bluuebunny/crossref_metadata_2025 huggingface dataset:
Identification of lipid synthesis genes in Schizochytrium sp. and their application in improving eicosapentaenoic acid synthesis in Yarrowia lipolytica
Authors: Jia Yu-Lei , Zhang Qing-Ming , Du Fei , Yang Wen-Qian , Zhang Zi-Xu , Xu Ying-Shuang , Ma Wang , Sun Xiao-Man , Huang He
Published: February 2024

Background

Eicosapentaenoic acid (EPA) is widely used in the functional food and nutraceutical industries due to its important benefits to human health. Oleaginous microorganisms are considered a promising alternative resource for the production of EPA lipids. However, the storage of EPA in triglyceride (TG) becomes a key factor limiting its level.

Results

This study aimed to incorporate more EPA into TG storage through metabolic engineering. Firstly, key enzymes for TG synthesis, the diacylglycerol acyltransferase (DGAT) and glycerol-3-phosphate acyltransferase (GPAT) genes from Schizochytrium sp. HX-308 were expressed in Yarrowia lipolytica to enhance lipid and EPA accumulation. In addition, engineering the enzyme activity of DGATs through protein engineering was found to be effective in enhancing lipid synthesis by replacing the conserved motifs “HFS” in ScDGAT2A and “FFG” in ScDGAT2B with the motif “YFP”. Notably, combined with lipidomic analysis, the expression of ScDGAT2C and GPAT2 enhanced the storage of EPA in TG. Finally, the accumulation of lipid and EPA was further promoted by identifying and continuing to introduce the ScACC, ScACS, ScPDC, and ScG6PD genes from Schizochytrium sp., and the lipid and EPA titer of the final engineered strain reached 2.25 ± 0.03 g/L and 266.44 ± 5.74 mg/L, respectively, which increased by 174.39% (0.82 ± 0.02 g/L) and 282.27% (69.70 ± 0.80 mg/L) compared to the initial strain, respectively.

Conclusion

This study shows that the expression of lipid synthesis genes from Schizochytrium sp. in Y. lipolytica effectively improves the synthesis of lipids and EPA, which provided a promising target for EPA-enriched microbial oil production.
Bioprocess optimization for enhanced xylitol synthesis by new isolate Meyerozyma caribbica CP02 using rice straw
Authors: Singh Saumya , Arya Shailendra Kumar , Krishania Meena
Published: February 2024

The present work models the fermentation process parameters of the newly isolated, Meyerozyma caribbica CP02 for enhanced xylitol production and its fermentability study on rice straw hydrolysate. The study examined the impact of each of the process variables by one variable at a time optimization followed by statistical validation. Temperature of 32 °C, pH of 3.5, agitation of 200 rpm, 1.5% (v/v) inoculum, 80 gL−1 initial xylose was optimized. Subsequently, a sequential two-stage agitation approach was adopted for fermentation. At these optimized conditions, xylitol yield of 0.77 gg−1 and 0.64 gg−1 was achieved using media containing commercial and rice straw derived xylose, respectively. For scale up, in 3L batch bioreactor, the highest xylitol yield (0.63 gg−1) was attained at 72 h with rice straw hydrolysate media containing initial xylose (59.48 ± 0.82 gL−1) along with inhibitors (1.55 ± 0.10 gL−1 aliphatic acids, 0.0.048 ± 0.11 gL−1 furans, 0.64 ± 0.23 gL−1 total phenols). The results imply that even under circumstances characterized by an acidic pH and elevated initial xylose level, M. caribbica CP02, as an isolate, displays robustness and shows favorable fermentability of rice straw hydrolysate. Therefore, isolate CP02 has potential to be used in bio-refineries for high yield xylitol production with minimal hydrolysate processing requirements.

Graphical Abstract
In silico design of multipoint mutants for enhanced performance of Thermomyces lanuginosus lipase for efficient biodiesel production
Authors: Huang Jinsha , Xie Xiaoman , Zheng Wanlin , Xu Li , Yan Jinyong , Wu Ying , Yang Min , Yan Yunjun
Published: February 2024

Background

Biodiesel, an emerging sustainable and renewable clean energy, has garnered considerable attention as an alternative to fossil fuels. Although lipases are promising catalysts for biodiesel production, their efficiency in industrial-scale application still requires improvement.

Results

In this study, a novel strategy for multi-site mutagenesis in the binding pocket was developed via FuncLib (for mutant enzyme design) and Rosetta Cartesian_ddg (for free energy calculation) to improve the reaction rate and yield of lipase-catalyzed biodiesel production. Thermomyces lanuginosus lipase (TLL) with high activity and thermostability was obtained using the Pichia pastoris expression system. The specific activities of the mutants M11 and M21 (each with 5 and 4 mutations) were 1.50- and 3.10-fold higher, respectively, than those of the wild-type (wt–TLL). Their corresponding melting temperature profiles increased by 10.53 and 6.01 °C, $$T_{50}^{15}$$

T

50

15

(the temperature at which the activity is reduced to 50% after 15 min incubation) increased from 60.88 to 68.46 °C and 66.30 °C, and the optimum temperatures shifted from 45 to 50 °C. After incubation in 60% methanol for 1 h, the mutants M11 and M21 retained more than 60% activity, and 45% higher activity than that of wt–TLL. Molecular dynamics simulations indicated that the increase in thermostability could be explained by reduced atomic fluctuation, and the improved catalytic properties were attributed to a reduced binding free energy and newly formed hydrophobic interaction. Yields of biodiesel production catalyzed by mutants M11 and M21 for 48 h at an elevated temperature (50 °C) were 94.03% and 98.56%, respectively, markedly higher than that of the wt–TLL (88.56%) at its optimal temperature (45 °C) by transesterification of soybean oil.

