High-Quality and Diverse Few-Shot Image Generation via Masked Discrimination.

Few-shot image generation aims to generate images of high quality and great diversity with limited data. However, it is difficult for modern GANs to avoid overfitting when trained on only a few images. The discriminator can easily remember all the training samples and guide the generator to replicate them, leading to severe diversity degradation. Several methods have been proposed to relieve overfitting by adapting GANs pre-trained on large source domains to target domains using limited real samples. This work presents masked discrimination to realize few-shot GAN adaptation, which is the first feature-level augmentation method for generative tasks. Random masks are applied to features extracted by the discriminator from input images. We aim to encourage the discriminator to judge various images that share partially common features with training samples as realistic. Correspondingly, the generator is guided to generate diverse images instead of replicating training samples. In addition, we employ a cross-domain consistency loss for the discriminator to keep relative distances between generated samples in its feature space. It strengthens global image discrimination and guides adapted GANs to preserve more information learned from source domains for higher image quality, resulting in better cross-domain correspondence. The effectiveness of our approach is demonstrated both qualitatively and quantitatively with higher quality and greater diversity on a series of few-shot image generation tasks than prior methods.

Identification of a sugarcane bacilliform virus promoter that is activated by drought stress in plants.

Sugarcane (Saccharum spp.) is an important sugar and biofuel crop in the world. It is frequently subjected to drought stress, thus causing considerable economic losses. Transgenic technology is an effective breeding approach to improve sugarcane tolerance to drought using drought-inducible promoter(s) to activate drought-resistance gene(s). In this study, six different promoters were cloned from sugarcane bacilliform virus (SCBV) genotypes exhibiting high genetic diversity. In ß-glucuronidase (GUS) assays, expression of one of these promoters (PSCBV-YZ2060) is similar to the one driven by the CaMV 35S promoter and >90% higher compared to the other cloned promoters and Ubi1. Three SCBV promoters (PSCBV-YZ2060, PSCBV-TX, and PSCBV-CHN2) function as drought-induced promoters in transgenic Arabidopsis plants. In Arabidopsis, GUS activity driven by promoter PSCBV-YZ2060 is also upregulated by abscisic acid (ABA) and is 2.2-5.5-fold higher when compared to the same activity of two plant native promoters (PScRD29A from sugarcane and PAtRD29A from Arabidopsis). Mutation analysis revealed that a putative promoter region 1 (PPR1) and two ABA response elements (ABREs) are required in promoter PSCBV-YZ2060 to confer drought stress response and ABA induction. Yeast one-hybrid and electrophoretic mobility shift assays uncovered that transcription factors ScbZIP72 from sugarcane and AREB1 from Arabidopsis bind with two ABREs of promoter PSCBV-YZ2060. After ABA treatment or drought stress, the expression levels of endogenous ScbZIP72 and heterologous GUS are significantly increased in PSCBV-YZ2060:GUS transgenic sugarcane plants. Consequently, promoter PSCBV-YZ2060 is a possible alternative promoter for genetic engineering of drought-resistant transgenic crops such as sugarcane.

Microbiota in adult perianal abscess revealed by metagenomic next-generation sequencing.

The microbiota of perianal abscesses is scarcely investigated. Identifying causative bacteria is essential to develop antibiotic therapy. However, culture-based methods and molecular diagnostics through 16S PCR technology are often hampered by the polymicrobial nature of perianal abscesses. We sought to characterize the microbiota composition of perianal abscesses via metagenomic next-generation sequencing (mNGS). Fourteen patients suffering from perianal abscesses between March 2023 and August 2023 underwent retrospective assessment. Information from medical records was used, including clinical information, laboratory data, and culture and mNGS results. Forty bacterial taxa were identified from perianal abscesses through mNGS, with Bilophila wadsworthia (71.4%), Bacteroides fragilis (57.1%), and Escherichia coli (50.0%) representing the most prevalent species. mNGS identified an increased number of bacterial taxa, with an average of 6.1 compared to a traditional culture-based method which only detected an average of 1.1 in culture-positive perianal abscess patients, predominantly E. coli (75.0%), revealing the polymicrobial nature of perianal abscesses. Our study demonstrates that a more diverse bacterial profile is detected by mNGS in perianal abscesses, and that Bilophila wadsworthia is the most prevalent microorganism, potentially serving as a potential biomarker for perianal abscess.IMPORTANCEAccurately, identifying the bacteria causing perianal abscesses is crucial for effective antibiotic therapy. However, traditional culture-based methods and 16S PCR technology often struggle with the polymicrobial nature of these abscesses. This study employed metagenomic next-generation sequencing (mNGS) to comprehensively analyze the microbiota composition. Results revealed 40 bacterial taxa, with Bilophila wadsworthia (71.4%), Bacteroides fragilis (57.1%), and Escherichia coli (50.0%) being the most prevalent species. Compared to the culture-based approach, mNGS detected a significantly higher number of bacterial taxa (average 6.1 vs 1.1), highlighting the complex nature of perianal abscesses. Notably, Bilophila wadsworthia emerged as a potential biomarker for these abscesses. This research emphasizes the importance of mNGS in understanding perianal abscesses and suggests its potential for improving diagnostic accuracy and guiding targeted antibiotic therapy in the future.

