In the process of modernization and development, a human being always needed energy, which increased the dependency on the available sources of fossil fuel. Tetraselmis, a green algal genus belong to the order Chlorodendrales, are described by their strong green coloured chloroplast, flagellated cell bodies, and the occurrence of a pyrenoid within the chloroplast. In this study, four different strains of Tetraselmis species were successfully isolated from the saltpans Kovelong, Chennai, Tamil Nadu, India. The isolated strains were cultured in the normal basal medium and their morphological features were subsequently studied. The species of Tetraselmis straiata (T. straiata) Butcher BBRR1 was confirmed using molecular identification of 18S rRNA gene analysis and its observed systematic position. Among the four different isolates, T. straiata Butcher BBRR1 recorded a highest biomass concentration of 0.58 ± 0.021 g L^-1, 15% lipids, 19% proteins and 17% carbohydrates when it grown under laboratory condition. Whereas, in open raceway ponds, T. straiata BBRR1 produced 0.95 ± 0.06 g L^-1 biomass, 19% lipids, 28% proteins and 21% carbohydrates in an modified CFTRI I medium. The fatty acids profile of T. straiata Butcher BBRR1showed the presence of 33.14 % Palmitic acid, 22.64% 11- Octadecenoic acid and 21.94% Heptadecanoic acid. Since T. straiata BBRR1 can be cultivated in open ponds without a major contaminations, this species can be used as novel biomass feedstock to produce biofuels. This study may suggest the potential of T. straiata BBRR1 for biofuel production and could compete the energy demand in the future. In addition, this species contains healthful components of carotenoids, lipids and proteins, all these may provide a health benefits beyond basic nutrition.

Taiwan’s Chi Mei Medical Center has a vision of becoming a sustainable organization. They found they violated the sustainable development goal (SDG) 13 (“Climate Action”) since its workflows consume excessive tangible resources and waste much operation time. To fulfill the vision, the Chi Mei Medical Center first introduced electronic invoicing. Implementing this electronic invoicing included adopting cloud E-invoice data and creating a software robot for auditing them. This study presents this software robot and its contributions. The software robot replaces an internal auditor to log into Taiwan’s E-invoice platform, download cloud E-invoice data, and detect the inconsistency between these cloud and on-premise data. Internal auditors of the Chi Mei Medical Center only needed to confirm the detection results. They welcome this software robot since it significantly reduces their work burdens. They approved more software robots for assisting other workflows. Besides, the Chi Mei Medical Center earned profits after eliminating paper invoices. This elimination helped release less carbon. This study concludes that chasing a sustainable organization is unnecessarily equivalent to the requirement of more costs. A software robot represents the last puzzle for constructing a paperless workflow since it can resolve the resistance of existing workers to a new workflow.

Taiwan’s auditors have suffered from processing excessive audit data, including drawing audit evidence. This study advances sampling techniques by integrating machine learning with sampling. This machine learning integration helps avoid sampling bias, keep randomness and variability, and target the risker samples. We first apply a Naive Bayes classifier to classify data into some classes. Next, a user-based, item-based, or hybrid approach is employed to draw audit evidence. The representativeness index is the primary metric for measuring the representativeness of audit evidence. The user-based approach denotes the selection of samples between two percentiles in a class as audit evidence. It may be equivalent to a combination of monetary and variable sampling methods. The item-based approach represents the choice of risky samples as audit evidence. It may be identical to a combination of non-statistical and monetary sampling methods. Auditors can hybridize those user-based and item-based approaches to balance representativeness and riskiness in selecting audit evidence. Three experiments show that sampling using machine learning integration has the benefits of drawing unbiased samples, handling complex patterns, correlations, and unstructured data, and improving efficiency in sampling big data. However, the limitations are the classification accuracy output by machine learning algorithms and the range of prior probabilities.

This paper presents a bibliometric analysis of highly cited papers published in the journal Sustainability between 2009 and 2023. The aim is to identify influential countries, authors, and papers, as well as patterns in authorship and citation trends. The analysis focuses on frequently cited sources, the most cited research papers and references within the journal, and trends in author keywords. The analysis shows that Sustainability is a leading publication in sustainability research, with an annual growth rate of 53.57%. The selected papers, published between 2013 and 2022, have an average age of 2.11 years and an average of 88.12 citations each. The study highlights the most influential countries in sustainability research published in Sustainability, with China leading, followed by the United States and Germany. The most prolific authors are from China, Spain, and Italy. Interdisciplinary collaboration is essential to address complex sustainability challenges, as shown in the papers published in Sustainability. The study emphasizes the importance of staying informed about emerging trends and research directions in the field of sustainability published in this journal Sustainability. It underscores the significance of fostering international collaborations and partnerships to address complex sustainability challenges facing our world today, as evidenced by the papers published in Sustainability. Overall, this bibliometric analysis provides valuable insights into the current state of sustainability research published in Sustainability and its implications for policy and practice. It highlights key areas for future research and underscores the need for interdisciplinary collaboration to address complex sustainability challenges, as demonstrated by the papers published in Sustainability. These findings have important implications for policymakers, researchers, and practitioners interested in promoting sustainable development in the field of sustainability., as published in Sustainability.

A predictive approach to the phase behavior of four-component poly-mer-water-surfactant-electrolyte systems is formulated, by viewing the four-component system as a binary polymer-pseudosolvent system, with the pseudosolvent representing water, surfactant, and the electrolyte. The phase stability of this binary system is examined using the framework of the lattice fluid model of Sanchez and Lacombe. In the lattice fluid model, a pure component is represented by three equation of state parameters, the hard-core volume of a lattice site ( ), the number of lattice sites occupied by the component (r) and its characteristic energy ( ). We in-troduce the extra thermodynamic postulate that r and for the pseudosolvent are the same as for water and all surfactant-electrolyte composition dependent characteristics of the pseudosolvent can be represented solely through its characteristic energy parameter. The key implication of the postulate is that the phase behavior of polymer-pseudosolvent systems will be identical for all pseudosolvents with equal values of the characteristic energy, despite their varying real compo-sitions. Based on the pseudosolvent model, illustrative phase diagrams have been computed for several four-component systems containing alkyl sulfonate/sulfate surfactants, electrolytes and anionic or nonionic polymers. The pseudosolvent model is shown to describe all important trends in experimentally observed phase behavior, pertaining to polymer and surfactant molecular characteristics. Most importantly, the pseudosolvent model allows one to construct a priori phase diagrams for any polymer-surfactant-electrolyte system, knowing just one experimental com-position data for a system at the phase boundary, using available thermodynamic data on sur-factants and electrolytes and without requiring any information on the polymer.

Stable-isotope dimethyl labeling is a highly reactive and cost-effective derivatization procedure that could be utilized in proteomics analysis. In this study, a liquid chromatography-tandem mass spectrometry in multiple reaction monitoring mode (LC-MS-MRM) platform for the quantification of kiwi allergens was first developed using this strategy. Three signature peptides for target allergens Act d 1, Act d 5, and Act d 11 were determined and were derivatized with normal and deuterated formaldehyde as external calibrants and internal standards, respectively. The results showed that sample preparation with the phenol method provided comprehensive protein populations. Recoveries at four different levels ranging from 72.5–109.3% were achieved for the H-labeled signature peptides of Act d 1 (SPA1-H) and Act d 5 (SPA5-H) with precision ranging from 1.86–9.92%. The limit of quantification (LOQ) was set at 8 pg mL–1 for SPA1-H and at 4 ng mL–1 for SPA5-H. The developed procedure was utilized to analyze seven kinds of hand-made kiwi foods containing 0.0175–0.0515 mg g–1 of Act d 1 and 0.0252–0.0556 mg g–1 of Act d 5. This study extended the applicability of stable-isotope dimethyl labeling to the economical and precise determination of food allergens and peptides.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

In the new period, the state has made every effort to promote the new urbanization of public sports service. Entropy method, coupled coordination model, cold hot spot analysis is used to explore the dynamic relationship between public sports services and the development of new urbanization in China from 2008 to 2017. The results show that: (1) The development of the internal subsystem of public sports service is not balanced, the sports financial investment system grows rapidly, but the development of professional sports talent team is slow. (2) The imbalance of regional development cannot be ignored, and the public sports service level shows a decreasing gradient from east to west. (3) The regional development features are different. The eastern region is dominated by the coordinated development of sports public service and urbanization, while the central region is mainly in the type of public sports service lag, while the western region has multiple complex characteristics of low-level coordination and public sports service lag. Therefore, it is proposed that the construction of modern public sports service system should be investigated in the context of the development of new urbanization. It should be promoted from the following aspects: promoting the extension of public sports service to rural areas, engendering the "citizen's right" of sports health to the migrant population, conforming to the trend of mass sports intelligence, developing green sports and revitalizing idle sports assets in cities.

Tamm Plasmon Polariton (TPP) is a nanophotonic phenomenon that has attracted much attention due to its spatial strong field confinement, ease of mode excitation and polarization independence. TPP has applications in sensing, storage, lasing, perfect absorber, solar cell, nonlinear optics, and many others. In this work, we demonstrate a biosensing platform based on TPP resonant mode. Both theoretical analyses based on Transfer Matrix Method and experimental validation through nonspecific detection of liquids of different refractive indices and specific detection of SARS-CoV-2 nucleocapsid protein (N-protein) are presented. Results show that TPP biosensor has high sensitivity and good specificity. For N-protein detection, the sensitivity is 1.5 nm/(µg/ml) and the limit of detection can reach down to below 7 ng/ml with spectrometer of 0.01 nm resolution of wavelength shift. This work paves the way for design, optimization, fabrication, characterization, and performance analysis of TPP based biosensors

Preclinical studies have identified glial cells as pivotal players in the genesis and maintenance of neuropathic pain after nerve injury associated with diabetes, chemotherapy, major surgeries, and virus infections. Satellite glial cells (SGCs) in the dorsal root and trigeminal ganglia of the peripheral nervous system (PNS) and astrocytes in the central nervous system (CNS) express similar molecular markers and are protective under physiological conditions. They also serve similar functions in the genesis and maintenance of neuropathic pain, downregulating some of their homeostatic functions and driving pro-inflammatory neuro-glial interactions in the PNS and CNS, i.e. “gliopathy”. However, the role of SGCs in neuropathic pain is not simply as “peripheral astrocytes”. We delineate how these peripheral and central glia participate in neuropathic pain by producing different mediators, engaging different parts of neurons, and becoming active at different stages following nerve injury. Finally, we highlight the recent findings that SGCs are enriched with proteins related to fatty acid metabolism and signaling such as Apo-E, FABP7, and LPAR1. Targeting SGCs and astrocytes may lead to novel therapeutics for the treatment of neuropathic pain.

Earthquake-triggered landslides are one of the most significant hazards worldwide. These landslides, involving small or large volumes, can develop in debris flow or avalanche with high mobility and long-runout distance. The motion processes of this kind of landslide also quite complicated. This study reproduced the motion processes of two landslides using the LS-RAPID program. The Aso Bridge landslide occurred on April 16, 2016, with rapid and long-runout distance characteristics. The Kataragai landslide occurred on April 9, 2018, travelling with flow-like behavior. Through field investigations and laboratory experiments, features and mechanical parameters of these two landslides were obtained. In the LS-RAPID program, the pre-failure models and motion processes of these two landslides were established and reproduced. Results indicated that sliding speed and travelling morphology at different intervals were considered as two indicators to describe their motion process. However, while sliding speed of these two landslides have significant differences with sliding speeds of actual landslides, the final morphologies after failure were consistent with those observed in the field investigation.

Multi-view stereo (MVS) employs multi-point photography for image point positioning and three-dimensional reconstruction technology. Recently, this technology has been introduced into the monitoring of road slopes due to advances in photography and computing technology. In general, the various phases of post-image processing procedures are applied to various photographic data. In this study a novel, automated image-monitoring system is proposed to improve the ability of automatic processing. First, an Internet of things (IoT)-based digital photography system architecture was constructed to provide automatic control of camera photography and real-time transmission of image data. In addition, a visual SfM-MVS 3D reconstruction technique was used to develop related software and hardware interfaces based on the built-in Python computing framework of Photoscan Pro. The software integrates fully automatic photography, image transmission, monitoring of data processing and product release programs. The experimental results show that the system architecture can be applied to fully automatic three-dimensional monitoring of road slopes.

To determine promethazine (PMZ) and its metabolites promethazine sulfoxide (PMZSO) and monodesmethyl-promethazine (Nor1PMZ) in swine muscle, fat, kidney, and liver, a sample preparation and high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis method were established and validated. The sample was extracted with 0.1% formic acid-acetonitrile, and the extract was purified with acetonitrile-saturated n-hexane. After concentration by rotary evaporation, the extract was re-dissolved in 0.1% formic acid-water and acetonitrile (80:20, v/v). The HPLC-MS/MS column used was a Waters Symmetry C18 (100 mm × 2.1 mm i.d., 3.5 μm), with 0.1% formic acid-water and acetonitrile as the mobile phase, and the target compounds were determined by positive ion scan and multiple reaction monitoring. PMZ and Nor1PMZ were quantified with deuterated promethazine (PMZ-d6) as the internal standard, while PMZSO was quantified by external standard method. The limits of detection (LOD) and limits of quantification (LOQ) of PMZ and PMZSO in muscle, liver, and kidney spiked samples were 0.05 μg/kg and 0.1 μg/kg, respectively, while those of Nor1PMZ were 0.1 μg/kg and 0.5 μg/kg, respectively. The LOD and LOQ of analytes in fat spiked sample were 0.05 μg/kg and 0.1 μg/kg, respectively. The sensitivity of this method reaches or exceeds its presented in previous reports. The analytes PMZ and PMZSO showed good linearity within the range of 0.1 μg/kg to 50 μg/kg, while Nor1PMZ showed good linearity within the range of 0.5 μg/kg to 50 μg/kg, with correlation coefficients (r) greater than 0.99. The recoveries of the target compounds in the sam-ples were between 81.73% and 107.17%, and the precision ranged from 1.78% to 10.47%. This study developed for the first time an HPLC-MS/MS method for the determination of PMZ and its metabolites PMZSO and Nor1PMZ in four swine edible tissues, comprehensively covered target tissues of monitoring object, which is applicable for monitoring veterinary drug residues in ani-mal-derived foods and ensuring food safety.

