Miracle-dz/UniFAR-FTUs huggingface dataset:
Stereo Matching Algorithm With Deep Learning Method Using Nvidia Platform

Autonomous vehicle has become a hot topic for researchers in recent years. One of the important sensors used in these vehicles is Stereo Cameras/Vision. Stereo vision systems are used to estimate the depth from the two cameras installed on the robots or vehicles. This method can deliver the 3D position of all objects captured in the scene at a lower cost and higher density compared to LIDAR. Recently, neural networks are vastly investigated and used in image processing problems and deep learning networks which has surpassed traditional computer vision methods specially in object recognition. In this paper, we propose to use a GPU with a new Siamese deep learning method to speed up the stereo matching algorithm. In this work, we use a high end Nvidia Platform DGX workstation to train and test our algorithm and compare the results with normal GPUs and CPUs. Based on numerical evaluation, the Nvidia DGX can train a neural network with higher input image resolution approximately 8 times faster than a normal GPU and 40 times faster than a Core i7 8 Cores CPU. Since it has the ability to train on a higher resolution the network can be trained in more iteration and results in higher accuracy.
A Sea-Surface-Zoning Method Based on Fractal Characteristics

In this paper, a criterion for sea surface zoning based on the fractal characteristics of disturbances is demonstrated. To improve radar detection performance in heavy-tailed sea clutter, a multitude of sea clutter models and corresponding optimum and suboptimum detectors have been designed in recent years. However, there are cases where these models and detectors become insufficient to describe the coexistence of noise and sea clutter. The commonly used signal-to-clutter ratio (SCR) can hardly serve as an indicator revealing which kind of disturbances dominate in a certain area since it is difficult to decide the level of SCR at which sea clutter or noise exceeds the other. Therefore, it is necessary that a set of rules reflecting essential differences between sea clutter and noise are proposed to tell areas where sea clutter dominates, areas where sea clutter and noise coexist and areas where noise dominates. Analyzing fractal characteristics of disturbances, we consider the Hurst exponent H as a feature distinguishing sea clutter and noise from each other. A modified Sigmoid function is employed to model the variation in H with range bins, and the derivative of the function helps to formulate a set of rules for sea surface zoning.
Non-Iterative Methods for the Extraction of the Single-Diode Model Parameters of Photovoltaic Modules: A Review and Comparative Assessment

The extraction of the photovoltaic (PV) model parameters remains to this day a long-standing and popular research topic. Numerous methods are available in the literature, widely differing in accuracy, complexity, applicability, and their very nature. This paper focuses on the class of non-iterative parameter extraction methods and is limited to the single-diode PV model. These approaches consist of a few straightforward calculation steps that do not involve iterations; they are generally simple and easy to implement but exhibit moderate accuracy. Seventeen such methods are reviewed, implemented, and evaluated on a dataset of more than one million measured I-V curves of six different PV technologies provided by the National Renewable Energy Laboratories (NREL). A comprehensive comparative assessment takes place to evaluate these alternatives in terms of accuracy, robustness, calculation cost, and applicability to different PV technologies. For the first time, the irregularities found in the extracted parameters (negative or complex values) and the execution failures of these methods are recorded and are used as an assessment criterion. This comprehensive and up-to-date literature review will serve as a useful tool for researchers and engineers in selecting the appropriate parameter extraction method for their application.
Numerical Modeling of Thermo-Mechanically Induced Stress in Substrates for Droplet-Based Additive Manufacturing Processes

Within the scope of additive manufacturing (AM) methods, a large number of popular fabrication techniques involve high-temperature droplets being targeted to a substrate for deposition. In such methods, an “ink” to be deposited is tailor-made to fit the desired application. Concentrated stresses are induced on the substrate in such procedures. A numerical simulation framework that can return quantitative and qualitative insights regarding the mechanical response of the substrate is proposed in this paper. A combined smoothed particle hydrodynamics (SPH)-finite element (FE) model is developed to solve the governing coupled thermo-mechanical equations, for the case of Newtonian inks. We also highlight the usage of consistent SPH formulations in order to recover first-order accuracy for the gradient and Laplacian operators. This allows one to solve the heat-equation more accurately in the presence of free-surfaces. The proposed framework is then utilized to simulate a hot droplet impacting a flat substrate.
Effects of Galactomannan Oligosaccharides on Growth Performance, Mycotoxin Detoxification, Serum Biochemistry, and Hematology of Goats Fed Mycotoxins-Contaminated Diets

