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This study evaluated the effects of cinnamon extract immersion treatment on the quality improvement of prefabricated small yellow croaker during refrigeration. The changes in total volatile base nitrogen (TVB-N) content, total viable count (TVC), K value, sensory evaluation, pH, texture, color, thiobarbituric acid (TBA) content, total sulfhydryl content, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE), and muscle tissue microstructure of prefabricated small yellow croaker treated with cinnamon extract immersion group (CE) and distilled water immersion group (CK) during storage at 4 ℃ for 14 days were investigated. Results revealed that, the TVB-N content of the CK group reached 31.85 mg/100 g at day 12, which exceeded the limit requirement for qualified products, while the CE group did not exceed 30 mg/100 g at day 14. At the 10th d, the TVC and K values of the CK group were 7.65 lg CFU/g and 59.82%, respectively, which exceeded the qualified aquatic product limit (7.00 lg CFU/g). At this time, the TVC and K values of the CE group were 6.42 lg CFU/g and 40.65%, respectively, which were still in compliance with the qualified aquatic product limit, and effectively delayed the increase in TVC and K values. At the 14 d, the TBA content and pH values of the CE group were lower than those of the CK group, and sensory score, total sulfhydryl content, hardness, adhesiveness, and chewiness were better than those of the CK group. However, it did not significantly affect its elasticity and gumminess (P>0.05), while maintaining the integrity of the muscle tissue structure. Consequently, cinnamon extract immersion treatment improved the freshness, texture, sensory properties, lipid oxidation, as well as protein oxidation and degradation of prefabricated small yellow croaker during refrigeration, thereby retarding the deterioration of quality. This research provides technical and data support for quality regulation, safety assurance, and shelf-life extension of prefabricated small yellow croaker.

Abstract Immune cell therapy based on chimeric antigen receptor (CAR) technology platform has been greatly developed. The types of CAR immune cell therapy have expanded from T cells to innate immune cells such as NK cells and macrophages, and the diseases treated have expanded from hematological malignancies to non-tumor fields such as infectious diseases and autoimmune diseases. Among them, CAR-T and CAR-NK therapy have observed examples of rapid remission in approved clinical trials, but the efficacy is unstable and plagued by tumor resistance. Trogocytosis is a special phenomenon of intercellular molecular transfer that is common in the immune system and is achieved by recipient cells through acquisition and internalization of donor cell-derived molecules and mediates immune effects. Recently, a novel short-term drug resistance mechanism based on trogocytosis has been proposed, and the bidirectional molecular exchange between CAR immune cells and tumor cells triggered by trogocytosis partially explains the long-term relapse phenomenon after treatment with CAR immune cells. In this review, we summarize the research progress of trogocytosis in CAR immunotherapy, discuss the influencing factors of trogocytosis and its direct and indirect interference with CAR immune cells and emphasize that the interference of trogocytosis can further release the potential of CAR immune cell therapy.

Objectives: One of the most common sensory impairments in the elderly is age-related hearing loss, and individuals with this condition have a higher risk of mild cognitive impairment than the overall aged population. The purpose of this study was to conduct a systematic review of the literature in order to evaluate the evidence supporting the hypothesis that mild cognitive impairment may be developed in patients with age-related hearing loss. Methods: The PRISMA principles were followed when searching the databases of the China Knowledge Network, Wanfang, China Biomedical Literature Database, Pub Med, Cochrane Library, Embase, and Web of Science. Two investigators independently carried out the quality assessment, data extraction, and literature review of the eligible studies. Stata 17.0 was used to finish the statistical analysis and descriptive results. Results: A total of 13 articles containing 2,222,036 individuals who were evaluated for demographic traits, factors associated with age-related hearing loss, vascular neurologic factors, and psychological factors were included after 2166 search records were found in the database. In patients with age-related hearing loss, eleven factors were found to be risk factors for the development of mild cognitive impairment: age (OR = 1.63; 95% CI 1.09–2.43), male (OR = 1.29; 95% CI 1.14–1.47), degree of hearing loss (OR = 1.35; 95% CI 1.03–1.75), not wearing hearing aids (OR = 1.56; 95% CI 1.37–1.79), cerebrovascular disease (OR = 1.41; 95% CI 1.17–1.69), cardiovascular disease (OR = 1.29; 95% CI 1.07–1.55), diabetes mellitus (OR = 1.28; 95% CI 1.20–1.35), head injury (OR = 1.22; 95% CI 1.13–1.33), alcohol consumption (OR = 1.28; 95% CI 1.14–1.43), and tobacco use (OR = 1.19; 95% CI 1.14–1.25), and depression (OR = 1.63; 95% CI 1.47–1.81). Conclusion: Caregivers can customize care strategies to decrease the occurrence of mild cognitive impairment in elderly deaf patients by considering demographic traits, factors associated with age-related hearing loss, vascular-neurologic factors, and psychological factors.

