Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial or Random Cross-Validation? The Effect of Resampling Methods in Predicting Groundwater Salinity with Machine Learning in Mediterranean Region

Machine learning (ML) algorithms are extensively used with outstanding prediction accuracy. However, in some cases, their overfitting capabilities, along with inadvertent biases, might produce overly optimistic results. Spatial data are a special kind of data that could introduce biases to ML due to their intrinsic spatial autocorrelation. To address this issue, a special resampling method has emerged called spatial cross-validation (SCV). The purpose of this study was to evaluate the performance of SCV compared with conventional random cross-validation (CCV) used in most ML studies. Multiple ML models were created with CCV and SCV to predict groundwater electrical conductivity (EC) with data (A) from Rhodope, Greece, in the summer of 2020; (B) from the same area but at a different time (summer 2019); and (C) from a new area (the Salento peninsula, Italy). The results showed that the SCV provides ML models with superior generalization capabilities and, hence, better prediction results in new unknown data. The SCV seems to be able to capture the spatial patterns in the data while also reducing the over-optimism bias that is often associated with CCV methods. Based on the results, SCV could be applied with ML in studies that use spatial data.
Efficient Method for Continuous IoT Data Stream Indexing in the Fog-Cloud Computing Level

Internet of Things (IoT) systems include many smart devices that continuously generate massive spatio-temporal data, which can be difficult to process. These continuous data streams need to be stored smartly so that query searches are efficient. In this work, we propose an efficient method, in the fog-cloud computing architecture, to index continuous and heterogeneous data streams in metric space. This method divides the fog layer into three levels: clustering, clusters processing and indexing. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to group the data from each stream into homogeneous clusters at the clustering fog level. Each cluster in the first data stream is stored in the clusters processing fog level and indexed directly in the indexing fog level in a Binary tree with Hyperplane (BH tree). The indexing of clusters in the subsequent data stream is determined by the coefficient of variation (CV) value of the union of the new cluster with the existing clusters in the cluster processing fog layer. An analysis and comparison of our experimental results with other results in the literature demonstrated the effectiveness of the CV method in reducing energy consumption during BH tree construction, as well as reducing the search time and energy consumption during a k Nearest Neighbor (kNN) parallel query search.
Proof-of-Principle Study of Inflammasome Signaling Proteins as Diagnostic Biomarkers of the Inflammatory Response in Parkinson’s Disease

Parkinson’s disease (PD) is a neurodegenerative disorder marked by the death of dopaminergic neurons in the midbrain, the accumulation of α-synuclein aggregates, and motor deficits. A major contributor to dopaminergic neuronal loss is neuroinflammation. The inflammasome is a multiprotein complex that perpetuates neuroinflammation in neurodegenerative disorders including PD. Increases in inflammasome proteins are associated with worsened pathology. Thus, the inhibition of inflammatory mediators has the potential to aid in PD treatment. Here, we investigated inflammasome signaling proteins as potential biomarkers of the inflammatory response in PD. Plasma from PD subjects and healthy age-matched controls were evaluated for levels of the inflammasome protein apoptosis-associated speck-like protein containing a caspase recruitment domain (ASC), caspase-1, and interleukin (IL)-18. This was carried out using Simple Plex technology to identify changes in inflammasome proteins in the blood of PD subjects. The area under the curve (AUC) was obtained through calculation of the receiver operating characteristics (ROC) to obtain information on biomarker reliability and traits. Additionally, we completed a stepwise regression selected from the lowest Akaike information criterion (AIC) to assess how the inflammasome proteins caspase-1 and ASC contribute to IL-18 levels in people with PD. PD subjects demonstrated elevated caspase-1, ASC, and IL-18 levels when compared to controls; each of these proteins were found to be promising biomarkers of inflammation in PD. Furthermore, inflammasome proteins were determined to significantly contribute to and predict IL-18 levels in subjects with PD. Thus, we demonstrated that inflammasome proteins serve as reliable biomarkers of inflammation in PD and that inflammasome proteins provide significant contributions to IL-18 levels in PD.
Hypericum perforatum L. and the Underlying Molecular Mechanisms for Its Choleretic, Cholagogue, and Regenerative Properties

