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The integration of micro-arc oxidation (MAO) film and chemical conversion (PCC) technology is a promising surface treatment for magnesium alloys. In this study, a MAO treatment of PCC film layers in a Na2SiO3 electrolyte system was used. The composition, structure, corrosion resistance, and formation mechanism of composite films were thoroughly investigated and discussed. Results showed that the composite-coated samples could effectively retard the corrosion of magnesium alloy. Additionally, the MAO treatment of zinc phosphate PCC coatings led to a reduction in pore size and enhanced coating compactness. The electrochemical test results showed that the composite coating has a higher impedance modulus in the low-frequency region (|Z|MAO/PCC-5 (2.38 × 105 Ω cm2) >|Z|MAO (1.31 × 104 Ω cm2) >|Z|PCC-5 (1.54 × 103 Ω cm2) >|Z|AZ91D (2.08 × 102 Ω cm2)), which improves the corrosion resistance of both the single MAO coating and the PCC coating. Meanwhile, the introduction of zinc effectively improves the antimicrobial properties of the coatings. This study provides a new idea for the preparation of anticorrosive and antimicrobial composite coatings on light metal surfaces. [ABSTRACT FROM AUTHOR]

To assess the agreement and repeatability of scotopic pupil size measurement using 2WIN-S (Adaptica, Padova, Italy) portable refractor in Chinese adults. This prospective non-randomized open-label controlled study assessed the scotopic pupil size of 100 right eyes using OPD-Scan III (Optical path difference) (Nidek Technologies, Gamagori, Japan) and 2WIN-S. OPD-Scan III and 2WIN-S measure pupil size using infrared light and detector, while 2WIN-S measures bilateral eyes simultaneously, OPD-Scan III measures unilateral eyes individually. Participants were first measured once using OPD-Scan III and two consecutive measurements were performed using 2WIN-S after 15 min of rest interval. The primary outcome was to evaluate the agreement between 2WIN-S and OPD-Scan III, and the secondary outcome was to evaluate the repeatability of 2WIN-S. Scotopic pupil size of 100 right eyes of 100 adults (28 male and 72 female) aged 18–53 years (mean 36 ± 12 years) was assessed using OPD-Scan III and 2WIN-S, respectively. The mean scotopic pupil size of OPD-Scan III and 2WIN-S was recorded to be 6.24 ± 0.88 mm and 6.27 ± 0.81 mm, respectively. For the mean scotopic pupil size of OPD-Scan III and 2WIN-S the difference was − 0.03 mm (95%CI − 0.10 to 0.04 mm), p = 0.445, the 95% limits of agreement (LOA) was − 0.71 to 0.66 mm. ICC between the two devices was 0.92 (95% CI 0.88–0.94) (ICC > 0.9 indicates excellent consistency). Coefficients of repeatability (CoR) of 2WIN-S was 0.37, which has a high repeatability. For the mean scotopic pupil size of 2WIN-S of the repeated measurements, the difference was -0.04 mm (95%CI − 0.08 to 0.01 mm), p = 0.019, the 95% limits of agreement (LOA) was − 0.41 to 0.32 mm, with a narrow LOA. However, the majority of the variations were less than ± 0.50 mm (98% of scotopic pupil size measurements were below this threshold), within the clinically acceptable range (± 0.50 mm). Our study showed excellent agreement between 2WIN-S and OPD-Scan III (ICC > 0.9) and a good repeatability of 2WIN-S (CoR = 0.37). This study suggests a novel technique for measuring pupillary responses in low light conditions, which can be considered an alternative to OPD-Scan III in clinical settings. [ABSTRACT FROM AUTHOR]

Spinal cord injury (SCI) is a serious disabling central nervous system injury that can lead to motor, sensory, and autonomic dysfunction below the injury level. SCI can be divided into primary injury and secondary injury according to pathological process. Primary injury is mostly irreversible, while secondary injury is a dynamic regulatory process. Apoptosis is an important pathological event of secondary injury and has a significant effect on the recovery of nerve function after SCI. Nerve cell death can further aggravate the microenvironment of the injured site, leading to neurological dysfunction and thus affect the clinical outcome of patients. Therefore, apoptosis plays a crucial role in the pathological progression of secondary SCI, while inhibiting apoptosis may be a promising therapeutic strategy for SCI. This review will summarize and explore the factors that lead to cell death after SCI, the influence of cross talk between signaling pathways and pathways involved in apoptosis and discuss the influence of apoptosis on SCI, and the therapeutic significance of targeting apoptosis on SCI. This review helps us to understand the role of apoptosis in secondary SCI and provides a theoretical basis for the treatment of SCI based on apoptosis. [ABSTRACT FROM AUTHOR]

Pedestrian detection in densely populated scenes, particularly in the presence of occlusions, remains a challenging issue in computer vision. Existing approaches often address detection leakage by enhancing model architectures or incorporating attention mechanisms; However, small-scale pedestrians have fewer features and are easily overfitted to the dataset and these approaches still face challenges in accurately detecting pedestrians with small target sizes. To tackle this issue, this research rethinks the occlusion region through small-scale pedestrian detection and proposes the You Only Look Once model for efficient pedestrian detection(YOLO-EPD). Firstly, we find that Standard Convolution and Dilated Convolution do not fit well with pedestrian targets with different scales due to a single receptive field, and we propose the Selective Content Aware Downsampling (SCAD) module, which is integrated into the backbone to attain enhanced feature extraction. In addition, to address the issue of missed detections resulting from insufficient feature extraction for small-scale pedestrian detection, we propose the Crowded Multi-Head Attention (CMHA) module, which makes full use of multi-layer information. Finally, for the challenge of optimizing the performance and effectiveness of small-object detection, we design Unified Channel-Task Distillation (UCTD) with channel attention and a Lightweight head (Lhead) using parameter sharing to keep it lightweight. Experimental results validate the superiority of YOLO-EPD, achieving a remarkable 91.1% Average Precision (AP) on the Widerperson dataset, while concurrently reducing parameters and computational overhead by 40%. The experimental findings demonstrate that YOLO-EPD greatly accelerates the convergence of model training and achieves better real-time performance in real-world dense scenarios. [ABSTRACT FROM AUTHOR]

Both atezolizumab (a PD-L1 inhibitor) plus bevacizumab (A+B) and sintilimab (a PD-1 inhibitor) plus bevacizumab (S+B) are recommended as the first-line regimen for advanced hepatocellular carcinoma (HCC) in China. Different efficacy between the two regimens combined with transvascular intervention for unresectable HCC (uHCC) remain unknown. We retrospectively analyzed uHCC patients treated in three centers by simultaneous combination of A+B or S+B with transarterial chemoembolization (TACE) and FOLFOX-based hepatic arterial infusion chemotherapy (HAIC). Objective response rate (ORR), progression-free survival (PFS), overall survival (OS) and treatment-related adverse events (TRAEs) were compared. Totally 188 patients were included, with 92 and 96 administered A+B+TACE-HAIC (ABTH) and S+B+TACE-HAIC (SBTH), respectively. ORRs (62.0 vs. 70.8%, respectively; P = 0.257) and disease control rates (88.0 vs. 93.8%, P = 0.267) were similar between groups by the mRECIST criteria. ABTH showed no survival advantage over SBTH, with median PFS times of 11.7 months and 13.0 months, respectively (HR = 0.81, 95% CI, 0.52–1.26, P = 0.35) and similar OS times (HR = 1.19, 95% CI, 0.32–4.39, P = 0.8). No significant differences were observed in grade 3–4 TRAEs between groups. Either PD-L1 or PD-1 inhibitor plus bevacizumab combined with TACE-HAIC have similarly excellent therapeutic efficacy with manageable adverse events, representing promising treatment options for uHCC. [ABSTRACT FROM AUTHOR]

