Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of Direct-Fed Lactobacillus Species on Milk Production and Methane Emissions of Dairy Cows

Simple Summary Mitigating methane emissions from ruminants requires strategies that are sustainable and acceptable to both consumers and producers. Direct-fed microbials could meet these requirements. Forty Holstein-Friesian cows were randomly allocated one of two treatments, a control or control plus a direct-fed microbial (MYLO®—a mixture of Lactobacillus species; Terragen Biotech Pty Ltd., Coolum Beach, Queensland, Australia). Adding the direct-fed microbial had no significant effect on feed intake, milk yield, feed conversion efficiency, or methane parameters. While these results are contrary to our expectations, all were numerically in a favorable direction. Given there are reports that diet and dose rate may impact the size of any effect, we recommend a dose–response study be undertaken using a basal diet that is commonly used in pasture-based dairy systems. Abstract Using direct-fed microbials to mitigate enteric methane emissions could be sustainable and acceptable to both consumers and producers. Forty lactating, multiparous, Holstein-Friesian cows were randomly allocated one of two treatments: (1) a base of ad libitum vetch (Vicia sativa) hay and 7.0 kg DM/d of a grain mix, or (2) the basal diet plus 10 mL of MYLO® (Terragen Biotech Pty Ltd., Coolum Beach, Queensland, Australia) delivering 4.17 × 108 cfu of Lactobacillus per mL. Neither feed intake (25.4 kg/d vs. 24.8 kg/d) nor milk yield (29.9 vs. 30.3 kg/d) were affected by treatment. Feed conversion efficiency was not affected by treatment when expressed on an energy-corrected milk basis (1.15 vs. 1.18 kg/kg DMI). Neither methane yield (31.6 vs. 31.1 g/kg DMI) nor methane intensity (27.1 vs. 25.2 g/kg energy corrected milk) were affected by treatments. While these results are contrary to our expectations and not significant, all were numerically in a favorable direction. Given there are reports that diet and dose rate may impact the size of any effect, we recommend a dose–response study be undertaken using a basal diet that is commonly used in pasture-based dairy systems.
Diamond-based single-photon emitters

The exploitation of emerging quantum technologies requires efficient fabrication of key building blocks. Sources of single photons are extremely important across many applications as they can serve as vectors for quantum information—thereby allowing long-range (perhaps even global-scale) quantum states to be made and manipulated for tasks such as quantum communication or distributed quantum computation. At the single-emitter level, quantum sources also afford new possibilities in terms of nanoscopy and bio-marking. Color centers in diamond are prominent candidates to generate and manipulate quantum states of light, as they are a photostable solid-state source of single photons at room temperature. In this review, we discuss the state of the art of diamond-based single-photon emitters and highlight their fabrication methodologies. We present the experimental techniques used to characterize the quantum emitters and discuss their photophysical properties. We outline a number of applications including quantum key distribution, bio-marking and sub-diffraction imaging, where diamond-based single emitters are playing a crucial role. We conclude with a discussion of the main challenges and perspectives for employing diamond emitters in quantum information processing.
A coupled element-based finite-volume method for the solution of incompressible Navier-Stokes equations

ABSTRACT This article presents a new element-based finite-volume discretization approach for the solution of incompressible flow problems on co-located grids. The proposed method, called the method of proper closure equations (MPCE), employs a proper set of physically relevant equations to constrain the velocity and pressure at integration points. These equations provide a proper coupling between the nodal values of pressure and velocity. The final algebraic equations are not segregated in this study and are solved in a fully coupled manner. To show the applicability and performance of the method, it is tested on several steady two-dimensional laminar-flow benchmark cases. The results indicate that the method simulates the fluid flow in complex geometries and on nonorthogonal computational grids accurately. Also, it is shown that the method is robust in the sense that it does not require severe underrelaxation even at relatively high Reynolds numbers. In each test case, the required underrelaxation parameter, the number of iterations, and the corresponding CPU time are reported.
High-resolution mid-infrared observations of NGC 7469

We present a high-resolution 11.7 micrometer image of the starburst/Seyfert hybrid galaxy NGC 7469 using the Hale 5 m telescope at Palomar Observatory. Our map, with diffraction limited spatial resolution of 0.6 sec, shows a 3 sec diameter ring of emission around an unresolved nucleus. The map is similar to the Very Large Array (VLA) 6 cm map of this galaxy made with 0.4 sec resolution by Wilson et al. (1991). About half of the mid-infrared flux in our map emerges from the unresolved nucleus. We also present spatially resolved low resolution spectra that show that the 11.3 micrometer polycyclic aromatic hydrocarbon (PAH) feature comes from the circumnuclear ring but not from the nucleus of the galaxy.
Fuzzy evaluation on the integrated benefit of regulated deficit irrigation for pear‐jujube tree based on information entropy

