Introduction: Acute lower respiratory infection (ALRI) is recognized as a leading cause of morbidity and mortality among children worldwide. Respiratory viruses, particularly respiratory syncytial virus (RSV) and influenza virus A (IVA), are the leading causes of hospitalization among children. Meteorological conditions significantly influence seasonal respiratory virus epidemics, yet the connection between these factors and virus infection in children remains poorly understood. We aimed to investigate the relationship between meteorological conditions and the incidence of respiratory viruses among hospitalized children. Methods: We carried out a retrospective study examining children under 18 hospitalized with ALRI from January 2013 to January 2020. Using negative binomial regression, we analyzed the relationship between meteorological conditions (average monthly temperature, relative humidity, rainfall, and wind speed) and the monthly incidence of respiratory viruses. Results: Out of the 5313 children included in the study, HRV (31.9%), RSV (23.8%), and IVA (16.0%) were identified as the most common respiratory viruses. In the analysis, the monthly RSV and IVA infections were independently associated with temperature [(IRR 0.84; 95% CI 0.79-0.90; P <.001) and (IRR 0.86; 95% CI 0.81-0.92; P <.001)] and rainfall [(IRR 1.19, 95% CI 1.01-1.39; P =.03) and (IRR 1.20, 95% CI 1.06-1.37; P =.005)]. Temperature was the notable predictor for HRV, IVB, and HCoV infections, as well as HMPV infections, which were also positively affected by low relative humidity. Conclusions: Low temperatures are linked to higher RSV, IVA, IVB, HCoV, and HMPV infections. Rainfall predicts RSV and IVA infections, while relative humidity predicts HMPV infections.

Commercially available plant-based milks are milk analogues manufactured to mimic the emulsion structural, nutritional, and functional properties of animal milks by combining plant materials extracted from e.g. oat or almond combined with added fats, vitamins and minerals. It is not yet clear how the molecules in plant-based milks interact to form the milk structures or even what the composition of the final products is. The purpose of this review is to bring together evidence relating to the molecular composition of plant-based milks and the structural arrangement of the molecules in the final products. Much of the available work involves chromatographic methods, microscopy, gravimetric, volumetric and elemental analyses methods. Although confocal microscopy with fluorescence labelling has been used to stain for different molecules in milk, there is little information on inter-molecular interactions. There is thus a need for new methods to investigate component interactions to ensure the maintenance of plant milk product quality.

A document by Rıfat YILDIRIM. Click on the document to view its contents.

Physical-layer specific emitter identification (SEI) faces significant misclassification challenges of unknown devices, especially in closed-set environments and the scarcity of available labeled data. To address these limitations, we introduce a Few-Spot Self-Supervised Adversarial Augmentation Specific Emitter Identification (FS-SA2SEI) framework that integrates adversarial augmentation, and open-set recognition (OSR) mechanisms. FS-SA2SEI enhances spectral and multi-resolution feature extraction while enabling robust classification of known emitters and rejection of unknown ones. Evaluated on Wi-Fi and publicly available datasets (ADS-B, FIT/CorteXlab), the framework achieves a closed-set accuracy of 89.9%, surpassing prior benchmarks by >5%, and an open-set detection rate (OSDR) of 64.0% at a worst-case openness of 0.6. These results highlight FS-SA2SEI’s potential as a scalable solution for real-time SEI in resource-constrained IoT systems, where adaptability to dynamic environments and unseen devices is critical.

We study the Birman-Schwinger operator for a self-adjoint realisation of the one-dimensional Hamiltonian with the Coulomb potential. We study both the case in which this Hamiltonian is defined on the whole real line and when it is only defined on the positive semiaxis. In both cases, the Birman-Schwinger operator is Hilbert-Schmidt, even though it is not trace class. Then, we have considered some approximations to the Hamiltonian depending on a positive parameter, under given conditions, and proved the convergence of the Birman-Schwinger operators of these approximations to the original Hamiltonian as the parameter goes to zero. Further comments and results have been included.