The practices of prefabricated buildings illustrate the incentives in prefabricated markets as well as the decision-making behavior of stakeholders, which can influence the transformation, upgrading, and sustainability of the buildings sector. The game between the stakeholders in the prefabricated buildings market becomes complicated by the fact that they dynamically adjust their strategies in response to changing market conditions. With the aim of quantitatively studying the implications of the dynamic decision behavior of prefabricated construction stakeholders on the prefabricated construction market, this study introduces component suppliers as participating agents and government subsidies and penalties as the main measures. And a three-way model of the evolutionary game involving government subsidies and punitive schemes is constructed by this study. The essay examines the evolutionary equilibrium strategies of each game subject as well as the effect of original strategies and different parameter choices on the decision-making of each subject using MATLAB. The findings reveal that (1) decision-making behaviors among the government, component suppliers, and developers are both interrelated and constrained, but governments are the dominant agents in the evolution of prefabricated buildings. (2) Parameters such as subsidies, penalties, costs, and benefits affect the stability of the tripartite evolutionary model, which remains consistent with the previous research. (3) Component suppliers have an equally important position in the development of prefabricated buildings as recognized entities such as developers and contractors. (4) When subsidies are kept at 40% of the incremental cost and penalties at 80% of the incremental cost, the model combines a fast evolutionary rate with stable model evolution. In conclusion, the article's research findings not only validate the rationality and feasibility of component suppliers as research subjects and confirm the importance of component suppliers but also propose a more reasonable boundary value for penalties and subsidies, which provides a reference for the government to improve the incentive and punishment measures as well as the dynamic adjustment strategy of stakeholders and also provides a new perspective to achieve the goal of sustainable development of construction. [ABSTRACT FROM AUTHOR]

Coal-rock interface identification technology was pivotal in automatically adjusting the shearer's cutting drum during coal mining. However, it also served as a technical bottleneck hindering the advancement of intelligent coal mining. This study aimed to address the poor accuracy of current coal-rock identification technology on comprehensive working faces, coupled with the limited availability of coal-rock datasets. The loss function of the SegFormer model was enhanced, the model's hyperparameters and learning rate were adjusted, and an automatic recognition method was proposed for coal-rock interfaces based on FL-SegFormer. Additionally, an experimental platform was constructed to simulate the dusty environment during coal-rock cutting by the shearer, enabling the collection of coal-rock test image datasets. The morphology-based algorithms were employed to expand the coal-rock image datasets through image rotation, color dithering, and Gaussian noise injection so as to augment the diversity and applicability of the datasets. As a result, a coal-rock image dataset comprising 8424 samples was generated. The findings demonstrated that the FL-SegFormer model achieved a Mean Intersection over Union (MIoU) and mean pixel accuracy (MPA) of 97.72% and 98.83%, respectively. The FL-SegFormer model outperformed other models in terms of recognition accuracy, as evidenced by an MIoU exceeding 95.70% of the original image. Furthermore, the FL-SegFormer model using original coal-rock images was validated from No. 15205 working face of the Yulin test mine in northern Shaanxi. The calculated average error was only 1.77%, and the model operated at a rate of 46.96 frames per second, meeting the practical application and deployment requirements in underground settings. These results provided a theoretical foundation for achieving automatic and efficient mining with coal mining machines and the intelligent development of coal mines. [ABSTRACT FROM AUTHOR]

To emulate the ordered arrangement of monomer units found in natural macromolecules, single-unit monomer insertion (SUMI) have emerged as a potent technique for synthesizing sequence-controlled vinyl polymers. Specifically, numerous applications necessitate vinyl polymers encompassing both radically and cationically polymerizable monomers, posing a formidable challenge due to the distinct thiocarbonylthio end-groups required for efficient control over radical and cationic SUMIs. Herein, we present a breakthrough in the form of interconvertible radical and cationic SUMIs achieved through the manipulation of thiocarbonylthio end-groups. The transition from a trithiocarbonate (for radical SUMI) to a dithiocarbamate (for cationic SUMI) is successfully accomplished via a radical-promoted reaction with bis(thiocarbonyl) disulfide. Conversely, the reverse transformation utilizes the reaction between dithiocarbamate and bistrithiocarbonate disulfide under a cationic mechanism. Employing this strategy, we demonstrate a series of synthetic examples featuring discrete oligomers containing acrylate, maleimide, vinyl ether, and styrene, compositions unattainable through the SUMI of a single mechanism alone. To emulate the ordered arrangement of radically and cationically polymerizable monomers using single-unit monomer insertion (SUMI) remians challenging. Here the authors demonstrate sequence-defined vinyl polymers via SUMI by manipulating thiocarbonylthio end-groups. [ABSTRACT FROM AUTHOR]

Drawing on the dual-systems theory (DST), this study proposes a research model that focuses on how the characteristics of the key opinion leader influence consumers' purchase intention in live streaming commerce (LSC). We collected data through questionnaire surveys from samples of consumers in China (N = 467), which indicated that key opinion leader's characteristics (i.e., attractiveness, trustworthiness, expertise) are all positively related to purchase intention. Importantly, the mediator analyses indicated that the effect of systems 1 on the relationship between attractiveness and purchase intention persisted is persistent, regardless of the type of goods purchased by the consumers (utilitarian or hedonic). This finding highlights the importance of attractiveness and reveals unconscious thought (UT) of consumers when shopping in LSC. This study provides a new theoretical perspective (i.e., DST) to identify attractiveness as a determinant of purchase intention in LSC and influence purchase intention by activating systems 1, thus solving the problem of identifying key factors in stimulus–organism–response theory. Besides, our results identify and test UT in LSC. The practical implications of these findings are to provide guidance for the selection of key opinion leaders in LSC and the development of live streaming industry. [ABSTRACT FROM AUTHOR]

