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Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) pose significant burdens on individuals and society, necessitating accurate prediction methods. Machine learning (ML) algorithms utilizing electronic health records and survey data offer promising tools for forecasting these conditions. However, potential bias and inaccuracies inherent in subjective survey responses can undermine the precision of such predictions. This research investigates the reliability of five prominent ML algorithms—a Convolutional Neural Network (CNN), Random Forest, XGBoost, Logistic Regression, and Naive Bayes—in predicting MDD and GAD. A dataset rich in biomedical, demographic, and self-reported survey information is used to assess the algorithms’ performance under different levels of subjective response inaccuracies. These inaccuracies simulate scenarios with potential memory recall bias and subjective interpretations. While all algorithms demonstrate commendable accuracy with high-quality survey data, their performance diverges significantly when encountering erroneous or biased responses. Notably, the CNN exhibits superior resilience in this context, maintaining performance and even achieving enhanced accuracy, Cohen’s kappa score, and positive precision for both MDD and GAD. This highlights the CNN’s superior ability to handle data unreliability, making it a potentially advantageous choice for predicting mental health conditions based on self-reported data. These findings underscore the critical importance of algorithmic resilience in mental health prediction, particularly when relying on subjective data. They emphasize the need for careful algorithm selection in such contexts, with the CNN emerging as a promising candidate due to its robustness and improved performance under data uncertainties.

BackgroundClinical decision support systems (CDSSs) are important for the quality and safety of health care delivery. Although CDSS rules guide CDSS behavior, they are not routinely shared and reused. ObjectiveOntologies have the potential to promote the reuse of CDSS rules. Therefore, we systematically screened the literature to elaborate on the current status of ontologies applied in CDSS rules, such as rule management, which uses captured CDSS rule usage data and user feedback data to tailor CDSS services to be more accurate, and maintenance, which updates CDSS rules. Through this systematic literature review, we aim to identify the frontiers of ontologies used in CDSS rules. MethodsThe literature search was focused on the intersection of ontologies; clinical decision support; and rules in PubMed, the Association for Computing Machinery (ACM) Digital Library, and the Nursing & Allied Health Database. Grounded theory and PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines were followed. One author initiated the screening and literature review, while 2 authors validated the processes and results independently. The inclusion and exclusion criteria were developed and refined iteratively. ResultsCDSSs were primarily used to manage chronic conditions, alerts for medication prescriptions, reminders for immunizations and preventive services, diagnoses, and treatment recommendations among 81 included publications. The CDSS rules were presented in Semantic Web Rule Language, Jess, or Jena formats. Despite the fact that ontologies have been used to provide medical knowledge, CDSS rules, and terminologies, they have not been used in CDSS rule management or to facilitate the reuse of CDSS rules. ConclusionsOntologies have been used to organize and represent medical knowledge, controlled vocabularies, and the content of CDSS rules. So far, there has been little reuse of CDSS rules. More work is needed to improve the reusability and interoperability of CDSS rules. This review identified and described the ontologies that, despite their limitations, enable Semantic Web technologies and their applications in CDSS rules.

Bacillus anthracis has gained international attention as a deadly bacterium and a potentially deadly biological warfare agent. Dipicolinic acid (DPA) is the main component of the protective layer of anthracis spores, and is also an anthrax biomarker. Therefore, it is of great significance to explore an efficient and sensitive DPA detection method. Herein, a novel ratio hybrid probe (CQDs-PIL-Eu3+) was prepared by a simple one-step hydrothermal method using carbon quantum dots (CQDs) as an internal reference fluorescence and a covalent bond between CQDs and Eu3+ by using a polyionic liquid (PIL) as a bridge molecule. The ratiometric fluorescence probe was found to have the characteristics of sensitive fluorescence visual sensing in detecting DPA. The structure and the sensing properties of CQDs-PIL-Eu3+ were investigated in detail. In particular, the fluorescence intensity ratio of Eu3+ to CQDs (I616/I440) was linear with the concentration of DPA in the range of 0–50 μM, so the detection limit of the probe was as low as 32 nm, which was far lower than the DPA dose released by the number of anthrax spores in human body (60 μM) and, thus, can achieve sensitive detection. Therefore, the ratiometric fluorescence probe in this work has the characteristics of strong anti-interference, visual sensing, and high sensitivity, which provides a very promising scheme for the realization of anthrax biomarker DPA detection.

doi：10.3969/j.issn.1672⁃6731.2021.10.013

Abstract Background In real-world pragmatic administrative databases, patient reported remission is often missing. Objective We evaluate if, in administrative data, five features of antidepressant use patterns can replace patient-reported symptom remission. Method We re-examined data from Sequence Treatment Alternatives to Relieve Depression (STAR*D) study. Remission was measured using 50% reduction in Hamilton index. Pattern of antidepressant use was examined through five variables: (a) number of prior ineffective antidepressants, (b) duration of taking current antidepressant, (c) receiving therapeutic dose of the medication, and (d) switching to another medication, or (e) augmenting with another antidepressant. The likelihood ratio (LR) associated with each of these predictors was assessed in 90% of data (3329 cases) and evaluated in 10% of data (350 cases) set-aside for evaluation. The accuracy of predictions was calculated using Area under the Receiver Operating Curve (AROC). Results Patients who took antidepressants for 14 weeks (LR = 2.007) were more likely to have symptom remission. Prior use of 3 antidepressants reduced the odds of remission (LR = 0.771). Patients who received antidepressants below therapeutic dose were 5 times less likely to experience remission (LR = 0.204). Antidepressant that were augment or switched, almost never led to remission (LR = 0.008, LR = 0.002 respectively). Patterns of antidepressant use accurately (AROC = 0.93) predicted symptom remission. Conclusion Within the first 100 days, antidepressants use patterns could serve as a surrogate measure for patient-reported remission of symptoms.

Abstract Background Summarization networks are compact summaries of ontologies. The “Big Picture” view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have outgoing lateral relationships, we have developed the "partial-area taxonomy" summarization network. Prior research has identified one kind of outlier concepts, concepts of small partials-areas within partial-area taxonomies. Previously we have shown that the small partial-area technique works successfully for four ontologies (or their hierarchies). Methods To improve the Quality Assurance (QA) scalability, a family-based QA framework, where one QA technique is potentially applicable to a whole family of ontologies with similar structural features, was developed. The 373 ontologies hosted at the NCBO BioPortal in 2015 were classified into a collection of families based on structural features. A meta-ontology represents this family collection, including one family of ontologies having outgoing lateral relationships. The process of updating the current meta-ontology is described. To conclude that one QA technique is applicable for at least half of the members for a family F, this technique should be demonstrated as successful for six out of six ontologies in F. We describe a hypothesis setting the condition required for a technique to be successful for a given ontology. The process of a study to demonstrate such success is described. This paper intends to prove the scalability of the small partial-area technique. Results We first updated the meta-ontology classifying 566 BioPortal ontologies. There were 371 ontologies in the family with outgoing lateral relationships. We demonstrated the success of the small partial-area technique for two ontology hierarchies which belong to this family, SNOMED CT’s Specimen hierarchy and NCIt’s Gene hierarchy. Together with the four previous ontologies from the same family, we fulfilled the “six out of six” condition required to show the scalability for the whole family. Conclusions We have shown that the small partial-area technique can be potentially successful for the family of ontologies with outgoing lateral relationships in BioPortal, thus improve the scalability of this QA technique.

