Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of fly ash and hemihydrate gypsum on the properties of unfired compressed clay bricks

The effect of fly ash type F and hemihydrate gypsum on the mechanical and thermal properties of unfired compressed clay bricks (UCSB) using a semi-dry mixture was determined. UCSB were molded from two different semi-dry mixtures, the bricks made with dark-brown soil + sand + chemical additives were labeled as DBS-LG while the other bricks made with the mixture dark-brown soil + sand + fly ash + chemical additives were labeled as DBS-FALG. SEM and XRD were used to investigate microstructure and mineralogical composition, respectively. Results showed that the addition of fly ash and hemihydrate gypsum improves the mechanical properties of UCSB compared to those of a clay-polymers system; thermal conductivity was similar to other clay based bricks. These results reinforce the suitability of these mixtures in low cost building bricks with energy conservation. Key words: Carbon footprint, Earth construction, unfired clay bricks, fly ash.
Women Empowerment in Comparison to Asian Female Gender Roles and Stereotypes in Crazy Rich Asians Novel

The issue regarding female gender roles has been circulating for so many years in many cultures. The issue can be seen in many media including a novel where it brings up the matter along the plot in the story. This article aims to see women empowerment in comparison to the female gender roles represented in Crazy Rich Asians novel by Kevin Kwan. To support this research, the theory used is Eagly’s Gender Role theory and Malhotra’s Women empowerment theory. The method used in this study is a descriptive qualitative method to elaborate on the female gender roles and women empowerment. The results showed that this novel portrays that the female gender roles and stereotypes came from the residual culture and the women empowerment happened when the female characters can choose their own life path for their own sake by their own decisions. It shows that despite the culture that bonds the female characters for generations, they can still speak up for themselves and choose what is good for them.
A Hybrid Learning-Based Network Model for Security Establishment in IoT Environment

Internet of Things (IoT) is an innovative idea, combines the IoT with social platforms to enable inanimate objects to connect. Despite this, customers are hesitant to accept this new norm. Users are worried that personnel data will be exposed and that privacy will be violated. IoT won't take the lead as a technology until tested with proven methods to strengthen reliable connectivity between nodes. The complexity of maintaining data privacy as a result makes it much more challenging to offer top-notch services and complete security. Here, security and data privacy seems to be challenging where this problem has been examined in several existing works. They created a variety of models based on various criteria and classification strategies for safe nodes on the IoT network. On the other hand, earlier attempts did not provide a method for identifying fake nodes or discriminating between different attack kinds. To segregate hostile nodes from the network and identify assaults that initiated, revolutionary hybrid network model (HNM) with embedded CNN and LSTM is recommended. To get the optimum performance in the suggested research, performance measures including accuracy, precision, recall, and loss are examined and compared with the current methodologies.
Study on The Influence of Green Credit Policy on The Stock Price Synchronicity of Enterprise

Stock price synchronicity is an important indicator reflecting the information efficiency of the capital market. In order to effectively reduce stock price synchronicity, this paper is based on the data of Chinese A-share listed enterprises from 2008 to 2020, and takes the implementation of the Green Credit Guideline in 2012 as the natural experiment. This paper discusses the relationship between green credit policy and stock price synchronicity of high-polluting enterprises and its inner mechanism by building a DID model. According to the baseline regression, green credit policy can significantly reduce the stock price synchronicity of enterprises. The mechanism verification finds that this impact is due to the promotion of enterprise information disclosure driven by green credit policies and the mitigation of financing constraints. Heterogeneity analysis shows that green credit policy has a more significant impact on stock price synchronicity of enterprises that are with more analysts' attention, in highly competitive industry, larger and state-owned. This study complements the discussion on the factors affecting the stock price synchronicity, and provides valuable thinking for reducing the stock price synchronicity and promoting the healthy development of Chinese capital market.
The transcriptome of the entomopathogenic fungus Culicinomyces clavisporus contains an ortholog of the insecticidal ribotoxin Hirsutellin

