Worst Value Research Articles

The TOPSIS method: Figuring the landslide susceptibility using Excel and GIS

The current study introduced Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance landslide susceptibility. It determines the relative distance of each alternative from the ideal best and ideal worst value. The ArcGIS environment was used to prepare eleven landslide conditioning factors, while raster values were extracted for the decision matrix preparation. We utilized subjective expert judgment to create a weighted matrix that considers the roles of each conditioning component. In addition, a Euclidean distance was measured from each alternative to the ideal best and worst values. The relative closeness value (Ri) has been used to prepare the landslide susceptibility index by the inverse distance weighting (IDW) interpolation. Furthermore, the precision of the landslide susceptibility was justified by area under curve-receiver operating characteristic (AUC-ROC) which was 0.987. Hence, multi-criteria decision-making (MCDM) techniques like the TOPSIS method are very useful for natural hazard mapping.•The simplified TOPSIS approach described by Hwang and Yoon (1981) is applied in this study. The criteria have been categorized and assigned weights based on expert judgment and previously published material.•The TOPSIS approach and GIS integration has significantly enhanced the creation of a landslide susceptibility map for a sensitive area.•The method is easiest and suitable for short term operation research.

Psychological Correlates of Post-COVID Condition

<span lang="SK">This article deals with psychological correlates of the post-COVID condition - depression, anxiety, and memory problems including remembering and forgetting. The work has a longitudinal character, while it examines the post-COVID condition in a group of participants based on infection of the disease Covid-19. At the same time, participants who never had this disease (N=86, for the 1. measure and N=38 for the 2. measure) are compared with those who were infected with COVID-19 (N=112, for the 1. measure and N=36 for the 2. measure), while participants were separated for analysis in groups based on the time from infection. Group of respondents who were infected within 3 months, from 3-9 months from infection and 9+ months since infecting with the disease. We used tests for comparison, such as the Kruskal Wallis test and multivariate procedures for within-subject and between-subject changes, using Anova for mixed experimental designs. We also determined the risk of being included in a group based on the time of infection with COVID-19 through multinominal logistic regression. We found differences in all variables in general between those infected with COVID-19 and those not. In neuropsychiatric aspects- anxiety and depression were confirmed cyclical features in those who were infected with COVID-19 in time, with the worst value of variables in the group from 3-9 months from infecting with the disease. In the current memory scale and its subscale, the act of remembering was a value that worsened over time and it was confirmed as an effect of group inclusion.</span>

Prevalence and Neurological Outcomes of Comatose Patients With Extracorporeal Membrane Oxygenation

To investigate prevalence, risk factors, and in-hospital outcomes of comatose extracorporeal membrane oxygenation (ECMO) patients. Retrospective observational. Tertiary academic hospital. Adults received venoarterial (VA) or venovenous (VV) ECMO support between November 2017 and April 022. None. We defined 24-hour off sedation as no sedative infusion (except dexmedetomidine) or paralytics administration over a continuous 24-hour period while on ECMO. Off-sedation coma (comaoff) was defined as a Glasgow Coma Scale score of ≤8 after achieving 24-hour off sedation. On-sedation coma (comaon) was defined as a Glasgow Coma Scale score of ≤8 during the entire ECMO course without off sedation for 24 hours. Neurological outcomes were assessed at discharge using the modified Rankin scale (good, 0-3; poor, 4-6). We included 230 patients (VA-ECMO 143, 65% male); 24-hour off sedation was achieved in 32.2% VA-ECMO and 26.4% VV-ECMO patients. Among all patients off sedation for 24 hours (n = 69), 56.5% VA-ECMO and 52.2% VV-ECMO patients experienced comaoff. Among those unable to be sedation free for 24 hours (n = 161), 50.5% VA-ECMO and 17.2% VV-ECMO had comaon. Comaoff was associated with poor outcomes (p < 0.05) in VA-ECMO and VV-ECMO groups, whereas comaon only impacted the VA-ECMO group outcomes. In a multivariable analysis, requirement of renal replacement therapy was an independent risk factor for comaoff after adjusting for ECMO configuration, after adjusting for ECMO configuration, acute brain injury, pre-ECMO partial pressure of oxygen in arterial blood, partial pressure of carbon dioxide in arterial blood, pH, and bicarbonate level (worst value within 24 hours before cannulation). Comaoff was common and associated with poor outcomes at discharge. Requirement of renal replacement therapy was an independent risk factor.

Return to Play Assessment After Lateral Ankle Sprains - German Male Elite Youth Football (Soccer) Academy Baseline Data.

