Length Of Interval Research Articles

Assessing the impact of hard data patterns on Bayesian Maximum Entropy: a simulation study.

This study empirically tested the robustness of Bayesian Maximum Entropy (BME) in predicting spatiotemporal data, with an emphasis on skewness, sample size, and spatial dependency level. Simulated data, both Gaussian and non-Gaussian, were generated using the unconditional sequential simulation method, with sample sizes ranging from 100 to 500 at the interval length of 50 and varying skewness (0, 1, 3, 6 and 9) and spatial dependency levels (weak, moderate, and strong). Findings revealed sample size variations and spatial dependence levels did not significantly influence BME prediction's Mean Square Error (MSE) and bias. While skewness significantly impacted MSE (p-value < 0.001), bias remained unaffected. Moreover, skewness and spatial dependence interactions affected both MSE and bias. Despite this, BME proved robust to sample size and skewness, demonstrating a negligible MSE on the graphical plot (heatmap).

Evaluation of BLE Star Network for Wireless Wearable Prosthesis/Orthosis Controller

Concomitant improvements in wireless communication and sensor technologies have increased capabilities of wearable biosensors. These improvements have not transferred to wireless prosthesis/orthosis controllers, in part due to strict latency and power consumption requirements. We used a Bluetooth Low Energy 5.3 (BLE) network to study the influence of the connection interval (10–100 ms) and event length (2500–7500 μs), ranges appropriate for real-time myoelectric prosthesis/orthosis control on the maximum network size, power consumption, and latency. The number of connections increased from 4 to 12 as the connection interval increased from 10 to 50 ms (event length of 2500 μs). For connection intervals ≤50 ms, the number of connections reduced by ≥50% with the increasing event length. At a connection interval of 100 ms, little change was observed in the number of connections vs. event length. Across event lengths, increasing the connection interval from 10 to 100 ms decreased the average power consumed by approximately 16%. Latency measurements showed that an average of one connection interval (maximum of just over two) elapses between the application of the signal at the peripheral node ADC input and its detection on the central node. Overall, reducing the latency using shorter connection intervals reduces the maximum number of connections and increases power consumption.

The Statistics of Parametrized Syncmers in a Simple Mutation Process Without Spurious Matches.

Introduction: Often, bioinformatics uses summary sketches to analyze next-generation sequencing data, but most sketches are not well understood statistically. Under a simple mutation model, Blanca et al. analyzed complete sketches, that is, the complete set of unassembled k-mers, from two closely related sequences. The analysis extracted a point mutation parameter θ quantifying the evolutionary distance between the two sequences. Methods: We extend the results of Blanca et al. for complete sketches to parametrized syncmer sketches with downsampling. A syncmer sketch can sample k-mers much more sparsely than a complete sketch. Consider the following simple mutation model disallowing insertions or deletions. Consider a reference sequence A (e.g., a subsequence from a reference genome), and mutate each nucleotide in it independently with probability θ to produce a mutated sequence B (corresponding to, e.g., a set of reads or draft assembly of a related genome). Then, syncmer counts alone yield an approximate Gaussian distribution for estimating θ. The assumption disallowing insertions and deletions motivates a check on the lengths of A and B. The syncmer count from B yields an approximate Gaussian distribution for its length, and a p-value can test the length of B against the length of A using syncmer counts alone. Results: The Gaussian distributions permit syncmer counts alone to estimate θ and mutated sequence length with a known sampling error. Under some circumstances, the results provide the sampling error for the Mash containment index when applied to syncmer counts. Conclusions: The approximate Gaussian distributions provide hypothesis tests and confidence intervals for phylogenetic distance and sequence length. Our methods are likely to generalize to sketches other than syncmers and may be useful in assembling reads and related applications.