The entomopathogenic fungus Culicinomyces clavisporus is known to infect and kill mosquito larvae and therefore has been seen as a potential biological control agent against disease vector mosquitoes. Whereas most fungal entomopathogens infect hosts by penetrating the external cuticle, C. clavisporus initiates infection through ingestion (per os). This unique infection strategy suggests that the C. clavisporus genome may be mined for novel pathogenicity factors with potential for vector control. To this end, an Isoseq-based transcriptome analysis was initiated, and resulted in a total of 3,512,145 sequences, with an average length of 1,732 bp. Transcripts assembly and annotation suggested that the C. clavisporus transcriptome lacked the cuticle-degrading proteins that have been associated with other entomopathogenic fungi, supporting the per os pathogenicity process. Furthermore, mining of the sequence data unexpectedly revealed C. clavisporus transcripts homologous to the Hirsutellin toxin. Comparative sequence analyses indicated that the C. clavisporus Hirsutellin predicted protein has retained the canonical molecular features that have been associated with the ribotoxic and insecticidal properties of the original toxin isolated from Hirsutella thompsonii. The identification of an Hirsutellin ortholog in C. clavisporus was supported by phylogenetic analyses demonstrating that Culicinomyces and Hirsutella were closely related genera in the Ophiocordycipitaceae family. Validation of the mosquitocidal activity of this novel C. clavisporus protein has yet to be performed but may help position Hirsutellin orthologs as prime candidates for the development of alternative biocontrol approaches complementing the current toolbox of vector mosquito management strategies.
Pseudomonas putida Metallothionein: Structural Analysis and Implications of Sustainable Heavy Metal Detoxification in Madinah

Heavy metals, specifically cadmium (Cd) and lead (Pb), contaminating water bodies of Madinah (Saudi Arabia), is a significant environmental concern that necessitates prompt action. Madinah is exposed to toxic metals from multiple sources, such as tobacco, fresh and canned foods, and industrial activities. This influx of toxic metals presents potential hazards to both human health and the surrounding environment. The aim of this study is to explore the viability of utilizing metallothionein from Pseudomonas putida (P. putida) as a method of bioremediation to mitigate the deleterious effects of pollution attributable to Pb and Cd. The use of various computational approaches, such as physicochemical assessments, structural modeling, molecular docking, and protein–protein interaction investigations, has enabled us to successfully identify the exceptional metal-binding properties that metallothionein displays in P. putida. The identification of specific amino acid residues, namely GLU30 and GLN21, is crucial in understanding their pivotal role in facilitating the coordination of lead and cadmium. In addition, post-translational modifications present opportunities for augmenting the capacity to bind metals, thereby creating possibilities for focused engineering. The intricate web of interactions among proteins serves to emphasize the protein’s participation in essential cellular mechanisms, thereby emphasizing its potential contributions to detoxification pathways. The present study establishes a strong basis for forthcoming experimental inquiries, offering potential novel approaches in bioremediation to tackle the issue of heavy metal contamination. Metallothionein from P. putida presents a highly encouraging potential as a viable remedy for environmental remediation, as it is capable of proficiently alleviating the detrimental consequences related to heavy metal pollution.
Estimating stream solute loads from fixed frequency sampling regimes: the importance of considering multiple solutes and seasonal fluxes in the design of long‐term stream monitoring networks

