The effect of internet-administered support (carer eSupport) on preparedness for caregiving in informal caregivers of patients with head and neck cancer compared with support as usual: a study protocol for a randomized controlled trial.

BACKGROUND: Informal caregivers (ICs) of patients with cancer provide essential and mainly uncompensated care. A self-perceived preparedness to care for the patient is associated with a lower caregiver burden, described as the extent to which caregiving is perceived as having adverse effects on IC functioning and well-being. ICs' well-being is associated with patient-perceived quality of care, suggesting that interventions to optimize ICs' health are essential in order to improve patient care. Head and neck cancer (HNC) is the seventh most common malignant disease in the world. The disease and its treatment have a significant negative impact on the patient's health and quality of life. Symptoms usually interfere with swallowing, food and fluid intake, breathing, speaking, and communication. ICs frequently manage patients' symptoms and side effects, especially problems related to nutrition and oral pain, without being properly prepared. Carer eSupport is an Internet-administered intervention, based on focus group discussions with ICs, developed in collaboration with ICs and healthcare professionals, tested for feasibility, and deemed feasible. This study protocol outlines the methods of investigating the effects of Carer eSupport plus support as usual (SAU) on self-reported preparedness for caregiving, caregiver burden, and well-being in the ICs of patients with HNC, compared with ICs receiving SAU only. METHODS AND ANALYSIS: In this randomized controlled trial, 110 ICs of patients with HNC, undergoing radiotherapy combined with surgery and/or medical oncological treatment, will be randomized (1:1) to Carer eSupport plus SAU or SAU only. Data will be collected at baseline (before randomization), post-intervention (after 18 weeks), and 3 months after post-intervention. The primary outcome is self-reported preparedness for caregiving. Secondary outcomes are self-reported caregiver burden, anxiety, depression, and health-related quality of life. The effect of Carer eSupport plus SAU on preparedness for caregiving and secondary outcomes, compared with SAU only, will be evaluated by intention to treat analyses using linear regression models, mixed-model regression, or analysis of covariance. DISCUSSION: If proven effective, Carer eSupport has the potential to significantly improve ICs' preparedness for caregiving and their wellbeing, thereby improving patient-perceived quality of care and patient wellbeing. TRIAL REGISTRATION: ClinicalTrials.gov; NCT06307418, registered 12.03.2024 (https://clinicaltrials.gov/search? term=NCT06307418).

Benign-by-design plant extract-mediated preparation of copper oxide nanoparticles for environmentally related applications.

A facile, cost-competitive, scalable and novel synthetic approach is used to prepare copper oxide (CuO) nanoparticles (NPs) using Betel leaf (Piper betle) extracts as reducing, capping, and stabilizing agents. CuO-NPs were characterized using various analytical techniques, including Fourier-transform infrared (FTIR) spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), high-resolution transmission electron microscopy (HRTEM), as well as photoluminescence (PL) measurements. The activity of CuO-NPs was investigated towards Congo red dye degradation, supercapacitor energy storage and antibacterial activity. A maximum of 89% photodegradation of Congo red dye (CR) was obtained. The nanoparticle modified electrode also exhibited a specific capacitance (Csp) of 179 Fg-1. Furthermore, the antibacterial potential of CuO NPs was evaluated against Bacillus subtilis and Pseudomonas aeruginosa, both strains displaying high antibacterial performance.

Green synthesis of ZnO nanocubes from Ceropegia omissa H. Huber extract for photocatalytic degradation of bisphenol An under visible light to mitigate water pollution.