Lateral ankle sprain (LAS) is one of the most common types of injury in football (soccer). Normative baseline data of performance tests for Return to Play (RTP) decision are still lacking. The primary aim of this study was to generate baseline values for uninjured elite youth football players for a multifactorial RTP assessment and compare with previously published data. A secondary aim was to investigate the use of the Limb Symmetry Index (LSI) as a method to determine whether an athlete passes a performance test or not. Observational Cohort study. Baseline data of performance tests (Y-Balance [YBT-LQ], Heel Rise [HRT]; Singe Leg Squat [SLST]; Single Leg Drop Jump [SLDJ]; Side Hop [SHT]; Figure of 8 Hop [F-8]; Modified Agility T-Test [MAT]) were assessed in 20 elite youth football players, aged 16-21 years. Additionally, the traditional LSI (dividing the result of the non-dominant leg by the result of the dominant leg and multiplying by 100) and directionally corrected LSI (the worst value is divided by the better value and multiplied by 100) were calculated. The test values were compared to previously reported study results. LSI and side-to-side comparisons between dominant and non-dominant leg sides were analyzed using the Wilcoxon test. Male elite youth football players achieved better results in the dynamic performance tests (SHT, F-8, and MAT) compared to reference values of the cohorts previously described in the literature: YBT-LQ total score (cm) dominant (dom) 99.3±8.3, non-dominant (ND) 99.5±10.4; HRT (average number) dom. 27.1±5.4, ND 25.2±5.1); SLDJ height (cm) dom 15±5, ND 15±5 and contact time (sec) dom 0.29±0.08, ND 0.29±0.07, Reactive Strength Index (RSI) dom 0.52±0.12, ND 0.50±0.13); SHT (sec) dom 7.12±0.73, ND 7.39±0.93; F-8 (sec) dom 10.52±1.02, ND 10.37±1.04; and MAT (sec) 5.82±0.22. Directionally corrected LSI differed significantly from the traditional calculated LSI (p<0.05). The findings of this study highlight the need to determine specific baseline data for RTP testing in male elite youth football players after LAS. The traditional LSI should not be used as a "stand alone method" for determining RTP. LSI calculations should consider the direction of asymmetry to determine passing a performance test or not. 3b.

(001) INHIBITION AND EXCITATION IN THE SEXUAL BRAIN: AN USEFUL TOOL FOR THE PREDICTION OF THE DIAGNOSIS AND TREATMENT OF HYPOACTIVE SEXUAL DESIRE IN WOMEN WITH SEXUAL DYSFUNCTION

