The recurrent coronavirus outbreaks in China (SARS-CoV and its relative, SARS-CoV-2) have raised speculations that perhaps Asians are somehow more susceptible to these coronaviruses. Here, we test this possibility based on an analysis of the lung-specific expression of ACE2, which encodes the known cell-entry receptor of both SARS-CoV and SARS-CoV-2. We show that ACE2 expression is not affected during tumorigenesis, supporting that the abundant transcriptomes in cancer genomic studies can be informatively used to study ACE2 expression among diverse individuals without cancer. We find that ACE2 expression in the lung increases with age, but is not associated with sex. Further, Asians do not differ from other populations for ACE2 expression and do not harbor unique genetic polymorphisms in the ACE2 locus. Thus, beyond illustrating an innovative method for assessing the potential impacts of demographic factors for non-cancer diseases from large-scale cancer sample datasets, our statistically robust findings emphasize that individuals of all races require the same level of personal protection against SARS-CoV-2.

Tulou dwellings in Southeast China have captivated global interest due to their distinctive appearance, sustainable construction materials and technologies, and their defensive and collective housing functions. Despite several recognized as World Cultural Heritage sites, the vast majority of tulou buildings are undergoing irreversible decline and destruction, necessitating a comprehensive and systematic study. Taking 83 Tulou buildings in Raoping County, Chaozhou City, Guangdong Province as the research object, this study reconstructs the historical scenes and systematically reveals the emergence, popularity, and consolidation process of tulou dwellings as integrated defensive and residential buildings for ordinary people by conducting a comprehensive analysis of historical documents and local chronicles. Based on an extensive field investigation, the study systematically analyzes the geospatial distribution and the spatial characteristics of Raoping tulou and its residential unit. The results demonstrate the adaptability and flexibility of tulou dwellings, showcasing their developmental process and revealing the inclusive nature of these traditional residences, as well as the initiative of those who reside within them. The research findings contribute to a more dynamic, comprehensive, and authentic understanding of tulou and Chinese traditional residences, providing valuable references for the preservation and sustainable development of tulou architectural heritage.

Abiogenic hydrocarbons are fundamentally important for understanding the deep microbial communities and the origin of life. The generation of abiogenic hydrocarbons was proposed to be limited to ultramafic-hosted hydrothermal systems, fueled by the serpentinization product H₂. Here, we present the discharge of short-chain alkanes from an andesitic rock-hosted Lutao geothermal field in the north Luzon arc, carrying abiotic chemical and isotopic signals. These abiogenic hydrocarbons were generated from CO₂-H₂O-rich fluid inclusions, where the long-term storage since Lutao volcanism (~ 1.3 Ma) allowed overcoming the sluggish kinetics of CO₂ to CH₄ reduction at temperatures of 174 - 206 ^oC. Natural abiogenic production of hydrocarbons, therefore, can be more ubiquitous than previously thought. The hypothesis regarding the origin of methane in Earth’s early atmosphere and its implication to the origin of life may require reconsideration.

We give a simple proof of the Chen inequality for the Chen invariant $\underbrace{\delta (2,...,2)}_{k\mbox{ terms}}$ of submanifolds in Riemannian space forms.

Due to the high effectiveness of cancer screening and therapies, the diagnosis of second primary cancers (SPCs) has increased in women with endometrial cancer (EC). However, there’s no previous literature mentioned about adequate evidence to support screening for SPCs in endometrial cancer. This study was aimed to develop effective risk prediction models of second primary endometrial cancer in women with obesity (Body-mass index; BMI > 25) and this study includes datasets of the incidence of SPCs and the other risks of SPCs in 4480 primary cancer survivors by a hospital-based cancer registry database. In our study, we found the obesity played a key role in SPCs. There’re 10 independent variables used as predicting variables, which corelated to obesity should be monitored for the early detection of SPCs in endometrial cancer. In conclusion, it is a promising SPCs prediction. The proposed scheme can support the important influence of obesity and clinical data representations in all cases after primary treatments. Our results suggested that obesity is still a crucial risk factor to SPCs in endometrial cancer.

We propose a chemical language processing model to predict polymers’ glass transition temperature (Tg) through a polymer language (SMILES, Simplified Molecular Input Line Entry System) embedding and recurrent neural network. This model only receives the SMILES strings of polymer’s repeat units as inputs and considers the SMILES strings as sequential data at the character level. Using this method, there is no need to calculate any additional molecular descriptors or fingerprints of polymers, and thereby, being very computationally efficient and simple. More importantly, it avoids the difficulties to generate molecular descriptors for repeat units containing polymerization point `*’. Results show that the trained model demonstrates reasonable prediction accuracy on unseen polymer’s Tg. Besides, this model is further applied for high-throughput screening on an unlabeled polymer database to identify high-temperature polymers that are desired for applications in extreme environments. Our work demonstrates that the SMILES strings of polymer’s repeat units can be used as an effective feature representation to develop a chemical language processing model for predictions of Tg. The framework of this model is general and can be used to construct structure-property relationships for other polymer’s properties.

Blind image quality assessment (BIQA) aims to evaluate image quality in a way that closely matches human perception. To achieve this goal, the strengths of deep learning and the characteristics of human visual system (HVS) can be combined. In this paper, inspired by the ventral pathway and dorsal pathway of HVS, a dual-pathway convolutional neural network is proposed for BIQA task. The proposed method consists of two pathways: “what” pathway, which mimics the ventral pathway of HVS to extract the content features of distorted images, and the “where” pathway, which mimics the dorsal pathway of HVS to extract the global shape features of distorted images. Then, the features from the two pathways are fused and mapped to an image quality score. Additionally, the gradient images weighted by the contrast sensitivity are used as the input to the “where” pathway, allowing it to extract global shape features that are more sensitive to human perception. Moreover, a dual-pathway multi-scale feature fusion module is designed to fuse the multi-scale features of the two pathways, enabling the model to capture both global features and local details, thus improving the overall performance of the model. The experiments conducted on six databases show that the proposed method achieves the state-of-the-art performance.

Based on the 2013–2017 Chinese Family Database and China Household Finance Survey, the study examines the impact of farmland transfer on the income structure of agricultural households. We observe a significant rise in the income of transferred-out households, while that of transferred-in households is unchanged. A further empirical decomposition of income shows a significant increase in both the wage and asset generated incomes of transferred-out households. Although the income generated by transferred-in households through agricultural production and management increases significantly, the decrease in wage income is larger. The study’s empirical designs are robustly tested with propensity score matching and instrumental variables. Moreover, we conduct a comparative analysis of the external constraints faced by the two groups to explore the reasons for the divergence of the income effect. The results show that transferred-in households face highly pronounced external constraints in terms of capital, technology, and farmland size, while transferred-out households face relatively fewer impediments to non-agricultural employment. Our empirical results imply that external constraints can limit the social welfare improvements of agricultural land reform, suggesting that other complementary measures would be required for future policy improvements to work better.

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<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<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<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.

The Chen circuit system, a three-dimensional autonomous system with intriguing dynamics, has gained considerable attention due to its potential applications in diverse scientific fields. In this article, a Chen circuit-like system is defined and a comprehensive dynamics has been studied. The system exhibits chaotic dynamics, limit cycles, and bifurcations, making it a captivating subject of study. By employing numerical simulations and analytical techniques, we explore the system's stability and identify critical parameter values leading to qualitative changes. Notably, we delve Hopf bifurcations, which give rise to stability changes and the emergence of limit cycles. Furthermore, we analyze the fractal dimension of the system's attractor, providing insights into its complexity and self-similarity. Through a systematic examination of the Chen circuit-like system, we deepen our understanding of its intricate dynamics and offer valuable insights into the underlying mechanisms. The findings contribute to the field of dynamical systems and hold potential implications in areas such as chaos-based secure communications, signal processing, and nonlinear control. This work serves as a valuable reference for researchers and practitioners interested in the dynamics and bifurcation analysis of nonlinear systems.

Mapping or quantitative inversion through remote sensing technology is an active way for mineral monitoring in large or uncultivated forest areas. Different spectral features of minerals, induced by ionic composition, can be identified which are related to mineral type or abundance. Based on the distinctive spectral absorption around 2.33µm induced by the carbonate ion, we use it as an analytic target to propose an improved continuum removal (ICR) algorithm to couple with normalized abundance to evaluate the relationship between continuum removal band depth (CRBD) and carbonate ion abundance. Through experimentally testing with synthetic and real image data, ICR with ratio abundance normalization can enhance the linear relation of CRBD and abundance. We find this technique performs best for abundance retrieval. The lowest root mean square error is 0.0400 for synthetic data and the mean relative error is as low as 6.80% for real image data. Compared with five other algorithms, coupling normalized carbonate mineral abundance with ICR can improve the quantitative retrieval accuracy of carbonate ion. By using a hyperspectral library, we also present a way to retrieve abundance without ground samples. These results make the quantitative inversion of mineral abundance more reasonable by distinct or enhanced features and provide great potential for use to extend mineral information extraction in the absence of sample data, even for surveys of the Moon and Mars for mineral quantitative analysis.

(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.

Two austenitic stainless steel (ASS) plates, 304L and 316L, were cold-rolled (304R and 316R) with a 10 % reduction in thickness then subjected to laser welding. Cold-rolling caused a slight surface hardening and introduced residual tensile stress into the ASS plates. The susceptibility to stress corrosion cracking (SCC) of the welds (304RW and 316RW) was determined using the U-bend test pieces in a salt spray. To highlight the stress concentration at the weld’s fusion boundary (FB), the top weld reinforcement was not ground off before bending. Moreover, micro-shot peening (MSP) was performed to mitigate the SCC of the welds by imposing high residual compressive stress and forming a fine-grained structure. Cold-rolling increased the susceptibility of the 304R specimen to pitting corrosion (PTC) and intergranular (IG) microcracking. Moreover, PTC and SCC were found more often at the FBs of the 304RW. The corrosion pits of the peened 304RW (304RWSP) were finer but greater in amount than the un-peened one. The results also indicated that the 316L ASS welds with MSP was resistant to the incidence of PTC and SCC in a salt spray. The better reliability and longer service life of dry storage canister could be achieved by using 316L ASS for construction and application of MSP on it.

The organic coating of bridge steel girders is subjected to physical scratches, corrosion, and aging in natural weathering. The breakdown of the coating may cause serviceability and safety problems if left unnoticed. A hyperspectral imaging method is proposed to detect the condition of steel coatings based on coating-responsive features in reflectance spectra. A field test was conducted on the real-world bridge which shows obvious signs of degradation. The hyperspectral signature enables an assessment of the coating health and defect severity. The results indicated that the coating scratch can be effectively located in the domain of a hyperspectral image and the scratch depth can be determined by mapping a scratch depth indicator (SDI=R532nm / R641nm). Rust sources and products in steel girders can be identified by the unique spectral signatures and the rust stains (and thus stain areas) scattered on the coating can be pinpointed at pixel level by the corrosion rust indicators. The chemical integrity of a topcoat is demonstrated by the short-wave infrared spectroscopy and the topcoat degradation can be evaluated by the absorption at 8000 cm-1 and 5850 cm-1.

When the image quality is evaluated, the human visual system (HVS) infers the details in the image through its internal generative mechanism. In this process, the HVS integrates both local and global information of the image, utilizes contextual information to restore the original image information, and compares it with the distorted image information for image quality evaluation. Inspired by this mechanism, a no-reference image quality assessment method is proposed based on a multitask image restoration network. The multitask image restoration network generates a pseudo-reference image as the main task and produces structural similarity index measure map as an auxiliary task. By mutually promoting the two tasks, a higher quality pseudo-reference image is generated. In addition, when predicting the image quality score, both the quality restoration features and the difference features between the distorted and reference images are used, thereby fully utilizing the information from the pseudo-reference image. To enable the model to focus on both global and local features, a multi-scale feature fusion module is proposed. Experimental results demonstrate that the proposed method achieves excellent performance on both synthetically and authentically distorted databases.

With the significant annual increase in the market demand for biopesticides, the industrial production demand for predatory mites, which hold the largest market share among biopesticides, has also been rising.To achieve efficient and low energy consumption control of predatory mite breeding environmental parameters, accurate estimation of breeding environmental parameters is necessary. This paper collects and pre-processing hourly time-series data of temperature and humidity from industrial breeding environments. Time series prediction models such as SVR, LSTM, GRU, and LSTNet are applied to model and predict historical data of the breeding environment. Experiments validate that the LSTNet model is more suitable for such environmental modeling. To further improve prediction accuracy, the training data for the LSTNet model is enhanced using hierarchical clustering of time-series features. After augmentation, the root mean square error (RMSE) of temperature prediction decreased by 27.3%, and the RMSE of humidity prediction decreased by 32.8%, significantly improving the accuracy of multi-step predictions and providing substantial industrial application value.

3CL^pro is the main protease of the novel coronavirus (SARS-CoV-2) responsible for their intracellular duplication. Based on virtual screening technology, we found 23 approved clinical drugs such as Carfilzomib, Saquinavir, Thymopentin and etc., which showed high affinity with the 3CL^pro active sites. These findings suggest that 3CL^pro inhibitors might be potential candidates for further activity detection and molecular modification.

