Multivariate Equation Research Articles

Development and Validation of the American Heart Association's PREVENT Equations.

Multivariable equations are recommended by primary prevention guidelines to assess absolute risk of cardiovascular disease (CVD). However, current equations have several limitations. Therefore, we developed and validated the American Heart Association Predicting Risk of CVD EVENTs (PREVENT) equations among US adults 30 to 79 years of age without known CVD. The derivation sample included individual-level participant data from 25 data sets (N=3 281 919) between 1992 and 2017. The primary outcome was CVD (atherosclerotic CVD and heart failure). Predictors included traditional risk factors (smoking status, systolic blood pressure, cholesterol, antihypertensive or statin use, and diabetes) and estimated glomerular filtration rate. Models were sex-specific, race-free, developed on the age scale, and adjusted for competing risk of non-CVD death. Analyses were conducted in each data set and meta-analyzed. Discrimination was assessed using the Harrell C-statistic. Calibration was calculated as the slope of the observed versus predicted risk by decile. Additional equations to predict each CVD subtype (atherosclerotic CVD and heart failure) and include optional predictors (urine albumin-to-creatinine ratio and hemoglobin A1c), and social deprivation index were also developed. External validation was performed in 3 330 085 participants from 21 additional data sets. Among 6 612 004 adults included, mean±SD age was 53±12 years, and 56% were women. Over a mean±SD follow-up of 4.8±3.1 years, there were 211 515 incident total CVD events. The median C-statistics in external validation for CVD were 0.794 (interquartile interval, 0.763-0.809) in female and 0.757 (0.727-0.778) in male participants. The calibration slopes were 1.03 (interquartile interval, 0.81-1.16) and 0.94 (0.81-1.13) among female and male participants, respectively. Similar estimates for discrimination and calibration were observed for atherosclerotic CVD- and heart failure-specific models. The improvement in discrimination was small but statistically significant when urine albumin-to-creatinine ratio, hemoglobin A1c, and social deprivation index were added together to the base model to total CVD (ΔC-statistic [interquartile interval] 0.004 [0.004-0.005] and 0.005 [0.004-0.007] among female and male participants, respectively). Calibration improved significantly when the urine albumin-to-creatinine ratio was added to the base model among those with marked albuminuria (>300 mg/g; 1.05 [0.84-1.20] versus 1.39 [1.14-1.65]; P=0.01). PREVENT equations accurately and precisely predicted risk for incident CVD and CVD subtypes in a large, diverse, and contemporary sample of US adults by using routinely available clinical variables.

Direct and Indirect Linkages Between Trace Element Status and Health Indicators - a Multi-tissue Case-Study of Two Deer Species in Denmark

Measuring trace element concentrations in tissue can be a valuable approach to monitor animal health status. Temporal variation in the absorption, transport, and storage of elements between different tissues can, however, complicate the assessment of element-health relationships. Here, we measured concentrations of selected essential (copper (Cu), zinc (Zn), selenium (Se)) and non-essential (arsenic (As), cadmium (Cd), lead (Pb)) trace elements within blood, liver, kidney, and hair of fallow deer (Dama dama; N=20) and red deer (Cervus elaphus; N=21). Using multivariate regression and structural equation models, we estimated direct and indirect linkages between tissue-specific trace element profiles and long- (body condition) and short-term (serum protein biomarkers for acute inflammation, infection, and malnutrition) health indicators. Trace element concentrations varied markedly and were weakly correlated among tissues, with the exception of Se. After accounting for sex- and site-differences in trace element concentrations, body condition of red deer was directly, and positively, associated to trace element status in liver and hair, but not in kidney. For both deer species, trace element status in blood was directly linked to serum protein status with an indirect positive association to deer body condition. For fallow deer, no direct association between trace element status and body condition was detected in any of the tissues, possibly because of elemental homeostasis, and because all individuals were in good clinical health. This study shows that hair can serve as an effective, non-invasive, biomarker in deer health assessments, yet, to fully uncover trace element-health relationships a variety of sample matrices is preferred.

