Probability Index Research Articles

Emotional valence, cloze probability, and entropy: Completion norms for 403 French sentences.

Sentence-final completion norms are a useful way to select materials in the study of psycholinguistics, neurosciences, and language processing. In recent decades, the literature has focused on measuring cloze probability and sentence constraint indexes to account for various contextual expectation effects. However, the emotional content of target words is another factor that may affect word prediction and has not yet been examined. The purpose of the present study was to design a French corpus of sentence completion norms for final words varying in both valence and arousal. A total of 1322 young adults participated in an online written cloze procedure, in which they were asked to guess the final missing word in given sentences. At least 275 individuals evaluated each sentence. Cloze probability index was estimated for each sentence ending with a negative, neutral or positive word, as well as the level of sentence uncertainty through the calculation of sentence entropy. We also estimated the emotionality of the beginning of each sentence as complementary information with valence and arousal values of sentence-ending words. The final corpus of 403 French sentences offers a wide range of cloze predictability contexts for all emotional categories of final words. We hope that these norms may help to implement new research investigating the interplay between language and emotional processing. The collected data and norms are accessible through the Open Science Framework at the following depository link: https://osf.io/7pc46/?view_only=a1ec1c23e28a45b9951c7cecc073e1ac.

Predicting brain tumour growth patterns using a novel MRI-based tumour spread map: application to radiotherapy planning.

The treatment of glioblastomas (GBM) with radiation therapy is extremely challenging due to their invasive nature and high recurrence rate within normal brain tissue. In this work, we present a new metric called the tumour spread (TS) map, which utilizes diffusion tensor imaging (DTI) to predict the probable direction of tumour cells spread along fiber tracts. We hypothesized that the TS map could serve as a predictive tool for identifying patterns of likely recurrence in patients with GBM and, therefore, be used to modify the delivery of radiation treatment to pre-emptively target regions at high risk of tumour spread. In this proof-of-concept study, we visualized the white matter fiber tract pathways within the brain using diffusion tensor tractography and developed an algorithm which mathematically calculates a relative probability index in each voxel, resulting in the generation of the TS map. Based on the information provided by the TS map, the original radiotherapy target volume was then modified to include areas with a higher probability of tumour spread and exclude other areas with a lower probability of spread. A volumetric modulated arc therapy (VMAT) treatment plan was then developed utilizing the modified target volumes and subsequently compared to that using the original target volumes. Follow-up anatomical imaging obtained 8 months post-surgery was assessed to validate our findings. A TS map was generated on a glioblastoma patient demonstrating a relative probability of tumour spread along fiber tracts throughout the brain. The modified planning target volume better covered brain regions with a higher risk of tumour spread while still demonstrating a 21% reduction in volume compared to the original planning target volume, resulting in greater preservation of normal tissue. The modified VMAT plan resulted in an average mean dose to four identified recurrences of 80% of the prescription dose, while the original VMAT plan delivered only 63% of the prescription dose as the average mean dose to the recurrences. The utilization of tractography and the generation of corresponding TS maps offer a promising approach to predicting patterns of tumour recurrence and optimizing treatment delivery. Further research is needed to validate the predictive value of the TS map on a larger cohort of patients and explore its potential in personalized treatment strategies for GBM patients.

Realized Probability Index is a Better Market Timing Indicator

Abstract In practice, market timing is a well-known trading strategy among investors, and different indicators have been proposed for market timing methods. This paper compares three indicators used in market timing strategy: the return, the 0–1 binary index, and the realized probability index. It is shown that realized probability index is more informative and more efficient than the 0–1 binary index in terms of market timing, and tends to be more predictable than the return itself. This finding is interesting and important as it proves for the first time that the realized probability index is a more efficient market timing indicator and thus should be given more attention by both academic researchers and practitioners. An empirical study is performed on different stock indices, and the results confirm our finding.

