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Climate change can lead to and intensify drought disasters. Quantifying the vulnerability of disaster-affected elements is significant for understanding the mechanisms that transform drought intensity into eventual loss. This study proposed a growth-stage-based drought vulnerability index (GDVI) of soybean using meteorological, groundwater, land use, and field experiment data and crop growth model simulation. The CROPGRO-Soybean model was used to simulate crop growth and water deficit. Four growth stages were considered since the sensitivity of soybean to drought is strictly related to the growth stage. The GDVI was applied to the Huaibei Plain, Anhui Province, China, with the goal of quantifying the spatiotemporal characteristics of soybean drought vulnerability in typical years and growth stages. The results show that: (1) The sensitivity of leaf-related parameters exceeded that of other parameters during the vegetative growth stage, whereas the top weight and grain yield showed a higher sensitivity in the reproductive growth stage; (2) A semi-logarithmic law can describe the relationship between the drought sensitivity indicators and the GDVI during the four growth stages. The pod-filling phase is the most vulnerable stage for water deficit and with the highest loss upper limit (over 70%); (3) The 2001 and 2002 seasons were the driest time during 1997−2006. Fuyang and Huainan Cities were more vulnerable to drought than other regions on the Huaibei Plain in 2001, while Huaibei and Suzhou Cities were the most susceptible areas in 2002. The results could provide effective decision support for the categorization of areas vulnerable to droughts.

Drug-drug interactions are one of the main concerns in drug discovery. Accurate prediction of drug-drug interactions plays a key role in increasing the efficiency of drug research and safety when multiple drugs are c o-prescribed. With various data sources that describe the relationships and properties between drugs, the comprehensive approach that integrates multiple data sources would be considerably effective in making high-accuracy prediction. In this paper, we propose a Deep Attention Neural Network based Drug-Drug Interaction prediction framework, abbreviated as DANN-DDI, to predict unobserved drug-drug interactions. First, we construct multiple drug feature networks and learn drug representations from these networks using the graph embedding method; then, we concatenate the learned drug embeddings and design an attention neural network to learn representations of drug-drug pairs; finally, we adopt a deep neural network to accurately predict drug-drug interactions. The experimental results demonstrate that our model DANN-DDI has improved prediction performance compared with state-of-the-art methods. Moreover, the proposed model can predict novel drug-drug interactions and drug-drug interaction-associated events.

Depression is the most common mental disorder in the world. Sleep deprivation (SD) is a well-known antidepressant. Several recombination protocols (including medications, bright light treatment [BLT], cognitive-behavioral therapy, sleep phrase advance/sleep phrase delay [SPA/SPD], and repetitive transcranial magnetic stimulation [rTMS]) have been developed to improve and maintain the effect of SD. However, relapse after recovery sleep has been reported, and different recombination protocols result in different outcomes.The Embase, Cochrane, PubMed, CBM, Web of Science, and CINAHL databases were searched for clinical trials assessing depression and SD. Three independent reviewers classified forty-three abstracts. The Hamilton Depression Rating Scale was used to assess the outcomes.Compared with existing therapy, patients receiving SD displayed a significant improvement in clinician-rated depressive symptoms (MD -1.48 [95 % CI -2.60, -0.37], p 0.05). A significant decrease was found in the subgroups of SD plus SPA/SPD (odds ratio 3.90 [95 % CI 1.66, 9.17], p 0.05), total sleep deprivation[TSD] plus BLT (MD -3.28 [95 % CI -5.06, -1.50], p 0.05), and partial sleep deprivation[PSD] plus rTMS (MD -7.94 [95 % CI -11.44, -4.45], p 0.05). No significant differences were observed in the other subgroups.Adding SD to existing therapies showed a positive outcome in improving depression treatment, which provides evidence for the use of SD in treating depression. Further studies are needed to determine the precise effects of SD plus other interventions.

