Miracle-dz/UniFAR-FTUs huggingface dataset:
Spread the word: Sharing information on social media can stabilize conservation funding and improve ecological outcomes

Conservation needs adequate support and funding to address our ecological crises. People support conservation in different ways, from social media engagement to donating money. Various factors influence how people choose to support conservation, including social norms and ecological status. The rise of social media has provided people with an easy and low‐cost way to support conservation: sharing information online. How valuable is social media engagement and activism for conservation funding and outcomes? Here, we develop an evolutionary game‐theoretic framework to understand the complex interactions between individuals in the context of social media information sharing, conservation philanthropy, and how these interactions ultimately impact ecological outcomes. From a game theory perspective, we can consider donors to be hard‐cooperators, sharers of information on social media to be soft‐cooperators, and those who do nothing to be non‐cooperators. Our model shows that soft‐cooperators can help stabilize conservation funding flows and develop social norms. Supporting conservation through social media sharing can ultimately contribute to conservation success. Our study conceptualizes the complex decision‐making processes of conservation funding and affirms the importance and value of mobilizing all types of supporters in conservation.
Solar seismology. II - The stochastic excitation of the solar p-modes by turbulent convection

We test the hypothesis that the solar rho-modes are stabilized by damping due to turbulent viscosity in the convective zone. Starting from the assumption that the modes are stable, we calculate expectation values for the modal energies. We find that the interaction between a p-mode and the turbulent convection is such that the modal energy tends toward equipartition with the kinetic energy of turbulent eddies whose lifetimes are comparable to the modal period. From the calculated values of the modal energies, we compute rms surface velocity amplitudes. Our predicted rms surface velocities range from 1 x 10/sup -2/ cm s/sup -1/ for the fundamental radial mode to 0.6 cm s/sup -1/ for the radial mode whose period is approximately 5 minutes. The predicted surface velocities for the low order p-modes (periods >20 min) are much smaller than the velocities inferred from recent observations by Hill, Stebbins, and Brown and by Brookes, Isaak, and van der Raay.
Process Monitoring for Nitride Dielectric Defect Density

We have implemented a process monitor for defects in the silicon nitride deposition sub-process of a GaAs PHEMT fab line. The nitride is used as the dielectric in MIMCAPs (metalinsulator-metal capacitors). The defect monitor is based upon ramped breakdown testing of test capacitors on each wafer. In order to interpret the ramped breakdown data, the TDDB theory was utilized, suitably modified for the silicon nitride dielectric. Six months of process monitoring was carried out and an upper control limit established for the nitride defect density.
An in‐silico investigation of fluoride ions impact on pancreatic lipase

Fluorine is a halogen beneficial to teeth and bones at a lower concentration. But in excess, it is a toxin and causes adverse effects. Fluoride is toxic to enzymes generally when it inhibits the enzyme activity involved in metabolic pathways. Here we study invitro and invivo findings on the interaction of fluoride on the enzymes Aconitase, Adenylyl cyclase, Arginase, Cytochrome‐c‐oxidase, Glucose‐6‐phosphatase, Protein phosphatase, Succinate dehydrogenase from liver and lipase from pancreas by using molecular docking and simulations to gain insights into the mechanism by which fluoride modifies the activity of pancreatic lipase. our molecular modeling and docking studies identified that lipase is the most strongly inhibited enzyme compared to other enzymes mentioned above with −0.42 Kcal/mol binding energy and 495.78 milli molar of predicted IC50 value with interaction with Phe227 residue. To further validate this, we have taken the lipase enzyme in presence of fluoride ions for molecular dynamic simulations of 100 ns. To analyze the impact of fluoride ions on the lipase dynamics, two different simulations of 100 ns each were performed. In one simulation, we have simulated lipase in its apo form in the aqueous environment without any fluoride ions and in another simulation lipase in its apo form was kept in the presence of randomly placed fluoride ions countered with sodium ions to maintain the pH as neutral. The simulation analysis revealed that major fluctuations in lipase was observed between 230 and 300 residues in presence of fluoride ions. Interestingly, this is the exact location of the “lid” like acting loop of residues responsible for the inward/outward movement of the substrate to lipase catalytically active site containing catalytic triad of residues Leu153, His263, and Pro177. His263 residue random flip is believed to be the critical incident that causes the substrate's inward/outward movement at the catalytically active site coordinated by “lid” opening, providing enough space for the substrate.
Robust Certificateless Authentication Protocol for the SAE J1939 Commercial Vehicles Bus