Objectives: To compare prostate-specific membrane antigen (PSMA) PET with multiparametric MRI (mpMRI) in the diagnosis of pretreatment prostate cancer (PCa). Methods: Pubmed, Embase, Medline, Web of Science, and Cochrane Library were searched for eligible studies published before June 22, 2022. We assessed risk of bias and applicability by using QUADAS-2 tool. Data synthesis was performed with Stata 17.0 software, using the "midas" and "meqrlogit" packages. Results: We included 29 articles focusing on primary cancer detection, 18 articles about primary staging, and two articles containing them both. For PSMA PET versus mpMRI in primary PCa detection, sensitivities and specificities in the per-patient analysis were 0.90 and 0.84 (p<0.0001), and 0.66 and 0.60 (p <0.0001), and in the per-lesion analysis they were 0.79 and 0.78 (p <0.0001), and 0.84 and 0.82 (p <0.0001). For the per-patient analysis of PSMA PET versus mpMRI in primary staging, sensitivities and specificities in extracapsular extension detection were 0.59 and 0.66 (p =0.005), and 0.79 and 0.76 (p =0.0074), and in seminal vesicle infiltration (SVI) detection they were 0.51 and 0.60 (p =0.0008), and 0.93 and 0.96 (p =0.0092). For PSMA PET versus mpMRI in lymph node metastasis (LNM) detection, sensitivities and specificities in the per-patient analysis were 0.68 and 0.46 (p <0.0001), and 0.91 and 0.90 (p =0.81), and in the per-lesion analysis they were 0.67 and 0.36 (p <0.0001), and 0.99 and 0.99 (p =0.18). Conclusion: PSMA PET has higher diagnostic value than mpMRI in the detection of primary PCa. Regarding the primary staging, mpMRI has potential advantages in SVI detection, while PSMA PET has relative advantages in LNM detection. Clinical relevance statement: The integration of prostate-specific membrane antigen (PSMA) PET into the diagnostic pathway may be helpful for improving the accuracy of prostate cancer detection. However, further studies are needed to address the cost implications and evaluate its utility in specific patient populations or clinical scenarios. Moreover, we recommend the combination of PSMA PET and mpMRI for cancer staging. Key Points: • Prostate-specific membrane antigen PET has higher sensitivity and specificity for primary tumor detection in prostate cancer compared to multiparametric MRI. • Prostate-specific membrane antigen PET also has significantly better sensitivity and specificity for lymph node metastases of prostate cancer compared to multiparametric MRI. • Multiparametric MRI has better accuracy for extracapsular extension and seminal vesicle infiltration compared to ate-specific membrane antigen PET. [ABSTRACT FROM AUTHOR]

We study Hill’s differential equation with potential expressed by elliptic functions which arises in some problems of physics and mathematics. Analytical method can be applied to study the local properties of the potential in asymptotic regions of the parameter space. The locations of the saddle points of the potential are determined, the locations of turning points can be determined too when they are close to a saddle point. Combined with the quadratic differential associated with the differential equation, these local data give a qualitative explanation for the asymptotic eigensolutions obtained recently. A relevant topic is about the generalisation of Floquet theorem for ODE with doubly-periodic elliptic function coefficient which bears some new features compared to the case of ODE with real valued singly-periodic coefficient. Beyond the local asymptotic regions, global properties of the elliptic potential are studied using numerical method. [ABSTRACT FROM AUTHOR]

Objectives: To develop an interactive, non-invasive artificial intelligence (AI) system for malignancy risk prediction in cystic renal lesions (CRLs). Methods: In this retrospective, multicenter diagnostic study, we evaluated 715 patients. An interactive geodesic-based 3D segmentation model was created for CRLs segmentation. A CRLs classification model was developed using spatial encoder temporal decoder (SETD) architecture. The classification model combines a 3D-ResNet50 network for extracting spatial features and a gated recurrent unit (GRU) network for decoding temporal features from multi-phase CT images. We assessed the segmentation model using sensitivity (SEN), specificity (SPE), intersection over union (IOU), and dice similarity (Dice) metrics. The classification model's performance was evaluated using the area under the receiver operator characteristic curve (AUC), accuracy score (ACC), and decision curve analysis (DCA). Results: From 2012 to 2023, we included 477 CRLs (median age, 57 [IQR: 48–65]; 173 men) in the training cohort, 226 CRLs (median age, 60 [IQR: 52–69]; 77 men) in the validation cohort, and 239 CRLs (median age, 59 [IQR: 53–69]; 95 men) in the testing cohort (external validation cohort 1, cohort 2, and cohort 3). The segmentation model and SETD classifier exhibited excellent performance in both validation (AUC = 0.973, ACC = 0.916, Dice = 0.847, IOU = 0.743, SEN = 0.840, SPE = 1.000) and testing datasets (AUC = 0.998, ACC = 0.988, Dice = 0.861, IOU = 0.762, SEN = 0.876, SPE = 1.000). Conclusion: The AI system demonstrated excellent benign-malignant discriminatory ability across both validation and testing datasets and illustrated improved clinical decision-making utility. Critical relevance statement: In this era when incidental CRLs are prevalent, this interactive, non-invasive AI system will facilitate accurate diagnosis of CRLs, reducing excessive follow-up and overtreatment. Key Points: The rising prevalence of CRLs necessitates better malignancy prediction strategies. The AI system demonstrated excellent diagnostic performance in identifying malignant CRL. The AI system illustrated improved clinical decision-making utility. [ABSTRACT FROM AUTHOR]

Background: Clear cell renal cell carcinoma (ccRCC), the most common pathological subtype of kidney cancer, accounts for approximately 70% to 80% of all cases. Histone deacetylase 10 (HDAC10) belongs to the HDAC class IIb subgroup, one of the histone deacetylases (HDAC) family. Previous studies suggest that HDAC10 may regulate the development of multiple tumor types. The specific molecular mechanisms employed by HDAC10 in the etiology of ccRCC still need to be discovered. Methods: The analysis included examining HDAC10 expression levels and their clinical importance within a cohort of inpatients and ccRCC patients documented in the Tumor Genome Atlas (TCGA). Moreover, the biological functions and underlying molecular mechanisms of HDAC10 were investigated. Results: HDAC10 showed increased expression in ccRCC tumor tissues. Subsequent analysis revealed overexpression of HDAC10 was associated with advanced clinical phenotype and unfavorable prognosis. The absence of HDAC10 significantly decreased ccRCC cell proliferation and migration capabilities. Mechanistic research suggests that HDAC10 may promote RCC development by activating the Notch-1 pathway and downregulating PTEN expression levels. Conclusion: In summary, HDAC10 can modulate critical biological processes in ccRCC, including proliferation, migration, and apoptosis. Notably, the Notch-1 pathway and PTEN serve as crucial signaling pathways and target genes through which HDAC10 regulates the progression of ccRCC. These findings offer a novel outlook for ccRCC treatment. [ABSTRACT FROM AUTHOR]

This paper presents a massively parallel approach of the multilevel fast multipole algorithm (PMLFMA) on homegrown many-core SW26010 cluster of China, noted as (SW-PMLFMA), for 3-D electromagnetic scattering problems. In this approach, the multilevel fast multipole algorithm (MLFMA) octree is first partitioned among management processing elements (MPEs) of SW26010 processors following the ternary partitioning scheme using the message passing interface (MPI). Then, the computationally intensive parts of the PMLFMA on each MPI process, matrix filling, aggregation and disaggregation are accelerated by using all the 64 computing processing elements (CPEs) in the same core group of the MPE via the Athread parallel programming model. Different parallelization strategies are designed for many-core accelerators to ensure a high computational throughput. In coincidence with the special characteristic of local Lagrange interpolation, the compressed sparse row (CSR) and the compressed sparse column (CSC) sparse matrix storage format is used for storing interpolation and anterpolation matrices, respectively, together with a specially designed cache mechanism of hybrid dynamic and static buffers using the scratchpad memory (SPM) to improve data access efficiency. Numerical results are included to demonstrate the efficiency and versatility of the proposed method. The proposed parallel scheme is shown to have excellent speedup. [ABSTRACT FROM AUTHOR]