Objective: Thrombectomy greatly improves the clinical prognosis of patients with acute ischemic stroke (AIS). The aim of this study is to develop a nomogram model that can predict the prognosis of patients with acute ischemic stroke undergoing thrombectomy. Methods: We retrospectively collected information of patients with acute ischemic stroke who were admitted to the stroke Green Channel of the First Affiliated Hospital of Soochow University from September 2018 to May 2022. The main outcome was defined as a three-month unfavorable outcome (modified Rankin Scale 3-6). Based on the results of multivariate regression analysis, a nomogram was established. We tested the accuracy and discrimination of our nomogram by calculating the consistency index (C-index) and plotting the calibration curve. Results: National Institutes of Health Stroke Scale (NIHSS) score (OR, 1.418; 95% CI, 1.177-1.707; P＜0.001), low density lipoprotein cholesterol (LDL-C) (OR, 2.705; 95% CI, 1.203-6.080; P = 0.016), Alberta Stroke Program Early Computed Tomography Score (ASPECTS) (OR, 0.633; 95% CI, 0.421-0.952; P = 0.028), infarct core volume (OR, 1.115; 95% CI, 1.043-1.192; P = 0.001) and ischemic penumbra volume (OR, 1.028; 95% CI, 1.006-1.050; P = 0.012) were independent risk factors for poor clinical prognosis of AIS patients treated with thrombectomy. The C-index of our nomogram was 0.967 and the calibration plot revealed a generally fit in predicting three-month unfavorable outcomes. Based on this nomogram, we stratified the risk of thrombectomy population. We found that low-risk population is less than or equal to 65 points, and patients of more than 65 points tend to have a poor clinical prognosis. Conclusion: The nomogram, composed of NIHSS, LDL-C, ASPECTS, infarct core volume and ischemic penumbra volume, may predict the clinical prognosis of cerebral infarction patients treated with thrombectomy.

The transtibial pull-out repair (TP) is a relatively new method for treating meniscal root tear; however, the clinical evaluation of its healing effect remains controversial. Due to ethical constraints and limitations of imaging techniques in humans, here we dynamically observe the healing effects of TP and TP with platelet-rich plasma gel (PRG) at the histological level using an animal model.Platelet-rich plasma (PRP) and PRG of rabbits were prepared. Platelet-derived growth factor (PDGF) and transforming growth factor-β1 (TGF-β1) levels in PRP and PRG were determined using an enzyme-linked immunosorbent assay. A rabbit model of anterior horn tear of the medial meniscus and TP surgery were created. PRG was injected between the anterior horn of the medial meniscus and the tibial tunnel. Rabbits were divided into three groups: the anterior horn tear group (Tear group), the anterior horn tear + TP group (TP group), and the anterior horn tear + TP + PRG group (TP + PRG group). The healing effect was observed dynamically using histopathological studies and biomechanical experiments.The platelet content in PRP significantly increased to approximately 4.57 times that of whole blood. PDGF and TGF-β1 concentrations in PRG increased to 2.46 and 4.15 times those in PRP, respectively. Hematoxylin and eosin (HE) and Masson staining showed that the number of inflammatory cells in healing tissue decreased and the collagen fibers significantly increased in TP and TP + PRG groups at 4, 8, and 12 weeks postoperatively compared to those in Tear group. Neatly arranged, interlaced, and dense collagen fibers were found between the anterior horn and bone at 12 weeks. HE and toluidine blue staining showed that the injury to the femoral condyle cartilage was alleviated. The healing performance in TP + PRG group was better and faster than that in TP group. The maximum tensile fracture strength of the meniscus progressively increased at 8 and 12 weeks postoperatively.Anterior horn injury of the medial meniscus in rabbits can be repaired using the TP technique, and the addition of autologous PRG to the bone tunnel promotes early healing of the meniscus and bone postoperatively. Meanwhile, both treatments can reduce the secondary damage to the cartilage due to osteoarthritis.