EFFECTS OF ORTHODONTIC TREATMENT ON PERIAPICAL HEALTH IN ENDODONTICALLY TREATED TEETH

This retrospective study evaluated the impact of orthodontic treatment on endodontically treated teeth. 32 teeth from 25 patients were analyzed, focusing on CBCT evaluations. All endodontic treatments utilized EDTA and 5.25% NaOCl in conjunction with Er:YAG laser-activated irrigation. Post-treatment assessment revealed that 21 teeth (66%) had root canal fillings of correspondent length, while 10 teeth (31%) were insufficient, and 1 tooth (3%) was uncertain. In terms of density and homogeneity, 25 teeth (78%) were classified as correspondent, 5 teeth (16%) as inadequate, and 2 teeth (6%) as uncertain. The periapical bone destruction probability index (PRI) demonstrated a significant increase in periapical destruction following orthodontic treatment. Specifically, the odds ratios for bone destruction were 1.67 (90% CI: 1.16–2.49, P=0.008) for present versus absent and 1.77 (90% CI: 1.11–2.85, P=0.031) for present versus uncertain. The proportion of teeth without periapical destruction decreased from 15 (14.9%) during treatment to 14 (23.9%) post-treatment. These findings highlight the critical relationship between endodontic quality and treatment outcomes, emphasizing the need for meticulous endodontics during orthodontic therapies.

Analysis of Blood Utilization Practices and Quality Indicators in a South Indian Teaching Hospital in Puducherry, India

Abstract Introduction: The transfusion of donated blood is the mainstay of treatment for medical or surgical conditions. It is the primary responsibility of blood transfusion services to provide a safe, sufficient, and timely supply of blood products. It is recommended to conduct regular audits to know usage trends. This study aims to analyze the utilization pattern and quality indicators of transfusion services. Materials and Methods: This is a retrospective study conducted in the blood center of a tertiary care teaching hospital in Puducherry, India. We collected and analyzed data on the request and utilization of blood and its products from January 2023 to December 2023. The department-wise utilization of blood and its components, crossmatch to transfusion ratio (C: T ratio), transfusion probability (T%), and transfusion index (TI), were calculated. Results: Packed red blood cells (PRBCs) were the most utilized blood product. The intensive care unit ward received the highest blood supply, followed by obstetrics/gynecology and orthopedics. Patients with anemia, followed by surgery and pregnancy, required a majority of PRBCs. The CT ratio, TI, and TP% were 2.7%, 0.42%, and 0.37%, respectively. Conclusions: The overall transfusion indicators, namely C/T ratio, TI, and TP, were near optimal compared to standard values. However, the majority of the cross-matched blood remained unused. It is crucial to conduct a periodic review of the blood component usage in a hospital.

Subjective Assessment of Rdoc-Related Constructs in Addiction and Compulsive Disorders: A Scoping Review.

Obsessive-compulsive and related disorders (OCRDs) and disorders due to addictive behavior (DABs) are prevalent conditions that share common neurobiological and behavioral characteristics. This scoping review aims to identify and map the range of subjective assessment tools (e.g., interviews and self-report instruments) for assessing Research Domain Criteria (RDoC) and related constructs underlying DABs and OCRDs, such as impaired response inhibition, habit formation, and compulsivity. A scoping review was performed following the PRISMA Extension for Scoping Reviews (PRISMA ScR). The search was conducted in Medline, Web of Science, PsycINFO, and EMBASE databases. No constraints of data or document type were adopted. The search yielded 615 instruments, of which 79 were deemed transdiagnostic and capable of assessing at least one of the target constructs. Noteworthy tools included are the Cambridge-Chicago Compulsivity Trait Scale, the Self-report Habit Index, the Reward Probability Index, the Threat-Related Reassurance-Seeking Scale, and the recent Positive Valence Systems Scale. Despite the growing body of literature on OCRDs and DABs as new diagnostic chapters and the number of tools with the potential to assess their transdiagnostic constructs clinically, most instruments were designed to capture dimensions or psychopathology not directly (or primarily) related to OCRDs, DABs and the concepts of impaired response inhibition, habit formation, and compulsivity in the context of these conditions. Further studies exploring the correlation between subjective assessments, corresponding behavior paradigms, and neuroimaging data would be of great value in the translation of RDoC constructs and domains into clinical settings.

