Multidimensional Method Research Articles

Mapping Abandoned Uranium Mine Features Using Worldview-3 Imagery in Portions of Karnes, Atascosa and Live Oak Counties, Texas

Worldview-3 (WV3) 16-band multispectral data were used to map exposed bedrock and mine waste piles associated with legacy open-pit mining of sandstone-hosted roll-front uranium deposits along the South Texas Coastal Plain. We used the “spectral hourglass” approach to extract spectral endmembers representative of these features from the image. This approach first requires calibrating the imagery to reflectance, then masking for vegetation, followed by spatial and spectral data reduction using a principal component analysis-based procedure that reduces noise and identifies homogeneous targets which are “pure” enough to be considered spectral endmembers. In this case, we used a single WV3 image which covered an ~11.5 km by ~19.5 km area of Karnes, Atascosa and Live Oak Counties, underlain by mined rocks from the Jackson Group and Catahoula Formation. Up to 58 spectral endmembers were identified using a further multi-dimensional class segregation method and were used as inputs for spectral angle mapper (SAM) classification. SAM classification resulted in the identification of at least 117 mine- and mine waste-related features, most of which were previously unknown. Class similarity was further evaluated, and the dominant minerals in each class were identified by comparison to spectral libraries and measured samples of actual Jackson Group uranium host rocks. Redundant classes were eliminated, and SAM was run a second time using a reduced set of 23 endmembers, which were found to map these same features as effectively as using the full 58 set of endmembers, but with significantly reduced noise and spectral outliers. Our classification results were validated by evaluating detailed scale mapping of three known mine sites (Esse-Spoonamore, Wright-McCrady and Garbysch-Thane) with published ground truth information about the vegetation cover, extent of erosion and exposure of waste pile materials and/or geologic information about host lithology and mineralization. Despite successful demonstration of the utility of WV3 data for inventorying mine features, additional landscape features such as bare agricultural fields and oil and gas drill pads were also identified. The elimination of such features will require combining the spectral classification maps presented in this study with high-quality topographic data. Also, the spectral endmembers identified during the course of this study could be useful for larger-scale mapping efforts using additional well-calibrated WV3 images beyond the coverage of our initial study area.

Study of energy-efficient heat resistance and cooling technology for high temperature working face with multiple heat sources in deep mine

In the present research, we proposed a scheme to address the issues of severe heat damage, high energy consumption, low cooling system efficiency, and wastage of cold capacity in mines. To elucidate the seasonal variations of environmental temperature through field measurements, we selected a high-temperature working face in a deep mine as our engineering background. To enhance the heat damage control cability of the working face and minimize unnecessary cooling capacity loss, we introduced the multi-dimensional heat hazard prevention and control method called "Heat source barrier and cooling equipment". First, we utilize shotcrete and liquid nitrogen injection to eliminate the heat source and implemented pressure equalization ventilation to disrupt the heat transfer path, thereby creating a heat barrier. Second, we establish divisional prediction models for airflow temperature based on the variation patterns obtained through numerical simulation. Third, we devise the location and dynamic control strategy for the cooling equipment based on the prediction models. The results of field application show that the heat resistance and cooling linkage method comply with the safety requirement throughout the entire mining cycle while effectively reducing energy consumption. The ambient temperature is maintained below 30 °C, resulting in the energy saving of 10% during the high-temperature period and over 50% during the low-temperature period. These findings serve as a valuable reference for managing heat damage in high-temperature working faces.

Декларированные и латентные социальные группы: феномен, эволюция, детерминанты. Часть 2

