of a medical argon plasma device on gingival cells. Human gingival fibroblasts, keratinocytes, and tissue biopsies were treated with NIPP for different durations. Crucial markers associated with wound healing were examined at the mRNA and protein levels by real-time PCR, ELISA and immunohistochemistry. NIPP treatment led to an increase in Ki67 and MMP1 at mRNA and protein levels. NIPP application lasting longer than 60 s resulted in an increase in apoptotic genes at mRNA level and superficial damage to the epithelium in the tissue biopsies. Overall, our experimental setup demonstrated that NIPP application times of 30 s were most suitable for the treatment of gingival cells and tissue biopsies. Our study provides evidence for potential use of NIPP in dentistry, which would be a promising treatment option for oral surgery.
Current Status of Approach to Thyroid Nodules

The prevalence of thyroid nodules (TNs) in the community is high, and the rate of detection of TNs by using high-resolution ultrasonography (US) is approximately 60%. Less than 5% of TNs are malignant (1). TNs are seen approximately 4 times more frequently in women than in men. The prevalence of palpable TNs in areas without iodine defficiency is approximately 5% in women and 1% in men. The rate of thyroid cancer is two times higher in men than in women (4% vs. 8%) (2). In a screening study conducted with randomly selected individuals in the population, TNs were detected more frequently in women and the elderly (3). It is very important to distinguish between benign and malignant nodules. Clinical evaluation and US should be performed in palpable TNs (4). Physical examination alone may reveal 5% to 7% of TN. Ultrasound shows a prevalence of 20% to 76% in the same population, and this is in line with autopsy findings (2).
Does Social Support Matter in the Workplace? Social Support, Job Satisfaction, Bullying and Harassment in the Workplace during COVID-19

This study aims to examine social support at work amongst the employees of Icelandic municipalities and its relationship to job satisfaction, bullying and harassment. The study is based on an online survey conducted in 2021. A total of 4973 employees answered the questionnaire in part or in full after three reminders (57% response rate). The majority of the participants in the study were women (82%), but this gender ratio was representative of the population. The results show that social support gave an average score of 4.2 on a scale of 1–5; 87% of the participants were rather often or always satisfied with their job, 8% had experienced bullying at work, 2% had experienced sexual harassment and 3% had experienced gender-based harassment. Social support has a positive, moderately strong correlation with employee job satisfaction and a weak negative correlation with bullying at work. Based on the results, social support is an important factor related to the job satisfaction of employees and is a protective factor against bullying and sexual harassment at work. This finding demonstrates that managers and those responsible for employee well-being in the workplace should focus on social support at work, especially now that the psychosocial work environment is fragile because of COVID-19.
A Large-Scale Empirical Study of Real-Life Performance Issues in Open Source Projects

Software performance is a critical quality attribute that determines the success of a software system. However, practitioners lack comprehensive and holistic understanding of how real-life performance issues are caused and resolved in practice from the technical, engineering, and economic perspectives. This paper presents a large-scale empirical study of 570 real-life performance issues from 13 open source projects from various problem domains, and implemented in three popular programming languages, Java (192 issues), C/C++ (162 issues), and Python (216 issues). From the technical perspective, we summarize eight general types of performance issues with corresponding root causes and resolutions that apply for all three languages. We also identify available tools for detecting and resolving different types of issues from the literature. In addition, we found that 27% of the 570 issues are resolved by design-level optimization—coordinated revision of a group of related source files and their design structure. We reveal four typical design-level optimization patterns, including classic design patterns, change propagation, optimization clone, and parallel optimization that practitioners should be aware of in resolving performance issues. From the engineering perspective, this study analyzes how test code changes in performance optimization. We found that only 15% of the 570 performance issues involve revision of test code. In most cases, the revised test cases focus on the functional logic of the performance optimization, rather than directly evaluate the performance improvement. This finding points to the potential lack of engineering standard for formally verifying performance optimization in regression testing. Finally, from the economic perspective, we analyze the “Return On Investment” of performance optimization. We found that design-level optimization usually requires more investment, but not always yields to higher performance improvement. However, developers tend to use design-level optimization when they concern about other quality attributes, such as maintainability and readability.
Effect of Using Sweetness Products Fortified by Stevia Plant and other Materials on some Biochemical Parameters in Diabetic Rats

