Miracle-dz/UniFAR-FTUs huggingface dataset:
Joint PEV Charging Network and Distributed PV Generation Planning Based on Accelerated Generalized Benders Decomposition

Integration of plug-in electric vehicles (PEVs) with distributed renewable power sources will reduce PEVs’ well-to-wheels greenhouse gas emissions, promote renewable power adoption, and defer power system investments. This paper proposes a multidisciplinary approach to jointly plan PEV charging stations and distributed photovoltaic (PV) power plants on a coupled transportation and power network. We formulate a two-stage stochastic programming model to determine the sites and sizes of: 1) PEV charging stations and 2) PV power plants. This proposed method incorporates comprehensive models of: 1) transportation networks with explicit PEV driving range constraints; 2) PEV charging stations with probabilistic quality of service constraints; 3) PV power generation with reactive power control; and 4) alternating current distribution power flow. The formulation results in a mixed-integer second-order cone program. We then design a generalized Benders decomposition algorithm to efficiently solve it. Numerical experiments show that investing in distributed PV power plants with PEV charging stations has multiple benefits, e.g., reducing social costs, promoting renewable power integration, and alleviating power congestion. The benefits become more prominent when utilizing PV generation with reactive power control, which can also help to enhance power supply quality.
Effect of acoustic stimuli in patients with disorders of consciousness: a quantitative electroencephalography study

Auditory stimuli are proposed as beneficial neurorehabilitation methods in patients with disorders of consciousness. However, precise and accurate quantitative indices to estimate their potential effect remain scarce. Fourteen patients were recruited from the Neuro-Rehabilitation Unit of Hangzhou Hospital of Zhejiang Armed Police Corps of China. Altogether, there were seven cases of unresponsive wakefulness syndrome (five males and two females, aged 45.7 ± 16.8 years) and seven cases of minimally conscious state (six males and one female, aged 42.3 ± 20.8 years). Simultaneously, fourteen healthy controls (10 males and 4 females, aged 51.7 ± 9.7 years) also participated in this case-control experiment. Brain response to music, subjects’ own name, and noise was monitored by quantitative electroencephalography (QEEG) in the resting state and with acoustic stimulation. Predictive QEEG values in various brain regions were investigated. Our results show that cerebral activation was high in subjects stimulated by their own name, especially in the temporal lobe in patients with disorders of consciousness, and the frontal lobe in the control group. Further, during resting and stimulation, QEEG index (δ + θ/α + β ratio) negatively correlated with the Coma Recovery Scale-Revised score in traumatic disorders of consciousness patients. Hence, we speculate that a subject’s own name might be an effective awakening therapy for patients with disorders of consciousness. Moreover, QEEG index in specific stimulation states may be used as a prognostic indicator for disorders of consciousness patients (sensitivity, 75%; specificity, 50%). This clinical study has been registered at ClinicalTrials.gov (identifier: NCT03385291).
A Chance-Constrained Two-Stage Stochastic UC Considering Uncertain Renewable Energy Output And Demand Response

A unit commitment problem based on two-stage stochastic theory, considering demand response (DR) and uncertain renewable energy output is presented. Wind power and hydroelectric power are considered as renewable energy in the proposed model. Firstly, wind power output is forecasted using LHS with random permutation (LHSRP) method. Two kinds of DR, incentive-based DR (IDR) and price-based DR (PDR) are incorporated. In view of the characteristics of different users, various price elasticity and responsive ratios are presented in the PDR. Charging strategy of electric vehicles (EVs) considering the actual requirement of users and charging constraints, based on real-time electricity price, is formulated to decrease the impact on system that EVs bring when disordered charging. A chance-constrained two-stage stochastic UC model is proposed to maximize the social welfare. Chance constraint ensures that a large portion of wind power output wm be utilized with high probability. A revised IEEE 24-bus system is analyzed and the results show that, stochastic optimization theory can overcome the uncertainty of wind power output; DR has the effect to flatten the load curve as well as reducing the frequent rescheduling of thermal units. Meanwhile, the proposition of EVs charging strategy can reduce the charging cost and decrease the difference between the peak time period and valley time period.
Modeling of Effective Thermal Resistance in Sub-14-nm Stacked Nanowire and FinFETs

