Miracle-dz/UniFAR-FTUs huggingface dataset:
A Low-Power Indirect Time-of-Flight CMOS Image Sensor With Fixed Depth Noise Compensation and Dual-Mode Imaging for Depth Dynamic Range Enhancement

We present a low-power indirect time-of-flight (iTOF) image sensor with fixed depth noise compensation and dual-mode imaging for depth dynamic range (DDR) enhancement. To reduce the power consumption from high-frequency pixel modulation, a TX driver with a single-sided clock chain is employed in the sensor. The inherent phase delay of the clock chain and the delay of the row bus are measured using row-parallel and column-parallel time-to-digital converters (TDCs) to compensate for the column and row fixed depth noise (FDN). To achieve a wide depth dynamic range (WDDR), the reconfigurable pixels and column circuits support dual-mode: short-range (SR) and long-range (LR) modes. A WDDR image is generated in a single frame through the mixed reconfiguration of the pixel array and interpolation. In addition, the temporal noise is suppressed without a significant time budget through a fast multiple sampling (FMS) scheme with 10b successive approximation register (SAR) analog-to-digital (ADCs). A prototype iTOF image sensor was fabricated using a 110 nm frontside illumination (FSI) CMOS image sensor (CIS) process and fully characterized. The sensor achieved a DDR of 4 m (0.7 to 4.7 m) with less than 1.7% nonlinearity and 0.9% depth noise. The FDN was suppressed to less than 2.1 cm at a low power consumption below 70 mW through the proposed compensation scheme using row and column TDCs. The temporal noise was only 0.48 mV $_{\mathbf {rms}}$ owing to the FMS.
An explanation of or-deletions and other paradoxical disjunctive inferences

ABSTRACT Some inferences of the sort: A or B; therefore A, which are invalid in standard logics, are sensible in life: You can enter now or later; therefore, you can enter now. That these "or-deletions" follow necessarily or only possibly is a by-product of a theory of mental models. Its semantics for "or" refers to conjunctions of possibilities holding in default of knowledge to the contrary. It predicts new sorts of or-deletion, such as: He likes to drink red wine or white wine. So, he likes to drink red wine. and: You are permitted to do only one of the following: You can enter now. You can enter later. Therefore, you are permitted to enter now. They are invalid in standard logics, and neither previous pragmatic nor semantic theories predicted them. Four experiments corroborated their occurrence.
Earthquake‐induced damage detection and localization in masonry structures using smart bricks and Kriging strain reconstruction: A numerical study

The intrinsic vulnerability of masonry structures to seismic events makes structural health monitoring of the utmost importance for the conservation of the built heritage. The development of piezoresistive bricks, also termed smart bricks, is an innovative technology recently proposed by the authors for the monitoring of such structures. Smart bricks exhibit measurable variations in their electrical properties when subjected to external loads or, alternatively, strain self‐sensing capabilities. Therefore, the deployment of a network of smart bricks into a masonry structure confers self‐diagnostic properties to the host structure. In this light, this paper presents a theoretical investigation on the application of smart bricks to full‐scale masonry structures for seismic assessment. This includes the study of the convenience of providing electrical isolation conditions to the sensors, as well as the effectiveness of smart bricks when installed into either new constructions or in pre‐existing structures. Secondly, numerical results are presented on the seismic analysis of a three‐dimensional masonry building equipped with a network of smart bricks. Finally, in order to map the strain field throughout the structure exploiting the outputs of a limited number of sensors, an interpolation‐based strain reconstruction approach is proposed.
Emerging methodologies in stability and optimization problems of learning‐based nonlinear model predictive control: A survey

