Miracle-dz/UniFAR-FTUs huggingface dataset:
The Association between the Oral-Gut Axis and the Outcomes of Severe COVID-19 Patients Receiving Extracorporeal Membrane Oxygenation: A Case-Control Study

The novel conceptual disease model, the oral–gut axis, which represents the immunomodulatory mutual relationship between oral and gut microbial compartments, has been attracting attention in relation to systemic health issues. We investigated whether this unique crosstalk influences the systemic condition of patients with COVID-19 infections who received extracorporeal membrane oxygenation (ECMO) in the intensive care unit (ICU) during April and December 2020. In this case-control study, patients were divided into two groups according to their survival (total entry size, n = 21; survivors, n = 13; non-survivors, n = 8). Patients were evaluated using the oral assessment guide from Fukuoka University (OAG-F) and the Bristol Stool Form Scale (BSFS) to examine the oral and fecal conditions. A blood-based inflammatory factor, the neutrophil-to-lymphocyte ratio (NLR), was used as an indicator of systemic immunity. The high total OAG-F scores were associated with both elevated BSFS and NLR values, and a mutually positive correlation between BSFS and NLR was observed. This indicated an interplay between oral deterioration, gut dysbiosis, and the impairment of immunity. Furthermore, oral deterioration was more frequently observed in non-survivors on day 14 of ICU admission. In addition, on days 7 and 21 of ICU admission, impaired immunity, reflected by an elevated NLR, was observed in non-survivors. However, the distribution of the gut microbiome—reflected by increased BSFS values—with the time it was examined was not directly observed in non-survivors. Taken together, these findings suggested that oral–gut health may be specifically associated with mortality in COVID-19 patients receiving ECMO in the ICU.
Generating Concise Patches for Newly Released Programming Assignments

In programming courses, providing students with concise and constructive feedback on faulty submissions (programs) is highly desirable. However, providing feedback manually is often time-consuming and tedious. To release tutors from the manual construction of concise feedback, researchers have proposed approaches such as CLARA and Refactory to construct feedback automatically. The key to such approaches is to fix a faulty program by making it equivalent to one of its correct reference programs whose overall structure is identical to that of the faulty submission. However, for a newly released assignment, it is likely that there are no correct reference programs at all, let alone correct reference programs sharing identical structure with the faulty submission. Therefore, in this paper, we propose AssignmentMender generating concise patches for newly released assignments. The key insight of AssignmentMender is that a faulty submission can be repaired by reusing fine-grained code snippets from submissions (even when they are faulty) for the same assignment. It automatically locates suspicious code in the faulty program and leverages static analysis to retrieve reference code from existing submissions with a graph-based matching algorithm. Finally, it generates candidate patches by modifying the suspicious code based on the reference code. Different from existing approaches, AssignmentMender exploits faulty submissions in addition to bug-free submissions to generate patches. Another advantage of AssignmentMender is that it can leverage submissions whose overall structures are different from those of the to-be-fixed submission. Evaluation results on 128 faulty submissions from 10 assignments show that AssignmentMender improves the state-of-the-art in feedback generation for newly released assignments. A case study involving 40 students and 80 submissions further provides initial evidence showing that the proposed approach is useful in practice.
Improved Modulation Strategy for Reactive Energy Transmission Loss of Auxiliary Commutated Circuit of Novel Parallel RDCL Inverter

To overcome the challenges of large reactive energy transmission loss and high current stress, which ocurr during the operation of auxiliary commutated circuit (ACC) of novel parallel resonant dc-link inverter (PRDCLI), an improved modulation strategy for reactive energy transmission loss is herein proposed based on the discontinuous pulsewidth modulation (DPWM), which adopts sawtooth carrier wave with alternating positive and negative slopes and shunt dead zone. Compared with the original modulation strategy, based on minimizing the ACC operation frequency, the proposed modulation strategy is able to realize all switches soft-switching, and avoid the superposition of resonant current and load current during the operation of ACC, thus, effectively reducing the reactive energy transmission loss and the current stress of auxiliary switches of the ACC. Under the proposed modulation strategy, the equivalent circuits in different operation modes are divided, and the operation principle, voltage/current stress, loss distribution, and optimal parameter design method of novel PRDCLI are researched. Eventually, the proposed modulation strategy is verified by experiments on a 5-kW/40-kHz prototype made by SiC mosfet.
Impact of Socio–Economic, Health and Patient Related Factors on Medication Adherence in Patients with Hypertension and Type II Diabetes

