Standard Class Research Articles

Latent class choice models with an error structure: Investigating potential unobserved associations between latent segmentation and behavior generation

Latent class choice modeling has gained great popularity in the transportation and choice modeling communities across the years. However, discussion of principles associated with the specification of the class membership model has barely appeared in the literature. Related to this issue, this study questions whether one of the basic assumptions of latent class choice modeling, that of independence between latent segmentation and the behavior generation process, is tenable. We formulate latent class choice models where the unobserved influences on latent segmentation and behavior generation are correlated, by introducing an error structure reflecting that supposition. The proposed method is applied to two empirical settings. In the first application, the dependent variable is an ordinal variable measuring willingness to share autonomous vehicle rides with strangers. In the second application, the dependent variable is a binary indicator of whether a person has used ridehailing services for social purposes. In both applications, error correlations were statistically significant, indicating that the segmentation and behavior generation processes are jointly determined. Although goodness of fits and parameter estimates per se are similar to those of the standard latent class choice models for these particular applications, allowing an error structure leads to a subtle change in model implications. In particular, our scenario analyses, which present marginal effects, illustrate the value of the proposed model for considering jointness arising from correlated errors, in contrast to standard latent class models. Lastly, we propose several avenues for future research.

The effect of mini-till and no-till technologies on productivity and quality of malting barley grain

The purpose of the current work was to study the effect of mini-till, no-till and traditional agricultural technologies on productivity and quality of malting barley grain. Field trials were carried out in three crop rotation sequences ‘winter rye – spring wheat – barley’ on medium loamy gray forest soil of Chuvashia with 2.42 % of humus; 188 mg/kg of mobile phosphorus; 160 mg/kg of exchangeable potassium and 6.2 of exchangeable acidity. During the vegetation period of 2020, the hydrothermal coefficient was 1.04; in 2021 it was 0.60; and in 2022 it was 1.05. The object of the study was an early-maturing variety ‘Elf’. Traditional agricultural technology was based on autumn disk plowing and autumn plowing, early spring harrowing, seedbed cultivation and sowing with subsequent rolling. Mini-till cultivation included autumn disk plowing, spring cultivation and sowing with the multifunctional complex “Cultibar 9000”. No-till cultivation consisted of autumn treatment with the non-selective herbicide “Sprut Extra" and “direct” spring sowing “Cultibar 9000”. The seeding rate was 200 kg/ha. The dose of mineral fertilizers was N30P20К20. The crops were protected from weeds, diseases, and pests. On average, the largest (2.49 t/ha) productivity of malting barley grain was obtained using mini-till technology, and the smallest (2.34 t/ha) when using no-till. The mean productivity with traditional agricultural technology was lower than the maximum by 0.03 t/ha, but larger than the minimum by 0.12 t/ha. The analysis of the qualitative characteristics has shown a reliable effect of agricultural technologies on the brewing properties of barley grain. Thus, traditional technology contributed to obtaining grain of the 1st class, mini-till technology contributed to obtaining grain of the 2nd class, and no-till technology contributed to obtaining grain of the 3rd class of the interstate standard.

Abstract 4136202: Incident Hypertension and Survival Outcomes After Immune Checkpoint Inhibitor Initiation

