Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Biocrust Development and Plant Growth through Inoculation of Desiccation-Tolerant Cyanobacteria in Different Textured Soils

In recent years, there has been a burgeoning interest in the utilization of cyanobacteria for the purpose of land rehabilitation via enhancements in soil fertility, prevent erosion, and counter desertification. This study evaluated the ability of Nostoc calcicola BOT1, Scytonema sp. BOT2, and their consortia to form biocrusts on the substrate of coarse sand, fine sand, and loamy soil. A nutrient- and water-deficient substrate was inoculated with cyanobacteria to facilitate biocrust formation and evaluate their impact on agriculture. Cyanobacteria inoculation resulted in significant improvements in soil fertility, especially in coarse and fine sand, which initially had the lowest fertility. The findings of this investigation underscore that the consortium of cyanobacteria exhibited greater efficacy than individual strains in enhancing soil fertility and stimulating plant growth. The loamy soil treated with the consortium had the highest plant growth across all soil types, in contrast to the individual strains. The consortium of cyanobacteria showed promising results in promoting biocrust formation and fostering rice seedling growth in fine sand. This study provides empirical evidence supporting the potential utility of cyanobacterial consortia as a valuable tool for the rehabilitation of degraded land. Furthermore, the results indicate that cyanobacterial species can persist in soil environments even following prolonged periods of desiccation.
Build Network Intrusion Detection System based on combination of Fractal Density Peak Clustering and Artificial Neural Network

Imbalanced data poses a serious problem in intrusion detection systems. In this article, we propose a network intrusion detection system based on fractal density peak clustering and an artificial neural network (FD-ANN). The proposed detection system consists of three parts: data clustering based on the density-peak clustering (DPC) method, using the fractal concept as a membership weight of all data to the cluster, and a neural network to classify the data. The DPC method uses categorization of the tare data into subgroups with strongly correlated attributes to reduce the size of the training data and the imbalance of the sample. Each subgroup has its neural network to train the data. Based on fractal membership weights, the output of all classifiers of the sub-neural networks is combined using the aggregation function. The benchmarks of this model are based on the data sets NSL-KDD and UNSW-NB15. The proposed solution outperforms other known classification approaches in terms of overall accuracy, recall, precision, and F1 score.
Comparative Evaluation of Egg Quality in Response to Temperature Variability: From Farm to Table Exposure Scenarios

Abstract This study aimed to develop appropriate temperature management practices and provide scientific evidence to support the development of sell-by-date guidance for eggs. Washed and unwashed eggs were subjected to storage under six different scenarios, and both types of eggs were stored at temperatures up to 35°C to evaluate the sell-by-date. Despite temperature fluctuations or continuous storage at 30°C for 5 days, subsequent storage at 10°C resulted in significantly higher Haugh unit and yolk index on day 15. These results indicate that refrigerating eggs from retail sales until consumption is effective for egg quality management, despite the exposure of up to 35°C during distribution. In terms of sell-by-date evaluation, washed eggs retained class B quality for an additional 37 days beyond the recommended sell-by-date at 15°C, which is above the regulated storage temperature. However, unwashed eggs maintained class B quality for approximately 20 days at 30°C–35°C, emphasizing the need for sell-by-date guidelines for unwashed eggs. This study is the first to provide appropriate egg-handling practices based on the actual distribution environment in Korea.
Method of Evaluating Multiple Scenarios in a Single Simulation Run for Automated Vehicle Assessment

With advances in the technology applied to automated driving systems (ADSs), active efforts have been made to evaluate the safety of ADS in various complex situations using simulations. In accordance with these efforts, numerous institutions have developed single-scenario pools that reflect a variety of road and traffic characteristics and ADS performances. However, a single scenario has limitations in comprehensively evaluating the performance of complex ADS. Therefore, this study proposed a methodology that combines and transforms single scenarios into multiple scenarios. This aided in continuously evaluating the ADS performance over entire road segments and implemented this methodology in the simulations.
Population differences in spatial learning in three–spined sticklebacks

In a changing environment, learning and memory are essential for an animal's survival and reproduction. The role played by the environment in shaping learning and memory is now attracting considerable attention. Until now, studies have tended to compare the behaviour of two, or at best a few species but interspecific comparisons can be misleading as many life history variables other than environment may differ between species. Here we report on an experiment designed to determine how learning varies between different populations of the same species, the three–spined stickleback. We found differences between the populations in their ability to solve a spatial task and also in the spatial strategies they used. A second simple learning task showed that these differences were not the result of gross differences in learning ability or adaptation to laboratory conditions. We discuss these results and suggest that the behavioural differences may relate to features of the respective habitats from which the fish were sampled.
Uncertainties in bathymetric retrievals

