Outlier Detection Method of Dam Monitoring Data Based on Robust Estimation and Variable Separation by LIANG Huibin, ZHANG Han, ZHANG Linsong, CAO Yuxin, ZHOU Jingren

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Spectral Lags and Characteristic Time Scales of GRBs with Known Redshift by Eda Sonbaş, Dilem Göktaş, İlham Nasıroğlu

“…The analysis suggests short-duration bursts exhibit a shorter variability time scale than long-duration bursts. Although the MTS value for most long- and short-duration GRBs is shorter than T90, a few cases approach the equality limit. …”
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Formation of a dynamic knowledge base of fuzzy inference systems for estimating changing in time objects by A. Kostikova, N. Skiter

“…The factors that influence the change of fuzzy set in time and its membership function, for example, the change of the range of included values of variables in the fuzzy set leads to set for the “old” value of the variable a “new” value of the membership function; transformation of the type of membership function are allocated. …”
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Gaussian Process Modeling Coronal X-Ray Variability of Active Galactic Nuclei by Haiyun Zhang, Dahai Yan, Li Zhang, Niansheng Tang

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Positive Solution Pairs for Coupled <i>p</i>-Laplacian Hadamard Fractional Differential Model with Singular Source Item on Time Variable by Cheng Li, Limin Guo

“…Some existence results are obtained for the case in which the nonlinearity is allowed to be singular with regard to the time variable. Several examples are correspondingly provided to show the correctness and applicability of the obtained results, where nonlinear terms are controlled by the integrable functions <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>1</mn><mrow><mi>π</mi><msup><mrow><mo>(</mo><mo form="prefix">ln</mo><mi>t</mi><mo>)</mo></mrow><mfrac><mn>1</mn><mn>2</mn></mfrac></msup><msup><mrow><mo>(</mo><mn>1</mn><mo>−</mo><mo form="prefix">ln</mo><mi>t</mi><mo>)</mo></mrow><mfrac><mn>1</mn><mn>2</mn></mfrac></msup></mrow></mfrac></mstyle></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mstyle scriptlevel="0" displaystyle="true"><mfrac><mn>1</mn><mrow><mi>π</mi><msup><mrow><mo>(</mo><mo form="prefix">ln</mo><mi>t</mi><mo>)</mo></mrow><mfrac><mn>3</mn><mn>4</mn></mfrac></msup><msup><mrow><mo>(</mo><mn>1</mn><mo>−</mo><mo form="prefix">ln</mo><mi>t</mi><mo>)</mo></mrow><mfrac><mn>3</mn><mn>4</mn></mfrac></msup></mrow></mfrac></mstyle></semantics></math></inline-formula> in Example 1, and by the integrable functions <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>θ</mi><mo>,</mo><mover><mi>θ</mi><mo>¯</mo></mover></mrow></semantics></math></inline-formula> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>φ</mi><mo>(</mo><mi>v</mi><mo>)</mo><mo>,</mo><mi>ψ</mi><mo>(</mo><mi>u</mi><mo>)</mo></mrow></semantics></math></inline-formula> in Example 2, respectively. …”
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Exploring the Correlation Between Salt Tolerance and Seed Nutritional Value of Different Quinoa Genotypes Grown Under Saharan Climatic Conditions by Rahma Goussi, Hatem Ben Jouira, Ouiza Djerroudi Zidane, Jemaa Essemine, Halima Khaled, Salma Nait Mohamed, Malek Smida, Salim Azib, Alia Telli, Arafet Manaa

“…Quinoa is an annual pseudocereal highly adapted to extreme environments and has become, at this point in time, an extremely popular food due to its exceptional and high nutritional quality. …”
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Association between oxygen debt (DEOx) variability over time and clinical outcomes in critically ill COVID-19 patients: an observational study by Eduardo Tuta-Quintero, Alirio Bastidas-Goyes, Henry Robayo-Amortegui, Michel Pérez-Garzón, Isacio Serna-Palacios, Cristian Peña-Quimbayo, Julian Espitia, Daniel Pinto, Johan Rincón, Juan Sánchez, Jesus Pérez