Authentication for controller area network (CAN) buses in an intra-vehicular network involving electronic control units (ECUs) is a challenging factor. The Society of Automotive Engineers standard (SAE J1939) incorporating the ISO 11898-1 specification for the data link and physical layers of the standard CAN and CAN-flexible data rate (CAN-FD) handles communication among ECUs. The SAE J1939 is vulnerable to replay, masquerading and machine-in-the-middle (MITM) attacks. To prevent such attacks, there exist protocol suites for resource-constrained and resource-unconstrained nodes proposed in the literature which are not formally analysed. We formally analyse one of the comprehensive protocol suites using the state-of-the-art Tamarin automated validation tool. To mitigate the identified attacks, we propose two new authentication protocols. At first, we propose one pass authentication protocol for computationally restricted nodes. For nodes that are not restricted computationally, we present a certificateless signature-based authentication protocol. Additionally, we present a new certificateless key insulated manageable signature (CL-KIMS) scheme for signature-based authentication protocol. CL-KIMS ensures key insulation and random access key update properties, and assures self-healing property. The security of the proposed protocol suite and signature scheme is formally analysed using the random oracle model (ROM). Especially, CL-KIMS scheme is provably secure in the ROM against Type-I and Type-II adversaries. A detailed performance comparison and simulation study show that the proposed protocol suite has lesser communication overhead and ensures robust security as compared to the existing protocol suites.
The sigma‐1 receptor curtails endogenous opioid analgesia during sensitization of TRPV1 nociceptors

Peripheral sensitization contributes to pathological pain. While prostaglandin E2 (PGE2) and nerve growth factor (NGF) sensitize peptidergic C‐nociceptors (TRPV1+), glial cell line‐derived neurotrophic factor (GDNF) sensitizes non‐peptidergic C‐neurons (IB4+). The sigma‐1 receptor (sigma‐1R) is a Ca2+‐sensing chaperone known to modulate opoid analgesia. This receptor binds both to TRPV1 and the μ opioid receptor, although the functional repercussions of these physical interactions in peripheral sensitization are unknown.
Feature Selection Using Neighborhood based Entropy

Feature selection plays an important role as a preprocessing step for pattern recognition and machine learning. The goal of feature selection is to determine an optimal subset of relevant features out of a large number of features. The neighborhood discrimination index (NDI) is one of the newest and the most efficient measures to determine distinguishing ability of a feature subset. NDI is computed based on a neighborhood radius (E). Due to the significant impact of E on NDI, selecting an appropriate value of E for each data set might be challenging and very time-consuming. This paper proposes a new approach based on targEt PointS To computE neIgh- borhood relatioNs (EPSTEIN). At first, all the data points are sorted in the descending order of their density. Then, the highest density data points are selected as many as the number of classes. To determine the neighborhood relations, the circles centered on the target points are drawn and the points inside or on the circles are considered to be neighbors. In the next step, the significance of each feature is computed and a greedy algorithm selects appropriate features. The performance of the proposed approach is compared to both the commonest and newest methods of feature selection. The experimental results show that EPSTEIN could select more efficient subsets of features and improve the prediction accuracy of classifiers in comparison to the other state-of-the-art methods such as Correlation-based Feature Selection (CFS), Fast Correlation-Based Filter (FCBF), Heuris- tic Algorithm Based on Neighborhood Discrimination Index (HANDI), Ranking Based Feature Inclusion for Optimal Feature Subset (KNFI), Ranking Based Feature Elimination (KNFE) and Principal Component Analysis and Information Gain (PCA-IG).
Collagen scaffolds derived from bovine skin loaded with MSC optimized M1 macrophages remodeling and chronic diabetic wounds healing

