Present Methods Research Articles

The measurement of "high-impact chronic pain": Limitations and alternative methods.

Chronic pain is known to be an important construct in clinical practice and a particular form of chronic pain, high-impact chronic pain (HICP), has gained recent interest and attention by pain clinicians, epidemiologists, and clinical researchers. The purpose of our Topical Review is to describe the historical development of measures of HICP and to explore the psychometric properties of HICP as well as to present alternative measurement methods. We identified strengths and weaknesses of the psychometric characteristics of HICP measures. Limitations of existing HICP measures were discussed and summarized and alternatives to current methods were proposed. HICP operational definitions show variability across studies. All definitions cannot be correct, but which ones are incorrect cannot be determined as there is no gold standard. Random measurement error and recall bias are among the other limitations of current HICP measures. Model-based definitions of HICP, the discrete (for epidemiologic applications) and continuous (for clinical applications) latent variable models are discussed as likely superior alternatives to current methods. Limitations of existing HICP methods are discussed and alternative development approaches to HICP measures are presented. The use of either discrete or continuous latent variable models would improve upon the psychometric characteristics of current HICP evidence. Examples are used to illustrate the benefits of latent variable models over traditional observed variable conceptualizations as the measurement of HICP continues to develop. This work takes the position that current methods of measuring high impact chronic pain (HICP) likely contain substantial error. We have endorsed an alternative approach for several psychometrically grounded reasons. We recommend that future work consider the discrete latent variable framework for dichotomous measures of HICP and the continuous latent variable framework for continuous measures of HICP. The paper provides illustrative examples of these methods for a different patient reported measure that is lacking a gold standard, much like HICP measures.

Carbon Sequestration in Agricultural Soil: Technique and their Efficiency

Developing technologies to slow the rate of increase in the atmospheric concentration of carbon dioxide (CO2) from annual emissions, such as energy, process industries, land-use change, and soil cultivation, is a major challenge of the twenty-first century. Severe ecological and economic disruptions result from the erratic changes in climate systems caused by the skyrocketing amounts of atmospheric CO2 and other greenhouse gases (GHGs). Through the process of carbon sequestration, net greenhouse gas emissions can be reduced, hence mitigating climate change. Both biotic and abiotic variables can contribute to the long-term sequestration of carbon, or carbon stabilisation. The compilation of past and present methods for sequestering soil organic carbon is crucial, considering the need of measuring and tracking soil carbon at the point, field, regional, and ecosystem levels. This study attempts to provide an overview of the literature about the function of various agricultural management techniques for sequestering carbon and the ways in which they help to stabilize atmospheric carbon.

Competitive Team-Based Learning (CTBL): A Revolutionary Approach to Contemporary Language Teaching/Education

This article dissects part of the socio-educational/political background to my innovative approach to Language Teaching/Education namely Competitive Team-Based Learning (CTBL), which he formulated based on his seminal edu-political theories. (See, 2023) It then clarifies certain misgivings regarding integrating the element of competition within cooperative learning settings to pave the way to a to-the-point introduction to CTBL. The article also discusses – at length – distinguishing features and characteristics of CTBL with reference to the present methods and approaches like Communicative Language Teaching (CLT) and particularly Cooperative Learning (CL) methods. It also throws light on the mechanisms underlying the implementation of CTBL in real classroom situations and illustrates presentations and classroom techniques in classes where this approach may be applied by teachers. Moreover, the article highlights the kind of design, objectives, evaluation system, syllabi, materials, tasks, and activities emphasized by CTBL. Importantly, the significance of motivation in CTBL settings has been thrown into sharp relief. Finally, the article gives a glimpse of the importance of CTBL for today (language) classes in our complicated competitive world context, and elaborates the howabouts of its contribution to significant changes in our societies, for peace making and compassionate civilizations building. CTBL makes it possible via bringing that sort of changes in our students’ minds first.

