Studies of Cobalt and Iron Oxides/Oxyhydroxides Nanostructures for Electrochemical Applications

Ph.DDOCTOR OF PHILOSOPH

Palm Oil As Feed Stocks For Biodiesel Production Via Heterogeneous Transesterification: Optimization Study.

Fatty acid methyl ester (FAME) prepared by transesterification process using heterogeneous catalyst has receive a lot of interest lately as a sustainable and reliable source of bio fuel. Apart from that, palm oil, being the worlds’ cheapest edible oil has the economical potential to become the source of FAME

Graded Nodal/Activin Signaling Titrates Conversion of Quantitative Phospho-Smad2 Levels into Qualitative Embryonic Stem Cell Fate Decisions

Nodal and Activin are morphogens of the TGFbeta superfamily of signaling molecules that direct differential cell fate decisions in a dose- and distance-dependent manner. During early embryonic development the Nodal/Activin pathway is responsible for the specification of mesoderm, endoderm, node, and mesendoderm. In contradiction to this drive towards cellular differentiation, the pathway also plays important roles in the maintenance of self-renewal and pluripotency in embryonic and epiblast stem cells. The molecular basis behind stem cell interpretation of Nodal/Activin signaling gradients and the undertaking of disparate cell fate decisions remains poorly understood. Here, we show that any perturbation of endogenous signaling levels in mouse embryonic stem cells leads to their exit from self-renewal towards divergent differentiation programs. Increasing Nodal signals above basal levels by direct stimulation with Activin promotes differentiation towards the mesendodermal lineages while repression of signaling with the specific Nodal/Activin receptor inhibitor SB431542 induces trophectodermal differentiation. To address how quantitative Nodal/Activin signals are translated qualitatively into distinct cell fates decisions, we performed chromatin immunoprecipitation of phospho-Smad2, the primary downstream transcriptional factor of the Nodal/Activin pathway, followed by massively parallel sequencing, and show that phospho-Smad2 binds to and regulates distinct subsets of target genes in a dose-dependent manner. Crucially, Nodal/Activin signaling directly controls the Oct4 master regulator of pluripotency by graded phospho-Smad2 binding in the promoter region. Hence stem cells interpret and carry out differential Nodal/Activin signaling instructions via a corresponding gradient of Smad2 phosphorylation that selectively titrates self-renewal against alternative differentiation programs by direct regulation of distinct target gene subsets and Oct4 expression

The use of low cost zeolites for the removal of selected contaminants and combination with biological process for wastewater treatment

Two types of low cost zeolites, namely natural mordenite and synthetic zeolite Y synthesized from a local agro-wastes, rice husk ash were applied to remove various types of contaminants from water. Zeolite Y was synthesized under hydrothermal conditions with appropriate seeding and aging methods, in which the overall relative composition of Na2O: Al2O3: SiO2: H2O is 5.1: 1.0: 10.5: 184.0. The physico-chemical properties of the zeolites were characterized using various techniques. Ammonium removal studies were carried out with the raw mordenite and as-synthesized zeolite Y. Pseudo first order kinetic model and pseudo second order kinetic model were employed to understand the sorption kinetics, while several isotherm equations such as Langmuir, Freundlich and Temkin to study the sorption behavior. To bombard against oxyanions such as nitrate, sulfate and phosphate, the surface chemistry of the zeolites were altered by a cationic surfactant, quaternary amine HDTMA-Br in proportional to the external cation exchange capacity of the zeolites. Both the surfactant-modified zeolites (SMZ) presented significant affinity and adsorption capacity towards the oxyanions. Besides that, while the unmodified zeolites had no affinity towards anionic organic, Acid Orange 7 (AO7), the SMZ showed impressively high adsorption capacity with a rapid removal rate. Suitable kinetics and isotherms models were employed to further understand the sorption behaviors. Combination of the adsorption and biological treatment process in wastewater treatment is interesting. Prior to the study of the combined process, the powdered zeolites and its modified form were first fabricated to the small round particle; several studies were carried out to study the physico-chemical characteristics of the zeolite particles. Indigenous bacteria strains were isolated from a wastewater source and the performance of the bacteria to remove different contaminants was screened. Finally the use of zeolite particle in textile wastewater treatment together with the mixed cultures of bacteria was studied in several approaches

Kinetic and equilibrium studies of the removal of ammonium ions from aqueous solution by rice husk ash-synthesized zeolite Y and powdered and granulated forms of mordenite

The removal of ammonium from aqueous solutions using zeolite NaY prepared from a local agricultural waste, rice husk ash waste was investigated and a naturally occurring zeolite mordenite in powdered and granulated forms was used as comparison. Zeolite NaY and mordenite were well characterized by powder X-ray diffraction (XRD), energy dispersive X-ray (EDX) analysis and the total cation exchange capacity (CEC). CEC of the zeolites were measured as 3.15, 1.46 and 1.34 meq g-1 for zeolite Y, powdered mordenite and granular mordenite, respectively. Adsorption kinetics and equilibrium data for the removal of NH4+ ions were examined by fitting the experimental data to various models. Kinetic studies showed that the adsorption followed a pseudo-second-order reaction. The equilibrium pattern fits well with the Langmuir isotherm compared to the other isotherms. The monolayer adsorption capacity for zeolite Y (42.37 mg/g) was found to be higher than that powdered mordenite (15.13 mg/g) and granular mordenite (14.56 mg/g). Thus, it can be concluded that the low cost and economical rice husk ash-synthesized zeolite NaY could be a better sorbent for ammonium removal due to its rapid adsorption rate and higher adsorption capacity compared to natural mordenite

