Rank Coefficient Research Articles

Multivariate spatiotemporal models with low rank coefficient matrix

Multivariate spatiotemporal models with low rank coefficient matrix

Access to healthcare services during the COVID-19 pandemic: a cross-sectional analysis of income and user-access across 16 economically diverse countries

BackgroundNational health systems have different strengths and resilience levels. During the COVID-19 pandemic, resources often had to be reallocated and this impacted the availability of healthcare services in many countries. To date there have been few quantitative contemporary studies of inequalities in access to healthcare within and between countries.In this study, we aim to compare inequality within and between 16 economically diverse countries.MethodsOnline surveys were conducted on 22 150 adults in 16 countries across six continents in 2022. Quota sampling and post-stratification weighting was used to obtain an age, gender, geographically, and educationally representative sample. The study assesses the differences in challenges in access to healthcare during the pandemic (for GP, surgical/clinical and digital GP services) using country-specific expanded health-needs-adjusted Erreygers’ concentration indices and compares these values between countries using a Spearman’s rank correlation coefficient.ResultsResults show wide variation in income-related challenges in access within countries for different types of care. For example, Erreygers’ concentration index for digital services in Colombia exhibited highly regressive inequality at 0·17, compared to Japan with an index of -0·15. Inequalities between countries were also evident, with Spearman rank coefficients of -0·69 and -0·65 (p-values of 0·003 and 0·006) for digital and surgical access, indicating that lower income countries had greater inequality in healthcare access challenges.ConclusionDuring the pandemic, inequalities in challenges to accessing healthcare were greatest in low and middle-income countries. Digital technologies offer a reasonable means to address some of this inequality if adequate support is provided and accessible digital infrastructure exists.

Assessing Team Performance in a Longitudinal Neonatal Resuscitation Simulation Training Program: Comparing Validity Evidence to Select the Best Tool.

Introduction Neonatal resuscitation is a high-acuity, low-occurrence event that requires ongoing practice by interprofessional teams to maintain proficiency.Simulation provides an ideal platform for team training and evaluation of team performance. Our simulation center supports a longitudinal in situ simulation training program for delivery room teams. In addition to adherence to the Neonatal Resuscitation Program standards, team performance assessment is an essential component of program evaluation and participant feedback. Multiple published teamwork assessment tools exist. Our objective was to select the tool with the best validity evidence for our program's needs. Methods We used Messick's framework to assess the validity of evidence for potential teamwork assessment tools. Four possible tools were identified from the literature: the Mayo High Performance Teamwork Scale (Mayo), Team Performance Observation Tool (TPOT), Clinical Teamwork Scale (CTS), and Team Emergency Assessment Measure (TEAM). Relevant context included team versus individual focus, external evaluator versus self-evaluation, and ease of use (which included efficiency, clarity of interpretation, and overall assessment). Three simulation experts identified consensus anchors for each tool and independently reviewed and scored 10 pre-recorded neonatal resuscitation simulations. Raters assigned each tool a rating according to efficiency, ease of interpretation, and completeness of teamwork assessment. Interrater reliability (IRR) was calculated using intraclass correlation for each tool across the three raters. Average team performance scores for each tool were correlated with neonatal resuscitation adherence scores for each video using Spearman's rank coefficient. Results There was a range of IRR between the tools, with Mayo having the best (single 0.55 and multi 0.78). Each of the three raters ranked Mayo optimally in terms of efficiency (mean 4.66 + 0.577) and ease of use (4+1). However, TPOT and CTS scored highest (mean 4.66 ± 0.577) for overall completeness of teamwork assessment. There was no significant correlation to NRP adherence scores for any teamwork tool. Conclusion Of the four tools assessed, Mayo demonstrated moderate IRR and scored highest for its ease of use and efficiency, though not completeness of assessment. The remaining three tools had poor IRR, which is not an uncommon problem with teamwork assessment tools. Our process emphasizes the fact that assessment tool validity is contextual. Factors such as a relatively narrow (and high) performance distribution and clinical context may have contributed to reliability challenges for tools that offered a more complete teamwork assessment.