Ovarian tumors can be divided into epithelial tumors, germ cell tumors, sex cord-stromal tumors and metastatic tumors according to histological types. Their biological behaviors are different. Lymphangioma is a rare benign tumor that can occur anywhere in the body. Among them, ovarian lymphangioma is particularly rare. The case we reported is the case of ovarian lymphangioma. The patient was admitted to the hospital one month after the physical examination found the ovarian mass. After the examination, the patient was treated with laparoscopic surgery. The patient recovered well after the operation, and no recurrence was found after the follow-up.

With the advancement of Fuel Cell Vehicles (FCVs), detecting hydrogen leaks is critically important in facilities such as hydrogen refilling stations. Despite its significance, the dynamic response performance of hydrogen sensors in confined spaces, particularly under ceilings, has not been comprehensively assessed. This study utilizes a catalytic combustion hydrogen sensor to monitor hydrogen leaks in a confined area. It examines the effects of leak size and placement height on the distribution of hydrogen concentrations beneath the ceiling. Results indicate that hydrogen concentration rapidly decreases within a 0.5–1.0 m range below the ceiling and declines more gradually from 1.0 to 2.0 m. The study further explores the attenuation pattern of hydrogen concentration radially from the hydrogen jet under the ceiling. By normalizing the radius and concentration, it was determined that the distribution conforms to a Gaussian model, akin to that observed in open space jet flows. Utilizing this Gaussian assumption, the model is refined by incorporating an impact reflux term, thereby enhancing the accuracy of the predictive formula.

BackgroundIn the field of audiology, numerous studies have sought to understand and improve hearing rehabilitation programs for older adults afflicted with presbycusis. Despite this, the field lacks uniform standards pertaining to the intervention methods, frequency, and duration of such programs. These discrepancies have led to varying test results and inconsistent findings across multiple studies.ObjectiveThis meta-analysis aimed to evaluate the efficacy of hearing rehabilitation programs in enhancing the utilization of hearing aids among older adults with presbycusis.MethodsWe conducted a comprehensive exploration of PubMed, Embase, Cochrane Library, and Web of Science to identify randomized controlled trials assessing the role of hearing rehabilitation programs for patients with age-related hearing loss. The search period spanned from the inception of each database to September 12, 2024. Outcomes were synthesized using RevMan 5.4 software.ResultsEight studies met the inclusion criteria, involving 598 patients (290 in the intervention group and 308 in the control group). It was observed that hearing rehabilitation programs significantly diminished self-perceived hearing impairment [MD = −5.80, 95% CI = (−8.16, −3.44), p < 0.00001] and negative emotional states [MD = −1.66, 95% CI = (−3.02, −0.29), p = 0.02], while enhancing hearing aid utilization [MD = 0.22, 95% CI = (0.08, 0.36), p = 0.002]. Nonetheless, these programs did not significantly augment patients’ satisfaction with their hearing aids [MD = 0.09, 95% CI = (−0.17, 0.26), p = 0.66].ConclusionHearing rehabilitation programs significantly improve hearing aid outcomes, reduce self-perceived hearing impairment, and alleviate negative emotional states in patients. However, the current body of evidence is insufficient to conclusively indicate that these programs enhance patient satisfaction with daily hearing aid usage.

Abstract Background Paradoxical embolism is a rare cause of acute arterial occlusion. This phenomenon arises when embolic material travels from the venous system crosses an abnormal shunt such as patent foramen ovale, atrial septal defects, ventricular septal defects, or pulmonary arteriovenous malformations, into the arterial system. Impending paradoxical embolism refers to the presence of an entrapped thrombus in the patent foramen ovale. Case presentation We report a case of a 68-year-old female patient who presented with an impending paradoxical embolism, alongside both concomitant pulmonary embolism and myocardial infarction with ST-segment elevation. Swiftly addressed through emergency cardiac surgery and systemic anticoagulation, the patient’s condition was effectively treated. Conclusions While the ideal treatment strategy for impending paradoxical embolism remains a topic of debate due to limited and inconclusive evidence, emergent open surgery should be contemplated in patients as it signifies a critical clinical emergency.

Abstract Background The chimeric antigen receptor (CAR)-T therapy has a limited therapeutic effect on solid tumors owing to the limited CAR-T cell infiltration into solid tumors and the inactivation of CAR-T cells by the immunosuppressive tumor microenvironment. Macrophage is an important component of the innate and adaptive immunity, and its unique phagocytic function has been explored to construct CAR macrophages (CAR-Ms) against solid tumors. This study aimed to investigate the therapeutic application of CAR-Ms in ovarian cancer. Methods In this study, we constructed novel CAR structures, which consisted of humanized anti-HER2 or CD47 scFv, CD8 hinge region and transmembrane domains, as well as the 4-1BB and CD3ζ intracellular domains. We examined the phagocytosis of HER2 CAR-M and CD47 CAR-M on ovarian cancer cells and the promotion of adaptive immunity. Two syngeneic tumor models were used to estimate the in vivo antitumor activity of HER2 CAR-M and CD47 CAR-M. Results We constructed CAR-Ms targeting HER2 and CD47 and verified their phagocytic ability to ovarian cancer cells in vivo and in vitro. The constructed CAR-Ms showed antigen-specific phagocytosis of ovarian cancer cells in vitro and could activate CD8+ cytotoxic T lymphocyte (CTL) to secrete various anti-tumor factors. For the in vivo model, mice with human-like immune systems were used. We found that CAR-Ms enhanced CD8+ T cell activation, affected tumor-associated macrophage (TAM) phenotype, and led to tumor regression. Conclusions We demonstrated the inhibition effect of our constructed novel HER2 CAR-M and CD47 CAR-M on target antigen-positive ovarian cancer in vitro and in vivo, and preliminarily verified that this inhibitory effect is due to phagocytosis, promotion of adaptive immunity and effect on tumor microenvironment.