Background: Adherence to therapies is a primary determinant for treatment success in chronic diseases. Despite increased awareness, poor adherence to treatments for chronic diseases still remains a global problem. Failure to adherence, seriously affects the patient and the health care system. Aim: The main purpose of this study was to evaluate the level of drug adherence in patients with hypertension and type II diabetes. A prospective cross sectional study was carried out in tertiary care hospitals of Khammam region, Telangana with a size of 2880 patients. A structured questionnaire has been designed using MMAS 8 scale to determine the compliance level and the socioeconomic status of the objects was analyzed by Kuppuswamy scale. Results: In our study, the following results were reported, age (P <0.001), gender (P <0.001, OR = 1.954), residence (P <0.0001, OR = 3.102), level of education (P <0.0001), profession (p <0.0001), net monthly income (P <0.001), socio economic class (P <0.001), medication Costs (P <0.001 OR = 0.2346), Health Literacy (P <0.001, OR =0.2051), Social support (P <0.001, OR =3.549, 95% CI=2.701 to 4.649). Frequency of Visits (P <0.001, OR =0.09421), No of medications (P <0.001, OR =0.2506), Complexity (P <0.001, OR =0.1862), Self-Monitoring (P <0.001, OR = 0.1011), felt worse (p<0.0001,OR=0.1591). Conclusion: Our results showed that demographic variables, socio economic factors, health care factors had direct influence on medication adherence. Illiterates, lower-economy patients have not followed the recommendations of health care providers who insist on the need to increase drug adherence in primary care. Our findings call for the need to design new interventions on multidimensional factors likely to interfere with this study, such as patient knowledge and information to improve compliance.
Prädiktive biomechanische Simulation am Beispiel von ergonomischer Produktoptimierung in Burkina Faso/Predictive biomechanical simulation based on the example of ergonomic product optimization in Burkina Faso

Inhalt: In der Produktentwicklung gewinnen nutzerzentrierte Designprozesse zunehmend an Bedeutung. Muskuloskelettale Simulationstools ermöglichen die Abbildung und Simulation des menschlichen Bewegungsapparats während der Nutzer-Produkt-Interaktion auf Basis experimentell erhobener Bewegungsdaten. Durch prädiktive Methoden der Bewegungserzeugung soll der Aufwand der experimentellen Bewegungserfassung reduziert und eine proaktive sowie virtuelle Analyse von Produktergonomie und Gebrauchstauglichkeit ermöglicht werden. Dieser Beitrag präsentiert eine solche prädiktive Methode zur Abbildung der Nutzer-Produkt-Interaktion. Diese wurde für die Designoptimierung eines Trikes für Menschen mit Behinderungen in Burkina Faso entwickelt.
Teledermatology versus Face-to-Face Dermatology: An Analysis of Cost-Effectiveness from Eight Studies from Europe and the United States

(1) Background: The aim of this systematic review was to compare the cost-effectiveness of two follow-up methods (face-to-face and telemedicine) used in dermatology in the last ten years. (2) Methods: A search for articles that included economic analyses was conducted in August 2021 in the databases PubMed, Medline, Scielo and Scopus using the following keywords: “Cost–Benefit Analysis”, “Dermatology”, “Telemedicine”, “Primary Health Care”, as well as other search terms and following the PICOS eligibility criteria. (3) Results: Three clinical trials and five observational studies were analyzed, providing information for approximately 16,539 patients (including four cost-minimization or saving analyses, three cost-effectiveness analyses, and one cost–utility analysis) in Europe and the United States. They describe the follow-up procedures in each of the cases and measure and analyze the direct and indirect costs and effectiveness. All the articles indicate that teledermatology lowers costs and proves satisfactory to both patients and professionals. (4) Conclusions: Although it has been found that follow-up via teledermatology can be more efficient than traditional hospital follow-up, more work is needed to establish evaluation protocols and procedures that measure key variables more equally and demonstrate the quality of the evidence of said studies.
Exploring the Relationships between Four New Species of Boletoid Fungi from Northern China and Their Related Species

