Large Time Span Research Articles

7815 Pembrolizumab-Induced Autoimmune Hypophysitis with “Isolated” ACTH Deficiency: Need for Heightened Awareness and Action Among Medical Fraternity

Abstract Disclosure: S. Shankar: None. S.S. Sundar: None. M.S. Vaishnav: None. L. Lekkala: None. K. Thummala: None. S. Srikanta: None. T. Deepak: None. R.B. Vijay: None. K. Muniraj: None. V. Nath: None. C. Siddlingappa: None. P. Ravikumar: None. M.D. Chitra: None. Introduction: Autoimmune hypophysitis caused by immune checkpoint inhibitors [ICIs; anti-CTLA-4 (Ipilimumab alone 7.9%), anti-PD-1 (Pembrolizumab alone 1.7%; nivolumab alone 0%)] are being increasingly documented, with anterior hypopituitarism affecting corticotrophs more commonly than thyrotrophs and gonadotrophs (large time span of onset; different recovery patterns). Clinical Case 2021 Sep Age 65 years (type 2 diabetes, hypertension). Renal Cell Carcinoma S/P radical nephrectomy. 2023 Jul PET-CT= Metastatic pleuropulmonary nodules. Four admissions to Specialist Oncology Hospital [Four 2 weekly cycles of Inj Pembrolizumab 200 mg (with Tab Axitinib 10 mg/day)]. After first cycle: progressive fatigue, body aches, drowsiness. S Sodium= Pre-pembrolizumab= 137 mEq/L (135-145); Post-pembrolizumab= 124, 134, 132, 124; T3= 1.63 to 0.60 to 1.24 to 1.35 ng/mL (0.97-1.69); T4= 6.83 to 4.93 to 10.44 to 11.44 mcg/dL (5.53-11); TSH= 10.46 to 6.28 to 5.39 to 9.48 mIU/mL (0.46-4.68); S Cortisol 8 am= 1.54 mcg/dL (5-25); S Potassium= 4.59 mEq/dL (3.5-5.1)]. One episode of loss of consciousness; EEG= abnormal; MRI Brain= normal. During every hospital admission, oncology, medical, endocrinology and nephrology teams attributed the same to “illness” (no specific diagnosis) and provided symptomatic treatment (IV 3% saline, tolvaptan and sodium bicarbonate tablets).2023 Nov Medicine: Very severe nausea, anorexia, generalised weakness, myalgia, hiccoughs, and inability to walk. Frustrated family members sought admission in “new” General Hospital. S Sodium= 119, 120; S Potassium= 4.8; S Creatinine= 1.67 mg/dL (0.7-1.3); S Uric acid= 4.5 mg/dL (4.40-7.60); Urine spot Sodium= 84 mmol/L; ESR= 144 mm. Endocrinology: S Cortisol 8 am= 0.09 mcg/dL;S Cortisol post 250 mcg Inj Synacthen= 3.76 (>20);Plasma ACTH= 5.4 pg/ml (9-52). S T3= 1.35; S T4= 11.44; S TSH= 9.48; LH= 3.61mIU/mL (1.5-9.3); FSH= 1.4mIU/mL (1.4-18.1); PRL= 30.1 (2.6-13.3); Testosterone total= 314 ng/dL (241-827); TPO antibodies negative. MRI-Pituitary: Partial empty sella; infundibulum neurohypophysis normal; mild asymmetric enhancement (5.5 mm) left cavernous sinus. Treatment: Tab Hydrocortisone 25 mg/day, with complete clinical and biochemical response [Suggestion of gonadotroph dysfunction and partial recovery of thyrotrope dysfunction/ injury. Hence, not on thyroxine replacement]. Clinical Lessons: Mechanisms for differential cellular vulnerability for ICI induced autoimmune pathologies [thyroid (destructive versus stimulatory), islet beta cells, adrenal cortical cells, various anterior pituitary cells (corticotrophs vs thyrotrophs and gonadotrophs] need elucidation. Specific molecular and cellular immunopathogenic pathways in different autoimmune endocrinopathies appear distinct and disparate. Presentation: 6/2/2024