The Departmental Scholarly Index: A Metric of Research Productivity.

While bibliometric ranking systems have been designed to use citations, funding, and alumni productivity, there is a need for a simple metric that objectively evaluates the work of a group or organization. The present study describes a bibliometric tool, the Departmental Scholarly Index (DSI), for this purpose. Publications from academic plastic surgery programs in qualifying states of the Southeastern Society of Plastic and Reconstructive Surgeons released in 2022 were collected via PubMed affiliation search. Publications were recorded in a running list alongside the title and 2022 impact factor of their respective journals. The impact factors were averaged by summing the impact factors and dividing by the number of articles to obtain a raw average. Any publication in a journal with an impact factor greater than five multiples of the raw average was removed as an outlier. The remaining impact factors were then summed and give the final numerical value representing the DSI. A total of 464 articles published in 139 individual journals were returned from PubMed between January 1, 2022, and December 31, 2022, for the 22 constituent departments. Calculated Spearman's rank coefficients comparing the DSI ranking with both the Doximity and Persad-Paisley rankings yielded values of 0.66 (P < 0.01) and 0.62 (P < 0.01), respectively. Overall, the DSI rankings largely agree with either the Persad-Paisley or Doximity rankings with notable differences seen in the rankings of Mayo Florida and the University of Alabama. A clear academic ranking of Southeastern Society of Plastic and Reconstructive Surgeons programs was generated from these data. The DSI represents a novel and simple approach to applying objective value to research with the advantage of using data bound to the most recent publication productivity.

MRI-based assessment of the mylohyoid muscle in oral squamous cell carcinoma, a 7-point scoring method.

To investigate preoperative MRI evaluation of the features of the mylohyoid muscle (MM) predictive of its infiltration in oral squamous cell carcinoma (OSCC) treatment planning, defining the most appropriate sequences to study its deep extension into the floor of the mouth (FOM). We applied a 7-point score to retrospectively evaluate preoperative imaging of patients who underwent surgery for OSCC over 11 years. The results were compared with histopathological findings using Spearman's rank coefficient. Receiver operating characteristic curves were employed to assess the score's ability to predict MM infiltration, determining optimal thresholds for sensitivity, specificity, and predictive values. The Mann-Whitney U-test confirmed that infiltration judgments did not overlap around this threshold. Cohen's K statistical coefficient was used to evaluate the interobserver agreement. Fifty-two patients (mean age 66.4 ± 11.9 years, 36 men) were evaluated. Histopathological examination found MM infiltration in 21% of cases (n = 11), with 90% classified in the highest Score categories. A score > 4 proved to be the best cut-off for predicting the risk of MM infiltration, with a sensitivity of 91% (CI: 0.57-0.99), specificity 61% (CI: 0.45-0.76), PPV 38% (CI: 0.21-0.59), and NPV 96% (CI: 0.78-0.99). At the subsequent single-sequence assessment, the TSE-T2wi had the highest diagnostic accuracy, with sensitivity 90% (CI: 0.57-0.99), specificity 70% (CI: 0.53-0.82), PPV 45% (CI: 0.25-0.67), and NPV 96% (CI: 0.80-0.99). The 7-point score is a promising predictor of safe surgical margins for MM in OSCC treatment, with the particular benefit of T2-weighted sequences. Our scoring system for tumor infiltration of MM, which is easy to use even for less experienced radiologists, allows for uniformity in radiological language, thereby ensuring crucial preoperative information for the surgeon. The relationship of the MM to an oral lesion may impact surgical planning. As the score increases, there is a greater incidence of infiltration in the MM. Our score system improves radiologists' reporting for MM involvement by tumor.

