Miracle-dz/UniFAR-FTUs huggingface dataset:
Using the Machine Learning Naive Bayes Algorithms for Sentiment Analysis on Online Product Reviews in the Air of Energy Optimization

The purpose of this study was to explore how consumers perceive two of the leading smartphone brands, Samsung and iPhone, using a corpus of tweets. Our approach involved sifting through the tweets to remove any irrelevant content, followed by a sentiment analysis to gain an overall perspective of how each brand was viewed. Our analysis demonstrated that Samsung received a higher proportion of tweets with negative sentiment as compared to iPhone. Moreover, the most common terms in tweets referring to Samsung reflected negative emotions like “concern,” “issue,” and “trouble,” while tweets about iPhone expressed positive emotions such as “like,” “great,” and “best. ” These findings have significant implications for marketing research and offer valuable insights for businesses on how they can utilize social media to enhance their brand reputation and image.
Altered Liver Gene Expression Due to Hypertension and Age in Rats

Hypertension and metabolic syndrome, both of which increase with age, are multifactorial disorders. Their etiology is complex, making it challenging to isolate involved genes. This study aimed to characterize the hepatic gene expression in spontaneously hypertensive rats (SHR) at different ages. Blood pressure in SHR was determined by tail-cuff method at one and three months of age. Hepatic RNA was isolated and gene expression was compared using microarrays. Comparison between SHR and normotensive rats revealed significant variation in gene expression: 98 genes were upregulated and 122 were downregulated in SHR; while 88 genes were upregulated and 139 genes were downregulated in age-matched normotensive rats. Furthermore, within the SHR group, 110 genes were found to be upregulated and 168 genes downregulated across different ages. Analyses via the Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes pathways revealed that several genes are potentially implicated in both, hypertension and metabolic syndrome. The results suggest that SHR display variations in gene expression due to aging, and when compared to normotensive rats. These variations could contribute to the development of hypertension and metabolic syndrome. Microarray studies involving older rats are necessary to further validate these findings.
A Quantitative Study of the Relationship Between Interprofessional Collaboration and Job Satisfaction Among Child Welfare Caseworkers

There is a pressing need to improve job satisfaction among child welfare caseworkers given historically high turnover rates that adversely affect family outcomes. Guided by the job demands-resources model, this study examined whether caseworkers’ job satisfaction was associated with their quality of interprofessional collaboration (IPC). Linear regression models were estimated using cross-sectional data provided by the National Child Welfare Workforce Institute. The sample included caseworkers (N = 1,489) in two states and one urban county in the United States. Results indicated that caseworker job satisfaction increased as their quality of IPC with service providers and court professionals improved. These findings suggest that agency leaders should foster and support IPC as a means of enhancing caseworker job satisfaction.
Objective Extraction for Simplifying Many-Objective Solution Sets

Multi-objective evolutionary algorithms (MOEAs) can find a set of Pareto solutions to the multi-objective optimization problem. However, it is still a challenge for the decision-maker to understand the relationship between various Pareto solutions and pick up the really preferred solution. This article proposes an objective extraction method to simplify the many-objective solution set by reducing the objective dimensionality but keeping the dominance and distribution relationships between solutions. First, a sparse regularized self-representation (SRSR) model is developed to learn the linear relationship among objectives, in which all objectives are determined by a set of base ones. Second, an alternating direction method of multipliers (ADMM) is constructed to solve such a model. Finally, an objective extraction method (SRSR-OE) that can preserve the dominance and distribution relationships between solutions is invented by exploiting the learned relationship. Experimental results show that our SRSR model and ADMM algorithm are efficient for extracting the linear objective relationship, and the developed objective extraction method also has advantages over some state-of-the-art ones in preserving dominance and distribution relationships between solutions after solution set simplification.
FG-4592 relieves diabetic kidney disease severity by influencing metabolic profiles via gut microbiota reconstruction in both human and mouse models

