Interaction of ubiquitin-like protein SILENCING DEFECTIVE 2 with LIKE HETEROCHROMATIN PROTEIN 1 is required for regulation of anthocyanin biosynthesis in Arabidopsis thaliana in response to sucrose.

The regulatory mechanisms of anthocyanin biosynthesis have been well documented at the transcriptional and translational levels. By contrast, how anthocyanin biosynthesis is epigenetically regulated remains largely unknown. In this study, we employed genetic, molecular biology, and chromatin immunoprecipitation-quantitative polymerase chain reaction assays to identify a regulatory module essential for repressing the expression of genes involved in anthocyanin biosynthesis through chromatin remodeling. We found that SILENCING DEFECTIVE 2 (SDE2), which was previously identified as a negative regulator for sucrose-induced anthocyanin accumulation in Arabidopsis, is cleaved into N-terminal SDE2-UBL and C-terminal SDE2-C fragments at the first diglycine motif, and the cleaved SDE2-C, which can fully complement the sde2 mutant, is localized in the nucleus and physically interacts with LIKE HETEROCHROMATIN PROTEIN 1 (LHP1) in vitro and in vivo. Genetic analyses showed that both SDE2 and LHP1 act as negative factors for anthocyanin biosynthesis. Consistently, immunoblot analysis revealed that the level of LHP1-bound histone H3 lysine 27 trimethylation (H3K27me3) significantly decreases in sde2 and lhp1 mutants, compared to wild-type (WT). In addition, we found that sugar can induce expression of SDE2 and LHP1, and enhance the level of the nucleus-localized SDE2-C. Taken together, our data suggest that the SDE2-C-LHP1 module is required for repression of gene expression through H3K27me3 modification during sugar-induced anthocyanin biosynthesis in Arabidopsis thaliana.

Medical education and the epidemics: How educational technology responded.

The global disruption created by the Coronavirus Disease 2019 (COVID-19) pandemic in medical education and healthcare institutions is unparalleled. Consequently, it is essential to evaluate the usability of forms of educational technology and to identify their viability and suitability for medical education. The objective of the investigation was to present an assessment of the state of medical education during the COVID-19 epidemic and to identify the obstacles faced by educators while introducing online learning systems for medical students. Two cross-sectional surveys were conducted with 200 medical students and 75 staff members from Saudi Arabia's University of Health. A descriptive method was used to focus on the mechanisms of analysis, foresight, and comprehension of reality. The most significant findings were the obstacles posed by instructors' most urgent requirements for educational technology training and its applications in order to activate distance education in medical education. In addition to a detailed description of the academic and technological concerns and obstacles encountered by students and faculty of health colleges during the pandemic, this report includes a discussion of the pandemic itself. Several prospective recommendations for the use of online and blended learning in health colleges post-pandemic were also made. Additionally, the requirement to activate learning via virtual professional learning groups.

La perturbation mondiale créée par la pandémie de maladie à coronavirus 2019 (COVID-19) dans les établissements d'enseignement médical et de soins de santé est sans précédent. Par conséquent, il est essentiel d'évaluer l'utilisabilité des formes de technologie éducative et d'identifier leur viabilité et leur adéquation à l'enseignement médical. L'objectif de l'enquête était de présenter une évaluation de l'état de l'enseignement médical pendant l'épidémie de COVID-19 et d'identifier les obstacles rencontrés par les éducateurs lors de l'introduction de systèmes d'apprentissage en ligne pour les étudiants en médecine. Deux enquêtes transversales ont été menées auprès de 200 étudiants en médecine et de 75 membres du personnel de l'Université de la Santé d'Arabie Saoudite. Une méthode descriptive a été utilisée pour se concentrer sur les mécanismes d'analyse, de prospective et de compréhension de la réalité. Les résultats les plus significatifs ont été les obstacles posés par les besoins les plus urgents des instructeurs en matière de formation en technologie éducative et ses applications afin d'activer l'enseignement à distance en médecine. éducation. En plus d'une description détaillée des préoccupations et des obstacles académiques et technologiques rencontrés par les étudiants et les professeurs des collèges de santé pendant la pandémie, ce rapport comprend une discussion sur la pandémie elle-même. Plusieurs recommandations prospectives concernant l'utilisation de l'apprentissage en ligne et mixte dans les établissements de santé après la pandémie ont également été formulées. À cela s'ajoute l'obligation d'activer l'apprentissage via des groupes d'apprentissage professionnel virtuels.