Experimental study on the influence of the riser on the gas-liquid flow in the horizontal pipeline of the offshore pipeline-riser system

The study of gas-liquid interface evolution and pressure fluctuation mechanism in the pipeline-riser system is the key to ensuring the safety of oil and gas transportation. This paper investigates the influence of the riser on the gas-liquid interface in the system with a 1657 m pipeline and risers of 16 m, 22 m, and 29 m. In severe slugging, the differential pressure in the horizontal pipeline exhibits a low-frequency large-amplitude fluctuation consistent with those in the riser. During the gas blowdown of the riser, the pressure fluctuation breaks the force equilibrium of the gas-liquid interface and induces numerous liquid slugs in the horizontal pipeline. A strong correlation is found between the differential pressure in the riser and the slug velocity in the horizontal pipeline by the Spearman Rank coefficient. The correlations between the slug velocity and the gas volume fraction and the void fraction under different riser heights are established, and the errors are 15% and 10%, respectively. The linear relationship between the Strouhal number of liquid slugs and the Lockhart-Martinelli parameter is constructed during the gas blowdown.

Prostate magnetic resonance imaging utilization and its relationship with advanced prostate cancer detection

BackgroundThe rise in advanced prostate cancer has coincided with increased use of Magnetic Resonance Imaging (MRI), leading to the hypothesis that this increase in surveillance registries is an artifact of more sensitive imaging tools. We assessed the association between regional variation in prostate MRI and advanced prostate cancer diagnoses. MethodsWe utilized SEER-Medicare data (2004–2015), including men > 65 diagnosed with localized prostate cancer. The predictor variable was the utilization of prostate MRI in each hospital referral region (HRR, representing regional healthcare markets). We compared the proportion of disease recorded as locally advanced or of regional risk group (cT3, cT4, and cN1) which would plausibly have been detected by prostate MRI. We conducted adjusted multivariable analysis and performed correlation analysis with Spearman rank coefficient at the level of the HRR. Sensitivity analysis for years 2011 to 2015 was conducted. ResultsOf 98,921 men diagnosed, 4.01% had locally advanced or regional disease. The median prostate MRI utilization rate was 4.58% (IQR [3.03%, 8.12%]). Adjusted multivariable analysis revealed no statistically significant correlation between MRI utilization and proportion of advanced prostate cancer (aOR = 1.01, 95% CI, [0.99,1.03]) in each region. The correlation between MRI usage and advanced diagnosis was not significant (Spearman Ρ = 0.09, P = 0.4). Sensitivity analysis conducted between 2011 and 2015 showed similar results (aOR = 1.008, 95% CI, [0.989, 1.027]; Spearman Ρ = 0.16, P = 0.1). ConclusionsDuring our study period, HRR-level utilization of MRI was not associated with higher incidences of advanced prostate cancer. This suggests the rising advanced prostate cancer diagnoses observed in this period are unlikely an artifact of greater sensitivity of modern imaging tests, but potentially due to other factors such as changes in screening or risk factors. With increased utilization and evolving techniques in recent years, the association between MRI and advanced prostate cancer detection warrants continued monitoring.

Assessment of the assimilation potential (by carbon) of urban green areas (on the example of the city of Penza)

The dependence of carbon assimilation in mixed plantings of the Penza city on the influence factors used in the ROBUL algorithm was studied. Specific carbon assimilation in the city by 99 % depends on the forest cover of the residential area, assimilation age rank and average conversion coefficient. The first factor has the greatest influence, while the conversion coefficient has the least one. The average carbon assimilation by the tree stand of the residential zone was 0.199 t/year/ha (43.6 kg/year/person). The highest indicators were in districts with forest park zones, the lowest ones were in districts with development not earlier than 2000. A positive carbon balance is observed relative to respiration of the population, but this balance is negative within the administrative borders of districts. A comparison of specific carbon assimilation at the Penza agglomeration sites calculated using the ROBUL algorithm and the obtained general regression assimilation model (RMA) showed no significant differences between them with a significant difference in the labor intensity of obtaining results in favor of the RMA model. The PMA model can be used to determine the temporal dynamics of carbon assimilation based on the planned area and composition of plantations. For the maximum possible share (42.6 %) of the green residential area of the Penza city, the potential carbon assimilation according to the RMA model for mixed species is 0.44 t/year/ha and is achieved in 40 years from tree planting, after which there is a decrease due to self-cutting.