This study was conducted to investigate the protective effects of mycotoxin adsorbent galactomannan oligosaccharides (GMOS) on growth performance, fermentation parameters, mycotoxins residues, serum biochemistry and oxidative stress parameters of the goats. The in vitro test indicated that 0.05% GMOS outperformed yeast cell wall (YCW) and montmorillonite (MMT) in aflatoxins absorption. Then 20 3-month-old Xiangdong black goats (15.0 ± 1.9 kg) were randomly divided into two dietary treatments for the animal test. The control group (CON group) was fed a multi-mycotoxins contaminated diet, whereas the experimental group (GMOS group) received multi-mycotoxins contaminated diet plus 0.05% GMOS. The trail lasted for 60 days, with 12 days of adaptation period and 48 days of formal experiment period. There were no treatment effects (P > 0.10) on growth performance, serum antioxidant capacity and activities of serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), and alkaline phosphatase (ALP). The concentrations of zearalenone in the rumen were lower (P < 0.05) in the GMOS group. GMOS significantly reduced (P < 0.05) propionate concentration in the cecum, resulting in a rise (P < 0.01) in acetate/propionate ratio in GMOS as compared to CON. Goats of GMOS exhibited considerably greater (P < 0.05) levels of creatine kinase but lower (P = 0.02) levels of creatinine than CON. Compared with CON, GMOS supplementation significantly increased (P < 0.05) platelet count (PLT), platelet volume distribution width (PDW), and platelet hematocrit (PCT), while decreased (P < 0.05) albumin content (ALB). The 0.05% GMOS protected goats in ruminal fermentation parameters, mycotoxins residues and serum biochemistry. Moreover, GMOS had no adverse effect on goat health. To our knowledge, this is the first report of GMOS in small ruminants. These findings suggested the feasibility of dietary GMOS as a health-maintaining addictive in goat diets.
Influence of a single hemodialysis on left ventricular energy loss and wall shear stress in patients with uremic cardiomyopathy assessed with vector flow mapping

Background The influence of hemodialysis (HD) on hydromechanics of the left ventricle has not been reported. This study evaluated the left ventricular summation of energy loss (EL-SUM), average energy loss (EL-AVE), and wall shear stress (WSS) before and after HD using vector flow mapping (VFM) in patients with end-stage renal disease (ESRD). Methods We prospectively recruited 40 patients receiving long-term HD and excluded those with structural cardiac disease. Echocardiography was performed before and within 24 hours after HD. Conventional echocardiographic parameters, summation, and average energy loss (EL-SUM, EL-AVE, EL-base, EL-mid and EL-apex), and WSS in each segment were compared. Results A total of 40 patients with uremia were recruited. After HD, left ventricular EL-AVE-total, and EL-SUM-total decreased significantly in the early diastolic [29.43 (18.76 to 46.28) vs. 17.70 (10.76 to 95.60) N/(m2·s) and 12 (6 to 17) vs. 5 (3 to 11) e−2 J; P<0.001, respectively], mid-diastolic [17.07 (10.38 to 24.35) vs. 10.29 (5.86 to 16.30) N/(m2·s) and 7 (3 to 10) vs. 4 (2 to 6) e−2 J; P<0.001, respectively], and early systolic [17.82 (12.79 to 24.77) vs.14. 90 (10.23 to 19.05) N/(m2·s) P=0.011 and 8 (5 to 11) vs. 5 (4 to 8) e−2 J, P=0.002, respectively] phases. It was revealed that HD did not change EL-AVE-total and EL-SUM-total in the late diastolic and late systolic phases. The EL-AVE decreased after HD in the left ventricular (LV) basal [50.70 (24.19 to 77.92) vs. 26.00 (11.50 to 47.68) N/(m2·s); P<0.001] and mid [15.52 (8.88 to 20.90) vs. 9.47 (6.41 to 14.21) N/(m2·s); P=0.001] segments during the early diastolic phase; in the LV basal [18.64 (10.33 to 29.80) vs. 10.25 (6.98 to 19.43) N/(m2·s); P<0.001), mid (15.70 (9.93 to 23.08) vs. 9.99 (6.03 to 16.25) N/(m2·s); P<0.001), and apical [9.78 (4.06 to 15.77) vs. 4.52 (3.14 to 10.36) N/(m2·s); P=0.001) segments during the mid-diastolic phase; in the LV mid [14.34 (8.34 to 23.88) vs. 9.36 (6.48 to 17.05) N/(m2·s); P=0.013] and apex [11.25 (6.37 to 21.88) vs. 6.60 (5.33 to 12.17) N/(m2·s); P=0.016] segments during the late diastolic phase; and in the apical [10.28 (6.05 to 17.01) vs. 7.59 (3.73 to 13.20) N/(m2·s) P=0.025] segment during the early systolic phase. After HD, WSS significantly reduced in the mid-diastolic [0.51 (0.32 to 0.69) vs. 0.38 (0.30 to 0.46) Pa, P=0.001] and early systolic [0.60 (0.45 to 0.81) vs. 0.57 (0.42 to 0.68) Pa, P=0.029] phases. There was no change in WSS during the early diastolic, late diastolic, and late systolic phases. Conclusions After HD, EL and WSS of LV decrease during the systolic and diastolic phases. The VFM can reflect the LV hemodynamics in patients undergoing HD under different fluid loads.
Epidemiology of Δ8THC-Related Carcinogenesis in USA: A Panel Regression and Causal Inferential Study

