Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and Transmission of Soil Transmitted Helminths among Farmers Living Along the Metropolitan Section of River Kaduna, Nigeria

Soil-transmitted helminths (STHs) are one of the world’s most important causes of physical and intellectual growth retardation. The study was conducted to determine the prevalence and transmission of soil-transmitted helminths among farmers living along the metropolitan section of river Kaduna, Nigeria. Two billion people are infected globally and four billion at risk of infection to STH. Nigeria ranking first globally, accounts for about 156 million cases of STH. A total of 210 stool samples were randomly collected from farmers of seven (7) different farms located along the riverbank. The stool samples collected were examined for STHs using direct wet mount and formal ether sedimentation techniques. Questionnaires were administered to the farmers to assess their hygiene, sanitation, and health maintenance. The prevalence of STH based on the farmers' age and gender was also determined. Out of the total stool samples collected, 81(38.6%) were infected with at least one out of the four STH eggs. The eggs of hookworm and Ascaris lumbricoides were the only helminths eggs detected. Hookworm was found to have a prevalence of 54.3% while A. lumbricoides have a prevalence of 45.7%. Strongyloides stercoralis and Trichuris tichuira both were found to have 0% prevalence. The risk factors such as personal hygiene, sanitation and health maintenance were found to have a significant influence on the prevalence (38.6%) (P<0.05) of STH among the farmers. The age prevalence shows that group 10 – 25 have the highest prevalence of 81.3% while age 36 – 45 shows the lowest prevalence of 2.4%. The gender prevalence shows that male farmers have the highest prevalence of 41.4% out of the total infected farmers (81). The findings could be as a result of farmers’ hygiene, sanitation and health maintenance on their various farms and their use of contaminated farm tools which acts as a medium for the transmission of the parasite eggs, while the younger age group work more hours than the older age group and the male farmer spends more time in the farm than the female.
MODELING AND CONTROL OF SPLIT CAPACITOR TYPE ELEMENTARY ADDITIONAL SERIES POSITIVE OUTPUT SUPER LIFT CONVERTER

Super lift converter is a new series of DC/DC converter possessing high voltage transfer gain, high efficiency, reduced ripple voltage and current. Super lift technique armed by split capacitors increases the output voltage in higher geometric progression. This paper focuses on splitting the input side capacitor of the additional series positive output super lift converter in order to obtain a high voltage transfer gain. The proposed super lift converter is modeled using state space averaging technique. A suitable PI controller has been designed to regulate the converter against audio susceptibility and output impedance variation. Simulation study of the proposed converter along with the controller has been carried out in MATLAB/SIMULINK to investigate the static and dynamic response of the converter.
External Loading at the Knee Joint for Landing Movements in Alpine Skiing

The purpose of this study was to determine resultant knee joint forces and moments during a specific movement in Alpine ski racers. The movement analyzed consisted of a landing from a bump and the initiation of recovery (if necessary). Resultant loads were obtained using an inverse dynamics approach. Results of two specific skiers are contrasted, one skier landing in good form, the second skier landing in poor form. The skier landing in poor form exhibited larger knee flexion, and larger knee joint resultant forces and moments than the skier landing in good form. The movement of the skier landing in poor form has been associated with isolated anterior cruciate ligament (ACL) injury. However, the data obtained in this study do not indicate that either skier was in danger of ACL injury.
Impact of the vertical SOI 'DELTA' structure on planar device technology

A fully depleted lean channel transistor (DELTA) with its gate incorporated into a new vertical ultrathin silicon-on-insulator (SOI) structure is presented. In the deep-submicrometer region, selective oxidation produces and isolates an ultrathin SOI MOSFET that has high crystalline quality, as good as that of conventional bulk single-crystal devices. Experiments and three-dimensional simulations have shown that this new gate structure has effective channel control and that the vertical ultrathin SOI structure provides superior device characteristics: reduction in short-channel effects, minimized subthreshold swing, and high transconductance. >
Health economic modelling of diabetic kidney disease in patients with type 2 diabetes treated with Canagliflozin in Belgium

