Miracle-dz/UniFAR-FTUs huggingface dataset:
Fuzzy ARTMAP-Based Fast Object Recognition for Robots Using FPGA

Fast object recognition and classification is highly important when handling operations with robots. This article shows the design and implementation of an invariant recognition machine vision system to compute a descriptive vector called the Boundary Object Function (BOF) using the FuzzyARTMAP (FAM) Neural Network. The object recognition machine is integrated in the Zybo Z7-20 module that includes reconfigurable FPGA hardware and a RISC processor. Object encoding, description and prediction is carried out rapidly compared to the processing time devoted to video capture at the camera’s frame rate. Benefiting from parallel computing, we calculated the object’s centroid and boundary points while acquiring the progressive image frame; all that was done with the intention of readying it for neural processing. The remaining time was devoted to recognising the object, this caused low latency (1.47 ms). Our test-bed also included TCP/IP communication to send/receive part location for grasping operations with an industrial robot to evaluate the approach. Results demonstrate that the hardware integration of the video sensor, image processing, descriptor generator, and the ANN classifier for cognitive decision on a single chip can increase the speed and performance of intelligent robots designed for smart manufacturing.
Accelerated Aging Experiment of IGBT under Pulsed Power and Reliability Studies

Pulsed power technology gives full play to the characteristics of high pulses in the form of short pulses, and gradually occupies a certain position in industrial applications. It needs to ensure stability and durability while ensuring that the working parameters are met, the switching performance is particularly important. , therefore, the reliability study of IGBT power module becomes an inevitable requirement for reliability evaluation in engineering. This article mainly introduces the experimental method of the accelerated aging experiment of IGBT under pulsed power conditions. The electro-thermal simulation is carried out through PLECS and the low-power experimental platform is built to obtain experimental data. Finally, the experimental data is analyzed, and the change rule of the failure characteristic parameters with the aging process under the pulse power condition and the IGBT failure standard different from the typical operating condition are obtained.
Is Elastography Useful in Assessing Necrotizing Enterocolitis in Rats?

Background: Necrotizing enterocolitis (NEC) is among the most common and destructive diseases in the neonatal period. Imaging methods are important in the early diagnosis and treatment of such diseases. Ultrasound elastography (USE) is a fast and non-invasive imaging technique that deals with the viscoelastic properties of tissues. Objectives: The purpose of this study is to assess the effectiveness of USE, which determines tissue stiffness with grayscale and colored images, as an imaging tool in the diagnosis and treatment of NEC. Materials and Methods: Sixteen newborn Wistar albino gender rats were separated into two groups including eight rats each. The first group (G-I) was taken as a control group and was not exposed to any intervention. The second group (G-II) was exposed to 100% CO2 for 5 minutes and 4°C for 10 minutes. All these interventions were applied twice per day for 4 days. We observed elastographic data at 24, 48, and 96 hours. All rats were sacrificed on the fourth day. The combination of gray-scale US and elastography was performed by a 4-13 MHz with an average of 12 MHz bandwidth linear probe in Esaote Ultrasonography Systems, MyLab60 model, produced in Geneva, Italy; with ElaXto imaging application. Results: Statistically significant differences were detected in elastosonography ratios of terminal ileum at 24, 48, and 96 hours (P < 0.05). As ischemia period in NEC was prolonged, elastosonographic ratios of intestinum increased significantly. Conclusion: It was found that USE is a reliable technique with superior features in the assessment of the terminal ileum in the neonatal age group. It is due to its wide image window and better assessment of tissue stiffness with gray scale and color image. It has been observed that the USE technique is helpful in the diagnosis.
UTILIZATION OF BINARY BLENDS OF LIQUID NATURAL RUBBER AND POLYVINYL ACETATE IN EMULSION PAINT