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Informal status has strong positive implications in the field of organizational behavior, but it also has some harmful effects on individuals. Based on conservation of resources (COR) theory, this study constructs a model to explore the double-edged sword effect of informal status on employees' work procrastination behavior. A questionnaire survey of 202 employees was conducted at two time points, and analysis found that informal status can reduce work procrastination by enhancing employees' career calling, but it will also increase the workload of employees and in turn, increase work procrastination. In addition, the moderating effect of Zhongyong thinking was not significant, but, its pluralistic dimension of thinking strengthened the relationship between informal status and career calling. Contrariwise, the harmony dimension weakens the relationship between informal status and career calling and workload. The findings not only broaden and complement existing research in the field, but also have certain practical implications. [ABSTRACT FROM AUTHOR]

Objective: Sleep disorders such as insomnia, apnea, and restless leg syndrome can negatively affect a person's overall health and may cause hypertension, heart failure, and coronary heart disease. Likewise, periodontitis, a gum disease, can lead to both physical and psychological health issues, exerting a considerable effect on one's overall well-being—periodontitis stands as a primary cause of tooth loss. Nevertheless, there has been insufficient research on the correlation between the amount of sleep individuals get and the occurrence of periodontitis/tooth loss among Americans. Therefore, this study aimed to assess the influence of sleep length on periodontitis in the American population. Methods: Periodontitis severity was classified (none, mild, moderate, and severe) using American Periodontal Association criteria. Sleep duration was assessed by self-reported data and categorized into three groups (deficient, adequate, and excessive). Tooth loss was assessed by the oral examination. To establish a connection between the duration of sleep and periodontitis/tooth loss, a weighted multivariable logistic regression analysis was employed. A GAM analysis and smooth curve fitting assessment were conducted to identify non-linear relationships. Subgroup, interaction, and mediation analyses were also performed. Results: The prevalence of tooth loss was significantly high, affecting 96.4% of the individuals, whereas 46.6% of the study sample experienced moderate to severe periodontitis. The average age of participants was 52.7 years. After adjusting for potential confounding factors, the analysis of weighted multivariable logistic regression revealed a significant association between sleep insufficiency and moderate/severe periodontitis (OR 1.15, 95% CI 1.01–1.30, P = 0.0298), as well as tooth loss (OR 1.16, 95% CI 1.01–1.33, P = 0.0371). Additionally, the research showed a correlation between the length of sleep and periodontitis that followed a U-shaped pattern. In addition, the analysis of mediation revealed that high blood pressure explained 7.0% (95% CI 4.0% to 12.9%; P < 0.0001) of the link between the amount of sleep and the likelihood of losing teeth. Conclusion: Sleep duration was independently correlated with moderate/severe periodontitis/tooth loss and had a non-linear relationship. [ABSTRACT FROM AUTHOR]

Microblade assemblages are among the most common prehistoric archaeological materials found on the Tibetan Plateau (TP) and are thought to indicate large scale migration to and settlement of the TP. Few microblade sites, however, have been systematically excavated, especially in the remotest, highest-elevation regions of the TP. The timing of the large-scale arrival, spread, and permanent settlement of people on the TP therefore remains controversial. In this paper, we report on a recently excavated site, Locality 3 of the Nwya Devu Site (ND3), located at 4600 meters above sea level (masl), near the shore of Ngoin Lake, on the interior TP. Our analyses reveal a fairly typical microblade technological orientation and two types of microblade cores: wedge-shaped and semi-conical, which are similar to those found throughout North China. Using Optically Stimulated Luminescence (OSL) dating and AMS 14C dating, the age of ND3 ranges from 11 to 10 ka. This date range indicates ND3 is the oldest microblade site yet recorded in the remote, high-elevation regions of the TP and thus provides important information about when and how hunter-gatherers using microblades began exploiting the higher altitudes of the TP. Taken together, studies at ND3 and throughout the TP suggest that a microblade adaptation is associated with the first prolonged human occupation of the plateau and that microblades played a significant role in mediating the risks and facilitating the mobility necessary to permanently inhabit the TP. [ABSTRACT FROM AUTHOR]

At present, in addressing security challenges within 5 G-era Vehicular Ad-Hoc Networks (VANET), a new protocol has been designed in this paper, named V2X-GKA (Dynamic Group Authentication and Key Agreement Protocol based on C-V2X). V2X-GKA utilizes cryptographic techniques such as ECDLP and DBDH to effectively mitigate risks associated with certificate forgery and key theft. Through the integration of authentication and group key agreement mechanisms, the protocol facilitates dynamic member management and secure key updates without necessitating complete protocol re-execution. This approach not only ensures both forward and backward security but also optimizes algorithmic processes, rendering it highly suitable for real-time, high-speed mobile environments. Through necessary security analysis, it is confirmed that the V2X-GKA scheme in this paper meets the existing security objectives. Compared with other similar schemes, it exhibits a certain degree of completeness and superiority, particularly in open-channel scenarios. [ABSTRACT FROM AUTHOR]

Mid-infrared wavelength switchable and dual-wavelength random laser output has many potential applications. A polarization-maintaining random fiber Bragg grating (PMRFBG) array based on the photonic localization effect of longitudinal invariant transverse disorder in fiber structure is proposed, which can be used as random feedback of dual-wavelength and wavelength switchable output of random fiber laser (RFL). The random fiber Bragg grating (RFBG) array was designed on the panda-type polarization-maintaining fiber (PMF), and the two center wavelengths were 2 151.60 nm and 2 152.22 nm, respectively. The RFBG array was designed on the bow tie-type PMF, and the two center wavelengths were obtained, which were 2 153.08 nm and 2 153.96 nm, respectively. The RFBG array with a center wavelength of 2 139.27 nm was designed on single-mode fiber (SMF). The length of individual fiber Bragg grating (FBG) and PMRFBG, the refractive index modulation depth, the number of cascaded gratings, and the distance between gratings have different effects on the full width at half maximum (FWHM) and reflectance of the RFBG and PMRFBG array, but not on the central wavelength, as obtained by simulation using the transmission matrix method. The designed PMRFBG array provides theoretical support for the design of the feedback mechanism of RFL. [ABSTRACT FROM AUTHOR]