Abstract Based on the experimental data of regulated deficit irrigation at different growth stages on field pear‐jujube tree (Zizyphus jujube Mill.) during 2005–2007 in Northwest China, the regulated deficit irrigation integrated benefits (RDIIB) with different water deficit treatments at different growth stages were evaluated and classified using a model. The results in 2005–2006 showed that the RDIIB under single‐stage water deficit at fruit maturity stage were better than the other treatments, and the best RDIIB were gained under moderate (IVSD) or severe deficit (IVMD) at fruit maturity stage. The results in 2006–2007 also indicated that the four double‐stage water deficit schemes have the better RDIIB, and the best scheme was severe water deficit at bud burst to leafing stage plus moderate water deficit at fruit maturity stage. The RDIIB evaluation model based on information entropy method provided the reliable technical guidance for the optimal RDI scheme of pear‐jujube tree.
Cross Dataset Analysis of Domain Shift in CXR Lung Region Detection

Domain shift is one of the key challenges affecting reliability in medical imaging-based machine learning predictions. It is of significant importance to investigate this issue to gain insights into its characteristics toward determining controllable parameters to minimize its impact. In this paper, we report our efforts on studying and analyzing domain shift in lung region detection in chest radiographs. We used five chest X-ray datasets, collected from different sources, which have manual markings of lung boundaries in order to conduct extensive experiments toward this goal. We compared the characteristics of these datasets from three aspects: information obtained from metadata or an image header, image appearance, and features extracted from a pretrained model. We carried out experiments to evaluate and compare model performances within each dataset and across datasets in four scenarios using different combinations of datasets. We proposed a new feature visualization method to provide explanations for the applied object detection network on the obtained quantitative results. We also examined chest X-ray modality-specific initialization, catastrophic forgetting, and model repeatability. We believe the observations and discussions presented in this work could help to shed some light on the importance of the analysis of training data for medical imaging machine learning research, and could provide valuable guidance for domain shift analysis.
Deep Learning Depends on Segregated Dendritic Compartments and Spike Frequency Adaptation

Deep learning mimics the function of the biological nervous system via adopting strategies motivated by neurophysiology. However, integrating biophysical characteristics to make deep learning more brain-like remains challenging. To investigate whether the more realistic simulated neurons could make deep learning more realistic from the biology perspective, we propose a three-layer multicompartment deep learning network with spike frequency adaptation (SFA). We utilize the segregated apical dendrites in the hidden layer to implement the credit assignment and coordinate the distribution of information flow. The introduction of SFA serves as the teaching signal. The results show that the apical dendrites separate the feedforward and feedback signals and instruct the credit assignment problem. The apical dendrites diverse the firing types of target neurons and further decrease the firing rate of nontarget neurons via switching their firing types from the tonic firing type to predominantly burst firing. Furthermore, the expression of SFA in the nontarget neurons further amplifies the difference between the firing rate of target and nontarget signals. This work provides new insight into a deep learning network with more biophysical neurons and is a meaningful supplementary for deep learning.
Motion Analysis of Core Stabilization Exercise in Women: Kinematics and Electromyographic Analysis

As core stabilization exercise is essential for maintaining a stable spine and improving functional performance, understanding the activation of core muscles and the stabilization of the trunk and pelvis during such exercise is crucial. The purpose of this study was to investigate the muscle activation and stabilization of the lumbar–pelvic region during core stabilization exercise, with a specific focus on analyzing EMG and 3D motion kinematic data. The study aimed to understand how different tension settings on the reformer affect muscle activation and hip motion, as well as how these factors impact pelvic and trunk stability during the exercise. The reformer consists of a carriage that slides back and forth on rails, with springs providing resistance. The springs can be adjusted to vary the resistance level. Twenty-eight healthy women participating in this study were asked to perform ‘side splits’, a hip abduction exercise, on the reformer in both heavy and light tension settings. Activation of the internal oblique (IO), rectus abdominis (RA), multifidus (MU), costal lumbosacral (IL), gluteus medius (GM), and adductor muscles (AL) were measured using electromyography (EMG) and 3D motion. Kinematic data using an assay were also measured during exercise. GM, IO, and MU muscles were more active when heavy springs were used, and AL muscles were more active when light springs were used. Hip motion was more symmetrical when lighter springs were used with a greater range of hip motion. There was less pelvis and torso weight transfer and more torso and pelvis stability when the heavier springs were used. In this study, we confirmed that core stabilization exercise on an unstable surface activates the deep muscles of the abdomen and back and is effective for pelvic and trunk stabilization training.
Polyethylene/silica nanocomposites: absorption current and the interpretation of SCLC

