Miracle-dz/UniFAR-FTUs huggingface dataset:
Finger knuckle recognition, a review on prospects and challenges based on PolyU dataset

In the previous few years, Finger knuckle (Fk) has received a lot of interest as a biometric trait in recent years. It will provide economic human identification performance due to its distinct difference between human-specific alternatives of visible lines, wrinkles, and ridges spread on the surface external of all finger knuckles. The foundation for most biometric systems is Fks. This report presents a thorough analysis of the pertinent Finger knuckle investigations. The foundation for most biometric systems is Fks. The identification system through finger knuckles usually contents of 4 steps, specifically image Acquisition, image preprocessing, feature extraction, and have matched. There are numerous methods used during this research at each level. The paper is likely to highlight these methods used in the PolyU database
Coupled effects of impact and orogeny: Is the marine Lockne crater, Sweden, pristine?

Abstract— Our current understanding of marine‐impact cratering processes is partly inferred from the geological structure of the Lockne crater. We present results of a mapping campaign and structural data indicating that this crater is not pristine. In the western part of the crater, pre‐impact, impact, and post‐impact rocks are incorporated in Caledonian thrust slices and are subjected to folding and faulting. A nappe outlier in the central crater depression is a relic of the Caledonian nappe cover that reached a thickness of more than 5 km. The overthrusted crater is gently deformed. Strike of strata and trend of fold axes deviate from standard Caledonian directions (northeast‐southwest). Radially oriented crater depressions, which were previously regarded as marine resurge gullies formed when resurging seawater erosively cut through the crater brim, are interpreted to be open synclines in which resurge deposits were better preserved.
Dissipative particle dynamics simulation of pore‐scale multiphase fluid flow

Multiphase fluid flow through porous media involves complex fluid dynamics, and it is difficult to model such complex behavior, on the pore scale, using grid‐based continuum models. In this paper, the application of dissipative particle dynamics (DPD), a relatively new mesoscale method, to the simulation of pore‐scale multiphase fluid flows under a variety of flow conditions is described. We demonstrate that the conventional DPD method using purely repulsive conservative (nondissipative) particle‐particle interactions is capable of modeling single‐phase flow fields in saturated porous media. In order to simulate unsaturated multiphase flow through porous media, we applied a modified model for the conservative particle‐particle interactions that combines short‐range repulsive and long‐range attractive interactions. This form for the conservative particle‐particle interactions allows the behavior of multiphase systems consisting of gases, liquids, and solids to be simulated. We also demonstrated that the flow of both wetting and nonwetting fluids through porous media can be simulated by controlling the ratios between the fluid‐fluid and fluid‐solid (fluid‐wall) interparticle interaction strengths.
On Generalized Dominance Structures for Multi-Objective Optimization

Various dominance structures have been proposed in the multi-objective optimization literature. However, a systematic procedure to understand their effect in determining the resulting optimal set for generic domination principles, besides the standard Pareto-dominance principle, is lacking. In this paper, we analyze and lay out properties of generalized dominance structures which help provide insights for resulting optimal solutions. We introduce the concept of the anti-dominance structure, derived from the chosen dominance structure, to explain how the resulting non-dominated or optimal set can be identified easily compared to using the dominance structure directly. The concept allows a unified explanation of optimal solutions for both single- and multi-objective optimization problems. The anti-dominance structure is applied to analyze respective optimal solutions for most popularly used static and spatially changing dominance structures. The theoretical and deductive results of this study can be utilized to create more meaningful dominance structures for practical problems, understand and identify resulting optimal solutions, and help develop better test problems and algorithms for multi-objective optimization.
Joint Design of Mismatched Filter and Phase Coded Waveform via Mainlobe Broadening

