Set Of Values Research Articles

Unveiling optimal half-cell potentials in RCC slabs through cutting-edge ANFIS, ANN and genetic algorithm integration

PurposeThe purpose of this study is to compare the prediction models for half-cell potential (HCP) of RCC slabs cathodically protected using pure magnesium anodes and subjected to chloride ingress.The models for HCP using 1,134 data set values based on experimentation are developed and compared using ANFIS, artificial neural network (ANN) and integrated ANN-GA algorithms.Design/methodology/approachIn this study, RCC slabs, 1000 mm × 1000 mm × 100 mm were cast. Five slabs were cast with 3.5% NaCl by weight of cement, and five more were cast without NaCl. The distance of the point under consideration from the anode in the x- and y-axes, temperature, relative humidity and age of the slab in days were the input parameters, while the HCP values with reference to the Standard Calomel Electrode were the output. Experimental values consisting of 80 HCP values per slab per day were collected for 270 days and were averaged for both cases to generate the prediction model.FindingsIn this study, the premise and consequent parameters are trained, validated and tested using ANFIS, ANN and by using ANN as fitness function of GA. The MAPE, RMSE and MAE of the ANFIS model were 24.57, 1702.601 and 871.762, respectively. Amongst the ANN algorithms, Levenberg−Marquardt (LM) algorithm outperforms the other methods, with an overall R-value of 0.983. GA with ANN as the objective function proves to be the best means for the development of prediction model.Originality/valueBased on the original experimental values, the performance of ANFIS, ANN and GA with ANN as objective function provides excellent results.

Environmental Constitutionalism in China: A Constitution without Constitutionalism?

Abstract There is a long tradition of constitutionalising environmental protection in the People's Republic of China ('China'). This is illustrated, for example, by the constitutionalisation of the need to construct ‘ecological civilisation’ – a set of values and development concepts included in 2018 as part of constitutional amendments. Yet, the Constitution of China is often described as a constitution without constitutionalism. This article examines the constitutional environmental provisions in China, as well as the underpinning constitutional theories, to demonstrate how China enjoys environmental constitutionalism. This version of constitutionalism, however, is absent of rights and overwhelmingly enforced through state-based approaches, which means that it is distinct from the rights-based and courts-centred versions of liberal constitutionalism. This study thus exemplifies how constitutional practices may adopt different formulations and environmental constitutionalism exists without being committed to liberal principles.

The Transmission of Values Specific to Midwifery and their Integration by Student Midwives

Québec midwives adhere to a set of values viewed as essential. These values set midwives apart from other obstetrics professionals and play an important role in the formation of their professional identity. This article explores whether these values are transmitted to student midwives. To achieve our research objectives, we presented 21 student midwives with scenarios where a client's behaviour corresponds only more or less to midwifery values (as defined by the regroupement Les sages-femmes du Québec). Student responses were analyzed according to their level of correspondence with these values. The results show that regardless of the scenario, first-year students are most likely to form negative attitudes about the behaviour submitted to their attention and, contrary to their more advanced sisters, they base interventions with a client less on the need to refrain from judgment. Starting with the second year, the students' evaluations of behaviour tend to be neutral. The difference observed between the first-year cohort and the others leads us to believe that the start of the mentoring stage is the pivotal moment of training.

The influence of different Cheek and lip retractors and emissivity on intraoral infrared thermography.

