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Hybrid precoding is considered as a promising low-cost technique for millimeter wave (mm-wave) massive Multi-Input Multi-Output (MIMO) systems. In this work, referring to the time-varying propagation circumstances, with semi-supervised Incremental Learning (IL), we propose an online hybrid beamforming scheme. Firstly, given the constraint of constant modulus on analog beamformer and combiner, we propose a new broad-network-based structure for the design model of hybrid beamforming. Compared with the existing network structure, the proposed network structure can achieve better transmission performance and lower complexity. Moreover, to enhance the efficiency of IL further, by combining the semi-supervised graph with IL, we propose a hybrid beamforming scheme based on chunk-by-chunk semi-supervised learning, where only few transmissions are required to calculate the label and all other unlabelled transmissions would also be put into a training data chunk. Unlike the existing single-by-single approach where transmissions during the model update are not taken into the consideration of model update, all transmissions, even the ones during the model update, would make contributions to model update in the proposed method. During the model update, the amount of unlabelled transmissions is very large and they also carry some information, the prediction performance can be enhanced to some extent by these unlabelled channel data. Simulation results demonstrate the spectral efficiency of the proposed method outperforms that of the existing single-by-single approach. Besides, we prove the general complexity of the proposed method is lower than that of the existing approach and give the condition under which its absolute complexity outperforms that of the existing approach.

Abstract With the continuous increase in carbon dioxide emissions due to human activities and the resulting severe climate issues, there is global concern about energy conservation and emission reduction. However, detailed data on energy consumption and emissions at a fine-grained scale, particularly regarding spatial dimensions and sector-specific emissions, remains insufficient and in need of refinement and timely updates. In Japan, following the Fukushima nuclear disaster, there has been a significant shift from nuclear power generation to reliance on fossil fuels across various sectors, highlighting disparities in emissions data across different regions and industries. Our work extends the emissions time series for Japan’s 47 prefectures, incorporating their socioeconomic characteristics over a broader time frame and with a more detailed sectoral classification. The emissions inventory, covering the period from 1990 to 2020, is based on the consumption of the three main fossil fuels across 32 sectors, with emissions carefully allocated for regional power generation. This dataset, presented in a unified format, is expanded to include longer time scales and more detailed socioeconomic data. It is anticipated to offer crucial insights for establishing regional emission reduction targets and identifying sectoral priorities for decarbonization.

Abstract Urban livability has become a major policy and practice priority in many parts of the world. However, its attainment remains challenging in many cities of developing and emerging economies. The lack of data with appropriate quality, coverage, and spatial and temporal resolution often complicates both the assessment of livability in such cities and the identification of priority areas for improvement. Here we develop a framework to mobilize and synthesize open-source data to analyze spatially urban livability patterns in Shanghai. The framework brings together diverse types of open-source data including housing characteristics, population distribution, transportation networks, and points of interest to identify city areas with low livability, and thus priority areas for improvement. Such findings can provide a comprehensive overview of the residential living conditions in Shanghai, as well as useful information to urban planners and decision-makers. Furthermore, subject to data availability, the proposed method has the potential for application in other cities.

Summary: Stem cell therapy for intrauterine adhesions (IUAs) has been widely used in clinical treatment. However, intravenous injection lacks sufficient targeting capabilities, while in situ injection poses challenges in ensuring the effective survival of stem cells. Furthermore, the mechanism underlying the interaction between stem cells and endometrial cells in vivo remains poorly understood, and there is a lack of suitable in vitro models for studying these problems. Here, we designed an extracellular matrix (ECM)-adhesion mimic hydrogel for intrauterine administration, which was more effective than direct injection in treating IUAs. Additionally, we analyzed the epithelial-mesenchymal transition (EMT) and confirmed that the activation of endometrial epithelial stem cells is pivotal. Our findings demonstrated that umbilical cord mesenchymal stem cells (UC-MSCs) secrete WNT7A to activate endometrial epithelial stem cells, thereby accelerating regeneration of the endometrial epithelium. Concurrently, under transforming growth factor alpha (TGFA) stimulation secreted by the EMT epithelium, UC-MSCs upregulate E-cadherin while partially implanting into the endometrial epithelium.