Plastic pollution has become a major environmental problem because it does not break down and poses risks to ecosystems and human health. This study focuses on the environmentally friendly synthesis of ZnO nanocubes using an extract from Ceropegia omissa H. Huber plant leaves. The primary goal is to investigate the viability of these nanocubes as visible-light photocatalysts for the degradation of bisphenol A (BPA). The synthesized ZnO nanocubes have a highly crystalline structure and a bandgap of 3.1 eV, making them suitable for effective visible-light photocatalysis. FTIR analysis, which demonstrates that the pertinent functional groups are present, demonstrates the chemical bonding and reducing processes that take place in the plant extract. The XPS method also studies zinc metals, oxygen valencies, and binding energies. Under visible light irradiation, ZnO nanocubes degrade BPA by 86% in 30 min. This plant-extract-based green synthesis method provides a long-term replacement for traditional procedures, and visible light photocatalysis has advantages over ultraviolet light. The study's results show that ZnO nanocubes may be good for the environment and can work well as visible light photocatalysts to break down organic pollutants. This adds to what is known about using nanoparticles to clean up the environment. As a result, this study highlights the potential of using environmentally friendly ZnO nanocubes as a long-lasting and efficient method of reducing organic pollutant contamination in aquatic environments.

Support based metal incorporated layered nanomaterials for photocatalytic degradation of organic pollutants.

An effective approach to producing sophisticated miniaturized and nanoscale materials involves arranging nanomaterials into layered hierarchical frameworks. Nanostructured layered materials are constructed to possess isolated propagation assets, massive surface areas, and envisioned amenities, making them suitable for a variety of established and novel applications. The utilization of various techniques to create nanostructures adorned with metal nanoparticles provides a secure alternative or reinforcement for the existing physicochemical methods. Supported metal nanoparticles are preferred due to their ease of recovery and usage. Researchers have extensively studied the catalytic properties of noble metal nanoparticles using various selective oxidation and hydrogenation procedures. Despite the numerous advantages of metal-based nanoparticles (NPs), their catalytic potential remains incompletely explored. This article examines metal-based nanomaterials that are supported by layers, and provides an analysis of their manufacturing, procedures, and synthesis. This study incorporates both 2D and 3D layered nanomaterials because of their distinctive layered architectures. This review focuses on the most common metal-supported nanocomposites and methodologies used for photocatalytic degradation of organic dyes employing layered nanomaterials. The comprehensive examination of biological and ecological cleaning and treatment techniques discussed in this article has paved the way for the exploration of cutting-edge technologies that can contribute to the establishment of a sustainable future.

Hydrothermal synthesis of V2O5/TiO2 decorated graphitic carbon nitride nanocomposite for biomolecule oxidation inhibition and dye degradation applications.

Oxides of vanadium, titanium and graphitic carbon nitride (g-C3N4) are well known for their catalytic activities. In order to achieve synergic catalytic effects, a novel nanocomposite (NC) i.e. V2O5/TiO2/g-C3N4 has been synthesized by a very simple, ecofriendly and nonhazardous hydrothermal method. The fabricated NC was characterized employing UV-Visible, FTIR, SEM, and XRD techniques. UV-Visible and FTIR analysis indicated the formation of the nanocomposite and XRD analysis confirmed the association of V2O5 and TiO2 with g-C3N4 in nanocomposite. SEM study indicated the hetero-structure of NC having size ranging from 50 to 80 nm and it was found having hexagonal crystallite structure. The synthesized nanocomposite exhibited excellent scavenging of free radicals DPPH● (91%) and ABTS●+ (64%) that are responsible for the oxidation of biomolecules. Therefore, NC can be claimed having biomolecule oxidation protective potential. In addition, photocatalytic ability for the degradation of methylene blue (MB) and methyl orange (MO) was also achieved up to 94% and 89% respectively. The synthesized novel nanocomposite exhibited excellent potential to remove free radicals and dyes from aqueous medium which can be further used for the environmental remediation.

Sugarcane-bagasse-ash in enhanced mesophilic Co-digestion for biogas and nutrient recovery: A concept of developing rural circular bioeconomy.