Abstract Background Ontologies house various kinds of domain knowledge in formal structures, primarily in the form of concepts and the associative relationships between them. Ontologies have become integral components of many health information processing environments. Hence, quality assurance of the conceptual content of any ontology is critical. Relationships are foundational to the definition of concepts. Missing relationship errors (i.e., unintended omissions of important definitional relationships) can have a deleterious effect on the quality of an ontology. An abstraction network is a structure that overlays an ontology and provides an alternate, summarization view of its contents. One kind of abstraction network is called an area taxonomy, and a variation of it is called a subtaxonomy. A methodology based on these taxonomies for more readily finding missing relationship errors is explored. Methods The area taxonomy and the subtaxonomy are deployed to help reveal concepts that have a high likelihood of exhibiting missing relationship errors. A specific top-level grouping unit found within the area taxonomy and subtaxonomy, when deemed to be anomalous, is used as an indicator that missing relationship errors are likely to be found among certain concepts. Two hypotheses pertaining to the effectiveness of our Quality Assurance approach are studied. Results Our Quality Assurance methodology was applied to the Biological Process hierarchy of the National Cancer Institute thesaurus (NCIt) and SNOMED CT’s Eye/vision finding subhierarchy within its Clinical finding hierarchy. Many missing relationship errors were discovered and confirmed in our analysis. For both test-bed hierarchies, our Quality Assurance methodology yielded a statistically significantly higher number of concepts with missing relationship errors in comparison to a control sample of concepts. Two hypotheses are confirmed by these findings. Conclusions Quality assurance is a critical part of an ontology’s lifecycle, and automated or semi-automated tools for supporting this process are invaluable. We introduced a Quality Assurance methodology targeted at missing relationship errors. Its successful application to the NCIt’s Biological Process hierarchy and SNOMED CT’s Eye/vision finding subhierarchy indicates that it can be a useful addition to the arsenal of tools available to ontology maintenance personnel.

Purpose: Although research evidence indicates positive associations between stressful life events and postpartum depression, limited research assessed these associations in women with disabilities. This study examined the effects of stressful life events on postpartum depressive symptoms in women with disabilities. Methods: Data from the 2012–2017 Massachusetts Pregnancy Risk Assessment Monitoring System ( n = 8453) were used in this study. Women were asked if they experienced any life stressors (e.g. financial, traumatic, relational, and emotional) during the 12 months prior to giving birth. Disability was measured based on reports of emotional and physical functioning. Descriptive statistics, bivariate, and binary logistic regression analyses were conducted to estimate the effect of stressful life events on postpartum depressive symptoms among women with and without disabilities. Results: Findings show that 37.4% of women with disabilities had postpartum depressive symptoms, which was significantly higher than 8.79% of women without disabilities. Stressful life events were reported in 86.6% of women with disabilities, compared to 66.6% for women without disabilities. Prevalence of three or more stressful life events and postpartum depressive symptoms was greater among women with disabilities (50.8% and 62.9%, respectively) than women without disabilities (22.6% and 37.0%, respectively). Women with disabilities experiencing six or more stressful life events were more likely (odds ratio = 3.78, 95% confidence interval = [1.57–9.10]) to report postpartum depressive symptoms, compared to those with no stressful life events. Women with disabilities who experienced relational (odds ratio = 2.36, 95% confidence interval = [1.44–3.87]) and traumatic (odds ratio = 1.75, 95% confidence interval = [1.02–3.00]) life stressors had higher odds for postpartum depressive symptoms relative to those reporting no such life stressors. Conclusion: Women with disabilities are at an amplified risk for stressful life events and postpartum depressive symptoms. Relational and traumatic stressful life events particularly increase the odds for postpartum depressive symptoms among this group of mothers. Early prenatal and postnatal screening for life stressors and depressive symptoms, coupled with timely referral for appropriate prenatal and postnatal care, are vital to mitigate the harmful effects of depression among mothers with disabilities and the health of their children.

The existing adaptive growth technique deducted the optimization iteration formula according to the condition named Karush-Kuhn-Tucker condition. It is high efficiency and good, which is aimed to strain energy and bound to the volume against optimization problem of stiffener distribution for plate and shell structures. However, different optimization iteration formula, which deducted by different kinds of problem, is poor and difficult to generalize, especially for the optimization problems with more than one constraint. Against with the lack of adaptive growth technique, a new method that is moving asymptotes（MMA） is suggested by this article and the adaptive growth technique is applied to truss structure topology optimization design. The design of typical truss structures with single constraint and multiple constraints is discussed, and the multi load cases are studied. The results of numerical examples show that the proposed method can obtain clear information of rod distribution and dimension, and has high design efficiency and good applicability. It is convenient for practical machining and has a good application prospect.

This work investigated the effect of controlled malolactic fermentation starters (Lactobacillus plantarum NoVA and Oenococcus oeni Oenos) and an un-inoculated culture on cherry wine’s physical, biochemical and sensory properties. NoVA promoted MLF most efficiently (15d), resulted in a large increase in the concentration of many esters and aromatic alcohols, and reinforced the cherry wine’s ‘fruity’ note and overall aroma. MLF carried out by Oenos lasted for 18 days, accompanied by the increase of many volatile compounds (with 2-phenylethyl acetate and benzaldehyde as major representatives) and several biogenic amines. With respect to spontaneous MLF, Tatumella, Pantoea, Lactococcus, and Lactobacillus were identified as the dominant genera, with a fermentation period of 25 d and the total biogenic amine amount 1.6-fold than that at the end of alcoholic fermentation. This study has proved that the use of Viniflora NoVA to conduct MLF is a worthwhile alternative to the traditional cherry wine-making.

For patients with rare comorbidities, there are insufficient observations to accurately estimate the effectiveness of treatment. At the same time, all diagnosis, including rare diagnosis, are part of the International Classification of Disease (ICD). Grouping ICD into broader concepts (i.e., ontology adjustment) can not only increase accuracy of estimating antidepressant effectiveness for patients with rare conditions but also prevent overfitting in big data analysis. In this study, 3,678,082 depressed patients treated with antidepressants were obtained from OptumLabs® Data Warehouse (OLDW). For rare diagnoses, adjustments were made by using the likelihood ratio of the immediate broader concept in the ICD hierarchies. The accuracy of models in training (90%) and test (10%) sets was examined using the area under the receiver operating curves (AROC). The gap in training and test AROC shows how much random noise was modeled. If the gap is large, then the parameters of the model, including the reported effectiveness of the antidepressant for patients with rare conditions, are suspect. There was, on average, a 9.0% reduction in the AROC gap after using the ontological adjustment. Therefore, ontology adjustment can reduce model overfitting, leading to better parameter estimates from the training set.