ZusammenfassungEine 10-jährige Mischlingshündin wurde aufgrund einer zervikalen Umfangsvermehrung zur Schilddrüsen-Szintigrafie vorgestellt.Aufgrund einer zusätzlichen Hypothyreose, die einen „kalten“ Knoten vermuten ließ, und zur Metastasensuche, erfolgte neben der 99m-Technetium-Pertechnetat (Tc-Pertechnetat)-Szintigrafie eine zweite Szintigrafie mit 99m-Technetium-Sestamibi (Tc-MIBI).Zwanzig Minuten nach intravenöser Gabe von 38 MBq Tc-Pertechnetat waren ein „heißer“ zervikaler und ein intrathorakaler Knoten mit einem „Uptake“ von 8,40 und 0,25 % sichtbar. In der zweiten Szintigrafie 20 Minuten nach intravenöser Gabe von 364 MBq Tc-MIBI und 70 Minuten nach der ersten Szintigrafie zeigten die Knoten nach Abzug der Pertechnetat-Aktivität und Zerfallskorrektur einen „Uptake“ von 0,99 und 0,03 %. Zudem stellten sich in der Schilddrüsenloge beide Schilddrüsenlappen mit einer geringen Tc-MIBI-Aufnahme dar. Das Verhältnis Tc-„Uptake“/Tc-MIBI-„Uptake“ betrug für beide Läsionen 8,48 bzw. 8,33.Nach Exstirpation des zervikalen Tumors ergab die histopathologische Untersuchung atrophisches Schilddrüsengewebe, das von einem expansiv wachsenden gut differenzierten follikulären Schilddrüsenkarzinom fast vollständig verdrängt wurde.Dieser Fallbericht beschreibt Durchführung, Nutzen und rechnerische Korrektur einer aufeinanderfolgenden Pertechnetat- und MIBI-Szintigrafie, die eine Darstellung von hypofunktionellem Schilddrüsengewebe ermöglichte. Die beiden heißen Knoten waren daher und aufgrund ihrer gleichen MIBI-Stoffwechselaktivität als dystopes Gewebe/Metastasen zu werten, wodurch die Hündin in das prognostisch ungünstigere WHO-Stadium IV klassifiziert werden musste. Anders als beim Menschen sollten beim Hund zur Vermeidung einer erneuten Narkose beide Szintigrafien kurz hintereinander durchgeführt werden. Eine qualitative/visuelle Beurteilung des MIBI-Szintigramms ist daher nicht sicher möglich, sodass eine quantitative Beurteilung über den „Uptake“ nach rechnerischer Korrektur der Pertechnetat-Aktivität erfolgen muss.

Live streaming has become popular among various e-commerce models. As an efficient way of marketing, live streaming can stimulate consumers' impulse purchasing behavior by creating a compelling experience, flow experience. Even though research on flow experience has been applied to understand consumer behavior in e-commerce, few studies have been conducted in live streaming e-commerce, let alone the influencing factors. Drawing on the stimulus-organism-response (S-O-R) model, this paper examines the impact of cognitive stimuli and perceptive stimuli on the urge to buy impulsively via flow experience. The results indicate that information content, website design, time pressure, and personalized recommendation positively relate to flow experience and the urge to buy impulsively. They also find the direct effect of time pressure and personalized recommendation on the urge to buy impulsively. The theoretical contributions and the practical implications for e-commerce live streaming are presented.