To reveal the role of gut microbiota (GM) in the occurrence and development of idiopathic central precocious puberty (ICPP) using 16S rDNA sequencing and bioinformatics analysis. The Danazol-induced ICPP model was successfully constructed in this study. ZBDH and GnRHa treatments could effectively inhibit ICPP in rats, as manifested by the delayed vaginal opening time, reduced weight, decreased uterine organ coefficient, and decreased uterine wall thickness and corpus luteum number, as well as remarkably reduced serum hormone (LH, FSH, and E2) levels. According to 16S rDNA sequencing analysis results, there was no significant difference in the GM community diversity across different groups; however, the composition of the microbial community and the abundance of the dominant microbial community were dramatically different among groups. ZBDH and GnRHa treatments could effectively reduce the abundance of Muribaculateae and Lactobacillus and promote Prevotella abundance. ZBDH and GnRHa were effective in treating Danazol-induced ICPP model rats. The therapeutic effects of ZBDH and GnRHa could be related to the changes in GM in rats.

Abstract Food consumption, which delivers fundamental energy and essential nutrients to human beings, is crucial for achieving a series of sustainable goals. Alongside rising population growth and living standards, there has been a significant increase in food cultivation demands, supply chain complexities, and waste management. Therefore, to protect human health and the environment, promoting sustainable food systems and the uptake of sustainable dietary habits are vital. Yet, information on the environmental and health impact of dietary choices remains inconsistent across multiple evaluation methods, which fail to deliver essential ideas to consumers. In this study, we formulate an integrated approach using Environmentally Extended Input-Output analysis, covering the food supply chain from production to the distribution phase, complemented with a hybrid Life Cycle Assessment for cooking and disposal processes, to quantify the carbon footprint of specific recipes. Our dataset also includes the distinct nutritional values of each recipe. This dataset not only informs the food industry and recipe platforms, enabling more sustainable choices, but also helps individuals balance nutritional value with environmental impact, leading to more informed and sustainable dietary decisions.

Summary: The household sector is a major source of greenhouse gas (GHG) emissions and is key to achieving decarbonization targets. Household characteristics, influenced by demographic transitions such as population aging and shrinking, have a profound impact on energy use and emissions. This study explores how demographic changes in Japan may affect long-term emission mitigation in the household sector through the adoption of photovoltaics (PVs) and new energy vehicles (NEVs) under various scenarios for 2040. Using a comprehensive survey of 9,996 households, we develop a nuanced typology of households to understand variations in emissions and mitigation technology adoption. Household size and age emerge as key factors influencing emissions. The findings reveal that the increasing prevalence of smaller and elderly households may impede emission mitigation efforts in Japan, posing substantial obstacles to achieving long-term decarbonization goals in the household sector. Science for society: In the quest for a sustainable future, understanding the relationship between demographic change and climate change becomes paramount, as demographic shifts directly impact energy consumption patterns and the effectiveness of interventions. This study reveals how demographic transitions in Japan influence household-level energy consumption and greenhouse gas emissions. Different household types exhibit varied patterns in emissions and the adoption of green technologies such as photovoltaics and new energy vehicles. This is shaped by factors such as people’s age, household size, and income. Demographic transitions toward smaller and elderly households will complicate achieving decarbonization in the household sector. The work emphasizes that a sustainable, low-carbon future requires a deep understanding of societal shifts and needs. It calls for tailored approaches in the household sector to manage climate change, particularly in societies experiencing demographic transitions.

Abstract Household consumption significantly contributes to greenhouse gas emissions as it is the largest component of final demand in the national accounting system. Nevertheless, there is an apparent lack of comprehensive and consistent datasets detailing emissions from household consumption. Here, we expand and update Japan’s multiscale monthly household carbon footprint from January 2011 to September 2022, combining data from government statistics and surveys. We constructed a dataset comprising 37,692 direct and 4,852,845 indirect emission records, covering households at the national, regional, and prefectural city levels. The dataset provides critical spatiotemporal information that allows for revealing carbon emission patterns, pinpointing primary sources of emissions, and discerning regional variances. Moreover, the inclusion of micro-scale carbon footprint data enables the identification of specific consumption habits, thereby regulating individual consumption behavior to achieve a low-carbon society.