Mapping paleoelevations along active continental margins with igneous geochemistry: A case study from South America

Mountains and mountain ranges, often situated at convergent plate margins, play a pivotal role in many fields of the Earth, climate, and biological sciences. Reconstructing past episodes of mountain building from the geological rock record is one of the main challenges for unravelling the ancient physical geography of Earth’s surface. Established methods for quantifying past elevations traditionally relied on sedimentary rocks, but in recent years, alternative approaches have emerged on the basis that geochemical signatures of magmatic rocks formed in convergent settings correlate with crustal thickness or elevation. Consequently, methods based on igneous samples have the potential to allow quantitative mapping of past topographic change for large spans of space and time where existing maps are largely based on a qualitative approach. Here, we investigate the application of paleoelevation estimates derived from geochemistry using the western margin of South America as a case study. We investigate their consistency with independent indicators of past elevations such as stratigraphy, stable isotopes, fossils etc. for Cenozoic samples along the Andean margin. For older times, we compare the estimated paleoelevations with more general aspects of the geological record, as well as paleoelevations from global paleogeography models widely used in climate modelling studies, to evaluate the extent to which these models are consistent with the igneous geochemical proxies. We find that estimates based on multiple geochemical proxies, and which account for variations in elevation as a function of MgO, are preferable to those based on individual proxies. The multi-mohometer estimates yield estimates of elevation that better match both present-day topography and Cenozoic paleoelevations, and retain more samples during the data filtering stage. In deeper time, we show that igneous geochemistry quantifies changes in elevation related to documented phases of crustal thickening and thinning, and is thus likely to allow improvements to existing maps of paleotopography.

Indigenous Knowledge Collection in NICRA-AICRPAM Domain Districts for Weather Events

Indigenous Technical Knowledge (ITK) is the experience of local people gained from past generation and forefathers. Knowledge base is gained through tradition and culture. Prevailing knowledge is used in making farming operational management for gain in crop production. Crop and irrigation cycles are also being followed through traditional knowledge base and advanced techniques are available now. However, importance of the treasure of knowledge gained from forefathers and inherited to local people in present situation can't be ignored. Indigenous technical knowledge (ITK) is the assemblage of awareness and understanding of various facts which people have developed over a large span of time and continue to expand it. Social participation gives an idea of the respondent's participation in social activities. The NICRA-AICRPAM project has been carried out since 2011 in Chhattisgarh state. Main objective of the project is developing climate resilient technologies in agriculture. This ITK collection can be one effective mean to achieve this objective. The study was conducted to identify indigenous knowledge prevailing among the village side in NICRA domain districts Mahasamund and Kanker (Chhattisgarh state). The study was to examine traditional knowhow of farmers in Kanker and Mahasamund districts of Chhattisgarh during 2021 and their scope of application in farming activities. The objective of survey was to collect and document traditional knowledge base from the local farmers so as to work towards climate resilience in agriculture. As rainfall is the main factor in rainfed agriculture, stress was on collection of knowledge regarding rainfall prediction. The study was conducted under CRIDA, Hyderabad sponsored NICRA-AICRPAM project entitled “National Innovations on Climate Resilient Agriculture”. Project has been implemented in Department of Agrometeorology, Indira Gandhi Krishi Vishwavidyalaya, Raipur, (C.G.) since 2011. Here in this paper the astronomical, environmental and biological indicators perceived by local masses in forecasting rainfall have been collected, identified and examined. This knowledge will help its utilization in agricultural operations and practices. Interviews were conducted by Field Information Facilitators by contacting masses and peasants. Various indigenous technical knowledge of the project domain area were collected and analyzed. Experience of seasonal rainfall forecasting can be strengthened by using this knowledge base. ITK techniques of rainfall prediction may serve as supplemental knowledge base to advanced scientific technologies.