A series of penta-1,4-dien-3-one containing a H-phosphonate scaffold were designed and synthesized. The structures of all title compounds were determined by 1H-NMR, 13C-NMR, 31P-NMR, and HRMS. Bioassay results showed that several of the title compounds exhibited remarkable antibacterial and antiviral activities. Among these, compounds 3c and 3o exhibited substantial antibacterial activities against Xanthomonas oryzae pv. Oryzae (Xoo) and Xanthomonas axonopodis pv. citri (Xac). In addition, compounds 3c, 3f, and 3r showed remarkable curative activities against tobacco mosaic virus (TMV), with 50% effective concentration (EC50) values of 290.0, 234.0, and 373.6 μg/mL, respectively. These were superior to that of ningnanmycin (386.2 μg/mL). Compound 3r exhibited comparative protective activity against TMV, with an EC50 value of 291.1 μg/mL, which was better than that of ningnanmycin (297.1 μg/mL). Notably, the solubility of all title compounds improved relative to the lead compound curcumin. These results suggest that penta-1,4-dien-3-one containing a H-phosphonate scaffold may be considered as an activator for antibacterial and antiviral agents.

The papaya mealybug Paracoccus marginatus is an invasive, polyphagous pest and poses a quarantine threat to tropical and subtropical countries. Infested commodity internationally should be undergoing phytosanitary treatment, while irradiation is recommended to replace methyl bromide fumigation. Dose-response tests were conducted on the 2-, 4-, and 6-d-old eggs and gravid females of P. marginatus using the X-ray radiation doses of 15–105 Gy with an interval of 15 Gy, respectively. Radiotolerance was compared using fiducial overlapping and lethal dose ratio (LDR) test, resulting in insignificant difference except for LDR test at LD90 (leading 90% mortality at 95% confidence level (CL)); the estimated dose for 99.9968% mortality at 95% CL was 176.5–185.2 Gy, which was validated in the confirmatory tests using gamma irradiation because gammy and X-rays have equal biological effect on pests. Therefore, a total of estimating 60,386 gravid females of papaya mealybug irradiated with 146.8–185.0 Gy resulted in no F1 nymphs developing. Eggs can therefore be used as an alternative to gravid females for dose-response tests; the recommended minimum dose for phytosanitary treatment of P. marginatus on infested commodity is 185 Gy, with treatment efficacy ≥ 99.9950% at 95% CL.

Federated learning trains a neural network model using the client's data to maintain the benefits of centralized model training, while maintaining the privacy. However, if the client data are not independently and identically distributed (non-IID) because of different environments, the accuracy of the model may suffer from client drift during training owing to discrepancies in each client's data. This study proposes a personalized federated learning algorithm based on the concept of multitask learning to divide each client model into two layers: a feature extraction layer and a category prediction layer. The feature extraction layer maps the input data to a low-dimensional feature vector space. Furthermore, the parameters of the neural network are aggregated with those of other clients using an adaptive method. The category prediction layer maps low-dimensional feature vectors to the label sample space, with its parameters remaining unaffected by other clients to maintain client uniqueness. The proposed personalized federated learning method produces faster learning model convergence rates and higher accuracy rates for the non-IID datasets in our experiments.

Viral infections have long been the biggest threat to human survival, and from a medical perspective, the development of noninvasive high-throughput screening methods that target the incubation period to either treat diseases or limit viral spread would be strikingly effective. Using this technology to target viral incubation periods would also be inexpensive to perform. The current study proposes to transform pulse signals into a rapid diagnostic test using “coincidence analysis” in the hope of preventing or reducing the symptoms of viral infections. The heart plays a critical role in calculating and supplying the needs of all tissues of the body. Pulse waves are pressurized signals in response to heart’s calculations and include all phases of the cardiac cycle, which maintains life and provides energy needed to perform tasks. Any small movement gives a corresponding signal to pulse waves. The current study investigated conclusive data on self-limiting infections, such as common cold. We used pulse wave, coincidence analysis technology to capture signals from individuals with common cold during the incubation period and investigated if particular characteristic signals could be applied to influenza during the incubation period. Preliminary work demonstrated that pulse waves could generate signals using this technology that would be worthwhile for future research. A small amount of analytical data from common cold existed previously. The data structure is based on the idea that a single pulse wave at differing physiological conditions would have slight modifications that would be amplified and presented by various geometrical shapes after extensive data are accumulated. These geometric shapes can then be sliced vertically or horizontally to extract data during different illness stages. The significance of these findings are impressive; from a personal or a public hygiene perspective, this analytical technology provides many benefits, such as rapid and precise decision-making that can be directly visualized or can be analyzed using software programs. Also, this technology also uses futuristic wearable technology that brings practical problem solving to physiology.

In order to assess the range of impact of thermal wastewater discharge from the third Nuclear Power Plant (NP_No.3) on the local ecosystem, a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings is employed to study the present work. Tides and daily wind forcings are incorporated into the MITgcm model to examine their effects on the thermal plume and the water circulation in Nan Wan Bay. The model results reveal that the thermal plume is most likely to disperse to the southwest in summer; it is unlikely to drift to the southeast or northeast because of the presence of gentle southwesterly monsoon. In winter, the thermal plume is most likely to be directed to the southwest but barely visible in the northeast or southeast directions because of prevailing northeasterly monsoon. Additionally, it is worth emphasizing that strong tidal currents generate a pair of counter-rotating eddies that significantly dominate the dispersal of the thermal plume. However, seasonal monsoons also play an essential role in modifying the plume’s direction and dispersion. The model results reveal that the flow field and thermal plume agree well with observational data.

The images captured by UAVs during inspection often contain numerous small targets related to transmission lines, which are critical and vulnerable elements for ensuring the safe operation of these lines. However, due to various factors such as the small size of the targets, low resolution, complex background, and potential line aggregation, achieving accurate and real-time detection becomes challenging. To address these issues, this paper proposes a detection algorithm called P2-ECA-EIOU-YOLOv5 (P2E-YOLOv5). Firstly, in order to address the challenges posed by the complex background and environmental interference that impact small targets, an ECA attention module is integrated into the network. This module effectively enhances the network's focus on small targets while concurrently mitigating the influence of environmental interference. Secondly, considering the characteristics of small target size and low resolution, a new high-resolution detection head is introduced, which is more sensitive to small targets. Lastly, the network utilizes the EIOU-Loss as the regression Loss function to improve the positioning accuracy of small targets, as they tend to aggregate. Experimental results demonstrate that the proposed P2E-YOLOv5 detection algorithm achieves an accuracy P of 96.0% and an average accuracy (mAP) of 97.0% for small target detection in transmission lines.

In northern Canada where permafrost is prevalent, a shortage of accessible, affordable, and high-quality housing has been ongoing for decades. Design of foundations in permafrost presents unique engineering challenges due to permafrost soil mechanics and climate change. There is no specific design code for pile or shallow foundations in northern Canada. Consequently, the design process heavily relies on the expertise and experience of Arctic geotechnical engineers who have specialized knowledge in this field. Therefore, a comprehensive review of the practice or literature in foundation design in the Arctic would be necessary. The main objective of this review paper is to provide an overview of the common foundations in permafrost and the techniques adopted to counteract the effects of frozen soils. This study conducted a literature review of state-of-the-art practices on deep and shallow foundations used in northern Canada, including common steel pipe piles and thermosyphons. The review summarized the current principles, including adfreeze strength, creep settlement, and frost heave, used in the foundation design in permafrost. Then this paper summarized the findings from interviewing several engineers or professionals who have experiences in the design of foundations in permafrost. The interviews revealed the technical and non-technical aspects of foundation design practice in northern Canada. Lastly, in order to demonstrate the design methods, the paper presented two examples where screw piles and steel pipe piles were designed to support a residential building in northern Canada, according to the state-of-practice criteria for adfreeze strength, long term settlement and frost heave.

Alzheimer's disease (AD) is a multifaceted neurodegenerative disorder characterized by cognitive decline and neuronal loss, representing a most challenging health issue. We present a computational analysis of transcriptomic data of AD tissues vs. healthy controls, focused on elucidation of functional roles played by long non-coding RNAs (lncRNAs) throughout the AD progression. We first assembled our own lncRNA transcripts from the raw RNA-Seq data generated from 527 samples of dorsolateral prefrontal cortex, resulting in the identification of 31,574 novel lncRNA genes. Based on co-expression analyses between mRNAs and lncRNAs, a co-expression network is constructed. Maximal subnetworks with dense connections are identified as functional clusters. Pathway enrichment analyses are conducted over mRNAs and lncRNAs in each cluster, which serve as the basis for the inference of functional roles played by lncRNAs involved in each of the key steps in an AD development model that we have previously build based on transcriptomic data of protein-encoding genes. Detailed information is presented about the functional roles by lncRNAs in activities related to stress response, reprogrammed metabolism, cell-polarity, and development. Our analyses have also revealed that lncRNAs have discerning power in distinguishing between AD samples of each stage and healthy controls. This study represents the first of its kind.

Azo dyes are the most widely used synthetic dyes in the printing and dyeing process. However, the discharge of untreated azo dyes poses potential threat for human health and aqueous ecosystem. Herein, we fabricated a novel heterogenous catalyst - activated carbon fiber-supported ferric alginate (FeAlg-ACF) . Together with peroxymonosulfate (PMS) and visible light, this photocatalytic oxidation system was used to remove an azo dye - azophloxine. The results indicated that the proposed catalytic oxidation system can remove 100% azophloxine within 24 min, while under the same system, the removal rate was only 92 % and 84 % when ferric alginate was replaced with ferric citrate and ferric oxalate respectively, which showed the superiority of activated carbon fiber-supported ferric alginate. The degradation of azophloxine is achieved by the active radicals (SO4•− and •OH) released from PMS and persistent free radicals from activated carbon fiber. After treating for 24 min, the total organic carbon of azophloxine solution (50 μmol/L) decreased from 1.82 mg/L to 79.3 μg/L and the nitrate concentration of ions increased from 0.3 mg/L to 8.6 mg/L. That is, up to 93.5% azophloxine molecules were completely degraded into inorganic compounds. Consequently, potential secondary contamination by intermediate organic products during catalytic degradation was prohibited. The azophloxine removal ratio was kept almost constant after seven cycles, indicating the recyclability and longevity of this system. Furthermore, the azophloxine removal was still promising at high concentrations of Cl-, HCO3-, CO32-. Therefore, our proposed system is potentially effective to remove dye pollutants from seawater. It provides a feasible method for the development of efficient and environmental friendly PMS activation technology combined with FeAlg-ACF, has significant academic and application value.

Background: While intimate feminine hygiene products are widely used by women as part of daily cleansing routines, little is known about how these products impact the vulvovaginal area and its microbiome stability. A novel gel wash containing lactic acid (pH 4.2) for external daily use was formulated to provide gentle cleansing, freshness, and antimicrobial protection to maintain a healthy balance of the vulvar skin area. This 4-week clinical study assessed tolerance of the gel wash when used on the external genital area and its effects on skin hydration, vulvar skin pH, and the vulvar microbiome. After a 7-day pre-study conditioning period, 36 healthy females in 3 balanced age groups (18-29, 30-44, and 45-55 years) used the gel wash to cleanse their external genital area (mons pubis and vulva) and entire body at least once per day for 28 days. The primary endpoint wasSkin tolerance of the gel wash was assessed by the gynecologist. Effects of the gel wash on vulvar skin microbiota were studied by performing bacterial 16S rRNA and fungal ITS microbial richness and diversity analysis. Results: Based on gynecologic assessment after 28 days of use, the gel wash showed acceptable tolerance, with no signs of increased dryness, redness, edema, itching, stinging, or burning. Use of the gel wash was associated with a significant increase in both short-term (single application) and longer-term (daily use for 28 days) skin moisturization. There was no significant change in vulvar skin pH over time with daily product use, and the gel wash did not significantly affect the natural vulvar microbiome species richness or diversity for bacteria or fungi. Conclusions: Results of the study showed that this new gel wash is a mild, moisturizing cleanser that does not harm and instead maintains the natural pH and microbial diversity of vulvar skin. To our knowledge, this was the first study to assess the effect of an antimicrobial feminine gel wash on the natural pH and vulvar microbiome habitat of the skin using bacterial 16S rRNA and fungal ITS genetic sequencing techniques, thereby providing a better understanding of the bacterial and fungal communities that inhabit the external vulvar area in healthy women.

Aim: Aging is companied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging on different phases of insulin secretion (ISEC); i.e., the first- and second-phase of insulin secretion (FPIS, SPIS) and glucose effectiveness (GE). Methods: Totally 169 individuals (43 men and 126 women) with the similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18- to 78-year-old. Men had higher FPIS but lower HDL-C levels than women (2.067±0.159, 1.950±0.186 μU/min and 1.130±0.306, 1.348±0.357 mmol/dl, accordingly). The results of Pearson correlation revealed that age was negatively related to IR and GE in both genders (IR: r = -0.39, p < 0.001 for men, r = -0.24, p < 0.003 for women; GE: r = 0.66, p < 0.001 for men, r = 0.78, p < 0.001 for women). In the meanwhile, FPIS was also only found to be negatively correlated with age in female (r = -0.238, p = 0.003). But there was no different with SPIS and age in both of genders. Conclusions: We have found that in Chinese with normal FPG level (90 mg/dl) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to IR and GE in both genders. At the same time, only FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest are, GE, FPIS and IR accordingly. The importance of GE should be re-evaluated. These results should be interpreted with caution because of the small sample size.

