Time Of Occurrence Research Articles

Significant Influence of Cardiac Radiation Dose on the Risk of Cardiotoxicity in Patients Receiving Adjuvant Trastuzumab and Radiation Therapy for Breast Cancer.

This study aimed to analyze the incidence of cancer therapy-related cardiovascular toxicity (CTRCVT) and identify the radiation dosimetric and clinical risk factors for these events in patients with HER2-positive breast cancer. Data from 1,378 patients who were treated with curative surgery and adjuvant trastuzumab for breast cancer were retrospectively analyzed. A total of 959 patients underwent postoperative radiation therapy (RT), while 419 patients were managed without RT (no-RT). CTRCVT were categorized according to the time of occurrence in relation to trastuzumab as follows: during trastuzumab cycles (CTRCVT-during T) or after completing trastuzumab (CTRCVT-after T). The cardiac radiation dose was extracted from the RT plan of each individual patient. The incidence of and contributing factors for CTRCVT-during T and -after T were evaluated. After a median follow-up of 95.8 months (range, 4.3-181.1 months), 69 patients (5.0%) had experienced CTRCVT. CTRCVT-during T was detected in 41 patients (3.0%), and the 8-year rate of CTRCVT-after T was 2.2%. Of the patients developing CTRCVT-during T, 27 (2.0%) discontinued trastuzumab. The cardiac radiation doses were significantly associated with the risk of both CTRCVT-during T (odds ratio, 1.087; P = 0.001) and -after T (hazard ratio, 1.177; P <0.001). The 8-year rates of CTRCVT-after T were not significantly different between the no-RT and RT groups (2.0% vs. 2.4%, P = 0.956). However, the rate was significantly higher in patients with heart V25Gy ≥3% compared to those with heart V25Gy <3% (5.7% vs. 1.5%, P = 0.019). Patients who received <17 cycles of trastuzumab had worse oncological outcomes than those who received ≥17 cycles. Both CTRCVT-during T and -after T were associated with the cardiac radiation dose. Therefore, evaluation of the cardiac radiation dose is necessary to prevent early termination of trastuzumab treatment, which could lead to worse outcomes.

Multi-condition hawser tension prediction of offshore offloading system based on long and short-term memory network and transfer learning

Real-time prediction of hawser tension of the side-by-side oil offloading system of Floating Production Storage and Offloading (FPSO) can provide early warnings for hawser breakages and ship collision risk, thus improving structural, property, and environmental security. Although offline numerical models and Long Short-Term Memory (LSTM) could offer substantial precision, they confront intensive time costs in recalibrating or retraining models. This paper proposes an integration method of LSTM networks and transfer learning for real-time tension prediction considering inputs of actual remote wave elevations. We use short-term environmental data and numerical simulation data of correlated hawser tensions during offloading operations to train a pre-trained benchmark model for transfer learning. Then, a highly generalized and efficient transferred model is constructed by using a small sample to realize short-term tension predictions in time-varying environments. The results show the occurrence time and value of extreme tensions predicted by transfer learning nearly match the reference data, and their maximum errors are 3 s and 0.11, respectively, superior to LSTM direct training. Therefore, it provides sufficient demand for real-time prediction and early collision risk prevention in dynamically changing ocean environment. The research results could provide an alternative framework for intelligent monitoring of large-scale marine structures.

Role of warming trend in occurrence of record‐breaking high‐temperature events in China during the past 40 years

AbstractRecord high temperatures and heatwaves are increasingly being reported worldwide, sparking significant public concern. In a stable climate, occurrences of record‐breaking events (RBEs) should naturally decrease over time. Therefore, the increasing occurrence of record high temperatures signifies significant instability in the current climate change, potentially attributed to global warming. In this study, we aim to quantitatively investigate the impact of the warming trend on RBE occurrence by examining high‐temperature RBEs based on observations in China over the past 40 years. Additionally, we introduce statistical theory based on random processes to assess its applicability to real‐world scenarios. By comparing the frequency, intensity, and waiting time for RBEs derived from the original and detrended high‐temperature series‐, we find that approximately 10% of RBE frequency in Nanjing station over the past 40 years can be linked to the warming trend. Furthermore, the intensity of RBEs weakens and the occurrence time advances for the same reason. Especially, the increase in high‐temperature RBE frequency attributed to the upward temperature trend in the southwest region of China is estimated to be around 10%–20%, significantly surpassing that in other regions. Meanwhile, the observed RBE occurrence probability and intensity align with the theoretical results, while notable discrepancies exist in RBE prediction, highlighting the need for improvement in theory and skill for RBE forecasting given its complexity and uncertainty.