Adaptive Decision Spatio-temporal neural ODE for traffic flow forecasting with Multi-Kernel Temporal Dynamic Dilation Convolution

Traffic flow prediction is crucial for efficient traffic management. It involves predicting vehicle movement patterns to reduce congestion and enhance traffic flow. However, the highly non-linear and complex patterns commonly observed in traffic flow pose significant challenges for this task. Current Graph Neural Network (GNN) models often construct shallow networks, which limits their ability to extract deeper spatio-temporal representations. Neural ordinary differential equations for traffic prediction address over-smoothing but require significant computational resources, leading to inefficiencies, and sometimes deeper networks may lead to poorer predictions for complex traffic information. In this study, we propose an Adaptive Decision spatio-temporal Neural Ordinary Differential Network, which can adaptively determine the number of layers of ODE according to the complexity of traffic information. It can solve the over-smoothing problem better, improving overall efficiency and prediction accuracy. In addition, traditional temporal convolution methods make it difficult to deal with complex and variable traffic time information with a large time span. Therefore, we introduce a multi-kernel temporal dynamic expansive convolution to handle the traffic time information. Multi-kernel temporal dynamic expansive convolution employs a dynamic dilation strategy, dynamically adjusting the network’s receptive field across levels, effectively capturing temporal dependencies, and can better adapt to the changing time data of traffic information. Additionally, multi-kernel temporal dynamic expansive convolution integrates multi-scale convolution kernels, enabling the model to learn features across diverse temporal scales. We evaluated our proposed method on several real-world traffic datasets. Experimental results show that our method outperformed state-of-the-art benchmarks.

Long-term annual estimation of forest above ground biomass, canopy cover, and height from airborne and spaceborne sensors synergies in the Iberian Peninsula

The Mediterranean Basin has experienced substantial land use changes as traditional agriculture decreased and population migrated from rural to urban areas, which have resulted in a large forest cover increase. The combination of Landsat time series, providing spectral information, with lidar, offering three-dimensional insights, has emerged as a viable option for the large-scale cartography of forest structural attributes across large time spans. Here we develop and test a comprehensive framework to map forest above ground biomass, canopy cover and forest height in two regions spanning the most representative biomes in the peninsular Spain, Mediterranean (Madrid region) and temperate (Basque Country). As reference, we used lidar-based direct estimates of stand height and forest canopy cover. The reference biomass and volume were predicted from lidar metrics. Landsat time series predictors included annual temporal profiles of band reflectance and vegetation indices for the 1985–2023 period. Additional predictor variables including synthetic aperture radar, disturbance history, topography and forest type were also evaluated to optimize forest structural attributes retrieval. The estimates were independently validated at two temporal scales, i) the year of model calibration and ii) the year of the second lidar survey. The final models used as predictor variables only Landsat based metrics and topographic information, as the available SAR time-series were relatively short (1991–2011) and disturbance information did not decrease the estimation error. Model accuracies were higher in the Mediterranean forests when compared to the temperate forests (R2 = 0.6–0.8 vs. 0.4–0.5). Between the first (1985–1989) and the last (2020–2023) decades of the monitoring period the average forest cover increased from 21 ± 2% to 32 ± 1%, mean height increased from 6.6 ± 0.43 m to 7.9 ± 0.18 m and the mean biomass from 31.9 ± 3.6 t ha−1 to 50.4 ± 1 t ha−1 for the Mediterranean forests. In temperate forests, the average canopy cover increased from 55 ± 4% to 59 ± 3%, mean height increased from 15.8 ± 0.77 m to 17.3 ± 0.21m, while the growing stock volume increased from 137.8 ± 8.2 to 151.5 ± 3.8 m3 ha−1. Our results suggest that multispectral data can be successfully linked with lidar to provide continuous information on forest height, cover, and biomass trends.