Studies were conducted on blends of liquid natural rubber (LNR) and polyvinyl acetate (PVAc). The two polymers were characterized based on their physicochemical properties, and used in paint production. Results obtained showed that viscometric measurement and density of the polymers did not differ much. Five paints of different compositions labeled; Paint 1 (100% PVAc), Paint 2 (100% LNR), Paint 3 (75% LNR: 25% PVAc), Paint 4 (50% PVAc: 50% LNR), and Paint 5 (25% LNR: 75% PVAc) using standard emulsion paint formulation and method of production were employed. The paint samples were subjected to quality test. Most of the emulsion paint showed good quality test when compared by the Standard Organisation of Nigeria (SON). Paint 1 had an excellent viscosity and adhesion when compared with Paint 2 and other samples. Also, Paint 5 recorded 22.0poise for viscosity and 0.68kgf for adhesion when compared with other paint blends. This shows that, emulsion paint formulated blends of LNR/PVAc with percentage composition 25% LNR; 75%PVAc exhibited best performance characteristics in terms of test conducted. The results suggest that LNR and PVAc are compatible as binders in emulsion paint production. Therefore, LNR/PVAc blends could be used as binder in the coating industry as an alternative to PVAc binder based emulsion paint.
Examining Landscape-Scale Fuel and Terrain Controls of Wildfire Spread Rates Using Repetitive Airborne Thermal Infrared (ATIR) Imagery

The objectives of this study are to evaluate landscape-scale fuel and terrain controls on fire rate of spread (ROS) estimates derived from repetitive airborne thermal infrared (ATIR) imagery sequences collected during the 2017 Thomas and Detwiler extreme wildfire events in California. Environmental covariate data were derived from prefire National Agriculture Imagery Program (NAIP) orthoimagery and USGS digital elevation models (DEMs). Active fronts and spread vectors of the expanding fires were delineated from ATIR imagery. Then, statistical relationships between fire spread rates and landscape covariates were analyzed using bivariate and multivariate regression. Directional slope is found to be the most statistically significant covariate with ROS for the five fire imagery sequences that were analyzed and its relationship with ROS is best characterized as an exponential growth function (adj. R2 max = 0.548, min = 0.075). Imaged-derived fuel covariates alone are statistically weak predictors of ROS (adj. R2 max = 0.363, min = 0.002) but, when included in multivariate models, increased ROS predictability and variance explanation (+14%) compared to models with directional slope alone.
Optimizing Forward‐Looking Missile‐Borne BSAR Imaging With Convolutional Neural Network

During the guidance of the missile, the target needs to be positioned in real time. The detonating missile will look forward to the target area during the flight, and the imaging distance becomes closer as the missile approaches the target. The image quality of forward‐looking missile‐borne bistatic synthetic aperture radar (FM‐BSAR) deteriorates rapidly when the detonator enters a rapid dive stage. One of the most serious problem is the azimuth defocusing, the more deviated from the center of the imaging aperture, the more defocusing. In this paper, a method of using convolutional neural network (CNN) to accomplish image focusing is proposed to improve the image quality of BSAR. The advantage of this method is to focus the image accurately with inaccurate imaging parameters. The experimental results show that the proposed method can accurately locate and focus the defocusing points, which has practical significance for improving the BSAR close‐range imaging effect of high‐maneuvering platform.
Is Item Imputation Always Better? An Investigation of Wave-Missing Data in Growth Models

ABSTRACT Questionnaire data present challenges, as a missing item of a multi-item scale would lead to a total missing scale. A researcher applying multiple imputation to an incomplete multi-item questionnaire can impute the incomplete items prior to computing scale scores or impute the scale score entirely. Methodologist have favored item-level imputation because it greatly enhances precision in comparison to scale-level imputation; however, this benefit in precision might not translate into longitudinal data studies where entire questionnaire batteries are missing. We investigated the performance of item- and scale-level imputation model and found that item-level imputation did not produce a precision advantage in estimating any of the growth model parameters and scale-level showed better precision in estimating the slope variance parameter than item-level imputation.
Curricular Analytics to Characterize Educational Trajectories in High-Failure Rate Courses That Lead to Late Dropout

