General Type Research Articles

ФОРМОУТВОРЕННЯ НАМОТУВАННЯМ КОМПОЗИТНОГО ПЕРЕДНЬОГО ГОРИЗОНТАЛЬНОГО ОПЕРЕННЯ ЛЕГКОГО ЛІТАКА

A process has been developed for modeling the trajectory of laying reinforcing material (RM) during the formation of composite aerodynamic surfaces (AS). The work provides a brief description of the types of structures of aircraft of complex shape according to the criterion of the possibility of manufacturing by the winding method, in which certain types of surface shapes are highlighted according to the condition of determining the laying trajectory and developing a winding control program (WCP) for CNC machines. It is shown that the process of developing technology for manufacturing structures such as aerodynamic load-bearing surfaces has significant differences from the process of developing technology for axisymmetric products. The general technique for determining the trajectory of laying reinforcing material is shown and new approaches to specifying the reinforcement pattern are described. The general methodology for calculating the WCP for winding the AS is described. Calculation of the movements of the working parts of a winding machine (WM) includes several subtasks: choosing the order of passage of individual turns of the RM, calculating the movements of the working parts of the WM when laying each turn, and determining the program for transition from turn to turn. It is shown that the most important stage in the development of general-type AS winding technology is the choice of a winding scheme that determines the structural-force diagram (SFD) of the structure. For this purpose, the concept of the limiting point of winding has been introduced. The winding pattern of any type of product can be described by an array of coordinates of boundary points and reinforcement angles. An algorithm for calculating the trajectory of RM placement on the surface of the mandrel is presented. The features of choosing the order of passage of turns are described. The order in which the turns pass affects the number of weaves in the structure of the composite material obtained during the winding process and the strength of the product. The optimal order of passing turns according to the strength criterion is determined experimentally through repeated development tests. The features of choosing programs for transition from turn to turn are described. The algorithm of actions of the WM during the transition from one turn to another - the transition program consists of two programs: the program for entering the turn and the program for exiting the turn. The algorithm of transition programs depends on the chosen order of turns and in each specific case depends on the design features of the product. To test the developed methodology, a test calculation of the front horizontal tail of a light aircraft was carried out. As a result of the work done, it was possible to solve the problem of modeling the RM laying trajectory for bodies of complex shape with a fixed type of section, manufactured by the winding method from a polymer composite material (PCM). This technology can be used to produce aircraft structures such as “wing”, “fuselage” of an airplane, helicopter, and the like. Thus, the possibility of winding a general type AS has been proven using the example of the horizontal front tail of a light aircraft. The range of production of wound products has expanded - bodies with an arbitrary convex section and a straight generatrix. A technology has been developed for manufacturing from PCM by winding non-axisymmetric aerodynamic power structural elements such as aircraft wings, helicopter blades, air and water propellers. A surface reinforcement scheme has been found that makes it possible to obtain a variable wall thickness with its decrease from the root to the end rib. The trajectories of laying reinforcing material on a surface with an arbitrary convex section and the movement of working parts for a three-axis winding machine are determined. The developed calculation method can be used to create various aerodynamic structural elements with positive surface curvature from PCM by winding. The use of advanced high-performance technology for automated winding of reinforcing fiber material provides a significant reduction in labor costs in the manufacture of these units, reducing their prices compared to the prices of existing metal and composite aircraft of comparable size and equipment

Construction of General Types of Fuzzy Implications Produced by Comparing Different t-Conorms: An Application Case Using Meteorological Data

The objective of this paper is to compare a fuzzy implication produced by t-conorm probor with three other fuzzy implications constructed by t-conorms max, Einstein, and Lukasiewicz. Firstly, in methodology, six pairs of combinations of five t-conorm comparisons are performed in order to find the ranking order of five fuzzy implications. Moreover, the evaluation and calculation of the four fuzzy implications (probor, max, Einstein, and Lukasiewicz) are made using meteorological data, fuzzifying the crisp values of temperature and humidity, constructing four membership degree functions, and inserting as inputs the membership degrees of meteorological variables into the two variables of the fuzzy implications. Finally, extensive tests are made so as to find which membership degree function and which fuzzy implication receives the best and the worst results. The key findings are that the application of isosceles trapezium to the fuzzy implications of Probor and Einstein gives the best values, while fuzzy implication Lukasiewicz, although it was found to be first in the ranking order, is rejected due to unreliable results. As a result, the crucial role of these implications lies in the fact that they are non-symmetrical, i.e., there is a clear difference between the cause and the causal.