Testing of morphological sex estimation traits with a sex‐known collection: Ottoman period skulls

AbstractSexual dimorphism patterns vary across geographic regions due to the influence of genetic characteristics and environmental factors. Therefore, sex estimation models are being developed specifically for each population or group. The applicability of morphological sex estimation methods has not been tested in Turkey. Hence, by using skulls, the present study aims to analyze the reliability of the visual morphological method and test the equations developed in different populations. The study material consists of 192 skulls (96 male, 96 female) with known sexes, excavated from Istanbul's Karacaahmet cemetery in 1925. In the present study, glabella, mastoid process, supraorbital margin, and nuchal crest traits were scored on a scale of 1 to 5 according to the instructions provided in standard protocols. Intra‐observer and inter‐observer agreements were analyzed by two experts having the same level of experience. When equations derived from other populations were applied to our samples, they exhibited high sex biases (up to 50%). Therefore, new equations were derived through binary logistic regression analysis. Glabella had the highest performance in terms of repeatability (0.83) and reproducibility (0.74), whereas the nuchal crest showed the lowest performance (0.60–0.52). The most significant sexual dimorphism was observed in the glabella. Based on cross‐validated results using a single criterion, it accurately classified 80% of females and 84% of males. The nuchal crest was not significantly affecting the sex discriminative equations (p > 0.05). Multivariate equations achieved an accuracy of over 90% and cross‐validated results ranged between 80% and 90%. The results obtained from present study support the hypothesis that sexual dimorphism patterns vary under different conditions and highlight the importance of population variation in sex estimation. The models derived from the present study were found to be suitable for sex estimation from skulls and demonstrated high performance.

Determination of normative value of Psychometric hepatic encephalopathy score in Bangladeshi volunteers

Background and Objectives: The psychometric hepatic encephalopathy score (PHES) is a composite score of five different neuropsychological tests. It is considered as gold standard test to diagnose Minimal Hepatic Encephalopathy(MHE). But one problem with PHES is that it needs normative value of its five components as they vary from population to population. So population based normative value should be derived before it is applied to that population. MHE is diagnosed when variation from this normal value occur, provided other criteria are fulfilled. The aim of this study is to find out the normative value of PHES test batteries. Methods: This cross sectional observational study among healthy volunteers took place in department of Gastroenterology, Dhaka medical college from May 2019 to April 2020. All participants in this study took part in the test according to international norm. Results: Among the 300 study population,age and years of education had significant impact on all tests score. Hence, multivariate equation adjusting age and years of education were derived. A scoring method was applied depending on deviation from predicted score for all tests. Finally, -5 PHES was determined as cut off value for normal and pathological. Conclusion: Age and education adjusted normative value of five components of PHES were constructed in Bangladeshi population. PHES cut off value was also determined. Now it is possible to calculate PHES among liver cirrhosis patients of Bangladesh. J Bangladesh Coll Phys Surg 2023; 41(4): 277-281

Experimental and numerical simulation verification of depositional characteristics of NH4Cl particles under variable conditions

ABSTRACT The primary cause of U-tube heat exchanger leakage and perforation is attributed to the deposition and corrosion of NH4Cl within the condensing pipeline located at the summit of the crude oil distillation tower. This paper aims to investigate the deposition law of NH4Cl in U-shaped tubes under variable operating conditions and the impact of diverse factors on the deposition features of NH4Cl. To achieve this objective, the study establishes appropriate experimental equipment, designs a 4-factor and 4-level orthogonal experimental table, and manipulates the variables of particle incidence velocity (v), relative humidity (RH), particle size (d), and temperature (T). The experimental results of each group are recorded and analyzed. The observed experimental data reveals that under the operational parameters of Group H (v: 7 m/s, RH: 50%, d: 0.7 mm, T: 140°C), particle accumulation peaks at the elbow outlet, resulting in a substantial volume ratio of 17.14%. Conversely, Group M (v: 10 m/s, RH: 1%, d: 0.1 mm, T: 140°C) demonstrated the minimal particle deposition in the angular sector between 30° − 60° of the elbow, yielding a minimal volume ratio of 0.22%. Further scrutiny suggests that environmental humidity and incident flow velocities significantly influence particle deposition, whilst ambient temperature and particle size exert less substantial effects. A multivariate linear deposition equation between NH4Cl deposition and v, RH, d, T was derived through linear regression, yielding an Rc2 of 0.913, indicating a high level of concordance. A mathematical model was constructed, incorporating computational fluid dynamics (CFD), to simulate and analyze the flow characteristics of ammonium chloride particles in U-shaped tube bundles, which was subsequently validated with the experimental results obtained, the comparison results showed a good degree of coincidence, with an error of 4.41%.