In this experiment, the eutrophication system was established by adding sucrose and yeast powder, and the pH and dissolved oxygen were measured in a bioreactor in real time to study the effect of aerobic environment on the fermentation process of Polygonati Rhizoma extract by Lactiplantibacillus plantarum. To further analyze metabolic changes, UPLC-Q-Exactive MS was used for metabolomic analysis and metabolic profiling. Multivariate analysis was performed using principal component analysis and Orthogonal projections to latent structures discriminant analysis. Finally, 313 differential metabolites were selected, 196 of which were annotated through database matching. After fermentation, the content of short-chain fatty acids, lactic acid, and their derivatives increased significantly, and there were 13 kinds and 4 kinds, respectively. Both compounds and their derivatives are beneficial to the intestinal flora. Consequently, incorporating L. plantarum into the aerobic fermentation process of Polygonati Rhizoma extract within the eutrophic system is potentially advantageous in enhancing the impact of its fermentation solution on the gut microbiota and its effects on human health. Our findings for this kind of edible and medicinal material research and development offer useful insights.Highlights: First report of polygonati Rhizoma fermentation in eutrophic bioreactor system. Fermentative components were characterized by UHPLC-QE-MS/MS and multi-data analysis. The different metabolites were obtained by comparing before and after fermentation. Short-chain fatty acids, lactic acid and their derivatives contents increased. [ABSTRACT FROM AUTHOR]

Intrusion detection in industrial control systems (ICS) is crucial for maintaining the security of physical information systems. However, the existing models predominantly rely on black-box approaches, which exhibit limitations in result credibility and the ability to adapt to complex and dynamic environments. Consequently, this paper proposes an online updatable extended belief rule base model (O-EBRB) for intrusion detection in ICS. Firstly, an industrial intrusion detection model rooted in the extended belief rule base (EBRB) is established. This model excels in concurrently processing both quantitative and qualitative data, ensuring the reliability of its outcomes. Subsequently, a novel domain-based rule update methodology for integrating new observation data is proposed. By incorporating or merging fresh data into the original model, it enhances the model's adaptability in dynamic settings. Finally, employing the domain-based rule weight calculation approach, the model continues to effectively compute model parameters even with the continuous expansion of rules. Through extensive experimentation on two real-world industrial intrusion detection datasets, the results demonstrate the effectiveness of the proposed model in handling information and its robust performance in dynamic environments. [ABSTRACT FROM AUTHOR]

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes. A study utilizing unsupervised deep learning to generate interpretable brain imaging phenotypes from brain T1 and T2-FLAIR MRI identified 97 genetic loci enhancing understanding of brain structure genetics. [ABSTRACT FROM AUTHOR]

Spatial transcriptomics has revolutionized the study of gene expression within tissues, while preserving spatial context. However, annotating spatial spots' biological identity remains a challenge. To tackle this, we introduce Pianno, a Bayesian framework automating structural semantics annotation based on marker genes. Comprehensive evaluations underscore Pianno's remarkable prowess in precisely annotating a wide array of spatial semantics, ranging from diverse anatomical structures to intricate tumor microenvironments, as well as in estimating cell type distributions, across data generated from various spatial transcriptomics platforms. Furthermore, Pianno, in conjunction with clustering approaches, uncovers a region- and species-specific excitatory neuron subtype in the deep layer 3 of the human neocortex, shedding light on cellular evolution in the human neocortex. Overall, Pianno equips researchers with a robust and efficient tool for annotating diverse biological structures, offering new perspectives on spatial transcriptomics data. Recognising spatial spots' biological identity in spatial transcriptomics remains a challenge. Here, authors introduce Pianno, a tool that helps annotate the biological structures or cell-type constructions across diverse tissues, offering new perspectives on understanding spatial transcriptomics. [ABSTRACT FROM AUTHOR]

To enhance the quality of tobacco leaves and optimize the smoking experience, diverse strains of functional bacteria and their associated metabolites have been used in tobacco aging. Exogenous cellulase additives are frequently employed to facilitate the degradation of cellulose and other macromolecular matrices and enhance the quality of the tobacco product. However, little is known about how microbial metabolites present in exogenous enzyme additives affect tobacco quality. In this study, crude cellulase solutions, produced by a tobacco-originating bacterium Bacillus subtilis FX-1 were employed on flue-cured tobacco. The incorporation of cellulase solutions resulted in the reduction of cellulose crystallinity in tobacco and the enhancement of the overall sensory quality of tobacco. Notably, tobacco treated with cellulase obtained from laboratory flask fermentation demonstrated superior scent and flavor attributes in comparison to tobacco treated with enzymes derived from industrial bioreactor fermentation. The targeted and untargeted metabolomic analysis revealed the presence of diverse flavor-related precursors and components in the cellulase additives, encompassing sugars, alcohols, amino acids, organic acids, and others. The majority of these metabolites exhibited significantly higher levels in the flask group compared to the bioreactor group, probably contributing to a pronounced enhancement in the sensory quality of tobacco. Our findings suggest that the utilization of metabolic products derived from B. subtilis FX-1 as additives in flue-cured tobacco holds promise as a viable approach for enhancing sensory attributes, establishing a solid theoretical foundation for the potential development of innovative tobacco aging additives. Cellulase solutions obtained from Bacillus subtilis FX-1, a bacterium originating from tobacco, were applied to flue-cured tobacco during the aging process. The cellulase structure of tobacco was analyzed using 13C cross-polarization magic angle spinning NMR spectroscopy. Sensory evaluation was utilized to assess the sensory attributes and quality characteristics. Targeted and untargeted metabolomics were utilized to investigate the chemical components present in the cellulase solutions. The inclusion of cellulase additives altered the cellulose structure in tobacco and introduced various flavor-related precursors and components. The utilization of cellulase additives derived from B. subtilis FX-1 substantially improved the overall quality of the tobacco product. [ABSTRACT FROM AUTHOR]

Constructing an artificial solid electrolyte interphase (SEI) on lithium metal electrodes is a promising approach to address the rampant growth of dangerous lithium morphologies (dendritic and dead Li0) and low Coulombic efficiency that plague development of lithium metal batteries, but how Li+ transport behavior in the SEI is coupled with mechanical properties remains unknown. We demonstrate here a facile and scalable solution-processed approach to form a Li3N-rich SEI with a phase-pure crystalline structure that minimizes the diffusion energy barrier of Li+ across the SEI. Compared with a polycrystalline Li3N SEI obtained from conventional practice, the phase-pure/single crystalline Li3N-rich SEI constitutes an interphase of high mechanical strength and low Li+ diffusion barrier. We elucidate the correlation among Li+ transference number, diffusion behavior, concentration gradient, and the stability of the lithium metal electrode by integrating phase field simulations with experiments. We demonstrate improved reversibility and charge/discharge cycling behaviors for both symmetric cells and full lithium-metal batteries constructed with this Li3N-rich SEI. These studies may cast new insight into the design and engineering of an ideal artificial SEI for stable and high-performance lithium metal batteries.Constructing an artificial solid electrolyte interphase to protect the lithium metal electrode is promising but challenging. Here, authors report a facile approach to form a layer to simultaneously overcome diffusion and advection-limited ion transport to achieve dendrite-free Li plating/stripping. [ABSTRACT FROM AUTHOR]