Bearing Electrical Erosion Signal Detection Technique Based on Current Signal Analysis for Electric Motors

Abstract In modern industries, enhancing the efficiency and performance of electric motors is a critical requirement. Pulse width modulation (PWM) inverters utilized to enhance the energy efficiency of electric motors generate complex shaft voltages and bearing currents, leading to bearing electrical erosion. This study proposes a new method for detecting high-frequency (HF) circulating current and electric discharge machining (EDM) current signals in bearings for electric motors. The proposed method utilizes common mode voltage (CMV) and bearing current data, analyzing the relationship between these signals. Subsequently, it applies filtering techniques and differentiation for signal preprocessing. The Interquartile Range (IQR) method is used to detect outliers, classify HF circulating current and EDM current signals, and perform time-series data clustering to determine the occurrence frequency and timing of EDM signals. Finally, the implementation outcomes of the proposed method are validated, and its classification efficacy is evaluated and benchmarked against established methodologies through a comprehensive performance analysis. The proposed technique is anticipated to be applicable to the maintenance and prediction of modern electric motors in future developments, contributing to enhanced durability and reliability.

Statistical Analysis of Atmospheric Delay Gradient and Rainfall Prediction in a Tropical Region

In recent years, precipitable water vapor has emerged as a key atmospheric parameter in weather prediction research. However, relying on only one parameter does not always accurately predict rainfall, as other atmospheric parameters also contribute to initiating rain events. In our previous study, we explored a methodology for rainfall forecasting based on the atmospheric delay gradient at an individual station in the tropical region. Commonly referred to as the atmospheric gradient, it accounts for the delay in GNSS signals due to changes in horizontal refractivity while propagating through the troposphere to the ground station. This paper discusses the spatial and temporal correlation of the gradient with precipitation occurring over a region. We have investigated different features, such as gradient magnitude, gradient convergence, and the flux of the atmospheric gradient, to propose potential nowcasting criteria for precipitation in the tropical climatic zone. The atmospheric gradient in the surrounding region orients toward the area of precipitation as the rain event approaches. This gradient gradually alters its orientation and converges toward the region of rainfall at the time of precipitation, introducing the concept of gradient convergence. This phenomenon results in an inward gradient flux at the time of the downpour, which presents a potential parameter for rainfall prediction over an area. We also proposed investigating area sizes of 4° × 4° or 8° × 8°, depending on the gradient feature, to establish a forecasting methodology for rainfall. The weather front in the tropical region begins to initiate 12 h before the actual time of occurrence and advances toward the area where it will have an impact from a more distant location. This article presents a detailed investigation of various features of the atmospheric gradient and its potential to nowcast rainfall for a region, as well as proposes the lead time for long-term weather predictions. Furthermore, a deep neural network has been employed to predict rainfall events for the next 6 h over an area in the tropical region.

Heterogeneous Online Computational Platform for GEM-Based Plasma Impurity Monitoring Systems

The fusion energy research field presents many intricate challenges that require resolution. Many diagnostic systems employed in experiments are approaching the limits of current technology. Implementing efficient measurements requires using an appropriate set of tools to facilitate the optimal utilization of hardware. Fusion energy measurements must provide low latency processing with the capacity for future improvements and the ability to handle complex data flows efficiently. The presented work addresses these requirements and describes the implementation of a high-performance, low-latency software platform with convenient development for soft X-ray (SXR) plasma impurities emission tracing—the Asynchronous Complex Computation Platform (AC2P). This article presents the architectural design, implementation details, and performance and latency measurements based on the raw data acquired from the WEST tokamak and laboratory tests. AC2P provides the tools to develop low-latency, multi-core, multi-device complex data flow graph scale-up solutions for measuring impurities in hot plasmas. The system has been designed to operate online during experiments, calculate the energy distribution, position and occurrence time of SXR photons, monitor the data stream’s quality and archive any abnormalities for subsequent offline verification and algorithm improvement. This article presents AC2P, which operates as part of the SXR measurement system on the WEST tokamak.