Automatic sleep spindles identification and classification with multitapers and convolution.

Sleep spindles are isolated transient surges of oscillatory neural activity present during sleep stages 2 and 3 in the nonrapid eye movement (NREM). They can indicate the mechanisms of memory consolidation and plasticity in the brain. Spindles can be identified across cortical areas and classified as either slow or fast. There are spindle transients across different frequencies and power, yet most of their functions remain a mystery. Using several electroencephalogram (EEG) databases, this study presents a new method, called the "spindles across multiple channels" (SAMC) method, for identifying and categorizing sleep spindles in EEGs during the NREM sleep. The SAMC method uses a multitapers and convolution (MT&C) approach to extract the spectral estimation of different frequencies present in sleep EEGs and graphically identify spindles across multiple channels. The characteristics of spindles, such as duration, power, and event areas, are also extracted by the SAMC method. Comparison with other state-of-the-art spindle identification methods demonstrated the superiority of the proposed method with an agreement rate, average positive predictive value, and sensitivity of over 90% for spindle classification across the three databases used in this paper. The computing cost was found to be, on average, 0.004 seconds per epoch. The proposed method can potentially improve the understanding of the behavior of spindles across the scalp and accurately identify and categories sleep spindles.

Photocatalytic fixation and oxygenation of NAD+ /NADP+ and sulfides using solar light: Exploring mechanistic investigations and their impact on synthetic applications.

Sulfur-doped Eosin-B (SDE-B) photocatalysts were synthesized for the first time utilizing sublimed sulfur (S8 ) as a dopant in an in situ thermal copolymerization technique. Sulfur doping not only increased Eosin-B (E-B) absorption range for solar radiation but also improved fixation and oxygenation capabilities. The doped sulfur bridges the S-S bond by substituting for the edge bromine of the E-B bond. The improved photocatalytic activity of SDE-B in the fixation and oxygenation of NAD+ /NADP+ and sulfides using solar light is attributed to the photo-induced hole of SDE-B's high fixation and oxygenation capacity, as well as an efficient suppression of electron and hole recombination. The powerful light-harvesting bridge system created using SDE-B as a photocatalyst works extremely well, resulting in high NADH/NADPH regeneration (79.58/76.36%) and good sulfoxide yields (98.9%) under solar light. This study focuses on the creation and implementation of a sulfur-doped photocatalyst for direct fine chemical regeneration and organic transformation.

Copper (II) Ions Induced Self-Disproportionation of Enantiomers in Capillary Electrophoresis for the Quantification of Atenolol Enantiomers.

Despite the fact that the self-disproportionation of enantiomers (SDE) has been found for several decades and has been widely used in crystallization, sublimation and chromatography for the purification or separation of nonracemic compounds, the phenomenon of SDE in capillary electrophoresis (CE) has never been reported up to now. Here, a new approach to separate enantiomers in CE based on SDE was demonstrated by introducing copper (II) ions into the separation media. The enantiomers of atenolol interact with copper ions to produce positively charged complexes with different electrophoretic mobilities from the single molecules. The dynamic equilibrium between homo- or heterochiral complexes (associates) and single molecules of atenolol enantiomers supports the manifestation of SDE. Different mobilities of the single molecules and associates, and different distribution of two enantiomers between the single molecules and associates caused by their different concentrations, produce a net difference in electrodriven migration velocities of the two enantiomers. The relative movement of two enantiomers causes a zone depleted in one enantiomer at the rear end of sample segment, giving a trapezoidal CE curve with a step at the end. Quantification of enantiomers is achieved according to the step height. The analysis does not rely on the use of enantiomerically pure chiral selector and the result agrees with that obtained by conventional chiral CE using a chiral selector.

