A scoping review of somatosensory interaction design for mental health and well-being.

This study explores the efficacy of somatosensory interactions in enhancing mental health care by examining the deployment and impact of these technologies. Based on a scoping review of 46 research studies, our analysis reveals that traditional mental health interventions often fail to align with prevalent technological trends. However, somatosensory interactions bridge this gap by creating immersive and engaging experiences.

Estimating in vivo power deposition density in thermotherapies based on ultrasound thermal strain imaging.

In thermal therapies, accurate estimation of in-tissue power deposition density (PDD) is essential for predicting temperature distributions over time or regularizing temperature imaging. Based on our previous work on ultrasound thermometry, namely, multi-thread thermal strain imaging (MT-TSI), this work develops an in vivo PDD estimation method. Specifically, by combining the TSI model infinitesimal echo strain filter with the bio-heat transfer theory (the Pennes equation), a finite-difference time-domain model is established to allow online extraction of the PDD.

Heatstroke characteristics and meteorological conditions in Hefei, China: thresholds and driving factors.

Background: Due to climate change and rapid urbanization, the frequency of heatwave events in East China has increased considerably since the 21st century, which has a considerable influence on human health, such as heatstroke. However, few studies have been conducted in this region on the relationship between heatstroke and meteorological conditions. To address this point, this study aimed to analyze the characteristics of heatstroke and their relationship with meteorological conditions in Hefei, China.

A dual-stream model based on PRNU and quaternion RGB for detecting fake faces.

The forensic examination of AIGC(Artificial Intelligence Generated Content) faces poses a contemporary challenge within the realm of color image forensics. A myriad of artificially generated faces by AIGC encompasses both global and local manipulations. While there has been noteworthy progress in the forensic scrutiny of fake faces, current research primarily focuses on the isolated detection of globally and locally manipulated fake faces, thus lacking a universally effective detection methodology.

Intelligent classification of computer vulnerabilities and network security management system: Combining memristor neural network and improved TCNN model.

To enhance the intelligent classification of computer vulnerabilities and improve the efficiency and accuracy of network security management, this study delves into the application of a comprehensive classification system that integrates the Memristor Neural Network (MNN) and an improved Temporal Convolutional Neural Network (TCNN) in network security management. This system not only focuses on the precise classification of vulnerability data but also emphasizes its core role in strengthening the network security management framework. Firstly, the study designs and implements a neural network model based on memristors.

Molecular Engineering of Amino Acid Crystals with Enhanced Piezoelectric Performance for Biodegradable Sensors.

Amino acid crystals have emerged as promising piezoelectric materials for biodegradable and biocompatible sensors; however, their relatively low piezoelectric coefficients constrain practical applications. Here, we introduce a fluoro-substitution strategy to overcome this limitation and enhance the piezoelectric performance of amino acid crystals. Specifically, we substituted hydrogen atoms on the aromatic rings of L-tryptophan, L-phenylalanine, and N-Cbz-L-phenylalanine with fluorine, resulting in significantly elevated piezoelectric coefficients.

Temperature seasonality regulates organic carbon burial in lake.

Organic carbon burial (OCB) in lakes, a critical component of the global carbon cycle, surpasses that in oceans, yet its response to global warming and associated feedbacks remains poorly understood. Using a well-dated biomarker sequence from the southern Tibetan Plateau and a comprehensive analysis of Holocene total organic carbon variations in lakes across the region, here we demonstrate that lake OCB significantly declined throughout the Holocene, closely linked to changes in temperature seasonality. Process-based land surface model simulations clarified the key impact of temperature seasonality on OCB in lakes: increased seasonality in the early Holocene saw warmer summers enhancing ecosystem productivity and organic matter deposition, while cooler winters improved organic matter preservation.

Zero-Trust Access Control Mechanism Based on Blockchain and Inner-Product Encryption in the Internet of Things in a 6G Environment.