Gastrodia elata Bl., one of the well-known edible plants in China, belongs to the family of Orchidaceae. In recent years, the consumption rate of this plant as food supplements or health products is gradually rising in China. However, the traditional industrialization processing procedures (TP) for this plant was found to be too complicated and not friendly to the environment with time and energy consuming. Hence, we investigated whether the processing procedures could be simplified without affecting its overall chemical profile and anti-oxidation activity. In this experiment, a new processing procedure (NP) was designed for processing this plant, and the chemical compositions of the extract for Gastrodia elata produced by two different processing procedures were identified by UPLC-Q-TOF/MS. It was found that phenols and parisins were the most abundant chemical components for this extract. Among all the identified components, the contents of gastrodin and its citric acid derivatives were obviously higher than that of other components. Therefore, the contents of six gastrodin derivatives and ethanol soluble extract rate for Gastrodia elata produced by two different processing procedures, traditional and newly designed processing procedures, were further comparatively investigated for the validation of the applicability. The DPPH radical scavenging activities of the extract from Gastrodia elata produced by two different processing procedures were also investigated. The results demonstrated that the contents of gastrodin and p-hydroxybenzyl alcohol in all samples were slightly decreased in NP samples compared with that of TP samples (except batches of S3 and S6 samples), but no significant difference was observed between these two groups (p = 0.8273 for gastrodin and p= 0.2320 for p-hydroxybenzyl alcohol). Additionally, the total contents of parisins were also in a decreased trend in NP samples but with no significant difference when comparing with that in TP samples (p = 0.1721). The results for ethanol soluble extract rate also had the same situation (p = 0.1094). Taken together, it was suggested that the chemical profiles and contents of gastrodin derivatives and ethanol soluble extract rate for NP samples was not significant different to that of TP samples. The DPPH radical scavenging activity of the extract of Gastrodia elata produced with NP method was not significant different from that of TP samples. As a result, the industrial processing procedures for the preservation of this material plant could be simplified to a more time and energy saving procedure without changing the quality of the products, which is also consistent with the concept of green and sustainable industrial production.

Rapid analysis and characterization of compounds by mass spectrometry may overlook trace compounds, although targeted analysis methods can significantly improve detection sensitivity, it is difficult to discover novel scaffold compounds. This study developed a strategy for discovering trace compounds in the aging process of traditional Chinese medicine based on MS fragmentation and known metabolic pathway. Specifically, we found that the characteristic component of C. reticulata 'Chachi', methyl N-methylanthranilate (MMA), fragmented in ESI-CID to produce rearrangement ion 3-hydroxyindole, which has been proven to exist in trace amounts in C. reticulata 'Chachi' comparing with the reference substance by LC-MS/MS. By combining the known metabolic pathways of 3-hydroxyindole and the possible methylation reactions that may occur during aging, 10 possible indole derivatives were untargeted predicted. These compounds were confirmed to originate from MMA by purchasing or synthesizing reference substances and all of them were detected in C. reticulata 'Chachi' through LC-MS/MS analysis, achieving trace compound analysis from untargeted to targeted. It may contribute to explain the aging mechanism of C. reticulata 'Chachi' and the strategy of CID-induced special rearrangement ion binding metabolic pathway has potential application value in discovering trace compounds.

The traditional Chinese drug Bombyx Batryticatus mori.L (BBm) which is also named the white stiff silkworm has been widely used in Chinese clinics for thousands of years. It is famous for its antispasmodic and blood circulation promoting effects. Cardiomyocyte hypertrophy, interstitial cell hyperplasia and myocardial fibrosis are closely related to the N-glycosylation of key proteins. To examine the alterations of N-glycosylation that occur in diabetic myocardium during the early stage of the disease and clarify the therapeutic effect of 1-DNJ extracted from BBm, we used the db/db mouse model and an approach based on hydrophilic chromatography solid-phase extraction integrated with an LC-MS/MS identification strategy to perform a site-specific N-glycosylation analysis of left ventricular cardiomyocyte proteins. AGEs, hydroxyproline, CTGF and other serum biochemical indicators were measured with ELISA. In addition, the α1,6-fucosylation of N-glycans was profiled with LCA lectin blots and FITC-labelled lectin affinity histochemistry. The results indicated that 1-DNJ administration obviously downregulated myocardium protein N-glycosylation in db/db mice. The expression levels of serum indicators and fibrosis-related cytokines were reduced significantly by 1-DNJ in a dose-dependent manner. The glycan α1,6-fucosylation level of the db/db mouse myocardium was elevated, and the intervention effect of 1-DNJ administration on N-glycan α1,6-fucosylation was significant. To verify this result, the well-known TGF-β/smad2/3 pathway was selected, and core α1,6-fucosylated TGFR-βⅡ was analysed semi-quantitatively with western blotting. The result supported the conclusions obtained from LCA lectin affinity histochemistry and lectin blot analysis. The expression level of FUT8 mRNA was also detected, and the results showed that 1-DNJ administration did not cause obvious inhibitory effects on FUT8 expression. Therefore, the mechanism of 1-DNJ to relieve the DCM-associated fibrosis can be concluded as the inhibition of N-GlcNAc formation and the reduction of substrate concentration.

Drought stress is a major abiotic factor affecting tomato production and fruit quality. However, the genes and metabolites associated with tomato responses to water deficiency and rehydration are poorly characterized. To identify the functional genes and key metabolic pathways underlying tomato responses to drought stress and recovery, drought-susceptible and drought-tolerant inbred lines underwent transcriptomic and metabolomic analyses. A total of 332 drought-responsive and 491 rehydration-responsive core genes were robustly differentially expressed in both genotypes. The drought-responsive and rehydration-responsive genes were mainly related to photosynthesis–antenna proteins, nitrogen metabolism, plant–pathogen interactions, and the MAPK signaling pathway. Various transcription factors, including homeobox-leucine zipper protein ATHB-12, NAC transcription factor 29, and heat stress transcription factor A-6b-like, may be vital for tomato responses to the water status. Moreover, 24,30-dihydroxy-12(13)-enolupinol, caffeoyl hawthorn acid, adenosine 5′-monophosphate, and guanosine were the key metabolites identified in both genotypes under drought and recovery conditions. The combined transcriptomic and metabolomic analysis highlighted the importance of 38 genes involved in metabolic pathways, biosynthesis of secondary metabolites, biosynthesis of amino acids, and ABC transporters for tomato responses to water stress. Our results provide valuable clues regarding the molecular basis of drought tolerance and rehydration. The data presented herein may be relevant for genetically improving tomato to enhance drought tolerance.

Image encryption is increasingly becoming an important area of research in information security and network communications, as digital images are widely used in various applications and are vulnerable to various types of attacks. In this research work, a color image cryptosystem that is based on a 3-layer permutation-substitution network (PSN) is proposed. For every layer, an encryption key and an S-box are generated and utilized. Those are based on a four-dimensional (4D) dynamical Chen system of a fractional-order, the Mersenne Twister, OpenSLL, Rule 30 Cellular Automata and Intel’s MKL. The sequential application of Shannon’s ideas of diffusion and confusion for 3 times guarantees a total distortion of any input plain image, resulting in a totally encrypted one. Apart from the excellent and comparable performance to counterpart algorithms from the literature, showcasing resistance to visual, statistical, entropy, differential, known plaintext and brute-force attacks, the proposed image cryptosystem provides an exceptionally superior performance in 2 aspects: a vast key space of 2^1658 and an average encryption rate of 3.34 Mbps. Furthermore, the proposed image cryptosystem is shown to successfully pass all the tests of the NIST SP 800 suite.

Cancer immunotherapy targeting immune checkpoints has exhibited promising clinical outcomes in many cancers, but it offers only limited benefits for pancreatic cancer (PC). Cancer stem cells (CSCs), a minor subpopulation of cancer cells, play important roles in tumor initiation, progression, and drug resistance. Accumulating evidence suggests that CSCs employ immunosuppressive effect to evade the immune recognition. However, clinical implications of the associations among CD8+ T cells infiltration, programmed death receptor ligand-1 (PD-L1) expression, and CSCs existence are poorly understood in PC. Immunostaining and quantitative analysis were performed to assess CD8+ T cells infiltration, PD-L1 expression, and their relationship with CD44+/CD133+ CSCs and disease progression in PC. CD8+ T cells infiltration was associated with better survival while PD-L1 expression was correlated with PC recurrence. Both the low CD8+ T cells infiltration/high PD-L1 expression group and the high CD8+ T cells infiltration/high PD-L1 expression group show high levels of CD44+/CD133+ CSCs, but patients with low CD8+ T cells infiltration/high PD-L1 expression had worse survival and higher recurrence risk than those with high CD8+ T cells infiltration/high PD-L1 expression. Moreover, CD8+ T cells infiltration could reduce unfavorable prognostic effect of high co-expression of PD-L1 and CD44/CD133. Our study highlights an interaction among CD8+ T cells infiltration, PD-L1 expression, and CD44+/CD133+ CSCs existence, which contributes to PC progression and immune evasion.

This work aims to develop an integrated fault location and restoration approach for microgrids (MGs). This work contains two parts. Part I presents the fault location algorithm, and Part II shows the restoration algorithm. The proposed algorithms are implemented by particle swarm optimization (PSO). The fault location algorithm is based on network connection matrices, which are the modifications of bus-injection to branch-current and branch-current to bus-voltage (BCBV) matrices, to form the new system topology. The backward/forward sweep approach is used for the prefault power flow analysis. After the occurrence of fault, the voltage variation at each bus is calculated by using the Zbus modification algorithm to modify Zbus. Subsequently, the voltage error matrix is computed to search for the fault section by using PSO. After the allocation of the fault section, the multi-objective function is implemented by PSO for optimal restoration with its constraints. Finally, the IEEE 37-bus test system connected to distributed generations is utilized as the sample system for a series simulation and analysis. The outcomes demonstrated that the proposed optimal algorithm can effectively solve the fault location and restoration problem in MGs.

The collapsible loess will rapidly soften and lose its bearing capacity when soaked in water. Under a mild condition (20°C), the biomimetic inorganic agent, Diammonium phosphate (DAP), reacts with calcite in the collapsible loess, producing a stronger bonding material, hydroxyapatite (HAP), to modify and stabilize the soil. Uniaxial compression, permeability tests and morphological analysis using XRD and SEM/EDX microscopy were carried out to assess the effectiveness of DAP stabilization on the collapsible loess. The results indicated that HAP improved the inter-particle bonding within loess, filled the pores within particles, reduced the permeability, and consequently mitigated collapsibility of loess. The compressive strength of DAP-treated loess increased as DAP concentration increased. Following 28-days curing, the compressive strength of the loess treated with a 3.0 mol/L DAP solution was six times greater than that of the untreated group. DAP's reinforcement effect on loess was superior to that of cement. The compressive strength of DAP-treated loess was about double that of cement-treated loess and the permeability coefficient was reduced by more than 50% at equivalent solid content. Furthermore, DAP generated 68% fewer carbon emissions compared to Portland cement. Considering eco-friendly and sustainable development, DAP offers a more competitive alternative for modification and stabilization of loess.

A rapid and efficient method using an alkyl functionalized magnetic nanoparticles-based extraction technique combined with Ultra-High Performance Liquid Chromatography was developed for the detection of trace amounts of polycystic aromatic hydrocarbons in tea leaves. As a popular coating for chromatographic column packing materials, C18-alkyl has been demonstrated to be effective in separating polycystic aromatic hydrocarbons. And the magnetism of the nanomaterials accelerates the extraction process while their high surface ratio enables desirable dispersity in the sample matrix. Meanwhile, the adsorbents can be washed and reused 30 times without compromise on recovery, which greatly reduced the budget. The effects of various parameters were investigated and optimized, and the recoveries for five analytes were in the range of 84.8–103.7%. The reproducibility rate of intra-day and inter-day were below 7.1% and 11.3% respectively. The limits of detection and limits of quantification ranged from 1.69–9.97 ng g-1 and 5.12–30.21 ng g-1, indicating satisfactory sensitivity. Thus, the proposed methodology is rapid, highly efficient, and economical, and it expands the application of magnetic cleanup approaches in complex food matrices.

： Anti-MDA5 antibody bearing (anti-MDA5+)-dermatomyositis (DM) or polymyositis (PM) is notorious for causing rapidly progressive interstitial lung disease (RPILD) &amp;/or cancers with high mortality rate. However, anti-MDA5 antibodies (Abs) are also found in other connective tissue diseases and their link with RPILD especially with regards to the mortality rate are unknown. We retrospectively recruited 71 patients bearing anti-MDA5-Abs in serum, stratified them in terms of a presence or absence of RPILD, and evaluated their clinical features, laboratory findings, associated myositis antibodies, concurrent connective tissue disease (CTD) as well as newly developed malignancies. Thirty-nine (55%) patients presented with DM/PM but 32 (45%) didn’t. Twenty-two of the former and 11 of the latter developed RPILD eventually, accounting for a total of 46% of all MDA5 bearing patients. On the other hand, 15 of all 71 (21.1%) patients had cancers. Among 32 patients who didn’t have DM/PM, 27 (38.0% of all 71) had other CTDs, indicating that only 5 (7.0% of 71) patients did not have CTDs. Senility (odds ratio [OR]=1.816, P=0.032), presence of anti-Ro-52 antibody (OR=1.676, P=0.018), elevated C-reactive protein (CRP, OR= 4.354, P&lt;0.001) and carcinoembryonic antigen (CEA, OR=2.625, P=0.005) posed risks for RPILD. High lactose dehydrogenase (LDH, p=0.009), CRP (p=0.001), CEA (p=0.001), ferritin (p ≤ 0.001) and low albumin (p ≤ 0.001) were significantly associated with mortality. Anti-SAE antibodies were negatively correlated with RPILD as analyzed by univariate (OR=0.245, P=0.017) and multivariate (OR= 0.058, P=0.036) regressions, indicating that they may be a protective factor from RPILD (OR= 0.543, P=0.008) or fatality (OR= 0.707, P=0.012), which was also demonstrated in subgroup analyses. In contrast to various risk factors for RPILD or mortality, anti-SAE antibodies might be conversely a protective factor in anti-MDA5+ patients.