To assess the influence of two conventional and one adapted cheek and lip retractors and three emissivity setting values on intraoral infrared thermography (IT) temperature values. The sample was composed by 50 volunteers. Three cheek and lip retractors were tested: Group 1 - flex retractor (FR); Group 2 - FR adapted with Styrofoam; Group 3 - U-type retractor (UR) for cheek and lip. All thermograms were acquired using FLIR T650 infrared camera. A set of three thermograms in frontal norm were acquired for each lip and cheek retractor at 0.91, 0.96 and 0.98Ɛ, with an interval of 15 minutes between each set of images to avoid thermal interference. All images were assessed by two observers. The ROIs' mean temperature of the four upper incisors were recorded. Two-way ANOVA and Sidak posttest were used for data assessment with a significance level of 5%. Group 3 showed higher mean temperature than groups 1 and 2 at all emissivity settings for all assessed teeth (p < 0.05). 0.91Ɛ showed higher temperature than 0.96Ɛ and 0.98Ɛ for all assessed variables (p < 0.01). Contralateral teeth assessed using Group 3 at 0.91Ɛ showed statistical differences between each other (p < 0.05). No statistical difference was observed between contralateral teeth assessed using Group 1 and 2 at 0.96 and 0.98Ɛ (p > 0.05). The choice of cheek and lip retractor and emissivity setting can interfere on intraoral IT temperature values. U-type cheek and lip retractor and 0.91Ɛ setting should not be used for IT image acquisition when assessing dental tissues.

GA-BP neural network-based nonlinear regression model for machining errors of compressor blades

Given that blade machining errors can substantially degrade aeroengine performance and reliability, there is a critical imperative to implement stringent control over blade machining errors during the manufacturing process. Nevertheless, the prevailing complexity surrounding the numerous machining error types and their obfuscated interrelationships impedes the comprehensive control of blade profile errors. Consequently, unveiling the nonlinear relationships between the distinct machining errors represents a task of paramount importance. To uncover these nonlinear relationships, this work pioneers the application of factor analysis and Genetic Algorithm-optimized BP neural networks to enable nonlinear regression for diverse blade machining errors. Specifically, this paper first constructs an orthogonal factor analysis model to reduce the dimensionality of complex, high-dimensional blade machining error data and extract underlying correlations. This analysis reveals three distinct error groups, each dominated by a latent common factor. Building on these factor analysis outputs, GA-BP neural networks are then leveraged to perform nonlinear regression for intra-group errors. Guided by the Maximal Information Coefficients (MIC) between different errors, we identify control error types within each group to serve as network inputs, with other errors designated as outputs. To prevent overfitting and accelerate convergence of the neural network, Monte Carlo method is used to augment the limited raw error dataset. The augmented data trains the GA-BP network, establishing multivariate nonlinear models with control errors as independent variables and other errors as dependent variables. The model accuracy is validated by a separate validation set. The comparisons between the predicted and true values in the validation set reveal that the relative errors are around 5 %, indicating that the models achieve an accuracy of approximately 95 %. These results demonstrate the satisfactory performance of the established models. Overall, this work elucidates previously unclear relationships between distinct blade machining errors. These new insights establish the foundation for comprehensive error control and will directly benefit blade design, manufacturing, and performance.

Numerical Optimization of Variable Blank Holder Force Trajectories in Stamping Process for Multi-Defect Reduction.

An intelligent optimization technology was proposed to mitigate prevalent multi-defects, particularly failure, wrinkling, and springback in sheet metal forming. This method combined deep neural networks (DNNs), genetic algorithms (GAs), and Monte Carlo simulation (MCS), collectively as DNN-GA-MCS. Our primary aim was to determine intricate process parameters while elucidating the intricate relationship between processing methodologies and material properties. To achieve this goal, variable blank holder force (VBHF) trajectories were implemented into five sub-stroke steps, facilitating adjustments to the blank holder force via numerical simulations with an oil pan model. The Forming Limit Diagram (FLD) predicted by machine learning algorithms based on the Generalized Incremental Stress State Dependent Damage (GISSMO) model provided a robust framework for evaluating sheet failure dynamics during the stamping process. Numerical results confirmed significant improvements in formed quality: compared with the average value of training sets, the improvements of 18.89%, 13.59%, and 14.26% are achieved in failure, wrinkling, and springback; in the purposed two-segmented mode VBHF case application, the average value of three defects is improved by 12.62%, and the total summation of VBHF is reduced by 14.07%. Statistical methodologies grounded in material flow analysis were applied, accompanied by the proposal of distinctive optimization strategies for the die structure aimed at enhancing material flow efficiency. In conclusion, our advanced methodology exhibits considerable potential to improve sheet metal forming processes, highlighting its significant effect on defect reduction.

