Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality attributes of different marinated oven-grilled pork neck meat

ABSTRACT Whereas herbs/spices serve as natural preservatives, and thermal processing makes animal meat products edible, combining them should complement each other. Additionally, the application of oven grilling to meat products continues to increase in popularity. However, there is a paucity of relevant published information specific to different marinated oven-grilled pork neck meat. Therefore, the quality attributes of different marinated oven-grilled pork neck meat were investigated, which involved chemical (pH, thiobarbituric acid reactive substance [TBARS], 2,2′-azinobis(3-ethylbenzothiaziline-6-sulfonate) [ABTS], 1,1-diphenyl-2-pierylhydrazy [DPPH], ferric reducing antioxidant power [FRAP]), physical (cooking weight loss, L*a*b* color, and textural cutting force), as well as organoleptic (sensory: flavor, appearance, tenderness, taste, and off-flavor; texture: hardness, chewiness, gumminess, graininess, and greasiness) aspects. In particular, the pork neck meat was procured from a porcine farm in Poland. Different marinated variants comprised constituent 0.5, 1, and 1.5% quantities of cranberry pomace (CP), grape pomace (GP), and Baikal skullcap (BS) that subsequently incorporated either African spice (AS) or industrial marinade/pickle (IM). Results showed decreases in ABTS, DPPH, FRAP, and TBARS in some marinated oven-grilled pork neck meat samples, alongside pH variations by difference that seemingly associated with increasing concentrations of either CP, BS, or GP, which might not always coincide with L*a*b* color trends as AS and IM were incorporated. Despite the many resemblances (p > .05), the sensory aspects fluctuated as textural chewiness, gumminess, and hardness increased in some samples, more evident when incorporating AS compared to IM. Overall, oven-grilling promises to moderate the range values of key quality attributes of different marinated pork neck meat samples in this study.
State Estimation in Partially Observable Power Systems via Graph Signal Processing Tools

This paper considers the problem of estimating the states in an unobservable power system, where the number of measurements is not sufficiently large for conventional state estimation. Existing methods are either based on pseudo-data that is inaccurate or depends on a large amount of data that is unavailable in current systems. This study proposes novel graph signal processing (GSP) methods to overcome the lack of information. To this end, first, the graph smoothness property of the states (i.e., voltages) is validated through empirical and theoretical analysis. Then, the regularized GSP weighted least squares (GSP-WLS) state estimator is developed by utilizing the state smoothness. In addition, a sensor placement strategy that aims to optimize the estimation performance of the GSP-WLS estimator is proposed. Simulation results on the IEEE 118-bus system show that the GSP methods reduce the estimation error magnitude by up to two orders of magnitude compared to existing methods, using only 70 sampled buses, and increase of up to 30% in the probability of bad data detection for the same probability of false alarms in unobservable systems The results conclude that the proposed methods enable an accurate state estimation, even when the system is unobservable, and significantly reduce the required measurement sensors.
A New Image-Based Temperature Prediction Method

The hearth temperature is an important index to measure the condition of blast furnace (BF). A good and reasonable hearth temperature can maintain the stable production of BF, which is a direct guarantee to realize the longevity and efficiency of BF. Therefore, an image-based multiple rank matrix regression (MRMR) temperature prediction method is proposed to study the change of tuyere raceway temperature. This method takes matrix as the input of the model and considers the spatial position information of the matrix elements. According to the intrinsic property of the projection vectors, the relevant constraints are applied to avoid the overfitting problem. Finally, the prediction performance of the model is validated by using BF data.
Extraction of key geometric parameters from segmented masonry arch bridge point clouds