Research on Voltage Prediction Using LSTM Neural Networks and Dynamic Voltage Restorers Based on Novel Sliding Mode Variable Structure Control

To address the issue of uncertainty in the occurrence time of voltage sags in power grids, which affects power quality, a voltage state prediction method based on LSTM neural networks is proposed for predicting voltage states. For the problem of quickly and accurately compensating for voltage sags, a DVR system based on a new approach law of sliding mode variable structure control is proposed, which significantly reduces chattering, improves response speed, and enhances the robustness of the system. The stability of the system is proven based on Lyapunov stability theory. Simulation experiments are conducted to analyze the voltage state prediction effect based on the LSTM neural network and the compensation effect of the novel reaching law of sliding mode variable structure control under different levels of voltage sag, validating the effectiveness and correctness of the proposed solution.

Expected First Occurrence Time of Uncertain Future Events in One-Dimensional Linear Systems

The rapid advancement of machine learning algorithms has significantly enhanced tools for monitoring system health, making data-driven approaches predominant in Prognostics and Health Management (PHM). In contrast, model-based approaches have seen modest progress, as they are often constrained by the need for prior knowledge of specific governing equations, limiting their applicability to a wide range of problems. Recently, rigorous theoretical foundations have been established to extend dynamical systems theory by incorporating prognosis of uncertain events. This article leverages this formal framework to introduce and demonstrate a fundamental mathematical result for one-dimensional linear dynamical systems. The presented theorem offers an exact expression for calculating the expected time at which an event will first occur in the future. Unlike typical thresholds, this event is triggered by a hazard zone, defined as an uncertain event likelihood function over the system's state space. Applications of this theorem can be found in implementing real-time prognostic frameworks, where it is crucial to quickly estimate the magnitude of impending failures. Emphasis is placed on minimizing computational burden to facilitate prognostic decision-making.

Efficacy and safety of Shengjiang Xiexin decoction on irinotecan-induced diarrhea in small cell lung cancer patients: a multicenter, randomized, double-blind, placebo-controlled trial

BackgroundIrinotecan is a standard chemotherapeutic agent in small cell lung cancer (SCLC), however, as a common adverse reaction, diarrhea limits the use of irinotecan. Shengjiang Xiexin decoction (SXD) has been used in various gastrointestinal diseases in China two thousand years ago. We designed this clinical trial to supply more evidences on the use of SXD as prophylaxis for irinotecan-induced diarrhea, especially for high-risk population predicted by gene testing of uridine diphosphate glucuronosyl transferase 1A1 (UGT1A1).MethodsIn this clinical trial, 120 patients with SCLC were recruited from six hospitals in China. They received two cycles of chemotherapy, meanwhile they were randomized to receive SXD or placebo for 14 days of oral administration in each cycle of chemotherapy. The primary outcome is the incidence of diarrhea. And secondary outcomes include the the degree of diarrhea and neutropenia, the number of chemotherapy cycles with diarrhea, first occurrence time and duration of diarrhea. To evaluate the effect of SXD on the intestine, a rat model with delayed-onset diarrhea induced by irinotecan was established, and the expression of inflammatory factors including IL-1β, IL-6 and TNF-α, anti-inflammatory factors including IL-10, TGF- β in jejunal tissue was detected by ELISA.Results101 patients (53 in SXD group, 48 in placebo group) completed the trial. The incidence of diarrhea in SXD group and placebo group were 26.42% (14/53) and 52.08% (25/48), respectively (P < 0.05), and the degree of diarrhea also had significant differences (P < 0.05). In UGT1A1 high-risk population, the incidence of diarrhea in two groups were 9.09% and 66.67% (P < 0.05), but there was no significant differences in UGT1A1 low-risk population. The incidence of neutropenia with degree 1–3 between two groups was 20.75% vs 20.83%, 13.21% vs 18.57%, 9.43% vs 20.83% (P < 0.05). No severe adverse events were reported in any group. And animal studies had shown SXD reduced content of IL-1β, IL-6, TNF-α, increased content of IL-10, TGF-β in jejunum tissue.ConclusionsSXD had a prophylactic effect in the diarrhea induced by irinotecan, especially for UGT1A1 high-risk population, and this effect from SXD appeared to be maintained the completion of chemotherapy schedule. The mechanism of action of SXD was related to the regulation of inflammatory factors.Trial registration Chinese Clinical Trial Register: ChiCTR1800018490. Registered on 20 September 2018. https://www.chictr.org.cn/showproj.html?proj=25250. The preliminary protocol of this clinical study has been published in the journal “Trials” in the form of protocol before this paper (Deng et al. in Trials 21:370, 2020).