Abstract Owing to the persistent inflammatory microenvironment and unsubstantial dermal tissues, chronic diabetic wounds do not heal easily and their recurrence rate is high. Therefore, a dermal substitute that can induce rapid tissue regeneration and inhibit scar formation is urgently required to address this concern. In this study, we established biologically active dermal substitutes (BADS) by combining novel animal tissue‐derived collagen dermal‐replacement scaffolds (CDRS) and bone marrow mesenchymal stem cells (BMSCs) for the healing and recurrence treatments of chronic diabetic wounds. The collagen scaffolds derived from bovine skin (CBS) displayed good physicochemical properties and superior biocompatibility. CBS loaded with BMSCs (CBS‐MCSs) could inhibit M1 macrophage polarization in vitro. Decreased MMP‐9 and increased Col3 at the protein level were detected in CBS‐MSCs‐treated M1 macrophages, which may be attributed to the suppression of the TNF‐α/NF‐κB signaling pathway (downregulating phospho‐IKKα/β/total IKKα/β, phospho‐IκB/total IκB, and phospho‐NFκB/total NFκB) in M1 macrophages. Moreover, CBS‐MSCs could benefit the transformation of M1 (downregulating iNOS) to M2 (upregulating CD206) macrophages. Wound‐healing evaluations demonstrated that CBS‐MSCs regulated the polarization of macrophages and the balance of inflammatory factors (pro‐inflammatory: IL‐1β, TNF‐α, and MMP‐9; anti‐inflammatory: IL‐10 and TGF‐β3) in db/db mice. Furthermore, CBS‐MSCs facilitated the noncontractile and re‐epithelialized processes, granulation tissue regeneration, and neovascularization of chronic diabetic wounds. Thus, CBS‐MSCs have a potential value for clinical application in promoting the healing of chronic diabetic wounds and preventing the recurrence of ulcers.
Soft-Shelled Turtle Peptides Extend Lifespan and Healthspan in Drosophila

In traditional Chinese medicine, soft-shelled turtle protein and peptides serve as a nutraceutical for prolonging the lifespan. However, their effects on anti-aging have not been clarified scientifically in vivo. This study aimed to determine whether soft-shelled turtle peptides (STP) could promote the lifespan and healthspan in Drosophila melanogaster and the underlying molecular mechanisms. Herein, STP supplementation prolonged the mean lifespan by 20.23% and 9.04% in males and females, respectively, delaying the aging accompanied by climbing ability decline, enhanced gut barrier integrity, and improved anti-oxidation, starvation, and heat stress abilities, while it did not change the daily food intake. Mechanistically, STP enhanced autophagy and decreased oxidative stress by downregulating the target of rapamycin (TOR) signaling pathway. In addition, 95.18% of peptides from the identified sequences in STP could exert potential inhibitory effects on TOR through hydrogen bonds, van der Walls, hydrophobic interactions, and electrostatic interactions. The current study could provide a theoretical basis for the full exploitation of soft-shelled turtle aging prevention.
Constrained sequential lamination: nonconvex optimization and material microstructure

A practical algorithm has been developed to construct, through sequential lamination, the partial relaxation of multiwell energy densities such as those characteristic of shape memory alloys. The resulting microstructures are in static and configurational equilibrium, and admit arbitrary deformations. The laminate topology evolves during deformation through branching and pruning operations, while a continuity constraint provides a simple model of metastability and hysteresis. In cases with strict separation of length scales, the method may be integrated into a finite element calculation at the subgrid level. This capability is demonstrated with a calculation of the indentation of a Cu-Al-Ni shape memory alloy by a spherical indenter. In verification tests the algorithm attained the analytic solution in the computation of three benchmark problems. In the fourth case, the four-well problem (of, e.g., Tartar), results indicate that the method for microstructural evolution imposes an energy barrier for branching, hindering microstructural development in some cases. Although this effect is undesirable for purely mathematical problems, it is reflective of the activation energies and metastabilities present in applications involving natural processes. The method was further used to model Shield's tension test experiment, with initial calculations generating reasonable transformation strains and microstructures that compared well with the sequential laminates obtained experimentally.
Classical orbits and semiclassical wavepacket propagation in the Coulomb potential

