Miracle-dz/UniFAR-FTUs huggingface dataset:
Does Lead Have a Connection to Autism? A Systematic Review and Meta-Analysis

Environmental pollutants, particularly toxic trace metals with neurotoxic potential, have been related to the genesis of autism. One of these metals that stands out, in particular, is lead (Pb). We conducted an in-depth systematic review and meta-analysis of peer-reviewed studies on Pb levels in biological materials retrieved from autistic children (cases) and neurotypical children (controls) in this work. A systematic review was conducted after the careful selection of published studies according to established criteria to gain a broad insight into the higher or lower levels of Pb in the biological materials of cases and controls, and the findings were then strengthened by a meta-analysis. The meta-analysis included 17 studies (hair), 13 studies (whole blood), and 8 studies (urine). The overall number of controls/cases was 869/915 (hair), 670/755 (whole blood), and 344/373 (urine). This meta-analysis showed significantly higher Pb levels in all three types of biological material in cases than in controls, suggesting a higher body Pb burden in autistic children. Thus, environmental Pb exposure could be related to the genesis of autism. Since no level of Pb can be considered safe, the data from this study undoubtedly point to the importance of regularly monitoring Pb levels in autistic children.
Codes of conduct for indigenous-inspired spa and wellness tourism

While the growing global tourism industry currently provides best practices guidance and certification possibilities for ecotourism, green spas, and Indigenous tourism, no codes of conduct exist for spas operations that aim to sustainably integrate Indigenous-inspired healing modalities into their menu of services. I interviewed both Indigenous healers and wellness experts around the globe who incorporate ancient healing practices into spas. My analysis of these data culminated with recommended codes of conduct for Indigenous-inspired spas. The need for cultural sensitivity and guidelines unique to this sector are growing. Compared to examples such as handcrafts or cultural dance, wellness experiences are more personal, spiritual or at times even ceremonial. Spas that do not follow the codes of conduct may exploit culture amongst presenting other serious risks. Benefits to Indigenous communities when following codes of conduct include meaningful employment and the preserving of ancient healing practices that otherwise may be at risk of erosion. Benefits to destination spa or day spa clients include experiential cross-cultural learning and healing body therapies that reduce stress or improve well-being.
Improving the efficiency of symbolic execution by clustering the input data based on the complexity of test generation

The object of research is means to increase computational effectiveness for automatic unit test generation process. It provides arguments for developing new method to achieve wider use of symbolic execution in commercial software development. The main task of the research is to create adaptive code clustering method that considers test generation complexity for structural source code elements and available computational resources that will increase effectiveness of computations. It is achieved by estimating test generation complexity and balancing the it for produced clusters during clusterization. As a result, proposed clustering method is adaptive to hardware and source code variability. It is shown that developed approach provides up to 30 % increase in computation effectiveness compared to clustering based on code structural properties alone for selected samples and up to 250 % in separate cases. This is caused by balanced estimated test generation complexity within generated clusters. It limits path explosion to expected levels that match computational resources for every cluster. Estimate of test generation complexity makes it possible to stop the computation when the spent time exceeds the corresponding complexity limit. Consequently, it makes it possible to prevent performing unnecessary computations. Proposed method makes it possible to use symbolic execution in commercial software development due to higher adaptability for source code and hardware variations. It will allow to reduce expenses on early-stage software testing and provide means for determining feasibility of symbolic execution for commercial projects
Prognostic Efficacy of Complete Blood Count Indices for Assessing the Presence and the Progression of Myxomatous Mitral Valve Disease in Dogs

Simple Summary The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) are inflammatory indicators calculated using blood counts that serve as potential biomarkers in various diseases. This study investigated healthy dogs and those with a common heart disease, myxomatous mitral valve disease (MMVD). Dogs with MMVD had higher NLR, MLR, and PLR, which could be useful for diagnosing and predicting this condition. Abstract This study investigated the complete blood count (CBC) indices, including neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) in dogs with myxomatous mitral valve disease (MMVD) and analyzed their correlation with conventional biomarkers, as well as the effect of CBC indices on survival time in dogs with MMVD. Medical records of 75 healthy controls and 249 dogs with MMVD from March 2015 to October 2022 were analyzed. The NLR, MLR, and PLR were calculated by dividing the absolute counts of the CBC parameters. Dogs with MMVD had significantly higher NLR, MLR, and PLR than healthy dogs (all p < 0.0001), especially those in the symptomatic MMVD group with pulmonary edema (p < 0.0001, p = 0.0002, and p = 0.0387, respectively). The NLR and MLR were significantly correlated with N-terminal pro-B type natriuretic peptide levels (both p < 0.0001). The CBC indices showed potential as biomarkers for detecting the presence of MMVD (all p < 0.0001) and severity of MMVD (p < 0.0001, p < 0.0001, and p = 0.006, respectively) using receiver operating characteristic curve analysis. The negative effects of increased NLR, MLR, and PLR on survival were confirmed using Kaplan–Meier curve analysis. In conclusion, NLR, MLR, and PLR could be cost-effective and readily available potential diagnostic and prognostic biomarkers for MMVD in dogs.
Understanding the Invasion, Ecological Adaptations, and Management Strategies of Bactrocera dorsalis in China: A Review

