Miracle-dz/UniFAR-FTUs huggingface dataset:
Anterior Lumbar Interbody Fusion With Robotic-Assisted Percutaneous Screw Placement: A Case Report

Recently, there has been an increase in robotic-assisted spine fusion for degenerative spondylosis of the lumbar spine. We present the case of a 60-year-old female with grade 1 spondylolisthesis at L4/5 and L5/S1 who underwent L4-S1 anterior lumbar interbody fusion (ALIF) with percutaneous robotic-assisted pedicle screw fixation. We provide a detailed analysis of the procedure including the speed of robotic screw placement and pitfalls of this surgical approach.
Design and Multiobjective Optimization of an Auxiliary Wireless Power Transfer Converter in Medium-Voltage Modular Conversion Systems

This article proposes an optimized design for a wireless power transfer converter serving as an auxiliary power supply in a medium-voltage, high $\mathrm{d}v/\mathrm{d}t$ modular conversion system. A CLLC-CL circuit topology is implemented to generate a load-independent output voltage with a coupling-coefficient-independent resonant frequency. The output voltage of the circuit can be tuned by changing one pair of resonant LC parameters, which decouples the circuit gain from the coil design. Essential parameters of coil and magnet are extracted analytically or numerically to avoid time-consuming 3-D finite element analysis simulations for the subsequent optimization. After the design of the circuit and coil, a multiobjective optimization is carried out with objectives being efficiency, isolation capacitance, and insulation rating of the converter. Finally, experiments demonstrate a 48- to 48-V dc–dc converter with 100 W output power, 92.78% efficiency, 2.78 pF isolation capacitance, and 27 kV insulation rating to validate the optimization result.
Investigation of a derived adverse outcome pathway (AOP) network for endocrine-mediated perturbations

An adverse outcome pathway (AOP) is a compact representation of the available mechanistic information on observed adverse effects upon environmental exposure. Sharing of events across individual AOPs has led to the emergence of AOP networks. Since AOP networks are expected to be functional units of toxicity prediction, there is current interest in their development tailored to specific research question or regulatory problem. To this end, we have developed a detailed workflow to construct a comprehensive endocrine-specific AOP (ED-AOP) network. Connectivity analysis of the ED-AOP network comprising 48 AOPs reveals 7 connected components and 12 isolated AOPs. Subsequently, we apply standard network measures to perform an in-depth analysis of the two largest connected components of the ED-AOP network. Notably, the graph-theoretic analyses led to the identification of important events including points of convergence or divergence in the ED-AOP network. Detailed analysis of the largest component in the ED-AOP network gives insights on the systems-level perturbations caused by endocrine disruption, emergent paths, and stressor-event associations. In sum, the derived ED-AOP network can be used to address the current knowledge gaps in the existing regulatory framework and aid in better risk assessment of environmental chemicals.
Unions in society, unions in the state: New forms of irregular workers’ movements beyond the factory in South Korea

In this study, the authors explore the ways that new forms of labor politics emerge in civil society in the era of flexible labor markets and fragmented workplaces (through outsourcing and subcontracting). First, a theoretical framework is developed that accounts for the formation processes of three modes of irregular, non-standard labor politics: politics of influence, politics of substitution, and politics of occupation. Each of these delineates positional politics of issue-specific threats and alliance, unions’ functional replacement of local civic governance, and unions’ takeover of the state’s institutional space. Then, using unique qualitative field interviews of labor activists and union leaders, a comparative case study is conducted to examine three instances of non-standard workers’ struggles against their employers in South Korean labor politics in the 2000s and the 2010s: the Hyundai Motors Irregular Workers’ Union, the Hope Union, and the Youth Community Union. The study highlights grassroots-based community activism and the institutionalized civil-society space within the state as newly arising forms of labor politics, and discusses their implications in relation to the state, civil society, and partisan politics.
Forecasting Emergency Department Crowding using Data Science Techniques

The provision of insufficient resources during periods of high demand can lead to overcrowding in emergency departments. This issue has been extensively addressed through time series forecasting and regression problems. Despite the fact the increasing number of studies, accurate forecasting of demand remains a challenge. Thus, the purpose of this study was to develop a tool to predict the future evolution of emergency department occupancy in order to anticipate overcrowding episodes, avoid their negative effects on health and improve efficiency. This article presents a novel approach under the premise that the ability of the system to drain patients is the most determining factor in overcrowding episodes as opposed to previous approaches focused on patient demand. The forecasts model were based on the hourly number of patients occupying the general Emergency Department of Insular University Hospital of Gran Canaria Island, mainly given data of the flow of patients through the emergency department as well as performance indicators from other areas of the hospital extracted from the information system.
Medicinal Plants Used in Management of Various Mental Illnesses in Goma City, Democratic Republic of Congo