The sensitivity of the remotely-sensed water reflectance to variations in water depth and bottom albedo is investigated using a semianalytical model and the radiative transfer numerical model HYDROLIGHT. Properties of the water column are taken from published observations made on 14 Feb 2001 in the coastal waters of Moreton Bay (southeast Queensland). The sensitivities of reflectance to depth and albedo are computed using partial derivatives derived from the semianalytical model, and with finite differences using the numerical model. These are compared for various depths and bottom conditions, and also to the instrumental resolution of the Hyperion satellite remote sensing system. Sensitivity to albedo is found to be greater than sensitivity to depth under some situations making the depth signal in reflectance ambiguous. These sensitivities are then applied to bathymetry algorithms to produce error bars for depth retrievals under variable bottom albedo conditions. This is done for both the standard algorithm that uses reflectances at 550 and 650 nm corrected for optically deep water reflectance, and a blue/green ratio algorithm intended for use over low albedo areas. In the standard algorithm variations of 10% in albedo produce errors in depth estimates of approximately 0.05m over sandy bottoms which is small compared with the 2m depth resolution required to reach the bottom in the Moreton Bay experiment. The blue/green ratio algorithm showed no skill for bathymetric mapping with this dataset.
Visual Relation Identification Using BoFT Labels in Social Media Feeds

- Social media is an online platform that became an inevitable part of individuals. Interest of online users can be detected from social graph. Social graph interrupts the privacy of online users so it is dubious. This paper adapt users interest from user shared images. Users share images on social media, it depicts the interest of users or criticism about a real time issue or despatch of users. These user shared images are reachable to other users in contact which provide an easier and systematic alternative for discovering connection between users. The proposed methodology investigates to discover user connection through a better alternative called bag-of-features tagging (BoFT). User shared images also helps to establish connection between users. By BoFT, the users interest are recognized and thereby estimate tag recommendation for users. This paper identifies the connection between users using the image sharing mechanism and determines the tag recommendation for friendship. These findings are useful for interest discovery which categorize users based on propensity of topic and the virality of user shared images are predicted. Predicting the virality of user shared images are computed based on the occurrence of images in social network .
Targeting mitophagy for depression amelioration: a novel therapeutic strategy

Major depressive disorder is a global psychiatric condition characterized by persistent low mood and anhedonia, which seriously jeopardizes the physical and mental well-being of affected individuals. While various hypotheses have been proposed to explicate the etiology of depression, the precise pathogenesis and effective treatment of this disorder remain elusive. Mitochondria, as the primary organelles responsible for cellular energy production, possess the ability to meet the essential energy demands of the brain. Research indicated that the accumulation of damaged mitochondria is associated with the onset of depression. Mitophagy, a type of cellular autophagy, specifically targets and removes excess or damaged mitochondria. Emerging evidence demonstrated that mitophagy dysfunction was involved in the progression of depression, and several pharmacological interventions that stimulating mitophagy exerted excellent antidepressant actions. We provided an overview of updated advancements on the regulatory mechanism of mitophagy and the mitophagy abnormality in depressed patients and animals, as well as in cell models of depression. Meanwhile, various therapeutic strategies to restore mitophagy for depression alleviation were also discussed in this review.
The Precambrian crystalline complex of south-western Sweden. The geology and petrogenetic development of the Varberg Region

Abstract Investigations of the crystalline complex of the Varberg region of south-western Sweden have shown the existence of two major rock series in a modified cover/basement relationship. The reworked basement rocks, the Varberg Series, now comprise belts of mixed, banded, hypersthene–granulites within more widespread granitic gneisses which are partially charnockitised in situ. The series is cut by a discrete, internally differentiated, granitic complex with charnockitic elements, the Charnockite—Granite Association. The most sialic member of the association, a silicic hornblende—biotite—microcline granite, crosses the interface to the cover rocks, but is mainly contained in an extensive sheet within the plane of the interface. Garnet-pyribolite, of three generations, is a further prominent feature. Despite strong recrystallisation and partial migmatisation, the Bua Series cover sequence has partially retained its supracrustal character, although distinction of sedimentary and volcanic elements is now .
Adsorption Behavior of a Ternary Covalent Organic Polymer Anchored with SO3H for Ciprofloxacin