Metal creep has been a subject of extensive study for more than 110 years, because it affects the useful life of engineering components operating at high temperatures. It is even more so with ever-increasing operating temperatures of propulsion/power-generation systems by the environmental regulations to reduce greenhouse emissions. This review summaries the recent development in creep modeling with regards to creep strain evolution, creep rate, creep ductility, creep life and fracture mode, attempting to provide a comprehensive mechanism-based framework to address all the important creep phenomena and the long-standing issue of long-term creep life prediction with microstructural evolution and environmental effects.

In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which may hamper better communication performance. To address these issues, reconfigurable intelligent surfaces (RIS) have been proposed as a helpful tool to enhance UAV communication networks. However, due to the high mobility of UAV, complex channel environments, and dynamic RIS configurations, it is challenging to estimate the link quality of ground users. In this paper, we propose a link quality estimation model using a gated recurrent unit (GRU) to assess the link quality of ground users for a multi-user RIS-assisted UAV-enabled wireless communication system. Our proposed framework uses a time series of user channel data and RIS phase shift information to estimate the quality of the link for each ground user. Simulation results showed that the proposed GRU model effectively and accurately estimates the link quality of the ground users in the RIS-assisted UAV-enabled wireless communication network.

IMPORTANCE: On December 10, 2021, the FDA published a Determination Letter, along with a Statistical Review and Evaluation Report, and concluded that under the non-informative prior, the local Bayesian optimal interval design (BOIN) design, in its revised form, can be designated fit-for-purpose for identifying the maximum tolerated dose of a new drug, assuming that dose-toxicity relationship is monotonically increasing. Although setting the BOIN design parameter p.tox = 1.4 * target.DLT.rate is recommended in almost all BOIN methodology articles and is the default value in the R package BOIN, it's unclear if the choice of p.tox should only depend on the target DLT rate and if certain range of p.tox could produce the same BOIN boundary table. DESIGN: In this simulation study, following parameters were varied one at a time, using R package BOIN, to explore their effects on the equivalence intervals of p.saf and p.tox: 1) target DLT rate, 2) n.earlystop, 3) cutoff.eli, 4) cohortsize, and 5) ncohort. And a simple 3+3 design was used as an example to explore equivalent sets of BOIN design parameters that can generate the same boundary table. RESULTS: When the early stopping parameter n.earlystop is relatively small or the cohortsize value is not optimized via simulation, it might be better to use p.tox < 1.4 * target.DLT.rate, or try out different cohort sizes, or increase n.earlystop, whichever is both feasible and provides better operating characteristics. This is because if the cohortsize was not optimized via simulation, even when n.earlystop = 12 and cohortsize > 3, the BOIN escalation/de-escalation rules generated using p.tox = 1.4 * target.DLT.rate could be exactly the same as those calculated using p.tox > 3 * target.DLT.rate, which might not be acceptable for some pediatric trials targeting 10% DLT rate. The traditional 3+3 design stops the dose finding process when 3 patients have been treated at the current dose level, 0 DLT has been observed, and the next higher dose has already been eliminated. If additional 3 patients were required to be treated at the current dose in the situation described above, the decision rules of this commonly used 3+3 design could be generated using BOIN design with target DLT rates ranging from 18% to 29%, p.saf ranging from 8% to 26%, and different p.tox values ranging from 39% to 99%. These BOIN parameters also need to satisfy a set of conditions. Meaning: This study demonstrates the importance of interpreting BOIN design parameter p.tox as an interval of toxicity rates that are considered too toxic, rather than one prespecified value that corresponds to the lowest toxicity probability that is deemed overly toxic. When designing a dose-finding trial using BOIN, it is important to perform simulation studies to identify equivalent sets of BOIN design parameters that can generate the same boundary table so that we can better compare the safety properties of different boundary tables.

The parameter estimation problem for polynomial phase signals (PPSs) arises in a number of fields, including radar, sonar, biology, etc. In this paper, a fast algorithm of parameter estimation for monocomponent PPS is considered. We propose the so-called LSU-EKF estimator, which combines the least squares unwrapping (LSU) estimator and the extended Kalman filter (EKF). First, the coarse estimates of the parameters of PPS are obtained by the LSU estimator using a small number of samples. Subsequently, these coarse estimates are used to initial the EKF. Monte-Carlo simulations show that the computation complexity of the LSU-EKF estimator is much less than that of the LSU estimator, with little performance loss. Similar to the LSU estimator, the proposed algorithm is able to work over the entire identifiable region. Moreover, in the EKF stage, the accurate estimated results can be output point-by-point, which is useful in real applications.

In the neuroscience research field, specific for medical imaging analysis, how to mining more latent medical information from big medical data is significant for us to find the solution of diseases. In this review, we focus on neuroimaging data that is functional Magnetic Resonance Imaging (fMRI) which non-invasive techniques, it already becomes popular tools in the clinical neuroscience and functional cognitive science research. After we get fMRI data, we actually have various software and computer programming that including open source and commercial, it's very hard to choose the best software to analyze data. What's worse, it would cause final result imbalance and unstable when we combine more than software together, so that's why we want to make a pipeline to analyze data. On the other hand, with the growing of machine learning, Python has already become one of very hot and popular computer programming. In addition, it is an open source and dynamic computer programming, the communities, libraries and contributors fast increase in the recent year. Through this review, we hope that can make neuroimaging data analysis more easy, stable and uniform base the one platform system.

Helicobacter Pylori (H. Pylori) is a common pathogen with high prevalence of infection in human populations. Diagnosis of H. Pylori infection is critical for its treatment, eradication, and prognosis. Biosensors have been demonstrated to be powerful for rapid onsite detection of pathogens, particularly for point-of-care test (POCT) scenarios. In this work, we propose a novel optical biosensor, based on nanomaterial porous silicon (PSi) and photonic surface state Tamm Plasmon Polariton (TPP), for detection of cytotoxin-associated antigen A (CagA) antigen of H. Pylori bacterium. We fabricated the PSi TPP biosensor, analysed its optical characteristics and demonstrated through experiments towards sensing of CagA antigen, that TPP biosensor has sensitivity of 100 pm/(ng/ml), limit of detection of 0.01 ng/ml, and specificity in terms of positive-to-negative ratio of more than six. From these performance factors, it can be concluded that TPP biosensor can serve as an effective tool for diagnosis of H. Pylori infection, either in analytical labs or in POCT applications.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

Trace amine-associated receptor 5 (TAAR5) is a G protein-coupled receptor that belongs to the TAARs family (TAAR1-TAAR9). TAAR5 is expressed in the olfactory epithelium and is responsible for sensing 3-methylamine (TMA). However, recent studies showed that TAAR5 is also expressed in the limbic brain regions and is involved in the regulation of emotional behaviour and adult neurogenesis, suggesting that TAAR5 antagonism may represent a novel therapeutic strategy for anxiety and depression. We used the AtomNet® model, the first deep learning neural network for structure-based drug discovery, to identify putative TAAR5 ligands and tested them in an in vitro BRET assay. We found two mTAAR5 antagonists with low to submicromolar activity that are able to inhibit the cAMP production induced by TMA. Moreover, these two compounds also inhibited the mTAAR5 downstream signalling, such as the phosphorylation of CREB and ERK. These two hits exhibit drug-like properties and could be used to develop further more potent TAAR5 ligands with putative anxiolytic and antidepressant activity.

We describe a machine learning (ML) approach to process the signals collected from Covid-19 optical-based detector. Multilayer Perceptron (MLP) and Support Vector Machine (SVM) were used to process both raw data and feature engineering data, and high performances for qualitative detection of the SARS-CoV-2 virus with concentration down to 1 TCID50/ml has been achieved. Valid detection experiments contain 486 negative and 108 positive samples; and control experiments, in which biosensors without antibody functionalization were used to detect SARS-CoV-2, contains 36 negative samples and 732 positive samples. Data distribution patterns of the valid and control detection dataset, based on T-distributed Stochastic Neighbor Embedding (t-SNE), was used to study the distinguishability between positive and negative samples, and explain the ML prediction performances. This work demonstrates that ML can be a generalized effective approach to process signals and dataset of biosensors dependent on resonant modes as biosensing mechanism.

Based on the analysis of the working principle, circuit design and working loss of the common charger DC/DC converter, this paper designs a ZVS half-bridge three-level DC/DC converter based on non-phase-shift control mode, and proposes a multi-stage constant current and voltage limiting charging control strategy based on modulation wave selection control. The simulation results show that the proposed method and control strategy have faster voltage regulation ability and wider stability margin, and can achieve stable current sharing control in the charging process.

In March 2013, a novel avian influenza A H7N9 virus was emerged in China, which cause rapidly progressive pneumonia and with a high fatality rate. Serologic studies to evaluate neutralizing antibodies of infected patients and birds are invaluable tools for immunogenicity research of H7N9 and epidemiological investigation. Conventional neutralization assays are laborious and time-consuming which also hampered by biosafety requirement. In this study, We construct and produce pseudovirus bearing the full-length hemagglutinin (HA) of H7N9 virus in the Env-defective, luciferase-expressing HIV-1 backbone. The production of lentiviral pseudovirus was analysed by HA gene specific real-time reverse-transcription PCR, transmission electron microscopy (TEM), and Western Blot assay to prove the nucleic acid replication, the morphology of virus, and the expression of HA protein in pseudovirus. After that pseudovirus based inhibition assay was established to detect neutralizing antibodies of a panel of serum samples. Our results demonstrated that H7N9 pseudovirus which had single-cycle infection was generated. By comparing the neutralization antibody titers, pseudovirus based neutralization test could be recognized as an alternative of conventional microneutralization (MN). Hence, we conclude that it is possible to use pseudovirus inhibition assay to screen sera samples, as well as evaluate vaccine-induced neutralizing antibodies against H7N9 virus.

Deep reinforcement learning is one of the research hotspots in artificial intelligence and has been successfully applied in many research areas, however, the low training efficiency and high demand for samples are problems that limit the application To address these problems, a hierarchical episodic control model extending episodic memory to the domain of hierarchical reinforcement learning is proposed in this paper. The model is theoretically justified and employs a hierarchical implicit memory planning approach for counterfactual trajectory value estimation. Starting from the final step and recursively moving back along the trajectory, a hidden plan is formed within the episodic memory. Experience is aggregated both along trajectories and across trajectories, and the model is updated using a multi-headed backpropagation similar to bootstrapped neural networks. This model extends the parameterized episodic memory framework to the realm of hierarchical reinforcement learning and is theoretically analyzed to demonstrate its convergence and effectiveness. Experiments conducted in Four Room, Mujoco, and UE4-based active tracking , highlight that the hierarchical episodic control model effectively enhances training efficiency. It demonstrates notable improvements in both low-dimensional and high-dimensional environments, even in cases of sparse rewards.

Deoxynivalenol (DON) is a mycotoxin produced by Fusarium spp. that causes Fusarium head blight (FHB) disease in cereal crops. Ingestion of food contaminated with DON poses serious human health complications. However, the DON cytotoxicity has been mostly deduced from animal studies. In this study, we used the nematode Caenorhabditis elegans (C. elegans) as a tractable animal model to dissect the toxic effect of DON. Our results indicate that DON reduces the fecundity and lifespan of C. elegans. The real-time RT-PCR analysis showed that DON upregulates innate immunity-related genes including C17H12.8 and K08D8.5 encoding PMK-1 (mitogen activated protein kinase-1)-regulated immune effectors, and F35E12.5 encoding a CUB-like domain-containing protein. Furthermore, our RNAseq data demonstrate that out of ~ 17,000 C. elegans genes, 313 are upregulated and 166 were downregulated by DON treatment. Among the DON-upregulated genes, several are ugt genes encoding UDP-glucuronosyl transferase (UGTs) which are known to be involved in chemical detoxification. The three upregulated genes, F52F10.4 (oac-32), C10H11.6 (ugt-26) and C10H11.4 (ugt-28) encoding the O-acyltransferase homolog, UGT26 and UGT 28, respectively, are shown to contribute to DON tolerance by RNAi bacterial feeding experiment. The results of this study provide insights to the targets of DON cytotoxicity and potential mitigation measures.

Due to their short range (2–500 nm), Auger electrons (Auger e-) have the potential to induce nano-scale physiochemical damage to biomolecules. Although DNA is the primary target of Au-ger e-, it remains challenging to maximize the interaction between Auger e- and DNA. To assess the DNA-damaging effect of Auger e- released as close as possible to DNA without chemical damage, we radio-synthesized no-carrier-added (n.c.a.) [189, 191Pt]cisplatin and evaluated both its in vitro properties and DNA-damaging effect. Cellular uptake, intracellular distribution, and DNA binding were investigated, and DNA double-strand breaks (DSBs) were evaluated by im-munofluorescence staining of γH2AX and gel electrophoresis of plasmid DNA. Approximately 20% of intracellular radio-Pt was in a nucleus, and about 2% of intra-nucleus radio-Pt bound to DNA, although uptake of n.c.a. radio-cisplatin was low (0.6% incubated dose after 25-h incuba-tion), resulting in the frequency of cells with γH2AX foci was low (1%). Nevertheless, some cells treated with radio-cisplatin had γH2AX aggregates unlike non-radioactive cisplatin. These findings suggest n.c.a. radio-cisplatin binding to DNA causes severe DSBs by release of Auger e- very close to DNA without chemical damage by carriers. Efficient radio-drug delivery to DNA is necessary for successful clinical application of Auger e-.

The pop-in effect in nanoindentation of metals represents a major collective dislocation phenome-non that displays sensitivity in the local surface microstructure and residual stresses. To under-stand the deformation mechanisms behind pop-ins in metals, large scale molecular dynamics simulations are carried out to investigate the pop-in behavior and indentation size effect in unde-formed and deformed Cu single crystals. Tensile loading, unloading and reloading simulations are performed to create a series of samples subjected to a broad range of tensile strains with/without pre-existing dislocations. The subsequent nanoindentation simulations are con-ducted to study the coupled effects of pre-strain, the presence of resulting dislocations and surface morphology, as well as indenter size effects on the mechanical response in indentation processes. Our work provides detailed insights into the deformation mechanisms and microstruc-ture-property relationships of nanoindentation in the presence of residual stresses and strains.

