Terms Of Statistics Research Articles

NNT and NNH: statistics and stochastics in the evaluation of added therapeutic value

Any pharmacological, invasive, surgical health intervention should have an added therapeutic value as well as the requirements of quality, safety, efficacy, to be considered as a medical device based on scientific evidence and of clinical utility for the patient. The intervention should be shared between the doctor and the patient who should have rigorous but simple tools to decide on the best therapy to undertake. Assessment of relative risk reduction is commonly used in the scientific literature to quantify both statistical and clinical significance. The reduction of the relative risk is independent of the baseline risk and is useful for comparing the results of trials conducted on populations at different risk levels. A biased reading of relative risk reduction can be used to emphasize the magnitude of the benefit for market innovation. The absolute risk reduction, on the other hand, is proportional to the magnitude of the baseline risk and is a more useful parameter for physicians and patients to understand the extent of benefit and harm, especially if the parameter is expressed in terms of the number needed to treat (NNT) or to harm (NNH). The mode of scientific communication is important for doctors' choices and patients' trust. Even true data can be fake in communication and perception by resorting to verbose paraphrases. Presenting the results of clinical trials in stochastic as well as statistical terms is useful for doctors and patients to verify whether it is worth practicing a certain treatment whose success sometimes has the probability of winning the lottery, also considering side effects and adverse events. One of the most important challenges in precision medicine will be understanding the relationship between probability and randomness.

Context-Aware Embedding Techniques for Addressing Meaning Conflation Deficiency in Morphologically Rich Languages Word Embedding: A Systematic Review and Meta Analysis

This systematic literature review aims to evaluate and synthesize the effectiveness of various embedding techniques—word embeddings, contextual word embeddings, and context-aware embeddings—in addressing Meaning Conflation Deficiency (MCD). Using the PRISMA framework, this study assesses the current state of research and provides insights into the impact of these techniques on resolving meaning conflation issues. After a thorough literature search, 403 articles on the subject were found. A thorough screening and selection process resulted in the inclusion of 25 studies in the meta-analysis. The evaluation adhered to the PRISMA principles, guaranteeing a methodical and lucid process. To estimate effect sizes and evaluate heterogeneity and publication bias among the chosen papers, meta-analytic approaches were utilized such as the tau-squared (τ2) which represents a statistical parameter used in random-effects, H-squared (H2) is a statistic used to measure heterogeneity, and I-squared (I2) quantify the degree of heterogeneity. The meta-analysis demonstrated a high degree of variation in effect sizes among the studies, with a τ2 value of 8.8724. The significant degree of heterogeneity was further emphasized by the H2 score of 8.10 and the I2 value of 87.65%. A trim and fill analysis with a beta value of 5.95, a standard error of 4.767, a Z-value (or Z-score) of 1.25 which is a statistical term used to express the number of standard deviations a data point deviates from the established mean, and a p-value (probability value) of 0.2 was performed to account for publication bias which is one statistical tool that can be used to assess the importance of hypothesis test results. The results point to a sizable impact size, but the estimates are highly unclear, as evidenced by the huge standard error and non-significant p-value. The review concludes that although contextually aware embeddings have promise in treating Meaning Conflation Deficiency, there is a great deal of variability and uncertainty in the available data. The varied findings among studies are highlighted by the large τ2, I2, and H2 values, and the trim and fill analysis show that changes in publication bias do not alter the impact size’s non-significance. To generate more trustworthy insights, future research should concentrate on enhancing methodological consistency, investigating other embedding strategies, and extending analysis across various languages and contexts. Even though the results demonstrate a significant impact size in addressing MCD through sophisticated word embedding techniques, like context-aware embeddings, there is still a great deal of variability and uncertainty because of various factors, including the different languages studied, the sizes of the corpuses, and the embedding techniques used. These differences show how future research methods must be standardized to guarantee that study results can be compared to one another. The results emphasize how crucial it is to extend the linguistic scope to more morphologically rich and low-resource languages, where MCD is especially difficult. The creation of language-specific models for low-resource languages is one way to increase performance and consistency across Natural Language Processing (NLP) applications in a practical sense. By taking these actions, we can advance our understanding of MCD more thoroughly, which will ultimately improve the performance of NLP systems in a variety of language circumstances.