he effect of using food products fortified with stevia leaves and other materials such as pomegranate molasses, ginger, sesame seeds, and pumpkin seeds on the general acceptability of the sweetness and its ameliorative impacts on diabetes caused by STZ in rats. The sweets were prepared as (control and supplemented with stevia leaves individually and in combination with the other materials). The proximate chemical composition of raw materials, products, and sensory properties were evaluated. The results revealed that STZ induced diabetes in rats caused a significant decrease in FBW, BWG%, G%, FI and FER compared to the negative control group. While, found a increase in ALT and AST, TC, TG, VLDLC, and LDL-C, however, serum HDL-C level, testosterone, LH and FSH, SOD, activity and GPA and NO were decreased significantly compared to the healthy rats. Administration of stevia with other materials such as pomegranate molasses, ginger, sesame seeds, and pumpkin seeds alleviates the impact of diabetic disease. The conclusion was that sweetness products supplemented with stevia received acceptable sensory scores and exhibited protection in diabetes. This effect can be attributed to their high nutritional quality and their rich content of the antioxidant activity, and minerals especially phosphorus, calcium, sodium, zinc, copper, iron, and magnesium.
Distributed Task Scheduling in Serverless Edge Computing Networks for the Internet of Things: A Learning Approach

By delegating the infrastructure management, such as provisioning or scaling to third-party providers, serverless edge computing has recently been widely adopted in several applications, especially Internet of Things (IoT) applications. Task scheduling is a critical issue in serverless edge computing as it significantly impacts the quality of user experience. In contrast to the centralized scheduling in the cloud center, serverless edge task scheduling is more challenging due to the heterogeneous and resource-constrained nature of edge resources. This article aims to study the distributed task scheduling for the IoT in serverless edge computing networks, in which heterogeneous serverless edge computing nodes are rational individuals with interests to optimize their own scheduling utility while the nodes only have access to local observations. The task scheduling competition process is formulated as a partially observable stochastic game (POSG) to enable serverless edge computing nodes to noncooperatively schedule tasks and allocate computing resources depending on their locally observed system state, which takes into account the associated task generation state, data queue state, communication channel state, and previous computing resource allocation state. To solve the proposed POSG and deal with the partial observability, a multiagent task scheduling algorithm based on the dueling double deep recurrent $Q$ -network (D3RQN) method is developed to approximate the optimal task scheduling and resource allocation solution. Finally, extensive simulation experiments are conducted to validate the effectiveness and superiority of the proposed scheme.
Milling simulation analysis of spiral bevel gear based on tooth generating line

Based on the generating principle of the tooth surface of spiral bevel gear with spherical involute,the formation theory of generating line of tooth surface was studied.A method was proposed to machine this kind of gear tooth surface with the generating line as the milling cutter edge and using 3-axis linkage.A 3-D model was built for the bevel gear machine tool,the simulation of bevel gear machining process was performed and the tooth surface contact trace of the bevel gear generated by simulation was analyzed.The results indicated that the milling process of the spiral bevel gear based on the proposed theory is characterized by a simple motion and an easy control,and being able to realize the line-contact transmission with large dip-angle.
Novel Adaptive Fuzzy Feedback Neural Network Controller for Narrowband Active Noise Control System

With the development of science and technology in recent years, many operating machines have become sources of noise affecting quality of life. Hence, the topic of noise diminution using an active noise control (ANC) system has attracted many researchers. This paper develops a new adaptive fuzzy feedback neural network controller (AFFNNC) to improve the performance for narrowband active noise control (NANC) systems. The proposed controller combines fuzzy inference and adaptive feedback neural network controllers that are based on the filtered-s least mean square (FSLMS) algorithm. The AFFNNC comprises five network layers, in which the output layer of the controller uses an adaptive algorithm to tune directly the parameters of filters without prior training. The computational complexity, convergence and stability of the AFFNNC are analyzed. Evaluations are performed on both linear and nonlinear NANC systems with a recorded noise signal that was obtained from a transformer. Numerical simulations confirm the efficiency of the proposed controller compared with other ANC controllers.
Utilization of Android-Based ToSM (Test of Second Mathematics) Instrument for Mapping Intuitive Basic Calculation Competencies (IBCC) in Students