Conclusions

An integrating strategy was first adopted to realize the co-evolution of catalytic efficiency and thermostability of lipase. Two promising mutants M11 and M21 with excellent properties exhibited great potential for practical applications for in biodiesel production.
Long-stay ICU patients with frailty: mortality and recovery outcomes at 6 months
Authors: Wozniak Hannah , Beckmann Tal Sarah , Dos Santos Rocha Andre , Pugin Jérôme , Heidegger Claudia-Paula , Cereghetti Sara
Published: February 2024

Background

Prolonged intensive care unit (ICU) stay is associated with physical, cognitive, and psychological disabilities. The impact of baseline frailty on long-stay ICU patients remains uncertain. This study aims to investigate how baseline frailty influences mortality and post-ICU disability 6 months after critical illness in long-stay ICU patients.

Methods

In this retrospective cohort study, we assessed patients hospitalized for ≥ 7 days in the ICU between May 2018 and May 2021, following them for up to 6 months or until death. Based on the Clinical Frailty Scale (CFS) at ICU admissions, patients were categorized as frail (CFS ≥ 5), pre-frail (CFS 3–4) and non-frail (CFS 1–2). Kaplan–Meier curves and a multivariate Cox model were used to examine the association between frailty and mortality. At the 6 month follow-up, we assessed psychological, physical, cognitive outcomes, and health-related quality of life (QoL) using descriptive statistics and linear regressions.

Results

We enrolled 531 patients, of which 178 (33.6%) were frail, 200 (37.6%) pre-frail and 153 (28.8%) non-frail. Frail patients were older, had more comorbidities, and greater disease severity at ICU admission. At 6 months, frail patients presented higher mortality rates than pre-frail and non-frail patients (34.3% (61/178) vs. 21% (42/200) vs. 13.1% (20/153) respectively, p < 0.01). The rate of withdrawing or withholding of care did not differ significantly between the groups. Compared with CFS 1–2, the adjusted hazard ratios of death at 6 months were 1.7 (95% CI 0.9–2.9) for CFS 3–4 and 2.9 (95% CI 1.7–4.9) for CFS ≥ 5. At 6 months, 192 patients were seen at a follow-up consultation. In multivariate linear regressions, CFS ≥ 5 was associated with poorer physical health-related QoL, but not with poorer mental health-related QoL, compared with CFS 1–2.

Conclusion

Frailty is associated with increased mortality and poorer physical health-related QoL in long-stay ICU patients at 6 months. The admission CFS can help inform patients and families about the complexities of survivorship during a prolonged ICU stay.
RETRACTED ARTICLE: Network security threat detection technology based on EPSO-BP algorithm
Authors: Lan Zhu
Published: February 2024

With the development of Internet technology, the large number of network nodes and dynamic structure makes network security detection more complex, which requires the use of a multi-layer feedforward neural network to build a security threat detection model to improve network security protection. Therefore, the entropy model is adopted to optimize the particle swarm algorithm to decode particles, and then the single-peak and multi-peak functions are used to test and compare the particle entropy and fitness values to optimize the weights and thresholds in the multi-layer feedforward neural network. Finally, Suspicious Network Event Recognition Dataset discovered by data mining is sampled and applied to the entropy model particle swarm optimization for training. The test results show that there are four functions for the optimal mean and standard deviation in this algorithm, with values of 5.712e − 02, 4.805e − 02, 4.914e − 01, 1.066e − 01, 1.577e − 01, 1.343e − 01, and 2.089e + 01, 5.926, respectively. Overall, the algorithm proposed in the study is the best. Finally, the detection rate of attack types is calculated. The multi-layer feedforward neural network algorithm is 83.80%, the particle swarm optimization neural network algorithm is 91.00%, and the entropy model particle swarm optimization algorithm is 95.00%. The experiment shows that the research model has high accuracy in detecting network security threats, which can provide technical support and theoretical assistance for network security protection.
Effect of capsular tension ring on the refractive outcomes of patients with extreme high axial myopia after phacoemulsification
Authors: Zhao Hui-Ying , Zhang Jing-Shang , Li Meng , Chen Dong-Jun , Wan Xiu-Hua
Published: February 2024

Purpose

The aim of the study is to evaluate the effect of capsular tension ring (CTR) implantation following cataract surgery on the refractive outcomes of patients with extreme high axial myopia.