The family Boletaceae primarily represents ectomycorrhizal fungi, which play an essential ecological role in forest ecosystems. Although the Boletaceae family has been subject to a relatively global and comprehensive history of work, novel species and genera are continually described. During this investigation in northern China, many specimens of boletoid fungi were collected. Based on the study of their morphology and phylogeny, four new species, Butyriboletus pseudoroseoflavus, Butyriboletus subregius, Tengioboletus subglutinosus, and Suillellus lacrymibasidiatus, are introduced. Morphological evidence and phylogenetic analyses of the single or combined dataset (ITS or 28S, rpb1, rpb2, and tef1) confirmed these to be four new species. The evidence and analyses indicated the new species’ relationships with other species within their genera. Detailed descriptions, color photographs, and line drawings are provided. The species of Butyriboletus in China were compared in detail and the worldwide keys of Tengioboletus and Suillellus were given.
Design of Brushless DC Motor Control System Based on Variable Universe Fuzzy Adaptive PID

In order to improve the timing performance of brushless DC motor(BLDCM in brief),and in view of the shortages of the normal fuzzy controller,the paper investigates variable universe fuzzy adaptive PID(VU-Fuzzy PID in brief) controller used in BLDCM control system.Based on Matlab,the model of BLDCM is built up and the simulation system of BLDCM with double loop controller was established.The speed loop was controlled by the VU-Fuzzy PID controller and the current loop was controlled by the common PID controller.The simulation results show that,for the control system with the VU-Fuzzy PID,it is not overshooting and has a faster dynamic response and higher precision as well as more adaptive performance than the normal Fuzzy PID or common PID.
A New Class of PSMA-617-Based Hybrid Molecules for Preoperative Imaging and Intraoperative Fluorescence Navigation of Prostate Cancer

The development of PSMA-targeting low-molecular-weight hybrid molecules aims at advancing preoperative imaging and accurate intraoperative fluorescence guidance for improved diagnosis and therapy of prostate cancer. In hybrid probe design, the major challenge is the introduction of a bulky dye to peptidomimetic core structures without affecting tumor-targeting properties and pharmacokinetic profiles. This study developed a novel class of PSMA-targeting hybrid molecules based on the clinically established theranostic agent PSMA-617. The fluorescent dye-bearing candidates of the strategically designed molecule library were evaluated in in vitro assays based on their PSMA-binding affinity and internalization properties to identify the most favorable hybrid molecule composition for the installation of a bulky dye. The library’s best candidate was realized with IRDye800CW providing the lead compound. Glu-urea-Lys-2-Nal-Chx-Lys(IRDye800CW)-DOTA (PSMA-927) was investigated in an in vivo proof-of-concept study, with compelling performance in organ distribution studies, PET/MRI and optical imaging, and with a strong PSMA-specific tumor uptake comparable to that of PSMA-617. This study provides valuable insights about the design of PSMA-targeting low-molecular-weight hybrid molecules, which enable further advances in the field of peptidomimetic hybrid molecule development.
A quantitative analysis of student’s satisfaction: A study of Girne American University, North Cyprus

Student satisfaction surveys are a common method for analyzing the general level of satisfaction of the students in schools. The goal of this study is to scale the level of students’ satisfaction by services provided by Girne American University located in North Cyprus region, mainly focused on the education quality along with other services provided by the university. A quantitative research was conducted to measure the students’ satisfaction. A questionnaire sample was distributed to more than 50 students. However, only 50 usable sample were used in the study. The analysis is made over the four main aspects stated above. Students' opinions about services provided by the university were somewhat convergent. Results showed that students are greatly satisfied with quality level of education and not satisfied with the general services provided by Girne American University. The University may use the surveys’ outcome to work on enhancing services that didn’t meet students’ expectations. Keywords: student satisfaction; university services; quality education; Quantitative Analysis.
Automated Extraction of Ground Fissures Due to Coal Mining Subsidence Based on UAV Photogrammetry