A Nekhoroshev-type theorem for the nonlinear Schrödinger equations on the d-dimensional torus

We prove a Nekhoroshev type long time stability result for the following nonlinear Schrödinger (NLS) equations on the d-dimensional torus i u t = − △ u + V ∗ u + ∂ F ( | u | 2 ) ∂ u ¯ ( u , u ¯ ) , x ∈ T d , t ∈ R , where V is a smooth convolution potential, F ( z ) is a real-valued polynomial function in z satisfying F ( 0 ) = F ′ ( 0 ) = 0 . More precisely, it is proved that in modified Sobolev space (see (2)) if the norm of initial datum is smaller than ε ( 0 < ε ≪ 1 ) , then the corresponding solution is bounded by 2 ε over time-intervals of length e e 1 ε . The result generalizes the 1-dimensional case in L. Biasco, J.E. Massetti, M. Procesi. [An abstract Birkhoff normal form theorem and exponential type stability of the 1d NLS. Comm Math Phys. 2020;375(3):2089–2153] to d-dimensional NLS equations.

A pilot study of the impact of repeated blink refrainment on ocular surface temperature and the interblink period.

This study examines a potential stress test of repeated blink refrainment and its effects on the interblink period and the rate of evaporative ocular surface cooling. Such a test could aid in the study of computer vision syndrome, in which screen users unconsciously delay blinking, leading to onset of symptoms. This study aimed to examine the relationship between the length of the maximum achievable interblink time and the rate of ocular surface cooling under stress test conditions of repeated refrainment from blinking for as long as possible. Subjects acclimated to the examination room for 10 minutes before measurement and then were asked to hold the eyes open and refrain from blinking for as long as possible (the maximum blink interval), while ocular surface temperature was recorded using an infrared thermographic video camera. Subjects completed 20 trials with four successive blinks separating each trial. Fifteen subjects (8 female and 7 male subjects) completed the study. The grand mean ocular surface cooling rate was -0.027°C/s (range, -0.338 to +0.014°C/s). A faster ocular surface cooling rate was significantly related to an exponentially shorter maximum blink interval (p<0.001). An increasing number of trials was related to a clinically insignificant increase in the length of the maximum blink interval overall, and a post hoc analysis revealed subject subgroups for whom the stress test was effective or ineffective. The ocular surface evaporatively cools exponentially during periods of blink refrainment. With a subgroup of subjects with initially stable tear films and normal lipid layer thickness, cumulative tear film stress from repeated, longer-term blink refrainment could contribute to tear evaporation and symptoms of computer vision syndrome.

Atrial Topology for a Unified Understanding of Typical and Atypical Flutter.

Macroreentry stands as the predominant mechanism of typical and atypical flutter. Despite advances in mapping, many aspects of macroreentrant atrial tachycardia remain unsolved. In this translational study, we applied principles of topology to understand the activation patterns, entrainment characteristics, and ablation responses in a large clinical macroreentrant atrial tachycardia database. Because the atrium can be topologically seen as a closed sphere with holes, we used a computational fixed spherical mesh model with a finite number of holes to induce and analyze macroreentrant atrial tachycardia. The ensuing insights were used to interpret high-density activation maps, postpacing interval-tachycardia cycle length values (difference between postpacing interval and tachycardia cycle length), and ablation response in 131 cases of typical and atypical flutter (n=106 left atrium, n=25 right atrium). Modeling of macroreentrant atrial tachycardia revealed that reentry on closed surfaces consistently manifests itself as paired rotation and that an odd number of critical boundaries is mathematically impossible. Together with mathematical confirmation by the index theorem, this led to a unifying construct that could explain the number of loops, difference between postpacing interval and tachycardia cycle length values, and ablation outcomes (termination, no change, or prolongation in tachycardia cycle length) in all 131 cases. Combining topology with the index theorem offers a novel and cohesive framework for understanding and managing typical and atypical flutter.

Visual Implicit Pre-Cueing Improves Response Time in Decision-Making in Dyslexic Children.

This study aimed to examine the effect of visual pre-cueing presented at different time intervals in the response time of dyslexic and non-dyslexic children. Fifteen dyslexic and 15 non-dyslexic children performed a computerised four-choice reaction time task across four conditions: no pre-cue and a 43-ms time interval (or duration) of a centralised dot appearing in the stimulus circle at 43, 86 or 129 ms prior to the stimulus. Each condition was repeated eight times, totaling 32 trials, and presented in a random order. Response correctness and response times were recorded for each trial, and z-scores were obtained by standardising performance in the three pre-cued conditions relative to the no pre-cue condition. Dyslexic children took longer to respond in the task than non-dyslexic children. Both dyslexic and non-dyslexic children had faster response times in the pre-cued conditions than in the conditions without the pre-cue. These lower response times were inversely correlated with the length of the pre-cueing interval. These results suggest that dyslexic children use visual pre-cueing to improve decision-making. The ability of dyslexic children to use pre-cues may offer an interesting avenue for the exploration of interventions aimed at minimising behavioural and cognitive difficulties resulting from dyslexia.

