Miracle-dz/UniFAR-FTUs huggingface dataset:
Removal of Cu(II) Ions from Aqueous Solutions by Ferrochrome Ash: Investigation of Mechanism and Kinetics

The release of Cu into water is an immediate concern that negatively affects environmental health. To eliminate this problem, the adsorption of Cu(II) on varying substances has been studied widely for two decades. The utilization of low-cost adsorbents obtained from industrial wastes hits two targets with one arrow. In the present study, ferrochrome ash (FCA) obtained from the baghouse filters of ferrochrome facilities was utilized to adsorb Cu(II) for the first time in the literature. To achieve this goal, initially the FCA was characterized by XRD, XRF, SEM, EDS, and BET analyses, and then washing and grinding pretreatment was conducted to eliminate the Cr dissolution and increase the surface area of the FCA. Adsorption experiments were conducted in 100–1000 mg/L Cu(II) solution on 0.4–8 g/L FCA for 0–300 min. As a result, it was concluded that a maximum adsorption capacity was obtained as 298.75 mg/g, which makes the FCA an applicable adsorbent for Cu(II) adsorption. Additionally, a pH range of 3–6 is favorable. The Cu(II) adsorption on FCA fits the pseudo-second order (PSO) kinetics and Freundlich isotherm models well. The Cu(II)-adsorbed FCA was investigated by SEM, EDS, and FT-IR analyses. According to the results, it can be deduced that the adsorption mechanism is chemisorption, which involves the valency forces between the metal and the adsorbent.
Network Pharmacology Revealed the Mechanisms of Action of Lithospermum erythrorhizon Sieb on Atopic Dermatitis

Aim The application of network analysis algorithms promoted the development of network pharmacology. This study aimed to combine network pharmacology and signed random walk with restart (SRWR) to reveal the mechanism by which Lithospermum erythrorhizon Sieb (LES) exerts effects on atopic dermatitis (AD). Methods The compounds and targets of LES were retrieved from Traditional Chinese Medicine Integrated Database (TCMID) and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), and important compounds and targets were identified by intersection analysis and protein–protein interaction (PPI) network. Results We found that active LES-derived compounds such as caffeic acid, Isovaleric acid, Arnebinol, and Alannan may inhibit PTGS2, HSP90AA1 and MAPK14, which are key mediators involved in PI3K-Akt pathway, vascular endothelial growth factor signaling pathway, Fc epsilon RI signaling pathway, and calcium signaling pathway. Conclusion The application of SRWR could identify potential targets of LES with a low false-positive rate and help elucidate the mechanism of action of traditional Chinese medicine.
Prescribed performance synchronization for fractional-order chaotic systems

In this paper the synchronization for two different fractional-order chaotic systems, capable of guaranteeing synchronization error with prescribed performance, is investigated by means of the fractional-order control method. By prescribed performance synchronization we mean that the synchronization error converges to zero asymptotically, with convergence rate being no less than a certain prescribed function. A fractional-order synchronization controller and an adaptive fractional-order synchronization controller, which can guarantee the prescribed performance of the synchronization error, are proposed for fractional-order chaotic systems with and without disturbances, respectively. Finally, our simulation studies verify and clarify the proposed method.
Fuzzy adaptive event-triggered control for a class of uncertain nonlinear systems subject to actuator dead-zone

The article inquiries an event-trigger-based adaptive fuzzy state feedback control for indeterminate nonlinear systems comprising input dead-zone. We estimate unknown nonlinear terms containing the uncertain parameter by utilizing fuzzy logic systems (FLSs) . An adaptive controller and an auxiliary system are co-construct to get rid of the impact of dead-zone. The event-triggered control (ETC) algorithm is raised to alleviate the corresponding encumbrance. Furthermore, a variable interval technology is adopted to handle the algebraic ring issue generated by nonstrict-feedback nonlinear systems. The presented control framework can ensure that all closed ring signs are limited. Finally, a practical emulation consequence of an underwater vehicle is developed to certify the availability of the given control project.
On the Alleged Backwards Referral of Experiences and Its Relevance to the Mind-Body Problem

