Lipid metabolism and its implications in tumor cell plasticity and drug resistance: what we learned thus far?

Metabolic reprogramming, a hallmark of cancer, allows cancer cells to adapt to their specific energy needs. The Warburg effect benefits cancer cells in both hypoxic and normoxic conditions and is a well-studied reprogramming of metabolism in cancer. Interestingly, the alteration of other metabolic pathways, especially lipid metabolism has also grabbed the attention of scientists worldwide. Lipids, primarily consisting of fatty acids, phospholipids and cholesterol, play essential roles as structural component of cell membrane, signalling molecule and energy reserves. This reprogramming primarily involves aberrations in the uptake, synthesis and breakdown of lipids, thereby contributing to the survival, proliferation, invasion, migration and metastasis of cancer cells. The development of resistance to the existing treatment modalities poses a major challenge in the field of cancer therapy. Also, the plasticity of tumor cells was reported to be a contributing factor for the development of resistance. A number of studies implicated that dysregulated lipid metabolism contributes to tumor cell plasticity and associated drug resistance. Therefore, it is important to understand the intricate reprogramming of lipid metabolism in cancer cells. In this review, we mainly focused on the implication of disturbed lipid metabolic events on inducing tumor cell plasticity-mediated drug resistance. In addition, we also discussed the concept of lipid peroxidation and its crucial role in phenotypic switching and resistance to ferroptosis in cancer cells. Elucidating the relationship between lipid metabolism, tumor cell plasticity and emergence of resistance will open new opportunities to develop innovative strategies and combinatorial approaches for the treatment of cancer.

Dynamic interplay of nuclear receptors in tumor cell plasticity and drug resistance: Shifting gears in malignant transformations and applications in cancer therapeutics.

Recent advances have brought forth the complex interplay between tumor cell plasticity and its consequential impact on drug resistance and tumor recurrence, both of which are critical determinants of neoplastic progression and therapeutic efficacy. Various forms of tumor cell plasticity, instrumental in facilitating neoplastic cells to develop drug resistance, include epithelial-mesenchymal transition (EMT) alternatively termed epithelial-mesenchymal plasticity, the acquisition of cancer stem cell (CSC) attributes, and transdifferentiation into diverse cell lineages. Nuclear receptors (NRs) are a superfamily of transcription factors (TFs) that play an essential role in regulating a multitude of cellular processes, including cell proliferation, differentiation, and apoptosis. NRs have been implicated to play a critical role in modulating gene expression associated with tumor cell plasticity and drug resistance. This review aims to provide a comprehensive overview of the current understanding of how NRs regulate these key aspects of cancer biology. We discuss the diverse mechanisms through which NRs influence tumor cell plasticity, including EMT, stemness, and metastasis. Further, we explore the intricate relationship between NRs and drug resistance, highlighting the impact of NR signaling on chemotherapy, radiotherapy and targeted therapies. We also discuss the emerging therapeutic strategies targeting NRs to overcome tumor cell plasticity and drug resistance. This review also provides valuable insights into the current clinical trials that involve agonists or antagonists of NRs modulating various aspects of tumor cell plasticity, thereby delineating the potential of NRs as therapeutic targets for improved cancer treatment outcomes.

Exploring the nexus of nuclear receptors in hematological malignancies.

Hematological malignancies (HM) represent a subset of neoplasms affecting the blood, bone marrow, and lymphatic systems, categorized primarily into leukemia, lymphoma, and multiple myeloma. Their prognosis varies considerably, with a frequent risk of relapse despite ongoing treatments. While contemporary therapeutic strategies have extended overall patient survival, they do not offer cures for advanced stages and often lead to challenges such as acquisition of drug resistance, recurrence, and severe side effects. The need for innovative therapeutic targets is vital to elevate both survival rates and patients' quality of life. Recent research has pivoted towards nuclear receptors (NRs) due to their role in modulating tumor cell characteristics including uncontrolled proliferation, differentiation, apoptosis evasion, invasion and migration. Existing evidence emphasizes NRs' critical role in HM. The regulation of NR expression through agonists, antagonists, or selective modulators, contingent upon their levels, offers promising clinical implications in HM management. Moreover, several anticancer agents targeting NRs have been approved by the Food and Drug Administration (FDA). This review highlights the integral function of NRs in HM's pathophysiology and the potential benefits of therapeutically targeting these receptors, suggesting a prospective avenue for more efficient therapeutic interventions against HM.

Increased Peripheral Venous Catheter Bloodstream Infections during COVID-19 Pandemic, Switzerland.

Studies suggest that central venous catheter bloodstream infections (BSIs) increased during the COVID-19 pandemic. We investigated catheter-related BSIs in Switzerland and found peripheral venous catheter (PVC) BSI incidence increased during 2021-2022 compared with 2020. These findings should raise awareness of PVC-associated BSIs and prompt inclusion of PVC BSIs in surveillance systems.

Natural compounds targeting nuclear receptors for effective cancer therapy.