Reduced sampling frequency is known to increase the error associated with estimates of stream solute load. However, the extent to which the magnitude of error differs among commonly measured solutes and across seasons is unclear. In this study, a high sampling frequency data set from two forested streams (one upland‐draining and one wetland‐draining stream) in south‐central Ontario was systematically sub‐sampled to simulate weekly, fortnightly and monthly fixed frequency sampling regimes for 12 stream solutes. We found that solutes which had a higher degree of temporal variation in concentration (i.e. higher %RSD) had poorer precision (Cv) in estimates of annual load relative to solutes with a lower %RSD. In addition, the magnitude and direction of bias varied considerably among solutes and were related to differences in spring concentration‐discharge relationships (m[spring Q vs C]) among the 12 solutes. Solutes which decreased in concentration with increases in spring flow (i.e. m[spring Q vs C] <0) exhibited positive bias in annual load while solutes which increased in concentration with increases in spring flow (i.e. m[spring Q vs C] >0) were negatively biased. In terms of differences between seasonal and annual load errors, precision was generally lower for estimates of seasonal load relative to annual load while bias varied in both magnitude and direction among seasons. When the root mean square error (RMSE) of load estimates was compared to a threshold of acceptable error (<15%), the proportion of solutes attaining acceptable levels of uncertainty ranged from 11/12 for annual load estimates at a weekly sampling frequency to only 4/12 at a monthly frequency when both annual and seasonal loads were considered. Our results demonstrate that commonly measured solutes do not behave uniformly in response to changes in sampling frequency and that estimates of seasonal loads are often less accurate than estimates of annual load. These findings provide important insights into the design of stream monitoring programs and the evaluation of existing long‐term data sets. Copyright © 2015 John Wiley & Sons, Ltd.
An improved method for detecting anthropogenic CO2 in the oceans

An improved method has been developed for the separation of the anthropogenic CO 2 from the large natural background variability of dissolved inorganic carbon (C) in the ocean. This technique employs a new quasi-conservative carbon tracer ΔC * , which reflects the uptake of anthropogenic CO 2 and the air-sea disequilibrium when a water parcel loses contact with the atmosphere. The air-sea disequilibrium component can be discriminated from the anthropogenic signal using either information about the water age or the distribution of ΔC * in regions not affected by the anthropogenic transient. This technique has been applied to data from the North Atlantic sampled during the Transient Tracers in the Ocean North Atlantic (TTO NAS) and Tropical Atlantic study (TTO TAS) cruises in 1981-1983. The highest anthropogenic CO 2 concentrations and specific inventories (inventory per square meter) are found in the subtropical convergence zone. In the North Atlantic, anthropogenic CO 2 has already invaded deeply into the interior of the ocean, north of 50°N it has even reached the bottom. Only waters below 3000 m and south of 30°N are not yet affected. We estimate an anthropogenic CO 2 inventory of 20 ± 4 Gt C in the North Atlantic between 10°N and 80°N. The 2.5-dimensional ocean circulation model of Stocker et al. [1994] and the three-dimensional ocean general circulation biogeochemistry model of Sarmiento et al. [1995] predict anthropogenic CO 2 inventories of 18.7 Gt C and 18.4 Gt C, respectively, in good agreement with the observed inventory. Important differences exist on a more regional scale, associated with known deficiencies of the models.
Identification of Metabolomic Signatures for Ischemic Hypoxic Encephalopathy Using a Neonatal Rat Model

A study was performed to determine early metabolomic markers of ischemic hypoxic encephalopathy (HIE) using a Rice–Vannucci model for newborn rats. Dried blood spots from 7-day-old male and female rat pups, including 10 HIE-affected animals and 16 control animals, were analyzed by liquid chromatography coupled with mass spectrometry (HPLC-MS) in positive and negative ion recording modes. Multivariate statistical analysis revealed two distinct clusters of metabolites in both HPLC-MS modes. Subsequent univariate statistical analysis identified 120 positive and 54 negative molecular ions that exhibited statistically significant change in concentration, with more than a 1.5-fold difference after HIE. In the HIE group, the concentrations of steroid hormones, saturated mono- and triglycerides, and phosphatidylcholines (PCs) were significantly decreased in positive mode. On the contrary, the concentration of unsaturated PCs was increased in the HIE group. Among negatively charged molecular ions, the greatest variations were found in the categories of phosphatidylcholines, phosphatidylinositols, and triglycerides. The major metabolic pathways associated with changed metabolites were analyzed for both modes. Metabolic pathways such as steroid biosynthesis and metabolism fatty acids were most affected. These results underscored the central role of glycerophospholipid metabolism in triggering systemic responses in HIE. Therefore, lipid biomarkers’ evaluation by targeted HPLC-MS research could be a promising approach for the early diagnosis of HIE.
The Green Synthesis of Silver Nanoparticles from Avena fatua Extract: Antifungal Activity against Fusarium oxysporum f.sp. lycopersici

