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This study introduces a novel Blind Image Quality Assessment (BIQA) approach leveraging a multi-stream spatial and channel attention model. Our method addresses challenges posed by diverse image content and distortions by integrating feature maps from two distinct backbones. Through spatial and channel attention mechanisms, our algorithm prioritizes regions of interest, enhancing its ability to capture crucial image details. Extensive evaluations on four benchmark datasets demonstrate superior performance compared to existing methods, closely aligning with human perceptual assessment. Our approach exhibits exceptional generalization capabilities on both authentic and synthetic distortion databases. Moreover, it demonstrates a distinctive focus on perceptual foreground information, enhancing its practical applicability. Thorough quantitative analyses underscore the algorithm's superior performance, establishing its dominance over existing methods., (© 2024. The Author(s).)

Impulse waves are generated by rapid subaerial mass movements including landslides, avalanches and glacier break-offs, which pose a potential risk to public facilities and residents along the shore of natural lakes or engineered reservoirs. Therefore, the prediction and assessment of impulse waves are of considerable importance to practical engineering. Tsunami Squares, as a meshless numerical method based on a hybrid Eulerian-Lagrangian algorithm, have focused on the simulation of landslide-generated impulse waves. An updated numerical scheme referred to as Tsunami Squares Leapfrog, was developed which contains a new smooth function able to achieve space and time convergence tests as well as the Leapfrog time integration method enabling second-order accuracy. The updated scheme shows improved performance due to a lower wave decay rate per unit propagation distance compared to the original implementation of Tsunami Squares. A systematic benchmark testing of the updated scheme was conducted by simulating the run-up, reflection and overland flow of solitary waves along a slope for various initial wave amplitudes, water depths and slope angles. For run-up, the updated scheme shows good performance when the initial relative wave amplitude is smaller than 0.4. Otherwise, the model tends to underestimate the run-up height for mild slopes, while an overestimation is observed for steeper slopes. With respect to overland flow, the prediction error of the maximum flow height can be limited to ± 50% within a 90% confidence interval. However, the prediction of the front propagation velocity can only be controlled to ± 100% within a 90% confidence interval. Furthermore, a sensitivity analysis of the dynamic friction coefficient of water was performed and a suggested range from 0.01 to 0.1 was given for reference., (© 2024. The Author(s).)

Magnetoelectric materials which simultaneously exhibit electric polarization and magnetism have attracted more and more attention due to their novel physical properties and promising applications for next-generation devices. Exploring new materials with outstanding magnetoelectric performance, especially the manipulation of magnetization by electric field, is of great importance. Here, we demonstrate the cross-coupling between magnetic and electric orders in polycrystalline Co4Nb2O9, in which not only magnetic-field-induced electric polarization but also electric field control of magnetism is observed. These results reveal rich physical phenomenon and potential applications in this compound. [ABSTRACT FROM AUTHOR]

Bulk ultrafine grained (UFG)/nanocrystal metals possess exceptional strength but normally poor ductility and thermal stability, which hinder their practical applications especially in high-temperature environments. Through microalloying strategy that enables the control of grains and precipitations in nanostructured regime, here we design and successfully produce a highly microstructure-stable UFG Al-Cu-Sc alloy with ~275% increment in ductility and simultaneously ~50% enhancement in yield strength compared with its Sc-free counterpart. Although the precipitations in UFG alloys are usually preferentially occurred at grain boundaries even at room temperature, minor Sc addition into the UFG Al-Cu alloys is found to effectively stabilize the as-processed microstructure, strongly suppress the θ-Al2Cu phase precipitation at grain boundary, and remarkably promote the θ'-Al2Cu nanoparticles dispersed in the grain interior in artificial aging. A similar microalloying strategy is expected to be equally effective for other UFG heat-treatable alloys. [ABSTRACT FROM AUTHOR]

The objective of this study was to examine the relationships among environmental and health values, ecological worldview, perception of consequences, the ascription of responsibility, and personal norms in the context of the value-belief-norm (VBN) model and how compatibility influences the intentions and behaviors of Chinese youth regarding the use of hydroponic farming technology. The study employed a survey questionnaire to collect data from the target population. The sample size was determined through a power analysis to ensure sufficient statistical power for the analysis. A total of 727 potential respondents' responses were analyzed using SmartPLS (4.0) to perform structural equation modeling. The results confirmed that environmental, emotional, and health values significantly associated with individuals' ecological worldviews. There was an interconnection between ecological worldview, awareness of consequences, and ascription of responsibility, and all three significantly influenced personal norms. The key determinants of the intentions and behaviors to adopt hydroponic farming technology are personal norms and technology compatibility. Therefore, to promote and motivate the interest and intention to use hydroponics among unemployed youth, government agencies, and related companies should focus on providing technology-related and pro-environmental information and training. This is expected to increase the acceptance and awareness of hydroponics among this group, thus increasing the adoption rate of hydroponics., (© 2024. The Author(s).)

Investigating how human disturbance affects the ecosystem service scarcity value (ESSV) is crucial for maintaining ecosystem stability and achieving sustainable development goals (SDGs). This study separately assessed ESSV and human disturbance in Guangxi from 1990 to 2020, revealing their spatiotemporal distribution differences over time. The environmental Kuznets curve (EKC) is used to analyze the interrelationship between the two, with the purpose of filling the gap in current research. The main results are as follows: (1) From 1990 to 2020, ESSV in Guangxi increased significantly and reached its highest value in 2020. Under the four scenarios, ESSV increased significantly in Scenarios 2 and 4. Spatially, high ESSV was mainly distributed in some cities in central, southern, western and northeastern Guangxi. (2) The index of human disturbance in Guangxi continued to increase during the study period, with a high level of human disturbance in the central urban area and a low level of human disturbance in the peripheral areas, which were distributed in a radial pattern. (3) According to the EKC, the relationship between ESSV and human disturbance in Guangxi followed an inverted N-shaped curve. In addition, after 2010, the coupling and coordination level was dominated by "slightly balanced development", and the area of "ESSV significantly lagged" gradually increased. This study provides a new perspective for understanding ESSV and its relationship with human disturbances, and provides an important reference for the sustainable management of ecosystems and the formulation of ecological conservation policies. [ABSTRACT FROM AUTHOR]

This work investigates the efficiency of green-synthesized WO3 nanoflakes for the removal of methylene blue dye. The synthesis of WO3 nanoflakes using Hyphaene thebaica fruit extract results in a material with a specific surface area of 13 m2/g and an average pore size of 19.3 nm. A combined theoretical and experimental study exhibits a complete understanding of the MB adsorption mechanism onto WO3 nanoflakes. Adsorption studies revealed a maximum methylene blue adsorption capacity of 78.14 mg/g. The pseudo-second-order model was the best to describe the adsorption kinetics with a correlation coefficient (R2) of 0.99, suggesting chemisorption. The intra-particle diffusion study supported a two-stage process involving surface adsorption and intra-particle diffusion. Molecular dynamic simulations confirmes the electrostatic attraction mechanism between MB and the (002) WO3 surface, with the most favorable adsorption energy calculated as -0.68 eV. The electrokinetic study confirmed that the WO3 nanoflakes have a strongly negative zeta potential of -31.5 mV and a uniform particle size of around 510 nm. The analysis of adsorption isotherms exhibits a complex adsorption mechanism between WO3 and MB, involving both electrostatic attraction and physical adsorption. The WO3 nanoflakes maintained 90% of their adsorption efficiency after five cycles, according to the reusability tests. [ABSTRACT FROM AUTHOR]