Abstract Introduction HSDD (Hypoactive Sexual Desire Disorder) is one of the most common sex-related disorders among women. Despite its considerable prevalence, factors affecting sexual desire as well as therapeutic outcomes of treatment of HSDD in women have been scarcely studied. According to the Dual Control Model (DCM), for years female sexual desire has been identified as the result of two mainly centrally acting brain processes: excitation or inhibition towards sexual cues. In this context, the SIS (Sexual Inhibition Scale)/SES (Sexual Excitation Scale) validated questionnaire could represent an useful tool for the clinician to better characterize patients’ lack of desire. Objective This study was aimed at exploring both the inhibitory and excitatory components of sexual desire in women referring to our Clinic for sexual dysfunction, in order to find a cut-off value in the SIS/SES score predicting a diagnosis of HSDD. A secondary aim was also to identify clinical, relational and biochemical parameters significantly associated with these two dimensions of sexual desire. Methods We retrospectively recruited a consecutive series of 133 women consulting for Female Sexual Dysfunction (FSD). Patients underwent clinical and biochemical evaluation, a structured interview and completed several self-administered questionnaires, including SIS/SES, Female Sexual Function Index (FSFI), Female Sexual Distress Scale-Revised (FSDS-R), Body Uneasiness Test (BUT), Emotional Eating Scale (EES) and Middlesex Hospital Questionnaire (MHQ). Results The ROC curve for SES score showed an accuracy of 0.687 ± 0.05 (p&amp;lt;0.0001) in identifying HSDD; considering a cut-off value of 47.5, the sensitivity and specificity for HSDD detection were 70.5% and 55.6%, respectively. In addition, the best cut-off value for SIS1 to diagnose HSDD was 32.5, with 0.664 ± 0.048 AUC (p=0.002), 68.2% sensitivity and 53.3% specificity. We next stratified FSD women according to these SES/SIS1 cut-off values, thus identifying patients with pathological (pSES, pSIS1) or non-pathological (npSES, npSIS1) scores and the following 4 different subgroups: group 1 npSES/npSIS1; group 2 npSES/pSIS1; group 3 pSES/npSIS1; group 4 pSES/pSIS1. Among the 4 groups we did not find any statistically significant difference concerning the main characteristics explored, including lifestyle, hormonal and metabolic factors, with the exception of age, which was associated with a progressive worsening of either SES and SIS1 scores (F=4.299, p=0.006). Concerning relational factors, we demonstrated that the longer the duration of the relationship, the more pathological the excitatory/inhibitory scores, even when adjusted for age (F=5.588, p=0.001). Noteworthy, with exception for FSFI orgasm (FSFI-O) and satisfaction (FSFI-S) domains, all others FSFI domains scores showed similar significant differences with the worst values observed in pSES subgroups, independently from the presence of pSIS1. In contrast, FSDS-R score showed a highly significant variation among subgroups, but with the pSIS1 subgroup displaying the worst distress score independently from the presence of pSES. Among endocrinological factors, only total testosterone levels showed significant variation among groups (F=5.952, p&amp;lt;0.001), with the lower level observed in FSD women with pSES or pSIS1, in whatever combination as compared to npSES/npSIS1, even after age-adjustment (F=3.176, p=0.027). Regarding psychopathological factors, in an age-adjusted model, we found a significantly different MHQ total score among the 4 groups, with the worst value associated with the pSIS1 group combined or not with pSES. We also explored eating disorder symptoms. The 4 groups reported significantly different values in the EES, with pSES/pSIS1 group showing the highest score, even after adjusting for age (F=3.316, p=0.023). We then investigated the relevance of stratifying HSDD patients according to SIS1 and SES np/p scores in predicting the beneficial effects of treatments for HSDD (improvement yes/no). Interestingly, we found that SES, but not SIS scores, could predict HSDD treatment outcome after 6 months; in particular, the lower the level of SES at baseline, the higher the improvement in FSFI-D domain during treatment is predictable. Finally, we explored which were the main determinants for SES/SIS1 scores in the study population. Noteworthy, a significantly stepwise increase of SES score was observed as a function of total testosterone levels (r=0.192, p=0.049). Conclusions In conclusion, the cutoffs of SIS1/SES found in this study could help characterizing HSDD women and identifying subgroups of patients with the highest probability to benefit from testosterone treatment. From a broader viewpoint, our study suggests that women diagnosed with HSDD should be evaluated by using more appropriate tools, including those not routinely employed in clinical practice, so that different “nuances” of this sexual disorder could be recognized and consequently adequately treated in a tailored therapy perspective. Disclosure No.

Clinical characteristics and prognosis of acute gastrointestinal injury in patients with sepsis-associated acute respiratory distress syndrome