Breast Augmentation in Transwomen: Can We have a Formula?

Background Breast augmentation in transwomen is a surgical challenge as there is no available guideline for preoperative assessment of breast implant size, which caters to them specifically. The aim of our study is to derive a formula for preoperative breast implant size estimation, which would remove the personal bias, help in one-to-one discussion, and better understanding, reducing operative time, cost, and revision surgery rate. Methods This is a retrospective study conducted from October 2018 to December 2020. We maintained a routine protocol for measurements in our patients, which has been previously published. Linear multivariate regression equation was applied to derive a formula using minimum of parameters, namely, CC (chest circumference at the inframammary fold [IMF]), POMP (circumference at the point of maximum projection of breast mound), and LOWERDIFF (lower value of difference in each breast between the stretched nipple [IMF] and the nonstretched nipple [IMF distance]). Results A total of 51 transwomen underwent surgery in this period. The mean volume of implant used was 354.51 mL. Complications consisted of pain and discomfort in six patients, delayed healing in two patients, and wound dehiscence in one. A formula for preoperative calculation of breast implant was obtained with these data. A mathematical correlation was found between complications encountered and the percentage by which the inserted implants exceeded the calculated size. Conclusion We could estimate the breast implant size preoperatively through a simple formula that require only four anthropometric measurements. This equation is a significant advantage for the surgeon and a useful tool for patient education. Its usefulness will be established if applied in prospective studies. From our study, it appears 9% above the calculated size is better avoided.

Look-up the Rainbow: Table-based Implementation of Rainbow Signature on 64-bit ARMv8 Processors

The Rainbow Signature Scheme is one of the finalists in the National Institute of Standards and Technology (NIST) Post-Quantum Cryptography (PQC) standardization competition, but failed to win because it has lack of stability in the parameter selection. It is the only signature candidate based on a multivariate quadratic equation. Rainbow signatures have smaller signature sizes compared with other post-quantum cryptography candidates. However, they require expensive tower-field based polynomial multiplications. In this article, we propose an efficient implementation of Rainbow signatures using a look-up table–based multiplication method. The polynomial multiplications in Rainbow signatures are performed on the 𝔽 16 field, which is divided into sub-fields 𝔽 4 and 𝔽 2 under the tower-field method. To accelerate the multiplication process on target processors, we propose a look-up table–based tower-field multiplication technique. In 𝔽 16 , all values are expressed in 4-bit data format and can be implemented using a 256-byte look-up table access. The implementation uses the TBL and TBX instructions of the 64-bit ARMv8 target processor. For Rainbow III and Rainbow V, they are computed on the 𝔽 256 field using an additional 16-byte table instead of creating a new look-up table. The proposed technique uses the vector registers of 64-bit ARMv8 processors and can calculate 16 result values with a single instruction. We also proposed implementations that are resistant to timing attacks. There are two types of implementations. The first one is the cache side-attack resistant implementation, which utilizes the 128-byte cache lines of the M1 processor. In this implementation, cache misses do not occur, and cache hits always occur. The second type is the constant-time implementation. This method takes a step-by-step approach to finding the required look-up table value and ensures that the same number of accesses is made regardless of which look-up table value is called. This implementation is designed to be constant-time, meaning it does not leak timing information. Our experiments on modern Apple M1 processors showed up to 428.73× and 114.16× better performance for finite field multiplications and Rainbow signatures schemes, respectively, compared with previous reference implementations. To the best of our knowledge, this proposed Rainbow implementation is the first optimized Rainbow implementation for 64-bit ARMv8 processors.

A recursive representation for decoupling time-state dependent jumps from jump-diffusion processes

We establish a recursive representation that fully decouples jumps from a large class of multivariate inhomogeneous stochastic differential equations with jumps of general time-state dependent unbounded intensity, not of Lévy-driven type that essentially benefits a lot from independent and stationary increments. The recursive representation, along with a few related ones, are derived by making use of a jump time of the underlying dynamics as an information relay point in passing the past on to a previous iteration step to fill in the missing information on the unobserved trajectory ahead. We prove that the proposed recursive representations are convergent exponentially fast in the limit, and can be represented in a similar form to Picard iterates under the probability measure with its jump component suppressed. On the basis of each iterate, we construct upper and lower bounding functions that are also convergent towards the true solution as the iterations proceed. We provide numerical results to justify our theoretical findings.