Protocol for a feasibility and acceptability study for UK general population paediatric type 1 diabetes screening-the EarLy Surveillance for Autoimmune diabetes (ELSA) study.

The EarLy Surveillance for Autoimmune (ELSA) study aims to explore the feasibility and acceptability of UK paediatric general population screening for type 1 diabetes. We aim to screen 20,000 children aged 3-13 years for islet-specific autoantibodies through dried blood spot sample collection at home, hospital or community settings. Children with two or more autoantibodies are offered metabolic staging via oral glucose challenge testing. Feasibility assessments will compare recruitment modalities and uptake according to demographic factors (age, gender, ethnicity, level of deprivation and family history of diabetes) to determine optimal approaches for general population screening. The study is powered to identify 60 children (0.3%) with type 1 diabetes (stage 1-3). Parents are invited to qualitative interviews following ELSA completion (child screened negative or positive, single autoantibody or multiple, stage 1-3) to share their screening experience, strengths of the programme and any areas for improvement (acceptability assessments). Parents who decline screening or withdraw from participation are invited to interview to explore any concerns. Finally, we will interview professional stakeholders delivering the ELSA study to explore barriers and facilitators to implementation. Early detection of type 1 diabetes allows insulin treatment to be started sooner, avoids diagnosis as an emergency, gives families time to prepare and the opportunity to benefit from future prevention trials and treatments. ELSA will provide essential feasibility and acceptability assessments for UK general population screening to inform a future national screening programme for paediatric type 1 diabetes.

Methodological Advances with Penalized Structural Equation Models

Penalized structural equation models (PSEM) is a powerful technique that unlocks a variety of new modeling frameworks. PSEM applications have been established previously for standard SEM and ESEM models. In this note we aim to extend these ideas to more general types of models such as finite mixture models, multilevel models as well as models with more general types of outcomes. Maximum likelihood and weighted least squares estimation methods naturally accommodate a penalty term. In Mplus 8.12 the PSEM methodology is implemented for all models that can be estimated with these two estimators. Therefore we can now easily combine the more general models with the features of PSEM such as EFA, Alignment, and parameter invariance. Some additional basic SEM applications are also included.

An annual land cover dataset for the Baltic Sea Region with crop types and peat bogs at 30 m from 2000 to 2022

We present detailed annual land cover maps for the Baltic Sea region, spanning more than two decades (2000–2022). The maps provide information on eighteen land cover (LC) classes, including eight general LC types, eight major crop types and grassland, and two peat bog-related classes. Our maps represent the first homogenized annual dataset for the region and address gaps in current land use and land cover products, such as a lack of detail on crop sequences and peat bog exploitation. To create the maps, we used annual multi-temporal remote sensing data combined with a data encoding structure and deep learning classification. We obtained the training data from publicly available open datasets. The maps were validated using independent field survey data from the Land Use/Cover Area Frame Survey (LUCAS) and expert annotations from high-resolution imagery. The quantitative and qualitative results of the maps provide a reliable data source for monitoring agricultural transformations, peat bog exploitation, and restoration activities in the Baltic Sea region and its surrounding countries.

Optimal error estimate of fully discrete HDG-IEQ scheme for the general type Cahn-Hilliard equation

Optimal error estimate of fully discrete HDG-IEQ scheme for the general type Cahn-Hilliard equation

Insights into cancer characteristics among SARS-CoV-2 infected hospitalized patients: a comprehensive analysis from the National Clinical Registry for COVID-19.

