Miracle-dz/UniFAR-FTUs huggingface dataset:
MEC-assisted Low Latency Communication for Autonomous Flight Control of 5G-Connected UAV

Proliferating applications of unmanned aerial vehicles (UAVs) impose new service requirements, leading to several challenges. One of the crucial challenges in this vein is to facilitate the autonomous navigation of UAVs. Concretely, the UAV needs to individually process the visual data and subsequently plan its trajectories. Since the UAV has limited onboard storage constraints, its computational capabilities are often restricted and it may not be viable to process the data locally for trajectory planning. Alternatively, the UAV can send the visual inputs to the ground controller which, in turn, feeds back the command and control signals to the UAV for its safe navigation. However, this process may introduce some delays, which is not desirable for autonomous UAVs’ safe and reliable navigation. Thus, it is essential to devise techniques and approaches that can potentially offer low-latency solutions for planning the UAV’s flight. To this end, this paper analyzes a multi-access edge computing aided UAV and aims to minimize the latency of the task processing. More specifically, we propose an offloading strategy for a UAV by optimally designing the offloading parameter, local computational resources, and altitude of the UAV. The numerical and simulation results are presented to offer various design insights, and the benefits of the proposed strategy are also illustrated in contrast to the other baseline approaches.
Multilocus Genetic Profile Reflecting Low Dopaminergic Signaling Is Directly Associated with Obesity and Cardiometabolic Disorders Due to Antipsychotic Treatment

Treatment with second-generation antipsychotics (SGAs) can cause obesity and other cardiometabolic disorders linked to D2 receptor (DRD2) and to genotypes affecting dopaminergic (DA) activity, within reward circuits. We explored the relationship of cardiometabolic alterations with single genetic polymorphisms DRD2 rs1799732 (NG_008841.1:g.4750dup -> C), DRD2 rs6277 (NG_008841.1:g.67543C>T), COMT rs4680 (NG_011526.1:g.27009G>A), and VNTR in both DRD4 NC_000011. 10 (637269-640706) and DAT1 NC_000005. 10 (1392794-1445440), as well as with a multilocus genetic profile score (MLGP). A total of 285 psychiatric patients treated with SGAs for at least three months were selected. Cardiometabolic parameters were classified according to ATP-III and WHO criteria. Blood samples were taken for routinely biochemical assays and PCR genotyping. Obesity (BMI, waist (W)), high diastolic blood pressure (DBP), and hypertriglyceridemia (HTG) were present in those genetic variants related to low dopaminergic activity: InsIns genotype in rs1799732 (BMI: OR: 2.91 [1.42–5.94]), DRD4-VNTR-L allele (W: OR: 1.73 [1.04–2.87]) and 9R9R variant in DAT1-VNTR (W: OR: 2.73 [1.16–6.40]; high DBP: OR: 3.33 [1.54–7.31]; HTG: OR: 4.38 [1.85–10.36]). A low MLGP score indicated a higher risk of suffering cardiometabolic disorders (BMI: OR: 1.23 [1.05–1.45]; W: OR: 1.18 [1.03–1.34]; high DBP: OR: 1.22 [1.06–1.41]; HTG: OR: 1.20 [1.04–1.39]). The MLGP score was more sensitive for detecting the risk of suffering these alterations. Low dopaminergic system function would contribute to increased obesity, BDP, and HTG following long-term SGA treatment.
The Structure Analysis of Industrial Association Network in Digital Economy Based on Blockchain Technology