With buildings representing a substantial portion of global energy consumption, exploring alternatives to traditional fossil fuel-based heating and cooling systems is critical. Thermoelectricity offers a promising solution by converting temperature differentials into electrical voltage or vice versa, enabling efficient indoor thermal regulation. This paper presents a comprehensive investigation into the integration of thermoelectric wall systems for sustainable building climate control through numerical simulations and experimental analyses. Numerical simulations using computational fluid dynamics (CFD) techniques were conducted to model fluid flow and heat transfer within the thermoelectric wall systems under various operating conditions. These simulations provided insights into the system's thermal behavior, which were validated through experimental setups designed to measure temperature differentials, airflow rates, and power consumption. The results showed that power consumption is directly correlated with electrical current, ranging from 0.19 W to 77.4 W as the current increased from 0.1 A to 2 A. Additionally, the heat absorbed by the system increased significantly with electrical current, by 706–1044%, depending on the air velocity. The thermal energy released from the hot side of the thermoelectric modules also rose substantially, ranging from 9850 to 5285% with increasing electrical current, and from 275 to 51% with higher air velocities. Moreover, increasing air velocity led to a 6.78–9.37% reduction in power consumption for currents between 0.1 A and 2 A. The coefficient of performance (COP) analysis revealed that optimizing both electrical current and air velocity is essential for maximizing system efficiency. While fan power consumption reduces COP at higher air velocities, neglecting fan power consumption results in COP improvements ranging from 6.5 × 10⁻⁴ to 49.0%. These findings highlight the potential of thermoelectric wall systems to enhance indoor comfort and energy efficiency in buildings. [ABSTRACT FROM AUTHOR]

High altitude is characterized by low oxygen, low pressure, and high radiation. When migrates from low to high altitudes, the body's tissues and organs experience hypoxic stress and will present acoustic adaptation as the protective response. However, the mechanisms of acoustic adaptation at high altitudes remain unclear. In this study, cochlear tissues from Wistar rats were collected at 15, 30, 60, 120, and 180 days after high-altitude migration. Transcriptome sequencing was conducted and DESeq algorithm revealed expression patterns of Differentially Expressed Genes(DEGs) after high altitude migration. Day 60 is a critical stage for cochlear tissue "damage" and "repair" in high-altitude conditions. Transmission Electron Microscopy (TEM) observations of structures also support the findings. A time-series gene co-expression network algorithm was used to investigate gene regulatory patterns and key genes after migration. Immunofluorescence, immunohistochemistry, and qPCR were per-formed for key gene validation and localization. At Day 60, the peak DEG count occurs in rats migrating to high altitude, aligning with the critical phase for cochlear tissue damage and repair at high altitudes. Repair hinges on synaptic plasticity and myelination-linked processes, influencing modules M4 to M6. Module M4's activation gradually diminishes from its peak. However, the 'damage' effect is orchestrated by inflammation-related processes in modules M3 to M5, with module M3's activation also waning. Key gene module M4, pivotal for repair during this pivotal phase, encompasses Sptbn5, Cldn1, Gfra2, and Lims2 as its core genes. Immunohistochemistry reveals Sptbn5's presence in cochlear neurons, hair cells, Schwann cells and stria vascularis tissue. Cldn1 and Gfra2 predominantly localize within the cochlear neuron region. These results may suggest new directions for future research on acoustic acclimatization to high altitude. [ABSTRACT FROM AUTHOR]

A new control approach based on fuzzy sliding mode control (FSMC) is proposed to regulate the chaotic vibration of an axial string. Hamilton's principle is used to formulate the nonlinear equation of motion of the axial translation string, and the von Kármán equations are used to analyse the geometric nonlinearity. The governing equations are nondimensionalized as partial differential equations and transformed into a nonlinear 3-dimensional system via the third-order Galerkin approach. An active control technique based on the FSMC approach is suggested for the derived dynamic system. By using a recurrent neural network model, we can accurately predict and effectively apply a control strategy to suppress chaotic movements. The necessity of the suggested active control method in the regulation of the nonlinear axial translation string system is proven using different chaotic vibrations. The results show that the study of the chaotic vibrations of axially translating strings requires nonlinear multidimensional dynamic systems of axially moving strings; the validity of the proposed control strategy in controlling the chaotic vibration of axially moving strings in a multidimensional form is demonstrated. [ABSTRACT FROM AUTHOR]

The characterisation of novel materials presents a challenge that requires new and original developments. To face some of these demands for making measurements at the nanoscale, a new microsphere-assisted white light interference nanoscope performing local reflectance mapping is presented. This technique presents the advantages of being non-destructive, full-field and label-free. A 145 μm diameter microsphere, glued to the end of an optical fiber, is inserted inside the white light interference microscope to improve the lateral resolution from 940 nm to 520 nm. The acquisition and the Fourier transform processing of a stack of interference images superimposed on the virtual image produced by the microsphere allows the extraction of the local reflectance over a wavelength range of 460 nm to 900 nm and a field of view of 8 μm in diameter. The enhancement in the lateral resolution of the reflectance is demonstrated through the spectral distinction of neighboring ripples on a laser-textured colored stainless-steel sample that cannot be resolved without the microsphere, on regions with a surface of 279 × 279 nm2 horizontally spaced 279 nm apart. Future improvements could potentially lead to a lateral resolution of reflectance measurement over a 100 nm diameter area in air, paving the way to sub-diffraction reflectance mapping. [ABSTRACT FROM AUTHOR]

In natural language processing, document-level relation extraction is a complex task that aims to predict the relationships among entities by capturing contextual interactions from an unstructured document. Existing graph- and transformer-based models capture long-range relational facts across sentences. However, they still cannot fully exploit the semantic information from multiple interactive sentences, resulting in the exclusion of influential sentences for related entities. To address this problem, a novel Semantic-guided Attention and Adaptively Gated (SAAG) model is developed for document-level relation extraction. First, a semantic-guided attention module is designed to guide sentence representation by assigning different attention scores to different words. The multihead attention mechanism is then used to capture the attention of different subspaces further to generate a document context representation. Finally, the SAAG model exploits the semantic information by leveraging a gating mechanism that can dynamically distinguish between local and global contexts. The experimental results demonstrate that the SAAG model outperforms previous models on two public datasets. [ABSTRACT FROM AUTHOR]

This paper presents the detailed design configuration and investigation of a small-scale dual-band metamaterial absorber (MTMA) for solid and liquid sensing applications. The overall dimension of the MTMA unit cell is 10 × 10 × 1.57 mm3 and constitutes an affordable FR-4 substrate. The absorber exhibits dual absorption peaks at 3.470 GHz for the S-band and 7.219 GHz for the C-band, respectively. Both absorption characteristics have been validated through comprehensive simulation and experimental procedures. The dual-band absorption rate exceeded 99% during simulations, and experimental validation showed an absorption rate above 98%. For sensing applications, various solid materials, including different Rogers substrates (RT 5880, RT 5870, RT 4003 and RT 4835) and liquids such as sunflower and crown oil, were utilized. Our findings indicate that the proposed MTMA achieves a maximum Q-factor of 191 and a sensitivity of up to 2.5 for both solid and liquid sensing applications compared to previous studies. The simulation and experimental validation of the result indicate that suggested MTMA can be effectively used in different sensing applications such as the medical and communications industry. [ABSTRACT FROM AUTHOR]

Detecting defects on photovoltaic panels using electroluminescence images can significantly enhance the production quality of these panels. Nonetheless, in the process of defect detection, there often arise instances of missed detections and false alarms due to the close resemblance between embedded defect features and the intricate background information. To tackle this challenge, we propose an Adaptive Complementary Fusion (ACF) module designed to intelligently integrate spatial and channel information. This module is seamlessly integrated into YOLOv5 for detecting defects on photovoltaic panels, aiming primarily to enhance model detection performance, achieve model lightweighting, and accelerate detection speed. In order to validate the efficacy of the proposed module, we conducted experiments using a dataset comprising 4500 electroluminescence images of photovoltaic panels. Compared to the cutting-edge detection capability of YOLOv8, our YOLO-ACF method exhibits enhancements of 5.2, 0.8, and 2.3 percentage points in R, mAP50, and mAP50-95, respectively. In contrast to the lightest and fastest YOLOv5, YOLO-ACF achieves reductions of 12.9%, 12.4%, and 4.2% in parameters, weight, and time, respectively, while simultaneously boosting FPS by 5%. Through qualitative and quantitative comparisons with various alternative methods, we demonstrate that our YOLO-ACF strikes a good balance between detection performance, model complexity, and detection speed for defect detection on photovoltaic panels. Moreover, it demonstrates remarkable versatility across a spectrum of defect types. [ABSTRACT FROM AUTHOR]

