Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of the excitation trajectory of particle gray wolf optimization algorithm

Aiming at the excitation trajectory design in the identification of inertial parameters of industrial robots, this paper proposes a step-by-step identification and particle gray wolf optimisation algorithm (PSOGWO) to optimise the design of excitation trajectory parameters. First of all, the robot's minimum inertial parameter observation matrix is derived and established by Newton-Eura recursive method, and the observation matrix condition number criterion is used as the optimisation objective function; secondly, the particle gray wolf optimisation algorithm (PSOGWO) is introduced; finally, the periodic Fourier series that meets multi-constraint conditions is optimised and designed as the incentive trajectory using the particle gray wolf optimisation algorithm (PSOGWO). Experimental results show that the excitation trajectory designed with the proposed optimisation method can fully stimulate the dynamic characteristics of the robot, improve the anti-noise ability of parameter identification, and lay a foundation for accurately obtaining the dynamic parameters of the robot.
Acute and Subchronic Oral Toxicity of Anthraquinone in Sprague Dawley Rats

Objective: This study was conducted to evaluate the acute and subchronic toxicity of anthraquinone. An acute toxicity test was performed in female Sprague Dawley (SD) rats, and the oral median lethal dose (LD50) of anthraquinone was estimated to be >5000 mg/kg body weight (BW). In the subchronic study, groups of 10 male and 10 female rats were dosed with anthraquinone by gavage at 0, 1.36, 5.44, 21.76, and 174.08 mg/kg BW, 7 days/week for 90 days followed by a recovery period of 28 days. No appreciable toxic-related changes were observed in the 1.36 mg/kg BW group. When the animals received 5.44 mg/kg BW or more of anthraquinone, hyaline droplet accumulation in the renal tubules was observed in both the male and female rats, and anemia was observed in the females. When the anthraquinone dose reached 174.08 mg/kg BW, mild hepatocellular hypertrophy around the central vein of the hepatic lobule and hypothyroidism were observed in the female rats. During the recovery period, changes in clinical symptoms and parameters were considerably alleviated. Based on the results of this study, the no observed adverse effect level (NOAEL) for anthraquinone in rats was set at 1.36 mg/kg BW, and the lowest observed adverse effect level (LOAEL) was 5.44 mg/kg BW.
Recent Advances in the Seed-Directed Synthesis of Zeolites without Addition of Organic Templates

Zeolites have been widely employed in fields of petroleum refining, fine chemicals and environmental protection, but their syntheses are always performed in the presence of organic templates, which have many drawbacks such as high cost and polluted wastes. In recent years, the seed-directed synthesis of zeolites has been paid much attention due to its low-cost and environmentally friendly features. In this review, the seed-directed synthesis of Al-rich zeolites with homonuclear and heteronuclear features, the seed-directed synthesis of Si-rich zeolites assisted with ethanol and the utility of seed-directed synthesis have been summarized. This review could help zeolite researchers understand the recent progress of seed-directed synthesis.
Quantitative Measurements of Brain Activations in Virtual Reality Environments

Electrophysiology measures of the brain indicate substantial responses when the brain participates in tasks of varying complexity levels. These responses vary widely depending on the context and support in better understanding of brain functioning in healthy persons and those with neurodevelopmental problems. Virtual Reality (VR) environments of different complexities induce significantly varying event-related potentials (ERP) in the brain. In this work, the P300 wave, which is an ERP that is employed in the analysis of cognitive abilities of people has been considered for identifying brain engagement during VR based gaming processes. This work primarily focuses on identifying the brain regions that are active during virtual reality gaming environments of varying complexity levels. Further, the analysis to identify the optimal electrode locations for the P300 acquisition for the respective Brain-Computer Interface (BCI) application has also been performed. Various performance metrics such as task engagement, arousal and valence have been identified to infer the participant's mental state at the time of cognitive training with P300 based BCI. Thus, this work seems to support the neuro game developers to identify the active brain regions under various cognitive tasks and assist the participants to be more engaged in the VR based game.
Modeling of workers’ learning behavior in construction projects using agent-based approach: The case study of a steel structure project