Many mentally ill people in Goma city, Democratic Republic of Congo (DRC), seek treatment from Traditional Health Practitioners (THPs) that utilize medicinal plants (MPs) in management of various ailments. The study aimed to document the MPs used locally to manage mental illnesses (MIs). An in-depth ethnobotanical survey including 43 respondents selected using snow ball method and interviewed using semi-structured questionnaires was conducted in Goma city, in DRC, from May to September 2021. Voucher specimens were collected from the study area and identified at Makerere University Herbarium (MHU). Data were analyzed using ethnobotanical parameters, frequency index, Rahman’s similarity index (RSI) and non-parametric tests as well as Spearman correlation coefficient. A total of 30 plant species, represented amongst 29 genera and 19 families were reportedly used to treat MIs. Of these 63.33% were reported for anxiety, 36.67% for psychosis and 30% for depression. Most abundant taxa were reported for three families including Asteraceae, Lamiaceae and Solanaceae. Among MPs used in Goma city, the two priority plant species for anxiety were Euphorbia abyssinica and Cleome gynandra L. While, the two priority plant species for depression were Conyza sumatrensis and Emilia coccinea. High similarity (RSI = 77.42%) was observed in the use of common species for MIs between THPs from both Goma and Karisimbi communes. Results prove that local people of Goma city use MPs species against MIs that could be further studied for pharmacological
Análise e estruturação de um modelo de gestão de processos de negócios nas pequenas e médias empresas situadas no polo têxtil do agreste de Pernambuco

Modern management initiatives touch and talk with a vision towards processes, that which by themselves integrate the discussion bottom line for the improvement of performance in organizations and of support to the implantation of managerial process models. In this sense, the Business Process Management (BPM) treats the business processes as assets of the organization, granting conformity in all of their activities. The present paper has the objective of analyzing and elaborating a business processes management model for the businesses that are installed at the textile pole of Pernambuco’s barrens. The goal of this model proposes the improvement on the efficiency of the business processes in the target organization and at the Supply Chain (SC). In that case, the approach applied by this research has diagnosed the main aspects of the BMP in five textile organizations of the region, based in personal interviews and the application of a questionnaire, which is a process comparing evaluation in the SC via the model by Lambert et al. (1998) and through a SWOT analysis. This research has used a qualitative approach which was adapted as exploratory for the development of the case study. The results of the research show that there is a lack of practising of the processes management models at the textile organizations, as well as the necessity of formalizing key processes of the supply line.
Rental Market Liquidity, Seasonality, and Distance to Universities

Abstract This paper explores how liquidity in the UK rental markets reacts to variations in demand across time and space. We employ a survival analysis approach with a non-parametric hazard rate to investigate whether the probability of a property to exit the market changes across calendar months. Our unique dataset comes from Zoopla.com and contains 300,198 rental listings in 13 major UK university cities over the 2015–2017 period. Our results suggest that the probability of exit is lower during the winter season compared to summer. This could be explained by students’ higher housing demand at the start of the academic term. The results become more pronounced (i.e. the seasonal difference is higher) when the distance between marketed property and university campuses is taken into account.
Twin Delayed Deep Deterministic Policy Gradient-Based Target Tracking for Unmanned Aerial Vehicle With Achievement Rewarding and Multistage Training

Target tracking using an unmanned aerial vehicle (UAV) is a challenging robotic problem. It requires handling a high level of nonlinearity and dynamics. Model-free control effectively handles the uncertain nature of the problem, and reinforcement learning (RL)-based approaches are a good candidate for solving this problem. In this article, the Twin Delayed Deep Deterministic Policy Gradient Algorithm (TD3), as recent and composite architecture of RL, was explored as a tracking agent for the UAV-based target tracking problem. Several improvements on the original TD3 were also performed. First, the proportional-differential controller was used to boost the exploration of the TD3 in training. Second, a novel reward formulation for the UAV-based target tracking enabled a careful combination of the various dynamic variables in the reward functions. This was accomplished by incorporating two exponential functions to limit the effect of velocity and acceleration to prevent the deformation in the policy function approximation. In addition, the concept of multistage training based on the dynamic variables was proposed as an opposing concept to one-stage combinatory training. Third, an enhancement of the rewarding function by including piecewise decomposition was used to enable more stable learning behaviour of the policy and move out from the linear reward to the achievement formula. The training was conducted based on fixed target tracking followed by moving target tracking. The flight testing was conducted based on three types of target trajectories: fixed, square, and blinking. The multistage training achieved the best performance with both exponential and achievement rewarding for the fixed trained agent with the fixed and square moving target and for the combined agent with both exponential and achievement rewarding for a fixed trained agent in the case of a blinking target. With respect to the traditional proportional differential controller, the maximum error reduction rate is 86%. The developed achievement rewarding and the multistage training opens the door to various applications of RL in target tracking.
Filtering mobile spam by support vector machine

