Predictive Control of an Intelligent Energy-saving Operation System Based on Deep Learning

An intelligent energy-saving operation system is a high-tech product specifically designed to transform the air conditioning systems, motor systems, and lighting systems, to reduce energy consumption. The concentration of equipment distribution within these systems leads to a strong coupling relationship between them. By conducting an overall energy efficiency prediction, the intelligent energy-saving operation system can fully explore its energy-saving potential. The existing research methods for the online control process of intelligent energy-saving operation systems are not accurate enough to predict energy-saving operations when numerous devices are involved. Consequently, this article focuses on studying the predictive control of an intelligent energy-saving operation system using deep learning techniques. The Generalized Regression Neural Network (GRNN) network is selected to describe the energy consumption of the system. The Beetle Antennae search algorithm is then employed to iteratively optimize the smoothing factor of the model, eliminating the need to rely on experiential parameter determination and enhancing the predictive performance of the model. For the predictive control of the intelligent energy-saving operation system, the optimized GRNN network model serves as the prediction model. The primary control objective is to minimize energy consumption while maintaining a unified carrying capacity, thus achieving intelligent energy-saving effects. Experimental results validate the effectiveness of the model

Population genetics of foxtail millet and its wild ancestor

<p>Abstract</p> <p>Background</p> <p>Foxtail millet (<it>Setaria italica </it>(L.) P. Beauv.), one of the most ancient domesticated crops, is becoming a model system for studying biofuel crops and comparative genomics in the grasses. However, knowledge on the level of genetic diversity and linkage disequilibrium (LD) is very limited in this crop and its wild ancestor, green foxtail (<it>Setaria viridis </it>(L.) P. Beauv.). Such information would help us to understand the domestication process of cultivated species and will allow further research in these species, including association mapping and identification of agricultural significant genes involved in domestication.</p> <p>Results</p> <p>In this study, we surveyed DNA sequence for nine loci across 50 accessions of cultivated foxtail millet and 34 of its wild progenitor. We found a low level of genetic diversity in wild green foxtail (θ = 0.0059), θ means Watterson's estimator of θ. Despite of a 55% loss of its wild diversity, foxtail millet still harbored a considerable level of diversity (θ = 0.0027) when compared to rice and sorghum (θ = 0.0024 and 0.0034, respectively). The level of LD in the domesticated foxtail millet extends to 1 kb, while it decayed rapidly to a negligible level within 150 bp in wild green foxtail. Using coalescent simulation, we estimated the bottleneck severity at k = 0.6095 when ρ/θ = 1. These results indicated that the domestication bottleneck of foxtail millet was more severe than that of maize but slightly less pronounced than that of rice.</p> <p>Conclusions</p> <p>The results in this study establish a general framework for the domestication history of foxtail millet. The low level of genetic diversity and the increased level of LD in foxtail millet are mainly caused by a population bottleneck, although gene flow from foxtail millet to green foxtail is another factor that may have shaped the pattern of genetic diversity of these two related gene pools. The knowledge provided in this study will benefit future population based studies in foxtail millet.</p

Urinary Aromatic Amino Acid Metabolites Associated With Postoperative Emergence Agitation in Paediatric Patients After General Anaesthesia: Urine Metabolomics Study

Background: Emergence agitation (EA) is very common in paediatric patients during recovery from general anaesthesia, but underlying mechanisms remain unknown. This prospective study was designed to profile preoperative urine metabolites and identify potential biomarkers that can predict the occurrence of EA.Methods: A total of 224 patients were screened for recruitment; of those, preoperative morning urine samples from 33 paediatric patients with EA and 33 non-EA gender- and age-matched patients after being given sevoflurane general anaesthesia were analysed by ultra-high-performance liquid chromatography (UHPLC) coupled with a Q Exactive Plus mass spectrometer. Univariate analysis and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were used to analyse these metabolites. The least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive variables. The predictive model was evaluated through the receiver operating characteristic (ROC) analysis and then further assessed with 10-fold cross-validation.Results: Seventy-seven patients completed the study, of which 33 (42.9%) patients developed EA. EA and non-EA patients had many differences in preoperative urine metabolic profiling. Sixteen metabolites including nine aromatic amino acid metabolites, acylcarnitines, pyridoxamine, porphobilinogen, 7-methylxanthine, and 5′-methylthioadenosine were found associated with an increased risk of EA, and they all exhibited higher levels in the EA group than in the non-EA group. The main metabolic pathways involved in these metabolic changes included phenylalanine, tyrosine and tryptophan metabolisms. Among these potential biomarkers, L-tyrosine had the best predictive value with an odds ratio (OR) (95% CI) of 5.27 (2.20–12.63) and the AUC value of 0.81 (0.70–0.91) and was robust with internal 10-fold cross-validation.Conclusion: Urinary aromatic amino acid metabolites are closely associated with EA in paediatric patients, and further validation with larger cohorts and mechanistic studies is needed.Clinical Trial Registration:clinicaltrials.gov, identifier NCT0480799