Passive marine listening, involving the acoustic monitoring of underwater environments, has become increasingly vital for scientific research, environmental monitoring, and defense applications. However, the success of such applications critically depends on the ability to extract meaningful information from the often noisy and dynamic underwater acoustic environment. In this context, Mel-frequency cepstral coefficients (MFCCs) have emerged as an essential tool for feature extraction, capturing the spectral characteristics of marine sounds and making them ideal for species identification and sound event detection. This research presents an innovative approach to enhance the robustness of MFCC-based passive marine listening through adaptive noise reduction techniques. The proposed approach utilizes dynamic spectral subtraction to counter underwater noise, resulting in enhanced signal-to-noise ratios for desired sounds. This adaptive system adjusts to dynamic underwater noise, allowing it to concentrate on target sounds and suppress interference effectively. The experimentation further validates the effectiveness of the proposed approach, with results reaching 99% on the full dataset of 570 mammals and vessels, demonstrating the effectiveness of SVM and Random Forests in the classification of underwater audio.

In the study of rough sets, there are many covering approximation spaces, how to classify covering approximation spaces has become a hot issue. In this paper, we propose concepts covering approximation $T_{1}$-space, $F-$symmtry, covering rough continuous mapping, covering rough homeomorphism mapping to solve this question. We also propose a new method for constructing topology in Theorem 5.1, and get the following properties: (1) For each $x\in U$, $\{X_{i}:i\in I\}\subseteq \mathcal{P}(U)$ is all the subsets of $U$ which contains $x$ and $*$ is a reflexive relation on $U$. If $V\in \tau$ is a subset of $U$ and $x\in V$, then $\underline{*}(\bigcap \limits_{i\in I}X_{i})$ is the smallest subset of $U$ and $x \in \underline{*}(\bigcap \limits_{i\in I}X_{i})\subseteq V$. Denoted by $C(x)=\bigcap \{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$. (2)If $V\in \tau$ is a subset of $U$, then $V =$ $\bigcup \limits_{x\in V} C(x)$. (3) Let $\{\underline{*}(X_{i}):x\notin \underline{*}(X_{i}), i\in I\}$, then $\overline{\{x\}}$ $=$ $U \setminus \bigcup \limits_{x\notin \underline{*}(X_{i}), i\in I}\underline{*}(X_{i})$; (4) Let $*$ be a reflexive relation on $U$. For every $X\subseteq U$, we have $int(\underline{*}(X))=\underline{*}(X)$. Where $int(\underline{*}(X))$ represents the interior of $\underline{*}(X)$. (5) Let $\{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$ be a family subsets of $U$, then $\{\underline{*}(X_{i}):x\in \underline{*}(X_{i}),i\in I\}$ is a base for $(U,\tau)$ at the point $x$. \\

The entry and exit method is a simple and practical method to determine the critical slip surface of slope. However, it has the drawback of sacrificing computational efficiency to improve search accuracy. To solve this problem, this paper proposes an improved entry and exit method to search for the critical slip surface. Based on the random fields generated by using Karhunen–Loève expansion method, the simplified Bishop’s method combined with the improved entry and exit method is used to determine the critical slip surface and its corresponding minimum factor of safety. Then, the failure probability is calculated by conducting Monte Carlo simulation. Two examples are reanalyzed to verify the accuracy and efficiency of the proposed method. Meaningful comparisons are made to demonstrate the calculating accuracy and calculating efficiency of the improved entry and exit method in searching for the minimum safety factor of slope, based on which the effect of the reduced searching range on slope reliability was explored. The results indicate that the proposed method provides a practical tool for evaluating the reliability of slopes in spatially variable soils. It can greatly improve the computational efficiency in relatively high-computational accuracy of slope reliability analysis.

CO2 has characteristic properties and reactions at converter smelting temperature, and the chemical reaction between CO2 and elements such as C and Si in the molten pool has bubble proliferation and cooling effects, which can effectively improve the kinetic and thermodynamic conditions of converter smelting. Here, an experimental study and industrial test on the application of CO2 in converter smelting were carried out. The smelting effects of Mode-1 and Mode-2 with total CO₂ injection amounts of 229 Nm³ and 196 Nm³, respectively, were compared, and the changes in molten steel and slag compositions, dust removal, and gas are analyzed. The test results show that converter top and bottom blowing CO₂ technology (COMI-B)technology had significant metallurgical advantages over the N-Mode; the dephosphorization rate increased by 4.2%, slag (FeO) content was reduced by 2.04%, end point nitrogen content of molten steel was reduced by 20%, gas recovery increased by 8.29 Nm³/t, and soot production reduced by 14.7%. The results of the study provide reference for the application of COMI-B technology in converters in the iron and steel industry and develop a new path for resource utilization of CO₂.

The mechanization of agricultural activities has led to indiscriminate deposition of toxic xenobiotics, including organophosphates in the biomes, and this has led to intoxication characterized with deleterious oxidative and neuronal changes. This study investigated the consequences of oxidative and neurogenic disruptions that follow exposure to two organophosphates, chlorpyrifos (CPF) and dichlorvos (DDVP) on neuro-cognitive performance and anxiety-like behaviors in rats Thirty-two adult male Wistar rats (150 – 170g) were randomly divided into 4 groups, orally exposed to normal saline (NS), DDVP (8.8mg/kg), CPF (14.9mg/kg) and DDVP+CPF for 14 consecutive days. On day 10 of exposures, anxiety-like behaviors and amygdala dependent fear learning were assessed using Open Field and Elevated Plus Maze paradigms respectively, while spatial working memory was assessed on day 14 in the Morris water maze paradigm, following 3 training trials each on days 11, 12 and 13. On day 15, the rats were euthanized, and their brains excised, hippocampus and amygdala removed, 5 of which were homogenized and centrifuged to analyze nitric oxide (NO) metabolites, total reactive oxygen species (ROS), and acetylcholinesterase (AChE) activity, and the other three processed for histology (cresyl violet stain) and proliferative marker (Ki67 immunohistochemistry). Marked (p≤0.05) loss in body weight, AChE depletion, and overproduction of both NO and ROS were observed after repeated exposure to individual and combined doses of CPF and DDVP. Insults from DDVP exposure appeared more severe owing to the observed greater losses in the body weights of exposed rats. There was also a significant (p≤0.05) effect on the cognitive behaviors recorded from the exposed rats, and these deficits were related to the oxidative damage and neurogenic cell loss in the hippocampus and the amygdala of the exposed rats. Taken together, these results provided an insight that oxidative and neurogenic damages are central to the severity of neuro-cognitive dysfunction and increased anxiety-like behaviors that follow organophosphate poisoning.

Infrared dim and small target detection is a key technology of various detection tasks. However, due to the lack of shape, texture, and other information, it is a challenging task to detect dim and small targets. Recently, since many traditional algorithms ingore global information of infrared images, they generate some false alarms in complicated environments. To address this problem, in this paper, a coarse-to-fine deep learning-based method is proposed to detect dim and small targets. Firstly, a coarse-to-fine detection framework integrating deep learning and background prediction is applied for detecting targets. The framework contains of coarse detection module and fine detection module. In coarse detection stage, Region Proposal Network (RPN) is employed to generate masks in target candidate regions. Then, for further optimize the result, inpainting is utilized to predict the background by the global semnantic of images. In this paper, inpainting algorithm with a mask aware dynamic filtering module is incorporated into the fine detection stage to estimate background in candidate target areas. Finally, compared with existing algorithms, the experimental results indicate that the proposed framework have effective detection capability and robustness for complex surroundings.

The emergence of various electronic devices and equipment such as electric vehicles and drones requires higher energy density energy storage devices. Lithium-sulfur batteries (LSBs) are considered as the most promising new generation energy storage system owing to high theoretical specific capacity and energy density. However, the severe shuttle behaviors of soluble lithium polysulfides (LiPSs) and the slow redox kinetics lead to low sulfur utilization and poor cycling stability, which seriously hinder the commercial application of LSBs. Therefore, various catalytic materials have been employed to solve these troublesome problems. High entropy materials (HEMs), as advanced materials, can provide unique surface and electronic structures that expose plentiful catalytic active sites, which opens new ideas for the regulation of LiPSs redox kinetics. Notwithstanding many instructive reviews in the land of LSBs, while this review aims to offer a complete and shrewd summary of the current progresses in HEMs-based LSBs, including in-depth interpretation of design principles and mechanistic electrocatalysis functions as well as pragmatic perspectives.

Severe COVID-19 is a major cause of morbidity and mortality worldwide, especially to those with co-morbidities, the elderly and the immunocompromised. However, the molecular determinants critical for severe COVID-19 progression remain to be fully elucidated. Meta-analysis of transcriptomic RNAseq and single-cell sequencing datasets comparing between severe and mild COVID-19 patients have demonstrated that the early expansion of myeloid-derived suppressor cells (MDSCs) could a key feature of severe COVID-19 progression. Besides serving as potential early prognostic biomarkers for severe COVID-19 progression, several studies have also indicated the functional roles of MDSCs in severe COVID-19 pathogenesis and possibly even long COVID. Given the potential links between MDSCs and severe COVID-19, we examined the existing literature summarizing the characteristics of MDSCs, the evidence of MDSCs in facilitating severe COVID-19 pathogenesis and discuss the potential therapeutic avenues that can be explored to reduce the risk and burden of severe COVID-19. We also provide a web app where users can visualise the temporal changes of specific genes or MDSC-related gene sets during severe COVID-19 progression and disease resolution at https://temporal-severe-covid.streamlit.app/, based on our previous study described by Ong et al., 2021.

Choroidal neovascularization (CNV) is a key pathological feature of several of the leading causes of vision loss including neovascular age-related macular degeneration. Here we show that a calreticulin anti-angiogenic domain (CAD)-like peptide 27, CAD27, inhibited in vitro angiogenic activities, including tube formation and migration of endothelial cells, and suppressed vascular sprouting from rat aortic ring explants. In rat model of laser-induced CNV, we demonstrate that intravitreal injection of CAD27 significantly attenuated the formation of CNV lesions as measured via fundus fluorescein angiography and choroid flat-mounts (19.5% and 22.4% reductions at 10μg and 20μg of CAD27 injected, respectively). Similarly, the reduction of CNV lesions was observed in the groups of rats that had received topical applications of CAD27 (choroid flat-mounts: 17.9% and 32.5% reductions at 10μg/mL and 20μg/mL of CAD27 installed, respectively). Retinal function was unaffected, as measured using electroretinography in both groups received interareal injection or topical applications of CAD27 at least for 9 days. These findings show that CAD27 can be used as a potential therapeutic alternative for targeting CNV in the diseases such as neovascular age-related macular degeneration.

Climate change is a global issue that draws widespread attention from the international society. As an important component of the climate system, the water cycle is directly affected by climate change. Thus, it is very important to study the influences of climate change on the basin water cycle with respect to maintenance of healthy rivers, sustainable use of water resources, and sustainable socioeconomic development in the basin. In this study, by assessing the suitability of multiple General Circulation Models (GCMs) recommended by the Intergovernmental Panel on Climate Change, Statistical Downscaling Model (SDSM) and Automated Statistical Downscaling model (ASD) were used to generate future climate change scenarios. These were then used to drive distributed hydrologic models (Variable Infiltration Capacity, Soil and Water Assessment Tool) for hydrological simulation of the Yangtze River and Yellow River basins, thereby quantifying the effects of climate change on the basin water cycle. The results showed that suitability assessment adopted in this study could effectively reduce the uncertainty of GCMs, and that statistical downscaling was able to greatly improve precipitation and temperature outputs in global climate mode. Compared to a baseline period (1961–1990), projected future periods (2046–2065 and 2081–2100) had a slightly decreasing tendency of runoff in the lower reaches of the Yangtze River basin. In particular, a significant increase in runoff was observed during flood seasons in the southeast part. However, runoff of the upper Yellow River basin decreased continuously. The results provide a reference for studying climate change in major river basins of China.

Background: Antiplatelet medications such as aspirin and clopidogrel are used following thrombotic stroke or transient ischemic attack (TIA) to prevent a recurrent stroke. However, the antiplatelet treatments fail frequently, and patients experience recurrent stroke. One approach to lower the rates of recurrence, may be the individualized antiplatelet therapies (antiplatelet therapy modification (ATM)) based on the results of platelet function analysis (PFA). This review was undertaken to gather and analyse the evidence about the effectiveness of such approaches. Methods: We searched Medline, CINAHL, Embase, Web of Science and Cochrane databases to 7 January 2020. Results: Two observational studies involving 1136 patients were included. The overall effects of PFA-based ATM on recurrent strokes (OR 1.05; 95% CI 0.69 to 1.58), any bleeding risk (OR 1.39; 95% CI 0.92 to 2.10) or death hazard from any cause (OR 1.19; 95% CI 0.62 to 2.29) were not significantly different from the standard antiplatelet therapy without ATM. Conclusions: The two studies showed opposite effects of PFA-guided ATM on the recurrent strokes in aspirin non-responders, leading to an insignificant difference in the subgroup meta-analysis (OR 1.59; 95% CI 0.07 to 33.77), while the rates of any bleeding events (OR 1.04; 95% CI 0.49 to 2.17) or death from any cause (OR 1.17; 95% CI 0.41 to 3.35) were not significantly different between aspirin non-responders with ATM and those without ATM. There is a need for large randomized controlled trials which account for potential confounders such as ischemic stroke subtypes, technical variations in the testing protocols, patient adherence to therapy, and pharmacogenetic differences.

