Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of the Slaughter Method on the Hygienic Quality of Beef Cattle Meat and Animal Welfare Biomarkers

Simple Summary The objective of this study was to investigate the influence of the slaughter method on the microbiology of the meat and the animal welfare physiological indicators for beef cattle. Three slaughter procedures were compared, as follows: regular slaughter (with a penetrative captive bolt), halal slaughter, and halal slaughter with a non-penetrative captive bolt (reversible stunning accepted by some halal religious authorities). We conclude that the halal slaughter with stunning showed the best results for microbial counts (enterobacteria and coliforms) and for the considered biomarkers of animal welfare, lactate dehydrogenase, glucose, and creatine kinase; however, this slaughter type gave the highest amount of cortisol. Abstract The main objective of this research was to carry out a comparative study between different types of slaughter in beef cattle with and without stunning. In addition, the hygienic quality of the obtained meat was determined through microbiological analysis and the animal welfare at the time of slaughtering was assessed by means of physiological parameters. A total of 52 blood samples collected at the slaughterhouse during slaughter (10 for each type of slaughter: regular, halal, and halal with stunning; 10 at the time of resting; and 12 from rotating box slaughter) were analysed for physiological parameters indicating animal welfare status, namely, glucose, cortisol, lactate dehydrogenase (LDH) and creatine kinase (CK). In addition, the meat from 30 of the above animals was analysed for aerobic mesophilic bacteria, enterobacteria and coliforms. Moreover, a radiological study of the possible skull damage due to the non-penetrative captive bolt used at the time of stunning in the halal rite slaughter was carried out. A significance difference (p < 0.05) in the microbiological counts per type of slaughter was observed. It was proven that the amounts of glucose, LDH, CK, and cortisol in plasma were influenced (p < 0.05) by the type of slaughter. The halal rite slaughter using stunning with a non-penetrative captive bolt resulted in the best hygienic quality of meat and obtained the lowest values for all animal welfare biomarkers.
Upregulation of Sarcolemmal Hemichannels and Inflammatory Transcripts with Neuromuscular Junction Instability during Lower Limb Unloading in Humans

Simple Summary Skeletal muscles need to be continually active. Physical inactivity, reduced gravity, such as when humans are in space, or aging itself can cause neuromuscular frailty and weakness, causing major diseases. Comprehension of the molecular mechanisms that cause skeletal muscle atrophy can be beneficial to limit such processes and improve human health in different conditions: allowing humans to go into space for a long period, to be inactive for a long period or to age in a better way. When skeletal muscles are chronically inactive, within 5 days and more after 10 days, there is an increase of two molecules, called agrin fragments and neurofilaments, which become highly present in the blood, suggesting neuromuscular instability. The process is accompanied by changes in the membranes of single muscle fibres, the unit that forms our skeletal muscles. They could potentially start to lose important electrolytes and molecules and gradually promote a deleterious process. It has been proved in mice that blocking the appearance of these molecules, called hemichannels, can limit the severity of the loss of muscle mass. Interestingly, these hemichannels also appear during inactivity in humans, opening a possible application for human health and space missions. Abstract Human skeletal muscle atrophy and a disproportionate force loss occur within a few days of unloading in space and on Earth, but the underlying mechanisms are not fully understood. Disruption of neuromuscular junction homeostasis has been proposed as one of the possible causes. Here, we investigated the potential mechanisms involved in this neuromuscular disruption induced by a 10-day unilateral lower limb suspension (ULLS) in humans. Specifically, we investigated hemichannels’ upregulation, neuromuscular junction and axonal damage, neurotrophins’ receptor downregulation and inflammatory transcriptional signatures. Biomarkers were evaluated at local and systemic levels. At the sarcolemmal level, changes were found to be associated with an increased expression of connexin 43 and pannexin-1. Upregulation of the inflammatory transcripts revealed by deep transcriptomics was found after 10 days of ULLS. The destabilisation of the neuromuscular junction was not accompanied by changes in the secretion of the brain-derived neurotrophic factor and neurotrophin-4, while their receptor, BDNF/NT growth factors receptor (TrkB), decreased. Furthermore, at 5 days of ULLS, there was already a significant upregulation of the serum neurofilament light chain concentration, an established clinical biomarker of axonal injury. At 10 days of ULLS, other biomarkers of early denervation processes appeared. Hence, short periods of muscle unloading induce sarcolemmal hemichannels upregulation, inflammatory transcripts upregulation, neuromuscular junction instability and axonal damage.
A Deep-Ensemble-Learning-Based Approach for Skin Cancer Diagnosis

