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This paper presents the results of the simulations of the thermal storage and thermal release processes in a spouted bed using a self-developed computational fluid dynamics–discrete element method (CFD–DEM) model to analyze the thermal energy storage (TES) characteristics of the spouted bed with varying nozzle numbers. The thermal storage capacity, thermal release capacity and thermal storage efficiency were analyzed. Additionally, the effects of gas inlet jet number and gas flowrate on the thermal storage characteristics are discussed. The results showed that a higher number of nozzles resulted in a faster change of particle temperature, higher gas phase temperature field update rate and a higher thermal storage capacity. However, when the number of nozzles is increased from 1 to 2 and then 3, the rate of increase in total thermal storage and total thermal release decreases, and the increase in thermal release is always higher than the increase in thermal storage. When the number of nozzles is increased from one through three, the thermal efficiency increased from 52.9% to 75.6%, establishing that a higher number of nozzles improves the thermal efficiency.

According to characteristics of various modulation and demodulation modes, bit error rate of modulation modes including binary amplitude shift keying, binary frequency shift keying and binary differential phase shift keying under different demodulation modes were simulated and compared on the basis of characteristics of mine through-the-earth communication channel. The results show that the binary frequency shift keying coherent demodulation mode can reduce the bit error rate in transmission process of voice signal effectively, and improve reliability and accuracy of the through-the-earth communication with certain ability to resist noise and frequency selective fading, which is more suitable for modulation and demodulation of voice signal in mine through-the-earth communication.

Background: Skin moisture management is important for maintaining healthy skin and treating inflammatory skin diseases, and skin barrier function can be assessed by measuring trans-epidermal water loss (TEWL) and skin moisture content. Aim: This study was designed to investigate the effects of a topical cream containing 17% herbal extract (Cream17) on skin barrier function. Materials and Methods: In this study, the ability of investigational product (IP) to improve skin barrier function was investigated in 33 subjects using a randomized and assessor-blinded four-week clinical trial. In our study, the effects of IP on TEWL, skin water content, and the degree of itching were investigated. Results: After four weeks of application, TEWL was significantly reduced by IP (p < 0.001), and skin water content was significantly increased (p < 0.001) compared to non-treated control. In addition, topical application of IP significantly lowered the visual analog scale at the second and fourth weeks after treatment commencement as compared with those in the untreated control group (visit 3 at the second week, p < 0.05; visit 4 at the fourth week, p < 0.001). Conclusion: These results indicate that Cream17 can improve the skin barrier function, which is important for managing dry skin conditions such as atopic dermatitis. [ABSTRACT FROM AUTHOR]

Population aging has increased the global prevalence of aging‐related diseases, including cancer, sarcopenia, neurological disease, arthritis, and heart disease. Understanding aging, a fundamental biological process, has led to breakthroughs in several fields. Cellular senescence, evinced by flattened cell bodies, vacuole formation, and cytoplasmic granules, ubiquitously plays crucial roles in tissue remodeling, embryogenesis, and wound repair as well as in cancer therapy and aging. The lack of universal biomarkers for detecting and quantifying senescent cells, in vitro and in vivo, constitutes a major limitation. The applications and limitations of major senescence biomarkers, including senescence‐associated β‐galactosidase staining, telomere shortening, cell‐cycle arrest, DNA methylation, and senescence‐associated secreted phenotypes are discussed. Furthermore, explore senotherapeutic approaches for aging‐associated diseases and cancer. In addition to the conventional biomarkers, this review highlighted the in vitro, in vivo, and disease models used for aging studies. Further, technologies from the current decade including multi‐omics and computational methods used in the fields of senescence and aging are also discussed in this review. Understanding aging‐associated biological processes by using cellular senescence biomarkers can enable therapeutic innovation and interventions to improve the quality of life of older adults. [ABSTRACT FROM AUTHOR]