Based on the data of A-share listed companies in Shanghai and Shenzhen of China from 2011 to 2018 and the digital inclusive finance index of Peking University (2011-2018), this paper empirically tests the impact of digital finance development on corporate social responsibility in various provinces of China and its impact mechanism. The results show that: (1) the development of digital finance helps to promote the fulfillment of corporate social responsibility; (2) the influence mechanism of the development of digital finance to promote the fulfillment of corporate social responsibility lies in that it reduces the cost of debt financing and leads to the improvement of corporate social responsibility.(3) Further research shows that the positive relationship between digital finance and corporate social responsibility is more significant in private enterprises. At the same time, the impact is more significant in areas with poor market environment. The above research shows that the development of digital finance has a significant positive effect, which will improve the level of corporate social responsibility.

There is increasing evidence that some adult mitral valve pathologies may have developmental origins involving errors in cell signaling and protein deposition during valvulogenesis. While early and late gestational stages are well-documented in zebrafish and small mammalian models, longitudinal studies in large mammals with a similar gestational period to humans are lacking. Further, the mechanism of chordae tendineae formation and multiplication remains unclear. This current study presents a comprehensive examination of mitral anterior leaflet and chordae tendineae development in a bovine model (with a gestational period of 9 months). Remarkably distinct from small mammals, bovine development displayed early branched chordae, with increasing attachments only until birth, while the anterior leaflet grew both during gestation and postnatally. Chordae also exhibited accelerated collagen deposition, maturation, and crimp development during gestation. These findings suggest that the bovine anterior leaflet and chordae tendineae possess unique compartmentalized processes of development despite being a continuous collagenous structure.

The Chinese drug Bombyx Batryticatus mori.L which also named as the white stiff silkworm is widely used in clinics, due to the significant antispasmodic and promotional blood circulation effects. In addition, its hypoglycemic effect is also recognized in recent years. From a pathological point of view, the enzymatic glycosylation and non-enzymatic glycation both have important roles in regulating properties of proteins and are associated with Diabetes. With the db/db mouse model, we examined the alterations of N-glycosylation of diabetic myocardium at primary stage and clarify the differences in glycosylation of myocardium before and after with 1-DNJ treatment. Hydrophilic chromatography solid phase extraction enrichment and LC-MS/MS identification was applied to profile the alternations in protein glycosylation. Meanwhile, N-glycan α1, 6-fucosylation alterations were profiled with LCA lectin blot and FITC-labelled lectin affinity histochemistry. Our results showed that AGES, hydroxyproline, CTGF and other serum indicators and fibrosis related cytokines expressional levels were reduced significantly by 1-DNJ in a dose-dependent manner. In order to verify this result, the well-known pathway of TGF-β/smad2/3 was picked out and α1, 6-core fucosylated TGFR-βⅡwas semi-quantified with western blot method. The result sustained the conclusion from LCA lectin affinity histochemistry and lectin blot analysis. The expressional level of α1, 6-fucosyltransferase mRNA was increased in the myocardium of db/db mice, however, the 1-DNJ administration did not show obvious inhibitory effect on FU8 expression. This unexpected result can be interpreted as 1-DNJ plays the roles by reducing the concentration of substrate rather than inhibiting α1，6-fucose glycosyltransferase expression. Meanwhile, 1-DNJ crude extract from BBm with some flavonoids accompany can also play the roles of anti-oxidant, and all the chemicals protect the diabetic myocardium from hyperglycemia damage commonly.

Bacillus amyloliquefaciens GL18 has been proven to have good resistance ability and can promote the growth of Avena sativa cultivar ‘Qingyan 1’. Herein, Illumina high-throughput transcriptome sequencing technology was used to analyze the differential expression of genes between the interaction group (LB) and the control group (LCK) when ‘Qingyan 1’ roots interacted with GL18 bacterial suspension or sterile water for 12 h under 4 °C low-temperature stress. The gene function annotation information was obtained using Gene Ontology (GO) functional classification and enrichment analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and annotation of differentially expressed genes was used to explore the related signal transduction pathway of ‘Qingyan 1’ response to cold stress induced by Bacillus GL18. The results showed that after ‘Qingyan 1’ seedlings interacted with GL18 bacterial suspension or sterile water for 12 h, comparing the LB with the LCK or CK (the control group at 26 °C), there were 12,061 and 25,489 differentially expressed genes, respectively. Their functions were mainly related to metabolic process, cellular process, catalytic activity, binding, and cellular parts, and they were significantly enriched in plant tissue growth and development, cell wall, organelle membrane synthesis, thiamine and its compounds, biosynthesis, polyamine decomposition, and other metabolic processes. Signal transduction was detected through KEGG pathway enrichment analysis, and corresponding genes, such as AUXI, PP2C, SNRK2, ABF, BRI1, and PIF4, were expressed. The expression of genes directly involved in plant growth was upregulated in the presence of GL18, as shown by real-time quantitative PCR analysis. It was speculated that the normal growth and development of ‘Qingyan 1’ under low-temperature stress promoted by GL18 is a result of the integration of multiple pathways in terms of regulating endogenous hormone metabolism, secondary metabolite synthesis, and photosynthesis.

The working environment of mining electric locomotives is wet and muddy coal mine 1 roadway. There may be idling or slipping between the wheels and rails of mining electric locomotives 2 due to low friction between the wheel and rail and insufficient utilization of creep rate. Therefore, it 3 is necessary to control the creep rate within a reasonable range. In this paper, the autonomous control 4 algorithm for mining electric locomotives based on improved ε-greedy is theoretically proven to be 5 convergent and effective firstly. Secondly, after analyzing the contact state between the wheel and rail 6 under wet and slippery road conditions, it was concluded that the value of creep rate is an important 7 factor affecting the autonomous driving of mining electric locomotives. Therefore, the autonomous 8 control method for mining electric locomotives based on creep control is proposed in this paper. 9 Finally, the effectiveness of the proposed method was verified through simulation. The problem of 10 wheel slipping and idling caused by insufficient friction of mining electric locomotives in coal mining 11 environments is effectively suppressed. Autonomous operation of vehicles with optimal driving 12 efficiency can be achieved through quantitative control and utilization of the creep rate between 13 wheels and rails

A series of novel sulfonylurea benzothiazoline were designed by splicing active groups and bioisosterism. A solvent-free synthetic route was developed for the sulfonylurea benzothiazoline derivatives via the cyclization and carbamylation. All the compounds were characterized by IR, 1H-NMR, 13C-NMR, HRMS. The biological activity tests indicated the compounds could protect maize against the injury caused by chlorsulfuron to some extent. The molecular docking result showed that the new compound competed with chlorosulfuron to bind with the herbicide target enzyme active site to attain detoxification.

The shear stress generated by wall turbulence is the main cause of wall friction resistance in turbulent flow through pipes. This paper investigates the impact of inserting rest periods (regions of constant Reynolds number) within the pulsating operating cycle of velocity on the fully turbulent flow at large time-averaged Reynolds numbers, using the Large Eddy Simulation (LES) method. The study aims to explore the effect of increasing rest periods within pulsations on drag resistance. The dimensionless shear stress and drag reduction rates during different time periods of rest were analyzed. Numerical simulation results indicate that the pulsating velocity operation mode does not necessarily lead to drag reduction; it may even result in increased resistance. Inserting rest periods within the pulsation cycle can achieve drag reduction effects, with the maximum drag reduction rate reaching 21.8\%. Comparisons with experimental data and Direct Numerical Simulation (DNS) from the literature validate the feasibility of using the LES method for pipe pulsating operation modes.

Characterization of cancer cells and neural stem cells indicates that tumorigenicity and pluripotency are coupled cell properties determined by neural stemness, and tumorigenesis represents a process of progressive loss of original cell identity and gain of neural stemness. This reminds of a most fundamental process required for the development of the nervous system and body axis during embryogenesis, i.e., embryonic neural induction. Neural induction is that, in response to extracellular signals that are secreted by the Spemann-Mangold organizer in amphibians or the node in mammals and inhibit epidermal fate in ectoderm, the ectodermal cells lose their epidermal fate and assume the neural default fate and consequently, turn into neuroectodermal cells. They further differentiate into the nervous system and also some non-neural cells via interaction with adjacent tissues. Failure in neural induction leads to failure of embryogenesis, and ectopic neural induction due to ectopic organizer or node activity or activation of embryonic neural genes causes a formation of secondary body axis or a conjoined twin. During tumorigenesis, cells progressively lose their original cell identity and gain of neural stemness, and consequently, gain of tumorigenicity and pluripotency, due to various intra-/extracellular insults in cells of a postnatal animal. Tumorigenic cells can be induced to differentiation into normal cells and integrate into normal embryonic development within an embryo. However, they form tumors and cannot integrate into animal tissues/organs in a postnatal animal because of lack of embryonic inducing signals. Combination of studies of developmental and cancer biology indicates that neural induction drives embryogenesis in gastrulating embryos but a similar process drives tumorigenesis in a postnatal animal. Tumorigenicity is the manifestation of aberrant occurrence of pluripotent state in a postnatal animal. Pluripotency and tumorigenicity are both but different manifestations of neural stemness in pre- and postnatal stage, respectively, of animal life. The unique property of neural stemness is derived from the evolutionary advantage of neural genes and the neural-biased state of the last common unicellular ancestors of metazoan. Based on these findings, I discuss about some confusion in cancer research, propose to distinguish the causality and associations and discriminate causal and supporting factors involved in tumorigenesis, and suggest revisiting the focus of cancer research.

This paper introduces the AltumView Sentinare smart activity sensor for senior care and patient monitoring. The sensor uses an AI chip and deep learning algorithms to monitor the activity of people, collect activity statistics, and notify caregivers when emergencies such as falls are detected. To protect privacy, only skeleton (stick figure) animations are transmitted instead of videos. The sensor is highly affordable, accessible, and versatile. It was a CES 2021 Innovation Award Honoree, and has been selected by Amazon as one of only three fall detection devices integrated into its Alexa Together urgent response service, and has received very positive reviews from Amazon customers. It has also been used in different senior care settings in about ten different countries. The paper presents the main features of the system, the evidences and lessons learned from its practical applications, and future directions.

Inflammation is the response of the immune system to infection and injury, with complex interactions with the body, tissues and cells, and plays an important role in the initiation and progression of many diseases such as cancer and cardiovascular disease. Traditional excipients functioning as drug delivery systems can reduce the side effects of systemic distribution of inflammatory drugs. Oil phase, a common excipient in nanoemulsions (NEs), has the advantages of assisting the formation of emulsions, loading lipophilic drugs, thermodynamic stability, wide sources, low price and easy availability. In particular, some of them, like linolenic acid and medium chain triglyceride (MCT), also function as inhibitors of systemic inflammation marker and vascular inflammation marker. However, the influences of different oil phases on the construction of NEs and their distribution in vivo have not been fully investigated. Herein, Tween 80 and ethyl alcohol were screened out as emulsifiers and co-emulsifiers, and three different oil phases used in clinical practice widely, including MCT, oleic acid (OA), and ethyl oleate (EO), were selected as the oil phase to prepare NEs delivery platform. Three NEs had consistent size, potential, morphology, excellent stability and mitochondrial localization function. Importantly, they exhibited superior cellular uptake capacity in inflammatory-injuried human umbilical vein endothelial cells and significantly targeted the brain, lung, heart and thoracic aorta in the lipopolysaccharide-induced mouse and zebrafish larvae inflammation models. Meanwhile, the fluorescence intensities of three NEs were different in these organs, suggesting that their differential enrichment might provide alternative delivery platform for disease treatment in the corresponding organs.

In the TANGO study, the long-term noninferior efficacy of switching to dolutegravir/lamivudine (DTG/3TC) compared to continuing tenofovir alafenamide–based regimens was demonstrated in treatment-experienced adults with HIV. However, there is limited real-world data comparing the effectiveness and safety of bictegravir/emtricitabine/tenofovir alafenamide fumarate (BIC/FTC/TAF) and DTG/3TC in Asia. This retrospective observational study, conducted at a designated HIV-care hospital from March 2019 to January 2023, aimed to address this gap. Demographic, clinical, and laboratory data, including HIV viral loads and lipid profiles, were collected and analyzed. The primary outcome was the proportion of patients with HIV RNA <50 copies/mL at week 48 in both groups, utilizing a snapshot, per-protocol–exposed population. A total of 1086 patients were included, with 511 in the DTG/3TC group and 575 in the BIC/FTC/TAF group. At week 48, 98% of patients in the DTG/3TC group and 94% in the BIC/FTC/TAF group achieved HIV RNA <50 copies/mL (p <0.01). Logistic regression analysis identified risk factors for detectable viral loads at week 48, including HIV RNA >100,000 copies/mL (AOR 5.13, 95% CI 1.42–18.53), low-level viremia (AOR 3.91, 95% CI 1.07–14.25), and record of virologic failure ≥2 times (AOR 4.21, 95% CI 1.64–10.85) before the switch. Furthermore, no significant difference was found between the DTG/3TC and BIC/FTC/TAF regimens (AOR: 1.51, 95% CI 0.70–3.24). In conclusion, the study demonstrates that the effectiveness and safety profiles of DTG/3TC and BIC/FTC/TAF were comparable in treatment-experienced adults with HIV, particularly among those with undetectable viral loads at baseline.