Skin cancer is one of the widespread diseases among existing cancer types. More importantly, the detection of lesions in early diagnosis has tremendously attracted researchers’ attention. Thus, artificial intelligence (AI)-based techniques have supported the early diagnosis of skin cancer by investigating deep-learning-based convolutional neural networks (CNN). However, the current methods remain challenging in detecting melanoma in dermoscopic images. Therefore, in this paper, we propose an ensemble model that uses the vision of both EfficientNetV2S and Swin-Transformer models to detect the early focal zone of skin cancer. Hence, we considerthat the former architecture leads to greater accuracy, while the latter model has the advantage of recognizing dark parts in an image. We have modified the fifth block of the EfficientNetV2S model and have included the Swin-Transformer model. Our experiments demonstrate that the constructed ensemble model has attained a higher level of accuracy over the individual models and has also decreased the losses as compared to traditional strategies. The proposed model achieved an accuracy score of 99.10%, a sensitivity of 99.27%, and a specificity score of 99.80%.
Dietary Antioxidant Capacity Indices are Negatively Correlated to LDL-Oxidation in Adults

Introduction Former research studies have demonstrated controversial associations between dietary indices and oxidative stress biomarkers including oxidized low-density lipoprotein (ox-LDL) and malondialdehyde (MDA). So, in this cross-sectional study, we aimed to assess the association of dietary total antioxidant capacity (DTAC), oxidative balance score, and phytochemical index (PI) with ox-LDL/MDA in a healthy adult population of Shiraz, Iran. Methods 236 individuals participated in this cross-sectional study. DTAC, OBS, and PI were calculated using a 168-item food frequency questionnaire (FFQ), which was previously validated in Iran. We measured ox-LDL and MDA in blood samples of the participants using commercially existing kits. Crude and adjusted models of linear regression were used to evaluate the relation of dietary indices with ox-LDL and MDA. Results There was a significant association between ox-LDL and DTAC in both crude (β = −1.55; 95% CI: −2.53, −0.58; P-trend = 0.002) and adjusted (β = −1.65 95% CI: −2.66, −0.64; P-trend = 0.001) models. Also, a negative association was observed between ox-LDL and PI in the crude (β = −1.26 95% CI: −2.33, −0.29; P-trend = 0.01) and adjusted (β = −1.36 95% CI: −2.38, −0.34; P-trend = 0.01) models. Conclusion Results of this study showed that DTAC and PI were inversely associated with ox-LDL as markers of lipid peroxidation. But no correlations were seen between MDA and dietary antioxidant indices.
AN UNREFLECTED U-235 CRITICAL ASSEMBLY

An unreflected, spherical U235 critical assembly has been in operation at the Los Alamos Scientific Laboratory since August, 1951. A remotely controlled mechanical system is used to assemble subcritical components of the sphere, and reactivity is adjusted with U235 control rods. The maximum power level during sustained operation is about 1 kw. Investigations with the assembly include studies of the neutron spectrum, observation of the changes of reactivity produced by inserting foreign materials into the assembly, and determination of parameters such as the temperature coefficient of reactivity. In addition, experiments at reactivities above prompt critical have been carried out. The assembly has also been used as a source of short, high-intensity bursts of neutrons in the study of delayed neutrons following fission.
A Real-Time Registration Algorithm of UAV Aerial Images Based on Feature Matching

This study aimed to achieve the accurate and real-time geographic positioning of UAV aerial image targets. We verified a method of registering UAV camera images on a map (with the geographic location) through feature matching. The UAV is usually in rapid motion and involves changes in the camera head, and the map is high-resolution and has sparse features. These reasons make it difficult for the current feature-matching algorithm to accurately register the two (camera image and map) in real time, meaning that there will be a large number of mismatches. To solve this problem, we used the SuperGlue algorithm, which has a better performance, to match the features. The layer and block strategy, combined with the prior data of the UAV, was introduced to improve the accuracy and speed of feature matching, and the matching information obtained between frames was introduced to solve the problem of uneven registration. Here, we propose the concept of updating map features with UAV image features to enhance the robustness and applicability of UAV aerial image and map registration. After numerous experiments, it was proved that the proposed method is feasible and can adapt to the changes in the camera head, environment, etc. The UAV aerial image is stably and accurately registered on the map, and the frame rate reaches 12 frames per second, which provides a basis for the geo-positioning of UAV aerial image targets.
The effects of microstructural defects on hot spot formation in cyclotrimethylenetrinitramine-polychlorotrifluoroethylene energetic aggregates