Currently mobile spam has been a major menace to the development of wireless networks. In this paper, the mobile spam problem and its countermeasures are analysed. In particular, we propose a Support Vector Machine to filter mobile spam. This mobile spam filtering system can be deployed in current wireless networks and achieve good performance in protecting end users and operators from mobile spam. Legislation issues and challenges to defend mobile spam are also discussed in the latter part of this paper.
A Case Study of Mobile Health Applications: The OWASP Risk of Insufficient Cryptography

Mobile devices are being deployed rapidly for both private and professional reasons. One area of that has been growing is in releasing healthcare applications into the mobile marketplaces for health management. These applications help individuals track their own biorhythms and contain sensitive information. This case study examines the source code of mobile applications released to GitHub for the Risk of Insufficient Cryptography in the Top Ten Mobile Open Web Application Security Project risks. We first develop and justify a mobile OWASP Cryptographic knowledgegraph for detecting security weaknesses specific to mobile applications which can be extended to other domains involving cryptography. We then analyze the source code of 203 open source healthcare mobile applications and report on their usage of cryptography in the applications. Our findings show that none of the open source healthcare applications correctly applied cryptography in all elements of their applications. As humans adopt healthcare applications for managing their health routines, it is essential that they consider the privacy and security risks they are accepting when sharing their data. Furthermore, many open source applications and developers have certain environmental parameters which do not mandate adherence to regulations. In addition to creating new free tools for security risk identifications during software development such as standalone or compiler-embedded, the article suggests awareness and training modules for developers prior to marketplace software release.
PIV Uncertainty Methodologies for CFD Code Validation at the MIR Facility

Currently, computational fluid dynamics (CFD) is widely used in the nuclear thermal hydraulics field for design and safety analyses. To validate CFD codes, high quality multi dimensional flow field data are essential. The Matched Index of Refraction (MIR) Flow Facility at Idaho National Laboratory has a unique capability to contribute to the development of validated CFD codes through the use of Particle Image Velocimetry (PIV). The significance of the MIR facility is that it permits non intrusive velocity measurement techniques, such as PIV, through complex models without requiring probes and other instrumentation that disturb the flow. At the heart of any PIV calculation is the cross-correlation, which is used to estimate the displacement of particles in some small part of the image over the time span between two images. This image displacement is indicated by the location of the largest peak. In the MIR facility, uncertainty quantification is a challenging task due to the use of optical measurement techniques. Currently, this study is developing a reliable method to analyze uncertainty and sensitivity of the measured data and develop a computer code to automatically analyze the uncertainty/sensitivity of the measured data. The main objective of this study is to develop a well established uncertainty quantification method for the MIR Flow Facility, which consists of many complicated uncertainty factors. In this study, the uncertainty sources are resolved in depth by categorizing them into uncertainties from the MIR flow loop and PIV system (including particle motion, image distortion, and data processing). Then, each uncertainty source is mathematically modeled or adequately defined. Finally, this study will provide a method and procedure to quantify the experimental uncertainty in the MIR Flow Facility with sample test results.
Pangium edule Reinw: A Promising Non-edible Oil Feedstock for Biodiesel Production

Biodiesel production from non-edible feedstocks is currently drawing much attention due to legitimate concerns about the effects of using edible oil for fuel. Pangium edule Reinw is a non-edible feedstock. Pangium is a tall tree native to the Micronesia, Melanesia and the mangrove swamps of South-East Asia. In this study, biodiesel production and characterization from P. edule oil was reported. The seeds were obtained from Bogor, Indonesia. The oil was found to have an acid value of 19.62 mg KOH/g oil. Therefore, a two-step acid–base-catalysed transesterification was used to produce biodiesel. This was followed by evaluating the physical and chemical properties of biodiesel and its blends with diesel. It has been found that the determined properties of P. edule methyl ester indicate that the oil can be considered as a future biodiesel source. The most remarkable feature of P. edule is its cloud, pour and cold filter plugging points. This biodiesel yielded cloud, pour and cold filter plugging points of −6, −4 and −8 ◦C, respectively. This indicates the viability of using this biodiesel in cold countries. ThereA. E. Atabani (B) Department of Mechanical Engineering, Faculty of Engineering, Erciyes University, 38039 Kayseri, Turkey e-mail: a_atabani2@msn.com A. E. Atabani · I. A. Badruddin · H. H. Masjuki · W. T. Chong Department of Mechanical Engineering, Faculty of Engineering, University of Malaya, 50603 Kuala Lumpur, Malaysia A. E. Atabani Erciyes Teknopark A. Ş, Yeni Mahalle Aşıkveysel Bulvarı Erciyes Teknopark, Tekno 3 Binası 2, Kat No: 28, 38039 Melikgazi, Kayseri, Turkey K. T. Lee School of Chemical Engineering, Universiti Sains Malaysia (USM), Engineering Campus, Seri Ampangan, 14300 Nibong Tebal, Pulau Pinang, Malaysia fore, it is suggested that more research should be conducted on P. edule for future biodiesel production.
Algorithm for Onset/Offset Detection of EMG Signals for Real-time Control of a Low-cost Open-source Bionic-hand

