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Abstract Water is necessary for the alkali aggregate reaction to occur and this study investigates the impact of waterproofing on alkali-aggregate reaction (AAR) in concrete by separating water from alkali reactive aggregates through surface, aggregate, and matrix treatments. Accelerated mortar bar tests (AMBT) are conducted to analyze the expansion caused by alkali aggregates. Furthermore, the suppressive mechanism of waterproofing on AAR is explored using scanning electron microscopy (SEM), while the influence of waterproof concrete aggregate and matrix on pore characteristics and hydration products is assessed using nuclear magnetic resonance (NMR) and X-ray diffraction (XRD). The results demonstrate that surface waterproofing with silane and polyvinyl alcohol (PVA) effectively suppress AAR. Moreover, PVA-coated aggregates significantly enhance the compactness of the interfacial transition zone (ITZ) in concrete. Based on these findings, an improved model considering waterproofness is proposed to quantify the degree of alkali aggregate reaction. These findings offer valuable guidance for controlling AAR.

Abstract Low visibility weather easily leads to traffic accidents, posing threats to human life and property. To accurately forecast visibility, we conduct an empirical study focusing on Jiangsu Province. Firstly, we collect the monitoring data from meteorological stations and environmental stations for 2017-2018. Secondly, we analyze the changes in visibility from both spatial and temporal perspectives. Next, the maximum Relevance Minimum Redundancy (mRMR) algorithm is employed to select factors affecting visibility, finding that humidity and $$PM_{2.5}$$ P M 2.5 concentrations are the primary factors. Finally, we propose GCN-GRU (Graph Convolutional Network and Gated Recurrent Unit) model for short-term visibility forecasting, which employs GCN to capture the interactions between stations and uses GRU to learn the interactions between times. Experimental results indicate that GCN-GRU outperforms the standalone GRU model and three machine learning models regarding 6-hour visibility forecasting. Compared to the best competitor, GCN-GRU achieves an average increase of 3.32% in Correlation Coefficient (CORR), a decrease of 17.52% in Root Mean Square Error (RMSE), a reduction of 26.62% in Mean Absolute Percentage Error (MAPE), and a decline of 16.53% in Mean Absolute Error (MAE).

Abstract Landslides are highly destructive geological disasters that pose a serious threat to the safety of people’s lives and property. In this study, historical records of landslides in Yunnan Province, along with eight underlying factors of landslide (elevation, slope, aspect, lithology, land cover type, normalized difference vegetation index (NDVI), soil type, and average annual precipitation (AAP)), as well as historical rainfall and current rainfall data were utilized. Firstly, we analyzed the sensitivity of each underlying factor in the study area using the frequency ratio (FR) method and obtained a landslide susceptibility map (LSM). Then, we constructed a regional rainfall-induced landslides (RIL) probability forecasting model based on machine learning (ML) algorithms and divided warning levels. In order to construct a better RIL prediction model and explore the effects of different ML algorithms and input values of the underlying factor on the model, we compared five ML classification algorithms: extreme gradient boosting (XGBoost), k-nearest neighbor (KNN), support vector machine (SVM), logistic regression (LR), and random forest (RF) algorithms and three representatives of the input values of the underlying factors. The results show that among the obtained forecasting models, the LSM-based RF model performs the best, with an accuracy (ACC) of 0.906, an area under the curve (AUC) of 0.954, a probability of detection (POD) of 0.96 in the test set, and a prediction accuracy of 0.8 in the validation set. Therefore, we recommend using RF-LSM model as the RIL forecasting model for Yunnan Province and dividing warning levels.

Abstract Anxiety/stress-related disorders have been associated with multiple diseases, whereas a comprehensive assessment of the structure and interplay of subsequent associated diseases and their genetic underpinnings is lacking. Here, we first identify 136, out of 454 tested, medical conditions associated with incident anxiety/stress-related disorders attended in specialized care using a population-based cohort from the nationwide Swedish Patient Register, comprising 70,026 patients with anxiety/stress-related disorders and 1:10 birth year- and sex-matched unaffected individuals. By combining findings from the comorbidity network and disease trajectory analyses, we identify five robust disease clusters to be associated with a prior diagnosis of anxiety/stress-related disorders, featured by predominance of psychiatric disorders, eye diseases, ear diseases, cardiovascular diseases, and skin and genitourinary diseases. These five clusters and their featured diseases are largely validated in the UK Biobank. GWAS analyses based on the UK Biobank identify 3, 33, 40, 4, and 16 significantly independent single nucleotide polymorphisms for the link to the five disease clusters, respectively, which are mapped to several distinct risk genes and biological pathways. These findings motivate further mechanistic explorations and aid early risk assessment for cluster-based disease prevention among patients with newly diagnosed anxiety/stress-related disorders in specialized care.