To observe the clinical characteristics and prognosis of patients with acute respiratory distress syndrome (ARDS) in sepsis combined with acute gastrointestinal injury (AGI) of different grades, and to further explore the risk factors associated with the poor prognosis of patients. The clinical data of patients with septic ARDS admitted to the intensive care unit (ICU) of Tianjin First Central Hospital from March to October 2023 were collected. According to the 2012 European Association of Critical Care Medicine AGI definition and grading criteria, the patients were categorized into AGI grade 0- IV groups. The clinical characteristics and 28-day clinical outcomes of the patients were observed; the risk factors related to the prognosis of patients with septic ARDS combined with AGI were analyzed by using univariate and multivariate Logistic regression; and the receiver operator characteristic curve (ROC curve) and calibration curves were plotted to evaluate the predictive value of each risk factor on the prognosis of patients with septic ARDS combined with AGI. A total of 92 patients with septic ARDS were enrolled, including 7 patients in the AGI 0 group, 20 patients in the AGI I group, 38 patients in the AGI II group, 23 patients in the AGI III group, and 4 patients in the AGI IV group. The incidence of AGI was 92.39%. With the increase of AGI grade, the ARDS grade increased, and acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), intra-abdominal pressure (IAP), white blood cell count (WBC), neutrophil count (NEU), lymphocyte count (LYM), lymphocyte percentage (LYM%), and 28-day mortality all showed a significant increasing trend, while the oxygenation index (PaO2/FiO2) showed a significant decreasing trend (all P < 0.05). Pearson correlation analysis showed that APACHE II score, SOFA score, and ARDS classification were positively correlated with patients' AGI grade (Pearson correlation index was 0.386, 0.473, and 0.372, respectively, all P < 0.001), and PaO2/FiO2 was negatively correlated with patients' AGI grade (Pearson correlation index was -0.425, P < 0.001). Among the patients with septic ARDS combined with AGI, there were 68 survivors and 17 deaths at 28 days. The differences in APACHE II score, SOFA score, ARDS grade, AGI grade, PaO2/FiO2, IAP, AGI 7-day worst value, length of ICU stay, and total length of hospital stay between the survival and death groups were statistically significant. Univariate Logistic regression analysis showed that SOFA score [odds ratio (OR) = 1.350, 95% confidence interval (95%CI) was 1.071-1.702, P = 0.011], PaO2/FiO2 (OR = 0.964, 95%CI was 0.933-0.996, P = 0.027) and AGI 7-day worst value (OR = 2.103, 95%CI was 1.194-3.702, P = 0.010) were the risk factors for 28-day mortality in patients with septic ARDS combined with AGI. Multivariate Logistic regression analysis showed that SOFA score (OR = 1.384, 95%CI was 1.153-1.661, P < 0.001), PaO2/FiO2 (OR = 0.983, 95%CI was 0.968-0.999, P = 0.035) and AGI 7-day worst value (OR = 1.992, 95%CI was 1.141-3.478, P = 0.015) were the independent risk factors for 28-day mortality in patients with septic ARDS combined with AGI. ROC curve analysis showed that SOFA score, PaO2/FiO2 and AGI 7-day worst value had predictive value for the 28-day prognosis of patients with septic ARDS combined with AGI. The area under the ROC curve (AUC) was 0.824 (95%CI was 0.697-0.950), 0.760 (95%CI was 0.642-0.877) and 0.721 (95%CI was 0.586-0.857), respectively, all P < 0.01; when the best cut-off values of the above metrics were 5.50 points, 163.45 mmHg (1 mmHg≈0.133 kPa), and 2.50 grade, the sensitivities were 94.1%, 94.1%, 31.9%, respectively, and the specificities were 80.9%, 67.6%, 88.2%, respectively. The incidence of AGI in patients with septic ARDS is about 90%, and the higher the AGI grade, the worse the prognosis of the patients. SOFA score, PaO2/FiO2 and AGI 7-day worst value have a certain predictive value for the prognosis of patients with septic ARDS combined with AGI, among which, the larger the SOFA score and AGI 7-day worst value, and the smaller the PaO2/FiO2, the higher the patients' mortality.

Differential neural network robust constrained controller using approximate dynamic programming

This study focuses on developing a continuous differential neural network (DNN) approximating min–max robust control by applying dynamic neural programming. The suggested controller is applied to a class of nonlinear perturbed systems providing satisfactory dynamics for a given cost function depending on both the trajectories of the perturbed system and the designed constrained control actions. The min–max formulation for dynamic programming offers reliable control for restricted modeling uncertainties and perturbations. The suggested design considers control norm restrictions in the optimization problem. DNN’s approximation of the worst (with respect to the admissible class of perturbations and uncertainties) value function of the Hamilton–Jacobi–Bellman (HJB) equation enables the estimation of the closed-loop formulation of the controller. The robust version of the HJB partial differential equation is studied to create the learning law class for the time-varying weights in the DNN. The controller employs a time-varying Lyapunov-like differential equation and the solution of the corresponding learning laws. A recurrent algorithm based on the Kiefer–Wolfowitz technique can be used by modifying the weights’ initial conditions to fulfill the specified cost function’s end requirements. A numerical example tests the robust control proposed in this study, validating the robust optimal solution based on the DNN approximation for Bellman’s value function.

Mortality rates among adult critical care patients with unusual or extreme values of vital signs and other physiological parameters: a retrospective study.

We evaluated relationships of vital signs and laboratory-tested physiological parameters with in-hospital mortality, focusing on values that are unusual or extreme even in critical care settings. We retrospectively studied Philips Healthcare-MIT eICU data (207 U.S. hospitals, 20142015), including 166,959 adult-patient critical care admissions. Analyzing most-deranged (worst) value measured in the first admission day, we investigated vital signs (body temperature, heart rate, mean arterial pressure, and respiratory rate) as well as albumin, bilirubin, blood pH via arterial blood gas (ABG), blood urea nitrogen, creatinine, FiO2 ABG, glucose, hematocrit, PaO2 ABG, PaCO2 ABG, sodium, 24-hour urine output, and white blood cell count (WBC). In-hospital mortality was ≥50% at extremes of low blood pH, low and high body temperature, low albumin, low glucose, and low heart rate. Near extremes of blood pH, temperature, glucose, heart rate, PaO2 , and WBC, relatively. Small changes in measured values correlated with several-fold mortality rate increases. However, high mortality rates and abrupt mortality increases were often hidden by the common practice of thresholding or binning physiological parameters. The best predictors of in-hospital mortality were blood pH, temperature, and FiO2 (scaled Brier scores: 0.084, 0.063, and 0.049, respectively). In-hospital mortality is high and sharply increasing at extremes of blood pH, body temperature, and other parameters. Common-practice thresholding obscures these associations. In practice, vital signs are sometimes treated more casually than laboratory-tested parameters. Yet, vitals are easier to obtain and we found they are often the best mortality predictors, supporting perspectives that vitals are undervalued.