Shoot-to-root communication via GmUVR8-GmSTF3 photosignaling and flavonoid biosynthesis fine-tunes soybean nodulation under UV-B light.

Legume nodulation requires light perception by plant shoots and precise long-distance communication between shoot and root. Recent studies have revealed that TGACG-motif binding factors (GmSTFs) integrate light signals to promote root nodulation; however, the regulatory mechanisms underlying nodule formation in changing light conditions remain elusive. Here, we applied genetic engineering, metabolite measurement, and transcriptional analysis to study soybean (Glycine max) nodules. We clarify a fine-tuning mechanism in response to ultraviolet B (UV-B) irradiation and rhizobia infection, involving GmUVR8-dependent UV-B perception and GmSTF3/4-GmMYB12-GmCHS-mediated (iso)flavonoid biosynthesis for soybean nodule formation. GmUVR8 receptor-perceived UV-B signal triggered R2R3-MYB transcription factors GmMYB12-dependent flavonoid biosynthesis separately in shoot and root. In shoot, UV-B-triggered flavonoid biosynthesis relied on GmUVR8a, b, c receptor-dependent activation of GmMYB12L-GmCHS8 (chalcone synthase) module. In root, UV-B signaling distinctly promotes the accumulation of the isoflavones, daidzein, and its derivative coumestrol, via GmMYB12B2-GmCHS9 module, resulting in hypernodulation. The mobile transcription factors, GmSTF3/4, bind to cis-regulatory elements in the GmMYB12L, GmMYB12B2, and GmCHS9 promoters, to coordinate UV-B light perception in shoot and (iso)flavonoid biosynthesis in root. Our findings establish a novel shoot-to-root communication module involved in soybean nodulation and reveal an adaptive strategy employed by soybean roots in response to UV-B light.

Value of preoperative biliary drainage in pancreatic head cancer patients with severe obstructive jaundice: A multicenter retrospective study.

BACKGROUND: Pancreatic head cancer accompanied by obstructive jaundice is a common clinical situation. The aim of this study was to assess the impact of preoperative biliary drainage (PBD) on clinical outcomes in patients with severe obstructive jaundice. METHODS: Patients with a bilirubin level of ≥250 mmol/L at diagnosis who underwent PBD were included. The primary endpoints and secondary endpoints were the postoperative severe complications rates. Secondary endpoints were the degree of improvement in general condition, predictors of severe postoperative complications, and the impact of PBD on patients with bilirubin levels >300 mmol/L. RESULTS: In total, 289 patients were included, and 188 patients (65.1%) underwent PBD. The patients who met the American Society of Anesthesiologists (ASA) classification II-III stages decreased from 119 to 100 (P = 0.047) after PBD. The overall severe complications were significantly more frequent in the direct surgery (DS) group than in the PBD group (34.7% vs. 22.9%, P = 0.031), especially the postoperative hemorrhage (6/43 [14.0%] vs. 9/35 [25.7%], P = 0.038) and intra-abdominal infection (6/43 [14.0%] vs. 10/35 [28.6%], P = 0.018). The ASA classifications II-III (odds ratio [OR]=2.89, 95% confidence interval [CI]: 1.38-4.31), P = 0.01) and DS (OR = 3.65, 95% CI: 1.45-7.08; P = 0.003) were independently associated with severe postoperative complications. The occurrence rate of severe postoperative complications in patients with a bilirubin level >300 mmol/L who underwent PBD was significantly lower than in patients who underwent DS (25.6% vs. 40.6%, P = 0.028), but the benefit of PBD was not observed in patients who had a bilirubin level between 250 and 300 mmol/L. CONCLUSION: PBD is useful in reducing severe postoperative complications, especially in patients with bilirubin levels >300 mmol/L.