Late dropout is one of the most pressing challenges currently facing higher education, and the process that each student follows to arrive at that decision usually involves several academic periods. This work presents a curricular analytics approach at the program level, to analyze how educational trajectories of undergraduate students in high-failure rate courses help to describe the process that leads to late dropout. Educational trajectories (n = 10,969) of high-failure rate courses are created using Process Mining techniques, and the results are discussed based on established theoretical frameworks. Late dropout was more frequent among students who took a stopout while having high-failure rate courses they must retake. Furthermore, students who ended in late dropout with high-failure rate courses they must retake had educational trajectories that were on average shorter and less satisfactory. On the other hand, the educational trajectories of students who ended in late dropout without high-failure rate courses they must retake were more similar to those of students who graduated late. Moreover, some differences found among ISCED fields are also described. The proposed approach can be replicated in any other university to understand the educational trajectories of late dropout students from a longitudinal perspective, generating new knowledge about the dynamic behavior of the students. This knowledge can trigger improvements to the curriculum and in the follow-up mechanisms used to increase student retention.
Prognostic effects of arterial carbon dioxide levels in patients hospitalized into the cardiac intensive care unit for acute heart failure.

AIMS Although both hypercapnia and hypocapnia are common in acute heart failure (AHF) patients, routine assessment of arterial blood gas is not recommended. Additionally, no association between hypercapnia and increased mortality has been found, and the prognostic value of hypocapnia in AHF patients remains to be elucidated. In this observational study, we aimed to investigate the relationship between partial pressure of arterial carbon dioxide (PaCO2), especially low PaCO2, and long-term mortality in AHF patients. METHODS AND RESULTS Acute heart failure patients hospitalized in the cardiac intensive care unit of our institution between 2007 and 2011 were screened. All eligible patients were divided into two groups based on the inflection point (i.e. 31.0 mmHg) of the 3-knot cubic spline curve of the hazard ratio (HR), with a PaCO2 of 40 mmHg as a reference. The association between PaCO2 levels and all-cause mortality was assessed using Cox proportional hazards regression models. Among 435 patients with a median follow-up of 1.8 years, 115 (26.4%) died. Adjusted analysis with relevant variables as confounders indicated that PaCO2 <31 mmHg was significantly associated with increased all-cause mortality [HR 1.71, 95% confidence interval (CI) 1.05-2.79; P = 0.032]. When PaCO2 was considered as a continuous variable, the lower was the log-transformed PaCO2, the greater was the increased risk of mortality (HR 0.71, 95% CI 0.52-0.96; P = 0.024). CONCLUSIONS In AHF patients, lower PaCO2 at admission was associated with increased long-term mortality risk.
Closing the loop between wearable technology and human biology: a new paradigm for steering neuromuscular form and function

Wearable technologies such as bionic limbs, robotic exoskeletons and neuromodulation devices have long been designed with the goal of enhancing human movement. However, current technologies have shown only modest results in healthy individuals and limited clinical impact. A central element hampering progress is that wearable technologies do not interact directly with tissues in the composite neuromuscular system. That is, current wearable systems do not take into account how biological targets (e.g. joints, tendons, muscles, nerves) react to mechanical or electrical stimuli, especially at extreme ends of the spatiotemporal scale (e.g. cell growth over months or years). Here, we outline a framework for ‘closing-the-loop’ between wearable technology and human biology. We envision a new class of wearable systems that will be classified as ‘steering devices’ rather than ‘assistive devices’ and outline the suggested research roadmap for the next 10–15 years. Wearable systems that steer, rather than assist, should be capable of delivering coordinated electro-mechanical stimuli to alter, in a controlled way, neuromuscular tissue form and function over time scales ranging from seconds (e.g. a movement cycle) to months (e.g. recovery stage following neuromuscular injuries) and beyond (e.g. across ageing stages). With an emphasis on spinal cord electrical stimulation and exosuits for the lower extremity, we explore developments in three key directions: (a) recording neuromuscular cellular activity from the intact moving human in vivo, (b) predicting tissue function and adaptation in response to electro-mechanical stimuli over time and (c) controlling tissue form and function with enough certainty to induce targeted, positive changes in the future. We discuss how this framework could restore, maintain or augment human movement and set the course for a new era in the development of bioprotective wearable devices. That is, devices designed to directly respond to biological cues to maintain integrity of underlying physiological systems over the lifespan.
Germination Parameters of Selected Summer Weeds: Transferring of the AlertInf Model to Other Geographical Regions