The Effects of Macroeconomic and Financial Development on Income Inequality: Evidence from the Western Balkans

Abstract Using data from 1996 to 2019 covering five Western Balkan countries and applying the linear panel data estimation method, this paper examines the effect of macroeconomic indicators and financial market development on income inequality. Regression results with Driscoll-Kraay standard errors demonstrate that income per capita increases income disparities. Theoretically, there are grounds for both a positive and negative relationship between economic growth and income inequality. In addition, contrary to prevailing literature, our analysis finds no significant impact of financial market development on income inequality, while the rule of law is found to have no effect on income inequalities in these countries. We depart from previous literature by bringing new evidence on the relationship between income inequality and economic growth in the specific context of Western Balkan countries. We study this relationship in an integrated framework and rely on a larger time span, both of which are seemingly important for comprehending the income inequality-economic growth nexus. Certainly, the obtained results bear important policy implications as discussed in this paper.

CLUSTER ANALYSIS OF PULSE WAVE VELOCITY LONGITUDINAL TRENDS IN HYPERTENSIVE PATIENTS

Objective: Arterial stiffness (AS) is an important predictor of cardiovascular disease and mortality. Its trend over time, assessed through multiple measurements, is still largely unexplored. The aim of this study was to assess the determinants of trajectories of carotid-femoral pulse wave velocity (PWV) in a cohort of Italian hypertensive adults. Design and method: From a population of 2581 hypertensive patients referred to Hypertension Unit of Internal Medicine Division at University Hospital Città della Salute e della Scienza of Turin (Italy) from 2005 to 2023, those who had at least 3 PWV recordings over time were included in this study. Those with rare vascular diseases were excluded. Cluster analysis of PWV trajectories was performed using K-means method. Results: A total of 271 patients were included. Median follow-up time was 4.5 [0.6-8.4] years). Three clusters of PWV trends were identified: low-stable (A, n=126), high-increasing (B, n=107), and high-stable (C, n= 38) clusters. Patients in the clusters B and C were progressively older than those in cluster A (60.4±8.9 and 65.8±10.3 vs. 51.9±13.3 years, respectively). Mean BP (MBP) and PWV at baseline were progressively higher in the high-increasing and high-stable clusters compared to the low-stable one (MBP was 103±15 and 111±22 mmHg in clusters B, and C vs. 97±11mmHg in cluster A; PWV was 10.1±0.7 and 13.6±1.4 m/s in clusters B, and C vs. 7.8±0.9 m/s in cluster A; all p<0.001). There were no significant differences in sex distribution or anti-hypertensive treatment among the clusters. On multinomial regression analysis, older age and higher MBP at baseline were independently associated to increased probability of belonging to either B or C clusters when compared to the low-stable one. Conclusions: Through multiple PWV assessment in hypertensive patients during a large time span, this study shows that patients with less favorable arterial stiffness behavior present higher PWV values at baseline. Older age and higher MBP at baseline are associated with worse evolution of PWV over time.

Exploring the future: introduction of a new paradigm to examine intergroup experiences

Intergroup contact theory, as one of the most established research strands in social psychology, has mostly relied on overall measured averages of intergroup contact over larger time spans. Yet, in everyday life, intergroup contact experiences are far more complex: they are sequential and cumulative and may vary on a range of dimensions, such as, for example, their perceived valence. In this article, I introduce a new experimental paradigm, primarily developed as a research manipulation, to examine intergroup contact, manipulated on the unit of single interactions in a video-game setting, which can also be run from a web server, so that participants can join from their home computers. Depending on experimental condition, in a first study, participants rated the perceived quality of multiple positive or negative intergroup interactions with an alien species and intergroup attitudes in a storytelling questionnaire setting (Pilot Study, N = 242). Study 1 implemented these positive and negative interactions in a video game, which was played in the laboratory (N = 44), and examined their effects on the perceived contact quality and intergroup attitudes. Study 2 (N = 64) utilized a web-based version of the video game to test the effects on intergroup attitudes. In all three studies participants in the positive condition evaluated the interactions, as well as the overall outgroup, more positive than participants in the negative condition. Furthermore, Study 1 and 2 explored participants' perception of the virtual environment and previous experiences with video games. The results suggest that specifically developed video games offer new pathways to study intergroup interactions.