Conductive agro-industrial wastes as accelerants in the anaerobic digestion (AD) of organic waste is a good technique for developing a rural circular economy, such as producing bioenergy and biofertilizer. This study disclosed the a role of sugar cane bagasse ash (SCBA) in enhancing the bioenergy (biogas) yield and digestate fertility via anaerobic co-digestion (AcoD) of buffalo dung (BD) and vegetable residue (VR) under mesophilic conditions (37 á´¼C). Firstly, an optimal BD/VR ratio (1:3) was determined based on biogas yield by introducing five different BD/VR ratios (1:0, 3:1, 1:1, 1:3, and 0:1) into AcoD systems. Secondly, the biogas yield was increased further by adding SCBA at five different concentrations (0, 0.5, 1, 1.5, and 2 wt%). Experimental results disclosed that the 1.5 wt% of SCBA gave the highest cumulative biogas yield (153.67 mL/g VS), COD removal rate (31.18%), and fertility (5.08%). Moreover, a framework is suggested to understand the role of SCBA in the enhanced DIET mechanism. This work documents an environmentally friendly and economical technique for developing a rural circular bioeconomy via the AD of organic agro-waste.

Doubtful Clinical Value of Subtyping Anti-U1-RNP Antibodies Regarding the RNP-70 kDa Antigen in Sera of Patients with Systemic Lupus Erythematosus.

The detection of antinuclear antibodies is central to the diagnosis and prognosis of systemic lupus erythematosus (SLE), primary Sjögren's syndrome (pSS) and mixed connective tissue disease (MCTD). Anti-U1-RNP and anti-RNP70 antibodies were assayed in the sera of patients with SLE (n = 114), pSS (n = 54) and MCTD (n = 12). In the SLE group, 34/114 (30%) were anti-U1-RNP positive, and 21/114 (18%) were both anti-RNP70 positive and anti-U1-RNP positive. In the MCTD group, 10/12 (83%) were anti-U1-RNP positive, and 9/12 (75%) were anti-RNP70 positive. Only one individual with pSS was antibody positive (for both anti-U1-RNP and anti-RNP70). All anti-RNP70-positive samples were also anti-U1-RNP positive. Anti-U1-RNP-positive subjects with SLE were younger (p < 0.0001); showed lower concentrations of complement protein 3 (p = 0.03); had lower eosinophil (p = 0.0005), lymphocyte (p = 0.006) and monocyte (p = 0.03) counts; and had accrued less organ damage (p = 0.006) than the anti-U1-RNP-negative SLE patients. However, we observed no significant clinical or laboratory parameter differences between the anti-U1-RNP-positive individuals with/without anti-RNP70 in the SLE group. In conclusion, anti-RNP70 antibodies are not exclusive to MCTD but are rarely detected in pSS and healthy individuals. In SLE, anti-U1-RNP antibodies are associated with a clinical phenotype that resembles MCTD, with hematologic involvement and less damage accrual. Based on our results, the clinical value of subtyping anti-RNP70 in anti-U1-RNP-positive sera appears to be of limited value.

Flowers Like α-MoO3/CNTs/PANI Nanocomposites as Anode Materials for High-Performance Lithium Storage.

Lithium-ion batteries (LIBs) have been explored to meet the current energy demands; however, the development of satisfactory anode materials is a bottleneck for the enhancement of the electrochemical performance of LIBs. Molybdenum trioxide (MoO3) is a promising anode material for lithium-ion batteries due to its high theoretical capacity of 1117 mAhg-1 along with low toxicity and cost; however, it suffers from low conductivity and volume expansion, which limits its implementation as the anode. These problems can be overcome by adopting several strategies such as carbon nanomaterial incorporation and polyaniline (PANI) coating. Co-precipitation method was used to synthesize α-MoO3, and multi-walled CNTs (MWCNTs) were introduced into the active material. Moreover, these materials were uniformly coated with PANI using in situ chemical polymerization. The electrochemical performance was evaluated by galvanostatic charge/discharge, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). XRD analysis revealed the presence of orthorhombic crystal phase in all the synthesized samples. MWCNTs enhanced the conductivity of the active material, reduced volume changes and increased contact area. MoO3-(CNT)12% exhibited high discharge capacities of 1382 mAhg-1 and 961 mAhg-1 at current densities of 50 mAg-1 and 100 mAg-1, respectively. Moreover, PANI coating enhanced cyclic stability, prevented side reactions and increased electronic/ionic transport. The good capacities due to MWCNTS and the good cyclic stability due to PANI make these materials appropriate for application as the anode in LIBs.

