Linear Approach Research Articles

A window into the forest: post‐release behaviour of rehabilitated Bornean sun bears Helarctos malayanus euryspilus in Sabah, Malaysia

As the number of threatened wildlife species increases globally, captive rehabilitation and release of wild caught animals plays an increasingly significant role in conservation efforts, particularly where poaching threatens wild populations. Sun bear Helarctos malayanus populations are decreasing globally, with habitat loss and fragmentation and poaching as key threats to the species. This study aimed to assess post‐release behaviour of rehabilitated sun bears (n = 12) using GPS‐collar data to inform ongoing efforts to rehabilitate wild caught bears. We assessed spatial patterns of movement using kernel density estimates and utilisation distributions. We utilised an information theory (IT) and generalised linear modelling approach to assess temporal patterns of sun bear movement (n = 9). Post‐release home range estimates (mean = 56.68 km2, range:1.9–202.4) and behaviour varied widely between bears, with no significant difference in home range size between males (n = 3) and females (n = 6). Home ranges of most bears stabilised within the first month. Bears that were rehabilitated and released together did not spend a significant amount of time together following release. Bears were most active during daytime hours and most established a post‐release home range encompassing the riverside. The ultimate success of the releases is unknown, due to collar malfunction and damage, and the inaccessibility of the study terrain. We find that future releases of sun bears would benefit from soft‐release and in situ rehabilitation techniques. This study provides important insights into the complexity of bear reintroductions informing future rehabilitation and releases for threatened bear species.

The impact of syndemic burden, age, and sexual minority status on internalized HIV stigma among people living with HIV in South Florida.

Internalized HIV stigma has been associated with several poor mental and physical health outcomes among people living with HIV (PLWH); yet, little research has explored how internalized HIV stigma may be affected by syndemic burden. This study sought to examine the relationship between syndemic conditions and HIV stigma over and above the potential effects of two social determinants of health, age and sexual minority status, using a linear regression approach (N = 1343). Syndemic burden was significantly positively associated with internalized HIV stigma above and beyond the effects of age and sexual minority status (b = 0.23). Additionally, age (b = -0.02) and being a sexually minority (b = -0.31) were significantly negatively associated with internalized HIV stigma. Findings should inform future treatment targets for this population by specifically working to reduce internalized HIV stigma for people with a greater syndemic burden and, potentially, among young adults and heterosexual PLWH.

Serum urate levels and neurodegenerative outcomes: a prospective cohort study and mendelian randomization analysis of the UK Biobank

BackgroundPrevious studies on the associations between serum urate levels and neurodegenerative outcomes have yielded inconclusive results, and the causality remains unclear. This study aimed to investigate whether urate levels are associated with the risks of Alzheimer’s disease and related dementias (ADRD), Parkinson’s disease (PD), and neurodegenerative deaths.MethodsThis prospective study included 382,182 participants (45.7% men) from the UK Biobank cohort. Cox proportional hazards models were used to assess the associations between urate levels and risk of neurodegenerative outcomes. In the Mendelian randomization (MR) analysis, urate-related single-nucleotide polymorphisms were identified through a genome-wide association study. Both linear and non-linear MR approaches were utilized to investigate the potential causal associations.ResultsDuring a median follow-up period of 12 years, we documented 5,400 ADRD cases, 2,553 PD cases, and 1,531 neurodegenerative deaths. Observational data revealed that a higher urate level was associated with a decreased risk of ADRD (hazard ratio [HR]: 0.93, 95% confidence interval [CI]: 0.90, 0.96), PD (HR: 0.87, 95% CI: 0.82, 0.91), and neurodegenerative death (HR: 0.88, 95% CI: 0.83, 0.94). Negative linear associations between urate levels and neurodegenerative events were observed (all P-values for overall < 0.001 and all P-values for non-linearity > 0.05). However, MR analyses yielded no evidence of either linear or non-linear associations between genetically predicted urate levels and the risk of the aforementioned neurodegenerative events.ConclusionAlthough the prospective cohort study demonstrated that elevated urate levels were associated with a reduced risk of neurodegenerative outcomes, MR analyses found no evidence of causality.