Cancer outcome is dependent on multiple predetermining factors including cancer, type of cancer and its related factors. This study aims to investigate the association between COVID-19 & cancer/cancer types, focusing on risk of in-hospital mortality within 30days of hospitalization of COVID-19 patients with cancer. We did a registry (National Clinical Registry for COVID-19) based retrospective observational study including 51,544 patients, of whom 976 were patients with cancer, admitted with COVID-19 between August 2020 and August 2023 across 42 hospitals of India. Out of 51,544 patients, 976 (1.8%) had cancer. Hematological malignancies made up 15.06% (147 cases), while solid cancers accounted for 29.5% (288 cases), with genitourinary (18.4%, 80 cases), gastrointestinal (15.2%, 49 cases), and lung cancers (10.1%, 34 cases) being the most common. Solid cancers had the highest in-hospital mortality rate at 25%. Survival analysis showed that cancer-related hazards were highest at admission but decreased to levels comparable with other morbidities within nine to ten days. For each cancer type, the hazard was significantly elevated compared to that of the cancer-free (Other Comorbidities and No Comorbiditiy) groups during the initial period of hospitalization. The use of Remdesivir, steroids, and anticoagulants reduced mortality risk, and prior COVID-19 vaccination was protective against mortality across all cancer types. This study shows that both cancer in general and specific cancer types significantly increase the risk of severe outcomes among SARS-CoV-2-infected patients, especially immediately after hospitalization. The findings highlight the need for close monitoring and personalized interventions for COVID-19 patients with cancer for at least 10days post-hospitalization, with a more specific high-risk period ranging from 7 to 18days depending on the type of cancer.

A stability result for viscoelastic piezoelectric system with nonlinear feedback

In this work, we consider a nonlinear viscoelastic piezoelectric beam in the presence of an infinite memory and a nonlinear frictional damping of general type. We investigate the interaction between the two dampings and establish, under general assumptions on the relaxation function and the nonlinear feedback, an explicit formula for the energy decay rates of this system.

Generalized Tensorial Simpson type Inequalities for Convex functions of Selfadjoint Operators in Hilbert Space

Several generalized Simpson tensorial type inequalities for self adjoint operators have been obtained with variation depending on the conditions imposed on the function f.

Identification of a class of singular Boolean control networks

System identification, recognized as an inverse control problem, is a significant aspect of modern control theory. This study focuses on addressing the identification problem related to a specific category of singular Boolean networks (SBNs) and singular Boolean control networks (SBCNs). The introduction of two novel concepts, namely the admissibility and solvability matrices, enables the establishment of conditions for determining the existence and uniqueness of solutions for SBNs and SBCNs. Then criteria are deduced to identify the number of dynamic equations. Based on observability, controllability and detectability, several conditions are presented to characterize identification. Among them, two crucial results show: When the solution to an SBN or SBCN is unique, the SBN is identifiable if and only if it is observable, and the SBCN is identifiable if and only if it is O1-observable, which is the most general type of observability. Besides, effective algorithms are devised to implement identification. Furthermore, the study delves into the normalization issue using the admissibility matrix, which provides a possibility to reduce the identified SBN or SBCN to a lower-order BN or BCN.

Geschichten vom Ingenieur

Abstract Based on various representative examples, this article shows which images of the “Ingenieur” (engineer) appear in narratives written in German, focusing on the years 1900 to 1930. While a general type of engineers appears as a representative of progress and a hallmark of the time, incorporating this conception as the norm, three further models can be identified, which are embedded within conflicting constellations of normality/deviation, daily routine/emotional emphasis, and the collective/individual: the engineer as a figure who mediates the crossing of borders, the engineer as a condensation of a life felt to be deficient, the engineer as the savior of the world.

Determining Elementary Teachers’ Competencies Using Practical Content Development Technologies

In education, as in all areas of our lives, the rapid development of computers and the Internet has brought about radical changes. The variety and use of technology in the educational environment is becoming increasingly widespread. A qualified teacher should have a personality that is in a state of constant renewal and development, which is directly proportional to the development of science and technology. Therefore, it is valuable for elementary teachers to become digitally literate and to know how to use this technology in teaching. The aim of this study was to investigate the competence of elementary teachers in the use of practical technologies for content development. This study is descriptive in the general survey type. The "Personal Information Form" and the "Competence Scale for Using Practical Content Development Technologies" were used to collect the research data. According to the results of the research, elementary teachers’ competence in the use of practical content development technologies was very low. It was found that the competences of the teachers with a good level of Internet use were higher than those of the teachers with a poor level of Internet use.