: The digital economy, as a new driver of economic growth in China, has garnered extensive attention from various sectors. The 14th Five-Year Plan emphasizes the need to accelerate digital development and promote the deep integration of the digital economy with the real economy. In order to conduct in-depth research on the economic status, industry structure characteristics, and the main industries influenced by the digital industry in China, a network relationship management model was constructed based on blockchain technology. The maximum spanning tree algorithm, Louvain community detection algorithm, and threshold network algorithm were employed to analyze the structural characteristics of China's digital industry within the entire industry network. This analysis provides empirical support at the industry level for advancing the development of China's digital economy. The research findings indicate the following: Firstly, based on the current stage of economic development and industry structure, the digital industry is not the core or leading industry in the Chinese economy. However, it possesses significant potential and room for growth. In the future, consideration can be given to adjusting the macroeconomic structure, strengthening the application of digital technologies in core industries, promoting the adoption of digital technologies in a wider range of industries, and enhancing its overall economic status. Secondly, considering the main industries influenced by the digital industry, there exist variations in the degree of digitalization across different sectors. Therefore, differentiated policies are necessary in practice.
Tomato Aphid (Aphis gossypii) Secreted Saliva Can Enhance Aphid Resistance by Upregulating Signaling Molecules in Tomato (Solanum lycopersicum)

This study investigated the impact of Aphis gossypii watery saliva on the induction of tomato (Solanum lycopersicum) plant resistance. To examine the role of A. gossypii saliva, we collected watery saliva from A. gossypii after a 48 h feeding period on an artificial diet. SDS-PAGE resolving gel 12% was used to separate the salivary proteins. Relative expression of gene analysis revealed that the intrusion of A. gossypii saliva dripping onto S. lycopersicum leaves triggered robust defense responses mediated by a signaling molecule, i.e., salicylic acid, while the signaling molecule’s jasmonic acid-dependent defense responses were moderately activated. Aphid saliva infiltrated S. lycopersicum leaves slowed the intrinsic rate of population growth of A. gossypii and significantly reduced the number of nymphs produced daily, compared to untreated leaves. During a choice test with untreated S. lycopersicum, aphids showed a repellent response towards saliva-infiltrated S. lycopersicum. Moreover, the (EPG) electrical penetration graph analysis demonstrated that the eating pattern of A. gossypii compared to untreated S. lycopersicum, that had been exposed to saliva was negatively impacted. These results provide compelling evidence for the involvement of salivary components of A. gossypii in inducing resistance against aphids in S. lycopersicum plants. Furthermore, the study underscores the crucial role of watery saliva in the intricate interactions between aphids and plants. The activation of pathways was also part of the defensive response (jasmonic acid (JA), salicylic acid (SA) signaling molecules). The findings of this research deliver valuable insights into the potential of watery aphid saliva as a natural defense mechanism against aphid infestations in S. lycopersicum crops.
AdaptCD: An Adaptive Target Region-based Commodity Detection System

With the rapid development of computer vision, the detection and counting of goods through computer vision techniques has become practicable. The AICity competition has focused its attention on the automatic recognition and counting of commodities, and has significantly propelled the advancement of this field through the organization of competitive events. Minimizing false positives and false negatives is critical to the success of this task. An Adaptive Target Region-based Commodity Detection System has been designed in this study to accurately identify the trajectory and category of goods. To alleviate the difference between training and testing data, two data augmentation methods are utilized, and various data synthesis methods are also designed to meet the training needs of different network models in the framework. Additional Adaptive Algorithms are designed to solve the problem of camera movement during product shooting. An Effective Fusion Algorithm is proposed for Dual Detectors to complement their advantages and minimize detection errors. To maximize the efficiency of the well-trained commodity classifier, an innovative Multi-layer Perception Fusion Module(MPFM) is devised to enhance the commodity classification capabilities, thereby generating more dependable features for tracking purposes. The system has been validated in Multi-Class Product Counting & Recognition for Automated Retail Checkout (2023 AI CITY Challenge Task4) competition, where our results achieve F1 Score of 0.9787 in Task4 testA, ranking second in 2023 AI CITY Challenge Task4 [17]. The code will be released at: https://github.com/mzl163/AICITY23_Task4.
PREDICTING CONSUMER LOYALTY TO ONLINE TAXI SERVICES USING THE TECHNOLOGY ACCEPTANCE MODEL (TAM)