Sepiolite-modified nano-zero-valent iron (S-nZVI) is used as an amendment and incubated to remediate As-Cd-contaminated soil under three different soil‒water management conditions [moderately wet (MW), continuously flooded (CF) and alternately wet and dry (AWD)]. The results showed that soil pH is in the order of CF > AWD > MW. The soil pH increased approximately 0.5 to 1 unit by 3% and 5% doses after 36 d of incubation. Soil pH was negatively correlated with available As-Cd content under the three water regimes (p < 0.01). All doses of S-nZVI significantly reduced soil available As-Cd under the three soil moistures by 45-80% for As and 5-45% for Cd. Moreover, S-nZVI addition also promoted the transformation of As-Cd in the acid-extracted fraction, oxidation fraction, and reduced fraction to a more stable residue fraction. High-throughput sequencing results showed that high doses of S-nZVI had a significant adverse effect on soil bacterial diversity and richness. After 36 d of incubation, the Chao1 index and the Shannon index were significantly decreased in MW, CF, and AWD, respectively. Decreasing the S-nZVI dose and increasing the incubation time simultaneously reduced As-Cd availability and S-nZVI ecotoxicity in the soil, thereby effectively maintaining the survivability of the original dominant bacteria, increasing the soil pH, and promoting the interaction between dominant bacteria and soil factors in As-Cd cocontaminated soil. [ABSTRACT FROM AUTHOR]

To scrutinize the spatial distribution attributes of soil heavy metal content and discern its pollution status within the expanse of Wulongdong National Forest Park, a meticulous investigation is imperative. Three altitude gradients of 900, 1000, and 1069 m were selected on the shady and sunny slopes of Wulongdong National Forest Park, and a total of 300 soil sample points were collected. Soil samples were collected in layers, and the contents of seven soil heavy metal elements, Cr, Cd, Hg, Ni, Se, As, and Pb, were measured. With regard to the national soil element background values, the single factor index method, Nemerow index method, and pollution load index were employed to undertake a thorough assessment of soil heavy metal pollution. (1) The contents of heavy metal elements Cr, Se, As, and Pb in the 0–20 cm soil layer of Wulongdong National Forest Park are lower than the national soil element background value and the Henan soil element background value; the Cd and Hg contents exceed the national soil element background value. The value and Henan soil element background value are 2.2 times and 2.92 times the national soil element background value, and 2.75 times and 9.5 times the Henan soil element background value respectively; Ni content is lower than the Henan soil element background value, but higher than the national soil element background value. The background value is 1.03 times its content. The coefficients of variation of the contents of seven heavy metal elements are all greater than 50%, among which Hg shows extreme variation, and the remaining six are highly variable. (2) In the same soil layer, the Cr and As contents are lower on sunny slopes than on shady slopes, and the contents of Pb, Ni, and Hg are generally higher on sunny slopes than on shady slopes. On sunny slopes, the contents of As, Cd, and Hg decrease with increasing altitude, and the Se content increases with increasing altitude; while on shady slopes, the contents of Cr, Se, and As decrease with increasing altitude, and Pb and Hg content increase with the increase of altitude; the content of heavy metal element As increases with the deepening of the soil layer on shady slopes, and the Hg content decreases with the deepening of the soil layer on sunny slopes. The contents of other heavy metal elements have no obvious regularity among different slope directions, altitudes and soil layers. (3) The single factor index evaluation results show that in the 0 ~ 20c soil layer and on the sunny slope, Hg is heavily polluted, Cd is moderately polluted, Ni is lightly polluted, and Cr, Se, As, and Pb are all non-polluted; On the shady slope, Cd and Hg are moderately polluted, and the other five heavy metal elements are in a non-polluting state. (4) The Nemerow index method evaluation results show that in the 0 ~ 20 cm soil layer, the soil on sunny slopes is significantly more polluted by heavy metals than on shady slopes, and the main pollutants are Ni, Cd and Hg. (5) In the 0 ~ 20 cm soil layer of Wulongdong National Forest Park, the three heavy metal elements Ni, Cd and Hg have reached pollution levels, of which Ni is slightly polluted, Cd and Hg are moderately or above polluted; the sunny slope soil is slightly polluted. Heavy metal pollution, no heavy metal pollution on shady slopes. [ABSTRACT FROM AUTHOR]

Objective: Previous observational studies have indicated associations between various inflammatory cytokines and diabetic nephropathy (DN) caused by type 2 diabetes mellitus (T2DM). However, the causality remains unclear. We aimed to further evaluate the causal association between 91 inflammatory cytokines and DN using bidirectional two-sample Mendelian randomization (MR) analysis. Method: Summary statistics for DN were obtained from a publicly available genome-wide association study (GWAS) analysis. Data pertaining to inflammatory cytokines were derived from a GWAS protein quantitative trait locus (pQTL) study. The primary analytical approach employed the inverse variance weighted (IVW) method, complemented by MR-Egger regression, weighted mode (WM), and weighted median (WME) methods to evaluate the causal association between inflammatory cytokines and DN. Sensitivity analyses were conducted to validate the robustness of the findings. Result: Among individuals of European ancestry, the IVW method results revealed a positive causal association between the gene expression of tumor necrosis factor ligand superfamily member 14 (TNFSF14), and TNF-related activation-induced cytokine (TRANCE) with DN. Conversely, a negative causal association was observed between the gene expression of interleukin-1-alpha (IL-1α), and transforming growth factor-alpha (TGF-α) with DN. Among individuals of East Asian ancestry, the IVW method results indicated a negative causal association between the gene expression of glial cell line-derived neurotrophic factor (GDNF) and DN. Notably, these findings persisted without evidence of horizontal pleiotropy or heterogeneity, ensuring their robustness and reliability. Conclusion: The MR analysis underscores a causal association between inflammatory cytokines and DN, providing an important reference and evidence for the study of DN. [ABSTRACT FROM AUTHOR]

With technology development, the growing self-communicating devices in IoT networks require specific naming and identification, mainly provided by IPv6 addresses. The IPv6 address in the IoT network is generated by using the stateless auto address configuration (SLAAC) mechanism, and its uniqueness is ensured by the DAD protocol. Recent research suggests that IPv6 deployment can be a risky decision due to the existing SLAAC-based addressing scheme and the DAD protocol being prone to reconnaissance and denial of service (DoS) attacks. This research paper proposes a new IPv6 generation scheme with an improved secure DAD mechanism to address these problems. The proposed addressing scheme generates IPv6 addresses by taking a hybrid approach based on vendor id of medium access control (MAC) address, physical location, and arbitrary random numbers, which mitigates reconnaissance attacks by malicious nodes. To prevent the DAD process from DoS attacks, hybrid values of interface identifier (IID) are multicast instead of actual values. The proposed scheme is evaluated under reconnaissance and DoS attacks in the presence of malicious nodes. The evaluation results demonstrate that the proposed method effectively mitigates reconnaissance and DoS attacks, outperforming the EUI-64 and SEUI-64 schemes in terms of address success rate (ASR), energy consumption, and communication overhead. Specifically, the proposed method significantly reduces the average probing rate for scanning the existence of an IPv6 address, with only a 1% probing rate compared to SEUI-64's 5% and EUI-64's 100%. Furthermore, the additional communication overhead introduced by the proposed method is less than 13% and 11% compared to EUI-64 and SEUI-64, respectively. Additionally, the energy consumption required to assign an IPv6 address using the proposed method is lower by 12% and 5% when compared to EUI-64 and SEUI-64, respectively. These findings highlight the effectiveness of the proposed method in enhancing security and optimizing resource utilization in IPv6 addressing. [ABSTRACT FROM AUTHOR]