Landslide Studies in the Context of Disaster Management in Bangladesh—A Systematic Literature Review

Landslides and their resulting impacts on property and human life have become an ongoing challenge in the hilly regions of Bangladesh. This study aims to systematically review diverse landslide studies in Bangladesh, particularly focusing on landslide disaster management (LDM) from 2008 to 2023, encompassing the pre-disaster, syn-disaster, and post-disaster phases. Several key attributes of landslide studies were considered, including general trends, data types, study scales, contributing factors, methodologies, results, and validation approaches, to investigate challenges and subsequently identify research gaps. This study evaluated 51 research articles on LDM using a systematic literature review (SLR) technique that adhered to the Preferred Reporting Item for Systematic Reviews and Meta-Analyses (PRISMA) framework. Our finding revealed that articles on LDM were dominated by the pre-disaster (76%) and the syn-disaster phases (12%), with the post-disaster phase (12%) receiving equal attention. The SLR revealed a growing number of studies since 2020 that used data-driven methods and secondary spatial data, often focused on medium-scale analyses (district level) that, however, often lacked field-based validation. From the factors examined in various landslide studies, topographical and hydrological factors were found to be the most significant attributes in assessment. This study identified key challenges, such as insufficient landslide inventories including poor site accessibility and a lack of high-resolution geological, soil, and rainfall data. It also highlighted critical research gaps, including the need for advanced technologies in susceptibility mapping for national hazard atlas, the investigation of underexplored causative factors, effective early warning systems, detailed post-event characterization, health impact assessment, risk-sensitive land use planning, and interactive web portals for landslide prone areas. This study would thus aid researchers in understanding the depth of existing knowledge and provide insights into how landslides fit into broader disaster management frameworks, facilitating interdisciplinary approaches.

Definition and understanding of "efficiency" in healthcare provision research: a scoping review.

With rising healthcare costs over the last decades, the concept of efficiency has gained popularity in healthcare provision research. As efficiency can be understood and measured in many different ways, it is often unclear what is meant by "efficient health systems" or "efficient healthcare providers". This study aims to analyze and categorize the different definitions and understandings of "efficiency" used in healthcare provision research over time. We searched five databases (Medline, Embase, CINAHL, Business Source Premier, and EconLit) to conduct a scoping review. Sources were screened independently by two researchers, using the online software Rayyan. Results are reported using PRISMA-ScR. Of 1,441 individual sources identified, 389 were included in the review. Most papers (77.3%) using the term "efficiency" do not include explicit definitions or explanations of their understanding of it. Almost all papers (99.0%) are interested in productive efficiency (vs. allocative efficiency) and more specifically technical efficiency, therefore comparing the number of inputs used and outputs produced. While many papers (70.4%) include some elements of quality of care or health outcomes in their discussion, few (30.3%) include aspects of quality in their measurement of efficiency. Over the last decades, Data Envelopment Analysis has become the main method to measure efficiency. We propose a broad categorization of efficiency definitions that could be used by researchers to improve the comprehensibility and comparability of their research. Key features are the general type of efficiency, inclusion of quality or outcome information, and inclusion of cost information. To allow for better comparability and comprehensibility, researchers in healthcare provision should state explicitly which type of efficiency they are studying. To do this, we propose to use combinations of the terms productive efficiency, allocative efficiency, quality-inclusive efficiency, and cost efficiency.