: This work was carried out as part of a project to develop a low-cost open source bionic hand using electromyographic (EMG) signals. Probably the most important task for the success of this bionic hand is to achieve a correct determination of muscle activation intervals. In this paper it is presented an algorithm for the detection of Onset/Offset to be executed in an Arduino UNO. The aim of this algorithm is to be executed in this ATmega328 microprocessor with a 16 MHz clock speed and 32 kBytes of memory in order to accomplish with effectiveness the real-time control of the bionic hand. The tests performed up to its application in real-time detection of muscle activation will also be described. The preliminary results presented show a 100% success rate in most gestures performed by the bionic hand but with the occurrence of a few false activations.
Multiview Embeddings for Soundscape Classification

Acoustic scenes (or soundscapes) can be composed of various background and foreground sound events. Classification of soundscapes have to deal with the overlap of these sound events. In this work, we propose to reduce this overlap by considering foreground sound events and background sound events as multiple views of the soundscape. Robust principal components analysis is used to decompose a soundscape into the background view and the foreground view. We can control the amount of information retained in this decomposition by using the subspace projection technique of nuisance attribute projection. We represent the audio samples as features from a convolutional neural network, and view-invariant representations are derived using a deep neural network based multi-view learning algorithm. Experimental results demonstrate the effectiveness of our proposed method on standard datasets for acoustic scene classification.
A horizontal–vertical anisotropy in spatial short-term memory

ABSTRACT Visual perception and saccadic eye-movements are more precise when directed at isoeccentric locations along the horizontal compared to vertical meridian. This effect is known as horizontal-vertical anisotropy (HVA). Given that the eye-movement system plays an important role in spatial short-term memory (STM) it was hypothesized that spatial STM would also show a horizontal-vertical anisotropy. Consistent with this hypothesis an online experiment revealed a significant HVA in spatial STM (Experiment 1). This effect persisted even when eye-movements were precluded by using very short display durations (Experiment 2). However, there was no HVA in a colour span or orientation change detection task. It is argued that the HVA in spatial STM may result from greater imprecision in the representation of spatial locations along the vertical meridian relative to the horizontal meridian in the spatial maps underpinning spatial STM, a bilateral field advantage, or some combination of these mechanisms.
Teacher’s Technology Integration ELT Based on SAMR Model in Writing Skill

This study is aimed to know the technology categories integrated by the teacher and classify the teacher’s technology integration level. Descriptive qualitative is used to describe the result of this study. The data is collected through interview and observation at SMA N 1 SENTOLO. It is focused on the teaching of writing. the subject of this research were 2 teacher. The data were transformed into descriptive text and interviewed transcripts. The data analysis used reduction data, the data display, and conclusion drawing or verification. The data validation used triangulation of technique of collecting data and triangulation of source of data.The source of data taken from interview . Based on the result of finding and discussion, it is found that the teacher integrated more than four technology categories which are word processing, spreadsheet software, organizing and brainstorm, multimedia, and web resources. The teacher integrated those technologies in teaching listening, reading and writing skill. While the activities is analysed based on SAMR model to know the teacher’s technology integration . The result shows that the teacher is on the augmentation level in teaching writing skill, which the teacher uses word processing with additional functions like spell check, cut, and paste the documents. Therefore, the teacher is classified on passing the substitution level, because the teacher is on the augmentation level, which integrates technology as a direct tool substitute, with functional improvement.
e-Health Services to Support the Perinatal Decision-making Process: An Analysis of Digital Solutions to Create Birth Plans

This research aims to provide an overview of the existent digital solutions for birth plans’ creation, intending to contribute for the advance of e-health services focused on the perinatal decision-making process. Primary data was found through a web search procedure. Better ranked options complying with the following criteria were included: (a) available online and for free; (b) pregnant people as the target audience; (c) labor and/or birth plan creation features; (d) in English. Four online services were found, and a two part study was conducted: a) a non-exhaustive benchmarking-like analysis of webpages where the digital solutions to create birth plans were provided, according to six dimensions; b) followed by a content analysis of the digital solutions, resulting in 13 categories emerging, that were scored according to their occurrence and completeness. “Consent and Information” category had the lowest score, what is considered critical for the full purpose of a birth plan creation; while, “Freedom”, “Ambience and Equipment”, “People”, “Type of birth” and “Pain management” categories achieved the highest scores. Two solutions were considered particularly incomplete. Results show three solutions based on checklists, and one on visual icons. All solutions were based on a delivery approach, not including interactive or audiovisual components.