For Synthetic Aperture Radar (SAR) image registration, successive processes following feature extraction are required by both the traditional feature-based method and the deep learning method. Among these processes, the feature matching process—whose time and space complexity are related to the number of feature points extracted from sensed and reference images, as well as the dimension of feature descriptors—proves to be particularly time-consuming. Additionally, the successive processes introduce data sharing and memory occupancy issues, requiring an elaborate design to prevent memory leaks. To address these challenges, this paper introduces the OptionEM-based reinforcement learning framework to achieve end-to-end SAR image registration. This framework outputs registered images directly without requiring feature matching and calculation of the transformation matrix, leading to significant processing time savings. The Transformer architecture is employed to learn image features, while a correlation network is introduced to learn the correlation and transformation matrix between image pairs. Reinforcement learning, as a decision process, can dynamically correct errors, making it more efficient and robust compared to supervised learning mechanisms like deep learning. We present a hierarchical reinforcement learning framework combined with episodic memory to mitigate the inherent problem of invalid exploration in generalized reinforcement learning algorithms. This approach effectively combines coarse and fine registration, further enhancing training efficiency. Experiments conducted on three sets of SAR images, acquired by TerraSAR-X and Sentinel-1A, demonstrate that the proposed method’s average runtime is sub-second, achieving subpixel registration accuracy.

The Station logo is a way for a TV station to claim copyright, which can realize the analysis and understanding of the video by the identification of the station logo, so as to ensure that the broadcasted TV signal will not be illegally interfered. In this paper, we design a station logo detection method based on Convolutional Neural Network by the characteristics of the station, such as small scale-to-height ratio change and relatively fixed position. Firstly, in order to realize the preprocessing and feature extraction of the station data, the video samples are collected, filtered, framed, labeled and processed. Then, the training sample data and the test sample data are divided proportionally to train the station detection model. Finally, the sample is tested to evaluate the effect of the training model in practice. The simulation experiments prove its validity.

Lung cancer (LC) is the second most common cancer and the leading cause of cancer deaths in the U.S. Insulin therapy, a key treatment for managing Type 2 Diabetes Mellitus (T2DM), may increase LC risk. The impact of non-insulin antidiabetic drugs, particularly GLP-1 receptor agonists (GLP-1RAs), on LC risk is not well understood. This study evaluated LC risk in T2DM patients comparing seven non-insulin antidiabetic agents to insulin. Using the TriNetX Analytics platform, we analyzed de-identified electronic health records of 1,040,341 T2DM patients treated between 2005-2019, excluding those with prior antidiabetic use or LC diagnoses. We calculated hazard ratios and confidence intervals for LC risk and used propensity score matching to control for confounding factors. All non-insulin antidiabetic drugs, except alpha-glucosidase inhibitors, significantly reduced LC risk compared to insulin, with GLP-1RAs showing the greatest reduction (HR: 0.49, 95% CI: 0.41, 0.59). GLP-1RAs were consistently associated with lowered LC risk across all histological types, races, genders, and smoking statuses. These findings suggest that non-insulin antidiabetic drugs, particularly GLP-1RAs, may be preferable for managing T2DM while reducing LC risk.

Semiconductor photocatalytic performances can be modulated through morphology modification. Herein porous hierarchical BiOBr microspheres (BiOBr-MS) of ~3 m was firstly self-assembled without the assistance of a template via a facile solvothermal synthesis in triethylene glycol (TEG) at 150 oC for 3 h. KBrO3 was exploited as a bromine source, which slowly provided bromide ions upon reduction in TEG and controlled the growth and self-assembly of primary BiOBr nanoplates. The addition of PVP during solvothermal synthesis of BiOBr-MS reduced the particle size by about three-fold to generate BiOBr sub-microspheres (BiOBr-sMS) of <1 m. BiOBr-sMS exhibited significantly higher photocatalytic activity than BiOBr-MS for aerobic photooxidation of benzyl alcohol (BzOH) to benzaldehyde (BzH) under simulated sunlight irradiation (conversions of BzOH (50 mM) over BiOBr-sMS and BiOBr-MS were respectively 51.3% and 29.6% with 100% selectivity to BzH after Xenon illumination for 2 h at 25 oC). The photogenerated holes and •O2- were found to be main reactive species for the BzOH oxidation over BiOBr spheres by scavenging tests and spin-trapping EPR spectra. The higher photocatalytic activity of BiOBr-sMS was attributed to its more open hierarchical structure, efficient charge separation, more negative conduction band position and generation of larger amounts of •O2-.

An undescribed diterpene, stellerterpenoid A (1) and two undescribed sesquiterpenoids, stellerterpenoids B and C (2-3), together with six known compounds, were isolated from the roots of Stellera chamaejasme L. Their structures were elucidated by extensive spectroscopic data (1D, 2D NMR, IR, UV and HR-ESI-MS). The absolute configuration of 1-3 were elucidated based on ECD calculation. Among of them, stellerterpenoid A was a rare 13, 14 - seco nortigliane diterpenoid and stellerterpenoid B was a guaiacane type sesquiterpenoid with an unusual 1, 2-diketone moiety. The known stelleraguaianone B (5) exhibited moderate activity to suppress NO production in LPS - simulated macrophages with an IC50 value of 24.76 ± 0.4 μM. None of the compounds showed inhibitory influenza virus and tumor activity.

Dystonia and tremor are distinct movement disorders, but they overlap in certain circumstances. First, dystonia and tremor may co-exist in the same individual, in the same or different regions of the body. Second, dystonic movements are sometimes rapid and repetitive, and they may mimic tremor. The term dystonic tremor first appeared in the literature to describe a rapid and repetitive dystonic movement that mimicked tremor but could be discriminated from essential tremor. With the first consensus statement on tremor, the term dystonic tremor was instead used to describe any combination of dystonia with tremor in the same body region, a definition retained in the latest consensus statement. Both definitions continue to be used in the modern literature. To address this problem, a group of specialists in dystonia and tremor met to review the problem and develop recommendations for more consistent approach. The group agreed that a terminology that could be applied in the clinic was essential, even though laboratory-based measures may sometimes be required. The group also agreed that the term tremor should exclusively refer to rhythmic movements, and the establishment of boundaries for rhythmicity is needed. The group also agreed that repetitive movements that are grossly arrhythmic in the context of dystonia, should be called jerky dystonia, rather than terms that imply tremor. Moreover, when both tremor and dystonia coexist, they should be described according to affected body regions rather than given distinct labels.

Survival models have become popular for credit risk estimation. Most current credit risk survival models use an underlying linear model. This is beneficial in terms of interpretability but is restrictive for real-life applications since it cannot discover hidden nonlinearities and interactions within the data. This study uses discrete time survival models with embedded neural networks as estimators of time to default. This provides flexibility to express nonlinearities and interactions between variables, and hence allows for models with better overall model fit. Additionally, the neural networks are used to estimate Age-Period-Cohort (APC) models so that default risk can be decomposed into time components for loan age (maturity), origination (vintage) and environment (e.g., economic, operational and social effects). These can be built as general models, or as local APC models for specific customer segments. The local APC models reveal special conditions for different customer groups. The corresponding APC identification problem is solved by a combination of regularization and fitting the decomposed environment time risk component to macroeconomic data, since the environmental risk is expected to have a strong relationship with macroeconomic conditions. Our approach is shown to be effective when tested on a large publicly available US mortgage data set. This novel framework can be adapted by practitioners in the financial industry to improve modelling, estimation and assessment of credit risk.

Rational delineation of urban–rural boundaries is a foundational prerequisite for holistic urban and rural development planning and rational resource allocation. However, the results of division of urban–rural boundaries extracted using a single data source are non-comprehensive. To address this problem, the present study proposes a method for using multiple sources such as population data, nighttime light data, land use, and points of interest (POI) data to extract urban–rural boundaries. Considering Guizhou Province for a case study, we here present a two-step method for identifying urban–rural boundaries. First, the random forest model was combined with the dasymetric mapping method to obtain the population spatialization data with a 30-m resolution in the studied province. Second, using the breaking point method, we extracted the urban–rural boundary for Guizhou Province in 2020 based on the spatialized population. This method fully integrated the benefits of various data and judiciously extracted the boundaries of the main urban areas and small- and medium-sized towns of each city in the study province at the same spatial scale. The stratified random sampling method revealed that the average overall accuracy was 88.05%. The method proposed has certain universality and application value and allows identifying the urban–rural boundaries more accurately and practically.

Nicotine is a pharmacologically active component of tobacco which adversely affects the male reproductive system and fertility and Icariin (ICA) is the main active ingredient of Epimedium herba which has been used to treat several male reproductive problems. This study was aimed at investigating the protective or ameliorative effect of ICA against reproductive toxicity induced by intraperitoneal injection of nicotine in mice. Forty male mice were randomly divided into 4 groups: control, nicotine (0.75 mg/kg intraperitoneally), icariin (ICA, 75 mg/kg), and icariin plus nicotine (ICA + nicotine) group. After 35 days of treatment, the mice were weighed, sacrificed, and their reproductive organs were collected and examined for further studies. In the nicotine-treated group, epididymal sperm density and serum testosterone concentrations significantly decreased relative to the control group. Nicotine also caused oxidative damage as shown by significant reduction in the activities of antioxidant enzymes and an elevation in Malondialdehyde (MDA) levels. Icariin on the other hand, improved the reduction in sperm characteristics, hormone levels, and activities of antioxidant enzymes alterations observed in the nicotine treated mice. These findings indicate that the nicotine-induced reproductive toxicity and oxidative damages on male reproductive tissues can be effectively attenuated by icariin.

As a high fatal disease, fat embolism syndrome is complication, which brought great pain to patient and their family served as a serious social burden. The mechanism of FES remains unclear. Autophagy controls the cell survival and homeostasis by removing the mis-folded proteins and damaged organelles as well as intracellular pathogens through a lysosomal degradation pathway. Increasing research documented that autophagy was wildly involved in variety of human diseases and had huge therapeutic potential. In our study, we first established the rat model of FES with the liquid fat by tail vein injection. We observed the up-regulated MPO expression and activity, increased Wet-to-Dry (W/D) lung weight, promoted quantity of fat granules, and the dominant disorder in the lung rat model of FES, compared to the control group. These observations demonstrated that we successfully build the rat model of FES. Then, we sought to dissect the role of the autophagy in the rat model of FES. The western blots analysis showed that the autophagy was inhibited in the rat model of FES constructed with liquid fat. Furthermore, Rapamycin could restore the repression of autophagy in rat model of FES. These investigations illustrated that autophagy was involved in FES. In addition, our experiments showed that Rapamycin could alleviate the symptoms of FES. Taken together, our study demonstrated the participation of autophagy in FES and further, as a potential therapeutic target, the modulation of autophagy could affect the symptom of rat model of FES.

Fully mechanized mining face production involves complex geological conditions; mining pressure; gas, water, fire and other mining environments. The working face needs a shearer, hydraulic support, a scraper conveyor and other equipment for coordination. The deep integration of intelligent technology with factors such as "humans, machines, the environment, and management" in the workplace is the core content of intelligent coal mines. This paper puts forward an advanced framework for coal mining robot technology systems, including single robots, robotized equipment, robot clusters and unmanned systems. The framework clarifies the common key technologies of coal mining robot research and development and cross-integration with new technologies such as 5G, the industrial internet, big data, artificial intelligence, and digital twins to improve the autonomous and intelligent application of coal mining robots. By establishing a scientific and complete standard system for coal mining robots, we aim to achieve customized research and development and standardized production of various types of robots. A specific analysis was conducted on the research progress of common key technologies such as explosion-proof design, mechanical system innovation, power drive, intelligent sensing, positioning and navigation, and underground communication of coal mining robots. The current research and application status of various types of coal mining robots in China are summarized. A new direction for future coal mine robot research and development is proposed. Moreover, robotic mining systems should be promoted to enhance the overall intelligence level and mining efficiency of mining equipment. To develop human‒machine environment-integrated robots to improve the autonomy and collaboration level of coal mining robots. The digital twinning of the entire mine robot system should be accelerated, the normalized operation level of coal mine robots should be improved, research on coal mining robots, support robots, and transportation robots should be carried out, intelligence should be achieved in fully mechanized mining faces, and equipment support for fewer and unmanned fully mechanized mining faces should be provided. The practical process of implementing coal mining robotization has been summarized, and the technical and engineering feasibility of the coal mining machine population has been verified.

Copper (Cu) is a critical element for cancer cell proliferation and considerably accumulates in the nucleus. 64Cu2+ is an anticancer radiopharmaceuticals targeting the copper requirement of cancer cells. However, intravenously injected 64Cu2+ ions primarily accumulate in the liver. Ligand complexation of 64Cu2+ would be a promising method for increasing tumor delivery by reducing liver uptake. Herein, we used three tripodal amine ligands [tris(2-aminoethyl)amine (Tren), diethylenetriamine (Dien), and tris(2-pyridylmethyl)amine (TPMA)] to enclose 64Cu2+ ions and compared their in vivo tumor and liver uptake using a tumor-bearing xenograft mouse model of the extrahepatic bile duct carcinoma cell line TFK-1. We examined intracellular Cu distribution using microparticle-induced X-ray emission (micro-PIXE) analysis for these compounds. 64Cu2+-Tren and 64Cu2+-Dien showed higher tumor uptake than 64Cu2+-TPMA and 64Cu2+ ions in TFK-1 tumors. Among the three 64Cu2+ complexes and 64Cu2+ ions, liver uptake was inversely correlated with tumor uptake. Micro-PIXE analysis showed that in vitro cellular uptake was similar to in vivo tumor uptake and nuclear delivery was the highest for 64Cu2+-Tren. Conclusively, an inverse correlation between tumor and liver uptake was observed using three 64Cu2+ complexes of tripodal amine ligands and 64Cu2+ ions. These results provide useful information for the future development of anticancer 64Cu radiopharmaceuticals.