Abstract Background Bio-ontologies are becoming increasingly important in knowledge representation and in the machine learning (ML) fields. This paper presents a ML approach that incorporates bio-ontologies and its application to the SEER-MHOS dataset to discover patterns of patient characteristics that impact the ability to perform activities of daily living (ADLs). Bio-ontologies are used to provide computable knowledge for ML methods to “understand” biomedical data. Results This retrospective study included 723 cancer patients from the SEER-MHOS dataset. Two ML methods were applied to create predictive models for ADL disabilities for the first year after a patient’s cancer diagnosis. The first method is a standard rule learning algorithm; the second is that same algorithm additionally equipped with methods for reasoning with ontologies. The models showed that a patient’s race, ethnicity, smoking preference, treatment plan and tumor characteristics including histology, staging, cancer site, and morphology were predictors for ADL performance levels one year after cancer diagnosis. The ontology-guided ML method was more accurate at predicting ADL performance levels (P

In order to obtain optimum packaging materials for peanut kernels, the effects of four types of packaging materials on peanut storage quality (coat color, acid value, germination rate, relative damage, and prevention of aflatoxin contamination) were examined. The results showed that packaging materials had a major influence on peanut storage quality indexes. The color of the peanut seed coat packaged in the polyester/aluminum/polyamide/polyethylene (PET/AL/PA/PE) composite film bag did not change significantly during the storage period. Color deterioration was slower with polyamide/polyethylene (PA/PE) packaging materials than with polyethylene (PE) film bags and was slower in PE bags than in the woven bags. The use of PET/AL/PA/PE and PA/PE bags maintained peanut quality and freshness for more than one year and both package types resulted in better germination rates. There were significant differences between the four types of packaging materials in terms of controlling insect pests. The peanuts packaged in the highly permeable woven bags suffered serious invasion from insect pests, while both PET/AL/PA/PE and PA/PE bags effectively prevented insect infection. Peanuts stored in PET/AL/PA/PE and PA/PE bags were also better at preventing and controlling aflatoxin contamination.

Bovine leukemia virus (BLV), a deltaretrovirus, causes B-cell leukemia/lymphoma in cattle and is prevalent in herds globally. A previous finding of antibodies against BLV in humans led us to examine the possibility of human infection with BLV. We focused on breast tissue because, in cattle, BLV DNA and protein have been found to be more abundant in mammary epithelium than in lymphocytes. In human breast tissue specimens, we identified BLV DNA by using nested liquid-phase PCR and DNA sequencing. Variations from the bovine reference sequence were infrequent and limited to base substitutions. In situ PCR and immunohistochemical testing localized BLV to the secretory epithelium of the breast. Our finding of BLV in human tissues indicates a risk for the acquisition and proliferation of this virus in humans. Further research is needed to determine whether BLV may play a direct role in human disease.

Liquefaction of cornstalk in sub-critical solution of ethanol without and with catalysts (K2CO3, Na2CO3 and ZnCl2) was performed in a stainless steel reactor (1 L) at temperatures of 200 to 300 oC. The cornstalk and the products of decomposition were divided into five lumps (gas, organic dissolved, heavy oil, volatile organic compounds, and residue). The effects of reaction temperature and the catalyst amount on the five lump yields were studied. The bio-oils produced with and without catalysts were characterized by GC/MS. Results showed that an increment in the temperature and the addition of catalysts had a synergetic effect on the lumps yield as compared to the non-catalytic experiments, and different catalytic procedures had an important effect on the lump yields and compounds of the bio-oils. The addition of the catalyst enhanced the gas yield and the total conversion rate. A high temperature, lower amount of Na2CO3, moderate amount of K2CO3, and a high amount of ZnCl2 were propitious to enhance the heavy oil. The formation of volatile organic compounds with the presence of ZnCl2 and K2CO3 was less than that in non-catalytic experiments at the higher temperatures. However, a higher conversion temperature had a negative impact on the bio-oils yield from liquefaction of cornstalk with and without catalysts.

Gene terminologies are playing an increasingly important role in the ever-growing field of genomic research. While errors in large, complex terminologies are inevitable, gene terminologies are even more susceptible to them due to the rapid growth of genomic knowledge and the nature of its discovery. It is therefore very important to establish quality- assurance protocols for such genomic-knowledge repositories. Different kinds of terminologies oftentimes require auditing methodologies adapted to their particular structures. In light of this, an auditing methodology tailored to the characteristics of the NCI Thesaurus’s (NCIT’s) Gene hierarchy is presented. The Gene hierarchy is of particular interest to the NCIT’s designers due to the primary role of genomics in current cancer research. This multiphase methodology focuses on detecting role-errors, such as missing roles or roles with incorrect or incomplete target structures, occurring within that hierarchy. The methodology is based on two kinds of abstraction networks, called taxonomies, that highlight the role distribution among concepts within the IS-A (subsumption) hierarchy. These abstract views tend to highlight portions of the hierarchy having a higher concentration of errors. The errors found during an application of the methodology

Age, reproductive history, hormones, genetics, and lifestyle are known risk factors for breast cancer, but the agents that initiate cellular changes from normal to malignant are not understood. We previously detected bovine leukemia virus (BLV), a common oncogenic virus of cattle, in the breast epithelium of humans. The objective of this study was to determine whether the presence of BLV DNA in human mammary epithelium is associated with breast cancer.This was a case-control study of archival formalin fixed paraffin embedded breast tissues from 239 donors, received 2002-2008 from the Cooperative Human Tissue Network. Case definition as breast cancer versus normal (women with no history of breast cancer) was established through medical records and examination of tissues by an anatomical pathologist. Breast exposure to BLV was determined by in situ-PCR detection of a biomarker, BLV DNA, localized within mammary epithelium.The frequency of BLV DNA in mammary epithelium from women with breast cancer (59%) was significantly higher than in normal controls (29%) (multiply- adjusted odds ratio = 3.07, confidence interval = 1.66-5.69, p = .0004, attributable risk = 37%). In women with premalignant breast changes the frequency of BLV DNA was intermediate (38%) between that of women with breast cancer and normal controls (p for trend < .001).Among the specimens in this study, the presence of amplified BLV DNA was significantly associated with breast cancer. The odds ratio magnitude was comparable to those of well-established breast cancer risk factors related to reproductive history, hormones, and lifestyle and was exceeded only by risk factors related to genetics (familial breast cancer), high dose ionizing radiation, and age. These findings have the potential for primary and secondary prevention of breast cancer.