Universal generative modeling in dual domains for dynamic MRI.

Dynamic magnetic resonance image reconstruction from incomplete k-space data has generated great research interest due to its ability to reduce scan time. Nevertheless, the reconstruction problem remains a thorny issue due to its ill posed nature. Recently, diffusion models, especially score-based generative models, have demonstrated great potential in terms of algorithmic robustness and flexibility of utilization. Moreover, a unified framework through the variance exploding stochastic differential equation is proposed to enable new sampling methods and further extend the capabilities of score-based generative models. Therefore, by taking advantage of the unified framework, we propose a k-space and image dual-domain collaborative universal generative model (DD-UGM), which combines the score-based prior with a low-rank regularization penalty to reconstruct highly under-sampled measurements. More precisely, we extract prior components from both image and k-space domains via a universal generative model and adaptively handle these prior components for faster processing while maintaining good generation quality. Experimental comparisons demonstrate the noise reduction and detail preservation abilities of the proposed method. Moreover, DD-UGM can reconstruct data of different frames by only training a single frame image, which reflects the flexibility of the proposed model.

Comparative study of the impact of malting on the aroma profiles of barley (Hordeum vulgare L.) and rye (Secale cereale L.).

Barley (Hordeum vulgare L.) remains the traditional malted cereal used for beverages, whereas rye (Secale cereale L.) is mainly used in baked goods. To evaluate the potential of rye malt for beverage production, malt quality indicators and the volatile composition of different rye malts were compared to barley malt. Sensory assessment revealed that pleasant malty and caramel aromas were formed by malting. Subsequently, three complementary isolation techniques and gas chromatography-olfactometry/mass spectrometry (GC-O/MS) were used for volatile analysis. Instrumental analysis detected 50 and 56 odor active volatiles in barley and rye, respectively. In part two, storage and the impact of three malting parameters on volatile formation were examined. Similarities in the malt volatile patterns were detected but the perceived intensity and composition varied. In barley, characteristic malty volatiles were lost during storage and staling compounds were formed. Conversely, nutty pyrazines and caramel furanones remained dominant in rye malts even after storage.

Design of a concept vehicle for future-oriented urban mobility using design-driven methodologies.

Due to ever-increasing technological acceleration leading to rapid changes in society and its needs, just as today's habits and needs turn out to be completely different from those of only a few years ago, likewise it is reasonable to assume that the same trend will continue in its growth path, making today's solutions rapidly obsolete as time passes and technological innovations follow. This study aims to investigate possible solutions in search of a futuristic and breakthrough response to what is present today. The idea concerns the design of a new type of means of transportation that can best interface with what today are the various criticalities given by vehicular traffic mainly urban but also suburban, going to solve by generating new opportunities from previous problems. This system will be able to go alongside and gradually replace a substantial portion of the current means of transport going to conceptually redefine some elements taken for granted today. In this regard, the application of the IDeS (Industrial Design Structure) methodology has been found to be of great use, which, thanks to the scientific and repeatable methods contained within, has made it possible to arrive at a very clear visualization of the problem, a precise definition, and a level of innovation that is fully satisfactory with respect to the contemporary scenario, while always keeping an eye on feasibility while taking into account the conceptual and therefore deliberately very driven nature of the solution being designed.

Multi-release software model based on testing coverage incorporating random effect (SDE).