Does the RBNZ respond to exchange rate fluctuations?

This note re-visits the evidence on whether the Reserve Bank of New Zealand targets exchange rates in its Taylor rule. Estimating a standard small-open-economy DSGE model of the New Zealand economy using Bayesian methods, we find that the DSGE model with exchange rate in the Taylor rule generates a statistically significant better fit compared to the model without the exchange rate. This supports the view that while inflation has the highest weight in the Taylor rule, the RBNZ targets the exchange rate when making interest rate decisions. We also find a large weight on the smoothing parameter. The weight on the exchange rate is statistically significant but is smaller compared to the parameter attached to output. We use a large time span (1975–2018) for New Zealand standards for the full sample, and we also perform various subsample analyses and find time-variation in the Taylor rule parameters.

Effect of sinusoidal pressure gradient on MHD flow of viscoelastic fluid in a channel

Unsteady Hydro Magnetic oscillatory flow of incompressible viscoelastic fluid in a channel packed with porous material is investigated under the influence of oscillatory pressure gradient. Moreover, the applied magnetic field of moderate strength interacts with electrically conducting fluid, to generate a resistive volumetric body force. In addition to it, viscoelastic fluidity, characterizing the non-Newtonian behavior in conjunction with permeability of the medium as well as sinusoidal sheared flow due to imposed favorable pressure gradient, contribute to the novelty of the study. The previous work was confined to constant motion of the lower plate but the present work includes the sinusoidal motion of the lower plate in addition to the constant motion. The importance lies with the fact that the coupling effect of sinusoidal fluctuation and viscoelastic fluidity go hard in industrial applications, particularly in process industry. The governing equations characterizing the flow are solved analytically. The striking results of this study are: the formation of inverted boundary layer in case of oscillatory lower plate with moderately escalated time span but such instability leading to flow reversal, does not appear in case of constant motion of the lower plate. Hence, it is recommended that for stability of flow and to avoid flow reversal, higher frequency of oscillation as well as larger time span is not desirable. The elastico-viscosity property reduces the volume flow rate which may be useful to control the efflux and differentiates the state of motion (resulting low skin friction) and state of rest (resulting high skin friction) in respect shearing effects at the bounding surfaces.

Multi-temporal analysis to support the management of torrent control structures

In the last decade with increasing frequency of extreme weather events, an accurate, sustainable, and effective planning of torrent control structures has become essential to reduce hydro-geomorphic risk. Quite often in planning interventions, there is a lack of information on the effectiveness of existing structures, the evolution of the ongoing hydro-geomorphic process, and a priori in-depth study to analyze the sediment morphology dynamics and the interaction with possible existing torrent control structures.Nowadays, High-Resolution Topography data (HRT) greatly simplifies the monitoring of sediment morphology dynamics and the understanding of the interaction with torrent control structures over time. Therefore, thanks to repeated HRT surveys, it is possible to derive multi-temporal Digital Terrain Models (DTMs), and DTMs of Difference (DoDs) to quantify the morphological changes and study continuously the catchment morphodynamics. This information can be very valuable to support watershed management plans if combined with up-to-date field surveys that identify the existing torrent control structures, and asses their current status and functionality.The present work aims at introducing a methodological approach based on the integration of the sediment morphology dynamics data over large time spans (e.g., from 2003 to 2022), obtained by multi-temporal DoDs (realized from three DTMs at 1 m resolution), with an updating cadastre of torrent control structures enriched by a very simple, quick, and user-friendly Maintenance Priority index (MPi). The proposed workflow proved to be very useful in the test basins analysed, providing more complete data on torrent control structures and sediment dynamics evidence to stakeholders compared to the past. Moreover, it served as a proxy to assess the long-term effectiveness of the management interventions. The approach also helped to constantly identify the areas most prone to hazards, improve the intervention planning, and find more appropriate solutions or direct the maintenance works.Finally, the suggested workflow could be the starting point to outline up-to-date guidelines to be used in other catchments equipped with torrent control structures, emphasizing possible intervention priorities on where decision-makers could better invest resources. By providing current information and accurate tools to realize a more complete decision-making chain, which is often neglected, it is certainly possible to support more sustainable and effective risk management decisions.