Using the Nasopalatine Canal for Enhanced Distribution in Severely Atrophic Maxilla With Immediate Loading of Zygomatic Implants: An 8-Year Retrospective Cohort Study.

This study presents retrospective 8-year clinical performance data from a patient cohort treated with immediately loaded maxillary full prostheses supported by zygomatic implants combined with implants placed in the nasopalatine canal, as a treatment for severely resorbed edentulous ridges. A retrospective analysis was conducted on data of maxillary edentulous patients with severe bone atrophy. All of them received zygomatic implants in combination with an implant placed in the nasopalatine foramen and an immediately loaded fixed temporary prosthesis in the first 24 hours. The frequency of major and minor adverse events was presented according to the time of occurrence. Fifteen patients were included in the study, without cases of implant loss or sensitivity in the nasopalatine region were observed up to 8 years. Only 1 major complication was observed, whereas minor complications were more frequent. In conclusion, this 8-year follow-up study demonstrated that the nasopalatine canal can be considered a viable implant site, with no major risks, to improve biomechanics by enabling a polygonal distribution in severely atrophic maxillae treated with zygomatic implants and immediate loading.

Alterations of Excitation-Inhibition Balance and Brain Network Dynamics Support Sensory Deprivation Theory in Presbycusis.

Sensory deprivation theory is an important hypothesis involving potential pathways between hearing loss and cognitive impairment in patients with presbycusis. The theory suggests that prolonged auditory deprivation in presbycusis, including neural deafferentation, cortical reallocation, and atrophy, causes long-lasting changes and reorganization in brain structure and function. However, neurophysiological changes underlying the cognition-ear link have not been explored. In this study, we recruited 98 presbycusis patients and 60 healthy controls and examined the differences between the two groups in gamma-aminobutyric acid (GABA) and glutamate (Glu) levels in bilateral auditory cortex, excitation-inhibition (E/I) balance (Glu/GABA ratio), dynamic functional network connectivity (dFNC), hearing ability and cognitive performance. Then, correlations with each other were investigated and variables with statistical significance were further analyzed using the PROCESS Macro in SPSS. GABA levels in right auditory cortex and Glu levels in bilateral auditory cortex were lower but E/I balance in right auditory cortex were higher in presbycusis patients compared to healthy controls. Hearing assessments and cognitive performance were worse in presbycusis patients. Three recurring connectivity states were identified after dFNC analysis: State 1 (least frequent, middle-high dFNC strength with negative functional connectivity), State 2 (high dFNC strength), and State 3 (most frequent, low dFNC strength). The occurrence and dwell time of State 3 were higher, on the other hand, the dwell time of State 2 decreased in patients with presbycusis compared to healthy controls. In patients with presbycusis, worse hearing assessments and cognition were correlated with decreased GABA levels, increased E/I balance, and aberrant dFNC, decreased GABA levels and increased E/I balance were correlated with decreased occurrence and dwell time in State 3. In the mediation model, the fractional windows, as well as dwell time in State 3, mediated the relationship between the E/I balance in right auditory cortex and episodic memory (Auditory Verbal Learning Test, AVLT) in presbycusis. Moreover, in patients with presbycusis, we found that worse hearing loss contribute to lower GABA levels, higher E/I balance, and further impact aberrant dFNC, which caused lower AVLT scores. Overall, the results suggest that a shift in E/I balance in right auditory cortex plays an important role in cognition-ear link reorganization and provide evidence for sensory deprivation theory, enhancing our understanding the connection between neurophysiological changes and cognitive impairment in presbycusis. In presbycusis patients, E/I balance may serve as a potential neuroimaging marker for exploring and predicting cognitive impairment.