Masonry arch bridges constitute the majority of the European bridge stock. Most of these bridges were constructed in the 19th century and feature a wide range of geometric characteristics. Since construction drawings rarely exist, the first step in the assessment of these bridges is the characterisation of their in-situ geometry, which may involve significant geometric distortions. In recent years, LIDAR devices have been widely used by bridge owners due to their ability to remotely and rapidly collect point cloud data. To enable the engineering assessment practice to benefit from this data, this research uses the recently developed deep learning (DL) neural network BridgeNet to autonomously segment masonry bridge point clouds into different components. Due to the limited availability of 3D point clouds, BridgeNet is trained using a synthetic multi-span masonry arch bridge dataset; the network is then tested on real arch bridge point clouds. By fitting appropriate primitive shapes to bridge component point clouds using Random Consensus Sampling (RANSAC) techniques the bridge geometry is effectively characterised by a few parameters.
Afterslip of the Mw 8.3 2015 Illapel Earthquake Imaged Through a Time‐Dependent Inversion of Continuous and Survey GNSS Data

We use continuous and survey GNSS data to image the spatial and temporal evolution of afterslip during the 2 months following the Mw 8.3 2015 Illapel earthquake. Our approach solves for the incremental daily slip at the subduction interface using nonnegative least squares with spatial and temporal Laplacian regularization constraints. We find that afterslip developed at three specific areas at the megathrust, surrounding the coseismic rupture. In addition, well resolved afterslip also occurs within the coseismic rupture area that experienced ∼4 m of seismic slip. Our afterslip model shows striking correlations with the spatial distribution of aftershocks and repeating earthquakes. We capture the local afterslip triggered by a Mw 6.8 and two 6.9 aftershocks that ruptured downdip and north of the coseismic rupture, respectively. The latter ones were possibly triggered by the afterslip that developed north of the rupture. We also find a pulse of enhanced aseismic slip lasting a few days south of the rupture that spatially and temporally correlates with a seismicity burst. We finally find that areas of enhanced afterslip spatially correlates with areas having experienced regular seismic swarms observed during the years prior to the Illapel earthquake. This correlation supports the view of localized fluid high pore pressure areas behaving aseismically and surrounding a highly locked asperity, preventing the seismic rupture to propagate into them.
Water demands of permitted and unpermitted cannabis cultivation in Northern California

Illicit water use for irrigated agriculture can have substantial impacts on the environment and complicates water management decision-making. Water demand for illicit cannabis farming in California has long been considered a threat to watershed health, yet an accounting of cannabis irrigation has remained elusive, thereby impeding effective water policy for the state’s nascent legal cannabis industry. Using data obtained from both permitted and unpermitted cultivation operations, the current study applies novel water-use models to cannabis farms in Northern California to estimate their cumulative and relative water footprints. Our results indicated substantial variation in total water extraction volumes for cannabis farming between watersheds and that most cannabis water use was concentrated in a subset of watersheds, rather than evenly spread across the landscape. Water extraction volumes for unpermitted cannabis were consistently greater than permitted cannabis in the dry season, when streams are most vulnerable to impacts from water diversions. Results from scenario modeling exercises indicated that if all existing unpermitted farms were to become permitted and comply with regulations that prohibit surface water diversions in the dry season, nearly one third (34 of 115) of the study watersheds would experience a 50% reduction in dry season water extraction. In comparison, modest expansion of off-stream storage by all cannabis farms could reduce dry season extraction by 50% or greater in more than three quarters (96 of 115) of study watersheds. Combining diversion limits with enhanced storage could achieve dry season extraction reductions of 50% or greater in 100 of 115 watersheds. Our findings suggest that efforts to address the environmental impacts of unpermitted cultivation should focus on watersheds with greatest water demands and that programs that support expansion of off-stream storage can be helpful for reducing pressures on the environment and facilitating the transition of unpermitted farms to the regulated market.
Solar Wind Protons Forming Partial Ring Distributions at Comet 67P