The aim of the research is to study the features of the social environment as potential conditions for the formation, functioning and evolution of latent social groups. Hypotheses: 1) there are pre-forms of social alliances of people (which can be tentatively called latent social groups); 2) different conditions of a subject’s external and internal environment (including features perceived by a person as subjectively significant for them in relation to certain life goals) might be the reasons why the pre-forms appear. The methods of the research are as follows: theoretical and categorical analysis, the study of literary sources, empirical research (questionnaires), multidimensional methods of parametric statistics. According to the author’s methodology (questionnaire “Dynamics of professional life style” – DPLS), respondents assessed the following variables: the role conditions of the social environment play as “factors of professionalism”, and the dynamics of their professionalism from 20 to 65 years (retrospectively to the current age and prospectively – predicting the dynamics of subsequent evolution); their socio-demographic and official characteristics were also recorded. 482 employees, men and women aged 30 to 50 years (132 civil servants, 129 engineers and heads of departments of manufacturing plants, 221 managers) were interviewed as participants of the study. The total sample was divided into groups several times. As criteria for division, relative characteristics (calculated by the formulas) of “career speed”, “managerial experience”, “family life experience” were used. The results of the empirical study confirm the working hypotheses. When dividing the sample according to different criteria – both obvious (men / women, specialists / managers, etc.) and relative, the groups differ significantly in a number of variables (environmental conditions marked as “factors of professionalism”). Conclusion: in one social space-time, different social alliances, structures, to a greater or lesser extent of their expression (manifestation), development, and active functioning as social groups can coexist. There are reasons to single out the phenomenon of latent social groups (LSG) as pre-forms of manifest social groups with subsequent different trajectories of their possible development. LSG are possible alliances of people who are similar to each other in a number of important aspects of life (value orientations, lifestyle, etc.), and who are potentially capable of integration and interaction (to achieve common goals, to establish comfortable interpersonal communication, to maintain typical patterns of behavior, etc.). LGS are the pre-stages of various social structures representing their possible formation and development. Representatives of some latent social groups differ from others both in terms of their preference and recognition of the role of individual environmental conditions and individual social spaces (parental family, their family, work groups, etc.). There may be some other “deep factors” behind people’s recognition of the subjective significance of different conditions of the social environment for them.

Study on the spatial spillover effect and path mechanism of green finance development on China's energy structure transformation

Green finance is essential for supporting the development of green, low-carbon projects and preventing environmental and climate financial risks. Investigating and studying whether and how it can aid in implementing energy transformation is worthwhile. This paper uses 30 provinces from 2004 to 2020 as research samples, the entropy method to construct a green finance measurement system, and the weighted multidimensional vector angle index method to construct an energy low-carbon transformation index based on the actual situation of green finance in China and the existing theoretical research basis. We systematically analyzed each province's spatiotemporal evolution characteristics of green finance and energy structure transformation by constructing a fixed effect model, a GMM model, an intermediary effect model, and a spatial Dubin model. We empirically tested the effect direction, internal mechanism, spatial spillover, and regional heterogeneity of green finance development (GFD) on energy structure transformation (EST) to investigate the low-carbon transformation of energy structures. The findings indicate the following:(1) Green finance plays a positive role in promoting the transformation and development of China's energy structure. (2) The influence of green finance development on the transformation of China's energy structure has significant spatial spillover, exhibiting “local and neighborhood” reciprocity. Through the spatial spillover effect, green finance can encourage the low-carbon transformation of local energy structures and increase the level of low-carbon transformation in neighboring areas. (3) The improvement of the level of green technology innovation and the intensity of environmental regulations are essential channels for green finance to support the low-carbon transformation of the energy structure, and regional heterogeneity will alter this transmission mechanism. The findings of this study provide empirical evidence for the vital role of green finance in achieving the double dividend of economic growth and low-carbon emission reduction. This study provides a new perspective for constructing a green finance system and advancing the dual-carbon objective and a resource for formulating effective regional energy transformation policies.

Nonlinear main components of the cytokine profile in children with community-acquired pneumonia