Veterinary Evidence: moving forward

Unrecognised and unknown information needs can significantly impact on the quality of decision making, advice, and patient care. In the practice of veterinary medicine, additional information may be required in one or more of epidemiology, diagnosis, treatment, prognosis, control (risk reduction), and prevention (risk avoidance), in order to optimise patient care. Veterinary Evidence publishes Knowledge Summaries, which aim to answer a specific and focused clinical query by appraising the best available evidence published in peer-reviewed scientific journals. By presenting the evidence in a structured and easily digestible format, Knowledge Summaries enable veterinary professionals to stay informed and apply the best available evidence to their decision-making. To assist in the identification of unrecognised deficits and the generation of clinical queries Veterinary Evidence has developed a list of common conditions for each species, alongside the different categories of information. The aim is to prompt and support the generation of new clinical queries in a more systematic format. This resource sits alongside our species-based lists of clinical queries that have already been suggested by practicing veterinarians, veterinary nurses, and other paraprofessionals (see veterinaryevidence.org/index.php/ve/clinical-queries). We hope readers and prospective authors will use these resources to generate new clinical queries or as a starting point for writing their own Knowledge Summaries. Most of the papers published in Veterinary Evidence are Knowledge Summaries, but the journal has always accepted and will continue to accept and encourage other types of reviews and original research that provide evidence to inform clinical practice. For example, in this issue we have published a commentary paper by Professor Jonathan Elliott regarding the processes and evidence required for the registration of veterinary medicinal products which provides some important insights and debate into the publication of evidential information (Elliott, 2024). A Knowledge Summary may not always be the best format to synthesise and summarise evidence on a multifaceted topic; scoping reviews, systematic reviews, or narrative reviews maybe more appropriate. Munn et al. (2018) provide a useful account of scoping reviews and how they differ from traditional literature and systematic reviews. In particular, we are keen to receive articles on artificial intelligence applications, sustainability, and quality improvement in clinical practice, as the impact and importance of these topics grows. We are also making some changes to the presentation of Knowledge Summaries in Veterinary Evidence, to help readers more easily understand the details and context of the summarised evidence. In order to support everyone in appraising and understanding quantitative clinical studies, we will be publishing a glossary and guidance on basic statistical terms and tests on the journal website.

An analysis of direct-to-consumer genetic testing portals and their communication of health risk and test limitations.

Direct-to-consumer (DTC) genetic testing has become incredibly popular for assessing health risk related to specific diseases. However, how this risk is conveyed and whether the limitations of the tests are fully communicated can impact how customers interpret results. Through a qualitative content analysis of three different DTC genetic testing online portals, we examine how companies communicate relative and absolute health risks, the extent to which limitations are communicated, and how this information is presented. Findings suggest that relative risk was more prominently communicated than absolute risk and that it was used to organize and prioritize results. Further, risk information was often communicated using statistical terms and concepts that may not be accessible to all users. Test limitations that were communicated included the inability to diagnose a disease, the importance of lifestyle factors, and that the tests do not account for all genetic variants. Although companies included this information, it was not visually prominent.

NON-INVASIVE FORENSIC EXAMINATION OF INSCRIPTIONS IN A HISTORICAL DOCUMENT AS AN ATTEMPT TO EVALUATE THE DIVERSITY OF THE COMMERCIAL OFFER OF INKS

In the history of the German state, the world-wide economic crisis (1929-1939) probably also had an impact on the availability of inks. The research aimed to find out whether it is possible to discriminate between inks and determine the prevalence of ink manufacturers in a specific area, which, in statistical terms, could provide insight into the development of regional ink producers. The research covered selected inscriptions in ink written in a Diary from a small geographical area. Ink examination was carried out using non-invasive VIS-NIR and RS spectroscopic methods involving a statistical approach. The obtained results allowed effective discrimination of the inks and divided them into several groups. Research has shown that iron-gall inks from several ink manufacturers were used to prepare the entries in the Diary. It cannot be ruled out that the differences in individual inks resulted from technological changes in their production process. Additionally, the research revealed a multitude of entries made with iron-gall inks, which may testify to the development of small-scale production of iron-gall inks confined to one geographical area. This type of historical document may constitute a forgery in whole or in specific parts of the inscriptions executed to falsify significant facts, therefore it is an object of interest of forensic science. The non-invasive VIS-NIR and RS spectroscopic methods supported by statistical approach should continue to develop to become an alternative and reliable solution offering great potential in forensic examination of inks.