Shock initiation due to hot spot formation has been investigated in energetic aggregates subjected to dynamic thermo-mechanical loading conditions. A dislocation-density based crystalline plasticity and specialized finite-element formulations were used to predict hot spot formation due to dynamic thermo-mechanical loading conditions in cyclotrimethylenetrinitramine-polymer energetic aggregates. The effects of grain boundary misorientations, porosity, grain morphology, dislocation densities, and crystal-binder interactions were coupled with adiabatic plasticity heating, thermal decomposition, and dissipated heat to analyze hot spot formation. The predictions indicate that hot spot formation occurs when temperatures become unbounded in localized regions between voids. The time to hot spot formation decreases with increases in dynamic pressure loads, which is consistent with experimental results.
A Multiple-Modes Resonant Switched Capacitor DC/DC Converter With Variable Voltage Ratios

High step-down dc/dc converters with high efficiency and high power density are widely used in data centers, dc distribution grids and hybrid electric vehicles. In this article, a new resonant switched capacitor converter is proposed, which can not only realize high step-down conversion, but also operate in multiple-modes to achieve various voltage ratios. The duty cycle can be allocated to one-half and one-third, enabling the converter to operate in double-mode and triple-mode accordingly. In addition, the state of the basic resonant cell can be switched between series and parallel, which enriches the operating modes, and thus allowing the converter to achieve different voltage ratios. Furthermore, the principle and strategy of switching between operating modes with different voltage ratios and switching between operating modes with same voltage ratio are presented. With the mode switching strategy, this converter can operate in the optimal mode over the wide voltage range and the full load range, thus achieves high efficiency over the full operating range. Finally, five operating modes are selected to verify the feasibility and the correctness of the theoretical analysis
Robotic medium and thick plate welding planning based on laser vision

For the problems of positioning deviation and poor welding quality in the welding of medium and heavy plates [1] by robot [2], a robot medium and heavy plate welding system [3] based on laser vision is introduced, and a multilayer and multi-pass welding method [4] which can be used for different angles and multiple passes is proposed. The robot and computer are connected through PLC [5]. After the laser sensor [6] collects the weld information, the computer generates the welding plan through algorithm processing, and uploads the relevant information to the robot to realize the welding of the weld [7]. The results show that this method can realize the welding of multiple welds with different angles and directions, and has a good application prospect.
Localized Multi-Site Knee Bioimpedance as a Predictor for Knee Osteoarthritis Associated Pain Within Older Adults During Free-Living

The drastic increase in the aging population has increased the prevalence of osteoarthritis in the United States. The ability to monitor symptoms of osteoarthritis (such as pain) within a free-living environment could improve understanding of each person's experiences with this disease and provide opportunities to personalize treatments specific to each person and their experience. In this work, localized knee tissue bioimpedance and self-reports of knee pain were collected from older adults (<inline-formula><tex-math notation="LaTeX">$N=20$</tex-math></inline-formula>) with and without knee osteoarthritis over 7 days of free-living to evaluate if knee tissue bioimpedance is associated with persons' knee pain experience. Within the group of persons' with knee osteoarthritis increases in 128 kHz per-length resistance and decreases in 40 kHz per-length reactance were associated with increased probability of persons having active knee pain (<inline-formula><tex-math notation="LaTeX">$p=0.038$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$p=0.044$</tex-math></inline-formula>).
Silicon-based, fractal metamaterial structure for IR broadband absorption

Over a century ago, the study of blackbody radiation led to the development of quantum mechanics. A blackbody is a perfect absorber, absorbing all the electromagnetic light that illuminates it. There is no radiation passing through it, and none is reflected. Now, “bodies” with high absorption qualities are very important in many disciplines of research and technology. Perfect absorbers, for example, can be utilized as photodetectors, thermal pictures, microbolometers, an d thermal photovoltaic solar energy conversion. The Mid-infrared (MIR) wavelength spectrum has numerous advantages in a variety of applications. One of these uses is chemical and biological detection. In this paper, a metasurface mid -IR absorber based on the fractal technology of a doped silicon geometry resonator to realize wideband cross-fractal formation is introduced. The structure exhibits a broadband absorption within a wide range of IR wavelength spectrum extending from 3 to 9 μm. The structure was based on the Sierpinski carpet where different building blocks were simulated to reach the highest absorption. It is shown that light coupling over a broad wavelength range to the proposed fractal metamaterial absorber structure is due to multiple resonance mechanisms at different wavelengths. The propo sed structure is CMOS-compatible. Moreover, this proposed design opens the door to the development of new silicon -based absorbers for different applications such as energy harvesting and photodetection.
A Step-by-Step High-Order Extended Kalman Filter for Fractional-order System