Objective: Diabetic kidney disease (DKD) is one of the most prevalent complications of diabetes mellitus (DM) and is highly associated with devastating outcomes. Hypoxia-inducible factor (HIF), the main transcription factor that regulates cellular responses to hypoxia, plays an important role in regulating erythropoietin (EPO) synthesis. FG-4592 is the HIF stabilizer that is widely used in patients with renal anemia. We investigated the effect of FG-4592 on DKD phenotypes and the pharmacologic mechanism from the perspective of gut microbiota and systemic metabolism. Design: We collected the clinical data of 73 participants, including 40 DKD patients with combined renal anemia treated with FG-4592, and 33 clinical index-matched DKD patients without FG-4592 treatment from The First Affiliated Hospital of Zhengzhou University at the beginning and after a 3–6-month follow-up period. We established DKD mouse models treated by FG-4592 and performed fecal microbiota transplantation from FG-4592-treated DKD mice to investigate the effects of FG-4592 on DKD and to understand this mechanism from a microbial perspective. Untargeted metabolome–microbiome combined analysis was implemented to globally delineate the mechanism of FG-4592 from both microbial and metabolomic aspects. Result: DKD phenotypes significantly improved after 3–6 months of FG-4592 treatment in DKD patients combined with renal anemia, including a decreased level of systolic blood pressure, serum creatinine, and increased estimated glomerular infiltration rate. Such effects were also achieved in the DKD mouse model treated with FG-4592 and can be also induced by FG-4592-influenced gut microbiota. Untargeted plasma metabolomics-gut microbiota analysis showed that FG-4592 dramatically altered both the microbial and metabolic profiles of DKD mice and relieved DKD phenotypes via upregulating beneficial gut microbiota-associated metabolites. Conclusion: FG-4592 can globally relieve the symptoms of DKD patients combined with renal anemia. In the animal experiment, FG-4592 can reconstruct the intestinal microbial profiles of DKD to further upregulate the production of gut-associated beneficial metabolites, subsequently improving DKD phenotypes.
Complete stealthiness false data injection attack design in multisensor systems with attack resource constraints

This article is concerned with the attack design problem of multisensor cyber‐physical systems. Compared with the existing results developed for the single‐sensor system, the attacker is limited to modify partial sensors. To avoid generating alarm for the given detect mechanism, the correlation influence between the attacked and normal sensors is eliminated in the designed stealthiness condition. Then the trace of error covariance is used to measure the attack effect and the coupling information between sensors is also involved. By using the design freedom of stealthiness condition, the detailed attack parameters design and attacked channels selection strategy are derived to achieve the optimal attack performance via a two‐stage method including backstepping and eigenvalue sorting techniques. Finally, numerical simulation examples are provided to verify the effectiveness and advantages of the proposed attack method.
Empirical analysis of traffic volume for the application of the options theory to highway concessions

*************************************************************************************** EL WCTR es un Congreso de reconocido prestigio internacional en el ambito de la investigacion del transporte que hasta el 2010 publicaba sus libros de abstracts con ISBN. Por ello consideramos que deberia seguir teniendose en cuenta para los indicadores de calidad ******************************************************************************************* Investment projects in the field of transportation infrastructures have a high degree of uncertainty and require an important amount of resources. In highway concessions in particular, the calculation of the Net Present Value (NPV) of the project by means of the discount of cash flows, may lead to erroneous results when the project incorporates certain flexibility. In these cases, the theory of real options is an alternative tool for the valuation of concessions. When the variable that generates uncertainty (in our case, the traffic) follows a random walk (or Geometric Brownian Motion), we can calculate the value of the options embedded in the contract starting directly from the process followed by that variable. This procedure notably simplifies the calculation method. In order to test the hypothesis of the evolution of traffic as a Geometric Brownian Motion, we have used the available series of traffic in Spanish highways, and we have applied the Augmented Dickey-Fuller approach, which is the most widely used test for this kind of study. The main result of the analysis is that we cannot reject the hypothesis that traffic follows a Geometric Brownian Motion in the majority of both toll highways and free highways in Spain.
Remote Sensing Image Scene Classification Based on Head-Tail Global Joint Dual Attention Discrimination Network

High-resolution, multi-channel remote sensing images have complex spatial layout and channel structure. Traditional Convolutional Neural Networks (CNNs) methods do not make full use of the features of remote sensing images, ignoring contextual relevance and globality, resulting in insufficient features discrimination and limiting the accuracy of scene classification. To address these issues, we propose a discriminative network HCA-TSA based on head-tail global joint dual attention mechanism. Considering the characteristics between the spatial dimension and the channel dimension, the channel attention module Head-Channel Attention (HCA) and the spatial attention module Tail-Spatial Attention (TSA) are proposed. This network uses the context information discrimination ability of the Gated Recurrent Unit (GRU) module and the structure of the global layout to learn and output the importance weights of different channels and spatial features, pay more attention to the salient features in the remote sensing image, and ignore the insignificant features, thus improve the discriminative power of feature representation. The proposed network can be connected to any benchmark CNNs, and the whole network structure can be trained end-to-end. Through a comprehensive comparative experiment on three public datasets with large differences, AID, UC-Merced and HSRS-SC, the highest classification accuracies in the experimental results are 97.68%, 99.41% and 98.38%, respectively. The results show that the proposed method can effectively discriminate scenarios and obtain competitive classification results, which verifies the effectiveness of the proposed method.
Codium fragile Suppresses PM2.5-Induced Cognitive Dysfunction by Regulating Gut–Brain Axis via TLR-4/MyD88 Pathway