Gene terminologies are playing an increasingly important role in the ever-growing field of genomic research. While errors in large, complex terminologies are inevitable, gene terminologies are even more susceptible to them due to the rapid growth of genomic knowledge and the nature of its discovery. It is therefore very important to establish quality-assurance protocols for such genomic-knowledge repositories. Different kinds of terminologies oftentimes require auditing methodologies adapted to their particular structures. In light of this, an auditing methodology tailored to the characteristics of the NCI Thesaurus's (NCIT's) Gene hierarchy is presented. The Gene hierarchy is of particular interest to the NCIT's designers due to the primary role of genomics in current cancer research. This multiphase methodology focuses on detecting role-errors, such as missing roles or roles with incorrect or incomplete target structures, occurring within that hierarchy. The methodology is based on two kinds of abstraction networks, called taxonomies , that highlight the role distribution among concepts within the IS-A (subsumption) hierarchy. These abstract views tend to highlight portions of the hierarchy having a higher concentration of errors. The errors found during an application of the methodology are reported. Hypotheses pertaining to the efficacy of our methodology are investigated.

Collaborative robots, or cobots, have become popular due to their ability to safely operate alongside humans in shared environments. These robots use compliant actuators as a key design element to prevent damage during unintended collisions. In prosthetic and orthotic applications, compliant actuators are crucial for ensuring user safety and comfort. However, most compliant cobots for these applications are excessively expensive and complex to construct. Our study introduces an innovative, cost-effective, and sensorised elastic actuator design tailored for prosthetics and orthotics. The design uses a modular approach and leverages 3D printing technology for rapid customisation, enabling efficient and affordable fabrication. Both hardware and software components are open-source, facilitating unrestricted access for students, researchers, and practitioners. Our design supports impedance and admittance control techniques, enhancing the system’s capabilities. Validation results show a standard deviation of 9.67 Nm between calculated and measured torque in impedance control and 0.2563 radians between calculated and measured angles in admittance control. This allows for improved adaptability to varying operational requirements in prosthetics and orthotics. By introducing this educational framework encompassing a low-cost, sensorised elastic actuator design, we aim to address the need for accessible solutions in the field of collaborative robotics for prosthetics and orthotics.

Recent research has shown that bilinguals outperform monolinguals on tasks requiring non-linguistic executive control skills, thereby generating an interest in the relationship between bilingual language processing and non-linguistic control abilities. Based on this, the present study further examined the bidirectional interaction between language control and non-linguistic control in unbalanced Chinese-English bilinguals. These bilinguals completed a Flanker task in three types of language control contexts (i.e., L1, L2, and Mixed language contexts) in the interleaved word-comprehension-to-Flanker sequence and performed a picture-word matching task in three types of non-linguistic executive control contexts (i.e., color, shape and color-shape mixed contexts) in the interleaved color-shape-switching-to-word-comprehension sequence. The results showed that the Flanker effect in mixed language context was smaller than in single (L1 and L2) context, suggesting language control leads to a better non-linguistic control ability. Additionally, the language switching cost was found smaller in the mixed task context (color/shape switching), indicating that non-linguistic control can enhance the language control ability. Therefore, we conclude that there is a bidirectional interaction between language control and non-linguistic control even in unbalanced bilinguals.

Although extensive research has been conducted on securing the Internet of Things (IoT) communication protocols, various vulnerabilities and exploits are continuously discovered and reported. Since vulnerabilities are introduced from either insecure communication protocols or defectiveness of applications, it is difficult to identify them during the software development or testing phase. In this paper, we present IoTVerif, a system that automatically verifies the Secure Socket Layer/Transport Layer Security (SSL/TLS) certificate for IoT applications that utilize broker-based messaging protocols. IoTVerif constructs the specification of an IoT protocol and verifies its security properties, without relying on prior knowledge about communication protocols. Once the specification is constructed, a general-purpose model checker automatically verifies those properties, as well as generates counter-examples if any property does not hold. We analyze the effectiveness of IoTVerif with real-world IoT-related applications. Our evaluation results show that IoTVerif can successfully identify vulnerabilities from IoT applications, which are exploitable by the man-in-the-middle (MITM) and TLS renegotiation attacks. IoTVerif holds a great promise for reverse-engineering emerging IoT messaging protocols and identifies the vulnerabilities from IoT-related applications.

The practice of carbon emission accurate measurement system application scenario of carbon electricity coupling and carbon real measurement is carried out, based on the carbon constraint background, the whole process of carbon production and emission is accurately pictured, and the carbon measurement real measurement and carbon electricity factor measurement model adapted to multiple industries is constructed in this way. The carbon measurement is carried out by collecting data from power plants in the field and automatically matching various carbon emission parameters with the calculation model to calculate the carbon emissions of the group in real time. Carbon electricity factor measurement for energy data that cannot be directly obtained, build an industry-wide carbon emission measurement and monitoring mechanism driven by electricity ties, and combine with third-party accounting agencies to certify the measurement results to indirectly display carbon emission data by electricity.

Current research on hydraulic punching technology seldom considers that pressure relief range of hydraulic punching in inclined coal seam varies with direction and influence of coal seam inclination on the effective radius of hydraulic punching pressure relief. In view of the above problem,taking the coal seam No.3 of a coal mine as research object, the effective influence radius for inclined coal seam under hydraulic punching was numerically simulated by using multi-physics coupling numerical simulation software COMSOL Multiphysics. The effective extraction radius of borehole in different directions was studied. The numerical simulation results show that under the action of punching, the range of extraction influences continues to increase with the increase of extraction time, but the expansion speed decreases with time. Due to the stress relief under punching, the permeability of coal seam is greatly increased, and the influence range around the borehole is approximately elliptic. After 90 days of continuous extraction, the influence radius is about 6 m in the upper direction, the influence radius is about 4 m in the lower direction and the influence radius is about 5 m in the horizontal direction. In order to reach the gas extraction standard, the horizontal drilling arrangement spacing of the hydraulic drilling tunnel of the coal seam is about 3.5 m, and the longitudinal drilling arrangement spacing is about 4.0 m. The research results have important practical significance for optimizing hydraulic punching process parameters, guiding the accurate layout of extraction boreholes, and enhancing the gas control effect of the mine.