Colorectal cancer (CRC) is one of the deadliest cancers worldwide. Numerous studies have reported a correlation between uric acid (UA) level and CRC risk. Here, we investigated the role and prognostic value of UA-related genes in CRC progression. CRC-associated gene expression and clinical data were retrieved from The Cancer Genome Atlas (TCGA), and UA-related genes were identified by overlapping the TCGA and GeneCards databases. The Gene Ontology annotation, Kyoto Encyclopedia of Genes and Genomes pathway, and Molecular Signatures Database dataset were subjected to gene set enrichment analysis. A prognostic model was constructed using the univariate and multivariate COX regression and least absolute shrinkage and selection operator (LASSO) analyses and validated using the Gene Expression Omnibus cohort. Competing endogenous RNA network, CellMiner, and Human Protein Atlas were used to detect the signature of 13 UA-related genes in the prediction model. The expression of five potential UA-related genes in CRC cell lines was confirmed via qPCR. CIBERSORT was used to evaluate immune cell infiltration in the TCGA-CRC dataset. Thirteen highly prognostic UA-related genes were used to construct a prognostic model of CRC with risk score accuracy and predictive efficacy. Abundance of activated M0 macrophages, monocytes, CD8+ T cells, and natural killer cells positively correlated with the risk score. Five promising UA-related genes showed higher expression levels in CRC than in colonic cell lines. Thus, our model posits a direct relationship between UA-related genes and CRC risk, offering novel insights into diagnosis, prognosis, and treatment.

Background Anti-β2GPI-domain I (β2GPI-DI) antibody is pathogenic in patients with antiphospholipid syndrome (APS), but its additional clinical associations and diagnostic value are controversial.Methods A total of 378 patients were included, of which 119 patients diagnosed with primary APS, 50 with APS secondary to SLE (SAPS group), 209 with SLE without APS (SLE group). Serum anti-β2GPI-DI IgG was measured using chemiluminescent immunoassay. Extra-criteria manifestations were analysed, including thrombocytopenia, autoimmune haemolytic anaemia, valvular lesions, APS nephropathy and non-vascular neurological manifestations.Results In 169 patients with APS, 55 (32.5%) were positive for anti-β2GPI-DI IgG, accounting for 77.5% of those with anti-β2GPI IgG positivity. It is shown that 96.4% of those with anti-β2GPI-DI IgG also showed triple positivity in classic antiphospholipid antibodies (aPLs). The positivity of anti-β2GPI-DI IgG was significantly associated with recurrent thrombosis before APS diagnosis (p=0.015), microvascular thrombosis (p=0.038), but not with pregnancy morbidity (PM). Notably, patients with extra-criteria manifestations showed significantly higher positivity (p=0.001) and titres (p

Abstract The recent emergence of non‐fullerene acceptors (NFAs) has energized the field of organic photodiodes (OPDs) and made major breakthroughs in their critical photoelectric characteristics. Yet, stabilizing inverted NF‐OPDs remains challenging because of the intrinsic degradation induced by improper interfaces. Herein, a tin ion‐chelated polyethyleneimine ethoxylated (denoted as PEIE‐Sn) is proposed as a generic cathode interfacial layer (CIL) of NF‐OPDs. The chelation between tin ions and nitrogen/oxygen atoms in PEIE‐Sn contributes to the interface compatibility with efficient NFAs. The PEIE‐Sn can effectively endow the devices with optimized cascade alignment and reduced interface defects. Consequently, the PEIE‐Sn‐OPD exhibits properties of anti‐environmental interference, suppressed dark current, and accelerated interfacial electron extraction and transmission. As a result, the unencapsulated PEIE‐Sn‐OPD delivers high specific detection and fast response speed and shows only slight attenuation in photoelectric performance after exposure to air, light, and heat. Its superior performance outperforms the incumbent typical counterparts (ZnO, SnO2, and PEIE as the CILs) from metrics of both stability and photoelectric characteristics. This finding suggests a promising strategy for stabilizing NF‐OPDs by designing appropriate interface layers.

Abstract As urbanization accelerates worldwide, substantial energy and services are required to meet the demand from cities, making cities major contributors to adverse environmental consequences. To bridge the knowledge gap in the absence of fine-grained city-level climate protection measures due to data availability and accuracy, this study provides a detailed carbon emission inventory for analyzing the monthly fluctuations based on citizens’ daily consumption behaviors. Here, carbon emissions embodied in approximately 500 household consumption items were calculated in 47 prefectural-level cities in Japan from 2011 to June 2021. We analyzed the results considering the regional, seasonal, demand, and emission way-specific aspects, and compared the emission before and during the COVID-19 pandemic. Notably, the carbon footprints during the pandemic were consistent with the previous level despite downtrends in specific categories. This study provides an example of utilizing city-level emission data to improve household green consumption behavior as references for enriching city-level decarbonization paths.