Bactrocera dorsalis (Hendel, 1912) (Diptera: Tephritidae), commonly known as the oriental fruit fly, is a highly destructive pest that globally infests fruits and vegetables, resulting in significant annual economic losses. Initially detected in Taiwan Island, it has rapidly expanded its distribution range to various regions in mainland China since the 1980s, with a continuous northward spread. To mitigate the damage caused by this pest, extensive efforts have been undertaken to comprehend its ecological and physiological adaptations and develop management strategies. This review article provides an overview of the invasion history of B. dorsalis in China, its ecological and physiological mechanisms facilitating its invasion, and the progress made in understanding its major biological characteristics. Moreover, the key approaches for managing B. dorsalis that have been or are likely to be implemented in China are presented, including quarantine measures, monitoring procedures, physical controls, biological controls, the sterile insect technique, RNA interference, and CRISPR-Cas-9. Finally, some suggestions for future research directions are provided.
Treatment of Asymptomatic Bacteriuria after Kidney Transplantation: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background and Objectives: Asymptomatic bacteriuria (ASB) is prevalent in kidney transplant recipients (KTRs) and is hypothesized to heighten the risk of subsequent urinary tract infections (UTIs). Whether antibiotic treatment of ASB in KTRs is beneficial has not been elucidated. Materials and Methods: We carried out a systematic review and meta-analysis of all randomized controlled trials (RCTs) and quasi-RCTs that examined the merits of managing asymptomatic bacteriuria in KTRs. The primary outcomes were rates of symptomatic urinary tract infections (UTIs) and antimicrobial resistance. Results: Five studies encompassing 566 patients were included. No significant difference in symptomatic UTI rates was found between antibiotics and no treatment groups (relative risk (RR) 1.05, 95% confidence interval (CI) = 0.78–1.41), with moderate heterogeneity (I2 = 36%). Antibiotic treatment was found to present an uncertain risk for the development of drug-resistant strains (RR = 1.51, 95% CI = 0.95–2.40, I2 = 0%). In all trials, no significant difference between study arms was demonstrated regarding patient and graft outcomes, such as graft function, graft loss, hospitalization due to UTI, all-cause mortality, or acute rejection. Conclusions: The practice of screening and treating kidney transplant patients for asymptomatic bacteriuria does not curtail the incidence of future symptomatic UTIs, increase antimicrobial resistance, or affect graft outcomes. Whether early treatment of ASB after kidney transplantation (<2 months) is beneficial requires more RCTs.
MULTI-TEMPORAL URBAN LAND-USE CHANGE DETECTION AND PREDICTION USING CNN-BASED CA-MARKOV MODEL FROM GAOFEN SATELLITE IMAGES

Abstract. The intelligent interpretation of land-use change has become a research frontier. Reasonably and effectively utilizing limited land resources and making scientific predictions to promote sustainable utilization of land resources is significant for establishing a resource-saving and environmentally friendly society. Remote sensing technology can efficiently complete multi-temporal and dynamic land-use change detection, especially using high-spatial resolution remote sensing images. However, the existing land-use change and prediction have not been combined. In addition, land-use change detection mainly relies on shallow feature design, resulting in low prediction accuracy and weak generalization performance. To solve the above problems, we proposed a CNN-based CA Markov model using multi-temporal GaoFen satellite remote sensing images for the change detection and prediction of land cover. Taking the city of Panzhihua in China as an example, the study constructed training sample data that includes a multi-temporal remote sensing training dataset from 2006, 2010, 2015, and 2021 using GaoFen satellite remote sensing images. Meanwhile, a multitemporal CNN land-use detection model was constructed to generate a land-use transfer matrix by training the dataset. Furthermore, the comprehensive driving factors were selected, including terrain factors (height and slope) and social factors (economic and population density). Then, the CA-Markov model was constructed to predict the land-use development trend in Panzhihua City after ten years. Compared with the traditional methods, experimental results demonstrate that the proposed model can improve the model's automatic interpretation ability and prediction accuracy with an increase of 24.6% in the FoM index and 4.37% in the Kappa coefficient.
Beneficial Effects of Asparagus officinalis Extract Supplementation on Muscle Mass and Strength following Resistance Training and Detraining in Healthy Males