The use of Δ8THC is increasing at present across the USA in association with widespread cannabis legalization and the common notion that it is “legal weed”. As genotoxic actions have been described for many cannabinoids, we studied the cancer epidemiology of Δ8THC. Data on 34 cancer types was from the Centers for Disease Control Atlanta Georgia, substance abuse data from the Substance Abuse and Mental Health Services Administration, ethnicity and income data from the U.S. Census Bureau, and cannabinoid concentration data from the Drug Enforcement Agency, were combined and processed in R. Eight cancers (corpus uteri, liver, gastric cardia, breast and post-menopausal breast, anorectum, pancreas, and thyroid) were related to Δ8THC exposure on bivariate testing, and 18 (additionally, stomach, Hodgkins, and Non-Hodgkins lymphomas, ovary, cervix uteri, gall bladder, oropharynx, bladder, lung, esophagus, colorectal cancer, and all cancers (excluding non-melanoma skin cancer)) demonstrated positive average marginal effects on fully adjusted inverse probability weighted interactive panel regression. Many minimum E-Values (mEVs) were infinite. p-values rose from 8.04 × 10−78. Marginal effect calculations revealed that 18 Δ8THC-related cancers are predicted to lead to a further 8.58 cases/100,000 compared to 7.93 for alcoholism and −8.48 for tobacco. Results indicate that between 8 and 20/34 cancer types were associated with Δ8THC exposure, with very high effect sizes (mEVs) and marginal effects after adjustment exceeding tobacco and alcohol, fulfilling the epidemiological criteria of causality and suggesting a cannabinoid class effect. The inclusion of pediatric leukemias and testicular cancer herein demonstrates heritable malignant teratogenesis.
The Validity of the 2-Point Method for Assessing the Force-Velocity Relationship of the Knee Flexors and Knee Extensors: The Relevance of Distant Force-Velocity Testing