Occurrence of Gravitational Collapse in the Accreting Neutron Stars of Binary-driven Hypernovae

The binary-driven hypernova (BdHN) model proposes long gamma-ray bursts (GRBs) originate in binaries composed of a carbon–oxygen (CO) star and a neutron star (NS) companion. The CO core collapse generates a newborn NS and a supernova that triggers the GRB by accreting onto the NSs, rapidly transferring mass and angular momentum to them. This article aims to determine the conditions under which a black hole (BH) forms from NS collapse induced by the accretion and the impact on the GRB’s observational properties and taxonomy. We perform three-dimensional, smoothed particle hydrodynamics simulations of BdHNe using up-to-date NS nuclear equations of state, with and without hyperons, and calculate the structure evolution in full general relativity. We assess the binary parameters leading either NS in the binary to the critical mass for gravitational collapse into a BH and its occurrence time, t col. We include a nonzero angular momentum of the NSs and find that t col ranges from a few tens of seconds to hours for decreasing NS initial angular momentum values. BdHNe I are the most compact (about 5 minute orbital period), promptly form a BH, and release ≳1052 erg of energy. They form NS–BH binaries with tens of kiloyears merger timescales by gravitational-wave emission. BdHNe II and III do not form BHs, and release ∼1050–1052 erg and ≲1050 erg of energy, respectively. They form NS–NS binaries with a range of merger timescales larger than for NS–BH binaries. In some compact BdHNe II, either NS can become supramassive, i.e., above the critical mass of a nonrotating NS. Magnetic braking by a 1013 G field can delay BH formation, leading to BH–BH or NS–BH with tens of kiloyears merger timescales.

Using acoustic emission to understand the early-age reaction and cracking evolution of alkali-activated slag-brick powder paste

Real-time monitoring and accurately understanding the continuous occurring psychical-chemical characterization during the hardening process of alkali-activated materials present a formidable challenge. In this study, the early-age reaction process of alkali-activated slag-waste brick powder paste (ASWP) was in-situ and continuous monitored by using acoustic emission (AE) system and temperature. A novel machine learning method was employed to categorize the evolution of AE signals into three distinct stages: reaction acceleration, reaction stabilization and volume shrinkage stage.During reaction acceleration stage (0-2h), the waste brick powder (WBP) increased AE counts rate (4000-7300 counts/h), with RT values exceeding 200μs, indicating the settlement of WBP. Additionally, WBP reduced the high r-value AE activity in volume shrinkage stage, effectively mitigated the drastic volume shrinkage, and delayed its occurrence time by approximately 4 hours. Semi-quantitative analyses of FTIR and TG-DTG indicate that WBP reduced gel phase formation in the early-age stage, decreasing the relative areas in Q2 site by 16% before 36 hours. However, WBP positively impacted ASWP hydration at long ages, increasing Q2 site d areas by 60%-100%. AE technique offers a new perspective for in-depth understanding of the reaction mechanism and microstructural development of alkali-activated materials in situ and continuously.

Impact of Three Gorges Dam construction on spatiotemporal variations in the hydrodynamic regime of Poyang Lake (China)

As an important large-scale river-connected lake in the middle–lower reaches of the Yangtze River, Poyang Lake has complex interactions with the main stream of the river. The full operation of the Three Gorges Dam (TGD) on the main stream of the Yangtze River has caused substantial changes in the relationship between the river and the lake, and the hydrological and hydrodynamic regime of Poyang Lake have also shown obvious variations in response. This study constructed a 2D hydrodynamic model of Poyang Lake based on GPU acceleration to realize a long-term simulation of the water flow evolution of Poyang Lake. By comparing the differences in water level at Hukou station between 20-year periods before and after TGD construction, the impact of TGD construction on Poyang Lake was characterized. Results showed that in comparison with the values for the pre-dam period, the water level of Poyang Lake decreased by 0.4–2.0 m and the flow velocity increased by 0.01–0.04 m/s in the post-dam period, and both showed a trend of reduction spatially from the north toward the south. Additionally, the inundation area of the lake decreased by 9 %, the 10-m characteristic water level at Xingzi station advanced by 27 days, the duration of low water extended by 37 days, and in typical dry, normal, and wet years, the time of occurrence of low water advanced. Moreover, TGD construction has aggravated the conditions of Poyang Lake in the dry season. The findings of this study are of great importance in relation to refining the spatiotemporal distribution characteristics of habitats, and supporting further investigation of the changes in the aquatic ecosystem of Poyang Lake under TGD regulation.