Cultural Identity and the Academic, Social, and Psychological Adjustment of Adolescents with Immigration Background

As Western societies become more ethnically and culturally diverse, understanding the acculturation of immigrant youth is essential for fostering social cohesion. How the cultural identity formation of ethnic minority adolescents relates to their academic, social, and psychological adjustment is an important and as yet unresolved research question. This study examined to what extent identifying with the heritage and/or host culture is an individual resource or risk factor for the adjustment of immigrant youth in Germany. A random sample of 15–17-year-olds (N = 1992; Mage_w1 = 15.3 years, SD = 0.64; 44.5% girls; 44.7% students with immigrant background) was assessed twice: at the end of 9th and 10th grade. Academic performance and three dimensions of social/psychological adjustment (school attachment, self-esteem, and life satisfaction) were examined. Results showed that biculturalism was the modal identification pattern. Contrary to expectations, cultural identification did not differ systematically with perceived distance from the majority culture. Multivariate structural equation modeling revealed that both heritage and host identification can be developmental resources, but that their effects are dependent on the dimension of adjustment; biculturalism only proved to be a cumulative resource for school attachment. The domain specificity of the findings challenges the generalization claims of predominant acculturation theories.

Analysis of left-turn behaviors of non-motorized vehicles and vehicle-bicycle conflicts.

In order to further study the expansion characteristics of left-turning non-motorized vehicles at intersections and the relationship between expansion characteristics and vehicle-bicycle conflicts, the trajectory point data of left-turning non-motorized vehicles are extracted using video trajectory tracking technology, and construct the cubic curve expansion envelope equation with the highest fitting degree. For the purpose of quantifying the expansion degree of non-motor vehicles after starting, two intersections in Guangxi Zhuang Autonomous Region were selected for case analysis, and the numerical range of expansion degree of the intersection with a left-turn waiting area and the intersection without a left-turn waiting area was obtained. Study the mathematical relationship between the expansion degree and its influencing factors, and establish the multivariate nonlinear regression equation between the expansion degree and the left-turn non-motorized vehicle flow, the number of parallel non-motorized vehicles, and the left-turn green light time. Analyze the vehicle-bicycle conflicts caused by the expansion of left-turning non-motorized vehicles, determine the essential factors affecting the number of non-motorized vehicles, and establish the multiple linear regression equation between the number of non-motorized vehicles and the number of left-turning non-motorized vehicles, the expansion degree, and the number of parallel non-motorized vehicles, the results show that the model has high accuracy. By analyzing the expansion characteristics of left-turning non-motorized vehicles at intersections, the relationship between different influencing factors and the expansion degree is obtained. Then the vehicle-bicycle conflicts under the influence of expansion characteristics is analyzed, providing theoretical ideas for improving traffic efficiency and optimizing traffic organization at intersections.

Reduced Left Ventricular Twist Early after Acute ST-Segment Elevation Myocardial Infarction as a Predictor of Left Ventricular Adverse Remodelling.

The left ventricular (LV) remodelling process represents the main cause of heart failure after a ST-segment elevation myocardial infarction (STEMI). Speckle-tracking echocardiography (STE) can detect early deformation impairment, while also predicting LV remodelling during follow-up. The aim of this study was to investigate the STE parameters in predicting cardiac remodelling following a percutaneous coronary intervention (PCI) in STEMI patients. The study population consisted of 60 patients with acute STEMI and no history of prior myocardial infarction treated with PCI. The patients were assessed both by conventional transthoracic and ST echocardiography in the first 12 h after admission and 6 months after the acute phase. Adverse remodelling was defined as an increase in LVEDV and/or LVESV by 15%. Adverse remodelling occurred in 26 patients (43.33%). By multivariate regression equation, the risk of adverse remodelling increases with age (by 1.1-fold), triglyceride level (by 1.009-fold), and midmyocardial radial strain (mid-RS) (1.06-fold). Increased initial twist decreases the chances of adverse remodelling (0.847-fold). The LV twist presented the largest area under the receiver operating characteristic (ROC) curve to predict adverse remodelling (AUROC = 0.648; 95% CI [0.506;0.789], p = 0.04). A twist value higher than 11° has a 76.9% specificity and a 72.7% positive predictive value for reverse remodelling at 6 months.