Cytokines are the key mediators which control and regulate immune and inflammatory responses via complex networks and serve as biomarkers of many diseases. Quantitative determination of cytokines is helpful in assessing immune status and adjusting therapy for various inflammatory diseases, such as sepsis and pneumonia. Since community-acquired pneumonia remains a common cause of childhood morbidity and mortality. At the present stage, prognosis of the disease severity in children is an urgent problem. The aim of our study was to identify associations between cytokine levels in healthy children and in children with community-acquired pneumonia (CAP), depending on the age of patients and severity of the pathological process. The work was carried out at the Department of Microbiology, Virology and Immunology, Department of Propaedeutics of Childhood Diseases and Pediatrics, and at the Research Institute of Immunology at the South Ural State Medical University. The study included 117 children aged 1 to 18 years with radiologically confirmed diagnosis of CAP, either severe or mild degree. The comparison group was composed from 28 healthy children who did not have community-acquired pneumonia, as well as other signs of acute respiratory viral infection at the time of examination, being observed for any chronic disorders. The levels of IL-1β, IFNγ, IL-6, IL-4, IL-10, IL-2, TNFα, IFNλ2 (IL-28A), IFNλ3 (IL-28B), IL-8, MCP-1, IL-17AF, GM-CSF were determined in blood serum by means of ELISA test systems (a “sandwich” technique with peroxidase as an indicator enzyme). For statistical analysis, a multidimensional method was used, i.e., non-linear analysis of the principal components using the CATPCA algorithm. Among the children with CAP, our study revealed a consistent increase of IL-1ß, IL-4, IL-10, IL-2, TNFα, IFNλ2 (IL-28A), IFNλ3 (IL-28B), IL-8, MCP-1, IL-17AF, GM-CSF in blood serum. The highest correlation with severity was shown for IFNλ2 (IL-28A), IFNλ3 (IL-28B) and MCP-1, which may be considered additional biomarkers of the CAP severity. There was also a significant variability of the cytokine profile in healthy children and its significant skewing in pneumonia, especially in severe cases.

Research on force model and characteristics of large wind turbine pitch system based on SCADA data

In large-scale wind turbines, the force state of the pitch system greatly influences safe operation and service life. This paper provides a novel method to estimate blade pitch load, bearing friction torque, and motor pitch torque. In this method, the force equilibrium equations are established by investigating the force of the pitch system under multiple operating conditions. The multidimensional BIN method is employed to classify the supervisory control and data acquisition (SCADA) data of wind turbines into several intervals. The multidimensional scatter data is processed in a single-valued way. Then, the estimating model of the pitch system forces is established by combining the obtained data and the equilibrium equations. Taking a 2 MW wind turbine as an example, the variation characteristics of blade pitch load, bearing friction torque, and motor pitch torque under multiple operating conditions are analyzed. Some interesting and valuable conclusions are obtained. For example, when the wind speed increases, the blade pitch load increases significantly in the maximum wind energy tracking region, but there is no obvious change in the observed constant power output region. The wind speed and azimuth have little effect on the bearing friction torque. The variation trend of motor pitch torque is consistent with that of blade pitch load in the maximum wind energy tracking region.

Reassessing Resettlement-Associated Poverty Induced by Water Conservancy Projects in China: Case Study of the “Yangtze to Huai River Inter-Basin” Water Diversion Project

The displacement and resettlement-associated poverty caused by water conservancy projects (WCP) is a worldwide issue. Re-settlers are often impoverished for extended periods due to loss, difficult re-establishment, and insufficient compensation. Addressing poverty has become a worldwide concern, and accurate measurements of poverty remain a fundamental issue. Before 2020, the Chinese government used the absolute income method to measure re-settler poverty. However, this method reflected neither the overall income gap nor potential benefits of social development and poverty alleviation policies. Therefore, we used the relative income and multidimensional methods alongside the absolute income poverty method to measure the poverty in recently resettled households. Based on survey data from over resettled 1000 households we conclude that: (1) The remaining poor measured by the absolute poverty line were mainly caused by serious diseases, disabilities and loss of labor ability, which means they have no ability to be lifted out of poverty except through the bottom line of local governments. As a result, the absolute poverty line loses its distinction to poverty. (2) Rural re-settlers were more resilient to forced majeure because land guarantees employment and food supply, allowing households to avoid secondary livelihood destruction. (3) Income derived measurement of re-settler poverty masks the benefits of poverty alleviation and other socioeconomic aid programs. A few households showed improvements in child school attendance, child mortality, nutrition, cooking fuel, asset ownership, and social insurance following resettlement. (4) To reduce the multidimensional gap, government aid programs should focus on years of schooling (including training), nutrition, household savings, and household labor force rather than simply providing monetary assistance. At the same time, we suggest that the government adopt a variety of compensation methods, such as: sharing the benefits of water conservancy projects, industrial support and improving the bottom line guarantee.