The phytoecdysteroid 20-hydroxyecdysone (20E) is widely used for resistance training (RT). Little is known about its potential ergogenic value and detraining effects post-RT. This study aimed to examine the effects of 20E extracted from Asparagus officinalis (A. officinalis) on muscle strength and mass, as well as anabolic and catabolic hormones following RT and detraining. Twenty males, aged 20.1 ± 1.1 years, were matched and randomly assigned to consume double-blind supplements containing either a placebo (PLA) or 30 mg/day of 20E for 12 weeks of RT and detraining. Before and after RT and detraining, muscle strength and mass and anabolic and catabolic hormones were measured. This study found that 20E reduced cortisol levels significantly (p < 0.05) compared to the PLA, yet no effect was observed on muscle mass, strength, or anabolic hormones after RT. Subsequent to 6 weeks of detraining, the 20E demonstrated a lower percentage change in 1RM bench press/FFM than the PLA (p < 0.05). Compared to the PLA, detraining throughout the 12 weeks resulted in a lower percentage change in thigh (p < 0.05) and chest (p < 0.01) circumferences, as well as reduced cortisol levels (p < 0.01), with 20E. Our findings demonstrate that 20E supplementation is a promising way to maintain muscle mass and strength during detraining. Accordingly, 20E may prevent muscle mass and strength loss due to detraining by lowering catabolic hormone levels.
Immunization with Multiple Virulence Factors Provides Maternal and Neonatal Protection against Group B Streptococcus Serotypes

Group B streptococcus (GBS) commonly colonizes the vaginal tract and is a leading cause of life-threatening neonatal infections and adverse pregnancy outcomes. No effective vaccine is clinically available. Conserved bacterial virulence factors, including those of GBS, have been employed as vaccine components. We investigated serotype-independent protection against GBS by intranasal immunization with six conserved GBS virulence factors (GBSV6). GBSV6 induced systemic and vaginal antibodies and T cell responses in mice. The immunity reduced mouse mortality and vaginal colonization by various GBS serotypes and protected newborn mice of immunized dams against GBS challenge. Intranasal GBSV6 immunization also provided long-lasting protective immunity and had advantages over intramuscular GBSV6 immunization regarding restricting vaginal GBS colonization. Our findings indicate that intranasal immunization targeting multiple conserved GBS virulence factors induces serotype-independent immunity, which protects against GBS infection systemically and vaginally in dams and prevents newborn death. The study presents valuable strategies for GBS vaccine development.
Repeated Transcranial Photobiomodulation with Light-Emitting Diodes Improves Psychomotor Vigilance and EEG Networks of the Human Brain

Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group’s singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.
The Effect of Surface Treatment/Polymer Type on Formation of 3D-Boron Nitride Foams

In this study, the use of boron nitride (BN) foam composites as adsorbents in wastewater treatment using polyvinyl alcohol (PVA), polyvinyl butyral (PVB) and polyester (PE) polymers has been investigated. BN powder has been functionalized by Hummer’s and sodium hydroxide (NaOH) methods to facilitate BN binding with the polymer. Fourier Transform Infrared (FT-IR) results show that hydroxyl (-OH) groups are effectively bounded to the BN structure. Scanning Electron Microscope (SEM) observation demonstrated the 3D interconnected porous structure of the obtained BN foams using different polymers. It is observed that BN and polymer interaction is better in foams formed with PVA and PVB compared to PE polymers. PVA and PVB structure shows a bridge property to link the layers so that a porous network structure is formed. It has been determined that the foam composite modified with Hummer’s method and using PVB as a polymer (h-BN-PVB-H) reaches an adsorption capacity of 8.843 mg/g in 44 hours and provides approximately 18% Crystal Violet (CV) dye removal. h-BN-PVB-H foam composite removes approximately 26% of Reactive Blue 49 (RB 49) dye with an adsorption capacity of 12.313 mg/g in the first 10 minutes. The 3D BN/Polymer foams showed reasonable absorption capacities for olive oil, cyclohexane and toluene from 200-980 wt% relative to the foam’s dry weight. It shows that the produced composite foams can absorb approximately 2-10 times their own weight.
ECMT Framework for Internet of Things: An Integrative Approach Employing In-Memory Attribute Examination and Sophisticated Neural Network Architectures in Conjunction With Hybridized Machine Learning Methodologies