Particle filter-based damage prognosis using online feature fusion and selection

Damage prognosis generally resorts to damage quantification functions and evolution models to quantify the current damage state and to predict the future states and the remaining useful life (RUL). The former typically consists of a function describing the relationship between the damage state and a statistical feature extracted from the measured signals, thus the prognostic performance will strongly depend on the selection of a proper feature. Given the best feature may vary for different specimens or even at each time instant for the same specimen during damage progression, such selection is a challenging task but has received little investigation so far. In this context, this paper proposes a particle filter-based damage prognosis framework, which involves an online feature fusion and selection scheme. A prognostic model is considered for each feature, with a multivariate process equation, formulated using both a damage degradation function and a bias parameter, and a measurement equation linking the damage state and that feature considering a data-driven model and the bias. One PF is used to estimate the damage state, its evolution parameters, and the bias for each model. Then, at each step, the feature with the smallest estimated bias is selected as the best feature providing the most likely state vectors and is used to select the most likely samples of the damage state and growth parameters for predicting the RUL and for calculating the prior at the next step. The proposed prognostic framework is demonstrated by an experimental study, where an aluminum lug structure subject to fatigue crack growth is monitored by a Lamb wave measurement system.

Nonlinear multivariate constitutive equations for modeling hot deformation behavior

Nonlinear constitutive equations are proposed to model variations in flow stress as a function of strain rate and temperature during hot deformation. Modified constitutive are applied to seventy data sets about hot deformation of alloys. Two modifications to conventional constitutive models are introduced, viz. (1) nonlinear and (2) multivariate models with the fitting of flow stress simultaneously with two variables. The predictive accuracy of constitutive equations was evaluated using three statistical parameters and compared with a conventional Arrhenius-like model. It is shown that nonlinear constitutive equations have improved predictive accuracy for variations in flow stress during hot deformation. The advantages of multivariate models include less computation and material parameters that are constants independent of temperature or strain rate. In another type of multivariate model, flow stress is expressed as linear and nonlinear polynomial functions of the Zener-Holloman parameter. This approach gives a single value of the activation energy of hot deformation. The results have indicated that a generalized second-order multivariate constitutive equation can be used to better predict flow stress, as a function strain rate and temperature, during hot deformation.

Factors influencing investment attraction in road infrastructure BOT projects: A comprehensive analysis in the southern key economic zone of Vietnam

Over the course of the last two decades, Vietnam has demonstrated a growing interest in public-private partnership (PPP) investments within the domain of road transport infrastructure. However, the overall success rate of these endeavors has remained constrained and, in fact, has displayed a propensity for decline. Understanding the primary determinants behind this phenomenon, particularly the internal factors within the management system, has been a perplexing and protracted process, hindering the development of viable solutions. This research employs a qualitative analysis approach, leveraging in-depth interviews conducted with 250 road traffic infrastructure PPP project managers and experts. The objective is to discern the factors that exert influence over the investment attractiveness of build-operate-transfer (BOT) projects in the vital Southern Key Economic Zone of Vietnam. Subsequently, utilizing the collated data, this study employs a quantitative methodology to measure the impact of these factors via a derived multivariate regression equation. The findings reveal the existence of five distinct groups of factors that affect the investment attractiveness of BOT projects in the Southern Key Economic Zone, classified by their respective levels of influence. These groups encompass factors relating to the role of the state, the legal framework, human resources engagement in PPP ventures, supportive financial instruments, and the allocation of risk. Notably, these outcomes align with previous research efforts, further substantiating the robustness and reliability of the findings presented within this study.

Caffeinated non-alcoholic beverages on the postpartum mental health related to the COVID-19 pandemic by a cross-sectional study in Argentina.