At present, the speed of the reel of soybean combine harvester is mainly adjusted manually, and basically does not have the ability to automatically adjust the speed of the reel according to changes in crops or working speed. In the maize-soybean strip intercropping mode, soybean plants are densely planted. During harvesting, the feeding rate increases, making it even more necessary to adjust the reel speed according to the growth status of the crops. This article uses PLC as the main control platform to design a reel speed control system for the existing combine harvester. Tests have shown that the control system can meet the requirements for reel speed control. The relative error of the reel control system's speed test is 2.6%, the relative error of the operating speed is 6.77%, and the maximum relative error of the automatic control of the reel speed is 5.38%. Compared with traditional reel, it reduces header loss by 2.12%. The soybean combine harvester reel speed control system designed in this article can realize automatic adjustment of the reel speed, reduce feeding losses caused by changes in crop height, changes in feed volume, and untimely adjustment of the reel, and can reduce header loss, increased crop yield. [ABSTRACT FROM AUTHOR]

Human bone marrow mesenchymal stem cells (hBMSCs) are adult stem cells residing in the bone marrow, characterized by their capacity for multi-directional differentiation, self-renewal, migration, and engraftment. Serving as seed cells, BMSCs play a pivotal role in the regeneration of bone defects. Hence, investigating the transcription factors and signaling pathways involved in the regulation of osteogenic differentiation in BMSCs holds significant importance. Recent research has unveiled that certain circular RNAs (circRNAs) can function as molecular sponges, influencing the osteogenic differentiation process of mesenchymal stem cells. However, many circRNAs remain undiscovered, and their precise mechanisms remain elusive. Therefore, the objective of this study is to construct an osteogenic differentiation-related circRNA-miRNA-mRNA network in hBMSCs. Subsequently, through bioinformatics analysis, we constructed a ceRNA network related to the osteogenic differentiation ability of hBMSCs, comprising 22 circRNAs, 17 miRNAs, and 15 mRNAs. The potential circRNA-miRNA-mRNA axes, including the role of hsa_circ_0001600 in promoting the osteogenic differentiation of hBMSCs through the targeted regulation of hsa-miR-542-3p, were validated through in vitro experiments. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities. [ABSTRACT FROM AUTHOR]

This study explored the factors influencing serum 25(OH)D3 levels and the effects of Vitamin D deficiency (VDD) and VD supplementation on 25(OH)D3 levels and neuropsychobehavioral development in premature infants, to provide a theoretical basis for improving their prognosis. Physical examination, neuropsychobehavioral development and serum 25(OH)D3 levels were assessed regularly in 158 preterm infants supplemented with VD formulation. 25(OH)D3 levels were analyzed at 3, 6, 9, 12, and 18 months after birth. The Gesell neuropsychological development test was conducted at 6, 9, 12, and 18 months after birth to obtain the developmental quotient (DQ). Based on the serum 25(OH)D3 levels at 42 days of age, the infants were divided into VDD and non-VDD groups. Preterm infants in the VDD group were supplemented with more VD until their 25(OH)D3 levels were normal, and were divided into sustained VDD (SVDD) and corrected VDD (CVDD) groups according to serum 25(OH)D3 levels at 3 months of age. Appropriate statistical methods were chosen to compare differences in 25(OH)D3 and DQ between or among different groups, screen for the factors influencing 25(OH)D3 levels in preterm infants at 42 days of age, and analyze the relationship between 25(OH)D3 and DQ. The 25(OH)D3 levels of preterm infants at 42 days of age were positively correlated with VD supplementation during pregnancy, and before 42 days after birth (P < 0.05). The 25(OH)D3 levels in preterm infants at 42 days and 3 months of age were positively correlated with the DQ levels at 6, 9, 12, and 18 months of age (P < 0.05). The DQ level in the VDD group, especially SVDD group, was lower than that in CVDD and non-VDD groups at the same time point (P < 0.05). This research thus demonstrates that VD supplementations during pregnancy and after birth is a major factor affecting 25(OH)D3 levels in premature infants. Early VDD and SVDD can affect their neuropsychobehavioral development, and effective VD supplementation can gradually correct VDD and mitigate this influence. [ABSTRACT FROM AUTHOR]

Physical unclonable functions (PUFs) have emerged as a favorable hardware security primitive, they exploit the process variations to provide unique signatures or secret keys amidst other critical cryptographic applications. CMOS-based PUFs are the most popular type, they generate unique bit strings using process variations in semiconductor fabrication. However, most existing CMOS PUFs are found to be vulnerable to modeling attacks based on machine learning (ML) algorithms. Memristors leveraging nanotechnology fabrication processes and highly nonlinear behavior became an interesting alternative to the existing CMOS-based PUF technology, introducing cryptographic and resilient random outputs. Memristor-based PUFs are emerging due to the inherent randomness at both the memristor level due to the cycle-to-cycle (C2C) programming variation of the device and the fabrication process level such as the cross-sectional area and variations. Our study focuses on building a machine learning analysis and attack framework of tools on C u / H f O 2 - x / p + + S i memristor-based PUF (MR-PUF). Our objective is to test the resiliency of the security margins of the presented PUF using machine learning analysis tools, on-top of holistic NIST cryptographic randomness testing initially provided, to provide a high level of certainty in predicting the randomness output of the verified Memrister-based PUF. Our main contribution is a holistic study that focuses on attacking the randomness output resiliency based on building randomness predictors using Logistic Regression (LR), Support Vector Machine (SVM), Gaussian Mixture Models (GMM), K-means, K-means + + , Random Forest, XGBoost and LSTM, within efficient time, and data complexity. Our results yield low accuracy and ROC results of within 0.49 - 0.52 and 0.49 - 0.52 respectively, indicating failure in predicting random data demonstrates efficient randomness prediction resiliency of the MR-PUF. The efficient time and data complexities of these attacks illustrated in this study are yielded to be linear and quadratic resulting in attack execution time in seconds and 5032 training samples combined with 2157 testing samples to verify the randomness of PUF. [ABSTRACT FROM AUTHOR]

Hyperspectral image (HSI) data has a wide range of valuable spectral information for numerous tasks. HSI data encounters challenges such as small training samples, scarcity, and redundant information. Researchers have introduced various research works to address these challenges. Convolution Neural Network (CNN) has gained significant success in the field of HSI classification. CNN's primary focus is to extract low-level features from HSI data, and it has a limited ability to detect long-range dependencies due to the confined filter size. In contrast, vision transformers exhibit great success in the HSI classification field due to the use of attention mechanisms to learn the long-range dependencies. As mentioned earlier, the primary issue with these models is that they require sufficient labeled training data. To address this challenge, we proposed a spectral-spatial feature extractor group attention transformer that consists of a multiscale feature extractor to extract low-level or shallow features. For high-level semantic feature extraction, we proposed a group attention mechanism. Our proposed model is evaluated using four publicly available HSI datasets, which are Indian Pines, Pavia University, Salinas, and the KSC dataset. Our proposed approach achieved the best classification results in terms of overall accuracy (OA), average accuracy (AA), and Kappa coefficient. As mentioned earlier, the proposed approach utilized only 5%, 1%, 1%, and 10% of the training samples from the publicly available four datasets. [ABSTRACT FROM AUTHOR]

Backfilling is a promising measure for controlling surface subsidence in mined-out areas and disposing solid wastes from the mineral processing, there are increasing demands of enhanced toughness and anti-cracking properties of backfill materials to prolong the service life under the complex loads. In this study, polypropylene (PP) fibers were employed to improve performance of backfills, four-point bending and uniaxial compression tests were conducted to investigate the failure process and damage evolution of fiber-reinforced aeolian-sand backfill materials (FABs) using Digital Image Correlation (DIC) and Acoustic Emission (AE) techniques. The results show that the compressive strength tends to decrease with the increasing fiber volume fractions, while the four-point bending strength shows a tendency to increase initially and then decrease, and the optimum volume fraction of PP fiber is 0.6%. At the optimal fiber volume fraction, PP fibers with lengths of 3 mm and 9 mm resulted in a 65.25% and 81.62% increase in the four-point bending strength of FABs, respectively. As indicated by DIC measurements, PP fibers with a length of 9 mm were more effective in controlling the horizontal and vertical displacements of FABs under four-point bending loads than that of 3 mm, and the cracks developed more slowly at the same deflection. In addition, PP fibers with a length of 9 mm have stronger crack extension delay characteristics due to longer effective anchorage distance, as evidenced by more frequent acoustic emission ringing counts and higher cumulative ringing counts. The results of the study may provide a theoretical basis for the application of FABs materials in backfilling. [ABSTRACT FROM AUTHOR]