Evaluating neurocognitive outcomes in out-of-hospital cardiac arrest survivors: A comparative study of performance-based and reported measures

AimsTo (1) describe the prevalence of cognitive dysfunctions using performance-based and reported measures, and (2) explore the correlations between selected performance-based, patient-reported, and observer-reported neurocognitive outcome measures three months after hospital discharge in a population of out-of-hospital cardiac arrest (OHCA) survivors. MethodsData from 193 OHCA survivors was derived from the Danish multicenter REVIVAL cohort study. At three months, four subtests of the performance-based Delis-Kaplan Executive Function System (D-KEFS) (Trail making, Color-word interference, Verbal fluency, and Figure design), the patient-reported Behavior Rating Inventory of Executive Function − Adult (BRIEF-A), and the observer-reported 16-item Short Form (SF) Informant Questionnaire on Cognitive Decline after Cardiac Arrest (SF-16 IQCODE-CA) were collected. Spearman’s rank coefficient correlation analysis was performed to examine correlations between D-KEFS, BRIEF-A, and SF-16 IQCODE-CA. ResultsOverall, 21% of survivors exhibited impairment in executive functioning using the D-KEFS subtest Color-word interference, while only 9% self-reported executive impairment (BRIEF-A) and 7% of relatives reported cognitive decline (SF-16 IQCODE-CA) in survivors at three months post-arrest. All correlations between D-KEFS, BRIEF-A and SF-16 IQCODE-CA were negligible to low. ConclusionThe results of this REVIVAL substudy suggest that although the performance-based and reported measures did not correlate, dual neurocognitive screening tools containing both a self-reported and an informant-reported version may have the potential to detect executive discrepancies in the return to everyday life and guide targeted neurorehabilitation after OHCA.

Immunohistochemical characterization of inflammatory infiltrates in unstable vitiligo

Objectives: Disease instability in vitiligo is a prominent step during the development or extension of disease. The presence of marked inflammatory infiltrate may be considered a diagnostic clue for disease instability. However, there is a paucity of literature regarding this. Therefore, the present study was carried out to characterize the nature of inflammatory infiltration in cases of unstable vitiligo. Materials and Methods: Thirty patients of unstable vitiligo diagnosed clinically were enrolled and two biopsies: Lesional and perilesional obtained. Histopathological examination with respect to five parameters, i.e., spongiosis, epidermal lymphocytes, basal cell vacuolation, dermal lymphocytes, and melanophages was done including histological scoring. Immunohistochemical characterization was done for T lymphocytes, Langerhans cells (LCs), macrophages, and B cells by studying their number and distribution. Statistical analysis: Statistical analysis was done using Spearman’s rank coefficient correlation test. Results: Mean T-lymphocytes, macrophages, and LC count were significantly higher in lesional skin. The three parameters correlated with vitiligo histological score. T cells were present more frequently in the dermis and stratum basale. Macrophages were found more in the dermis whereas LC was mainly located in the epidermis. Conclusions: An increase in the population of inflammatory cells, especially T lymphocytes and LC, may serve as an indicator of unstable vitiligo. The relative distribution of these cells points toward signaling between them and their role in the destruction of melanocytes and keratinocytes. A better understanding of the underlying mechanisms may lead to the development of novel targeted therapies.

A transfer learning-based ensemble learning model for electric vehicles lithium-ion battery capacity estimation using electrochemical impedance spectroscopy

Lithium-ion battery capacity estimation is crucial to ensure the operational reliability and safety of electric vehicles. Electrochemical Impedance Spectroscopy (EIS) can provide rich physical degradation information of the battery, which makes the EIS-based data-driven method a promising solution for accurate battery capacity estimation. However, batteries tend to present diverse degradation patterns due to the diverse operating conditions and manufacturing, resulting in large capacity estimation errors in practical applications. Therefore, this paper proposes a transfer learning (TL) based ensemble learning (EL) method based on multi-layer perception for the battery capacity estimation. First, the influential impedance features are identified from the EIS using Spearman rank coefficient analysis. Second, three TL models are developed based on distinct TL strategies to enable sufficient knowledge transfer considering the different degradation pattern. Further, an EL method with Gaussian kernel-based weighted assignment technique is proposed to integrate the developed TL models and improve the estimation robustness. The performance of the developed model has been successfully validated only using the first 1/3 cycles of the historical data from target battery obtained under different operating conditions and batteries. The results reveal that the proposed method can largely suppress estimation errors, presenting more accurate capacity estimation compared to other methods with an RMSE lower than 1%.