Efficient photo-driven ion pump through slightly reduced vertical graphene oxide membranes.

Solar energy can be harvested using biological light-driven ion pumps for the sustainability of life. It remains a significant challenge to develop high-performance artificial light-driven ion pumps for solar energy harvesting in all solid-state materials. Here, we exploit the benefits of short channel lengths and efficient light absorption to demonstrate efficient photo-driven ion transport in slightly reduced vertical graphene oxide membranes (GOMs). Remarkably, this photo-driven ion pump exhibits excellent ability, countering a 10-fold electrolyte concentration gradient. We propose a plausible mechanism where light illumination enhances the electric potential of ion channels on GOMs triggered by the separation of photoexcited charge carriers between the sp2 and sp3 carbon clusters. This results in the establishment of an electric potential difference across the effective ion channels composed of sp3 carbon clusters, thus driving the directional transport of cations from the illuminated side to the non-illuminated side. The promising results of this study provide new possibilities for the application of vertical 2D nanofluidic membranes in areas such as artificial photosynthesis, light harvesting, and water treatment.

Improving Adversarial Robustness Against Universal Patch Attacks Through Feature Norm Suppressing.

Universal adversarial patch attacks, which are readily implemented, have been validated to be able to fool real-world deep convolutional neural networks (CNNs), posing a serious threat to practical computer vision systems based on CNNs. Unfortunately, current defending approaches are severely understudied facing the following problems. Patch detection-based methods suffer from dramatic performance drops against white-box or adaptive attacks since they rely heavily on empirical clues. Methods based on adversarial training or certified defense are difficult to be scaled up to large-scale datasets or complex practical networks due to prohibitively high computational overhead or over strong assumptions on the network structure. In this article, we focus on two cases of widely adopted universal adversarial patch attacks, namely the universal targeted attack on image classifiers and the universal vanishing attack on object detectors. We find that, for popular CNNs, the attacking success of the adversarial patch relies on feature vectors centered at the patch location with large norm in classifiers and large channel-aware norm (CA-Norm) in detectors, and further present a mathematical explanation for this phenomenon. Based on this, we propose a simple but effective defending method using the feature norm suppressing (FNS) layer, which can renormalize the feature norm by nonincreasing functions. As a differentiable module, FNS can be adaptively inserted in various CNN architectures to achieve multistage suppression of the generation of large norm feature vectors. Moreover, FNS is efficient with no trainable parameters and very low computational overhead. We evaluate our proposed defending method across multiple CNN architectures and datasets against the strong adaptive white-box attacks in both visual classification and detection tasks. In both tasks, FNS significantly outperforms previous defending methods on adversarial robustness with a relatively low influence on the performance of benign images. Code is available at https://github.com/jschenthu/FNS.

A web-based prediction model for long-term cancer-specific survival of middle-aged patients with early-stage gastric cancer: a multi-institutional retrospective study.

BACKGROUND: This study constructed and validated a prognostic model to evaluate long-term cancer-specific survival (CSS) in middle-aged patients with early gastric cancer (EGC). METHODS: We extracted clinicopathological data from relevant patients between 2004 and 2015 from Surveillance, Epidemiology, and End Results (SEER) database, and randomly divided the patients into a training group (N = 688) and a validation group (N = 292). In addition, 102 Chinese patients were enrolled for external validation. Univariate and multivariate Cox regression models were used to screen for independent prognostic factors, and a nomogram was constructed to predict CSS. We used the concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the predictive performance of the model. RESULTS: Univariate and multivariate COX regression analyses showed that tumor location, differentiation grade, N stage, chemotherapy, and number of regional nodes examined were independent risk factors for prognosis, and these factors were used to construct the nomogram. The C-index of the model in the training cohort, internal validation cohort, and external validation cohort was 0.749 (95% CI 0.699-0.798), 0.744 (95% CI 0.671-0.818), and 0.807 (95% CI 0.721-0.893), respectively. The calibration curve showed that the model had an excellent fit. The DCA curve showed that the model had good predictive performance and practical clinical value. CONCLUSION: This study developed and validated a new nomogram to predict CSS in middle-aged patients with EGC. The prediction model has unique and practical value and can help doctors carry out individualized treatment and judge prognosis.