To reduce the ash content of bone collagen peptide and improve the quality of bone collagen peptide products. In this paper, the method of nanofiltration desalination was used to remove ash. The process parameters for nanofiltration desalination of bone collagen peptides were optimized through design response tests. The changes in physical and chemical indicators, amino acid content, molecular weight distribution, content of various elements, and sensory scores of samples treated with nanofiltration membranes were analyzed. Results showed that, the optimal desalination process conditions were sample concentration of 5%, cycle times of 7 times and pressure of 0.5 MPa. Under this condition, the desalination rate was 65.89%±1.25%. After nanofiltration membrane treatment, the quality of the sample was significantly improved, but the amino acid content did not change much. Through the measurement of molecular weight distribution, it was found that nanofiltration desalination had little impact on the change of molecular weight distribution, the components with molecular weight less than 3000 Da accounted for 97%, which was in line with the provisions of the national food safety standard GB 31645-2018 bone collagen peptides. ICP-MS was used to analyze the changes in the content of various elements before and after desalination, and it was found that the content of various elements in the sample decreased to varying degrees, the content of Na, K, P, Mg, Ca decreased significantly (P

IntroductionAs deep learning has achieved state-of-the-art performance for many tasks of EEG-based BCI, many efforts have been made in recent years trying to understand what have been learned by the models. This is commonly done by generating a heatmap indicating to which extent each pixel of the input contributes to the final classification for a trained model. Despite the wide use, it is not yet understood to which extent the obtained interpretation results can be trusted and how accurate they can reflect the model decisions.MethodsWe conduct studies to quantitatively evaluate seven different deep interpretation techniques across different models and datasets for EEG-based BCI.ResultsThe results reveal the importance of selecting a proper interpretation technique as the initial step. In addition, we also find that the quality of the interpretation results is inconsistent for individual samples despite when a method with an overall good performance is used. Many factors, including model structure and dataset types, could potentially affect the quality of the interpretation results.DiscussionBased on the observations, we propose a set of procedures that allow the interpretation results to be presented in an understandable and trusted way. We illustrate the usefulness of our method for EEG-based BCI with instances selected from different scenarios.

Lunar in-situ resource utilization (ISRU) has been put on the agenda by many countries. Due to the special material nature and low gravity environment, the lunar regolith demonstrates significantly different behavior from terrestrial geomaterials. However, the systematic understanding of its geotechnical behavior is now seriously restricted by the scarcity of lunar regolith and the difficulty in simulating lunar gravity. A new lunar regolith simulant, termed as China University of Mining and Technology Number One (CUMT-1), has been developed to recover properties of the lunar regolith and simulate the lunar gravity by adopting the recently advanced geotechnical magnetic-similitude-gravity model testing (GMMT) method. The CUMT-1 simulant was prepared by reproducing the in-situ formation and fragmentation of the lunar matrix, which plays a key role in the irregular particle morphology. The mineralogical compositions, particle morphology and gradation, specific gravity, bulk density, void ratio, shear strength, and compressibility were determined. After quantifying the magnetization and magnetic-similitude-gravity characteristics, an application of the cone penetration resistance under low gravity was further given. The obtained results are compared to the values known for lunar regolith samples and other simulants, which demonstrates promising characteristics for use in geotechnical engineering-based and scientific-based applications, especially considering the influence of lunar gravity.

Lytic replication of human cytomegalovirus (HCMV), a member of β-herpesvirus, is a highly complicated and organized process that requires its DNA polymerase processivity factor, UL44, the first-reported HCMV replication protein subjected to SUMO post-translational modification (PTM). SUMOylation plays a pleiotropic role in protein functions of host cells and infecting viruses. Particularly, formation of herpesviral replication compartments (RCs) upon infection is induced in proximity to ND10 subnuclear domains, the host cell’s intrinsic antiviral immune devices and hot SUMOylation spots, relying just on SUMOylation of their protein components to become mature and functional in restriction of the viral replication. In this study, to unveil the exact role of SUMO PTM on UL44 involved in HCMV replication, we screened and identified PIAS3, an annotated E3 SUMO ligase, as a novel UL44-interacting protein engaged in cellular SUMOylation pathway. Co-existence of PIAS3 could enhance the UBC9-based SUMO modification of UL44 specifically at its conserved 410lysine residue lying within the single canonical ψKxE SUMO Conjugation Motif (SCM). Intriguingly, we found this SCM-specific SUMOylation contributes to UL44 co-localization and interaction with subnuclear ND10 domains during infection, which in turn exerts an inhibitory effect on HCMV replication and growth. Together, these results highlight the importance of SUMOylation in regulating viral protein subnuclear localization, representing a novel way of utilizing ND10-based restriction to achieve the self-controlled slower replication and reproduction of herpesviruses.