Effective weed management depends on correct control timing, which depends on seedling emergence dynamics. Since soil temperature and soil moisture are the two main factors that determine weed germination, the hydrothermal time model can be used to predict their emergence. The aim of this study was to estimate the base temperature (Tb) and base water potential (Ψb) for the germination of Chenopodium album, Amaranthus retroflexus, Setaria pumila, and Panicum capillare collected from fields in continental Croatia and then to compare these values with those of Italian populations embedded in the AlertInf model. Germination tests were performed at seven constant temperatures (ranging from 4 to 27 °C) and eight water potentials (0.00–1.00 MPa). The estimated Tb and Ψb were 3.4 °C and −1.38 MPa for C. album, 13.9 °C and −0.36 MPa for A. retroflexus, 6.6 °C and −0.71 MPa for S. pumila, and 11.0 °C and −0.87 MPa for P. capillare, respectively. According to the criterion of overlap of the 95% confidence intervals, only the Tb of C. album and the Ψb of A. retroflexus of the Croatian and Italian populations were similar. Further field experiments should be conducted to monitor the weed emergence patterns of C. album and calibrate the AlerInf equation parameters.
Convective rain cell characteristics and scaling in climate projections for Germany

Extreme convective precipitation is expected to increase with global warming. However, the rate of increase and the understanding of contributing processes remain highly uncertain. We investigated characteristics of convective rain cells like area, intensity, and lifetime as simulated by a convection‐permitting climate model in the area of Germany under historical (1976–2005) and future (end‐of‐century, RCP8.5 scenario) conditions. To this end, a tracking algorithm was applied to 5‐min precipitation output. While the number of convective cells is virtually similar under historical and future conditions, there are more intense and larger cells in the future. This yields an increase in hourly precipitation extremes, although mean precipitation decreases. The relative change in the frequency distributions of area, intensity, and precipitation sum per cell is highest for the most extreme percentiles, suggesting that extreme events intensify the most. Furthermore, we investigated the temperature and moisture scaling of cell characteristics. The temperature scaling drops off at high temperatures, with a shift in drop‐off towards higher temperatures in the future, allowing for higher peak values. In contrast, dew point temperature scaling shows consistent rates across the whole dew point range. Cell characteristics scale at varying rates, either below (mean intensity), at about (maximum intensity and area), or above (precipitation sum) the Clausius–Clapeyron rate. Thus, the widely investigated extreme precipitation scaling at fixed locations is a complex product of the scaling of different cell characteristics. The dew point scaling rates and absolute values of the scaling curves in historical and future conditions are closest for the highest percentiles. Therefore, near‐surface humidity provides a good predictor for the upper limit of for example, maximum intensity and total precipitation of individual convective cells. However, the frequency distribution of the number of cells depending on dew point temperature changes in the future, preventing statistical inference of extreme precipitation from near‐surface humidity.
Optimal sports betting strategies in practice: an experimental review

We investigate the most popular approaches to the problem of sports betting investment based on modern portfolio theory and the Kelly criterion. We define the problem setting, the formal investment strategies and review their common modifications used in practice. The underlying purpose of the reviewed modifications is to mitigate the additional risk stemming from the unrealistic mathematical assumptions of the formal strategies. We test the resulting methods using a unified evaluation protocol for three sports: horse racing, basketball and soccer. The results show the practical necessity of the additional risk-control methods and demonstrate their individual benefits. Particularly, an adaptive variant of the popular ‘fractional Kelly’ method is a very suitable choice across a wide range of settings.
The impact of Covid-19 on the mental health of professional footballers