Microphysical structures and processes in a case of precipitating stratiform clouds in North China on 21 May 2018 are investigated using joint observations from an aircraft and an X-band polarimetric radar. The results show that there are enhancements in differential reflectivity (ZDR) and specific differential phase (KDP) above the 7-km altitude, consistent with the existence of dendrites and platelike ice crystals. The horizontal reflectivity factor (ZH) increases and ZDR decreases downward above the melting layer (ML), due to the prevalent aggregation process, which is confirmed by the downward increasing volume-weighted mean diameter (Dm) and decreasing total number concentration (Nt) observed by the aircraft. Within the ML, the concentration of median-sized particles (2–5 mm) decreases rapidly downward due to the melting process. Within approximately the top 2/3 of the ML, the melting particles’ mean and maximum sizes increase, demonstrating the dominance of the aggregation process. This causes the enhancements of ZH and ZDR within the radar bright band together with the increase in the dielectric constant. Within the bottom 1/3 of the ML, the breakup process is responsible for the decreasing Dm and increasing Nt observed by the aircraft. Below the ML, the measurements by the polarimetric radar and the aircraft only show slight variance with altitude, indicating the near balance between microphysical processes favored by the nearly saturated air. The results of the microphysics in the stratiform case would help improve the microphysical parameterization of numerical modeling in the future.

Pancreatitis patients are at an increased risk of malnutrition due to impaired digestion, absorption, and metabolism. The degree of malnutrition is dependent on the duration, viz. acute or chronic. Studies on nutritional status in patients with pancreatitis are limited. Prevalence of nutritional status, physical functioning, and muscle strength among the subjects are scarce globally. The main aim of this study was to screen the status of malnutrition using appropriate screening tools and to assess hand muscle strength among subjects.A cross-sectional study was conducted on 64 subjects (18-80 years old, 59 males and 5 females) in Mysore city, Karnataka. The patients were screened for malnutrition using a standard tool Patient-Generated Subjective Global Assessment (PG-SGA) and handgrip strength on both dominant and nondominant hands.The majority of patients (This study was able to identify patients at risk of malnutrition when the PG-SGA tool was used along with handgrip strength and other anthropometric parameters.

In order to clarify the thermal deformation and failure mechanism of the nodular cast iron cylinder head of marine diesel engines during long-term service, a high-efficiency thermal cycling experiment was conducted on scaled cylinder head specimen based on the similarity principle, and the thermal cycling load was simulated by flame heating and water spray cooling method. Then the Chaboche combined hardening model considering temperature and cumulative effect was established. The cyclic plastic behavior of the scaled specimen model during non-uniform thermal cycling was verified from transient temperature, cumulative out-of-round deformation and crack failure. Subsequently, the law of cyclic plastic deformation of specimens under thermal cycling was studied. The results showed that with the increase of the cycle number, the plastic strain of the valve bridge region of the scaled specimens accumulated gradually, showing a large amount of permanent strain of the circular hole within a maximum of 20.3 μm out-of-round deformation. The difference between the calculated and tested deformation is 1.9 μm (10.5%), which shows the excellent predictability of the numerical model. The research findings are valuable for predicting and evaluating the thermal-structural behavior of the prototype cylinder head.

Glomerular disease is the leading cause of chronic kidney disease globally. No scoping review reports have focused on China's spectrum of glomerular diseases in children. This study aimed to systematically identify and describe retrospective studies on pediatric glomerular disease based on available data on sex, age, study period, and region.Six databases were systematically searched for relevant studies from initiation to December 2021 in PubMed, Embase, Web of Science, Global Health Library, Wangfang Database, and CNKI.Thirty-four studies were identified in the scoping review, including 40,430 patients with biopsy-proven diagnoses. The proportion of boys was significantly higher than that of girls. In this study, 28,280 (70%) cases were primary glomerular disease, 10,547 (26.1%) cases were diagnosed as secondary glomerular disease, and 1146 (2.8%) cases were hereditary glomerular disease. Minimal change disease is the most common glomerular disease among children in China, followed by mesangial proliferative glomerulonephritis, IgA nephropathy, and purpura nephritis. We observed increments in glomerular diseases in periods 2 (2001-2010) and 3 (2011-2021). The proportion of major glomerular diseases varies significantly in the different regions of China.The spectrum of pediatric glomerular diseases varied across sex, age groups, study periods, and regions, and has changed considerably over the past 30 years.

