Corporate capital structure effects on corporate performance pursuing a strategy of innovation in manufacturing companies

Within the sphere of finance, the concept of capital structure has long been a subject of intense debate, serving as a quantitative depiction of the balance between debt, preference shares, and common stock within a company. This structure serves a crucial role in optimizing the utilization of a company's existing resources while simultaneously elevating the revenue streams for stakeholders. This particular study delves into the intricate relationship between corporate performance and capital structure, focusing on 78 publicly listed firms within the Dhaka Stock Exchange (DSE). Bangladesh holds the 29th position globally in terms of purchasing power, lending significant weight to this investigation. To comprehensively analyze this correlation, panel data encompassing the span from 2017 to 2021 was collected for these 78 sample companies operating within the DSE. Several key determinants of capital structure were considered in this analysis, namely the debt-to-equity ratio, short-term leverage ratio, long-term leverage ratio, and total debt ratio. Meanwhile, the performance of these firms was gauged using key metrics such as Return on Assets (ROA), Return on Equity (ROE), and Earnings Per Share (EPS). To ensure a robust analysis, factors such as inflation, liquidity, growth rate, tax rate, and firm size were meticulously controlled for. The findings unveiled a compelling narrative: all forms of debt ratios—be it short-term, long-term, or the total debt ratio—exhibited a substantial negative impact on ROA at a significant level of 1 %. Conversely, specific debt ratios, like the short-term total debt and the total debt-to-total asset ratio, displayed a notable positive correlation with ROE at a 1 % significance level. Intriguingly, the long-term total debt ratio yielded a negative and insignificant effect on ROE. Moreover, within the spectrum of predictors influencing a firm's performance, the liquidity ratio emerged as a non-significant factor—a notable discovery that highlights the nuanced nature of the interplay between capital structure and performance within these companies.</p

Detecting Autism Spectrum Disorder Using Spectral Analysis of Electroretinogram and Machine Learning: Preliminary results

Autism spectrum disorder (ASD) is a neurodevelopmental condition that impacts language, communication and social interactions. The current diagnostic process for ASD is based upon a detailed multidisciplinary assessment. Currently no clinical biomarker exists to help in the diagnosis and monitoring of this condition that has a prevalence of approximately 1%. The electroretinogram (ERG), is a clinical test that records the electrical response of the retina to light. The ERG is a promising way to study different neurodevelopmental and neurodegenerative disorders, including ASD. In this study, we have proposed a machine learning based method to detect ASD from control subjects using the ERG waveform. We collected ERG signals from 47 control (CO) and 96 ASD individuals. We analyzed ERG signals both in the time and the spectral domain to gain insight into the statistically significant discriminating features between CO and ASD individuals. We evaluated the machine learning (ML) models using a subject independent cross validation-based approach. Time-domain features were able to detect ASD with a maximum 65% accuracy. The classification accuracy of our best ML model using time-domain and spectral features was 86%, with 98% sensitivity. Our preliminary results indicate that spectral analysis of ERG provides helpful information for the classification of ASD

New approaches in W-gravities

We have devoted an effort to study some nonlinear actions, characteristics of the ${\cal W}$-theories, in the framework of the soldering formalism. We have disclosed interesting new results concerning the embedding of the original chiral ${\cal W}$-particles in different metrical spaces in the final soldered action, i.e., the metric gets modified by the soldering interference process. The results are presented in a weak field approximation for the ${\cal W}_N$ case when N is greater than 3 and also in an exact way for ${\cal W}_2$. We have promoted a generalization of the interference phenomena to ${\cal W}_N$-theories of different chiralities and shown that the geometrical features introduced can yield a new understanding about the interference formalism in quantum field theories.Comment: 28 pages, Late

Dihexyl-Substituted Poly(3,4-Propylenedioxythiophene) as a Dual Ionic and Electronic Conductive Cathode Binder for Lithium-Ion Batteries

