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Highlights This review offers an overview of recent advancements in conjugated polymers (CPs), with a thorough discussion of their molecular engineering. Key electronic properties are put forth that complement traditional inorganic semiconductor devices. Key concepts and innovations in molecular engineering are discussed, highlighting advancements that improve device performance, with a particular focus on photovoltaics, organic field-effect transistors, and nonvolatile memory devices. The current challenges in fabricating CP-based devices are explored, along with anticipated future developments and growing market demand. Conjugated polymers (CPs) have emerged as an interesting class of materials in modern electronics and photonics, characterized by their unique delocalized π-electron systems that confer high flexibility, tunable electronic properties, and solution processability. These organic polymers present a compelling alternative to traditional inorganic semiconductors, offering the potential for a new generation of optoelectronic devices. This review explores the evolving role of CPs, exploring the molecular design strategies and innovative approaches that enhance their optoelectronic properties. We highlight notable progress toward developing faster, more efficient, and environmentally friendly devices by analyzing recent advancements in CP-based devices, including organic photovoltaics, field-effect transistors, and nonvolatile memories. The integration of CPs in flexible sustainable technologies underscores their potential to revolutionize future electronic and photonic systems. As ongoing research pushes the frontiers of molecular engineering and device architecture, CPs are poised to play an essential role in shaping next-generation technologies that prioritize performance, sustainability, and adaptability.

This research presents work on control of a prosthetic arm using surface electromyography (sEMG) signals acquired from triceps and biceps of fifteen healthy and four amputated subjects. Myo armband was used to acquire sEMG signals corresponding to four different arm motions: elbow extension, elbow flexion, wrist pronation, and wrist supination. Ten time-domain features were extracted and considered for classification to recognize the four-arm motions. These features and their various combinations were used to train four different classifiers, in both offline and real-time settings. It was found that the combination of signal mean and waveform length as a feature and k-nearest neighbors as classifier performed significantly better (p < 0.05) than all other combinations in both offline and real-time settings. The offline accuracies of 95.8% and 68.1% and real-time accuracies of 91.9% and 60.1% were obtained for healthy and amputated subjects, respectively. Results obtained using the presented scheme successfully demonstrate that using suitable features and classifier, classification accuracies can be significantly improved for transhumeral prosthesis, thereby, providing better, wearable and non-invasive control of prostheses using sEMG signals.

This study reports light energy harvesting characteristics of bismuth ferrite (BiFeO 3 ) and BiFO 3 doped with rare-earth metals such as neodymium (Nd), praseodymium (Pr), and gadolinium (Gd) dye solutions that were prepared by using the co-precipitation method. The structural, morphological, and optical properties of synthesized materials were studied, confirming that 5–50 nm sized synthesized particles have a well-developed and non-uniform grain size due to their amorphous nature. Moreover, the peaks of photoelectron emission for bare and doped BiFeO 3 were observed in the visible region at around 490 nm, while the emission intensity of bare BiFeO 3 was noticed to be lower than that of doped materials. Photoanodes were prepared with the paste of the synthesized sample and then assembled to make a solar cell. The natural and synthetic dye solutions of Mentha, Actinidia deliciosa , and green malachite, respectively, were prepared in which the photoanodes were immersed to analyze the photoconversion efficiency of the assembled dye-synthesized solar cells. The power conversion efficiency of fabricated DSSCs, which was confirmed from the I–V curve, is in the range from 0.84 to 2.15%. This study confirms that mint ( Mentha ) dye and Nd-doped BiFeO 3 materials were found to be the most efficient sensitizer and photoanode materials among all the sensitizers and photoanodes tested.