Abstract Skin infections caused by drug-resistant Staphylococcus aureus occur at high rates nationwide. Mouse primary epidermal organoids (mPEOs) possess stratified histological and morphological characteristics of epidermis and are highly similar to their derived tissue at the transcriptomic and proteomic levels. Herein, the susceptibility of mPEOs to methicillin-resistant S. aureus USA300 infection was investigated. The results show that mPEOs support USA300 colonization and invasion, exhibiting swollen epithelial squamous cells with nuclear necrosis and secreting inflammatory factors such as IL-1β. Meanwhile mPEOs beneficial to observe the process of USA300 colonization with increasing infection time, and USA300 induces mPEOs to undergo pyroptosis and autophagy. In addition, we performed a drug screen for the mPEO infection model and showed that vancomycin restores cell viability and inhibits bacterial internalization in a concentration-dependent manner. In conclusion, we establish an in vitro skin infection model that contributes to the examination of drug screening strategies and antimicrobial drug mechanisms.

Acute kidney injury (AKI) leads to unacceptably high mortality due to difficulties in timely intervention and less efficient renal delivery of therapeutic drugs. Here, a series of polyvinylpyrrolidone (PVP)-curcumin nanoparticles (PCurNP) are designed to meet the renal excretion threshold (∼45 kDa), presenting a controllable delivery nanosystem for kidney targeting. Renal accumulation of the relatively small nanoparticles, 89Zr-PCurNP M10 with the diameter between 5 and 8 nm, is found to be 1.7 times and 1.8 times higher than the accumulation of 89Zr-PCurNP M29 (20–50 nm) and M40 (20–50 nm) as revealed by PET imaging. Furthermore, serum creatinine analysis, kidney tissues histology, and tubular injury scores revealed that PCurNP M10 efficiently treated cisplatin-induced AKI. Herein, PCurNP offers a novel and simple strategy for precise PET image-guided drug delivery of renal protective materials.

Examining household carbon emissions through a supply chain perspective reveals the climate impact of consumption behaviors and variations across societal structures and features. Despite the evident and expanding environmental inequality, strategies for its mitigation and prioritization remain debated. This study investigates the origins of carbon emission inequalities from household consumption, using Japan as a case study, a society characterized by aging demographics and comparatively equal income redistribution. By quantitatively analyzing household carbon footprints, we observe a U-shaped distribution in emissions as income levels increase. Notably, the carbon footprint sizes are strikingly similar between the lowest and highest income groups, yet inequalities emerge in education and investments in future generations. Integrating these findings, this study further conducts a scenario analysis to project shifts in future low-carbon lifestyles, indicating that middle-income groups are more prone to achieving personal-level decarbonization. This projection is vital in understanding how to effectively address carbon footprint inequalities, especially considering the entrenched preferences in wealthier demographics for investing in future generations.

Triple combination conversion therapy, involving transcatheter arterial chemoembolization (TACE) or hepatic arterial infusion chemotherapy (HAIC) combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), has shown an encouraging objective response rate (ORR) and successful conversion surgery rate in initially unresectable hepatocellular carcinoma (HCC). However, the safety and long-term survival outcomes of subsequent liver resection after successful conversion still remain to be validated. From February 2019 to February 2023, 726 patients were enrolled in this retrospective study (75 patients received hepatectomy after conversion therapy [CLR group], and 651 patients underwent pure hepatectomy [LR group]). Propensity score matching (PSM) was used to balance the preoperative baseline characteristics. After PSM, 68 patients in the CLR group and 124 patients in the LR group were analyzed, and all the matching variables were well-balanced. Compared with the LR group, the CLR group experienced longer Pringle maneuver time, longer operation time, and longer hospital stays. In addition, the CLR group had significantly higher incidence rates of intra-abdominal bleeding, biliary leakage, post-hepatectomy liver failure (PHLF), and Clavien–Dindo grade IIIa complications than the LR group. There were no significant statistical differences in overall survival (OS) (hazard ratio [HR] 0.724; 95% confidence interval [CI] 0.356–1.474; p = 0.374) and recurrence-free survival (RFS) (HR 1.249; 95% CI 0.807–1.934; p = 0.374) between the two groups. Liver resection following triple combination conversion therapy in initially unresectable HCC may achieve favorable survival outcomes with manageable safety profiles; presenting as a promising treatment option for initially unresectable HCC.