Within the framework of 6G networks, the rapid proliferation of Internet of Things (IoT) devices, coupled with their decentralized and heterogeneous characteristics, presents substantial security challenges. Conventional centralized systems face significant challenges in effectively managing the diverse range of IoT devices, and they are inadequate in addressing the requirements for reduced latency and the efficient processing and analysis of large-scale data. To tackle these challenges, this paper introduces a zero-trust access control framework that integrates blockchain technology with inner-product encryption.

Preparation of CHS-FeO@@ZIF-8 peroxidase-mimic with an ultra-thin hollow layer for ultrasensitive electrochemical detection of kanamycin.

A highly sensitive and selective electrochemical biosensor was developed for the detection of kanamycin using a core-hollow-shell structured peroxidase-mimic nanozyme, CHS-Fe₃O₄@@ZIF-8. The synthesized CHS-FeO@@ZIF-8 was characterized with scanning electron microscopy, transmission electron microscopy, and X-ray photoelectron spectroscopy. It was found that the CHS-FeO@@ZIF-8 exhibits excellent peroxidase-like activity due to  its ultra-thin hollow layer.

Role of copper homeostasis and cuproptosis in heart failure pathogenesis: implications for therapeutic strategies.

Copper is an essential micronutrient involved in various physiological processes in various cell types. Consequently, dysregulation of copper homeostasis-either excessive or deficient-can lead to pathological changes, such as heart failure (HF). Recently, a new type of copper-dependent cell death known as cuproptosis has drawn increasing attention to the impact of copper dyshomeostasis on HF.

Quantification of Fugitive Carbon Emissions from Uncontrolled Combustion in Coal Fire Area: the Sandaoba Coalfield, Xinjiang, China.

Spontaneous coal fires are a significant source of greenhouse gas emissions, contributing to global warming. However, the lack of reliable estimation methods and research has obscured the full environmental impact of these emissions. This paper presents a novel quantification method for fugitive carbon emissions from spontaneous coal combustion.

Trade-offs of different types of dose-responses following temporal gradients of Pb stress in tillandsia usneoides.

The dose-response relationship between toxicants and organisms is the most fundamental principle in toxicological risk assessment. However, multiphasic non-linear responses are poorly understood and the underlying mechanisms remain elusive. In this study, we subjected the indicator plant Tillandsia usneoides to 5 or 10 time gradients of 1 mM Pb, and assessed the response patterns of five damage markers and eight resistance markers in the leaves.

Differentiation of early-stage endometrial carcinoma from benign endometrial lesions: a comparative study of six diffusion models.

Background: Accurate differentiation between benign and malignant endometrial lesions holds substantial clinical importance. This study aimed to evaluate the efficacy of various diffusion models in the preoperative diagnosis of early-stage endometrial carcinoma (EC).

Methods: A total of 72 consecutive patients with benign or malignant endometrial lesions from the First People's Hospital of Yunnan Province were prospectively enrolled between April 2021 and July 2023.

A Spiro-Based NIR-II Photosensitizer with Efficient ROS Generation and Thermal Conversion Performances for Imaging-Guided Tumor Theranostics.

Organic photosensitizers (PSs) possessing NIR-II emission and photodynamic/photothermal effect have received a great sense of attention for their cutting-edge applications in imaging-guided multimodal phototherapy. However, it is highly challenging to design efficient PSs with high luminescence and phototherapy performance simultaneously. In this study, a spiro-functionalization strategy is proposed to alleviate aggregate-caused quenching of PSs and promote photodynamic therapy, and the strategy is verified via a spiro[fluorine-9,9'-xanthene]-modified NIR-II PS (named SFX-IC) with an acceptor-donor-acceptor configuration.

Association between exposure to environmental pollutants and increased oral health risks, a comprehensive review.

The burden of disease and death attributable to environmental pollution is a growing public health challenge worldwide, particularly in developing countries. While the adverse effects of environmental pollution on oral health have garnered increasing attention, a comprehensive and systematic assessment remains lacking. This article delves into the intricate relationship between environmental pollution and oral health, highlighting significant impacts on various aspects such as dental caries, periodontal diseases, oral facial clefts, cancer, as well as other oral diseases.