Estimation of mean using under-reported and overdispersed count data

Count data arising in various fields of applications are often under-reported. Ignoring undercount naturally leads to biased estimators and inaccurate confidence intervals. Further, overdispersion in count data may arise due to inherent heterogeneity of the data. Negative Binomial distribution is a viable candidate for modeling overdispersed count data. However, in presence of undercount the negative binomial model needs to be adjusted. In this paper, we shall develop likelihood-based methodologies for estimation of mean using validation data after accounting for underreporting and overdispersion. The impact of ignoring undercount on the coverage and length of the confidence intervals is investigated using extensive numerical studies. The study is supplemented with a real-life data analysis.

Entanglement in ( 1+1 )-dimensional free scalar field theory: Tiptoeing between continuum and discrete formulations

We review some classic works on ground state entanglement entropy in (1+1)-dimensional free scalar field theory. We point out identifications between the methods for the calculation of entanglement entropy and we show how the formalism developed for the discretized theory can be utilized in order to obtain results in the continuous theory. We specify the entanglement spectrum and we calculate the entanglement entropy for the theory defined on an interval of finite length L. Finally, we derive the modular Hamiltonian directly, without using the modular flow, via the continuum limit of the expressions obtained in the discretized theory. In a specific coordinate system, the modular Hamiltonian assumes the form of a free field Hamiltonian on the Rindler wedge. Published by the American Physical Society 2024

Population changes in a Southern Ocean krill predator point towards regional Antarctic sea ice declines

While foraging, marine predators integrate information about the environment often across wide-ranging oceanic foraging grounds and reflect these in population parameters. One such species, the southern right whale (Eubalaena australis; SRW) has shown alterations to foraging behaviour, declines in body condition, and reduced reproductive rates after 2009 in the South African population. As capital breeders, these changes suggest decreased availability of their main prey at high-latitudes, Antarctic krill (Euphausia superba). This study analysed environmental factors affecting prey availability for this population over the past 40 years, finding a notable southward contraction in sea ice, a 15–30% decline in sea ice concentration, and a more than two-fold increase in primary production metrics after 2008. These environmental conditions are less supportive of Antarctic krill recruitment in known SRW foraging grounds. Additionally, marginal ice zone, sea ice concentration and two primary production metrics were determined to be either regionally significant or marginally significant predictors of calving interval length when analysed using a linear model. Findings highlight the vulnerability of recovering baleen whale populations to climate change and show how capital breeders serve as sentinels of ecosystem changes in regions that are difficult or costly to study.

Comparison of different concentrations atropine in controlling children and adolescent myopia: an umbrella review of systematic reviews and meta-analyses.

To evaluate the myopia control effect of different concentrations atropine in children and adolescent. Meta-analyses and systematic reviews available in the Pubmed, Embase, and Cochrane Library databases from the databases' inception to August 2023 were searched to evaluate the efficacy and tolerability of different concentrations' atropine in controlling myopia progression. Overall effects were performed using random-effects model. AMSTAR 2 tool was used to assess the quality of included studies. Prespecified outcomes were weight mean difference (WMD) with 95% credible interval (95% CI) of annual spherical equivalent refraction (SER) changes and annual axial length (AL) changes. 19 systematic reviews/meta-analyses of different atropine concentrations were included in the analysis. 14 studies reported SER changes, and 17 reported AL changes. In terms of the studies' overall methodological quality level (measured using AMSTAR 2), 1 study was rated high, 7 moderate, 7 low, and 4 critically low. The 0.01% atropine was found to have statistically significance (annual SER change WMD 0.27 [95% CI 0.21 - 0.34] D/year; annual AL change WMD -0.09 [95% CI -0.1 to -0.07]) mm/year), 0.05% atropine was preferred considering efficacy and tolerability (annual SER change WMD 0.54 [95% CI 0.49 - 0.58] D/year; annual AL change WMD -0.21 [95% CI -0.12 to -0.02]) mm/year). Different atropine concentrations alleviated children and adolescent myopia progression. However, higher-quality evidence and further investigation are needed to clarify the dose-response relationship, and practical guidelines must be developed to determine myopia control efficacy.