ПРИРОДНЫЕ И ТЕХНОГЕННЫЕ АНОМАЛИИ ПОТЕНЦИАЛЬНО ТОКСИЧНЫХ ЭЛЕМЕНТОВ В ПОЧВАХ ВОКРУГ ТМО КОУНРАДСКОГО РУДНИКА: ПРЕДВАРИТЕЛЬНЫЕ ИССЛЕДОВАНИЯ ТЕРРИТОРИИ МЕТОДАМИ ГИС И ДЗ

The paper analyzes multispectral remote sensing data to identify surface scattering halos of potentially toxic elements in the area of the Kounrad mine dumps (Pribalkhashye, Central Kazakhstan). As a result of processing the satellite imaging data, spectral indices were obtained that characterize the material features of the studied surface deposits. The obtained results allowed specifying the necessary elements of the geological structure of the territory, to identify areas of probable accumulation of toxic elements, which are of the main interest for subsequent lithological and geochemical studies. In particular, indices were obtained that characterize the general geological structure of the territory. Including its structural and tectonic elements and probability indices of the spatial distribution of three different types of substances identical to those contained in the dumps of the Kounrad mine were constructed. Using the obtained data, two main types of anomalies, both natural and anthropogenic, were identified in the area around the mine and its dumps, which in some places spatially overlap. The obtained results served as a base for integrating heterogeneous data into a single information system (GIS). The high efficiency of the used techniques demonstrated. In addition, it is confirmed not only by both the comparison of the results obtained in the control areas, and by subsequent lithological and geochemical studies.

A Human Behavior Wildfire Ignition Probability Index for Application to Mainland Portugal

A Human Behavior Wildfire Ignition Probability Index for Application to Mainland Portugal

Assesses of Chronic Lymphocytic Leukemia Cases with Isoform P53 Protein Using Elisa Method

Background P53 gene mutation is a very common event in human neoplasia, and genetic mutations in the P53 gene in a single allele are responsible for a hereditary cancer susceptibility syndrome (Li Fraumeni). These variants encode distinct isoforms of the p53 protein, which may disrupt its transcriptional activity. These point mutant proteins are more stable than the normal protein and the mutant product accumulates at a high level that allows obtaining important information about p53 gene expression in malignant cells, especially in Chronic Lymphocytic Leukemia, (CLL). By Enzyme Linked Immune-Absorbent Assay method, (ELISA), was analyzed the frequency of p53 protein expression to 20 eligible patients diagnosed with CLL for to investigate the relationship of this protein in the stages of the disease and the impact on treatment response and survival. In ELISA technique was used the specific antibodies for isoform p53 protein, PAb 240 antibodies. These antibodies bind specifically to denatured p-53 protein. Species reactivity is for human in conformity with the prospect from Manual, Catalog No. LS-F174, Bio-Rad. Results The average concentrations of p53 proteins in 17 of 20 cases were found 16.76 μg / dl, with CV = 0.5% and the probability index p = 0.034. Very high pathological values in the 3 cases of isoform p53 protein were calculated in 2 men, (PM) in the value of 60 µg / dL, respectively at 40 µg / dL and in the case of females, (PW), in 40 µg / dL value, with the transformation into Diffuse Large Lymphoma, (DLL). Conclusion This ELISA method has proven to be a useful prognostic tool for the application of personalized treatment of on-immune therapy, in cases diagnosed with the type BCLL.