Cachexia is associated with various diseases, such as heart disease, infectious disease, and cancer. In particular, cancer‐associated cachexia (CAC) accounts for more than 20% of mortality in cancer patients worldwide. Adipose tissue in CAC is characterized by adipocyte atrophy, mainly due to excessively increased lipolysis and impairment of adipogenesis. CAC is well known for the loss of skeletal muscle mass and/or fat mass. CAC induces severe metabolic alterations, including protein, lipid, and carbohydrate metabolism. The objectives of this study were to evaluate the effects of bee wax (Apis mellifera L. 1758) (BW) extract on adipogenesis, lipolysis, and mitochondrial oxygen consumption through white adipocytes, 3T3‐L1. To achieve this study, cancer‐associated cachexia condition was established by incubation of 3T3‐L1 with colon cancer cell line CT26 cultured media. BW extract recovered the reduced adipogenesis under cachectic conditions in CT26 media. Treatment of BW showed increasing lipid accumulation as well as adipogenic gene expression and its target gene during adipogenesis. The administration of BW to adipocytes could decrease lipolysis. Also, BW could significantly downregulated the mitochondrial fatty acid oxidation‐related genes, oxygen consumption rate, and extracellular acidification rate. Our results suggest that BW could improve metabolic disorders such as CAC through the activation of adipogenesis and inhibition of lipolysis in adipocytes, although we need further validation in vivo CAC model to check the effects of BW extract. Therefore, BW extract supplements could be useful as an alternative medicine to reverse energy imbalances. [ABSTRACT FROM AUTHOR]

Cachexia is a devastating fat tissue and muscle wasting syndrome associated with every major chronic illness, including cancer, chronic obstructive pulmonary disease, kidney disease, AIDS, and heart failure. Despite two decades of intense research, cachexia remains under-recognized by oncologists. While numerous drug candidates have been proposed for cachexia treatment, none have achieved clinical success. Only a few drugs are approved by the FDA for cachexia therapy, but a very low success rate is observed among patients. Currently, the identification of drugs from herbal medicines is a frontier research area for many diseases. In this milieu, network pharmacology, transcriptomics, cheminformatics, and molecular docking approaches were used to identify potential bioactive compounds from herbal medicines for the treatment of cancer-related cachexia. The network pharmacology approach is used to select the 32 unique genes from 238 genes involved in cachexia-related pathways, which are targeted by 34 phytocompounds identified from 12 different herbal medicines used for the treatment of muscle wasting in many countries. Gene expression profiling and functional enrichment analysis are applied to decipher the role of unique genes in cancer-associated cachexia pathways. In addition, the pharmacological properties and molecular interactions of the phytocompounds were analyzed to find the target compounds for cachexia therapy. Altogether, combined omics and network pharmacology approaches were used in the current study to untangle the complex prognostic genes involved in cachexia and phytocompounds with anti-cachectic efficacy. However, further functional and experimental validations are required to confirm the efficacy of these phytocompounds as commercial drug candidates for cancer-associated cachexia. [ABSTRACT FROM AUTHOR]

Spirodela polyrhiza (L.) SCHLEID. has been used to treat epidemic fever, dysuria, and various skin ailments, such as measles eruptions, eczema, and pruritus, in China, Japan, and Korea. In this study, the active compounds in S. polyrhiza and their target genes were identified by network-based analysis. Moreover, the study evaluated the effects of a 70% ethanolic extract of S. polyrhiza (EESP) on skin lesions, histopathological changes, inflammatory cytokines, and chemokines in mice with contact dermatitis (CD) induced by 1-fluoro-2,4-dinitrobenzene (DNFB), and examined the inhibitory effects of EESP on mitogen-activated protein kinase (MAPK) signalling pathways. In our results, 14 active compounds and 29 CD-related target genes were identified. Among them, tumour necrosis factor (TNF) and interleukin 6 (IL-6) were identified as hub genes, and luteolin and apigenin showed a strong binding affinity with TNF (<−8 kcal/mol) and IL-6 (<−6 kcal/mol). Our in vivo studies showed that topical EESP ameliorated DNFB-induced skin lesions and histopathological abnormalities, and reduced the levels of TNF-α, interferon (IFN)-ɣ, IL-6, and monocyte chemotactic protein (MCP)-1 in inflamed tissues. In conclusion, our findings suggest the potential for dermatological applications of S. polyrhiza and suggest that its anti-dermatitis action is related to the inhibition of TNF and IL-6 by luteolin and luteolin glycosides. [ABSTRACT FROM AUTHOR]