This study was conducted to evaluate the cognitive dysfunction improvement effect of aqueous extract of Codium fragile (AECF) by regulating the imbalance of the gut–brain axis in chronic particulate matter (PM)2.5-exposed mice. The physiological compounds of AECF were identified as hexadecanamide, oleamide, octadecanamide, stearidonic acid, and linolenic acid by the ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC Q-TOF MSE) analysis. To evaluate the effect of PM2.5 on the antioxidant system, superoxide dismutase (SOD) contents, reduced glutathione (GSH) contents, and malondialdehyde (MDA) contents were measured in colon and brain tissues. AECF significantly ameliorated the imbalance of the antioxidant systems. Also, AECF improved intestinal myeloperoxidase (MPO) activity, the abundance of the gut microbiome, short-chain fatty acids (SCFAs) contents, and tight junction protein expression against PM2.5-induced damage. In addition, AECF prevented PM2.5-induced inflammatory and apoptotic expression via the toll-like receptor-4 (TLR-4)/myeloid differentiation primary response 88 (MyD88) pathway in colon and brain tissues. Additionally, AECF enhanced the mitochondrial function, including the mitochondrial membrane potential (MMP) and reactive oxygen species (ROS) contents in brain tissues. Furthermore, AECF regulated the cholinergic system, such as acetylcholine (ACh) contents, acetylcholinesterase (AChE) activity, and protein expression levels of AChE and choline acetyltransferase (ChAT) in brain tissues. To evaluate the effect of cognitive dysfunction caused by PM2.5-induced intestinal dysfunction, behavior tests such as Y-maze, passive avoidance, and Morris water maze tests were performed. From the results of the behavior tests, AECF ameliorated spatial learning and memory, short-term memory, and long-term learning and memory function. This study confirmed that AECF reduced PM2.5-induced cognitive dysfunction by regulating gut microbiome and inflammation, apoptosis, and mitochondrial function by enhancing the gut–brain axis. Based on these results, this study suggests that AECF, which contains fatty acid amides, might be a potential material for ameliorating PM2.5-induced cognitive dysfunction via gut–brain axis improvement.
Toward Improved Real‐Time Rainfall Intensity Estimation Using Video Surveillance Cameras

Under global climate change, urban flooding occurs frequently, leading to huge economic losses and human casualties. Extreme rainfall is one of the direct and key causes of urban flooding, and accurate rainfall estimates at high spatiotemporal resolution are of great significance for real‐time urban flood forecasting. Using existing rainfall intensity measurement technologies, including ground rainfall gauges, ground‐based radar, and satellite remote sensing, it is challenging to obtain estimates of the desired quality and resolution. However, an approach based on processing distributed surveillance camera network imagery through machine learning algorithms to estimate rainfall intensities shows considerable promise. Here, we present a novel approach that first extracts raindrop information from the surveillance camera images (rather than using the raw imagery directly), followed by the use of convolutional neural networks to estimate rainfall intensity from the resulting raindrop information. Evaluation of the approach on 12 rainfall events under both daytime and nighttime conditions shows that generalization ability, and especially nighttime predictive performance, is significantly improved. This represents an important step toward achieving real‐time, high spatiotemporal resolution, measurement of urban rainfall at relatively low cost.
Combined Nano-Vector Mediated-Transfer to Suppress HIV-1 Infection with Targeted Antibodies in-vitro

Introduction Broadly neutralizing antibodies (bNAbs) have the ability to neutralize a considerable breadth of genetically diverse human immunodeficiency virus (HIV) strains. Passive immunization can potentially provide protection against HIV infection in animal models. However, the direct antibody infusion effect is limited due to the short half-life and deficient immunogenicity of the antibody. As an alternative strategy, we propose the use of nano viral vectors, specifically the adeno-associated virus (AAV), to continuously and systematically produce bNAbs against HIV. Methods Plasmids expressing bNAbs PG9, PG16, 10E8, and NIH45-46 antibodies were constructed, targeting three different epitopes of HIV. Additionally, the bNAbs gene mediated by rAAV8 was administered to generate long-term expression with a single injection. We established both single and combined immunization groups. The neutralizing activity of antibodies expressed in mice sera was subsequently evaluated. Results The expression of bNAbs in BALB/c mice can last for >24 weeks after a single intramuscular injection of rAAV8. Further studies show that neutralization of the HIV pseudovirus by sera from co-immunized mice with rAAV8 expressing 10E8 and PG16 was enhanced compared with mice immunized with 10E8 or PG16 alone. Conclusion The prolonged expression of neutralizing antibodies can be maintained over long periods in BALB/c mice. This combined immunization is a promising candidate strategy for HIV treatment.
Khanty : people of the taiga : surviving the twentieth century