Manajemen Anestesi Gravida dengan Plasenta Akreta yang dilakukan Seksio Sesarea dengan Transarterial Ballooning

Bleeding before (antepartum) and after (postpartum) delivery remains a major contributor to perinatal mortality and maternal morbidity worldwide. Placenta accreta is a cause of maternal morbidity and mortality, recently becoming the most common reason for emergency postpartum hysterectomy. A 35-year-old woman weighing 55 kg, height 151 cm, G3P1101Ab000 at a gestational age of 34-36 weeks, with a history of antepartum bleeding and suspicion of placenta accreta from the ultrasound, is scheduled for pregnancy termination via cesarean section. Before the surgery, a transarterial balloon catheter is inserted, and the estimated blood loss during the operation is around 10,000 ml. In this patient, the choice of general anesthesia is made considering the history of third-trimester bleeding, a high probability index score of 51% for accreta, and the plan for hysterectomy, leading to an anticipated prolonged operation time. Additionally, the risk of significant bleeding during the surgery prompts the selection of general anesthesia for hemodynamic management, and the placement of a catheter balloon is done to anticipate massive bleeding. To obtain a more comprehensive comparison and understanding of estimated blood loss, a comparison with other cases involving catheter balloon procedures before or after surgery is needed.

Performance of the systemic lupus erythematosus risk probability index (SLERPI) in the Egyptian college of rheumatology (ECR) study cohort

ObjectivesThis study aimed to evaluate the performance of systemic lupus erythematosus Risk Probability Index (SLERPI) in Egyptian patients with SLE using a national rheumatology database.MethodsThe Egyptian College of Rheumatology (ECR) database comprised of 1,162 patients with SLE and 4,327 with miscellaneous rheumatological diseases who were recruited from the Rheumatology Departments across the country. The diagnosis of SLE was established by expert rheumatologists. Variables of the SLERPI were extracted and recorded as present or absent for each patient. The absolute value for the SLERPI score was calculated for each patient, and the diagnosis of SLE was accounted for if the score was greater than 7 points.ResultsOf 1,162 SLE patients evaluated, 1,031 (88.7%) patients were diagnosed with SLE according to the SLERPI, with an average score of 13.1 (3.8). Differences in the 14 SLERPI variables were significant between the SLE-SLERPI groups, except for the presence of leukopenia and positive ANA. As a score reduction item, the SLE-SLERPI > 7 group had lower interstitial lung diseases. Patients diagnosed with SLE according to SLERPI had significantly higher disease activity (p < 0.001), and this group more commonly received corticosteroids and mycophenolate mofetil. Compared to other miscellaneous rheumatological groups, all 14 SLERPI items are indeed more common in the SLE group. In terms of the overall performance of SLERPI in the diagnosis of SLE, the accuracy of SLERPI was 91.9% (95% CI 90.9%—92.9%), with a specificity of 96.95% and sensitivity of 86.9%. SLERPI showed that accuracy went up to 93.3% (95%CI 92.4%-94.2%), with a specificity of 94.9% and a sensitivity of 91.6% when patients with connective tissue diseases were taken out of the study.ConclusionUsing a large cohort of SLE, the SLERPI revealed excellent diagnostic efficacy and specificity. The use of SLERPI in clinical practice may contribute to improved patient diagnosis and prognosis.Key Points• SLERPI's performance has high diagnostic efficiency in Egyptian SLE patients.• SLERPI score can efficiently distinguish patients with SLE from other CTDs.• Within the SLERPI score, interstitial lung disease is the lowest predictor of SLE.

Is Idiopathic Granulomatous Mastitis a Subgroup of Systemic Lupus Erythematosus? A Preliminary Study

Objective: The study aimed to use the systemic lupus erythematosus risk probability index (SLERPI) to assess if patients with idiopathic granulomatous mastitis (IGM) meet the criteria for systemic lupus erythematosus (SLE). Methods: A total of 62 patients with IGM and 55 age- and sex-matched healthy controls (HC) were enrolled. The study included patients who were over 18 years old and had been diagnosed with IGM using a true-cut biopsy. The participants’ demographic, clinical, and laboratory data were recorded in detail. The presence of autoantibodies, such as RF, CCP, C3, C4, ANA, ENA profile, and Anti-dsDNA was documented. For the detection of SLE in IGM patients, we used the SLERPI (SLE risk probability index). Results: A total of 62 patients diagnosed with idiopathic granulomatous mastitis (age 35.22 ± 8.34, BMI 27.15 ± 3.41) were compared to 55 healthy controls (age 32.54 ± 8.67, BMI 26.97 ± 3.54). The present study assessed the performance of SLERPI in IGM, and SLERPI positivity was observed in 12 out of 62 (19.4%) IGM patients. There was a significant difference in arthritis and ANA levels in the SLERPI subgroups (p &lt; 001). Conclusions: The SLERPI index can be utilized to identify patients suspected of having systemic lupus erythematosus (SLE) in the IGM cohort.