ObjectiveTo analyze the cost changes of cervical cancer inpatients after the implementationof diagnosis related group (DRG) payment in public grade-A tertiary hospitals, and to provide reference for public hospitals to improve management strategies and optimize the utilization of medical insurance funds.MethodsCase data of cervical cancer patients discharged from a public grade-A tertiary hospital in Shandong Province from April to December 2021 (before the implementation of DRG) and from April to December 2022 (after the implementation of DRG) were retrospectively collected. Patients with medical insurance were treated as the policy group and patients with full self-payment were treated as the control group. The changes in the relevant indicators such as total hospitalization costs, drug costs and consumable costs of cervical cancer patients before and after the implementation of the DRG policy were analyzed using the double difference-in-difference (DID) method.ResultsA total of 10 383 hospitalized patients with cervical cancer were enrolled in this study, including 9711 cases in the policy group (including 5418 cases before the implementation of DRG and 4293 cases after the implementation of DRG) and 672 cases in the control group (including 426 cases before the implementation of DRG and 246 cases after the implementation of DRG). Compared with the pre-DRG policy implementation, there were no significant changes in the complication rate, mortality rate, unplanned rehospitalization rate within 30 days, and length of hospital stay between the patients in the policy group and the control group after the DRG policy implementation. However, the total cost of the policy group decreased from ￥11 453.49 to ￥8780.94 (a decrease of 23.33%), in which the cost of medicines decreased by ￥617.37 (a decrease of 25.17%), and the cost of consumables decreased by ￥28.93(a decrease of 28.49%). The results of the double DID mode showed that the total cost of hospitalization in the policy group decreased by 14.40%(R2=0.616, P < 0.05), the cost of medicines decreased by 13.80%(R2=0.364, P < 0.01), and the cost of consumables decreased by 15.40%(R2=0.565, P < 0.01) compared to the control group after the implementation of the DRG policy.ConclusionsThe implementation of DRG policy can reasonably reduce the cost of disease groups and achieve more effective utilization of medical resources on the basis of ensuring accurate clinical diagnosis and high treatment standards.

ObjectiveTo evaluate the impact of diagnosis-related group(DRG) payment reform on medical resource utilization and healthcare quality among hospitalized lung cancer patients, so as to provide critical insights into China's healthcare payment reform and enhance medical efficiency and quality.MethodsA retrospective analysis was conducted using medical records from a tertiary oncology hospital in Shandong province, with a focus on patients diagnosed with malignant lung tumors between January 28, 2021 and April 16, 2024. A self-paired design was implemented, with October 26, 2021 serving as the intervention point. Data from the same patients were collected for two periods: pre-DRG payment (January 28, 2021-October 25, 2021) and post-DRG payment (October 26, 2021-April 16, 2024). An interrupted time series(ITS) regression model was employed to compare the changes in medical resource utilization indicators (e.g., length of stay, total hospital expenses, reimbursement expenses, out-of-pocket expenses, number of chemotherapy/radiotherapy sessions, number of targeted/immunotherapy sessions, and number of nursing examinations) and healthcare quality indicators, including the incidence of major complications or comorbidities (MCC), complications or comorbidities (CC), and 30-day readmission rates.ResultsA total of 944 patients were included in the analysis, with 49.4% male and 50.6% female; 67.1% were under 65 years of age, while 32.9% were 65 years or older. After the DRG payment, there was a significant reduction in length of stay (β2=-3.235, P < 0.001), total hospital expenses (β2=-5155.900, P < 0.001), reimbursement expenses (β2=-2120.350, P=0.020), and out-of-pocket expenses (β2=-3035.555, P < 0.001). However, the number of chemotherapy/radiotherapy sessions, targeted/immunotherapy sessions, and nursing examinations did not exhibit significant changes. The incidence of MCC/CC significantly increased (β2=3.011, P < 0.001), whereas the 30-day readmission rate remained unchanged.ConclusionsThe DRG payment reform effectively reduces medical costs and shortens hospitalization duration, thereby enhancing hospital management efficiency. However, it may also lead to an increased incidence of complications, which could potentially affect healthcare quality. Therefore, the possible implications of DRG reform on healthcare quality should be carefully monitored and addressed.