Wavelet analysis of low-frequency quasi-periodic oscillations in MAXI J1803−298 observed with Insight-HXMT and NICER

Abstract With data observed by the Hard X-ray Modulation Telescope (Insight-HXMT) and the Neutron star Interior Composition Explorer (NICER), we study low-frequency quasi-periodic oscillations (LFQPOs) of the black hole candidate MAXI J1803−298 during the 2021 outburst. Based on hardness intensity diagram and difference of the QPOs properties, Type-C and Type-B QPOs are found in the low-hard state and soft intermediate state, respectively. After searching for and classifying QPOs in Fourier domains, we extract the QPO component and study it with wavelet analysis. The QPO and no-QPO time intervals are separated by the confidence level, so that the S-factor, which is defined as the ratio of the QPO time interval to the total length of good time interval, is calculated. We found S-factors decrease with QPOs frequency for Type-C QPOs but stay stable around zero for Type-B QPOs. The relation of S-factor of Type-C QPOs and photon energy, the correlation of S-factor and counts are also studied. Different correlation of S-factor and counts for different energy bands indicates different origins of QPOs in high energy and low energy bands, which may be due to a dual-corona scenario.

Safety of 3-month flushing interval for prevention of occlusion in totally implantable venous access ports: An analysis focused on intraluminal clots.

This study aimed to assess the safety and feasibility of a 3-month flushing interval for totally implantable venous access ports (TIVAPs), particularly regarding intraluminal clot formation. Between May 2017 and September 2018, we established a single-center cohort of 151 patients who were referred for TIVAP removal and categorized them into three flushing-interval groups: A (⩽1 month), B (1-2 months), and C (2-3 months). Odds ratios (OR) with 95% confidence intervals (CI) were computed using logistic regression to determine the risk of intraluminal clot occurrence. To compare clot lengths among the groups, we employed linear regression. Restricted cubic splines were used to model the flushing interval as a continuous variable. Compared to Group A, Groups B and C had adjusted ORs of 0.82 (0.35-1.92) and 0.78 (0.29-2.11) for intraluminal clot risk. Occlusion was rare (1/151; 0.7%) and successfully treated with mechanical recanalization. Adjusted differences in clot length compared to Group A were 0.01 (-0.85 to 0.87) for Group B and -0.23 (-1.21 to 0.76) for Group C. Spline regression analysis showed no significant association between the flushing interval and clot length (p for trend = 0.84). The incidence and burden of intraluminal clots did not increase significantly within the first 3 months. Occlusion was rare, even in the presence of clots, and was successfully treated. Therefore, a 3-month flushing interval appears to be a safe and practical option, aligning with the common recommendation for surveillance intervals in patients with cancer.

ENHANCING WEIGHTED FUZZY TIME SERIES FORECASTING THROUGH PARTICLE SWARM OPTIMIZATION

Climate change is a complex process that has far-reaching consequences for daily living. Temperature is one of the climatic features. Knowing its future value through a forecasting model is critical, as it aids in earlier strategic decision-making. Without considering spatial factors, this study investigates an Air Temperature variable forecasting. Weighted Fuzzy Time Series (WFTS) is one of the forecasting techniques. Furthermore, the length of the interval and the extent to which previous values (Order length) are utilized in predicting the subsequent value are pivotal factors in WFTS modelization and its forecasting accuracy. Therefore, this research investigates the interval length and the Order length of the WFTS through the Particle Swarm Optimization (PSO) approach. The variable used is the air temperature in Malang, Indonesia. The dataset is taken from BMKG-Indonesia. The forecasting performance of classical WFTS is enhanced by setting an appropriate order level and employing Particle Swarm Optimization (PSO) to determine the optimal interval fuzzy length. As indicated by the Evaluation matrices in the result section, the proposed optimization overtaken the classical WFTS in term of accuracy. The evaluation indicates a Mean Absolute Percentage Error (MAPE) value of 1.25 and a Root Mean Square Error (RMSE) of 0.32 for the Proposed model. In contrast, the classical WFTS demonstrates a MAPE of 2.26 and RMSE of 0.58. The implementation of the PSO provides solid insights for Air temperature forecasting accuracy.