In the past, various Software Reliability Growth Models (SRGMs) have been proposed using different parameters to improve software worthiness. Testing Coverage is one such parameter that has been studied in numerous models of software in the past and it has proved its influence on the reliability models. To sustain themselves in the market, software firms keep upgrading their software with new features or enhancements by rectifying previously reported faults. Also, there is an impact of the random effect on testing coverage during both the testing and operational phase. In this paper, we have proposed a Software reliability growth model based on testing coverage with random effect along with imperfect debugging. Later, the multi-release problem is presented for the proposed model. The proposed model is validated on the dataset from Tandem Computers. The results for each release of the models have been discussed based on the different performance criteria. The numerical results illustrate that models fit the failure data significantly.•The random effect in the testing coverage rate is handled using Stochastic Differential Equations (SDE).•Three testing coverage functions used are Exponential, Weibull, and S-shaped.•Four Releases of the software model has been presented.

Self-generated cognitive fluency: consequences on evaluative judgments.

ABSTRACTPeople can support abstract reasoning by using mental models with spatial simulations. Such models are employed when people represent elements in terms of ordered dimensions (e.g. who is oldest, Tom, Dick, or Harry). We test and find that the process of forming and using such mental models can influence the liking of its elements (e.g. Tom, Dick, or Harry). The presumed internal structure of such models (linear-transitive array of elements), generates variations in processing ease (fluency) when using the model in working memory (see the Symbolic Distance Effect, SDE). Specifically, processing of pairs where elements have larger distances along the order should be easier compared to pairs with smaller distances. Elements from easier pairs should be liked more than elements from difficult pairs (fluency being hedonically positive). Experiment 1 shows that unfamiliar ideographs are liked more when at wider distances and therefore easier to process. Experiment 2 replicates this effect with non-words. Experiment 3 rules out a non-spatial explanation of the effect while Experiments 4 offers a high-powered replication. Experiment 5 shows that the spatial effect spontaneously emerges after learning, even without a task that explicitly focuses on fluency. Experiment 6 employed a shorter array, but yielded no significant results.

Spatio-temporal characteristics of soil Cd pollution and its influencing factors: A Geographically and temporally weighted regression (GTWR) method.

Soil Cd pollution is the result of the combined influence of various human activities over a long period of time, and then quantifying the influence is essential for the prevention and control. Based on published literature data during 2000-2020, this study investigated the pollution characteristics and influencing factors of soil Cd in the Yangtze River Delta. The results were as follows: (1) The average Cd concentration was higher than the Chinese soil criteria value (0.30 mg/kg), and the proportion of Cd concentration exceeding its background value was 87.43%. (2) The assessment results using Contamination factor (CF) and Geo-accumulation index (Igeo) indicated that the soil Cd pollution risk could not negligible in the study area. (3) The pollution center shifted significantly owing to the combined effect of human activities. (4) The main influencing factors of Cd pollution obtained by Geographically and temporally weighted regression (GTWR) model were GDP per capita, Consumption of chemical fertilizer, Output value of primary industry, and Output value of secondary industry, but there were significant differences in the dominant factors for different provinces. Our findings contribute to the current understanding of the relationship between Cd pollution and human activities, and provide a scientific basis for pollution control.

Neural stochastic differential equations network as uncertainty quantification method for EEG source localization.

EEG source localization remains a challenging problem given the uncertain conductivity values of the volume conductor models (VCMs). As uncertain conductivities vary across people, they may considerably impact the forward and inverse solutions of the EEG, leading to an increase in localization mistakes and misdiagnoses of brain disorders. Calibration of conductivity values using uncertainty quantification (UQ) techniques is a promising approach to reduce localization errors. The widely-known UQ methods involve Bayesian approaches, which utilize prior conductivity values to derive their posterior inference and estimate their optimal calibration. However, these approaches have two significant drawbacks: solving for posterior inference is intractable, and choosing inappropriate priors may lead to increased localization mistakes. This study used the Neural Stochastic Differential equations Network (SDE-Net), a combination of dynamical systems and deep learning techniques that utilizes the Wiener process to minimize conductivity uncertainties in the VCM and improve the inverse problem. Results revealed that SDE-Net generated a lower localization error rate in the inverse problem compared to Bayesian techniques. Future studies may employ new stochastic dynamical systems-based techniques as a UQ technique to address further uncertainties in the EEG Source Localization problem. Our code can be found here:https://github.com/rrwabina/SDENet-UQ-ESL.