Alleviating lead-induced phytotoxicity and enhancing the phytoremediation of castor bean (Ricinus communis L.) by glutathione application: new insights into the mechanisms regulating antioxidants, gas exchange and lead uptake.

Heavy metals pollution represents a serious issue for cultivable lands and ultimately threatens the worldwide food security. Lead (Pb) is a menacing metal which induces toxicity in plants and humans. Lead toxicity reduces the photosynthesis in plants, resulting in the reduction of plant growth and biomass. The excessive concentration of Pb in soil accumulates in plants body and enters into food chain, resulting in health hazards in humans. The phytoremediation is eco-friendly and cost-efficient technique to clean up the polluted soils. However, to the best of our Knowledge, there are very few reports addressing the enhancement of the phytoremediation potential of castor bean plants. Therefore, the present study aimed to investigate the potential role of glutathione (GSH), as a promising plant growth regulator, in enhancing the lead stress tolerance and phytoremediation potential of castor bean plants grown under lead stress conditions. The results indicated that Pb stress reduced the growth, biomass, chlorophyll pigments and gas exchange attributes of castor bean plants, causing oxidative damage in plants. Pb stress induced the oxidative stress markers and activities of antioxidant enzymes. On the other hand, the application of GSH reduced oxidative stress markers, but enhanced the growth, biomass, photosynthetic pigments, gas exchange attributes, Pb accumulation and antioxidant enzymes activities of lead-stressed castor bean plants. Both Pb uptake and Pb accumulation were increased by increasing concentrations of Pb in a dose-additive manner. However, at high dose of exogenous GSH (25 mg L-1) further enhancements were recorded in the Pb uptake in shoot by 48% and in root by 46%; Pb accumulation was further enhanced in shoot by 98% and in root by 101% in comparison with the respective control where no GSH was applied. Taken together, the findings revealed the promising role of GSH in enhancing the lead stress tolerance and phytoremediation potential of castor bean (Ricinus communis) plants cultivated in Pb-polluted soils through regulating leaf gas exchange, antioxidants machinery, and metal uptake.

The excessive concentration of Lead (Pb) in soil accumulates in plants body and enters into food chain, resulting in health hazards in humans. Phytoremediation is eco-friendly and cost-efficient technique to clean up the polluted soils. However, to the best of our knowledge, there are very few reports addressing the enhancement of the phytoremediation potential of castor bean plants. Therefore, the novelty of this research is that this research studied the potential role of glutathione (GSH), as a promising plant growth regulator, in enhancing the lead stress tolerance and phytoremediation potential of castor bean plants grown under lead stress conditions. The results indicated that Pb stress reduced the growth, biomass, chlorophyll pigments and gas exchange attributes of castor bean plants, causing oxidative damage in plants. Pb stress induced the oxidative stress markers and activities of antioxidant enzymes. On the other hand, the application of GSH reduced oxidative stress markers, but enhanced the growth, biomass, photosynthetic pigments, gas exchange attributes, Pb accumulation and antioxidant enzymes activities of lead-stressed castor bean plants. Taken together, the findings revealed the promising role of GSH in enhancing the lead stress tolerance and phytoremediation potential of castor bean plants cultivated in lead-polluted soils.

Towards Cognitive Authentication for Smart Healthcare Applications.