With the continuous development of network technology, the scale of data has shown explosive growth, which leads gradually to replacing traditional single machine databases with distributed databases. Distributed databases solve large-scale data storage problems through collaborative work among nodes, but due to increased communication costs between nodes, its query efficiency is not as good as a standalone database. In a distributed architecture, the data of storage nodes is only used as redundancy for multiple backups, providing data recovery in case of system failure, and it is not utilized to improve query efficiency. In response to the above issues, this article proposes an operator parallel optimization strategy for distributed databases. By splitting key physical operators, the split sub requests are evenly distributed to multiple nodes in the storage layer, which are processed in parallel by multiple nodes, thereby reducing query response time. The above strategy has been applied on distributed database CBase, and experiments have shown that the parallel optimization strategy proposed in this paper can significantly shorten SQL request query time and improve system resource utilization.

The AES is one of the most widely used block ciphers in the world, the 3D block cipher is a 3-dimensional AES-like cipher proposed at CANS 2008, and the TANGRAM block cipher is an awardwinning algorithm of the recent National Cryptographic Algorithm Design Competition in China. The yoyo tricks is a powerful cryptanalysis technique based on zero difference, and its main idea is based on whether a plaintext pair and a pair generated by this plaintext pair share the same property after several rounds of encryption. This paper uses yoyo tricks to make an attack on 6-round AES with restricted ciphertexts, reducing the best previously published time complexity by 25:6 in the context of yoyo tricks. Second, the yoyo tricks are extended to n-tuple (n ≥ 3) and relations between the yoyo tricks and related differentials are established, more specifically, the related differentials can be represented by yoyo tricks, and 3-tuple yoyo tricks are used to launch a key recovery attack on 11-round 3D. Finally, the early abort technique is used to the exchange attack, where 2126 chosen plaintexts are used to make a distinguishing attack on 25-round TANGRAM with a 128-bit block size (denoted as TANGRAM-128), which is the first 25-round distinguisher for TANGRAM-128. [ABSTRACT FROM AUTHOR]

Objective To evaluate the Health Education Accurately Linking System (HEALS) combined with case-based leaning (CBL)I n nursing teaching ward round in the encephalopathy clinic. Methods Totally 19 registered nurses were recruited. The routing management had been adopted in nursing teaching ward round between January and December. 2021. A modified model based on the HEALS combined with CBL was adopted in the in nursing teaching ward round between January and December. 2021. Practical skills of nurses and their evaluation on nursing teaching ward round were measured. Results Nurses had achieved a higher score of practical skills assessment after implementation of HEALS combined with CBL model (P＜0. 05). The evaluation of enhancing interest, problem solving skills and independent learning in nursing ward rounds based on HEALS combined with CBL was superior to that in routine nursing ward rounts (P＜0. 05). Conclusion The HEALS combined with CBL model has obvious advantages in nursing teaching ward rounds, which can better meet the needs of clinical nursing teaching, effectively cultivate clinical practice and thinking ability, and is conducive to teaching management. (目的 分析健康教育精准连接系统(HEALS)助手联合基于案例学习(CBL)模式在脑病科护理教学查房中的应用效果。方法 选择脑病科19名注册护士作为研究对象。2021年1月—12月实施常规护理查房; 2022年1月—12月护理查房中采用HEALS助手联合CBL模式。比较实施前和实施后护士技能操作成绩, 对比两种模式下护士对护理教学查房效果的评价。结果 实施HEALS助手联合CBL模式后, 护士各项技能操作成绩高于实施前, 差异有统计学意义(P＜0. 05)。在提升兴趣、问题解决能力、自主学习能力方面, 护士对HEALS助手联合CBL模式下护理教学查房的评价优于常规护理查房, 差异有统计学意义(P＜0. 05)。结论 在脑病科护理教学查房中, 应用基于HEALS助手联合CBL模式优势明显, 能更好地满足临床护理教学需求, 有效培养护士临床实践和思维能力, 利于教学管理。)