Integrating financial literacy, regulatory technology, and decentralized finance: A new paradigm in Fintech evolution

This study investigates the implications of the interaction of financial literacy, regulatory technology, and decentralized finance applications for financial sector development. A two-step analytical regression approach on EViews 10 was used, which performs a one-factor analysis for each variable to identify the individual impact of each factor. A linear FMOLS approach was used to evaluate the cooperative effect of integration. The methodology was implemented on a dataset comprising 2,880 observations from 23 financial institutions in Jordan.The findings support the hypothesized dynamic interrelations between the essential Fintech factors relevant to the sustainable development of the financial sector, including significant and insignificant factors with the impact of inflation, which provides an adequate understanding of Fintech’s evolution. Additionally, the outcomes consider post-2017 regulatory changes that reflect the role of supervision and regulation for the financial sector’s flexibility and efficiency. Therefore, the results reveal the essential contribution of integrating decentralized finance applications, financial literacy, and regulatory technology to the development of Jordan’s financial sector. Financial literacy serves as a facilitator, regulatory technology is a compliance enabler, and decentralized finance applications are driving forces of innovation and financial inclusion, ensuring a robust and sustainable financial ecosystem. It is shown that the interaction of factors forces the sector’s development, reflecting the world’s trend in digital inclusion and viable financial development.

Transcranial alternating current stimulation over frontal eye fields mimics attentional modulation of visual processing.

Attentional control over sensory processing has been linked to neural alpha oscillations and related inhibition of cerebral cortex. Despite the wide consensus on the functional relevance of alpha oscillations for attention, precise neural mechanisms of how alpha oscillations shape perception and how this top-down modulation is implemented in cortical networks remain unclear. Here, we tested the hypothesis that alpha oscillations in frontal eye fields (FEF) are causally involved in the top-down regulation of visual processing in humans (male and female). We applied sham-controlled, intermittent transcranial alternating current stimulation (tACS) over bilateral FEF at either 10 Hz (alpha) or 40 Hz (gamma) to manipulate attentional preparation in a visual discrimination task. Under each stimulation condition, we measured psychometric functions for contrast perception and introduced a novel linear mixed modeling approach for statistical control of neurosensory side effects of the electric stimulation. TACS at alpha frequency reduced the slope of the psychometric function, resulting in improved sub-threshold and impaired super-threshold contrast perception. Side effects on the psychometric functions were complex and showed large interindividual variability. Controlling for the impact of side effects on the psychometric parameters by using covariates in the linear mixed model analysis reduced this variability and strengthened the perceptual effect. We propose that alpha tACS over FEF mimicked a state of endogenous attention by strengthening a fronto-occipitoparietal network in the alpha band. We speculate that this network modulation enhanced phasic gating in occipitoparietal cortex leading to increased variability of single-trial psychometric thresholds, measurable as a reduction of psychometric slope.Significance statement Attention is fundamental to the voluntary control of perception and behavior. Yet, precise underlying neural mechanisms remain unclear. Here, we provide evidence for a vital role of frontal alpha oscillations in the regulation of gating of visual information by using intermittent transcranial alternating current stimulation (tACS). We show that modulation of frontal alpha oscillations affected the slope of psychometric functions of visual contrast perception, leading to contrast-dependent improvement and impairment of perception. Our data adds to work on alpha oscillations in spatial attention and studies on the psychometrics of attention. Furthermore, we introduce a novel approach for the statistical control of tACS side effects and thereby contribute to the ongoing debate on outcome variability in studies using transcranial neurostimulation methods.

Identification of Ground Response Parameters of Itanagar City, Arunachal Pradesh, India, Using Varying Seismic Intensities and Equivalent Linear Analysis Approach

Identification of Ground Response Parameters of Itanagar City, Arunachal Pradesh, India, Using Varying Seismic Intensities and Equivalent Linear Analysis Approach

Irr and equivalence of cash-flow streams, loans, and portfolios of bonds

AbstractWe show, through a Linear Algebra approach, that a general deterministic cash-flow stream admits a given Internal Rate of Return (irr, either constant or time-varying) if, and only if, it can be replicated by a suitable portfolio of bonds, each with yield to maturity equal to that same irr. Five particular replicating portfolios are examined, including and generalizing other representations known from the the literature, which allow for a unified, irr-based, interpretation of apparently diverse objects. Considering the amortization of a loan as a particular case, further equivalences are found and lead to some original consideration.