Photochromic Azobenzene Inverse Opal Film toward Dynamic Anti-Fake Pattern.

Azobenzene mesogens have garnered considerable research attention in the realm of photo-responsive materials due to their reversible trans-cis isomerization. In this paper, we demonstrate an azobenzene inverse opal film synthesized via photo-polymerization from a SiO2 opal template. The proposed design exhibits intriguing optical properties, including dynamic fluorescent features, distinct fluorescent enhancement, and an anti-fake micropattern with a switchable structure color. This work holds significant importance for advancing the development of novel optical devices.

A new probabilistic assessment process for human health risk (HHR) in groundwater with extensive fluoride and nitrate optimized by non parametric estimation method.

Excessive amounts of fluoride (F-) and nitrate (NO3-) in groundwater pose a significant threat to human health. However, a quantitative approach to assessing the human health risks caused by these harmful substances is lacking. To optimize the probabilistic assessment process for human health risk (HHR), this study introduced kernel density estimation (KDE) into the stochastic simulation of F- and NO3- content in groundwater samples. The potential HHRs caused by F- and NO3- in Songyuan City were summarized by combining the probabilistic and deterministic assessments. This study found that the concentrations of F- and NO3- did not follow common probability density functions (PDFs), but the KDE method passed the Kolmogorov-Smirnov test with the critical value of 0.067 and 0.062, showing high fitting accuracy. Monte Carlo simulation indicated that the probability of NO3- for children and adult exceeding the standard is 21.95% and 15.14%, respectively, which is comparable with the results of the deterministic assessment, but the probabilistic assessment emphasized lower probability of HHRs in children caused by excess F-(4.14%). Global sensitivity analysis revealed that excessive NO3- in groundwater has the highest sensitivity of the HHR (>0.1), followed by other factors representing water use habits (>0.01). This study presents a refined probabilistic assessment method for HHR and provides a scientific reference for understanding the state of groundwater environments.

Genetic dissection of protein and starch during wheat grain development using QTL mapping and GWAS.

Protein, starch, and their components are important for wheat grain yield and end-products, which are affected by wheat grain development. Therefore, QTL mapping and a genome-wide association study (GWAS) of grain protein content (GPC), glutenin macropolymer content (GMP), amylopectin content (GApC), and amylose content (GAsC) were performed on wheat grain development at 7, 14, 21, and 28 days after anthesis (DAA) in two environments using a recombinant inbred line (RIL) population of 256 stable lines and a panel of 205 wheat accessions. A total of 29 unconditional QTLs, 13 conditional QTLs, 99 unconditional marker-trait associations (MTAs), and 14 conditional MTAs significantly associated (p < 10-4) with four quality traits were found to be distributed on 15 chromosomes, with the phenotypic variation explained (PVE) ranging from 5.35% to 39.86%. Among these genomic variations, three major QTLs [QGPC3B, QGPC2A, and QGPC(S3|S2)3B] and SNP clusters on the 3A and 6B chromosomes were detected for GPC, and the SNP TA005876-0602 was stably expressed during the three periods in the natural population. The QGMP3B locus was detected five times in three developmental stages in two environments with 5.89%-33.62% PVE, and SNP clusters for GMP content were found on the 3A and 3B chromosomes. For GApC, the QGApC3B.1 locus had the highest PVE of 25.69%, and SNP clusters were found on chromosomes 4A, 4B, 5B, 6B, and 7B. Four major QTLs of GAsC were detected at 21 and 28 DAA. Most interestingly, both QTL mapping and GWAS analysis indicated that four chromosomes (3B, 4A, 6B, and 7A) were mainly involved in the development of protein, GMP, amylopectin, and amylose synthesis. Of these, the wPt-5870-wPt-3620 marker interval on chromosome 3B seemed to be most important because it played an important role in the synthesis of GMP and amylopectin before 7 DAA, in the synthesis of protein and GMP from 14 to 21 DAA, and in the development of GApC and GAsC from 21 to 28 DAA. Using the annotation information of IWGSC Chinese Spring RefSeq v1.1 genome assembly, we predicted 28 and 69 candidate genes for major loci from QTL mapping and GWAS, respectively. Most of them have multiple effects on protein and starch synthesis during grain development. These results provide new insights and information for the potential regulatory network between grain protein and starch synthesis.