Design of Automatic Power Factor Correction for Optimization of Electric Energy Consumption

Electrical energy is a major human need which, when viewed from its main source, namely fossil energy, will increasingly run out. There needs to be an effort to utilize electrical energy more optimally. The problem discussed in this research is the decline in power factor. The State Electricity Company (PLN) has a minimum power factor standard of above 0.85 which is found in the SPLN 70-1 regulation and PERMEN ESDM No. 09 of 2011. If the power factor is below the minimum limit, it will result in losses, because consumers have to pay for excess kilo Volt Ampere Reactive hours (kVARh). Power factor drops are caused by the use of inductive loads. With automatic power factor correction, the poor power factor from the use of inductive loads will be resolved and optimization of the use of electrical energy can be achieved. From the test results conducted using 3 cumulative loads, the worst power factor value was obtained before PF repair was carried out by the system, namely 0.38 and after PF repair by the best power factor system reached 0.99 and obtained the value of active power and apparent power after PF repair is almost the same (comparable) and it can be said that the optimization of electrical energy occurs in this study.

Enhanced Dung Beetle Optimization Algorithm for Practical Engineering Optimization

An enhanced dung beetle optimization algorithm (EDBO) is proposed for nonlinear optimization problems with multiple constraints in manufacturing. Firstly, the dung beetle rolling phase is improved by removing the worst value interference and coupling the current solution with the optimal solution to each other, while retaining the advantages of the original formulation. Subsequently, to address the problem that the dung beetle dancing phase focuses only on the information of the current solution, which leads to the overly stochastic and inefficient exploration of the problem space, the globally optimal solution is introduced to steer the dung beetle, and a stochastic factor is added to the optimal solution. Finally, the dung beetle foraging phase introduces the Jacobi curve to further enhance the algorithm’s ability to jump out of the local optimum and avoid the phenomenon of premature convergence. The performance of EDBO in optimization is tested using the CEC2017 function set, and the significance of the algorithm is verified by the Wilcoxon rank-sum test and the Friedman test. The experimental results show that EDBO has strong optimization-seeking accuracy and optimization-seeking stability. By solving four engineering optimization problems of varying degrees, EDBO has proven to have good adaptability and robustness.

The Effect of Using Clay-CaCO&lt;sub&gt;3&lt;/sub&gt; as Filler on Tensile Strength, %Elongation, and Young's Modulus Value in Modified Poly Lactic Acid (PLA)

Plastic is an important necessity with the characteristics of being light, strong, relatively cheap, and durable. However, plastic cannot decompose in a short time so that it becomes a pollutant. The using of Poly lactic acid (PLA) is an alternative to synthetic plastics substitute such as Low-Density Polyethylene (LDPE) because it is degradable. However, PLA is brittle, so it requires a plasticizer in the form of additives, namely Polyethylene glycol (PEG) 200 and fillers in the form of clay and CaCO3 to improve the mechanical properties of PLA which is brittle and has poor toughness. The purpose of this study was to determine the effect of adding additives to mechanical properties of PLA. The method used is solvent blending using chloroform as a solvent, stirring at 200 rpm for 6 hours at 30 . The research was conducted through testing the effect of the ratio of filler addition on the condition that the ratio of PLA/Additives was constant, i.e., 70%PLA/30% Additives. The resulting film is white and slightly transparent and has a smooth surface. The effect of adding additives in the form of plasticizers and fillers was tested through Dynamic Mechanical Analysis (DMA) analysis to determine the value of tensile strength, Young's modulus, and elongation break. The best result was obtained at a ratio of 25%CaCO3/Clay, which was increasing elongation at break 7.62%. It also indicated with best decreased percentage value of Young’s modulus, and highest crystallinity index of 39.86%. The worst value is obtained in variant of 50%CaCO3/Clay that indicated with lowest tensile strength and decreased of % elongation at break. From this study, the best variant was recommended as a laminating plastic, that does not require high tensile strength for application.