This work aimed to study postpartum mental outcomes and determinants of the intake of caffeinated beverages during the pandemic in women from Argentina. This cross-sectional study recruited 619 women who responded to online self-report questionnaires during the first and second waves of COVID-19, including validated instruments (Insomnia Severity Index, Perceived Stress Scale, Postpartum Depression Screening Scale, Memory Complaint Scale, and Breastfeeding Self-Efficacy Scale), and general data. Intake frequency and amount of caffeinated beverages were estimated. Multivariate regression and structural equation models identified associations and effects (p<0.05). Women were under social restrictions for 60.39 days, with home and essential activities increasing caffeinated intake. They ingested (mL/d): yerba mate (1457.71), coffee (66.85), tea (67.61), and soft drinks (50.95), which provided 646.20mg/d of caffeine. Intakes of coffee and yerba mate were higher than pre-pandemic ones. Coffee was positively associated with stress and insomnia, and indirectly linked to higher levels of depression and memory complaints, and lower breastfeeding self-efficacy. Tea showed a similar but weaker association. Yerba mate correlated inversely with depression (through direct pathways), insomnia, and memory complaints (through indirect pathways), promoting breastfeeding self-efficacy. Soft drinks and caffeine did not present significant associations. Although findings do not imply causation, results suggest that beverages would exhibit caffeine-independent affective and cognitive roles, which might be anxiogenic in the case of coffee and tea (to a lesser extent). Yerba mate showed antidepressant potential. Given that breastfeeding might be compromised during the pandemic, yerba mate intake is promissory to protect postpartum mental health.

Hyperspectral multivariate linear prediction model of tobacco (nicotiana tabacum L.) Leaf nitrogen content

In order to accurately and effectively obtain the nitrogen content of tobacco leaves during the whole growth period, in the present study the field canopy spectrum of the three critical periods of tobacco rosette stage, vigorous growth stage and topping stage were used. The correlation analysis of field canopy spectrum, first derivative spectrum, hyperspectral parameters and vegetation index with the nitrogen content of tobacco leaves was carried out one by one, and the prediction model was established by multiple linear regression using the variables with the best correlation coefficient. Results showed that the first derivative spectrum, EVI II and green peak position had strong correlation, which is suitable for introducing multivariate equations as independent variables. Finally, the modeling determination coefficient (R2) was 0.66, RMSE was 0.40, and MAPE was 11%. The validation results showed that R2 was 0.73, RMSE was 0.38, and MAPE was 8.33%, which proved that this model could accurately predict the nitrogen content of tobacco leaves and could meet the requirements of large-scale statistical monitoring of tobacco quality indicators in the field. Bangladesh J. Bot. 52(2): 575-584, 2023 (June) Special

Hyperspectral multivariate linear prediction model of tobacco (nicotiana tabacum L.) Leaf nitrogen content

In order to accurately and effectively obtain the nitrogen content of tobacco leaves during the whole growth period, in the present study the field canopy spectrum of the three critical periods of tobacco rosette stage, vigorous growth stage and topping stage were used. The correlation analysis of field canopy spectrum, first derivative spectrum, hyperspectral parameters and vegetation index with the nitrogen content of tobacco leaves was carried out one by one, and the prediction model was established by multiple linear regression using the variables with the best correlation coefficient. Results showed that the first derivative spectrum, EVI II and green peak position had strong correlation, which is suitable for introducing multivariate equations as independent variables. Finally, the modeling determination coefficient (R2) was 0.66, RMSE was 0.40, and MAPE was 11%. The validation results showed that R2 was 0.73, RMSE was 0.38, and MAPE was 8.33%, which proved that this model could accurately predict the nitrogen content of tobacco leaves and could meet the requirements of large-scale statistical monitoring of tobacco quality indicators in the field. Bangladesh J. Bot. 52(2): 575-584, 2023 (June) Special

Impact Of The Taxpayer Understanding And Awareness, Tax Sanctions, Fiscus Services, E-Filing System On Taxpayer Compliance In Jakarta During The Covid-19 Pandemic

