The Morse index theorem for mechanical systems with reflections

We prove a Morse index theorem for action functionals on paths that are allowed to reflect at a hypersurface (either in the interior or at the boundary of a manifold). Both fixed and periodic boundary conditions are treated.Comment: v2: 31 pages, added a Morse Index Theorem for composition of path

SportsTrack: An Innovative Method for Tracking Athletes in Sports Scenes

The SportsMOT dataset aims to solve multiple object tracking of athletes in different sports scenes such as basketball or soccer. The dataset is challenging because of the unstable camera view, athletes' complex trajectory, and complicated background. Previous MOT methods can not match enough high-quality tracks of athletes. To pursue higher performance of MOT in sports scenes, we introduce an innovative tracker named SportsTrack, we utilize tracking by detection as our detection paradigm. Then we will introduce a three-stage matching process to solve the motion blur and body overlapping in sports scenes. Meanwhile, we present another innovation point: one-to-many correspondence between detection bboxes and crowded tracks to handle the overlap of athletes' bodies during sports competitions. Compared to other trackers such as BOT-SORT and ByteTrack, We carefully restored edge-lost tracks that were ignored by other trackers. Finally, we reached the SOTA result in the SportsMOT dataset.Comment: 7 pages,9 figure

COVIDanno, COVID-19 Annotation in Human

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 19 (COVID-19), has caused a global health crisis. Despite ongoing efforts to treat patients, there is no universal prevention or cure available. One of the feasible approaches will be identifying the key genes from SARS-CoV-2-infected cells. SARS-CoV-2-infected in vitro model, allows easy control of the experimental conditions, obtaining reproducible results, and monitoring of infection progression. Currently, accumulating RNA-seq data from SARS-CoV-2 in vitro models urgently needs systematic translation and interpretation. To fill this gap, we built COVIDanno, COVID-19 annotation in humans, available at http://biomedbdc.wchscu.cn/COVIDanno/. The aim of this resource is to provide a reference resource of intensive functional annotations of differentially expressed genes (DEGs) among different time points of COVID-19 infection in human in vitro models. To do this, we performed differential expression analysis for 136 individual datasets across 13 tissue types. In total, we identified 4,935 DEGs. We performed multiple bioinformatics/computational biology studies for these DEGs. Furthermore, we developed a novel tool to help users predict the status of SARS-CoV-2 infection for a given sample. COVIDanno will be a valuable resource for identifying SARS-CoV-2-related genes and understanding their potential functional roles in different time points and multiple tissue types

An investigation of annealing methods for benzodithiophene terthiophene rhodanine based all small molecule organic solar cells

Mainstream organic solar cells (OSCs) suffer a great variation of photovoltaic performance among different batches of polymers, which brings an opportunity for all-small-molecule OSCs to take leading position of industrialization. In recent years, benzodithiophene terthiophene rhodamine (BTR), as small molecule donor, has played an important role in this field. Here we investigated two typical BTR based all-small-molecule OSCs processed with different annealing methods, to explore the morphology optimization brought by them. As a result, BTR:PC71BM system was optimized by solvent vapor annealing (SVA) reaching an excellent fill factor (FF) of 79.1% via tuning molecular packing intensity, while BTR:Y6 with temperature annealing (TA) yielded a power conversion efficiency (PCE) of 12.125% whose molecular packing orientation had been changed. Additionally, by crossing using SVA and TA methods, we found that these two method can't be utilized together to further improve the PCE for either system. Therefore, our work offers better PCEs for these two reported combinations and further studies the compatibility between specific BTR based active layers and designated annealing methods, providing deeper understanding of device engineering on all-small-molecule OSCs.publishe

Methanol extract of Aruncus dioicus exerts antidiabetic effect via PCSK9/LDLR pathway

Purpose: To investigate the antidiabetic effect of methanol extract of Aruncus dioicus, and the underlying mechanism(s). Methods: Twenty-four adult female albino mice were randomly assigned to four groups of six mice each: normal control group, diabetic control group and two treatment groups. With the exception of normal control group, the diabetic control and treatment groups consisted of leptin receptor-deficient (db/db) type 2 diabetic mice. The diabetic control group was not treated, while the treatment groups received 200 or 400 mg/kg extract/day orally for 4 weeks. The effect of the extract on fasting blood glucose (FBG), proprotein convertase subtilisin/kexin type 9 (PCSK9), glycogen and lipid profiles were determined. The expressions of PCSK9, low-density lipoprotein receptor (LDL-R) and glucokinase (GCK) were determined in liver tissues using western blotting and real-time quantitative polymerase chain reaction (qRT-PCR). Results: Fasting blood glucose (FBG) was significantly and dose-dependently reduced in the treatment groups, relative to diabetic control group at different time-points (p < 0.05). Total cholesterol (TC), triacylglycerol (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were significantly higher in the diabetic control group than in normal control group (p < 0.05). However, treatment with methanol extract of A. dioicus significantly and dose-dependently reversed the changes in the levels of these parameters (p < 0.05). The expressions of LDLR and GCK were significantly down-regulated in diabetic control group, when compared with normal control group, but their expressions were significantly dose-dependently upregulated in the treatment groups (p < 0.05). Treatment with the extract significantly and dose-dependently down-regulated PCSK9 expression (p < 0.05). Liver injury characterized by large distended lipid droplets and fat accumulation was seen in diabetic mice, but treatment with methanol extract of A. dioicus significantly reversed the histopathological changes induced by DM. Conclusion: These results indicate that the antidiabetic effect of methanol extract of A. dioicus is exerted via a mechanism involving PCSK9/LDLR pathway