Introduction: Immune checkpoint inhibitors (ICIs) are commonly used as anticancer agents linked with dramatic antitumor response but are associated with cardiotoxicity. Recent isolated reports have suggested ICIs may link with hypertension (HTN) after years of treatment. Yet, the timing and long-term ramifications of this HTN are unknown. Methods: From a large cohort of well-phenotyped cancer patients treated with ICIs from 2011-2022, we assessed the incidence of new or worsened HTN [systolic blood pressure (SBP) ≥130 mmHg (or in a higher HTN stage) on two occasions within a three-month period or addition of an antihypertensive medication] after ICI initiation. Secondary endpoints included major cardiovascular events (MACE), defined as symptomatic arrhythmia, myocardial infarction, stroke, heart failure, or cardiac death. Observed incident HTN rates were compared to Framingham-predicted rates, using JNC 8 cutoffs of 140/90 mmHg. Landmark analysis, excluding patients who were observed to have new HTN but had SBPs ≥130 mmHg on two occasions within six-months prior to ICI initiation, identified patients with possible undiagnosed HTN. Multivariable regression and survival analysis were used to define factors associated with new worsened HTN and MACE and the relationship between SBP increase and MACE risk. Further, the effect of standard antihypertensive classes on the prevention of ICI-related HTN will be assessed. Results: Overall, from 312 patients treated with ICIs (mean age 63.5 years, 67.4% baseline HTN, 11.0% on dual ICI-therapy), 50.0% (156/312) developed new or worsened HTN over a mean of 27 months follow-up. Cumulative incidence of new HTN by 1-year was 50.0% wherein the mean peak increase in SBP was 12 mmHg. In landmark analysis, excluding those with undiagnosed HTN and applying the JNC 8 cutoff of ≥140/90 mmHg, the observed new HTN rate was 21.4% at 1 year, >2-fold higher than the Framingham-predicted rate of 9.3% (RR 2.3, P <0.0001). In those with preexisting HTN, 49% developed worsened HTN. In multivariate analysis, only time on ICI treatment, ECOG status, and autoimmune disease history were associated with new or worsened HTN after ICI-initiation ( P <0.05 for all). Further, only prior autoimmune disease and ECOG status associated with MACE; while beyond traditional cancer factors, only new or worsening HTN associated with lower mortality. Conclusions: Collectively, these data suggest that HTN may be common with ICIs, and prognosticates survival.

How Intense and Authentic Communication in Foreign Language Classes Has a Positive Effect on Learner Emotions

This cross-sectional mixed methods study investigates how intense and authentic communication shapes learners’ enjoyment (FLE), anxiety (FLCA), and boredom (FLCB) in class. Participants were 181 beginning English foreign language learners aged 11 in three secondary schools in France. Statistical analyses revealed that pupils in classes with a special focus on intense and authentic communication experienced significantly more FLE and less FLCA and FLCB than their peers in standard classes. Structural equation modelling revealed that intense and authentic communication had the strongest (positive) effect on FLE, followed by negative effects on FLCB and FLCA. FLE was found to be negatively correlated with FLCA and FLCB, while FLCA and FLCB were positively correlated. An axiological analysis of the qualitative data showed that pupils in intense, authentic communication classes reported more FLE, less FLCB, and equal FLCA compared with peers in the standard teaching classes. Pedagogical implications are presented.

The first derivative test and the classification of stationary points

Given a real differentiable function f we say that a point x0 is a stationary point of f if f′ (x0) = 0.In any standard single-variable calculus class, students learn how to determine the nature of a stationary point by checking the sign of f(x) in intervals to the left and to the right of the stationary point. In doing so, they are performing the first derivative test.

Telehealth based parental support over 6 months improves physical activity and sleep quality in children with autism: a randomized controlled trial.

Sleep disturbances are prevalent in autistic children. The emergence of telehealth offers new possibilities for remote professional intervention. By combining telehealth with parental support, this study aims to explore a novel family-based model to enhance moderate-to-vigorous physical activity (MVPA) and improve sleep quality in children with autism. Thirty-four autistic children (mean age = 15.7 years) were randomly assigned to either a 6-month intervention group or a control group. Both groups received standard physical education classes at school. The intervention group received additional after-school telehealth support. MVPA and sleep quality were assessed 1 week before the intervention and at the 6-month follow-up. After 6 months, children in the intervention group nearly doubled their daily MVPA compared to the control group (Cohen's d = 8.34, CI95% = 6.17-10.52). Actigraphy-assessed sleep efficiency was notably higher (d = 2.35, CI95% = 1.44-3.26), and there were reductions in wake time (d = 1.65, CI95% = 0.84-2.46), sleep fragmentation (d = 0.80, CI95% = 0.07-1.52), and sleep latency (d = 0.82, CI95% = 0.09-1.54) were all reduced. These improvements in objective sleep metrics were corroborated by subjective assessments using the Sleep Disturbance Scale for Children (d = 0.86, CI95% = 0.13-1.59). Telehealth combined with parental support addresses barriers to enhancing health behaviors at home. This innovative model not only improves after-school MVPA and sleep quality in autistic children but also holds significant potential for benefiting other populations requiring remote support. https://clinicaltrials.gov/study/NCT06444659?id=NCT06444659&rank=1 (NCT06444659).