Owing to the poor treatment efficiency of wastewater containing fluoroquinolones (FQs), effective removal of such pollutants has become a significant issue in waste management. In this study, a ternary covalent organic polymer anchored with SO3H (COP-SO3H) was designed using the Schiff reaction and a multicomponent solvent thermal method. The synthesized COP-SO3H polymer possesses multiple functional binding sites, including amide groups, sulfonic groups, and aromatic frameworks, enabling it to effectively adsorb ciprofloxacin (which belongs to FQs) through mechanisms such as pore-filling effects, electrostatic interactions, hydrogen bonding, π-π electron donor–acceptor (EDA) interactions, and hydrophilic–lipophilic balance. COP-SO3H demonstrated outstanding adsorption performance for ciprofloxacin, exhibiting a high adsorption capacity, broad pH stability, strong resistance to ionic interference, and good regenerability. Moreover, it displayed preferential selectivity toward fluoroquinolone antibiotics. The present study not only investigates the intricate structural and functional design of COP-SO3H materials but also presents potential applications for the efficient adsorption of specific antibiotics.
The 600–750 hPa relative humidity minimum observed during PEM‐Tropics B

The height where cumulus convection over tropical oceans directly transports air from the boundary layer is statistically investigated, making use of the NASA Pacific Exploratory Mission‐Tropics B (PEM‐Tropics B) observed data. The cumulus convection detrainment levels are inferred by high CH3I concentrations and relative humidity. The relationship between the injection height and stability is also discussed. Tropical cumulus convection directly transported boundary layer air to the 350–600 hPa and 750–800 hPa levels. These pressure levels coincided with the heights where stable layers were frequently observed. On the other hand, the cumulus convection infrequently transported boundary layer air directly to the 600–750 hPa levels, being consistent with the fact that stability around these levels was weak.
Alpha-Glucosidase Inhibitory Peptides: Sources, Preparations, Identifications, and Action Mechanisms

With the change in people’s lifestyle, diabetes has emerged as a chronic disease that poses a serious threat to human health, alongside tumor, cardiovascular, and cerebrovascular diseases. α-glucosidase inhibitors, which are oral drugs, have proven effective in preventing and managing this disease. Studies have suggested that bioactive peptides could serve as a potential source of α-glucosidase inhibitors. These peptides possess certain hypoglycemic activity and can effectively regulate postprandial blood glucose levels by inhibiting α-glucosidase activity, thus intervening and regulating diabetes. This paper provides a systematic summary of the sources, isolation, purification, bioavailability, and possible mechanisms of α-glucosidase inhibitory peptides. The sources of the α-glucosidase inhibitory peptides were introduced with emphasis on animals, plants, and microorganisms. This paper also points out the problems in the research process of α-glucosidase inhibitory peptide, with a view to providing certain theoretical support for the further study of this peptide.
Geologic constraints on bedrock river incision using the stream power law

Denudation rate in unextended terranes is limited by the rate of bedrock channel incision, often modeled as work rate on the channel bed by water and sediment, or stream power. The latter can be generalized as KA m S n , where K represents the channel bed's resistance to lowenng (whose variation with lithology is unknown), A is drainage area (a surrogate for discharge), S is local slope, and m and n are exponents whose values are debated. We address these uncertainties by simulating the lowering of ancient river profiles using the finite difference method. We vary m, n, and K to match the evolved profile as closely as possible to the corresponding modern river profile over a time period constrained by the age of the mapped paleoprofiles. We find at least two end-member incision laws, KA 0.3-0.5 S for Australian rivers with stable base levels and K f A 0.1-0.2 S n for rivers in Kauai subject to abrupt base level change. The long-term lowering rate on the latter expression is a function of the frequency and magnitude of knickpoint erosion, characterized by K f Incision patterns from Japan and California could follow either expression. If they follow the first expression with m = 0.4, K varies from 10 -7 -10 -6 m 0.2 /yr for granite and metamorphic rocks to 10 -5 -10 -4 m 0.2 /yr for volcaniclastic rocks and 10 -4 -10 -2 m 0.2 /yr for mudstones. This potentially large variation in K with lithology could drive strong variability in the rate of long-term landscape change, including denudation rate and sediment yield.
The application of data mining techniques for the regionalisation of hydrological variables