Forecasting Non-stationary Time Series Using Deep Learning in a Fuzzy Time Series Framework and its Application to Stock Markets

Non-stationary time series prediction is challenging due to its dynamic and complex nature. Fuzzy time series models offer a promising solution for forecasting such data, but a key challenge lies in partitioning the universe of discourse, which significantly impacts forecasting accuracy. Traditional fuzzy time series models often use equal-length interval partitioning, which is more suited for stationary data and limits their adaptability to non-stationary time series. This paper introduces a novel variable-length interval partitioning method designed specifically for non-stationary time series. The developed method combines a Long Short-Term Memory (LSTM) Autoencoder with K-means clustering, enabling dynamic, data-driven partitioning that adapts to the changing characteristics of the data. The LSTM Autoencoder encodes the time series, which is clustered using K-means, and intervals are defined based on cluster centers. Furthermore, the Variable Length Interval Partitioning-based Fuzzy Time Series model (VLIFTS) is developed by incorporating this partitioning method and the concepts of Markov chain and transition probability matrix. In this model, fuzzy sets are viewed as states of a Markov chain, and transition probabilities are used in the forecasting phase. The model is validated on stock market indices Nifty 50, NASDAQ, S&amp;P 500, and Dow Jones. Stationarity and heteroscedasticity are tested using Augmented Dickey-Fuller (ADF) and Levene's tests respectively. Statistical forecast accuracy metrics Root Mean Squared Error (RMSE) and Mean Absolute Percent Error (MAPE) show that VLIFTS significantly improves forecasting accuracy over traditional models. This hybrid approach enhances fuzzy time series modelling and can be applied to various non-stationary time series forecasting problems.

Vibration characteristics of a pretwisted multi-blade-shaft system with blade stiffness mismatch

The substructure mode synthesis method is employed to establish a mathematical model in this paper. The main body is represented by shaft, while the branching components are represented by blades. By solving this model, accurate frequency results of the rotating blade-shaft system are obtained at a high computational speed that meets engineering requirements. The resulting mode diagram aligns with that of the finite element model. Utilizing this model, the stiffness detuning of the rotating blade shaft system is investigated through a combination of surrogate modeling and ant colony algorithm, leading to several significant findings. It is observed that an increase in the standard deviation of stiffness detuning amplifies the length of frequency interval while minimally affecting the frequency mean value. Moreover, an increase in average stiffness expands the interval length for system frequencies. Additionally, higher rotational speeds reduce the interval length for blade-dominant vibrations but extend it for shaft-dominant vibrations.

Delays in Presentation, Diagnosis, and Treatment Among Patients With GI Cancer in Southwest Nigeria.

The incidence of GI cancers is increasing in sub-Saharan African countries. We described the oncological care pathway and assessed presentation, diagnosis, and treatment intervals and delays among patients with GI cancer who presented to the Obafemi Awolowo University Teaching Hospitals Complex in Ile-Ife, Nigeria. We analyzed data from 545 patients with GI cancer in the African Research Group for Oncology (ARGO) database. We defined presentation interval as the interval between symptom onset and presentation to tertiary hospital, diagnostic interval as between presentation and diagnosis, and treatment interval as between diagnosis and initiation of treatment. We considered >3 months, >1 month, and >1 month to be presentation, diagnosis, and treatment delays, respectively. We compared lengths of intervals using Mann-Whitney U tests and logistic regression. The most frequent cancer types were pancreatic (32%) and colorectal (28%). Most patients presented at stages III (38%) and IV (30%). The median presentation interval was 84 days (IQR, 56-191), and 49% presented after 3 months or longer. The median diagnosis and treatment intervals were 0 (IQR, 0-8) and 7 (IQR, 0-23) days, respectively. There was no relationship between age, sex, education, or distance to tertiary hospital and presentation delay, but patients with stage III to IV versus I to II had higher odds of presentation delay (odds ratio [OR], 1.68 [95% CI, 1.13 to 2.50]). Among patients with pancreatic cancer, older patients were less likely to have a diagnosis delay (OR, 0.50 [95% CI, 0.25 to 0.98]). About half of patients with GI cancer in Ile-Ife, Nigeria, did not present to tertiary hospitals until more than 90 days after noticing symptoms. Efforts are warranted to improve public knowledge of GI cancer symptoms and to strengthen health systems for prompt diagnosis and referral to specialty care.