Study protocol of a breathing and relaxation intervention included in antenatal education: A randomised controlled trial (BreLax study).

Antenatal education is part of antenatal care in many countries. Physical and mental preparation for childbirth and information on pain management are considered key elements of antenatal education classes. Evidence suggests that women who participate in antenatal education classes appear to benefit in terms of self-efficacy and childbirth experience. In particular, women with increased fear of childbirth benefit from trained breathing and relaxation techniques in antenatal education. However, little is known about the effect of breathing and relaxation techniques on the outcomes of healthy pregnant women without fear of childbirth or who do not have medical or obstetric risks, or on neonatal outcomes. The aim of this study is to test whether including a breathing and relaxation technique in an antenatal education class will improve self-efficacy towards birth compared to a standard antenatal education class. The study will be a two-armed randomised controlled trial (RCT). Healthy pregnant women between the 12th and 30th week of gestation with singleton low-risk pregnancies and who are receiving routine antenatal care will be recruited in a hospital in Switzerland. All women included will attend an 8-hour antenatal education class. The intervention group will additionally practise a breathing and relaxation technique, receive a handbook to guide their exercise practice at home, and be provided with access to an online brochure with video and audio recordings for guidance. Data on maternal and neonatal outcomes will be collected after recruitment, in the 37th week of pregnancy, and two to four weeks postpartum. The effectiveness of including a breathing and relaxation technique in antenatal education classes on women's self-efficacy is discussed as a means to improving women's pregnancy and childbirth outcomes. NCT06003946, SNCTP000005672.

THE MINIMUM ECCENTRIC-DOMINATING ENERGY OF A GRAPH

Let be a simple graph. A subset of vertices in is said to be an eccentric-dominating set if for each vertex not in , there exists at least one eccentric vertex in and . The cardinality of the minimum eccentric-dominating set is called the eccentric domination number, denoted by . In this article, we define and study the minimum eccentric-dominating energy , and compute the exact value for some standard classes of graphs. Also, we establish some bounds for .

Shaping the Bilingualism of Game-Addicted Players

In today's world, many people who spend more and more time in front of their computer and treat it as something more than a popular pass-time activity are often referred to being game addicted. At the same time, however, many of them, because of being exposed to different forms of dialogic English may be observed to excel the language and react to quite many situations they are exposed to both during the play and out of it. This study is meant to show how gaming addicts shape their bilingualism. Due to our research, it was found that such people who are truly addicted to games often reach a higher level of English much faster when contrasted to average L2 users. The research was based on the surveys filled by 54 carefully selected Internet respondents that fit the definition of a game addicted person (APA, 2022) and a standardized CEFR test they were requested to complete; the same test was also requested to be completed by the people who attend standardized blended L2 classes and who play similar games sporadically for pleasure. Consequently, a correlation between addicted and non-addicted people, and their CEFR test results was carried out. What followed was an analysis of the research results and the their detailed description.

Double domination number of graphs generated from unary products

A subset $S$ of $V(G)$ is a double dominating set of a graph $G$ if $S$ dominates every vertex of $G$ at least twice. The minimum cardinality of a double dominating set denoted by $\gamma_{2\times}(G)$, is the double domination number of $G$. In this paper, we identified the double domination number of graphs generated by applying various unary operations on standard graph classes.

The Dustiest Galactic S Stars: Mid-infrared Spectra from SOFIA/FORCAST

We present spectra of 12 of the reddest, and hence dustiest, S stars in the Milky Way, observed with the FORCAST grisms on SOFIA. S stars are asymptotic giant branch (AGB) stars with C/O ∼ 1, so their molecular and dust chemistries are dominated by neither O nor C, often leading to atypical spectral features from their molecules and dust grains. All of the stars in our sample have strong dust emission features at 10–11 μm, but the shape of the feature in most of the stars differs from the shapes commonly observed in either oxygen-rich or carbon-rich AGB stars. Two stars also show the 13 μm feature associated with crystalline alumina. Two have a water absorption band at ∼6.5–7.5 μm, and a third has a tentative detection, but only one of these three has the more common SiO absorption band at 7.5 μm. Three others show a red 6.3 μm emission feature from complex hydrocarbons consistent with “Class C” objects, and in a fourth it appears at 6.37 μm, redder than even the standard Class C hydrocarbon feature. Class C spectra typically indicate complex hydrocarbons that have been less processed by UV radiation, resulting in more aliphatic bonds relative to aromatic bonds. None of the S stars show a strong 11.3 μm hydrocarbon feature, which is also consistent with the presence of aliphatic hydrocarbons.