A simple and elegant semiclassical theory for propagating wavepackets is presented. The development of the theory avoids the explicit use of the Green-function formalism. It involves expanding the potential to a quadratic time-dependent form and the use of multiple reference trajectories. The classical analogue in phase space predicts the accuracy of the results. The theory is applied to the calculation of the autocorrelation function in a Coulomb field in one dimension. Remarkable agreement with an exact quantum calculation is obtained in many circumstances in spite of the Coulomb singularity. All the detailed quantum behaviour, including the long-time recurrences and the spectrum, is reproduced.
Fountain Coded Streaming for SAGIN With Learning-Based Pause-and-Listen

Efficient adaptive bitrate streaming (ABS) over long-distance and lossy space-air-ground-integrated network (SAGIN) links is an important demand, where fountain transmission is attractive as it does not require feedback/retransmissions. However, the conventional fountain scheme may waste many packets due to the propagation delay of stop messages. This letter proposes a novel fountain coded ABS design with a pause-and-listen approach which, across segments of ABS, learns proper pause time in an on-line manner based on multi-armed bandit modeling. Evaluation using a real-life implementation shows that the scheme can avoid most packet wastes while still maintaining the key benefits of the fountain transmission.
ResNet and LSTM Based Accurate Approach for License Plate Detection and Recognition

The identification and recognition of automatic license plates (ALP) are critical for traffic surveillance, parking management, and preserving the rhythm of modern urban life. In this paper, a deep learning-based method is proposed for ALP. In the proposed work, the license plate region is initially segmented in a given vehicle image, and the plate number and city region are extracted from the segmented license plate region. Residual neural networks (ResNet) architecture-based deep feature extraction is considered. The fully connected layer of the ResNet model is used to obtain the deep features for the cropped Arabic numbers and city regions, respectively. The extracted features are fed into the sequential input layer of the Long Short-Term Memory (LSTM) classifier. Various experiments are carried out on a dataset that was collected in the northern Iraq region and the classification accuracy score is used for performance evaluation. According to the obtained results, the proposed method is effective where the calculated accuracy scores were 98.51% and 100% for Arabic numbers and city regions, respectively. The performance comparison of the proposed method with some of the existing methods indicates the high performance of the proposed study.
New Statistical Results of Partial Sums of Ordered Gamma-Distributed RVs for Performance Evaluation of Wireless Communication Systems

With the increase in the complexity of communication systems, order statistics have become increasingly significant in performance evaluation, especially for advanced diversity techniques over fading channels. However, existing analytical approaches are not useful owing to their high complexity. In this paper, we present novel and insightful statistical results of the partial sums of ordered Gamma-distributed random variables. By adopting a unified analytical framework to obtain the desired joint probability density function from the joint moment-generating function, we redefine and derive the common key functions specialized for the Gamma distribution. The derived formula is presented in the form of either general closed-form expressions or at least a single integral form instead of the originally complicated multiple-integral form. In terms of a feasible application of our results, we present a complete and general closed-form analysis of the statistics of the combined received signal-to-noise ratio of the distributed cyclic delay diversity with the cyclic prefix single-carrier scheme. We also show that our analytical results can provide potential mathematical solutions for other wireless communication systems. Selected numerical examples are presented and discussed to illustrate the effectiveness of the applied approach and related results. All the derived analytical results were compared and verified by using Monte Carlo simulations to verify the accuracy of our analysis.
Investigation of a method for solving a hyperbolic-parabolic system on a sphere