A "Candidatus Liberibacter asiaticus"-secreted polypeptide suppresses plant immune responses in Nicotiana benthamiana and Citrus sinensis.

Citrus Huanglongbing (HLB), known as the most economically devastating disease in citrus industry, is mainly caused by phloem-restricted Gram-negative bacterium "Candidatus Liberibacter asiaticus" (CLas). To date, CLas is still unculturable in vitro, which has been dramatically delaying the research on its pathogenesis, and only few Sec-dependent effectors (SDEs) have been identified to elucidate the pathogenesis of CLas. Here, we confirmed that a CLas-secreted Sec-dependent polypeptide, namely SECP8 (CLIBASIA_05330), localized in nucleus, cytoplasm and cytoplasmic membrane, and showed remarkably higher transcript abundance in citrus than in psyllids. Potato virus X (PVX)-mediated transient expression assays indicated that mSECP8 (the mature form of SECP8) suppressed pro-apoptotic mouse protein BAX and Phytophthora infestans elicitin INF1-triggered hypersensitive response (HR) associated phenotypes, including cell death, H2O2 accumulation and callose deposition. Intriguingly, mSECP8 also inhibited SDE1 (CLIBASIA_05315)-induced water-soaked and dwarfing symptoms in Nicotiana benthamiana. In addition, mSECP8 can promote the susceptibility of transgenic Wanjincheng orange (Citrus sinensis) to CLas invasion and further HLB symptom development, and it contributes to the proliferation of Xanthomonas citri subsp. citri (Xcc). Moreover, the expression of ten immunity-related genes were significantly down-regulated in mSECP8 transgenic citrus than those in wide-type (WT) plants. Overall, we propose that mSECP8 may serve as a novel broad-spectrum suppressor of plant immunity, and provide the first evidence counteractive effect among CLas effectors. This study will enrich and provide new evidences for elucidating the pathogenic mechanisms of CLas in citrus host.

Contemporary Management of Intracranial Subdural Empyema: An Institutional Experience.

Background: Intracranial subdural empyema (SDE) is a seemingly uncommon life-threatening ailment with varying presentations and outcomes. A variety of risk factors have been associated with predisposition to intracranial SDEs; however, they may be cryptogenic. There is an increased predilection for intracranial SDE in children and teenagers with paranasal sinusitis or middle ear infections. The clinical presentation is non-specific and thus a high index of suspicion is required. Neuroimaging is an invaluable diagnostic tool for early diagnosis and surgical intervention. There have been multiple proponents for either burr hole or craniotomy to treat intracranial SDEs; however, despite surgical intervention, adverse neurologic sequelae and even mortality still occur. Extended antibiotic therapy is mandatory and impacts significantly on patients' outcomes. Objectives: This study describes the demographics, clinical presentation, and surgical outcomes in patients with intracranial SDEs over the study period. Design: This is a retrospective single-centre case series. Setting: This study takes place in a tertiary referral centre, university hospital. Materials and Methods: This was a retrospective review of patients presenting with intracranial SDEs over a 10-year period in a tertiary neurosurgical unit serving south-western Nigeria. Demographic, clinical, and radiologic data were retrieved from patient records. Results: Forty-nine patients presented with intracranial SDEs during the review period. These patients aged between 16 months and 75 years, most of whom were 20 years of age and below. The mean age was 21.37 ± 19.29 years with a median age of 15 years. There were 35 males and 14 females giving a male-to-female ratio of 2.5:1. The most common presentations were headache (73.5%), altered sensorium (55.1%), and seizures (38.8%). Forty patients (81.6%) had evacuation of SDE by burr hole and subdural washout. There was a significant post-op residual SDE in six patients. There were eight (16.3%) mortalities in this series. Forty-seven (95.9%) patients had sterile cultures of the subdural pus collection. Conclusion: Intracranial SDE affects mostly children and teenagers. Early diagnosis, emergent surgery, extended antibiotic therapy, and concurrent source control employing a multidisciplinary approach are essential in managing this condition. Burr hole and subdural washout help control the disease process, reduce operation time, and may yield outcomes similar to craniotomies, which are more invasive.