Intrusion Detection System Using Chaotic Walrus Optimization-based Convolutional Echo State Networks for IoT-assisted Wireless Sensor Networks

Wireless Sensor Networks (WSN) based Internet of Things (IoT) networks have achieved greater research interest due to their multi-purpose data collection and transmission over different geographical locations. However, the fabrication of different cyber-attacks in these networks has been a severe concern for applications such as remote healthcare, military communications, etc. These attacks question the integrity and security of WSN-IOT networks for such applications, and the traditional Intrusion Detection Systems (IDS) have shown increased false alarm rates because of their substantial processing overhead, resource constraints, and low detection rates. This paper presents an intelligent IDS model using Chaotic Walrus Optimization-based Convolutional Echo State Networks (CWO-CESN) to solve existing problems. It increases the detection accuracy of different attacks. In this CWO-CESN-based IDS model, the data are gathered from the sensor/IoT nodes and are pre-processed. Then, the proposed CWO-CESN learns the features from these data and classifies them into attacks and standard data classes. This proposed CWO-CESN is a hybrid classifier model that integrates Convolutional Neural Networks (CNN) and Echo State Networks (ESN) as a single model and employs Chaotic map-based population initialized Walrus Optimizer for optimizing the hyperparameters. Validated on benchmark datasets, the proposed CWO-CESN-based IDS model attained accuracies of 99%, 99.5%, and 99.8% for the detection of different attacks for NSL-KDD, WSN-DS and IoT-23 datasets, respectively, and ensured secured and reliable application in significant fields.

Cluster Randomized Controlled Trial of a Standard Versus Postures-Only Yoga Session: Potential Self-Regulatory and Neurophysiological Mechanisms of an Ancient Practice.

It is well-recognized that maintaining a regular yogic practice is associated with numerous physical and psychological health benefits. However, few studies have explored the possible psychological and neurophysiological mediators through which the component parts of yoga-ethics, breath regulation, postures, and meditation-work to produce salutary effects. To address this gap, we conducted a cluster randomized trial to test the following set of theory-based mechanisms: emotion regulation for ethics, self-control for breath regulation, discomfort and distress tolerance for postures, and mindfulness for meditation. We also explored yoga's effects on the autonomic nervous system by examining salivary acetylcholinesterase levels. Participants (N = 260) were randomly assigned in clusters (n = 37) to a single, hour-long standard or postures-only yoga class. Findings suggest that a single yoga class may confer both psychological and neurophysiological benefits, yet there were few differences between the two types of yoga classes. Pre- to post-session main effects of time, all in the expected direction, emerged for five of eight theoretical mediators, as well as for salivary acetylcholinesterase levels. Time X condition interactions observed for three of the mediators-cognitive reappraisal, discomfort tolerance, and expressive suppression-along with findings from the exploratory mediation analysis suggest potential unique benefits of the two yoga sessions for certain outcomes. Additional studies are needed to replicate these results and to test other potential mediators and/or primary outcomes through which yoga might work to promote health.

A novel approach for the numerical solution of nonlinear Fredholm integral equations using Hosoya polynomial method

Abstract In this paper, we study the graph theoretical polynomial known as the Hosoya polynomial obtained from one of the standard classes of graphs called path. Using this polynomial applied for the numerical solution of the nonlinear Fredholm integral equation, which reduces in the algebraic system of equation with collocation points, then solving this system using Newton’s iterative with the help of MATLAB, we obtain the required approximate solution. The desired results in terms of a set of continuous polynomials over a closed interval [0, 1]. Illustrative applications show the efficiency, accuracy and validity of the proposed technique.

Comparative evaluation of plasma biomarkers of Schistosoma haematobium infection in endemic populations from Burkina Faso.