Methods

Sixty eyes (with an axial length of ≥26 mm) were retrospectively reviewed and classified into two groups: CTR group (n = 30), which underwent CTR implantation following phacoemulsification, and control group (n = 30), which did not undergo CTR implantation. Intraocular lens (IOL) calculation was performed using Barrett Universal II (UII), Haigis, and SRK/T formulas. The refractive prediction error (PE) was calculated by subtracting the postoperative refraction from predicted refraction. The mean PE (MPE), mean absolute error (MAE), and percentages of eyes that had a PE of ±0.25, ±0.50, ±1.00, or ±2.00 diopters (D) were calculated and compared.

Results

No significant differences were observed in PE between the two groups. The Barrett UII formula revealed a lower AE in the CTR group than in the control group (p = 0.015) and a lower AE than the other two formulas (p = 0.0000) in both groups. The Barrett UII formula achieved the highest percentage of eyes with a PE of ±0.25 D (66.67%).

Conclusions

The refractive outcomes were more accurate in eyes with CTR implantation than in those with routine phacoemulsification based on the Barrett UII formula. The Barrett UII formula was recommended as the appropriate formula when planning CTR implantation in high myopia.
Love after lockup: examining the role of marriage, social status, and financial stress among formerly incarcerated individuals
Authors: Bather Jemar R. , McSorley Anna-Michelle Marie , Rhodes-Bratton Brennan , Cuevas Adolfo G. , Rouhani Saba , Nafiu Ridwan T. , Harris Adrian , Goodman Melody S.
Published: February 2024

Background

Upon reintegration into society, formerly incarcerated individuals (FIIs) experience chronic financial stress due to prolonged unemployment, strained social relationships, and financial obligations. This study examined whether marriage and perceived social status can mitigate financial stress, which is deleterious to the well-being of FIIs. We also assessed whether sociodemographic factors influenced financial stress across marital status. We used cross-sectional data from 588 FIIs, collected in the 2023 Survey of Racism and Public Health. The financial stress outcome (Cronbach’s $$\mathrm{\alpha }$$
α
= 0.86) comprised of five constructs: psychological distress, financial anxiety, job insecurity, life satisfaction, and financial well-being. Independent variables included marital and social status, age, race/ethnicity, gender identity, educational attainment, employment status, and number of dependents. Multivariable models tested whether financial stress levels differed by marital and perceived social status (individual and interaction effects). Stratified multivariable models assessed whether social status and sociodemographic associations varied by marital status.

Results

We found that being married/living with a partner (M/LWP, b = -5.2) or having higher social status (b = -2.4) were protective against financial stress. Additionally, the social status effect was more protective among divorced, separated, or widowed participants (b = -2.5) compared to never married (NM, b = -2.2) and M/LWP (b = -1.7) participants. Lower financial stress correlated with Black race and older age, with the age effect being more pronounced among M/LWP participants (b = -9.7) compared to NM participants (b = -7.3). Higher financial stress was associated with woman gender identity (overall sample b = 2.9, NM sample b = 5.1), higher education (M/LWP sample b = 4.4), and having two or more dependents (overall sample b = 2.3, M/LWP sample b = 3.4).

Conclusions

We provide novel insights into the interrelationship between marriage, perceived social status, and financial stress among FIIs. Our findings indicate the need for policies and programs which may target the family unit, and not only the individual, to help alleviate the financial burden of FIIs. Finally, programs that offer legal aid to assist in expungement or sealing of criminal records or those offering opportunities for community volunteer work in exchange for vouchers specific to legal debt among FIIs could serve to reduce financial stress and improve social standing.
Achievement of adequate nutrition contributes to maintaining the skeletal muscle area in patients with sepsis undergoing early mobilization: a retrospective observational study
Authors: Abe Ryo , Shimazui Takashi , Sugo Masayuki , Ogawa Akihiro , Namekawa Michito , Kitamura Nobuya , Kido Satoshi
Published: February 2024

Background

The onset of muscle loss in critically ill patients, known as intensive care unit-acquired weakness (ICU-AW), worsens their outcomes. Preventing muscle loss, which begins in the early phase of critical illness, is crucial in patient care. Adequate nutrition management may contribute to maintaining muscles; however, its evidence in patients with sepsis is insufficient. This study aimed to analyze the association between energy achievement rate in the first 7-days of critical care and muscle area changes evaluated by computed tomography (CT).

Methods

This was a retrospective observational study. Patients with sepsis admitted to the intensive care (ICU) of a tertiary care hospital in Japan were included. They were divided into three groups according to tertiles of the first 7-day energy achievement rate calculated using administered energy doses and basement energy expenditure. Skeletal muscle area (SMA) and changes in SMA were determined by CT on ICU admission and within days 7–10 of ICU admission. SMA maintenance was defined as SMA change ≥ 100%. Logistic regression analyses were performed to analyze the association of energy achievement rate with SMA changes (primary outcome) and in-hospital 28-day mortality (secondary outcome).