The phenomenon of suicide considered from criminological, sociological and legal perspectives. Case study – Warmia and Mazury Voivodship

Aim: The aim of the study is to characterise the phenomenon of suicide and to carry out a comprehensive analysis of the phenomenon, reaching to its aetiology, characterising its symptomatic forms, confronting it with the norms of Polish criminal law and assessing the symptomological tendencies in the area in question. Method: the point of reference for the study is suicides committed or attempted in the area of the selected territorial unit in Poland. Warmińsko-Mazurskie Voivodeship is a specific region in the context of the whole country. First of all, the Second World War interrupted the relay of generations. The population is largely made up of displaced persons from the east. This community had to forge new interpersonal bonds and create cultural resources from scratch. In addition, the region was hit by high unemployment and a phenomenon of social pauperisation during the political transformation of the 1990s. From a psychological point of view, many suicidogenic factors have accumulated in the region. In terms of police services, the area is under the jurisdiction of the Regional Police Headquarters in Olsztyn. The chosen aim of the research and the research problems determined the choice of methods. The multifaceted nature of the studied phenomenon required the use of several complementary research methods, such as: the formal-dogmatic method, the historical-legal method and the comparative method. The following considerations are also based on the analysis of statistical data on the research subject. Results: Analysing the phenomenon in question, it was found that the approach to it was and still is conditioned by historical, civilisational circumstances. It is also reflected in legal codifications, in which the legislator departs from punishing potential suicides. At the same time, when considering the phenomenon on a regional scale, no significant deviations from the general trends are noticeable. However, taking into account the social territorial dissimilarity, the local specificity should be taken into account in the creation of support for persons at risk of various dysfunctions that may be the cause of suicide. Theoretical implications (if applicable): not applicable. Practical implications (if applicable): The presented analysis of the phenomenon in a regional context will undoubtedly contribute to further research on suicidal behaviour. The local perspective of the article fosters a comprehensive understanding of the factors influencing the decision to take one's own life. Thus, it may influence the creation of a system of support for people in this regard, taking into account the specifics of the region and social problems resulting from economic and living relations. Originality/value: the article integrates contemporary knowledge on the symtomology, phenomenology of suicide, allows to identify the main causes of this phenomenon and characterises the legislation in this field. The following article analyses the phenomenon of suicide on a regional scale. The local perspective makes it possible to know in more detail the problems causing negative social behaviour. At the same time, it adequately identifies the problems oscillating around the phenomenon in question. It can be a useful tool for researchers and decision-makers looking for answers to questions in this area and indicate directions for the development of social policy instruments in this area. Research limitations/ Future research: The phenomenon of self-harm is a very interesting process or moment in the life of the person who commits it. Although suicide has received a great deal of attention in the specialist literature, it still remains completely unexplored. The phenomenon itself touches the realm of the mysterious on the borderline between life and death. Hence the interest in it by many scientific disciplines. In statistical terms, the Polish Police collect detailed data on suicides. Research limitations in this area result from ethical and moral aspects of the issue, the lack of direct contact with the suicide's environment. The research results themselves are socially internalised and significantly influence the perception of reality. Technically, the use of research is not always morally acceptable. At the same time, research fulfils social needs and expectations for the creation of instruments to prevent suicide attacks.

Energy and productivity-based theory of cycle and crisis: the monistic approach of Vladimir Bazarov (1874–1939)

Vladimir Bazarov (1874–1939) tried to construct a monistic theory of cycles and crises on the basis of energy. His analysis of energy principles leads him, in a second step, to put the emphasis on productive forces and labour productivity, whose behaviour plays a determining role in the manifestation of both the cycle and the crisis. Finally, in empirical and statistical terms, the dynamics of labour productivity and of most of the economic series in Bazarov’s model are considered to be the result of a moving stochastic equilibrium (different from the purely mechanic dynamic equilibrium).