A map matching algorithm based on modified hidden Markov model considering time series dependency over larger time span

With the advancement of geopositioning systems and mobile devices, much research with geopositioning data are currently ongoing. Along with the research applications, map matching is a technology that infers the actual position of error-prone trajectory data. It is a core preprocessing technique for trajectory data. Among various map matching algorithms, map matching using Hidden Markov Model (HMM) has gained high attention. However, the HMM model simplifies the dependency of time series data excessively, which leads to inferring incorrect matching results for various situations. For example, complex road relationships or movement patterns, such as in urban areas, or serious observation errors and sampling intervals make matching more difficult. In this research, we propose a new algorithm called trendHMM map matching, which complements the assumptions of HMM. This algorithm considers a wider range of dependencies of geopositioning data by incorporating the movements of neighboring data into the matching process. For this purpose, the concept of the window containing adjacent geopositioning data is introduced. Thus trendHMM can utilize relationships among continuous geopositioning data and showed considerable enhancement over HMM-based algorithm. Through experiments, we demonstrated that trendHMM map matching provides more accurate results than the existing HMM map matching for various environments and geopositioning data sets. Our trendHMM algorithm shows up to 17.58% of performance enhancement compared to HMM based one in terms of Route Mismatch Fraction.

Investigating the Effect on Productivity of a Geospatial Ticket Management System for Power Distribution Network Studies

Increasing productivity without jeopardizing the network’s operation, consumers’ experience, and the safety and integrity of procedures, is a major goal for all utilities. Scheduling of work has a direct impact on productivity, especially in the case of utilities that cover a wide geographical area using a limited number of employees. In the case of power utilities, however, scheduling has to consider, apart from the location of issues, the type and technical characteristics of each issue as well as its priority has to be considered in order to produce an optimum schedule. This paper focuses on the impact on productivity of a geospatial ticket management system considering the experience from such a system applied on network studies performed by HEDNO, the Greek Distribution Network Operator, in Patras Area. The term "network studies" is used to describe the study of all expansion and alteration works, ranging from a single Low Voltage (LV) pole installation to major Medium Voltage (MV) network rearrangements/expansion, and includes visits and measurements on the actual location as well as in-door calculations. In Patras Area, the local HEDNO division implemented in 2021-2022 a geospatial ticket managing system, based on available network data and custom Google Maps, aiming to increase its productivity by optimizing the scheduling process. Initial results published in February 2022, showed a significant productivity increase (up to 42%). However, the initial results considered a time span of only one month and thus could easily be misleading. This paper revisits the issue considering a larger time span (more than two years) that should provide more trustworthy results. It also briefly presents the latest updates and improvements made to the system. Results show that the increase in the number of studies and their predicted costs are similar to the initial results, with the increase in productivity being around 41%. In September 2022, HEDNO set the very ambitious goal of significantly increasing the overall production of network studies (more than double in terms of predicted costs) and the use of such a system can provide valuable help towards achieving this goal.

Architectural Features of the First Period (13th-15th Century) Tekkes in the Balkan

Islamic religion spreading was influenced by the different local traditions among which Sufism, a religious mysticism (tasavvuf) organized under the institutions of tariqa emerged. This was followed by the emergence of as a place where divisions (orders) members were gathered known under names of tekke, zaviye, hankâh, ribat and a dervish lodge. This study elaborates several tekkes established by the Ottomans in the Balkans. Building style of the tekkes varied according to the procedures as well as manners of the order. Tekkes, which have a simple appearance, generally consist of a mosque, semahane, cellar, kitchen, cells, çilehane, selâmlık and harem. However, most of the buildings within the tekke are constructed over a large span of time. The aim of this study is to better understand the spatial setup of this organizational structure, which directly contributed to the conquest in the Balkans through the janissary corps and to the futuwwa (a set of religious and moral vocational norms) through the ahis (religious and moral vocational chamber). For this purpose, the locations of the tekkes and their architectural features, which were established successively one after the other with the conquests, have been analyzed. In final, the architectural typological of the tekkes is obtained according to the belief tradition, positioning, foundation schemes and special plans of the early period structures set within the tekke.