Lancaster correlation: A new dependence measure linked to maximum correlation

AbstractWe suggest novel correlation coefficients which equal the maximum correlation for a class of bivariate Lancaster distributions while being only slightly smaller than maximum correlation for a variety of further bivariate distributions. In contrast to maximum correlation, however, our correlation coefficients allow for rank and moment‐based estimators which are simple to compute and have tractable asymptotic distributions. Confidence intervals resulting from these asymptotic approximations and the covariance bootstrap show good finite‐sample coverage. In a simulation, the power of asymptotic as well as permutation tests for independence based on our correlation measures compares favorably with competing methods based on distance correlation or rank coefficients for functional dependence, among others. Moreover, for the bivariate normal distribution, our correlation coefficients equal the absolute value of the Pearson correlation, an attractive feature for practitioners which is not shared by various competitors. We illustrate the practical usefulness of our methods in applications to two real data sets.

To a dispersion law of an electromagnetic wave in a medium having a double anisotropy

Dispersion relations for a transverse electromagnetic wave in a hypothetical medium having a low crystalline symmetry and double anisotropy are formulated phenomenological based on the general concepts of Maxwell's equations. Formalism for electrical and magnetic ordering of a medium is represented by tensor coefficients of the second rank in a general coordinate system corresponding to an external problem of incidence, reflection and refraction of a transverse wave at the interface. Based on the obtained dispersion law, the Snell law of refraction for the wave vector is displayed, as well as, some special cases for a section of a wave surface and a ray surface in the plane of incidence. Following Fresnel approach as usual, two characteristic types of linear polarization of an electric induction vector of a propagating wave are considered for a wave entering a double anisotropic medium at an arbitrary angle to the interface. Based on a character of a cross-section of a wave surface and of a ray surface for the plane of incidence, the degree of influence of anisotropy on a propagating field is discussed in terms of external/internal conic refraction of ordinary/extraordinary waves in a transparent medium. Following to initially general form of the permittivity ε^ and the magnetic permeability μ^ tensors some particular cases of a more favorable choice of coordinate system are analyzed to decrease a number of non-zero components in mentioned tensors, as well as to decrease in the number of elements in vector relations.

Changes in Maxillary Sinus Volume and Mucosal Thickness Post Bimaxillary Advancement Procedures: A Retrospective Study

Background: Bimaxillary surgery is an elemental procedure in the field of cranio-maxillofacial surgery. It allows for the correction of even the most challenging cases of maxillomandibular disorders, malocclusion, facial asymmetry, and disproportion. The osteotomies and maneuvers carried out during the procedure result in changes to the surrounding tissues, including the maxillary sinuses (MS). The aim of this study was to assess the change in the maxillary sinus volume and the thickness of the mucosa after maxillomandibular advancement (MMA) surgeries. Methods: A group of 25 patients who underwent MMA surgery were included in the study. Computed tomography (CT) of the head and neck region was performed 2 weeks preoperatively and 6 months postoperatively. Acquired Digital Imaging and Communications in Medicine (DICOM) files were analyzed using different software programs to calculate the medium MS mucosa thickness and MS volume. Results: A statistically significant reduction in MS volume was observed (p = 0.015). The change in the median thickness of the MS mucosa was not statistically significant. The median sella-nasion-A point angle (SNA angle) value of the group increased from 80.2 to 83.4 degrees. A weak negative correlation between the SNA delta and the MS volume delta was observed. Spearman’s rank coefficient: (ρ s = −0.381, p = 0.060). Conclusions: The MMA surgery results in a reduction in the MS volume. The amount of forward movement of the maxilla may be correlated with the extent of the MS volume reduction.