\received DD MMMM YYYY \acceptedDD MMMM YYYY BackgroundThe prognostic role of systemic inflammation markers in pediatric soft tissue sarcomas (STS) remains unclear. ProcedureThis multicenter study investigated the prognostic significance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), C-reactive protein (CRP), and lactate dehydrogenase (LDH) in 213 pediatric patients diagnosed with STS in years 2002-2023. Patients were categorized into groups: rhabdomyosarcoma (RMS, n=126), RMS-like (n=57), and non-RMS (n=30). Clinicopathological data, including complete blood counts (CBCs), CRP, and LDH levels, were collected and age-adjusted. Optimal cutoffs for predicting outcomes were determined, and the prognostic value of the inflammatory markers was assessed using Kaplan-Meier survival analysis, log-rank tests, and Cox regression models. ResultsNo significant differences in NLR, PLR, LMR, and CRP levels were observed between RMS, RMS-like, and non-RMS groups. However, LDH levels were significantly elevated in the RMS group compared to the RMS-like group. A consistent trend toward higher NLR, PLR, and CRP values was noted in patients with more advanced disease stages. Multivariate Cox regression analysis across the entire cohort identified CRP (HR 3.39, 95% CI 1.55-7.4, p=0.002), NLR (HR 2.06, 95% CI 1.07-3.99, p=0.03), and disease stage (HR=0.49, 95% CI 0.26-0.95, p=0.035) as independent prognostic factors for survival. Subgroup analyses revealed that the prognostic impact of these markers varied across histopathological subtypes, with limited utility in the RMS-like group. Conclusions These findings highlight the prognostic value of systemic inflammatory markers in pediatric STS, emphasizing their potential to refine risk assessment and guide treatment.

Background Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood. Historically classified based on histology, advancements in molecular profiling have allowed for further sub-classification which has improved risk-stratification. While molecular profiling has improved the understanding of disease progression and risk, the molecular evolution of therapy resistance in patients with RMS has not been well described. Transcriptomic profiling of patients with high-risk, refractory RMS was undertaken with the goal of uncovering insights into the biology of treatment-resistant RMS. Procedure Formalin-fixed paraffin-embedded (FFPE) tissue samples from patients with refractory RMS who had samples archived at diagnosis and relapse were obtained. Histologic subtype and PAX3/7-FOXO1 fusion status was confirmed. Transcriptomic profiling of the pre- and post-treatment FFPE tissue samples was performed using the HTG Transcriptome Panel (HTG Molecular Diagnostics). Results We identified 11 patients with refractory RMS who had FFPE tissue samples archived at diagnosis and relapse following multimodality therapy. All patients were stratified as high-risk, including 5 with PAX3/7-FOXO1 fusion-positive RMS (FP-RMS) and 6 with PAX3/7-FOXO1 fusion-negative RMS (FN-RMS). The transcriptomic analysis revealed that the myogenesis pathway and markers associated with myogenic differentiation were enriched pre-treatment in patients with FP-RMS and enriched post-treatment in patients with FN-RMS. Conclusions Using a probe-based transcriptome panel to characterize matched pre- and post-treatment tissue samples from patients with RMS, we report that treatment-resistant RMS follows a fusion status-dependent evolutionary trajectory, marked by differential expression of myogenesis associated genes and myogenic differentiation markers.

Reinforcement learning works best when the impact of the agent’s actions on its environment can be perfectly simulated or fully appraised from available data. Some systems are however both hard to simulate and very sensitive to small perturbations. An additional difficulty arises when a RL agent is trained offline to be part of a multi-agent system using only anonymous data, which makes it impossible to infer the state of each agent, thus to use data directly. Typical examples are competitive systems without agent-resolved data such as financial markets. We introduce consistent data time travel for offline RL as a remedy for these problems: instead of using historical data in a sequential way, we argue that one needs to perform time travel in historical data, i.e., to adjust the time index so that both the past state and the influence of the RL agent’s action on the system coincide with real data. This both alleviates the need to resort to imperfect models and consistently accounts for both the immediate and long-term reactions of the system when using anonymous historical data. We apply this idea to market making in limit order books, a notoriously difficult task for RL; it turns out that the gain of the agent is significantly higher with data time travel than with naive sequential data, which suggests that the difficulty of this task for RL may have been overestimated.