Palmitic acid-modified GnRH-Th epitope peptide immunocastration vaccine (W/O/W adjuvant) can effectively ensure the castration and reduce the smelly smell in boars

IntroductionRecent studies have demonstrated the effectiveness of Gonadotropin-releasing hormone (GnRH) in inhibiting testicular growth and development in male animals to achieve castration while improving the meat quality of various livestock species, including cattle, sheep, goats, and pigs.MethodsIn this research, a GnRH-Th vaccine was synthesized using the Fmoc solid-phase synthesis technique, and the T helper (Th) antigen was modified with palmitic acid to improve its efficacy. The vaccine was then coated with a water-in-oil-in-water adjuvant to improve stability and safety. After passing safety and stability tests, the vaccine was administered to 13-week-old boars.ResultsThe results showed that it was stable, safe, and effective for up to 15 months. Moreover, the vaccine did not negatively affect the growth rate and body weight of the pigs. The palmitic acid-modified “GnRH-Th epitope peptide immunocastration vaccine (Water-in-Oil-in-Water (W/O/W)) effectively reduced the testosterone concentration and achieved castration. The concentration of androstenone and skatole hormones significantly decreased, leading to improved meat quality in the boars. The boars were then slaughtered at 33 weeks of age, and the results showed that the meat quality of the vaccinated boars was superior to that of the non-vaccinated control group (p &lt; 0.05).DiscussionThis study demonstrated that GnRH can safely and effectively achieve immune castration in boars after coupling T cell epitopes, palmitic acid modification and W-O-W coating. Provide a better method for the further development of GnRH and the realization of animal welfare

GPX8 regulates pan-apoptosis in gliomas to promote microglial migration and mediate immunotherapy responses

IntroductionGliomas have emerged as the predominant brain tumor type in recent decades, yet the exploration of non-apoptotic cell death regulated by the pan-optosome complex, known as pan-apoptosis, remains largely unexplored in this context. This study aims to illuminate the molecular properties of pan-apoptosis-related genes in glioma patients, classifying them and developing a signature using machine learning techniques.MethodsThe prognostic significance, mutation features, immunological characteristics, and pharmaceutical prediction performance of this signature were comprehensively investigated. Furthermore, GPX8, a gene of interest, was extensively examined for its prognostic value, immunological characteristics, medication prediction performance, and immunotherapy prediction potential. ResultsExperimental techniques such as CCK-8, Transwell, and EdU investigations revealed that GPX8 acts as a tumor accelerator in gliomas. At the single-cell RNA sequencing level, GPX8 appeared to facilitate cell contact between tumor cells and macrophages, potentially enhancing microglial migration. ConclusionsThe incorporation of pan-apoptosis-related features shows promising potential for clinical applications in predicting tumor progression and advancing immunotherapeutic strategies. However, further in vitro and in vivo investigations are necessary to validate the tumorigenic and immunogenic processes associated with GPX8 in gliomas

A Novel Memductor-Based Chaotic System and Its Applications in Circuit Design and Experimental Validation