Hunting stability control of high-speed bogie based on active yaw damper

Hunting stability is an inherent property of railway vehicles that determines the operational speed. This paper establishes a half-vehicle model with nonlinear wheel/rail equivalent conicity and interactive forces. Additionally, the dynamic performances of vehicle under various levels of wheel wear with passive suspension are compared and analyzed. Importantly, the investigation delves into the hunting stability of the vehicle system, employing both linear and nonlinear control approaches. The results demonstrate a notable reduction in critical speed during the end-worn period with a passive suspension. However, this reduction can be substantially countered through the application of active control, resulting in a significant speed increase. The implementation of stiffness control raises the frequency of limit cycles, whereas damping control serves to diminish it. Notably, an appropriate linear cubic stiffness control effectively mitigates the amplitudes of limit cycles during instances of instability. Moreover, the control strategy derived from the simplified model is extended to enhance the stability of the entire vehicle system. The research findings hold the potential to offer a promising strategy for the active control of high-speed vehicles, particularly during periods of wheel wear.

Fintech's influence on green credit provision: Empirical evidence from China’s listed banking sector

We explore the impact of financial technology (fintech) advancements on green credit provision, investigating publicly traded banks in China from 2007 to 2022. We particularly focus on credit modelling innovation, examining the non-linear dynamics between fintech evolution and green credit distribution. Results reveal a positive U-shaped correlation. Initial stages of fintech are associated with increased green credit risk, negatively affecting the volume of green credit. However, more established fintech infrastructures significantly enhance green credit volumes by improving resource allocation and credit risk assessment. Utilizing a multiple linear regression approach, we highlight the transformative nature of fintech in advancing sustainable banking practices, particularly through innovations in credit modeling that enhance green credit risk management and resource allocation efficiency.

Mindfulness and psychological capital: examining the role of intention from the person perspective in a multi-week mindfulness training program

PurposeWhen evaluating the efficacy of mindfulness interventions, most studies take a linear approach to explore how an intervention impacts different outcomes for individuals, and rarely is the role of intention examined. This research takes a configural approach to consider how various elements of a participant’s training expectations and their experience in the training condition combine to predict increases in psychological capital.Design/methodology/approachEmployees from hospital settings were randomized into three conditions (mindfulness training, active control (Pilates), and wait-list control group) and completed surveys at three time points (baseline, post-training and three months post-training). A qualitative comparative analysis was applied to see what combinations of motivational elements were associated with increases in psychological capital.FindingsWe find that all three conditions can boost their psychological capital based on different configurations involving efficacy beliefs, baseline states of well-being (psychological capital and perceived stress) and changes in levels of mindfulness and perceived stress.Research limitations/implicationsIndividual characteristics, like motivation, expectancy and baseline needs, are an important consideration in addition to the training condition itself when determining whether a training is efficacious.Practical implicationsIt is of increasing importance that organizations find ways to support employee well-being. Offering a variety of psychological and physical interventions can improve psychological capital. Applying needs assessments that clarify the desires, needs and expectations employees hold may help with intervention efficacy.Originality/valueThe current study offers an innovative methodology through which realist evaluation approaches can consider multiple factors to predict outcomes.

Comparison of linear and nonlinear modeling approaches to develop an abundance index based on voyage and market data for a data-limited fishery