Widespread ground fissures caused by coal mining subsidence are a main cause of ecological destruction in coal mining areas, and the rapid monitoring of ground fissures is essential for ecological restoration. Traditional fissure monitoring technologies are time consuming and laborious. Therefore, we developed a method to automatically extract ground fissures from high-resolution UAV images. First, a multiscale Hessian-based enhancement filter was utilized to enhance the ground fissures in grayscale images. Then, a simple single-thresholding operation was applied to segment the enhanced image to generate a binary ground fissure map. Finally, incomplete path opening was performed to eliminate the noises in the fissure extraction results. We selected the N1212 working face of the Ningtiaota Coal Mine in Shenmu County, China, as the study area. The results indicated that the ranges of correctness, completeness, and the kappa coefficient of the extracted results were 66.23–79.00%, 69.03–73.22%, and 67.91–75.88%, respectively. Image resolution is the key factor for successful fissure detection; the method proposed in this paper can extract ground fissures with a width greater than one pixel (2.64 cm), and the detection ratio for fissures with a width greater than two pixels was over 87%. Our research has solved the problem of the rapid monitoring of ground fissures to a certain extent and can act as a valuable tool for ecological restoration in mining areas.
A 2.5–32 Gb/s Gen 5-PCIe Receiver With Multi-Rate CDR Engine and Hybrid DFE

This brief presents a 2.5 – 32 Gb/s Gen 5-PCIe receiver with a multi-rate clock and data recovery (CDR) engine and a hybrid decision feedback equalizer (DFE). The receiver for the PCIe requires wide-range operation and compensation for high insertion loss. The proposed multi-rate CDR engine enables the receiver to operate with multi-rate clocking schemes according to the data rates, which does not need any additional high-speed analog circuits normally used for wide-range operation. In addition, the hybrid DFE architecture not only meets the DFE feedback timing constraint and but also reduces the equalization power. By using clock gating, the receiver can save power when operating at lower generations such as Gen 1, 2, 3, and 4. The prototype chip is fabricated in a 40-nm CMOS technology and occupies an active area of 0.14 mm2. The receiver achieves BER less than 10−12 with various PCIe channels, satisfying PCIe jitter tolerance masks. It consumes 62.7 mW at 32 Gb/s, compensating for 27.5-dB inserting loss, and the figure of merit (energy efficiency per channel loss at Nyquist frequency) of 0.07 pJ/b/dB is achieved.
SYSTEMATIC DISINFORMATION: THE SPREAD OF MISLEADING INFORMATION AS A COLLECTIVE DYNAMIC ON TWITTER

Disinformation is a worldwide problem and has been a key scholarship in the last few years. This paper contributes to the ongoing discussion on how disinformation spread on social media. This study uses a mixed-methods approach (Social Network Analysis, Connected Concept Analysis and Content Analysis) to analyze four political discussions on Twitter. The results show a structure of asymmetric polarization, in which one group (that supported Bolsonaro in the 2018 Brazilian elections) is strongly associated with disinformation spread. In addition, this study identifies a collective dynamic in disinformation spread as the volume of disinformation floats similarly for different levels of users depending on the context of the discussion analyzed. Based on these results, the idea of “systematic disinformation” is discussed.
LbSP: Load-Balanced Secure and Private Autonomous Electric Vehicle Charging Framework With Online Price Optimization