ABSTRACT Objectives The Canagliflozin and Renal Events in Diabetes with Established Nephropathy Clinical Evaluation (CREDENCE) trial showed reduced renal and cardiovascular (CV) events in patients with type 2 diabetes (T2D) and diabetic kidney disease (DKD) treated with canagliflozin 100 mg added to Standard of Care (SoC) versus SoC alone. This led to an extension of the canagliflozin 100 mg European marketing authorisation, making canagliflozin the first pharmacological therapy to receive authorisation for the treatment of DKD since the RENAAL and IDNT trials more than 20 years ago. Given the importance of cost-effectiveness analyses in health care, this study aimed to leverage the CREDENCE trial outcomes to estimate the cost-effectiveness of canagliflozin 100 mg from the perspective of the Belgian healthcare system. Methods A microsimulation model (CREDENCE Economic Model of DKD), developed using patient-level CREDENCE trial data, was leveraged to model the progression of DKD and CV outcomes, associated costs, and life quality. Unit costs and quality-adjusted life years (QALYs) were sourced from the literature. The time horizon was 10 years and sensitivity analyses were performed. Results Canagliflozin was associated with sizable gains in life-years and QALYs over 10 years, and the incremental cost-effectiveness ratio cost offsets associated with reductions in CV and renal complications resulted in overall net cost savings from the perspective of the Belgian healthcare system. Conclusion Model-based results suggest that adding canagliflozin 100 mg to SoC can improve outcomes for patients with DKD while reducing overall net costs for the Belgian healthcare system. Graphical Abstract
A datalogical reading of online performance

ABSTRACT This article offers a datalogical reading of online performance. In constructing the framework for this new mode of analysing online, computationally centred performance practice, it draws on discussions of data and the datalogical in Blackman [Blackman, L. 2019. Haunted Data: Affect, Transmedia, Weird Science. London: Bloomsbury Academic]; Clough et al [Clough, P. T. , K. Gregory, B. Haber, and R. Scannell. 2015. “The Datalogical Turn. ” In Non-representational Methodologies: Re-envisioning Research, edited by P. Vannini. London: Taylor & Francis Group] and Chun [Chun, W. 2016. Updating to Remain the Same: Habitual New Media. Cambridge, MA: The MIT Press], as well as the practices of surveillance capitalism outlined by Zuboff [The Age of Surveillance Capitalism: The Fight for the Future at the New Frontier of Power. London: Profile Books]. In conducting the analysis, attention is specifically paid to data as a ‘process of translation’ [Blackman, L. 2019. Haunted Data: Affect, Transmedia, Weird Science. London: Bloomsbury Academic], how the audience-participant as data-subject is identified and known and the ways in which data passes in and out of bodies in these works. In looping together these underlying computational happenings with the dramaturgical practices of the performances, I argue that a richer and expanded perspective of online performance practice is afforded – one which opens up the relationships between what we see, feel and experience and the other unseen, but present happenings centred in data exchange and processing within the events in question.
Scaling issues and Ge profile optimization in advanced UHV/CVD SiGe HBT's

The SiGe heterostructure device simulation tool SCORPIO is used to investigate profile optimization in SiGe HBT's for high-performance analog circuit applications. After calibrating SCORPIO to measured data, the effects of germanium profile shape on current gain, cut-off frequency, Early voltage and maximum oscillation frequency are compared over the temperature range of 200-360 K. The impact of aggressive base profile scaling on device performance is also investigated as a function of SiGe film stability.
Early Detection of Wild Rocket Tracheofusariosis Using Hyperspectral Image-Based Machine Learning