A remarkable hypothesis has recently been advanced by Libet and promoted by Eccles which claims that there is standardly a backwards referral of conscious experiences in time, and that this constitutes empirical evidence for the failure of identity of brain states and mental states. Libet's neurophysiological data are critically examined and are found insufficient to support the hypothesis. Additionally, it is argued that even if there is a temporal displacement phenomenon to be explained, a neurophysiological explanation is most likely.
Disaggregated Attendance Demand: Comparing Daily Ticket Purchasers and Season Ticket Holders in K-League 1

This study investigates differences in the preferences of daily ticket purchasers and season ticket holders, focusing on outcome uncertainty. Using unique game-level attendance data of both daily ticket purchasers and season ticket holders for every team in the Korean top-tier professional soccer league, we find heterogeneity in demand between daily ticket purchasers and season ticket holders with respect to outcome uncertainty, preference for home team success, team performance, geographical distance between competing teams, and weekend games. Our results suggest that season ticket holders do not care as much about their team's performance and outcome uncertainty as daily ticket purchasers do.
An Infrared image process approach for Military Aircraft Recognition with single training sample

Military target recognition task often faces the situation of lack of training samples. In some extreme conditions, each category of military target may have only one training sample. This paper proposed a method to deal with the military aircraft recognition task with only one training sample, first the HOG and Hu moment invariant features are extracted, and then sparse based classification framework is used as the recognition algorithm. Experimental results show that the proposed method can achieve better recognition accuracy rate than the existing methods when there is only one single training sample.
Identification of IRAK1BP1 as a candidate prognostic factor in lung adenocarcinoma

Introduction Lung cancer is one of the major causes of cancer-related mortality worldwide. High-throughput RNA sequencing (RNA-seq) of surgically removed tumors has been used to identify new biomarkers of lung cancer; however, contamination by non-tumor cells in the tumor microenvironment significantly interferes with the search for novel biomarkers. Tumor organoids, as a pre-clinical cancer model, exhibit similar molecular characteristics with tumor samples while minimizing the interference from other cells. Methods and Results Here we analyzed six RNA-seq datasets collected from different organoid models, in which cells with oncogenic mutations were reprogrammed to mimic lung adenocarcinoma (LUAD) tumorigenesis. We uncovered 9 LUAD-specific biomarker genes by integrating transcriptomic data from multiple sources, and identified IRAK1BP1 as a novel predictor of LUAD disease outcome. Validation with RNA-seq and microarray data collected from multiple patient cohorts, as well as patient-derived xenograft (PDX) and lung cancer cell line models confirmed that IRAK1BP1 expression was significantly lower in tumor cells, and had no correlation with known markers oflung cancer prognosis. In addition, loss of IRAK1BP1 correlated with the group of LUAD patients with worse survival; and gene-set enrichment analysis using tumor and cell line data implicated that high IRAK1BP1 expression was associated with suppression of oncogenic pathways. Discussion In conclusion, we demonstrate that IRAK1BP1 is a promising biomarker of LUAD prognosis.
Efficient Pause Extraction and Encode Strategy for Alzheimer’s Disease Detection Using Only Acoustic Features from Spontaneous Speech

