Methods Of Analyses Research Articles

Improving the methodology for assessing the effectiveness of State and municipal procurement

Subject. This article considers the problem of efficient budget funds spending, creation of a unified system of accounting for public procurement, and meeting the needs of society. Objectives. The article aims to develop a system of indicators that should be taken into account to assess the effectiveness of public procurement at the present stage of development of the Russian economy. Methods. For the study, we used the methods of logical and statistical analyses. Results. The article analyzes the methodology for assessing the effectiveness of public procurement developed by the Federal Antimonopoly Service of the Russian Federation. The article proposes the author-developed approach to improve the methodology mentioned. Conclusions. At present, there is a need to develop a universal approach to assess the effectiveness of State and municipal procurement.

Industrial hydrocarbon production and the new opportunities for green energy

Subject. This article discusses the issues of development of the petrochemical and oil refining industry of the Republic of Bashkortostan. Objectives. The article aims to assess the prospects for the use of renewable energy sources and the modernization of traditional manufacturing industries. Methods. For the study, we used the methods of graphic and statistical analyses. Results. The article finds that with the depletion of proven oil reserves in the Republic of Bashkortostan, the fuel balance can be restored through oil supplies from the Arctic areas and that the development of green energy in the region is primarily associated with the production of composite fuel. Relevance. The results of the study can be used when designing plans for the production of innovative products by enterprises of the fuel and energy complex.

Images of a Good and Evil Person in Russian and Chinese Paremiological Pictures of the World

The linguoculturological studies in paremiology make one of the most actively developing, researchers have repeatedly analyzed the concepts of GOOD and EVIL on the material of paremias of a particular language. However, the study of character traits «good» and «evil» on the basis of the proverbs of the Russian and Chinese languages has not yet been considered, which is the novelty of this study. The article studies paremiological units of the Russian and Chinese languages, representing a good and evil person. The goal of the work is to identify common and peculiar ethno-specific features reflected in the proverbs of the Russian language against the background of their counterparts in the Chinese language, as well as to establish their motivation. To achieve this goal, methods of comparative and linguoculturological analyses were applied. The sources of the material were the proverbs dictionary, as well as data from Russian and Chinese corpora. The paper concludes that there are much more different cultural attitudes contained in the proverbs we are interested in than common ones, which causes a big difference in understanding the character traits of «good» and «evil» between native Russian and Chinese speakers. Understanding the universal and nationally marked ideas of Russians and Chinese effectively contributes to cultural communication between peoples.

Lexico-Semantic Group of Verbs of Interpersonal Relations in Russian and Chinese: based on the Translation of F.M. Dostoevsky’s Novel “Crime and Punishment”

This study is devoted to the analysis of lexico-semantic group of verbs, which express attitude to someone in Russian and the ways of their translation into Chinese. A group of emotional and evaluative verbs included in the lexico-semantic field of interpersonal relations is analyzed. The choice of the study material is determined by the fact that this group of verbs is one of the most frequent in the use and widely represented in the novel “Crime and punishment” by F.M. Dostoyevsky, occurring 561 times. The significance of this research lies in the absence of a special systematic study of this lexico-semantic group on the material of literature in Russian and Chinese languages, as well as in the need to develop a comprehensive research methodology, methods of comparative and contextual analyses. The study reveals the semantic features of verbs in the Russian and Chinese languages. It is established that the lexico-semantic group under study consists of verbs that are perceived as categorical-lexical semes “relation” and can have both positive and negative semantic meaning. The semes ‘positive attitude’, ‘love’, ‘faith’, ‘respect’, ‘compassion’, ‘pity’ and ‘negative attitude’, ‘suffering’, ‘doubt’, ‘fear’ are subjected to study. These features determine the structure of the group in question in the lexical and semantic system of the Russian and Chinese languages, are expanding the understanding of the content and structure of the group of verbs. The result of the study is that the analysis of interlingual gaps reveals the presence of incomplete lexical correspondence to a foreign language word. The analyzed linguistic material made it possible to identify similarities and differences in the semantics of verbs when translating the text of the novel into Chinese.