Development Potential Assessment for Wind and Photovoltaic Power Energy Resources in the Main Desert–Gobi–Wilderness Areas of China

The large-scale centralized development of wind and PV power resources is the key to China’s dual carbon targets and clean energy transition. The vast desert–Gobi–wilderness areas in northern and western China will be the best choice for renewable energy development under multiple considerations of resources endowment, land use constraints, technical conditions, and economic level. It is urgent to carry out a quantitative wind and PV resource assessment study in desert–Gobi–wilderness areas. This paper proposed a multi-dimensional assessment method considering the influence of the power grid and transportation infrastructure distributions, which includes three research levels, namely, the technical installed capacity, the development potential, and the development cost. Nine main desert–Gobi–wilderness areas were assessed. The wind and PV technical installed capacities were 0.6 TW and 10.7 TW, and the total development potentials were over 0.12 TW and 1.2 TW, with the full load hours of 2513 and 1759 and the average development costs of 0.28 CNY/kWh and 0.20 CNY/kWh. Finally, this paper proposed the meteorological–electrical division distribution. A case study in the Kubuqi and Qaidam Deserts was carried out on wind–wind and wind–PV collaborative development across different meteorological–electrical divisions, which can reduce by 58% the long-term energy storage capacity and decrease the total system LCOE from 0.488 CNY/kWh to 0.445 CNY/kWh.

Multidimensional separation methods can improveseparation performance forextremely complicated proteomics samples and provide a powerful tool for comprehensive proteome profiling of low-microgram samples.

Tweetable abstract Multidimensional separation methods with improved sensitivity andpeak capacity and throughput allow in-depth proteome profiling of low-microgram samples.

Multiomics and Multidimensional Testing for Efficacy Monitoring of Patients with Lymphoma

To explore the role of a new blood-based, multiomics and multidimensional method for evaluating the efficacy of patients with lymphoma. 10 ml peripheral blood was extracted from each patient, and the genomic copy number aberrations (CNA) and fragment size (FS) were evaluated by low-depth whole genome sequencing of cfDNA, and the level of a group of plasma tumor marker (PTM) were detected at the same time. The cancer efficacy score (CES) was obtained by standardized transformation of the value of above three numerical indexes, and the changes of CES before and after treatment were compared to evaluate the patient's response to the treatment regimen. A total of 35 patients' baseline data were collected, of which 23 cases (65.7%) had elevated CES values. 18 patients underwent the first time test. The results showed that the CES value of 9 patients with positive baseline CES decreased significantly at the first test, and the efficacy evaluation was PR, which was highly consistent with the imaging evaluation results of the same period. At the same time, the CNA variation spectrum of all patients were evaluated and it was found that 23 patients had partial amplification or deletion of chromosome fragments. The most common amplification site was 8q24.21, which contains important oncogenes such as MYC. The most common deletion sites were 1p36.32, 4q21.23, 6q21, 6q27, 14q32.33, and tumor suppressor-related genes such as PRDM1, ATG5, AIM1, FOXO3 and HACE1 were expressed in the above regions, so these deletions may be related to the occurrence and development of lymphoma. With the advantages of more convenience, sensitivity and non-invasive, this multiomics and multidimensional efficacy detection method can evaluate the tumor load of patients with lymphoma at the molecular level, and make more accurate efficacy evaluation, which is expected to serve the clinic better.

“Ship-port-country” multi-dimensional research on the fine analysis of China's LNG trade