This short communication develops an existence result for a general non-linear parabolic equation and related eigenvalue problem. The method of proof comprises a variational approach for establishing a concerning solution existence at each instant of time, related to a model discretized in time.

1. Natural selection drives the allocation of resources between growth, reproduction, and other processes in organisms, especially under limited resource availability. 2. This study investigates how the fern Ophioglossum vulgatum L. allocates resources between photosynthetic growth and spore production under competition and simulated herbivory. 3. A large-scale field experiment was conducted in meadows and peatlands in Imielenko, Poland, involving 10 transects with three squares each. Four treatments were applied: clipping of O. vulgatum ramets, mowing surrounding plants, no intervention (control), combined clipping and mowing. 4. A total of 533 ramets were marked, and biometric parameters such as leaf blade area, sporophore size, and sporangia number were recorded and analyzed. 5. Key findings: • Mowing increased leaf blade area but reduced sporophore size and sporangia production in the following year. • Control plots displayed the highest resource allocation to reproduction, with larger sporophores and more sporangia compared to treated plots. • Clipping and mowing negatively impacted reproductive allocation, reflecting a trade-off in resource distribution. • Simulated herbivory did not significantly influence growth or reproduction, suggesting resilience to herbivory. 6. The results demonstrate that mowing alters resource allocation patterns, prioritizing photosynthetic growth at the expense of reproduction. 7. These findings highlight the importance of management practices, such as controlled mowing, in maintaining population persistence of rare ferns like O. vulgatum. 8. Implications for conservation: • Balancing growth and reproduction through tailored management strategies can support the conservation of O. vulgatum in meadow-wetland ecosystems. • The resilience of O. vulgatum to herbivory underscores its adaptive potential, but care must be taken in applying treatments that could disrupt natural resource allocation.

1. Passive acoustic monitoring (PAM) is a powerful tool for wildlife monitoring, but the time and expertise required to process large volumes of data pose significant challenges. Automated acoustic detectors improve efficiency by speeding up data processing. Class imbalance, resulting from fewer target signals relative to noise, complicates development and can negatively impact performance. However, training datasets should also reflect the conditions of real-world PAM datasets. 2. We developed an automated acoustic detector for chimpanzee loud calls while addressing class imbalance. We predicted that greater data diversity and high-quality data (clear signals, minimal noise interference) would enhance network performance and that class imbalance, by supporting diversity, is essential for functionality. We built training datasets with data recorded in wild settings and applied a temporal convolutional neural network approach using Deep Audio Segmenter (DAS). We trained networks using datasets containing varying levels of noise (50%, 75%, 90%, 99%) and also tested the effectiveness of frequency removal in improving performance. 3. The network performances varied significantly, with F1 scores of 0.44 to 0.86, exceeding a previous study (5% F1). The most imbalanced dataset produced the best performing network, capturing 90% of pant-hoot events and annotating them with 90% (SD = 20.9) accuracy. The results showed that increased class size was associated with greater intraclass diversity and improved precision (0.41–0.83). The networks showed consistently high recall rates, especially when frequency removal was not applied (0.89–0.92). 4. This study stresses the importance of class size and diversity in developing automated acoustic detectors. It also highlights the value of high-quality data for accurate pattern recognition of the target signal and the importance of the noise class for effective class decoupling and detector functionality. This research supports the advancement of PAM in chimpanzee studies, opening new opportunities to integrate remote sensing for efficient wildlife monitoring.