Architectural Features of the First Period (13th-15th Century) Tekkes in the Balkan

Islamic religion spreading was influenced by the different local traditions among which Sufism, a religious mysticism (tasavvuf) organized under the institutions of tariqa emerged. This was followed by the emergence of as a place where divisions (orders) members were gathered known under names of tekke, zaviye, hankâh, ribat and a dervish lodge. This study elaborates several tekkes established by the Ottomans in the Balkans. Building style of the tekkes varied according to the procedures as well as manners of the order. Tekkes, which have a simple appearance, generally consist of a mosque, semahane, cellar, kitchen, cells, çilehane, selâmlık and harem. However, most of the buildings within the tekke are constructed over a large span of time. The aim of this study is to better understand the spatial setup of this organizational structure, which directly contributed to the conquest in the Balkans through the janissary corps and to the futuwwa (a set of religious and moral vocational norms) through the ahis (religious and moral vocational chamber). For this purpose, the locations of the tekkes and their architectural features, which were established successively one after the other with the conquests, have been analyzed. In final, the architectural typological of the tekkes is obtained according to the belief tradition, positioning, foundation schemes and special plans of the early period structures set within the tekke.

Multi-Time-Scale Simulation of Complex Reactive Mixtures: How Do Polyoxometalates Form?

Understanding the dynamics of reactive mixtures still challenges both experiments and theory. A relevant example can be found in the chemistry of molecular metal-oxide nanoclusters, also known as polyoxometalates. The high number of species potentially involved, the interconnectivity of the reaction network, and the precise control of the pH and concentrations needed in the synthesis of such species make the theoretical/computational treatment of such processes cumbersome. This work addresses this issue relying on a unique combination of recently developed computational methods that tackle the construction, kinetic simulation, and analysis of complex chemical reaction networks. By using the Bell-Evans-Polanyi approximation for estimating activation energies, and an accurate and robust linear scaling for correcting the computed pKa values, we report herein multi-time-scale kinetic simulations for the self-assembly processes of polyoxotungstates that comprise 22 orders of magnitude, from tens of femtoseconds to months of reaction time. This very large time span was required to reproduce very fast processes such as the acid/base equilibria (at 10-12 s), relatively slow reactions such as the formation of key clusters such as the metatungstate (at 103 s), and the very slow assembly of the decatungstate (at 106 s). Analysis of the kinetic data and of the reaction network topology shed light onto the details of the main reaction mechanisms, which explains the origin of kinetic and thermodynamic control followed by the reaction. Simulations at alkaline pH fully reproduce experimental evidence since clusters do not form under those conditions.

The effects of small class sizes on students' academic achievement, socioemotional development and well-being in special education: A systematic review.

The effects of small class sizes on students' academic achievement, socioemotional development and well-being in special education: A systematic review.

Role of Taxa Age and Geologic Range: Survival Analysis of Marine Biota over the Last 538 Million Years

Understanding past extinction processes is an important and current matter, and regression methods in the domain of survival analysis can be applied to fossil data. The chief goal of this study is to relate genus-level lifetimes to ancient environmental conditions (e.g., sea level and surface temperatures or carbon dioxide concentration). The Cox proportional hazards model was used to characterize the extinction risks of marine genera, enabling quantitative and graphical comparisons between selected taxonomic groups over geologic time. The environment was confirmed to be a significant factor, and both age-dependent coefficients and time-dependent covariates were required to accommodate the data. The Cox model analyzed in this study provides new insights into the extinction patterns of marine biota over the past 538.8 million years (Ma). Previous works focusing on specific groups at certain geologic times suggest that the extinction risk is related to taxa age, taxonomic group, and, in some particular cases, geologic time. Here, this idea is confirmed for a larger taxonomic group, during a larger time span (ca. 530 Ma), providing a more complete and complex scenario than previous works. After applying survival analyses, conjoint effects were observed between taxa and their age, their time of existence, and the prevailing environmental conditions found at any particular moment.