Secure and reliable sensing plays the key role for cognitive tracking i.e., activity identification and cognitive monitoring of every individual. Over the last years there has been an increasing interest from both academia and industry in cognitive authentication also known as biometric recognition. These are an effect of individuals' biological and physiological traits. Among various traditional biometric and physiological features, we include cognitive/brainwaves via electroencephalogram (EEG) which function as a unique performance indicator due to its reliable, flexible, and unique trait resulting in why it is hard for an un-authorized entity(ies) to breach the boundaries by stealing or mimicking them. Conventional security and privacy techniques in the medical domain are not the potential candidates to simultaneously provide both security and energy efficiency. Therefore, state-of-the art biometrics methods (i.e., machine learning, deep learning, etc.) their applications with novel solutions are investigated and recommended. The experimental setup considers EEG data analysis and interpretation of BCI. The key purpose of this setup is to reduce the number of electrodes and hence the computational power of the Random Forest (RF) classifier while testing EEG data. The performance of the random forest classifier was based on EEG datasets for 20 subjects. We found that the total number of occurred events revealed 96.1% precision in terms of chosen events.

Flower-like Highly Open-Structured Binder-Free Zn-Co-Oxide Nanosheet for High-Performance Supercapacitor Electrodes.

Scientific research is being compelled to develop highly efficient and cost-effective energy-storing devices such as supercapacitors (SCs). The practical use of SC devices is hindered by their low energy density and poor rate capability due to the binding agents in fabricating electrodes. Herein, we proposed flower-like highly open-structured binder-free ZnCo2O4 micro-flowers composed of nanosheets supported in nickel foam (ZnCoO@NF) with improved rate capability up to 91.8% when current varied from 2 to 20 A·g-1. The ZnCoO@NF electrode exhibited a superior specific capacitance of 1132 F·g-1 at 2 A·g-1 and revealed 99% cycling stability after 7000 cycles at a high current density of 20 A·g-1. The improved performance of the ZnCoO@NF electrode is attributed to the highly stable structure of the micro/nano-multiscale architecture, which provides both the high conduction of electrons and fast ionic transportation paths simultaneously.

Combined use of different nanoparticles effectively decreased cadmium (Cd) concentration in grains of wheat grown in a field contaminated with Cd.

Cadmium (Cd) accumulation in arable lands has become a serious matter for food security. Among various approaches, the application of nanoparticles (NPs) for remediation of contaminated water and soils is attaining more popularity worldwide. The current field experiment was executed to explore the impacts of single and combined use of ZnO NPs, Fe NPs and Si NPs on wheat growth and Cd intake by plants in a Cd-contaminated field. Wheat was sown in a field which was contaminated with Cd and was irrigated with the raw-city-effluent while NPs were applied as foliar spray alone and in all possible combinations. The data revealed that straw and grain yields were enhanced in the presence of NPs over control. Chlorophyll, carotenoids contents and antioxidants activities were enhanced while electrolyte leakage was reduced with all NPs over control. In comparison with control, Cd uptake in wheat straw was reduced by 84% and Cd uptake in grain was reduced by 99% in T8 where all three NPs were foliar-applied simultaneously. Zinc (Zn) and iron (Fe) contents were increased in those plants where ZnO and Fe NPs were exogenously applied which revealed that ZnO and Fe NPs enhanced the bio-fortification of Zn and Fe in wheat grains. Overall, foliar application of different NPs is beneficial for better wheat growth, yield, nutrients uptake and to lessen the Cd intake by plants grown in Cd-contaminated soil under real field conditions.

Current status and future possibilities of molecular genetics techniques in Brassica napus.