Abstract Hydrocarbons and carbon oxides are typical dissolved gases in transformer oil that reflect the latent pitfalls, on‐line monitoring of their concentrations can effectively evaluate the operating status of the power transformer. However, these low‐concentration targets (especially for CH4) show high chemical inertness at room temperature, challenging the sensitive performance of current commonly used chemiresistive gas sensors. Herein, a strategy by combining traditional inorganic semiconductors to carbon nanofiber (CNF) via electrospinning–annealing route is described. Three optimized 3D mosaic films, CNFs scaffold incorporated with WO3, SnO2 and MoS2 nanoparticles, are obtained. Due to the large specific surface area of the 3D network, and the synergic and heterojunction effects between nanoparticles and CNFs, all three sensors exhibit high response to CH4 at room temperature, and also record distinguishable signals toward H2, C2H4, CO and CO2, revealing the three sensors are cross‐sensitive to the five analytes. Accordingly, preliminary discrimination of five dissolved gases is realized by principle component analysis. This study provides an effective and extendable solution of preparing room‐temperature chemiresistive sensors for the detection of CH4 and other gases, and offers a strategy for the construction of sensor array to achieve a high discrimination capability.

Unsupervised feature selection aims to derive a compact set of features with desired generalization ability via removing the irrelevant and redundant features, yet challenging due to the unavailability of labels. Works about unsupervised feature selection always need to construct the similarity matrix, which makes the selected features highly depend on the accuracy of similarity measurement. However, existing works usually leverage a single fixed metric to build similarity matrix, which cannot fit various feature types very well and even damage the local manifold structure. To address this problem, we propose an adaptive multi-metric fusion by automatically integrating similarity across different metrics according to the specific data. Besides, to capture the global structure more precisely, a novel low-rank approximation method is proposed, which is relatively insensitive to the rank-norm parameter. Via the proposed novel low-rank approximation method, better tradeoff between the performance and robustness can be provided. Experimental results show that the accuracy performance of the proposed method can be boosted by $2\%-11\%$ , compared with previous methods.

Measurement(s) carbon dioxide emission Technology Type(s) Consumption of Goods Factor Type(s) urban carbon footprint Sample Characteristic - Environment city Sample Characteristic - Location Japan Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.15188058

ABSTRACT Background: Among patients with acute ischemic stroke with a mismatch between deficit severity and infarct volume, thrombectomy performed within a 6-24 hours time window has efficacy and safety similar to treatment within 6 hours. However, whether magnetic resonance imaging with T2 diffusion-weighted imaging (DWI) is feasible remains to be validated. Objective: To investigate prognosis among stroke patients receiving endovascular treatment (EVT) within 6 hours and 6-24 hours using non-contrasted computed tomography (NCCT) and DWI. Methods: Overall, 209 anterior-circulation ischemic stroke patients with large-vessel occlusion who underwent EVT were divided into ≤ 6 hours and 6-24 hours groups. Patients presenting symptoms within 6 hours were treated if their NIHSS score was ≥ 7 and ASPECTS score was ≥ 5, whereas those with wake-up stroke (WUS) or presenting symptoms 6-24 hours after last seen well (WUS/late-presenting stroke, LPS) were managed if their NIHSS score was ≥ 7 and ASPECTS score was ≥ 5. Results: The percentages of patients undergoing intracranial stenting and intracranial ballooning without stenting significantly differed between two groups (p < 0.001). Grades 0, 1, 2a and 2b recanalization rates did not differ between the 6 hours and 6-24 hours groups (all p > 0.05). Grade 3 recanalization rate in the 6 hours group was significantly lower than in the 6-24 hours group (p = 0.043). The 3-month Rankin Scale score did not significantly differ between the two groups (p = 0.629). Conclusions: EVT is a safe and effective treatment for patients with WUS and LPS selected through NCCT and DWI-based simple imaging.

Abstract Households are responsible for a large fraction of the direct and indirect emissions of greenhouse gases (GHG) at the national level. However, emission patterns are not homogeneous within the residential sector, with several factors affecting them. This study explores how income‐related divergences in consumption and time allocation affect the carbon footprint of the Japanese residential sector. To achieve this, we combine data on emission intensities from national input‐output tables with household‐level consumption and time allocation data from two large‐scale nationally representative surveys. Overall, we find that indirect emissions account for approximately 78% of the overall carbon footprint of the residential sector across the studied income groups. The overall carbon footprint and the emissions of several individual consumption categories follow an N‐shaped curve, with some of the lower‐income groups having disproportionately higher emissions compared to middle‐ and higher‐income groups. Conversely, emissions for other individual consumption categories increase almost linearly with income. This points to the fact that different factors can affect emissions across income groups. Specifically, the N‐shaped curves are driven by the propensity of lower‐income households to spend more time at home and rely on inefficient technologies, while the linear trend is driven by the propensity of higher‐income households to consume more. A detailed understanding of how these factors affect emissions patterns can provide useful insights for designing and implementing effective policies to achieve decarbonization the residential sector.