A method: multi-scale calculation life of welded beams with residual stress

To improve the accuracy of the probability of life value calculation while ensuring computational efficiency, a study was conducted on the finite element probability of life calculation method for beam-shell coupling. On the basis of the finite element heat and stress coupling model of Type I welded beam, a fatigue fracture model of residual stress and cyclic load coupling was established. The probability of life calculation of beam-shell elements was theoretically derived, and the expression of the probability of life model was unified. The probability of life of Type I welded beam was calculated, and it was compared with the model of beam assumption and the full life test result. The results show that the computational efficiency of the beam-shell coupling model is higher than that of the shell element model. In addition, the probability of life calculation result obtained by the beam-shell coupling model is highly consistent with the experimental result in statistical terms, and it has higher accuracy at low stress levels than the calculation result of the beam element, with the relative error between the median of the calculation result and the experimental result being less than 10%.

Quantitative estimates of the regulatory influence of long non-coding RNAs on global gene expression variation using TCGA breast cancer transcriptomic data.

Long non-coding RNAs (lncRNAs) have received attention in recent years for their regulatory roles in diverse biological contexts including cancer, yet large gaps remain in our understanding of their mechanisms and global maps of their targets. In this work, we investigated a basic unanswered question of lncRNA systems biology: to what extent can gene expression variation across individuals be attributed to lncRNA-driven regulation? To answer this, we analyzed RNA-seq data from a cohort of breast cancer patients, explaining each gene's expression variation using a small set of automatically selected lncRNA regulators. A key aspect of this analysis is that it accounts for confounding effects of transcription factors (TFs) as common regulators of a lncRNA-mRNA pair, to enrich the explained gene expression for lncRNA-mediated regulation. We found that for 16% of analyzed genes, lncRNAs can explain more than 20% of expression variation. We observed 25-50% of the putative regulator lncRNAs to be in 'cis' to, i.e., overlapping or located proximally to the target gene. This led us to quantify the global regulatory impact of such cis-located lncRNAs, which was found to be substantially greater than that of trans-located lncRNAs. Additionally, by including statistical interaction terms involving lncRNA-protein pairs as predictors in our regression models, we identified cases where a lncRNA's regulatory effect depends on the presence of a TF or RNA-binding protein. Finally, we created a high-confidence lncRNA-gene regulatory network whose edges are supported by co-expression as well as a plausible mechanism such as cis-action, protein scaffolding or competing endogenous RNAs. Our work is a first attempt to quantify the extent of gene expression control exerted globally by lncRNAs, especially those located proximally to their regulatory targets, in a specific biological (breast cancer) context. It also marks a first step towards systematic reconstruction of lncRNA regulatory networks, going beyond the current paradigm of co-expression networks, and motivates future analyses assessing the generalizability of our findings to additional biological contexts.

Thermodynamic Geometry of Nonequilibrium Fluctuations in Cyclically Driven Transport.

Nonequilibrium thermal machines under cyclic driving generally outperform steady-state counterparts. However, there is still lack of coherent understanding of versatile transport and fluctuation features under time modulations. Here, we formulate a theoretical framework of thermodynamic geometry in terms of full counting statistics of nonequilibrium driven transports. We find that, besides the conventional dynamic and adiabatic geometric curvature contributions, the generating function is also divided into an additional nonadiabatic contribution, manifested as the metric term of full counting statistics. This nonadiabatic metric generalizes recent results of thermodynamic geometry in near-equilibrium entropy production to far-from-equilibrium fluctuations of general currents. Furthermore, the framework proves geometric thermodynamic uncertainty relations of near-adiabatic thermal devices, constraining fluctuations in terms of statistical metric quantities and thermodynamic length. We exemplify the theory in experimentally accessible driving-induced quantum chiral transport and Brownian heat pump.

Enhanced predictive optimization of methane dry reforming via ResponseSurface methodology and artificial neural network approaches: Insights using a novel nickel-strontium-zirconium-aluminum catalyst