This paper is expected to introduce a novel memductor-based chaotic system. The local dynamical entities, such as the basic dynamical behavior, the divergence, the stability of equilibrium set, and the Lyapunov exponent, are all investigated analytically and numerically to reveal the dynamic characteristics of the new memductor-based chaotic system as the system parameters and the initial state of memristor change. Subsequently, an active control method is derived to study the synchronous stability of the novel memductor-based chaotic system through making the synchronization error system asymptotically stable at the origin. Further to these, a memductor-based chaotic circuit is designed, realized, and applied to construct a new memductor-based secure communication circuit by employing the basic electronic components and memristor. Furthermore, the design principle of the memductor-based chaotic circuit is thoroughly analyzed and the concept of “the memductor-based chaotic circuit defect quantification index” is proposed for the first time to verify whether the chaotic output is consistent with the mathematical model. A good qualitative agreement is shown between the simulations and the experimental validation results

Physiological and Gene Expression Analysis of Herbaceous Peony Resistance to <i>Alternaria tenuissima</i> Infection

Leaf spot disease caused by Alternaria pathogens seriously threatens peony production. The physiological mechanism of peony resistance to the pathogen is little reported. This study aimed to reveal the defensive mechanism of peonies in response to the pathogen Alternaria tenuissima. The disease-resistant (R) variety ‘Zi Fengyu’ and susceptible (S) variety ‘Heihai Botao’ were employed, and some parameters in the leaves were analyzed after inoculation with A. tenuissima, mainly including the hypersensitive response (HR), activity of defensive enzymes, and expression of disease-resistance genes. The results showed that compared with the responses in the S genotype, HR occurred more rapidly in the R genotype. Meanwhile, the activity of antioxidant enzymes (superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase) and other two defense enzymes (polyphenol oxidase and phenylalanine ammonia-lyase) increased more significantly, and the expression of pathogenesis-related (PR) genes (PlPR1, PlPR2, PlPR4B, PlPR5, and PlPR10) and two WRKY genes (PlWRKY13 and PlWRKY65) was more strongly induced. These responses collectively contributed to the disease resistance of the R genotype. These findings provided a theoretical basis for understanding the intrinsic mechanism of peony resistance to Alternaria leaf spot disease and breeding the disease-resistant peony varieties using a molecular approach

A Rapid Therapeutic Drug Monitoring Strategy of Carbamazepine in Serum by Using Coffee-Ring Effect Assisted Surface-Enhanced Raman Spectroscopy

Carbamazepine (CBZ) has a narrow therapeutic concentration range, and therapeutic drug monitoring (TDM) is necessary for its safe and effective individualized medication. This study aims to develop a procedure for CBZ detection in serum using coffee-ring effect assisted surface-enhanced Raman spectroscopy (SERS). Silver nanoparticles deposited onto silicon wafers were used as the SERS-active material. Surface treatment optimization of the silicon wafers and the liquid&ndash;liquid extraction method were conducted to eliminate the influence of impurities on the silicon wafer surface and the protein matrix. The proposed detection procedure allows for the fast determination of CBZ in artificially spiked serum samples within a concentration range of 2.5&ndash;40 &mu;g&middot;mL&minus;1, which matches the range of the drug concentrations in the serum after oral medication. The limit of detection for CBZ was found to be 0.01 &mu;g&middot;mL&minus;1. The developed method allowed CBZ and its metabolites to be ultimately distinguished from real serum samples. The developed method is anticipated to be a potential tool for monitoring other drug concentrations

Investigation on the skidding dynamic response of rolling bearing with local defect under elastohydrodynamic lubrication

The rolling element skidding may lead to the failure of the rolling bearing. The skidding characteristics can be effectively analyzed by using dynamic response of the rolling bearing. A dynamic model is established to investigate the vibration response of the rolling bearing with local defect on inner/outer race in this paper. In the proposed model, the rolling element skidding, contact stiffness and displacement, the interaction force between ball and race, the interaction force between cage and race, elastohydrodynamic lubrication are taken into consideration. The dynamic responses of the rolling bearing with the rolling element skidding are solved by the proposed model in the time and frequency domains. The effects of defect size, rotational speed, external load, and compound factors on skidding characteristics are investigated. The proposed model is verified by the experiments. The results show that the rolling element skidding leads to the significant difference of dynamic characteristics in the time and frequency domains, which aggravates the failure of the rolling bearings