Mechanoluminescence (ML) sensing technologies open up new opportunities for intelligent sensors, self-powered displays and wearable devices. However, the emission efficiency of ML materials reported so far still fails to meet the growing application requirements due to the insufficiently understood mechano-to-photon conversion mechanism. Herein, we propose to quantify the ability of different phases to gain or lose electrons under friction (defined as triboelectric series), and reveal that the inorganic-organic interfacial triboelectricity is a key factor in determining the ML in inorganic-organic composites. A positive correlation between the difference in triboelectric series and the ML intensity is established in a series of composites, and a 20-fold increase in ML intensity is finally obtained by selecting an appropriate inorganic-organic combination. The interfacial triboelectricity-regulated ML is further demonstrated in multi-interface systems that include an inorganic phosphor-organic matrix and organic matrix-force applicator interfaces, and again confirmed by self-oxidization and reduction of emission centers under continuous mechanical stimulus. This work not only gives direct experimental evidences for the underlying mechanism of ML, but also provides guidelines for rationally designing high-efficiency ML materials. Mechanoluminescence enables sensing applications of mechanical stimuli. Here, the authors reveal the importance of interfacial triboelectricity to this phenomenon in inorganic-organic composite materials. [ABSTRACT FROM AUTHOR]

Microbubble reactors play an important role in the development of gas-liquid reaction process enhancement. However, the urgent demand for high efficiency and low energy consumption in gas-liquid reaction processes, as well as the trend towards large-scale production, have put forward higher requirements for the design and optimization of microbubble reactors. In this study, a self-priming microbubble reactor was designed and its structure parameters were optimized by (computational fluid dynamics) CFD simulations. Based on the grid division method combining structured and unstructured grids, the most suitable mesh number is selected, and the simulation calculation time is saved on the premise of ensuring the accuracy. The effects of five structural parameters on the gas content and energy loss was discussed and the optimal structural parameters of the microbubble reactor were determined as follows: the diffusion section length is 75 mm, the contraction angle is 22°, the diffusion angle is 10.5°, the inlet diameter of the gas phase is 6 mm, the inlet diameter of the liquid phase flowing into the gas chamber is 3 mm, the diffusion section inlet diameter is 5 mm. Under the condition of the same inlet flow rate, the outlet gas content of the optimized gas-liquid reactor is increased by 42.9% compared with the initial structure. In the wastewater treatment experiment, the microbubble reactor reduced the chemical oxygen demand of wastewater by 61% within three hours. This study provides significant references for the design of the self-priming microbubble reactor. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is an essential staple crop in China. Appropriate storage methods and technology are critical to ensure the quality of seed potatoes, which is closely related to the field performance. So far, the diffused light storage (DLS) technique has been widely applied to potato crop. In this paper, two special potato varieties ('Chuanyu 117' and 'Mira') were treated at DLS for 60 days, and the effects of growth conditions on tuber sprouts and subsequent field performance were evaluated. The results showed that the DLS treatment significantly promoted the greening of potato tubers from highland and simultaneously affected the average sprouting rate, sprout length and number of sprouts at different storage stages, which indicated obvious interacting correlations between DLS treatments and potato varieties. Especially for 'Mira', the shortest average sprout length (2.7 mm) was obtained under 40–200 lx light level, while 'Chuanyu 117' had the shortest average sprout length (1.3 mm) under 5–10 lx and its sprout length was also controlled within 2.3 mm under 200–2000 lx. In the cultivation experiment that followed, the potato tubers with 4–6 mm and 2–3 mm sprout length had the highest yield after 90 days and 110 days planting, respectively. Overall, these results demonstrated that for seed potatoes harvested from the highland area followed by storing for 30 days in the lowland, the sprout length can be better controlled at 2–3 mm to obtain short and strong sprouts when stored under 40–200 lx or 200–2000 lx diffused light for 60 days, which is especially suitable in terms of fast field emergence after planting and final tuber yield for the autumn and winter cultivation of potato in the Chengdu Plain. It is also suggested that the DLS technique on seed potatoes could be used in the mixed single and double-cropping areas in Sichuan and other areas with similar geographical and climatic conditions. The findings of this study have several important implications in the storage, transportation, processing as well as seed potato market for commercial practice. [ABSTRACT FROM AUTHOR]

To enhance the fire safety and wear resistance of epoxy, phosphorus-containing nickel phyllosilicate whiskers (FP-NiPS) were synthesized using a facile hydrothermal technology, with 9,10-dihydro-9-oxa-10-phosphaphenanthrene as the organic modifier. The impacts of FP-NiPS on the thermal stability, flame retardancy, and mechanical and tribological properties of EP composites were explored. The findings demonstrated that 5 wt % FP-NiPS elevated the limiting oxygen index of the EP composite from 23.8% to 28.4%, achieving a V-0 rating during vertical burning tests. FP-NiPS could enhance the thermal stability of epoxy resin (EP) and facilitate the development of a dense and continuous carbon layer, thereby significantly improving the fire safety of the EP composites. The FP-NiPS led to an 8.2% increase in the tensile strength and a 38.8% increase in the elastic modulus of the EP composite, showing outstanding mechanical properties. Furthermore, FP-NiPS showed remarkable potential in enhancing the wear resistance of EP. The wear rate of 1 wt % FP-NiPS is 2.34 × 10−5 mm3·N−1·m−1, a decrease of 66.7% compared to EP. This work provides a novel promising modification method to enhance the fire safety, mechanical and wear resistance properties of EP. [ABSTRACT FROM AUTHOR]

Due to the harsh operating environment and ultralong operating hours of wireless sensor networks (WSNs), node failures are inevitable. Ensuring the reliability of the data collected by the WSN necessitates the utmost importance of diagnosing faults in nodes within the WSN. Typically, the initial step in the fault diagnosis of WSN nodes involves extracting numerical features from neighboring nodes. A solitary data feature is often assigned a high weight, resulting in the failure to effectively distinguish between all types of faults. Therefore, this study introduces an enhanced variant of the traditional belief rule base (BRB), called the belief rule base with adaptive attribute weights (BRB-AAW). First, the data features are extracted as input attributes for the model. Second, a fault diagnosis model for WSN nodes, incorporating BRB-AAW, is established by integrating parameters initialized by expert knowledge with the extracted data features. Third, to optimize the model's initial parameters, the projection covariance matrix adaptive evolution strategy (P-CMA-ES) algorithm is employed. Finally, a comprehensive case study is designed to verify the accuracy and effectiveness of the proposed method. The results of the case study indicate that compared with the traditional BRB method, the accuracy of the proposed model in WSN node fault diagnosis is significantly improved. [ABSTRACT FROM AUTHOR]

With the advancement of technology, the demand for increased production efficiency has gradually risen, leading to the emergence of new trends in agricultural automation and intelligence. Precision classification models play a crucial role in helping farmers accurately identify, classify, and process various agricultural products, thereby enhancing production efficiency and maximizing the economic value of agricultural products. The current MobileNetV2 network model is capable of performing the aforementioned tasks. However, it tends to exhibit recognition biases when identifying different subcategories within agricultural product varieties. To address this challenge, this paper introduces an improved MobileNetV2 convolutional neural network model. Firstly, inspired by the Inception module in GoogLeNet, we combine the improved Inception module with the original residual module, innovatively proposing a new Res-Inception module. Additionally, to further enhance the model's accuracy in detection tasks, we introduce an efficient multi-scale cross-space learning module (EMA) and embed it into the backbone structure of the network. Experimental results on the Fruit-360 dataset demonstrate that the improved MobileNetV2 outperforms the original MobileNetV2 in agricultural product classification tasks, with an accuracy increase of 1.86%. [ABSTRACT FROM AUTHOR]