Using plant extracts as eco-friendly reducing and stabilizing agents for the synthesis of nanoparticles has gained significant attention in recent years. The current study explores the green synthesis of silver nanoparticles (AgNPs) using the Avena fatua extract and evaluates their antifungal activity against Fusarium oxysporum f.sp. lycopersici (Fol), a fungal plant pathogen. A green and sustainable approach was adopted to synthesize silver nanoparticles before these nanoparticles were employed for anti-fungal activity. The primary indication that AgNPs had formed was performed using UV-vis spectroscopy, where a strong peak at 425 nm indicated the effective formation of these nanoparticles. The indication of important functional groups acting as reducing and stabilizing agents was conducted using the FTIR study. Additionally, morphological studies were executed via SEM and AFM, which assisted with more effectively analyzing AgNPs. Crystalline behavior and size were estimated using powder XRD, and it was found that AgNPs were highly crystalline, and their size ranged from 5 to 25 nm. Synthesized AgNPs exhibited significant antifungal activity against Fol at a concentration of 40 ppm. Furthermore, the inhibitory index confirmed a positive correlation between increasing AgNPs concentration and exposure duration. This study suggests that the combined phytochemical mycotoxic effect of the plant extract and the smaller size of synthesized AgNPs were responsible for the highest penetrating power to inhibit Fol growth. Moreover, this study highlights the potential of using plant extracts as reducing and capping agents for the green synthesis of AgNPs with antifungal properties. The study concludes that A. fatua extract can synthesize antifungal AgNPs as a sustainable approach with robust antifungal efficacy against Fol, underscoring their promising potential for integration into plant protection strategies.
Chapter Two. Hierarchical Modeling of Lek Habitats of Greater Prairie-Chickens

Greater Prairie-Chickens ( Tympanuchus cupido) are a lek-mating prairie grouse of the central Great Plains. Males gather each spring at communal display grounds or leks to compete for mating opportunities with females, and lek sites are essential for the reproductive biology of prai- rie-chickens. We obtained geographic coordinates for 166 active leks located in eastern Kansas. Using GIS analysis, we developed a spatially explicit model to identify landcover and geomorphological variables associated with lek locations. We used a hierarchical approach to model selection to iden- tify the best predictor variables at three spatial scales (0 m, 200 m, and 5 km), and then combined factors from the best models into a global multi- scale model. We found that a synthetic variable, weighted elevation or the point elevation stand- ardized by the elevation of the surrounding land- scape, best explained lek occurrence at a lek point scale of 0 m. At broader spatial scales of 200 m and 5 km, avoidance of agricultural, urban, and forest habitats, avoidance of high densities of roads, and a preference for grassland cover were the best predictors of lek site locations. Next, we created an entropy model based on factors from our minimum Bayesian Information Criterion global model to create an index of suitable lek hab- itat across the Flint Hills, Smoky Hills, and Osage Plains ecoregions of eastern Kansas. The entropy model showed that 85% of lek sites were in hab- itat strata that comprised 20% of the regional landscape, suggesting that prairie-chickens may be utilizing areas that are of marginal quality. Our research results have important implications for conservation because Kansas prairies are the core of extant distribution of Greater Prairie-Chickens and include the largest remaining intact grass- lands in the United States.
Molecular dynamics simulations evidence the thermoresponsive behavior of PNIPAM and PDEA in glycerol solutions