Plant triterpenoids represent a diverse group of secondary metabolites and are thought to be valuable for therapeutic applications. For drug development, lead optimization, better knowledge of biological pathways, and high-throughput detection of secondary metabolites in plant extracts are crucial. This paper describes a qualitative method for the rapid and accurate identification of various triterpenoids in plant extracts using the LC-HR-ESI-MS/MS tool in combination with the data-dependent acquisition (DD) approach. A total of 44 isolated, purified, and characterized triterpenoids were analyzed. HR-MS spectra and tandem mass spectra (MS/MS) of each compound were recorded in the positive ionization mode in two different sets of collisional energies, i.e., (25–62.5 eV), and fixed collisional energies (10, 20, 30, and 40 eV). As a result, three triterpenoids were identified in all plant extracts using the retention time, high-resolution mass spectra, and/or MS/MS spectra. The developed method will be helpful with other plant extracts/botanicals, as well as in the search for new triterpenoids in the kingdom Plantae.

Biofunctionalized polyacrylamide (PAAm) hydrogels are important 2D substrates for studying cell physics and mechanobiology. In this work, an arylmethylsulfone (MS) comonomer is developed that can be incorporated into PAAm gels under aqueous radical polymerization conditions. The resulting hydrogels show similar properties to unmodified PAAm gels, indicating that the comonomer is incorporated without affecting PAAm physical properties. The MS‐containing PAAm hydrogels allow efficient conjugation of thiol derivatized biomolecules and require very low comonomer content (2 mM, 0.18 mol% relative to AAm) and thiol incubation amounts (≥ 0.15 µg per gel) to achieve functional densities that elicit cell responses. Compared to carboxyl‐functionalized PAAm hydrogels, a 10‐fold lower comonomer concentration and a 10‐fold lower ligand feed concentration are sufficient to achieve comparable cell adhesion responses. The new comonomer opens up possibilities for efficient and straightforward biofunctionalization of PAAm hydrogels used in cell biophysical studies. A new methylsulfone comonomer is presented that can be integrated into polyacrylamide hydrogels for efficient biofunctionalization with thiol‐bearing ligands. Very low comonomer and ligand incubation amounts are required to achieve ligand densities that elicit cell responses, offering an efficient pathway to bioactive hydrogel surfaces for cell physics and mechanobiology studies.

Background: Dilated cardiomyopathy significantly impacts mortality and hospitalizations in the U.S., yet trends in dilated cardiomyopathy-related mortality are underreported. This retrospective study examines the trends in dilated cardiomyopathy-related mortality between 1999 and 2020. Methods: The Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database was analyzed to study the trends in dilated cardiomyopathy-related mortality. Age-adjusted mortality rates per 100,000 people and annual percent changes with 95% CIs were determined. Joinpoint regression analysis was used to assess the trends in the overall demographic, geographic, and place-of-death variables. Results: There were 168,702 dilated cardiomyopathy-related deaths reported between 1999 and 2020. The age-adjusted mortality rate declined from 3.40 in 1999 to 1.71 in 2020. Men unfailingly had a higher age-adjusted mortality rate than women. Non-Hispanic Black or African Americans had the highest age-adjusted mortality rate compared to other races, with a recent increase in annual percent change from 2015 to 2020. Hispanics, or Latinos, also showed an alarming rise in annual percent change of 11.10 from 2018 to 2020. Significant geographical variations were noted, with states in the top 90th percentile (Michigan, Washington, and Delaware) having approximately three times the age-adjusted mortality rate compared to states that fell in the lower 10th percentile. Conclusion: Despite overall declines, racial and regional disparities persist, owing to the growing clinical burden. Targeted research and interventions are key to addressing disparities and reducing dilated cardiomyopathy-related mortality.

This research study proposes a unique framework that takes input from a surface electromyogram (sEMG) and functional near-infrared spectroscopy (fNIRS) bio-signals. These signals are trained using convolutional neural networks (CNN). The framework entails a real-time neuro-machine interface to decode the human intention of upper limb motions. The bio-signals from the two modalities are recorded for eight movements simultaneously for prosthetic arm functions focusing on trans-humeral amputees. The fNIRS signals are acquired from the human motor cortex, while sEMG is recorded from the human bicep muscles. The selected classification and command generation features are the peak, minimum, and mean ΔHbO and ΔHbR values within a 2-s moving window. In the case of sEMG, wavelength, peak, and mean were extracted with a 150-ms moving window. It was found that this scheme generates eight motions with an enhanced average accuracy of 94.5%. The obtained results validate the adopted research methodology and potential for future real-time neural-machine interfaces to control prosthetic arms.