Infection with Schistosoma haematobium causes urogenital disease associated with organ disfunction, bleeding, pain, and higher susceptibility to infections and cancer. Timely and accurate diagnosis is crucial for prompt and appropriate treatment as well as surveillance efforts, and the use of plasma biomarkers offers important advantages over parasitological examination of urine, including increased sensitivity and the possibility to use the same specimen for multiple investigations. The present study aims to evaluate the diagnostic performance of different plasma biomarkers in endemic populations from Burkina Faso, West Africa. Schistosoma spp. Circulating Anodic Antigen (CAA), cell free S. haematobium DNA (cfDNA), class M and G antibodies against S. haematobium Soluble Worm Antigen Preparation (SWAP) and Soluble Egg Antigen (SEA) were measured in 406 plasma samples. Results of each biomarker test were compared to those of CAA, a Composite Reference Standard (CRS) and Latent Class Analysis (LCA). An identical proportion of positive samples (29%) was observed as a result of CAA and cfDNA testing, with a substantial agreement (84%, Cohen k = 0.62) between the results of the two tests, and a comparable agreement with the results of CRS and LCA. A higher positivity was observed, as expected, as a result of specific antibody testing (47%-72%), with IgG showing a higher agreement than IgM with the three references. Also, higher IgG levels were observed in current vs past infection, and ROC analysis identified optimal cutoff values for improved testing accuracy. This study provides compelling evidence that can inform the choice of the most appropriate diagnostic plasma biomarker for urogenital schistosomiasis in endemic areas, depending on the purpose, context, and available resources for testing. Either CAA or cfDNA testing can be used for the diagnosis of patients and for epidemiological investigations, even in absence of urine filtration microscopy, whereas anti-SWAP or anti-SEA IgG can be employed for surveillance and integrated monitoring of control interventions against poverty-associated diseases.

Standardizing Chemotherapy Education to Improve Patient Satisfaction at an Ambulatory Oncology Center.

This quality improvement project implemented a standardized chemotherapy class for newly diagnosed patients receiving oncology care at an urban ambulatory oncology center. Results showed high scores on patient satisfaction qu.

Matters of assuring functional dependability compliance of digital manufacturing

Aim. To propose a methodological approach to ensuring the functional dependability of industrial facilities using SMART documents in the context of import-independent digital processes. Methods. The evolving applicability of the dependability theory and information systems design has defined the methodological provisions for algorithmising the application of SMART standards for minimising functional faults and failures of industrial processes. Digital models of production lines were examined as tools for machine-recognisable representation of standards. The proposed form of regulatory documents is intended to enable the transition from machine-readable data to machine-understandable content. Findings. The application of the proposed methods of content systematisation in the context of manufacturing process standardisation shows that the classification of process data based on standardised characteristics of digital information exchange processes is one of the key methodological provisions ensuring unambiguous interpretation of regulatory requirements. Specialised projects often use individual provisions rather than complete regulatory documents. In this case, in order to ensure machine-understandability of the developed content, it is proposed using special identifiers, e.g., «paragraph», «graphic object», «table cell». The deployment of such identification tools will allow creating a class of SMART standards that collect into a single document the provisions regarding the delivery of intended results in situations when the operating equipment is diverse. Publications created using intelligent processing of SMART documents are considered as containers of structured and unstructured data that take into account the conditions of particular projects. The existing dynamics of the demand for advanced industrial products often determines the admissibility of its industrial production by various companies with the parallel use of unique technologies. The conditions of such an organisation impose their limitations on the comparability of various process requirements, therefore, it is proposed to harmonise the presentation of the results of managerial, design, and process engineering solutions using the term «manufacturing system asset». The introduction of relative result estimates as part of the digital format is an efficient mechanism for ensuring management consistency. In this context, the importance of a uniform regulatory framework as the foundation for such assessments is growing. As one of the ways of minimising faults and failures of industrial equipment, it is proposed to create a situation centre with a decision support system based on the regulatory data with harmonised manufacturing system asset requirements. An experience of Industry 4.0 regulation is described in the review of the ISA digital manufacturing series of standards. It was shown that the deployment of SMART standards improves the stability of interaction between information management systems and the functional dependability of production lines. The introduction of provisions regulating the use of algorithms for the development, editing, and examination of draft regulatory documents into the content machine-understandability facilities is an important factor in ensuring the functional dependability of products. Conclusions. The presented approach is focused on the methodology for developing standards that take into account requirements from various subject areas. In the context of ongoing import substitution in manufacturing, the paper examines the feasibility of minimizing digital process faults and failures caused by the use of regulatory frameworks that are not equivalent to the provisions of international documents and take into account the specificity of Russian industrial systems.