This research aims to find out the usefulness of an android-based ToSM (test of second mathematics) instrument for mapping the competency of intuitive basic calculation (CIBC) in students. ToSM (Test of Second Mathematics) is the standard instrument of Mathematics Seconds to measure IBCC (Intuitive Basic Calculation Competencies). ToSM only covers arithmetic operations (addition, subtraction, multiplication, and division), most essential. ToSM measures the number of operation counts per minute (OPM), time per operation category completion. The method used in writing review literature begins with the selection of topics. It then determines the keywords for the search for journals so that several journals are selected to be analyzed. Searches for the journal through google scholar are limited from 2015 to 2021. Meanwhile, the keyword used is "ToSM Seconds Mathematics. " This research was conducted by reviewing journals or literature related to this study plus statistical data and scientific works related to ToSM, which the Center for The Development of Mathematics Seconds (CDMS) team updates. Mapping essential calculation competencies among students are no less critical because ToSM has other uses, namely as an instrument to train concentration and resilience in learning.
The research for the best situation of FFR+IFR model based on the comparisons among FFR+IFR methods with different frequency reuse factor for cellular network

The IFR method is known as one of the simplest frequency reuse methods being used in cellular networks. However, it always carries out the frequency reuse progress regardless of the location of users. Thus, FFR method is combined to IFR method to compensate for the defect of IFR method. The research aims to find out the best models using the combination of FFR+IFR methods. The paper will firstly start with the introduction of the two frequency reuse methods, and provide the principles of how they are combined. Then, the ideas of the MATLAB coding for modelling and simulating the models are further introduced in the paper. According to the results of the comparisons among the FFR+IFR models with the frequency reuse factor1, 3, 4, it is found that the FFR+IFR3 model is the most efficient and available. By doing this research, the best model could be used in reality since it is in line with the actual situation to the greatest extent.
Augmenting awareness in data-intensive web-based collaboration

Much research has been performed on how computer-based technologies might facilitate awareness among cooperating actors. However, existing approaches in providing awareness services prove to be inadequate in data-intensive situations. Moreover, they fail to address the needs of dynamic, web-based communities. In this context, this paper presents a list of awareness mechanisms that have been integrated in an innovative web-based collaboration support tool, the ultimate aim being to satisfy the requirements associated to the above remarks. The proposed mechanisms are described and elaborated with respect to various awareness types reported in the literature.
Diverse in Local, Overlapping in Official Medical Botany: Critical Analysis of Medicinal Plant Records from the Historic Regions of Livonia and Courland in Northeast Europe, 1829–1895

Works on historical ethnobotany can help shed light on past plant uses and humankind’s relationships with the environment. We analyzed medicinal plant uses from the historical regions of Livonia and Courland in Northeast Europe based on three studies published within the 19th century by medical doctors researching local ethnomedicine. The sources were manually searched, and information extracted and entered into a database. In total, there were 603 detailed reports of medicinal plant use, which refer to 219 taxa belonging to 69 families and one unidentified local taxon. Dominant families were Asteraceae (14%), Solanaceae (7%), Rosaceae (6%), and Apiaceae (5%). The majority of use reports were attributed to the treatment of four disease categories: digestive (24%), skin (22%), respiratory (11%), and general (11%). The small overlapping portion (14 taxa mentioned by all three authors and another 27 taxa named by two authors) contained a high proportion of taxa (46%) mentioned in Dioscorides, which were widespread during that period in scholarly practice. Despite the shared flora, geographical vicinity, and culturally similar backgrounds, the medicinal use of plants in historical Courland and Livonia showed high biocultural diversity and reliance on wild taxa. We encourage researchers to study and re-evaluate the historical ethnobotanical literature and provide some suggestions on how to do this effectively.
Next-generation sequencing (NGS) detection of PIK3CA somatic mutations in Hepatocellular carcinoma (HCC) Egyptians