Since the implementation of the Materials Genome Project by the Obama administration in the United States, the development of various computational materials databases has fundamentally expanded the choices of industries such as materials and energy. In the field of thermoelectric materials, the thermoelectric figure of merit ZT quantifies the performance of the material. From the viewpoint of calculations for vast materials, the ZT values are not easily obtained due to their computational complexity. Here, we show how to build a database of thermoelectric materials based on first-principles calculations for the electronic and heat transport of materials. Firstly, the initial structures are classified according to the values of bandgap and other basic properties using the clustering algorithm K-means in machine learning, and high-throughput first principles calculations are carried out for narrow-bandgap semiconductors which exhibiting potential thermoelectric application. The present framework of calculations mainly includes deformation potential module, electrical transport performance module, mechanical and thermodynamic properties module. We have also set up a search webpage for the calculated database of thermoelectric materials, providing searching and viewing the related physical properties of materials. Our work may inspire the construction of more computational databases of first-principle thermoelectric materials and accelerate research progress in the field of thermoelectrics.

Imbalanced classes can cause machine learning models to classify positive class instances poorly, and the models require hyperparameter sets to optimal values. This study aims to develop random forest (RF) and support vector machine (SVM) models that use the optimal hyperparameters obtained through 5-fold cross-validation data. Both models were trained using optimal hyperparameter pairs that fit two data scenarios, the original and oversampling training sets, to produce the benchmark and best models. The model's performance was evaluated using six metrics, including training and testing data. The acquired optimal RF hyperparameter pair was (500, 10) for the minimum number of instances and tree depth level. In contrast, the acquired optimal SVM hyperparameter pair was (0.001, 500) for the gamma and constant values. The benchmark model performed approximately 98% on Accuracy, Precision, Recall, and F1 score metrics but failed to deliver any performance on Mathew's Correlation Coefficient (MC) and Area under Curve (AUC) metrics. The best RF and SVM perform less than both benchmark models in four famous metrics. Both best models have performance improvements of approximately 6% and 11% for the MCC and AUC metrics, respectively. The best RF performance was slightly better than the best SVM performance.

Next-generation sequencing (NGS) has been a widely-used technology in biomedical research for understanding the role of molecular genetics of cells in health and disease. A variety of computational tools have been developed to analyse the vastly growing NGS data, which often require bioinformatics skills, tedious work and significant amount of time. To facilitate data processing steps minding the gap between biologists and bioinformaticians, we developed CSI NGS Portal, an online platform which gathers established bioinformatics pipelines to provide fully automated NGS data analysis and sharing in a user-friendly website. The portal currently provides 16 standard pipelines for analysing data from DNA, RNA, smallRNA, ChIP, RIP, 4C, SHAPE, circRNA, eCLIP, Bisulfite and scRNA sequencing, and is flexible to expand with new pipelines. The users can upload raw data in fastq format and submit jobs in a few clicks, and the results will be self-accessible via the portal to view/download/share in real-time. The output can be readily used as the final report or as input for other tools depending on the pipeline. Overall, CSI NGS Portal helps researchers rapidly analyse their NGS data and share results with colleagues without the aid of a bioinformatician. The portal is freely available at: https://csibioinfo.nus.edu.sg/csingsportal

In cosmology, the cosmic curvature $K$ and the cosmological constant $\Lambda$ are two most important parameters, whose values have strong influence on the behavior of the universe. By analyzing the energy-momentum tensor and equations of state of ideal gas, scalar, spinor and vector potential in detail, we find that the total mass density of all matter is always positive, and the initial total pressure is negative. Under these conditions, by qualitatively analyzing the global behavior of the dynamical equation of cosmological model, we get the following results: (i) $K= 1$, namely, the global spatial structure of the universe should be a 3-dimensional sphere $S^3$. (ii) $0\le\Lambda < 10 ^ {-24} {\rm ly} ^ {-2}$, the cosmological constant should be zero or an infinitesimal. (iii) $a(t)>0$, the initial singularity of the universe is unreachable, and the evolution of universe should be cyclic in time. This means that the initial Big Bang is impossible at all. Since the matter components considered are quite complete and the proof is very elementary and strict, these logical conclusions should be quite reliable. Obviously, these conclusions will be much helpful to correct some popular misconceptions and bring great convenience to further research other problems in cosmology such as property of dark matter and dark energy.

The description of the microscopic world in quantum mechanics is very different from that in classical physics, and there are some points of view that are contrary to intuition and logic. The first is the loss of reality, the behavior of micro particles shows randomness and hopping. The second is the loss of certainty, the conjugate physical variables of a system cannot be determined synchronously, they satisfy the Heisenberg uncertainty principle. The third is the non-local correlation. The measurement of one particle in the quantum entanglement pair will change the state of the other entangled particle simultaneously. In this paper, some concepts related to quantum entanglement, such as EPR correlation, quantum entanglement correlation function, Bell's inequality and so on, are analyzed in detail. Analysis shows that the mystery and confusion in quantum theory may be caused by the logical problems in its basic framework. Bell's inequality is only a mathematical theorem, but its physical meaning is actually unclear. The Bell state of quantum entangled pair may not satisfy the dynamic equation of quantum theory, so it cannot describe the true state of microscopic particles. In this paper, the correct correlation functions of spin entanglement pair and photonic entanglement pair are strictly derived according to normal logic. Quantum theory is a more fundamental theory than classical mechanics, and they are not parallel relation in logic. However, there are still some unreasonable contents in the framework of quantum theory, which need to be improved. In order to disclose the real relationship between quantum theory and classical mechanics, we propose some experiments which show the wave-particle duality simultaneously and provide intuitionistic teaching materials for the new interpretation of quantum theory.

Trehalose is a non-reducing disaccharide and participates in physiological activities such as or-gan formation, energy metabolism, and stress resistance of insects. In the present study, phylo-genetic analysis divided 21 Bmtret1 orthologs into three clades. These genes are equally distrib-uted on the nine chromosomes. Cis-elements in the promoter regions of Bmtret1s indicated the possible function of Bmtret1s in response to hormones and environmental stimulus. The qPCR analysis showed the significantly different expression levels of Bmtret1s in different tissues and organs, indicating possible functional divergence. In addition, most Bmtret1s showed disturbed expression levels in response to BmNPV stresses. Our results provide a foundation for further functional dissection of Tret1s in Bombyx mori and implicate them as potential regulators for an-tiviral responses.

Tumorigenesis is a complex biological phenomenon that includes extensive genetic and phenotypic heterogeneities and complicated regulatory mechanisms. In the recent few years, our studies demonstrate that tumor-initiating cells are similar to neural stem/progenitor cells in regulatory networks, tumorigenicity and pluripotent differentiation potential. In the review, I will make further discussion on these observations and propose a rule of cell biology by integrating these findings with evidence from developmental biology, tumor biology and evolution, which suggests that neural stemness underlies two coupled cell properties, tumorigenicity and pluripotent differentiation potential. Tumorigenicity and phenotypic heterogeneity in tumor is a result of acquirement of neural stemness in cells. The neural stemness property of tumor-initiating cells can hopefully integrate different concepts/hypotheses underlying tumorigenesis. Neural stem cells/neural progenitors and tumor-initiating cells share regulatory networks; both exhibit neural stemness, tumorigenicity and differentiation potential; both are dependent on expression or activation of ancestral genes (the atavistic effect); both rely primarily on aerobic glycolytic metabolism; both can differentiate into various cells or tissues that are derived from three germ layers, resembling severely disorganized or more severely degenerated process of embryonic development; both are enriched in long genes with more splice variants that provide more plastic scaffolds for cell differentiation, etc. The property of neural stemness might be a key point to understand tumorigenesis and pluripotent differentiation potential, and possibly explain certain pathological observations in tumors that have been inexplicable. Therefore, behind the complexity of tumorigenesis might be a general rule of cell biology, i.e., neural stemness represents the ground state of cell tumorigenicity and pluripotent differentiation potential.

Betel quid (BQ) use disorder (BUD) is prevalent in many Asian countries, impacting approximately 600 million people. We conducted a randomized clinical trial to analyze the impact of MAOA genetic variations on the severity of BQ craving. This was measured using DSM-5 criteria and Yale-Brown Obsessive Compulsive Scale modified for betel-quid (Y-BOCS-BQ). Participants were grouped according to the severity of BUD and MAOA gene single nucleotide polymorphism (SNP) rs5953210 genotypes. Y-BOCS-BQ were assessed at baseline (week 0) and during follow-up at weeks 2, 4, 6, and 8. The AA genotype group showed significantly greater reductions in Y-BOCS-BQ at weeks 2 (p=0.0194), 4 (p=0.0078), 6 (p=0.0277), and 8 (p=0.0376) compared to the GG genotype group. Additionally, within the antidepressant group, the AA genotype showed significant reductions in Y-BOCS-BQ at weeks 2 (p=0.0313), 4 (p=0.0134), 6 (p=0.0061), and 8 (p=0.0241) compared to the GG genotype. Statistical analysis revealed a significant interaction between the treatment and placebo groups based on MAOA genotypes, with the AA genotype in the treatment group exhibiting a more pronounced decrease in Y-BOCS-BQ (p interaction <0.05) at week 6. These findings highlight the importance of considering genetic factors when developing personalized treatment plans for BUD.

The magnetic field of the earth plays an important role in the ecosystem, and the magnetic field of celestial bodies is also important in the formation of cosmic large-scale structures, but the origin and evolution of the celestial magnetic field is still an unresolved mystery. Many hypotheses to explain the origin have been proposed, but there are some insurmountable difficulties for each one. At present, the theory widely accepted in scientific society is the dynamo model, it says that, the movement of magnetofluid inside celestial bodies, which can overcome the Ohmic dissipative effect and generate persistent weak electric current and macroscopic magnetic field. However, this model needs an initial seed magnetic field, and the true values of many physical parameters inside the celestial body are difficult to obtain, and there is no stable solution to the large range of fluid motion. These are all difficulties for the dynamo model. Furthermore, it is difficult for the dynamo to explain the correlation between the dipole magnetic field and angular momentum of a celestial body. In this paper, by calculating the interaction between spin of particles and gravity of celestial body according to Clifford algebra, we find that a rotational celestial body provides a field $\Omega^\alpha$ for spins, which is similar to the magnetic field of a dipole, and the spins of charged particles within the celestial body are arranged along the flux line of $\Omega^\alpha$, then a macroscopic magnetic field is induced. The calculation shows that the strength of $\Omega^\alpha$ is proportional to the angular momentum of the celestial body, which explains the correlation between the magnetic intensity and angular momentum. The results of this paper suggest that further study of the effects of internal variables such as density, velocity, pressure and temperature of a celestial body on $\Omega^\alpha$ may provide some new insights into the origin and evolution of celestial magnetic field.

Abstract: The COVID-19 pandemic significantly disrupted global healthcare systems. The impacts of SARS-CoV-2 infection on urticaria and its management are unknown. To collect information about patients with urticaria infected with SARS-CoV-2 and to investigate the impact of SARS-CoV-2 infection on urticaria severity, course, and treatment to better support recovery. This was a questionnaire-based study of patients with urticaria infected with SARS-CoV-2. Changes in urticaria severity (measured with the urticaria activity score (UAS)), course, and treatment were assessed before, during, and after SARS-CoV-2 infection. Mean (± SD) UAS scores were 5.17 ± 1.67, 4.23 ± 1.98, and 4.37 ± 1.93 before, during, and after SARS-CoV-2 infection, respectively (F = 8.839, p < 0.01). The median (IQR) wheal score was 0.464 (0.464, 0.763), 0.464 (0.138, 0.763), and 0.464 (0.138, 0.763) before, during, and after infection, respectively (Kruskal-Wallis H-test, H=12.230, p = 0.02). The median (IQR) pruritus score was 0.695 (0.395, 0.695), 0.394 (0.123, 0.695), and 0.394 (0.123, 0.695) before, during, and after infection, respectively (Kruskal-Wallis H-test, H = 21.001, p < 0.01). Within the limitations of a questionnaire study, urticaria appears to improve during SARS-CoV-2 infection, worsens slightly after recovery, and the frequency of Western medicine use increases.

The theory of fractional calculus extends the order of classical integer calculus from integer to non-integer. As a new engineering application tool, it has made many important research achievements in many fields, including image processing. This paper mainly studies the application of fractional calculus theory in image enhancement and denoising, including the basic theory of fractional calculus and its amplitude frequency characteristics, the application of fractional differential operator in image enhancement, and the application of fractional integral operator in image denoising. The experimental results show that the fractional calculus theory has more special advantages in image enhancement and denoising. Compared with the existing integer order image enhancement operators, the fractional differential operator can more effectively enhance the "weak edge" and "strong texture" details of the image. The fractional order integral image denoising operator can not only improve the signal-to-noise ratio of the image compared to traditional denoising methods, but also better preserve detailed information such as edges and textures of the image.

This study establishes a multivariate function model for natural human load carrying walking in some typical scenarios like college equipments and materials relocation for students. For classified materials relocation needs and constraints, we obtain the relationship between walking speed and load weight for single person, as well as the time cost for different round trips. By establishing an integer programming model with the minimum total transportation time cost and quality assurance as the objective function and the requirements of negative weight and speed as the constraints conditions, we reach the optimal item allocation methods considering time cost and shelf life were obtained. We discover that there is an approximate linear relationship between the change in natural walking speed and travel time when the load is small, thus obtaining the time cost of student transportation under different round-trip situations. The Monte Carlo simulation algorithm is used to obtain the optimal allocation scheme that meets the efficiency and quality requirements. The analysis methods and results can be used as guidance for task scheduling optimization for material relocation in educational organizations as well as commercial agencies.