Association between left ventricular ejection fraction, mortality and use of mechanical circulatory support in patients with non-ischaemic cardiogenic shock

BackgroundCurrently, use of mechanical circulatory support (MCS) in non-ischaemic cardiogenic shock (CS) is predominantly guided by shock-specific markers, and not by markers of cardiac function. We hypothesise that left ventricular ejection fraction (LVEF) can identify patients with a higher likelihood to benefit from MCS and thus help to optimise their expected benefit.MethodsPatients with non-ischaemic CS and available data on LVEF from 16 tertiary-care centres in five countries were analysed. Cox regression models were fitted to evaluate the association between LVEF and mortality, as well as the interaction between LVEF, MCS use and mortality.ResultsN = 807 patients were analysed: mean age 63 [interquartile range (IQR) 51.5–72.0] years, 601 (74.5%) male, lactate 4.9 (IQR 2.6–8.5) mmol/l, LVEF 20 (IQR 15–30) %. Lower LVEF was more frequent amongst patients with more severe CS, and MCS was more likely used in patients with lower LVEF. There was no association between LVEF and 30-day mortality risk in the overall study cohort. However, there was a significant interaction between MCS use and LVEF, indicating a lower 30-day mortality risk with MCS use in patients with LVEF ≤ 20% (hazard ratio 0.72, 95% confidence interval 0.51–1.02 for LVEF ≤ 20% vs. hazard ratio 1.31, 95% confidence interval 0.85–2.01 for LVEF > 20%, interaction-p = 0.017).ConclusionThis retrospective study may indicate a lower mortality risk with MCS use only in patients with severely reduced LVEF. This may propose the inclusion of LVEF as an adjunctive parameter for MCS decision-making in non-ischaemic CS, aiming to optimise the benefit–risk ratio.Graphical abstractImpact of left ventricular ejection fraction on mortality and use of mechanical circulatory support in non-ischaemic cardiogenic shock. Hazard ratio for 30-day mortality across the LVEF continuum, adjusted for age, sex, SCAI shock stage, worst value of lactate and pH within 6 h, prior resuscitation and mechanical ventilation during the index shock event. LVEF: Left ventricular ejection fraction; MCS: Mechanical circulatory support; HR: Hazard ratio; CI: Confidence interval.

Minimizing non-processing energy consumption/total weighted tardiness &amp; earliness, and makespan into typical production scheduling model-the job shop scheduling problem

This manuscript proposes a hybrid method to solve the job shop scheduling problem (JSP). Here, the machine consumes different amounts of energy for processing the tasks. The proposed method is the joint execution of Feedback Artificial Tree (FAT) and Atomic Orbital Search (AOS), hence it is called the FAT-AOS method. The aim of the proposed multi-objective method is to lessen the non-processing energy consumption (NEC), total weighted tardiness and earliness (TWET), and makespan (Cmax). Depending on the machine’s operating status, such as working, standby, off, or idle, the energy-consumption model of the machine is constructed. The NEC is the essential metric and the Cmax and TWET are the classical performance metrics used to predict the effects of energy effectiveness in JSP. The proposed AOS technique optimizes the objective of the system and FAT is used to predict the optimal outcome. The proposed method’s performance is implemented in MATLAB and is compared with various existing methods. From this simulation, under the 15x15_1 instance, the proposed method makes the span the best value of 1370, the median is 1720, and the worst value become 2268 is obtained.

Effects of magnet shapes on total harmonic distortion and cogging torque in a permanent magnet synchronous generator for wind turbines

Abstract This paper explores and theoretically reports the effects of different magnet structures on the cogging torque and the total harmonic distortion of the output waveforms from a permanent magnet generator. The generator is a radial flux machine and four different structures are considered for the magnet arrangement in the rotor component and modelled in the Ansys/Maxwell electromagnetic simulation program. This three-phase machine exhibits different behaviours towards various magnet structures, i.e. rectangular, inclined slotted rectangular, skewed double rectangular and inclined slotted skewed double rectangular, respectively. It has been proven by finite element analysis and Fourier analysis that both the cogging and total harmonic distortion values vary significantly for all models. The cogging torque values change in the range of 89.95 to 436.75 mNm and the lowest cogging torque is measured for the inclined slotted skewed double rectangular magnet geometry, while the conventional rectangular magnet geometry yields the worst value with 436.75 mNm. Furthermore, the total harmonic distortion values varies between 1.63 and 3.55 for different magnetic orientations. While the worst total harmonic distortion value is obtained from the inclined slotted rectangular magnet, the best total harmonic distortion is acquired from the skewed double rectangular magnet. All these results will provide scientists and engineers with important information in order to obtain more efficient machines.