Abstract The outlet temperature of the heat recovery reservoir is an important parameter in the design of refrigeration with heat recovery systems. In this paper the second law of thermodynamics has been applied to an irreversible Carnot refrigerator with heat recovery (CRHR) coupled to variable-temperature heat reservoirs. The refrigerating rate, input power, refrigeration coefficient, heat recovery coefficient, comprehensive coefficient of performance and exergy efficiency are chosen as the objective functions. The design rule chosen for this study is that the heat transfer area should be constrained. The mathematical expressions for assessing performance parameters with respect to area ratio, were derived for this study. These expressions are transcendental equations. The numerical solution method was employed to calculate the approximate solutions of the optimum performance parameters in a numerical example. The results indicate that the increase in the outlet temperature of heat recovery reservoir could lead to a rise in the maximum value of refrigerating rate and minimum value of input power; also it will lead to the decline in the maximum value of refrigeration coefficient, heat recovery coefficient, comprehensive coefficient and the exergy efficiency. When the ratio of heat recovery heat exchanger area to the summation of high temperature heat exchanger area and the heat recovery heat exchanger area is 1.0, the performance coefficients would attain their limit values and all of the condensing heat could be recycled. Our findings are helpful to the design and optimization to inform preparation of standard relating to the development of refrigerator with heat recovery.

Abstract Pepper (Capsicum spp.) is one of the earliest cultivated crops and includes five domesticated species, C. annuum var. annuum, C. chinense, C. frutescens, C. baccatum var. pendulum and C. pubescens. Here, we report a pepper graph pan-genome and a genome variation map of 500 accessions from the five domesticated Capsicum species and close wild relatives. We identify highly differentiated genomic regions among the domesticated peppers that underlie their natural variations in flowering time, characteristic flavors, and unique resistances to biotic and abiotic stresses. Domestication sweeps detected in C. annuum var. annuum and C. baccatum var. pendulum are mostly different, and the common domestication traits, including fruit size, shape and pungency, are achieved mainly through the selection of distinct genomic regions between these two cultivated species. Introgressions from C. baccatum into C. chinense and C. frutescens are detected, including those providing genetic sources for various biotic and abiotic stress tolerances.

Abstract Primary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by chronic inflammation and progressive fibrosis of the biliary tree. The majority of PSC patients suffer from concomitant inflammatory bowel disease (IBD), which has been suggested to promote disease development and progression. However, the molecular mechanisms by which intestinal inflammation may aggravate cholestatic liver disease remain incompletely understood. Here, we employ an IBD-PSC mouse model to investigate the impact of colitis on bile acid metabolism and cholestatic liver injury. Unexpectedly, intestinal inflammation and barrier impairment improve acute cholestatic liver injury and result in reduced liver fibrosis in a chronic colitis model. This phenotype is independent of colitis-induced alterations of microbial bile acid metabolism but mediated via hepatocellular NF-κB activation by lipopolysaccharide (LPS), which suppresses bile acid metabolism in-vitro and in-vivo. This study identifies a colitis-triggered protective circuit suppressing cholestatic liver disease and encourages multi-organ treatment strategies for PSC.

Abstract Retrosynthesis is a procedure where a target molecule is transformed into potential reactants and thus the synthesis routes can be identified. Recently, computational approaches have been developed to accelerate the design of synthesis routes. In this paper,we develop a generative framework G 2 Retro for one-step retrosynthesis prediction. G 2 Retro imitates the reversed logic of synthetic reactions. It first predicts the reaction centers in the target molecules (products), identifies the synthons needed to assemble the products, and transforms these synthons into reactants. G 2 Retro defines a comprehensive set of reaction center types, and learns from the molecular graphs of the products to predict potential reaction centers. To complete synthons into reactants, G 2 Retro considers all the involved synthon structures and the product structures to identify the optimal completion paths, and accordingly attaches small substructures sequentially to the synthons. Here we show that G 2 Retro is able to better predict the reactants for given products in the benchmark dataset than the state-of-the-art methods.