This study investigates the molecular dynamics of methane dry reforming catalyzed by a novel nickel-strontium-zirconium-aluminum (5Ni+3Sr/10Zr+Al) catalyst, leveraging both Response Surface Methodology (RSM) and Radial Basis Function Neural Network (RBFNN) for predictive optimization. Focusing on the impact of operational parameters—hourly space velocity, reaction temperature, and CO2:CH4 mole ratio—on the conversion rates and formation of reaction components, we aim to predict optimal conditions and corresponding process variables. Through a comparison of a three-layer Feed Forward Neural Network, optimized at a 3:10:1 topology, with traditional RSM approaches, our findings highlight the superior predictive capabilities of ANN models. Notably, ANN demonstrated exceptional performance with Radj2and F_Ratio values significantly surpass those of RSM, alongside lower statistical error terms. This superiority is attributed to ANN's robust handling of nonlinear relationships between inputs and outputs, asserting its potential for enhancing predictive accuracy in chemical process optimization. At optimum predicted conditions like 1 CH4/CO2,750 °C reaction temperature, 12000 cm3g−1h−1 space velocity, NiSrZrAl outperformed with > 85 % CH4 and CO2 conversion with H2/CO ∼1 up to 20 h time on stream. Our research underscores the importance of integrating advanced modeling techniques for the efficient and accurate prediction of catalytic reactions, offering valuable insights for future applications in chemical engineering and catalysis.

Influence of Loan Size on Growth of Women Entrepreneurship in Rubirizi District, Uganda

Women have actively participated in the economic development of many nations. However, women-owned enterprises have continued to face tough competition in the market. Resultantly, most of their businesses collapse at the infancy stage leaving many women languishing in poverty. This is against the Sustainable Development Goals (SDGs), especially on poverty (SDG 1), zero hunger (SDG 2), and gender equality (SDG 5). This study sought to evaluate the influence of loan sizes on the growth of women entrepreneurship in Rubirizi District in Uganda. The study specifically sought to examine the extent to which loan size affects the growth of women entrepreneurship in the Rubirizi District of Uganda. The study was anchored on a Resource Based Theory. The study adopted a quantitative approach while a descriptive research design was used to describe the respondents’ opinions numerically in statistical terms. The target population constituted 3720 participants from which a sample size of 361 was selected using the Sloven formula. Primary data was collected using structured questionnaires framed on a Likert scale of 1-5. Respondents were selected randomly using stratified and simple random sampling techniques. Quantitative data was analyzed using descriptive and inferential statistics. Descriptive statistics analyzed the responses obtained from the research questions while inferential statistics showed the influence of the independent variables on the dependent variable. The null hypothesis was tested at a 0.05 significance level. The analyzed data was displayed by use of suitable frequency distribution tables. The results showed that loan size is statistically insignificant in the growth of women entrepreneurship (P=.334, P>0.05). The study concluded that there is no statistically significant relationship between loan sizes obtained from Village Saving Loan Associations and the growth of women's entrepreneurship. Keywords: Entrepreneurship, Loan Size, Growth, Village Savings, Loan Associations

Influence of Advisory Services on the Growth of Women Entrepreneurship in Rubirizi District, Uganda

The participation of women in the economic development of many nations has been vital. Their role in the economy has been addressed in many international, regional and national development goals, including Sustainable Development Goals (SDGs) of the United Nations. Consequently, many nations have initiated and supported entrepreneurial activities meant to uplift the status of women to move out of poverty (SDG1), attain gender parity(SDG 5) and reduce inequality (SDG10) in the economic possessions. In Uganda, this agenda is being implemented by Village Savings and Loan Association Services (VSLAs), among other initiatives. Despite these strategies, women in Uganda continue to languish in poverty. Most of their businesses collapse at infancy leaving many women economically hopeless more so in rural areas. This study therefore sought to assess the influence of advisory services on the growth of women entrepreneurship in Rubirizi District in Uganda. The study specifically sought to examine the extent to which advisory services influence growth of women entrepreneurship in Rubirizi District of Uganda. The study was anchored on a Resource Based Theory. The study adopted a quantitative approach while a descriptive research design was used to describe the respondents’ opinions numerically in statistical terms. The target population constituted 3720 participants from which a sample size of 361 was selected using Sloven formula. Primary data was collected using structured questionnaires framed on a Likert scale 1-5. Respondents were selected randomly using stratified and simple random sampling techniques. Quantitative data was analysed using descriptive and inferential statistics. Descriptive statistics analysed the responses obtained from the research questions while inferential statistics showed the influence of the independent variables on the dependent variable. The null hypothesis was tested at 0.05 significance level. The analysed data was displayed by use of suitable frequency distribution tables. The results showed that advisory services are statistically significant on growth of women entrepreneurship (t=9.118, P=.000, P<.05). The study concluded that there is a strong positive significant relationship between advisory services offered to women beneficiaries of VSLAs and growth of women entrepreneurship. Keywords: Entrepreneurship, Advisory Services, Growth, Village Savings, Loan Associations