Subdural Effusion Evolves into Chronic Subdural Hematoma after Deep Brain Stimulation Surgery: Case Report and Review of the Literature.

BACKGROUND: Although chronic subdural hematoma (CSDH) has been known for over several hundred years, the etiology and pathogenesis of it are still not completely understood. Neurosurgical procedures resulting in CSDH are a rare clinical complication, and there was no report about how subdural effusion (SDE) evolves into CSDH after deep brain stimulation (DBS) surgery. The formation mechanism of CSDH after surgery, especially in DBS surgery, and the effect of recovery, need to be explored. METHODS: We present two cases, complicated with SDE after DBS surgery, serious dysfunction complications such as hemiplegia and aphasia occurred on the postoperative day 36 and 49 individually, and images showed CSDH. Fusion image showed the bilateral electrodes were significantly shifted. Then, they were performed to drill craniotomy with a closed system drainage. RESULT: The symptoms of hemiplegia and aphasia caused by CSDH were completely recovered, and the follow-up images showed CSDH was disappeared. However, DBS stimulation is poorly effective, it cannot reach the preoperative level, especially in the ipsilateral side of CSDH. CONCLUSIONS: The iatrogenic SDE that evolved into CSDH in the present two cases shows that SDE is one of the causes of CSDH. Patients develop SDE after DBS, which increases the risk of developing CSDH. CSDH after DBS can be successfully treated. however, the postoperative efficacy of DBS will decline.

Efficiency of Sidestream Nitritation for Modern Two-Stage Activated Sludge Plants.

The operational costs of wastewater treatment plants (WWTPs) are mainly driven by electric power consumption, making the energy-efficient operation an all-time present target for engineers and operators. A well known approach to reduce the demand for purchased electricity is the operation of an anaerobic sludge stabilisation process. Although anaerobic digesters make it possible to recover large quantities of energy-rich methane gas, additional strategies are required to handle the increased internal return flow of nitrogen, which arises with the sludge dewatering effluent (SDE). SDE treatment increases the oxygen demand and in turn the energy required for aeration. In this study, different SDE treatment processes were compared with regard to the treatment in mainstream, sidestream nitritation, as well as nitritation combined with anammox for two-stage and single-stage WWTPs. Although SDE treatment in sidestream nitritation was found to have no effect on the energy demand of single-stage WWTPs, this concept allows the treatment capacity in the activated sludge tank to be raised, while contributing to a high nitrogen removal under carbon limitation. In contrast, SDE sidestream treatment showed great potential for saving energy at two-stage WWTPs, whereby sidestream nitritation and the further treatment in the first stage was found to be the most efficient concept, with a savings of approx. 11% of the aeration energy.

Monte Carlo Simulation of Stochastic Differential Equation to Study Information Geometry.

Information Geometry is a useful tool to study and compare the solutions of a Stochastic Differential Equations (SDEs) for non-equilibrium systems. As an alternative method to solving the Fokker-Planck equation, we propose a new method to calculate time-dependent probability density functions (PDFs) and to study Information Geometry using Monte Carlo (MC) simulation of SDEs. Specifically, we develop a new MC SDE method to overcome the challenges in calculating a time-dependent PDF and information geometric diagnostics and to speed up simulations by utilizing GPU computing. Using MC SDE simulations, we reproduce Information Geometric scaling relations found from the Fokker-Planck method for the case of a stochastic process with linear and cubic damping terms. We showcase the advantage of MC SDE simulation over FPE solvers by calculating unequal time joint PDFs. For the linear process with a linear damping force, joint PDF is found to be a Gaussian. In contrast, for the cubic process with a cubic damping force, joint PDF exhibits a bimodal structure, even in a stationary state. This suggests a finite memory time induced by a nonlinear force. Furthermore, several power-law scalings in the characteristics of bimodal PDFs are identified and investigated.