Potential drug-drug interactions analysis in Polish pediatric pneumonology units, including cystic fibrosis patients.

The lack of data on drug-drug interactions in pediatrics represents a relevant problem in making appropriate therapeutic decisions. Our study aimed to investigate the incidence and risk factors for potential drug-drug interactions (pDDIs) in pediatric pneumonology units, including cystic fibrosis patients. We performed a 6-month prospective observational study during which clinical pharmacists, using the Lexicomp Drug Interactions checker, screened medical records to identify pDDIs. Spearman's rank coefficient, logistic regression, and the Mann-Whitney U test were used to identify correlations, analyze risk factors for pDDIs, and compare cystic fibrosis patients with the rest, respectively. Recommendations were provided for the D and X pDDIs categories. Within the 218 patients, 428 pDDIs were identified, out of which 237 were classified as clinically significant. Almost 60% of patients were exposed to at least one relevant interaction. The number of pDDIs correlated with the number of; drugs (rs = 0.53, P < .001), hospitalization length (rs = 0.20, P < .01), and off-label medicines (rs = 0.25, P < .001). According to the multivariate analysis, at least 6 administered medications (OR = 4.15; 95% CI = 2.21-7.78), 4 days of hospitalization (OR = 6.41; 95% CI = 2.29-17.97), and off-label therapy (OR = 3.37; 95% CI = 1.69-6.70) were the risk factor for pDDIs. Despite significant differences in the number of medications taken, comorbidities, and off-label drugs, cystic fibrosis patients were not more exposed to pDDI. Given the lack of data on pDDIs in the pediatric population, the need for close cooperation between clinicians and clinical pharmacists to improve the safety and efficacy of pharmacotherapy is highlighted.

Association of Scholarly Impact to Industrial Contributions Among Academic Interventional Radiologists

ObjectiveThe Physician Sunshine Act of 2010 aimed to increase public awareness of physician-industry relationships. Our objective was to evaluate whether there is an association between scholarly impact and industry funding among academic interventional radiologists. MethodsA database from a prior study with our group was used in which we had investigated H-indices among US interventional radiologists; academic rank, gender, institution, and geographic location were obtained. The Scopus database was queried to determine all physicians’ H-index. The CMS Open Payments database was used to determine industry payments from 2015 to 2021 for each interventional radiologist. ResultsH-index and professor rank positively and significantly correlated with industrial funding (H-index coefficient = $6,977, P < .001 and professor rank coefficient = $183,902, P = .003). Industry funding was found to be significantly different between all ranks. Among 830 academic interventional radiologists, the mean industrial funding of male physicians was $130,034, which was significantly higher than female physicians’ $28,166 (P = .00013). By academic rank, male primary investigators of associate professor and unranked position had higher industrial funding than female primary investigators (Wilcoxon test, P = .029 and P= .039, respectively). Professor and assistant professor ranks had no significant difference in industrial funding between male and female physicians (Wilcoxon’s test, P = .080 and P = .053, respectively). ConclusionScholarly activity as defined by the H-index and academic rank seem to have a positive association with industry funding of academic interventional radiologists.

Coastal ecological security assessment in Laizhou Bay, China: from the perspective of demographic-social-economic-natural complex ecosystem.

Assessment of ecological security is essential for understanding the status of bay ecosystem and developing appropriate management strategy. Based on the driving force-pressure-state-impact-response (DPSIR) model, the demographic, economic, social, and ecological data of Laizhou Bay and its three neighboring counties were selected for the period from 2015 to 2021. An ecological security evaluation index system of Laizhou Bay containing 26 indicators was established, and the weights of each indicator were determined by the methods of AHP and EWM, and a comprehensive evaluation of the ecological security of Laizhou Bay was carried out by ESI. Correlations between indicators were analyzed by the Spearman's rank coefficient of correlation. The results showed that there were significant correlations between marine conditions and indicators such as population size in the surrounding area, mariculture area, industrial and domestic wastewater discharge, and treatment rate. Overall, from 2015 to 2021, the ecological security of Laizhou Bay showed a favorable trend, from a relatively unsafe level to a generally safe level, and then to a relatively safe level. Through the comprehensive evaluation of the ecological security of Laizhou Bay, we can recognize the utilization of marine resources and ecological carrying capacity, guide the rational development and utilization of marine resources, and promote the sustainable development of the marine economy.