Fusarium oxysporum f. sp. raphani is responsible for wilting wild rocket (Diplotaxis tenuifolia L. [D.C.]). A machine learning model based on hyperspectral data was constructed to monitor disease progression. Thus, pathogenesis after artificial inoculation was monitored over a 15-day period by symptom assessment, qPCR pathogen quantification, and hyperspectral imaging. The host colonization by a pathogen evolved accordingly with symptoms as confirmed by qPCR. Spectral data showed differences as early as 5-day post infection and 12 hypespectral vegetation indices were selected to follow disease development. The hyperspectral dataset was used to feed the XGBoost machine learning algorithm with the aim of developing a model that discriminates between healthy and infected plants during the time. The multiple cross-prediction strategy of the pixel-level models was able to detect hyperspectral disease profiles with an average accuracy of 0.8. For healthy pixel detection, the mean Precision value was 0.78, the Recall was 0.88, and the F1 Score was 0.82. For infected pixel detection, the average evaluation metrics were Precision: 0.73, Recall: 0.57, and F1 Score: 0.63. Machine learning paves the way for automatic early detection of infected plants, even a few days after infection.
Verification of 14DOF Full Vehicle Model Based on Steering Wheel Input

This paper presents a 14DOF full vehicle model which consists of ride, handling and tire subsystems to study vehicle dynamics behavior. The full vehicle model is then verified with well-known vehicle dynamics software namely CarSimEd based on the driver input from the steering wheel. Three types of vehicle dynamics test are performed for the purpose of model verification namely step steer test, double lane change test and slalom test. The results of model verification show that the behaviors of the model closely follow the behaviors obtained from CarSimEd software with acceptable error.
Gait Improvement in Chronic Stroke Survivors by Using an Innovative Gait Training Machine: A Randomized Controlled Trial

Chronic stroke leads to the impairment of lower limb function and gait performance. After in-hospital rehabilitation, most individuals lack continuous gait training because of the limited number of physical therapists. This study aimed to evaluate the effects of a newly invented gait training machine (I-Walk) on lower limb function and gait performance in chronic stroke individuals. Thirty community-dwelling chronic stroke individuals were allocated to the I-Walk machine group (n = 15) or the overground gait training (control) group (n = 15). Both groups received 30 min of upper limb and hand movement and sit-to-stand training. After that, the I-Walk group received 30 min of I-Walk training, while the control followed a 30-minute overground training program. All the individuals were trained 3 days/week for 8 weeks. The primary outcome of the motor recovery of lower limb impairment was measured using the Fugl–Meyer Assessment (FMA). The secondary outcomes for gait performance were the 6-minute walk test (6 MWT), the 10-meter walk test (10 MWT), and the Timed Up and Go (TUG). The two-way mixed-model ANOVA with the Bonferroni test was used to compare means within and between groups. The post-intervention motor and sensory subscales of the FMA significantly increased compared to the baseline in both groups. Moreover, the 6 MWT and 10 MWT values also improved in both groups. In addition, the mean difference of TUG in the I-Walk was higher than the control. The efficiency of I-Walk training was comparable to overground training and might be applied for chronic stroke gait training in the community.
Cross-Layer Optimization for Industrial Internet of Things in NOMA-Based C-RANs

This article investigates nonorthogonal multiple access (NOMA)-based cloud radio access networks (C-RANs), where edge caching is adopted to cut down the crowdedness of the fronthaul links. We aim to maximize the energy efficiency (EE) by jointly optimizing the power allocation, analog, and digital precoding, which turns out to be an intractable nonconvex optimization problem. To tackle this problem, we first select cluster heads using the selecting cluster-head (SCH) algorithm, where the analog precoding matrix can be resolved by means of maximizing the array gains. Then, the device grouping algorithm is proposed to group devices according to the equivalent channel correlations, and thus, the NOMA devices in the same beam are capable of sharing the same digital precoding vector. Finally, the joint digital precoding design and power allocation algorithm is proposed to decompose the resultant optimization problem into two subproblems and solve them iteratively by applying the Taylor expansion operation and the minimum mean square error (MMSE) detection. Simulation results validate that the proposed NOMA-based C-RANs with a hybrid precoding (HP) scheme can achieve higher spectral efficiency and EE than the traditional orthogonal multiple access (OMA)-based approach and two-stage HP scheme.
Implementation of a new digital controller for a permanent magnet brushless DC motor