IntroductionWorldwide coastal fish resources face severe threats from fisheries overexploitation. However, the evaluation of abundance trends in most coastal fisheries is constrained by limited data. This study took blackmouth croaker (Atrobucca nibe), a stock depleted by coastal trawl fishery in southwestern Taiwan, as an example to showcase the development of a relative abundance index from data-limited fishery (only landing data were available).MethodsThis study employed unique data sourcing from voyage data recorders (VDRs) to estimate fishing effort (in combination with landing data to estimate the catch per unit effort, CPUE) that demonstrated the potential application in global data-limited fisheries and assessed alternative approaches for predictors of fishery-targeting practices to condition effort for producing more accurate metrics of relative abundance. The nominal CPUE was standardized using three statistical models: generalized linear model, generalized additive model (GAM), and vector-autoregressive spatiotemporal models (VASTs) with two treatments of each of the four effects: environmental (sea temperature, salinity, density of mixing layer, seafloor temperature, and chlorophyll), vessel, spatial, and targeting effects. A total of 15 models were designed and compared for these effects, and their explanatory power (EP) was evaluated using cross-validation R2 and other metrics.Results and discussionResults indicated that the targeting effect exerted the most significant influence on standardization and was suggested to be addressed through the principal component analysis (PCA) approach. Both vessel and spatial effects demonstrated considerable influence, whereas the environmental effect exhibited a limited impact, possibly due to the small fishing area in this study. Regarding models’ EP, given the nonlinear nature of the PCA algorithm and environmental data, the study highlighted the superiority of the GAM over linear-based models. However, incorporating nonlinear features in VAST (M15) makes it the most effective model in terms of predictive power in this study. Concerning the stock status, despite variations in relative CPUE trends among major models, a general declining trend since 2015 signals the potential decline of the blackmouth stock and urges fishery managers to consider further design of management measures.

Causal association of blood cell traits with inflammatory bowel diseases: a Mendelian randomization study

BackgroundObservational studies have found associations between blood cell traits and inflammatory bowel diseases (IBDs), whereas the causality and dose-effect relationships are still undetermined.MethodsTwo-sample Mendelian randomization (MR) analyses using linear regression approaches, as well as Bayesian model averaging (MR-BMA), were conducted to identify and prioritize the causal blood cell traits for Crohn’s disease (CD) and ulcerative colitis (UC). An observational study was also performed using restricted cubic spline (RCS) to explore the relationship between important blood cell traits and IBDs.ResultsOur uvMR analysis using the random effects inverse variance weighted (IVW) method identified eosinophil (EOS) as a causal factor for UC (OR = 1.36; 95% CI: 1.13, 1.63). Our MR-BMA analysis further prioritized that high level of lymphocyte (LYM) decreased CD risk (MIP = 0.307; θ^MACE = −0.059; PP = 0.189; θ^λ = −0.173), whereas high level of EOS increased UC risk (MIP = 0.824; θ^MACE = 0.198; PP = 0.627; θ^λ = 0.239). Furthermore, the observational study clearly depicts the nonlinear relationship between important blood cell traits and the risk of IBDs.ConclusionUsing MR approaches, several blood cell traits were identified as risk factors of CD and UC, which could be used as potential targets for the management of IBDs. Stratified genome-wide association studies (GWASs) based on the concentration of traits would be helpful owing to the nonlinear relationships between blood cell traits and IBDs, as demonstrated in our clinical observational study. Together, these findings could shed light on the clinical strategies applied to the management of CD and UC.

Muscle fatigue detection based on sEMG signal using autocorrelation function and neural networks

Abstract Feature extraction from an recorded surface electromyography (sEMG) signal plays an important role in identifying and quantifying the characteristics of muscle activities. These features can be used for various applications like muscle function assessment, muscle fatigue detection, etc. Common features extracted from sEMG signal are time-domain or frequency-domain features. However, features which are sensitive to uncertainties in the signal like noise, movement artifacts, and outliers should be avoided. Autocorrelation function (ACF), which is a measure of similarity between a signal and its time delayed version, is considered in this work as a feature to overcome the impact of noise, artifacts, and outliers. An artificial neural network (ANN) is developed to differentiate between fatigue and non-fatigue conditions using the calculated ACF from sEMG segments. The performance of an ANN model that can be adapted by means of various regularization methods was investigated. The proposed ANN model achieved an accuracy of about 97.62 %, a precision of about 95.50 % and a sensitivity of about 100 % in the classification of fatigue and non-fatigue sEMG segments, outperforming k-means and linear support vector machine approaches that served as references.