Mouse embryonic stem cells (mESCs) possess remarkable characteristics of unlimited self-renewal and pluripotency, which render them highly valuable for both fundamental research and clinical applications. A comprehensive understanding of the molecular mechanisms underlying mESC function is of utmost importance. The Human Silence Hub (HUSH) complex, comprising FAM208A, MPP8, and periphilin, constitutes an epigenetic silencing complex involved in suppressing retroviruses and transposons during early embryonic development. However, its precise role in regulating mESC pluripotency and differentiation remains elusive. In this study, we generated homogenous miniIAA7 tagged Mpp8 mouse ES cell lines. Upon induction of MPP8 protein degradation, we observed impaired proliferation and reduced colony formation ability of mESCs. Furthermore, this study unveils the involvement of MPP8 in regulating the activity of the LIF/STAT3 signaling pathway and Nanog expression in mESCs. Finally, we provide compelling evidence that degradation of the MPP8 protein impairs the differentiation of mESC.

During their growth, bacteria respond to complex environmental changes through equally com-plex and orderly regulatory mechanisms. sRNA has an important role as a post-transcriptional regulator in the environmental adaptation of Bacillus. In this study, we identified an sRNA Bvs091 located in the intergenic region of the Bacillus velezensis, which is widely present in the genus Bacillus and whose expression is upregulated by salt treatment. The deletion of bvs091 in B. ve-lezensis PEBA20 led to a reduced growth rate and a change in the phenotypes, with simple colony structures and low and easily degradable biofilm. Salt tolerance tests indicated that the deletion of bvs091 results in a reduced salt tolerance. galT2 mRNA is supposed to be a direct target of Bvs091 according to results obtained by using the bioinformatic method and performing qRT-PCR analysis. The microscale thermophoresis (MST) analysis showed that Bvs091 could directly bind 28‒51 bases in front of the promoter of galT2. Subsequently, the deletion of galT2 in B. velezensis resulted in increased salt tolerance. Based on the techniques of double plasmids and a half-life period, sRNA Bvs091 is confirmed as a trans-encoded sRNA that negatively regulates the mRNA expression of galT2. In brief, the trans-encoded sRNA Bvs091 acts by pairing the incomplete complementary bases of galT2 mRNA, reducing galT2 mRNA’s stability and affecting the trans-lation efficiency.

This study explores the public library service evaluation domain through user-generated content on Google Maps, highlighting digital feedback's significant yet underexplored potential in understanding public library patronage across Taiwan's six major cities. Utilizing a mixed-methods research design, this study integrates Google Maps review content analysis with Social Network Analysis to delineate public perceptions and identify areas for service enhancement in public libraries. It innovatively leverages personal experiences extracted from over 60,000 Google Maps reviews to evaluate public library services in cities such as Taipei, New Taipei, Taoyuan, Taichung, Tainan, and Kaohsiung. The research taps into the National Library of Taiwan's National Library Statistics System to provide a robust analysis of library performance and user satisfaction, offering a novel perspective by emphasizing user-centric feedback from Google Maps as a primary data source. This approach provides quantitative data on library usage and geographic distribution and enriches our understanding of the qualitative experiences of library users. In analyzing the keywords from Google Maps reviews of public libraries, we categorize and interpret these under the three core LibQUAL+ dimensions—Affect of Service, Information Control, and Library as Place. The findings expose variances in perceived service quality among the cities, with Kaohsiung and Taichung receiving the highest accolades for service satisfaction. Simultaneously, the study identifies potential areas for improvement, particularly in cities with lower satisfaction ratings like Taipei. This personalized feedback illustrates the intimate relationship between public libraries and their communities, offering invaluable insights for policymakers and library management to enhance service delivery and user experience.

Currently, urban renewal activities in China are booming. And promoting the renovation of public buildings is the key due to its large scale, high cost and significant impact to the nature and social environment. To reduce the ambiguity and uncertainty in evaluating the potential for renewal of existing public buildings, a renewal potential evaluation model combining game theory combination weighting method and cloud model theory is proposed. The paper constructs a comprehensive evaluation index system based on relevant standards and literature. Game theory is used to optimize the weights obtained by AHP and entropy weight methods to obtain a combined weight. MATLAB programming is used to calculate the comprehensive cloud parameters of the evaluation index for the potential renewal of existing public buildings and therefore generate cloud Graphs. Through case study in Nanjing of China, it has been demonstrated that the combination empowerment cloud model can objectively reflect the relationship between the fuzziness and randomness of evaluation indicators for public building renewal potential. The expression of cloud Graphs can intuitively reflect the magnitude of renewal and renovation potential and the degree of uncertainty in evaluation results. The research result provides useful references for the sustainable utilization of building resources in the era of building.

In this study, a new type of temperature sensor device was developed. The circular electrode of the thermal sensitive sensor was modified with TMT and O₂ plasma to enhance the conductivity by forming a thin SnOxCy layer on the electrode surface. The Nano-Au particles were subjected to O₂ plasma pretreatment to form peroxide groups on the surface. The thermally sensitive sensor was made by mixing the above-treated Nano-Au particles with N-isopropylacrylamide (NIPAAm) to form solution and then UV-induced grafting polymerization of the NIPAAm-containing solution onto the electrode substrate. The composite hydrogels on the electrode introduce thermo-sensitive polymeric surface films for temperature sensing. Using ambient environment resistance test to measure the resistance, the LCST (lower critical solution temperature) of Nano-Au (MUA) mixed with NIPAAm hydrogel was found to be 32 °C. At ambient temperatures higher than LCST, the electrode resistance decreases linearly.

Cellular oxidation is responsive to external and internal stimulation and is generated via signal molecules in defense mechanisms through networks of cell proliferation, differentiation, intracellular detoxification, bacterial infection, and immune reactions. Oxidative stress is not necessarily harmful per se; it depends on the balance between oxidation and antioxidation cascades, which are induced according to stimuli and can maintain oxygen homeostasis. The reactive oxygen species (ROS) that are generated during influenza virus (IV) infection have critical effects on both the virus and host cells. In this review, we outline the link between viral infection and ROS production, using IV as an example. We introduce the current state of knowledge on the molecular relationship between cellular oxidation mediated by ROS production and various effects of IV infection. We also summarize the potential anti-IV agents that act by targeting oxidative stress.

This study presents a vibration control using actively tunable vibration absorbers (ATVA) to suppress vibration of a thin plate. The ATVA’s is made of a sandwich hollow structure embedded with the electrorheological fluid (ERF). ERF is considered to be one of the most important smart fluids and it is suitable to be embedded in a smart structure due to its controllable viscosity property. ERF’s apparent viscosity can be controlled in response to the electric field and the change is reversible in 10 microseconds. Therefore, the physical properties of the ERF-embedded smart structure, such as the stiffness and damping coefficients, can be changed in response to the applied electric field. A mathematical model is difficult to be obtained to describe the exact characteristics of the ERF embedded ATVA because of the nonlinearity of ERF’s viscosity. Therefore, a fuzzy modeling and experimental validations of ERF-based ATVA from stationary random vibrations of thin plates are presented in this study. Because Type-2 fuzzy sets generalize Type-1 fuzzy sets so that more modelling uncertainties can be handled, a semi-active vibration controller is proposed based on Type-2 fuzzy sets. To investigate the different performances by using different types of fuzzy controllers, the experimental measurements employing type-1 fuzzy and interval type-2 fuzzy controllers are implemented by the Compact RIO embedded system. The fuzzy modeling framework and solution methods presented in this work can be used for design, performance analysis, and optimization of ATVA from stationary random vibration of thin plates.

The molecular clusters ((HO)3Si-O-Si(OH)3, and (HO)3Al-O-Si(OH)3 ) representative of aluminosilicate mineral surface were employed to study the dissolution of aluminosilicate in acidic condition via density functional theory with the M06-2X+G(d,p) methodology. The surface termination sites (Si and Al) were both tetra-coordinated and the terminal oxygen was protonated in acidic condition. In the dissolution reaction, the calculated barrier height of the six-membered ring transition state complex containing two water molecules was predicted to be lower than that of four-membered ring transition state complex containing one water molecule. In addition, the calculated barrier heights for Al-terminated sites were predicted to be lower than those for the Si-terminated sites, suggesting that breaking the Al-O bond is easier than Si-O bond in the aluminosilicate mineral surface; the barrier heights of the surface termination sites with protonated terminal oxygen were lower than those without protonated terminal oxygen. With the fracture of Si-O and Al-O bonds, the Si and Al release from the aluminosilicate. These results confirm the experimental conclusions that the acidic condition facilitates the release of Si and Al from the aluminosilicate, and the concentration of Al leaching from aluminosilicate is higher than Si.

Our results demonstrated that SWT stimulates osteoblastogenesis and increase the cell number of osteoblasts, suggesting positive regulatory effects on osteoblast differentiation. However, the effect of SWT on bone formation need further examination, since the expression of alp gene is downregulated. On the other hand, SWT appears to negatively regulate osteoclast differentiation and bone resorption, as number of osteoclasts and the expression of critical bone resorptive genes are all downregulated. Collectively, SWT might change the equilibrium of bone remodeling and increase the bone mass. Our data provided supportive evidences that this medicine formulation can be applied to treat osteoporosis or bone destructive diseases.

The advent of large models, also known as foundation models, has significantly transformed the AI research landscape, with models like Segment Anything (SAM) achieving notable success in diverse image segmentation scenarios. Despite its advancements, SAM encountered limitations in handling some complex low-level segmentation tasks like camouflaged object and medical imaging. In response, in 2023, we introduced SAM-Adapter, which demonstrated improved performance on these challenging tasks. Now, with the release of Segment Anything 2 (SAM2)—a successor with enhanced architecture and a larger training corpus—we reassess these challenges. This paper introduces SAM2-Adapter, the first adapter designed to overcome the persistent limitations observed in SAM2 and achieve new state-of-the-art (SOTA) results in specific downstream tasks including medical image segmentation, camouflaged (concealed) object detection, and shadow detection. SAM2-Adapter builds on the SAM-Adapter's strengths, offering enhanced generalizability and composability for diverse applications. We present extensive experimental results demonstrating SAM2-Adapter's effectiveness. We show the potential and encourage the research community to leverage the SAM2 model with our SAM2-Adapter for achieving superior segmentation outcomes. Code, pre-trained models, and data processing protocols are available at http://tianrun-chen.github.io/SAM-Adaptor/.

The composition and pattern of ecosystems are important factors determining the overall status and spatial differences of ecosystem service functions. However, under the background of differential land policies and ecological protection policies, research on the trend of ecological system pattern changes in the Fenhe River Basin is insufficient. Taking the upper and middle reaches of the Fenhe River Basin as the study area, based on long-term NDVI index and multi-period LUCC remote sensing images, this study used spatial statistics and time trend analysis methods to analyze the spatio-temporal dynamic changes of vegetation, land use, landscape pattern, and explored the impact of major driving factors on ecosystem changes. The results show that: (1) From 2010 to 2020, the vegetation cover in the upper and middle reaches of the Fenhe River Basin increased, with an annual NDVI increment of 0.003 (P<0.001). NDVI showed an increasing trend spatially, with significant statistics (P<0.001) and significant changes (P<0.05) in vegetation in high-altitude mountain areas, and the vegetation cover was mostly forests or grasslands. There was no significant change in vegetation cover in the low-lying urban agglomeration area. (2) From 2010 to 2020, the area of water bodies or wetlands in the study area significantly decreased, with 51.3% converted to arable land and 33.9% transferred to construction land, while only 2.2% remained as water bodies or wetlands. From 2015 to 2020, the trend of water body changes slowed down, with the proportions of conversion to arable land and construction land being 44.0% and 18.4% respectively, while the area of wetlands or water bodies remained at 16.3%. During the period of 2015-2020, the area of water bodies or wetlands converted to other land types increased by more than 14% compared to 2010-2015. This proportion reached more than 30% compared to the 13th Five-year Plan Period. (3) From 2010 to 2020, the spatial changes of landscape diversity (SHDI) and evenness (SHEI) of LUCC showed heterogeneous characteristics. In the high-altitude areas near the river basin boundary, the values of SHDI and SHEI were below 1.0. While in the low-altitude plain areas and urban areas with relatively frequent human activities, the values of SHDI and SHEI were above 1.0, and the values in urban areas could reach above 1.5. The evolution of ecosystem patterns in the upper and middle reaches of the Fenhe River Basin in the past decade has been clarified, providing a scientific basis for the construction and management of ecological environment governance and restoration projects in the Fenhe River Basin, and providing practical references for ecological protection and high-quality development practice in the Yellow River Basin.

With the introduction of policies to promote intangible cultural heritage into schools, intangible cultural heritage plays an increasingly important role in primary education. However, the implementation of the intangible cultural heritage policy in primary schools is mostly formalized, which leads to many problems in the introduction of intangible cultural heritage, such as mainly staying at the level of visual display and public opinion publicity, carrying out a small number of intangible cultural experience activities, and insufficient materialization and scenization of intangible cultural heritage, so that students cannot feel the inherent charm of intangible cultural heritage. In order to promote the development of intangible cultural heritage education, this paper uses the AGIL model of Parsons, literature analysis, case analysis and interview methods to study the promotion path of intangible cultural heritage in primary schools, and proposes solutions such as setting educational goals for school segments, setting up intangible cultural experience activities in schools, combining intangible cultural heritage with subject courses, and establishing a good maintenance mode. After the program is applied into practice, it is found that the use of storytelling by teachers to popularize the relevant knowledge of intangible cultural heritage is conducive to stimulating students' interest and prompting students to think. In addition, teaching and life practice should be combined, and students' five education should be emphasized at the same time to avoid teaching uniformity.