Vibrio parahaemolyticus （VP） is one of the most common pathogens that cause food poisoning in coastal areas of China. In fact， the food safety incidents of VP have been increasing on a yearly basis. The current national standard method for quantitatively detecting VP in food is the most probable number method. This method is time-consuming and tedious， and cannot be used to achieve rapid quantitative detection. Owing to modern biotechnology， new quantitative methods have been generated. In fact， a series of rapid and sensitive methods have been developed to quantify VP. This review seeks to discuss recent research and application progress of rapid methods for quantifying VP using biotechnology methods， and highlight the characteristics of each rapid method to provide a theoretical reference and development direction for the rapid and accurate quantitation of VP in food.

To mitigate the impact of oscillations on new energy power systems， it is crucial to assess the system stability state online and identify weak points susceptible to oscillations for proactive measures. To achieve this， two methods for locating weak points in new energy power systems are proposed， each from the perspectives of frequency domain characteristics and time-domain responses of the ports. The frequency domain method involves evaluating the system’s stability state based on the impedance characteristics of the ports at new energy substations， pinpointing weak substations according to the magnitude of the real part of the impedance at each substation. The time-domain method involves actively injecting a wideband small disturbance signal and utilizing the HHT （Hilbert-Huang transform） to analyze the current response at each port of new energy substations. Damping ratios of weak modes are extracted， and weak substations are located based on their magnitudes. The effectiveness of these location methods is validated using a small-scale new energy system composed of three wind farms. The results indicate that both methods accurately identify weak points in the system oscillations.

In the learning process of the metric-based meta-learning, there are some problems, such as the lack of prior knowledge acquired due to the distribution of scarce data, the interference of weakly related or unrelated features extracted from a single-view sample, and the deviations of representative features caused by classification. To solve these problems, a prototype rectification few-shot classification model with dual-path cooperation is proposed in this paper. Firstly, the dual-path cooperation module adaptively highlights key features and weakens weakly related features from a multi-view perspective, and makes full use of feature information to obtain prior knowledge to improve the expression ability of features. Secondly, the problem of intra-class prototype with deviations is solved by the prototype rectification classification strategy with the sample feature information of the query set. Finally, the model parameters are updated reversely by means of the loss function, and the classification accuracy of the model is improved. Comparative experiments of 5-way 1-shot and 5-way 5-shot are conducted on five public datasets. Compared with baseline model, on the miniImageNet dataset, the accuracy is increased by 5.57 percentage points and 3.90 percentage points. On the tieredImageNet dataset, the accuracy is increased by 5.68 percentage points and 3.93 percentage points. On the CUB dataset, the accuracy is increased by 6.93 percentage points and 3.13 percentage points. On the CIFAR-FS dataset, the accuracy is increased by 8.03 percentage points and 1.65 percentage points. On the FC-100 dataset, the accuracy is increased by 4.25 percentage points and 4.89 percentage points. Experimental results show that the proposed model has good performance in the field of few-shot learning, and the modules in the model can be migrated to other models.