Comparing of CFD Contours Using Image Analysing Method: A Study on Velocity Distributions

Contour plotting, a widely utilized graphical technique for visualizing CFD (Computational Fluid Dynamics) outcomes, is highly valuable. It provides an effective and practical approach to analysing distributions of magnitudes belonging to fluid domains such as; velocity, temperature, pressure, volume fraction, etc. Nevertheless, when analysing multiple contours, especially showing similar distribution, identifying the ideal contour can be difficult and open to speculation. In this research, the issue was addressed by employing the Image Analysis Method for the classification of velocity distribution contours. This led to determining which picture has the best distribution among a few of the contour’s pictures. Firstly, velocity distribution contours downstream of the diffuser located in Air Handling Unit (AHU) unit were obtained by using CFD. The contour pictures were then transferred to MATLAB environment. With pixel analysis in MATLAB, the pictures were able to be classified based on which parameters had an effect on the velocity distribution. Variable parameters are the length of the fan channel (x) and the ratio of cross-sectional areas of the AHU (A/Ao). The results showed that x=250 mm and A/Ao=0.5 improved velocity distributions by 6% and 20%, respectively.

Arctium lappa root extract based emulgels attenuate inducible cytokines and prostaglandins formation: Potential in the management of chronic inflammatory disorders

BackgroundChronic inflammation contributes significantly to the burden suffered in many disease conditions in Africa with modern treatments often inaccessible to many. Phytotherapy presents a useful way to accelerate access to Universal health coverage with minimal incurred costs. The study was aimed at exploring the in vitro anti-inflammatory action and formulation of Arctium lappa root, a plant grown and available in different regions in Africa, as an herbal emulgel for the management of chronic inflammation MethodsMethanol root extract of Arctium lappa (0.25, 0.50 and 1.00 % w/w) was used for pre-formulation analysis. Phytochemical screening of the extract was done using the Harborne's standardized method for phytochemical analyses. In vitro anti-inflammatory activity was studied by evaluating inhibitory actions of the extracts on Prostaglandin-E (PGE), tumour necrotic factor-α (TNF-α) and cyclooxygenase II (COX-2) using Enzyme-Linked Immunosorbent Assay. Post formulation, the percentage inhibition of the pro-inflammatory cytokines by the herbal emulgels were compared with commercial diclofenac emulgel. The physicochemical properties of the herbal emulgels were also determined. ResultsThe preliminary qualitative phytochemical analysis of Arctium lappa root extract gave tannins, saponins, phenolics, steroids, glycosides, flavonoids, anthocyanin, terpenoids, and alkaloids as its contents. The extract's inhibitory activities on PGE-2, COX-2 and TNF-α were dose dependent. The formulated herbal emulgel showed that the activities of PGE-2, COX-2 and TNF-α were significantly inhibited in comparison with vehicle-treated control. The physical appearance (which reflected the concentration gradient of the Arctium lappa root extract in the emulgels), consistency and homogeneity of the emulgels were acceptable and spreadable. The pH and viscosity of the emulgels were from 4.97 ± 0.04 to 5.42 ± 0.05 and 3.36 ± 0.40 and 3.95 ± 0.50 Pas, respectively. ConclusionHere, the emulgel of Arctium lappa root extract showed promising anti-inflammatory property evidenced in its ability to attenuate PGE-2, COX-2 and TNF-α activities in-vitro, which was similar to the effect of diclofenac (a currently used anti-inflammatory agent of synthetic origin). This study is novel, important and of great impact because it provides a useful indication of Arctium lappa as a topical agent in the management of chronic inflammatory disorders. As compared to previous studies, key advances in this research include the first successful attempt to formulate the root extract of Arctium lappa into an emulgel, advancing the application of pharmaceutics in phytotherapy for prospects of improved treatment of inflammation, especially in Africa; and this can be adapted globally beyond the region.

Conducting a bayesian multi-armed trial with response adaptive randomization for comparative effectiveness of medications for CSPN