Abstract A method for the numerical solution of a hyperbolic-parabolic system on a sphere is studied. The method is based on the application of a splitting scheme and a special iterative algorithm for the implementation of one of the steps of this scheme. Estimates of the spectrum for the ‘pressure operator’ are obtained and the convergence rate of this iterative process is studied. Results of numerical experiments are presented.
Optical flow estimation of the heart's short axis view using a perceptual approach

This article describes a perceptual approach to calculate the optical flow estimation of the left ventricle in a short axis view of the heart in computer tomography images. The method is based on the the Hermite transform which is an image representation model that incorporates some of the more important properties of the first stages of the human visual system. Our optical flow estimation approach incorporates a differential approach that uses the steered Hermite coefficients as local constraints and uses the implicit multiresolution scheme of the Hermite transform to compute large displacements. It also involves several of the constraints seen in the current differential methods which allows obtaining an accurate optical flow. We use the anatomic short axis view of the heart to calculate the optical flow estimation instead of the original CT images of the axial plane. This view allows visualizing the left ventricle like a circular structure, which is more suitable for visualization of the left ventricle motion.
AUTOMATED DETECTION OF MAMMOGRAPHIC ASYMMETRY USING ANATOMICAL FEATURES

Breast asymmetry is an important radiological sign of cancer. This paper describes the first approach aiming to detect all types of asymmetry; previous asymmetry-based research has been focussed on the detection of mass lesions. The conventional approach is to search for brightness or texture differences between corresponding locations on left and right breast images. Due to the difficulty in accurately identifying corresponding locations, asymmetry cues generated in this way are insufficiently specific to be used as prompts for small and subtle abnormalities in a computer-aided diagnosis system. We have undertaken studies to discover more about the visual cues utilized by radiologists. As a result, we propose a new automatic method for detecting asymmetry based on the comparison of corresponding anatomical structures, identified by an automatic segmentation of breast tissue types. We describe methods for comparing the shape and brightness distribution of these regions, and we present promising results obtained by combining evidence for asymmetry.
The International Journal of Biostatistics Relative Risk Estimation in Randomized Controlled Trials : A Comparison of Methods for Independent Observations

The relative risk is a clinically important measure of the effect of treatment on binary outcomes in randomized controlled trials (RCTs). An adjusted relative risk can be estimated using log binomial regression; however, convergence problems are common with this model. While alternative methods have been proposed for estimating relative risks, comparisons between methods have been limited, particularly in the context of RCTs. We compare ten different methods for estimating relative risks under a variety of scenarios relevant to RCTs with independent observations. Results of a large simulation study show that some methods may fail to overcome the convergence problems of log binomial regression, while others may substantially overestimate the treatment effect or produce inaccurate confidence intervals. Further, conclusions about the effectiveness of treatment may differ depending on the method used. We give recommendations for choosing a method for estimating relative risks in the context of RCTs with independent observations.
Microbial vitamin production mediates dietary effects on diabetic risk

ABSTRACT Adequate levels of essential vitamins are important for the prevention of diabetes. While the main efforts to address this are currently focused on the intake of vitamin supplements, improving and maintaining intrinsic vitamin production capacity, which is determined by gut microbes, has received insufficient attention. In this study, we systematically investigated the relationship between gut microbial vitamin production and factors related to diabetes and cardiometabolic health in a deeply phenotyped cohort, Lifelines-DEEP (N = 1,135). We found that blood glucose–related factors, lipids, circulating inflammation, and fecal short-chain fatty acids are associated with gut microbial vitamin production. Use of laxatives and metformin are associated with increased levels of vitamin B1/B6 biosynthesis pathways. We further reveal a mediatory role for microbial vitamin B1/B2 production on the influence of fruit intake on diabetes risk. This study provides preliminary evidence for microbiome-targeted vitamin metabolism interventions to promote health.