This study aims to measure the factors that can affect customer loyalty in using the mobile taxi service application using the Technology Acceptance Model (TAM). The research model used involves several variables, namely perceived usefulness, perceived ease of use, attitude, customer loyalty and customer satisfaction as additional variables. The analysis used was Structural Equation Modeling (SEM) and respondents numbered 105 people from the city of Bandung. This research proves that in addition to the variables contained in the Technology Acceptance Model (TAM), in achieving loyalty the users of the mobile taxi service application must achieve customer satisfaction first. The results of this study indicate that the presence of customer satisfaction as an additional variable can increase understanding in technology acceptance by completing variables that are part of the Technology Acceptance Model (TAM).
Improving WaveRNN with Heuristic Dynamic Blending for Fast and High-Quality GPU Vocoding

Auto-regressive vocoders are typically less efficient at inference due to their serial nature, making it difficult to fully utilize graphics processing units (GPUs). In this context, batched inference with upsampled feature folding can be used to speed up vocoding. However, speech quality degradation caused by blending folded waveform segments making it hard to be applied to production. To address this issue, we propose a novel blending approach called heuristic dynamic blending (HDB), which effectively addresses the voice trembling and echo artifacts of conventional static blending. We also propose a parallel algorithm of HDB running on GPUs, which significantly reduces the additional time overhead introduced by the naive HDB algorithm. Experimental results demonstrate that using a multi-band WaveRNN with HDB can effectively improve parallelism for real-time GPU vocoding while maintaining high speech quality comparable to non-folding inference.
Stress Intensity Factor Solutions for Eccentric Annular External Cracks in Notched Round Bars under Tensile Loading

In this paper, stress intensity factor (SIF) solutions of eccentric annular external cracks in elliptical notched round bars under tension loading have been obtained from 3D finite element analysis, along with their relation to the energy release rate obtained with the J-integral contour. The analysis variables have been the ligament diameter, its eccentricity, and the elliptical notch aspect ratio. The maximum SIF increases with the ligament eccentricity, the presence of the notch (compared to when the bar is smooth), and the elliptical notch axial semi-axis (for the same notch depth); it decreases with the ligament diameter. For external cracks, eccentricity induces bending of the bar subjected to tensile loading, which can produce partial and full contact of the crack surface, relevant phenomena in terms of the SIF value at the different points of the crack front.
Gastrointestinal Transit Times in Health as Determined Using Ingestible Capsule Systems: A Systematic Review

Background: Ingestible capsule (IC) systems can assess gastrointestinal (GI) transit times as a surrogate for gut motility for extended periods of time within a minimally invasive, radiation-free and ambulatory setting. Methods: A literature review of IC systems and a systematic review of studies utilizing IC systems to measure GI transit times in healthy volunteers was performed. Screening for eligible studies, data extraction and bias assessments was performed by two reviewers. A narrative synthesis of the results was performed. Results: The literature review identified 23 different IC systems. The systematic review found 6892 records, of which 22 studies were eligible. GI transit time data were available from a total of 1885 healthy volunteers. Overall, seventeen included studies reported gastric emptying time (GET) and small intestinal transit time (SITT). Colonic transit time (CTT) was reported in nine studies and whole gut transit time (WGTT) was reported in eleven studies. GI transit times in the included studies ranged between 0.4 and 15.3 h for GET, 3.3–7 h for SITT, 15.9–28.9 h for CTT and 23.0–37.4 h for WGTT. GI transit times, notably GET, were influenced by the study protocol. Conclusions: This review provides an up-to-date overview of IC systems and reference ranges for GI transit times. It also highlights the need to standardise protocols to differentiate between normal and pathological function.
Unraveling the Link Between Periodontal Disease and High Cholesterol: A Cross-Sectional Study