Abstract Background Electrostimulation (ES) therapy for wound healing is limited in clinical use due to barriers such as cumbersome equipment and intermittent delivery of therapy. Methods We adapted a human skin xenograft model that can be used to directly examine the nanogenerator-driven ES (NG-ES) effects on human skin in vivo—an essential translational step toward clinical application of the NG-ES technique for wound healing. Results We show that NG-ES leads to rapid wound closure with complete restoration of normal skin architecture within 7 days compared to more than 30 days in the literature. NG-ES accelerates the inflammatory phase of wound healing with more rapid resolution of neutrophils and macrophages and enhances wound bed perfusion with more robust neovascularization. Conclusion Our results support the translational evaluation and optimization of the NG-ES technology to deliver convenient, efficient wound healing therapy for use in human wounds. Graphic abstract

Biodegradable electronics have great potential to reduce the environmental footprint of electronic devices and to avoid secondary removal of implantable health monitors and therapeutic electronics. Benefiting from the intensive innovation on biodegradable nanomaterials, current transient electronics can realize full components’ degradability. However, design of materials with tissue-comparable flexibility, desired dielectric properties, suitable biocompatibility and programmable biodegradability will always be a challenge to explore the subtle trade-offs between these parameters. In this review, we firstly discuss the general chemical structure and degradation behavior of polymeric biodegradable materials that have been widely studied for various applications. Then, specific properties of different degradable polymer materials such as biocompatibility, biodegradability, and flexibility were compared and evaluated for real-life applications. Complex biodegradable electronics and related strategies with enhanced functionality aimed for different components including substrates, insulators, conductors and semiconductors in complex biodegradable electronics are further researched and discussed. Finally, typical applications of biodegradable electronics in sensing, therapeutic drug delivery, energy storage and integrated electronic systems are highlighted. This paper critically reviews the significant progress made in the field and highlights the future prospects.

Abstract Although it has been emphasized for years, there remains insufficient knowledge on how to decompose the driving forces of carbon emissions that fluctuate with time, especially when considering the major natural or socio‐economic events. To bridge the knowledge gap, we use the structural decomposition analysis method and select Japan for a case study. The results show that such events were followed by temporary emission increases due to economic recovery, but the general decreasing trend of carbon emissions has been unchanged in a long run. In the case of Japan, during the financial crisis period (2005–2011), emissions increased due to production structure (136.2 Mt‐CO2) and consumption structure (61.8 Mt‐CO2). However, the intensity change and per capita consumption effect were the main driving forces that offset this increasing trend, which reduced by 209.7 Mt‐CO2 in total. After the 2011 earthquake, a significant gain in upgraded production structure led to a 78.2 Mt‐CO2 reduction until 2015, partially offset the 126.4 Mt‐CO2 increase caused by per capita consumption and export volume. In conclusion, although post‐event economic recovery has led to an increasing trend of carbon emissions, continuously optimized emission intensity and production structure are the major driving forces for repressing carbon emission rebound brought by unexpected events.

AIM: To investigate the effect of high concentration of glucose (HCG) on double stranded RNA-activated protein kinase-like ER kinase (PERK)-eukaryotic initiation factor-2α (eIF2α)-transcription factor C/EBP homologous protein (CHOP)-cysteine aspartate specific proteinase (caspase-12) signaling pathway activation and apoptosis in rabbit corneal epithelial cells (RCECs). METHODS: RCECs were treated by different concentrations of glucose for 0-48h. The expressions of PERK, p-PERK, eIF2α, p-eIF2α, 78 kDa glucose-regulated protein 78 (GRP78), CHOP, B-cell lymphoma 2 (Bcl-2), B-cell lymphoma-2-associated X protein (Bax) and caspase-12 were determined by Western blot. Apoptosis was detected by TUNEL assay. Meanwhile, the function of PERK-eIF2α-CHOP-caspase-12 signaling pathway activation in high glucose-induced apoptosis was evaluated using PERK inhibitor, GSK2606414. RESULTS: HCG significantly promoted the expression of p-PERK, p-eIF2α, GRP78, CHOP, Bax and cleaved caspase-12 in RCECs (P0.05). TUNEL assay showed that the apoptosis rate of RCECs in the HCG group increased significantly in contrast with that in the normal concentration of glucose or osmotic pressure control group (P0.05). Correspondingly, GSK2606414 also significantly reduced the apoptosis rate induced by high glucose (P