Results

Patients (n = 93) were classified into low, middle, and high groups according to their 7-day energy achievement rate (median rates, 16.8%, 38.8%, and 73.4%, respectively). The CT scans showed that SMA decreased between the CT scans in the low and middle groups, whereas it was maintained in the high group (median changes, -8.5%, -11.7%, and 2.8%, respectively). Univariate and multivariate logistic regression analyses showed that high energy achievement rate was significantly associated with SMA maintenance (reference, middle energy achieved group; univariate, odds ratio [95% confidence interval] 6.23 [2.04–19.10], P = 0.0013; multivariate, odds ratio [95% confidence interval] 5.92 [1.90–18.40], P = 0.0021). There was no significant difference in the association between energy achievement rate and mortality among the three groups.

Conclusions

Our study found that a fulfillment of energy achievement in the first 7 days of hospitalization was associated with maintenance of muscle area. Thus, satisfying adequate energy should be considered even in patients with sepsis.
Sustaining connections: feasibility and impact of long-term virtual patient engagement
Authors: Stefanik-Guizlo Kelsey , Allen Claire , Brush Sarah , Mogk Jessica , Canada Starette , Peck Marina , Ramos Kathryn , Volpe Karen , Lozano Paula
Published: February 2024

Background

Virtual patient engagement has become more common in recent years. Emerging research suggests virtual engagement can increase accessibility for patients managing long-term health conditions and those living in larger geographic areas, but it can also be challenging to establish relationships and maintain engagement over time. Little is known about virtual engagement lasting more than two years, nor about the specific contributions of patients to virtual engagement projects. Here we describe a project where virtual engagement was sustained over a long period of time (3.5 years), measure patients’ contributions to the work, and describe the facilitators and challenges of the project using the Valuing All Voices (VAV) patient engagement framework.

Methods

Five researchers recruited four patient partners living with persistent pain to work together virtually on a project to improve care for others with long-term pain. Researchers documented engagement activities and patient partner contributions and categorized them using Carman et al.’s 3 types of engagement. They also collected data via semi-structured group interviews with patient partners about the facilitators and challenges of the project using the VAV framework.

Results

In 3.5 years, patient partners contributed 487 h to the project, averaging 3.0 h per month, and participated in 40 meetings. They contributed to 17 products for patients, health care teams, and researchers. Most products (12 of 17) were created using the more in-depth engagement approaches of involvement or partnership and shared leadership. The group identified facilitators of the project across the five VAV domains of relationship-building, trust, understanding & acceptance, education & communication, and self-awareness, as well as some specific challenges such as keeping track of products across virtual platforms and managing the high volume of project information.

Conclusions

Long-term virtual patient engagement is feasible and can use more in-depth engagement approaches. Additionally, it can result in substantial contributions from patients in terms of time, effort, and products. These findings can inform future long-term virtual patient engagement efforts and provide insight into how researchers can structure their activities to encourage and maintain deep engagement over time.
Associations between simultaneous use of alcohol and cannabis and cannabis-related problems in 2014–2016: evidence from the Washington panel survey
Authors: Zhu Yachen , Ye Yu , Greenfield Thomas K. , Kerr William C.
Published: February 2024

Background

To address the research question of how simultaneous users of alcohol and cannabis differ from concurrent users in risk of cannabis use problems after the recreational marijuana legalization in Washington State.

Methods

We used generalized estimating equations with a Poisson distribution to analyze the association between simultaneous use of alcohol and marijuana (SAM) and cannabis-related problems compared to concurrent use. The data is a longitudinal sample of drinkers and cannabis users (n = 257, 47% female) aged 18 years and older from Washington State in 2014–2016. We adjusted for survey weights to account for differential probability of selection and response rates. The primary outcome is the past-six-month CUDIT problem subscale (ranging from 0 to 28), which is the total score for seven CUDIT problem items, after excluding the three items that covered marijuana use frequency. Covariates include marijuana use frequency (daily/near daily use, regular use, or infrequent use), marijuana daily quantity, alcohol daily volume, panel survey cycle, medical marijuana recommendation, driving time to nearest marijuana outlet, age of marijuana use onset, and other demographics.

Results

After adjusting for covariates, we found that compared to concurrent use, SAM was significantly positively associated with CUDIT problem subscale (IRR = 1.68, 95% CI: 1.25–2.27, p < 0.001); daily/near daily use of marijuana was strongly significantly associated with CUDIT problem subscale compared with infrequent use (IRR = 5.1, 2.71–9.57, p < 0.001) or regular use (IRR = 3.05, 1.91–4.85, p < 0.001). Secondary analyses using CUDIT total score as the outcome also showed a significant positive association with SAM compared to concurrent use (IRR = 1.17, 1.02–1.34, p < 0.05).