The plots of many literary works are very complex, which hinders the readers' comprehension of these literary works. Thus, to help readers' comprehension of complex literary works, tools should be proposed to support their comprehension by presenting the most important information to readers. In the case of literary works, the most important information may be the most important people, also called the key people. Key people play an important role in promoting the development of the plot of literary works. Thus, identifying key people helps to simplify readers' comprehension of literary works. The traditional way to comprehend literary works mainly depends on intensive reading, and no previous work has been done to explore the problem of key people identification in literary works. In this paper, we define the concept of key people and propose an approach, IPWC, to Identify key People in Chinese literary Works using e -Core decomposition. First, it uses the Weighted People co-occurrence Network (WPN) to represent people and their coupling relationships, and the frequency of the relationship. Second, an e -core decomposition is proposed and applied to decompose the WPN into shells and obtain the coreness of each people. Finally, all the people are sorted in a descending order according to their coreness, and the top-ranked people are the key people identified by our approach. The empirical experiments performed on a famous Chinese literary work, The History of the Three Kingdoms, show that WPN has small world and scale-free features. Furthermore, our approach is feasible and more effective than other compared approaches. Our approach can be used to build an automatic tool that can identify the key people for readers to aid their comprehension of a Chinese literary work.

Collaborative robots (or cobots) are robots that can safely work together or interact with humans in a common space. They gradually become noticeable nowadays. Compliant actuators are very relevant for the design of cobots. This type of actuation scheme mitigates the damage caused by unexpected collision. Therefore, elastic joints are considered to outperform rigid joints when operating in a dynamic environment. However, most of the available elastic robots are relatively costly or difficult to construct. To give researchers a solution that is inexpensive, easily customisable, and fast to fabricate, a newly-designed low-cost, and open-source design of an elastic joint is presented in this work. Based on the newly design elastic joint, a highly-compliant multi-purpose 2-DOF robot arm for safe human-robot interaction is also introduced. The mechanical design of the robot and a position control algorithm are presented. The mechanical prototype is 3D-printed. The control algorithm is a two loops control scheme. In particular, the inner control loop is designed as a model reference adaptive controller (MRAC) to deal with uncertainties in the system parameters, while the outer control loop utilises a fuzzy proportional-integral controller to reduce the effect of external disturbances on the load. The control algorithm is first validated in simulation. Then the effectiveness of the controller is also proven by experiments on the mechanical prototype.

Dependency injection (DI) is generally known to improve maintainability by keeping application classes separate from the library. Particularly within the Java environment, there are many applications using the principles of DI with the aim to improve maintainability. There exists some work that provides an inference on the impact of DI on maintainability, but no conclusive evidence is provided. The fact that there are no publicly available tools for quantifying DI makes such evidence more difficult to be produced. In this paper, we propose two novel metrics, dependency injection-weighted afferent couplings (DCE) and dependency injection-weighted coupling between objects (DCBO), to measure the proportion of DI in a project based on weighted couplings. We describe how DCBO can serve as a more meaningful metric in assessing maintainability when DI is also considered. The metric is implemented in the CKJM-Analyzer, an extension of the CKJM tool to perform static analysis on DI detection. We discuss the algorithmic approach behind the static analysis and prove the soundness of the tool using a set of open-source Java projects.

Software maintenance is indispensable in the software development process. Developers need to spend a lot of time and energy to understand the software when maintaining the software, which increases the difficulty of software maintenance. It is a feasible method to understand the software through the key classes of the software. Identifying the key classes of the software can help developers understand the software more quickly. Existing techniques on key class identification mainly use static analysis techniques to extract software structure information. Such structure information may contain redundant relationships that may not exist when the software runs and ignores the actual interaction times between classes. In this paper, we propose an approach based on dynamic analysis and entropy-based metrics to identify key classes in the Java GUI software system, called KEADA (identifying KEy clAsses based on Dynamic Analysis and entropy-based metrics). First, KEADA extracts software structure information by recording the calling relationship between classes during the software running process; such structure information takes into account the actual interaction of classes. Second, KEADA represents the structure information as a weighted directed network and further calculates the importance of each node using an entropy-based metric OSE (One-order Structural Entropy). Third, KEADA ranks classes in descending order according to their OSE values and selects a small number of classes as the key class candidates. In order to verify the effectiveness of our approach, we conducted experiments on three Java GUI software systems and compared them with seven state-of-the-art approaches. We used the Friedman test to evaluate all approaches, and the results demonstrate that our approach performs best in all software systems.

Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with uncertainties and disturbance on the load side of the robot arm. For the inner loops, model reference adaptive controllers (MRAC) are utilised to handle the uncertainties on the motor side of the robot arm. To show the effectiveness of the proposed controller, extensive simulation experiments and a comparison with the conventional sliding mode controller (SMC) are carried out. As a result, the ASMC has a 50.35% lower average RMS error than the SMC controller, and a shorter settling time (5% criterion) (0.44 s compared to 2.11 s).

Corporate executives have the decision-making power of resource allocation, and efficient resource allocation is an important measure of high-quality development of enterprises. It is a focal issue whether the compensation incentive can promote the executives to make better use of the enterprise resource allocation. We investigate this question using the data of the Chinese listed companies in 2015–2019 based on Data Envelopment Analysis (DEA) and fixed effect model. The results show the following: (1) both monetary compensation incentive and equity incentive can significantly improve the efficiency of resource allocation, and the former is more significant; (2) there is an inverted U-shaped relationship between perquisite consumption incentive and resource allocation efficiency; (3) the above conclusion is still true in state-owned enterprises; (4) in private enterprises, the effect of equity incentive is more effective, but the effect of perquisite consumption incentive is less significant. The results highlight the relationship between compensation incentive and enterprise resource allocation. Our study is expected to guide the executives to formulate reasonable compensation incentives and improve the efficiency of resource allocation.

Aircraft icing detection system is very important to guarantee flight safety. It is also a new problem to assess safety of the aircraft icing detection system. The major function of aircraft icing detection system is analyzed by fault tree analysis method in this paper. The fault tree of icing detection system is built and simplified, and then the minimal cut sets are calculated and discussed here. According to qualitative analysis results, the requirements of icing detection system on aircraft top-level design are suggested. The quantitative analysis results show that the system design can meet the failure rate of icing detection system requirements.

Aiming at the requirement for detecting and processing the information of laser pulse in the optical scanning measurement network such as workspace measuring and positioning system, a system based on programmable logic device that can detect and discriminate the laser pulse information has been proposed. Using the Zynq chip produced by Xilinx, the system designs logic circuit in the FPGA to capture and latch the laser pulse information, and it also has the IP module based on AXI bus protocol to accelerate the communication speed. The simulation shows that this design has little time overhead and can operate in real-time system, therefore increases the efficiency of the measuring system. It can also be used in other optical equipments for the use of navigation orientation system, to increase the positioning accuracy.