Quality and Agronomic Trait Analyses of Pyramids Composed of Wheat Genes NGli-D2, Sec-1s and 1Dx5+1Dy10.

Due to rising living standards, it is important to improve wheat's quality traits by adjusting its storage protein genes. The introduction or locus deletion of high molecular weight subunits could provide new options for improving wheat quality and food safety. In this study, digenic and trigenic wheat lines were identified, in which the 1Dx5+1Dy10 subunit, and NGli-D2 and Sec-1s genes were successfully polymerized to determine the role of gene pyramiding in wheat quality. In addition, the effects of ω-rye alkaloids during 1BL/1RS translocation on quality were eliminated by introducing and utilizing 1Dx5+1Dy10 subunits through gene pyramiding. Additionally, the content of alcohol-soluble proteins was reduced, the Glu/Gli ratio was increased and high-quality wheat lines were obtained. The sedimentation values and mixograph parameters of the gene pyramids under different genetic backgrounds were significantly increased. Among all the pyramids, the trigenic lines in Zhengmai 7698, which was the genetic background, had the highest sedimentation value. The mixograph parameters of the midline peak time (MPT), midline peak value (MPV), midline peak width (MPW), curve tail value (CTV), curve tail width (CTW), midline value at 8 min (MTxV), midline width at 8 min (MTxW) and midline integral at 8 min (MTxI) of the gene pyramids were markedly enhanced, especially in the trigenic lines. Therefore, the pyramiding processes of the 1Dx5+1Dy10, Sec-1S and NGli-D2 genes improved dough elasticity. The overall protein composition of the modified gene pyramids was better than that of the wild type. The Glu/Gli ratios of the type I digenic line and trigenic lines containing the NGli-D2 locus were higher than that of the type II digenic line without the NGli-D2 locus. The trigenic lines with Hengguan 35 as the genetic background had the highest Glu/Gli ratio among the specimens. The unextractable polymeric protein (UPP%) and Glu/Gli ratios of the type II digenic line and trigenic lines were significantly higher than those of the wild type. The UPP% of the type II digenic line was higher than that of the trigenic lines, while the Glu/Gli ratio was slightly lower than that of the trigenic lines. In addition, the celiac disease (CD) epitopes' level of the gene pyramids significantly decreased. The strategy and information reported in this study could be very useful for improving wheat processing quality and reducing wheat CD epitopes.

Age estimation of bloodstains based on Raman spectroscopy and chemometrics.

The accurate estimation of the bloodstain age, which is one of the important biological evidence of crime scene, can provide a lot of information related to crime. How to extract the information quickly and accurately from bloodstains without damage has been a focused problem. In this study, a bloodstains age estimation method based on Raman spectroscopy and chemometrics was developed. As many as 11 simulated environments based on different temperature and humidity were constructed in the method, and bloodstains of three species including human were studied. The influence of environmental factors such as temperature and humidity on the variation of Raman spectral peaks during the aging process of bloodstains was analyzed using the e-index fitting. When the humidity was kept constant, the increase of temperature generally promoted the changes of the spectral peaks. When the temperature was kept constant, the increase of humidity generally slowed the changes of spectral peaks. These works provide data support for the further development of Raman spectroscopy for bloodstain age estimation and could accelerate its application in actual scenes.

Shaping Deep Feature Space Towards Gaussian Mixture for Visual Classification.