In response to the personalized needs of the tourism industry, intelligent tourism planning services should be adopted. Through artificial intelligence and Big data technology, users' travel preferences, time, budget and other information are analyzed and mined in depth to provide users with more suitable travel routes and services. Therefore, according to the demand of tourist path recommendation in cultural scenic spots, this paper proposes a light sensor positioning method based on deep learning algorithm. This paper expounds the advantages of using optical sensor positioning for path recommendation, and describes the specific steps and processes of the optical sensor positioning method based on deep learning algorithm in detail. Finally, the feasibility and effect of this method are verified by experiments and data analysis. The results show that the localization of light sensor based on deep learning algorithm has high accuracy and practicability in the travel path recommendation of cultural scenic spots. Therefore, this method can provide accurate and reasonable path recommendation for tourists in cultural scenic spots and improve tourism experience and benefits. With the continuous development of the tourism market and the changing needs of users, this personalized tourism route planning and recommendation system will be increasingly widely applied and promoted. [ABSTRACT FROM AUTHOR]

Microstructure evolution and growth kinetics of intermetallic compound (IMC) in Sn-3Ag-0.5Cu (SAC305) /Ag and SAC305/Cu solder joints were investigated during isothermal aging at temperatures of 140, 160, and 180 °C for up to 528 h. Top-view and cross-sectional images were analyzed to elucidate the transformation processes of Cu6Sn5 and Ag3Sn grains on Cu and Ag substrates, respectively. In the top-view images, the Cu6Sn5 grains on the Cu substrate, initially exhibiting a scallop-type morphology after reflow, transformed into hexagonal-type grains during isothermal aging. In contrast, the Ag3Sn grains formed on Ag substrate, characterized by a prism-type morphology after reflow, underwent a process of transformation from scallop-type to hexagonal-type grains. The cross-sectional images revealed the formation of a planar-type IMC layer on both the Ag and Cu substrates. In the SAC305/Cu joint, after the aging time, a double-layer structure was seen in the way of bottom Cu3Sn layer and top Cu6Sn5 layer outside with many Ag3Sn tiny particles. However, in the condition of SAC305/Ag joint, only a few Cu6Sn5 particles were observed around the surface of the Ag3Sn IMC with a single layer. Kinetic analyses showed that the control mechanism for IMC growth on both substrates was volume diffusion and the apparent activation energies for the IMC growth were calculated as 89.641 kJ/mol for the SAC305/Ag joint and 97.082 kJ/mol for the SAC305/Cu joint. [ABSTRACT FROM AUTHOR]

Soybean plants regulate morphology and carbohydrate metabolism for growth adaptation when leaves receive low red/far-red (R/Fr) and blue light (B) under shading. In this study, we assessed the effects of shoot morphology and trehalose-6-phosphate (Tre6P) metabolism on soybean growth under different combinations of R/Fr and B light. Soybean plants were treated with low and high light intensities of 200 and 400 µmol m−2 s−1, respectively, in combination with white light (W) and three levels of R/Fr + B. After 30 days, we conducted morphological measurements and determined Tre6P metabolism in leaves and transcriptomics in stems. Soybean seedlings grown under R76/Fr48 + B76 had higher Tre6P content, lower trehalose 6-phosphate phosphatase (TPP) activity in leaves, and significantly longer second petioles than those grown under R100/Fr10 + B90. Tre6P was stored in leaves under R76/Fr48 + B76 treatment, thereby contributing to photosynthate allocation into the second petiole elongation. Compared to stems under R100/Fr10 + B90, those under R76/Fr48 + B76 showed enhanced trehalose biosynthesis, which reduced Tre6P content and limited stem elongation to support the stems. Stems under R50/Fr100 + B250 and R25/Fr50 + B125 had significantly elongated first and second petioles compared with those under W400 and W200, respectively. However, soybean plants under R25/Fr50 + B125 showed inhibited stem apex growth and had no third leaf. Soybean plants responded to R/Fr- and B-light exposure, thus regulating Tre6P metabolism to improve petiole elongation when R/Fr decreased from 10 to 2 under low light intensity. Under shade, increasing the B-light intensity (R/Fr = 0.5) inhibited stem apex growth and increased petiole length, to prompt leaves to capture light. [ABSTRACT FROM AUTHOR]

Temperature-responsive polymers have garnered significant attention due to their ability to respond to external stimuli. In this work, dual temperature-responsive block copolymers are synthesized via reversible addition-fragmentation chain transfer polymerization (RAFT) polymerization utilizing zwitterionic monomer methacryloyl ethyl sulfobetaine (SBMA) and N-isopropyl acrylamide (NIPAAm) as monomers. The thermal responsive behaviors can be easily modulated by incorporating additional hydrophobic monomer benzyl acrylate (BN) or hydrophilic monomer acrylic acid (AA), adjusting concentration or pH, or varying the degree of polymerization of the block chain segments. The cloud points of the copolymers are determined by UV-Vis spectrophotometry, and these copolymers exhibit both controlled upper and lower critical solubility temperatures (LCST and UCST) in aqueous solution. This study analyzes and summarizes the influencing factors of dual temperature responsive block copolymers by exploring the effects of various conditions on the phase transition temperature of temperature-sensitive polymers to explore the relationship between their properties and environment and structure to make them more selective in terms of temperature application range and regulation laws. It is very interesting that the introduction of poly-acrylic acid (PAA) segments in the middle of di-block copolymer PSBMA55-b-PNIPAAm80 to form PSBMA55-b-PAAx-b-PNIPAAm80 results in a reversal of temperature-responsive behaviors from 'U' (LCST < UCST) to 'n' (LCST > UCST) type, while the copolymer PSBMA55-b-P(NIPAAm80-co-AAx) not. This work provides a clue for tuning the phase transition behavior of polymers for manufacture of extreme smart materials. [ABSTRACT FROM AUTHOR]

The timing and mechanisms of the human occupation of the demanding high-altitude Tibetan Plateau environment are of great interest. Here, we report on our reinvestigations and dating of the Nwya Devu site, located nearly 4600 meters above sea level on the central Tibetan Plateau. A new microblade techno-complex was identified on a lower lake shore at this site, distinct from the previously reported blade tool assemblage. These two lithic assemblages were dated to 45.6±2.6 and 10.3±0.5 ka using optically stimulated luminescence and accelerator mass spectrometry 14C methods. They represent, respectively, the earliest known Paleolithic and microlithic sites on the interior Tibetan Plateau, indicating multiple occupation episodes of hunter-gatherers during the past 45 ka. Our studies reveal that relatively stable depositional conditions and a paleoenvironment characterized by a comparatively warm climate facilitated these multiple occupations at Nwya Devu. The contemporaneous occurrence of the Upper Paleolithic blade technology on the Tibetan Plateau and most of Eurasia between 50 and 40 ka indicates rapid, large-scale dispersals of humans that profoundly affected human demography on a large scale. Combining new archaeological evidence and previously reported genetic data, we conclude that the Tibetan Plateau provided a relatively stable habitat for Upper Paleolithic hunter-gatherers, which may have contributed to the complex and multiple-origin gene pool of present-day Tibetans. [ABSTRACT FROM AUTHOR]