Since last 40 years, the theory and technology of model predictive control (MPC) have been developed rapidly. However, nonlinear MPC still faces difficulties such as high online computational complexity and inability to accurately model the system. In order to improve or solve the problems mentioned above of MPC, recent researches have deepened the learning‐based control. The learned method can model unknown or highly uncertain nonlinearities. And the emergence of efficient algorithms has greatly improved the feasibility of computing. Stability is at the heart of control design. Learning‐based nonlinear model predictive control (LB‐NMPC) has achieved systematic research results in the past 10 years. But the stability of LB‐NMPC is still an open question that has not been fully addressed in the literature. This review mainly summarizes the latest research progress of LB‐NMPC. More specifically, the uncertainty and online optimization problems of the considered systems are investigated mainly focusing on the use of learning techniques. At the same time, the research hotspots such as the control stability and constraint satisfaction of LB‐NMPC are briefly discussed. Finally, the application of LB‐NMPC technology in integrated circuits, path tracking control, and other fields is reviewed, which provides a reference for the research and application of LB‐NMPC.
SIMILARITY LIMITS OF ORIENTATION CHANGES IN AFFINE TRANSFORMATIONS WITH APPLICATIONS TO PLANAR PATTERN MATCHING

Besides descriptor designing, Factoring out the categorical effects of affine transformations is also an effective way to match features. This paper proposed and demonstrated a hypothesis that any coplanar orientations have limited geometrical changes when observed in the camera screen under given ranges of 3D affine transformations.Confirmatory experiments are accomplished by Matlab simulations focusing on specific influences of 3D affine transformations on similarity biases between concerned orientation changes. Statistical analyses and results show that rotations about plane axes mainly affect the geometrical biases of orientation changes. A set of fit limits standing for the biggest influences of most affine transformations in specified ranges are numerically approximated by total sample space distribution and experimental extreme values. We use these Similarity Limits of Orientation Changes (SLOC) as optimization constraints in matching problems, and an application example of planar pattern matching is given. The effectiveness and efficiency of SLOC are proved by the experimental results in Mikolajczyk and HPatches testbed.
An efficient Actor Critic DRL Framework for Resource Allocation in Multi-cell Downlink NOMA

In this paper, a tractable framework for downlink non-orthogonal multiple access (NOMA) is proposed based on a model-free reinforcement learning (RL) approach for dynamic resource allocation in a multi-cell network structure. With the aid of actor critic deep reinforcement learning (ACDRL), we optimize the active power allocation for multi-cell NOMA systems under an online environment to maximize the long-term sum rate. To exploit the dynamic nature of NOMA, this work utilizes the instantaneous data rate for designing the dynamic reward. The state space in ACDRL contains all possible resource allocation realizations depending on a three-dimensional association among users, base stations, and sub-channels. We propose an ACDRL algorithm with this transformed state space which is scalable to handle different network loads by utilizing multiple deep neural networks. Lastly, the simulation results validate that the proposed solution for multi-cell NOMA outperforms the conventional RL, DRL algorithms, and orthogonal multiple access (OMA) schemes in terms of the evaluated long-term sum rate.
Therapeutic interventions associated with improvements in the quality of life of patients with fibromyalgia: a systematic review

Fibromyalgia is a syndrome characterized by multifaceted symptoms that negatively impact the quality of life. With greater prevalence in women, the syndrome is manifested through widespread pain, fatigue, anxiety, and depression. While different interventions and guidelines for clinical management and diagnosis have been proposed, these are fraught with limiting factors due to the heterogeneity of associated symptoms, chronicity, and therapies with significative side effects. Based on the above, the objective of this study aims to evaluate the therapeutic interventions that improve the different domains of quality of life in patients with fibromyalgia. The research was conducted through systematic searches in the PUBMED, SCOPUS, LILACS and Web of Science databases between March 1, 2020, and May 08, 2021. Articles in Portuguese, English or Spanish were considered for analysis. To verify the risk of bias in each study, the levels of evidence were judged by two independent reviewers using the Cochrane collaboration tool. Articles in Portuguese, English or Spanish were considered for analysis. The scope of this review consisted of thirteen randomized clinical trials that met the pre-established inclusion criteria. The studies reviewed included 3,339 patients with a pre-established diagnosis of fibromyalgia, 92.2% of whom were female. Overall, fifteen interventions were observed that showed results for overall QOL and its physical and mental domains. The results showed high-quality evidence with positive findings for pain, physical functioning, anxiety, and depression with pharmacological and behavioral interventions. There is high-quality evidence supporting pregabalin for overall quality of life and the physical domain (pain and function), cognitive behavior therapy, and milnacipran for the physical domain of quality of life (pain and function), and moderate-quality evidence supporting cognitive behavioral therapy for the domain psychological (anxiety and depression).
Prevalence of Fascioliasis in Livestock and Humans in Pakistan: A Systematic Review and Meta-Analysis