Predicting the mechanical properties of stainless steels using Artificial Neural Networks

Abstract Knowing the material properties is of a crucial importance when planning to manufacture some structure. That is true for the steel structures, as well. Thus, for the proper planning of a certain steel part or a structure production, one must be aware of the properties of the material, to be able to make a qualified decision, which material should be used. Considering that the manufacturing of steel products is constantly growing in various branches of industry and engineering, the problem of predicting the material properties, needed to satisfy the requirements for the certain part efficient and reliable functioning, becomes an imperative in the design process. A method of predicting four material properties of the two stainless steels, by use of the artificial neural network (ANN) is presented in this article. Those properties were predicted based on the particular steels’ known chemical compositions and the corresponding material properties available in the Cambridge Educational System EDU PACK 2010 software, using neural network module of MathWorks Matlab. The method was verified by comparing the values of the material properties predicted by this method to known values of properties for the two stainless steels, X5CrNi18-10 (AISI 304), X5CrNiMo17-12-2 (AISI 316). The difference between the two sets of values was below 5% and, in some cases, even negligible.

Verification of a simplified aneurysm dimensionless flow parameter to predict intracranial aneurysm rupture status.

Aneurysm number (An) is a novel prediction tool utilizing parameters of pulsatility index (PI) and aneurysm geometry. An has been shown to have the potential to differentiate intracranial aneurysm (IA) rupture status. The objective of this study is to investigate the feasibility and accuracy of An for IA rupture status prediction using Australian based clinical data. A retrospective study was conducted across three tertiary referral hospitals between November 2017 and November 2020 and all saccular IAs with known rupture status were included. Two sets of An values were calculated based on two sets of PI values previously reported in the literature. Five hundred and four IA cases were included in this study. The results demonstrated no significant difference between ruptured and unruptured status when using An ≥1 as the discriminator. Further analysis showed no strong correlation between An and IA subtypes. The area under the curve (AUC) indicated poor performance in predicting rupture status (AUC1 = 0.55 and AUC2 = 0.56). This study does not support An ≥1 as a reliable parameter to predict the rupture status of IAs based on a retrospective cohort. Although the concept of An is supported by hemodynamic aneurysm theory, further research is needed before it can be applied in the clinical setting. This study demonstrates that the novel prediction tool, An, proposed in 2020 is not reliable and that further research of this hemodynamic model is needed before it can be incorporated into the prediction of IA rupture status.

Why Professional Branding: What difference will it make for me (as Gen Z)?

This article discusses professional branding that is rooted in marketing aimed at helping professionals differentiate themselves from others through personal branding to project their uniqueness and related values. It streamlines the process behind creating a robust profile that enhances simple elements of a resume by providing distinctive information to corporations or target markets. Furthermore, the article highlights the two broad theoretical underpinnings of personal branding: marketing-based and self-presentation behaviors. Marketing-based definitions frame the individual as a product to be marketed, while self-presentation-based definitions emphasize the formation of a person's public persona through strategic relationship management. Additionally, the article portrays personal branding as a defined set of individual characteristics, attributes, values, and beliefs crafted into a narrative and imagery that establishes a competitive advantage by influencing the perceptions of a targeted audience. It concludes that professional branding is an effective personal tool for individual differentiation and advancement in a highly globalized employment environment, particularly for Gen Z individuals with Arab cultural backgrounds in STEAM professional fields.