Mechanical Properties and Liquid Absorption of Calcium Phosphate Composite Cements.

Calcium phosphate cements present increased biocompatibility due to their chemical composition being similar to that of the hydroxyapatite in the hard tissues of the living body. It has certain limitations due to its poor mechanical properties, such as low tensile strength and increased brittleness. Thus, the optimal way to improve properties is through the design of novel composite cements. The purpose was fulfilled using a 25% hydroxyethyl methacrylate (HEMA) mixed with 3% urethane dimethacrzlate (UDMA) base matrix with various ratios of polyethylene glycol (PEG 400) and polycaprolactone (PCL). Mineral filler is based on tricalcium phosphate (TCP) with different chitosan ratio used as bio-response enhancer additive. Four mixtures were prepared: S0-unfilled polymer matrix; S1 with 50% TCP filler; S2 with 50% chitosan + TCP filler; and S3 with 17.5% chitosan + TCP mixed with 17.5% nano hydroxyapatite (HA). The mechanical properties testing revealed that the best compressive strength was obtained by S2, followed by S3, and the worst value was obtained for the unfilled matrix. The same tendency was observed for tensile and flexural strength. These results show that the novel filler system increases the mechanical resistance of the TCP composite cements. Liquid exposure investigation reveals a relative constant solubility of the used filler systems during 21 days of exposure: the most soluble fillers being S3 and S2 revealing that the additivated TCP is more soluble than without additives ones. Thus, the filler embedding mode into the polymer matrix plays a key role in the liquid absorption. It was observed that additive filler enhances the hydrophobicity of UDMA monomer, with the matrix resulting in the lowest liquid absorption values, while the non-additivated samples are more absorbent due to the prevalence of hydrolytic aliphatic groups within PEG 400. The higher liquid absorption was obtained on the first day of immersion, and it progressively decreased with exposure time due to the relative swelling of the surface microstructural features. The obtained results are confirmed by the microstructural changes monitored by SEM microscopy. S3 and S2 present a very uniform and compact filler distribution, while S1 presents local clustering of the TCP powder at the contact with the polymer matrix. The liquid exposure revealed significant pore formation in S0 and S1 samples, while S3 and S2 proved to be more resistant against superficial erosion, proving the best resistance against liquid penetration.

Diurnal Variation in and Optimal Time to Measure Holter-Based Late Potentials to Predict Lethal Arrhythmia after Myocardial Infarction.

Background and Objectives: Holter-based late potentials (LPs) are useful for predicting lethal arrhythmias in organic cardiac diseases. Although Holter-based LPs exhibit diurnal variation, no studies have evaluated the optimal timing of LP measurement over 24 h for predicting lethal arrhythmia that leads to sudden cardiac death. Thus, this study aimed to validate the most effective timing for Holter-based LP testing and to explore factors influencing the diurnal variability in LP parameters. Materials and Methods: We retrospectively analyzed 126 patients with post-myocardial infarction (MI) status and 60 control participants who underwent high-resolution Holter electrocardiography. Among the 126 post-MI patients, 23 developed sustained ventricular tachycardia (VT) (the MI-VT group), while 103 did not (the MI-non-VT group) during the observation period. Holter-based LPs were measured at 0:00, 4:00, 8:00, 12:00, 16:00, and 20:00, and heart rate variability analysis was simultaneously performed to investigate factors influencing the diurnal variability in LP parameters. Results: Holter-based LP parameters showed diurnal variation with significant deterioration at night and improvement during the day. Assessment at the time with the longest duration of low-amplitude signals < 40 μV in the filtered QRS complex terminus (LAS40) gave the highest receiver operating characteristics curve (area under the curve, 0.659) and the highest odds ratio (3.75; 95% confidence interval, 1.45-9.71; p = 0.006) for predicting VT. In the multiple regression analysis, heart rate and noise were significant factors affecting the LP parameters in the MI-VT and control groups. In the non-VT group, the LP parameters were significantly influenced by noise and parasympathetic heart rate variability parameters, such as logpNN50. Conclusions: For Holter-based LP measurements, the test accuracy was higher when the LP was measured at the time of the highest or worst value of LAS40. Changes in autonomic nervous system activity, including heart rate, were factors influencing diurnal variability. Increased parasympathetic activity or bradycardia may exacerbate Holter-based LP parameters.