Fascioliasis is a parasitic infection that affects both livestock and humans. Understanding the distribution of Fasciola spp. can help the development of preventive measures to control fascioliasis. This systematic review and meta-analysis aimed to estimate the status of fascioliasis among livestock and humans in Pakistan between 2000 and 2020. Based on the selection criteria, 25 articles were selected from Google Scholar, PubMed, and Scopus. This review included 76,099 animals, including 13,738 that were positive for fascioliasis. The overall prevalence was 18.1%; it was 0.3% in humans and 20.1% in livestock. Among animal hosts, the prevalence was highest in sheep (53.5%), followed by the goats (44.9%), cows (21.3%), buffaloes (16.8%), cattle (12.7%), and humans (0.3%). Sindh had the highest prevalence at 42.7%, followed by Baluchistan (25.2%), Punjab (17.7%), Khyber Pakhtunkhwa (10.7%), and Islamabad capital territory (1.5%). In the Punjab province, sheep had the highest prevalence (65.7%); in Khyber Pakhtunkhwa, it was buffalo (15.9%); and in Baluchistan, it was cows (28.5%). The prevalence of Fasciola spp. was higher in Sindh and Baluchistan than in the other provinces. The presented results are essential for developing preventive approaches for the management of human health and minimizing economic loss in the livestock industry in Pakistan. Preventive-curative treatments two times a year followed by a prophylactic treatment at the end of the dry season are crucial throughout the areas of Pakistan that serve as hotspots for infection by Fasciola sp. For humans, regular, prioritized surveys must be performed for high-risk populations so that the real situation can be assessed and addressed in a timely manner.
Bullying toward LGBTQI + students in Australian schools: Understanding teachers’ intentions to intervene

Abstract The bullying of sexual and/or gender minority youth at school is a social violence issue that is ubiquitous in most countries. In line with evidence-based practice, teachers are consistently shown to be a critical component of success when addressing this issue; however, teachers’ preparedness to respond to sexual and/or gender motivated bullying is under researched. Utilizing components of the theory of planned behavior, a sample of 437 Australian teachers were investigated to determine whether knowledge, perceived barriers, and attitudes toward both sexual and/or gender minorities predicted teachers’ intentions to intervene when a sexual and/or gender minority student is bullied above and beyond sociodemographic factors associated with prejudice. Results of hierarchical linear regression demonstrated that teachers with more positive views of gender minorities and less traditional views related to gender ideologies were more likely to endorse higher intentions to intervene in sexual and/or gender minority motivated bullying. Findings suggested teachers’ attitudinal biases inform their professional practices when a sexual and/or gender minority student is bullied.
Electromechanical interactions in a doubly fed induction generator drivetrain

Normally, electrical and mechanical systems are designed and analysed in separate domains but, in this study, interactions between electric and mechanical elements are analysed looking for improvement in the performance of electromechanical drivetrains. The work considers a doubly fed induction generator, evaluated with a frequency analysis of the full electromechanical drivetrain developed and applied to identify how tuning gains and system parameters affect the electromechanical interactions. Analytical transfer functions are presented and validated by simulation and test results.
Background Subtraction for Accurate Palm Oil Fruitlet Ripeness Detection