Clinical studies have shown that speech pauses can reflect the cognitive function differences between Alzheimer’s Disease (AD) and non-AD patients, while the value of pause information in AD detection has not been fully explored. Herein, we propose a speech pause feature extraction and encoding strategy for only acoustic-signal-based AD detection. First, a voice activity detection (VAD) method was constructed to detect pause/non-pause feature and encode it to binary pause sequences that are easier to calculate. Then, an ensemble machine-learning-based approach was proposed for the classification of AD from the participants’ spontaneous speech, based on the VAD Pause feature sequence and common acoustic feature sets (ComParE and eGeMAPS). The proposed pause feature sequence was verified in five machine-learning models. The validation data included two public challenge datasets (ADReSS and ADReSSo, English voice) and a local dataset (10 audio recordings containing five patients and five controls, Chinese voice). Results showed that the VAD Pause feature was more effective than common feature sets (ComParE: 6373 features and eGeMAPS: 88 features) for AD classification, and that the ensemble method improved the accuracy by more than 5% compared to several baseline methods (8% on the ADReSS dataset; 5.9% on the ADReSSo dataset). Moreover, the pause-sequence-based AD detection method could achieve 80% accuracy on the local dataset. Our study further demonstrated the potential of pause information in speech-based AD detection, and also contributed to a more accessible and general pause feature extraction and encoding method for AD detection.
Harnessing Machine Learning in Tackling Domestic Violence—An Integrative Review

Domestic violence (DV) is a public health crisis that threatens both the mental and physical health of people. With the unprecedented surge in data available on the internet and electronic health record systems, leveraging machine learning (ML) to detect obscure changes and predict the likelihood of DV from digital text data is a promising area health science research. However, there is a paucity of research discussing and reviewing ML applications in DV research. Methods: We extracted 3588 articles from four databases. Twenty-two articles met the inclusion criteria. Results: Twelve articles used the supervised ML method, seven articles used the unsupervised ML method, and three articles applied both. Most studies were published in Australia (n = 6) and the United States (n = 4). Data sources included social media, professional notes, national databases, surveys, and newspapers. Random forest (n = 9), support vector machine (n = 8), and naïve Bayes (n = 7) were the top three algorithms, while the most used automatic algorithm for unsupervised ML in DV research was latent Dirichlet allocation (LDA) for topic modeling (n = 2). Eight types of outcomes were identified, while three purposes of ML and challenges were delineated and are discussed. Conclusions: Leveraging the ML method to tackle DV holds unprecedented potential, especially in classification, prediction, and exploration tasks, and particularly when using social media data. However, adoption challenges, data source issues, and lengthy data preparation times are the main bottlenecks in this context. To overcome those challenges, early ML algorithms have been developed and evaluated on DV clinical data.
Monocyte and Macrophage in Neuroblastoma: Blocking Their Pro-Tumoral Functions and Strengthening Their Crosstalk with Natural Killer Cells

Over the past decade, immunotherapy has represented an enormous step forward in the fight against cancer. Immunotherapeutic approaches have increasingly become a fundamental part of the combined therapies currently adopted in the treatment of patients with high-risk (HR) neuroblastoma (NB). An increasing number of studies focus on the understanding of the immune landscape in NB and, since this tumor expresses low or null levels of MHC class I, on the development of new strategies aimed at enhancing innate immunity, especially Natural Killer (NK) cells and macrophages. There is growing evidence that, within the NB tumor microenvironment (TME), tumor-associated macrophages (TAMs), which mainly present an M2-like phenotype, have a crucial role in mediating NB development and immune evasion, and they have been correlated to poor clinical outcomes. Importantly, TAM can also impair the antibody-dependent cellular cytotoxicity (ADCC) mediated by NK cells upon the administration of anti-GD2 monoclonal antibodies (mAbs), the current standard immunotherapy for HR-NB patients. This review deals with the main mechanisms regulating the crosstalk among NB cells and TAMs or other cellular components of the TME, which support tumor development and induce drug resistance. Furthermore, we will address the most recent strategies aimed at limiting the number of pro-tumoral macrophages within the TME, reprogramming the TAMs functional state, thus enhancing NK cell functions. We also prospectively discuss new or unexplored aspects of human macrophage heterogeneity.
Inferior Vena Cava Ultrasonography for Volume Status Evaluation: An Intriguing Promise Never Fulfilled