Any defects in bile formation, secretion, or flow may give rise to cholestasis, liver fibrosis, cirrhosis, and hepatocellular carcinoma. As the pathogenesis of hepatic disorders is multifactorial, targeting parallel pathways potentially increases the outcome of therapy. Hypericum perforatum has been famed for its anti-depressive effects. However, according to traditional Persian medicine, it helps with jaundice and acts as a choleretic medication. Here, we will discuss the underlying molecular mechanisms of Hypericum for its use in hepatobiliary disorders. Differentially expressed genes retrieved from microarray data analysis upon treatment with safe doses of Hypericum extract and intersection with the genes involved in cholestasis are identified. Target genes are located mainly at the endomembrane system with integrin-binding ability. Activation of α5β1 integrins, as osmo-sensors in the liver, activates a non-receptor tyrosine kinase, c-SRC, which leads to the insertion of bile acid transporters into the canalicular membrane to trigger choleresis. Hypericum upregulates CDK6 that controls cell proliferation, compensating for the bile acid damage to hepatocytes. It induces ICAM1 to stimulate liver regeneration and regulates nischarin, a hepatoprotective receptor. The extract targets the expression of conserved oligomeric Golgi (COG) and facilitates the movement of bile acids toward the canalicular membrane via Golgi-derived vesicles. In addition, Hypericum induces SCP2, an intracellular cholesterol transporter, to maintain cholesterol homeostasis. We have also provided a comprehensive view of the target genes affected by Hypericum’s main metabolites, such as hypericin, hyperforin, quercitrin, isoquercitrin, quercetin, kaempferol, rutin, and p-coumaric acid to enlighten a new scope in the management of chronic liver disorders. Altogether, standard trials using Hypericum as a neo-adjuvant or second-line therapy in ursodeoxycholic-acid-non-responder patients define the future trajectories of cholestasis treatment with this product.
Mechanistic Insights into the Antibiofilm Mode of Action of Ellagic Acid

Bacterial biofilm is a major contributor to the persistence of infection and the limited efficacy of antibiotics. Antibiofilm molecules that interfere with the biofilm lifestyle offer a valuable tool in fighting bacterial pathogens. Ellagic acid (EA) is a natural polyphenol that has shown attractive antibiofilm properties. However, its precise antibiofilm mode of action remains unknown. Experimental evidence links the NADH:quinone oxidoreductase enzyme WrbA to biofilm formation, stress response, and pathogen virulence. Moreover, WrbA has demonstrated interactions with antibiofilm molecules, suggesting its role in redox and biofilm modulation. This work aims to provide mechanistic insights into the antibiofilm mode of action of EA utilizing computational studies, biophysical measurements, enzyme inhibition studies on WrbA, and biofilm and reactive oxygen species assays exploiting a WrbA-deprived mutant strain of Escherichia coli. Our research efforts led us to propose that the antibiofilm mode of action of EA stems from its ability to perturb the bacterial redox homeostasis driven by WrbA. These findings shed new light on the antibiofilm properties of EA and could lead to the development of more effective treatments for biofilm-related infections.
Establishment of a Murine Chronic Anorexia Nervosa Model