The softmax cross-entropy loss function has been widely used to train deep models for various tasks. In this work, we propose a Gaussian mixture (GM) loss function for deep neural networks for visual classification. Unlike the softmax cross-entropy loss, our method explicitly shapes the deep feature space towards a Gaussian Mixture distribution. With a classification margin and a likelihood regularization, the GM loss facilitates both high classification performance and accurate modeling of the feature distribution. The GM loss can be readily used to distinguish the adversarial examples based on the discrepancy between feature distributions of clean and adversarial examples. Furthermore, theoretical analysis shows that a symmetric feature space can be achieved by using the GM loss, which enables the models to perform robustly against adversarial attacks. The proposed model can be implemented easily and efficiently without introducing more trainable parameters. Extensive evaluations demonstrate that the method with the GM loss performs favorably on image classification, face recognition, and detection as well as recognition of adversarial examples generated by various attacks.

Identification of blood species based on surface-enhanced Raman scattering spectroscopy and convolutional neural network.

The identification of blood species is of great significance in many aspects such as forensic science, wildlife protection, and customs security and quarantine. Conventional Raman spectroscopy combined with chemometrics is an established method for identification of blood species. However, the Raman spectrum of trace amount of blood could hardly be obtained due to the very small cross-section of Raman scattering. In order to overcome this limitation, surface-enhanced Raman scattering (SERS) was adopted to analyze trace amount of blood. The 785 nm laser was selected as the optimal laser to acquire the SERS spectra, and the blood SERS spectra of 19 species were measured. The convolutional neural network (CNN) was used to distinguish the blood of 19 species including human. The recognition accuracy of the blood species was obtained with 98.79%. Our study provides an effective and reliable method for identification and classification of trace amount of blood.

Estimation of groundwater residence time with deeply-derived carbon mixture considered in California.

Groundwater has experienced long-term overdraft due to drought and human activities in California, resulting in issues of land subsidence and groundwater anthropogenic contamination. As a useful indicator of groundwater renewal rate and its residence time, groundwater age has been conventionally investigated based on 14C content and 3H concentration. However, the influence of deeply-derived (endogenic) CO2 mixture is not fully and quantitatively considered, although endogenic carbon contributes a large part of the dissolved inorganic carbon in groundwater. Combined with 3H concentration, both conventional and modified 14C-dating methods with endogenic CO2 mixture considered are employed for groundwater age determination in California. On average, the conventional groundwater 14C apparent age is overestimated by ~4.9 kyr or ~26.2 %, causing groundwater recharge rate underestimation and aquifer recovery time overestimation by ~46.0 % and ~26.2 %, respectively. High 3H concentration indicates modern water mixture in more than one fifth of groundwater samples, including those with high modified 14C apparent age (> 12 kyr, i.e., fossil groundwater) in the Central Valley and southern California, which are generally considered not to be recharged by modern water. Modern water mixture in old groundwater can potentially bring anthropogenic contamination to these groundwater resources, which should be paid attentions by the government and the managers. The results have important implications in evaluation of groundwater replenishment and its susceptibility to modern contamination in California, and in groundwater resources estimation globally.

Design of multi-axis micromotion system in TERS and its nonlinearity and crosstalk correction method.

Tip-Enhanced Raman Spectroscopy (TERS) is an advanced analytical measurement technology combining Raman spectroscopy with Scanning Probe Microscopy, which can detect the molecular structure and chemical composition in micro-nano-scale. As an indispensable part, the micromotion system directly determines TERS spatial resolution. The existing multi-axis system is often composed of several single-axis nonlinear systems, which solves whole problems with a superposition idea of single-axis part. But the multi-axis crosstalk under an overall idea is not fully considered and will cause system uncooperative and even oscillational. Therefore, a multi-axis micromotion system in TERS and its correction method are proposed. The improved Duhem model, simple calculation without inversion, accurate matching and fast response, has been built for nonlinearity. And the feedforward decoupling method is designed for crosstalk, having a favorable multi-axis coordination, good error tracking and simplified controllers. Experimental results show that it can greatly correct the nonlinearity and crosstalk of multi-axis system simultaneously.

Shrinking lakes of rift valley system in southern Tibet: Is it the climate?