PROMPT-IML: Image Manipulation Localization with Pre-trained Foundation Models Through Prompt Tuning

Deceptive images can be shared in seconds with social networking services, posing substantial risks. Tampering traces, such as boundary artifacts and high-frequency information, have been significantly emphasized by massive networks in the Image Manipulation Localization (IML) field. However, they are prone to image post-processing operations, which limit the generalization and robustness of existing methods. We present a novel Prompt-IML framework. We observe that humans tend to discern the authenticity of an image based on both semantic and high-frequency information, inspired by which, the proposed framework leverages rich semantic knowledge from pre-trained visual foundation models to assist IML. We are the first to design a framework that utilizes visual foundation models specially for the IML task. Moreover, we design a Feature Alignment and Fusion module to align and fuse features of semantic features with high-frequency features, which aims at locating tampered regions from multiple perspectives. Experimental results demonstrate that our model can achieve better performance on eight typical fake image datasets and outstanding robustness.Comment: Under Revie

Functional Antagonism of WRI1 and TCP20 Modulates \u3ci\u3eGH3.3\u3c/i\u3e Expression to Maintain Auxin Homeostasis in Roots

Auxin is a well-studied phytohormone, vital for diverse plant developmental processes. The GH3 genes are one of the major auxin responsive genes, whose expression changes lead to modulation of plant development and auxin homeostasis. However, the transcriptional regulation of these GH3 genes remains largely unknown. WRI1 is an essential transcriptional regulator governing plant fatty acid biosynthesis. Recently, we identified that the expression of GH3.3 is increased in the roots of wri1-1 mutant. Nevertheless, in this study we found that AtWRI1 did not activate or repress the promoter of GH3.3 (proGH3.3) despite of its binding to proGH3.3. Cross-family transcription factor interactions play pivotal roles in plant gene regulatory networks. To explore the molecular mechanism by which WRI1 controls GH3.3 expression, we screened an Arabidopsis transcription factor library and identified TCP20 as a novel AtWRI1-interacting regulator. The interaction between AtWRI1 and TCP20 was further verified by several approaches. Importantly, we found that TCP20 directly regulates GH3.3 expression via binding to TCP binding element. Furthermore, AtWRI1 repressed the TCP20-mediated transactivation of proGH3.3. EMSAs demonstrated that AtWRI1 antagonized TCP20 from binding to proGH3.3. Collectively, we provide new insights that WRI1 attenuates GH3.3 expression through interaction with TCP20, highlighting a new mechanism that contributes to fine-tuning auxin homeostasis

COV2Var, a Function Annotation Database of Sars-Cov-2 Genetic Variation

The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants

COVIDanno, COVID-19 annotation in human

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 19 (COVID-19), has caused a global health crisis. Despite ongoing efforts to treat patients, there is no universal prevention or cure available. One of the feasible approaches will be identifying the key genes from SARS-CoV-2-infected cells. SARS-CoV-2-infected in vitro model, allows easy control of the experimental conditions, obtaining reproducible results, and monitoring of infection progression. Currently, accumulating RNA-seq data from SARS-CoV-2 in vitro models urgently needs systematic translation and interpretation. To fill this gap, we built COVIDanno, COVID-19 annotation in humans, available at http://biomedbdc.wchscu.cn/COVIDanno/. The aim of this resource is to provide a reference resource of intensive functional annotations of differentially expressed genes (DEGs) among different time points of COVID-19 infection in human in vitro models. To do this, we performed differential expression analysis for 136 individual datasets across 13 tissue types. In total, we identified 4,935 DEGs. We performed multiple bioinformatics/computational biology studies for these DEGs. Furthermore, we developed a novel tool to help users predict the status of SARS-CoV-2 infection for a given sample. COVIDanno will be a valuable resource for identifying SARS-CoV-2-related genes and understanding their potential functional roles in different time points and multiple tissue types