BackgroundResponse adaptive randomization is popular in adaptive trial designs, but the literature detailing its execution is lacking. These designs are desirable for patients/stakeholders, particularly in comparative effectiveness research, due to the potential benefits including improving participant buy-in by providing more participants with better treatment during the trial. Frequentist approaches have often been used, but adaptive designs naturally fit the Bayesian methodology; it was developed to deal with data as they come in by updating prior information. MethodsPAIN-CONTRoLS was a comparative-effectiveness trial utilizing Bayesian response adaptive randomization to four drugs, nortriptyline, duloxetine, pregabalin, or mexiline, for cryptogenic sensory polyneuropathy (CSPN) patients. The aim was to determine which treatment was most tolerable and effective in reducing pain. Quit and efficacy rates were combined into a utility function to develop a single outcome, which with treatment sample size, drove the adaptive randomization. Prespecified interim analyses allowed the study to stop for early success or update the randomization probabilities to the better-performing treatments. ResultsSeven adaptations to the randomization occurred before the trial ended due to reaching the maximum sample size, with more participants receiving nortriptyline and duloxetine. At the end of the follow-up, nortriptyline and duloxetine had lower probabilities of participants that had stopped taking the study medication and higher probabilities were efficacious. Mexiletine had the highest quit rate, but had an efficacy rate higher than pregabalin. ConclusionsResponse adaptive randomization has become a popular trial tool, especially for those utilizing Bayesian methods for analyses. By illustrating the execution of a Bayesian adaptive design, using the PAIN-CONTRoLS trial data, this paper continues the work to provide literature for conducting Bayesian response adaptive randomized trials.

Electronic governancе in the human capital assessment system

Current affairs in our country necessitate the introduction of effective steps for the post-war restoration of various spheres of the state and society. One of the most important aspects of Ukraine’s post-war restoration is currently considered to be the recovery of human capital, which will have a positive impact on improving various aspects of the state’s functioning. At the same time, it is important to continuously assess human capital by determining the relevant indexes, which should be facilitated by electronic governance. The aim of the research is to study the possibility of using electronic governance in Ukraine as a tool for reflecting the process of post-war recovery of human capital. The research was conducted using methods of theoretical generalization, compara­tive and systemic analyses, modeling. The paper analyzed the concept of human capital as a special type of capital that is expressed in the form of intellectual abilities and practical skills that were acquired in the process of education and practical activity of a person. The state of human capital in Ukraine before the war, which remained relatively stable until 2021, and during the war period, when there were noticeable losses of human capital under the influence of various factors, were analyzed. The prospect of post-war recovery of human capital was considered, with special attention. In addition, the concept and features of electronic governance as a tool for reflecting the recovery of human capital and one of the strategies for Ukraine’s post-war restoration were consi­dered. The dynamics of the Human Capital Index in Ukraine for 2010–2021 was analyzed. It was found that electronic governance, by analyzing data from official sources, makes it possible to calculate the Human Capital Index. It was noted that Big Data and artificial intelligence can be used to determine changes in human capital, which is possible due to the availability of electronic governance. The results allow us to state that there are significant opportunities to use electronic governance to assess human capital with a reflection of its post-war recovery.

Bayesian inference of transition matrices from incomplete graph data with a topological prior

Many network analysis and graph learning techniques are based on discrete- or continuous-time models of random walks. To apply these methods, it is necessary to infer transition matrices that formalize the underlying stochastic process in an observed graph. For weighted graphs, where weighted edges capture observations of repeated interactions between nodes, it is common to estimate the entries of such transition matrices based on the (relative) weights of edges. However in real-world settings we are often confronted with incomplete data, which turns the construction of the transition matrix based on a weighted graph into an inference problem. Moreover, we often have access to additional information, which capture topological constraints of the system, i.e. which edges in a weighted graph are (theoretically) possible and which are not. Examples include transportation networks, where we may have access to a small sample of passenger trajectories as well as the physical topology of connections, or a limited set of observed social interactions with additional information on the underlying social structure. Combining these two different sources of information to reliably infer transition matrices from incomplete data on repeated interactions is an important open challenge, with severe implications for the reliability of downstream network analysis tasks.Addressing this issue, we show that including knowledge on such topological constraints can considerably improve the inference of transition matrices, especially in situations where we only have a small number of observed interactions. To this end, we derive an analytically tractable Bayesian method that uses repeated interactions and a topological prior to perform data-efficient inference of transition matrices. We compare our approach against commonly used frequentist and Bayesian approaches both in synthetic data and in five real-world datasets, and we find that our method recovers the transition probabilities with higher accuracy. Furthermore, we demonstrate that the method is robust even in cases when the knowledge of the topological constraint is partial. Lastly, we show that this higher accuracy improves the results for downstream network analysis tasks like cluster detection and node ranking, which highlights the practical relevance of our method for interdisciplinary data-driven analyses of networked systems.