3D Zernike moments based on 3D Zernike polynomials have been successfully applied to the field of voxelized 3D shape retrieval and have attracted more attention in biomedical image processing. As the order of 3D Zernike moments increases, both computational efficiency and numerical accuracy decrease. Due to this phenomenon, a more efficient and stable method for computing high-order 3D Zernike moments was proposed in this study. The proposed recursive formula for computing 3D Zernike radial polynomials combines the recursive calculation of spherical harmonics to develop a voxel-based algorithm for the calculation of 3D Zernike moments. The algorithm was applied to the 3D shape Michelangelo's David with a size of 150×150×150 voxels. As compared to the method without additional acceleration, the proposed method uses a group action of order sixteen orthogonal group and saving unnecessary iterations, the factor of speed-up is 56.783±3.999 when the order of Zernike moments is between 10 and 450. The proposed method also obtained an accurate reconstructed shape with the error rate (normalized mean square error) of 0.00 (4.17×10^-3) when the reconstruction was computed for all moments up to order 450.

Studies on the neurobiological causes of anxiety disorders suggest that the GABA system in-creases synaptic concentration and enhances the affinity of GABAA (type A) receptors for ben-zo-diazepine ligands. Flumazenil antagonizes the benzodiazepine binding site of the GABA (γ-aminobutyric acid) type /benzodiazepine receptor (BZR) complex in the central nervous sys-tem (CNS). The integration of the metabolites of flumazenil by LC-tandem mass spectrometry will complete understanding of the in vivo metabolism of flumazenil and accelerate radio-pharmaceutical inspection and registration. The main goal of our study was to investigate using reversed-phase HPLC (PR-HPLC) coupled with electrospray ionization triple quadrupole tan-dem mass spectrometry (ESI-QqQ MS) for the identification of flumazenil and its metabolites in a hepatic matrix. And a carrier-free nucleophilic fluorination with automatic synthesizer for [18F]flumazenil which applied to in vivo nano-positron emission tomography (Nano-PET)/computed tomography (CT) imaging and ex vivo bio-distribution used to analyze in normal rats. The study showed that 50% of the flumazenil was bio-transformed at 60 min by the rat liver homogenate, while one metabolite (M1) was a methyl transesterification product of flumazenil. In a rat liver microsomes system, two metabolites were identified (M2 and M3) as its carboxylic acid and hydroxylated ethylester forms, respectively. [18F]flumazenil in vivo nanoPET/CT imag-ing and ex vivo bio-distribution assay also showed significant effects on GABAA receptor availa-bility in the amygdala, prefrontal cortex, cortex, and hippocampus in the rat brain, worriless about the formation of metabolites. We showed completion of the bio-transformed course of flumazenil by the hepatic system; and [18F]flumazenil can be a good ligand and serve as a PET agent for determination of GABAA/BZR complex for multiplex neurological syndromes in the clinical stage.

Background: Cancer patients require cross-professional care during the diagnosis and treatment periods. Therefore, methods for effectively carrying out case management are essential to tumor care. Purpose: To investigate the effects of using the community software LINE Official Ac-count on oral cancer case management. Methods: An experimental design was used; 100 patients were randomly divided into two groups by using a computer-generated random number table. The experimental group used LINE Official Account, which gave them self-care information, timely messages, and one-on-one health-care consultations. The control group followed standard healthcare practices. Results: The experimental group was satisfied with the self-care information provided by LINE Official Account (86.9%), patients regularly checked the self-care information (89.4%) and would check the information when receiving a push notification (54.3%). Ten patients used the one-on-one consultation(20.0%). LINE Official Account had a significant effect on the rate of participation in support groups. Generalized estimating equations indicated a significant difference between the two groups regarding the overall quality of life over 7 days (P = 0.023). Conclusion: Community software applications used in oncological case management can improve self-management and empower, also enable tracking of long-term follow-up effectiveness and reinforce the case manager’s role as a family therapist. Therefore, this study recommends that case manager systems be incorporated into mobile applications to increase the sustainable management, accessibility, effectiveness, and satisfaction of oncological management systems. This study also provides the value of Sustainable Development Goals (SDGs) with Good Health and Well-being, and decreased social withdrawal among patients with oral cancer.

Bloodstream infection is a major health problem worldwide, with extremely high mortality. Detecting infection in the early stage is challenging due to the extremely low concentration of bacteria in the blood. Digital PCR provides unparalleled sensitivity and can achieve absolute quantification, but it is time-consuming. Moreover, the presence of unavoidable background signals in negative controls poses a significant challenge for single-molecule detection. Here, we propose a novel strategy called “Ultrafast flexible thin tube-based droplet digital PCR (utPCR)” that can shorten the digital PCR process from 2 hours to only 5 minutes, with primer annealing/extension time reduced from minutes to only 5 seconds. Importantly, the ultrafast PCR eliminates the nonspecific amplification and thus enables single-molecular detection. The utPCR enabled sensitive detection and digital quantification of E. coli O157 in the high background of 106-fold excess of E. coli K12 cells. Moreover, this method also displayed the potential to detect rare pathogens in blood samples, and the limit of detection (LOD) could be as low as 10 CFU per mL of blood without false positive results. Considering ultrafast (<5 min) and highly sensitive (single-molecule detection), the utPCR holds excellent prospects in the next generation of molecular diagnosis.

Brassica yellows virus (BrYV) is a tentative species of the genus Polerovirus, which occurs widely and mostly damage Brassicaceae plants in East Asia. Since BrYV could not be transmitted mechanically, an insect transmission method is required for further virus research. Here, a reliable and unrestricted method was described, in which non-viruliferous aphids (Myzus persicae) acquired BrYV from transgenic Arabidopsis thaliana plants with virus full length genome germinated from seeds and frozen infected leaves were used to transmit the virus to healthy plants, and there was no significant difference in acquisition rate though transmission rate from frozen infected leaves was somehow lower compared to fresh infected leaves. This novel simple method could be applied to preservation of virus inocula, evaluation of variety resistance to BrYV, biological research on interaction among BrYV, aphid and host, which also provide a new idea on establishing a basic method using virus genomic transgenic plants or frozen infected leaves for other poleroviruses research.

Simply Summary: Translation of new cancer treatments between pets and human were noticed in comparative oncological investigation. The current study aims at evaluating a polyacetylenic glucoside purified from an edible herb, Bidens pilosa, to present its anti-angiogenic effects. We innovatively find this polyacetylenic glucoside, cytopiloyne, shows anti-angiogenic effect on different in vitro assays and various in vivo animal models under hypoxia. Based on results of this study, cytopiloyne will be a prospective herb angiogenesis inhibitor candidate to control animal or human cancer formation as adjuvant therapy. Abstract: Anti-angiogenesis is a pivotal combination treatment approach in cancer therapy but rare using on companion animals. This study aimed at evaluating the anti-angiogenic effect of a B. pilosa sourced polyacetylenic glucoside, cytopiloyne, on various in vitro assays and in vivo models. We provide evidences showing that CP has anti-angiogenic activities. Firstly, CP inhibited sponge/ Matrigel plug angiogenesis from tumor cells and decreased the survival of tumor cells on hypoxic conditions. Besides, CP declined PKCα protein expression which a protein leads to the growth and spread of tumors under hypoxia. Secondly, inhibitory effects of CP on endothelial angiogenesis were confirmed by chick chorioallantoic membrane assay, tube formation of SVEC4-10 cells and Matrigel plug assay. A dose-dependent CP treatment inhibited 4T1 cells proliferation under hypoxia and migration. It also suppresses VEGF transcription under hypoxia. Finally, we found that CP decreased PDIA4, a novel regulator of cancer growth, expression in endothelial cells. This effect was confirmed by PDIA4 knockout mice with reduced angiogenesis in Matrigel plug assay. Taken together, these results suggest that CP might act as a promising anti-angiogenic herbal agent candidate to be used in animal hypervascularized cancer of veterinary medicine or in combination to control human cancer as adjuvant therapy.

With the prevalence of smartphones, the scope of mobile applications has been significantly broadened in the past few years including almost every aspect of our daily life. Among the applications, message dissemination services play a significant role. Traditionally, users send messages to the servers, which forward them according to friend lists. This client-server architecture is efficient with the support of infrastructures, however, it restricts the application scope and may hinder the wide deployment of location-based mobile applications. This paper proposes a novel communication model called passive broadcast for local message dissemination. In this new model, each node does not maintain a connection state and data delivery is initialized by a receiver via a ’scan’ operation. The representative carriers of passive broadcast include Bluetooth and WiFi-Direct, both of which define a mandatory ‘peer discovery’ function. Passive broadcast features negligible cost for establishing and maintaining direct links and is extremely suitable for short message dissemination in proximity. Furthermore, we study the operation management in the proposed communication model with complete protocols and in-depth analysis for optimization. We prototyped our solution on commercial phones and evaluated it with extensive experiments and simulation.

In the last decades, we have witnessed a spectacular information explosion over the Internet. Millions of users are consuming the Internet through various services, such as mobile applications, and online games. The service providers, at the back-end side, are supported by state-of-art infrastructures. Targeting on providing the services at scale, virtualization is one of the emerging technologies used in data centers and cloud environments to improve the quality of services. In this project, we aim to develop a dynamic resource management scheme based on virtual containers. It collects the runtime job progress from the running tasks and allocates the resources dynamically to improve the overall system performance.

Smartphone has become one of the most revolutionary devices in the history of computing. With various kinds of applications, the scope of smartphone has been significantly broadened in the past few years including almost every aspect in our daily life. However, due to the limited on-board resources such as CPU, storage, network bandwidth and battery power, smartphones and the mobile network serving them bring new challenges that have not been encountered in the traditional computing and networking environments. This dissertation focuses on the research areas of improving the network architecture and enhancing the current applications on smartphones. It mainly investigates the areas in the following two directions for three representative categories of mobile services. - In the first direction, the dissertation aims to develop new communication models for smartphone Ad-Hoc networks to achieve efficient communication in the proximity. It is motivated by the fact that smartphone Ad-Hoc networks can help improve the current location-based services and propel new applications. Moreover, the new communication models provide complementary alternatives to the traditional infrastructure-based wireless networks. - In the second direction, the dissertation focuses on improving the other two categories of services, cloud storage services and real-time video streaming services for mobile devices. In the field of cloud storage, we introduce a cloud-assisted approach to provide a set of advanced file operations, such as encryption, decryption and compression, on smartphones. Furthermore, by utilizing the on-board Near Field Communication(NFC) module, we develop an algorithm to securely share the files between mobile devices. For the services of real-time video streaming, we propose approaches that identify a user’s status by analyzing the accelerometer data and then, dynamically adjust the buffer mechanism to save network bandwidth on smartphones.

Many researches have identified that adverse childhood experiences (ACEs) are associated with non-suicidal self-injury (NSSI) and suicidality. However, most studies have been restricted to a few types of ACEs. This study aims to investigate associations of 13 common types of ACEs with NSSI, suicidal ideation (SI) and suicide attempt (SA), as well as the mediation of depressive and anxiety symptoms therein. A total of 1771 students aged 11-16 years who participated in the baseline survey of the Chinese Adolescent Health Growth Cohort study were included for the analysis. ACEs, SI, SA, depressive and anxiety symptoms were recorded by standard questionnaire. Of included participants, 92.0% reported one or more category of ACEs. Smoking, parent-child separation, emotional abuse, physical abuse and being bullied were positively associated with NSSI, with the adjusted odds ratio (aOR) of 2.41(95%CI, 1.01-5.75), 1.80(1.28-2.54), 1.69(1.21-2.37), 2.08(1.44-3.01) and 1.87(1.35-2.59), respectively; smoking (4.03, 1.66-9.81), parent-child separation (1.42, 1.07-1.90), emotional abuse (1.91, 1.41-2.59), physical abuse (1.80, 1.27-2.57), emotional neglect (1.78, 1.28-2.49) and being bullied (2.08, 1.54-2.81) were positively associated with SI; smoking(4.30, 1.67-11.10), emotional abuse (2.42, 1.58-3.72) and being bullied (1.75, 1.17-2.60) were positively associated with SA. The associations of ACEs with NSSI, SI and SA were each partially or completely mediated through depressive and anxiety symptoms. Children and adolescents who had experiences of smoking, physical abuse and being bullied during childhood are consistently and independently associated with NSSI and suicidality, and these associations may be largely mediated through depressive and anxiety symptoms.

Artificial intelligence (AI) is revolutionizing the textile industry by improving the prediction of fabric properties and handfeel, which are essential for assessing textile quality and performance. However, the practical application and translation of AI-predicted results into real-world textile production remain unclear, posing challenges for widespread adoption. This paper systematically reviews AI-driven techniques for predicting these characteristics by focusing on model mechanisms, dataset diversity, and prediction accuracy. Among 811 papers initially identified, 26 were selected for in-depth analysis through both bibliometric and content analysis. The review categorizes and evaluates various AI approaches, including machine learning, deep learning, and hybrid models, across different types of fabric. Despite significant advances, challenges remain, such as ensuring model generalization and managing complex fabric behavior. Future research should focus on developing more robust models, integrating sustainability, and refining feature extraction techniques. This review highlights the critical gaps in the literature and provides practical insights to enhance AI-driven prediction of fabric properties, thus guiding future textile innovations.