The topic of nanodielectrics continues to receive significant attention from today’s dielectrics community, due to the property enhancements that can stem from the unique interfacial features within such material systems. Nevertheless, understanding the interfacial phenomena that occur in nanodielectrics, which determine their electrical behaviour, is challenging. In this paper, we report on an investigation into the absorption current behaviour of two nanocomposite systems, one containing an untreated nanosilica and the other containing the same nanofiller chemically modified using trimethoxy(propyl)silane. The results indicate that the absorption current behaviour of all the nanocomposites is very different from that of the reference, unfilled polymer; while the current flowing through the unfilled polyethylene decreased monotonically with time in a conventional manner, all the nanocomposites revealed an initial decrease followed by a period in which the current increased with increasing time of electric field application. Possible mechanisms leading to the observed absorption current behaviour in the nanocomposites are discussed with the aid of space charge measurements. The presence of space charge limited conduction (SCLC) and its trap-filled limit is proposed.
Pesticide Use Practice and Associated Factors Among Rural Community of Malga District, Sidama Regional State, South Ethiopia

In Ethiopia, like that of the other developing countries, pesticides are widely used for a variety of purposes, but their unsafe use causes a major environmental and health hazard. The aim of this study was to assess pesticide use practice and its associated factors among the rural community of Malga district, Sidama region, southern Ethiopia. A community based cross-sectional study was conducted from February to March 2021 at Malga District. Data were collected from 549 farmers by a structured and pretested interviewer-administered questionnaire. Binary and multivariable logistic regression was used for the data analysis. Adjusted odds ratios and their 95% confidence intervals (CIs) were calculated to determine the association between safe practices of pesticide use and several related factors. Safe practice of pesticide use was observed in 193 (35.2%). The participants who had primary education [AOR = 5.605, 95% CI: 3.309, 9.495], secondary education and above [AOR = 9.847, 95% CI: 5.007, 19.368], used pesticide for 10 years and above [AOR = 6.790, 95% CI: 3.589, 12.843], used pesticide between 6 and 10 years [AOR = 1.913, 95% CI: 1.166, 3.141] pesticide bought from any shop [AOR = 2.320, 95% CI: 1.364, 3.947], agricultural office [AOR = 7.187, 95% CI: 3.654, 14.137] were associated with safe use of pesticides. The safe practice of pesticide use was low in the study area. Continuous training programs should be implemented on the safe practice of pesticide use to the local farmers.
Non-Bank Financial Institutions and Banks’ Fire-Sale Vulnerabilities

Banks carry significant exposures to nonbanks from direct dealings, but they can also be exposed, indirectly, through losses in asset values resulting from fire-sale events. We assess the vulnerability of U.S. banks to fire sales potentially originating from any of twelve separate non-bank segments and identify network-like externalities driven by the interconnectedness across non-bank types in terms of asset holdings. We document that such network externalities can contribute to very large multiples of an original fire sale, thus suggesting that conventional assessments of fire-sale vulnerabilities can be grossly understated and highlighting the value of treating non-bank financial institutions as one organic whole for monitoring purposes.
Non-Line-of-Sight Full-Duplex Ultraviolet Communications Under Self-Interference

The full-duplex optical communications can be achieved simply by separating the transmitting link and the receiving link in the space. However, it is challenging to achieve the non-line-of-sight (NLOS) full-duplex ultraviolet (UV) communication due to the serious self-interference caused by the strong multiple scattering effects of UV signals. To explore the capacity of NLOS full-duplex UV communications, in this paper, we first quantify the self-interference using an analytical channel impulse response function. Based on the quantified self-interference, we then derive the error rate and the corresponding achievable information rate (AIR) for on- off keying modulation, 4-digital-pulse-interval modulation and 4-pulse-position modulation. We further propose a self-interference cancelling (SIC) method to mitigate the impacts of self-interferences. Simulation results show that the proposed SIC method can significantly improve the error rate and AIR performances. Besides, we find that the NLOS full-duplex UV communication will gradually lose its advantage over the NLOS half-duplex UV communication as either the communication distance or the elevation angle increases. However, using the proposed SIC method, the NLOS full-duplex UV communication can hold its advantage in a wide range of system geometries.
Women in STEM Education and Employment: Insights from University Students in Morocco