Gravity is the most important load source in mining and geotechnical engineering, which causes both the stress level and stress gradient inside geomaterials. Different from the stress level, the influence of gravity-induced stress gradient on the behaviour of the material is still unknown. An in-deep study on it will help to promote the understanding of material behaviour, especially for those cases related to unconventional gravity such as terrestrial ng physical modelling and extraterrestrial resource exploitation (g is the terrestrial gravitational acceleration). In this study, a high-order homogenization for granular materials is proposed at first, in which the stress gradient is drawn into the constitutive representation by adopting a representative volume element (RVE). The consolidation and shear strength behaviour of RVE are then investigated by performing numerical biaxial tests. The results show that all the compressibility, shear strength, shear stiffness, volumetric deformation, and critical state behaviour show a stress gradient dependence. A coupling between stress gradient, stress level, and material properties is also observed. These observations suggest that, besides the stress level, extra attention needs to be paid to material responses related to stress gradient during engineering practices.

BackgroundDementia is a chronic progressive neurodegenerative disease that can lead to disability and death in humans, but there is still no effective prevention and treatment. Due to the neuroprotective effects of vitamin E, a large number of researchers have explored whether vitamin E can reduce the risk of dementia. Some researchers believe that vitamin E can reduce the risk of dementia, while others hold the opposite conclusion. We therefore performed a meta-analysis to clarify the relationship between them.MethodsWe searched PubMed, Embase, and Web of Science databases for articles on the connection of dietary and supplementation vitamin E with dementia risk from inception through April 2022 using the main keywords “dementia,” “Alzheimer's disease,” “vitamin E,” and “tocopherol,” and used a random-utility model for pooled effect sizes. Odds ratios (OR) and 95% confidence intervals were derived using lower and higher doses as contrasts. Obtained data were shown and assessed using Stata12.0 free software.ResultsWe included 15 articles in sum. Among them, there were nine articles containing AD. By comparing the highest intake with the lowest intake, Combined ORs for high intake were as follows: dementia (OR = 0.79, 95% CI 0.70–0.88 I2 = 35.0%), Alzheimer's disease (OR = 0.78, 95% CI 0.64–0.94 I2 = 36.9%). Subgroup analyses were also performed by study type, diet and supplementation, and NOS score.ConclusionsHigh vitamin E intake from diet and supplements significantly reduces the risk of dementia and Alzheimer's disease.

Lymphatic metastasis influences clinical treatment and prognosis of patients with non-small-cell lung cancer (NSCLC). There is an urgency to understand the molecular features and mechanisms of lymph node metastasis. We analyzed the molecular features on pairs of the primary tumor and lymphatic metastasis tissue samples from 15 NSCLC patients using targeted next-generation sequencing. The potential metastasis-related genes were screened from our cohort based on cancer cell fraction. After filtering with gene functions, candidate metastasis-related events were validated in the MSK cohort with Fisher’s exact test. The molecular signature and tumor mutational burden were similar in paired samples, and the average mutational concordance was 42.0% ± 28.9%. Its metastatic mechanism is potentially a linear progression based on the metastatic seeding theory. Furthermore, mutated ataxia telangiectasia mutated and Rad3-related (ATR) and tet methylcytosine dioxygenase 2 (TET2) genes were significantly enriched in lymphatic metastases (p ≤ 0.05). Alterations in these two genes could be considered metastasis-related driving events. Mutated ATR and TET2 might play an active role in the metastasis of lymph nodes with NSCLC. More case enrollment and long-term follow-up will further verify the clinical significance of these two genes.

Ulcerative colitis (UC) is a chronic idiopathic inflammatory bowel disease characterized by rapid progression and frequent comorbidities that make its treatment challenging. Nanomaterial-based strategies have been extensively studied to target the GI mucosal immune system in recent years. Herein, we propose a novel apigenin-Mn(II) loaded sodium hyaluronate nanoparticles where apigenin (API) was incorporated in the Mn2+ ramework, coated with hyaluronic acid. The apigenin-Mn(II) loaded sodium hyaluronate nanoparticles (API-Mn(II)@HA NPs) exhibited a diameter of 200 nm and were effective against UC. The preparation of the API-Mn(II) complex was relatively simple, and the mechanism underlying its therapeutic effect on UC induced by sodium dextran sulfate (DSS) was studied in detail. We found that API-Mn(II)@HA nanoparticles could effectively repair the intestinal barrier and significantly improve the damaged colon tissue by mediating inflammatory factors. This study provides novel insights on a new kind of active targeted nanoparticle for improving the efficacy of drugs for UC treatment.