We present partial ring distributions of solar wind protons observed by the Rosetta spacecraft at comet 67P/Churyumov‐Gerasimenko. The formation of ring distributions is usually associated with high activity comets, where the spatial scales are larger than multiple ion gyroradii. Our observations are made at a low‐activity comet at a heliocentric distance of 2.8 AU on 19 April 2016, and the partial rings occur at a spatial scale comparable to the ion gyroradius. We use a new visualization method to simultaneously show the angular distribution of median energy and differential flux. A fitting procedure extracts the bulk speed of the solar wind protons, separated into components parallel and perpendicular to the gyration plane, as well as the gyration velocity. The results are compared with models and put into context of the global comet environment. We find that the formation mechanism of these partial rings of solar wind protons is entirely different from the well‐known partial rings of cometary pickup ions at high‐activity comets. A density enhancement layer of solar wind protons around the comet is a focal point for proton trajectories originating from different regions of the upstream solar wind. If the spacecraft location coincides with this density enhancement layer, the different trajectories are observed as an energy‐angle dispersion and manifest as partial rings in velocity space.
Effects of magnesium-modified biochar on soil organic carbon mineralization in citrus orchard

In order to investigate the carbon sequestration potential of biochar on soil, citrus orchard soils with a forest age of 5 years was taken as the research object, citrus peel biochar (OBC) and magnesium-modified citrus peel biochar (OBC-mg) were selected as additive materials, and organic carbon mineralization experiments were carried out in citrus orchard soil. OBC and OBC-Mg were applied to citrus orchard soils at four application rates (0, 1, 2, and 4%), and incubated at a constant temperature for 100 days. Compared with CK, the cumulative mineralization of soil organic carbon decreased by 5.11% with 1% OBC and 2.14% with 1% OBC-Mg. The application of OBC and OBC-Mg significantly increased the content of soil organic carbon fraction, while the content of soil organic carbon fraction was higher in OBC-Mg treated soil than in OBC treated soil. Meanwhile, the cumulative mineralization of soil organic carbon was significantly and positively correlated with the activities of soil catalase, urease and sucrase. The enzyme activities increased with the cumulative mineralization of organic carbon, and the enzyme activities of the OBC-Mg treated soil were significantly higher than those of the OBC treated soil. The results indicated that the OBC-Mg treatment inhibited the organic carbon mineralization in citrus orchard soils and was more favorable to the increase of soil organic carbon fraction. The Mg-modified approach improved the carbon sequestration potential of biochar for citrus orchard soils and provided favorable support for the theory of soil carbon sink in orchards.
Ultrahigh resolution of calixarene negative resist in electron beam lithography

A nonpolymer material, calixarene derivative (hexaacetate p‐methnylcalix[6]arene) was tested as a high‐resolution negative resist under an electron beam lithography process. It showed under 10‐mm resolution with little side roughness and high durability to halide plasma etching. A sub‐10‐nm Ge quantum wire was perfectly etched off without defects. Such a performance is suitable for nanoscale device processes.
Research on 3D LiDAR Point Cloud Matching Localization Method

In 3D laser SLAM, the laser point cloud matching accuracy plays a decisive role in map building and localization. In order to better analyze the point cloud matching accuracy of LiDAR.In this paper, an experimental platform is built for two different point cloud matching algorithms commonly used, the nearest point iterative algorithm ICP and the normal distribution transform algorithm NDT. And the experiments are conducted in the experimental field to obtain the relative and absolute positional errors. The experimental results show that the localization accuracy of NDT is higher than that of ICP, and the robustness of NDT is significantly higher than that of ICP especially at the corner.
Exploiting uncalibrated stereo on a UAV platform

Uncalibrated stereo imagery experimental and analytical results are presented for path planning and navigation. An Army Research and Development Engineering Command micro-size UAV was outfitted with two commercial cameras and flown over varied landscapes. Polaris Sensor Technologies processed the data post flight with an image correspondence algorithm of their own design. Stereo disparity (depth) was computed despite a quick assembly, image blur, intensity saturation, noise and barrel distortion. No camera calibration occurred. Disparity maps were computed at a processing rate of approximately 5 seconds per frame to improve perception. Disparity edges (treeline to ground, voids and plateaus) were successfully observed and confirmed to be properly identified. Despite the success of localizing this disparity edges sensitivity to saturated pixels, lens distortion and defocus were strong enough to overwhelm more subtle features such as the contours of the trees, which should be possible to extract using this algorithm. These factors are being addressed. The stereo data is displayed on a flat panel 3D display well suited for a human machine interface in field applications. Future work will entail extraction of intelligence from acquired data and the overlay of such data on the 3D image as displayed.
Social media charity campaigns and pro-social behavior. Evidence from the Ice Bucket Challenge