Nowadays, autonomous electric vehicles (AEVs) are increasingly popular due to low resource consumption, low pollutant emission, and high efficiency. In practice, Vehicle-to-Grid (V2G) networks supply energy power to EVs to ensure the usage of EVs. However, there are still certain security and privacy concerns in V2G connections, such as identity impersonation and message manipulation. Additionally, the widespread usage of EVs brings significant pressure on the power grid, leading to undesirable effects like voltage deviations if EVs’ charging is not well coordinated. In this article, to tackle these issues, we design a novel load-balanced secure and private EV charging framework named load-balanced secure and private framework (LbSP) for secure, private, and efficient EV charging with a minimal negative effect on the existing power grid. It assures reliable and efficient charging services by a lightweighted encryption technique. Also, it balances the energy consumption of power grids via an online pricing strategy that minimizes load variance by optimizing energy prices in real time. Moreover, it preserves users’ privacy while not affecting online pricing using an advanced differential privacy technique. Furthermore, LbSP deploys on an edge-cloud structure for fast response and more precise pricing, where clouds balance overall load consumption by online price optimization while edges gather data for clouds and respond to charging requests from EVs. The evaluation results show that the proposed framework ensures secure and private EV charging, balances energy load consumption, and preserves users’ privacy.
Planar Pattern Manipulation Surfaces Using Dual-Polarized Pin-Loaded Patch Resonating Elements

This article proposes a novel design concept to realize planar pattern manipulation surfaces (PPMSs) using dual-polarized pin-loaded patch resonating elements. First, the resonant frequency and reflection coefficient of the pin-loaded patch element are investigated through its equivalent circuit model. By changing the positions of shorting pins, the reflection phase of such a patch element can be appropriately adjusted while maintaining the reflection magnitude unchanged. Additionally, varying the positions of shorting pins possesses a significant property of polarization independence. Then, the dual-polarized pin-loaded patch element is employed to design the proposed PPMS. In this way, the incident wave is manipulated for different reflection angles with the dual-polarization response by adjusting the position distributions of shorting pins in two orthogonal polarization directions. To prove our presented design concept, two prototypes with reflection angles of (<inline-formula> <tex-math notation="LaTeX">$\theta ^{r} = 45^{\circ }$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\phi ^{r} = 0^{\circ }$ </tex-math></inline-formula>) and (<inline-formula> <tex-math notation="LaTeX">$\theta ^{r} = 45^{\circ }$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$\phi ^{r} = 45^{\circ }$ </tex-math></inline-formula>) are finally implemented, fabricated, and measured. Measurements and calculations agree well with each other, which indicates that the reflection angle is experimentally obtained as predicted in theory. Thus, the proposed PPMS can be apparently viewed as a promising candidate to efficiently customize the radio environment in future wireless networks.
Application of machine learning tools: Potential and useful approach for the prediction of type 2 diabetes mellitus based on the gut microbiome profile

The gut microbiota plays an important role in the regulation of the immune system and the metabolism of the host. The aim of the present study was to characterize the gut microbiota of patients with type 2 diabetes mellitus (T2DM). A total of 118 participants with newly diagnosed T2DM and 89 control subjects were recruited in the present study; six clinical parameters were collected and the quantity of 10 different types of bacteria was assessed in the fecal samples using quantitative PCR. Taking into consideration the six clinical variables and the quantity of the 10 different bacteria, 3 predictive models were established in the training set and test set, and evaluated using a confusion matrix, area under the receiver operating characteristic curve (AUC) values, sensitivity (recall), specificity, accuracy, positive predictive value and negative predictive value (npv). The abundance of Bacteroides, Eubacterium rectale and Roseburia inulinivorans was significantly lower in the T2DM group compared with the control group. However, the abundance of Enterococcus was significantly higher in the T2DM group compared with the control group. In addition, Faecalibacterium prausnitzii, Enterococcus and Roseburia inulinivorans were significantly associated with sex status while Bacteroides, Bifidobacterium, Enterococcus and Roseburia inulinivorans were significantly associated with older age. In the training set, among the three models, support vector machine (SVM) and XGboost models obtained AUC values of 0.72 and 0.70, respectively. In the test set, only SVM obtained an AUC value of 0.77, and the precision and specificity were both above 0.77, whereas the accuracy, recall and npv were above 0.60. Furthermore, Bifidobacterium, age and Roseburia inulinivorans played pivotal roles in the model. In conclusion, the SVM model exhibited the highest overall predictive power, thus the combined use of machine learning tools with gut microbiome profiling may be a promising approach for improving early prediction of T2DM in the near feature.