Anorexia nervosa (AN) is associated with hyperactivity, amenorrhea, and brain atrophy. The underlying pathophysiology is mostly unknown, and new targets for therapeutic interventions are needed. This study aimed to systematically establish a murine AN model with the parameter extent of starvation, animal age, and length of starvation for functional studies. The activity-based anorexia (ABA) model combines food restriction with running wheel access. Early adolescent and adolescent mice received 40% of their baseline food intake until a 20% or 25% weight reduction was reached (acute starvation). To mimic chronic starvation, body weight loss was maintained for another two weeks. Running activity was examined using wheel sensors, while amenorrhea was investigated by analysis of vaginal smears. Brain sections were used to analyze cerebral cortex volumes. Acute starvation did not lead to either AN-related symptoms, whereas chronic starvation led to hyperactivity and amenorrhea except in the adolescent cohort with 20% weight reduction. Only ABA mice with 25% weight reduction revealed a cortex volume reduction. The optimal parameters to mirror AN-related symptoms included a 25% weight reduction, early adolescent or adolescent mice, and chronic starvation. The ABA model enables functional analysis of the impact of chronic AN on the underlying hormonal, behavioral, and brain pathophysiology.
Immature Stages of Genus Hexatoma (Diptera, Limoniidae) in the Korean Peninsula

The genus Hexatoma Latreille, 1809 is a large group of aquatic crane flies, with almost 600 species worldwide. The largest subgenus is Eriocera Macquart, 1838, which includes all nine species known from the Korean Peninsula. Molecular methods were used to associate Hexatoma larvae with their putative adult species from South Korea. Mitochondrial Cytochrome c Oxidase Subunit I (COI) gene fragment sequences (DNA barcodes) of recently collected adults of H. (E.) gifuensis, H. (E.) ilwola, H. (E.) pernigrina, and H. (E.) pianigra were compared with twelve sequences of Hexatoma larvae. The larvae of H. (E.) pernigrina, H. (E.) pianigra, and H. (E.) gifuensis were associated with their putative adults. The larvae of H. (E.) gifuensis and H. (E.) pianigra and the larvae and pupae of H. (E.) pernigrina are described and illustrated. The larvae of two species not associated with any adult are described, and their COI gene fragment sequences (DNA barcodes) are presented. This paper presents the morphological characteristics suitable for distinguishing larval species. A key for the identification of larvae of the genus Hexatoma on the Korean Peninsula has been compiled. H (E.) sachalinensis is recorded from the Korean Peninsula for the first time. Our study is the first contribution to the Hexatoma larvae taxonomy using phylogenetic analysis based on mitochondrial COI fragment (DNA barcode) and one of the first attempts to reveal phylogenetic relationships between Hexatoma species using molecular markers.
Suppression of Mainlobe Jammers with Quadratic Element Pulse Coding in MIMO Radar

The problem of suppressing mainlobe deceptive jammers, which spoof radar systems by generating multiple false targets, has attracted widespread attention. To tackle this problem, in this paper, the multiple-input multiple-output (MIMO) radar system was utilized by applying a quadratic element phase code (QEPC) to the transmitted pulses of different elements. In the receiver, by utilizing the spatial frequency and Doppler frequency offset generated after decoding, the jammers were equivalently distributed in the sidelobes of the joint Doppler-transmit-receive domain and were distinguishable from the true target. Then, further spatial frequency compensation and Doppler compensation were performed to align the true target to the zero point in the transmit spatial and Doppler domains. Moreover, by designing appropriate coding coefficients, the jammers were suppressed by data-independent Doppler-transmit-receive three-dimensional beamforming. However, the beamforming performance was sensitive to angular estimation mismatches, resulting in performance degradation of jammer suppression. To this end, a center-boundary null-broadening control (CBNBC) approach was used to broaden the nulls in the equivalent beampattern by generating multiple artificial jammers with preset powers around the nulls. Thus, the false targets (FTs) with deviations were sufficiently suppressed in the broadened notches. Numerical simulations and theoretical analysis demonstrated the performance of the developed jammer suppression method.
CRISPR/Cas9 Based Cell-Type Specific Gene Knock-Out in Arabidopsis Roots