The joint design of mismatched filter and waveform is an important technique in suppressing sidelobes of phase coded waveform. Conventionally, an implied constraint that the mainlobe response is of the same width as a chip or bit is included. In fact, a slightly broadened mainlobe is acceptable in most cases. More importantly, relaxation of the mainlobe width will provide more design freedom in sidelobe suppression. In this work, the mainlobe response is broadened into a fixed window shape. Under the constraints of the shape of mainlobe and waveform constant modular, the optimization problem is to minimize the integrated sidelobe level (ISL). The optimization problem is solved by Lagrange multiplier method and Alternating Direction Multiplier Method (ADMM). This method will obtain low sidelobes with a slight loss of signal-to-noise ratio. Additionally, the explanation that mainlobe broadening can further reduce the sidelobe is given in the frequency domain.
Prediction of Type 2 Diabetes through Risk Factors using Binary Logistic Regression

The main objective of this study is to arrive at a highly efficient prediction model for early prediction of diabetes by relying on risk factors for diabetes as predictor variables. Using a binary logistic regression model, a model was built for the data of study which taken from a sample of diabetics and non-diabetics persons. The results have shown the high ability of the binary logistic regression model in predicting the diabetes-infected persons. All indicators confirm the validity and quality of the model. The results of Chi-square test (sig=0.945>.05) indicated that the model is significant. Likewise, the results of Hosmer&Lemeshow test (sig=0.945>.05) confirm that the model represents the data very well. Classification table findings were also high, as the overall percentage for the correct classification was 91%. The significant risk factors that influential in predicting diabetes can be arranged as follows: (High blood pressure, Diabetes in the family first degree, High cholesterol, Smoking, Age above 35, Overweight and Gender). All these results confirm the quality and accuracy of this model in predicting the disease, the thing which may indicate that the model can be used as a primary tool for predicting type-2 diabetes through risk factors.
Detection of ASD Children through Deep-Learning Application of fMRI

Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable immediate, targeted interventions. This study unveils an advanced convolutional-neural-network (CNN) algorithm that was meticulously engineered to examine resting-state functional magnetic resonance imaging (fMRI) for early ASD detection in pediatric cohorts. The CNN architecture amalgamates convolutional, pooling, batch-normalization, dropout, and fully connected layers, optimized for high-dimensional data interpretation. Rigorous preprocessing yielded 22,176 two-dimensional echo planar samples from 126 subjects (56 ASD, 70 controls) who were sourced from the Autism Brain Imaging Data Exchange (ABIDE I) repository. The model, trained on 17,740 samples across 50 epochs, demonstrated unparalleled diagnostic metrics—accuracy of 99.39%, recall of 98.80%, precision of 99.85%, and an F1 score of 99.32%—and thereby eclipsed extant computational methodologies. Feature map analyses substantiated the model’s hierarchical feature extraction capabilities. This research elucidates a deep learning framework for computer-assisted ASD screening via fMRI, with transformative implications for early diagnosis and intervention.
Articular Cartilage—From Basic Science Structural Imaging to Non-Invasive Clinical Quantitative Molecular Functional Information for AI Classification and Prediction

This review presents the changes that the imaging of articular cartilage has undergone throughout the last decades. It highlights that the expectation is no longer to image the structure and associated functions of articular cartilage but, instead, to devise methods for generating non-invasive, function-depicting images with quantitative information that is useful for detecting the early, pre-clinical stage of diseases such as primary or post-traumatic osteoarthritis (OA/PTOA). In this context, this review summarizes (a) the structure and function of articular cartilage as a molecular imaging target, (b) quantitative MRI for non-invasive assessment of articular cartilage composition, microstructure, and function with the current state of medical diagnostic imaging, (c), non-destructive imaging methods, (c) non-destructive quantitative articular cartilage live-imaging methods, (d) artificial intelligence (AI) classification of degeneration and prediction of OA progression, and (e) our contribution to this field, which is an AI-supported, non-destructive quantitative optical biopsy for early disease detection that operates on a digital tissue architectural fingerprint. Collectively, this review shows that articular cartilage imaging has undergone profound changes in the purpose and expectations for which cartilage imaging is used; the image is becoming an AI-usable biomarker with non-invasive quantitative functional information. This may aid in the development of translational diagnostic applications and preventive or early therapeutic interventions that are yet beyond our reach.
Multi-objective trajectory planning over terrain using label-setting greedy-based algorithm