In advanced technology nodes, an increase in power density, use of nonplanar architectures, and novel materials can aggravate local self-heating due to active power dissipation. In this paper, 3-D device simulations are performed to analyze thermal effects in fin-shaped field-effect transistors (FinFETs) and stacked-nanowire FETs (NWFETs). Based on empirically extracted equations, a new model for thermal resistance estimation is proposed, which for the first time takes into account the aggregate impact of a number of fins, number of gate fingers, number, and dimensions of stacked nanowires. We have extracted the proposed model against calibrated 3-D TCAD simulations over a range of device design variables of interest. Our results show that the model may be useful for estimation of thermal resistance in FinFETs and NWFETs with large layouts.
The Interplay of Factors Affecting Learning of Introductory Programming: A Comparative Study of an Australian and an Indian University

Teaching introductory programming is a challenging task in tertiary education and various factors are believed to have influence on students' learning of programming. However, these factors were largely studied independently in a chosen context. This paper aims to investigate whether interrelationships exist among the factors and whether the interrelationships are context-dependent. In this empirical study, two universities were chosen from two continents, which represent different cultures, teaching methodologies, assessment criteria and languages used to teach programming in west and east worlds respectively. The results reveal that some interrelationships are common across the two different contexts, while others appear context-dependent.
A Novel Warehouse Multi-Robot Automation System with Semi-Complete and Computationally Efficient Path Planning and Adaptive Genetic Task Allocation Algorithms

We consider the problem of warehouse multi-robot automation system in discrete-time and discrete-space configuration with focus on the task allocation and conflict-free path planning. We present a system design where a centralized server handles the task allocation and each robot performs local path planning distributively. A genetic-based task allocation algorithm is firstly presented, with modification to enable heuristic learning. A semi-complete potential field based local path planning algorithm is then proposed, named the recursive excitation/relaxation artificial potential field (RERAPF). A mathematical proof is also presented to show the semi-completeness of the RERAPF algorithm. The main contribution of this paper is the modification of conventional artificial potential field (APF) to be semi-complete while computationally efficient, resolving the traditional issue of incompleteness. Simulation results are also presented for performance evaluation of the proposed path planning algorithm and the overall system.
Benchmarking Structure from Motion Algorithms of Urban Environments with Applications to Reconnaissance in Search and Rescue Scenarios

Structure from motion is a common approach to generate 3D models of objects and structures. The ease of the data acquisition and the wide selection of available algorithms makes the technique easily accessible. Previous benchmarks on the topic have been focused on scanning small structures, specially for archaeology, or have been limited to single or very few algorithms. In this work different algorithms are benchmarked regarding accuracy and processing time for datasets acquired in urban environments, with the goal of analyzing the feasibility of utilizing this technique on search and rescue operations. Real-world rescue scenarios are demanding due to the presence of challenging surfaces and smoke.
Impact of Chronic Medical Conditions on Academics of Children in the Child Welfare System

