Fluorinated lactide-based copolymers

Disclosed is a process for producing lactide-based copolymers and the copolymers produced by this process. Disclosed copolymers are formed in one embodiment through the copolymerization of a lactide monomer with a fluorinated diol, for example a perfluorinated polyether monomer, oligomer or copolymer. The disclosed materials may display improved mechanical characteristics, hydrolytic characteristics, and thermal characteristics as compared to previously known lactide-based materials

Attentive Fusion: A Transformer-based Approach to Multimodal Hate Speech Detection

With the recent surge and exponential growth of social media usage, scrutinizing social media content for the presence of any hateful content is of utmost importance. Researchers have been diligently working since the past decade on distinguishing between content that promotes hatred and content that does not. Traditionally, the main focus has been on analyzing textual content. However, recent research attempts have also commenced into the identification of audio-based content. Nevertheless, studies have shown that relying solely on audio or text-based content may be ineffective, as recent upsurge indicates that individuals often employ sarcasm in their speech and writing. To overcome these challenges, we present an approach to identify whether a speech promotes hate or not utilizing both audio and textual representations. Our methodology is based on the Transformer framework that incorporates both audio and text sampling, accompanied by our very own layer called "Attentive Fusion". The results of our study surpassed previous state-of-the-art techniques, achieving an impressive macro F1 score of 0.927 on the Test Set.Comment: Accepted in 20th International Conference on Natural Language Processing (ICON

Transferring a molecular foundation model for polymer property predictions

Transformer-based large language models have remarkable potential to accelerate design optimization for applications such as drug development and materials discovery. Self-supervised pretraining of transformer models requires large-scale datasets, which are often sparsely populated in topical areas such as polymer science. State-of-the-art approaches for polymers conduct data augmentation to generate additional samples but unavoidably incurs extra computational costs. In contrast, large-scale open-source datasets are available for small molecules and provide a potential solution to data scarcity through transfer learning. In this work, we show that using transformers pretrained on small molecules and fine-tuned on polymer properties achieve comparable accuracy to those trained on augmented polymer datasets for a series of benchmark prediction tasks

Effect of prestrain on the actuation characteristics of dielectric elastomers

Dielectric elastomers (DEs) represent a class of electroactive polymers that deform due to electrostatic attraction between oppositely charged electrodes under a varying electric field. Over the last couple of decades, DEs have garnered considerable attention due to their much-coveted actuation properties. As far as the precise measurement systems are concerned, however, there is no standard instrument or interface to quantify various related parameters, e.g., actuation stress, strain, voltage and creeping etc. In this communication, we present an in-depth study of dielectric actuation behavior of dielectric rubbers by the state-of-the-art “Dresden Smart Rubber Analyzer” (DSRA), designed and developed in-house. The instrument allowed us to elucidate various factors that could influence the output efficiency of the DEs. Herein, several non-conventional DEs such as hydrogenated nitrile rubber, nitrile rubber with different acrylonitrile contents, were employed as an electro-active matrix. The effect of viscoelastic creeping on the prestrain, molecular architecture of the matrices, e.g., nitrile content of nitrile-butadiene rubber (NBR) etc., are also discussed in detail

Effect of Prestrain on the Actuation Characteristics of Dielectric Elastomers

Dielectric elastomers (DEs) represent a class of electroactive polymers that deform due to electrostatic attraction between oppositely charged electrodes under a varying electric field. Over the last couple of decades, DEs have garnered considerable attention due to their much-coveted actuation properties. As far as the precise measurement systems are concerned, however, there is no standard instrument or interface to quantify various related parameters, e.g., actuation stress, strain, voltage and creeping etc. In this communication, we present an in-depth study of dielectric actuation behavior of dielectric rubbers by the state-of-the-art "Dresden Smart Rubber Analyzer" (DSRA), designed and developed in-house. The instrument allowed us to elucidate various factors that could influence the output efficiency of the DEs. Herein, several non-conventional DEs such as hydrogenated nitrile rubber, nitrile rubber with different acrylonitrile contents, were employed as an electro-active matrix. The effect of viscoelastic creeping on the prestrain, molecular architecture of the matrices, e.g., nitrile content of nitrile-butadiene rubber (NBR) etc., are also discussed in detail

Custard apple-shaped NaX zeolite with a large surface area derived from rice husk ash by a single-step template-free process