The objective of this study was to evaluate the impact of incorporating fermented feed into the daily diet on the slaughter performance, meat quality, and flavor compounds of cage-raised chicken. The control group (CK) of the Guangxi Partridge chicken was provided a standard base diet (CK), which was supplemented with 10% fermented banana peel (Pe-10), 20% fermented banana peel (Pe-20), 10% fermented banana pulp residue (Pu-10) and 20% fermented banana pulp residue (Pu-20). The slaughter performance, meat quality, and flavor compounds in the meat samples of the chicken in these groups were evaluated. The results demonstrated that the chicken in Pe-10, Pe-20, Pu-10, and Pu-20 had pectoral muscle percentages, thigh muscle percentages, and total fatty acid content of the chest meat in the Pe-10, Pe-20, Pu-10, and Pu-20 groups were higher than that observed in the CK group. The moisture content, meat color, carcass weight, total net weight, and abdominal fat percentage of the meat samples in these experimental groups exhibited no notable differences. The flavor compounds in the meat samples of the chicken fed with the two concentrations of fermented banana peel and banana pulp residue exhibited notable differences from those in the control group. An increase in the quantity of fermented banana peel incorporated into the daily diet from 10% to 20% resulted in a notable alteration in the flavor profile of the chest meat samples. In conclusion, the inclusion of varying proportions of fermented banana peels and dregs in the diet has been demonstrated to enhance both the slaughter performance and the quality of the chicken, while also influencing the flavor profile.

Construction productivity entails a wide range of work combinations. When human resources are scarce, it is critical to replace manpower with machinery, and calculating machinery productivity is crucial. Traditional labor productivity methods, however, cannot address dredging complex multi-attribute decision-making (MADM) problems. Aiming to address the limitations of the traditional labor productivity method, this paper extends the data envelopment analysis (DEA) and proposes a new dredging productivity evaluation method. The proposed method can solve the problem of evaluating various combinations of factors (single-input, multiple-input, sin-gle-output, and multiple-output) and the problem suggesting that the efficiency of the DEA method'scalculation results is equal to 1. The effectiveness of the proposed method was verified using reservoir dredging examples. The simulation results show that the proposed method has broad applicability, can accurately evaluate the related dredging performance issues, and provide directions for construction managers to improve labor productivity.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

In this research article we solve the problem of synchronization and anti-synchronization of chaotic systems described by discrete and time-delayed variable fractional order differential equations. To guarantee the synchronization and anti-synchronization of these systems, we use the well-known PID control theory and the Lyapunov-Krasovskii stability theory for discrete systems of variable fractional order.We illustrate the results obtained through simulation with examples, in which it can be seen that our results are satisfactory, thus achieving synchronization and anti-synchronization of chaotic systems of variable fractional order with discrete time delay.

Pattern recognition has long been regarded as key role for crime prevention and reduction. Crime analysts and policy makers can formulate effective strategies and allocate resources with reference to spatial and temporal pattern of crime. In order the combat and prevent severe crime in New York City (NYC), this study analyzed Felony Crime data of NYC in previous 5 years (2015 2020) and discovered criminal hotspots pattern and temporal patterns with open criminal complaint data provided by New York Police Department (NYPD). This study adapt a human computer interactive appraoch to draw patterns from crime data, whereas computations and visualization are performed by Python libraries, and human to inform the decision of visualization methods, computational parameters and direction of this exploratary analysis. Density based clustering algorithms, Grid Thematic Mapping and Density Heatmap are displayed to identify hotspots and demonstrates their associations with spatial features. Timeline analysis on moments of crime occurance demonstrates seasonality where crimes are mostly commited, while aoristic analysis showed hours of day when crime is mostly committed considering their timespan. Lastly, 3D visualization improved recognition of the displacement of hotspot over time, and suggested long term hotspots in NYC in 3 D visualization. This inform strategic plans for police deployment.

The interaction between spinors and gravity is the most complicated and subtle interaction in the universe, which involves the basic problem to unified quantum theory and general relativity. By means of Clifford Algebra, a unified language and tool to describe the rules of nature, this paper systematically discusses the dynamics and properties of spinor fields in curved space-time, such as the decomposition of the spinor connection, the classical approximation of Dirac equation, the energy momentum tensor of spinors and so on. To split spinor connection into Keller connection $\Upsilon_\mu\in\Lambda^1$ and pseudo-vector potential $\Omega_\mu\in\Lambda^3$ by Clifford algebra not only makes the calculation simpler, but also highlights their different physical meanings. The representation of the new spinor connection is dependent only on the metric, but not on the Dirac matrix. Keller connection only corresponds to geometric calculations, but the potential $\Omega_\mu$ has dynamical effects, which couples with the spin of a spinor and may be the origin of the celestial magnetic field. Only in the new form of connection can we clearly define the classical concepts for the spinor field and then derive its complete classical dynamics, that is, Newton's second law of particles. To study the interaction between space-time and fermion, we need an explicit form of the energy-momentum tensor of spinor fields. However, the energy-momentum tensor is closely related to the tetrad, and the tetrad cannot be uniquely determined by the metric. This uncertainty increases the difficulty of deriving rigorous expression. In this paper, through a specific representation of tetrad, we derive the concrete energy-momentum tensor and its classical approximation. In the derivation of energy-momentum tensor, we obtain a spinor coefficient table $S^{\mu\nu}_{ab}$, which plays an important role in the interaction between spinor and gravity. From this paper we find that, Clifford algebra has irreplaceable advantages in the study of geometry and physics.

Clifford algebra is unified language and efficient tool for geometry and physics. In this paper, we introduce this algebra to derive the integrable conditions for Dirac and Pauli equations. This algebra shows the standard operation procedure and deep insights into the structure of the equations. Usually, the integrable condition is related to the special symmetry of transformation group, which involves some advanced mathematical tools and its availability is limited. In this paper, the integrable conditions are only regarded as algebraic conditions. The commutators expressed by Clifford algebra have a neat and covariant form, which are naturally valid in curvilinear coordinate system and curved space-time. For Pauli and Schr\"odinger equation, many solutions in axisymmetric potential and magnetic field are also integrable. We get the scalar eigen equation in dipole magnetic field. By the virtue of Clifford algebra, the physical researches may be greatly promoted.

In this note we construct explicit complex and real matrix representations for the generators of real Clifford algebra $C\ell_{p,q}$. The representation is based on Pauli matrices and has an elegant structure similar to the fractal geometry. We find two classes of representation, the normal representation and exceptional one. The normal representation is a large class of representation which can only be expanded into $4m+1$ dimension, but the exceptional representation can be expanded as generators of the next period. In the cases $p+q=4m$, the representation is unique in equivalent sense. These results are helpful for both theoretical analysis and practical calculation. The generators of Clifford algebra are the faithful basis of $p+q$ dimensional Minkowski space-time or Riemann space, and Clifford algebra converts the complicated relations in geometry into simple and concise algebraic operations, so the Riemann geometry expressed in Clifford algebra will be much simple and clear.

Most fully developed galaxies have vivid spiral structure, but the formation and evolution of spiral structure is still a mystery that is not fully understood in astrophysics. We find that the currently used equations of galactic dynamics contain some unreasonable components. In this paper, the following three working assumptions are introduced to simplify the galactic structural equations. 1. In the research of large-scale structure, the retarded potential of the gravitational field should be taken into account. The propagating time of the gravitational field from center to border is longer than the revolution periods of the stars near the center of galaxy. Newton's gravitational potential is unreasonable for such case, and the weak field and low velocity approximation of Einstein's field equation should be adopted. 2. The stars in a fully developed galaxy should be zero-pressure and inviscid fluid, and the equation of motion is different from that of ordinary continuum mechanics. Stars move along geodesics. 3. The structure of the galaxy is only related to the total mass density distribution. The equation of state of dark halo is different from that of ordinary luminous interstellar matter, so their trajectories are also very different. Dark halo and ordinary matter in galaxy are automatically separated. The total mass density distribution can be presupposed according to the observation data, and then it can be determined by comparing the solution of the equations with the observed data. These assumptions and treatments are supported by theory and observation. The variables of the equations of simplified galactic dynamics are separated from each other, and the equations are well-posed and can be solved according to a definite procedure. Therefore, this simplified dynamic equation system provides a more reasonable and practical framework for the further study of galactic structure, and can solve many practical problems. Besides, it is closely related to the study of dark energy and dark matter.

In this paper, we provide some enlightening examples of the application of Clifford algebra in geometry, which show the concise representation, simple calculation and profound insight of this algebra. The definition of Clifford algebra implies geometric concepts such as vector, length, angle, area and volume, and unifies the calculus of scalar, spinor, vector and tensor, so that it is able to naturally describe all variables and calculus in geometry and physics. Clifford algebra unifies and generalizes real number, complex, quaternion and vector algebra, converts complicated relations and operations into intuitive matrix algebra independent of coordinate systems. By localizing the basis or frame of space-time and introducing differential and connection operators, Clifford algebra also contains Riemann geometry. Clifford algebra provides a unified, standard, elegant and open language and tools for numerous complicated mathematical and physical theories. Clifford algebra calculus is an arithmetic-like operation that can be well understood by everyone. This feature is very useful for teaching purposes, and popularizing Clifford algebra in high schools and universities will greatly improve the efficiency of students to learn fundamental knowledge of mathematics and physics. So Clifford algebra can be expected to complete a new big synthesis of scientific knowledge.

In this work, we examined the effect of tropospheric emissions on tropospheric ozone (O₃) by conducting three-dimensional (3D) chemistry transport model (CTM) simulations. For the control run, the CTM model simulates tropospheric O₃ levels with a complete set of anthropogenic, biomass burning, and vegetation emissions [8]. For the no-emission simulation, all anthropogenic, biomass burning, and vegetation emissions were turned off. Comparisons of results from these two simulations exhibit the emission impacts on the tropospheric O₃. In the no-emission simulation, distinctive low surface O₃ with concentrations less than 5 ppbv prevail over the Amazon basin, tropical South America, tropical South Africa, Southeast Asia. Transport of air from these land areas downwind contributes to the low O₃ over the remote marine boundary layer. In contrast, elevated O₃ levels over the extra-tropical remote marine boundary layer are less supported by the anthropogenic and biomass burning emissions but more sustained by the downward transport of O₃ from the stratosphere. These results demonstrate that the northern hemisphere continental areas (north of 30^◦N ), polar regions, and tropical continental regions are more sensitive to the tropospheric emissions. The northern hemisphere winter is mostly dominated by the stratospheric processes, while the tropospheric emissions dominate over the southern hemisphere tropical continental areas from tropics to 30^◦S latitudinal bands. The northern hemisphere continental regions are increasingly dominated by tropospheric emissions from spring, to reach maxima in summer, and started to reduce in autumn months.

It is important for food recognition to separate each ingredient within a food image at the pixel level. In this paper, we propose a new approach to segment ingredients by utilizing a CNN-based Single-Ingredient Classification Model. In detail, we firstly introduce a standardized biological-based hierarchical ingredient structure and construct a single-ingredient image dataset based on this structure. Then, we build a single-ingredient classification model based on a novel convolutional neural network (CNN) architecture that utilizes an attention mechanism. Afterwards, we propose a new framework for segmentation using the above single-ingredient classification model as the backbone. In this framework, two methods are involved in segmenting ingredients in the food images. We introduce five evaluation metrics (IoU, Dice, Purity, Entirety, Loss of GTs) to assess the performance of ingredient segmentation in terms of ingredient classification. Extensive experiments demonstrate the effectiveness of the proposed method, achieving an maximal mIoU of 0.65, mDice of 0.77, mPurity of 0.83, mEntirety of 0.80, and mLoGTs of 0.06 on the FoodSeg103 dataset. The results confirm that our CNN-based architecture achieves higher segmentation performance compared to ResNet18 and EfficientNet-B0 when used as the backbone for ingredient segmentation. We believe that our ingredient segmentation approach lays the foundation for subsequent ingredient recognition.

Incident rates of neurodegenerative diseases have steadily increased globally, but there is no therapeutic access available. We newly prescribed medicinal herbal remedy including five different herbal plants called, Chen-Ma-Dan-Sam-Ga-Mi-Bang (CMST), purposed to prove for pharmacological properties and corresponded actions on hippocampus neuronal cell injury by hypoxia-induced mice model. Mice were adapted to normoxia or hypoxia with or without CMST for 5 days. We gathered pharmacological effects of CMST on cell injury by enhancement of dihydroethidium and 4-hydroxynonenal signals which were correlated with abnormal redox status in the protein or gene expression levels (abnormal elevations of nitric oxide, reactive oxygen species, lipid peroxidation and deteriorations of total glutathione, total antioxidant capacity, and activities of superoxide dismutase and catalase) due to hypoxia. CMST also notably exerted to attenuates molecules for neuronal cell injury markers such as p-tau, cleaved caspase-3 due to DNA oxidations (53bp1and phosphor-histone H2AX), inflammatory cytokines, and hemeoxigenase-1. We further figured out the underlying actions of CMST by in vitro experiment through inactivation of microglial cell which can mediate neuronal cell injury. Collectively, CMST prevented from hippocampal neuronal cells via inactivation of microglial cell with normalization of redox status on hypoxia-induced hippocampus neuronal cell injury.

We provide representations for the generalized Drazin inverse of an anti-triangular matrix of the form $\left( \begin{array}{cc} a&b\\ 1&0 \end{array} \right)$ in a Banach algebra $\mathcal{A}$, under the condition that $ab=ba$. Specifically, we present the representation of Drazin inverse for these types of anti-triangular matrices in Banach algebras.

We investigate the existence and representation of the generalized core-EP inverse of some triangular matrices over a Banach algebra. Further, the general representations of the generalized core-EP inverse of a triangular matrix over a $C^*$-algebra are presented. As applications, the generalized core-EP inverses of some block operator matrices over Hilbert spaces are given.

In this paper, we introduce the notion of the generalized $w$-group inverse in a Banach algebra with proper involution. This is a natural generalization of generalized (weak) group inverse in Banach *-algebras. Many elementary properties of such new weighted generalized inverse are presented. We further establish the equivalent relations between generalized weighted group inverse and weighted generalized Drazin inverse. Related properties of generalized (weak) group inverse are extended to the wider cases.