With the continuous development of underground engineering construction in China, it is particularly important to study the identification of structural plane characteristics of rock masses. In this study, three types of pseudo-rock specimens with structural plane interlayers were fabricated to analyze the patterns of drilling parameter changes in rock bodies with structural planes during the drilling process and to explore the characterization and identification methods of rock body structural planes. Gneiss, granite, and sandstone were used as rock materials, with gypsum mortar as the interlayer material for the structural planes in these three types of specimens. The indoor digital drilling equipment was utilized for conducting indoor digital drilling experiments. The variation patterns of drilling parameters in rock bodies with structural surfaces under different interlayer inclinations and thicknesses were analyzed. The relationship between the ratio of the change in rotational speed and drilling speed during the stable phase of the upper rock mass and the peak torque and peak drilling pressure has been established. The relationship between the structural plane inclination angle and the ratio of change in rotational speed and drilling speed has been determined. By utilizing the variation in these ratios, the impacts of the structural plane inclination angle and the thickness of the structural plane on the peak torque and peak drilling pressure have been elucidated. The research results provide a theoretical basis for the stability evaluation of rock masses with structural planes under drilling action. [ABSTRACT FROM AUTHOR]

This study investigated the effects of corn cob biochar (CCB) and rice husk biochar (RHB) additions (at 0%, 5%, and 10% w/w) on nitrogen and carbon dynamics during co-composting with poultry litter, rice straw, and domestic bio-waste. The study further assessed the temperature, moisture, pH, and nutrient contents of the mature biochar co-composts, and their potential phytotoxicity effects on amaranth, cucumber, cowpea, and tomato. Biochar additions decreased NH4+-N and NO3- contents, but bacteria and fungi populations increased during the composting process. The mature biochar co-composts showed higher pH (9.0–9.7), and increased total carbon (24.7–37.6%), nitrogen (1.8–2.4%), phosphorus (6.5–8.1 g kg−1), potassium (26.8–42.5 g kg−1), calcium (25.1–49.5 g kg−1), and magnesium (4.8–7.2 g kg−1) contents compared to the compost without biochar. Germination indices (GI) recorded in all the plants tested with the different composts were greater than 60%. Regardless of the biochar additions, all composts treatments showed no or very minimal phytotoxic effects on cucumber, amaranth and cowpea seeds. We conclude that rice husk and corn cob biochar co-composts are nutrient-rich and safe soil amendment for crop production. [ABSTRACT FROM AUTHOR]

The digital economy has emerged as a new trend in economic development and has profoundly influenced the process of achieving common prosperity. However, current research on the correlation between the digital economy and common prosperity from the perspective of a river basin still needs to be strengthened. Based on this, the present study first theoretically elaborates the conceptual meanings of "digital economy" and "common prosperity", as well as the mechanism by which the digital economy empowers common prosperity. Subsequently, a scientifically-constructed performance evaluation index system for the digital economy and common prosperity is established. Considering the Yellow River Basin as an empirical case study area, this study investigates the mechanism and spatial spillover effects of the digital economy in empowering common prosperity from 2005 to 2020. The research findings reveal that: (1) The Yellow River Basin exhibits a basin characteristic with downstream > midstream > upstream areas regarding the level of common prosperity and digital economy. It indicates that a distinct spatial correlation exists between the two factors. However, the ongoing decrease in both high-level and very high-level areas reflects the lengthy and challenging journey of enhancing the quality and efficiency of the digital economy in empowering common prosperity. (2) The digital economy not only directly impacts common prosperity, but also fosters its development through spatial spillover effects. Among the control factors, informatization and housing levels have a major stimulating effect. (3) There exists a clear regional heterogeneity in how the digital economy affects common prosperity in the Yellow River Basin. Specifically, common prosperity of downstream cities is significantly impacted by the digital economy. The spatial spillover effects of the digital economy on common prosperity exhibit a pronounced "neighborhood as a moat" characteristic. (4) The digital economy facilitates the achievement of shared prosperity through the implementation of mechanisms centered on sharing, affluence, and sustainability. These research findings illuminate the empowering mechanisms and spatial spillover pathways of the digital economy in promoting shared prosperity, aligning with national strategies for ecological conservation and high-quality development in the Yellow River Basin. [ABSTRACT FROM AUTHOR]

Triple-negative breast cancer (TNBC) lacks estrogen, progesterone, and human epidermal growth factor receptors and has a poor prognosis as it is resistant to chemotherapy. A new treatment option for this type of cancer may be by putting these malignant cells into dormancy. The oocyte's embryonic milieu presents a unique tumor reversion microenvironment by inducing growth arrest and changing cells' phenotypes. We conducted an in-silico study to determine the most likely oocyte extract (OE) proteins involved in inducing dormancy using HDock, CluPro, and molecular dynamic (MD) simulation. Results showed low energy scores for complexes between OE proteins and four surface markers: K1C14, CLD3, CLD4, and ITA6. Apolipoprotein A1 (APOA1) and Apolipoprotein C3 (APOC3) showed the highest stability and affinity with these four surface markers: K1C14, CLD3, CLD4, and ITA6. These proteins are involved in key tumor-related pathways such as angiogenesis, proliferation, apoptosis, and migration. This will pave the way for exploring novel therapeutic options to induce dormancy in TNBC cells. [ABSTRACT FROM AUTHOR]

In calcium imaging studies, Ca2+ transients are commonly interpreted as neuronal action potentials (APs). However, our findings demonstrate that robust optical Ca2+ transients primarily stem from complex "AP-Plateaus", while simple APs lacking underlying depolarization envelopes produce much weaker photonic signatures. Under challenging in vivo conditions, these "AP-Plateaus" are likely to surpass noise levels, thus dominating the Ca2+ recordings. In spontaneously active neuronal culture, optical Ca2+ transients (OGB1-AM, GCaMP6f) exhibited approximately tenfold greater amplitude and twofold longer half-width compared to optical voltage transients (ArcLightD). The amplitude of the ArcLightD signal exhibited a strong correlation with the duration of the underlying membrane depolarization, and a weaker correlation with the presence of a fast sodium AP. Specifically, ArcLightD exhibited robust responsiveness to the slow "foot" but not the fast "trunk" of the neuronal AP. Particularly potent stimulators of optical signals in both Ca2+ and voltage imaging modalities were APs combined with plateau potentials (AP-Plateaus), resembling dendritic Ca2+ spikes or "UP states" in pyramidal neurons. Interestingly, even the spikeless plateaus (amplitude > 10 mV, duration > 200 ms) could generate conspicuous Ca2+ optical signals in neurons. Therefore, in certain circumstances, Ca2+ transients should not be interpreted solely as indicators of neuronal AP firing. [ABSTRACT FROM AUTHOR]