Semantic analysis of two-syllabic terms of metrology. Part 2: Risk in measurements and calculations

Prior to the requirement for testing and calibration laboratories to take into account the risk of statistical assumptions, false positive and false negative decisions in international documents, it was found that the methodology of the “Guide to Expressing Measurement Uncertainty” based on the Bayes approach and the Monte Carlo method for calculating probabilistic risk characteristics is not applicable. A later draft revision of the “Manual on the Expression of Measurement Uncertainty” attempted to shift the interpretation of measurement uncertainty from the scattering parameter to the probability distribution. An attempt to contribute to solving the problem of definitional uncertainty in the International Dictionary of Basic and Basic Terms of Metrology was also unsuccessful. In the new version of the dictionary of general statistical terms and probability theory terms, the term measurement uncertainty is excluded, and one of the notes states that “the probability distribution fully describes the probabilistic properties of the uncertainty of the result”. However, due to the new requirements for risk calculations, international documents were urgently put into effect without radical assessments of the inapplicability of the Bayes approach and the Monte Carlo method, the disadvantages were renamed limitations, but there are no specific instructions for calculating risks. Based on the experience of the compositional approach to estimating accuracy, a procedure based on the convolution of probability distributions in the form of a modified reversal formula is recommended, which allows taking into account the definitive uncertainty in the moment approach. It is established that the method of accounting for the definitive uncertainty by convolution of uniform distributions is practically suggested in the text of the “Manual on the expression of measurement uncertainty”, but not used.

Effect of Microstructure on the Precipitation of β-Mg2Si during Cooling after Homogenisation of Al-Mg-Si Alloys

For Al-Mg-Si alloys, cooling after homogenisation is a crucial step because the precipitation of the equilibrium β-Mg2Si phase determines the processing capabilities in subsequent steps, as well as the subsequent precipitation age hardening potential, and thus, the final properties. It is therefore important to understand how microstructural variations affect the transformation of β-Mg2Si during cooling after homogenisation. In the present work, alloys with similar effective solute contents of Mg and Si, but with different microstructures and a different amount of primary Al-Fe-Si phases, were produced. Characterisation of the precipitation reaction was performed using interrupted quench experiments with cooling rates of 1–6 K/min, monitored by light optical microscopy (LOM), scanning electron microscopy (SEM) and conductivity measurements. Precipitation kinetics for β-Mg2Si was found to increase in microstructures with shorter secondary dendrite arm spacing (DAS). However, despite measuring both a higher density and volume fraction of the primary phases, no effect on the phase transformation from an increased iron content was found in terms of precipitation kinetics or particle count statistics. Furthermore, comparisons with iron-free high-purity-based alloys revealed that the precipitation reaction for β-Mg2Si was identical in the two different microstructures both in terms of onset temperature and overall kinetics. The present results show that nucleation of β-Mg2Si is not dependent on the larger constituent phases and indicates that overall transformation kinetics is governed by bulk diffusion rates.

Deep learning and atlas-based models to streamline the segmentation workflow of total marrow and lymphoid irradiation.

To improve the workflow of total marrow and lymphoid irradiation (TMLI) by enhancing the delineation of organs at risk (OARs) and clinical target volume (CTV) using deep learning (DL) and atlas-based (AB) segmentation models. Ninety-five TMLI plans optimized in our institute were analyzed. Two commercial DL software were tested for segmenting 18 OARs. An AB model for lymph node CTV (CTV_LN) delineation was built using 20 TMLI patients. The AB model was evaluated on 20 independent patients, and a semiautomatic approach was tested by correcting the automatic contours. The generated OARs and CTV_LN contours were compared to manual contours in terms of topological agreement, dose statistics, and time workload. A clinical decision tree was developed to define a specific contouring strategy for each OAR. The two DL models achieved a median [interquartile range] dice similarity coefficient (DSC) of 0.84 [0.71;0.93] and 0.85 [0.70;0.93] across the OARs. The absolute median Dmean difference between manual and the two DL models was 2.0 [0.7;6.6]% and 2.4 [0.9;7.1]%. The AB model achieved a median DSC of 0.70 [0.66;0.74] for CTV_LN delineation, increasing to 0.94 [0.94;0.95] after manual revision, with minimal Dmean differences. Since September 2022, our institution has implemented DL and AB models for all TMLI patients, reducing from 5 to 2h the time required to complete the entire segmentation process. DL models can streamline the TMLI contouring process of OARs. Manual revision is still necessary for lymph node delineation using AB models.