Objective: Children in the Child Welfare System (CWS) are at high risk for multiple adverse outcomes. Since involvement in CWS and having a chronic medical condition are both risk factors for poor academic achievement, a logical view is that the combination is additive, increasing the odds of poor performance. However, several factors may complicate such an association. This study explores negative and positive factors that could affect academic achievement in children in CWS with chronic medical conditions. Method: In a secondary data analysis of a nationally representative, longitudinal sample of children in CWS (N = 5,501), subjects were divided into three groups based on chronic medical condition: High Prevalence, Low Severity (HPLS; asthma, eczema, allergy, diabetes), Other (OTH; all other chronic conditions, including those with primary central nervous system involvement), and NONE (children with no chronic condition). Using weighted analyses, hierarchical logistic regression models addressed factors associated with academic achievement. Predictor variables included chronic condition group, sex, income level, case substantiation, home placement, and school engagement. Intelligence quotient was a covariate. Outcome variables were strong performances for reading and math, defined by standard score ≥85. Results: In TOTAL group, 80% had strong reading; more in HPLS (85%) vs. NONE (79%) and OTH (80%), adjusted F = 433, p < 0.001. In TOTAL group, 67% had strong math; more in NONE (68%) and HPLS (68%) vs. OTH (60%), adjusted F = 1,278, p < 0.001. Models predicting to strong reading and math achievement were significant, R2 = 0.51, p < 0.001 and R2 = 0.43, p < 0.001, respectively. HPLS had increased odds of strong reading achievement (aOR 1.3, 95% CI 1.3–1.4); both HPLS and OTH had lower odds of strong math achievement (aOR 0.87 and 0.76), p < 0.001, respectively. Male sex had lower odds of strong reading (aOR 0.44) and math achievement (aOR 0.62); positive school engagement had higher odds of strong reading (aOR 1.18) and math achievement (aOR 2.04), all p < 0.001. Conclusion: If true, our findings challenge the general belief that chronic illness can only be associated with negative outcomes and that cumulative adversities are simply additive in terms of risk. Increased contact with the medical system may provide an opportunity for improving reading achievement for children in CWS and promoting positive school engagement.
Dynamic Time Warping Assisted SVM Classifier for Bangla Speech Recognition

In this paper, an automatic speech recognition system has been proposed for isolated Bangla word using Support vector machine with Dynamic time warping (DTW). For training purposes, we have collected data from 40 speakers for five different Bangla words. All the data was collected in a highly acoustic and noise-proof environment. Mel frequency cepstrum coefficients (MFCC’s) are considered as static features from the speech signal. For dynamic features, first and second derivatives of MFCC are utilized. After determining feature vectors, a modified DTW method is proposed for feature matching. Finally, for classification Support Vector Machine (SVM) with Radial basis function (RBF) is utilized. The model is tested for 12 speakers and the recognition rate that we achieved is 86.08%.
A Simple Diffuse Fluorescent BBRRDF Model

Fluorescence --- the effect of a photon being absorbed at one wavelength and re-emitted at another --- is present in many common materials such as clothes and paper. Yet there has been little research in rendering or modeling fluorescent surfaces. We discuss the design decisions leading to a simple model for a diffuse fluorescent BBRRDF (bispectral bidirectional reflection and reradiation distribution function). In contrast to reradiation matrix based models our model is continuous in wavelength space. It can be parameterized by artificially designed spectra as well as by many publicly available physical measurements. It combines fluorescence and non-fluorescent reflectance, as most real-world materials are not purely fluorescent but also reflect some light without changing its wavelength. With its simple parameterization the BBRRDF is intended as a starting point for any physically based spectral rendering system aiming to simulate fluorescence. To that end we show how to continuously sample both incident and exitant wavelengths from our BBRRDF which makes it suitable for bidirectional transport, and we discuss energy and photon conservation in the context of fluorescence.
Nine cases of catamenial pneumothorax: a report of a single-center experience.

Background Catamenial pneumothorax (CP) is defined as repeated pneumothorax related to menses and thoracic endometriosis. We performed a retrospective analysis of nine patients with CP to determine the clinical features as well as the effects of treatment and recurrence rates. Methods A retrospective review was conducted of the clinical and pathologic data in all CP patients undergoing treatment at our institution. Nine patients underwent treatment for CP. Of these, six underwent surgical treatment 8 times. Results The median age was 36 years. Six patients had experienced delivery. The laterality of the pneumothorax was right in all patients. Pelvic endometriosis was diagnosed in five patients. Six patients underwent surgical treatment. Partial resection of the lung was performed in four patients and partial resection of the diaphragm in five. Of these, both resections were performed in four patients. A pathological diagnosis of endometriosis was achieved in only three patients. The observation period was 16.7 months. In the six patients with surgical resection, five experienced recurrence at various intervals. Onset of pneumothorax occurred pre- or menstrual period in most cases. Conclusions The diagnosis and treatment of CP is not easy. A multidisciplinary approach and skillful management are required. Recurrence of CP is common following a temporary cure of pneumothorax by surgical treatment.
Pedicle Screw Placement Using Augmented Reality Surgical Navigation With Intraoperative 3D Imaging