Achieving high stability in Cryostat: A study on optimal thermal link parameters

Thermal link is an important carrier used to transfer the cooling capacity and suppress the temperature fluctuation in cryostat. To balance these two points, it is usually necessary to find the optimum thermal link parameters. This paper establishes a model for the cryocooler cold head-thermal link-second flange based on a cryostat. Utilizing the response surface method, response equations correlating thermal link parameters with the temperature and its fluctuations of the second stage flange are developed at the lowest temperature of cryocooler. Through dual-objective optimization of cooling capacity transfer and temperature fluctuations at the second flange, the optimal thermal link parameters are determined and experimentally validated based on predicted results. The experimental and predicted values show good agreement with an error of 2 %. The optimized thermal link led a minor temperature increase and a significant temperature fluctuation reduction, decreasing from 230mK at the cold head to 2.900mK at the second flange, achieving a 98.74 % reduction. Furthermore, compared with non-optimization structure, the optimization one has further lowered the temperature fluctuation at the second flange from 4.000mK to 2.900mK with 27.5 % improvement. These results show that the present methods are reliable and useful to help to realize highly stable low-temperature environment in cryostat.

Scale effect of rock discontinuity considering all morphological information

Having an accurate understanding of the scale effect of surface morphology characteristics is crucial to examining the mechanical behavior of rock structural plane. At present, the quantification and sampling methods of surface morphology show diversity, which is the potential reason for the inconsistent research conclusions on scale effect. Firstly, based on mathematical statistics and correlation analysis, the most representative parameter is proposed from hundreds of morphological parameters. Then, the previous scale effect sampling methods are analyzed. In order to ensure that the selected samples are representative, a novel sampling method, considering all morphological information, is proposed. By means of the novel quantification and sampling methods, the size effect characteristics are systematically analyzed. Under the conditions of different rock types, shear directions and sampling locations, etc., discontinuity roughness does not change significantly with sampling scale. As sampling scale increases, the distribution range of representative samples is gradually concentrated, the total amount decreases, and the proportion increases. However, the distribution of representative samples on the initial structural plane does not show obvious regularity. These findings would provide theoretical support for the deformation control and stability analysis of rock mass in engineering.

Effect of intercalant-assisted exfoliation of Sb2Se3 on preparation of thin layers

The atomically thin sheets of Sb2Se3 hold a great potential in semiconductor applications. The present work reports intercalant-assisted exfoliation methods using various types of intercalants for the preparation of Sb2Se3 thin layers. Bulk Sb2Se3 was intercalated with H2O, PVP, Na+ and Li+ and thereby exfoliated ultrasonically. The structural analysis indicated the absence of certain planes in exfoliated samples, whereas the Raman analysis illustrated a distinct layer-dependent Raman shifts of vibrational modes. The bulk and exfoliated samples, when exposed electrochemically to H+ and K+ ions exhibited unique redox activity, which was correlated to the thickness of the exfoliated layers. The intercalating ability of intercalants was compared to the degree of exfoliation and found to be highest for ionic intercalants.

Social Support Among Adolescents Across Immigrant Generations: A Mixed-Methods Study

The present mixed methods study explored perceived differences in social support across three immigrant generations of early adolescents residing in Canada. A total of 960 first-generation ( n = 249, M age = 13.02, σ = .69, 54.2% girls), second-generation ( n = 327, M age = 12.88, σ = .69, 57.5% girls) and third-plus-generation ( n = 384, M age = 12.81, σ = .69, 57.3% girls) early adolescent immigrants completed the self-reported Child and Adolescent Social Support Scale, and 16 of them participated in individual interviews on social support. Multivariate analyses of covariance (MANCOVA), in which we controlled for sex, mother tongue, and socioeconomic status (SES), showed that second-generation early adolescents perceived significantly less social support from their mother, teachers, school personnel, and classmates compared to their first- and/or third-plus-generation counterparts. Our mixed methods analysis revealed that these second-generation youth perceived several barriers to social support, such as an unsatisfactory quality of their relationships with these sources, a negative attitude from these sources, their limited availability or involvement, and their ineffectiveness in providing certain types of support. These findings highlight the importance of better understanding the unique challenges facing second-generation early adolescents in order to provide social support adapted to their needs.