Double weighted combat data quality evaluation method based on CVF optimized FAHP.

During multi-agent combat simulation exercises, accurately assessing the quality of collected combat data is a critical step. Addressing the current issue of low accuracy in combat data quality evaluation, which fails to effectively support simulation exercises, this paper proposes a Double-Weighted FAHP optimized by CVF (comparative value function) method for assessing combat data quality. First, a three-tiered evaluation framework for combat data quality indicators is established, with threshold values determined for each indicator.

Increasing certainty in projected local extreme precipitation change.

The latest climate models project widely varying magnitudes of future extreme precipitation changes, thus impeding effective adaptation planning. Many observational constraints have been proposed to reduce the uncertainty of these projections at global to sub-continental scales, but adaptation generally requires detailed, local scale information. Here, we present a temperature-based adaptative emergent constraint strategy combined with data aggregation that reduces the error variance of projected end-of-century changes in annual extremes of daily precipitation under a high emissions scenario by >20% across most areas of the world.

Enhanced dielectric losses in α-MnO protonation modulation.

MnO octahedra without distortions in α-MnO have a low dipole content, which limits their dielectric loss capabilities. Herein, we develop protonated MnO with distorted MnO octahedra for increased dipole numbers a two-step hydrothermal method. In comparison with α-MnO, this protonated MnO provides greatly improved dipole polarization loss capabilities, resulting in a reflection loss value of -19.

Pervasive aquatic vegetation organic carbon losses in China's lakes.

One of the major global concerns is to mitigate carbon dioxide emissions to addressing the detrimental impacts of climate change. Aquatic vegetation, as a natural carbon pool, offers a potential solution to such problems. However, a crucial impediment is the absence of comprehensive estimates of its organic carbon storage.

Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodetector.

Identifying and quantifying the dominant factors influencing heavy metal (HM) pollution sources are essential for maintaining soil ecological health and implementing effective pollution control measures. This study analyzed soil HM samples from 53 different land use types in Jiaozuo City, Henan Province, China. Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation.

Striking Improvement of N Selectivity in NH Oxidation Reaction on FeO-Based Catalysts via SiO Doping.

The emission of NH has been reported to pose a serious threat to both human health and the environment. To efficiently eliminate NH, catalysts for the selective catalytic oxidation of NH (NH-SCO) have been intensively studied. FeO-based catalysts were found to exhibit superior NH oxidation activity; however, the low N selectivity made it less attractive in practical applications.

Sources of PM exposure and health benefits of clean air actions in Shanghai.

Estimating PM exposure and its health impacts in cities involves large uncertainty due to the limitations of model resolutions. Consequently, attributing the sources of PM-related health impacts at the city level remains challenging. We characterize the health impacts associated with chronic PM exposure and anthropogenic emissions in Shanghai using a chemical transport model (GEOS-Chem) and its adjoint.

Glo-net: A dual task branch based neural network for multi-class glomeruli segmentation.

Accurate segmentation and classification of glomeruli are fundamental to histopathology slide analysis in renal pathology, which helps to characterize individual kidney disease. Accurate segmentation of glomeruli of different types faces two main challenges compared to traditional primitives segmentation in computational image analysis. Limited by small kernel size, traditional convolutional neural networks could hardly understand the complete context information of different glomeruli.

Symmetric deformable registration of multimodal brain magnetic resonance images via appearance residuals.

Background And Objective: Deformable registration of multimodal brain magnetic resonance images presents significant challenges, primarily due to substantial structural variations between subjects and pronounced differences in appearance across imaging modalities.

Methods: Here, we propose to symmetrically register images from two modalities based on appearance residuals from one modality to another. Computed with simple subtraction between modalities, the appearance residuals enhance structural details and form a common representation for simplifying multimodal deformable registration.