Objective The net energy requirement for the maintenance (NEm) of broilers was determined using regression models by the indirect calorimetry method (ICM) or the comparative slaughter method (CSM). Methods A 2×4 factorial arrangement of treatments including the evaluation method (ICM or CSM) and feed intake (25%, 50%, 75%, or 100% of ad libitum recommended) was employed in this experiment. In the ICM, 96 male Arbor Acres (AA) birds aged d 15 were used with 4 birds per replicate and 6 replicates in each treatment. In the CSM, 116 male AA birds aged d 15 were used. Among these 116 birds, 20 were selected as for initial data and 96 were assigned to 4 treatments with 6 replicate cages and 4 birds each. The linear regression between retained energy (RE) and metabolizable energy intake (MEI) or the logarithmic regression between heat production (HP) and MEI were used to calculate the metabolizable or net energy requirement for maintenance (MEm) or NEm, respectively. Results The evaluation method did not detect any differences in the metabolizable energy (ME), net energy (NE), and NE:ME of diet, and in the MEI, HP, and RE of broilers. The MEI, HP, and RE of broilers decreased (p

Software stability means the resistance to the amplification of changes in software. It has become one of the most important attributes that affect maintenance cost. To control the maintenance cost, many approaches have been proposed to measure software stability. However, it is still a very difficult task to evaluate the software stability especially when software becomes very large and complex. In this paper, we propose to characterize software stability via change propagation simulation. First, we propose a class coupling network (CCN) to model software structure at the class level. Then, we analyze the change propagation process in the CCN by using a simulation way, and by doing so, we develop a novel metric, SS (software stability), to measure software stability. Our SS metric is validated theoretically using the widely accepted Weyuker’s properties and empirically using a set of open source Java software systems. The theoretical results show that our SS metric satisfies most of Weyuker’s properties with only two exceptions, and the empirical results show that our metric is an effective indicator for software quality improvement and class importance. Empirical results also show that our approach has the ability to be applied to large software systems.

Data Distribution Service (DDS) has emerged as a potential solution for data communication challenges in smart grids. DDS is designed to support quality communication for large scale real-time systems through a wide range of QoS policies. However, a smart grid involves various types of communication applications running on different computing environments. Some environments have limited computing resources such as small memory and low performance, which makes it difficult to accommodate DDS. In this paper, we present a feature-based approach for tailoring DDS to configure lightweight DDS by selecting only the necessary features for the application in consideration of the resource constraints of its running environment. This allows DDS to serve as a uniform communication middleware across the smart grid, which is critical for interoperability. We analyze DDS in terms of features and design them using Unified Modeling Language (UML) and Object Constraint Language (OCL) based on inheritance and overriding. We define a formal notion of feature composition to build DDS configurations. We implemented the approach in OpenDDS and demonstrate its application to different application environments. We also experimented the approach for the efficiency of configured DDS in terms of resource utilization. The results show that configured DDS is viable for efficient and quality data communication for applications that run on an environment with limited computing capability.

A method has been reported in articles for the simultaneous determination of copper and silver in geological samples or samples of mineral processing and smelting by Atomic Absorption Spectrometry in an aqua regia-thiourea medium. However, interference from copper made the determination of silver in the aqua regia-thiourea medium difficult. In this paper, a method is decribed whereby the sample was dissolved with a four-acid system of HCl-HF-HNO3-HClO4, extracted by aqua regia and chelated by theorem. The continuous determination of silver and copper in silver concentrate was made by Flame Atomic Absorption Spectrometry (FAAS) in an aqua-thiourea medium. The interference of coexisting elements was eliminated by testing different sample digestion methods and different concentrations of the thiourea medium. The results show that the samples were completely dissolved with the four-acid system. By adding excessive amounts of thiourea within the 20 g/L, the white precipitation of Ag was completely transformed into the Ag[SC(NH2)2]3+ ion in order to eliminate interference from copper. This method was applied to the analysis of samples with relative standard deviations (RSD, n=6) for Cu and Ag in the range of 1.20%-2.11% and 0.61%-1.18%. With the standard addition, the recoveries for Cu and Ag were in the range of 96.5%-107.0% and 97.3%-104.7%. The determination results are in agreement with fire assay and iodometry results. The method has the merits of easy, practicality and low cost, which meet the demands for silver concentrate processing.

Abstract Background It’s unclear if excess visceral adipose tissue (VAT) mass in individuals with prediabetes can be countered by adherence to a Mediterranean lifestyle (MEDLIFE). We aimed to examine VAT mass, MEDLIFE adherence, and their impact on type 2 diabetes (T2D) and diabetic microvascular complications (DMC) in individuals with prediabetes. Methods 11,267 individuals with prediabetes from the UK Biobank cohort were included. VAT mass was predicted using a non-linear model, and adherence to the MEDLIFE was evaluated using the 25-item MEDLIFE index, encompassing categories such as “Mediterranean food consumption,” “Mediterranean dietary habits,” and “Physical activity, rest, social habits, and conviviality.” Both VAT and MEDLIFE were categorized into quartiles, resulting in 16 combinations. Incident cases of T2D and related DMC were identified through clinical records. Cox proportional-hazards regression models were employed to examine associations, adjusting for potential confounding factors. Results Over a median follow-up of 13.77 years, we observed 1408 incident cases of T2D and 714 cases of any DMC. High adherence to the MEDLIFE, compared to the lowest quartile, reduced a 16% risk of incident T2D (HR: 0.84, 95% CI: 0.71–0.98) and 31% for incident DMC (0.69, 0.56–0.86). Conversely, compared to the lowest quartile of VAT, the highest quartile increased the risk of T2D (5.95, 4.72–7.49) and incident any DMC (1.79, 1.36–2.35). We observed an inverse dose-response relationship between MEDLIFE and T2D/DMC, and a dose-response relationship between VAT and all outcomes (P for trend

The production and consumption of the greenhouse gases (GHGs) methane (CH4), carbon dioxide (CO2) and nitrous oxide (N2O) in soil profile are poorly understood. This work sought to quantify the GHG production and consumption at seven depths (0-30, 30-60, 60-90, 90-150, 150-200, 200-250 and 250-300 cm) in a long-term field experiment with a winter wheat-summer maize rotation system, and four N application rates (0; 200; 400 and 600 kg N ha(-1) year(-1)) in the North China Plain. The gas samples were taken twice a week and analyzed by gas chromatography. GHG production and consumption in soil layers were inferred using Fick's law. Results showed nitrogen application significantly increased N2O fluxes in soil down to 90 cm but did not affect CH4 and CO2 fluxes. Soil moisture played an important role in soil profile GHG fluxes; both CH4 consumption and CO2 fluxes in and from soil tended to decrease with increasing soil water filled pore space (WFPS). The top 0-60 cm of soil was a sink of atmospheric CH4, and a source of both CO2 and N2O, more than 90% of the annual cumulative GHG fluxes originated at depths shallower than 90 cm; the subsoil (>90 cm) was not a major source or sink of GHG, rather it acted as a 'reservoir'. This study provides quantitative evidence for the production and consumption of CH4, CO2 and N2O in the soil profile.