Long noncoding RNAs (lncRNAs) of virus origin accumulate in cells infected by many positive strand (+) RNA viruses to bolster viral infectivity. Their biogenesis mostly utilizes exoribonucleases of host cells that degrade viral genomic or subgenomic RNAs in the 5’-to-3’ direction until being stalled by well-defined RNA structures. Here we report a viral lncRNA that is produced by a novel replication-dependent mechanism. This lncRNA corresponds to the last 283 nucleotides of the turnip crinkle virus (TCV) genome, hence is designated tiny TCV subgenomic RNA (ttsgR). ttsgR accumulated to high levels in TCV-infected Nicotiana benthamiana cells when the TCV-encoded RNA-dependent RNA polymerase (RdRp), also known as p88, was overexpressed. Both (+) and (-) strand forms of ttsgR were produced in these cells in a manner dependent on the RdRp functionality. Strikingly, templates as short as ttsgR itself were sufficient to program ttsgR amplification, as long as the TCV-encoded replication proteins, p28 and p88, were provided in trans. Consistent with its replicational origin, ttsgR accumulation required a 5’ terminal G₃(A/U)₄ motif shown by others to be crucial for the replication of a TCV satellite RNA. More importantly, introducing a new G₃(A/U)₄ motif elsewhere in the TCV genome was alone sufficient to cause the emergence of another lncRNA. Collectively our results unveil a replication-dependent mechanism for the biogenesis of viral lncRNAs, thus suggesting that multiple mechanisms, individually or in combination, may be responsible for viral lncRNA production.

Hypochlorite (ClO−) and viscosity both affect the physiological state of mitochondria, and their abnormal levels are closely related to many common diseases. Therefore, it is of great significance to develop a mitochondria-targeting fluorescent probes for the dual sensing of ClO− and viscosity. Herein, we have explored a new fluorescent probe XTAP−Bn, which responds sensitively to ClO− and viscosity with off-on fluorescence changes at 558 and 765 nm, respectively. Because the emission wavelength gap is more than 200 nm, XTAP−Bn can effectively eliminate the signal crosstalk during the simultaneous detection of ClO− and viscosity. In addition, XTAP−Bn exhibits a series of advantages, including high selectivity, rapid response, good water solubility, low cytotoxicity, and excellent mitochondrial targeting ability. More importantly, probe XTAP−Bn has been successfully employed to monitor the dynamic change of ClO− and viscosity levels in mitochondria of living cells and zebrafish. Taken together, this work not only provides a reliable tool for identifying mitochondrial dysfunction, but also offers a potential approach for the early diagnosis of mitochondrial-related diseases.

This study aims to develop an elderly care system for improving the interpersonal relationship of the elderly with mild cognitive impairment (MCI) by employing the speaker recognition technique and association functionality of social network platforms. Firstly, the speaker recognition units based on the Gaussian Mixture Model (GMM) and Gaussian Mixture Model-Universal Background Model (GMM-UBM) are implemented to identify the visitor via individual input utterance. After the visitor is identified, the proposed system will be linked to the private database and social network platforms to extract the associated message of two parties. Experimental results indicate that the speaker recognition unit based on GMM-UBM achieves the best performance. Finally, five elderly persons are invited to measure the usability of the proposed system. A questionnaire is used to survey the five elderly persons, and the result indicates that the proposed system is highly potentially applicable in improving the interpersonal relationship of the elderly with MCI.

Bionic robotic hand can perform many movements similar to human hand. But there is still a significant gap in manipulation between robot and human hand. It is necessary to understand the finger kinematics and motion patterns of human hand to improve the performance of robotic hand. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hand of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a largest dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Besides, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by PIP joint. Regarding the finger sequence, the thumb started to move before four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided kinematic reference for the design of robotic hand and thus contribute to its development.

Design changes seem inevitable in engineering, procurement and construction EPC projects. Such changes create a need for a proactive approach to adjusting project scope, cost and time (the triple constraints) for efficiency and effectiveness in overall delivery. This study investigates the causes and implications of design changes in order to improve design change management practices. Data for the study was obtained through online interviews with New Zealand industry practitioners. Thematic analysis was used to collate the results into meaningful data. The study found that design changes were predominantly caused by clients' inadequate strategic planning, insufficient attention to design, EPC contractors' inadequate design ability, and on-site variations. There were three categories of such design changes: direct impact on the project, the reciprocal and complementary effect on stakeholders, and the far-reaching impact on the community. The study concludes by suggesting improvements, such as strengthening the integration of project teams to enhance design quality, strategic alignment of stakeholders at the planning stage, early contractor involvement (ECI) between the planning and design phases, and improving collaboration between design and construction teams. Further, a combination of high technical skills (e.g. design ability) and soft skills (can-do attitude, interpersonal skills, problem-solving skills, documentation skills, etc.) are needed to effect the desired improvement in design change management.

Geminiviruses possess single-stranded, circular DNA genomes, and control the transcription of their late genes, including BV1 of many bipartite begomoviruses, through transcriptional activation by the early expressing AC2 protein. DNA binding by AC2 is not sequence-specific, hence the specificity of AC2 activation is thought to be conferred by plant transcription factors (TFs) recruited by AC2 in infected cells. However, the exact TFs AC2 recruits are not known for most viruses. Here we report a systematic examination of the BV1 promoter (PBV1) of mungbean yellow mosaic virus (MYMV) for conserved promoter motifs. We found that MYMV PBV1 contains three abscisic acid (ABA)-responsive elements (ABREs) within its first 70 nucleotides. Deleting these ABREs, or mutating them all via site-directed mutagenesis, abolished the capacity of PBV1 to respond to AC2-mediated transcriptional activation. Furthermore, ABRE and other related ABA-responsive elements were prevalent in more than a dozen Old World begomoviruses we inspected. Together these findings suggest that ABA-responsive TFs may be recruited by AC2 to BV1 promoters of these viruses to confer specificity to AC2 activation. These observations are expected to guide the search for the actual TF(s), furthering our understanding of the mechanism of AC2 action.

In Taiwan, colorectal cancer is ranked second and third in terms of mortality and cancer incidence, respectively. In addition, medical expenditures related to colorectal cancer are considered to be the third highest. While advances in treatment strategies have provided cancer patients with longer survival, potentially harmful second primary cancers can occur. Therefore, second primary colorectal cancer analysis is an important issue with regard to clinical management. In this study, a novel predictive scheme was developed for predicting the risk factors associated with second colorectal cancer in patients with colorectal cancer by integrating five data mining classification techniques, including support vector machine, random forest, multivariate adaptive regression splines, extreme learning machine, and extreme gradient boosting. In total, 4,287 patients in the datasets provided by three hospital tumor registries were used. Our empirical results revealed that this proposed predictive scheme provided promising classification results and the identification of important risk factors for predicting second colorectal cancer based on accuracy, sensitivity, specificity, and area under the curve metrics. Collectively, our clinical findings suggested that the most important risk factors were the combined stage, age at diagnosis, BMI, surgical margins of the primary site, tumor size, sex, regional lymph nodes positive, grade/differentiation, primary site, and drinking behavior. Accordingly, these risk factors should be monitored for the early detection of second primary tumors in order to improve treatment and intervention strategies.

High dietary phosphate intake and poor adherence to phosphate-binding-therapy elevate the risk of hyperphosphatemia in maintenance hemodialysis (HD; MHD) patients. Therefore, chronic kidney disease-related mineral and bone disorder (CKD-MBD) indicators increase; consequently, risks of CKD-MBDs and inflammation are elevated. This double-blind, randomized control trial intervention study was designed to investigate the possibility of reducing blood CKD-MBD indicators and modulating inflammatory indicators by consuming low-phosphate (LP) meals accompanied by a minimum dose of a calcium-based phosphate binder (CaCO3). MHD patients were recruited and randomly assigned to an LP meal group (LP group) or a control group. After initial data collection, blood collection, and dietary counseling, subjects were asked to consume a washout diet for 1 week. During the washout diet period, subjects consumed their usual diet but took 1 tablet of calcium carbonate (1CaCO3) as a phosphate binder with each meal. After the washout diet period, subjects in the LP group and control group respectively consumed LP meals and regular meals twice a day for 1 week. Meat in the LP meals was boiled before the regular cooking process, but meat in control meals was not. All meals were supplied by a central kitchen so that the contents of phosphate and other nutrients could be identified. In total, 40 MHD patients completed the study program. After 1 week of the dietary intervention, the blood Ca x P product and dietary phosphate had significantly decreased in the LP group compared to the control group (p&lt;0.05). The LP group had significantly lower variations in dietary phosphate intake, blood calcium, Ca x P product, and tumor necrosis factor (TNF)-α than the control group by comparing differences between after the dietary intervention and the baseline (△after intervention - baseline, p&lt;0.05). The increase in dietary phosphate intake (△3rd - 2nd dietary phosphate intake) augmented the increase in the TNF-α level by 6.24-fold (odds ratio [95% confidence interval]: 6.24 [1.12~34.92], p&lt;0.05). These results highlighted the conclusion that LP meals accompanied by a minimum dose of CaCO3 downregulated pro-inflammation by reducing CKD-MBD indicators which was triggered by decreasing dietary phosphate intake.

We investigate the ammonium removal abilities of natural and synthetic zeolites, which have distinct Si/Al ratios and various surface areas, to study how adsorption and ion-exchange processes in zeolites perform under different ammonium concentrations and different temperatures. Five zeolites including natural mordenite, chabazite, erionite, clinoptilolite and synthetic merlinoite were immersed in 20 mg/kg, 50 mg/kg and 100 mg/kg ammonium solutions. The results demonstrate that zeolites under high ammonium concentrations (100 mg/kg) possess higher physical adsorption capacity (0.398–0.468 meq/g), whereas those under lower ammonium concentrations (20 mg/kg) possess greater ion-exchange property (64–99%). The ion-exchange ability of zeolites are extremely dependent on the cation content of the zeolites, and the cation content is affected by the Si/Al ratio. The surface area of zeolites also has a partial influence on its physical adsorption ability. When the surface area is less than 100 m²/g, the adsorption ability of zeolite increases obviously with surface area; however, adsorption ability is saturated as the surface area becomes larger than this critical value of 100 m²/g. When we carried out the zeolites in 50 mg/kg ammonium concentration at different temperatures (5~50 ℃), we found that zeolites exhibit the highest ammonium removal ability at 30°C and the potassium release was enhanced at 30~40 ℃.

The surface behavior of the ZnO-based films could be modulated via a postannealing and ultraviolet (UV) irradiation with different powers and time, respectively. These present results could provide modulate the microstructure related in grain-size distribution and photocatalytic behavior for potential guide in the field of wide bandgap semiconducting oxides. The ZnO films were prepared onto Corning-1737 glass substrates by using radio-frequency magnetron sputtering without supplying oxygen source at room temperature. For the purpose of obtaining modulable grain microstructures, the as-prepared ZnO films (Z0) were treated via a postannealing modification in vacuum furnace at 300°C for 30 minutes after deposition (Z300) accompanied with the adjustable internal stress. The contact angle (CA) value of ZnO film reduced from 95° to 68° was owning to the different grain microstructure accompanied by a change in size variation. In addition, the UV light with different irradiation powers could also be used to improve the hydrophilicity varied from hydrophobic status to superhydrophilic status due to the desirable surface characteristics of the photocatalytic action. In addition, the photocatalytic activity of ZnO film exhibited efficient photodegradation of methylene blue (MB) under UV irradiation, with a chemical reaction constant of 2.93×10-3 min−1. In this present work, we demonstrated that the CA value of the ZnO films not only caused from hydrophobic to hydrophilic status accompanied by a change in grain size combined with internal stress but also induced by the UV light irradiation combined with photocatalytic activity simultaneously. On the other hand, the enhanced surface plasmonic resonance could be observed that is due to couple electron and photon oscillations and can be generated at the interface between a flat, continuous Pt capping nanolayer. This designed structure could also be considered as a Pt electrode pattern onto ZnO (metal Pt/ ceramic ZnO) for multifunctional heterostructured sensors and devices in near future.

Abstract: Because of outstanding heat resistance and processing qualities, benzoxazine resins are widely employed in a variety of applications. However, traditional benzoxazine resins still confront hurdles in today's engineering applications, such as can’t long-term service in high-temperature settings and inadequate toughness. Four alkyne-functionalized benzoxazines with phthalide side group and cyano group of varying molecular weights were produced in this study. Fourier trans-form infrared spectroscopy (FT-IR) and hydrogen nuclear magnetic resonance spectroscopy ( 1H-NMR ) were used to characterize the resin structure, and differential scanning calorimetry (DSC) was used to investigate the thermal curing kinetics at different warming rates, the apparent activation energy was 116.9 kJ/mol. In-situ FTIR was used to investigate the cure mechanism. Dynamic mechanical analysis (DMA) was used to evaluate the gelationation time of BOZ series resins at various temperatures, and the curing process was designed by combined the results of DSC. The Tg of the composites made using BOZ-1N21 as the matrix was 336°C, which was much higher than the Tg of the BP-a resin made with aniline, phenolphthalein, and formaldehyde (Tg=251°C). As a result, the resin system is expected to be employed in applications requiring high-temperature resistance and toughness.

As major natural disasters in grassland areas, fires and dust events seriously threaten human safety, property, and animal husbandry. Furthermore, these phenomena may be mutually reinforcing, which can lead to more severe cascading disasters. However, few studies have been on the mechanisms of grassland fire and dust events disaster chain. Therefore, we selected Dornod aimag (province), a typical temperate grassland, as the study area and analyzed the spatiotemporal variation patterns of grassland fires and dust weather, as well as the effect of grassland fires on dust weather based on MCD64A1 Burnt Area data and SYNOP dust data. The mechanism of grassland fires on dust weather was further investigated using the MOD13A3 vegetation index product and ERA5 wind speed, wind direction, and precipitation data. The results revealed that grassland fires and dust weather varied spatially across the study area. Furthermore, grassland fires occurred mainly in spring (April to May), summer (June), and autumn (October), while dust weather mainly occurred in spring (March to May). Moreover, autumn, winter, and spring cumulative grassland fires (both days and area) substantially affected the spring total dust weather days and dust storm days, particularly the spring cumulative dust storm days. Additionally, higher precipitation in the summer of 2014 resulted in higher vegetation coverage and more fuel in the autumn and winter of 2014, and even in the spring of 2015. As a result, the cumulative grassland fire days was higher, and the area was larger from September 2014 to April 2015, leading to a considerable increase in the cumulative dust storm days in May 2015. This study has important implications for disaster prevention and mitigation, ecological and environmental protection, and sustainable development in grasslands.