A high performance digital controller for a permanent magnet brushless DC motor using dedicated control ICs (MC 33035 and MC 33039) is discussed. The ICs dramatically simplify the design of the motor control systems, reduce the required circuit area and parts count. Shorter design times and improved system design are the added benefits. The hardware implementation of the drive is presented. A prototype of the controller is constructed and tested with the brushless DC motor. The experimental results are discussed.
A Review of 3D Aircraft Image Recognition Methods

This paper provides a review of 3D aircraft object recognition methods based on 2D images. First, essentialities and advantages on 3D aircraft image recognition are analyzed. Second, in view of the aircraft image recognition system model, the traits of aircraft images are elaborated, then the methods of aircraft image recognition at every stage are discussed, especial the methods of feature extraction about aircraft image and the feasibilities, which some new methods about 3D object recognition are used to aircraft image recognition, are focused. At last, some issues about aircraft image recognition which should be further studied in the future are proposed.
Systematic Literature Review on Self-Assessment Inventory for Quality Teaching among Islamic Education Teachers

The impact of teaching behavior towards teaching quality and self-assessment has become an emerging drift in education, providing an option for teachers’ development. However, studies on teaching behavior and self-assessment are still scarce, despite their importance in improving education. Thus, this review thoroughly identifies the aspects of teaching behavior and teaching quality, as well as the instruments of self-assessment in the teaching profession. Initially, 116 articles published on Web of Science (WoS) and Scopus between 2017 to 2021 were identified, and 10 out of 116 articles were retained for review, based on the exclusion and inclusion criteria. The criteria include the significant findings listed the aspects of teaching behavior and teaching quality. Second, the approaches of self-assessment are emphasized in teaching. Third, the reliability of the instruments used for self-assessment mostly achieved the internal consistency criteria. These three criteria imply the importance of self-assessment for quality teaching and teacher development. In general, this review could help teachers cultivate quality teaching behavior and perform reflective practice for their personal development.
Smoothed Least-Laxity-First Algorithm for Electric Vehicle Charging: Online Decision and Performance Analysis With Resource Augmentation

Adaptive charging can charge electric vehicles (EVs) at scale cost effectively, despite of the uncertainty in EV arrivals. We formulate adaptive EV charging as a feasibility problem that meets all EVs’ energy demands before their deadlines while satisfying constraints in charging rate and total charging power. We propose an online algorithm, smoothed least-laxity-first (sLLF), that decides the current charging rates without the knowledge of future arrivals and demands. We characterize the performance of the sLLF algorithm analytically and numerically. Numerical experiments with real-world data show that it has a significantly higher rate of feasible EV charging than several other existing EV charging algorithms. Resource augmentation framework is employed to assess the feasibility condition of the algorithm. The assessment shows that the sLLF algorithm achieves perfect feasibility with only a 7% increase in the maximal power supply of the charging station.
An Adaptive DPCM Compression Scheme For Real-Time Applications

Differential pulse code modulation (DPCM) is a predictive coding scheme which has been studied extensively. This paper describes an adaptive DPCM compression scheme which is based on an algorithm used in National Image Transmission Format (NITF). This scheme estimates the pixel values using linear and bilinear interpolations. It allows more bits to be assigned to pixels in the noisy areas of the image and fewer bits to pixels in the homogeneous areas. Therefore the prediction is more reliable and the bit-rate reduction is more effective. Furthermore, in this paper, a method is proposed which optimizes the quantization of prediction residuals in the sense that the decision levels and output levels are chosen to minimize the mean square quantization error. Results of applying this technique to a gray-scale image are presented. Performance measures are also given. In addition, comparisons are made between this scheme and the algorithm used in NITF.
Riding the IoT Wave With VFuzz: Discovering Security Flaws in Smart Homes