Conclusions

This study highlighted the importance of SAM, in addition to cannabis use frequency for predicting cannabis-related problems.
Emperor Qianlong's Literary Aggrandizement in the Eighteenth Century
Authors: Zinan Yan
Published: February 2024

Generally disfavored from a modern aesthetic perspective, Emperor Qianlong's poetry was systematically aggrandized in the eighteenth century. Through commentaries on his own work, Qianlong managed to amplify his voice, especially as he adopted textual and evidential research to establish authority over the literary field. Copies of his poems were creatively produced and circulated through various official channels to reach the largest audience. During his reign, Qianlong's writings were elevated to a high position by himself and his officials. However, this elevation was not reflected in the compilation of the Complete Library of the Four Treasuries because the emperor was more concerned about protecting his impartial image as a Han Chinese cultural arbiter.
Early Versus Late Drainage Removal in Patients Who Underwent Pancreaticoduodenectomy: A Comprehensive Systematic Review and Meta-analysis of Randomized Controlled Trials Using Trial Sequential Analysis
Authors: Ricci Claudio , Grego Davide Giovanni , Alberici Laura , Ingaldi Carlo , Togni Stefano , De Dona Ermenegilda , Casadei Riccardo
Published: February 2024

Background

The superiority of early drain removal (EDR) versus late (LDR) after pancreaticoduodenectomy (PD) has been demonstrated only in RCTs.

Methods

A meta-analysis was conducted using a random-effects model and trial sequential analysis. The critical endpoints were morbidity, redrainage, relaparotomy, and postoperative pancreatic fistula (CR-POPF). Hemorrhage (PPH), delayed gastric emptying (DGE), length of stay (LOS), and readmission rates were also evaluated. Risk ratios (RRs) and mean differences (MDs) with a 95% confidence interval (CI) were calculated. Type I and type II errors were excluded, comparing the accrued sample size (ASS) with the required sample size (RIS). When RIS is superior to ASS, type I or II errors can be hypothesized.

Results

ASS was 632 for all endpoints except DGE and PPH (557 patients). The major morbidity (RR 0.55; 95% CI 0.32–0.97) was lower in the EDR group. The CR-POPF rate was lower in the EDR than in the LDR group (RR 0.50), but this difference is not statistically significant (95% CI 0.24–1.03). The RIS to confirm or exclude these results can be reached by randomizing 5959 patients. The need for percutaneous drainage, relaparotomy, PPH, DGE, and readmission rates was similar. The related RISs were higher than ASS, and type II errors cannot be excluded. LOS was shorter in the EDR than the LDR group (MD − 2.25; 95% CI − 3.23 to − 1.28). The RIS was 567, and type I errors can be excluded.

Conclusions

EDR, compared with LDR, is associated with lower major morbidity and shorter LOS.
Software Effort Estimation using Machine Learning Algorithms
Authors: Lavingia Kruti , Patel Raj , Patel Vivek , Lavingia Ami
Published: February 2024

Effort estimation is a crucial aspect of software development, as it helps project managers plan, control, and schedule the development of software systems. This research study compares various machine learning techniques for estimating effort in software development, focusing on the most widely used and recent methods. The paper begins by highlighting the significance of effort estimation and its associated difficulties. It then presents a comprehensive overview of the different categories of effort estimation techniques, including algorithmic, model-based, and expert-based methods. The study concludes by comparing methods for a given software development project. Random Forest Regression algorithm performs well on the given dataset tested along with various Regression algorithms, including Support Vector, Linear, and Decision Tree Regression. Additionally, the research identifies areas for future investigation in software effort estimation, including the requirement for more accurate and reliable methods and the need to address the inherent complexity and uncertainty in software development projects. This paper provides a comprehensive examination of the current state-of-the-art in software effort estimation, serving as a resource for researchers in the field of software engineering.
Interface Control and Status Monitoring of Electronic Information Equipment based on Nonlinear Data Encryption
Authors: Yan Min , Zhang Hua
Published: February 2024

An advanced electronic information equipment interface control and status monitoring system is proposed to ensure the fairness, objectivity, and security of information while identifying responsibility for traffic accidents. Through an in-depth analysis of the system's security requirements and the current landscape of information security technology, a robust security strategy is developed for each crucial system stage. A PC-based platform is developed for efficient data acquisition, secure processing, reliable transmission, and fortified storage, focusing on implementing nonlinear data encryption methods. Performance evaluation of the system involved rigorous testing using files ranging from 3MB to 10MB. The results of the proposed system revealed a significant improvement in the system's overall speed and efficiency, showcasing an average performance enhancement of one quarter compared to the original platform. The proposed system demonstrated an impressive 15% to 30% increase in processing speed, establishing its capability to ensure data integrity protection during information transmission, facilitate accurate identification of data recording equipment post-accident, and safeguard the security of stored data. The developed electronic information equipment interface control and status monitoring system effectively addresses critical challenges associated with ensuring data integrity and security in traffic accident investigations.
Improving the Efficiency and Reliability of Renewable Energy Systems
Authors: Chen Xing , Huang Dingguo , Ren Qingchun , Yang Yong , Yuan Ye
Published: February 2024