In this paper, the multi-objective trajectory planning problem for an unmanned aerial vehicle on a low altitude terrain following/threat avoidance mission is studied. Using a grid-based discrete scheme, the continuous constrained optimization problem into a combination of search and decision problem is transformed over a finite network. A variant of the minimum cost network flow approach, which is referred to as label-setting greedy-based algorithm, is then applied to this problem. Using the digital terrain elevation data and discrete dynamic equations of motion, an optimal four-dimensional trajectory (three spatial and one time dimensions) from a source to a destination is obtained deterministically by minimizing a nonlinear cost functional subject to dynamic and mission constraints of the unmanned aerial vehicle. For each arc in the grid, a cost functional is considered as a combination of the path length, fuel consumption, flight time, and risk-of-threat region. Moreover, due to the increasing deviation of inertial navigation system in terms of time, having a safe flight and collision avoidance with terrain at low altitude is a significant problem in the trajectory design of this type of the vehicles. In this work, it’s tried to meet this constraint in the trajectory planning. The simulation studies on the unmanned aerial vehicle flight planning problem are presented to verify the capability of the proposed algorithm to generate admissible trajectory in minimum possible time comparison to previous works.
Large-scale patterns in hurricane-driven shoreline change

The effects of storm events on cross-shore beach profiles have been the subject of concerted examination by nearshore researchers for decades. Because these investigations typically span relatively short (less than a kilometer) shoreline reaches, alongshore patterns of storm-driven shoreline change at multikilometer scales remain poorly understood. Here we measure shoreline position from seven airborne lidar surveys of coastal topography, spanning 12 years (1996–2008), along a continuous ∼80 km stretch of the northern North Carolina Outer Banks, United States. Two of the lidar surveys were flown in the wakes of Hurricane Bonnie (1998) and Hurricane Floyd (1999), allowing a rare window into storm-related alongshore coastline changes at large scales. In power spectra of shoreline change variance and in calculations of plan view shoreline curvature, we find evidence of transient behaviors at relatively small alongshore scales (less than a kilometer) and an interesting combination of both transient and cumulative shoreline change patterns at larger scales (1–10 km). Large-scale plan view shoreline undulations grow in amplitude during the storm intervals we examined, possibly forced by a large-scale morphodynamic instability. Long-term (decadal) shoreline adjustments, however, trend in the opposite direction, with an overall diffusion or smoothing of shoreline shape at multiple-kilometer scales, probably due to gradients in alongshore sediment transport. Although storms can significantly reshape the coastline across a wide range of scales, those changes do not necessarily accumulate to patterns of long-term change.
The Impact of Intermittent Fasting on Non-Alcoholic Fatty Liver Disease in Older Adults: A Review of Clinicaltrials.gov Registry

Background Non-alcoholic fatty liver disease (NAFLD) is a predominant health condition across the world due to its rising prevalence and association with various metabolic disorders. Intermittent fasting (IF) has attracted increasing attention as a dietary approach to addressing weight management and enhancing metabolic well-being, and its potential effects on NAFLD have been a topic of growing research interest. Aim This review aims to critically evaluate the current evidence on IF’s impact on NAFLD, including the mechanisms underlying the observed effects in older adults (65+). Methods A comprehensive search of Clinicaltrials.gov was conducted to identify relevant studies that investigated the effects of IF on NAFLD in older adults (65+). Data on study design, sample size, intervention details, and outcomes related to NAFLD were extracted and analyzed. Results As of April 12th, 2023, there were 1304 clinical trials on NAFLD. Most of these were interventional studies. The investigation focused on completed studies and found that limited clinical trials were identified with limited interventional measures. Only five out of the 1304 studies on NAFLD involved IF. Basic and advanced outcome measures were examined. Conclusion Although some studies suggest that IF may have potential benefits for NAFLD, the evidence is still limited and inconclusive.
Discovery of coesite from Indus Suture Zone (ISZ), Ladakh, India: Evidence for deep subduction