Over the past decade, force-velocity (F-v) profiling has emerged as a promising tool for assessing neuromuscular capacity to design individually tailored interventions in diverse populations. To date, a limited number of studies have addressed the optimization of the linear method for measuring F-v profiles of single-joint isokinetic movements. We aimed to simplify the measurement of knee extension (KE) and knee flexion (KF) isokinetic tasks by evaluating the most appropriate combination of two velocities (i.e., the 2-point method). Twenty-two healthy participants (11 males and 11 females) were included in the study. Isokinetic peak torque was measured at nine angular velocities (30-60-90-120-150-180-210-240-300°/s) and under isometric conditions (at 150° and 120° of KF for KE, and KF, respectively). Maximal theoretical force (F0), maximal theoretical velocity (v0), slope of the relationship (Sfv) and maximal theoretical power (Pmax) were derived from the linear F-v profiles of KE and KF and compared between the 9-point method and all possible combinations (36 in total) of the 2-point methods. The F-v profiles obtained from nine points were linear for KE (R2 = 0.95; 95% CI = 0.94–0.96) and KF (R2 = 0.93; 95% CI = 0.90–0.95), with F0 underestimating isometric force. Further analyses revealed great to excellent validity (range: ICCs = 0.89–0.99; CV = 2.54%–4.34%) and trivial systematic error (range: ES = −0.11–0.24) of the KE 2-point method when force from distant velocities (30°/s, 60°/s or 90°/s combined with 210°/s, 240°/s or 300°/s) was used. Similarly, great to excellent validity and trivial systematic error of the KF 2-point method for F0 and Pmax (range: ICC = 0.90–0.96; CV = 2.94%–6.38%; ES = −0.07–0.14) were observed when using the previously described combinations of velocities. These results suggest that practitioners should consider using more distant velocities when performing simplified isokinetic 2-point single-joint F-v profiling. Furthermore, the F-v profile has the potential to differentiate between the mechanical properties of knee extensors and flexors and could therefore serve as a potential descriptor of performance.
Accurate Micromanipulation of Optically Induced Dielectrophoresis Based on a Data-Driven Kinematic Model

The precise control method plays a crucial role in improving the accuracy and efficiency of the micromanipulation of optically induced dielectrophoresis (ODEP). However, the unmeasurable nature of the ODEP force is a great challenge for the precise automatic manipulation of ODEP. Here, we propose a data-driven kinematic model to build an automatic control system for the precise manipulation of ODEP. The kinematic model is established by collecting the input displacement of the optical pattern and the output displacements of the manipulated object. Then, the control system based on the model was designed, and its feasibility and control precise were validated by numerical simulations and actual experiments on microsphere manipulation. In addition, the applications of ODEP manipulation in two typical scenarios further demonstrated the feasibility of the designed control system. This work proposes a new method to realize the precise manipulation of ODEP technology by establishing a kinematic model and a control system for micromanipulation, and it also provides a general approach for the improvement of the manipulation accuracy of other optoelectronic tweezers.
A Completion of the S–invariance Technique by means of Fixed Point Algorithms

In this paper we transform bounded Petri net systems into transition systems in order to have a bridge between Petri nets and temporal logic. We then use structural knowledge of the Petri nets (S–invariants, traps) to accelerate fixed point calculations in the transition systems. This technique comprises solutions of such problems which are not solvable by S–invariance technique. By a new concept for a very compact representation of net markings, the ordered natural decision diagrams (ONDDs), we gain a further considerable acceleration of the fixed point calculations. The ONDDs are a generalization of the ordered binary decision diagrams (OBDDs) due to Bryant.
Diagnostic Classification Models for a Mixture of Ordered and Non-ordered Response Options in Rating Scales

When developing ordinal rating scales, we may include potentially unordered response options such as “Neither Agree nor Disagree,” “Neutral,” “Don’t Know,” “No Opinion,” or “Hard to Say. ” To handle responses to a mixture of ordered and unordered options, Huggins-Manley et al. (2018) proposed a class of semi-ordered models under the unidimensional item response theory framework. This study extends the concept of semi-ordered models into the area of diagnostic classification models. Specifically, we propose a flexible framework of semi-ordered DCMs that accommodates most earlier DCMs and allows for analyzing the relationship between those potentially unordered responses and the measured traits. Results from an operational study and two simulation studies show that the proposed framework can incorporate both ordered and non-ordered responses into the estimation of the latent traits and thus provide useful information about both the items and the respondents.
Spaceflight-Associated Changes of snoRNAs in Peripheral Blood Mononuclear Cells and Plasma Exosomes—A Pilot Study

