Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of Surgical Technique on Recurrence Rates After Inguinal Hernia Repair: a Retrospective Analysis

Inguinal hernia repair is a common surgical procedure to treat the condition of inguinal hernia, which is the escape of internal organ tissue through a gap or weakness in the lower abdominal wall. After undergoing surgery, the recurrence rate of inguinal hernia may vary. Therefore, it is important to conduct a retrospective analysis to understand the impact of surgical techniques on inguinal hernia recurrence rates. The aim of this study was to analyze the impact of surgical techniques on the recurrence rate of inguinal hernia. This study used a retrospective analysis method. Data were collected from questionnaires and medical records of patients who had undergone inguinal hernia repair surgery at X hospital. The data obtained included information about the surgical technique used, patient characteristics, such as age and gender, and the rate of recurrence of inguinal hernia that occurred after surgery. The collected data will be statistically analyzed using the IBM SPSS program. The results showed that surgical techniques with laparoscopic methods have a lower inguinal hernia recurrence rate than conventional methods. This can be seen from the results of the regression coefficient test with a recurrence rate of 28.7% compared to the conventional method of 32.6%.
Genetic and molecular analysis of starch physicochemical properties and its relationship with endosperm modification in quality protein maize

Quality protein maize (QPM) was created converting the soft opaque-2 endosperm into a vitreous phenotype, but the mechanisms involved in this modification are not completely understood. Recombinant inbred lines (RILs) derived from K0326Y QPM and W64Ao2 were used to identify quantitative trait loci (QTL) associated with starch physicochemical properties. RILs contrasting in vitreousness were also used to evaluate the expression of starch biosynthesis genes. Mapping identified 5-6 QTLs for each trait that explained 66 % of the phenotypic variation. Three QTLs on bins 4.05, 5.04, and 9.03 were found close to the starch biosynthesis genes Brittle-2 (Bt2), Amylose extender-1 (Ae1), and Waxy-1 (Wx1), respectively. The expression of Wx1 was three-fold greater in K0326Y QPM than W64Ao2 and eight-fold higher in vitreous than opaque RILs, which corresponded with the greater accumulation of granule bound starch synthase I (GBSSI) and the higher amylose content observed in the vitreous lines. The increased synthesis of amylose may result in starch granules with more amorphous regions that favor their compaction. These results suggest that endosperm modification in QPM is associated with the synthesis of starch containing more amylose during kernel development, which may facilitate the packing of the starch granules resulting in the vitreous phenotype.
Mapping of peanut crops in Queensland, Australia, using time-series PROBA-V 100-m normalized difference vegetation index imagery

Abstract. Mapping of peanut crops is essential in supporting peanut production, yield prediction, and commodity forecasting. While ground-based surveys can be used over small areas, the development of remote-sensing technologies could provide rapid and inexpensive crop area estimates with high accuracy over large regions. Some of these recent earth observation satellite systems, such as the Project for On-Board Autonomy Vegetation (PROBA-V), have the advantage of increased spatial and temporal resolution. With a study area located in the South Burnett region, Queensland, Australia, the primary aim of this study was to assess the ability of time-series PROBA-V 100-m normalized difference vegetation index (NDVI) for peanut crop mapping. Two datasets, i.e., PROBA-V NDVI time-series imagery and the corresponding phenological parameters generated from TIMESAT data analysis technique, were classified using maximum likelihood classification, spectral angle mapper, and minimum distance classification algorithms. The results show that among all methods used, the application of MLC in PROBA-V NDVI time series produced very good overall accuracy, i.e., 92.75%, with producer and user accuracy of each class ≥78.79 % . For all algorithms tested, the mapping of peanut cropping areas produced satisfactory classification results, i.e., 75.95% to 100%. Our study confirmed that the use of finer resolution 100 m of PROBA-V imagery (i.e., relative to MODIS 250-m data) has contributed to the success of mapping peanut and other crops in the study area.
Thermal considerations and architecture for Origins Space telescope (Conference Presentation)

This paper examines the architectural considerations for one of the designs being considered for the Origins Space Telescope (OST) a future far infra-red (~6-600 µm) space-based observatory. OST requires the temperature of the instruments and optics to operate at temperatures less than 4 Kelvin. Achieving these very low temperatures throughout the optical train in an executable and verifiable design is the defining architectural challenge for OST. This paper will discuss the main elements of OST’s thermal design, cooling, parasitics and thermal verification. This paper will include a discussion of how to modify the JWST for application in the far infra-red.
Aerodynamic optimization for low Reynolds number flight of a solar unmanned aerial vehicle