Objective – The objective of this paper is to examine the ways understanding and aware of taxpayers are regarding understanding and awareness of taxes, penalties, tax authorities, and electronic filing systems for taxpayers regarding taxpayer compliance in the DKI Jakarta area.. Design/methodology – The method of this study is quantitative. As part of this quantitative study, it is not in the form of statistics, but through the process of collecting data by distributing questionnaires and using sampling methods that aim to eliminate the problem of extensive data collection to make population conclusions so that data collection will be practical, cost-effective and convenient. The sampling technique is measurement model analysis in the outer model and structural model analysis in the inner model employing SmartPLS 3 Multivariate Structural Equation Model (SEM). Results – Partially the findings of this research suggest that the electronic filing system affects taxpayer compliance. Understanding and awareness of taxpayers has tax sanctions have had no effect on taxpayer compliance no effect on tax authorities' and taxpayers' compliance services have no effect on taxpayer compliance. The square root of R, or R2 simultaneously is 0.504 or 50.4%, This indicates that factors that influence compliance by taxpayers understanding and awareness of taxpayers, tax sanctions, tax authorities and e-filing systems of 50.4%. The contribution of this research shows that the electronic filing system a impact on compliance by taxpayers, in this instance taxpayers must learn more about taxes and the government must provide education and an adequate system for taxpayers. Research limitations/implications – The weakness of this study is that the number of respondents who are taxpayers registered at the DKI Jakarta KPP is still limited and does not represent the sample as a whole. The implication is that conclusions cannot be generalized and cannot be used as the main reference The number of taxpayers during a pandemic situation was reluctant to report and pay taxes, this had an impact on the level of compliance Novelty/Originality – The novelty of this study is that there are samples taken from the Covid pandemic, the variables of awareness and concern use different indicators.

Specificity of affective dynamics of bipolar and major depressive disorder.

Here, we examine whether the dynamics of the four dimensions of the circumplex model of affect assessed by ecological momentary assessment (EMA) differ among those with bipolar disorder (BD) and major depressive disorder (MDD). Participants aged 11-85years (n=362) reported momentary sad, anxious, active, and energetic dimensional states four times per day for 2weeks. Individuals with lifetime mood disorder subtypes of bipolar-I, bipolar-II, and MDD derived from a semistructured clinical interview were compared to each other and to controls without a lifetime history of psychiatric disorders. Random effects from individual means, inertias, innovation (residual) variances, and cross-lags across the four affective dimensions simultaneously were derived from multivariate dynamic structural equation models. All mood disorder subtypes were associated with higher levels of sad and anxious mood and lower energy than controls. Those with bipolar-I had lower average activation, and lower energy that was independent of activation, compared to MDD or controls. However, increases in activation were more likely to perpetuate in those with bipolar-I. Bipolar-II was characterized by higher lability of sad and anxious mood compared to bipolar-I and controls but not MDD. Compared to BD and controls, those with MDD exhibited cross-augmentation of sadness and anxiety, and sadness blunted energy. Bipolar-I is more strongly characterized by activation and energy than sad and anxious mood. This distinction has potential implications for both specificity of intervention targets and differential pathways underlying these dynamic affective systems. Confirmation of the longer term stability and generalizability of these findings in future studies is necessary.

Association between niacin intake and depression: A nationwide cross-sectional study

BackgroundThe association between dietary intake and depression is receiving increasing attention. However, the relationship between depressive symptoms and niacin intake is still unclear. The purpose of this study was to explore the association between niacin intake and depressive symptoms. MethodsWe used univariate analysis and multivariate logistic regression equations to explore the association between covariates or niacin intake and depression. Generalized additive models and smoothing fitted curves were used to examine the presence of nonlinear relationships. Upon finding a nonlinear relationship, a recursive algorithm was used to calculate the inflection point . Population differences were also explored through stratified analysis. ResultsIn the model adjusted for all covariates，the ORs (95 % CI) for the association between niacin intake and depression were 0.94 (0.87, 1.01), which was no statistical significance. However, the result of the linear trend test with quartiles of niacin intake indicated the association between niacin intake and depression may be U-shaped. The generalized additive model confirmed this U-shaped relationship, finding an inflection point (26.6 mg/d). An opposite relationship was observed before and after the inflection point, with ORs (95 % CI) of 0.77 (0.68, 0.87) before the inflection point and 1.13 (1.01, 1.28) after the inflection point. The association in men, Mexican American, White, adults aged<40, and BMI <30 was consistent with the overall tendency. ConclusionWe found a U-shaped association between niacin intake and depression in the general American population, and the same association was observed in men, Mexican American, White, adults aged < 40, and BMI < 30.