The polymer binders used in most lithium-ion batteries (LIBs) serve only a structural role, but there are exciting opportunities to increase performance by using polymers with combined electronic and ionic conductivity. To this end, here we examine dihexyl-substituted poly(3,4-propylenedioxythiophene) (PProDOT-Hx₂) as an electrochemically stable π-conjugated polymer that becomes electrically conductive (up to 0.1 S cm⁻¹) upon electrochemical doping in the potential range of 3.2 to 4.5 V (vs Li/Li⁺). Because this family of polymers is easy to functionalize, can be effectively fabricated into electrodes, and shows mixed electronic and ionic conductivity, PProDOT-Hx₂ shows promise for replacing the insulating polyvinylidene fluoride (PVDF) commonly used in commercial LIBs. A combined experimental and theoretical study is presented here to establish the fundamental mixed ionic and electronic conductivity of PProDOT-Hx₂. Electrochemical kinetics and electron spin resonance are first used to verify that the polymer can be readily electrochemically doped and is chemically stable in a potential range of interest for most cathode materials. A novel impedance method is then used to directly follow the evolution of both the electronic and ionic conductivity as a function of potential. Both values increase with electrochemical doping and stay high across the potential range of interest. A combination of optical ellipsometry and grazing incidence wide angle X-ray scattering is used to characterize both solvent swelling and structural changes that occur during electrochemical doping. These experimental results are used to calibrate molecular dynamics simulations, which show improved ionic conductivity upon solvent swelling. Simulations further attribute the improved ionic conductivity of PProDOT-Hx₂ to its open morphology and the increased solvation is possible because of the oxygen-containing propylenedioxythiophene backbone. Finally, the performance of PProDOT-Hx₂ as a conductive binder for the well-known cathode LiNi_(0.8)Co_(0.15)Al_(0.05)O₂ relative to PVDF is presented. PProDOT-Hx₂-based cells display a fivefold increase in capacity at high rates of discharge compared to PVDF-based electrodes at high rates and also show improved long-term cycling stability. The increased rate capability and cycling stability demonstrate the benefits of using binders such as PProDOT-Hx₂, which show good electronic and ionic conductivity, combined with electrochemical stability over the potential range for standard cathode operation

Comparison of Electrodermal Activity from Multiple Body Locations Based on Standard EDA Indices’ Quality and Robustness against Motion Artifact

The most traditional sites for electrodermal activity (EDA) data collection, palmar locations such as fingers or palms, are not usually recommended for ambulatory monitoring given that subjects have to use their hands regularly during their daily activities, and therefore, alternative sites are often sought for EDA data collection. In this study, we collected EDA signals (n = 23 subjects, 19 male) from four measurement sites (forehead, back of neck, finger, and inner edge of foot) during cognitive stress and induction of mild motion artifacts by walking and one-handed weightlifting. Furthermore, we computed several EDA indices from the EDA signals obtained from different sites and evaluated their efficiency to classify cognitive stress from the baseline state. We found a high within-subject correlation between the EDA signals obtained from the finger and the feet. Consistently high correlation was also found between the finger and the foot EDA in both the phasic and tonic components. Statistically significant differences were obtained between the baseline and cognitive stress stage only for the EDA indices computed from the finger and the foot EDA. Moreover, the receiver operating characteristic curve for cognitive stress detection showed a higher area-under-the-curve for the EDA indices computed from the finger and foot EDA. We also evaluated the robustness of the different body sites against motion artifacts and found that the foot EDA location was the best alternative to other sites

GAZEDA- Gaze-guided Cinematic Editing of Wide-Angle Monocular Video Recordings

We present GAZEDA- eye GAZe-guided EDiting for videos captured by a solitary, static, wide-angle and high-resolution camera. Eye-gaze has been effectively employed in computational applications as a cue to capture interesting scene content; we employ gaze as a proxy to select shots for inclusion in the edited video. Given the original video, scene content and user eye-gaze tracks are combined to generate an edited video comprising cinematically valid actor shots and shot transitions to generate an aesthetic and vivid representation of the original narrative. We model cinematic video editing as an energy minimization problem over shot selection, whose constraints capture cinematographic editing conventions. Gazed scene locations primarily determine the shots constituting the edited video. Effectiveness of GAZED against multiple competing methods is demonstrated via a psychophysical study involving 12 users and twelve performance videos.</p