Liquefied Natural Gas (LNG) is a clean and low-carbon energy source that plays an important role in combating global warming. As the world's largest greenhouse gas (GHG) emitter, China has taken coal-to-gas as an important measure to reduce GHG emissions, and has become the world's largest LNG importer. Studying the patterns and characteristics of China's LNG trade is of great significance for ensuring energy supply security, formulating and adjusting energy strategies. However, the refined analysis of China's LNG trade is still inadequate, mainly due to the lack of research on the details of ship trajectories and port attributes. Therefore, a “ship-port-country” multidimensional LNG trade analysis method is proposed to improve the timeliness, multi-dimensionality and fineness of China's LNG trade analysis. The multidimensional characteristics of China's LNG trade are analyzed by studying the big data of nearly 3.5 billion automatic identification system (AIS) records in 2017. The study has found that (1) The arrival frequency of China's LNG trading ships varies greatly with time. For example, the most frequent daily arrivals are between 04:00 and 05:00 in the morning, while the least frequent arrivals are between 15:00 and 17:00 in the afternoon. (2) The Chinese LNG trade network consisting of 79 ports has been formed, of which NANTONG Port is the most important port. (3) The LNG trade volume calculated in this study has shown a strong correlation with the national LNG trade statistics and can be used to analyze LNG trade with higher spatial and temporal resolution. According to the characteristics of LNG trade at the three levels of ship, port and country, China can optimize its LNG trade policy from the following aspects: (1) Dynamically allocate port resources according to the arrival frequency of LNG tankers to reduce port congestion and waste of resources. (2) Expand core LNG trading ports such as NANTONG Port, ZHOUSHAN Port, TANGSHAN (JINGTANG) Port, XIUYU Port, DALIAN Port and LUSHUN Port. (3) Actively realize the diversification of LNG trading partners to reduce the dependence of LNG import sources on one country or region, and ensure energy security. The “ship-port-country” multi-level LNG trade analysis method proposed in this study provides a new research perspective for the analysis of the LNG trade pattern. This study reveals the multidimensional characteristics of China's LNG trade, which can provide decision-making support for China to formulate reasonable LNG trade policies and energy security policies, and is conducive to the stable and sustainable development of global LNG trade.

Multidimensional nonadditivity in one-facet g-theory designs: A profile analytic approach.

We introduce a new method for estimating the degree of nonadditivity in a one-facet generalizability theory design. One-facet G-theory designs have only one observation per cell, such as persons answering items in a test, and assume that there is no interaction between facets. When there is interaction, the model becomes nonadditive, and G-theory variance estimates and reliability coefficients are likely biased. We introduce a multidimensional method for detecting interaction and nonadditivity in G-theory that has less bias and smaller error variance than methods that use the one-degree of freedom method based on Tukey's test for nonadditivity. The method we propose is more flexible and detects a greater variety of interactions than the formulation based on Tukey's test. Further, the proposed method is descriptive and illustrates the nature of the facet interaction using profile analysis, giving insight into potential interaction like rater biases, DIF, threats to test security, and other possible sources of systematic construct-irrelevant variance. We demonstrate the accuracy of our method using a simulation study and illustrate its descriptive profile features with a real data analysis of neurocognitive test scores. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Long-term probabilistic streamflow forecast model with “inputs–structure–parameters” hierarchical optimization framework

Accurate, reliable, and stable streamflow forecasts are essential for risk assessment and decision making in water resources management. Owing to the limited value of deterministic forecasting, probabilistic forecasting incorporating probability and confidence intervals is achieved by optimizing the predictors and forecast equation while identifying forecast error features. The combination of deterministic forecasts and error identification can facilitate water resources management. This study improved the traditional forecast model’s inputs selection, structure designation, and error parameters calibration to propose a long-term probabilistic streamflow forecast model with hierarchical optimization of the predictors, forecast equation, and errors characteristics. The model develops information entropy theory to screen the driving predictor set, the long short-term memory (LSTM) model to conduct deterministic forecasts, and the generalized autoregressive conditional heteroskedasticity (GARCH) model to identify time-varying errors. The proposed model, used in some case studies to forecast the monthly streamflow of two lakes, Hongze and Luoma lakes in China, was evaluated using the multidimensional index method considering “accuracy–reliability–stability” performance. The results revealed the following: (1) Predictor screening based on information entropy investigates the statistical characteristics of predictors, thereby improving the reliability of streamflow forecasts. (2) The LSTM model exploits the response between the driving predictors and streamflow, whereas GARCH model identifies the time-varying features of forecast errors effectively, which reduces the probability of forecast failure and increases the accuracy and stability of probabilistic forecasts. (3) Under current meteorological observation conditions and forecasting capability, the proposed forecasts can extend the maximum forecast lead time from 1 month to 3 months. (4) The proposed model improves the accuracy (root mean square error: 6.7%–34.8%), reliability (Brier score: 15.3%–27.9%), and stability (mistaken distance: 36.4–52.6%) in comparison with the benchmark of the two case studies, indicating that “inputs–structure–parameters” hierarchical optimization provides effective forecast information for water resources management.