Polymers exhibiting thermoresponsive behavior above a lower critical solution temperature (LCST) undergo a coil-to-globule phase transition that has many biomedical applications, including biosensing, the control of release devices, and gene or drug delivery systems. In addition, there has been sustained scientific interest in these polymers for their use in industrial applications, including water treatment and desalination. Since the coil-to-globule phase transition is greatly affected by the hydrophilic/hydrophobic balance of the polymer-solvent interactions, the LCST of a particular thermoresponsive polymer depends on the solvent environment and can be tuned through the modification of solution parameters such as co-solvent molar concentrations. While there have been numerous experimental and computational studies focused on the properties of these polymers in aqueous solutions, study of their behavior in more viscous solvents has been limited. In this article, the thermoresponsive behavior of poly (N-isopropylacrylamide) (PNIPAM) and poly (N,N-diethylacrylamide) (PDEA) has been evaluated when in solution with water, the highly viscous liquid glycerol, and both 50:50 and 90:10 glycerol:water mixtures. The adopted methodology includes molecular dynamics techniques and a modified OPLS all-atom force field, which is particularly challenging when the monomers of the targeted polymers have side-chains consisting of a hydrophobic isopropyl group and a hydrophilic amide group along the carbon backbone chain. Hence, our approach entailed simulations at the microsecond scale. The structural and energetic properties of the polymers were characterized, including radius of gyration, solvent accessible surface area, polymer-solvent hydrogen bonding, and interaction energies. Our predictions indicate that these polymers sustain a coil-to-globule phase transition in glycerol solvents at significantly higher LCSTs when compared to the LCST in less viscous aqueous solutions. These predictions highlight valuable insights that will prove advantageous for industrial and nano-scale applications requiring polymer phase behavior with elevated LCST well above ambient temperature.
Throughput Maximization for Covert UAV Relaying System

Covert communication protects the communication behavior from being monitored or eavesdropped, which is particularly vital for unmanned aerial vehicle (UAV) communications since they are more likely to establish line-of-sight link. This correspondence investigates the joint trajectory and transmit power optimization for covert UAV relaying systems. Considering covertness requirement, information causality, power and trajectory constraints, a general optimization framework characterized by dynamic and three-dimensional is proposed. The detection performance from warden and relay perspectives is analyzed, and the covertness constraint with uncertain information is converted to tractability expressions. For the joint optimization problem, we propose a covert relaying algorithm which simultaneously optimizes the trajectory and power. Simulation results verify that the proposed covert relaying method can improve the average throughput while satisfying the covertness constraint.
Studying the Impact of Varying Sample Length of ECG Signal on Classification Accuracy

ECG Signals in digital format are being used for gathering various vital information and for predicting diseases in patients using advanced artificial intelligence and digital signal processing technologies. It is important to process the data sufficiently to get the optimal results. In addition to cleaning the dataset, it is important to select the right signal length. This study uses three publicly available datasets (namely autonomic aging dataset, PTB-XL dataset, and PTB Diagnostic dataset) to study the impact of varying sample lengths on classification accuracy i.e., understanding whether varying sample lengths can impact the accuracy and if so how different sample lengths for certain classification problems can affect it. The experiments performed used three machine learning algorithms which are Decision Tree Classifier, Random Forest Classifier, and State Vector Machine Classifier, and it was found that the signal length does impact the accuracy when predicting diseases using an ECG signal, and the behavior can vary depending on the type of data being used and the nature of classification problem, even if the same model is used.
All-Optical Tuning of Microbottle Resonator Assisted by a Movable Probe With Magnetic Nanoparticles

We demonstrate an all-optical tunable device consisting of a microbottle resonator (MBR) and an internal movable probe based on the photothermal effect. The inner wall of MBR and probe tip are coated with magnetic nanoparticles (MNPs) for enhancing pump laser absorption efficiency. The increased temperature of MBR caused by laser-induced heat changes the effective refractive index of MBR and thus tunes the resonance wavelength of whispering gallery modes (WGMs). The simulation results reveal that the tuning efficiency can be enhanced by increasing pump laser power and decreasing the distance between probe tip and coupling position, which are verified by the experimental results. The demonstrated maximum tuning sensitivity and tuning range are 0.23 nm/mW and 3.7 nm, respectively. Moreover, the comparative experiments are conducted to investigate the influence of MNP coating on tuning performance, which reveals that the sensitivity of coated sensor is 42 times larger than that of uncoated. The proposed all-optical tuning scheme provides great potential in optical switches.