Understanding how community assembly processes vary across spatial scales and environmental gradients is key to predicting species coexistence and informing conservation priorities. Beta-diversity represents the spatial variation in biodiversity and is intimately linked to processes ranging from fully niche-based to neutral assembly processes. Here we investigated the beta-diversity patterns of rocky subtidal macrobenthic assemblages in two environmentally contrasting fjords of Chilean Patagonia and across three spatial scales and dimensions within each fjord: vertical scale (subtidal depth; 0 – 21 m), fine horizontal (within fjord sections; 1 - 10 km) and broad horizontal (between fjord sections; 10 - 100 km). We applied generalized dissimilarity models (GDMs) to analyse three underlying processes that shape ecological communities: density-independent responses to abiotic conditions (salinity and temperature), dispersal (geographical distances and depth), and stochasticity (beta-null deviations) on beta-diversity expressed as Bray-Curtis dissimilarities. Stochastic and dispersal processes dominated beta-diversity along horizontal gradients, particularly at larger spatial scales, while environmental filters consistently contributed to beta-diversity along depth gradients. The southern fjord presented higher community variation in line with higher environmental heterogeneity. Stochastic processes dominate the northern fjord, suggesting a greater influence of habitat homogenization. These results emphasize the scale-dependent nature of assembly processes in fjord ecosystems and underscore the importance of incorporating multiple spatial dimensions into biodiversity assessments.

The Casimir force still has a lot of unknown aspects. Here this force is measured in a tuning fork experiment in reduced gravity and compared with a measurement on ground. It seems like the Casimir force is strongly suppressed during free fall. This is a hint that the Casimir force does not have its origin in the Van der Waals force, which would not change in reduced gravity. Further conclusions concerning Dark Energy and MOND theory are raised.

Unusual Presentation of Parapharyngeal Neuroglial Heterotopia in a NeonateSultan Alsumairi1, Shmokh Alsalamah1, Salwa Alrashed2, Mazyad Alenezi3, Mohmmad Alessa2,4College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh, Saudi ArabiaDivision of Otorhinolaryngology-Head and Neck Surgery, Department of Surgery, King Abdulaziz Medical City, Riyadh, Saudi Arabia.Department of Otorhinolaryngology–Head and Neck Surgery, Ad Diriyah Hospital, Riyadh Third Health Cluster, Ministry of Health, Riyadh, Saudi ArabiaDepartment of Otolaryngology, Head and Neck Surgery, College of Medicine, King Saud University, Riyadh, Saudi Arabia.

\received DD MMMM YYYY \acceptedDD MMMM YYYY This paper focuses on the Newton iterative method solving for the inverse problem of reconstructing the shape of an impenetrable elastic cavity in R 2 . The incident field is generated by point sources inside the cavity, and the measurement fileds are also obtained inside the cavity. Benefiting from the Helmholtz decomposition and the Fourier-Bessel approximation, we deduce the expressions for the approximate scattered field and its derivative in the interior of Γ b , where Γ b a circle with radius large enough surrounding D. With the measurement data obtained, we can effortlessly compute the scattered and total fields in the interior of Γ b . For Dirichlet boundary condition, the curve on which the total field vanishes indicates the boundary of the cavity. The validity of the method has been confirmed by numerous error estimations and numerical results.

Small proteins (SPs, ≤50 amino acids) are usually ignored by automated bioinformatic algorithms and difficult to be detected by traditional protein purification. In this study, 193,281 prokaryotic SP clusters were generated using 433,311 small open reading frames (sORFs) predicted in assemblies of 71 full-ocean-depth marine water metagenomes from the western pacific. Further filtration with at least 5 copies per million reads resulted in 75,581 prevalent SP clusters, among which 4,307 clusters have coding capacity as predicted by RNAcode. For these RNAcode-filtered SP (RfSP) clusters hosted largely by Proteobacteria, Thaumarchaeota and Marinimicrobia, 29.16% of them show homology () in all prokaryotic genomes. About 2% of the RfSP clusters were estimated as potential antimicrobial peptides and were distributed across all depth zones. Transcription of 7.96% of the RfSP clusters was verified in 12 deep-sea metatranscriptomes, and translation of 34 prevalent SP clusters was detected in 14 metaproteomes. The transcribed RfSP clusters are involved in processes such as DNA stability under stress condition, betaine transport and cell division regulation for a rapid response to varying deep-sea environments. This study uncovers a vast reservoir of SPs with pivotal functions in potential antibiotic activities, hyperoxide detoxification and pressure resistance for fitness of marine prokaryotes in deep ocean.