“…DEOx was calculated using two validated formulas: one based on lactate (DEOx1) and another incorporating lactate and base excess (DEOx2). Variability in DEOx was assessed at different time points (≤6h, 6-12h, 12-24h, >24h) and its association with IMV and survival outcomes was analyzed. …”
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Markers of chronic low-grade inflammation and serum cytokine levels in patients with type 1 diabetes: associations with time in ranges and glucose variability by K. R. Mavlianova, Ju. F. Semenova, N. B. Orlov, V. V. Klimontov

“…In a sample of 130 patients and 20 healthy individuals (control), serum concentrations of interleukins (IL-1β, IL-4, IL-6, sIL-6Rα, IL-19, IL-20, IL-22, IL-26, IL-27, IL-28A, IL-29, IL-32, IL-34, IL-35) were assessed by multiplex analysis. Time in the ranges and GV parameters: Coefficient of Variability (CV), Mean Amplitude of Glycemic Excursions (MAGE), and Mean Absolute Glucose rate of changes (MAG) were derived from CGM data.RESULTS: Patients with Time In Range (TIR) &lt;70% had higher concentrations of hs-CRP and fibrinogen, higher SII values, and demonstrated a trend toward higher TIR compared with those with TIR ≥70% (p=0.018, p=0.026, p=0.037, p=0.101, respectively). …”
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Comparison of Dynamic State Estimation Methods in the Time Domain by Saeed Javadi, Ali Hesami Naghshbandy

“…A solution to these challenges is dynamic state estimation in short time intervals, such as the time domain. This paper simulates a standard 68-bus system in the presence of converter-based resources with a high penetration percentage in DIgSILENT software and compares the performance of four Bayesian filters in estimating the dynamic variables of the synchronous generators of the system using values in the time domain with each other. …”
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The Value of Clinical Variables and the Potential of Longitudinal Ultrasound Carotid Plaque Assessment in Major Adverse Cardiovascular Event Prediction After Uncomplicated Acute Co... by Leonid L. Bershtein, Alexey N. Sumin, Anna V. Kutina, Marina D. Lunina, Dmitrii S. Evdokimov, Tatyana V. Nayden, Viktoriya E. Gumerova, Igor N. Kochanov, Arkadii A. Ivanov, Svetlana A. Boldueva, Ekaterina D. Evdokimova, Elizaveta V. Zbyshevskaya, Alina E. Evtushenko, Vartan K. Piltakyan, Sergey A. Sayganov

“…Among the predictors assessed at 6 months, after adjustment for other variables, only ≥ 3 uncorrected risk factors and standardized AP GSM < 81 (cut-off value) at 6 months were significant (HR 3.11, 95% CI 1.17–8.25 and HR 3.77, 95% CI 1.43–9.92, respectively) (for all HRs above, all <i>p</i>-values < 0.05; HR and 95% CI values varied minimally across regression models). …”
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Assessing the predictive value of time-in-range level for the risk of postoperative infection in patients with type 2 diabetes: a cohort study by Ying Wu, Rui Xv, Qinyun Chen, Ranran Zhang, Min Li, Chen Shao, Guoxi Jin, Guoxi Jin, Xiaolei Hu, Xiaolei Hu

“…AimTo analyze the correlation between preoperative time-in-range (TIR) levels and postoperative infection in patients with type 2 diabetes mellitus (T2DM) and to evaluate the value of the TIR as a predictor of postoperative infection in patients with T2DM.MethodsA total of 656 patients with T2DM during the perioperative period were divided into a TIR standard group (TIR≥70%) and a TIR nonstandard group (TIR&lt;70%) according to the TIR value. …”
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Utility of nonlinear analysis of heart rate variability in early detection of metabolic syndrome by José Alberto Zamora-Justo, Myriam Campos-Aguilar, María del Carmen Beas-Jara, Pedro Galván-Fernández, Alberto Ponciano-Gómez, Santiago Cristóbal Sigrist-Flores, Rafael Jiménez-Flores, Alejandro Muñoz-Diosdado