A Safety Warning Model Based on IAHA-SVM for Coal Mine Environment.

Coal is an important resource that is closely related to people's lives and plays an irreplaceable role. However, coal mine safety accidents occur from time to time in the process of working underground. Therefore, this paper proposes a coal mine environmental safety early warning model to detect abnormalities and ensure worker safety in a timely manner by assessing the underground climate environment. In this paper, support vector machine (SVM) parameters are optimized using an improved artificial hummingbird algorithm (IAHA), and its safety level is classified by combining various environmental parameters. To address the problems of insufficient global exploration capability and slow convergence of the artificial hummingbird algorithm during iterations, a strategy incorporating Tent chaos mapping and backward learning is used to initialize the population, a Levy flight strategy is introduced to improve the search capability during the guided foraging phase, and a simplex method is introduced to replace the worst value before the end of each iteration of the algorithm. The IAHA-SVM safety warning model is established using the improved algorithm to classify and predict the safety of the coal mine environment as one of four classes. Finally, the performance of the IAHA algorithm and the IAHA-SVM model are simulated separately. The simulation results show that the convergence speed and the search accuracy of the IAHA algorithm are improved and that the performance of the IAHA-SVM model is significantly improved.

Numerical validation and optimization of hybrid composite beam hull using multiple failure criteria

The number of structurally deficient bridges continues to increase due to corrosion of steel sections and concrete rebar, therefore the replacement of decaying structures and the development of innovative systems have become of high priority to extend the life span of newly built bridges. Hybrid Composite Beam (HCB) produced by Hillman is one of those systems that use a combination of materials i.e., concrete, steel, and Glass Fiber-Reinforced Polymer (GFRP) to integrate each main advantage in a single bridge beam structure. Despite its several apparent advantages; it is not widely spread as expected within the last decade. The HCB is manufactured of self-consolidating concrete (SCC), which is poured in the shape of a traditional arch and tied at its ends by high-strength tendons. A durable FRP composite hull encapsulates the SCC arch and the high-strength tying tendons in order to create a structural beam element for bridge applications. The HCB's design aims to provide pure compressive stresses to the concrete and pure tensile stresses to the steel. The current study performs a deep numerical investigation of the FRP hull instead of other components comprehensively studied. Numerical validation is performed for the deflection results on the experimentally tested Knickerbocker HCB Bridge, the deformations are validated at four stages of HCB manufacturing and testing. Further, the FRP hull strength ratios are quantified for the worst value of four failure criteria. The results showed an excess use of FRP material, where more than 90% of FRP areas have strength ratios of 5 to 50. The FRP hull thickness is minimized using Genetic Algorithm optimization under the worst case of loading. The results achieved more than 60% decrease in FRP weight, that led to only 20% cost difference between traditional precast concrete and HCB girders. It is finally concluded that the overdesign of FRP hull contributed to the high cost of HCB usage consequently inefficient market spread.

Insight into single- and bi-objective optimization of industrial problems

ABSTRACT Evolutionary single- and bi-objective optimization of industrial problems, namely, naphtha cracking and styrene reactor are considered. Bi-objective optimization is solved using the HMODE-DLS algorithm, whereas an improved black hole optimizer (BHO) is employed for the single-objective optimization (SOO) problem. For the naphtha cracking process, ethylene selectivity (SE) and severity index (SI) are selected as objectives. Similarly, styrene selectivity (SST) and styrene flow rates (FST) are considered objectives for styrene reactor. Pareto ranking is carried out by using the net flow method (NFM) and the best solution is compared with the single- and multi-objective optimization results. In a single objective optimization study, the optimum solution corresponds to the lowest value of the SI (1.571) at the cost of the worst value of SE (0.269). Similarly, the highest values of FST (16.642 kmol/h) and SST (96.158%) are resulted in the SOO study of styrene reactor.

Optimization of Welding Process Parameters Using the VIKOR MCDM Method

Optimization of welding process parameters These welding parameters are welding current, welding voltage, gas flow rate, wire feed rate, etc. They affect welding strength, weld pool geometry of steel material during welding. By using the DOE method, the parameters can be optimized and have the best combination of parameters for the target quality. The VIKOR (VIšekriterijumsko Kompromisno Rangiranje) Optimal replacement Select method is used Biomass product, Catalyst, Solvent, Temperature/ K. in Evaluation. Alternatives Wood, Bio-oil, Lignin, Glucose, Saccharine is the Best and Worst Value. Saccharides is got the first rank whereas is the Glucose is having the Lowest rank.