The ecological compensation mechanism is a tool for managing regional development and promoting the green economy. This paper proposes a revised model for carbon emissions and absorption based on IPCC, then analyses the spatial and temporal variations of carbon emissions, absorption, and deficit in 31 provinces of China from 2001 to 2019. A model was developed to redistribute carbon deficits and compensate for ecological imbalances, with the aim of eliminating background differences between regions. The concept of ecological compensation sensitivity was proposed, and a redundancy analysis (RDA) was conducted to detect possible influencing factors. Results indicate that: (1) The carbon deficits were relatively substantial in the centre and developed coastal regions, which were the subject regions of China's ecological compensation. Meanwhile, the northwest and southwest regions were the object regions of ecological compensation, and the compensated object regions tended to extend towards the southeast. The majority of compensated subject areas are generally less sensitive than compensated object regions. (2) The graph of carbon deficit volume over time shows that China's two carbon targets are closely aligned. The distribution of China's ecological compensation amounts follows the pattern of provincial economic development levels, with higher compensation amounts concentrated in the central and coastal regions. There is a positive correlation between GDP, year, and population size with carbon emission and carbon deficit. Additionally, there is a positive correlation between year, region, and carbon absorption. (3) This compensation model can strongly incentivise the compensation subject area to proactively adjust its economic development model to cope with the significant compensation pressure. Additionally, it can fully encourage the compensation recipient area to continue adhering to the green economic development model. The conclusions of the study hold significant reference value for promoting the development of a green, low-carbon economy. [ABSTRACT FROM AUTHOR]

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease's tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies. [ABSTRACT FROM AUTHOR]

Zinc metal–organic frameworks have emerged as promising candidates, demonstrating excellent biological properties stemming from the unique characteristics of MOFs and zinc. In this study, we employed a facile method to synthesize a zinc metal–organic framework [Zn(IP)(H2O)] using ultrasound irradiation, with the linker being isophthalic acid (IPA) (1,3-benzene dicarboxylic acid). The parent Zn-MOF and two Ag/Zn-MOF samples prepared via loading and encapsulation methods were comprehensively characterized using various techniques, including FT-IR, XRD, SEM, TEM, N2 adsorption–desorption isotherm, UV–vis spectroscopy and TGA. The parent Zn-MOF and two Ag/Zn-MOF samples exhibited a broad spectrum of antibacterial effects. Remarkably, genomic DNA of P. aeruginosa was effectively degraded by Zn-MOF, further supporting its potent antibacterial results. The free radical inhibition assay demonstrated a 71.0% inhibition under the influence of Zn-MOF. In vitro cytotoxicity activity of Zn-MOF against HepG-2 and Caco-2 cell lines revealed differential cytotoxic effects, with higher cytotoxicity against Caco-2 as explored from the IC50 values. This cytotoxicity was supported by the high binding affinity of Zn-MOF to CT-DNA. Importantly, the non-toxic property of Zn-MOF was confirmed through its lack of cytotoxic effects against normal lung cell (Wi-38). The anti-inflammatory treatment of Zn-MOF achieved 75.0% efficiency relative to the standard Ibuprofen drug. DFT and docking provided insights into the geometric stability of Zn-MOF and its interaction with active amino acids within selected proteins associated with the investigated diseases. Finally, the synthesized Zn-MOF shows promise for applications in cancer treatment, chemoprevention, and particularly antibacterial purposes. [ABSTRACT FROM AUTHOR]

Formulating a course of action (COA) before a combat is crucial for operational command. Research in command and control (C2) artificial intelligence is currently focused on using intelligent auxiliary decision-making methods to implement COA. This paper proposes a COA planning method based on line of operation (LOO) and uses planning domain definition language (PDDL) to describe combat scenarios and COA. Following the effect-based optimization (EBO) principle, an effect evaluation model for COA was constructed, and dynamic bayesian networks (DBNs) was used to determine the reasoning and calculate the results of the effect evaluation network. To further improve the execution efficiency of the effect evaluation model in practical applications, the network was optimized through a back propagation neural network (BPNN). Relevant experiments based on the coordinated distributed air defense and anti-missile scenario were carried out using the LOO model to complete the planning of COA. A BPNN evaluation model based on the DBNs evaluation model was built. After training and fine-tuning, it achieved similar evaluation results, with a mean absolute percentage error (MAPE) of less than 0.02%. Compared with the DBNs model, the BPNN model achieved an efficiency improvement of no less than 65%, effectively reducing the consumption of computing resources. This research is the first time to realize the modeled description of COA planning, automatic evaluation, and calculation optimization of COA effects. It can support the development of decision support systems (DSS) and has the potential for practical application. [ABSTRACT FROM AUTHOR]

To identify patterns in big medical datasets and use Deep Learning and Machine Learning (ML) to reliably diagnose Cardio Vascular Disease (CVD), researchers are currently delving deeply into these fields. Training on large datasets and producing highly accurate validation results is exceedingly difficult. Furthermore, early and precise diagnosis is necessary due to the increased global prevalence of cardiovascular disease (CVD). However, the increasing complexity of healthcare datasets makes it challenging to detect feature connections and produce precise predictions. To address these issues, the Intelligent Cardiovascular Disease Diagnosis based on Ant Colony Optimisation with Enhanced Deep Learning (ICVD-ACOEDL) model was developed. This model employs feature selection (FS) and hyperparameter optimization to diagnose CVD. Applying a min–max scaler, medical data is first consistently prepared. The key feature that sets ICVD-ACOEDL apart is the use of Ant Colony Optimisation (ACO) to select an optimal feature subset, which in turn helps to upgrade the performance of the ensuring deep learning enhanced neural network (DLENN) classifier. The model reforms the hyperparameters of DLENN for CVD classification using Bayesian optimization. Comprehensive evaluations on benchmark medical datasets show that ICVD-ACOEDL exceeds existing techniques, indicating that it could have a significant impact on CVD diagnosis. The model furnishes a workable way to increase CVD classification efficiency and accuracy in real-world medical situations by incorporating ACO for feature selection, min–max scaling for data pre-processing, and Bayesian optimization for hyperparameter tweaking. [ABSTRACT FROM AUTHOR]

In addition to complex spin-ice and spin-liquid states of rare-earth pyrochlore oxides, A2Ir2O7 iridates have been recently proposed to host a cooling-field-controllable antiferromagnetic domain structure of iridium moments. Reliable and profound studies of the magnetic domain structure, including domains’ interfaces, have been frequently limited by insufficient sample quality or lack of single crystals. We report the magnetic properties of the for-the-first-time synthesised Lu2Ir2O7 and Er2Ir2O7 single crystals; focussing on the robust ferromagnetic component of magnetisation present in the material with the antiferromagnetically ordered state of the all-in-all-out (AIAO) type. Anisotropy of the system, as well as the effects of magnetic (Er3+) or nonmagnetic (Lu3+) local environments on Ir4+ moments, is studied. The size of the domains is calculated based on a simplified domain wall model. Results are discussed in the framework of AIAO and AOAI domains and interfaces on the geometrically frustrated lattice. [ABSTRACT FROM AUTHOR]

Highly dispersed Cobalt doped ZnS nanostructures were successfully fabricated on the surfaces of graphene sheets via a simple hydrothermal method. X-ray diffraction (XRD), X-ray photocurrent spectroscopy (XPS), Raman spectroscopy (RS), Fourier transform infrared spectroscopy (FTIR) and Scanning electron microscopy (SEM) were utilized to analyze the structural characteristics of the cobalt doped ZnS decorated with graphene Co x Zn 1 - x S rGO nanostructures (NSs). UV-visible optical absorption (UV-vis) studies were conducted to investigate their optical properties. In laboratory studies utilizing water and visible light, the photocatalytic activity of Co x Zn 1 - x S rGO NSs at (x = 0, 1, 2, 4 and 6 atm.%) were evaluated. Graphite Oxide (GO) was successfully transformed into sheets of graphene and Co x Zn 1 - x S rGO NSs possessed a crystalline structure according to the findings of XRD, RS and FTIR analysis. SEM investigation showed graphene sheets enhanced with ZnS NSs possessed cuboidal, spheroidal form of structure and displayed a paper like appearance. UV-vis confirmed a noticeable rapid increase in transmittance along the UV wavelength area and confirmed a highly transparent NSs in the wavelength range of (180-800 nm). Calculations using density functional theory (DFT) revealed that the Co NSs have more negative conduction bands than ZnS, allowing for effective electron transfer from cobalt to ZnS and exhibiting a band gap decrease as Co content increased. The Co 0.04 Zn 0.96 S rGO NSs sample had the highest photocatalytic activity, measured at 7648.9 μ mol h - 1 . A combination of improved dispersion properties, greater surface area, increased absorption and enhanced transfer of photogenerated electrons, Co x Zn 1 - x S rGO NSs increased the photocatalytic hydrogen generation activity. [ABSTRACT FROM AUTHOR]