Social media play a relevant role in shaping social attitudes and economic behaviors of individuals. One of the first very well-known examples of social media campaign is the Ice Bucket Challenge (IBC), a charity campaign that went viral on social networks in August 2014 aiming at collecting money for the research on amyotrophic lateral sclerosis (ALS). We rely on UK longitudinal data to investigate the causal impact of the Ice Bucket Challenge on pro-social behaviors. In detail, this study shows that having been exposed to the IBC increases the probability of donating money, and it increases the amount of donating money among those who donate at most £100. We also find that exposure to the IBC has increased the probability of volunteering and the level of interpersonal trust. However, all these results, but the one on the intensive margins of donations, have a short duration, limited to less than one year, supporting the prevalent consensus that social media campaigns may have only short-term effects.
Enhanced Teleoperation Interfaces for Multi-Second Latency Conditions: System Design and Evaluation

Adding human cognitive skills to planetary exploration through remote teleoperation can lead to more valuable scientific data acquisition. Still, even small amounts of latency can significantly affect real-time operations, often leading to compromised robot safety, goal overshoot, and high levels of cognitive workload. Thus, novel operational strategies are necessary to cope with these effects. This paper proposes three augmented teleoperation interfaces that allow the user to operate a robot subject to 3 seconds of latency: (1) Avatar-Aided Interface (AAI), a semi-autonomous approach based on a virtual element; (2) Predictive Interface (PI), an approach with direct control and predictive elements; and (3) Hybrid Interface (HI), where operators can easily switch between PI and AAI. We conducted a systematic within-subject experiment to evaluate the proposed interfaces in a realistic virtual environment with frequent traction losses. The user study compared AAI and PI to a Control Interface (CI), which did not display any augmented elements. The main results of this comparison showed that: (1) AAI led to a significant reduction in workload and a significant increase in usability and robot safety; (2) the use of the PI caused a significant increase in path length, indicating that operators overshoot their goals more often with this approach; (3) PI and AAI had lower reported effort; and (4) AAI is more flexible and effortless than PI and CI. Finally, during traction loss periods, PI and AAI had shortcomings that led to confusion from the operator, showing the need to integrate uncertainty measures in future interface design.
Simple but novel test method for quantitatively comparing robot mapping algorithms using SLAM and dead reckoning

This article presents a comparative study between a well-known SLAM (Simultaneous Localization and Mapping) algorithm, called Gmapping, and a standard Dead-Reckoning algorithm; the study is based on experimental results of both approaches by using a commercial skid-based turning robot, P3DX. Five main base-case scenarios are conducted to evaluate and test the effectiveness of both algorithms. The results show that SLAM outperformed the Dead Reckoning in terms of map-making accuracy in all scenarios but one, since SLAM did not work well in a rapidly changing environment. Although the main conclusion about the excellence of SLAM is not surprising, the presented test method is valuable to professionals working in this area of mobile robots, as it is highly practical, and provides solid and valuable results. The novelty of this study lies in its simplicity. The simple but novel test method for quantitatively comparing robot mapping algorithms using SLAM and Dead Reckoning and some applications using autonomous robots are being patented by the authors in U.S. Patent Application Nos. 13/400,726 and 13/584,862.
New Advances in Metabolic Syndrome, from Prevention to Treatment: The Role of Diet and Food

