SYNTHESIS OF STARCH MODIFIED MONTMORILLONITE AS AN EFFECTIVE ADSORBENT FOR Pb (II) REMOVAL FROM WATER

The adsorbent is prepared by the montmorillonite co-modification with starch for the removal of Pb (II) ions from aqueous solution. The Fourier-transformed infrared (FTIR), X-ray diffraction (XRD) spectroscopies were used to determine the structure and characteristics of the adsorbent. The main factors affecting the removal of Pb (II) ions were investigated, including the effect of pH, contact time, adsorbent dosage and the initial concentration of Pb (II). Batch process can be used for adsorption and equilibrium studies. The experimental data were fitted using Freundlich and Langmuir adsorption models. The Langmuir isotherm best fitted the experimental data with R2 0.99 and maximum Pb (II) adsorption capacity of 21.5 mg/g indicated monolayer adsorption. Kinetic studies using pseudo-first-order and pseudo-second-order rate models showed that the process complied well with the pseudo second-order rate model

Enabling Power Beacons and Wireless Power Transfers for Non-Orthogonal Multiple Access Networks, Journal of Telecommunications and Information Technology, 2021, nr 3

This paper studies downlink cellular networks relying on non-orthogonal multiple access (NOMA). Specifically, the access point (AP) is able to harvest wireless power from the power beacon (PB). In the context of an AP facilitated with multiple antennas, the transmit antenna selection procedure is performed to process the downlink signal, with the transmission guaranteed by energy harvesting. Therefore, a wireless power transfer-based network is introduced to overcome power outages at the AP. In particular, an energy-constrained AP harvests energy from the radio frequency signals transmitted by the PB in order to assist in transmitting user data. Outage performance and ergodic capacity are evaluated with the use of closed-form expressions. In order to highlight some insights, approximate computations are provided. Finally, numerical simulations are performed to confirm the benefits of combining the downlink NOMA transmission and the transmit power scheme at the AP in order to serve a multitude of user

Fairness in Visual Clustering: A Novel Transformer Clustering Approach

Promoting fairness for deep clustering models in unsupervised clustering settings to reduce demographic bias is a challenging goal. This is because of the limitation of large-scale balanced data with well-annotated labels for sensitive or protected attributes. In this paper, we first evaluate demographic bias in deep clustering models from the perspective of cluster purity, which is measured by the ratio of positive samples within a cluster to their correlation degree. This measurement is adopted as an indication of demographic bias. Then, a novel loss function is introduced to encourage a purity consistency for all clusters to maintain the fairness aspect of the learned clustering model. Moreover, we present a novel attention mechanism, Cross-attention, to measure correlations between multiple clusters, strengthening faraway positive samples and improving the purity of clusters during the learning process. Experimental results on a large-scale dataset with numerous attribute settings have demonstrated the effectiveness of the proposed approach on both clustering accuracy and fairness enhancement on several sensitive attributes

Study Structure and Properties of Nanocomposite Material Based on Unsaturated Polyester with Clay Modified by Poly(ethylene oxide)

In recent years, polymer clay nanocomposites have been attracting considerable interests in polymers science because of their advantages. There are many scientists who researched about this kind of material and demonstrated that when polymer matrix was added to little weight of clay, properties were enhanced considerably. Because clay is a hydrophilic substance so it is difficult to use as filler in polymer matrix having hydrophobic nature, so clay needs to be modified to become compatible with polymer. In this study, poly(ethylene oxide) was used as a new modifier for clay to replace some traditional ionic surfactants such as primary, secondary, tertiary, and quaternary alkyl ammonium or alkylphosphonium cations having the following disadvantages: disintegrate at high temperature, catalyze polymer degradation, and make nanoproducts colorific, and so forth. In order to evaluate modifying effect of poly(ethylene oxide), modified clay products were characterize d by X-ray spectrum. Then organoclay was used to prepare nanocomposite based on unsaturated polyester. Morphology and properties of nanocomposites were measure d by X-ray diffraction, transmission electron microscopy, tensile strength, and thermal stability. The results showed that clay galleries changed to intercalated state in the nanocomposites. Properties of nanocomposites were improved a lot when the loading of the organoclay was used at 1 phr

DyGLIP: A Dynamic Graph Model with Link Prediction for Accurate Multi-Camera Multiple Object Tracking