Hepatocellular carcinoma (HCC) is the tertiary greatest communal malignant cancer that origins mortality globally. A high prevalence of return means that even while cancer is getting more treatable in its early stages, advanced cases have a bad prognosis. To properly treat HCC, it is now necessary to understand its pathogenic process and its associated genetic abnormalities. The next-generation sequencing (NGS) was used to discover PIK3CA somatic mutations in HCC Egyptian patients. In the present study a unique NGS panel (AmpliSeq) containing the PIK3CA gene was utilized to examine 21 liquid biopsy samples from patients with HCC. The results indicated that over 40 - single-nucleotide-variation (SNV) were recognized in PIK3CA gene with incidence of 85.7%. The changes were dispersed between deleterious, undefined significance, and tolerated deviations, where the preponderance of the changes were the missense variants (68%),synonymous(25%), and (7%) for stop-gained. It was concluded from this research that detection of numerous somatic mutations of PIK3CA can assist in the etiology of HCC.
An Identity-Based Encryption Method for SDN-Enabled Source Routing Systems

In this study, we consider endpoints communicating over a software-defined networking (SDN)-based architecture using source routing, i.e., packets are routed through a path selected by the packet sender, and we provide a security solution that enforces the selected path. In particular, our solution allows a sender to select the path that a packet should go through using a constant-size cryptographic construction which is referred to as the authenticator. A recipient can examine an authenticator and verify that the received packet has followed the path selected by the sender. Additionally, any intermediate “programmable” switch can verify whether or not it is included in the path of a packet. Our solution can be used even for paths that include multiple recipients (e.g., multicast paths), as well as multiple parallel paths (e.g., multipath transmissions). We implement our solution by leveraging identity-based encryption (IBE), so it can be used by any sender that knows the identifiers of the links that compose the desired path, i.e., information that the sender usually already knows as part of the source routing protocol. Our solution is realistic since it can be implemented over a variety of platforms with tolerable overhead.
Processes Underlying the Relation between Cognitive Ability and Curiosity with Academic Performance: A Mediation Analysis for Epistemic Behavior in a Five-Year Longitudinal Study

Cognitive ability and curiosity are significant predictors of academic achievement; yet the processes underlying these relations are not well understood. I drew on ideas from the environmental enrichment hypothesis and the differential preservation hypothesis and hypothesized that epistemic behavior acts as a mediator. Longitudinal data were collected from 1964 individuals in three waves, spanning five years: cognitive ability and curiosity were assessed at time 1; epistemic behavior at time 2; at time 3, grade point average and highest degree of both secondary and tertiary academic education (if applicable) were obtained retrospectively via self-report. I found expected bivariate relations between all study variables, including a significant relation between cognitive ability and curiosity and significant relations of both of these variables with secondary academic performance. Epistemic behavior was related to curiosity and academic performance but, at odds with the hypothesis, did not mediate the relation between cognitive and personality variables and academic performance. It is concluded that the process underlying the behavioral consequences of cognitive ability and curiosity is not environmental enrichment.
MS-ALN:Multiscale Attention Learning Network for Pest Recognition

Complex backgrounds, occlusions, and non-uniform classes present great challenges to pest recognition in practical applications. In this paper, we propose a multiscale attention learning network to address these problems. This network recursively locates discriminative regions and learns region-based feature representation in four branches. Three newly designed modules, which are target localization, attention detection, and attention removal connect two feature extracting sub-networks in adjacent branches to generate images of different scales. The target localization and attention detection modules locate the discriminative regions to filter out complex backgrounds while the attention removal module randomly removes the discriminative region to encourage the model to tackle occlusions. Thereafter, the parameter-shared classification sub-network follows the feature extracting sub-network in every branch for pest recognition. A decoupled learning strategy is adopted to address the problem of non-uniform classes. We experimented on the widely used IP-102 dataset and achieved state-of-the-art performance.