The current study used the deep machine learning approach to differentiate human blood specimens from cow, goat, and chicken blood stains based on cell morphology. A total of 1,955 known Giemsa-stained digitized images were acquired from the blood of humans, cows, goats, and chickens. To train the deep learning models, the well-known VGG16, Resnet18, and Resnet34 algorithms were used. Based on the image analysis, confusion matrices were generated. Findings showed that the F1 score for the chicken, cow, goat, and human classes were all equal to 1.0 for each of the three algorithms. The Matthews correlation coefficient (MCC) was 1 for chickens, cows, and humans in all three algorithms, while the MCC score was 0.989 for goats by ResNet18, and it was 0.994 for both ResNet34 and VGG16 algorithms. The three algorithms showed 100% sensitivity, specificity, and positive and negative predictive values for the human, cow, and chicken cells. For the goat cells, the data showed 100% sensitivity and negative predictive values with specificity and positive predictive values ranging from 98.5% to 99.6%. These data showed the importance of deep learning as a potential tool for the differentiation of the species of origin of fresh crime scene blood stains.

The Brief Inventory of Thriving (BIT) provides a holistic measure of well-being, but has only been validated for adults, and does not have a Hindi version. The present study investigated the unidimensional structure, internal consistency, convergent/discriminant, and criterion validity of both the original English version of the BIT (BIT-E) and its Hindi-translated version (BIT-H) among adolescents in India. Further, we tested measurement invariance across these two language versions, gender, and academic disciplines. A total of 534 adolescents were recruited across two samples ( N 1  = 224 and N 2  = 310) from five schools using convenience sampling. Both versions demonstrated excellent psychometric properties, with unidimensional structure, good internal consistency, convergent/discriminant, and criterion validity with a number of psycho-educational correlates. Partial scalar invariance was achieved across language versions and gender, while strict invariance was established across academic disciplines. The BIT, in both English and Hindi, appears to be an excellent measure of well-being for adolescents. Limitations, directions for future research, and recommendations for using the BIT-E and BIT-H among adolescents in research and applied settings are discussed.

Background: Inflammatory bowel disease (IBD) is associated with systemic inflammation and potential cardiovascular complications. This meta-analysis evaluates long-term cardiovascular risks in IBD. Methods: Electronic databases were searched for studies examining cardiovascular, cerebrovascular, and thromboembolic risks in IBD. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were pooled using a random-effects model. Results: Fifty-three studies comprising 1,406,773 patients were analyzed. IBD was linked to increased risk of ischemic heart disease (aHR 1.25; p = 0.001) myocardial infarction (aHR 1.25; p = 0.01), acute coronary syndrome (aHR 1.43; p < 0.00001), heart failure (aHR 1.24; p < 0.00001), atrial fibrillation (aHR 1.20; p < 0.00001), and stroke (aHR 1.13; p < 0.00001). Elevated risks were also observed for peripheral arterial disease (aHR 1.41; p < 0.00001), diabetes mellitus (aHR 1.40; p < 0.00001), venous thromboembolism (aHR 1.98; p < 0.00001), deep vein thrombosis (aHR 2.85; p = 0.0004), and pulmonary embolism (aHR 1.98; p = 0.03). Importantly, IBD was associated with increased cardiovascular (aHR 1.14; p = 0.03) and all-cause mortality (aHR 1.53; p < 0.00001). Conclusions: IBD patients face higher risk for adverse cardiovascular outcomes, thromboembolic disease, and mortality, necessitating early cardiovascular risk assessment and targeted interventions in this population.