Obesity has shown a global epidemic trend. The high-lipid state caused by obesity can maintain the heart in a prolonged low-grade inflammatory state and cause ventricular remodeling, leading to a series of pathologies, such as hypertrophy, fibrosis, and apoptosis, which eventually develop into obese cardiomyopathy. Therefore, prolonged low-grade inflammation plays a crucial role in the progression of obese cardiomyopathy, making inflammation regulation an essential strategy for treating this disease. Cyy-272, an indazole derivative, is an anti-inflammatory compound independently synthesized by our laboratory. Our previous studies revealed that Cyy-272 can exert anti-inflammatory effects by inhibiting the phosphorylation and activation of C-Jun N-terminal kinase (JNK), thereby alleviating lipopolysaccharide (LPS)-induced acute lung injury (ALI). The current study aimed to evaluate the potential of Cyy-272 to mitigate the occurrence and progression of obese cardiomyopathy through the inhibition of the JNK signaling pathway. Our results indicate that the compound Cyy-272 has encouraging therapeutic effects on obesity-induced cardiac injury. It significantly inhibits inflammation in cardiomyocytes and heart tissues induced by high lipid concentrations, further alleviating the resulting hypertrophy, fibrosis, and apoptosis. Mechanistically, the protective effect of Cyy-272 on obese cardiomyopathy can be attributed to its direct inhibition of JNK protein phosphorylation. In conclusion, we identified a novel compound, Cyy-272, capable of alleviating obese cardiomyopathy and confirmed that its effect is achieved through direct inhibition of JNK.

Purpose. To assess outcome of 6 juvenile patients with osteochondritis dissecans (OCD) of the ankle treated conservatively. Methods. Records of 4 males and one female aged 10.8 to 14.1 (mean, 12.3) years who underwent cast immobilisation and/or restriction of physical activities for OCD of the talus (4 on the left and 2 on the right) were reviewed. OCD lesions were graded using the Berndt and Harty classification. Functional outcome was assessed using the ankle-hindfoot score of the American Orthopaedic Foot and Ankle Society. Clinical and radiographic outcomes were assessed according to the Higuera classification. Results. The mean follow-up period was 30.5 (range, 11–63) months. The mean ankle-hindfoot score was 90 (range, 86–100). Radiological resolution of OCD was noted in 2 ankles, although all ankles showed some degree of healing. All patients had resolution of pain after a mean of 7 (range, 3–12) months. According to the Higuera classification, clinical outcome was excellent in one and good in 5 ankles, whereas radiological outcome was excellent in 2, good in 2, and fair in 2 ankles. In one patient, the OCD of the right posteromedial talar dome resolved spontaneously. Conclusion. Almost all patients achieved good functional outcome after conservative management, regardless of the presence of radiological evidence of healing. Surgery should only be performed if the OCD is unstable.

Thí nghiệm được bố trí theo thể thức khối hoàn toàn ngẫu nhiên, 3 lần lặp lại, 12 nghiệm thức là 12 giống/dòng lúa: MTL 513, MTL549, MTL495, MTL 645, TPCT8, TPCT10, TPCT11, TPCT12, TPCT13, TPCT14, TPCT15 và giống OM4218 làm đối chứng. Thí nghiệm được thực hiện ở vụ Xuân Hè 2010 tại huyện Châu Thành A, huyện Vị Thủy và Thị xã Ngã Bảy của tỉnh Hậu Giang. Kết quả có 04 giống/dòng lúa thơm được chọn là: MTL 513, MTL 549, MTL495 và MTL 645 có hàm lượng amylose thấp đến trung binh (19,74-24,68%), hàm lượng protein cao (7,83 ? 8,3%), năng suất cao (7,23-7,46 tấn/ha), thời gian sinh trưởng ngắn (dưới 100 ngày), ít bị sâu bệnh hơn giống đối chứng, có hạt gạo thon dài và chất lượng gạo tốt, đạt mục tiêu đề ra.

ứng dụng qui trình kỹ thuật điện di SDS-PAGE protein (Bộ Nông nghiệp Nhật, 1996) để phân tích các giống lúa có nguồn gốc được thu thập từ địa phương và các dòng lai. Sau đó tiến hành thí nghiệm được bố trí theo thể thức khối hoàn toàn ngẫu nhiên, 3 lần lặp lại, 11 nghiệm thức là 11 giống/dòng lúa: TPCT1, TPCT2, TPCT6, Jasmine 01, Jasmine 08, Jasmine 10, VĐ20-03, VĐ20-07, VĐ20-17, VĐ20-17 và giống Jasmine85 làm giống đối chứng, được thực hiện ở vụ Hè-Thu 2008 tại Nông trại thực nghiệm trường Đại học Cần Thơ. Kết quả tất cả các giống/dòng thí nghiệm đều có mùi thơm, thời gian sinh trưởng ngắn (dưới 100 ngày), ít bị sâu bệnh, có năng suất cao hơn giống đối chứng, có hạt gạo thon dài và chất lượng hạt gạo tốt, đạt mục tiêu đề ra..

Thí nghiệm được bố trí theo thể thức khối hoàn toàn ngẫu nhiên, 3 lần lặp lại, 15 nghiệm thức là 15 giống/dòng lúa: MTL 513, MTL495, MTL549, MTL 645, TPCT1, TPCT6, TPCT7, TPCT8, TPCT10, TPCT11, TPCT12, TPCT13, TPCT14, TPCT15 và giống Jasmine85 làm đối chứng. Thí nghiệm được thực hiện ở vụ Đông Xuân 2009-2010 tại huyện Châu Thành A, huyện Vị Thủy và Thị xã Ngã Bảy của tỉnh Hậu Giang. Kết quả có 03 giống/dòng lúa thơm, thời gian sinh trưởng ngắn (dưới 100 ngày), ít bị sâu bệnh, có năng suất cao hơn giống đối chứng, có hạt gạo thon dài và chất lượng gạo tốt, đạt mục tiêu đề ra.

ứng dụng qui trình kỹ thuật điện di SDS-PAGE protein (Bộ Nông nghiệp Nhật, 1996) để phân tích các giống lúa có nguồn gốc được thu thập từ địa phương và các dòng lai. Sau đó tiến hành thí nghiệm được bố trí theo thể thức khối hoàn toàn ngẫu nhiên, 3 lần lặp lại, 11 nghiệm thức là 11 giống/dòng lúa: TPCT1, TPCT2, TPCT6, Jasmine 01, Jasmine 08, Jasmine 10, VĐ20-03, VĐ20-07, VĐ20-17, VĐ20-17 và giống Jasmine85 làm giống đối chứng, được thực hiện ở vụ Hè-Thu 2008 tại Nông trại thực nghiệm trường Đại học Cần Thơ. Kết quả tất cả các giống/dòng thí nghiệm đều có mùi thơm, thời gian sinh trưởng ngắn (dưới 100 ngày), ít bị sâu bệnh, có năng suất cao hơn giống đối chứng, có hạt gạo thon dài và chất lượng hạt gạo tốt, đạt mục tiêu đề ra.