Machine learning-based classification for Single Photon Space Debris Light Curves

The growing number of man-made debris in Earth’s orbit poses a threat to active satellite missions due to the risk of collision. Characterizing unknown debris is, therefore, of high interest. Light Curves (LCs) are temporal variations of object brightness and have been shown to contain information such as shape, attitude, and rotational state. Since 2015, the Satellite Laser Ranging (SLR) group of Space Research Institute (IWF) Graz has been building a space debris LC catalogue. The LCs are captured on a Single Photon basis, which sets them apart from CCD-based measurements. In recent years, Machine Learning (ML) models have emerged as a viable technique for analysing LCs. This work aims to classify Single Photon Space Debris LCs using the ML framework. We have explored LC classification using k-Nearest Neighbour (k-NN), Random Forest (RDF), XGBoost (XGB), and Convolutional Neural Network (CNN) classifiers in order to assess the difference in performance between traditional and deep models. Instead of performing classification on the direct LC data, we extracted features from the data first using an automated pipeline. We apply our models on three tasks, which are classifying individual objects, objects grouped into families according to origin, and grouping into general types. We successfully classified Space Debris LCs captured on Single Photon basis, obtaining accuracies as high as 90.7%. Further, our experiments show that the classifiers provide better classification accuracy with automated extracted features than other methods.

A rapid method for composition tracking in hydrogen-blended pipeline using Fourier neural operator

Blending hydrogen into natural gas for transportation is a crucial approach for achieving the widespread utilization of hydrogen. Tracking the concentration of the hydrogen within the pipeline is important for monitoring gas quality and managing pipeline operations. This study develops a rapid computational model to predict the hydrogen and natural gas concentrations within the pipeline during transportation based on the Fourier Neural Operator (FNO), an operator neural network capable of learning the differential operator in the partial differential equation. In the proposed model, the numerical method is employed to generate datasets, with the spline interpolation used to enhance data smoothness. The initial and boundary conditions are taken as the inputs to accommodate varying transportation scenarios. Comparison results indicate that the proposed model can notably reduce the time needed to predict the hydrogen and natural gas concentrations while maintaining prediction accuracy. The accuracy of the proposed model is validated by comparing its calculated results with the analytical solution and the concentrations of hydrogen and natural gas within the pipeline under two transportation scenarios, with relative errors of 0.49%, 0.31%, and 0.45%, respectively. Notably, the trained model demonstrates strong grid invariance, a type of model generalization. Trained on data generated from a coarse grid of 101 × 41 spatial-temporal resolution, the proposed model can accurately predict results on a fine grid of 401 × 81 spatial-temporal resolution with a relative error of only 0.38%. Regarding the prediction efficiency, the proposed model achieves an average 17.7-fold speedup compared to the numerical method. The positive results indicate that the proposed model can serve as a rapid and accurate solver for the composition transport equation.

Survey of bloodstain pattern analysts regarding pattern classifications on assorted fabrics

Because bloodstain pattern analysis (BPA) on absorbent surfaces, such as fabrics, is far more complex than its application on hard, nonporous surfaces, pattern type may be interpreted differently between fabric substrates and by analysts with more or less experience. Four bloodstain pattern types (impact spatter, transfer, drip stains, and cast-off) were created on seven fabrics (cotton, satin polyester, rayon, blended polyester/spandex, blended nylon/spandex, blended modal/polyester/spandex, and terry cloth), foamboard, or butcher paper and then photographed. A survey questionnaire that asked respondents to classify 16 patterns as to general pattern type, specific pattern type, and directionality was developed and disseminated among bloodstain pattern analysts. Respondents (n = 32, divided into five experience levels) classified the bloodstains differently based upon amounts of training and experience, the pattern type, and the substrate type. The ability to accurately classify the specific pattern type overall (p-value < 0.0002) as wells as on fabric (p-value < 0.001) was dependent upon respondent experience level. The more experienced respondents were less likely to specifically classify patterns than the less experienced respondents (p-value < 0.001). Furthermore, the ability to accurately classify the specific pattern type was dependent upon whether the pattern had been created on fabric or some other substrate (p-value < 0.0000000001). However, if the proper morphology was present in the stain, it was found that BPA on certain fabrics was possible. This finding supports the need for further research and the development of guidelines and standards for bloodstain pattern analysis on fabric materials.