The correct determination of volume status is a fundamental component of clinical evaluation as both hypovolaemia (with hypoperfusion) and hypervolaemia (with fluid overload) increase morbidity and mortality in critically ill patients. As inferior vena cava (IVC) accounts for two-thirds of systemic venous return, it has been proposed as a marker of volaemic status by indirect assessment of central venous pressure or fluid responsiveness. Although ultrasonographic evaluation of IVC is relatively easy to perform, correct interpretation of the results may not be that simple and multiple pitfalls hamper its wider application in the clinical setting. In the present review, the basic elements of the pathophysiology of IVC behaviour, potential applications and limitations of its evaluation are discussed.
Generalization of Bateman–Hillion progressive wave and Bessel–Gauss pulse solutions of the wave equation via a separation of variables

Two new families of exact solutions of the wave equation uxx + uyy + uzz − c−2utt = 0 generalizing Bessel–Gauss pulses and Bateman–Hillion relatively undistorted progressive waves, respectively are presented. In each of these families new simple solutions describing localized wave propagation are found. The approach is based on a kind of separation of variables.
Improvement of Salinity Tolerance in Water-Saving and Drought-Resistance Rice (WDR)

Rice is one of the most economically important staple food crops in the world. Soil salinization and drought seriously restrict sustainable rice production. Drought aggravates the degree of soil salinization, and, at the same time, increased soil salinity also inhibits water absorption, resulting in physiological drought stress. Salt tolerance in rice is a complex quantitative trait controlled by multiple genes. This review presents and discusses the recent research developments on salt stress impact on rice growth, rice salt tolerance mechanisms, the identification and selection of salt-tolerant rice resources, and strategies to improve rice salt tolerance. In recent years, the increased cultivation of water-saving and drought-resistance rice (WDR) has shown great application potential in alleviating the water resource crisis and ensuring food and ecological security. Here, we present an innovative germplasm selection strategy of salt-tolerant WDR, using a population that is developed by recurrent selection based on dominant genic male sterility. We aim to provide a reference for efficient genetic improvement and germplasm innovation of complex traits (drought and salt tolerance) that can be translated into breeding all economically important cereal crops.
A Systematic Literature Mapping on Using Blockchain Technology in Identity Management

Although blockchain is an emerging technology, it has been applied in a lot of domains by leveraging its features. Traditional identity management systems have many issues regarding security and privacy of personal data. Blockchain has the potential to mitigate and avoid such issues by creating trust among the parties involved in the system while reducing reliance on third-party authorities. The first blockchain-based identity management solutions were launched in 2016. Since then, due to high demand, numerous primary and experimental studies, and intatives have been carried out to provide solutions to this research topic. Along with that, there are also a lot of secondary studies to overview the current state of research on this topic. However, the number of systematic research articles is still limited and each research has its limitation. Through this study, we provide a novel systematic literature including categorization of studies into predefined categories (domain, research type, place of publication), analysis of publication frequency, co-authorship, number of papers citing each paper of all studied papers. Comparing to other systematic literature mapping studies, our paper provides a more comprehensive view of the studied articles. In particular, we analyze the number of citations, which no study has ever done. In this research, we studied 361 papers published from January 2009 to April 2022 in four big databases (IEEE Explore, ACM Digital Library, ScienceDirect, Springer Link), the largest number of articles studied compared to previous researches. The obtained results show that most of the articles under validation research type (providing solution and implementing that solution but not in real-world scenarios) propose solutions/systems, models/schemes and architectures to address general problems. We also find that the majority of authors works alone or collaborate in a separate group and co-work in only one paper. This shows that there is no long term collaboration in blockchain-based identity management, and thus subsequent publications presenting real-world blockchain-based identity management products do not exist.
Redshifts of galaxies in some southern groups and clusters