Z-Wave smart home Internet of Things devices are used to save energy, increase comfort, and remotely monitor home activities. In the past, security researchers found Z-Wave device vulnerabilities through reverse engineering, manual audits, and penetration testing. However, they did not fully use fuzzing, which is an automated cost-effective testing technique. Thus, in this paper, we present VFUZZ, a protocol-aware blackbox fuzzing framework for quickly assessing vulnerabilities in Z-Wave devices. VFUZZ assesses the target device capabilities and encryption support to guide seed selection and tests the target for new vulnerability discovery. It uses our field prioritization algorithm (FIPA), which mutates specific Z-Wave frame fields to ensure the validity of the generated test cases. We assessed VFUZZ on a real Z-Wave network consisting of 19 Z-Wave devices ranging from legacy to recent ones, as well as different device types. Our VFUZZ evaluation found 10 distinct security vulnerabilities and seven crashes among the tested devices and yielded six unique common vulnerabilities and exposures (CVE) identifiers related to the Z-Wave chipset.
If They Only Disrespect Us a Little, and the Story is Interesting, I Keep Watching: Navigation of Ethnic Media Gratifications by Latino Teens

The goal of this study was to apply insights from social identity gratifications and ethnic/racial identity development frameworks to better understand how adolescents perceive, select, and avoid media content which has the potential to damage self-and group-concept. We conducted focus groups with 32 Latino adolescents aged 13 to 15. We found mixed evidence that youth prioritized the ethnicity of characters in program selection. Most referenced personality or age as the primary identity-based factors of interest. Although students widely recognized negative stereotypes of Latinos in mainstream English-language media, this did not overwhelmingly dictate media choices, seemingly due to lack of alternative choices. In contrast, Spanish language programming offered a positive alternative to English-language media and may serve identity needs. The theoretical and practical implications are discussed.
A highly scalable fully non-blocking silicon photonic switch fabric

Large port count spatial optical switches will facilitate flexible and energy efficient data movement in future data communications systems, especially if they are capable of nanosecond-order reconfiguration times. In this work, we demonstrate an 8x8 microring-based silicon photonic switch with software controlled switching. The proposed switch architecture is modular as it assembles multiple identical components with multiplexing/demultiplexing functionalities. The switch is fully non-blocking, has path independent insertion loss, low crosstalk and is straightforward to control. A scalability analysis shows that this architecture can scale to very large port counts. This work represents the first demonstration of real-time firmware controlled switching with silicon photonics devices integrated at the chip scale.
The Impact of COVID-19 on Female Sexual Function: A Systematic Review and Meta-Analysis

Abstract Coronavirus disease 2019 (COVID-19) not only has put populations at risk for mental and sexual health risks. This systematic review and meta-analysis was performed on published articles reporting female sexual function before and during COVID-19 pandemic in PubMed, Web of Science, Scopus, Google Scholar, Magiran and SID databases till August 2021. From the initial 3198 articles, 8 articles were included in the review. Meta-analysis showed no significant difference in total FSFI score and its domains during the COVID-19 pandemic and the pre-pandemic period. Further studies should separately evaluate the effect of lockdown on female sexual function.
Kalman/Particle Filter for Integrated Navigation System

Particle filter is introduced. Since the particle filter would bring hard computation, a new Kalman/Particle mixed filter used on SINS/GPS integrated navigation system was proposed. The new method divides the system into two sub-models, one is linear, the other one is nonlinear, and then implement Kalman filter and particle filter separately. The simulation results show that their performance is almost equal, but the computation complexity of the Kalman/particle filter is much lower than traditional particle filter.
Four-band decomposition module with minimum rounding operations

A four-band decomposition module for 2D digital signals is proposed. The total amount of the error due to the rounding operation is reduced under the constraint that the module has compatibility with the conventional wavelet transform in JPEG 2000. The number of rounding operations and the standard deviation of the error are reduced by 33.3 and 22.9%, respectively, per one module.