We present a systematic assessment of polygenic risk score (PRS) prediction across more than 1,500 traits using genetic and phenotype data in the UK Biobank. We report 813 sparse PRS models with significant (p < 2.5 x 10-5) incremental predictive performance when compared against the covariate-only model that considers age, sex, types of genotyping arrays, and the principal component loadings of genotypes. We report a significant correlation between the number of genetic variants selected in the sparse PRS model and the incremental predictive performance (Spearman's ⍴ = 0.61, p = 2.2 x 10-59 for quantitative traits, ⍴ = 0.21, p = 9.6 x 10-4 for binary traits). The sparse PRS model trained on European individuals showed limited transferability when evaluated on non-European individuals in the UK Biobank. We provide the PRS model weights on the Global Biobank Engine (https://biobankengine.stanford.edu/prs).

Gravity is the primary load source in geotechnical engineering, and its effect becomes extremely important in these cases such as lunar research station construction and in situ resource utilization. However, at the current stage, the study on the effect of gravity-induced stress gradients on the behavior of geomaterials is seriously lacking. In this work, the size-dependent behaviour of representative volume element (RVE) of granular matter under the gravity-induced stress gradient is studied. A homogenization theory is proposed firstly, which homogenizes the granular matter into stress gradient continuum through RVE. Then, numerical triaxial loading for RVEs with various heights and particle sizes is carried out under 0∼10 g gravity. The results show that the size effect and its origination appear to have no obvious influence on isotropic compression. However, the macroscopic shear strength, elastic modulus, and volumetric deformation all show size effect dependence, and the gravity-induced stress gradient leads to significant differences between different originations of size effect. The valence, orientation, and elongation degree of microscopic void cells are further analyzed, which suggests that applying of stress gradient results in the evolution of void cells demonstrates a dependence on both the size effect and its origination. The results indicate that the gravity-induced stress gradient and corresponding size effect should be paid sufficient attention to granular mechanics of terrestrial and off-earth engineering.

Users who initiate continuous location queries are prone to trajectory information leakage, and the obtained query information is not effectively utilized. To address these problems, we propose a continuous location query protection scheme based on caching and an adaptive variable-order Markov model. When a user initiates a query request, we first query the cache information to obtain the required data. When the local cache cannot satisfy the user’s demand, we use a variable-order Markov model to predict the user’s future query location and generate a k-anonymous set based on the predicted location and cache contribution. We perturb the location set using differential privacy, then send the perturbed location set to the location service provider to obtain the service. We cache the query results returned by the service provider to the local device and update the local cache results according to time. By comparing the experiment with other schemes, the proposed scheme in this paper reduces the number of interactions with location providers, improves the local cache hit rate, and effectively ensures the security of the users’ location privacy.

Attention refers to the human psychological ability to focus on doing an activity. The attention assessment plays an important role in diagnosing attention deficit hyperactivity disorder (ADHD). In this paper, the attention assessment is performed via a classification approach. First, the single-channel electroencephalograms (EEGs) are acquired from various participants when they perform various activities. Then, fast Fourier transform (FFT) is applied to the acquired EEGs, and the high-frequency components are discarded for performing denoising. Next, empirical mode decomposition (EMD) is applied to remove the underlying trend of the signals. In order to extract more features, singular spectrum analysis (SSA) is employed to increase the total number of the components. Finally, some typical models such as the random forest-based classifier, the support vector machine (SVM)-based classifier, and the back-propagation (BP) neural network-based classifier are used for performing the classifications. Here, the percentages of the classification accuracies are employed as the attention scores. The computer numerical simulation results show that our proposed method yields a higher classification performance compared to the traditional methods without performing the EMD and SSA.

The number of software vulnerabilities is increasing year by year. In the era of big data, data-processing software with many users is more concerned by hackers. It is essential to improve the efficiency of discovering vulnerabilities in data-processing software. We noticed that in the process of discovering vulnerabilities, some problems of existing technology such as fuzzing, symbolic execution, and taint analysis have more or fewer relationships with data-processing functions. In fuzzing, there are two types of sanity checks toward the target program: NCC (Non-critical check) and CC (critical check). It is usually challenging to bypass such a sanity check, which leads to low code coverage during fuzzing. In symbolic execution, the constraint solver still has the problem of trying to deal with the constraints of complex algorithms. In taint analysis, the problem of over-taint and under-taint is always the key to affect the accuracy of the results. Therefore, to solve the above problems, it is necessary to identify the data-processing function. Based on identifying data-processing functions, we could identify those sanity checks, ease the solution of complex constraints, and understand the way of taints propagation to assist in software vulnerability discovery and analysis. This paper proposed a method called DPFI(data-processing function identification) for identifying data-processing functions with deep neural networks. We collected 37000 functions from GitHub and implemented the method on the data set with several neural networks, among which the performance of CNN achieved best and F1-score was 0.90. We then applied the trained model on CGC(cyber grand challenge) data and real softwares for testing. For CGC, we got 448 functions in 20 programs, in which 35 were identified as data-processing functions. For real softwares, such as FFmpeg, 7zip, jpeg, the precision rate all reached 0.90 and F1-score was above 0.87.