Drawing on nearly twenty years of fieldwork, as well as ethnohistory, politics, and economics, this volume takes a close look at changes in the lives of the indigenous Siberian Khanty people and draws crucial connections between those changes and the social, cultural, and political transformation that swept Russia during the transition to democracy. Delving deeply into the history of the Khanty - who were almost completely isolated prior to the Russian revolution - the authors show how the customs, traditions, and knowledge of indigenous people interact with and are threatened by events in the larger world.
Exploring transient modification of hyperbolic metamaterials using InAsSb-based semiconductor

Quantum photonics opens doors for applications in sensing, data transfer, and quantum computing. Application areas in many of these technologies require in some manner tunable single photon sources. Hyperbolic metamaterials, composed of metallic building blocks embedded in dielectric media control emission lifetime by modifying the photon density of states. However, no previous efforts have explored the transient modification of metamaterials to modulate emission. Antimony-based semiconductor hyperbolic metamaterials (SHMMs) offer a route to modulation of these resonances at the mid-infrared (IR) wavelength range, which would modulate emission. In this work, we demonstrate the ability to create an ultrafast hyperbolic momentum state in metallic InAsSb/dielectric GaSb stacks and explore the possibility of transient modification of metamaterials by controlling the optical properties of photon emission. If successful, this study will establish a new platform for deterministic single photon emission that can be integrable into opto-electronic platforms and dramatically advance optical quantum technologies. Properly engineered quantum well structures are grown by molecular beam epitaxy with Si-doping in order to convert the InAsSb layers from dielectric to metallic at IR frequencies. The carrier excitation scheme of the engineered hyperbolic stacks is investigated in a variety of excitation levels using pump–probe measurements. The photo-excited carriers in the structure with a metal fraction of ∼0.5 show a polarization dependent reflectivity change, which indicates a transient hyperbolic metamaterial state in the heterostructure induced by the pump laser.
Biologically Relevant Murine Models of Chronic Pseudomonas aeruginosa Respiratory Infection

Pseudomonas aeruginosa (P. aeruginosa) is an opportunistic pathogen and the leading cause of infection in patients with cystic fibrosis (CF). The ability of P. aeruginosa to evade host responses and develop into chronic infection causes significant morbidity and mortality. Several mouse models have been developed to study chronic respiratory infections induced by P. aeruginosa, with the bead agar model being the most widely used. However, this model has several limitations, including the requirement for surgical procedures and high mortality rates. Herein, we describe novel and adapted biologically relevant models of chronic lung infection caused by P. aeruginosa. Three methods are described: a clinical isolate infection model, utilising isolates obtained from patients with CF; an incomplete antibiotic clearance model, leading to bacterial bounce-back; and the establishment of chronic infection; and an adapted water bottle chronic infection model. These models circumvent the requirement for a surgical procedure and, importantly, can be induced with clinical isolates of P. aeruginosa and in wild-type mice. We also demonstrate successful induction of chronic infection in the transgenic βENaC murine model of CF. We envisage that the models described will facilitate the investigations of host and microbial factors, and the efficacy of novel antimicrobials, during chronic P. aeruginosa respiratory infections.
Use of Nanocarriers Containing Antitrypanosomal Drugs for the Treatment of Chagas Disease

Chagas disease, caused by the Trypanosoma cruzi parasitic protozoan, is a neglected tropical disease (NTD) of significant incidence in Latin America. Transmission to humans and other mammals is mainly via the vector insect from the Reduviidae family, popularly known as the kissing bug. There are other transmission means, such as through congenital transmission, blood transfusions, organ transplantations, and the consumption of contaminated food. For more than 50 years, the disease has been treated with benznidazole and nifurtimox, which are only effective during the acute phase of the disease. In addition to their low efficacy in the chronic phase, they cause many adverse effects and are somewhat selective. The use of nanocarriers has received significant attention due to their ability to encapsulate and release therapeutic agents in a controlled manner. Generally, their diameter ranges from 100 to 300 nanometers. The objective of this scoping review was to perform a search of the literature for the use of nanocarriers as an alternative for improving the treatment of Chagas disease and to suggest future research. Bibliographic searches were carried out in the Web of Science and PubMed scientific databases from January 2012 to May 2023, using the “Chagas disease and Trypanosoma cruzi and nanoparticles” keywords, seeking to gather the largest number of articles, which were evaluated using the inclusion and exclusion criteria. After analyzing the papers, the results showed that nanocarriers offer physiological stability and safety for the transport and controlled release of drugs. They can increase solubility and selectivity against the parasite. The in vitro assays showed that the trypanocidal activity of the drug was not impaired after encapsulation. In the in vivo assays, parasitemia reduction and high survival and cure rates in animals were obtained during both phases of the disease using lower doses when compared to the standard treatment. The scoping review showed that nanocarriers are a promising alternative for the treatment of Chagas disease.