Variation in bird clutch and egg sizes across geographical gradients are issues often debated among ecologists, where latitudinal cline is a central question in several discussions. It is understood that these patterns are primarily driven by climatic conditions, where latitude acts as a proxy. Here, we achieve a robust dataset that covers a large territorial extent to test the hypothesis clutch and egg size will show measurable variation based on environmental gradients. We predict that these traits will: a) increase with increasing latitude, b) be larger in more seasonal climates (Köppen-Geiger), c) increase in sites experiencing cooler winters, and d) increase in sites with warmer and wetter long-term climatic conditions. We considered the geographically diverse Tyrannus genus (kingbirds) and collected breeding data from 35 scientific egg collections. After several data control processes, including spatial, temporal and taxonomic checking, we analysed the relationship between kingbird’s clutch and egg sizes with different climatic conditions. The analyses of 1358 clutches and 4750 eggs collected during 158 years (1858-2016) confirmed that Kingbirds’ clutch and egg sizes increase towards the poles. Both breeding traits varied according to main climates, regional sub-climates, and local temperature and precipitation conditions. More seasonal regions had the largest clutches, but sites with colder winters did not have the largest clutches. Tyrannus egg size increased in environments with less extreme dry periods. The significant relationship between larger eggs with sites with lower temperatures provides insights about the increase of egg size with latitude. Our findings suggest a robust correlation of residual variation in breeding traits with climatic conditions at both regional and local levels. Highly locally adapted species using climatic conditions as cues should also respond to interannual weather variations. The insights provided in this work can assist in understanding how species will cope with future climate scenarios.

Understanding the morphology of pteridophyte spores provides fundamental information needed to study their biological distribution patterns. The present study investigates pteridophyte spore morphology by studying physical traits including structure dimensions in addition to shape features and colour variations and surface markings. A taxonomic examination reveals that observed spores belong to two different groups that either demonstrate advanced monolete morphologies or primitive trilete characteristics with individual spore measurements ranging between 15 µm and 150 µm. Clusters of Pyrossia porosa megaspores reached the largest dimensions at 70×95 micrometers whereas Polystichum aculeatum possessed the smallest spores sized at 21×26 micrometers. Surface ornamentation in spore structure mainly depends on exine and perine. Researchers detected numerous surface ornamentations as reticulate, regulate, cristate, folded, granulate, perforate, rugate, tuberculate and verrucate patterns. Median monolete advanced morphology was observed in 29 out of the 35 plant species identified during the study although trilete basic morphology was found in twelve different species. The systematic importance of features derives from spores in fern classification

Ecological differences among species influence population response to historical environmental changes, and genetic simulations now allow us to directly incorporate this variation into inferential models. However, the impact of life history strategies in demographic inference has been far less explored relative to the impact of other ecological differences, such as dispersal capacity and habitat preference. Here, we utilize individual-based simulations of a non-Wright-Fisher population to ask whether differences in the average age of first reproduction of individuals, the average adult mortality and the average number of mates per reproductive season lead to consistent and predictable differences in summary statistics of genetic diversity commonly used for simulation-based parameter estimation and demographic inference. Using a Random Forest model, we estimate three population parameters (variance in reproductive success, generation time, and effective population size) from genome-wide SNP variation for two bird species with distinct life history strategies that are directly built into the simulation machinery. Our results show that life history variation leads to predictable differences in patterns of genetic diversity. While prediction accuracy is low, parameter estimates from empirical datasets agree with the expectation that species with extreme polygamy, long adult longevity and later onset of reproduction will exhibit higher variance in reproductive success, longer generation time and smaller effective population sizes. Since the signal of life history differences is observed in the genetic summary statistics, we suggest that simulation- and model-based multi-species demographic inference should incorporate life history parameters.