The promotion of new energy vehicles is a grand plan across countries to achieve carbon neutrality and air purification. The sale volume of new energy vehicles is affected by many factors, yet it is the attitude of consumers themselves that has the final decisive role. We use four representative Baidu search indexes as the variables representing the attention of consumers and take variables of economic, population, and income as control variables for regression analysis from the national and sub-economic regional perspectives respectively. Results show that search indexes of “new energy vehiclek.” “new energy vehicles battery”, and ‘charging pile’ all have significant positive impacts on the sales of new energy vehicles to varying degrees while the index of ‘automobile spontaneous combustion’ has a significant negative impact on the sale volume. This study, therefore, verifies that the consumer attention represented by search indexes is an important yet uncovered factor affecting the sale volume of new energy vehicles. Besides, due to people’s prejudice against spontaneous combustion accidents of new energy vehicles, consumers have a cognitive bias about the spontaneous combustion rate of new energy vehicles especially in less developed areas of China.

Abstract To comprehensively investigate how regional household contribute to national carbon emission, this paper evaluates both the direct and indirect Japanese household carbon‐based emissions by using an environmentally extended input‐output table as well as the regional household consumption inventory. The results indicate that the household sector is the key driving force behind Japan's emissions, and it accounts for approximately 80% of the country's total emissions when indirect emissions are included. Moreover, significant regional differences exist in terms of the carbon footprint, which is in part caused by household and fuel‐type differences found across the country. Finally, this paper suggests that the impact of regional household and fuel‐type differences on Japan's overall carbon footprint should be a primary focus when practitioners design customized strategies to decarbonize Japan at the subnational scale.

Abstract Wearable and implantable electroceuticals (WIEs) for therapeutic electrostimulation (ES) have become indispensable medical devices in modern healthcare. In addition to functionality, device miniaturization, conformability, biocompatibility, and/or biodegradability are the main engineering targets for the development and clinical translation of WIEs. Recent innovations are mainly focused on wearable/implantable power sources, advanced conformable electrodes, and efficient ES on targeted organs and tissues. Herein, nanogenerators as a hotspot wearable/implantable energy‐harvesting technique suitable for powering WIEs are reviewed. Then, electrodes for comfortable attachment and efficient delivery of electrical signals to targeted tissue/organ are introduced and compared. A few promising application directions of ES are discussed, including heart stimulation, nerve modulation, skin regeneration, muscle activation, and assistance to other therapeutic modalities.

Developing new technologies for the neuromodulation of the vagus nerve can enable therapeutic strategies for body weight control in obese patients. Here, the authors present a battery-free self-powered implantable vagus nerve stimulation system that electrically responds to stomach movement.

The transport sector is a major contributor to anthropogenic climate change through the emissions of large amounts of greenhouse gases from fossil fuel combustion. Private vehicles account for almost half of the transport energy demand, and are thus a major target for climate change mitigation efforts. However, emissions from private vehicles can have large variability due to various geographic, demographic and socioeconomic factors. This study aims to understand how such factors affect private vehicle emissions in Japan using a nationally representative survey of household energy consumption ( n = 7370) for 2017. The results indicate a large temporal and spatial variability in private vehicle emissions. Annual emissions show three peaks associated with major holiday seasons in winter and summer. Some of the more noteworthy spatial patterns are the higher emissions in prefectures characterized by low population density and mountainous terrain. Income, city size and the fuel-saving driving behavior all have a significant effect on emissions. The results indicate the need for sub-regional and socioeconomically-sensitive mitigation efforts that reflect the very different emission patterns, and the factors affecting them. The strong effect of city size, which is often much more clear-cut than between prefectures, suggests that it is more appropriate to approach transport decarbonization in Japan at the city level.