The main objective of this study is to develop a Hapke photometric model that is suited for Chang’E-1 (CE-1) Interference Imaging Spectrometer (IIM) data. We first divided the moon into three areas including ‘maria’, ‘new highland’ and old ‘highland’ with similar photometry characteristic based on the Hapke parameters of the moon derived from Lunar Reconnaissance Orbiter Camera (LROC) Wide Angle Camera (WAC) multispectral data. Then, we selected the sample data in the ‘maria’ area and obtained a new set of Hapke model’s parameters that can best fit these data. Result shows that photometric correction using Hapke model with these new derived parameters can eliminate the effect of variations in viewing and luminating geometry, especially ‘opposition surge’, more efficiently than the empirical model. The corrected mosaic shows no significant artifacts along the tile boundaries, and more detailed information of the image can be exhibited due to a better correction of ‘opposition surge’ at small phase angle (g <15°).

Plants of the golden Camellia group are not only high-quality camellia germplasm , but also a plant group with rich medicinal and nutritional value, which are used as food, cosmetics and traditional medicine in China. There are approximately 50 species in this group around the world, and more than 30 species of golden camelliaplants have been published in China. The leaves and flowers of these species have similar shapes, so they are often confused as species. Our study used simplified genome sequencing technology to construct a phylogenetic tree of plants in the Chinese golden Camellia group and describe the evolutionary relationships . At the same time, the secondary metabolic indexes of total phenols, total flavonoids, total anthocyanins and ellagic acid in the leaves were determined., and principal component clustering analysis was performed . The results showed that the chemical classification and genetic phylogenetic trees showed some of the same trends, indicating that Camellia chinensis can be used as Biomarkers for chemical type. The research results provide phylogenetic information for the genotype and performance diversity of golden camelliaregionally distributed in China. At the same time, molecular biology phylogenetic methods are used to understand or explain the characteristics of secondary metabolites of golden Camellia , and provide theoretical basis for the search and development of potential bioactive substances.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

(1) Background: Previous systematic review suggested a beneficial effect of progressive muscle relaxation (PMR) for cancer patients receiving chemotherapy. However, poor quality of eligible studies impaired the reliability and validity of findings. Moreover, additional potential studies with good quality published in Chinese language have been published recently. The aim of the present systematic review was to investigate the value of PMR training in preventing and alleviating nausea and vomiting caused by chemotherapy among cancer patients. (2) Methods: We assigned two independent investigators to search all potential studies in PubMed, Cochrane Controlled Register of Trial (CENTRAL), Cumulative Index to Nursing and Allied Health Literature (CINAHL), China Biomedical Literature database (CBM), China National Knowledge Infrastructure (CNKI), and Wanfang data. We used data extraction sheet extracted all essential information, and used the Cochrane risk of bias assessment tool to appraise the quality of eligible studies. Finally, we qualitatively summarized the results of all included studies. (3) Results: Six studies enrolling 288 patients were considered to meet our selection criteria finally. Of these 6 studies, three were labeled as moderate quality, and the remaining studies were low quality. All included studies consistently suggested that PMR has a positive impact on nausea and vomiting caused by chemotherapy among cancer patients especially alleviating the incidence, frequency and degree of delayed nausea and vomiting. (4) Conclusions: Independent studies indicated that PMR was a beneficial approach to prevent and alleviate nausea and vomiting caused by chemotherapy among cancer patients. However, further studies considering other types of primary tumors should be designed in order to increase the generality of PMR because studies included in the present systematic review mainly enrolled lung cancer and breast cancer.

Most neuromorphic technologies use a point-neuron model, missing the spatiotemporal nature of neuronal computation performed in dendrites. Dendritic morphology and synaptic organization are structurally tailored for spatiotemporal information processing, enabling various computations like visual perception. Here, we report on a neuromorphic computational model termed ‘dendristor’, which integrates functional synaptic organization with dendritic tree-like morphology computation. The dendristor presents bioplausible nonlinear integration of excitatory and inhibitory synaptic inputs with silent synapses and diverse spatial distribution dependency. We show that the dendristor can emulate direction selectivity, which is the feature to react robustly to a preferred signal direction on the dendrite. We discover that silent synapses can remarkably enhance direction selectivity, turning out to be a crucial player in dendritic computation processing. Finally, we develop neuromorphic dendritic neural circuits that can emulate a cognitive function such as motion perception in the retina. Using dendritic morphology, we achieve visual perception of motion in 3D space by various mapping of spatial information on different dendritic branches. This neuromorphic dendritic computation innovates beyond current neuromorphic computation and provides solutions to explore new skylines in artificial intelligence, neurocomputation, and brain-inspired computing.

In this work, we have developed a non-ordinary state-based peridynamic model for multiple crack initiation and propagation due to compression-compression fatigue load. In each loading cycle, the fatigue loading is redistributed among the peridynamic solid body, leading to the progressive fatigue damage initiation and propagation in an autonomous fashion. The proposed fatigue model parameters are firstly validated by 3D numerical benchmark tests, and then it is applied to simulate widespread fatigue damage evolution of the aircraft wing corner box. The modified constitutive damage model has been implemented into the peridynamics framework at finite strain. Furthermore, the criterion algorithm from multiple initiation to propagation is discussed. It is shown that the numerical results obtained from peridynamics simulations are in general agreement with those from the experiment data. The comparison of experimental and numerical results indicates that the proposed non-ordinary state-based peridynamics fatigue model has the ability to capture the multiple crack initiation and propagation and other features of the aluminium alloy material.

It’s been reported that Mori Folium (MF) and Eucommiae Cortex (EC) exhibit pharmacological effects on the treatment of immunosuppression. However, the mechanism of MF and EC against immunosuppression remains unclear. This study aims to explore the mechanism of action of MF and EC for the treatment of immunosuppression through network pharmacology, molecular docking, molecular dynamics simulations and animal experiments. As a result, 11 critical components, 9 hub targets, and related-signaling pathways of treatment of immunosuppression were obtained based on network pharmacology. The molecular docking suggested that 11 critical components exhibited great binding affinity to 9 hub targets of immunosuppression. The molecular dynamics simulations results showed that (-)-Tabernemontanine-AR, beta-sitosterol-AR and Dehydrodieugenol-HSP90AA1 complexes are stably bound. Additionally, in the animal experiments, the treated group results compared to the control group suggest that MF and EC have a significant effect on the treatment of immunosuppression. Therefore, the MF and EC treatment for immunosuppression may take effects in a multi-component, multi-target, and multi-pathway manner. The results would provide novel insights into the treatment of immunosuppression in humans.

The welding and construction processes of H-type thick-plate-bridge steel involve complex multi-pass welding processes, which is difficulty to ensure its welding performance. Accordingly, it is crucial to explore the inherent correlation among the welding processes parameters and welding quality, and applied it into the welding robots, eliminating the instability from manual welding. In order to improve the welding quality, the GMAW (Gas Metal Arc Welding) welding process parameters are simulated using the Q345qD bridge steel flat joint model. Four welds with X-shaped grooves are designed to optimize the parameters of welding current, welding voltage, and welding speed. The optimal welding process parameters are investigated through thermal-elastic-plastic simulation analysis and experimental verification. The results indicate that when the welding current is set to 230A, the welding voltage to 32V, and the welding speed to 0.003m/s, the maximum deformation of the welded plate is 0.52mm, with a maximum welding residual stress of 345MPa. Both the simulation results of multi-pass welding and experimental tests meet the welding requirements, as they show no excessive stress or strain. These parameters can be applied into building large steel frame bridges with welding robots, improving the quality of welded joints.

Lung adenocarcinoma (LUAD) is the most common lung cancers, which accounts for about 35%-40% of all lung cancer patients. Despite therapeutic advancements in recent years, the overall survival time of the LUAD patients still remain poor, especially KRAS mutant LUAD. Therefore, it is necessary to further explore novel targets and drugs to improve the prognosis of LUAD. Ferroptosis, an iron-dependent regulated cell death (RCD）caused by lipid peroxidation, has attracted much attention recently as an alternative target for apoptosis in LUAD therapy. Ferroptosis has been found closely related with LUAD, at its every stage, including initiation, proliferation and progression. In this review, we will provide a comprehensive overview on ferroptosis mechanisms, it’s regulation in LUAD, and application of targeting ferroptosis for LUAD therapy.

The Danxia landform area of Jingbian Wave Valley is located in the central part of Ordos Basin. The near-red Danxia landform consisting of sandstone in this area is a new discovery in geological circles at home and abroad, and its depositional age and genesis remain a hot topic of discussion at present. As the material basis for its development, red sandstone is of great importance to the in-depth study on its formation date and origin. The paper explores the origin, tectonic significance and paleogeographic pattern of the red sandstone through field geological investigation and zircon U-Pb dating analysis of the red sandstone of the Luohe Formation. The results show that the original materials of the red sandstone was formed in three main age intervals, 252~456 Ma, 1657~2084 Ma, and 2129~2538 Ma, and regional tectonothermal events in the origin area during the three periods were recorded, among which the events in Mesoproterozoic and Paleoproterozoic periods were the most active. The comparative analysis of zircon U-Pb age spectra shows that for the sediment of red sandstone, the early origin is near-origin and late origin is distant-origin. The main origin areas in the study area are the Xingmeng orogenic belt, the North China massif and the Alashan massif; the vertical section reflects that the origin area has the strongest erosion and transport in the upper deposition period, the smallest erosion and transport in the middle deposition period, and the moderate erosion and transport in the lower deposition period. With origins system dominated by the northern origins and the paleogeographic pattern of multi-period and cyclonic, the area mainly experienced four tectonic movement cycles, such as Wutai, Lvliang, Caledon and Haixi.

: This study focuses on optimizing chlorophyll extraction techniques and strategically placing leaf disks to enhance chlorophyll concentration in sesame (Sesamum indicum L.) leaves. Thirty sesame genotypes, categorized into light green (LG), middle green (MG), and deep green (DG) pigment groups based on leaf coloration, were selected from a larger pool of field-grown accessions. The investigation involved determining optimal SPAD value index measurements, quantifying pigment concentrations, exploring extraction solvents, and selecting suitable leaf disk positions. Significant variations in chlorophyll content were observed across genotypes, greenness categories, and leaf disk positions. The categorization of genotypes into DG, MG, and LG groups revealed a correlation between leaf appearance and chlorophyll content. The study highlighted a consistent relationship between carotenoids and chlorophyll, indicating their role in adaptation to warm environments. Examination of leaf disk positions revealed a significant chlorophyll gradient along the leaf blade, emphasizing the need for standardized protocols. Chlorophyll extraction experiments identified DMSO and 96% ethanol, particularly the later incubated for 10 minutes at 85°C, as effective choices. This recommendation considers factors like cost-effectiveness, time efficiency, safety, and environmental regulations, ensuring consistent and simplified extraction processes. For higher chlorophyll extraction, focusing on leaf tips and the 75% position along the sesame leaf blade is suggested, consistently yielding higher chlorophyll content. Our findings therefore, underscores insightful knowledge on chlorophyll gradients and encouraging for standardized protocols, that enabling researchers to refine experimental designs for precise and comparable chlorophyll measurements. Recommended solvent choices ensure reliable outcomes in plant physiology, ecology, and environmental studies.

Currently, historical areas in China are facing issues of color authenticity and excessive commercialization. Colors, as an important element of historical areas, reflect their history and culture. However, there are some flaws in the existing research methods, so a more scientific and systematic method is needed to obtain accurate and objective color visualization results to promote the sustainable development of historical areas. In order to explore the methods and applications of visualizing the environmental color genes of historical areas, Shiquan Street in Suzhou, China was taken as the research object, ArcGIS 10.5 was used to obtain the street veiw photo samples, Matlab was used to summarize the architectural colors of the historical areas, and K-means clustering was used to generate the central color card of the historical areas, thus completing the color visualization of the historical areas, followed by further searching for the color patterns and central colors, so as to explore the strategies for sustainable development of historical areas. The various quantified color models of historical areas can explore the regional uniqueness and color locality of historical areas, which avoids problems such as homogenization of block colors, unclear styles and features, and excessive proportion of commercial colors caused by poor color guidance and control in the design related to historical areas, providing approaches to the research on the harmonious unity of environmental colors and features related to historical areas.

Background: The reported associations between time to first antibiotic dose after hospital arrival and short-term mortality have varied in prior studies of CAP. It is unclear the benefit of early antibiotics in all patients given the risks of antibiotic overuse and misdiagnosis; Methods: A PubMed and Google Scholar search was performed to identify articles detailing the epidemiology, prognosis, diagnosis, and preliminary management of CAP; Results: In sepsis, antibiotics should not be delayed, and should be administered as soon as possible after recognition. For moderate or severe CAP patients without sepsis, antibiotics should be administered as soon as the diagnosis of CAP is highly likely. For stable, non–critically ill patients with CAP, the timing of antibiotics is not as clear and available evidence does not recommend strict requirements. Antibiotic timing – both rapid and delayed could be used as indicators of quality care in differing clinical scenarios; Results: The dogma of starting antibiotics quickly, within a rigid timeframe of expectations and guidelines has not improved outcomes in pneumonia patients, and has led to an increase in antibiotic treatment in uninfected patients. Severity of illness is the key factor associated with poor outcomes and should more significantly guide the timing of antibiotic initiation.

Autonomous aerial refueling technology is an effective solution to extend flight duration of unmanned aerial vehicles, and also a great challenge due to its high risk. For autonomous probe-and-drogue refueling tasks, relative navigation to provide relative position between the receiver aircraft and the refueling drogue is the first and essential step, and vision-based method is the most frequently used. A new monocular vision navigation sensor with image processing strategy consisting of the drogue detection method and the tracking method is developed for autonomous aerial refueling in this paper. In the drogue detection method, thresholding and mathematical morphology method are adopted to eliminate image interference, and contours extraction method is applied to obtain all contours, which are then subsequently checked to achieve target contour of drogue. In the tracking method, a rectangle of interest (ROI) of current frame image is determined by positioning results of last frame, and then processed by the previous drogue detection method. Finally, the proposed image processing strategy in monocular vision navigation sensor is validated using real flight images, which are captured from an autonomous aerial refueling testbed using a micro six-rotor aircraft as receiver aircraft.