Human nuclear receptors (NRs) are a family of forty-eight transcription factors that modulate gene expression both spatially and temporally. Numerous biochemical, physiological, and pathological processes including cell survival, proliferation, differentiation, metabolism, immune modulation, development, reproduction, and aging are extensively orchestrated by different NRs. The involvement of dysregulated NRs and NR-mediated signaling pathways in driving cancer cell hallmarks has been thoroughly investigated. Targeting NRs has been one of the major focuses of drug development strategies for cancer interventions. Interestingly, rapid progress in molecular biology and drug screening reveals that the naturally occurring compounds are promising modern oncology drugs which are free of potentially inevitable repercussions that are associated with synthetic compounds. Therefore, the purpose of this review is to draw our attention to the potential therapeutic effects of various classes of natural compounds that target NRs such as phytochemicals, dietary components, venom constituents, royal jelly-derived compounds, and microbial derivatives in the establishment of novel and safe medications for cancer treatment. This review also emphasizes molecular mechanisms and signaling pathways that are leveraged to promote the anti-cancer effects of these natural compounds. We have also critically reviewed and assessed the advantages and limitations of current preclinical and clinical studies on this subject for cancer prophylaxis. This might subsequently pave the way for new paradigms in the discovery of drugs that target specific cancer types.

Natural compounds targeting YAP/TAZ axis in cancer: Current state of art and challenges.

Cancer has become a burgeoning global healthcare concern marked by its exponential growth and significant economic ramifications. Though advancements in the treatment modalities have increased the overall survival and quality of life, there are no definite treatments for the advanced stages of this malady. Hence, understanding the diseases etiologies and the underlying molecular complexities, will usher in the development of innovative therapeutics. Recently, YAP/TAZ transcriptional regulation has been of immense interest due to their role in development, tissue homeostasis and oncogenic transformations. YAP/TAZ axis functions as coactivators within the Hippo signaling cascade, exerting pivotal influence on processes such as proliferation, regeneration, development, and tissue renewal. In cancer, YAP is overexpressed in multiple tumor types and is associated with cancer stem cell attributes, chemoresistance, and metastasis. Activation of YAP/TAZ mirrors the cellular "social" behavior, encompassing factors such as cell adhesion and the mechanical signals transmitted to the cell from tissue structure and the surrounding extracellular matrix. Therefore, it presents a significant vulnerability in the clogs of tumors that could provide a wide window of therapeutic effectiveness. Natural compounds have been utilized extensively as successful interventions in the management of diverse chronic illnesses, including cancer. Owing to their capacity to influence multiple genes and pathways, natural compounds exhibit significant potential either as adjuvant therapy or in combination with conventional treatment options. In this review, we delineate the signaling nexus of YAP/TAZ axis, and present natural compounds as an alternate strategy to target cancer.

An investigation of the environmental implications of bioplastics: Recent advancements on the development of environmentally friendly bioplastics solutions.

The production and utilization of plastics may prove beneficial, but the environmental impact suggests the opposite. The single-use plastics (SUP) and conventional plastics are harmful to the environment and need prompt disposal. Bioplastics are increasingly being considered as a viable alternative to conventional plastics due to their potential to alleviate environmental concerns such as greenhouse gas emissions and pollution. However, the previous reviews revealed a lack of consistency in the methodologies used in the Life Cycle Assessments (LCAs), making it difficult to compare the results across studies. The current study provides a systematic review of LCAs that assess the environmental impact of bioplastics. The different mechanical characteristics of bio plastics, like tensile strength, Young's modulus, flexural modulus, and elongation at break are reviewed which suggest that bio plastics are comparatively much better than synthetic plastics. Bioplastics have more efficient mechanical properties compared to synthetic plastics which signifies that bioplastics are more sustainable and reliable than synthetic plastics. The key challenges in bioplastic adoption and production include competition with food production for feedstock, high production costs, uncertainty in end-of-life management, limited biodegradability, lack of standardization, and technical performance limitations. Addressing these challenges requires collaboration among stakeholders to drive innovation, reduce costs, improve end-of-life management, and promote awareness and education. Overall, the study suggests that while bioplastics have the potential to reduce environmental impact, further research is needed to better understand their life cycle and optimize their end-of-life (EoL) management and production to maximize their environmental benefits.

Bentonite SDBS-loaded composite for methylene blue removal from wastewater: An experimental and theoretical investigation.

This study addresses the urgent need for practical solutions to industrial water contamination. Utilizing Algerian Bentonite as an adsorbent due to its regional prevalence, we focused on the efficiency of the Bentonite/Sodium dodecylbenzene sulfonate (SDBS) matrix in Methylene Blue (MB) removal. The zero-charge point and IR spectroscopy characterized the adsorbent. Acidic pH facilitated SDBS adsorption on Bentonite, achieving equilibrium in 30 min with a pseudo-second-order model. The UPAC and Freundlich model indicated a qmax of 25.97 mg/g. SDBS adsorption was exothermic at elevated temperatures. The loaded Bentonite exhibited excellent MB adsorption (pH 3-9) with PSOM kinetics. Maximum adsorption capacity using IUPAC and GILES-recommended isotherms was qmax = 23.54 mg/g. The loaded Bentonite's specific surface area was 70.01 m2/g, and the Sips model correlated well with experimental data (R2 = 0.98). This study highlights adsorption, mainly Bentonite/SDBS matrices, as a promising approach for remediating polluted areas by efficiently capturing and removing surfactants and dyes, contributing valuable insights to address industrial water contamination challenges.