On a non-local problem for a fractional differential equation of the Boussinesq type

In recent years, the fractional partial differential equation of the Boussinesq type has attracted much attention from researchers due to its practical importance. In this paper, we study a non-local problem for the Boussinesq type equation Dtαu(t)+A Dtαu(t)+ν2Au(t) =0, 0&lt;t&lt;T, 1&lt;α&lt;3∕2, where Dtα is the Caputo fractional derivative, and A is an abstract operator. In the classical case, i.e., when α = 2, this problem has been studied previously, and an interesting effect has been discovered: the existence and uniqueness of a solution depend significantly on the length of the time interval and the parameter ν. In this note, we show that in the case of a fractional equation, there is no such effect: a solution of the problem exists and is unique for any T and ν.

Effect of Rest Interval Length on Oral Swallowing Pressure During Effortful Swallowing Exercises in Healthy Adults: A Crossover Design.

Evidence supporting the prescription of effortful swallowing (ES) as a rehabilitation exercise remains lacking. This study aimed to evaluate the effect of rest interval length between sets on oral swallowing pressure during ES exercises in healthy adults. This study was a randomized trial of participants using a crossover design. Forty-three healthy adults (25.0 ± 3.7 years; 32 women and 11 men) without swallowing difficulties were recruited and participated in all four conditions (rest intervals between sets: 0-, 1-, 3-, and 5-min intervals) in a random order. The exercise constituted five sets, each comprising 10 ES repetitions. ES was performed with saliva swallows. The rest interval between each repetition was fixed at 10s, and the oral swallowing pressure during ES was measured using a tongue pressure measuring device. Oral swallowing pressures were significantly lower in the fifth set than in the first set at the 0-min rest condition. In the comparison by condition, oral swallowing pressures were significantly higher in the 5-min than in the 0-min rest conditions in the fourth set and in the 3- and 5-min rest conditions than in the 0-min rest condition in the fifth set. A rest interval of appropriate length between sets during ES exercises may consistently maintain the targeted high swallowing pressures during the exercises. Further studies using more diverse equipment and targeting older patients and those with dysphagia are required to determine the effect of the rest interval length between sets on the degree of exercise intensity to improve the swallowing-related muscle strength.

Arrival-breeding interval is flexible in a songbird and is not constrained by migration carry-over effects.

As spring phenology advances with climate change, so too must the timing of life cycle events. Breeding at the right time is critical in many species as it maximizes fitness. For long-distance migratory birds, flexibility in the duration of the arrival-breeding interval (pre-breeding period) may allow populations to adjust their timing of breeding. However, whether first egg-lay dates are flexible to local environmental conditions after arrival, and if they are constrained by the time needed to replenish energy lost during migration, remains unclear. We investigated the regional flexibility of the arrival-breeding interval in an avian migrant, the purple martin, Progne subis, across their breeding range. We evaluated whether the duration of the arrival-breeding interval was flexible to temperature and precipitation at breeding sites, and if timing was limited by migration rate and stopover duration. We also tested if longer interval durations were associated with higher fledging success. To address our hypotheses, we used a combination of migration tracking, weather and breeding data collected from four regions across eastern North America (26.1° N to 52.4° N latitude). We found the arrival-breeding interval to be shortest in the north and longest in the south. Across all regions, warmer temperatures encountered at breeding grounds were associated with shorter intervals, and faster migration rates led to longer intervals. The length of the interval was not influenced by precipitation or stopover duration. Finally, longer intervals were not associated with higher fledge success. Currently, the longer arrival-breeding intervals in this study system, on average 28.3 days, may provide both early and late-arriving birds with ample time for recovery so birds can lay eggs according to temperature. Any negative effects of faster migration may have been buffered by longer arrival-breeding intervals, as interval length did not determine fledge success. With ongoing climate change, further research is needed to examine if arrival-breeding intervals become constrained by migration timing, which may limit opportunities for migrants to match the timing of breeding with key resources.