Mesure du redshift de 67 galaxies appartenant a des amas ou groupes situes dans l'Hemisphere Sud: Pavo, Klemola 2, Klemola 44, 2354-35, 2355-35, 0001-36, 0003-35, 0007-46, Sersic 40/6, Sersic 149/5, Sersic 149/10 et A496
Preparation and Evaluation of a Dosage Form for Individualized Administration of Lyophilized Probiotics

Probiotics have been used in human and veterinary medicine to increase resistance to pathogens and provide protection against external impacts for many years. Pathogens are often transmitted to humans through animal product consumption. Therefore, it is assumed that probiotics protecting animals may also protect the humans who consume them. Many tested strains of probiotic bacteria can be used for individualized therapy. The recently isolated Lactobacillus plantarum R2 Biocenol™ has proven to be preferential in aquaculture, and potential benefits in humans are expected. A simple oral dosage form should be developed to test this hypothesis by a suitable preparation method, i.e., lyophilization, allowing the bacteria to survive longer. Lyophilizates were formed from silicates (Neusilin® NS2N; US2), cellulose derivates (Avicel® PH-101), and saccharides (inulin; saccharose; modified starch® 1500). They were evaluated for their physicochemical properties (pH leachate, moisture content, water absorption, wetting time, DSC tests, densities, and flow properties); their bacterial viability was determined in conditions including relevant studies over 6 months at 4 °C and scanned under an electron microscope. Lyophilizate composed of Neusilin® NS2N and saccharose appeared to be the most advantageous in terms of viability without any significant decrease. Its physicochemical properties are also suitable for capsule encapsulation, subsequent clinical evaluation, and individualized therapy.
Public Acceptance and Willingness to Pay for Carbon Capture and Utilisation Products

Although the significance of the social science agenda reflecting and affecting the carbon capture and utilisation (CCU) value chain has been acknowledged, there is still a scarcity of research about it. This work contributes in developing an understanding of public perceptions regarding the acceptance, use, and purchasing of carbon dioxide (CO2)-derived products through an online quantitative survey. Our research suggests the awareness and acceptance of such products are relatively high. Respondents were in favour of CO2-derived product promotion by policy makers and the industry, approved the funding of such schemes by government, and supported companies that use captured CO2 in their products. The product category seems to influence the willingness of people to use and buy CO2-derived products, with our respondents being more willing to use CO2-derived fuels than food or beverages, showing a caution toward health-related risks. Respondents were also more willing to buy a CO2-derived product if it was cheaper or better for the environment. Male respondents were in general less willing to pay for CCU-based products, while people aged 25 to 29 were more positive toward them. We conclude that the public will be in favour of CCU-based products and willing to buy them if the involved stakeholders do their part in delivering a safe product at a comparable quality and price to existing ones. Better information provision can also support this cause.
Isometric immersions of space forms in space forms.

Let M be a connected ^-dimensional space form isometrically immersed in a simply connected (2w-l)-dimensional space form of strictly larger curvature. If M is minimal, it is proven that it must be a piece of the flat Clifford torus in the (2w-l)-sphere. If M is complete and simply connected, it is proven that M possesses a global coordinate system whose coordinate vectors are unit-length asymptotic vectors.
Imaging shear wave propagation for elastic measurement using OCT Doppler variance method

In this study, we have developed an acoustic radiation force orthogonal excitation optical coherence elastography (ARFOE-OCE) method for the visualization of the shear wave and the calculation of the shear modulus based on the OCT Doppler variance method. The vibration perpendicular to the OCT detection direction is induced by the remote acoustic radiation force (ARF) and the shear wave propagating along the OCT beam is visualized by the OCT M-scan. The homogeneous agar phantom and two-layer agar phantom are measured using the ARFOE-OCE system. The results show that the ARFOE-OCE system has the ability to measure the shear modulus beyond the OCT imaging depth. The OCT Doppler variance method, instead of the OCT Doppler phase method, is used for vibration detection without the need of high phase stability and phase wrapping correction. An M-scan instead of the B-scan for the visualization of the shear wave also simplifies the data processing.