Purpose Learning as the way in which labor acquire new knowledge and skills has important strategic implications for the competitive advantage of an organization. The purpose of this paper is to present an agent-based modeling (ABM) approach to investigate the learning behavior of workers. The effect of interactions among different workers as well as the factors affecting the workers’ learning behavior is assessed using the proposed ABM approach. Design/methodology/approach For this purpose, the processes through which the competency value of worker is changed are understood and the workers’ learning behavior is modeled, taking account of various influencing factors such as knowledge flow, social ability to teach and forgetting factor. Findings The proposed model is implemented on a real steel structure project to evaluate its applicability and performance. The variation in the competency value of different workers involved in the project is simulated over time taking account of all the influencing factors using the proposed ABM approach. Practical implications In order to assess the effect of interactions among welders as well as the welders’ characteristics on their learning behavior, the competence value of different welders is evaluated. Originality/value This research presents an ABM approach to investigate the workers’ learning behavior. To evaluate the performance of the proposed ABM approach, it was implemented on a real steel structure project. The learning behavior of different welders (agents) was simulated taking account of their interactions as well as the factors affecting the welders’ learning behavior. The project involved the welding of a 240-ton steel structure. The initial project duration was estimated as 100 days. In this project, it has been planned to execute the welding process using three different welders namely welder A, B and C.
A Low-Cost Online Data Acquisition and Processing System for Industrial Pollutants’ Monitoring

Recently, the prevention and control of industrial pollution has attracted extensive attention. Many studies based on emission data have achieved great success, but there are relatively few studies on the emission data acquisition. To this end, we propose a data acquisition and processing system (DAPS) for online monitoring of industrial pollutants. The system receives real-time emission data through the RS485, automatically generates periodic data, and saves it in the SQL Server database. Real-time Ethernet (RTE) is used to transmit control signals between the system and programmable logic controllers (PLCs). Emission data is transmitted to local industrial control systems and remote monitoring centers (RMCs) via a wireless network. We tested the acquisition function and communication function of the system through experiments and evaluated the overall performance of the system by observing the memory and CPU usage. The system is characterized by simple implementation and versatility and can be applied to continuous monitoring of various industrial pollutants.
Expression Analyses in the Rachis Hint towards Major Cell Wall Modifications in Grape Clusters Showing Berry Shrivel Symptoms

Berry shrivel (BS) is one of the prominent and still unresolved ripening physiological disorders in grapevine. The causes of BS are unclear, and previous studies focused on the berry metabolism or histological studies, including cell viability staining in the rachis and berries of BS clusters. Herein, we studied the transcriptional modulation induced by BS in the rachis of pre-symptomatic and symptomatic clusters with a custom-made microarray qPCR in relation to a previous RNASeq study of BS berries. Gene set analysis of transcript expression in symptomatic rachis tissue determined suppression of cell wall biosynthesis, which could also be confirmed already in pre-symptomatic BS rachis by CESA8 qPCR analyses, while in BS berries, a high number of SWITCH genes were suppressed at veraison. Additionally, genes associated with the cell wall were differently affected by BS in berries. A high percentage of hydrolytic enzymes were induced in BS grapes in rachis and berries, while other groups such as, e.g., xyloglucan endotransglucosylase/hydrolase, were suppressed in BS rachis. In conclusion, we propose that modulated cell wall biosynthesis and cell wall assembly in pre-symptomatic BS rachis have potential consequences for cell wall strength and lead to a forced degradation of cell walls in symptomatic grape clusters. The similarity to sugar starvation transcriptional profiles provides a link to BS berries, which are low in sugar accumulation. However, further studies remain necessary to investigate the temporal and spatial coordination in both tissues.
Frequency–dependence of power and efficiency for resonant inductive coupling and magnetoelectric wireless power transfer systems