Image background subtraction is an important and essential process in many computer vision applications as allows for a more effective processing of the foreground objects. Various methods have been proposed for performing background subtraction in the literature. In this study, we investigated various background subtraction to automatically identify the correct class of the foreground objects. There are only a few major producers of palm oil and Malaysia is the world’s second-largest producer and exporter of palm oil in terms of volume. In 2019, the gross domestic product (GDP) contribution from palm oil in Malaysia was estimated to be around 37.6 billion ringgit to Malaysia’s economy or at 2.7 percent of the country’s GDP. Among the many major industries, it is one of Malaysia’s primary industries, and a main agricultural export. There are various studies to automatically identify fruit ripeness, ranging from mangos to strawberries, etc. In addition, there have been some work in recent years to identify the maturity of the palm oil fruit bunches, and the use of Raman spectroscopy on individual fruitlets, etc. This study investigates the effect of background subtraction on the performance of a deep neural network to accurately identify the ripeness of palm oil fruitlets i.e. ripe, unripe and over ripe. This was compared with a feature based probabilistic approach.
An Intelligent Cardiopulmonary Training System and Adherence to Training Intensity: A Feasibility Study

Objective: Our aim was to evaluate the feasibility of our developed intelligent cardiopulmonary training system (ICTS) and of the percentage of time spent within the target HR range (%time) as an indicator of adherence to training intensity. Methods: In this noncontrolled trial, nine participants with sedentary lifestyles were recruited from the outpatient rehabilitation department of a teaching hospital. All participants received twelve 30 min sessions of cycling ergometer exercises (5 min warm up, 20 min training phase, and 5 min cool down) with the ICTS three times per week. Training intensity was determined at 60–80% heart rate reserve using cardiopulmonary exercise (CPET) pretests. During training, pedaling resistance was automatically adjusted by the ICTS to keep the user’s heart rate at the predetermined intensity range. Workload-peak and peak oxygen uptake (VO2-peak) were measured during the pretests and post-tests. We recorded the percentage of time spent within the target heart rate range (%time) during the 20 min training phase for each training session as an indicator of adherence. The correlation between %time and gains in VO2-peak was assessed. Results: After 4 weeks of training on the ICTS, workload-peak and VO2-peak significantly improved by 13.6 ± 7.2 w (mean ± SD, p = 0.008) and 1.5 ± 1.1 mL/kg/min (p = 0.011), respectively. The 12-session average %time ranged from 10.6% to 93.1% among the participants, and five participants achieved an average %time >80%. A positive correlation between average %time and training efficacy was found (rs = 0.85, p = 0.004). Conclusions: Cardiopulmonary training with an ICTS is feasible, and the percentage of time spent within the target heart rate range seems to be a reasonable indicator for monitoring training-intensity adherence.
Construction of approximate solutions to the riemann problem for two-phase flow of immiscible liquids by modifying the vanishing viscosity method

In the paper, we apply the vanishing viscosity method for an approximate solution to the Riemann problem. This approach gives the effects of the accuracy of the solution and the speed of convergence by discrediting time and spatial variables. The obtained method ensures the smoothness of the solution without taking into account the capillary pressure. The results confirm the negligible influence of cross-link conditions compared to the classical Darcy approach. The proposed solutions of the new approach are intended to improve the methods and schemes of discretization both in space and in time. This is achieved by minimizing viscosity, and discretization in space and time. These factors are of paramount importance for studying phenomena with variable saturation in the transient mode and analyzing water/oil flows and migrations in real time, since discretization in space and time affects the accuracy and convergence of calculations. Our result in the form of obtaining viscous solutions of the filtration process is interesting from a theoretical point of view. From a practical point of view, numerical modeling allows early prediction of performance. Thus, the applied aspect of using the obtained scientific result is the possibility of improving the process by taking into account the influence of phases of fluid flows
Improved soft-switching boost converter with coupled-inductor using passive EMI cancellation method