Survey of Chemical Unfolding Complexity as a Unique Stability Assessment Assay for Monoclonal Antibodies

Seventy-two intentionally sequence-diverse antibody variable regions were selected, expressed as IgG1 antibodies, and evaluated by chemical unfolding to survey the complexities of denaturant induced unfolding behavior. A two-transition fit well described the curves and uncovered a wide range of sensitivities to denaturant. Four general types of unfolding curves were observed: balanced traces (each transition responsible for half of the total unfolding transition), low-unfolding traces (first transition is a majority of the unfolding curve), high-unfolding traces (the second transition is the majority of the unfolding curve), and coincident traces (the two transitions are found close to each other, approximating a single transition).The complexity of the data from this survey indicates that focusing on the first inflection point or fitting a single transition model is likely an over-simplistic method for measuring stability by the chemical unfolding assay. Additionally, other conformational assays, such as thermal and low pH unfolding, showed no correlation with the chemical unfolding results, indicating that each of these assays provide alternate information on the different pathways of antibody conformational stability. These results provide a basis for beginning to better connect unfolding behavior to other physical phenotypic behaviors and production process behaviors.

Risk factors affecting all-cause mortality in cats hospitalized by a referral soft tissue service.

The objective of this study was to describe the all-cause mortality rate in cats hospitalized by the soft tissue surgery service of an academic referral hospital over a 5-year period and to identify specific risk factors for mortality. The hypotheses were that the all-cause mortality rate during hospitalization would be low, and cats undergoing emergency surgery and those with an American Society of Anesthesiologists (ASA) status of 3 or more would be at increased risk for mortality. The case log of cats hospitalized by the soft tissue surgery service at the University of Georgia was searched retrospectively to identify all cats hospitalized in the years 2015-2020. Data collected about each cat included age, sex and neuter status, weight, body condition score (1-9), pre-existing heart disease, chronic kidney disease, concurrent infection or cancer, emergency status, time of surgery (daytime vs after hours, which was defined as after 4 pm), if the surgery was performed on a weekday or weekend, and general type of surgery. Univariable logistic regressions were implemented to test and estimate odds ratios for the effects of risk factors on in-hospital mortality. A multivariable logistic regression was developed that initially included all risk factors with P <0.05 on univariable analysis. Log-likelihood ratio test P values and profile-likelihood confidence intervals were reported. The all-cause mortality rate was 6.1%. Analysis was limited because of low mortality, but multivariable analysis identified increasing ASA status and emergency surgery as significant risk factors for increased mortality while hospitalized. The findings of this study confirmed that increasing ASA status and emergency procedures are significant risk factors for mortality in cats. Clinicians should be aware of these risk factors and consider how to best monitor and manage these feline patients.

Epicardial adipose tissue volumes for long-term risk stratification in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement

Abstract Background Accurate risk stratification is important to improve patient selection and outcome of patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). As epicardial adipose tissue (EAT) is discussed to be involved in cardiovascular disease, it could be useful as a marker of poor prognosis in patients with severe AS undergoing TAVR. Purpose We hypothesized that EAT impacts long-term outcome of patients with severe AS undergoing TAVR independently from subtype and other risk factors. Methods A total of 416 patients diagnosed with severe AS by transthoracic echocardiography were assigned for TAVR and enrolled for systematic assessment. Patients underwent clinical surveys and 5-year long-term follow-up, with all-cause mortality as the primary endpoint. EAT volume was quantified on pre-TAVR planning CTs. Patients were retrospectively dichotomized at the median of 74cm3 of EAT into groups with low-EAT and high-EAT volumes. Mortality rates were compared using Kaplan-Meyer plots and uni- and multivariable cox regression analyses. Results A total number of 341 of 416 patients (median age 80.9years, 45% female) was included in the final analysis. Patients with high-EAT volumes had similar short-term outcome (p=0.794) but significantly worse long-term prognosis (p=0.023) compared to patients with low-EAT volumes. Increased EAT volumes were associated with worse long-term outcome (HR1.59;p=0.031) independently from concomitant cardiovascular risk factors, general type of AS and functional echocardiography parameters of AS severity (HR1.69;p=0.013). Conclusion Increased EAT volume is an independent predictor of all-cause mortality in patients with severe AS undergoing TAVR. It can be easily obtained from pre-TAVR planning CTs and may thus qualify as a novel marker to improve prognostication and management of patient with severe AS.Graphical Abstract