A specific diagnostic metabolome signature in adult IgA vasculitis

IntroductionIgA vasculitis diagnosis relies primarily on clinical features and is confirmed by pathological findings. To date, there is no reliable noninvasive diagnostic biomarker.ObjectiveWe aimed to explore the baseline serum metabolome of adult patients with IgA vasculitis to identify potential diagnostic biomarkers.MethodsWe performed a study comparing the serum metabolome of patients with IgA vasculitis to that of patients with inflammatory condition, namely spondyloarthritis. Serum analyses were performed by high-performance liquid chromatography-mass spectrometry.ResultsFifty-five patients with IgA vasculitis and 77 controls with spondyloarthritis (age- and sex-matched) were included in this study. The median age of IgA vasculitis patients was 53 years. Two-thirds of patients were female (n = 32). At the time of vasculitis diagnosis, 100% of patients had skin involvement and 69% presented with glomerulonephritis (n = 38). Joint and digestive involvement were observed in 56% (n = 31) and 42% (n = 23) of patients. Four discriminative metabolites between the two groups were identified: 1-methyladenosine, L-glutamic acid, serotonin, and thymidine. The multivariate model built from the serum metabolomes of patients with IgA vasculitis and spondyloarthritis revealed an accuracy > 90%. As this model was significant according to the permutation test (p < 0.01), independent validation showed an excellent predictive value of the test set: sensitivity 98%; specificity 98%, positive predictive value 97% and negative predictive value 98%.ConclusionTo our knowledge, this study is the first to use the metabolomic approach for diagnostic purposes in adult IgA vasculitis, highlighting a specific diagnostic metabolome signature.

THE LIFE SKILLS OF OUTSTANDING INDEPENDENT READERS: A MULTIPLE CASE STUDY

The purpose of this multiple case study was to describe the five different cases of outstanding independent readers in the public secondary schools in Davao del Norte in terms of their life skills. The unique cases revolved around a campus journalist, a volleyball athlete, a student leader, a consistent honor student, and a student with autism spectrum. The cases were identified using maximum variation sampling, and in-depth interviews were employed to explore and gather data in this research. Salient findings were noted as to the experiences of outstanding independent readers which include early reading opportunities and support, sharing of reading abilities to other students, allocation of time for reading, and utilization of gadgets for reading. More so, their coping strategies were summarized in the following themes: enrichment of vocabulary, adoption of reading tactics, development of set of values for reading, and application of leadership skills. In the cross-case analysis of research data, all cases were generally similar. Notably, the only difference is that the student with autism preferred reading by himself unlike the other cases of students who viewed reading as a collaborative experience. It was realized that while cognitive capacities are essential in learning reading, socio-emotional aspects of outstanding readers such as their life skills must also be considered in schools. KEYWORDS: independent reading, life skills, public secondary schools, multiple case study, Philippines

Association between Doppler assessment and secondary cesarean delivery for intrapartum fetal compromise in small-for-gestational-age fetuses

PurposeTo elucidate the association between arterial and venous Doppler ultrasound parameters and the risk of secondary cesarean delivery for intrapartum fetal compromise (IFC) and neonatal acidosis in small-for-gestational-age (SGA) fetuses.MethodsThis single-center, prospective, blinded, cohort study included singleton pregnancies with an estimated fetal weight (EFW) < 10th centile above 36 gestational weeks. Upon study inclusion, all women underwent Doppler ultrasound, including umbilical artery (UA) pulsatility index (PI), middle cerebral artery (MCA) PI, fetal aortic isthmus (AoI) PI, umbilical vein blood flow (UVBF), and modified myocardial performance index (mod-MPI). Primary outcome was defined as secondary cesarean section due to IFC.ResultsIn total, 87 SGA pregnancies were included, 16% of which required a cesarean section for IFC. Those fetuses revealed lower UVBF corrected for abdominal circumference (AC) (5.2 (4.5–6.3) vs 7.2 (5.5–8.3), p = 0.001). There was no difference when comparing AoI PI, UA PI, ACM PI, or mod-MPI. No association was found for neonatal acidosis. After multivariate logistic regression, UVBF/AC remained independently associated with cesarean section due to IFC (aOR 0.61 [0.37; 0.91], p = 0.03) and yielded an area under the curve (AUC) of 0.78 (95% CI, 0.67–0.89). A cut-off value set at the 50th centile of UVBF/AC reached a sensitivity of 86% and specificity of 58% for the occurrence of cesarean section due to IFC (OR 8.1; 95% CI, 1.7–37.8, p = 0.003).ConclusionLow levels of umbilical vein blood flow (UVBF/AC) were associated with an increased risk among SGA fetuses to be delivered by cesarean section for IFC.