Leaf senescence represents the final stage of leaf development, involving transcription factors (TFs)-mediated genetic reprogramming events. The timing of crop leaf senescence has a major influence on the yield and quality of crop in agricultural production. As important regulator of plant growth, the significance of TFs in the regulation of leaf senescence have been highlighted in various plant species by recent advances in genetics. However, studies on underlying molecular mechanisms are still not adequately explained. In this study, for analyzing the regulation of TFs on senescence of tobacco leaves, we combined gene differential expression analysis with weighted gene co-expression network analysis (WGCNA) to analyze the time-series gene expression profiles in senescing tobacco leaf. Among 3517 TF genes expressed in tobacco leaves, we identified 21, 35, and 183 TFs that were associated with early, middle, and late stages of tobacco leaf senescence, respectively. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotation results reveal that these senescence response TFs are correlated with several biological pathways such as plant hormone signal transduction, ubiquitin mediated proteolysis and MAPK signaling pathway, indicating the roles of TFs in regulating leaf senescence. Our results provide implications for future studies of the potential regulatory mechanisms of TFs involved in senescence of tobacco leaves. [ABSTRACT FROM AUTHOR]

Bruton tyrosine kinase inhibitor (BTKi) combined with rituximab-based chemotherapy benefits diffuse large B-cell lymphoma (DLBCL) patients. However, drug resistance is the major cause of relapse and death of DLBCL. In this study, we conducted a comprehensive analysis BTKi-resistance related genes (BRRGs) and established a 10-gene (CARD16, TRIP13, PSRC1, CASP1, PLBD1, CARD6, CAPG, CACNA1A, CDH15, and NDUFA4) signature for early identifying high-risk DLBCL patients. The resistance scores based on the BRRGs signature were associated with prognosis. Furthermore, we developed a nomogram incorporating the BRRGs signature, which demonstrated excellent performance in predicting the prognosis of DLBCL patients. Notably, tumor immune microenvironment, biological pathways, and chemotherapy sensitivity were different between high- and low-resistance score groups. Additionally, we identified TRIP13 as a key gene in our model. TRIP13 was found to be overexpressed in DLBCL and BTKi-resistant DLBCL cell lines, knocking down TRIP13 suppresses cell proliferation, promotes cell apoptosis, and enhances the apoptosis effect of BTKi on DLBCL cells by regulating the Wnt/β-catenin pathway. In conclusion, our study presents a novel BRRGs signature that could serve as a promising prognostic marker in DLBCL, and TRIP13 might be a potential therapeutic target for resistant DLBCL. [ABSTRACT FROM AUTHOR]

Non-alcoholic Fatty Liver Disease (NAFLD), noted for its widespread prevalence among adults, has become the leading chronic liver condition globally. Simultaneously, the annual disease burden, particularly liver cirrhosis caused by NAFLD, has increased significantly. Neutrophil Extracellular Traps (NETs) play a crucial role in the progression of this disease and are key to the pathogenesis of NAFLD. However, research into the specific roles of NETs-related genes in NAFLD is still a field requiring thorough investigation. Utilizing techniques like AddModuleScore, ssGSEA, and WGCNA, our team conducted gene screening to identify the genes linked to NETs in both single-cell and bulk transcriptomics. Using algorithms including Random Forest, Support Vector Machine, Least Absolute Shrinkage, and Selection Operator, we identified ZFP36L2 and PHLDA1 as key hub genes. The pivotal role of these genes in NAFLD diagnosis was confirmed using the training dataset GSE164760. This study identified 116 genes linked to NETs across single-cell and bulk transcriptomic analyses. These genes demonstrated enrichment in immune and metabolic pathways. Additionally, two NETs-related hub genes, PHLDA1 and ZFP36L2, were selected through machine learning for integration into a prognostic model. These hub genes play roles in inflammatory and metabolic processes. scRNA-seq results showed variations in cellular communication among cells with different expression patterns of these key genes. In conclusion, this study explored the molecular characteristics of NETs-associated genes in NAFLD. It identified two potential biomarkers and analyzed their roles in the hepatic microenvironment. These discoveries could aid in NAFLD diagnosis and management, with the ultimate goal of enhancing patient outcomes. [ABSTRACT FROM AUTHOR]

This paper proposes a new impulse excitation technique using a square plate. First, the functional relationship between the modal frequency of the specimen and the geometrical dimensions and mechanical parameters was established by using the finite element method. Then, the continuous functional relationship derived by a homotopy method allowed the frequency ratios to be related to the thickness-to-length ratio and Poisson's ratio. By measuring the frequency ratios and thickness-to-length ratio, Poisson's ratio could be calculated using this functional relationship. When the density and Poisson's ratio were known, Young's modulus could be identified inversely in conjunction with the finite element analysis. Finally, a comparison test between this method and the traditional impulse excitation technique was designed and implemented, and the results showed that this method has advantages in both testing efficiency and accuracy. The study provides a new idea for system identification, which has important application value and promotion significance. [ABSTRACT FROM AUTHOR]

Laser texturing seems to be a promising technique for reducing bacterial adhesion on titanium implant surfaces. This work aims to demonstrate the possibility of obtaining a functionally orientated surface of titanium implant elements with a specific architecture with specific bacteriological and photocatalytic properties. Femtosecond laser-generated surface structures, such as laser-induced periodic surface structures (LIPSS, wrinkles), grooves, and spikes on titanium, have been characterised by XRD, Raman spectroscopy, and scanning electron microscopy (SEM). The photocatalytic activity of the titanium surfaces produced was tested based on the degradation effect of methylene blue (MB). The correlation between the photocatalytic activity of TiO2 coatings and their morphology and structure has been analysed. Features related to the size, shape, and distribution of the roughness patterns were found to influence the adhesion of the bacterial strain on different surfaces. On the laser-structurised surface, the adhesion of Escherichia coli bacteria were reduced by 80% compared to an untreated reference surface. [ABSTRACT FROM AUTHOR]

KIFC3 is a member of the Kinesin superfamily proteins (KIFs). The role of KIFC3 in non-small cell lung cancer (NSCLC) is unknown. This study aimed to elucidate the function of KIFC3 in NSCLC and the underlying mechanism. Immunohistochemistry indicated that KIFC3 was highly expressed in NSCLC tissues and correlated with the degree of differentiation, tumor size, lymph node metastasis and TNM stage. MTT, colony formation and Transwell assays demonstrated that KIFC3 overexpression promoted the proliferation, migration and invasion of NSCLC cells in vitro, while KIFC3 knockdown led to the opposite results. The protein expression levels of PI3Kp85α and p-Akt were increased after KIFC3 overexpression, meanwhile the downstream protein expression levels such as cyclin D1, CDK4, CDK6, RhoA, RhoC and MMP2 were increased. This promotion effect could be inhibited by a specific inhibitor of the PI3K/Akt pathway, LY294002. Co-immunoprecipitation assays confirmed the interaction between endogenous/exogenous KIFC3 and PI3Kp85α. Tumor formation experiments in nude mice confirmed that KIFC3 overexpression promoted the proliferation, migration and invasion of NSCLC cells in vivo and performed its biological function through the PI3K/Akt signaling pathway.In conclusion, KIFC3 promotes the malignant behavior of NSCLC cells through the PI3K/Akt signaling pathway. [ABSTRACT FROM AUTHOR]