Fractional-order systems (FOS) are characterized by strong nonlinearity, which puts forward higher criteria for state estimation. This work suggests a step-by-step high order extended Kalman filter (SHEKF) for the FOS to address this issue. Based on fractional calculus, the state model and measurement model of FOS are established, in which the nonlinear parts of both models are defined as implicit variables. Following the discovered implicit variables by Kalman filter, the linear form of the state model and measurement model are constructed. Finally, the state variables of FOS are estimated based on linearized models and prior information. The efficacy and high state estimate accuracy of the proposed method for determining the state of FOS are shown by simulation results.
Emerging memristive neurons for neuromorphic computing and sensing

ABSTRACT Inspired by the principles of the biological nervous system, neuromorphic engineering has brought a promising alternative approach to intelligence computing with high energy efficiency and low consumption. As pivotal components of neuromorphic system, artificial spiking neurons are powerful information processing units and can achieve highly complex nonlinear computations. By leveraging the switching dynamic characteristics of memristive device, memristive neurons show rich spiking behaviors with simple circuit. This report reviews the memristive neurons and their applications in neuromorphic sensing and computing systems. The switching mechanisms that endow memristive devices with rich dynamics and nonlinearity are highlighted, and subsequently various nonlinear spiking neuron behaviors emulated in these memristive devices are reviewed. Then, recent development is introduced on neuromorphic system with memristive neurons for sensing and computing. Finally, we discuss challenges and outlooks of the memristive neurons toward high-performance neuromorphic hardware systems and provide an insightful perspective for the development of interactive neuromorphic electronic systems. GRAPHICAL ABSTRACT
On the application of Particle Swarm Optimization strategies on Scholte-wave inversion

SUMMARY We investigate different aspects concerning the application of swarm intelligence optimization to the inversion of Scholte-wave phase-slowness frequency (p–f) spectra with respect to shear wave velocity structure. Besides human influence due to the dependence on a priori information for starting models and interpretation of p–f spectra as well as noise, the model resolution of the inversion problem is strongly influenced by the multimodality of the misfit function. We thus tested the efficiency of global, stochastic optimization approaches with focus on swarm intelligence methods that can explore the multiple minima of the misfit function. A comparison among different PSO schemes by applying them to synthetic Scholte-wave spectra led to a hybrid of Particle Swarm Optimization and Downhill Simplex providing the best resolution of inverted shear wave velocity depth models. The results showed a very low spread of best fitting solutions of 7 per cent in shear wave velocity and an average of 9 per cent for noisy synthetic data and a very good fit to the true synthetic model used for computation of the input data. To classify this method we also compared the probability of finding a good fit in synthetic spectra inversion with that of Evolutionary Algorithm, Simulated Annealing, Neighbourhood Algorithm and Artificial Bee Colony algorithm. Again the hybrid optimization scheme showed its predominance. The usage of stochastic algorithms furthermore allowed a new way of misfit definition in terms of dispersion curve slowness residuals making the inversion scheme independent on Scholte-wave mode identification and allowing joint inversion of fundamental mode and higher mode information. Finally we used the hybrid optimization scheme and the misfit calculation for the inversion of 2-D shear wave velocity profiles from two locations in the North- and Baltic Sea. The models show acceptable resolution and a very good structural correlation to high resolution reflection seismic data.
A Bidirectional Guided Filter Used for RGB-D Maps

The red-green-blue-depth (RGB-D) cameras are widely used in the fields of robotic spray painting, packaging, and tracking. However, the quality of the depth maps of RGB-D maps is relatively low. Guided filters utilizing the color image as a guide map is a common method to deal with these problems. However, the noise in guidance will make the filtering output contains unexpected noise that does not contain before filtering. In this article, based on the classical guided filter, a bidirectional guided filter is proposed to filter the filtering input and the guidance simultaneously. The basic equations are proposed and the filter kernel is derived. The properties of the proposed bidirectional guided filter, such as edge-preserving filtering property, insensitivity to the noise of guidance, and filtering effects on guidance, are investigated. Four different groups of experiments are performed to further verify the effectiveness of the proposed method. The classical guided filter and the bidirectional guided filter are compared to verify that the proposed bidirectional guided filter can reduce the impact of the noise of the guidance; and the bidirectional guided filter and the box mean filter are compared to verify the filtering effect on guidance of the proposed bidirectional guided filter.