The definition of metabolic syndrome (MetS) has undergone several changes over the years due to the difficulty in establishing universal criteria for it. Underlying the disorders related to MetS is almost invariably a pro-inflammatory state related to altered glucose metabolism, which could lead to elevated cardiovascular risk. Indeed, the complications closely related to MetS are cardiovascular diseases (CVDs) and type 2 diabetes (T2D). It has been observed that the predisposition to metabolic syndrome is modulated by complex interactions between human microbiota, genetic factors, and diet. This review provides a summary of the last decade of literature related to three principal aspects of MetS: (i) the syndrome’s definition and classification, pathophysiology, and treatment approaches; (ii) prediction and diagnosis underlying the biomarkers identified by means of advanced methodologies (NMR, LC/GC-MS, and LC, LC-MS); and (iii) the role of foods and food components in prevention and/or treatment of MetS, demonstrating a possible role of specific foods intake in the development of MetS.
Constraints on r-process conditions from beta-decay properties far off stability and r-abundances

The measured beta -decay properties of the 'waiting-point' nuclei 130Cd and 80Zn, together with improved shell model predictions of T1/2 and Pn-values for their experimentally unknown N approximately=82 and 50 neighbours, can be directly related to the observed r-abundances in the A approximately=130 and 80 abundance peaks. Based on this result, new constraints are given on the stellar conditions under which the r-process has operated.
Theoretical research of chalcogenide waveguide CH4 sensor based on lift‐off method

Chalcogenide (ChG) waveguide gas sensor with good application prospect at mid‐infrared band can be fabricated by the lift‐off method with a simple process. However, the inclined sidewalls of the core layer caused by lift‐off are unavoidable. The TE and TM mode ChG rectangular waveguides were optimized and the influence of inclined angle on the sensing performance was studied. The performance of TE mode ChG waveguide is more affected by the fabrication error of the inclined angle. The relative variation of the external confinement factor and limit of detection of the TM mode waveguide are 10 and 23 times smaller than that of the TE mode waveguide. This work provides guidance for the design, fabrication, and application of the ChG waveguide gas sensors fabricated by the lift‐off method.
The Use of Stress Cardiovascular Imaging in Pediatric Population

Although not frequent in the pediatric population, ischemia could occur in children due to several congenital and acquired disease. Stress imaging is key for the non-invasive evaluation of myocardial abnormalities and perfusion defect in this clinical setting. Moreover, beyond ischemia assessment, it can provide complementary diagnostic and prognostic information in valvular heart disease and cardiomyopathies. When performed using cardiovascular magnetic resonance, it could detect, in addition, myocardial fibrosis and infarction, increasing the diagnostic yield. Several imaging modalities are currently available for the evaluation of stress myocardial perfusion. Advances in technologies have also increased the feasibility, safety and availability of these modalities in the pediatric age group. However, despite the established role of stress imaging and its increasing use in daily clinical practice, there are currently no specific guidelines, and little data are available in the literature on this topic. The aim of this review is to summarize the most recent evidence on pediatric stress imaging and its clinical application with a focus on the advantages and limitations of each imaging modality currently available.
Dynamic Zero Current Method to Reduce Measurement Error in Low Value Resistive Sensor Array for Wearable Electronics

One advantage of a resistive sensor array (RSA) with shared rows (M) and shared columns (N) is the reduced number of wires from M × N + 1 to M + N which can greatly lessen the complexity and burden on wearable electronic systems. However, the drawback is the crosstalk current effect between adjacent elements, which will lead to high measurement error. Although several solutions have been reported, they mainly focus on RSAs with high resistance (≥100 Ω). There is a lack of research that addresses RSAs with resistor values below 100 Ω. Here, we introduce a new circuit design named the dynamic zero current method (DZCM) to further decrease the measurement error. From the low value RSA test with ideal resistors, the DZCM exhibits lower error than the zero potential method (ZPM). In the case of the error variation ratio of amplifier offset voltage, the DZCM has a 4%/mV (row) to 7%/mV (column) ratio, while the ZPM has an almost 25%/mV (row) to 45%/mV (column) ratio and it increases with array size.