CRISPR/Cas9 (hereafter Cas9)-mediated gene knockout is one of the most important tools for studying gene function. However, many genes in plants play distinct roles in different cell types. Engineering the currently used Cas9 system to achieve cell-type-specific knockout of functional genes is useful for addressing the cell-specific functions of genes. Here we employed the cell-specific promoters of the WUSCHEL RELATED HOMEOBOX 5 (WOX5), CYCLIND6;1 (CYCD6;1), and ENDODERMIS7 (EN7) genes to drive the Cas9 element, allowing tissue-specific targeting of the genes of interest. We designed the reporters to verify the tissue-specific gene knockout in vivo. Our observation of the developmental phenotypes provides strong evidence for the involvement of SCARECROW (SCR) and GIBBERELLIC ACID INSENSITIVE (GAI) in the development of quiescent center (QC) and endodermal cells. This system overcomes the limitations of traditional plant mutagenesis techniques, which often result in embryonic lethality or pleiotropic phenotypes. By allowing cell-type-specific manipulation, this system has great potential to help us better understand the spatiotemporal functions of genes during plant development.
A Review of Groundwater Heat Pump Systems in the Italian Framework: Technological Potential and Environmental Limits

For new buildings in densely urbanised cities, groundwater heat pump systems (GWHPs) represent a concrete, effective solution for decarbonising existing energy systems. Environmental factors must be considered to limit the GWHP system’s impact on the subsurface. Particular attention must be given to the long-term sustainability of groundwater abstraction modalities and the development of a thermally affected zone around re-injection wells. Simplified solutions and numerical models have been applied to predict subsurface heat transport mechanisms; these simulations allow researchers to consider site-specific geological conditions, transient heat and groundwater flow regimes, and anisotropies in the subsurface media. This paper presents a comprehensive overview of the current research on GWHPs and discusses the benefits and limitations of their diffusion in Italy. The sources used provide information on and examples of the correct methodological approaches for depicting the induced variations while avoiding the overestimation or underestimation of the impact that GWHPs have on exploited aquifers.
Estimation of Physiologic Pressures: Invasive and Non-Invasive Techniques, AI Models, and Future Perspectives

The measurement of physiologic pressure helps diagnose and prevent associated health complications. From typical conventional methods to more complicated modalities, such as the estimation of intracranial pressures, numerous invasive and noninvasive tools that provide us with insight into daily physiology and aid in understanding pathology are within our grasp. Currently, our standards for estimating vital pressures, including continuous BP measurements, pulmonary capillary wedge pressures, and hepatic portal gradients, involve the use of invasive modalities. As an emerging field in medical technology, artificial intelligence (AI) has been incorporated into analyzing and predicting patterns of physiologic pressures. AI has been used to construct models that have clinical applicability both in hospital settings and at-home settings for ease of use for patients. Studies applying AI to each of these compartmental pressures were searched and shortlisted for thorough assessment and review. There are several AI-based innovations in noninvasive blood pressure estimation based on imaging, auscultation, oscillometry and wearable technology employing biosignals. The purpose of this review is to provide an in-depth assessment of the involved physiologies, prevailing methodologies and emerging technologies incorporating AI in clinical practice for each type of compartmental pressure measurement. We also bring to the forefront AI-based noninvasive estimation techniques for physiologic pressure based on microwave systems that have promising potential for clinical practice.
Weather Forecasting Using Radial Basis Function Neural Network in Warangal, India

Weather forecasting is an essential task in any region of the world for proper planning of various sectors that are affected by climate change. In Warangal, most sectors, such as agriculture and electricity, are mainly influenced by climate conditions. In this study, weather (WX) in the Warangal region was forecast in terms of temperature and humidity. A radial basis function neural network was used in this study to forecast humidity and temperature. Humidity and temperature data were collected for the period of January 2021 to December 2021. Based on the simulation results, it is observed that the radial basis function neural network model performs better than other machine learning models when forecasting temperature and humidity.
The Design and Development of a Foot-Detection Approach Based on Seven-Foot Dimensions: A Case Study of a Virtual Try-On Shoe System Using Augmented Reality Techniques