The accelerating growth of the public microbial genomic data imposes substantial burden on the research community that uses such resources. Building databases for non-redundant reference sequences from massive microbial genomic data based on clustering analysis is essential. However, existing clustering algorithms perform poorly on long genomic sequences. In this article, we present Gclust, a parallel program for clustering complete or draft genomic sequences, where clustering is accelerated with a novel parallelization strategy and a fast sequence comparison algorithm using sparse suffix arrays (SSAs). Moreover, genome identity measures between two sequences are calculated based on their maximal exact matches (MEMs). In this paper, we demonstrate the high speed and clustering quality of Gclust by examining four genome sequence datasets. Gclust is freely available for non-commercial use at https://github.com/niu-lab/gclust. We also introduce a web server for clustering user-uploaded genomes at http://niulab.scgrid.cn/gclust. Keywords: Microbial genome clustering, Parallelization, Sparse suffix array, Maximal exact match, Segment extension

Brain science accelerates the study of intelligence and behavior, contributes fundamental insights into human cognition, and offers prospective treatments for brain disease. Faced with the challenges posed by imaging technologies and deep learning computational models, big data and high-performance computing (HPC) play essential roles in studying brain function, brain diseases, and large-scale brain models or connectomes. We review the driving forces behind big data and HPC methods applied to brain science, including deep learning, powerful data analysis capabilities, and computational performance solutions, each of which can be used to improve diagnostic accuracy and research output. This work reinforces predictions that big data and HPC will continue to improve brain science by making ultrahigh-performance analysis possible, by improving data standardization and sharing, and by providing new neuromorphic insights. Keywords: Brain science, Big data, High-performance computing, Brain connectomes, Deep learning

This paper develops a distributed method, namely, distributed allocation with time windows (DATW) for managing the multi-UAV task assignment problem (MTAP) with complex time window constraints. By aiming directly to minimize the average task completion time, the pro-posed DATW intends to achieve a conflict-free result that allocates all tasks within the validity time windows. Based on the decentralized PI (Performance Impact) framework, the proposed algorithm addresses the MTAP in a three-phase task assignment strategy, which includes task inclusion, conflict resolution, and task reallocation. The newly introduced task allocation phase achieves a noteworthy increase in an average number of allocated tasks. Unlike the traditional PI methods, the start time of each task is broadcasted among agents via communication typology, and the significance value of each task is directly related to its validity time window, such that the vast majority of tasks are able to be assigned properly without imposing any extra communication burdens. In the obtained conflict-free allocation solution by DATW, each task is allocated to a proper UAV with all given constraints satisfied. Finally, the simulation results demonstrate the effectiveness and superiority of the proposed DATW. Compared with existing (CBBA-based) solutions, results show up to an 18% increase in success rate (SR) using the proposed method.

Fuzz testing is a widely used technique for software vulnerability detection, but it is still limited in finding bugs nested in the deep program states. Parallel testing is an augmented method aiming to make the best of the computing resource to expose more deep program bugs. However, current parallel testing methods cannot deal well with task slicing so that the parallel nodes show serious duplication with each other, thus decreasing the efficiency in total. For instance, the original parallel mode of the well-known fuzzer American fuzzy lop (AFL) does not split the task and just synchronizes the interesting seeds without any internal execution information. In this paper, we put forward a novel program state sensitive parallel testing method, which: 1) splits the task into low correlated subtasks according to the program states and 2) adjusts the mutation engine to confine one instance's testing among its subtask-related code region as more as possible. Our method is an objective to reduce the testing collision between parallel instances and therefore improve the performance. We developed a new fuzzer called PAFL and implemented some experiments to investigate that if our parallel testing framework is positive when deploying multiple instances and if it shows a better path discovery compared with two state-of-the-art fuzzers, AFL and AFLFast. In the experiments, we employed PAFL with 1/2/4/8/16 to observe their path discovery and conclude that our new parallel framework is positive when using more multiple instances. We also compared PAFL with AFL and AFLFast by employing eight parallel instances for each fuzzer, and the results prove that our tool has the best path discovery among the three fuzzers. Compared with the original parallel AFL, PAFL can achieve averaged performance gains of 3.98, 3.04, 4.18, and 1.45 on the c++filt, objdump, readelf, and tcpdump, respectively. Besides, we took PAFL on binutils and libtiff, and finally, we found ten new bugs.