Adult neurogenesis involves generation of functional neurons from neural progenitor cells, which have the potential to complement and restore damaged neurons and neural circuits. Therefore, the development of drugs that stimulate neurogenesis represents a promising strategy in stem cell therapy and neural regeneration, greatly facilitating the reconstruction of neural circuits in cases of neurodegeneration and brain injury. Our study reveals that compound A5, previously designed and synthesized by our team, exhibits remarkable neuritogenic activities, effectively inducing neurogenesis in neural stem/progenitor cells (NSPCs). Subsequently, transcriptome analysis using high-throughput Illumina RNA-seq technology was performed to further elucidate the underlying molecular mechanisms by which compound A5 promotes neurogenesis. Notably, comparative transcriptome analysis showed that the up-regulated genes were mainly associated with neurogenesis and the down-regulated genes were mainly concerned with cell cycle progression. Furthermore, we confirmed that compound A5 significantly affected the expression of transcription factors related to neurogenesis and cell cycle regulatory proteins. Collectively, these findings identify a new compound with neurogenic activity and may provide insights into drug discovery for neural repair and regeneration.

ALDH+ H1975 lung adenocarcinoma stem cells (LSCs) are a rare cell population identified in lung adenocarcinoma (LUAD). LSCs can self-renew, drive tumor initiation, growth, metastasis, and recurrence, and are also the predominant cause of poor prognosis due to their intrinsic resistance to drugs and chemotherapy. Consequently, LSCs are a promising target for LUAD therapy. Noncoding RNAs (ncRNAs), including microRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs), exert many significant regulatory functions in the pathogenesis of human cancers, showing the necessity for a comprehensive understanding of the mechanisms that underlie lung carcinogenesis. Nonetheless, research on many known transcripts and messenger RNAs (mRNAs) has already generated new information. Unknown biomarkers in ncRNAs and systematic and comprehensive interrelation with unknown ncRNAs and mRNAs may provide further insights into the biology of LUAD. Herein, a set of novel ncRNAs that include miRNAs, lncRNAs, circRNAs, were identified and differentially expressed patterns of ncRNAs and mRNAs in LSCs and ALDH- H1975 LUAD tumor cells (LTCs) were obtained using stringent bioinformatics pipelines. Through a meta-analysis of the identified landscapes, novel competitive endogenous RNA (ceRNA) networks were constructed to reveal the potential molecular mechanisms that regulate the hallmarks of LSCs and LTCs. This study presents a summary of novel ncRNAs and the fundamental roles of differentially expressed ncRNAs implicated in the activity of LSCs and LTCs. In addition, the study also provides a comprehensive resource for the future identification of diagnostic, therapeutic, and prognostic biomarkers in LUAD.

Since the outbreak of the COVID-19 pandemic, patients infected with COVID-19 may experience abnormal heart rates, posing potential health risks. This study proposes a non-contact method for measuring heart rate (HR) and heart rate variability (HRV) to effectively reduce the risk of infection and assist healthcare professionals in more accurate diagnosis and treatment. In this study, except for the different image acquisition method, other research processes and methods are similar to the research methods in [15]. The image acquisition method is changed from forehead image to palm image. The new non-contact measurement performance of the proposed method can effectively not only avoid infection concerns but also obtain heart rate and HRV quickly and conveniently, providing higher accuracy for physiological parameters, root mean square error (RMSE), and mean absolute percentage error (MAPE) compared to those in recently published papers.

The Paeonia suffruticosa, called as 'Feng Dan', has been used for thousands of years in traditional Chinese medicine. In our chemical investigation on the root bark of the plant, five new phenolic dimers, namely paeobenzofuranone A‒E (1‒5), have been characterized. Their structures were determined by spectroscopic analysis including 1D and 2D NMR, HRESIMS, UV, and IR, as well as ECD calculations. Compounds 2, 4, and 5 showed cytotoxicity against three human cancer cell lines with IC50 values ranging from 6.7 to 25.1 μM. Compounds 1 and 2 showed certain inhibitory activity on NO production. To the best of our knowledge, the benzofuranone dimers and their cytotoxicity of P. suffruticosa are reported for the first time.

Many positive sense RNA viruses, especially those infecting plants, are known to experience stringent, stochastic population bottlenecks inside the cells they invade, but exactly how and why these populations become bottlenecked are unclear. A model proposed ten years ago advocates that such bottlenecks are evolutionarily favored because they cause the isolation of individual viral variants in separate cells. Such isolation in turn allows the viral variants to manifest the phenotypic differences they encode. Recently published observations lend mechanistic support to this model, and prompt us to refine the model with novel molecular details. The refined model, designated Bottleneck, Isolate, Amplify, Select (BIAS), postulates that these viruses impose population bottlenecks on themselves by encoding bottleneck-enforcing proteins (BNEPs) that function in a concentration-dependent manner. In cells simultaneously invaded by numerous virions of the same virus, BNEPs reach the bottleneck-ready concentration sufficiently early to arrest nearly all internalized viral genomes. As a result, very few (as few as one) viral genomes stochastically escape to initiate reproduction. Repetition of this process in successively infected cells isolate viral genomes with different mutations in separate cells. This isolation prevents mutant viruses encoding defective viral proteins from hitchhiking on sister genome-encoded products, leading to the swift purging of such mutants. Importantly, genome isolation also ensures viral genomes harboring beneficial mutations accrue the cognate benefit exclusively to themselves, leading to the fixation of such beneficial mutations. Further interrogation of the BIAS hypothesis promises to deepen our understanding of virus evolution, and inspire new solutions to virus disease mitigation.

In the natural environment, sand accumulation and desertification can influence the efficiency of photovoltaic arrays. In this study, PV module output characteristics were examined under different sand particle size, varying sand densities and inclination angles, and at wind speeds of 5m/s, 10m/s, and 15m/s. Both theoretical and experimental results showed that the output power of the module declines with increasing sand density. As the sand particle size increases, the module maximum output power rises and then stabilizes. The two control variables, namely sand density and sand particle size, influence the module temperature and light transmittance distinctly. Contrary to the impact of sand density on the module filling factor curve, the module filling factor exhibits varying trends under different sand particle sizes. Additionally, the pattern of the module filling factor as a function of sand density contrasts with that of the module temperature under analogous conditions. Specifically, when the sand density on the PV module surface increases from 0 to 40g/m², there is a 32.2% reduction in maximum output power. At a wind speed of 15m/s, this reduction was found consistent across all wind speed categories. Furthermore, the trend of the module filling factor rel-ative to sand accumulation density contrasts with the module temperature trend under analogous conditions. Notably, the filling factor reached its apex at a sand accumulation density of 35g/m², which corresponded to the module temperature's nadir during the experiment.

Mangrove forests play a vital role in maintaining the ecological balance of coastal regions. Ac-curately assessing changes in their ecosystem service value (ESV) requires more than precise mangrove distribution data, an appropriate set of evaluation methods is also needed. In this study, we obtain the spatial distribution and structural changes of mangrove forests based on Sentinel-2 imagery and build a mangrove forest ESV evaluation system by combining spatial pattern and the millennium ecosystem services. The results showed that: (1) the area of mangroves in Guangxi increased from 6245.15 ha in 2016 to 6750.01 ha to 2020, with a net increase of 504.81 ha which mainly concentrated in Lianzhou Bay, Tieshan Harbour and Dandou Bay; (2) the ESV of mangrove forests was 379.85 million U.S. dollars (USD) in 2016 and 413.13 million USD in 2020; (3) the value of fishery, soil conservation, wave absorption, and pollution purification comprise the largest proportion of the ESV of mangrove forests. From 2016 to 2020, mangroves in Guangxi had demonstrated a positive development trend and was undergoing a process of recovery. Results and conclusions of this study provide valuable insights and information to facilitate a more profound comprehension of the relationship between the mangrove forest and its ecological significance.

Ferroptosis is a newly discovered iron-dependent form of regulated cell death driven by phospholipid peroxidation, associated with processes including iron overload, lipid peroxidation and dysfunction of cellular antioxidant systems. Ferroptosis is found closely related to many diseases including cancer, at its every stage. Epithelial-mesenchymal transition (EMT) in malignant tumors that originate from epithelia promotes cancer cell migration, invasion and metastasis by disrupting cell-cell and cell-martrix junctions, cell polarity, etc. Recent studies have shown that ferroptosis appears to share multiple initiators and overlapping pathways with EMT in cancers and identify ferroptosis as a potential predictor of various cancer grade and prognosis. Cancer metastasis involves multiple steps including local invasion of cancer cells, intravasation, survival in circulation, arrest at a distant organ site, extravasation and adaptation to foreign tissue microenvironments, angiogenesis and the formation of “premetastatic niche”. Numerous studies have revealed that ferroptosis is closely associated with cancer metastasis. From the cellular perspective, ferroptosis has been implicated in the regulation of cancer metastasis. From the molecular perspective, the signaling pathways activated during the two events interweave. This review briefly introduces the mechanisms of ferroptosis, and discusses how ferroptosis is involved in cancer progression including EMT, cancer angiogenesis, invasion and metastasis.

Hexabromocyclododecane (HBCD) was most important flame retardant in Expanded Polystyrene foam and Extruded Polystyrene foam in the past forty years in the world. China was the major producer and user of HBCD, and the total HBCD production was about 0.3 million tons. Although HBCD has been completely banned in China in 2021 because of its long-range transport, bioaccumulation and toxicity, there's still a lot of residues in environment. Therefore, we reviewed multiple studies concerning the distribution of HBCD in diverse environmental matrices, such as air, dust, soil, water, sediment and biota. Results revealed that HBCD levels in different environments in China present a geographical variation and were at high level compared with other countries. In all environmental media, relatively high HBCD concentrations have been found in industrial and urban areas. Industrialization and urbanization are two important factors that influence the concentration and distribution of HBCD in the environment. In terms of isomer, γ-HBCD was the dominant isomer in soil, water, and sediment, while in the biota, α-HBCD was the predominant isomer.

An optimal scheduling strategy for cooling, heating and power (CCHP) joint-power-supply system is proposed to improve energy utilization and minimize costs in this paper. Firstly, the mathematical model of CCHP system is established. Particle swarm optimization (PSO) is used to optimize the regularization coefficient C and the kernel parameter λ which can affect the prediction accuracy of KELM(PSO-KELM). Then PV generation and load prediction model are established by PSO-KELM. In order to jump out of local optimal solution, Cauchy variation is introduced in SFLA local update, and adaptive mutation operation is carried out on SFLA individuals. The predictions of PV generation and load power by PSO-KELM are imported into the objective function, and the microgrid dispatching model is solved by the improved SFLA algorithm. Compared with the traditional GA-KELM and KELM, PSO-KELM has faster convergence and prediction accuracy. Compared with the power supply division, the operation cost of the power grid is reduced by the proposed optimization dispatching strategy of CCHP micro-grid.

In recent years, a large-scale afforestation campaign has taken place in Inner Mongolia, China, to control desertification and soil erosion. However, the water consumption associated with large-scale afforestation significantly impacts the water resources in Inner Mongolia, resulting in a substantial ecological risk. This study aimed to evaluate the ecological risk of water resources caused by afforestation in the region. In this study, based on land cover data, Normalized Difference Vegetation Index (NDVI) data, and meteorological data, used trend analysis, water balance equation, and Water resources Security Index (WSI) index to analyze the ecological risks of water resources caused by afforestation in Inner Mongolia from 2000 to 2020. The results show that:(1) The afforestation area in Inner Mongolia was 5.37×104 km2 in 2000-2020; (2) Afforestation in arid and semi-arid areas leads to the reduction of water resources. (3) Afforestation reduces water resources in the study area by 0.76×108m3/year; (4) ~76% of afforestation regions face ecological risks of water resources.

Background: Currently, many detection methods have high sensitivity to the diagnosis of lung cancer. However, some postoperative patients with pulmonary nodule were eventually diagnosed as benign nodules. The ideal evaluation of an individual with a pulmonary nodule would expedite therapy for a malignant nodule and minimize testing for those with a benign nodule.Methods: This case-control study is designed to explore the relationship between ACE1 rs4646994 polymorphism and the risk of lung cancer in patients with pulmonary nodules, 400 individuals with lung cancer and benign pulmonary nodules were included. A DNA extraction kit was used to extract plasm DNA from peripheral blood. The relationship between ACE1 rs4646994 and the risk of lung cancer in patients with pulmonary nodules was determined by chi-square test, logistic regression analysis and cross analysis. Results: The results showed that the DD genotype of ACE1 rs4646994 may increase the risk of lung cancer in patients with pulmonary nodules, and this correlation was more significant in the female subgroup. In the age stratification analysis, it was found that the risk of lung cancer was significantly increased in the DD genotype of ACE1 rs4646994 in the older subgroup (&gt; 45 years). In addition, the possibility of EGFR mutation in lung adenocarcinoma patients with ACE1 rs4646994 DD genotype was lower than that of II or ID genotype carriers. Conclusions: Our study indicated that ACE1 rs4646994 polymorphism increases the risk of lung cancer in patients with pulmonary nodules from China.