RNA as a Precursor to N‑Doped Activated Carbon

Activated carbons (ACs) have applications in gas separation and power storage, and N-doped ACs in particular can be promising supercapacitors. In this context, we studied ACs produced from yeast-derived ribonucleic acid (RNA), which contains aza-aromatic bases and phosphate-linked ribose units, and is surprisingly inexpensive. The RNA was hydrothermally carbonized to produce hydrochars that were subsequently activated with CO₂, KOH, or KHCO₃ to give ACs. The ACs adsorbed up to ∼7 mmol/g at 0 °C and 1 bar and had capacitances as high as ∼300 F/g in a three-electrode cell and a 6 M KOH­(aq) electrolyte. The material that displayed the best capacitance was tested in a two-electrode cell, which displayed a specific capacitance of 181 F/g even at a current density of 10 A/g. The ACs with the highest uptake of CO₂ and the highest capacitance were those activated with KOH and KHCO₃; however, CO₂ activation is arguably less expensive and more suitable for industrialization

HGR-ViT: Hand Gesture Recognition with Vision Transformer

Hand gesture recognition (HGR) is a crucial area of research that enhances communication by overcoming language barriers and facilitating human-computer interaction. Although previous works in HGR have employed deep neural networks, they fail to encode the orientation and position of the hand in the image. To address this issue, this paper proposes HGR-ViT, a Vision Transformer (ViT) model with an attention mechanism for hand gesture recognition. Given a hand gesture image, it is first split into fixed size patches. Positional embedding is added to these embeddings to form learnable vectors that capture the positional information of the hand patches. The resulting sequence of vectors are then served as the input to a standard Transformer encoder to obtain the hand gesture representation. A multilayer perceptron head is added to the output of the encoder to classify the hand gesture to the correct class. The proposed HGR-ViT obtains an accuracy of 99.98%, 99.36% and 99.85% for the American Sign Language (ASL) dataset, ASL with Digits dataset, and National University of Singapore (NUS) hand gesture dataset, respectively

SDViT: Stacking of Distilled Vision Transformers for Hand Gesture Recognition

Hand gesture recognition (HGR) is a rapidly evolving field with the potential to revolutionize human–computer interactions by enabling machines to interpret and understand human gestures for intuitive communication and control. However, HGR faces challenges such as the high similarity of hand gestures, real-time performance, and model generalization. To address these challenges, this paper proposes the stacking of distilled vision transformers, referred to as SDViT, for hand gesture recognition. An initially pretrained vision transformer (ViT) featuring a self-attention mechanism is introduced to effectively capture intricate connections among image patches, thereby enhancing its capability to handle the challenge of high similarity between hand gestures. Subsequently, knowledge distillation is proposed to compress the ViT model and improve model generalization. Multiple distilled ViTs are then stacked to achieve higher predictive performance and reduce overfitting. The proposed SDViT model achieves a promising performance on three benchmark datasets for hand gesture recognition: the American Sign Language (ASL) dataset, the ASL with digits dataset, and the National University of Singapore (NUS) hand gesture dataset. The accuracies achieved on these datasets are 100.00%, 99.60%, and 100.00%, respectively

HGR-ResNet: Hand Gesture Recognition with Enhanced Residual Neural Network

Hand Gesture Recognition (HGR) has garnered increasing attention in recent years due to its potential to enhance human-computer interaction (HCI) and facilitate communication between individuals who are mute or deaf and the wider public. HGR can facilitate non-contact interaction between humans and machines, offering an effective interface for recognizing sign language used in everyday communication. This paper proposes a novel approach for static HGR using transfer learning of ResNet152 with early stopping, adaptive learning rate, and class weightage techniques, referred to as HGR-ResNet. Transfer learning enables the model to utilize previously acquired knowledge from pre-training on a large dataset, allowing it to learn from pre-extracted image features. Early stopping serves as a regularization technique, halting the training process before overfitting occurs. Adaptive learning rate adjusts the learning rate dynamically based on the model's error rate during training, promoting faster convergence and improved accuracy. Additionally, the class weightage technique is employed to address the issue of class imbalance in the data, ensuring fair representation and mitigating biases during the training process. To assess the effectiveness of the proposed model, we conduct a comparative analysis with multiple existing methods using three distinct datasets: the American Sign Language (ASL) dataset, ASL with digits dataset, and the National University of Singapore (NUS) hand gesture dataset. HGR-ResNet achieves remarkable results, with an average accuracy of 99.20% across all three datasets, and individual accuracies of 99.88% for the ASL dataset, 98.93% for the ASL with digits dataset, and 98.80% for the NUS hand gesture datase

Environmentally friendly solution route to kesterite Cu2ZnSn(S,Se)(4) thin films for solar cell applications

Quaternary kesterite Cu2ZnSnS4 (CZTS) and Cu2ZnSn(S,Se)4 (CZTSSe) thin films have been prepared from a mixture of CuS, ZnS and SnS2 nanoparticles and solar cells were made from the CZTSSe films. The binary sulfide nanoparticles were pre-synthesized in aqueous solution and then spray deposited onto glass substrates. The nano-sized binary sulfide nanoparticles have a large surface area that provides the driving force for solid-state reactions between the nanoparticles and results in the formation of the quaternary CZTS phase at moderate temperatures. The CZTSSe solar cells were prepared using the binary sulfide nanoparticles films annealed in Se vapor and the cells showed an encouraging efficiency of 5.12% (Voc = 378 mV, Jsc = 26.2 mA/cm2 and FF = 51.7%). Our synthetic approach provides a low-cost, environmentally friendly and easy to scale up option for the preparation of CZTSSe thin films for solar cell applications.Accepted versio