Frictional Behavior of Chestnut (Castanea sativa Mill.) Sawn Timber for Carpentry and Mechanical Joints in Service Class 2

Wood is poised to become a material of choice for future construction. When appropriately managed, it is a renewable material with unique mechanical properties. Thus, there has been a growing demand for hardwoods, including Castanea sativa Mill., the focal point of this investigation, for structural applications. Albeit in a limited capacity, Eurocode 5-2 offers friction coefficients for softwoods, but it falls short for hardwoods. These coefficients play a critical role in numerical simulations involving friction, enabling the optimization of joints and, by extension, the overall structural integrity. Test samples were evaluated at 15% and 18% moisture content (Service Class 2) for various orientations of timber-to-timber and timber-to-steel friction. The results provide an experimental database for numerical simulations and highlight the influence of moisture on the stick–slip phenomenon, which was absent for the timber-to-timber tests, as well as on the rising friction values. At 18%, the static and kinetic coefficients were 0.70 and 0.48 for timber-to-timber and 0.5 and 0.50 for timber-to-steel. The increase was around 50% for timber-to-timber friction and over 170% for timber-to-steel pairs. Moreover, the findings proved a relationship between both coefficients and the validity of the linear estimation approach within the 12–18% moisture commonly applied to softwoods.

Contribution of energy based circularity for better environmental quality: an evidence from Bias-corrected linear dynamic approach

Environmental behavior needs a keen intervention to avoid the upcoming worse outcomes of the energy utilization. Global warming is transitioning towards the global boiling stage and the reason behind the faster growth of renewable energy resources exploration. The present study empirically investigates the circularity impact of the renewable energy on the environment. Two different models of the environment were estimated by applying biased corrected method on 28 low income countries from 1990 to 2019. In this study, we develop a circularity index on the basis of renewable energy sources and found that in low income economies circularity brings a positive impact on the environment in both models. The study also concludes that digitization has also positive implication in terms of environmental quality. In the sample study trade shows negative as well as positive association with environment while economic growth, financial development and energy use have positive impact on the environment. The study suggested policies based on the circular practices for energy generation to achieve the sustainable development goals.

Enhancing cubic polynomial solutions: A comprehensive analysis and iterative refinement strategy in response to the versatility of cubic equations of state

The study presents a comprehensive evaluation of ten distinct methods for solving cubic equations, encompassing both analytical, numerical, and linear algebra-based approaches. Among these, an analytical technique involving the transformation of cubic equations into Chebyshev polynomials emerged as the most efficient. To mitigate issues arising from numerical round-off errors, the study proposes an iterative refinement strategy. Furthermore, the research introduces a novel criterion grounded in Vieta's formulas to identify and isolate areas where round-off errors may occur. This criterion aids in the application of the proposed iterative refinement technique. The novel solution method, which involves the conversion of cubic equations into Chebyshev polynomials and subsequent error-checking and iterative refinement, exhibits significant advantages. Firstly, it proves efficient, reducing computational time by 15–20 % in comparison to the well-established Cardano analytical method. It also demonstrates robustness in effortlessly identifying regions of potential error and offers a method for iterative improvement when needed. Additionally, its reliability is underscored by its independence from the specific cubic equation of state under consideration, making it well-suited for the intensive solution of a wide range of cubic equations.

2D equivalent linear ground response analysis for randomized site profiles

AbstractLocal soil conditions play a crucial role in shaping ground surface responses and impacting the intensity of ground shaking. In this study, the influence of different site profiles on computed ground motion was investigated using a 2D equivalent linear analysis approach. Four distinct site profiles: sand, clay, sand-clay-sand-clay, and clay-sand-clay-sand profiles were considered. The results were presented using multiple metrics, including surface acceleration, displacement, modulus decreasing ratio, and coherence analysis. Notably, the clay profile significantly influenced ground motion, while the sand profile exhibited relatively lower seismic activity. This suggests that softer sites significantly influence ground motion, leading to potentially high levels of shaking.