The implications of relevant sustainable practices have reflected the scholastic features to improve the environmental resources. The study highlights the importance of conservation of environment and power system in search of proven solutions to improve the penetration level. The need for flexibility has signified the special characteristics that are conventional in increasing the integrity of renewable resources. The ideologies have global trends have integrated the cost of affectivity with the growing applications of power projects. The architecture of wind and solar energy has touched successful benchmarks with respect to the real world implications. The conceptual practices help in initializing the practices towards biomass as well as determining the impact of renewable energy on wind and solar power energy in a significant manner. In addition to that, the applications of solar or photovoltaic cell have been mentioned in the study which has greater significance. The ideas based on the emission of greenhouse gases have been evaluated in the study that shows the after effects as well. The use of passive solar energy and active solar energy has clearly discussed the concept of sustainability and the process of administering towards various climatic conditions. Lastly, the impact of renewable resources on social, environmental, technical and economic aspects has verified the relevant practice of sustainability.
Research on the Design of Integrated Energy Management and Optimization Control Systems for Novel Power Systems
Authors: Yang Zhiqian , Wu Xianyou , Chen Qiuhua , Aisikaer  , Lv Liangnian , Wu Lei
Published: February 2024

This research paper is determining the impact of integrated energy management and optimization control for Novel power systems. Research objectives have been made based on integrating power system for reducing power consumption based on optimization parameters. Optimal control is mainly dealing with control law by finding out a given system and delivering certain criteria for achieving goals. There are mainly three parts for problem optimization purposes those are included decision, constraints and objective functions. Four different objectives has been made those are mainly discussed about the importance of the power systems regarding integrated management system. There are various factors that are affecting optimizations including the role of the multigrain recursion, global convergence, properties of the optimization model and local convergence. Along with this, the optimization control system has been played a crucial role for the power systems development purposes. Research has been based on the effective design of energy management for power systems. The primary application for the optimization techniques is based on the storage system, electromagnetic-based design and mapping design for the microwave structure. The rate of unsustainable energy management is increasing and sustainable energy management system is decreasing. The conclusion has been based on the significance of the optimization control for the power systems.
Stability Study of New Power System Based On Multi-Intelligent Body Collaboration
Authors: Wu Xianyou , Yang Zhiqian , Du Xin , Lv Liangnian , Aisikaer  , Yang Yanchen
Published: February 2024

Developing, implementing, and maintaining a multi-intelligent body collaboration system necessitates significant investments in finances, time, and expertise. While multi-intelligent body collaboration has the potential to enhance power system stability significantly, it also comes with challenges related to interoperability, security, system complexity, and resource allocation. Resource allocation and training costs can be substantial. Addressing these challenges is crucial to harnessing the full benefits of this approach and ensuring the reliable and efficient operation of power systems. Effective communication and coordination strategies among intelligent agents are integral to maintaining power system stability. Timely information exchange, load balancing, disturbance management, and the integration of AI contribute to a more resilient and adaptive energy grid. As technology advances, refining these strategies will be essential to meet the growing demands of an ever-evolving power landscape. As technology marches forward, it becomes increasingly evident that the refinement of these strategies is paramount. The dynamism of the power landscape, driven by technological advancements and evolving needs, necessitates an agile and adaptable power system. The fusion of multi-intelligent bodies and modern technology stands as a testament to our collective pursuit of a more reliable, efficient, and sustainable energy future. In this ever-evolving landscape, the innovation and enhancement of these strategies are our compass, guiding us toward a brighter and more efficient future.
Study on Grid-Connected Power Quality Improvement of Wind Farms Based on Repetitive Controller
Authors: Zhu Minjie , Lv Liangnian , Le Xubo , Aisikaer  , Li Haibo , Gao Yucheng
Published: February 2024

The project highlights the wind energy and the process followed in the wind farms in order to generate the energy by using wind power and wind capacity as well. Moreover, it has been observed that wind energy is also considered one of the most effective electrical energy sources. The application of wind energy can be beneficial for different aspects of the business sectors of different countries across the globe and this is possible because of its cost-effectiveness. Furthermore, this study encompasses the strategies employed within wind farms to preserve and efficiently harness wind power for the generation of electrical energy. Notably, the project delineates the utilization of a diverse array of instruments, each instrumental in the conversion of wind power into valuable wind energy. Beyond the realm of technology, wind farms grapple with a spectrum of formidable challenges, stemming from the inherently capricious nature of wind. In addition, various issues concerning power quality and the stability of the power system have also been identified within these wind farms. To ameliorate these multifaceted challenges, the project introduces a range of meticulous control measures for implementation.
Radiogenomics in Oncology
Authors: V L Sowmya , Malakreddy A Bharathi , Natarajan Santhi
Published: February 2024

The emergence of artificial intelligence in the digital era has brought about a significant transformation in the field of clinical decision support systems. The advent of technological advancements has led to the development of novel data-driven analytical algorithms, hence greatly augmenting human capacity to process information. The field of cancer radiogenomics presents a promising area within the realm of precision medicine. The objective of our research is to enhance our understanding of the genetic factors that contribute to the formation of tumors. This will be achieved by integrating extensive radiomics features extracted from medical imaging, genetic data obtained from clinical-epidemiological sources, and insights derived from high-throughput sequencing using mathematical modelling techniques. The aim of integrating radiomics and genomes is to gain a deeper understanding of the complex mechanisms behind cancer growth. The primary aim is to develop novel, empirically supported methodologies for the identification, prediction, and individualized therapeutic strategies for cancer, utilizing the acquired understanding. This comprehensive review aims to provide an overview of the existing body of research on the applications of radiogenomics, with a specific focus on solid malignancies. Additionally, we will examine the barriers that are now preventing the widespread integration of radiomics into therapeutic contexts.
Research on Speech Communication Enhancement of English Web-based Learning Platform based on Human-computer Intelligent Interaction
Authors: Gu Yufang
Published: February 2024