Predicting the Type of Narrow Bipolar Pulse: A Machine Learning Approach

Narrow Bipolar Pulses (NBP) depicts the electric field (E-Field) changes due to a Compact Intra-cloud Discharge (CID) and are of two types namely Positive NBP (PNBP) and Negative NBP (NNBP). In this study, 437 NBPs were statistically investigated using a dataset collected in Sri Lanka in 2013, 2015, 2016 and 2017. Seven independent variables (Pulse Duration (PD), Rise Time (RT), Slow Front Duration (SFD), Zero Crossing Time (ZCT), Full Width at Half Maximum (FWHM) and Ratio between the Initial and Overshoot Peak Amplitudes (RIOPA)) and one dependent variable (Type of NBP) were analyzed. Two machine learning classification models, the Random Forest (RF) model and the Binary Logistic Regression (BLR) model, were used to predict the dependent variable based on the independent variables. Two models were compared in terms accuracy (ACC), sensitivity (SE), specificity (SP), AUC (Area Under the Curve)-ROC (Receiver Operator Characteristic) curve and kappa statistic. RF model scored the highest in terms of ACC (0.91), specificity (0.94), Kappa statistics (0.82) and AUC (0.98). In conclusion, RF model had the best performance in predicting the type of NBP hence can be used as a suitable automated method to classify the type of NBP.

Q,t$q,t$‐Catalan measures

AbstractWe introduce the ‐Catalan measures, a sequence of piece‐wise polynomial measures on . These measures are defined in terms of suitable area, dinv, and bounce statistics on continuous families of paths in the plane, and have many combinatorial similarities to the ‐Catalan numbers. Our main result realizes the ‐Catalan measures as a limit of higher ‐Catalan numbers as . We also give a geometric interpretation of the ‐Catalan measures. They are the Duistermaat–Heckman measures of the punctual Hilbert schemes parametrizing subschemes of supported at the origin.

An Adaptive Moving Window Kriging Based on K-Means Clustering for Spatial Interpolation

Ordinary kriging (OK) is a popular interpolation method for its ability to simultaneously minimize error variance and deliver statistically optimal and unbiased predictions. In this work, the adaptive moving window kriging with K-means clustering (AMWKK) technique is developed to improve the estimation obtained from the moving window kriging based on the K-means clustering proposed by Abedini et al. This technique specifically addresses the challenge of selecting appropriate windows for target points located near the borders, which can potentially be the source of errors. The AMWKK algorithm introduces a dynamic clustering approach within the moving window kriging, where each target site sequentially serves as a cluster centroid. The OK is then applied within the cluster encompassing the target point, ensuring localized and adaptive interpolation. The proposed method is compared with ordinary kriging and other moving window kriging variant approaches to estimate Thailand’s mean annual pressure and humidity in 2018. The results indicate superior estimation capabilities of the AMWKK approach in terms of distinct quantitative performance statistics. The advantage of using the AMWKK method for spatial interpolation can be attributed to the fact that it facilitates the automatic tuning of the window size at any estimation point. The algorithm is particularly effective when observations in the same cluster as target points are sparse.

A new enhanced mountain gazelle optimizer and artificial neural network for global optimization of mechanical design problems

Abstract Nature-inspired metaheuristic optimization algorithms have many applications and are more often studied than conventional optimization techniques. This article uses the mountain gazelle optimizer, a recently created algorithm, and artificial neural network to optimize mechanical components in relation to vehicle component optimization. The family formation, territory-building, and food-finding strategies of mountain gazelles serve as the major inspirations for the algorithm. In order to optimize various engineering challenges, the base algorithm (MGO) is hybridized with the Nelder–Mead algorithm (HMGO-NM) in the current work. This considered algorithm was applied to solve four different categories, namely automobile, manufacturing, construction, and mechanical engineering optimization tasks. Moreover, the obtained results are compared in terms of statistics with well-known algorithms. The results and findings show the dominance of the studied algorithm over the rest of the optimizers. This being said the HMGO algorithm can be applied to a common range of applications in various industrial and real-world problems.