The effect of exercise and nutritional support on elderly and senile patients with sarcopenic obesity

The aim of the review. To analyze the prevalence of sarcopenic obesity among elderly and senile people, to assess its causes, and to present modern methods for its prevention and physical rehabilitation.This review article discusses the most recent evidence on age-related changes in fat and muscle tissue, and on calorie restriction and exercise that have positive effect on physical performance in older people with sarcopenic obesity. In addition, potential gaps in clinical practice guidelines that merit attention in future research are identified and analyzed.Search strategy. We used the following key words to define participation in the review:“sarcopenic obesity”, “sarcopenia with obesity”, “sarcopenia”, “elderly/old age”. Inclusion and exclusion criteria. The review included original research results (reviews, meta-analyses). Editorials, proceeding of the conferences, and research protocols were excluded. The study sample included women and men of any race aged ≥ 60 years with a diagnosis of sarcopenic obesity and with preserved locomotion function. Articles involving hospital patients were also excluded. Non-human studies and studies that did not report precise intervention criteria (e. g., nutrition, exercise, duration, etc.) were excluded.The literature search was conducted in four electronic databases: PubMed, Cochrane Library, Springer, Scopus, for the period from 2013 to August 1, 2023. There were no restrictions on the language of the publication.

Let’s measure it: An approach of high-resolution estimates of bottom fixed net fishing effort at national level

Fisheries are one of the most important food sources for human consumption whilst being amongst the most impacting and extractive activities happening within the marine environment, which makes it imperative to properly manage this activity. To improve fisheries management, the precise quantification of fishing effort is of the outmost importance. Yet, present methods for effort estimation, especially at broad scales, are hampered by difficulties in data access and usually rely on coarse effort metrics or on costly data collection for quantifying fishing effort with higher resolution. In the present work, we propose an approach of high-resolution fishing effort estimates of net fishing, as length of nets operated by a given fleet, at the national level. It relies on sampling of effort, derived from classified and easy to access vessel tracking data – AIS, and fishery dependent data – logbook and landings data. The proposed methodology combines trip-based effort estimates, derived from AIS data, as a foundation to extrapolate the total fishing effort, through the number of fishing trips linked to official landings and logbook data. It is estimated that in the years from 2014 to 2020 an average of 180 200 km of static nets (gillnets and trammel nets), which corresponds to approximately 4.5 and 210 times the lengths of the equator and the Portuguese Atlantic coastline respectively, are used in Portuguese mainland waters each year, by a fleet of slightly more than 100 vessels. The presented methodology allows to quantify and study the variation of the nominal fishing effort, at country level, with a higher resolution than what is usually used and at very low cost. We argue that such methodologies need to be developed and explored in order to have better and more comprehensive estimates of fishing effort which will contribute and improve the sustainable management of fisheries and the marine environment.

How is digital technology used to facilitate shared decision-making between healthcare professionals and patients in cardiovascular care? A scoping review

Abstract Introduction Shared decision-making (SDM) is a patient-centred approach in healthcare that emphasizes patient involvement in the decision-making process. Digital technologies (DTs), like Mobile apps and website tools, are on the rise in cardiovascular care (CVC) and healthcare in general. But DTs can play a role in facilitating SDM, for example, with tools such as decision aids (DAs) for patients and quality check frameworks for Health care professionals (HCPs). The aim of this scoping review (ScR) was to identify the types of DTs used to facilitate SDM within the field of CVC and the analysis of how support for SDM is implemented in these technologies; to examine the conceptualizations of SDM utilized in DTs and determine the theories underlying these conceptualizations within the field of CVC; and to present designs, methods, and outcomes of published evaluation studies concerning DTs for SDM within the field of CVC. Methods For this scoping review (ScR), ten databases were searched: eight biomedical and two technical databases between January 2022 and March 2022. After deduplicating the literature, the screening was conducted by the author and was independently double-screened by one of the four contributors. The selected articles were then analysed by the author on SDM and DT. Results From the initial 5719 search results, finished on the 6th of March 2023. 48 articles were included in this ScR. The PRISMA flow diagram is presented in Figure 1. All 48 articles were included after the screening report on one of the 31 applications selected in this ScR. The characteristics of the DTs of the applications were analysed as presented in Table 1. The SDM was all about treatment options, except only one application was on screening tests. Only one application made a direct reference to an SDM model, all the others hat references to literature Defining and explaining SDM. There is an ambiguous outcome of significance in the reported evaluative studies of these applications. making it important to evaluate which characteristics of DTs are efficacious in the variability of the clinical setting. Conclusion There has been an increase in DTs to facilitate SDM in CVC over the past years. Within the scientific literature, there is recognition of a variety of DT characteristics and outcomes of the evaluative studies. It is important to reflect users' needs to choose the right application. It is valuable for developers to see which characteristics of DTs add value to applications.Table 1.Characteristics of DTs

Derivation of the nonequilibrium generalized Langevin equation from a time-dependent many-body Hamiltonian.