A global analysis of nearshore and submarine springs: spatial distribution, controlling factors, and probability of presence

Coastal springs act as bi-directionally preferential flow paths between coastal aquifers and oceans. While these springs can supply coastal ecosystems with nutrients, they also present vulnerabilities such as contamination and seawater intrusion. Despite their significance, substantial knowledge gaps exist regarding coastal springs due to their complex hydrogeological nature. This study provides a comprehensive global assessment of coastal springs, focusing on their distribution, controlling factors, and likelihood of occurrence. A global dataset of known coastal springs was compiled and analyzed, revealing 66 % of identified springs in the Mediterranean region, mainly linked to karst systems. In contrast, fewer springs were noted in Africa, South America, and South Asia. Key factors influencing spring occurrence were examined using geostatistical methods and integrated into a multi-criteria decision-making framework to develop a Coastal Spring Probability Index (CSPI) along coastline. High-potential areas for coastal springs were identified in regions characterized by significant carbonate and volcanic rock formations, wetter climates, and active tectonic margins, such as southern Europe, the Caribbean, tropical islands, and eastern Asia. Conversely, regions with dry climates and high water demand, such as North Africa and South America, exhibited a lower likelihood of spring presence. These findings will serve as a baseline for local-scale studies and aimed at improving coastal spring inventories and establishing monitoring networks. It will contribute to vulnerability assessment studies, thereby enhancing the management of coastal groundwater resources. The study emphasizes the importance of multidisciplinary approaches to understand coastal spring dynamics and advocates for a strategic planning in groundwater management and conservation. Ongoing efforts to inventory and monitor coastal springs, coupled with targeted conservation measures, are essential for ensuring the long-term sustainability of coastal water resources and ecosystems.

A hybrid framework for Detection of Multivariate porphyry Cu Signatures and Anomaly Enhancement: Incorporation of SFA, GMPI, and Grey Wolf Optimization

Geochemical data from stream sediment are commonly employed for regional scale mineral exploration, as they can be utilized to detect geochemical anomalies associated with mineralization processes. However, recognizing efficient multielement geochemical signatures related to target mineralization using stream sediment geochemical data can be challenging due to the intricate nature of mineralization events. To achieve this goal, this article proposes a combination of statistics, logistic functions and machine learning techniques. Initially, the staged factor analysis (SFA) approach was applied to the data to determine the geochemical footprints associated with porphyry copper mineralization in the Varzaghan area. Subsequently, the geochemical mineralization probability index (GMPI) was utilized to facilitate appropriate separation, more precise identification, and the transfer of data into a fuzzy space. By using a combination of SFA and GMPI, it was feasible to enhance the detection of geochemical halos and concealed anomalies. Ultimately, the output of these two approaches was subjected to an improved clustering technique known as GWO-K-means to detect geochemical anomalies. The findings indicated that there is a strong relationship between known mineral occurrences (KMOs) and the identified anomalous areas. The success rate curve demonstrated that the optimized model outperformed the K-means model, proposing that optimization can boost the accuracy in identifying geochemical targets. Overall, the outcomes of this study can be beneficial for proper planning of future exploration activities.