Worldwide, women represent 35% of all students enrolled in science, technology, engineering, and mathematics (STEM) fields. In Morocco, 42.2% of women are engineering graduates. This study aims to investigate university students’ attitudes, experiences, and awareness about men and women in STEM education and employment. An online questionnaire was adopted to collect both quantitative and qualitative data. Using convenient sampling, 181 STEM university students participated in this study from four different institutions in Morocco which are: Faculty of Sciences and Techniques in Tangiers, The School of Technology in Essaouira, Hassan II Institute of Agronomy and Veterinary Sciences in Rabat, and the Higher School of Technical Education in Mohammadia. The findings show that the majority of students (83.2%) do not perceive the STEM fields as typically masculine. A minority (6.7%) believes that some professors behave differently with male and female students. Moreover, most respondents (55.6%) were not aware of the underrepresentation of women in STEM fields and were unable to recognize the importance of their contributions to fixing society’s challenges. This study, therefore, is relevant for decision makers in higher educational institutions to reconsider the methods and contents of STEM education in order to enhance a gender responsive pedagogy
Interdependence of Solvent and Catalyst Selection on Low Pressure Hydrogen-Free Reductive Catalytic Fractionation

: Hydrogen-free reductive catalytic fractionation (RCF) is a promising method to produce aromatic compounds directly from native biomass without the use of external hydrogen gas. In this work, we show that by using high boiling point diols as a solvent in hydrogen-free RCF, reaction pressures can be reduced by an order of magnitude compared to conventional RCF with methanol and hydrogen gas, while still producing appreciable aromatic monomer yields. Importantly, the use of diols with secondary alcohol functional groups increases hydrogenation activity on Ru/C, Pt/C, and Ni/C, measured by the yield of aromatic compounds with saturated propyl side chains, compared to processing in ethylene glycol, indicating that the choice of solvent and catalyst together can be tuned to control product selectivity of aromatic monomers in RCF.
Double Branch Parallel Network for Segmentation of Buildings and Waters in Remote Sensing Images

The segmentation algorithm for buildings and waters is extremely important for the efficient planning and utilization of land resources. The temporal and space range of remote sensing pictures is growing. Due to the generic convolutional neural network’s (CNN) insensitivity to the spatial position information in remote sensing images, certain location and edge details can be lost, leading to a low level of segmentation accuracy. This research suggests a double-branch parallel interactive network to address these issues, fully using the interactivity of global information in a Swin Transformer network, and integrating CNN to capture deeper information. Then, by building a cross-scale multi-level fusion module, the model can combine features gathered using convolutional neural networks with features derived using Swin Transformer, successfully extracting the semantic information of spatial information and context. Then, an up-sampling module for multi-scale fusion is suggested. It employs the output high-level feature information to direct the low-level feature information and recover the high-resolution pixel-level features. According to experimental results, the proposed networks maximizes the benefits of the two models and increases the precision of semantic segmentation of buildings and waters.
Harmonic functions on loop groups

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An alternative approach for numerical solutions of the Navier–Stokes equations

Conventional approaches for solving the Navier–Stokes equations of incompressible fluid dynamics are the primitive‐variable approach and the vorticity–velocity approach. In this paper, an alternative approach is presented. In this approach, pressure and one of the velocity components are eliminated from the governing equations. The result is one higher‐order partial differential equation with one unknown for two‐dimensional problems or two higher‐order partial differential equations with two unknowns for three‐dimensional problems. A meshless collocation method based on radial basis functions for solving the Navier–Stokes equations using this approach is presented. The proposed method is used to solve a two‐ and a three‐dimensional test problem of which exact solutions are known. It is found that, with appropriate values of the method parameters, solutions of satisfactory accuracy can be obtained. Copyright © 2006 John Wiley & Sons, Ltd.
Multiscale dynamics of C60 from attosecond to statistical physics

C60 is a fascinating object that has become remarkably useful for experimentalists and theoreticians to study photo-induced processes in large many-particle systems. In this review article, we discuss how the knowledge accumulated over the past 30 years on this molecule provides a large panel of mechanisms that occur from the intrinsic time scale of electronic motion that is attosecond, to long ‘macroscopic’ time scale (second). This illustrates the multiscale aspect of dynamics in photo-excited systems, which connects coherent quantum processes to classical and statistical mechanisms. This also shines light onto future experiments and theoretical work required to complete the global picture of light-induced mechanisms in fullerenes.
3-D reconstruction using a limited number of projections

We present a new iterative algorithm for 3D reconstruction under constraints from a limited number of radiographic projections with adjustment of the constraints during the iterations. The first step of the algorithm is a classical iterative reconstruction ART type method (Algebraic Reconstruction Technique) which provides a rough volumic reconstructed 3D zone containing a flaw. Then this reconstructed zone is modelled by a Markov Random Field (MRF) which allows us to estimate some 3D support and orientation constraints using a Bayesian restoration method. This fundamental step is an important one in the sense that it allows the introduction of local geometric a priori knowledge concerning the faults. The next step consists in reintroducing these strong constraints in the reconstruction algorithm. Few iterations of the algorithm are necessary to improve quality of the reconstructed 3D zone. Simulated radiographic projections allow the performance of the algorithm to be evaluated