Custard apple-shaped NaX zeolite with a large surface area was synthesized from rice husk ash without use of a templating agent via a single-step autoclave process at 90 degrees C/6h. The crystallinity of the particles was confirmed by XRD. An FTIR study shows the characteristic bands at 560 cm(-1) for a double 6-membered ring (D6R), while a Raman shift at around 500 cm(-1) indicates the bending mode of 4-membered ring fragments of NaX zeolite. The total BET surface area of the product was found to be 703 m(2)g(-1) comprising a micrpore surface area of 623 m(2)g(-1) and a mesopore surface area of 80 m(2)g(-1). A hierarchical porous structure with micropores in the range of 0.72-1.76nm and mesopores centred at 3.5nm was obtained. FESEM and TEM images of NaX zeolite show a custard apple-like morphology (1-2 mu m) of secondary particles which was formed by self-assembly of nanometer-sized (50-100nm) primary particles. A proposed formation mechanism was illustrated

RadRCom: A Relay-Assisted Radar Communication System Design Framework

This study introduces the novel communication topology, namely RadRCom, integrating radar and relay-assisted communication systems for single antenna configuration as a proof of concept. While simultaneous radar and communication operations within the same spectrum gain momentum, our work advances this concept by incorporating relay assistance, particularly crucial in applications like vehicle-to-anything (V2X) communication. The inclusion of relays significantly enhances communication system performance, addressing challenges such as interference management between radar, relay, and communication nodes. This topology attracts three design challenges such as optimal radar waveform, relay parameters and communication system parameters. However, the key bottlenecks are the interference from radar to the relay and communication receiver and similarly the one from communication transmitter and relay node to the radar. Therefore, the work addresses these challenges simultaneously meeting the quality of service. Our proposed RadRCom system optimizes radar waveform and relay parameters to improve signal-to-interference noise ratio (SINR) at the radar and mean square error (MSE) of data transmission. We introduce two frameworks for parameter design, i.e, radar-centric and relay-centric ones. We take a sub-optimal iterative approach to address the computational complexity. Numerical simulations are performed to evaluate the performances of the proposed RadRCom system with the proposed algorithms

Synergistic actions of melatonin in combination with anti-parkinsonian drugs in experimental model of Parkinson’s disease

Parkinson’s disease (PD) is a neurodegenerative disorder characterized by progressive degeneration and loss of nigrostriatal dopaminergic neurons in the midbrain, A9 substantia nigra neurons leading to severe striatal dopamine (DA) depletion resulting in tremor, rigidity and hypokinesia (Carlsson, 2002). PD is named after James Parkinson who first described the disease as “Shaking Palsy” (Paralysis Agitans) in his classic monograph “An essay on the Shaking Palsy” (Parkinson, 1817). This debilitating disorder has no cure existing, and recent epidemiological studies suggest an increasing trend in its incidents; predicting an alarming 2-fold increase in affected population by 2030 in several countries (Dorsey et al., 2007). Currently used drugs for PD provides symptomatic relief, and are based on increasing the striatal levels of DA, or controlling the DA transmission. However, these drugs are generally short acting, and with time develop serious side effects. There are cases when the drugs need to be discontinued due to exacerbation of DA-mediated effects. At this juncture, there is a great need of alternative therapies, or designs that would effectively reduce the dose of drugs that causes ‘on-off’ effects, dyskinesias, other undesirable motor effects, non-motor complications, and slower the progression of the disease. One of such effective therapy is using a peripheral aromatic amino acid decarboxylase inhibitor, carbidopa along with L-3,4-dihydroxyphenylalanine (L-DOPA). The present study mainly addressed such alternative approaches so as to find better therapeutic agents that may synergize with the existing PD drugs

Mechanical, thermal, morphological, and rheological characteristics of high performance 3D-printing lignin-based composites for additive manufacturing applications

The article presents different mechanical, thermal and rheological data corresponding to the morphological formation within various renewable lignin-based composites containing acrylonitrile butadiene styrene (ABS), acrylonitrile butadiene rubber (NBR41, 41 mol% nitrile content), and carbon fibers (CFs). The data of 3D-printing properties and morphology of 3D-printed layers of selected lignin-based composites are revealed. This data is related to our recent research article entitled “A general method to improve 3D-printability and inter-layer adhesion in lignin-based composites” (Nguyen et al., 2018 [1])