ABSTRACT The Covid-19 pandemic has had huge ramifications on professional football. This commentary focuses on the impact of the pandemic on the mental health of professional footballers. Specifically, footballers within the English Premier League, English Football League, FA Women’s Super League and FA Women’s Championship. This commentary considers a holistic approach to mental health, the environment of professional football, and the impact of career transitions and critical moments on mental health. The intention is to stimulate discussion and further research of mental health and wellbeing within professional football. This paper considers the impact of Covid-19 and makes recommendations for professional football clubs to develop a holistic mental health strategy. We recommend that professional clubs increase the level of emotional support for professional footballers, and that this should not be a temporary measure due to the pandemic. Clubs should develop a long-term strategy to encourage players to seek emotional support.
Increased zinc supply does not inhibit cadmium accumulation by rice (Oryza sativa L.)

ABSTRACT Rice (Oryza sativa L.) grown on cadmium (Cd)-contaminated soils has caused health problems in Asian subsistence rice farmers. For other crops, normal co-contaminant zinc (Zn) inhibits the increased uptake of Cd. We used a multi-chelator-buffered nutrient solution to characterize the interaction of Zn and Cd in uptake-translocation of Cd in “Lemont” rice. The activity of free Zn2+ varied from 10−7.6 to 10−5.2 M, while free Cd2+ held constant at 10−10.7 M. Zinc activity 10−5.6 M and higher was phytotoxic to rice, resulting in severe chlorosis, reduced growth, and increased Cd transport to shoots. In contrast to previous studies with wheat, lettuce, and spinach, free Zn2+ maintained at adequate to sub-phytotoxic levels (10−7.6 to 10−6.1) did not inhibit Cd uptake by rice. The inability of Zn to inhibit Cd uptake by rice is a key factor in Cd risk from zinc-lead mine waste contaminated soil compared with other crops.
Effect of Strategic Outsourcing Approaches on The Performance of Manufacturing Companies Listed at The Nairobi Security Exchange, Kenya

Purpose: This study sought to establish the effect of strategic outsourcing approaches on the performance of manufacturing. Methodology: A descriptive survey design was adopted, informed by the relatively small population of the listed manufacturing and allied companies, which doubled as the target population of the study. A structured and closed- ended questionnaire was used to collect primary data, administered by drop and pick a method. Total of (72) strategic managers drawn from the nine manufacturing firms were involved in the study. Data collected was quantitatively scrutinized based on research objectives and presented in form of tables and charts for interpretation. The data was then be analyzed through descriptive and inferential statistics supported by the statistical package for social sciences (SPSS), version 22. Regression analysis was done to ascertain the effect of strategic outsourcing approaches on performance. The response rate of the study was 92%. Results and conclusion: The findings of the study showed that strategic professional outsourcing, strategic manufacturing outsourcing, strategic business process outsourcing and strategic project outsourcing have a positive relationship with performance of performance of the manufacturing companies listed at the Nairobi Security Exchange. The results of the regression analysis revealed there is a significant positive relationship between the dependent variable and the independent variable. The independent variables reported R-value of . 805 indicating that there is a perfect relationship between a dependent variable and independent variables. R square value of 0.647 means that 64.7% of the corresponding variation in performance of manufacturing companies listed at the Nairobi Security Exchange can be explained or predicted by (strategic professional outsourcing, strategic manufacturing outsourcing, strategic business process outsourcing and strategic project outsourcing) which indicated that the model fitted the study data. The results of the regression analysis revealed that there was a significant positive relationship between the dependent variable and independent variable at (β = 0.647), p=0.000 <0.05). Unique contribution to theory, practice and policy: Finally, the study commends that manufacturing companies listed at the Nairobi Security Exchange embrace the various strategic outsourcing approaches as a way to improve their performance. Equally, the study recommends similar studies be carried out in other industries across the country and in abroad to ascertain if the same results can be obtained and generalized.