With the proliferation of connected devices in the Internet of Things (IoT), cybersecurity threats have increased. Identifying malicious attacks in IoT requires advanced techniques tailored to this ecosystem. Existing algorithms have limited effectiveness in detecting obfuscated IoT malware. This study proposes the elucidating cybersecurity-promulgated malware taxonomy (ECMT) framework, combining memory analysis and ensemble machine learning (ML), to enhance IoT malware categorization. ECMT integrates support vector classification, quadratic discriminant analysis, and AdaBoost on forensic artifacts from memory dumps to improve detection across families, such as ransomware, spyware, and trojans. ECMT can enable intrusion prevention, information protection, and cybercrime deterrence in IoT environments. Experiments on a balanced data set indicate AdaBoost achieved 96% accuracy, demonstrating ECMT‘s capabilities against complex IoT threats. The integrated approach provides automated, adaptable detection scalable to large IoT deployments through efficient linear models and robust ensemble learning. ECMT addresses concept drift and interpretability via retraining and explanation techniques. Results highlight advanced memory analysis and optimized ML classifiers as a promising solution for robust IoT malware detection despite adversaries’ evolving tactics. Further research can extend platform support, harden models against attacks, and refine streaming input. ECMT establishes a foundation for IoT security by unifying memory forensics, optimized neural architectures, and tailored ensemble learning.
Two Decades of Arrayed Imaging Reflectometry for Sensitive, High-Throughput Biosensing

Arrayed imaging reflectometry (AIR), first introduced in 2004, is a thin-film interference sensor technique that optimizes optical properties (angle of incidence, polarization, substrate refractive index, and thickness) to create a condition of total destructive interference at the surface of a silicon substrate. The advantages of AIR are its sensitivity, dynamic range, multiplex capability, and high-throughput compatibility. AIR has been used for the detection of antibodies against coronaviruses, influenza viruses, Staphylococcus aureus, and human autoantigens. It has also shown utility in detection of cytokines, with sensitivity comparable to bead-based and ELISA assays. Not limited to antibodies or antigens, mixed aptamer and protein arrays as well as glycan arrays have been employed in AIR for differentiating influenza strains. Mixed arrays using direct and competitive inhibition assays have enabled simultaneous measurement of cytokines and small molecules. Finally, AIR has also been used to measure affinity constants, kinetic and at equilibrium. In this review, we give an overview of AIR biosensing technologies and present the latest AIR advances.
Assessment of pesticide contamination in ground water and vegetables using environment friendly methodologies.

A multiclass and multiresidue method for pesticide analysis in tomato has been validated. Extraction and pre-concentration of the pesticide r esidues from acetonitrile extract was performed by using dispersive liquid–liquid microex traction (DLLME) technique followed by gas chromatography–mass detection. DLLME was per formed using carbon tetrachloride as extractive solvent and acetonitril e extract as dispersive solvent, in order to increase enrichment factor of extraction procedure. Parameters of validation indicated the suitability of the method for routine analyses of t hirty pesticides in a large number of samples. In general, pesticide recoveries ranged be tween 70-110% and repeatability ranged between 1 and 20%. The proposed method was applied to the monitoring of pesticide Capítulor 5 Monitoring pesticide residues in greenhouse tomato by combining acetonitrile-based extraction with dispersive liquid-liquid microextraction followed by gas-chromatography-mass spectrometry 116 levels in tomatoes grown during winter in greenhous es. Among compounds considered in this work, cyprodinil was found in tomato at concen trations of 0.33 mg/kg, other pesticides like azoxystrobin, fenhexanid, tolyfluanid, λ-cyhalothrin and trifloxystrobin were also detected but not quantified.
Spatiotemporal variation in bamboo Solar-induced chlorophyll fluorescence (SIF) in China based on the global Orbiting Carbon Observatory-2 (OCO-2) carbon satellite and study on the response to climate and terrain

ABSTRACT Bamboo forests have a high carbon sequestration potential. Solar-induced chlorophyll fluorescence (SIF) provides fresh insights into the temporal and geographical variations in bamboo development and its interactions with the environment. SIF can serve as a probe for photosynthesis. In this study, we used distribution information on Chinese bamboo forests as well as a global SIF product, the global Orbiting Carbon Observatory-2 (OCO-2) SIF (GOSIF), which is derived from the OCO-2 carbon satellite. Thus, we used SIF as an indicator of bamboo forest growth. We investigated the spatial and temporal variations as well as the trends of bamboo forest SIF in China from 2008 to 2019 and explained the response mechanisms of bamboo forest growth to climate change and terrain differences in the region. We also evaluated the combined effects of climate and terrain on bamboo forest growth using the partial least squares path model (PLS-PM). The results were as follows: (1) Low values were found in the west and north, while high values were found in the east and south, according to the average bamboo forest SIF values in China from 2008 to 2019. More than 88% of the pixels had significantly increasing values. In conclusion, bamboo forests in China are growing well. (2) Solar radiation (Rad) and minimum temperature (Tmin) promoted the growth of most bamboo stands, while precipitation (Pre) and maximum temperature (Tmax) did the opposite. (3) The terrain, with a digital elevation model (DEM) less than 1000 m and a slope less than 9°, had a positive effect on bamboo forest SIF. (4) Climate and terrain jointly explained 45% of the bamboo forest growth change, and the major factor was climate change.