AbstractThis study examines the seasonal preference for winter weddings, analyzing cultural, economic, and environmental factors that influence this trend globally. Focusing on regions such as Bangladesh and India, where winter weddings are predominant, the research highlights how favorable climatic conditions, alignment with cultural and religious traditions, and economic advantages drive this preference. Winter offers mild weather, suitable for outdoor events, and coincides with holidays and post-harvest periods, facilitating extended celebrations and family gatherings. Additionally, reduced costs for venues and the availability of seasonal produce contribute to the practicality and appeal of winter weddings. Conversely, in regions with harsh winters, such as Northern Europe and North America, summer and autumn are preferred due to more accommodating weather for outdoor ceremonies and reduced logistical challenges. The study acknowledges the obstacles of winter weddings, including adverse weather, limited daylight, and holiday scheduling conflicts, which can complicate planning. Despite these challenges, winter weddings remain a favored choice in many regions, reflecting a confluence of cultural practices, environmental factors, and economic considerations. This research underscores the intricate relationship between seasonal preferences, local traditions, and practical constraints in shaping global marriage patterns.Keywords:Winter weddings, marriage seasonality, wedding trends, cultural traditions, global marriage patterns.IntroductionMarriage is one of the most significant life events of an individual, representing an institutionalized formal union between two individuals, which can be also observed with cultural, religious, or legal rites (Khatun et al. 2022). Although the choice to marry is quite personal, the schedules of weddings tend to be quite regular. These patterns are driven by cultural practices, practical constraints, and environmental conditions. An intriguing pattern is that winter is a marriage season favored in many parts of the world (Rault et al. 2016; Ruiu & Gonano, 2015; Monger, 2013; Sanna & Danubio, 2008; Kussmaul, 1985).Winter weddings are not simply seasonal whim but the result of an interplay of cultural, economic, and environmental factors. In areas with mild winters, this seasonal temperature range is just right for outdoor weddings, and the festive atmosphere that usually accompanies the season is perfect for a wedding (Rault et al. 2016). Families utilize holidays or vacation periods to come together for these happy events. Practical benefits like lower costs for venues and the availability of fresh seasonal produce also make winter weddings appealing.In some cultures, winter holds special significance. As an example, in countries such as Bangladesh and India, the winter months are the best season for weddings since it avoids the hot season of summer and the monsoon season’s heavy rain (Tsaneva, 2020b). School holidays also occur at this time and region, so there are opportunities for family group gatherings and celebrations to be longer. However, this trend is not the same everywhere. In regions with harsh winters, like Northern Europe or parts of North America, summer and fall are more common for weddings because the weather is more accommodating (Rault et al., 2016; Baum & Hagen, 1999; González-Martín, 2007; Lee et al., 2020).This paper explores why so many people choose to marry in winter. It looks at cultural traditions, practical benefits, and the role of climate in shaping this preference. Special attention is given to countries like Bangladesh and India, where winter weddings are particularly popular, along with comparisons to other parts of the world. This review aims to uncover the reasons behind these seasonal trends and what they reveal about the relationship between culture, environment, and one of life’s biggest celebrations.