#3026 Uncovering the potential of HIF-PH inhibitors to treat renal anemia

Abstract Background and Aims Hypoxia-inducible factor prolyl hydroxylase enzyme inhibitors (HIF-PHis) are a novel class of agents that were developed for the treatment of renal anemia. The agents work by stabilizing the HIF complex and stimulating endogenous erythropoietin production. This research aims to gauge the potential utilization and impact of HIF-PHis based on the perspectives of nephrologists who are based in the EU5. Method Data were collected via an independent online survey of 204 nephrologists based in the EU5 (UK, Germany, Italy, France, and Spain) in November 2023. Results EU5 nephrologists report that most dialysis and CKD non-dialysis patients with renal anemia who are on ESA therapy have an optimal response to treatment; however, a substantial proportion of patients experience a suboptimal response to treatment and up to 13% of patients across dialysis modalities are classified as ESA hypo-responders. Regardless of their geographic location, EU5 nephrologists position HIF-PHis to offer the most value in the CKD non-dialysis patient setting, with a perceived high level of opportunity (80%) for roxadustat to improve renal anemia outcomes among non-dialysis patients. Not surprisingly, the perceived advantages of an oral agent over an injectable medication for the treatment of renal anemia are more substantial for dialysis patients who are receiving home therapies (peritoneal and home hemodialysis) compared to those receiving in-center hemodialysis treatment. EU5 nephrologists also tend to believe that roxadustat represents a high level (64%) of opportunity to improve renal anemia outcomes in dialysis patients, with similar ratings observed for vadadustat (63%) in the same patient population. Specific to the use of HIF-PH inhibitors in the CKD non-dialysis setting, nephrologists are most concerned about patient compliance (51%), followed by safety compared to ESAs in general and as they relate to cardiovascular events (36%). When considering the use of HIF-PH inhibitors in the dialysis setting, nephrologists express similar concerns compared to the non-dialysis setting, with patient compliance (50%) ranked as the top concern, followed by safety compared to ESAs (38%), and the potential for off target effects (33%). Most EU5 nephrologists agree that HIF-PH inhibitors represent a more physiologic way of treating anemia of CKD compared to ESAs (70%) and many would like gain more clinical experience with the class of medications (63%). Current roxadustat treatment rates in dialysis are slowly increasing across the EU5 region, with slightly higher adoption in peritoneal dialysis patients (10%) compared to in-center hemodialysis patients (8%). Meanwhile, their self-reported uptake of roxadustat in CKD non-dialysis patients is also increasing over time, with the largest increase observed in CKD Stage 4 patients (9%). There is little consensus among EU5 nephrologists regarding their expected time to trial vadadustat once it is available, as nearly the same proportion of prescribers project that they will prescribe the agent to their dialysis patients within three months (36%), six months (23%), and within one year (28%). Conclusion With HIF-PHis having more of a physiologic mechanism of action, oral administration, and a similar safety profile compared to ESAs, broader adoption of the novel agents will potentially help address unmet needs and improve patient outcomes in the treatment of renal anemia for both CKD non-dialysis and dialysis patients.

Ni, Cu, Zn, Pd, Ag and Cd Tetraphenylporphyrin Ab Initio Thermochemistry: Enthalpy of Formation of ZnTPP Revisited.

Groups 10-12 metalloporphyrins have been recognized for their numerous properties essential for the development of new sensing materials. In this work, accurate gas-phase enthalpies of formation, ΔfHm0(g,298.15), are predicted for the series of Ni, Cu, Zn, Pd, Ag, and Cd tetraphenylporphyrins (MTPPs) on the basis of the reaction-based Feller-Peterson-Dixon approach and high-level ab initio DLPNO-CCSD(T) calculations. Our recently developed automatic generator of the balanced chemical reactions was employed to reduce the bias of the theoretical ΔfHm0(g,298.15) toward a particular reaction. Theoretical ΔfHm0(g,298.15) for ZnTPP (227.0 ± 3.4 kcal mol-1) does not support the previously reported experimental value of 132 ± 2 kcal mol-1. The origin of the discrepancy probably lies in the experimental solid-state ΔfHm0(ZnTPP, cr,298.15) as it stems from our theoretical evaluations of the ΔfHm0(cr,298.15) values for the entire set of transition metal TPP complexes. The large discrepancy between experiment and theory also holds when different DFT functionals (ωB97M-V, PBE0-D4, and B3LYP-D4) paired with quadruple-ζ quality basis sets are used for the theoretical calculations. Experimental revisiting of the solid-state enthalpy of formation of ZnTPP and analogue measurements for other transition metal TPPs are needed to resolve the observed discrepancy. Based on the predicted enthalpies of formation of MTPPs, the relative energies of the metal-ligand bonding are evaluated and the trends are compared to those for the complexes of the unsubstituted porphyrin with the same set of metals derived in [Can. J. Chem., 2009, 87, 1063]. According to both studies, Pd complexes exhibit the strongest bonding, while the Cd species are the least stable metallocomplexes within the considered series.