Early body composition changes, associated with physical inactivity and disease advancement are devastating for patient-related outcomes in predialysis chronic kidney disease (CKD), thus warranting a detailed analysis of body composition beyond conventional measures.The study included 40 subjects diagnosed with CKD; recruited between January to May 2021. Body composition was measured using the multifrequency analyzer, InBody 770. International Physical Activity Questionnaire-Short Form was used to assess physical activity. Suitable statistical analyses were performed using SPSS 21.0.The mean age of the subjects was 58.68 ± 12.24 years. Sarcopenic obesity was prevalent in 62.5% of the subjects. Body mass index under identified obesity by 15% compared to percent body fat, especially in subjects with low muscle mass. The decline in a unit of estimated glomerular filtration rate (eGFR) significantly correlated with a decrease in weight (Changes in fat and fluid compartment were associated with eGFR decline, whereas higher physical activity positively affected body composition.

The deconfined quantum critical point (DQCP) represents a paradigm shift in quantum matter studies, presenting a “beyond Landau” scenario for order–order transitions. Its experimental realization, however, has remained elusive. Using high-pressure 11 B nuclear magnetic resonance measurements on the quantum magnet SrCu 2 (BO 3 ) 2 , we here demonstrate a magnetic-field induced plaquette-singlet to antiferromagnetic transition above 1.8 GPa at a notably low temperature, T c ≃ 0.07 K. First-order signatures of the transition weaken with increasing pressure, and we observe quantum critical scaling at the highest pressure, 2.4 GPa. Supported by model calculations, we suggest that these observations can be explained by a proximate DQCP inducing critical quantum fluctuations and emergent O(3) symmetry of the order parameters. Our findings offer a concrete experimental platform for the investigation of the DQCP.

Identification of lithology from drilling cuttings is a key step for reservoir characterization. At present, the traditional method is to collect and analyze the cuttings by manual interpretation, which is subjective and time-consuming. In order to improve the accuracy, timeliness, and automation of identification of cuttings lithology, this paper completed lithology identification and classification through batch iterative training based on Resnet-34 network. Automated rock type identification from cuttings images captured by a given camera is the goal of this work. The main challenge in cuttings recognition is the similarity of color and grain size in two or different cuttings. Another important factor is that the light source of the camera. In order to capture the images of cuttings more comprehensively for identification, a single light source with 8 channels (ultraviolet, blue, green, yellow, red, infrared, far infrared, and white light) was used to irradiate the cuttings during the imaging process, and the imaging information of cuttings in the full spectral segment can be obtained as the input of the deep learning network. In order to solve the overfitting problem caused by data duplication under different light sources, the input images are first preprocessed by brightness equalization and random cropping, so that each grayscale image can have the same brightness and do not have too much repetition under different light sources. In terms of the efficiency and accuracy, Resnet-34 is selected as the model framework of cuttings recognition and classification. The overall accuracy of the model is increased to 98.6% combined with the actual hardware support in the field, which promotes the more efficient identification of logging cuttings and provides a theoretical basis for improving the online logging of logging in the field.

Electrolyte engineering is crucial for improving battery performance, particularly for lithium metal batteries. Recent advances in electrolytes have greatly improved cyclability by enhancing electrochemical stability at the electrode interfaces, but concurrently achieving high ionic conductivity has remained challenging. Here we report an electrolyte design strategy for enhanced lithium metal batteries by increasing the molecular diversity in electrolytes, which essentially leads to high entropy electrolytes (HEEs). We find that in weakly solvating electrolytes, the entropy effect reduces ion clustering while preserving the characteristic anion-rich solvation structures, which is characterized by synchrotron-based X-ray scattering and molecular dynamics simulations. Electrolytes with smaller-sized clusters exhibit a 2-fold improvement in ionic conductivity compared to conventional weakly-solvating electrolytes, enabling stable cycling at high current densities up to 2C (6.2 mA cm-2) in anode-free LiNi0.6Mn0.2Co0.2 (NMC622) || Cu pouch cells. The efficacy of the design strategy is verified by performance improvements in three disparate weakly solvating electrolyte systems.