Qualitative and quantitative comparison of two semi-manual retinal vascular density analyzing methods on optical coherence tomography angiography images of healthy individuals

The aim of this study was to evaluate qualitative and quantitative differences in vascular density analysis of an established and a novel alternative for post-processing on optical coherence tomography angiography (OCTA) images in healthy individuals. OCTA examinations of 38 subjects were performed. After extracting the images, two semi-manual post-processing techniques, the already established Mexican hat filtering (MHF) and an alternative, the Shanbhag thresholding (ST) were applied. We assessed Vessel Density (VD), Skeleton Density (SkD) and Vessel Diameter Index (VDI). We analyzed the results in order to establish similarities or potentially relevant differences. Regarding SkD and VD, MHF generally gave higher values than ST. Simultaneously, mean values were also predominantly higher by MHF; however, standard deviations (SD) were higher by ST (range [mean ± SD]: 0.054 ± 0.038 to 0.134 ± 0.01 and 0.134 ± 0.095 to 0.362 ± 0.028 vs 0.012 ± 0.014 to 0.087 ± 0.03 and 0.039 ± 0.047 to 0.4 ± 0.095 for SkD and VD with MHF vs SkD and VD with ST, respectively). Values of VDI were considerably higher with ST than with MHF, while standard deviation was still significantly higher with ST (range [mean ± SD]: 2.459 ± 0.144 to 2.71 ± 0.084 and 2.983 ± 0.929 to 5.19 ± 1.064 for VDI with MHF and ST, respectively). The noise level reduction of the two methods were almost identical (noise levels: 65.8% with MHT and 65.24% with ST). Using MHF, the vascular network gets more fragmented by an average of 40% compared to ST. Both methods allow the segmentation of the vascular network and the examination of vascular density parameters, but they produce largely inconsistent results. To determine if these inconsistent results are clinically meaningful, and which method is more suitable for clinical use, our results provide further evidence that detailed understanding of the image analysis method is essential for reliable decision making for patients with retinal pathology. For longitudinal monitoring, use of the same image processing method is recommended.

An experimental platform for stochastic analyses of single serotonergic fibers in the mouse brain.

The self-organization of the serotonergic matrix, a massive axon meshwork in all vertebrate brains, is driven by the structural and dynamical properties of its constitutive elements. Each of these elements, a single serotonergic axon (fiber), has a unique trajectory and can be supported by a soma that executes one of the many available transcriptional programs. This "individuality" of serotonergic neurons necessitates the development of specialized methods for single-fiber analyses, both at the experimental and theoretical levels. We developed an integrated platform that facilitates experimental isolation of single serotonergic fibers in brain tissue, including regions with high fiber densities, and demonstrated the potential of their quantitative analyses based on stochastic modeling. Single fibers were visualized using two transgenic mouse models, one of which is the first implementation of the Brainbow toolbox in this system. The trajectories of serotonergic fibers were automatically traced in the three spatial dimensions with a novel algorithm, and their properties were captured with a single parameter associated with the directional von Mises-Fisher probability distribution. The system represents an end-to-end workflow that can be imported into various studies, including those investigating serotonergic dysfunction in brain disorders. It also supports new research directions inspired by single-fiber analyses in the serotonergic matrix, including supercomputing simulations and modeling in physics.

Strain regularisation using a non-local method in Coupled Eulerian-Lagrangian analyses

Conventional finite element analyses generally suffer from mesh dependency when considering softening effects. Non-local strain regularisation techniques have been developed to address this issue, which are generally complex to implement. In view of this, this paper introduces an more efficient procedure for implementation of a non-local method in Abaqus for Coupled Eulerian-Lagrangian (CEL) large deformation finite element undrained analyses. Results from a series of biaxial compression simulations demonstrate that the non-local method with a strain-softening Tresca model in CEL avoids mesh dependency. Owing to the stationary Eulerian element and the built-in mapping algorithm in CEL, high computational efficiency is achieved, adding no more than 12% to the computational cost. Guidance is provided on selection of internal length scales, element sizes and the search radius to ensure efficient non-local calculations, and it is shown that a softening scaling rule can also be used to allow use of practical mesh densities for some boundary value problems. Simulations of a number of classical geotechnical problems demonstrate the type of boundary value problems where the non-local method can effectively mitigate the mesh dependency, whilst also highlighting that the method fails to control the strain localisation that develops at soil-structure interfaces due to geometrical issues.