Development and Application of a Tornado Database for the Chinese Mainland

This study develops a preliminary tornado database for the Chinese mainland using information provided by the Yearbook of Meteorological Disasters in China (YMDC) from 2003 to 2019 and other public media report data. This database includes tornado occurrence time, geographical location, intensity, and damage descriptions. A modified Enhanced Fujita (EF) scale criterion adapted to the description of the damage indicator (DI) and degree of damage (DOD) in the YMDC and media reports is presented to better estimate the tornado intensity. The spatial and temporal distribution characteristics of tornadoes in Chinese mainland are examined. A stochastic simulation algorithm is proposed to perform a risk assessment of tornado hazards. The occurrence of tornadoes is randomly sampled using negative binomial distribution. The kernel density estimation (KDE) method based on the Gaussian kernel is applied to estimate the probability density of geographically dependent tornado occurrence before randomly generating tornado occurrence locations. The probability and conditional probability of tornado occurrence with different intensity levels are calculated for different counties in Jiangsu and Guangdong Provinces using Bayes’ theorem. The database provides a forward step toward rational assessment of tornado-induced disasters in Chinese mainland. The database can be accessed at https://doi.org/10.4121/19801633.v1 (Zhang et al., 2022).

Space-time modeling of cascading hazards: Chaining wildfires, rainfall and landslide events through machine learning

The current study sets out to explore yearly landslide susceptibility dynamics on slopes regularly affected by fires. To do so, two yearly inventories have been generated, one for the landslides and one for the wildfires, for an area of approximately 2 km2 and for a period of 24 years. It is important to stress that space–time data-driven models employed for susceptibility assessment are relatively new, and their application so far has mostly linked landslide occurrences to the precipitation trigger and the standard morphometric characteristics of the landscape at hand. Here we also consider an additional element of disturbance to the slope equilibrium, in the form of burnt areas tested from one up to three years priors to the reference landslide occurrence time. The relevance of the wildfire spatiotemporal signal is tested as part of a multi-variate modeling procedure. The results highlight at least a 10 % performance increase when these wildfire-related predictors are featured (from an average AUC of 0.75 to 0.85 in a random forest modeling framework). The associated yearly variations in the landslide occurrence probability are translated into individual maps, stressing the extent to which the standard and static definition of susceptibility does not hold especially in the context of multiple hazards and in an urban setting such as the Camaldoli hills (Naples, Italy) we chose for our test site.

An integrated approach of zero defect manufacturing and process mining to avoid defect occurrence in production and improve sustainability

Purpose This paper aims to integrate zero defect manufacturing (ZDM) with process mining (PM) to avoid defect occurrence during production and improve sustainability. Design/methodology/approach The method is developed based on literature review in ZDM and PM. It uses PM for process discovery as an initial strategy in priority to predict-prevent strategies of ZDM. Findings It presents the applicability of the proposed approach in observing manufacturing process behavior, identifying dynamic causes of defects during production, predicting the time of defect occurrence and preventing defective products. It also identifies, explains and measures criteria for environmental, social and economic pillars of sustainability affected by defects and presents the impacts of the proposed approach on sustainability improvement. Originality/value The extended view of this research, as well as its analytical approach, helps practitioners to develop their ZDM and PM approaches more holistically. The practical application of this research is illustrated through implementing it in a real-life manufacturing case, where the outcomes prove its applicability in avoiding defect occurrence and improving all three pillars of sustainability.

Wave–Tide–Surge Interaction Modulates Storm Waves in the Bohai Sea

Typhoons, extratropical cyclones, and cold fronts cause strong winds leading to storm surges and waves in the Bohai Sea. A wave–flow coupled numerical model is established for storm events observed in 2022 caused by three weather systems, to investigate how storm waves are modulated by wave–tide–surge interaction (WTSI). Wave response is basically controlled by water level change in coastal areas, where bottom friction or breaking dominates the energy dissipation, and determined by the current field in deep water by altering whitecapping. Wave height increases/decreases are induced by positive/negative water level or obtuse/acute wave–current interaction angle, leading to six types of field patterns for significant wave height (Hs) responses. For the three storm events, Hs basically changed within ±5% in central deep water, while the maximum increase/decrease reached 160%/−60% in the coastal area of Laizhou Bay/Liaodong Bay. Based on maximum Hs and its occurrence time, WTSI modulation is manifested as the superposition effect of wave–tide and wave–surge interactions in both space and time scales, and occurrence time depends more on tide than surge for all three storms. The enhancement/abatement of WTSI modulation happens for consistent/opposite changing trends of wave–tide and wave–surge interaction, with the ultimate result showing the side with a higher effect.