This study presents a novel web-based learning platform that leverages human-computer intelligent interaction to enhance English communication skills. The platform integrates cutting-edge technologies to create an immersive learning experience, combining natural language processing, speech recognition, and interactive exercises. Learners engage in real-time conversations with virtual tutors, receive personalized feedback, and access a vast repository of educational resources. The platform not only facilitates language acquisition but also encourages self-paced learning, making it a valuable tool for both educators and students. By harnessing the power of artificial intelligence, this web-based platform represents a significant advancement in the realm of English language education. To overcome these issues this paper proposed SVM with an improved satin Bower bird optimization algorithm (SVM-ISBBO). SVM-ISBBO uses fog computing services that minimize the latency and speeds up the process, effectively handling huge wearable devices. In this proposed work SVM-ISBBO monitors the students communication, vocal parameters, blood pressure, etc, and these values are obtained from wearable sensor devices and their notifications are sent back to teachers. Teachers diagnosed the student information and sent back the alert notifications to the students for taking proper medications. All this information is stored in fog-based cloud storage in a secure manner. The accuracy rate of KNN got 78.56%, NB got 81.74%, SVM got 85.15% and the proposed work of SVM-ISBBO got 92.34%.
Intelligent Detection and Analysis of Software Vulnerabilities based on Encryption Algorithms and Feature Extraction
Authors: Li Heng , Li Xinqiang , Wei Hongchang
Published: February 2024

Implement status detection of ship software, identify the source of faults in problematic software, and release new software versions. Based on the above requirements, the author regards the detection and control of ship software status as the core research content. Based on the actual operating environment of ship software, the functional requirements of software status detection were studied and analyzed, and a set of ship software status detection was designed and implemented, a software inspection and maintenance platform that integrates ship software operation and maintenance, as well as ship software version release and update. The author conducted practical verification of the SM3 and SM2 hybrid encryption algorithm and selected software on the ship for detection. After analyzing the experimental results, it has been proven that using a hybrid algorithm for encryption and decryption, the server can accurately obtain software information on the ship's platform, detect the software status on the ship, and locate specific problem files. For software that does not meet the standard status, the server can accurately transmit software information to the ``component integration framework'' and put the component in a ``prohibited'' scheduling state. After the server repairs the problematic software, the detection results of the software change and display as legal, while the software is in the ``allowed'' scheduling state in the ``component integration framework''.
A Method for Specifying Yoga Poses Based on Deep Learning, Utilizing OpenCV and Media Pipe Technologies
Authors: Anuradha T , Krishnamoorthy N. , Kumar C.S. Pavan , Prasad L.V. Narasimha , Chunduru Anilkumar , Moorthy Usha
Published: February 2024

Yoga is a years discipline that calls for physical postures, mental focus, and deep breathing. Yoga practice can enhance stamina, power, serenity, flexibility, and well‐being. Yoga is currently a well-liked type of exercise worldwide. The foundation of yoga is good posture. Even though yoga offers many health advantages, poor posture can lead to issues including muscle sprains and pains. People have become more interested in working online than in person during the last few years. People who are accustomed to internet life and find it difficult to find the time to visit yoga studios benefit from our strategy. Using the web cameras in our system, the model categorizes the yoga poses, and the image is used as input. However, the media pipe library first skeletonizes that image. Utilizing a variety of deep learning models, the input obtained from the yoga postures is improved to improve the asana. The algorithms like VGG16 (Visual Geometric Group), VGG19, Convo2d, CNN.
Application of Control Algorithm in the Design of Automatic Crimping Device for Connecting Pipe and Ground Wire
Authors: Sheng Congbing , Xing Peng , Cai Xiuzhong , Shao Zheng
Published: February 2024

Due to the low effectiveness and poor quality of manual crimping of grounding wires, the author proposes the design of an automatic crimping device for connecting tube grounding wires based on intelligent fully automatic technology. The device consists of a microcontroller, an upper computer control interface, an electric push rod, an infrared sensor, a pressure transmitter, and other devices. The staff used the upper computer monitoring interface to set the relevant parameters for grounding wire crimping, and used X-ray digital imaging technology to measure the crimping size of the grounding wire. The size met the set parameter conditions. Through the PID control algorithm in the microcontroller, the stepper motor was controlled to push the clamp to move, completing the automatic crimping of the grounding wire. The X-ray detection method was introduced to detect the quality of the grounding wire after the crimping was completed. The experimental results show that the average deviation between the measured crimping size of the grounding wire and the actual measurement size by the automatic crimping device is only 0.06 mm, indicating that its measurement results are accurate; The success rate of crimping exceeds 95%. The above experimental results verify that the designed crimping device has high stability and reliability, and good quality detection effect.
Network Traffic Monitoring and Real-time Risk Warning based on Static Baseline Algorithm
Authors: Wu Zhaoli , Liu Junwei
Published: February 2024