Direct Probability Integral Method for Seismic Performance Assessment of Earth Dam Subjected to Stochastic Mainshock–Aftershock Sequences

Studying the impact of mainshock–aftershock sequences on dam reliability is crucial for effective disaster prevention measures. With this purpose in mind, a new method for stochastic dynamic response analyses and reliability assessments of dams during seismic sequences has been proposed. Firstly, a simulation method of stochastic seismic sequences is described, considering the dependence between mainshock and aftershock based on Copula function. Then, a novel practical framework for stochastic dynamic analysis is established, combined with the improved point selection strategy and the direct probability integration method (DPIM). The DPIM is employed on a nonlinear system with one degree of freedom and compared with Monte Carlo simulation (MCS). The findings reveal that the method boasts exceptional precision and efficiency. Finally, the seismic performance of a practical dam was evaluated based on the above method, which not only accurately estimates the response probability distribution and dynamic reliability of the dam, but also greatly reduces the required calculations. Furthermore, the impact of aftershocks on dam seismic performance is initially evaluated through a probability approach in this research. It is found that seismic sequences will significantly increase the probability of earth dam failure compared with sequences of only mainshocks. In addition, the influence of aftershocks on reliability will further increase when the limit state is more stringent. Specifically, the novel analysis method proposed in this paper provides more abundant and objective evaluation indices, providing a dynamic reliability assessment for dams that is more effective than traditional evaluation methods.

Tatar appellatives in G. Yakhina’s novel “Zuleikha Opens Her Eyes”: polylinguality and transculturality

The article is devoted to the linguocultural meanings of nationally specific forms of vocatives used by G. Yakhina in her novel “Zuleikha Opens Her Eyes”. The research object is the corpus of language units, used in G. Yakhina’s novel “Zuleikha Opens Her Eyes”, which are selected by continuous sampling from the first part of the novel. To analyze the studied units (appellatives), we use the descriptive and comparative methods, the method of word-formation, component and contextual analyses, as well as the method of quantitative calculation. To reconstruct the world of the Tatar village, the Russian-speaking writer uses a variety of appellative words (exoticisms, diminutives, evaluative forms, etc.), which do not always adequately appeal to the content of the Tatar linguocultural discourse. In the present article, we examine appellatives, in the unity of their form and content, as units of a particular literary text in order to identify their semantic specificity, stylistic and linguocultural affiliation, while taking into account the context of their use. The transformation and substitution of linguistic units, associated with the national specificity of the linguistic picture of the world, prevents adequate and accurate perception of Tatar linguistic culture when the author creates artistic images in her novel, or subsequently conveys the meaning in translation. Thus, the article shows how the words of a foreign culture are introduced into the text and what consequently happens to the meanings they convey.

An analysis of the Vodolazkin’s novel "The Aviator" in senior high school

The study of the semiotic space of literature still remains interesting and in demand, and the semiotic analysis has proved to be a rather successful method in the collection of methods of a literature teacher at school. In the article, the author proceeds from the necessity of using a complex analysis of a fiction text based to a greater extent on semiotic consideration, which includes, in addition to semiotic analysis, analysis of biographical context and partly philological analysis, in senior high schools. The author substantiates the necessity of introducing such a method in the study of modern literature, showing it on the example of complex analysis of the Evgeny Vodolazhkin’s novel "The Aviator". Thus, the aim of the study is to describe the application of the method of semiotic analysis (in combination with others) of works of fiction in the course of literature in senior high school. The relevance of the chosen topic in the novelty of the researched material: the text of the novel. Modern literature still needs a comprehensive study. The novelty of the article consists in the chosen approach to the analysis of the novel with the use of semiotic arsenal of means, as well as in the description of the application of the novel's material in the curriculum at the lessons of literature in senior high school. Using the methods of semiotic, philological and contextual analyses, the author developed a literature lesson plan for the 11th grade of a comprehensive school. This plan can be used in practice, which will allow a teacher supplement and expand the school study of modern literature by a popular new author. As a result of the analysis, it was concluded that this kind of complex analysis of modern fiction can reveal lines of interconnection and continuity with classical literature. Finding such intertextual links with both Russian classical and world literature will allow students to build a logical and coherent picture of the development of the literary process up to the modern stage. As a result of the analysis, the conclusion is made about didactic applicability of the text of the novel in the practice of teaching literature, and the novel itself is presented within the framework of the analysis as a rather complex and rich artistic work in terms of meaning, involving numerous interpretations.