Unsuitable shoe shapes and sizes are a critical reason for unhealthy feet, may severely contribute to chronic injuries such as foot ulcers in susceptible people (e.g., diabetes patients), and thus need accurate measurements in the manner of expert-based procedures. However, the manual measure of such accurate shapes and sizes is labor-intensive, time-consuming, and impractical to apply in a real-time system. This research proposes a foot-detection approach using expert-like measurements to address this concern. It combines the seven-foot dimensions model and the light detection and ranging sensor to encode foot shapes and sizes and detect the dimension surfaces. The graph-based algorithms are developed to present seven-foot dimensions and visualize the shoe’s model based on the augmented reality (AR) technique. The results show that our approach can detect shapes and sizes more effectively than the traditional approach, helps the system imitate expert-like measurements accurately, and can be employed in intelligent applications for susceptible people-based feet measurements.
The Performance of Paralleling Technique and Bisecting Angle Technique for Taking Periapical Radiographs: A Systematic Review

Periapical radiography is a routine radiographic procedure performed by dentists on a daily basis. It can be taken with two techniques, the paralleling technique (P tech) and the bisecting angle technique (B tech). This systematic review aimed to identify the relevant literature, compare the use of P and B techs across various dental specialties, and determine the most appropriate technique to be used for different purposes in taking periapical radiographs. In January 2023, we searched PubMed, Web of Science, Scopus, and Google Scholar to identify the studies that compared the two radiographic techniques. The search string was: (paralleling AND (“bisecting angle” OR “bisected angle”)). Manual reference tracing was also performed to identify the studies potentially missed. After screening, 26 studies were included for the qualitative review. The 26 included studies were published between 1976 and 2021. Ten of the studies were about general dentistry (dental radiology in general applications), whereas another ten studies were related to endodontics, such as working length estimation. Most studies advocated the use of the P tech for general, endodontics, implantology, and other indications. B tech was advocated for patients with a low palatal height. More future studies are needed to evaluate their performance in different scenarios with standardized equipment and radiographic positioning.
Introducing Computerized Technology to Nurses: A Model Based on Cognitive Instrumental and Social Influence Processes

The use of computerized technologies as an integral part of nursing has become a reality in the health care system. Studies present different approaches that range from accepting technology as a health promoter to an approach that opposes computerization. This study, which examined social and instrumental processes that influence nurses’ attitudes toward computer technology, will present a model for the optimal assimilation of computer technology in the nurses’ work environment. The study, which included 224 participants, was designed as a mixed method and included questionnaires and semi-structured interviews of participants. The data were analyzed to understand the factors that influenced nurses’ attitudes toward the use of computer technology. The research findings show that the more clearly nurses understand the positive impact of using technology on the quality of care, the more positive their response to changes in registration and reporting methods. It is not surprising that the research findings found that cognitive instrumental processes and social influence processes have a positive effect on the perceived usefulness of using computer technologies. The unusual finding was the fact that cognitive instrumental processes were the main factor influencing the assimilation of computer technology even though nursing is a social profession.
Connecting the Dots between Housing Design and COVID-19

This article has aimed to analyze the intellectual structure associated with the contributions made by academics and practitioners of architecture in the association between housing and COVID-19 in the years 2019–2021. The main results reveal the possibility of establishing a classification, by topics that suggest the necessary interdisciplinary collaboration for housing, to meet the needs and desires of its users in the wake of this pandemic. The network analysis has allowed the identification of overlapping communities through interconnection concepts to other groups or clusters. Thus, it has been possible to explore the multidimensionality of the housing–COVID connection and the interrelationships for future research and its possible extension. In this sense, the importance of the specific concepts associated with very detailed elements, sensations and spaces in buildings has been identified, including concepts such as the air quality and the need for green spaces, the presence or not of balconies, the need for natural light, the existence of cross ventilation or the possibility of incorporating technology or home automation to facilitate and save resources in daily life.