Study Design. Prospective observational study. Objective. The aim of this study was to evaluate the accuracy of pedicle screw placement using augmented reality surgical navigation (ARSN) in a clinical trial. Summary of Background Data. Recent cadaveric studies have shown improved accuracy for pedicle screw placement in the thoracic spine using ARSN with intraoperative 3D imaging, without the need for periprocedural x-ray. In this clinical study, we used the same system to place pedicle screws in the thoracic and lumbosacral spine of 20 patients. Methods. The study was performed in a hybrid operating room with an integrated ARSN system encompassing a surgical table, a motorized flat detector C-arm with intraoperative 2D/3D capabilities, integrated optical cameras for augmented reality navigation, and noninvasive patient motion tracking. Three independent reviewers assessed screw placement accuracy using the Gertzbein grading on 3D scans obtained before wound closure. In addition, the navigation time per screw placement was measured. Results. One orthopedic spinal surgeon placed 253 lumbosacral and thoracic pedicle screws on 20 consenting patients scheduled for spinal fixation surgery. An overall accuracy of 94.1% of primarily thoracic pedicle screws was achieved. No screws were deemed severely misplaced (Gertzbein grade 3). Fifteen (5.9%) screws had 2 to 4 mm breach (Gertzbein grade 2), occurring in scoliosis patients only. Thirteen of those 15 screws were larger than the pedicle in which they were placed. Two medial breaches were observed and 13 were lateral. Thirteen of the grade 2 breaches were in the thoracic spine. The average screw placement time was 5.2 ± 4.1 minutes. During the study, no device-related adverse event occurred. Conclusion. ARSN can be clinically used to place thoracic and lumbosacral pedicle screws with high accuracy and with acceptable navigation time. Consequently, the risk for revision surgery and complications could be minimized. Level of Evidence: 3
Relationship between Rectal Temperature and Vaginal Temperature in Grazing Bos taurus Heifers

Simple Summary Body temperature is widely used to evaluate health status and thermal balance in cattle. There are numerous well-documented measures of body temperature in cattle including rectal, vaginal, tympanic, and rumen. However, in many instances, the relationship that exists between these measures has not been extensively evaluated. This study evaluated the relationship between rectal temperature and vaginal temperature in grazing beef heifers. Gaining a greater understanding of the relationships that exists between measures of body temperature may allow for greater between-study comparisons to occur. Abstract This study evaluated the relationship between rectal temperature (TREC, °C) and vaginal temperature (TVAG, °C) in grazing Bos taurus heifers, to develop an understanding of the reliability of these measures as estimates of core body temperature. Nineteen Angus heifers (BW = 232.2 ± 6.91 kg) were implanted with intra-rectal and intra-vaginal data loggers. Rectal temperature and TVAG were simultaneously recorded at 20 s intervals over 18.5 h. Heifers were housed as a singular cohort on grazing pastures for the duration of the study. A strong linear relationship (R2 = 0.72, p < 0.0001) between the measurement sites was identified. The mean difference between TREC and TVAG was small, in which TVAG was on average 0.22 ± 0.01 °C lower than TREC. Individual twenty second TREC and TVAG data were used to determine the pooled mean TREC and TVAG and then to highlight the within measure variation over time. The coefficient of variation was, on average, lower (p < 0.001) for TVAG (0.38%) than TREC (0.44%), indicating that TVAG exhibited less variation. Overall, the results from the current study suggest that a strong relationship exists between TREC and TVAG, and that TVAG may be a more reliable estimate of core body temperature than TREC in grazing Bos taurus heifers.
Locally-determined Voltage Droop Control for Distribution Systems