Development and validation of stability indicating UPLC methods for related substances and assay analyses of ricobendazole hydrochloride

Ricobendazole hydrochloride is an active ingredient of a veterinary antiparasitic drug. The aim of this study was to investigate the degradation of ricobendazole hydrochloride under stress and stability testing conditions, for which we developed and validated the first stability indicating, specific, precise, accurate, and robust assay and related substances UPLC methods. The Acquity UPLC BEH C18 column was used for the related substances and assay analyses of ricobendazole hydrochloride, and the analyses were performed at 25 °C sample and 30 °C column temperatures with a 2 µL injection volume. In both methods, a mixture of water and methanol (60:40, v/v) was used as the diluent, mobile phase A was a phosphate buffer (50 mM potassium dihydrogen phosphate solution, pH 3.2 ± 0.05, adjusted with 10% o-phosphoric acid), and mobile phase B was a mixture of mobile phase A and acetonitrile (50:50, v/v). For the analysis of related substances, a gradient elution system was used at a flow rate of 0.4 mL/min for 35 min with a detection wavelength of 220 nm, while for the assay analysis; a gradient elution system was used at a flow rate of 0.3 mL/min for 15 min with a detection wavelength of 290 nm. The calibration curves showed excellent linearity with high R-squared (R2) values for each compound, ricobendazole (0.9998, 0.249 – 3.740 µg/mL), ricobendazole amine (0.9998, 0.255 – 3.819 µg/mL), albendazole (0.9998, 0.255 – 7.646 µg/mL), and albendazole sulfone (1.0000, 0.251 – 15.090 µg/mL) indicating a strong correlation between the concentrations of the compounds and their respective peak areas in the UPLC analysis. The method showed excellent accuracy with relative standard deviation values of less than 2.5%. The stress and photostability studies showed that ricobendazole hydrochloride was insensitive to daylight and UV radiation and showed significant degradation at elevated temperature (85 °C, 9 days) and under all hydrolysis and oxidation conditions. The major impurity was ricobendazole amine under thermal and hydrolysis conditions, while albendazole sulfone was the major oxidative impurity.

Establishment of Analyzing Method of Fenpropathrin Residue in Angelica dahurica Radix and Osterici Radix

Background: Angelica dahurica Radix and Osterici radix, are perennial herbs belonging to the family Umbelliferae, which were attacked by red spiders, thus fenpropathrin was registered. Fenpropathrin is important in improving productivity and quality of medicinal herbs due to timely pest control. However, residue may likely remain after harvest, and therefore, the residue analysis is important to ensure pesticides safety management. Objective: This study aimed to establish analysis method for fenpropathrin residues in A. dahurica Radix and O. radix using GLC-ECD and GC-MS/MS. Methods: Samples were moisturized with distilled-water and extracted with acetonitrile. The interferences were removed using SPE cartridges and analyzed by GLC-ECD and GC-MS/MS. Results: Based on pre-experiment results, the analysis method was optimized using double-cleanup method (SPE-GCB/NH2 & SPE silica cartridges). Fenpropathrin peak confirmed by GC-MS at the same retention time and with its mass numbers. Nevertheless, the cleanup processes are laborious and require a rather long time. Thus, additional effortless analysis method was developed using the d-SPE method that can apply to highly selective and sensitive GC-MS/MS. The LOD of GC-ECD and GC-MS/MS was 0.1 and 0.01 ng, respectively. While the LOQ was 0.04 mg/kg for both. Linearity (r2) was > 0.998 (GLC-ECD) and 0.999 (GC-MS/MS). The recoveries at three spiking levels ranged 83.6-103.1% and 89.6-98.0% for A. dahurica Radix and O. radix, respectively. Conclusion: Accuracy of the improved method met the standard of the Korean Ministry of Food and Drug Safety. Therefore, the developed methods expected to be used for analyzing pesticide residues in herbal medicines in Korea and other countries.

Machine learning: Predicting hospital length of stay in patients admitted for lupus flares.