As PCR methods have improved over the last 15 years, there has been an upsurge in the number of new DNA marker tools, which has allowed the generation of high-density molecular maps for all the key Brassica crop types. Biotechnology and molecular plant breeding have emerged as a significant tool for molecular understanding that led to a significant crop improvement in the Brassica napus species. Brassica napus possess a very complicated polyploidy-based genomics. The quantitative trait locus (QTL) is not sufficient to develop effective markers for trait introgression. In the coming years, the molecular marker techniques will be more effective to determine the whole genome impairing desired traits. Available genetic markers using the single-nucleotide sequence (SNP) technique and high-throughput sequencing are effective in determining the maps and genome polymorphisms amongst candidate genes and allele interactions. High-throughput sequencing and gene mapping techniques are involved in discovering new alleles and gene pairs, serving as a bridge between the gene map and genome evaluation. The decreasing cost for DNA sequencing will help in discovering full genome sequences with less resources and time. This review describes (1) the current use of integrated approaches, such as molecular marker technologies, to determine genome arrangements and interspecific outcomes combined with cost-effective genomes to increase the efficiency in prognostic breeding efforts. (2) It also focused on functional genomics, proteomics and field-based breeding practices to achieve insight into the genetics underlying both simple and complex traits in canola.

Combining Bootstrap Aggregation with Support Vector Regression for Small Blood Pressure Measurement.

Blood pressure measurement based on oscillometry is one of the most popular techniques to check a health condition of individual subjects. This paper proposes a support vector using fusion estimator with a bootstrap technique for oscillometric blood pressure (BP) estimation. However, some inherent problems exist with this approach. First, it is not simple to identify the best support vector regression (SVR) estimator, and worthy information might be omitted when selecting one SVR estimator and discarding others. Additionally, our input feature data, acquired from only five BP measurements per subject, represent a very small sample size. This constitutes a critical limitation when utilizing the SVR technique and can cause overfitting or underfitting, depending on the structure of the algorithm. To overcome these challenges, a fusion with an asymptotic approach (based on combining the bootstrap with the SVR technique) is utilized to generate the pseudo features needed to predict the BP values. This ensemble estimator using the SVR technique can learn to effectively mimic the non-linear relations between the input data acquired from the oscillometry and the nurse's BPs.

Content Based Image Retrieval by Using Color Descriptor and Discrete Wavelet Transform.

Due to recent development in technology, the complexity of multimedia is significantly increased and the retrieval of similar multimedia content is a open research problem. Content-Based Image Retrieval (CBIR) is a process that provides a framework for image search and low-level visual features are commonly used to retrieve the images from the image database. The basic requirement in any image retrieval process is to sort the images with a close similarity in term of visually appearance. The color, shape and texture are the examples of low-level image features. The feature plays a significant role in image processing. The powerful representation of an image is known as feature vector and feature extraction techniques are applied to get features that will be useful in classifying and recognition of images. As features define the behavior of an image, they show its place in terms of storage taken, efficiency in classification and obviously in time consumption also. In this paper, we are going to discuss various types of features, feature extraction techniques and explaining in what scenario, which features extraction technique will be better. The effectiveness of the CBIR approach is fundamentally based on feature extraction. In image processing errands like object recognition and image retrieval feature descriptor is an immense among the most essential step. The main idea of CBIR is that it can search related images to an image passed as query from a dataset got by using distance metrics. The proposed method is explained for image retrieval constructed on YCbCr color with canny edge histogram and discrete wavelet transform. The combination of edge of histogram and discrete wavelet transform increase the performance of image retrieval framework for content based search. The execution of different wavelets is additionally contrasted with discover the suitability of specific wavelet work for image retrieval. The proposed algorithm is prepared and tried to implement for Wang image database. For Image Retrieval Purpose, Artificial Neural Networks (ANN) is used and applied on standard dataset in CBIR domain. The execution of the recommended descriptors is assessed by computing both Precision and Recall values and compared with different other proposed methods with demonstrate the predominance of our method. The efficiency and effectiveness of the proposed approach outperforms the existing research in term of average precision and recall values.

Real-time Medical Emergency Response System: Exploiting IoT and Big Data for Public Health.