With the rapid growth of network traffic, in order to monitor network traffic, the author proposes a baseline based traffic inspection method. The main objective is to develop a global system for identifying malicious traffic, rather than a precise method for detecting the types of worms produced by malicious traffic. Although traffic is caused by the causes, network administrators can use this international search technique to detect malicious traffic data. The system based approach mainly includes designing time based on the traditional traffic model, detecting various equipments and network traffic process, and configuring the traffic flow according to each time frame. This method uses Cisco's NetFlow Collector, a NetFlow Collector (NFC), to collect raw NetFlow data transmitted by the device through UDP every 5 minutes. the Then, three-dimensional data such as communication port, communication time, and traffic flow (bytes or packets) is used to filter, remove the different values, calculate the base values, and compare the real-time results with the base values to check the traffic defects in the current network. If there are differences between the monitoring data and the system configuration at the same time, the system will issue an abnormal warning, and as time accumulates, the alarm level will gradually escalate.
Design of Computer Information Management System Based on Machine Learning Algorithms
Authors: Li Yan
Published: February 2024

In order to improve the efficiency of office automation, regulate work frequency, and improve office efficiency, this paper presents a computer information management system design based on machine learning technology. Firstly, the basic design principles of computer information management systems are analyzed, and secondly, risk prediction is studied. The risk of computer information management systems is caused by the cross influence of different risk factor indicators, and has linear and nonlinear characteristics. Using a single prediction model cannot obtain accurate prediction results. Therefore, the risk prediction method for computer information management based on machine learning technology. The risk prediction method is established by using Analytic Hierarchy Method in machine learning algorithms, and the historical data is collected according to the index system. The weight of the initial prediction is determined by the combination of subjective and objective weight; In machine learning algorithms, risk prediction and benefit prediction are used as input and output methods for cloud machine learning. Through training and training, a risk prediction model is established to obtain higher prediction efficiency. The simulation results show that the prediction accuracy of this method is 95.5%, which can estimate the hazard existing in computer information management and improve the method.
The Effects of Integrated Feedback based on AWE on English Writting of Chinese EFL Learners
Authors: Liu Mei , Shao Changzhong
Published: February 2024

Through a two-semester experiment on the English writing of 64 Chinese EFL learners, this study examines the effects of three types web-based feedback (automatic feedback (AF), automatic feedback with teacher feedback (TF), automatic feedback with peer feedback (PF)) based on Pigai website. The results show that all the three modes of feedback can promote the writing of the English as Foreign Language (EFL) learners with different English proficiency ((high level: F = 2.672, P = .132; low level: F = .388, P = .766). The results also reveal that there is a significant difference in the high-level group between the automatic feedback + peer feedback group and the automatic feedback group (I - J = - 6.636, P = .000) as well as between the automatic feedback + teacher feedback group and the automatic feedback group (I - J = - 6.220, P = .001; I - J = - 5. 100, P =. 001), which indicate that automatic feedback + manual feedback (PF+TF) can promote the improvement of high-level learners’ English writing more than single AF. In the low-level group, between the AF + PF group and the AF group (I - J = -1.221, P = .925) and between the AF +TF group and the AF + PF group (I - J = 6.227, P =. 097). There is no significant difference, but there is a significant difference between the AF group and the AF + TF group (I - J = - 5.122, P =. 032), indicating that AF + TF is of great help in improving the English writing of low-level English learners.
A Study of Blockchain and Machine Learning-Enabled IoT Security in Time-Delayed Neural Network Vocal Pattern Recognition to Improve Web-Based Vocal Teaching
Authors: Long Kaiyi
Published: February 2024

With the development of information technology, online vocal teaching is becoming more and more popular, but the sound quality of teaching is also becoming more and more demanding. As online vocal instruction becomes more popular, the need for high-quality sound in these digital environments becomes more critical. This research tackles the problem of improving sound quality in real-time vocal teaching by integrating advanced technologies such as Blockchain and Machine Learning within the Internet of Things (IoT) security framework. We created a vocal recognition model using Time-Delay Neural Network (TDNN) and improved it with Generated Feature Vector (GFV). This integration yields a strong GTDNN vocal recognition system that is specifically designed to secure and optimize web-based vocal teaching. Our experiments show that GTDNN outperforms traditional TDNN and i-vector methods in feature vector extraction, adapting well to different speech environments. In various speech settings, GTDNN's Error Rates (EERs) are impressively low at 11.3%, 12.0%, 4.9%, 6.2%, and 6.1%, indicating superior performance over comparison models. GTDNN has an EER of 9.6% for short-duration speech and 2.3% for long-duration speech. Furthermore, the GTDNN system achieves an overall pass rate of 94% for target speech and an impressive rejection rate for non-target speech, ensuring high accuracy in a variety of speech environments.