Distributed energy resources have the potential to mitigate both undervoltage and overvoltage problems in distribution system through their reactive power capability. The most practical way to implement the voltage control is through a local droop control which requires no communication with the neigbouring buses or a centralised control centre. However, determining a suitable droop coefficient for the distributed energy sources at different locations in the system requires knowledge of the grid parameters. In this work, a practical way of determining the droop coefficients locally is proposed. The method is applied on most commonly used test systems, and validated against the traditional droop control. Results show that the proposed droop coefficient brought the voltage profile closer to the reference voltages for both overvoltage and undervoltage problems.
How People Negotiate? From the Analysis of a Dialogue Corpus to a Dialogue System

We study human-human negotiations in a dialogue corpus with the aim to develop a dialogue system. The empirical material is formed by telemarketing calls where sales clerks of an educational company are offering the training courses of the company to prospective customers. We consider how arguments are used by both sides for achieving their communicative goals and figure out the general structure of negotiations. The results of the analysis will be implemented in our dialogue system that interacts with the user in Estonian.
Voltage Modulation Using Virtual Positive Impedance Concept for Active Damping of Small DC-Link Drive System

Small dc-link drive systems, built with film capacitors in the dc-link, present a new trend in many industrial applications and are obtaining increasing interests. It has the advantages of longer lifetime and the possibility to achieve a more compact design of the capacitor bank, especially at medium and high power rates. However, it could exhibit instability problems, mainly in the form of oscillations. The unexpected oscillation may result in overvoltage and shorten the lifetime of the power devices and the dc-link capacitors; increase the total harmonic distortion and also the partially weighted harmonic distortion of the grid supply current. Therefore, active damping methods are usually needed in order to stabilize such drive systems. This paper first analyzes the system characteristics and the principles of existing active damping methods. Then, a new voltage modulation based method named as “virtual positive impedance” method is introduced to guarantee the dc-link stability. This new approach is simple to apply and its implementation does not require the knowledge of system parameters and machine operating conditions. The proposed method is analyzed in details and verified by experiments.
Argumentation Mining: Exploiting Multiple Sources and Background Knowledge

The field of Argumentation Mining has arisen from the need of determining the underlying causes from an expressed opinion and the urgency to develop the established fields of Opinion Mining and Sentiment Analysis. The recent progress in the wider field of Artificial Intelligence in combination with the available data through Social Web has create great potential for every sub-field of Natural Language Process including Argumentation Mining.
Effect of Manufacturing Tolerances and Assembly Errors on the Characteristics of Small Scale Slider Crank Mechanisms

Small scale slider crank mechanisms are used in many sophisticated applications, where the accuracy and precision of the mechanisms function are their main performance criteria. The input-output of the mechanism are the main criteria to define its characteristics and hence its capabilities to achieve specific application requirements. The tolerance analysis for the mechanism components are a key element for studying and improving mechanism characteristics and its transmission quality. In this paper kinematics contact approach models for small scale slider crank mechanism are presented. The models consider the mechanism characteristic range, sensitivity and input-output relations. The effect of mechanism manufacturing and assembly errors such as; components tolerances, revolute joints clearances and assembly deviations were investigated. The investigations are applied for the inline and offset types mechanisms. The study elaborates the effect of these errors on the mechanism characteristic, position errors and uncertainty. The effect of revolute joints clearances and offset on the mechanism hysteresis errors, position uncertainty, and dead zones are presented. The results of the proposed contact models are compared with those applying Ting rotatability method. The study is further condensed to define the most appropriate design parameters and manufacturing tolerance according to the permissible system errors.