Objective: This cross-sectional study aimed to investigate the association between high cholesterol levels and the prevalence of periodontal disease among patients in the United States, utilizing data from the National Health and Nutrition Examination Survey (NHANES) conducted between 2017 and 2020. We hypothesize that patients with high cholesterol levels will have a high prevalence of periodontal disease. Methods: The study utilized a cross-sectional design, analyzing data from NHANES 2017-March 2020 pre-pandemic survey, a nationally representative survey. The sub-sample consisted of 7,042 participants aged 30 years and older who underwent the NHANES survey questionnaire. Information on high cholesterol levels and periodontal disease was obtained through self-reported data. Statistical analyses, using SAS 9.4 (SAS Institute Inc., Cary, NC), were performed to assess the association between high cholesterol levels and periodontal disease prevalence while controlling the potential confounding variables. Descriptive statistics and multivariable logistic regression were used. Results: The study included a total of 7,042 participants. The mean age (SD) of the participants was 60.2 (13.7); 54% were females and 46% were males. Out of the total, 23% (1636) of the samples had periodontal disease and 52% (3669) of the participants had high cholesterol levels. Findings indicated a significant association between high cholesterol and periodontal disease (odds ratio, OR = 1.21, 95% confidence interval, CI = 1.06-1.40). Socioeconomic factors such as poverty and education, and other factors such as age, gender, race, smoking, physical activity, BMI, diabetes, hypertension, sugar intake, cholesterol intake, saturated fatty acids intake, and oral hygiene were identified as potential confounders. Conclusion: This large-scale cross-sectional study investigated the association between high cholesterol and periodontal disease while comprehensively controlling for potential confounding factors. After adjusting for the relevant confounders, we found a weak positive association between high cholesterol and periodontal disease. While these findings provide valuable insights into the interplay between systemic health and oral health, the cross-sectional nature of the study limits the establishment of causality.
An Evaluation of Monopolar and Bipolar Electrocautery in Transurethral Resection of Urinary Bladder Tumors

Background: Transurethral resection of bladder tumor (TURBT) has a role in the diagnostic evaluation and treatment of bladder cancer, which is traditionally conducted through monopolar electrocautery; however, bipolar electrocautery has gained attention these days. Cautery artifacts are known as the drawbacks of TURBT and can be seen in both monopolar and bipolar electrocautery but with varying severity. Studies comparing bipolar to monopolar TURBT have shown conflicting results. Objectives: This study was carried out to compare the occurrence of cautery artifacts and a number of important clinical outcomes between patients undergoing monopolar and bipolar electrocautery during TURBT. Methods: This prospective study included adult patients with age 18 years old or higher diagnosed with primary bladder tumors with a size ≤4 cm. The patients were randomized into monopolar and bipolar groups (34 patients per group). The occurrence of cautery artifacts, duration of surgery, the incidence of urinary bladder perforation, fall in hemoglobin, need for blood transfusion, transurethral resection syndrome, and postoperative hospital stay between the two groups. Results: In our study, the incidence of cautery artifacts was significantly lower in the bipolar group than in the monopolar group (P-value < 0.0001). The two groups were comparable in terms of the duration of surgery, urinary bladder perforation, fall in hemoglobin, need for blood transfusion, transurethral resection syndrome, and postoperative hospital stay. Conclusions: Bipolar TURBT is superior to monopolar TURBT regarding a reduction in the incidence of cautery artifacts.
Introducing benchmarks for evaluating user-privacy vulnerability in WiFi

WiFi-based crowdsensing is a major source of data in a variety of domains such as human-mobility, pollution-level estimation, and, opportunistic networks. MAC randomisation is a backbone for preserving user-privacy in WiFi, as devices change their identifiers (MAC addresses). MAC association frameworks in the literature are able to associate randomized MAC addresses with a device. Such frameworks facilitate the continuation and validity of works based on device-based identifiers. In this paper, we first question and verify the reliability of these frameworks with respect to the datasets (scenarios) used for their validation. Indeed, we observe a substantial discrepancy between the performances obtained by these frameworks when confronting them with different contextual environments. We identify that the device heterogeneity in the input scenario is privacy-preserving. Henceforth, we propose a novel metric: randomization complexity, capable of successfully catching the degree of randomization in evaluated datasets. Existing and new frameworks can thus be benchmarked using this metric to ensure their reliability for any datasets with similar or lower randomization complexities. Finally, we open discussions on the potential impact of the benchmarks in the domain of MAC randomization.
Dual Antiplatelet Therapy or Antiplatelet Plus Anticoagulant Therapy in Patients with Peripheral and Chronic Coronary Artery Disease: An Updated Review