EUROPE’S ENERGY SECURITY AMID RUSSO-UKRAINE WAR: NAVIGATING THE FUTURE BY EMPLOYING MODIFIED SCENARIO BUILDING TECHNIQUE

The Russo-Ukraine War has exposed the vulnerabilities of Western Europe’s energy security, which has traditionally relied heavily on Russian energy supplies. This excessive dependency has resulted in energy shortages, price volatility, and inflation due to continuing disruptions. By employing the scenario-building technique, this study offers insight into the implications of the War on energy security, strategic choices, and policy considerations for stakeholders as a result of scenario building. The scenario building technique used in this study is modified version that has been modelled by the author by totally overhauling the conventional model in practice. The study projects potential scenarios by leveraging the modified scenarios building and development technique. The findings signify the necessity of thoroughly reevaluating Europe’s stance towards the conflict, identifying looming threats, strategic adaptability regarding the diversification of energy resources and routes, and creating a collaborative European Union framework to articulate collective responses to mitigate the risks. Finally, the results are presented in four major probable future scenarios, each displaying unique challenges and strategic choices. Concluding with geopolitical, geostrategic and geoeconomic triggers and their graduation on impact and probability indices, offer a whole sum view to the stakeholders of the Western Europe to mitigate threats to their energy security amid ongoing Russo-Ukraine War. In a nutshell, while advancing the discourse on Western Europe’s energy security, the study offers a nuanced analysis and detailed strategic roadmap for the future of energy, where these scenarios underscore the critical need to pacify the conflict, anticipate the long-term risks and their mitigation, diversify the energy sources, enhance energy efficiency, formulate resilient energy policies, the collaborative framework within the European Union, collective energy purchase and storage mechanism.

Quantitative method for the probability of structural damage based on moment theory

In the context of uncertainty in the inverse problem of damage identification, this study proposes a moment theory based probabilistic damage identification (MbPDI) method. Noise errors in the identification process are treated as uncertain parameters, while structural stiffness parameters are treated as functions of noise errors. A limit state function for damage identification is defined, and its probability is computed. Utilizing the concept of moment theory, the expansion series is performed for the limit state function around the most probable point of failure, with gradient information derived using sensitivity matrices. Based on the gradient information and uncertainty inputs, damage probabilities for various elements can be obtained. Additionally, this paper addresses the calculation of structural damage probabilities under the non-normal distribution of random variables by transforming non-normal variables into equivalent normal variables. The proposed probability index and expected index of structural damage in the probabilistic damage identification method has a clear physical meaning, and the calculation has high accuracy. The proposed method is validated through a mathematical example and a numerical simulation. Meanwhile, the influence of damage extent, noise level, and modal order on identification results are analyzed. Experimental validation of the method is also presented.

Validation of a machine learning algorithm for identifying infants at risk of hypoxic ischaemic encephalopathy in a large unseen data set

ObjectiveTo validate a hypoxic ischaemic encephalopathy (HIE) prediction algorithm to identify infants at risk of HIE immediately after birth using readily available clinical data.DesignSecondary review of electronic health record data...

Performance of the Systemic Lupus Erythematosus Risk Probability Index (SLERPI) in a cohort of Colombian population