Coesite, the high-pressure polymorph of quartz has been identified for the first time in the Tso-Morari Crystalline Complex, Ladakh (India) in the Himalayan belt. The preservation of coesite grains as inclusions in garnet within eclogite boudins indicates the existence of UHP metamorphism in this continental collision setting. The coesite was identified optically and its presence confirmed by its characteristic Raman bands. Both coesite and polycrys-talline quartz inclusions exhibit prominent radial fractures in their host garnet. The silica inclusions (monomineralic coesite, monomineralic quartz and bimineralic quartz+coesite) are associated with various textural features and well-developed chemical zonation within the garnet, which show the prograde nature of the UHP metamorphism. Preliminary P-T estimates suggest that the coesite growth took place at pressure > 28 kbar (> 90 km depth) and temperatures > 640°C. Significantly, the coesite inclusions are interpreted as having suffered decompression during exhumation without changing to quartz, most likely due to the rapid uplift. This finding also indicates deep subduction of the Indian plate beneath the Asian continent. The occurrence of coesite and subduction of the Indian plate was essentially governed by a low geothermal gradient which occurred prior to rapid exhumation. This was vital for generating the coherent picture of metamorphism and exposure of UHP rocks.
Breakup of levitated frost particles

We have studied the sublimation and breakup of single 100-200 μm frost particles levitated electrically at temperatures in the range -2°C to -30°C. Breakup rates were largely independent of temperature and humidity in this range but strongly dependent on particle shape. Irregular particles of high aspect ratio were most likely to break up. Sublimation (evaporation) was accompanied by an increasing aspect ratio. A linearized sublimation model, presented in the appendix, accounts for the observation that thin neck regions were not subject to enhanced sublimation rates. Estimates of the forces involved in breakup suggest that the breaking strength of these frost particles is considerably less than that of bulk ice. We discuss possible implications of our results for ice particle multiplication in clouds.
Stratigraphy and geoarchaeology of the Red Canyon Rockshelter, Crook County, Wyoming

Excavation of a sandstone rockshelter on the northwestern periphery of the Black Hills uplift in Crook County, Wyoming, revealed a sequence of culture-bearing deposits at least 5 m thick that span the last 6 millennia. Although archaeological strata are present throughout the sequence, artifact return from the shelter was low, and chemical and micromorphological analyses demonstrate that anthropic alterations of the sediments are limited. This indicates that the shelter served as short-term, expedient cover for people moving through the area rather than a locus of long-term habitation. Evolution of the shelter involved a series of massive roof-collapse episodes that formed internal sediment traps that subsequently infilled with highly stratified gravels, silts, and sands. These deposits are interdigitated with dipping slopewash strata that represent a mixture of exogenic and endogenic sediments. One stratum appears to represent substantial input of eolian dust between approximately 4500 B.P. and 3300 B.P. Although the overall evolution of the shelter is largely a function of intrinsic processes not related directly to climate change, the presence of eolian dust implies that the climate may have been more arid during this time period than at present, although local degradation of the landscape may have actually been responsible. ©1997 John Wiley & Sons, Inc.
Effects of Vitamin D on Asprosin Immunoreactivity Against Cyclophosphamide-Induced Liver Injury in Rats