Predictive model of suicide risk in Colombian university students: quantitative analysis of associated factors

IntroductionThe risk of suicide and completed suicides among young university students presents critical challenges to mental and public health in Colombia and worldwide. Employing a quantifiable approach to comprehend the factors associated with these challenges can aid in visualizing the path towards anticipating and controlling this phenomenon.ObjectiveDevelop a predictive model for suicidal behavior in university students, utilizing predictive analytics.MethodWe conducted an observational, retrospective, cross-sectional, and analytical research study at the University of Manizales, with a focus on predictive applicability. Data from 2,436 undergraduate students were obtained from the research initiative “Building the Future: World Mental Health Surveys International College Students.”ResultsThe top ten predictor variables that generated the highest scores (ranking coefficients) for the sum of factors were as follows: history of sexual abuse (13.21), family history of suicide (11.68), medication (8.39), type of student (7.4), origin other than Manizales (5.86), exposure to cannabis (4.27), exposure to alcohol (4.42), history of physical abuse (3.53), religiosity (2.9), and having someone in the family who makes you feel important (3.09).DiscussionSuicide involves complex factors within psychiatric, medical, and societal contexts. Integrated detection and intervention systems involving individuals, families, and governments are crucial for addressing these factors. Universities also play a role in promoting coping strategies and raising awareness of risks. The predictive accuracy of over 80% in identifying suicide risk underscores its significance.ConclusionThe risk factors related to suicidal behavior align with the findings in specialized literature and research in the field. Identifying variables with higher predictive value enables us to take appropriate actions for detecting cases and designing and implementing prevention strategies.

Sensitivity analysis of the parameters for preference functions and rank reversal analysis in the PROMETHEE II method

The PROMETHEE II method is a classical multiple criteria decision making method. However, it also exists the rank reversal which is a highly important problem for analyzing the reliability of a MCDM method. The main objective of this study is to analyze the sensitivity of the parameters for preference functions and the rank reversal problem in the PROMETHEE II method. By analyzing the parameters for preference functions from the standpoint of theoretics, a method is proposed to calculate the ranges of the parameters for four types of preference functions to remain the ranking of all the alternatives unchanged. Second, the sufficient and necessary condition of the rank reversal is obtained in the PROMETHEE II method when there are only three types of criteria, i.e., usual criteria, U-shape criteria and level criteria. Finally, two minor modification methods for the PROMETHEE II method itself are proposed by observing the net outranking flow formula. Numerical simulations show that the occurrence of the rank reversal is clearly reduced and the ranges of fault tolerance of the parameters for preference functions are significantly larger for each new modified PROMETHEE II method. The similarity of rankings is tested by using the similarity rank coefficient WS. This indicates the rationality of the two proposed modifications.

Correlation Analysis of the Terrorist Attacks and Social Attributes in The Gulf States

Terrorist attacks are a significant threat to global security as they can cause a large number of deaths, economic losses, and trigger public panic. This paper focuses on the Gulf states as the survey region. This study comprehensively investigates the correlation between national-scale terrorist attacks and various potential factors in the social, political, economic, and military fields, based on the Spearman rank coefficient and gray correlation analysis. The potential factors are divided into two categories: those with a positive correlation and those with a negative correlation to terrorist attacks. The study shows a strong correlation between the adolescent fertility rate (births per 1,000 women aged 15-19) and the occurrence of terrorist attacks. This correlation has not been previously noted in relevant studies, indicating a need for greater attention to be paid to the impact of terrorist attacks on the human rights of children and adolescents.