Multi-dimensional feature extraction method for distributed optical fiber sensing signals

Multi-dimensional feature extraction method for distributed optical fiber sensing signals

Model for predicting prognosis and immunotherapy based on CD+8T cells infiltration in neuroblastoma.

Neuroblastoma (NBL) is an extracranial malignant tumor in children deriving from the neural crest in the sympathetic nervous system. Although various immunotherapy interventions have made significant breakthroughs in many adult cancers, the efficacy of these immunotherapies was still limited in NBL. NBL has low immunogenicity which results in a lack of tumor-infiltrating T lymphocytes in the tumor microenvironment (TME). Moreover, tumor cells can wield many immune evasion strategies both in the TME and systemically to impede lymphocyte infiltration and activation. All these factors hamper the anti-tumor effects of CD8+ T cells during immunotherapy and the levels of infiltrating CD8+ T cells correlate with therapy response. In this study, we utilized multidimensional bioinformatic methods to establish a risk model based on CD8+ T cells -related genes (CD8+ TRGs). We obtained 33 CD8+TRGs with well-predictive ability for prognosis in both GSE49711 and E-MTAB-8248 cohorts. Then, 12 CD8+TRGs including HK2, RP2, HPSE, ELL2, GFI1, SLC22A16, FCGR3A, CTSS, SH2D1A, RBP5, ATF5, and ADAM9 were finally identified for risk model construction and validation. This model revealed a stable performance in prognostic prediction of the overall survival (OS) and event-free survival (EFS) in patients with NBL. Additionally, our research indicated that the immune and stromal scores, immune-related pathways, immune cell infiltration, the expression of major histocompatibility complex (MHC) and immune checkpoint molecules, immunotherapy response, and drug susceptibility revealed significant differences between high and low-risk groups. According to our analyses, the constructed CD8+TRGs-based risk model may be promising for the clinical prediction of anti-tumor therapy responses and prognoses in NBL.

Multidimensional Separations in Top-Down Proteomics.

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

A mixed-method feasibility study of the use of the Complete Vocal Technique (CVT), a pedagogic method to improve the voice and vocal function in singers and actors, in the treatment of patients with muscle tension dysphonia: a study protocol

BackgroundMuscle tension dysphonia (MTD) results from inefficient or ineffective voice production and is the cause of voice and throat complaints in up to 40% of patients presenting with hoarseness. Standard treatment is voice therapy (SLT-VT) delivered by specialist speech therapists in voice disorders (SLT-V). The Complete Vocal Technique (CVT) is a structured, pedagogic method which helps healthy singers and other performers optimise their vocal function enabling them to produce any sound required. The aim of this feasibility study is to investigate whether CVT administered by a trained, non-clinical CVT practitioner (CVT-P) can be applied to patients with MTD before progressing to a pilot randomised control study of CVT voice therapy (CVT-VT) versus SLT-VT.Methods/designIn this feasibility study, we use a mixed-method, single-arm, prospective cohort design. The primary aim is to demonstrate whether CVT-VT can improve the voice and vocal function in patients with MTD in a pilot study using multidimensional assessment methods. Secondary aims are to assess whether (1) a CVT-VT study is feasible to perform; (2) is acceptable to patients, the CVT-P and SLT-VTs; and (3) whether CVT-VT differs from existing SLT-VT techniques. A minimum of 10 consecutive patients with a clinical diagnosis of primary MTD (types I–III) will be recruited over a 6-month period. Up to 6 video sessions of CVT-VT will be delivered by a CVT-P using a video link. The primary outcome will be a change in pre-/post-therapy scores of a self-reported patient questionnaire (Voice Handicap Index (VHI)). Secondary outcomes include changes in throat symptoms (Vocal Tract Discomfort Scale), acoustic/electroglottographic and auditory-perceptual measures of voice. Acceptability of the CVT-VT will be assessed prospectively, concurrently and retrospectively both quantitatively and qualitatively. Differences from SLT-VT will be assessed by performing a deductive thematic analysis of CVT-P transcripts of therapy sessions.ConclusionThis feasibility study will provide important data to support whether to proceed with a randomised controlled pilot study focusing on the effectiveness of the intervention compared to standard SLT-VT. Progression criteria will be based on demonstrating a positive outcome in treatment, successful delivery of the pilot study protocol, acceptability to all stakeholders and satisfactory recruitment rates.Trial registrationClinicalTrials.gov website (NCT05365126 Unique Protocol ID: 19ET004). Registered on 06 May 2022.