Abstract A 2 at.% Dy3+: CaYAlO4 single crystal was grown successfully. The electronic structures of Ca2+/Y3+ mixed sites in CaYAlO4 were investigated using first-principles based on density functional theory. The effects of Dy3+ doping on the structural parameters of host crystal were studied using XRD pattern. The optical properties including absorption spectrum, excitation spectrum, emission spectra and fluorescence decay curves were thoroughly investigated. The results show that the Dy3+: CaYAlO4 crystal could be pumped by the blue InGaN and AlGaAs or 1281 nm laser diodes. Furthermore, an intense 578 nm yellow emission was obtained directly under excitation at 453 nm, meanwhile, evident mid-infrared light emitting was observed by 808 or 1281 nm laser excitation. The fitted fluorescence lifetimes of 4F9/2 and 6H13/2 levels were about 0.316 ms and 0.038 ms, respectively. It can be concluded that this Dy3+: CaYAlO4 crystal could simultaneously act as a promising medium for both solid-state yellow and mid-infrared laser outputs.

Lateral hypothalamus (LH) plays an role in drug addiction. Here, authors present evidence for disinhibited LH glutamatergic neurons by neural circuits from nucleus accumbens to contribute to context-induced expression of morphine withdrawal memory.

Sun et al. has studied the genetically encodable halotyrosines in proteins of the prokaryotic cell division machinery to elucidate the general role of halogenation in cellular lifespan and oxidative damage-induced diseases such as aging and cancer.

Abstract A set of one-dimensional experimental device for solute transport in non-penetrating fractured clay are developed, which can study the laws of groundwater flow and solute transport under different hydraulic heads, fractured aperture, and thickness of non-penetrating zones. The experimental results show that the solute will quickly reach the bottom of the clay along the non-penetrating fracture, and there is an obvious dominant flow phenomenon compared with the intact clay. According to the experimental data and numerical calculation results, the model parameters of the fracture and each soil layer were identified, and the verified numerical model was used to simulate the solute transport in the non-penetrating fractured clay. The numerical results show that the increase of the thickness for the non-penetrating zone has a significant improvement on the anti-seepage ability of clay, and the increase of the hydraulic head pressure and fractured aperture leads to a faster growth rate of the solute concentration, which indicates that the solute breaks down the lower impermeable clay layer under high head pressure. The research results are of great significance for the bottom anti-seepage layer similar to landfill projects.

Limited stem cells and mismatched interface fusion have plagued biomaterial-mediated cranial reconstruction. Here, the authors engineer an instantly fixable and self-adaptive scaffold to promote calcium chelation and interface integration, regulate macrophage M2 polarization, and recruit endogenous stem cells.

Coronavirus main protease is essential for viral polyprotein processing and maturation. Here Fu et al. report efficient inhibition of SARS-CoV-2 replication using two inhibitors - Boceprevir and GC376 - targeting the active site of the main viral protease.

Controlling selectivity between homochiral and heterochiral reaction pathways on surfaces is intriguing but challenging. Here, the authors demonstrate strategies in steering the reactions of prochiral terminal alkynes between the homochiral and heterochiral pathways by tuning the precursor substituents and the kinetic parameters.

Conserved regions of the antibody molecule impact its downstream biological effects. Here the authors show that a rigid hinge conformation increases the agonistic activity of CD40 and DR5 antibodies, distinctly from FcγR-binding, suggesting that the hinge and FcR binding regions can be separately modified to optimize therapies.

Abstract We evaluated how metabolic disorders affected antihypertension therapy. 2,912 rural Chinese patients with hypertension who provided blood samples, demographic and clinical data at baseline and after 1 year of antihypertension therapy were evaluated. At baseline, 1,515 patients (52.0%) were already receiving drug therapy and 11.4% of them had controlled blood pressure (BP). After 1 year, all 2,912 patients were receiving antihypertension therapy that was administered by community physicians, and 59.42% of them had controlled BP. Central obesity and abnormal triglyceride, high-density lipoprotein cholesterol, and glucose were associated with 15–70% higher risks of uncontrolled hypertension. Metabolic syndrome using the JIS criteria was associated with poor BP control (odds ratio: 1.71 and 1.54 for the baseline and follow-up datasets, respectively). The risk of uncontrolled hypertension increased with the number of metabolic disorders (p for trend