ObjectiveTo evaluate the performance of the Systemic Lupus Erythematosus Risk Probability Index (SLERPI) in Colombian patients with systemic lupus erythematosus (SLE).MethodsThe Colombian cohort included 435 SLE patients and 430 controls with other autoimmune diseases (ADs). Clinical and serological data were collected, and SLE was indicated by SLERPI scores > 7. The American College of Rheumatology (ACR)-1997, Systemic Lupus International Collaborating Clinics (SLICC)-2012, and European League Against Rheumatism (EULAR)/ACR-2019 criteria were used as reference standards. The impact of overt polyautoimmunity (PolyA) on SLERPI performance was assessed. Additionally, multivariate lineal regression analysis was performed to evaluate the contribution of SLERPI features to the overall SLERPI score.ResultsSLE patients had higher SLERPI scores (P < 0.0001), with almost 90% meeting "definite" lupus criteria. Main factors influencing SLERPI included immunological disorder (β:44.75, P < 0.0001), malar/maculopapular rash (β:18.43, P < 0.0001), and anti-nuclear antibody positivity (β:15.65, P < 0.0001). In contrast, subacute cutaneous lupus erythematosus/discoid lupus erythematosus (β:2.40, P > 0.05) and interstitial lung disease (β:-21.58, P > 0.05) were not significant factors to the overall SLERPI score. SLERPI demonstrated high sensitivity for SLE, both for the overall SLE group and for those without overt PolyA (95.4% and 94.6%, respectively), but had relatively low specificity (92.8% and 93.7%, respectively). The model showed high sensitivity for hematological lupus (98.8%) and lupus nephritis (96.0%), but low sensitivity for neuropsychiatric lupus (93.2%). Compared to the ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria, SLERPI yielded the highest sensitivity and lowest specificity.ConclusionSLERPI efficiently identified SLE patients in a Colombian cohort, showing high sensitivity but low specificity. The model effectively distinguishes SLE patients, even in the presence of concurrent overt PolyA.Key Points•SLERPI has a high sensitivity, but low specificity compared to ACR-1997, SLICC-2012 and EULAR/ACR-2019 criteria in the Colombian population.•Within the SLERPI score, immunological disorder, malar/maculopapular rash, and anti-nuclear antibody positivity are the strongest predictors of SLE.•SLERPI model can efficiently distinguish patients with SLE, regardless of concomitant overt PolyA.•SLERPI demonstrates high sensitivity in identifying hematological and nephritic subphenotypes of SLE.

Statistical Study of the Mechanical Behavior of the New Fiber from the Strelitzia Juncea Plant Fibers: Application in Ecological Yarns

ABSTRACT To develop efficient, durable, and eco-friendly natural fiber composites, this study examines the physical properties of Strelitzia Juncea (SJ) fiber for potential industrial use. The focus is on how gauge length affects mechanical properties of SJ fibers, aiming to manufacture textile yarns. Tensile tests were performed on SJ yarns of varying diameters (0.95, 1.26, and 1.76 mm). In addition, 150 fibers across five-gauge lengths (GL) from 10 to 50 mm gave a strength of 731 to 270 MPa and a Young’s modulus of 28 to 31 GPa, with statistical analysis applied to evaluate the data’s variability. Statistical techniques were applied to assess and quantify this dispersion. Results were analyzed using Weibull distributions with different probability indices, along with least squares (LS) and maximum likelihood (ML) estimation techniques. Furthermore, for each tensile strength characteristic, a one-factor analysis of variance (ANOVA) was performed across the five groups.

Physiological and Psychological Factors Contribute to Real-Time Esophageal Symptom Reporting in Patients With Refractory Reflux.

Real-time symptom reporting during ambulatory reflux monitoring plays a key role in the evaluation of esophageal symptoms, although the underlying processes are poorly understood. We aim to identify the psychological and physiological factors associated with real-time reflux symptom reporting and symptom-reflux association parameters. Adult patients with refractory reflux symptoms completed psychosocial questionnaires and standard 24-hour pH-impedance monitoring. A hurdle-Poisson model evaluated the association between psychological and physiological (proton pump inhibitor [PPI] use, total number of reflux episodes) variables on real-time symptom frequency, assessed through a button press within 2 minutes of experiencing a symptom. Logistic regression assessed the variables associated with symptom association probability (SAP) and symptom index classification (positive/negative). Complementary machine learning analyses with 8-fold cross-validation further identified variables associated with symptom frequency and sought to optimize SAP classification performance. Both psychological (pain-related anxiety, depressive symptoms, trait anxiety) and physiological (total number of reflux episodes, off PPI during testing) variables were associated with symptom frequency. The total number of reflux episodes and being studied off PPI were significantly associated with a higher likelihood of being classified as SAP or symptom index positive. The best-performing model in the machine learning analysis demonstrated a poor job of correctly classifying patients as SAP positive/negative (misclassification rate = 41.4%). Real-time reflux symptom reporting is a multifactorial process, with both psychological and physiological processes contributing to different aspects of the reflux disease experience. Findings build on questionnaire-based research to underscore the importance of including psychological processes in our understanding of esophageal symptom reporting.