It has become standard practice to describe systems that remain far from equilibrium even in their steady state by Langevin equationswith colored noise which is chosen independently from the friction contribution. Since these Langevin equationsare typically not derived from first-principle Hamiltonian dynamics, it is not clear whether they correspond to physically realizable scenarios. By exact Mori projection in phase space we derive the nonequilibrium generalized Langevin equation(GLE) for an arbitrary phase-space dependent observable A from a generic many-body Hamiltonian with a time-dependent external force h(t) acting on the same observable A. This is the same Hamiltonian from which the standard fluctuation-dissipation theorem is derived, which reflects the generality of our approach. The observable A could, for example, be the position of an atom, of a molecule or of a macroscopic object, the distance between two such entities or a more complex phase-space function such as the reaction coordinate of a chemical reaction or of the folding of a protein. The Hamiltonian could, for example, describe a fluid, a solid, a viscoelastic medium, or even a turbulent inhomogeneous environment. The GLE, which is a closed-form equationof motion for the observable A, is obtained in explicit form to all orders in h(t) and without restrictions on the type of many-body Hamiltonian or the observable A. If the dynamics of the observable A corresponds to a Gaussian process, the resultant GLE has a similar form as the equilibrium Mori GLE, and in particular the friction memory kernel is given by the two-point autocorrelation function of the sum of the complementary and the external force h(t). This is a nontrivial and useful result, as many observables that characterize nonequilibrium systems display Gaussian statistics. For non-Gaussian nonequilibrium observables correction terms appear in the GLE and in the relation between the force autocorrelation and the friction memory kernel, which are explicitly given in terms of cubic correlation functions of A. Interpreting the external force h(t) as a stochastic process, we derive nonequilibrium corrections to the fluctuation-dissipation theorem and present methods to extract all GLE parameters from experimental or simulation time-series data, thus making our nonequilibrium GLE a practical tool to study and model general nonequilibrium systems.

Complexities and Innovations in Orchid Germination: A Review of Symbiotic and Asymbiotic Techniques

<i>Orchidaceae</i> is the second-largest family among flowering plants; one of the most fascinating characteristics is the morphology of the seed. One of the most important complications is that orchid seeds are tiny and lack endosperm, meaning they almost entirely depend on outside sources for nutrients while germinating or developing. The main objective of this review is to give a summary of the present methods being used in orchid germination, highlighting symbiotic and asymbiotic methods. Symbiotic germination requires interaction with mycorrhizal fungi, which provide the necessary nutrients and support for seedling growth. However, in asymbiotic approaches, controlled conditions are provided to promote germination by using nutrient-rich media. The article also highlights some of these advances that have taken place recently and ways that could be adopted to improve their effectiveness in the future. For example, the effectiveness and ability to grow orchids have improved due to recent developments in tissue culture and biotechnology. This study relies on applying the analytical approach to previous relevant studies on the subject. Nevertheless, further research is needed to refine these techniques and improve their usability in orchid conservation. To summarize, while significant progress has been achieved in understanding and enhancing orchid germination processes, further study and innovation are required. By resolving remaining issues and investigating new approaches, it may be possible to better assist orchid conservation and encourage the long-term cultivation of these wonderful plants.

Analytical solution for optimal protocols of weak drivings

One of the main objectives of science is the recognition of a general pattern in a particular phenomenon in some particular regime. In this work, this is achieved with the analytical expression for the optimal protocol that minimizes the thermodynamic work and its variance for finite-time, isothermal, and weak processes. The method that solves the Euler–Lagrange integral equation is quite general and depends only on the time-reversal symmetry of the optimal protocol, which is proven generically for the regime considered. The solution is composed of a straight line with jumps at the boundaries and impulse-like terms. Already known results are deduced, and many new examples are solved corroborating this pattern. Slowly-varying and sudden cases are deduced in their appropriate asymptotic limits. Comparison with numerical procedures is limited by the nonavailability of the present methods of the literature to produce solutions in the space of distributions.