The accurate identification of the gas–liquid two-phase flow pattern within the impeller of a centrifugal pump is critical to develop a reliable model for predicting the gas–liquid two-phase performance of the centrifugal pump. The influences of the inlet gas volume fraction, the liquid phase flow rate and the pump rotational speed on the flow characteristics of the centrifugal pump were investigated experimentally. Four typical flow patterns in the impeller of the centrifugal pump, i.e., the bubble flow, the agglomerated bubble flow, the gas pocket flow and the segregated flow, were obtained, and the corresponding flow pattern maps were drawn. After oversampling based on the SMOTE algorithm, a four-layer artificial neural network model with two hidden layers was constructed. By selecting the appropriate network super parameters, including the neuron numbers in the hidden layer, the learning rate and the activation function, the different flow patterns in the centrifugal pump impeller were identified. The identification rate of the model increased from 89.91% to 94.88% when the original data was oversampled by the SMOTE algorithm. It is demonstrated that the SMOTE algorithm is an effective method to improve the accuracy of the artificial neural network model. In addition, the Kappa coefficient, the Macro-F1 and the Micro-F1 were 0.93, 0.95 and 0.95, respectively, indicating that the model established in this paper can well identify the flow pattern in the impeller of a centrifugal pump.

A collision property analysis of the GMR-2 cipher used in the satellite phone was presented.By using the F-component as a bridge,the link between the difference of the key byte and the collision of the output ofFas well as the link between the collision of the output of F and the collision of keystream byte were analyzed,which finally revealed the relationship between the difference of the original key byte and the keystream collision.The theoretical analysis showed that for a random frame number,a special chosen key pair could lead to a keystream collision with a high probability,when the key pair has only one byte difference in which the most significant 4 bit of the difference was equal to the last significant 4 bit.The experimental result shows that the keystream collision probability is 2−8.248,which is far higher than the ideal collision probability 2−120.This proves once again,that there exists serious potential security hazards in the GMR-2 cipher.

The popularity of campus information intelligence aims to provide better applications and services. However, we found that a phenomenon that has brought great inconvenience to students is queuing when pay in smart campus which needs to be resolved urgently. For example, buying meals in the school cafeteria at lunch or dinner time, paying school tuition, and so on. Also the privacy security is the primary prerequisite for smart campus's mobile electronic payment while transaction information can be intercepted easily by Hacker or hidden HD camera. In this paper, we propose the SafeMP, a mobile security and multi-to-one payment system employing the mechanical-wave transmission to reduce queue time and improve efficiency. The biggest conundrum with implementing this system is how to separate the multiple aliasing signals. The SafeMP is designed with a key finding: although the multiple aliasing signals are irregular, coupling degree between different mechanical wave signals is highly stable. We divide our work into three parts. First, we present a novel compensation method addressing the attenuation with the transmission distance. In addition, we define the degree of coupling to discriminate the aliasing for mechanical wave in ever slot. Finally, we design the rules of orthogonal coding to further connect the data bitstream of each time slot and restore the complete information which transmitted by different user, then the information separated can be corresponded to correct user. Our evaluation results show that the transmission distance does not influence the performance of the SafeMP. The SafeMP achieves an average accuracy of 97%.

Background: The number of red blood cells (RBCs) increases significantly in response to high-altitude hypoxic environments, and the RBC microRNA (miRNA) expression pattern is similar to that in whole blood. Studies have shown that miRNA in plasma can act as a circulating hypoxia-associated marker, but the effect of a high-altitude hypoxic environment on RBC-derived miRNAs has not yet been reported.Methods: Blood samples were collected from 20 Han Chinese individuals residing at 500 m (Sichuan Han), 10 migrant Han Chinese citizens residing at 3,658 m (Tibet Han) and 12 native Tibetans, and RBC indices measurements and miRNA sequencing analyses were performed for the three sample groups. The levels of some markedly altered miRNAs at high altitude were subsequently measured from 5 randomly selected samples of each group by real-time PCR. Bioinformatic analyses was performed to determine the potential target genes of selected hypoxia-associated miRNAs.Results: Marked changes of several RBC indices were observed among the Tibet Han population, the Tibetan population and the Sichuan Han population. A total of 516 miRNAs derived from RBCs were initially identified by miRNA sequencing in the three sample groups. Compared with the Sichuan Han population, 49 miRNAs were differentially expressed in the Tibet Han population (17 upregulated and 32 downregulated). 12 upregulated and 21 downregulated miRNAs were observed in the Tibetan population compared with the Sichuan Han population. A total of 40 RBC miRNAs were differentially expressed in the Tibetan population (15 upregulated and 25 downregulated) compared with the Tibet Han population. Two significantly altered miRNAs with the highest expression levels (miRNA-144-5p and miR-30b-5p) were selected for real-time PCR analysis, and the results were consistent with those of miRNA sequencing. Furthermore, bioinformatic analyses showed that some potential target genes of miR-144-5p and miR-30b-5p are involved in the erythroid- hypoxia-, and nitric oxide (NO)-related signaling pathways in response to hypoxia.Conclusion: Our findings provide clear evidence, for the first time, that a high-altitude hypoxic environment significantly affects human RBC miRNA profiles.