An Optimized Fed-Batch Culture Strategy Based on Multidimensional Time Series Aggregation

An optimized feeding strategy for the fed-batch fermentation of 2-keto-L-gulonic acid (2-KGA) is proposed to enhance the total profit of a workshop. Instead of assigning the same quantity of substrate to each batch in the empirical scheduling, the online feeding strategy offers a practical approach that allows for the precise management of substrate feeding to maximize economic performance. The forecasting of the profit function has been achieved through the proposed similarity measurement and multidimensional time series aggregation method. This method solves the problem of predicting the total economic benefit at the end of fermentation, in the absence of fermentation substrate measurement data. Pseudo-online simulation has been conducted, utilizing data derived from ninety industrial batches. A 6% increase in total profit is observed, which indicates that the optimized strategy utilizes the substrate and other related resources more efficiently and leads to a higher overall profit.

Investigation of plate fuel performance under reactivity initiated accidents with developed multi-dimensional coupled method

A reactivity-initiated accident is a typical nuclear reactor accident during which the core fission rate and power increase unexpectedly, making the temperature of the fuel element soar, which causes a decreasing strength, large deformation, and even the failure of the element. To simulate the performance of the plate-type fuel during RIA, a neutronics–thermal hydraulics–mechanics coupling method was implanted in a fuel performance code BEEs-Plates. The coupling scheme was firstly verified and validated against the MTR benchmark. Then the RIA results with the consideration of the deformation effect were compared with the benchmark case, showing that the mechanics as well as the burnup effect have little impact on the neutronic–thermal hydraulics results when using the constant thermal properties. Lastly, the thermal-mechanical analysis was conducted for the fuel plate at different burnups (0% FIMA, 10% FIMA, 20% FIMA) under the RIA. The results show that the peak stress of the cladding increases with the burnup increases while it has an opposite trend for the fuel meat. Some special features such as over-shrinkage of the fuel meat have also been noticeable and analyzed.

Gaidai reliability method for long-term coronavirus modelling.

Novel coronavirus disease has been recently a concern for worldwide public health. To determine epidemic rate probability at any time in any region of interest, one needs efficient bio-system reliability approach, particularly suitable for multi-regional environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of novel coronavirus infection rate. Traditional statistical methods dealing with temporal observations of multi-regional processes do not have the multi-dimensionality advantage, that suggested methodology offers, namely dealing efficiently with multiple regions at the same time and accounting for cross-correlations between different regional observations. Modern multi-dimensional novel statistical method was directly applied to raw clinical data, able to deal with territorial mapping. Novel reliability method based on statistical extreme value theory has been suggested to deal with challenging epidemic forecast. Authors used MATLAB optimization software. This paper described a novel bio-system reliability approach, particularly suitable for multi-country environmental and health systems, observed over a sufficient period of time, resulting in a reliable long-term forecast of extreme novel coronavirus death rate probability. Namely, accurate maximum recorded patient numbers are predicted for the years to come for the analyzed provinces. The suggested method performed well by supplying not only an estimate but 95% confidence interval as well. Note that suggested methodology is not limited to any specific epidemics or any specific terrain, namely its truly general. The only assumption and limitation is bio-system stationarity, alternatively trend analysis should be performed first. The suggested methodology can be used in various public health applications, based on their clinical survey data.