Although rare, severe systemic lupus erythematosus (SLE) flares requiring hospitalization account for most of the direct costs of SLE care. New machine learning (ML) methods may optimize lupus care by predicting which patients will have a prolonged hospital length of stay (LOS). Our study uses a machine learning approach to predict the LOS in patients admitted for lupus flares and assesses which features prolong LOS. Our study sampled 5831 patients admitted for lupus flares from the National Inpatient Sample Database 2016-2018 and collected 90 demographics and comorbidity features. Four machine learning (ML) models were built (XGBoost, Linear Support Vector Machines, K Nearest Neighbors, and Logistic Regression) to predict LOS, and their performance was evaluated using multiple metrics, including accuracy, receiver operator area under the curve (ROC-AUC), precision-recall area under the curve (PR- AUC), and F1-score. Using the highest-performing model (XGBoost), we assessed the feature importance of our input features using Shapley value explanations (SHAP) to rank their impact on LOS. Our XGB model performed the best with a ROC-AUC of 0.87, PR-AUC of 0.61, an F1 score of 0.56, and an accuracy of 95%. The features with the most significant impact on the model were "the need for a central line," "acute dialysis," and "acute renal failure." Other top features include those related to renal and infectious comorbidities. Our results were consistent with the established literature and showed promise in ML over traditional methods of predictive analyses, even with rare rheumatic events such as lupus flare hospitalizations.

The Relationship Between Entrepreneurial Orientation and Firm Performance From the perspective of MASEM: The Mediation Effect of Market Orientation and the Moderated Mediation Effect of Environmental Dynamism

This research introduces Meta-Analysis Structural Equation Modeling (MASEM), a novel method that integrates meta-analysis (MA) and structural equation modeling (SEM). The method helps researchers to comprehensively understand issues in the strategic management field. Applying MASEM to analyze data from 112 papers, covering 101,981 observations, the results can be summarized as follows. (1) Entrepreneurial orientation (EO) is significantly positively correlated with firm performance (FP), which addresses the issue of inconsistency among prior studies’ findings. (2) There is a significantly positive correlation between EO and market orientation (MO) and a significantly positive relationship between MO and FP, indicating that MO is a mediator variable to the EO-FP. (3) Environmental dynamism (ED) increases a positive link exists between MO and FP; in other words, compared to low ED, the presence of high ED enhances the correlation between MO and FP significantly. (4) ED influences the slope of MO’s function as a mediator between EO and FP - that is, high ED increases the slope of the intermediary effect of MO on the MO-FP nexus, and low ED reduces the slope of the mediation effect of MO on the MO-FP nexus. These findings provide new thoughts and insights for studies on the correlation between EO and FP and offer substantial suggestions for enterprises. The aforementioned results indicate that besides providing deeper insights and a more comprehensive understanding, MASEM presents deeper insights for researchers and is more efficient than the traditional meta-analysis method. Moreover, MASEM can be applied to in other fields and used with other methods for greater in-depth analyses. Overall, the MASEM technique herein has high reliability and validity when utilized for discussing relationships among variables and gives more comprehensive and accurate conclusions in theoretical and practical aspects.

Spatiotemporal cluster of mpox in men who have sex with men: A modeling study in 83 countries.

Mpox outbroke globally during 2022-2023, with more than 90% of cases occurring in men who have sex with men (MSM). However, the spatiotemporal distribution of mpox is not well established yet. This study aimed to explore the spatiotemporal clustering of mpox cases in MSM worldwide. We obtained the numbers of mpox cases from Our World in Data, the number of MSM from the Joint United Nations Programme on HIV/AIDS (UNAIDS), UNAIDS DATA 2021 and UNAIDS Global AIDS Update 2022 and literature. We evaluated the spatiotemporal cluster of mpox in MSM using retrospective space-time analyses method. The total number of mpox cases was 85 795 during May 1, 2022 to March 31, 2023. The most likely cluster was Spain (likelihood ratio = 4764.97; p < 0.001), with a cluster period from July 26 to August 14, 2022. There were 11 secondary clusters, which included 46 countries located in western Europe, eastern and northern South America, northern Europe, Canada, Central Africa, southern and central Europe, Latin America, Turkey, Dominican Republic, New Zealand, and Australia. The findings may inform current and future control strategies of mpox and might provide references for the identification of the spatiotemporal distribution of new and emerging infectious diseases in specific populations.