During adaptation, gene flow can either accelerate or impede species divergence, sparking intense debate about how introgression shapes speciation. Although introgression is widely recognized for introducing genetic novelty, the precise conditions under which it promotes or suppresses reproductive isolation remain unclear, particularly when environmental differences and population dynamics vary. Here, using Fisher's geometric model, we examine how the timing and magnitude of migration influence adaptation and reproductive barriers in both mutation-order and ecological speciation scenarios. We show that early-phase or constant gene flow can facilitate evolutionary rescue for populations adapting to a shared optimum, whereas late-phase migration often delays final adaptation due to the introgression of large-effect mutations in initially isolated populations. In mutation-order speciation, parallel adaptation often reduces hybrid breakdown, whereas, in ecological speciation, alleles beneficial in one environment can be maladaptive in the other. Under both scenarios, early or continuous gene flow promotes allele sharing that eases adaptation but undermines reproductive isolation. We also find that intermediate levels of parental divergence can maximize the success of hybrid lineages, offering insights into when homoploid hybrid speciation may arise. Overall, this study clarifies how gene flow timing modulates the balance between adaptive introgression and isolating barriers. By integrating demography with fitness landscapes, we provide a theoretical framework to interpret genomic patterns of introgression and understand when it accelerates or hinders speciation.

Objective: Selective serotonin reuptake inhibitors (SSRIs) cross the placenta, and their use during pregnancy can impact neonatal outcomes. However, the effects of maternal SSRI treatment during pregnancy on neonatal urinary and gastrointestinal systems has not yet been investigated. Methods This retrospective case-control study compared neonates born to women who consumed SSRI drugs during pregnancy with the closest birth of healthy delivered newborn not exposed to SSRI in utero, matched for gestational age (GA) and weight for gestational age. The primary outcomes measured were the time to first void and the time to first stool. Results The cohort included 133 neonates in each group. Mothers in the SSRI-exposed group were older (34.5 vs 32.2 years, p<0.001) compared to those in the control group. The time to first stool was significantly shorter in neonates exposed to SSRIs compared to those who were not exposed (7.4 vs 8.6 hours, p=0.023), while the time to first void did not differ between the two groups. In regression analysis, the time to first stool was associated with the time to first void (β=0.138, p=0.032) and SSRI exposure (β=-1.561, p=0.030), but not with GA, gender, and maternal age. SSRI-exposed neonates had three times the rate of formula feeding compared to unexposed neonates (19.5% vs 6%, adjusted p=0.001). Conclusions Maternal SSRI use during pregnancy did not influence the timing of the first void but does impact gut motility.

In this paper, we address input load/generation uncertainty in the stochastic economic dispatch and unit commitment for forecasting and then scenario generation purposes. We propose a constrained multi-variate linear regression formulation to model the joint spatial-temporal distribution of load forecasts and renewable energy productions such as solar cells and wind turbines at various locations. This model adds l 0 and l 1 constraints to simulate exact counterparts for LASSO and Ridge regression models. We eliminate heavy tails from forecasted errors using extreme value theory to generate robust solutions for stochastic economic dispatch and unit commitment. We then employ a Monte Carlo sampling technique to generate scenarios. Finally, we propose a new exact model for scenario reduction. For this paper, we used data published at NYISO a and ERCOT b websites. Our numerical results show how energy loads and renewable energies can be forecasted using our methodology and forecasted values predict actual values.

\received DD MMMM YYYY \acceptedDD MMMM YYYY The rotor of a two-bladed turbine allows the implementation of an additional degree of freedom around the rotating hub y-axis. This idea is over 60 years old, and various research and commercial turbines have had a teeter hinge. Fatigue and extreme loads can be reduced significantly with a teeter hinge. Teetered turbines have been mainly below or around a rotor diameter of 100m. The research project X-Rotor, which has compared two- and three-bladed turbines with a power of 20MW and a diameter of 250m, observed that most teeter movements appear to become less harmful with rising turbine size. Using the analytical equations of the teeter movement combined with numerical simulations of the CART2 (600kW), 2-B Energy’s 2B6 (6MW), and the 2B20HAW-T (20MW, based on the INNWIND.eu turbine), this paper investigates the effects of teeter behavior over a wide range of turbine sizes. It concludes that the Lock number, the ratio of aerodynamic and inertia forces, increases with rotor size, which correlates with the turbine development over the past 50 years and results in a valuable increase in aerodynamic damping.