Abstract Non-isolated switching power supplies with coupled-inductor have more parasitic elements like the leakage inductance in comparison with the regular non-isolated converters. Due to the undesirable resonances between the leakage inductance and other parasitic capacitors, the conducted electromagnetic emissions increase. In order to improve electromagnetic compatibility, adopting passive or active parasitic cancellation methods can be used. In this paper, a passive cancellation circuit is combined with the converter`s coupled-inductor cell. Among the non-isolated converters, the boost converter where a lossless snubber with a coupled inductor is applied in its soft switching cell is selected to reveal the advantage of this proposed method with respect to EMC. To verify the advantage, the conducted EMI of this proposed converter is compared with the regular boost converter and boost converter with a lossless snubber. The experimental results indicate a considerable reduction in the conducted EMI levels. This proposed technique can be applied in other non-isolated topologies like buck, buck-boost, SEPIC, Ćuk and converters with tapped inductor.
Valuation of Guaranteed Maximum Price Contracts in Korea Using the Collar Option Model

This study assessed the levels of risk that contractors may be subject to while executing a GMP contract by applying a collar option model to the case study of an apartment project in Korea and identified implications for the application of GMP contracts in Korea. The payoff structure of the GMP contract was defined based on the collar option model and a profit sharing ratio calculated to evaluate the risks involved in GMP contracts. The results showed that an increase in the GMP and a decrease in the expected cost and cost range were accompanied by a decrease in the profit sharing ratio. The proposed valuation model for GMP contracts is expected to help clients and contractors in Korea negotiate reasonable contracts as it enables the contractor to utilize the proposed model as basic data, the client to evaluate the performance of the contractor, and both parties to agree a reasonable profit sharing ratio. Implementing GMP contracts with CMR is likely to have a number of positive effects on the Korean construction market. However, in order to maximize these effects, it is necessary to have the ability to evaluate cost uncertainty. Accordingly, it is very important to analyze the factors that influence cost volatility. In future work, the various factors that have an impact on the GMP must be studied to maximize the positive effects of the framework proposed in this paper. An analysis of the effect of each factor on the change in the GMP will help Korean construction companies who are attempting to introduce GMP contracts to perform their preconstruction services effectively.
Management of a Girl With Delayed Puberty and Elevated Gonadotropins

Abstract A girl presenting with delayed puberty and elevated gonadotropins may have a range of conditions such as Turner syndrome (TS), primary ovarian insufficiency (POI), and 46,XY disorders of sexual development (DSD). An organized and measured approach to investigation can help reach a timely diagnosis. Management of young people often requires specialist multidisciplinary input to address the endocrine and nonendocrine features of these complex conditions, as well as the psychological challenges posed by their diagnosis. Next-generation sequencing within the research setting has revealed several genetic causes of POI and 46,XY DSD, which may further facilitate an individualized approach to care of these young people in the future. Pubertal induction is required in many and the timing of this may need to be balanced with other issues specific to the condition (eg, allowing time for information-sharing in 46,XY DSD, optimizing growth in TS). Shared decision-making and sign-posting to relevant support groups from the outset can help empower young people and their families to manage these conditions. We describe 3 clinical vignettes of girls presenting with delayed puberty and hypergonadotropic amenorrhea and discuss their clinical management in the context of current literature and guidelines.
Robust Fixed-Time H∞ Trajectory Tracking Control for Marine Surface Vessels Based on a Self-Structuring Neural Network

In this study, a robust fixed-time H∞ trajectory tracking controller for marine surface vessels (MSVs) is proposed based on self-structuring neural network (SSNN). First, a fixed-time H∞ Lyapunov stability theorem is proposed to guarantee that the MSV closed-loop system is fixed-time stable (FTS) and the L2 gain is less than or equal to γ. This shows high accuracy and strong robustness to the approximation errors. Second, the SSNN is designed to compensate for the model uncertainties of the MSV system, marine environment disturbances, and lumped disturbances term constituted by the actuator faults (AFs). The SSNN can adjust the network structure in real time through elimination rules and split rules. This reduces the computational burden while ensuring the control performance. It is proven by Lyapunov stability that all signals in the MSV system are stable and bounded within a predetermined time. Finally, theoretical analysis and numerical simulation verify the feasibility and effectiveness of the control scheme.