Healthy people are important for any nation's development. Use of the Internet of Things (IoT)-based body area networks (BANs) is increasing for continuous monitoring and medical healthcare in order to perform real-time actions in case of emergencies. However, in the case of monitoring the health of all citizens or people in a country, the millions of sensors attached to human bodies generate massive volume of heterogeneous data, called "Big Data." Processing Big Data and performing real-time actions in critical situations is a challenging task. Therefore, in order to address such issues, we propose a Real-time Medical Emergency Response System that involves IoT-based medical sensors deployed on the human body. Moreover, the proposed system consists of the data analysis building, called "Intelligent Building," depicted by the proposed layered architecture and implementation model, and it is responsible for analysis and decision-making. The data collected from millions of body-attached sensors is forwarded to Intelligent Building for processing and for performing necessary actions using various units such as collection, Hadoop Processing (HPU), and analysis and decision. The feasibility and efficiency of the proposed system are evaluated by implementing the system on Hadoop using an UBUNTU 14.04 LTS coreTMi5 machine. Various medical sensory datasets and real-time network traffic are considered for evaluating the efficiency of the system. The results show that the proposed system has the capability of efficiently processing WBAN sensory data from millions of users in order to perform real-time responses in case of emergencies.

Blood cell image segmentation and classification: a systematic review.

Background: Blood diseases such as leukemia, anemia, lymphoma, and thalassemia are hematological disorders that relate to abnormalities in the morphology and concentration of blood elements, specifically white blood cells (WBC) and red blood cells (RBC). Accurate and efficient diagnosis of these conditions significantly depends on the expertise of hematologists and pathologists. To assist the pathologist in the diagnostic process, there has been growing interest in utilizing computer-aided diagnostic (CAD) techniques, particularly those using medical image processing and machine learning algorithms. Previous surveys in this domain have been narrowly focused, often only addressing specific areas like segmentation or classification but lacking a holistic view like segmentation, classification, feature extraction, dataset utilization, evaluation matrices, etc. Methodology: This survey aims to provide a comprehensive and systematic review of existing literature and research work in the field of blood image analysis using deep learning techniques. It particularly focuses on medical image processing techniques and deep learning algorithms that excel in the morphological characterization of WBCs and RBCs. The review is structured to cover four main areas: segmentation techniques, classification methodologies, descriptive feature selection, evaluation parameters, and dataset selection for the analysis of WBCs and RBCs. Results: Our analysis reveals several interesting trends and preferences among researchers. Regarding dataset selection, approximately 50% of research related to WBC segmentation and 60% for RBC segmentation opted for manually obtaining images rather than using a predefined dataset. When it comes to classification, 45% of the previous work on WBCs chose the ALL-IDB dataset, while a significant 73% of researchers focused on RBC classification decided to manually obtain images from medical institutions instead of utilizing predefined datasets. In terms of feature selection for classification, morphological features were the most popular, being chosen in 55% and 80% of studies related to WBC and RBC classification, respectively. Conclusion: The diagnostic accuracy for blood-related diseases like leukemia, anemia, lymphoma, and thalassemia can be significantly enhanced through the effective use of CAD techniques, which have evolved considerably in recent years. This survey provides a broad and in-depth review of the techniques being employed, from image segmentation to classification, feature selection, utilization of evaluation matrices, and dataset selection. The inconsistency in dataset selection suggests a need for standardized, high-quality datasets to strengthen the diagnostic capabilities of these techniques further. Additionally, the popularity of morphological features indicates that future research could further explore and innovate in this direction.

Improved Electrochemical Performance of Aqueous Hybrid Supercapacitors Using CrCo2O4 Mesoporous Nanowires: An Innovative Strategy toward Sustainable Energy Devices.