Aerodynamic Optimization for Low Reynoids Number Fiight of a Solar Unmanned Aerial Vehicle By Louis Dube Dr. Darrell Pepper, Examination Committee Chair Professor of Mechanical Engineering University of Nevada, Las Vegas A study has been conducted to optimize the aerodynamics of a solar powered unmanned aerial vehicle for low Reynolds number flight, in this study, three areas of the airframe, namely the fuselage, wing-fuselage junction and wingtips, were analyzed, tested, evaluated and developed in an iterative design process. A numérisai analysis method was employed to complete the aerodynamic study, the purpose of which was to minimize adverse flow conditions occurring near or about the aforementioned areas under most fiight conditions and to maximize their aerodynamic usefulness. The results were benchmarked internally through the iterative process using the initiai design as a control and externally by comparing with collected empirical figures characterizing solar airplanes of the past and present. The results showed that with carefui design practices, wingtip devices can be made to improve flight characteristics at low Reynolds number flight significantly enough to offset their structurai disadvantages, providing a substantial drag decrease over the entire flight envelope. It was also shown that fuselage shape can be modified to accommodate the airplane’s mission and fulfili a greater role than solely being a payload carrier by using this body to generate and control aerodynamic forces. Finally it was illustrated that careful design of the wing-fuselage junction could lead to significant improvements in both lift and drag characteristics.
Numerical simulation and convergence analysis for a system of nonlinear singularly perturbed differential equations arising in population dynamics

Abstract In this article, we consider a system of nonlinear singularly perturbed differential equations with two different parameters. To solve this system, we develop a weighted monotone hybrid scheme on a nonuniform mesh. The proposed scheme is a combination of the midpoint scheme and the upwind scheme involving the weight parameters. The weight parameters enable the method to switch automatically from the midpoint scheme to the upwind scheme as the nodal points start moving from the inner region to the outer region. The nonuniform mesh in particular the adaptive grid is constructed using the idea of equidistributing a positive monitor function involving the solution gradient. The method is shown to be second order convergent with respect to the small parameters. Numerical experiments are presented to show the robustness of the proposed scheme and indicate that the estimate is optimal.
Self-Alignment Capillary Gripper for Microfiber Manipulation

The assembly and arrangement of microfibers have wide applications in biomedicine, material science, and microsystem. However, current micromanipulation methods for positioning and orientating individual microfibers are complex and hard to use. In this article, we report a novel self-alignment capillary gripper for microfiber manipulation that is facile and convenient. We determine the key parameters of the gripper including the required meniscus volume and the tip aspect ratio of the gripper through both numerical simulation and experimental investigation. A two-stage self-alignment process is employed to achieve high precision. The gripper can pick up and self-align microfibers with an aspect ratio of up to 300:1 at an accuracy of <inline-formula><tex-math notation="LaTeX">$2.1 \pm 2.0\ \mu \mathrm{m}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$0.6 \pm 0.6 ^\circ$</tex-math></inline-formula> or better and create highly parallel linear arrays. The gripper is also versatile, where multiple types of microfibers including glass fibers, carbon fibers, dandelion seed fibers, and cat hairs can be picked up and self-aligned. Additionally, the gripper can construct two-dimensional patterns and plug a fiber into a microglass capillary.
ANALISIS KESUKSESAN SISTEM INFORMASI ONLINE LAYANAN ADMINISTRASI DI KEMENTERIAN DALAM NEGERI

Penelitian ini fokus pada kesuksesan penerapan e-government melalui Sistem Informasi Online Layanan Administrasi (SIOLA) di Kementerian Dalam Negeri (Kemendagri). Tujuan dari keberadaan aplikasi ini adalah untuk meningkatkan kualitas pelayanan dan menciptakan pelayanan yang efektif, efisien, cepat, mudah, serta semua pelayanan dapat diproses secara online tanpa ada lagi pelayanan secara manual. Pada penerapannya aplikasi ini masih mengalami beberapa kendala yaitu seperti masih ditemui pelayanan yang belum sepenuhnya dilakukan secara online dan ada beberapa layanan yang tidak aktif digunakan. Dengan menggunakan pendekatan post positivism, peneliti melakukan penilaian terhadap kesuksesan penerapan sistem informasi pelayanan administrasi untuk mengetahui sejauh mana peran sistem informasi ini dalam menunjang proses pelayanan di Kemendagri. Menggunakan Teknik pengumpulan data melalui wawancara dan studi dokumentasi serta studi literatur dengan menggunakan teori IS Success Model oleh DeLone dan McLean (2003) yang terdiri dari 6 (enam) variabel yaitu system quality, information quality, service quality, intention to use/use, user satisfaction , dan net benefit, peneliti mendapatkan data sebagai dasar penilaian kesuksesan penerapan e-government melalui aplikasi SIOLA. Hasil penelitian menunjukan bahwa tingkat kesuksesan penerapan e-government melalui aplikasi SIOLA di Kemendagri sudah berjalan dengan baik tetapi belum optimal, karena masih ada indikator pada variabel yang digunakan untuk mengukur tingkat kesuksesan sistem informasi yang belum terpenuhi.
Application of Wavelet Neural Network in Forward Kinematics Solution of 6-RSU Co-axial Parallel Mechanism Based on Final Prediction Error