The forming of large rivers are the integral consequences of the deep earth process and the surface. In contrast to the hot topics for rivers related to orogenic domains, rift-related large rivers are largely ignored especially in deep time studies. The Cenozoic East Asia margin provides very good opportunity to observe this kind of rivers. It has been believed that basin-and-swell physiography dominated the East Asia margin and impeded the forming of large rives in the early Cenozoic. In this paper, we combined provenance analysis of East China Sea Basin, where is a crucial place to trace the river evolution in East Asia margin, and regional geologic constraints to reveal drainage reorganizations. Detrital zircon U-Pb ages from the Early Eocene sediments of the East China Sea Basin are firstly reported. Our results together with literature data demonstrate that regional provenance changes occurred at the middle Eocene from one singe age peak at ~110 Ma of proximal sources to multiple age spectrum derived from far inland. Source to sink analysis indicated that the North China Block and Korea Peninsular provided the most detritus. Sedimentation and tectonic features of rift basins in the potential source areas indicated that rivers flowed into Bohai Basin and Jianghan Basin cannot provide terrigenous clasts for the lower reaches in the Eocene. Contrastingly, the dominantly fluvial sediments across the Subei-South Yellow Sea Basin suggested external river system and a bypassing region since the middle Eocene, coinciding with provenance change in ECSB. All these demonstrated that a large river (East Asia River) established in east Asia margin in the middle Eocene and flowed southwestward approximately 1500km to the sea in southern ECSB. This river might last to the middle Miocene. The deep earth processes driven by Izanagi-Pacific ridge subduction resulted in the overfilled stage of Subei-South Yellow Sea Basin and the post-rift subsidence in west depression of ECSB, and thus facilitated the initiation of the EAR. Our finding shed new light on the evolving landscape in East Asia and showed how subduction of deep earth process controlled the initiation of rift-related large rivers.

Cycas (family Cycadaceae), spread throughout tropical and subtropical regions, is crucial in con-servation biology. Due to the subtle morphological variations between species, a solid spe-cies-level phylogeny for Cycas is lacking. Because of the rapid progress in high-throughput se-quencing technology, it has become feasible to acquire complete chloroplast (cp) genome se-quences, which provide a molecular foundation for phylogenetic research. In the present study, we employed next-generation sequencing technology to assemble and analyze the chloroplast genomes of six Cycas plants, including their genome structure, GC content, and nucleotide di-versity. The Cycas chloroplast genome spans 162,038 to 162,159 bp and contains 131 genes, in-cluding 86 protein-coding genes, 37 transfer RNA (tRNA) genes, and 8 ribosomal RNA (rRNA) genes. Through a comparative analysis, we found that the chloroplast genome of Cycas was highly conserved, as indicated by the contraction and expansion of the inverted repeat (IR) re-gions and sequence polymorphisms. In addition, several non-coding sites (psbK-psbI, petN-psbM, trnE-UUC-psbD, ndhC-trnM-CAU, and rpl32-trnP-GGG) showed significant varia-tion. The utilization of phylogenetic analysis relying on protein-coding genes has substantiated the division of Cycas primarily into four groups. The application of these findings will prove valuable in evaluating genetic diversity and the phylogenetic connections among closely related species. Moreover, it will provide essential support for the advancement of wild germplasm re-sources.

Neurogenesis in the adult brain plays a major role in the cognitive ability of animals including learning and memory. Poria cocos (Schw.) Wolf (P. cocos) has been known as a traditional Chinese edible medicinal herb with the potential effect to improve learning and memory. However, the effect mechanisms are still elusive. In this study, significant neuronal differentiation-promoting activities of the ethanol extracts of P. cocos (EEPC) were tested in Neuro-2a cells and mouse cortical neural stem/progenitor cells (NSPCs). Subsequently, 97 compounds of EEPC were identified using UHPLC-Q-Exactive-MS/MS. After investigation of neuronal differentiation-promoting activities of 4 major compounds (Ethyl palmitoleate, L-(-)-Arabitol, Choline and Adenosine), only Choline has significant neuronal differentiation-promoting activity. In summary, we investigated the neuronal differentiation-promoting activity and chemical compositions of EEPC, the study of the neuronal differentiation-promoting effect of ether extract of P. cocos indicated P. cocos’s positive effect on learning and memory functions. This is the first investigation of the neuronal differentiation-promoting effect of ether extract of P. cocos based on similar research references.

Introduction: The treatment of peritoneal dialysis in end-stage renal disease is increasing in clinical practice. The main purpose of this study was to evaluate the effect of far-infrared radiation therapy on inflammation and the cellular immunity of patients undergoing peritoneal dialysis. Materials and Methods: We recruited 56 patients undergoing peritoneal dialysis, and we included 32 patients from the experimental group and 24 patients from the control group in the final analysis. The experimental evaluation in our study was as follows: (1) We used abdominal computed tomography to measure the diameter and degree of hardening of the abdominal veins and large blood vessels to explore the changes in abdominal blood vessels. (2) The study compared the effects of peritoneal dialysis using albumin, blood urea nitrogen, creatinine, white blood cell, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, erythrocyte sedimentation rate, Hs-CRP clearance rate, and HBAlC. (3) We compared the cytokine concentration of blood between the two groups while controlling for GM-CSF, IL-2, IFN-γ, IL-6, IL-18, IL-4, IL-5, IL-13, IL-12p70, TNF-α, and IL-1β. Results and Discussion: (1) There was no significant difference in the abdominal blood vessels of the experimental group relative to the control group according to abdominal CT measured over 6 months. (2) Our study demonstrates the statistically significant effect of FIR therapy on the following parameters: albumin (p = 0.048*), creatinine (p = 0.039*), and Hs-CRP (p < 0.001**) decreased significantly, and glomerular filtration rate (eGFR, p = 0.043*) and glucose (p < 0.001**) increased significantly. Our study found that, in the experimental group, albumin and creatinine decreased significantly due to FIR therapy for 6 months. However, our study also found that, in the experimental group, glucose (p < 0.001**) increased significantly due to FIR therapy for 6 months. Peritoneal dialysis combined with FIR can reduce the side effects of glucose in dialysis buffer, which interferes with peritoneal inflammation and peritoneal mesothelial cell fibrosis. In addition, we also found that, in the experimental group, Hs-CRP (p < 0.001**) decreased significantly due to FIR therapy for 6 months. (3) No statistical significance in the inflammatory cytokines related to FIR therapy differences was observed in our study. IFN-γ (p = 0.124), IL-12p70 (p = 0.093), IL-18 (p = 0.213), and TNF-α (p = 0.254) did not exhibit significant improvements in peritoneal dialysis with FIR treatment over 6 months. IFN-γ and IL-18 in the plasma of patients in the experimental group and the control group were higher in the third month than in the first month. Conclusion: We found that the effect of peritoneal dialysis improved significantly with FIR therapy, and significant improvements in the peritoneal permeability and inflammatory response were observed. end-stage renal disease; peritoneal dialysis; far-infrared therapy (FIR)

Ferroptosis is an iron-dependent and lipid peroxidation-driven cell death cascade, occurring when there is an imbalance of redox homeostasis in the cell. Nuclear factor E2 related factor 2 (NFE2L2, also known as NRF2) is key for cellular antioxidant responses, which promotes downstream gene transcription by binding to their antioxidant response elements (AREs). Numerous studies suggest that NRF2 assumes an extremely important role in the regulation of ferroptosis, for its various functions on iron, lipid and amino acid metabolism and so on. Many pathological states are relevant to ferroptosis. In cancer cells, ferroptosis is frequently found abnormal suppression. While during tissue damages, ferroptosis is recurrently promoted, resulting in a large number of cell deaths and ultimately loss of the functions of the corresponding organs. Therefore, targeting NRF2-related signaling pathways, to induce or inhibit ferroptosis, has become a great potential therapy for combating cancers, as well as preventing neurodegenerative and ischemic diseases. In this review, a brief overview of the research process of ferroptosis over the past decade will be presented. In particular, the mechanisms of ferroptosis and a focus on the regulation of ferroptosis by NRF2 will be discussed. Finally, the review will briefly list some clinical applications of targeting the NRF2 signaling pathway in the treatment of diseases.

The booming wearable market and recent advances in material science has led to the rapid development of the various wearable sensors, actuators, and devices that can be worn, embedded in fabric or accessories, or tattoos directly onto the skin. Wearable actuators, a subcategory of wearable technology, have attracted enormous interest from researchers in various disciplines and many wearable actuators and devices have been developed in the past few decades to assist and improve people's everyday lives. In this paper, we review the actuation mechanisms, structures, applications, and limitations of recently developed wearable actuators including pneumatic and hydraulic actuators, shape memory alloys and polymers, thermal and hygroscopic materials, dielectric elastomers, ionic and conducting polymers, piezoelectric actuators, electromagnetic actuators, liquid crystal elastomers, etc. Examples of the recent applications such as wearable soft robots, haptic devices, and personal thermal regulation textiles are highlighted. Finally, we point out the current bottleneck and suggest the prospective future research directions for wearable actuators.

Bacterial wilt (BW), caused by Ralstonia solanacearum is one of the major biotic factors limiting tomato production in the humid tropics. Pyramiding of resistance genes through marker-assisted selection is an efficient way to develop durable BW resistant cultivars. Tomato line ‘Hawaii 7996’ (H7996) is a stable and robust resistance source against various R. solanacearum strains. Major BW resistance quantitative trait loci (QTLs) Bwr-12 and Bwr-6, and several minor or strain specific QTLs have been coarse-mapped in this line, but none has been fine-mapped and validated. The objective of the current study was to construct a high density genetic map using single-nucleotide polymorphism (SNP) markers derived from genotyping-by-sequencing, fine-map Bwr-12 and Bwr-6 and determine the effects of these QTLs using a near isogenic line (NIL) population. A high density genetic map using 1,604 SNP markers with an average distance of 0.82 cM was developed for 188 F9 recombinant inbred lines derived from the cross H7996 × WVa700. A total of seven QTLs associated with BW resistance to race 1-phylotype I or/and race 3-phylotype II strains were located on chromosomes 6 (Bwr-6.1, 6.2, 6.3 and 6.4) and 12 (Bwr-12.1, Bwr-12.2 and Bwr-12.3) with logarithm of odds (LOD) scores of 6.2-15.6 and 6.2-31.1, explaining 14.2-33.4% and 15.9-53.9% of the total phenotypic variation contributed from H7996, respectively. To validate the genetic effects of the two QTL regions, a set of 80 BC3F3 NILs containing different sections of Bwr-6 with or without Bwr-12 was phenotyped for disease severity after challenge with either race 1-phylotype I Pss4 or race 3-phylotype II Pss1632 BW strains over two seasons. Bwr-6.1 specific to Pss4 and Bwr-6.3 specific to Pss1632 were mapped to an interval of 5.0 cM (P < 0.05) between 6_33,444,000_SLM6-47 and 6_33,868,000_SLM6-124 SNP marker, and to 2.7 cM (P < 0.01) between positions 6_35,949,000 _SLM6-107 to 6_36,750,000_SLM6-82 marker, respectively. In addition, the specific effect of Bwr-12 for resistance to Pss4 (LOD score of 5.8-16.1, P < 0.01) was confirmed and markers for this QTL have already been made available previously.

Echinococcus granulosus is a harmful cestode parasite which could cause Cystic Echinococcosis in humans, various livestock species and wild animals. Calmodulin (CaM), a Ca²⁺ sensor protein, is widely expressed in eukaryotes and mediates a variety of cellular signaling activities. In our study, the CaM in Echinococcus granulosus (rEgCaM) was successfully cloned and the molecular and biochemical characterizations of rEgCaM were identified. The results showed that rEgCaM was a highly conserved calcium-binding protein, consisting of 149 amino acids. Immunoblot analysis revealed that rEgCaM could be identified using E. granulosus infected sheep serum. The usage of rEgCaM as antigen was evaluated by indirect ELISA which exhibited a high sensitivity of 90.3% but low specificity (47.1%). rEgCaM was mainly located in the tegument tissues and parenchymal region of protoscoleces, the tegument and inner body of adult worm and predominantly expressed in the germinal layer. The mRNA expression of rEgCaM in PSCs were gradually decreased with the increase death of PSCs. In electrophoretic mobility tests and ANS assays, rEgCaM showed a typical calcium-binding protein characteristics. This is the first report on CaM from E. granulosus and rEgCaM is considered to be involved in some important biological function of E. granulosus as a calcium-binding protein.

Background：Increasingly, epidemiological surveys and experimental research findings indicate the involvement of immune cells in the onset and progression of prostate cancer. However, it remains unclear whether the relationship between specific immune cell types and prostate cancer is causal or influenced by bias. Through a two-sample Mendelian randomization design, our study aims to uncover the association between different immune cells and the risk of prostate cancer.Methods：A comprehensive study was conducted to investigate the association between immunophenotypes and prostate cancer risk. The study included a total of 731 immunophenotypes as potential exposure factors and analyzed data from 182,625 individuals of European ancestry from the UK Biobank. A screening of 12,097,504 single nucleotide polymorphisms (SNPs) was performed. The main analysis utilized the two-sample Mendelian randomization method with inverse variance weighting (IVW). Additionally, multiple analysis methods were combined, and various tests were conducted to assess heterogeneity and pleiotropy.Results：The resulting study showed a causal relationship between a total of 34 immune phenotypes and prostate cancer. Among them, the four immune phenotypes of CD62L- DC AC, CD19 on sw mem, FSC-A on plasmacytoid DC and HLA DR on monocyte simultaneously meet three or more statistical methods, suggesting a significant causal relationship with prostate cancer. Additionally, among the 34 immunophenotypes, CD28-CD8dim AC was shown to be positive in reverse Mendelian randomization. Most of these cell phenotypes have been reported to be potentially associated with prostate cancer.Conclusions：Our study demonstrates a causal link between immune cells and prostate cancer risk. Filled in the possible roles of all current immune cell pathways in the development and progression of prostate cancer. The next step is to verify the content and influencing mechanism of these immune phenotypes in cancer cells and adjacent cells through experiments, so as to provide new ideas and methods for the prevention and treatment of prostate cancer.

Regenerative braking energy (RBE) recovery of trains can improve energy efficiency as well as reduce the overall greenhouse gases emissions of electric rail systems. The train's speed limit, track elevation, track curvature, and headway time can affect the amount of RBE recovered. This study aims to investigate the impacts of these parameters on the RBE recovery for a DC third rail system. A DC third rail system has been modeled using the ETAP-eTraX software based on the Malaysia Mass Rapid Transit Line 2 (MRT Line 2) traction power system. The effects of the change of speed limit, track elevation, track curvature, and headway time of the trains on the RBE recovery have been evaluated under various scenarios. The results showed that the track’s elevation has the most significant influence on the overall energy consumptions of the train while the speed limit has the most significant influence on the amount of RBE recovery.