Effect of body mass index on mortality for diabetic patients with aortic stenosis

Abstract Background Several studies suggest an "obesity paradox," associating obesity with better cardiovascular outcomes compared to normal or underweight individuals (1-3). Purpose This study explores the impact of body mass index (BMI) on mortality in patients with diabetic mellitus (DM) and aortic stenosis (AS). Methods This is a retrospective cohort study conducted at a tertiary centre. Between 2014 and 2019, patients with DM who underwent echocardiography were screened (4). Patients were enrolled if AS was diagnosed, according to established guidelines (5). Two echocardiography specialists independently reviewed the echocardiography in the cohort. The index date of the DM-AS cohort was the first AS diagnosis by echocardiography, and detailed data collection methods are described in previous studies (6,7). Patients were categorized as underweight, normal weight, or obese based on BMI (&amp;lt;18.5, 18.5 to 27, and &amp;gt;27 kg/m2, respectively). Outcomes included all-cause mortality, cardiovascular, and non-cardiovascular death, which were adjudicated by a central committee. The occurrence times of the outcomes of interest were determined using diagnosis codes from electronic health records, and medical records were reviewed until the last clinical visit or death. Results Among 74,835 DM patients, 734 had AS. Normal weight comprised 65.5% (n=481), underweight 4.1% (N=30), and 30.4% were obese. With a median follow-up time of 34 months, 285 patients (38.8%) experienced outcomes of death, comprising 93 patients (32.7%) with cardiovascular death and 192 patients (67.3%) with non- cardiovascular death. Underweight patients had significantly higher all-cause mortality (HR 1.96, 95% CI 1.22 – 3.14, p = 0.005), while obese patients had significantly lower mortality (HR 0.79, 95% CI 0.68 - 0.91, p=0.001) compared to the normal group. Regarding etiologies, underweight patients had a higher risk of non- cardiovascular death (HR 2.47, 95% CI 1.44-4.25, p = 0.001), while obese patients had a lower risk of cardiovascular death (HR 0.66, 95% CI 0.50-0.86, p=0.003). Subgroup analysis showed a consistent trend without significant interaction. To elucidate the interaction of BMI as a continuous variable with outcomes, restricted cubic spline analysis was applied. Cardiovascular death showed a negative association with BMI across available BMI levels, and non-cardiovascular death exhibited a U curve, with the lowest hazard ratio occurring when BMI was between 25 to 30. Conclusion Our study underscored the significance of both cardiovascular and non-cardiovascular deaths as crucial contributors to overall mortality in DM patients with AS. Being underweight is associated with increased non- cardiovascular death, while obesity is linked to less cardiovascular death. Proposed mechanisms include reduced frailty, enhanced tolerance to guideline-directed medical therapies (GDMTs), and heightened disease awareness in the obese group (8,9).Kaplan–Meier analysis for outcomesAssociation between BMI and outcomes

An exploratory study of alternative life experiences in comparison to transcendental near‐death experiences

AbstractThe term near‐death experience (NDE) generally refers to a state of altered consciousness that can occur during real or presumed near‐death circumstances and/or life‐threatening incidents. The NDE usually includes the impression of being conscious while out of and/or away from the physical body, often accompanied by other specific features. Furthermore, when the experient has the impression of being in a perceived locality that transcends the observable physical Earth, it is referred to by researchers as a transcendental NDE. Whereas transcendental NDEs have been widely studied, there is also another type of experience that can occur under similar life‐threatening conditions that I refer to as an alternative life experience (ALE), which consists of a perception of living another alternative life where the experient is aware of the self, but does not believe at the time of occurrence that they are either out of or away from their physical body. After providing a total of 15 examples, I note some similarities and differences between ALEs and transcendental NDEs while providing some qualitative and quantitative results, suggesting that ALEs might be similar to some aspects of transcendental NDEs despite their neglect in the study of altered states of consciousness during near‐death circumstances. I further postulate that ALEs might be subjective psychological experiences of dissociation and/or absorption. It is then pointed out that symptoms of derealization are a common ALE aftereffect and so an awareness of that association is stressed as having therapeutic importance.