Abstract As a fundamental and ubiquitous body motion, respiration offers a large amount of biomechanical energy with an average power up to the Watt level through movements of multiple muscles. The energy from respiration featured with excellent stability, accessibility and continuality inspires the design and engineering of biomechanical energy harvesting devices, such as triboelectric nanogenerators (TENGs), to realize human‐powered electronics. This review article is thus dedicated to the emerging respiration‐driven TENG technology, covering fundamentals, applications, and perspectives. Specifically, the human breathing mechanics are first introduced serving as the base for the developments of TENG devices with different configurations. Biomedical applications including electrical energy generation, healthcare monitoring, air filtration, gas sensing, electrostimulation, and powering implantable medical devices are then analyzed focusing on the design‐application relationships. At last, current developments are summarized and critical challenges for driving these intriguing developments toward practical applications are discussed together with promising solutions.

Acid rain with a relatively high concentration of ammonium and nitrate can accelerate rock weathering. However, its impact on groundwater nitrate is uncertain. This study evaluated the dual isotopic composition of nitrate (δ15N-NO3- and δ18O-NO3-) from precipitation to groundwater in a rural mountainous area affected by acid rain. The average concentration for NH4+ is 1.25 mg/L and NO3- is 2.59 mg/L of acid rain. Groundwater NO3- concentrations ranged from

Aiming to store water in wet seasons and outflow water in dry seasons, and improve reservoirs’ performance, are of great importance. Given the developmental disparities across regions and uneven precipitation within one year, water transfer could be an efficient solution. Here, we formulated a three-stage decision-making framework to simulate possible hydrological, meteorological, economic, and demographic parameters in future scenarios and proposed a market-based dynamic multi-objective optimization model, which optimized the adjusted water allocation and water transfers strategies among regions. A case study was conducted in the Yiluo river basin to evaluate the optimal proportion of local water use and water transfers to verify the application and its effects. Results indicated that water use stress and environmental stress could be relieved from four simulated future scenarios, which further accelerated region- and basin-scale sustainability. The results also gave valuable insights into optimal water use options and transferred to maximize the economic, social, and environmental benefits and climate mitigation.

The baseline quality of pre-drilling shallow groundwater is essential for the evaluation of potential environmental impacts of shale gas development. The Xishui region in the northern Guizhou Province of Southwest China has the potential for shale gas development but there is a lack of commercial production. As for the future environmental concerns in this undeveloped area, this study presented the hydrochemical and isotopic characteristics of shallow groundwater and its dissolved gas before shale gas development and determined the sensitive monitoring indicators. Results showed that shallow groundwater with an average pH of 7.73 had low total dissolved solids (TDS) ranging between 102 and 397 mg/L, with the main water chemistry types of HCO3-Ca and HCO3-Ca·Mg. The quality of most groundwater samples satisfied the drinking water standards of China. The mass concentration of dissolved methane in groundwater was below the detection limit (13C-DIC, 87Sr/86Sr, and δ11B. Evidence from carbon isotopes of dissolved methane and CO2 (δ13C-CH4 and δ13C-CO2) and noble gas isotopes (3He/4He and 4He/20Ne) demonstrated that the biogenic methane mainly originated from acetate fermentation and the dissolved noble gas was a result of the dissolution of air. Based on the geochemical and isotopic differences between shallow groundwater and flowback and produced water (including shale gas) from the Weiyuan and Fuling shale gas fields as well as shale gas from Xishui, this study has provided the sensitive monitoring indicators and methods for identifying potential pollution of regional shallow groundwater related to shale gas development in the future.

A linear hydrogen-bond acidic (HBA) linear functionalized polymer (PLF), was deposited onto a bare surface acoustic wave (SAW) device to fabricate a chemical sensor. Real-time responses of the sensor to a series of compounds including sarin (GB), dimethyl methylphosphonate (DMMP), mustard gas (HD), chloroethyl ethyl sulphide (2-CEES), 1,5-dichloropentane (DCP) and some organic solvents were studied. The results show that the sensor is highly sensitive to GB and DMMP, and has low sensitivity to HD and DCP, as expected. However, the sensor possesses an unexpected high sensitivity toward 2-CEES. This good sensing performance can’t be solely or mainly attributed to the dipole-dipole interaction since the sensor is not sensitive to some high polarity solvents. We believe the lone pair electrons around the sulphur atom of 2-CEES provide an electron-rich site, which facilitates the formation of hydrogen bonding between PLF and 2-CEES. On the contrary, the electron cloud on the sulphur atom of the HD molecule is offset or depleted by its two neighbouring strong electron-withdrawing groups, hence, hydrogen bonding can hardly be formed.