Prediction of Protein-DNA Interface Hot Spots Based on Empirical Mode Decomposition and Machine Learning.

Protein-DNA complex interactivity plays a crucial role in biological activities such as gene expression, modification, replication and transcription. Understanding the physiological significance of protein-DNA binding interfacial hot spots, as well as the development of computational biology, depends on the precise identification of these regions. In this paper, a hot spot prediction method called EC-PDH is proposed. First, we extracted features of these hot spots' solid solvent-accessible surface area (ASA) and secondary structure, and then the mean, variance, energy and autocorrelation function values of the first three intrinsic modal components (IMFs) of these conventional features were extracted as new features via the empirical modal decomposition algorithm (EMD). A total of 218 dimensional features were obtained. For feature selection, we used the maximum correlation minimum redundancy sequence forward selection method (mRMR-SFS) to obtain an optimal 11-dimensional-feature subset. To address the issue of data imbalance, we used the SMOTE-Tomek algorithm to balance positive and negative samples and finally used cat gradient boosting (CatBoost) to construct our hot spot prediction model for protein-DNA binding interfaces. Our method performs well on the test set, with AUC, MCC and F1 score values of 0.847, 0.543 and 0.772, respectively. After a comparative evaluation, EC-PDH outperforms the existing state-of-the-art methods in identifying hot spots.

Generalized extreme value analysis of efficient evaluation of extreme values in random media criticality calculations

The uncertainty of fuel debris criticality can be estimated by Monte Carlo criticality calculations repeated over independent replicas of some properly modelled random medium. Incomplete randomized Weierstrass function (IRWF) is a modelling framework for such calculations. Under these approaches at hand, the theme of this paper is how to efficiently analyse extreme realizations of neutron effective multiplication factor (keff) over IRWF random media replicas. To this end, a new bounded amplification (BA) technique is applied to IRWF. The numerical results clearly indicate that the BA-applied IRWF reduces a required number of random media replicas at least by an order of magnitude. To rigorously validate this efficiency gain, generalized extreme value (GEV) analysis is applied to a data set of keff values obtained without applying BA. It turns out that the extreme values of these keff values follow the Weibull distribution. Therefore, the theory of GEV guarantees the existence of an upper limit for these keff values, and the actually computed upper limit is indeed smaller than or equal to the top two keff values obtained from an order-of-magnitude reduced number of BA-applied IRWF random media replicas. This means that the efficiency gain brought by BA has been confirmed by the GEV methodology. In addition, a method of rejecting spurious estimation values due to statistical fluctuation is demonstrated concerning the extreme value index in the GEV analysis.

Midwives' Belief in Normal Birth: The Canadian Survey of Maternity Care Providers’ Attitudes Toward Labour and Birth