High-rate aqueous hybrid supercapacitors (AHSCs) have attracted relevant scientific significance owing to their expected energy density, supercapacitor-level power density, and battery-level energy density. In this work, a bimetallic nanostructured material with chromium-incorporated cobalt oxide (CCO, i.e., CoCr2O4) was prepared via a hydrothermal method to form a stable cubic obelisk structure. Compared with CCO materials prepared using traditional methods, CCO displayed a nanowire structure (50 nm diameter), suggesting an enhanced specific surface area and a large number of active sites for chemical reactions. The electrode possessed a high specific capacitance (2951 F g-1) at a current density of 1 A g-1, minimum Rct (0.135 Ω), and the highest capacitance retention (98.7%), making it an ideal electrode material for AHSCs. Ex situ analysis based on X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS) showed a favorable stability of CCO after 10,000 cycles without any phase changes being detected. GGA and GGA + U methods employed in density functional theory (DFT) also highlighted the enhanced metallic properties of CCO originating from the synergistic effect of semiconducting Cr2O3 and Co3O4 materials.

Evaluation on microalgae for the production of bio-chemicals and electricity.

Recent advancement in biophotovoltaic systems using microalgae, coupled with biorefinery approach, would improve economy-feasibility in production. The major concern is its commercial strength in terms of scalability, strain selection and extraction procedure cost. It must compete with conventional feedstocks such as fossil fuels. This project proposes to enhance the economic feasibility of microalgae-based biorefinery by evaluating their performance for bio-electricity, bio-diesel and carotenoids production in a single cycle. The first part of the study was to construct and select a Bio-bottle Voltaic (BBV) device that would allow microalgae to grow and produce bioproducts, as well as generate the maximum current output reading derived from the microalgae's photosynthesis process. The second phase consisted of a 25-day investigation into the biorefinery performance of six different microalgal species in producing bio-electricity, bio-diesel and carotenoid in a prototype BBV device. The prototype BBV device with aluminium foil and pencil lead as its anode and cathode produced the highest carotenoid and biodiesel component production from the two microalgae tested, according to the results of the first phase of the experiment. In the second portion of the study, Scenedesmus dimorphus and Chlorella vulgaris were identified as the two microalgae most capable of maintaining their growth throughout the experiment. The maximum current reading observed for C. vulgaris was 653 mV. High Performance Liquid Chromatography analysis showed four major carotenoid compounds found which were Neoxanthin, Cantaxanthin, Astaxanthin and 9-cis antheraxanthin, and the highest carotenoid producer was C. vulgaris which recorded at 1.73 µg/mL. C. vulgaris recorded as the most alkanes producer with 22 compounds detected and Heptacosane and Heneicosane as the two major biodiesel compounds found in the extracts. Evaluation of C. vulgaris data showed that it has enormous potential for microalgal biorefinery candidates. Further ongoing research and development efforts for C. vulgaris will improve the economic viability of microalgae-based industries and reduce reliance on depleted fossil fuels.

Beyond Metallic Electrode: Spontaneous Formation of Fluidic Electrodes from Operational Liquid in Highly Functional Droplet-Based Electricity Generator.

The droplet-based electricity generator (DEG) has facilitated efficient droplet energy harvesting, yet diversifying its applications necessitates the incorporation of various to the DEG. This study first proposes a methodology for advancing the DEG by substituting its conventional metallic electrode with electrically conductive water electrode (WE), which is spontaneously generated during the operation of the DEG with operating liquid. Due to the inherent conductive and fluidic nature of water, the introduction of the WE maintains the electrical output performance of the DEG while imparting functionalities such as high transparency and flexibility. So, the resultant WE applied DEG (WE-DEG) exhibits high optical transmittance (≈99%) and retains its electricity-generating capability under varying deformations, including bending and stretching. This innovation expands the versatility of the DEG, and especially, a sun-raindrop dual-mode energy harvester is demonstrated by hybridizing the WE-DEG and photovoltaic (PV) cell. This hybridization effectively addresses the weather-dependent limitations inherent in each energy harvester and enhances the temperature-induced inefficiencies typically observed in PV cells, thereby enhancing the overall efficiency. The introduction of the WE will be poised to catalyze new developments in DEG research, paving the way for broader applicability and enhanced efficiency in droplet energy harvesting technologies.