With the exponential growth of devices, particularly Internet of things (IoT) devices, connecting to wireless networks, existing networks face significant challenges. Spectral efficiency is crucial for uplink, which is the dominant form of asymmetrical network in today’s communication landscape, in large-scale connectivity scenarios. In this paper, an uplink transmission scenario is considered and user equipment (UE) aggregation is employed, wherein some users act as cooperative nodes (CNs), and help to forward received data from other users requiring coverage extension, reliability improvement, and data–rate enhancement. Non–orthogonal multiple access (NOMA) technology is introduced to improve spectral efficiency. To reduce the interference impact to guarantee the data rate, one UE can be assisted by multiple CNs, and these CNs and corresponding assisted UEs are clustered into joint transmission pairs (JTPs). Interference-free transmission can be achieved within each JTP by utilizing different successive interference cancellation (SIC) decoding orders. To explore SIC gains and maximize data rates in NOMA–based UE aggregation, we propose a primary user CN–based channel–sorting algorithm for JTP construction and apply a whale optimization algorithm for JTP power allocation. Additionally, a conflict graph is established among feasible JTPs, and a greedy strategy is employed to find the maximum weighted independent set (MWIS) of the conflict graph for subchannel allocation. Simulation results demonstrate that our joint collaborative NOMA (JC–NOMA) design with two–hop multi–path UE aggregation significantly improves spectral efficiency and capacity under limited spectral resources.

The study characterized the aroma-active compounds produced by sesame hulls at three roasting temperatures and analyzed the similarities and differences in the aroma profile of sesame hulls with whole seeds and kernels after roasting. Roasting hulls produced mainly furans, aldehydes, and ketones volatiles. 140 Compounds were identified as aroma-active compounds, including 36 key aroma compounds (odor activity value, OAV ≥ 1). Among them, furanone (caramel-like, OAV = 80), 3-methylbutanal (fruity, OAV = 124), and 2-methoxy-4-vinylphenol (burnt, smoky, OAV = 160) gave hulls (180 °C) sweet, burnt, and smoky aroma. Due to the contribution of vanillin (fatty, sweet milk, OAV = 45), 2-hydroxy-3-butanone (caramel-like, roast, OAV = 46), and 2-methoxy-4-vinylphenol (OAV = 78), hulls (200 °C) shown strong sweet and roast note. These results identified compounds that contributed significantly to the aroma of sesame hulls and elucidated the contribution of sesame hulls to the flavor of roasted whole seeds and sesame oil.

This study developed a novel and green method to produce fragrant sesame oil using microwaves and subcritical extraction (SBE). Sesame seeds were microwaved at 540 W for 0–9 min before subcritical propane extraction at 40 °C and 0.5 MPa. SBE caused less deformation to the cellular microstructure of sesame cotyledons while dramatically improving oil yield (96.7–97.1 %) compared to screw processing (SP) (53.1–58.6 %). SBE improved extraction rates for γ-tocopherol (381.1–454.9 μg/g) and sesame lignans (917.9–970.4 mg/100 g) in sesame oil compared to SP (360.1–443.8 μg/g and 872.8–916.8 mg/100 g, respectively). Microwaves generated aroma-active heterocyclics and phenolics faster than hot-air roasting in sesame oil with a better sensory profile. SBE had a higher extraction rate for aroma-active terpenes, alcohols, and esters while reducing the concentrations of carcinogenic PAHs and HCAs in sesame oil. The novel combination process of microwaves and subcritical extraction is promising in producing fragrant sesame oil with superior qualities.

Objective: This study aimed to promote the deep development of safflower seed oil. Methods: Taking sterilization rate as an index, safflower seed oil/dragon fruits juice emulsion was treated by different processing distance, voltage and time. Response surface methodology was used to establish the conditions for low temperature plasma （LTP）sterilization of emulsion. The changes of physicochemical indexes (vitamin C and anthocyanin content, particle size and ζ potential, peroxide value and acid value) during storage were compared between thermal sterilization (at 80 ℃ for 20 min) and LTP sterilization. Results: The optimized process conditions of LTP sterilization were treatment distance at 5.1 cm and voltage of 6.4 kV for 151.0 s. Under the control of these conditions, the sterilization rate reached 98.2%. After storage for 20 days, the retention rate of vitamin C and anthocyanin in LTP-treated emulsion was higher than that in heat-treated emulsion, and the particle size was smaller than that in heat-treated emulsion; The ζ potential was higher than that in heat-treated emulsion, and the difference was significant（P＜0.05）. However, the difference of peroxide value and acid value was not significant. Conclusion: LTP treatment can not only effectively kill the microorganisms in the emulsion, but also maintain the quality of emulsion better than heat treatment, and the invention relates to a new method for sterilizing the safflower seed oil/dragon fruits juice emulsion.

Abstract Background Existing evidence concerning the relationship between daytime napping and type 2 diabetes (T2D) is inconsistent, and whether the effects of napping differ by body fat percentage (BFP) and C‐reactive protein (CRP) is unclear. We aimed to investigate the association between daytime napping frequency and T2D risk and whether such an association was modified by BFP and CRP. Methods We included 435 342 participants free of diabetes from the UK Biobank. Participants were categorized as nonnappers, occasional nappers, and frequent nappers based on napping frequency, and BFP/CRP was divided into quartiles. Cox proportional hazards models were used. Results During a median follow‐up of 9.2 years, 17 592 T2D cases occurred. Higher frequency of daytime napping was significantly associated with an increased risk of T2D. Compared with nonnappers, the adjusted hazard ratios (HRs) for occasional nappers and habitual nappers were 1.28 (95% confidence interval [CI]: 1.24–1.32) and 1.49 (95% CI: 1.41–1.57), respectively. There was a significant additive and multiplicative interaction (relative excess risk due to interaction [RERI] = 0.490, 95% CI 0.307–0.673; p for multiplicative interaction

Abstract Background Research on the association of physical activity and sedentary time with dementia is accumulating, though elusive, and the interaction effects of the two remain unclear. We analysed the joint associations of accelerometer-measured physical activity and sedentary time with risk of incident dementia (all-cause dementia, Alzheimer’s disease and vascular dementia). Methods A total of 90,320 individuals from the UK Biobank were included. Accelerometer-measured total volume of physical activity (TPA) and sedentary time were measured at baseline and dichotomised by median (low TPA [ 0.05). Conclusion Higher TPA level was related to a lower risk of incident dementia irrespective of sedentary time, which highlighted the implication of promoting physical activity participation to counteract the potential detrimental effect of sedentary time on dementia.