Background Cyclophosphamide (CP), commonly used as an anticarcinogenic drug, has the potential to induce detrimental effects on multiple tissues, including the liver. Asprosin, which is a glucogenic adipokine, induces the liver to secrete glucose, thus contributing to the maintenance of homeostasis. This study aims to investigate the immunoreactivity of asprosin in the liver tissue of rats exposed to CP administration, as well as the changes in its levels due to the supplementation of Vitamin D (Vit D). Materials and methods Four experimental groups were formed, including control, Vit D (200 IU/kg), CP (200 mg/kg), and Vit D+ CP. Histopathological analysis was carried out by employing staining methods on liver tissues. These techniques encompassed the application of hematoxylin-eosin (H&E), Masson’s trichrome, and periodic acid Schiff (PAS). Through the application of spectrophotometric methods, concentrations of malondialdehyde (MDA), total antioxidant status (TAS), total oxidant status (TOS), and asprosin were determined. Furthermore, apoptotic cells were identified by the terminal deoxynucleotidyl transferase (TdT) dUTP nick-end labeling (TUNEL) method, and the asprosin immunoreactivity was determined by immunohistochemistry. Results Under light microscope examination, the histopathological damage was found to be more notable in the CP group compared to the control group. Moreover, a decrease was observed in serum and tissue asprosin levels, while an increase was noted in the count of apoptotic cells, along with elevated MDA and TOS levels. However, in the CP+Vit D group, Vit D administration alleviated histopathological damage. Notably, there were significant increases in TAS and asprosin levels, accompanied by reductions in both MDA and TOS levels. Conclusions The effect of CP on liver tissue was observed to result in damage and a reduction in asprosin levels. Vit D supplementation revealed elevated asprosin levels and a distinct protective effect on the tissue. Considering the association between asprosin and liver injury induced by CP, further research is needed to elucidate the mechanisms that underlie the effect of asprosin on tissues. When combined with Vit D, asprosin holds promise for potential clinical applications as a therapeutic target.
A Low-Power i-ToF LiDAR With Nonlinearity Self-Calibration Technique

This article proposes a low-power <inline-formula> <tex-math notation="LaTeX">$320\times240$ </tex-math></inline-formula> indirect time-of-flight (i-ToF) vision system with a nonlinearity self-calibration technique. A pump gate modulator (PGM) technique is applied in the pixel to reduce the power consumption of pixel modulation. As a result, the pixel has a higher lateral electric field in a lower voltage swing of modulation, and the pixel can operate in the depletion state to achieve smaller load capacitance. To improve the nonlinearity of the sensor, nonlinearity self-calibration techniques are proposed. It includes the channel toggle technique and predistortion single-slope analog-to-digital converter (SS-ADC), which eliminates the quadratic nonlinearity in the readout channel and source follower (SF) nonlinearity in the pixel, respectively. Furthermore, it reduces the difficulty of nonlinear calibration of different batches of chips. The measured nonlinearity decreases greatly without back-end calibration, which is smaller than 0.8% within the distance range from 0.12 to 5 m. The receiver chip is fabricated in a 110-nm front-side illuminated (FSI) process with a <inline-formula> <tex-math notation="LaTeX">$5.6\times 5.6 \mu \text{m}$ </tex-math></inline-formula> pixel size. The chip power is only 130 mW.
Multivariate Statistical Techniques: A New Approach to Identify the Commercial Properties of Mixtures of Flours of Lentinula edodes and Cocoa Pod Husk

Lentinula edodes is known to show high nutritional and organoleptic properties and can be mixed with different by-products in the production of new foods with important functional characteristics. Cocoa pod husk (CPH) is the main by-product in the cocoa industry and presents important bioactivities. In this research, two mixtures were applied based on Lentinula edodes mushroom flour from fifty different strains (strain 1 to strain 50) and cocoa pod husk flour (CPHF): 60% Lentinula edodes mushroom flour from each strain mixed with 40% CPHF (Mixture 1), and 80% Lentinula edodes mushroom flour from each strain mixed with 20% CPHF (Mixture 2). The parameters evaluated were moisture, proteins, fat, total dietary fiber (TDF), ash, carbohydrates, antioxidant capacity, antimicrobial activity, pH and water activity (aw). The multivariate statistical techniques evaluated those samples that exhibited the highest degree of correlation with the distinct chemical and commercial parameters, showing that sample 13 of both mixture flours (M1 and M2) obtained by the mushrooms of L. edodes (strain 13) with CPH indicated the higher significant of the parameters. In addition, the sensory test of the best flour (sample 13) was applied to 50 panelists, presenting the best sensory characteristics, such as color, aroma, texture and general acceptability.