The frequency dependence of the maximum output power and efficiency of two wireless power transfer systems (WPTSs), resonant inductive coupling (RIC) and magnetoelectric (ME), are investigated. We find that in the weak–coupling regime, the power optimization and efficiency maximization problems are equivalent and yield the same optimal load and frequency. These properties apply to both topologies under consideration. Despite the apparent difference in the energy conversion mechanisms, the two structures result in similar explicit forms of maximum power delivered to the load, and so does the optimum transfer efficiency. We discuss the essential role of a figure of merit for each configuration and show how they affect the overall performance. For a weakly–coupled inductive WPTS, both the maximum transferred power and efficiency are positively proportional to drive frequency squared. In the case of a ME–based architecture, the dependence of power and efficiency on frequency is the consequence of the transducer geometry optimization problem, subject to a volume constraint. Under a constant mechanical quality factor condition, both quantities are linearly proportional to the operating frequency. While the focus of this paper is RIC and ME mechanisms, some of the findings are also valid for relevant inductive energy harvesting or magneto–mechano–electric WPTSs.
Haemodynamic monitoring in acute heart failure – what you need to know

Acute heart failure (AHF) is a sudden, life-threatening condition, defined as a gradual or rapid onset of symptoms and/or signs of HF. AHF requires urgent medical attention, being the most frequent cause of unplanned hospital admission in patients above 65 years of age. AHF is associated with a 4–12% in-hospital mortality rate and a 21–35% 1-year mortality rate post-discharge. Considering the serious prognosis in AHF patients, it is very important to understand the mechanisms and haemodynamic status in an individual AHF patient, thus preventing end-organ failure and death. Haemodynamic monitoring is a serial assessment of cardiovascular function, intended to detect physiologic abnormalities at the earliest stages, determine which interventions could be most effective, and provide the basis for initiating the most appropriate therapy and evaluate its effects. Over the past decades, haemodynamic monitoring techniques have evolved greatly. Nowadays, they range from very invasive to non-invasive, from intermittent to continuous, and in terms of the provided parameters. Invasive techniques contain pulmonary artery catheterization and transpulmonary thermodilution. Minimally invasive techniques include oesophageal Doppler and noncalibrated pulse wave analysis. Non-invasive techniques contain echocardiography, bioimpedance, and bioreactance techniques as well as non-invasive pulse contour methods. Each of these techniques has specific indications and limitations. In this article, we aimed to provide a pathophysiological explanation of the physical terms and parameters used for haemodynamic monitoring in AHF and to summarize the working principles, advantages, and disadvantages of the currently used methods of haemodynamic monitoring.
Brain Tumor Detection using Decision-Based Fusion Empowered with Fuzzy Logic

Brain tumor is regarded as one of the fatal and dangerous diseases on the planet. It is present in the form of uncontrolled and irregular cells in the brain of an infected individual. Around 60% of glioblastomas turn into large tumors if it is not diagnosed earlier. Some valuable literature is available on tumor diagnosis, but there is room for improvement in overall performance. Machine Learning (ML)-based techniques have been widely used in the medical domain for early diagnostic diseases. The use of ML techniques in conjunction with improved image-guided technology may help in improving the performance of the brain tumor detection process. In this work, an ML-based brain tumor detection technique is presented. Adaptive Back Propagation Neural Network (ABPNN) and Support Vector Machine (SVM) algorithms are used along with fuzzy logic. The fuzzy logic is used to fuse the result of ABPNN and SVM. The proposed technique is developed using the BRATS dataset. Experimental results reveal that the ABPNN model achieved 98.67% accuracy in the training phase and 96.72% accuracy in the testing phase. On the other hand, the SVM model has attained 98.48% and 97.70% accuracy during the training and testing phases. After applying fuzzy logic for decision-based fusion, the overall accuracy of the proposed technique reaches 98.79% and 97.81% for the training and the testing phases, respectively. The comparative analysis with existing techniques shows the supremacy of the proposed technique.
Does regional value chain participation affect global value chain positions? Evidence from China