CLINICAL AND DEMOGRAPHIC DETERMINANTS OF PULSE WAVE VELOCITY TRAJECTORIES IN HYPERTENSIVE PATIENTS: A RETROSPECTIVE STUDY

Objective: Arterial stiffness (AS) is a strong predictor of cardiovascular disease and all-cause mortality. Its behaviour over time, assessed through repeated measurements, is still largely unexplored. The aim of this study was to assess the clinical and demographic determinants of trajectories of carotid-femoral pulse wave velocity (cf-PWV) in a cohort of French hypertensive adults. Design and method: From a population of 7806 patients referred to HEGP Pharmacology Unit (Paris, France) from 1981 to 2022, we selected those who had at least 3 cf-PWV recordings over time. Those with missing treatment information or rare vascular diseases were excluded. Cluster of trajectories analysis was performed and multinomial regression was used to detect differences in baseline characteristics between the identified clusters. Results: 564 patients were included in the analysis (median follow-up was 4.2 [3.2-6.4] years). Four clusters of stiffness trajectories were identified: low-stable (A, n = 199), medium-stable (B, n = 184), high-increasing (C, n = 127), and high-low-high (D, n = 54) clusters (Figure 1). Mean BP (MBP) and cf-PWV at baseline were progressively higher in the medium-stable, high-increasing, and high-low-high clusters compared to the stable one (MBP was 96 ± 12, 99 ± 12 and 101 ± 15 mmHg in clusters B, C, and D vs 92 ± 12 mmHg in cluster A; cf-PWV was 9.7 ± 1.2, 11.6 ± 1.6 and 15.3 ± 2.7 m/s in clusters B, C, and D vs 7.7 ± 1.0 m/s in cluster A; all p < 0.001). On multinomial regression analysis, older age, higher MBP, and diabetes were associated to increased probability of belonging to either C or D clusters when compared to the stable one. Anti-hypertensive treatment with blockers of renin-angiotensin system (RAS) was associated with a decreased probability of belonging to the C or D clusters (Table 1). Conclusions: This real-life data obtained by repeated cf-PWV assessments on a large time span shows that patients who will experience PWV worsening over time are characterized by older age, higher MBP and diabetes at baseline. The use of RAS blockers has a protective effect on PWV trajectories.

Research on a working face gas concentration prediction model based on LASSO-RNN time series data

The effective prediction of gas concentration trends and timely and reasonable extraction measures can provide valuable references for gas control. The gas concentration prediction model proposed in this paper has the advantages of a large sample size and long time span for training data selection. It is suitable for more gas concentration change scenarios and can be used to adjust the data prediction length according to demand. To improve the applicability and practicability of the model, this paper proposes a prediction model based on the LASSO-RNN (least absolute shrinkage and selection operator) for mine face gas concentration based on actual gas monitoring data from a mine. First, the LASSO method is used to select the key eigenvectors that affect the gas concentration change. Second, the basic structural parameters of the RNN prediction model are preliminarily determined based on the broad strategy. Then, the MSE (mean square error) and the running time are used as the evaluation indicators to select the appropriate batch size and number of epochs. Finally, the appropriate prediction length is selected based on the optimized gas concentration prediction model. The results show that the RNN gas concentration prediction model has a better prediction effect than the LSTM (long short-term memory) prediction model. The average mean square error of the model fit can be reduced to 0.0029, and the predicted average absolute error can be reduced to 0.0084. The maximum absolute error of 0.0202, especially at the time inflection point of the change in the gas concentration curve, can better reflect the superiority of the RNN prediction model, that is, higher precision, robustness and applicability than LSTM.