Background: Midwifery has been integrated into the health care systems of over half of Canadian provinces and territories. While there are differences in legislation and payment mechanisms, the model of midwifery is fairly similar across the country. This study examined the similarities and differences among midwives' attitudestowardlabourandbirth. Inaddition,wecompareditemswhichrelatedtobeliefsaboutnormal birth between midwives and other care providers.Methods: A national cross-sectional survey was conducted comparing maternity care providers’ beliefs aboutchildbirthandintra-professionalvariationsinmidwives'attitudestowardsbirth. Therewere400 (54%) midwife respondents: 218 from Ontario, 75 from B.C, 53 from Quebec, 48 from the remaining regulated or pre-regulated provinces (six missed information for this field).Results: All midwives were critical of the routine use of interventions such as episiotomy, epidural analgesia andelectronicfetalmonitoring(EFM). Therewasstrongagreementaboutthesafetyofhomebirth,outof hospital birth centres and the importance of women's autonomy and decision-making in pregnancy and birth. However, some regional variations were identified. Quebec midwives were more opposed to epidural analgesia than BC and Ontario (p&lt;.001), and were more likely to believe that cesarean birth is more costly than vaginal birth (p=.005). Ontario midwives were most likely to believe that cesarean birth protects against urinary incontinence (p=.001), and sexual dysfunction (p=.002). Qualitative comments of midwives indicated a strong desire to reduce unnecessary medical intervention and to lower cesarean section rates.Conclusion: Canadian midwives share similar beliefs regarding place of birth, the routine use of episiotomy, EFM, and epidurals, but reported significant attitudinal differences for other issues. Regional differences may be related to midwives' primary practice settings, the historical development of midwifery in their region and the number of new midwives with less than 5 years of clinical experience. A set of core midwifery values was identified that demonstrate a strong belief in normal birth.

Optimization of machine tool settings for Spirac hypoid gears by controlling symmetry of contact paths

A novel optimization method to control the symmetry of contact paths on the concave and convex tooth surfaces of the gear then improves the meshing quality was proposed. By modifying the angular setting of the head cutter when cutting the pinion, the direction angles of the two contact paths are equated to estimate their symmetry. The relation between the direction angles is formulated precisely, the influence of the angular setting on the contact paths is investigated, and the equations for obtaining the values of the machine tool settings are derived. The proposed method is applied to a numerical example of a Spirac hypoid gear pair, and the results reveal that the contact paths on the concave and convex tooth surfaces are approximately symmetrical and the transmission errors of both sides are comparable.

Novel bow-shaped local resonance acoustic metamaterials with ultra-wide low-frequency stopband: design, modeling, and testing

This paper proposes a novel bow-spring local resonance (LR) structure featuring an exceptionally wide low-frequency stopband. Unlike traditional methods reliant on heavy mass or stiffness adjustments, this structure effectively manipulates and amplifies the dynamic characteristics of negative stiffness solely by designing parameter values for the bow-spring set. Through finite element method analysis, an ultra-wide stopband ranging from 91 to 570 Hz is achieved within the LR structure. Further modification of the connection pattern with a perforated plate extends the upper edge to 686 Hz while reducing the lower edge to 76 Hz. Most notably, within the novel bow-spring LR structure, a stopband width of 610 Hz is attained, resulting in a gap-mid gap ratio of 160.1%. The numerical and experimental results demonstrate good agreement. These findings offer a new perspective and guidelines for developing LR structures with ultra-wide low-frequency stopbands, potentially finding applications in the field of low-frequency vibration and noise reduction.

Cross-Regional Crop Classification Based on Sentinel-2

Accurate crop classification is of vital importance for agricultural water management. Most researchers have achieved crop classification by model optimization in the same temporal and regional domain by adjusting the value of input features. This study aims to improve the accuracy of crop classification across temporal and spatial domains. Sentinel-2 satellite imagery is employed for crop classification training and prediction in selected farming areas of Heilongjiang Province by calculating vegetation indices and constructing sequential input feature datasets. The HUNTS filtering method was used to mitigate the influence of cloud cover, which increased the stability and completeness of the input feature data across different years. To address the issue of shifts in the input feature values during cross-scale classification, this study proposes the hypothesis testing distribution method (HTDM). This method balances the distribution of input feature values in the test set even without knowing the crop distribution, thereby enhancing the accuracy of the classification test set. The results indicate that the HTDM significantly improves prediction accuracy in cases of substantial image quality variance. In 2022, the recognition accuracy for crop types at all farms processed by the HTDM was above 87%, showcasing the strong robustness of the HTDM.