Curriculum learning empowered reinforcement learning for graph-based portfolio management: Performance optimization and comprehensive analysis

Portfolio management (PM) is a popular financial process that concerns the occasional reallocation of a particular quantity of capital into a portfolio of assets, with the main aim of maximizing profitability conditioned to a certain level of risk. Given the inherent dynamicity of stock exchanges and development for long-term performance, reinforcement learning (RL) has become a dominating solution for solving the problem of portfolio management in an automated and efficient manner. Nevertheless, the present RL-based PM methods just take into account the variations in prices of portfolio assets and the implications of price variations, while overlooking the significant relationships among different assets in the market, which are extremely valuable for managerial decisions. To close this gap, this paper introduces a novel deep model that combines two subnetworks; one to learn a temporal representation of historical prices using a refined temporal learner, while the other learns the relationships between different stocks in the market using a relation graph learner (RGL). Then, the above learners are integrated into the curriculum RL scheme for formulating the PM as a curriculum Markov Decision Process, in which an adaptive curriculum policy is presented to enable the agent to adaptively minimize risk value and maximize cumulative return. Proof-of-concept experiments are performed on data from three public stock indices (namely S&P500, NYSE, and NASDAQ), and the results demonstrate the efficiency of the proposed framework in improving the portfolio management performance over the competing RL solutions.

Robust estimation of loss‐based measures of model performance under covariate shift

AbstractWe present methods for estimating loss‐based measures of the performance of a prediction model in a target population that differs from the source population in which the model was developed, in settings where outcome and covariate data are available from the source population but only covariate data are available on a simple random sample from the target population. Prior work adjusting for differences between the two populations has used various weighting estimators with inverse odds or density ratio weights. Here, we develop more robust estimators for the target population risk (expected loss) that can be used with data‐adaptive (e.g., machine learning‐based) estimation of nuisance parameters. We examine the large‐sample properties of the estimators and evaluate finite‐sample performance in simulations. Last, we apply the methods to data from lung cancer screening using nationally representative data from the National Health and Nutrition Examination Survey (NHANES) and extend our methods to account for the complex survey design of the NHANES.

The complete chloroplast genome sequences of nine melon varieties (Cucumis melo L.): lights into comparative analysis and phylogenetic relationships.

Melon (Cucumis melo L.) is one of the most extensively grown horticulture crops of the world. Based on the morphological characters, melon was formerly divided into two subspecies, Cucumis melo ssp. melo and C. melo ssp. agrestis. However, the present methods are still inadequate to distinguish between them. The phylogenetic analysis based on chloroplast genome sequences could provide essential evidence for the classification of melon varieties. We sequenced the chloroplast genomes of nine different melon varieties by the Illumina Hiseq and performed bioinformatic analyses including repeat element analysis, genome comparison and phylogenetic analysis. The results showed that the melon chloroplast genome has a typical quadripartite structure that was conserved across the analyzed sequences. Its length ranges between 155, 558 and 156, 569bp, with a total GC content varying from 36.7% to 37%. We found 127-132 genes in melon chloroplast genomes, including 85-87 protein-coding regions, 34-37 tRNA and 6-8 rRNA genes. The molecular structure, gene order, content, codon usage, long repeats, and simple sequence repeats (SSRs) were mostly conserved among the nine sequenced genomes. Phylogenetic analysis showed that the chloroplast genome could clearly distinguish between C. melo ssp. melo and C. melo ssp. agrestis. This study not only provides valuable knowledge on melon chloroplasts, but also offers a theoretical basis and technical support for the genetic breeding of melons.

Group-k consistent measurement set maximization via maximum clique over k-uniform hypergraphs for robust multi-robot map merging

This paper unifies the theory of consistent-set maximization for robust outlier detection in a simultaneous localization and mapping framework. We first describe the notion of pairwise consistency before discussing how a consistency graph can be formed by evaluating pairs of measurements for consistency. Finding the largest set of consistent measurements is transformed into an instance of the maximum clique problem and can be solved relatively quickly using existing maximum-clique solvers. We then generalize our algorithm to check consistency on a group- k basis by using a generalized notion of consistency and using generalized graphs. We also present modified maximum clique algorithms that function over generalized graphs to find the set of measurements that is internally group- k consistent. We address the exponential nature of group- k consistency and present methods that can substantially decrease the number of necessary checks performed when evaluating consistency. We extend our prior work to perform data association, and to multi-agent systems in both simulation and hardware, and provide a comparison with other state-of-the-art methods.