Does participation in the ASEAN-China regional value chain (RVC) affect China ’ s manufacturing enterprises ’ global value chain (GVC) positions in the context of the establishment of the ASEAN-China Free Trade Area (ACFTA)? In this paper, we discuss the theoretical mechanisms and impacts of RVC participation on GVC positions and use an input-output model to decompose the gross exports of China by different sources and destinations. The model measures China ’ s manufacturing industries ’ total, upstream and downstream participation within the ASEAN-China regional value chain. Using panel data from the OECD for 2005 to 2015, the empirical results show that (1) the participation of China ’ s manufacturing industries in the RVC is conducive to improvement in their GVC positions, (2) moving to more upstream can indeed promote the GVC positions of enterprises, and (3) in contrast to labour-intensive and capital-intensive manufacturing, knowledge-intensive manufacturing in upstream activities of the RVC contributes the most to GVC positions. It is suggested that China should develop knowledge-oriented industries and move to more upstream of the ASEAN-China RVC to raise manufacturing industries ’ positions in the GVC.
Fiber Bragg Gratings for Temperature Monitoring during Thyroid Microwave Ablation: a Preliminary Analysis

Traditional methods to treat thyroid nodules like thyroidectomy and radioiodine therapy can involve a multitude of risks, such as damages to parathyroid glands and aftercare hypothyroidism. Minimally invasive surgery (MIS) can represent an alternative solution, avoiding general anesthesia or radioactive substances. In the framework of MIS, thermal ablation therapies (TATs) are gaining momentum to treat both benign and malign tumors by inducing a significant temperature variation inside the treated tissue. Among TATs, microwave ablation (MWA) is a newly emerging technique which has proved to be an effective and safe method in treating tumors in different organs like liver and kidney, more recently including thyroid nodules. However, an experimental analysis of the temperature reached within the thyroid tissue during the treatment has not been performed yet. Temperature monitoring during TATs can be beneficial to ensure the complete tumor eradication, especially in case of new challenging organs like thyroid. In this regard, this work aims to assess the spatial and temporal distribution of the temperature increment during MWA by performing ex vivo tests on swine thyroid. Temperature variations have been recorded by means of different arrays of fiber optic Bragg grating sensors (FBGs), each of those embedding ten sensing points in parallel to the MW applicator inside the tissue. These trials could provide the first stage in the further investigation of thyroid MWA, towards a better understanding of the most suitable treatment settings for this kind of tumor to improve the treatment outcomes.
Overview of Research into mTOR Inhibitors

The mammalian target of rapamycin (mTOR) is a serine/threonine kinase that belongs to the phosphoinositide 3-kinase (PI3K)-related kinase (PIKK) family. The kinase exists in the forms of two complexes, mTORC1 and mTORC2, and it participates in cell growth, proliferation, metabolism, and survival. The kinase activity is closely related to the occurrence and development of multiple human diseases. Inhibitors of mTOR block critical pathways to produce antiviral, anti-inflammatory, antiproliferative and other effects, and they have been applied to research in cancer, inflammation, central nervous system diseases and viral infections. Existing mTOR inhibitors are commonly divided into mTOR allosteric inhibitors, ATP-competitive inhibitors and dual binding site inhibitors, according to their sites of action. In addition, there exist several dual-target mTOR inhibitors that target PI3K, histone deacetylases (HDAC) or ataxia telangiectasia mutated and Rad-3 related (ATR) kinases. This review focuses on the structure of mTOR protein and related signaling pathways as well as the structure and characteristics of various mTOR inhibitors. Non-rapalog allosteric inhibitors will open new directions for the development of new therapeutics specifically targeting mTORC1. The applications of ATP-competitive inhibitors in central nervous system diseases, viral infections and inflammation have laid the foundation for expanding the indications of mTOR inhibitors. Both dual-binding site inhibitors and dual-target inhibitors are beneficial in overcoming mTOR inhibitor resistance.
Association Between Inflammatory Biomarkers and Mental Health Symptoms in Middle Eastern Refugees in the US