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Nonlinear optimal control for robotic exoskeletons with electropneumatic actuators

Abstract PO3-19-04: The CROWN STUDY: A multicenter prospective cohort study of cardiovascular outcomes in premenopausal women with hormone receptor positive breast cancer treated with ovarian suppression and an aromatase inhibitor

Abstract Background: Treatment for premenopausal women with high or intermediate risk hormone receptor (HR)+ breast cancer (BC) includes the concurrent use of ovarian function suppression (OFS) and an aromatase inhibitor (AI) to induce near complete estrogen deprivation (NCED). The long-term cardiovascular (CV) sequela for women treated with NCED is unknown. Premature menopause in non-cancer populations is associated with CV disease. The CROWN study (CaRdiac Outcomes With Near complete estrogen deprivation) will use sophisticated imaging assessments of cardiac dysfunction to understand the evolution of CV injury, as well as biomarker and demographic correlates, with the goal of developing tools to assess and mitigate CV risk. Methods: This is a NIH funded prospective cohort study conducted at 3 regional NCI-supported Cancer Centers (Atrium Health Wake Forest Baptist, Virginia Commonwealth and Duke) that will include premenopausal women, age ≤ 55, with Stage I-III BC following completion of planned chemotherapy, surgery and radiation with an ECOG 0-1. HR+ BC patients will receive an AI and OFS. Women with HR- BC are included as comparators. CV imaging and biomarkers will be obtained at baseline, 1 year and 2 years (Table 1). These assessments will include serial cardiac magnetic resonance (CMR) and coronary computed tomography angiography (CCTA) imaging as well as laboratory measurements, including exploratory biomarkers. The primary objective is to determine the 24-month difference in stress myocardial blood flow as measured by adenosine CMR imaging in both groups. We will correlate CMR imaging with CCTA to provide complementary detail of coronary plaque changes. The study will also assess the relevance of pre-existing risk factors on study outcomes, including an emphasis on racial disparities, and dynamic change in modifiable and treatment related risk factors. We plan to enroll 90 women, 67 in the NCED group and 23 in the HR-group, allowing for a 10% drop out rate. There are two primary types of statistical analyses. The first includes testing hypotheses between group (NCED vs HR-) and within group (longitudinal changes within the NCED group). The second analyses, involve developing predictive equations utilizing a stepwise linear regression approach to determine if patient demographics, clinical parameters and serum biomarkers are associated with cardiovascular changes over time. A total of 17 patients are enrolled as of 07/2023. NCT05309655 Study Procedures XX- XX Citation Format: Susan Dent, Emily Douglas, Sarah Hatcher, Katherine Ansley, Carolyn Park, Nathaniel O'Connell, Mary Hackney, Ralph D'Agostino, Rani Bansal, Renee Avecilla, Monica Brown, Kacey Clayton-Stiglbauer, Igor Klem, Jennifer Jordan, Alexandra Thomas. The CROWN STUDY: A multicenter prospective cohort study of cardiovascular outcomes in premenopausal women with hormone receptor positive breast cancer treated with ovarian suppression and an aromatase inhibitor [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-19-04.

Analytical solution to a coupled system including tuned liquid damper and single degree of freedom under free vibration with modal decomposition method

This research focuses on employing a linear analytical approach to transform free surface waves and velocities into mode coordinates, with the aim of investigating the free vibration behavior of a coupled system consisting of a Single Degree of Freedom and a sloshing tank. Through a series of manipulations and simplifications of the coupled equations, a fourth-order ordinary differential equation is derived to showcase the overall response of the system, highlighting the contribution of each odd mode. Key concepts explored include system stability, mode-specific natural periods, establishment of initial boundary conditions, and formulation of the complete system response. The analytical method applied to study Tuned Liquid Dampers, a type of elevated sloshing tank, reveals that in higher modes, the lower frequency aligns with the structural natural frequency, while the higher frequency is approximately n times the structural natural frequency (where n is the odd mode number). This approach also elucidates why the system's response does not exhibit a higher-frequency component in higher modes. The study further investigates concepts such as employing an initial perturbation to excite higher frequencies and the potential for approximating the system through the first mode. Additionally, a numerical model was developed using variable separation and modal decomposition methods to complement and validate the analytical approach. Finally, further verification of the model was performed using the Preismann scheme applied to the relevant equations and the central upwind applied to nonlinear equations.