There is a need for affordable, widely deployable maternal-fetal ECG monitors to improve maternal and fetal health during pregnancy and delivery. Based on the diffusion-based channel selection, here we present the mathematical formalism and clinical validation of an algorithm capable of accurate separation of maternal and fetal ECG from a two channel signal acquired over maternal abdomen. The proposed algorithm is the first algorithm, to the best of the authors' knowledge, focusing on the fetal ECG analysis based on two channel maternal abdominal ECG signal, and we apply it to two publicly available databases, the PhysioNet non-invasive fECG database (adfecgdb) and the 2013 PhysioNet/Computing in Cardiology Challenge (CinC2013), to validate the algorithm. The state-of-the-art results are achieved when compared with other available algorithms. Particularly, the F1 score for the R peak detection achieves 99.3% for the adfecgdb and 87.93% for the CinC2013, and the mean absolute error for the estimated R peak locations is 4.53 ms for the adfecgdb and 6.21 ms for the CinC2013. The method has the potential to be applied to other fetal cardiogenic signals, including cardiac doppler signals.

Background and objective Multidrug resistance (MDR) is the main cause of chemotherapeutic failure in lung cancer, and vinorelbine (NVB) is one of the most efficient drugs that threaten non-small cell lung cancer (NSCLC). The current study aims to establish tumor xenografts and investigate the molecular mechanisms involved in the resistance of NVB in lung adenocarcinoma. Methods Nude mice were implanted with Anip973 and Anip973/NVB, and tumor-bearing mice were divided into the Anip973 treatment, Anip973 control, Anip973/NVB treatment, and Anip973/NVB control groups, respectively. The current study observes tumor growth, draws growth curves, and calculates inhibitory rates. The morphological changes in cell tumor were observed through the immunohistochemical method using an electron microscope to detect the expressions of MRP3 and Bcl-2 and to investigate the molecular mechanisms of Anip973/NVB cells. Results The tumor inhibitory rates of the Anip973 and Anip973/NVB cells treated with NVB were 60.00% and 4.65%, respectively, compared with the control group. The growth inhibition in the Anip973/NVB cell transplantation tumor had no significant difference. Apoptosis was observed using TEM when the Anip973 transplantation tumor was treated with NVB. On the other hand, no apoptosis was found in the Anip973/NVB transplantation tumor using TEM. Immunohistochemical staining (SP) shows the positive expressions of Bcl-2 and MRP3 proteins in Anip973/NVB transplantation tumor, which were observed to be higher than those in the Anip973 transplantation tumor. Conclusion The overexpression of Bcl-2 and MRP3 might be one of the major mechanisms of the MDR of Anip973/NVB.

To explore the impact of environmental factors on soil organic carbon (SOC) with machine learning (ML) model is of great significance for mitigating climate change and soil carbon sequestration and emission reduction. However, the traditional ML model is limited by the hyperparameter adjustment of artificially trial-and-error experimentation and the inexplicability of fitting process, and the precision and performance of ML model cannot be fully utilized. For the end, this study developed a tree-structured Parzen estimator-extreme gradient boosting (TPE-XGBoost) method based on SHapley additive explanations (SHAP) analysis to analyze the response of climate, human activities, soil properties and terrain for SOC (0-200cm) in different land use types of China. The results of descriptive statistics described the order of SOC content: forest land > grassland > cultivated land > unused land. With the increase of soil depth, the SOC content of all land types decreased continuously, and the values indicate a left-skewed non-normal distribution. The fitting accuracy (R2) of TPE-XGBoost model for SOC content was greater than 0.8. At the depth of 0-5cm, the prediction accuracy of cultivated land (R2 = 0.96), grassland (R2 = 0.93), forest land (R2 = 0.95) and unused land (R2 = 0.95) was the highest. The result of SHAP analysis showed that the factors that contributed the most to the fitting accuracy of cultivated land, grassland, forest land and unused land in all depths were temperature, soil pH, temperature and elevation. From surface to deep soil, the mean SHAP value showed a downward trend, indicating that the driving force of environmental factors on the content of SOC gradually weakened. The individual explanations of the variance partitioning (VP) analysis of climate, terrain, and soil property for cultivated land (0-200cm), forest land (30-60cm), and unused land (0-200cm) was as high as 0.32, 0.17, and 0.16, respectively, which indicated that these environmental factors had a high response to SOC content. It is found that the appropriate temperature not only promotes plant roots to obtain nutrients, but also interacts with soil pH on microorganisms, thereby increasing the SOC content. The results confirm that the TPE-XGBoost model based on SHAP analysis can reliably explain the nonlinear driving effect of environmental factors on the SOC, which provides credible decision support for accounting carbon budget and carbon sequestration in large-scale regions.