Introduction: Refugees are at increased risk for trauma-related mental health disorders, including anxiety, depression, and post-traumatic stress disorder (PTSD). The underlying biological mechanisms linking trauma to mental disorders need additional study, and the possible pathophysiological role of the immune system is attracting increasing interest. In this study, we investigated whether two well-known pro-inflammatory cytokines (interleukin (IL-8) and IL-6) are associated with mental health symptoms in Middle Eastern refugees displaced to the United States. Methods: Refugees (n=64, mean age=37.6 years) ages ranged from 21 to 74 years (mean=37.62, SD=11.84) were interviewed one month after arrival in Michigan, United States, using a validated survey in Arabic. Questions covered pre-displacement trauma, current anxiety, depression, and PTSD symptoms. Blood, collected immediately following the interview, was analyzed for the levels of interleukins. Multivariate linear regression was used to determine the association between mental health symptoms and IL-6 and IL-8. Results: In multivariate modeling, older age (β=0.37; p<0.01) and anxiety (β=0.31; p<0.05) were positively associated with IL-8. Age (β=0.28; p<0.05) and pre-displacement trauma (β=0.40; p<0.05) were positively associated with IL-6. Depression (β=-0.38) was negatively associated with IL-6. Conclusion/relevance: This study of inflammatory biomarkers suggests the possibility of differential associations between mental health symptoms (anxiety and depression) and pro-inflammatory markers (IL-6 and IL-8). To enhance our ability to prevent and more effectively treat trauma-exposed refugees, we need to better understand the neuroinflammatory mechanisms contributing to mental disorders.
Soft Liquid Metal-Based Conducting Composite with Robust Electrical Durability for a Wearable Electrocardiogram Sensor

Liquid metals not only have the electrical property of conductivity, but they also have a unique characteristic of existing in a liquid state at room temperature, unlike ordinary stiff solid metals. However, in bioelectronics, the modulus matching well between a device and skin or tissue is considered very advantageous, because high-quality biological signals can be recorded. Therefore, it is possible to implement soft electronics with stable and robust electrical characteristics by using LM as a conductive liquid-state filler. In this study, we changed a type of liquid metal, Eutectic Gallium Indium (EGaIn), into a particle form via tip sonication and mixed it with a solution that dissolved Styrene-Ethylene-Butylene-Styrene (SEBS) in toluene to fabricate a composite. The EGaIn-SEBS composite has high conductivity, excellent electrical durability under mechanically harsh conditions, and a degree of modulus similar to that of bare SEBS, which is lower than that of solid-filler-based SEBS composite. Finally, we demonstrated electrocardiogram signal monitoring using an EGaIn-Alginate two-layer electrode (EATE) that was fabricated by simply coating the surface of the composite with alginate hydrogel, which demonstrates excellent performance in bioelectronics.
Fabrication of g-C3N4/N,Fe co-doped CQDs composites: in situ decoration of g-C3N4 with N-CQDs and Fe and efficient visible-light photocatalytic degradation of tetracycline

Herein, for the first time, g-C3N4/N,Fe co-doped carbon quantum dots (CN/N,Fe-CQDs) composites were fabricated by a two-step fabrication route. N,Fe-CQDs were obtained via facile pyrolysis of ammonium ferric citrate. Through thermal condensation of the synthesized N,Fe-CQDs and urea, CN/N,Fe-CQDs composites were successfully fabricated for highly efficient photocatalytic degradation of tetracycline (TC). The optimized CN/N,Fe-CQDs composite obtained the degradation efficiency of 81.0% after 40 min visible-light illumination, and its apparent rate constant was 3.41 times higher than that of pure g-C3N4. The remarkable enhancement of photodegradation activity is mainly attributed to the synergetic effect of N-CQDs and Fe co-decoration in CN/N,Fe-CQDs arising from the incorporation of N,Fe-CQDs into the g-C3N4 matrix, which could increase the specific surface area, wide visible-light absorption range, and accelerate separation and transfer of interfacial charge. The active species capture experiments and electron spin resonance technique testified that ‧O2 −, ‧OH, 1O2 and h+ were all involved in the degradation of TC in the photocatalytic process. According to the result of mass spectrometry, TC underwent hydroxylation, demethylation, N-demethylation, deamination, dehydroxylation, ring opening processes, and was ultimately mineralized into CO2 and H2O. This research can provide a new understanding of the roles played by non-metal and metal ions co-doped CQDs in photocatalytic system and open up a new way to develop highly efficient photocatalysts for TC degradation.