In the context of global warming, the plateau lakes generally expand, but some lakes in the southern Tibetan Plateau appear to shrinkage, such as Duoqing Co Lake. We analyzed Duoqing Co which is located on the Yadong-Gulu Rift zone and two surrounding lakes using satellite and meteorological data. Optical and radar images were used to construct a time series of these lakes from 1988 to 2021. By comparing the area changes of surrounding lakes, it is found that Como Chamling Lake has shrunk, while Puma Yum Co Lake has shown an expansion trend. The interference deformation results show that both sides of the Yadong-Gulu Rift zone where the Duoqing Co Lake is located have experienced strong uplift and subsidence, sinking in the east and uplifting in the west. Under the northward compression of the Indian plate, the blocks on both sides of the Yadong-Gulu Rift zone have been relatively displaced. The disappearance of Duoqing Co Lake could be attributed to the existence of leakage channels in the Yadong-Gulu Rift zone. The north-south rift zones of the Tibetan Plateau pass through the Qiangtang Basin, and some lakes in this basin are shrinking, which could be related to the leakage of these rift zones. This work provides a new perspective for studying lake changes on the Tibetan Plateau and is a good reference for studying the lake water cycle on the plateau.

Open pollution routing problem of logistics distribution in medical union based on differential search algorithm.

Medical care is a guarantee of people's daily life. Improving healthcare contributes to people's well-being. However, healthcare resources are characterized by uneven distribution. Financially well-off areas will have higher quality health care resources. Most of the medical resources are concentrated in public general hospitals, however, primary care institutions can hardly meet the growing needs of people. To solve this problem, Medical Union achieves efficient deployment of resources by integrating various medical institutions in the same area. In the process of logistics integration of the medical union, the scale of logistics distribution expands accordingly. Transportation vehicles have high operating costs and produce greenhouse gases in the process of distribution. The optimization of the driving path of logistics distribution vehicles can reduce the operating cost, fuel consumption and carbon emission. To solve this kind of decentralized and complex vehicle routing problem, this paper proposes a pollution routing problem model considering electrical vehicle usage, customer's soft time window expectation, open path and carbon cost. A modified Differential Search Algorithm with the comprehensive learning strategy and dynamic Cauchy variation strategy is advanced to solve the problem. Results show that the improved algorithm has good solving performance, and verifies the rationality of the proposed model, which will help to reduce carbon emissions and save the logistics and operating costs of medical devices.

Systemic immune inflammatory index is an independent predictor for the requirement of decompressive craniectomy in large artery occlusion acute ischemic stroke patients after mechanical thrombectomy.

Background and purpose: Following mechanical thrombectomy (MT), patients with large artery occlusive acute ischemic stroke (LAO-AIS) often have cerebral herniation due to its complications, resulting in poor prognosis. Decompressive craniectomy (DC) can markedly improve patient prognosis. This study aimed to verify the predictive value of clinical parameters such as the systemic immune-inflammatory index (SII) for DC in patients with LAO-AIS after MT. Methods: Clinical data of a total of 173 patients with LAO-AIS treated with MT between January 2020 and January 2022 were retrospectively analyzed. Patients receiving DC were grouped into an experimental group or a control group (no DC). The patients were randomly divided into the training set (n = 126, 75%) and validation set (n = 43, 25%). Multivariate logistic regression was used to construct a nomogram predictive model. Results: The SII value in the experimental group (median: 2851.1×109/L) was significantly higher than that in the control group (median: 1898.6 × 109/L) (P = 0.019). Receiver operating characteristic (ROC) analyses showed that the best cutoff value of the SII was 2505.7 × 109/L with a sensitivity of 55%, a specificity of 75.8%, and an area under the curve (AUC) of 0.649. Multivariate logistic regression indicated that the SII was an independent predictor for performing DC in patients with LAO-AIS after MT (OR = 3.579, 95% CI = 1.360-9.422, P = 0.01). The AUC was 0.728 in the training set and 0.583 in the validation set. The average error of the calibration curve was 0.032 in the training set and 0.023 in the validation set. The average error was relatively small and consistent in the training set and validation set. The C-index of the nomogram was 0.804 suggesting good accuracy. Conclusions: The SII at admission is an independent predictor for the requirement of DC in patients with LAO-AIS after MT. The SII-based nomogram helps doctors make decisions on whether DC is needed timely and rationally, and thereby may improve the prognosis of these patients.