Application of artificial neural network (ANN) in forward kinematic solution (FKS) of a novel co-axial parallel mechanism with six degrees of freedom (6-DOF) is addressed in Current work. The mechanism is known as six revolute-spherical-universal (RSU) and constructed by 6-RSU co-axial kinematic chains in parallel form. First, applying geometrical analysis and vectorial principles the kinematic model is extracted and inverse kinematics solution is done. Due to highly nonlinear characteristic of the model, forward kinematic solution for 6-RSU is so complicated. Therefore, ANN based on wavelet analysis, as a powerful solution, is designed and applied to solve FK problem. The minimum prediction risk principle with using final prediction error (FPE) is applied to find the best and optimum topology of our proposed neural network (WNN) in this paper. Furthermore, proposed wavelet WNN is developed to approximate the specific reference trajectories for manipulated platform of mechanism and the results are obtained. Comparing the extracted results by WNN with closed form solution (CFS) demonstrates the accuracy and efficiency of the proposed WNN.
Hierarchical Refined Composite Multi-Scale Fractal Dimension and Its Application in Feature Extraction of Ship-Radiated Noise

The fractal dimension (FD) is a classical nonlinear dynamic index that can effectively reflect the dynamic transformation of a signal. However, FD can only reflect signal information of a single scale in the whole frequency band. To solve this problem, we combine refined composite multi-scale processing with FD and propose the refined composite multi-scale FD (RCMFD), which can reflect the information of signals at a multi-scale. Furthermore, hierarchical RCMFD (HRCMFD) is proposed by introducing hierarchical analysis, which successfully represents the multi-scale information of signals in each sub-frequency band. Moreover, two ship-radiated noise (SRN) multi-feature extraction methods based on RCMFD and HRCMFD are proposed. The simulation results indicate that RCMFD and HRCMFD can effectively discriminate different simulated signals. The experimental results show that the proposed two-feature extraction methods are more effective for distinguishing six types of SRN than other feature-extraction methods. The HRCMFD-based multi-feature extraction method has the best performance, and the recognition rate reaches 99.7% under the combination of five features.
Where drivers are looking at during takeover: Implications for safe takeovers during conditionally automated driving

Abstract Objective Safety has become one of the primary concerns of level 3 automated driving, especially during the takeover process. Since most studies have focused on impacts of various factors on takeover performance of drivers, there seems to be a gap between the causes of crashes and the desired means to mitigate their occurrence and consequences. Hence, the main objective of this study is to extract from crash data during takeovers drivers’ patterns of gaze behaviors and maneuvers and then utilize them to extract some guidance on human-machine-interface design to enhance safety and acceptability of automated driving. Methods A study involving 27 subjects was conducted on a high-fidelity driving simulator with a Steward motion platform of six degrees of freedom. Each subject participated in 6 takeover scenarios with a lead time of 5 s and different duration of monitoring (DoM), with their maneuvers recorded by the system and eye gazes recorded by the Smart Eye Pro and Smart Recorder. Crash data collected during the takeover process were then utilized for the analysis. Results From 132 valid takeovers collected from 23 out of the 27 participants, 15 crashes were recorded. Based on which, five typical patterns of unsafe behaviors were recognized that may have caused the crashes, denoted as Type I to Type V, respectively. Besides, it appears that even if drivers were given more time to observe the surroundings, i.e., longer DoM, the number of crashes has not decreased as anticipated. Therefore, what is more important seems to be drivers’ gaze behaviors and maneuvers shortly after TOR. Conclusions For takeovers to be safe, good cooperations between drivers’ gaze behaviors and maneuvers are essential. Overall, it seems that in emergent situations that require takeovers, some drivers have difficulty in allocating attentions reasonably, which appears to have less to do with the time left for drivers to observe the surroundings. While designing HMIs, we may as well consider providing enough information to guide drivers according to drivers’ states and maneuvers at the time to improve safety of takeovers in emergent situations, and more importantly, to provide the information timely and effectively.
A Channel Loss Model for THz Networks From 100–600 GHz Considering Both Molecular and Water Vapor Continuum Absorptions