Despite evidence-based therapies, patients presenting with atherosclerosis involving more than one vascular bed, such as those with peripheral artery disease (PAD) and concomitant coronary artery disease (CAD), constitute a particularly vulnerable group characterized by enhanced residual long-term risk for major adverse cardiac events (MACE), as well as major adverse limb events (MALE). The latter are progressively emerging as a difficult outcome to target, being correlated with increased mortality. Antithrombotic therapy is the mainstay of secondary prevention in both patients with PAD or CAD; however, the optimal intensity of such therapy is still a topic of debate, particularly in the post-acute and long-term setting. Recent well-powered randomized clinical trials (RCTs) have provided data in favor of a more intense antithrombotic therapy, such as prolonged dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor or a therapy with aspirin combined with an anticoagulant drug. Both approaches increase bleeding and selection of patients is a key issue. The aim of this review is, therefore, to discuss and summarize the most up-to-date available evidence for different strategies of anti-thrombotic therapies in patients with chronic PAD and CAD, particularly focusing on studies enrolling patients with both types of atherosclerotic disease and comparing a higher- versus a lower-intensity antithrombotic strategy. The final objective is to identify the optimal tailored approach in this setting, to achieve the greatest cardiovascular benefit and improve precision medicine.
Socio-Demographic Factors and Public Knowledge of Antibiotic Resistance

(1) Background: Antibiotic resistance is a serious health issue, and raising public awareness of it is crucial to combating it. This study aimed to assess the socio-demographic factors associated with knowledge of antibiotics and antibiotic resistance in Malaysia. (2) Methods: A cross-sectional study was carried out between April 2022 and March 2023. Malaysian adults aged ≥18 years old and able to understand English or Malay were recruited. During data collection, the WHO questionnaire “Antibiotic Resistance, Multi-Country Public Awareness Survey” was used. Data were collected across 14 states in Malaysia. (3) Results: A total of 517 participants completed the questionnaire. Most participants were females (67.9%), aged 30–49 (46%), and from central Malaysia (69.8%). Most participants (98.5%) reported taking antibiotics. A misconception presented was that sore throats, fevers, colds, and flu can be treated with antibiotics. A total of 58.8% of participants had high knowledge of antibiotic usage (scores 12–15), while 64% had high knowledge of antibiotic resistance (scores 9–14). Findings indicate that increasing age, income, and education were associated with higher knowledge. (4) Conclusions: This study highlights the knowledge deficiency of antibiotic resistance among Malaysians. Educational programs should engage a younger and lower socio-economic population to increase awareness.
SUMO1 and Defective Spermatozoa Correlate with Endogenous Hydrogen Peroxide and Live Birth Outcome in Intrauterine Insemination Cycles for Unexplained Infertility

This study aimed to investigate the correlation between hydrogen peroxide (H2O2), small ubiquitin-like modifier molecules (SUMO), and pregnancy outcomes in couples with unexplained infertility (UI) undergoing intrauterine insemination (IUI) treatment. We prospectively collected semen samples from 56 couples with UI and divided the spermatozoa into motile and immotile fractions by density gradient centrifugation (DSC). Immunofluorescence staining was used to examine the immunostaining and localization of nuclear pore complex (NPC), SUMO1, and SUMO2/3 in spermatozoa. We detected H2O2 levels by chemiluminescence methods. We found that H2O2 levels correlated with NPC (neck) (r = 0.400) and NPC (tail) (r = 0.473) in motile sperm fractions. In immotile fractions, H2O2 positively correlated with NPC (tail) (r = 0.431) and SUMO1 (neck) (r = 0.282). Furthermore, the positive NPC (tail) group had a significantly lower live birth rate than the negative NPC group (17.9% = 5/28 vs. 42.9% = 12/28). In conclusion, H2O2 positively correlated with SUMO1 (neck) and NPC (tail) in human spermatozoa. The DSC may partially eliminate defective spermatozoa (positive NPC staining); however, if defective spermatozoa remain in the motile fraction, this scenario is associated with a low live birth rate following IUI treatment.