Renewable Biocomposite Properties and their Applications

Recently, with increasing environmental awareness and expanding global waste problems, eco-friendly biofillers have been recognized as a promising alternative to inorganic fillers in the reinforcement of thermoplastic and biodegradable plastics. Therefore, many industries are seeking more eco-friendly materials that will decrease the level of environmental contamination and economic cost. Bacteria cellulose, rice straw, rice husk, natural fiber, lignocellulose, cellulose, and paper sludge are renewable resources owing many beneficial properties; these materials were used to manufacture composite products such as sound absorbing wooden construction materials, interior of bathrooms, wood decks, window frames, decorative trim, automotive panels, and industrial and consumer applications. This chapter elucidates the different renewable biocomposite properties and their applications

PPM1A Controls Diabetic Gene Programming through Directly Dephosphorylating PPAR?? at Ser273

Peroxisome proliferator-activated receptor gamma (PPAR gamma) is a master regulator of adipose tissue biology. In obesity, phosphorylation of PPAR gamma at Ser273 (pSer273) by cyclin-dependent kinase 5 (CDK5)/extracellular signal-regulated kinase (ERK) orchestrates diabetic gene reprogramming via dysregulation of specific gene expression. Although many recent studies have focused on the development of non-classical agonist drugs that inhibit the phosphorylation of PPAR gamma at Ser273, the molecular mechanism of PPAR gamma dephosphorylation at Ser273 is not well characterized. Here, we report that protein phosphatase Mg2+/Mn2+-dependent 1A (PPM1A) is a novel PPAR gamma phosphatase that directly dephosphorylates Ser273 and restores diabetic gene expression which is dysregulated by pSer273. The expression of PPM1A significantly decreases in two models of insulin resistance: diet-induced obese (DIO) mice and db/db mice, in which it negatively correlates with pSer273. Transcriptomic analysis using microarray and genotype-tissue expression (GTEx) data in humans shows positive correlations between PPM1A and most of the genes that are dysregulated by pSer273. These findings suggest that PPM1A dephosphorylates PPAR gamma at Ser273 and represents a potential target for the treatment of obesity-linked metabolic disorders

Intravitreal Bevacizumab (Avastin) as an Adjuvant for the Treatment of Posterior Scleritis

We report a case of posterior scleritis effectively managed with intravitreal bevacizumab. A 71-year-old woman was diagnosed with posterior scleritis. Although she was initially treated with systemic steroids, her clinical presentation deteriorated. She was then treated with a single intravitreal injection of bevacizumab and aqueous humor collection. The aqueous level of vascular endothelial growth factor prior to the intravitreal injection was 880.51 pg/mL, greater than that in the healthy control group (p < 0.001). One month later, the scleritis was completely resolved, and the patient remained stable during six months of follow-up. Intravitreal bevacizumab appears to be an effective adjuvant therapy for patients with posterior scleritis

Discriminating Pathological and Non-pathological Internet Gamers Using Sparse Neuroanatomical Features

Internet gaming disorder (IGD) is often diagnosed on the basis of nine underlying criteria from the latest version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Here, we examined whether such symptom-based categorization could be translated into computation-based classification. Structural MRI (sMRI) and diffusion-weighted MRI (dMRI) data were acquired in 38 gamers diagnosed with IGD, 68 normal gamers diagnosed as not having IGD, and 37 healthy non-gamers. We generated 108 features of gray matter (GM) and white matter (WM) structure from the MRI data. When regularized logistic regression was applied to the 108 neuroanatomical features to select important ones for the distinction between the groups, the disordered and normal gamers were represented in terms of 43 and 21 features, respectively, in relation to the healthy non-gamers, whereas the disordered gamers were represented in terms of 11 features in relation to the normal gamers. In support vector machines (SVM) using the sparse neuroanatomical features as predictors, the disordered and normal gamers were discriminated successfully, with accuracy exceeding 98%, from the healthy non-gamers, but the classification between the disordered and normal gamers was relatively challenging. These findings suggest that pathological and non-pathological gamers as categorized with the criteria from the DSM-5 could be represented by sparse neuroanatomical features, especially in the context of discriminating those from non-gaming healthy individuals