6G networks are expected to use the terahertz (THz) frequency spectrum in some way. However, relatively little is known about the transmission channel in this part of the spectrum. In this article, we propose a novel and accurate channel loss model that considers both molecular and water vapor continuum absorptions for THz networks based on the frequency range between 100 GHz and 600 GHz. The proposed channel model assumes that the atmospheric absorption is accurately accounted for by the molecular absorption coefficient and the water vapor continuum absorption coefficient. The new model is based on equations developed to accurately match the channel response given by a spectroscopic database. This makes the channel model robust and useful for evaluating the performance of THz networks. The model is validated against a spectroscopic database defined as a benchmark. The performance of the new channel loss model is evaluated against different models, including several error metrics. Numerical results show the new channel model is as accurate as the spectroscopic database by correctly reproducing the provided experimental dataset. Therefore, the proposed channel model is a reliable, robust and simple tool that can be successfully used to carry out performance evaluation of THz networks with accuracy.
A Study of Photoneutron Reactions Using Statistical Analysis

The well-known inputs for determining the reaction cross section are nuclear level density (NLD) and -ray strength functions. In this work, effects of -ray strength functions and NLD models on photoneutron reactions of 76,77,78Se isotopes are analyzed by using the latest version of TALYS computer code. For -ray strength functions, macroscopic and microscopic options which are available in the TALYS, are used in the calculations. Kopecky-Uhl and Brink Axel -ray strength function models as macroscopic options, Hartree-Fock BCS tables, Hartree-Fock Bogolyubov tables and Goriely’s hybrid model as microscopic options are preferred. The statistical analysis is carried out to determine the -ray strength function that reproduces the experimental data quite well. And then, calculations of photoneutron cross section are redone by using the determined -ray strength function via the NLD models. The Constant Temperature Model (CTM), Back Shifted Fermi Gas Model (BSFGM) and Generalized Superfluid Model (GSM) are preferred to use in NLD calculations. The predictions are compared with each other and the available experimental data. EXFOR library is used to take all experimental data.
A Novel Taxonomy for Arabic Fake News Datasets

: The proliferation of fake information on digital and social media platforms have become a surging concern for society. With the growing reliance on the internet as a source of information, it has become increasingly crucial to detect and mitigate the spread of fake news. To address this challenge, the field of Natural Language Processing and Machine Learning has directed considerable e ff orts toward the development of e ff ective Fake News Identification (FNI) methods. However, the lack of comprehensive and balanced datasets for fake news (FN) detection in a low-resourced language such as the Arabic language remains a major obstacle in this field. To bridge this gap, this research proposes an e ff ective taxonomy for Arabic FN datasets. The taxonomy provides insight of the characteristics and specifications of Arabic FN. The taxonomy is based on an extensive analysis of existing Arabic datasets and relevant literature in the field. This taxonomy can provide a useful framework for the building, categorization, and comparison of FN in the Arabic language and o ff er a clear understanding of the di ff erent types of fake news and how they can be di ff erentiated. Furthermore, this taxonomy provides solid ground for the development of high-quality and balanced Arabic datasets that can e ff ectively facilitate the development of FNI models in the Arabic language. In conclusion, this research paper o ff ers a valuable contribution to the field of FNI by proposing an e ff ective taxonomy for Arabic fake news datasets and support for building comprehensive and balanced datasets in the Arabic language.
High capacity passive optical network monitoring scheme using self-seeding Fabry–Pérot laser diode with direct modulation

Abstract. We propose and experimentally demonstrate a high capacity optical monitoring scheme using a self-seeding Fabry–Pérot laser diode (FP-LD) with direct modulation in a passive optical network (PON). A simple, stable, and low-cost monitoring source with side mode suppression ratio of 47 dB that consists of a FP-LD, a polarization controller, and a fiber Bragg grating is presented. The detecting signals can be encoded in two-dimension, i.e., pulse widths and wavelengths, which is very suitable for high capacity PON monitoring. The final recognition process is very simple because only the rectangular pulse width needs to be identified, especially compared with the complicated network recognition algorithm.
Recent Advances and Challenges in Textile Electrodes for Wearable Biopotential Signal Monitoring: A Comprehensive Review

The technology of wearable medical equipment has advanced to the point where it is now possible to monitor the electrocardiogram and electromyogram comfortably at home. The transition from wet Ag/AgCl electrodes to various types of gel-free dry electrodes has made it possible to continuously and accurately monitor the biopotential signals. Fabrics or textiles, which were once meant to protect the human body, have undergone significant development and are now employed as intelligent textile materials for healthcare monitoring. The conductive textile electrodes provide the benefit of being breathable and comfortable. In recent years, there has been a significant advancement in the fabrication of wearable conductive textile electrodes for monitoring biopotential signals. This review paper provides a comprehensive overview of the advances in wearable conductive textile electrodes for biopotential signal monitoring. The paper covers various aspects of the technology, including the electrode design, various manufacturing techniques utilised to fabricate wearable smart fabrics, and performance characteristics. The advantages and limitations of various types of textile electrodes are discussed, and key challenges and future research directions are identified. This will allow them to be used to their fullest potential for signal gathering during physical activities such as running, swimming, and other exercises while being linked into wireless portable health monitoring systems.