Extended DNA-binding interfaces beyond the canonical SAP domain contribute to the function of replication stress regulator SDE2 at DNA replication forks.

Elevated DNA replication stress causes instability of the DNA replication fork and increased DNA mutations, which underlies tumorigenesis. The DNA replication stress regulator silencing-defective 2 (SDE2) is known to bind to TIMELESS (TIM), a protein of the fork protection complex, and enhances its stability, thereby supporting replisome activity at DNA replication forks. However, the DNA-binding activity of SDE2 is not well defined. Here, we structurally and functionally characterize a new conserved DNA-binding motif related to the SAP (SAF-A/B, Acinus, PIAS) domain in human SDE2 and establish its preference for ssDNA. Our NMR solution structure of the SDE2SAP domain reveals a helix-extended loop-helix core with the helices aligned parallel to each other, consistent with known canonical SAP folds. Notably, we have shown that the DNA interaction of this SAP domain extends beyond the core SAP domain and is augmented by two lysine residues in the C-terminal tail, which is uniquely positioned adjacent to the SAP motif and conserved in the pre-mRNA splicing factor SF3A3. Furthermore, we found that mutation in the SAP domain and extended C terminus not only disrupts ssDNA binding but also impairs TIM localization at replication forks, thus inhibiting efficient fork progression. Taken together, our results establish SDE2SAP as an essential element for SDE2 to exert its role in preserving replication fork integrity via fork protection complex regulation and highlight the structural diversity of the DNA-protein interactions achieved by a specialized DNA-binding motif.

Effects of Different Extraction Methods on Vanilla Aroma.

To establish the analytic conditions for examining the aroma quality of vanilla pods, we compared different extraction methods and identified a suitable option. We utilized headspace solid-phase microextraction (HS-SPME), steam distillation (SD), simultaneous steam distillation (SDE) and alcoholic extraction combined with gas chromatography (GC) and gas chromatography-mass spectrometry (GC-MS) to identify volatile components of vanilla pods. A total of 84 volatile compounds were identified in this experiment, of which SDE could identify the most volatile compounds, with a total of 51 species, followed by HS-SPME, with a total of 28 species. Ten volatile compounds were identified by extraction with a minimum of 35% alcohol. HS-SPME extraction provided the highest total aroma peak areas, and the peak areas of aldehydes, furans, alcohols, monoterpenes and phenols compounds were several times higher than those of the other extraction methods. The results showed that the two technologies, SDE and HS-SPME, could be used together to facilitate analysis of vanilla pod aroma.

Gearbox Fault Diagnosis Based on Improved Variational Mode Extraction.

Gearboxes are widely used in drive systems of rotating machinery. The health status of gearboxes considerably influences the normal and reliable operation of rotating machinery. When a gearbox experiences tooth failure, a vibration signal with impulse features is excited. However, these impulse features tend to be relatively weak and difficult to extract. To solve this problem, a novel approach for gearbox fault feature extraction and fault diagnosis based on improved variational mode extraction (VME) is proposed. Since the initial value of the desired mode center frequency and the value of the penalty parameter in VME must be assigned, a short-time Fourier transform (STFT) was performed, and a new index, the standard deviation of differential values of envelope maxima positions (SDE), is proposed. The feasibility and effectiveness of the proposed approach was verified by a simulation signal and two datasets associated with a gearbox test bench. The results demonstrate that the VME-based approach outperforms the variational mode decomposition (VMD) approach.