Effects of prenatal yoga exercise on hepcidin and ferritin levels in pregnant women

Prenatal yoga is a modification of hatha yoga tailored for pregnant women. This exercise is recommended throughout pregnancy. This study aimed to determine the effect of prenatal yoga exercise on the serum levels of hepcidin and ferritin in pregnant women. The study employed a quasi-experimental design with a pre- and post-test. A total of 134 second-trimester pregnant women participated and were divided into two groups (intervention group = 62, control group = 72). The intervention group received prenatal yoga exercises for 8 weeks (twice a week), while the control group attended only the standard pregnancy class. Each group was further divided into subgroups: anemic pregnant women, normal pregnant women, and overweight pregnant women. Demographic data were obtained through a basic questionnaire, while pre-pregnancy BMI data, obstetric history, and pregnancy examinations were sourced from the KIA book. Serum hepcidin levels significantly decreased in pregnant women who participated in prenatal yoga exercises (p=0.002), with the highest significance observed in overweight pregnant women (p=0.001). The average serum ferritin levels increased in all groups but were not statistically significant (p=0.759). Regular prenatal yoga exercises can reduce serum hepcidin levels in pregnant women, with a significant reduction noted in overweight pregnant women. Ferritin levels might be influenced by iron supplementation.

The impact of virtual reality haptic simulators in pre-clinical restorative dentistry: a qualitative enquiry into dental students’ perceptions

PurposeIn the realm of restorative dentistry, the integration of virtual reality haptic simulation (VRHS) for learning operative skills has garnered varied perceptions among dental students. Therefore, the aim of this study was to delve deep into undergraduates dental students’ perceptions related to the impact of VRHS in pre-clinical restorative dentistry.MethodsA homogeneous purposive sampling method was utilized to gather data from third-year undergraduate dental students (n = 23) at the College of Dental Medicine, Qatar University, to thoroughly investigate their views on the impact of VRHS on their learning experience in preparing a standard class I cavity. An explorative qualitative method using face-to-face focus group sessions were conducted in English during 2023. Focus group sessions were recorded and transcribed using Microsoft Teams. Two authors independently read the transcripts, coded the text, and manually analyzed text using an inductive thematic approach.ResultsA total of 21 (91.3%) students participated in this study. Analysis of 3 focus group interviews revealed five primary themes summarized with the term “MASTR” (M = manual dexterity, A = assessment, S = sequence, T = training, and R = realism). Based on frequency of reported themes, students perceived realism/ lifelike nature of VRHS requiring further enhancement to achieve the desired learning objective.ConclusionAlthough, VRHS play a crucial role in modern dental education, offering innovative solutions for training, evaluation, and feedback, the need to enhance their ability to simulate real-life dental procedures and learning environment (realism), coupled with interactive and immersive learning experiences were the most frequently raised theme by students. In terms of curriculum design and learning pedagogies, dental educators should consider the appropriate sequence when integrating VRHS within the undergraduate curricula.

A learning-based model predictive control scheme for injection speed tracking in injection molding process

Injection molding is a pivotal industrial process renowned for its high production speed, efficiency, and automation. Controlling the motion speed of injection molding machines is a crucial factor that influences production processes, directly affecting product quality and efficiency. This paper aims to tackle the challenge of achieving optimal tracking control of injection speed in a standard class of injection molding machines (IMMs) characterized by nonlinear dynamics. To achieve this goal, we propose a learning-based model predictive control (LMPC) scheme that incorporates Gaussian process regression (GPR) to predict and model uncertainty in the injection molding process (IMP). Specifically, the scheme formulates a nonlinear tracking control problem for injection speed, utilizing a GPR-based learning residual model to capture uncertainty and provide accurate predictions. It learns the dynamics model and historical data of the IMM, automatically adjusting the injection speed according to target requirements for optimal production control. Additionally, the optimization problem is efficiently solved using a control-constrained differential dynamic programming approach. Finally, we conduct comprehensive numerical experiments to demonstrate the effectiveness and efficiency of the proposed LMPC scheme for controlling injection speed in IMP.