Brain-Driven Representation Learning Based on Diffusion Model

Interpreting EEG signals linked to spoken language presents a complex challenge, given the data's intricate temporal and spatial attributes, as well as the various noise factors. Denoising diffusion probabilistic models (DDPMs), which have recently gained prominence in diverse areas for their capabilities in representation learning, are explored in our research as a means to address this issue. Using DDPMs in conjunction with a conditional autoencoder, our new approach considerably outperforms traditional machine learning algorithms and established baseline models in accuracy. Our results highlight the potential of DDPMs as a sophisticated computational method for the analysis of speech-related EEG signals. This could lead to significant advances in brain-computer interfaces tailored for spoken communication

GIST-AiTeR Speaker Diarization System for VoxCeleb Speaker Recognition Challenge (VoxSRC) 2023

This report describes the submission system by the GIST-AiTeR team for the VoxCeleb Speaker Recognition Challenge 2023 (VoxSRC-23) Track 4. Our submission system focuses on implementing diverse speaker diarization (SD) techniques, including ResNet293 and MFA-Conformer with different combinations of segment and hop length. Then, those models are combined into an ensemble model. The ResNet293 and MFA-Conformer models exhibited the diarization error rates (DERs) of 3.65% and 3.83% on VAL46, respectively. The submitted ensemble model provided a DER of 3.50% on VAL46, and consequently, it achieved a DER of 4.88% on the VoxSRC-23 test set.Comment: 2023 VoxSRC Track

Stabilization of Lead (Pb) and Zinc (Zn) in Contaminated Rice Paddy Soil Using Starfish: A Preliminary Study

Lead (Pb) and zinc (Zn) contaminated rice paddy soil was stabilized using natural (NSF) and calcined starfish (CSF). Contaminated soil was treated with NSF in the range of 0-10 wt.% and CSF in the range of 0-5 wt.% and cured for 28 days. Toxicity characteristic leaching procedure (TCLP) test was used to evaluate effectiveness of starfish treatment. Scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDX) analyses were conducted to investigate the mechanism responsible for effective immobilization of Pb and Zn. Experimental results suggest that NSF and CSF treatments effectively immobilize Pb and Zn in treated rice paddy soil. TCLP levels for Pb and Zn were reduced with increasing NSF and CSF dosage. Comparison of the two treatment methods reveals that CSF treatment is more effective than NSF treatment. Leachability of the two metals is reduced approximately 58% for Pb and 51% for Zn, upon 10 wt.% NSF treatment. More pronounced leachability reductions, 93% for Pb and 76% for Zn, are achieved upon treatment with 5 wt.% CSF. Sequential extraction results reveal that NSF and CSF treatments of contaminated soil generated decrease in exchangeable/weak acid Pb and Zn soluble fractions, and increase of residual Pb and Zn fractions. Results for the SEM-EDX sample treated with 5 wt.% CSF indicate that effective Pb and Zn immobilization is most probably associated with calcium silicate hydrates (CSHs) and calcium aluminum hydrates (CAHs)

Quality Improvement of Acidic Soils by Biochar Derived from Renewable Materials

Biochar derived from waste plant materials and agricultural residues was used to improve the quality of an acidic soil. The acidic soil was treated for 1 month with both soy bean stover-derived biochar and oak-derived biochar in the range of 1 to 5 wt% for pH improvement and exchangeable cation enhancement. Following 1 month of treatment, the soil pH was monitored and exchangeable cations were measured. Moreover, a maize growth experiment was performed for 14 days with selected treated soil samples to confirm the effectiveness of the treatment. The results showed that the pH of the treated acidic soil increased by more than 2 units, and the exchangeable cation values were greatly enhanced upon treatment with 5 wt% of both biochars, after 1 month of curing. Maize growth was superior in the 3 wt% biochar-treated samples compared to the control sample. The presented results demonstrate the effective use of biochar derived from renewable materials such as waste plant materials and agricultural residues for quality improvement of acidic soils