“…HRV data were recorded at three time points: rest, exercise, and recovery.ResultsParticipants with MetS showed significantly lower SampEn and DFA values at rest compared to those without alterations, indicating reduced signal complexity. …”
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Heart Rate Variability Analysis in Congestive Heart Failure: The Need for Standardized Assessment Protocols by Monika Míková, David Pospíšil, Jan Řehoř, Marek Malik

“…Heart rate variability (HRV) analysis is a noninvasive tool that allows cardiac autonomic control to be assessed. …”
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Change of social value orientation affected by the observed mimical expression of the interaction partner by Joanna Lewczuk

“…The following tools were used: for the measurement of social value orientations, a modified version of the Ring Measure of Social Values; for the experimental manipulation, photographs of facial expressions (happiness, anger, neutrality).In the light of the data obtained, one may, for the very first time, speak of social value orientations as of a dimension being susceptible to a change under the influence of a facial expression. …”
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Learning path planning methods based on learning path variability and ant colony optimization by Jing Zhao, Haitao Mao, Panpan Mao, Junyong Hao

“…To address the limitations of learning path planning such as insufficient personalization, the study proposes a learning path planning method based on learning path variability and ant colony optimization. First, dynamic time regularization is used to obtain learning path variability, and the K-means algorithm is used to classify students' learning types. …”
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Heart rate variability and systemic hemodynamic state in adults with a first time, non-traumatic epileptic seizure during an orthoclinostatic stress test by O. V. Grebenyuk, V. M. Alifirova, M. V. Svetlik, N. G. Kataeva, V. N. Vasilyev

“…In patients with TLC, evidence of vegetative insufficiency in the vertical position was identified, with the indicators going back to the background values in the horizontal position.Conclusion. The revealed features of vegetative regulation in patients with absence of seizures and unprovoked seizures will allow to differentiate the mechanism of the first-time epileptic seizure more accurately.…”
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An efficient numerical method based on QSC for multi-term variable-order time fractional mobile-immobile diffusion equation with Neumann boundary condition by Jun Liu, Yue Liu, Xiaoge Yu, Xiao Ye

“…This new scheme was shown to be unconditionally stable and convergent with the accuracy $ \mathcal{O}(\tau^{\min{\{3-\alpha^*-\alpha(0), \ 2\}}} + \Delta x^{2}+\Delta y^{2}) $, where $ \Delta x $, $ \Delta y $, and $ \tau $ denoted the space-time mesh sizes. $ \alpha^{*} $ was the maximum of $ \alpha^{m}(t) $ over the time interval, and $ \alpha(0) $ was the maximum of $ \alpha^{m}(0) $ in all values of $ m $. …”
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Control of Wind-Power Systems Operating at Variable Wind Speeds to Optimize Energy Capture by Cristian Paul Chioncel, Samuel Ciucurita, Elisabeta Spunei

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Predictive value of the National Early Warning Score 2 for hospitalised patients with viral respiratory illness is improved by the addition of inspired oxygen fraction as a weighte... by Jonathan Clarke, David Grant, Guy Glover, Nishita Desai, Jack Gallifant

“…Sensitivity, positive predictive value (PPV), number needed to evaluate (NNE) and area under the receiver operating characteristic curve (AUROC) were calculated. …”
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Estimation of Fuel Cell Power Demand on Commercial Vehicles Based on Improved Multiple Grey Prediction Method Considering Dynamic Time Window by Yuan Wang, Yingjia Li, Jianshan Lu, Hongbo Zhou

“…Results showed that the multiple grey method showed a better prediction performance than the other models, indicated by the lowest error value of 16.944% under the CHTC-HT condition, the lowest error value of 2.169% under stable conditions with less variable load and 1.930% under dynamic conditions with frequent load changes in field testing. …”
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