Health condition assessment is the basis for formulating and optimizing maintenance strategies of complex systems, which is crucial for ensuring the safe and stable operation of these systems. In complex system health condition assessment, it is not only necessary for the model to handle various uncertainties to ensure the accuracy of assessment results, but also to have a transparent and reasonable assessment process and interpretable, traceable assessment results. belief rule base (BRB) has been widely used as an interpretable modeling method in health condition assessment. However, BRB-based models currently face two issues: (1) inaccuracies in expert-provided parameters that can affect the model's accuracy, and (2) after model optimization, interpretability may be reduced. Therefore, this paper proposes a new method for complex system health condition assessment called interpretable BRB with reference value optimization (I-BRB). Firstly, to address the issue of inaccurate reference values, a reference value optimization algorithm with interpretability constraints is designed, which optimizes the reference values without compromising expert knowledge. Secondly, the remaining parameters are optimized using the projection covariance matrix adaptation evolution strategy (P-CMA-ES) with interpretability constraints to improve the model's accuracy. Finally, a case study evaluating the bearing components of a flywheel system is conducted to validate the proposed method. Experimental results demonstrate that I-BRB achieves higher accuracy in health condition assessment. [ABSTRACT FROM AUTHOR]

Anomaly detection for multivariate time series has been widely used in industry and has become one of the hot research problems in the field of data mining. However, the existing anomaly detection methods still have the following limitations: (1) The topological relationship between sensors is complex and nonlinear, and it is difficult to effectively model the inter-sensor dependencies. (2) Most anomaly detection models tend to ignore the critical temporal information in different time steps when capturing the temporal dependencies. To address these problems, we propose a hybrid graph transformer network for multivariate time series anomaly detection (HGTMAD), which combines the transformer with graph convolution to predict multivariate time series-based anomalies. In the time domain, we design a new sparse metric transformer network to capture the time dependence, where the Wasserstein distance is used to measure out significant dot product pairs to learn a better time series representation. In the spatial domain, we design a new channel convolution transformer network fused with a graph convolution network to learn accurately the complex dependencies of multivariate time series in spatial and on feature dimensions based on a combination of local and global approaches. Extensive experiments on publicly available datasets further demonstrate that the proposed HGTMAD significantly outperforms the mainstream state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The eco-friendly PAA/Zn2+ conversion coatings, composed of PAA-Zn2+ complex and ZnO/Zn(OH)2, have been prepared by taking advantage of coordination-driven assembly method for suppressing steel corrosion. Because of high affinity of PAA for steel surface and various metal ions, metal ions-assisted organic molecule assembly strategy used to construct chemical conversion film on metal surface has been extended to the design and construction of polyelectrolyte–metal complex conversion coating. In this work, some film properties associated closely with film formation time containing corrosion resistance, surface microstructures, and chemical compositions were carefully investigated by using electrochemical measurements, morphologies tests, and spectra analysis and possible film-forming mechanism of PAA/Zn2+ film was proposed. The highest charge transfer resistance (Rct = 24,960 ohm cm2) was recorded for PAA/Zn2+ film based on EIS, which is about 30 times higher than that of the bare steel. And minimum corrosion current density (icorr = 1.01 × 10-7 A cm-2) was obtained for PAA/Zn2+ film from polarization curves, which is only 3.34% of that obtained from bare steel. Herein, the PAA/Zn2+ conversion coatings constructed between 30 and 60 min present outstanding corrosion resistance performance and the protection efficiencies are greater than 90%. Furthermore, PAA/Zn2+ films have a positive effect on improvement in adhesion of epoxy coating on steel surface, which can further improve corrosion resistance of whole paint system, especially for PAA/Zn2+ films fabricated for long film formation time (e.g., 30 min and 45 min). Due to environmental friendliness, strong corrosion resistance, and good adhesion performance, PAA/Zn2+ conversion coatings are expected to be an ideal substitute for the traditional chromating process. [ABSTRACT FROM AUTHOR]

During our studies on the microorganism diversity from air of manufacturing shop in a pharmaceutical factory in Shandong province, China, a Gram-stain-positive, aerobic, cocci-shaped bacterium, designated LY-0111T, was isolated from a settling dish. Strain LY-0111T grew at temperature of 10–42 °C (optimum 35 °C), pH of 5.0–10.0 (optimum pH 7.0) and NaCl concentration of 1–12% (optimum 0.5–3%, w/v). Based on the 16S rRNA gene sequence analysis, the strain shared the highest sequence similarities to Nesterenkonia halophila YIM 70179T (96.2%), and was placed within the radiation of Nesterenkonia species in the phylogenetic trees. The genome of the isolate was sequenced, which comprised 2,931,270 bp with G + C content of 66.5%. A supermatrix tree based on the gene set bac120 indicated that LY-0111T was close related to Nesterenkonia xinjiangensis YIM 70097T (16S rRNA gene sequence similarity 95.3%). Chemotaxonomic analysis indicated that the main respiratory quinones were MK-7, MK-8, and MK-9, the predominant cellular fatty acids were anteiso-C15:0 and iso-C15:0, and the major polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol and phosphatidylinositol. According to the phenotypic, chemotaxonomic and phylogenetic features, strain LY-0111T is considered to represent a novel species, for which the name Nesterenkonia aerolata sp. nov. is proposed. The type strain is LY-0111T (= JCM 36375T = GDMCC 1.3945T). In addition, Nesterenkonia jeotgali was proposed as a later synonym of Nesterenkonia sandarakina, according to the ANI (96.8%) and dDDH (72.9%) analysis between them. [ABSTRACT FROM AUTHOR]

Language is an advanced cognitive function of humans, and verbs play a crucial role in language. To understand how the human brain represents verbs, it is critical to analyze what knowledge humans have about verbs. Thus, several verb feature datasets have been developed in different languages such as English, Spanish, and German. However, there is still a lack of a dataset of Chinese verbs. In this study, we developed a semantic feature dataset of 1140 Chinese Mandarin verbs (CVFD) with 11 dimensions including verb familiarity, agentive subject, patient, action effector, perceptual modality, instrumentality, emotional valence, action imageability, action complexity, action intensity, and the usage scenario of action. We calculated the semantic features of each verb and the correlation between dimensions. We also compared the difference between action, mental, and other verbs and gave some examples about how to use CVFD to classify verbs according to different dimensions. Finally, we discussed the potential applications of CVFD in the fields of neuroscience, psycholinguistics, cultural differences, and artificial intelligence. All the data can be found at https://osf.io/pv29z/. [ABSTRACT FROM AUTHOR]