Flood quantile estimation for ungauged catchment areas continues to be a routine problem faced by the practising Engineering Hydrologist, yet the hydrometric networks in many countries are reducing rather than expanding. The result is an increasing reliance on methods for regionalising hydrological variables. Among the most widely applied techniques is the Method of Residuals, an iterative method of classifying catchment areas by their geographical proximity based upon the application of Multiple Linear Regression Analysis (MLRA). Alternative classification techniques, such as cluster analysis, have also been applied but not on a routine basis. However, hydrological regionalisation can also be regarded as a problem in data mining — a search for useful knowledge and models embedded within large data sets. In particular, Artificial Neural Networks (ANNs) can be applied both to classify catchments according to their geomorphological and climatic characteristics and to relate flow quantiles to those characteristics. This approach has been applied to three data sets from the south-west of England and Wales; to England, Wales and Scotland (EWS); and to the islands of Java and Sumatra in Indonesia. The results demonstrated that hydrologically plausible clusters can be obtained under contrasting conditions of climate. The four classes of catchment found in the EWS data set were found to be compatible with the three classes identified in the earlier study of a smaller data set from south-west England and Wales. Relationships for the parameters of the at-site distribution of annual floods can be developed that are superior to those based upon MLRA in terms of root mean square errors of validation data sets. Indeed, the results from Java and Sumatra demonstrate a clear advantage in reduced root mean square error of the dependent flow variable through recognising the presence of three classes of catchment. Wider evaluation of this methodology is recommended.
On Determining the Onset and Strength of Breaking for Deep Water Waves. Part II: Influence of Wind Forcing and Surface Shear

Abstract Part I of this study describes the authors' findings on a robust threshold variable that determines the onset of breaking for unforced, irrotational deep water waves and proposes a means of predicting the strength of breaking if the breaking threshold is exceeded. Those results were based on a numerical study of the unforced evolution of fully nonlinear, two-dimensional inviscid wave trains and highlight the fundamental role played by the nonlinear wave group dynamics. In Part II the scope of these calculations is extended to investigate the additional influence of wind forcing and background shear on the evolution to breaking. Using the methodology described in Part I, the present study focuses on the influence of wind forcing and vertical shear on long-term evolution toward breaking or recurrence of the maximum of the local energy density within a wave group. It investigates the behavior of a dimensionless local growth rate parameter that reflects the mean energy flux to the energy maximum in t.
Simplified Kinetic Model of Heart Pressure for Human Dynamical Blood Flow

The blood flow that carries various particles results in disturbed physical flow in the heart organ caused by speed, density, and pressure. This phenomenon is complicated resulting in a wide variety of medical problems. This research provides a mathematical technique and numerical experiment for a straightforward solution to cardiac blood flow to arteries. Finite element analysis (FEA) is used to study and construct mathematical models for human blood flow through arterial branches. Furthermore, FEA is used to simulate the steady two-dimensional flow of viscous fluids across various geometries. The results showed that the blood flow in the carotid artery branching is simulated after the velocity profiles obtained are plotted against the experimental design. The computational method's validity is evaluated by comparing the numerical experiment with the analytical results of various functions
Properties of deep convection in tropical continental, monsoon, and oceanic rainfall regimes

This study compares vertical structures and properties of deep convection for continental, monsoonal, and oceanic rainfall regimes based on 13‐yr TRMM measurements. There is evident regime separation in convective structures and properties of deep convection: continental and oceanic regimes are at two ends of the spectrum, with monsoon regimes intermediate between them. For example, most of the continental rainfall (70–80%) is contributed by storms having 40‐dBZ radar echoes reaching above 6‐km, strong ice scattering signature, and lightning flashes. This indicates that continental convection is dominated by robust mixed‐phase processes such as freezing of raindrops or riming of graupel supported by strong updrafts. In contrast, less monsoon rainfall (∼40%) or very limited oceanic rainfall (∼10%) involves these vigorous microphysical processes in mixed‐phase regions. Though monsoons are intermediate in convective intensity, both current and previous studies show that their active periods are closer to oceanic regimes and their break periods are slightly closer to continental regimes. In short, this study offers novel guidance for categorization of convective properties of three regime archetypes and will be important for future regional, climatological, and modeling studies.
Swirl development and enhanced heat transfer analysis of ferrofluid in elliptical ducts under thermal-magnetic-flow fields coupling

It is a new practical method to apply external magnetic field in magnetic working fluid to enhance heat transfer. In this paper, the swirl flow and heat transfer characteristics of ferrofluid in elliptical tubes under thermal-magnetic-flow fields coupling have been studied by using the finite volume method. The flow structure and secondary vortices evolution process of magnetic nanofluid in elliptical ducts under the action of the magnetic fields have been obtained. The effects of magnetic induction intensity and the ratio of major axis to minor axis of elliptical pipe on the flow and heat transfer performances have been main investigated. The results show that there is obvious secondary flow (with four vortices or eight vortices) on the cross section and the swirling flow is gradually formed due to the coupling of thermal-magnetic-velocity fields. With the increase of the ratio of major axis to minor axis, the heat transfer enhancement effect with the application of external magnetic field is weakened. The comprehensive performance of flow and heat transfer are better at lower Reynolds number and higher magnetic induction intensity.