A CONCEPTUAL FRAMEWORK FOR ASSESSING THE FIELD EFFICIENCY OF DRONES IN IDENTIFYING POTENTIAL BREEDING SITES OF THE Aedes MOSQUITO

The identification of breeding sites is key to dengue prevention strategies. Community involvement and breeding site surveillance play a vital role in controlling the Aedes population. Drones have emerged as a promising tool to be used in surveillance activities. Therefore, the aim of this paper is to develop a conceptual framework and present comprehensive intervention methods to control dengue cases. This study explores the concepts of community engagement, habitat profiling and mapping, and technology integration that will be implemented in the three main phases. Phase I: Community engagement, in which to understand the implementation characteristics of the proposed system using the Consolidated Framework for Implementation Research (CFIR) and Human-Centred Design (HCD); Phase II: Profiling and mapping potential breeding sites, in order to compare and characterise vector breeding sites of the Aedes mosquito in selected urban and rural areas using innovative drone technologies; Phase III: Technology integration by developing automated linkage of information on the mapping of mosquito breeding sites for dengue risk to an application platform. This conceptual framework can assess the efficiency of drones as an alternative tool for dengue surveillance and the use of technology to locate breeding sites effortlessly, which can later be applied in dengue-endemic regions.

Neuro-Optimal Event-Triggered Impulsive Control for Stochastic Systems via ADP.

This article presents a novel neural-network-based optimal event-triggered impulsive control method. First, a novel general-event-based impulsive transition matrix (GITM) is constructed to represent the probability distribution evolving characteristics regarding all system states across the impulsive actions, rather than the prefixed timing sequence. On the foundation of this GITM, the event-triggered impulsive adaptive dynamic programming (ETIADP) algorithm and its high-efficiency version (HEIADP) are developed to deal with the optimization problems for stochastic systems with event-triggered impulsive controls. It is shown that the obtained controller design scheme can reduce the computational and communication burden caused by updating the controller periodically. By analyzing the admissibility, monotonicity, and optimality properties of ETIADP and HEIADP, we further establish the approximation error bound of the neural networks to address the connection between the ideal and neural-network-based realizations of the present methods. It is proven that the iterative value functions of both the ETIADP and HEIADP algorithms fall in a small neighborhood of the optimum as the iteration index increases to infinity. By adopting a novel task synchronization mechanism, the proposed HEIADP algorithm fully utilizes the computing resources of multiprocessor systems (MPSs), while significantly reducing the memory requirement compared to traditional ADP approaches. Finally, we carry out a numerical study to show that the proposed methods can fulfill the desired goals.

Penggabungan Kearifan Lokal dan Teknopreneurship dalam Wisata Kuliner Desa Nongkosawit Gunungpati Semarang

Within the confront of fast worldwide nourishment patterns and modernization, concerns are rising almost the potential misfortune of nearby culinary conventions that exemplify a nation's imaginativeness, culture, history, and character. To address this, STIEPARI Semarang propelled a community benefit extend in Nongkosawit, Gunungpati, pointed at protecting and advancing its one of a kind culinary legacy. The venture included recording conventional formulas and their social centrality, guaranteeing that this information is passed down and shared. The group collaborated with neighborhood cooks to coordinated present day culinary methods whereas keeping up genuineness. Workshops were held to educate the community how to showcase their conventional dishes, emphasizing storytelling as a way to associate with visitors. To maintain these endeavors, the venture presented computerized stages for nearby culinary businesses to reach broader gatherings of people through social media and e-commerce. This activity not as it were jam Nongkosawit s culinary bequest but moreover engages the neighborhood community by making modern financial openings tied to their wealthy social conventions. Through these endeavors, Nongkosawit Town represents the significance of defending and celebrating culinary conventions that characterize our social personality.