Multi-Camera Multiple Object Tracking (MC-MOT) is a significant computer vision problem due to its emerging applicability in several real-world applications. Despite a large number of existing works, solving the data association problem in any MC-MOT pipeline is arguably one of the most challenging tasks. Developing a robust MC-MOT system, however, is still highly challenging due to many practical issues such as inconsistent lighting conditions, varying object movement patterns, or the trajectory occlusions of the objects between the cameras. To address these problems, this work, therefore, proposes a new Dynamic Graph Model with Link Prediction (DyGLIP) approach to solve the data association task. Compared to existing methods, our new model offers several advantages, including better feature representations and the ability to recover from lost tracks during camera transitions. Moreover, our model works gracefully regardless of the overlapping ratios between the cameras. Experimental results show that we outperform existing MC-MOT algorithms by a large margin on several practical datasets. Notably, our model works favorably on online settings but can be extended to an incremental approach for large-scale datasets.Comment: accepted at CVPR 202

Beyond Disentangled Representations: An Attentive Angular Distillation Approach to Large-scale Lightweight Age-Invariant Face Recognition

Disentangled representations have been commonly adopted to Age-invariant Face Recognition (AiFR) tasks. However, these methods have reached some limitations with (1) the requirement of large-scale face recognition (FR) training data with age labels, which is limited in practice; (2) heavy deep network architecture for high performance; and (3) their evaluations are usually taken place on age-related face databases while neglecting the standard large-scale FR databases to guarantee its robustness. This work presents a novel Attentive Angular Distillation (AAD) approach to Large-scale Lightweight AiFR that overcomes these limitations. Given two high-performance heavy networks as teachers with different specialized knowledge, AAD introduces a learning paradigm to efficiently distill the age-invariant attentive and angular knowledge from those teachers to a lightweight student network making it more powerful with higher FR accuracy and robust against age factor. Consequently, AAD approach is able to take the advantages of both FR datasets with and without age labels to train an AiFR model. Far apart from prior distillation methods mainly focusing on accuracy and compression ratios in closed-set problems, our AAD aims to solve the open-set problem, i.e. large-scale face recognition. Evaluations on LFW, IJB-B and IJB-C Janus, AgeDB and MegaFace-FGNet with one million distractors have demonstrated the efficiency of the proposed approach. This work also presents a new longitudinal face aging (LogiFace) database for further studies in age-related facial problems in future.Comment: arXiv admin note: substantial text overlap with arXiv:1905.1062

Clinical features, antimicrobial susceptibility patterns and genomics of bacteria causing neonatal sepsis in a children's hospital in Vietnam: protocol for a prospective observational study.

INTRODUCTION: The clinical syndrome of neonatal sepsis, comprising signs of infection, septic shock and organ dysfunction in infants ≤4 weeks of age, is a frequent sequel to bloodstream infection and mandates urgent antimicrobial therapy. Bacterial characterisation and antimicrobial susceptibility testing is vital for ensuring appropriate therapy, as high rates of antimicrobial resistance (AMR), especially in low-income and middle-income countries, may adversely affect outcome. Ho Chi Minh City (HCMC) in Vietnam is a rapidly expanding city in Southeast Asia with a current population of almost 8 million. There are limited contemporary data on the causes of neonatal sepsis in Vietnam, and we hypothesise that the emergence of multidrug resistant bacteria is an increasing problem for the appropriate management of sepsis cases. In this study, we aim to investigate the major causes of neonatal sepsis and assess disease outcomes by clinical features, antimicrobial susceptibility profiles and genome composition. METHOD AND ANALYSIS: We will conduct a prospective observational study to characterise the clinical and microbiological features of neonatal sepsis in a major children's hospital in HCMC. All bacteria isolated from blood subjected to whole genome sequencing. We will compare clinical variables and outcomes between different bacterial species, genome composition and AMR gene content. AMR gene content will be assessed and stratified by species, years and contributing hospital departments. Genome sequences will be analysed to investigate phylogenetic relationships. ETHICS AND DISSEMINATION: The study will be conducted in accordance with the principles of the Declaration of Helsinki and the International Council on Harmonization Guidelines for Good Clinical Practice. Ethics approval has been provided by the Oxford Tropical Research Ethics Committee 35-16 and Vietnam Children's Hospital 1 Ethics Committee 73/GCN/BVND1. The findings will be disseminated at international conferences and peer-reviewed journals. TRIAL REGISTRATION NUMBER: ISRCTN69124914; Pre-results