The first-order second-moment checking point method was introduced to judge the instability probability and evaluate the stability of the TCURM. The frequency–response stability calculation and the reliability results were compared, and a frequency–response stability and reliability analysis method was proposed. Taking the Zengziyan W12# unstable rock mass in Nanchuan, Chongqing, China, as an example, the calculation shows that the dynamic indexes and geological indexes decrease as the stiffness of the deterioration area decreases. According to the statistical data of the laboratory test and the field investigation, reliability theory is used to evaluate the stability of the TCURM, and the failure probabilities are 80.3% and 96.27% under natural and saturated conditions, which correspond to states of poor stability and instability, respectively. The reliability evaluation results are consistent with the conclusion of the frequency–response stability analysis. The new method can provide a theoretical basis for developing the dynamic monitoring and early warning indicators of the TCURM and disaster prevention and mitigation in mountainous areas. [ABSTRACT FROM AUTHOR]

The stability of the surrounding rock for the construction excavation and the reinforcement of the lining structure during operation in the water-rich area is a difficult problem for the design of high-head underground turnout pipes. Firstly, according to the mechanism of excavation load release and surrounding rock damage evolution, the seepage effect of excavation in the construction of the forked caves is coupled to the surrounding rock stress damage, and an iterative method of numerical simulation of the coupled mutual feedback effect of excavation surrounding rock stress and seepage is proposed. Then, based on the cracking characteristics of the high internal water pressure reinforced concrete turnpike lining, a numerical analysis method of the coupling interaction between lining cracking and internal water seepage is proposed by coupling internal water seepage to stress damage in the lining by cracking the forked pipe structure. Applying the aforementioned method to a forked pipe project, the results show that: during the construction period, there is a significant increase in the damage zone, stress, and displacement of the rock around the cavern after considering the coupled iterations; during the operation period, with the increase in internal water pressure, the lining structure accelerates cracking due to the external infiltration of internal water; after the internal water is applied, the surrounding rock bears the main internal water pressure and the reinforcement bears only part of the circumferential force. The method provides theoretical support for the analysis and calculation of the reinforcement of similar underground high-pressure tunnels for rock support and lining structures and has certain theoretical and engineering significance., (© 2023. Springer Nature Limited.)

Due to the repeated changes in the COVID-19 pandemic, we live in an era of various uncertainties that raise future anxiety and behavioral addiction problems. According to the Protection Motivation Theory (PMT), the present study attempted to explore the impact of COVID-19 intolerance of uncertainty (COVID-19 IU) on internet addiction (IA) among college students and the mediating role of future anxiety (FA) by constructing a mediating model. A questionnaire survey was conducted on 679 Chinese college students and PROCESS 3.5 was utilized to test the hypotheses. The results indicated that the COVID-19 IU was significantly positively correlated with IA and FA, and FA was significantly positively correlated with IA. COVID-19 IU had a significant positive predictive effect on IA; FA played a complementary partial mediating role between COVID-19 IU and IA. The results supported the PMT, which not only enriched our understanding of FA under uncertain life circumstances, but also deepened our understanding of the potential mechanisms of the effects of IA. Finally, discussions and suggestions were presented based on the results. [ABSTRACT FROM AUTHOR]

Obesity is a health problem characterized by large expansion of adipose tissue. During this expansion, genotoxic stressors can be accumulated and negatively affect the mesenchymal stem cells (MSCs) of adipose tissue. Due to the oxidative stress generated by these genotoxic stressors, senescence phenotype might be observed in adipose tissue MSCs. Senescent MSCs lose their proliferations and differentiation properties and secrete senescence-associated molecules to their niche thus triggering senescence for the rest of the tissue. Accumulation of senescent cells in adipose tissue results in decreased tissue regeneration and functional impairment not only in the close vicinity but also in the other tissues. Here we hypothesized that declined tissue regeneration might be associated with loss of stemness markers in MSCs population. We analyzed the expression of several stemness-associated genes of in vitro cultured MSCs originated from adipose tissue of high-fat diet and normal diet mice models. Since the heterogenous MSCs population covers a small percentage of the pluripotent stem cells, which have roles in proliferation and tissue regeneration, we measured the percentage of these cells via TRA-1-60 pluripotent state antigen. Additionally, by conducting a shotgun proteomic approach using LC-MS/MS, whole cell proteome of the adipose tissue MSCs of high-fat diet and normal diet mice were analyzed and identified proteins were evaluated via gene ontology and PPI network analysis. MSCs of obese mice showed senescent phenotype and altered cell cycle distribution due to a hostile environment with oxidative stress in adipose tissue where they reside. Additionally, the number of pluripotent markers expressing cells declined in the MSC population of the high-fat diet mice. Gene expression analysis evidenced the loss of stemness with a decrease in the expression of stemness-associated genes. Of the proteomic comparison of the normal and the high-fat diet group, MSCs revealed that stemness-associated molecules were decreased while inflammation and senescence-associated phenotypes emerged in obese mice MSCs. Our results showed us that the MSCs of adipose tissue may lose their stemness properties due to obesity-associated stress conditions. [ABSTRACT FROM AUTHOR]

Golden jackal optimization (GJO) is inspired by mundane characteristics and collaborative hunting behaviour, which mimics foraging, trespassing and encompassing, and capturing prey to refresh a jackal's position. However, the GJO has several limitations, such as a slow convergence rate, low computational accuracy, premature convergence, poor solution efficiency, and weak exploration and exploitation. To enhance the global detection ability and solution accuracy, this paper proposes a novel complex-valued encoding golden jackal optimization (CGJO) to achieve function optimization and engineering design. The complex-valued encoding strategy deploys a dual-diploid organization to encode the real and imaginary portions of the golden jackal and converts the dual-dimensional encoding region to the single-dimensional manifestation region, which increases population diversity, restricts search stagnation, expands the exploration area, promotes information exchange, fosters collaboration efficiency and improves convergence accuracy. CGJO not only exhibits strong adaptability and robustness to achieve supplementary advantages and enhance optimization efficiency but also balances global exploration and local exploitation to promote computational precision and determine the best solution. The CEC 2022 test suite and six real-world engineering designs are utilized to evaluate the effectiveness and feasibility of CGJO. CGJO is compared with three categories of existing optimization algorithms: (1) WO, HO, NRBO and BKA are recently published algorithms; (2) SCSO, GJO, RGJO and SGJO are highly cited algorithms; and (3) L-SHADE, LSHADE-EpsSin and CMA-ES are highly performing algorithms. The experimental results reveal that the effectiveness and feasibility of CGJO are superior to those of other algorithms. The CGJO has strong superiority and reliability to achieve a quicker convergence rate, greater computation precision, and greater stability and robustness. [ABSTRACT FROM AUTHOR]

Metabolic disorders such as insulin resistance and type 2 diabetes are associated with brain dysfunction and cognitive deficits, although the underpinning molecular mechanisms remain elusive. Epigenetic factors, such as non-coding RNAs, have been reported to mediate the molecular effects of nutrient-related signals. Here, we investigated the changes of miRNA expression profile in the hippocampus of a well-established experimental model of metabolic disease induced by high fat diet (HFD). In comparison to the control group fed with standard diet, we observed 69 miRNAs exhibiting increased expression and 63 showing decreased expression in the HFD mice's hippocampus. Through bioinformatics analysis, we identified numerous potential targets of the dysregulated miRNAs, pinpointing a subset of genes regulating neuroplasticity that were targeted by multiple differentially modulated miRNAs. We also validated the expression of these synaptic and non-synaptic proteins, confirming the downregulation of Synaptotagmin 1 (SYT1), calcium/calmodulin dependent protein kinase I delta (CaMK1D), 2B subunit of N-methyl-D-aspartate glutamate receptor (GRIN2B), the DNA-binding protein Special AT-Rich Sequence-Binding Protein 2 (SATB2), and RNA-binding proteins Cytoplasmic polyadenylation element-binding protein 1 (CPEB1) and Neuro-oncological ventral antigen 1 (NOVA1) in the hippocampus of HFD mice. In summary, our study offers a snapshot of the HFD-related miRNA landscape potentially involved in the alterations of brain functions associated with metabolic disorders. By shedding light on the specific miRNA-mRNA interactions, our research contributes to a deeper understanding of the molecular mechanisms underlying the effects of HFD on the synaptic function. [ABSTRACT FROM AUTHOR]