During spaceflight, astronauts are exposed to various physiological and psychological stressors that have been associated with adverse health effects. Therefore, there is an unmet need to develop novel diagnostic tools to predict early alterations in astronauts’ health. Small nucleolar RNA (snoRNA) is a type of short non-coding RNA (60–300 nucleotides) known to guide 2′-O-methylation (Nm) or pseudouridine (ψ) of ribosomal RNA (rRNA), small nuclear RNA (snRNA), or messenger RNA (mRNA). Emerging evidence suggests that dysregulated snoRNAs may be key players in regulating fundamental cellular mechanisms and in the pathogenesis of cancer, heart, and neurological disease. Therefore, we sought to determine whether the spaceflight-induced snoRNA changes in astronaut’s peripheral blood (PB) plasma extracellular vesicles (PB-EV) and peripheral blood mononuclear cells (PBMCs). Using unbiased small RNA sequencing (sRNAseq), we evaluated changes in PB-EV snoRNA content isolated from astronauts (n = 5/group) who underwent median 12-day long Shuttle missions between 1998 and 2001. Using stringent cutoff (fold change > 2 or log2-fold change >1, FDR < 0.05), we detected 21 down-and 9—up-regulated snoRNAs in PB-EVs 3 days after return (R + 3) compared to 10 days before launch (L-10). qPCR validation revealed that SNORA74A was significantly down-regulated at R + 3 compared to L-10. We next determined snoRNA expression levels in astronauts’ PBMCs at R + 3 and L-10 (n = 6/group). qPCR analysis further confirmed a significant increase in SNORA19 and SNORA47 in astronauts’ PBMCs at R + 3 compared to L-10. Notably, many downregulated snoRNA-guided rRNA modifications, including four Nms and five ψs. Our findings revealed that spaceflight induced changes in PB-EV and PBMCs snoRNA expression, thus suggesting snoRNAs may serve as potential novel biomarkers for monitoring astronauts’ health.
A Motion Planning and Tracking Framework for Autonomous Vehicles Based on Artificial Potential Field Elaborated Resistance Network Approach

This paper presents a novel motion planning and tracking framework for automated vehicles based on artificial potential field (APF) elaborated resistance approach. Motion planning is one of the key parts of autonomous driving, which plans a sequence of movement states to help vehicles drive safely, comfortably, economically, human-like, etc. In this paper, the APF method is used to assign different potential functions to different obstacles and road boundaries; while the drivable area is meshed and assigned resistance values in each edge based on the potential functions. A local current comparison method is employed to find a collision-free path. As opposed to a path, the vehicle motion or trajectory should be planned spatiotemporally. Therefore, the entire planning process is divided into two spaces, namely the virtual and actual. In the virtual space, the vehicle trajectory is predicted and executed step by step over a short horizon with the current vehicle speed. Then, the predicted trajectory is evaluated to decide if the speed should be kept or changed. Finally, it will be sent to the actual space, where an experimentally validated Carsim model controlled by a model predictive controller is used to track the planned trajectory. Several case studies are presented to demonstrate the effectiveness of the proposed framework.
Paws on the Street: Neighborhood-Level Concentration of Households with Dogs and Urban Crime

Abstract:The formative work of Jane Jacobs underscores the combination of "eyes on the street" and trust between residents in deterring crime. Nevertheless, little research has assessed the effects of residential street monitoring on crime due partly to a lack of data measuring this process. We argue that neighborhood-level rates of households with dogs captures part of the residential street monitoring process core to Jacobs' hypotheses and test whether this measure is inversely associated with property and violent crime rates. Data from a large-scale marketing survey of Columbus, OH, USA residents (2013; n = 43,078) are used to measure census block group-level (n = 595) rates of households with dogs. Data from the Adolescent Health and Development in Context study are used to measure neighborhood-level rates of trust. Consistent with Jacobs' hypotheses, results indicate that neighborhood concentration of households with dogs is inversely associated with robbery, homicide, and, to a less consistent degree, aggravated assault rates within neighborhoods high in trust. In contrast, results for property crime suggest that the inverse association of dog concentration is independent of levels of neighborhood trust. These associations are observed net of controls for neighborhood sociodemographic characteristics, temporally lagged crime, and spatial lags of trust and dog concentration. This study offers suggestive evidence of crime deterrent benefits of local street monitoring and dog presence and calls attention to the contribution of pets to other facets of neighborhood social organization.