Predicting concrete strength early age using a combination of machine learning and electromechanical impedance with nano-enhanced sensors.

To ensure the structural integrity of concrete and prevent unanticipated fracturing, real-time monitoring of early-age concrete's strength development is essential, mainly through advanced techniques such as nano-enhanced sensors. The piezoelectric-based electro-mechanical impedance (EMI) method with nano-enhanced sensors is emerging as a practical solution for such monitoring requirements. This study presents a strength estimation method based on Non-Destructive Testing (NDT) Techniques and Long Short-Term Memory (LSTM) and artificial neural networks (ANNs) as hybrid (NDT-LSTMs-ANN), including several types of concrete strength-related agents. Input data includes water-to-cement rate, temperature, curing time, and maturity based on interior temperature, allowing experimentally monitoring the development of concrete strength from the early steps of hydration and casting to the last stages of hardening 28 days after the casting. The study investigated the impact of various factors on concrete strength development, utilizing a cutting-edge approach that combines traditional models with nano-enhanced piezoelectric sensors and NDT-LSTMs-ANN enhanced with nanotechnology. The results demonstrate that the hybrid provides highly accurate concrete strength estimation for construction safety and efficiency. Adopting the piezoelectric-based EMI technique with these advanced sensors offers a viable and effective monitoring solution, presenting a significant leap forward for the construction industry's structural health monitoring practices.

Therapeutic potential of tocotrienols as chemosensitizers in cancer therapy.

Chemoresistance is the adaptation of cancer cells against therapeutic agents. When exhibited by cancer cells, chemoresistance helps them to avoid apoptosis, cause relapse, and metastasize, making it challenging for chemotherapeutic agents to treat cancer. Various strategies like dosage modification of drugs, nanoparticle-based delivery of chemotherapeutics, antibody-drug conjugates, and so on are being used to target and reverse chemoresistance, one among such is combination therapy. It uses the combination of two or more therapeutic agents to reverse multidrug resistance and improve the effects of chemotherapy. Phytochemicals are known to exhibit chemosensitizing properties and are found to be effective against various cancers. Tocotrienols (T3) and tocopherols (T) are natural bioactive analogs of vitamin E, which exhibit important medicinal value and potential curative properties apart from serving as an antioxidant and nutrient supplement. Notably, T3 exhibits a variety of pharmacological activities like anticancer, anti-inflammatory, antiproliferative, and so on. The chemosensitizing property of tocotrienol is exhibited by modulating several signaling pathways and molecular targets involved in cancer cell survival, proliferation, invasion, migration, and metastasis like NF-κB, STATs, Akt/mTOR, Bax/Bcl-2, Wnt/ß-catenin, and many more. T3 sensitizes cancer cells to chemotherapeutic drugs including cisplatin, doxorubicin, and paclitaxel increasing drug concentration and cytotoxicity. Discussed herewith are the chemosensitizing properties of tocotrienols on various cancer cell types when combined with various drugs and biological molecules.

Assessment of hydrocarbon degradation capacity and kinetic modeling of Chlorella vulgaris and Scenedesmus quadricauda for crude oil phycoremediation under mixotrophic conditions.

Crude oil spills imperil aquatic ecosystems globally, prompting innovative solutions such as microalgae-based bioremediation. This study explores the potential of Chlorella vulgaris and Scenedesmus quadricauda, for crude oil spill phycoremediation under mixotrophic conditions and varying crude oil concentrations (0.5-2%). C. vulgaris demonstrated notable resilience, thriving up to 1% crude oil exposure, while S. quadricauda adapted to lower concentrations. Optimal growth for both was observed at 0.5% exposure. Chlorophyll a content in C. vulgaris increases at 0.5% exposure but declines above 1%, while a decline was noticeable in chlorophyll b in treatment groups above 1%. Carotenoid levels varied, displaying the highest levels at higher concentrations above 1.5%. Similarly, S. quadricauda showed increased chlorophyll a content at 0.5% exposure, with stable carotenoid levels and a decline in chlorophyll b content at higher concentrations. GC/MS analyses indicated C. vulgaris efficiently degraded aliphatic compounds like decane and tridecane, surpassing S. quadricauda in degrading both aliphatic and aromatic hydrocarbons. Growth kinetics was best represented by the modified Gompertz and logistic models. These findings highlight the species-specific adaptability and optimal concentration for microalgae to degrade crude oil effectively, advancing phycoremediation processes and strategies critical for environmental restoration.

This study marks the first exploration of both Chlorella vulgaris and the previously unexplored Scenedesmus quadricauda for crude oil phycoremediation potential under mixotrophic conditions. Additionally, it pioneers the modeling and study of algae growth kinetics in response to crude oil exposure. Notably, this research demonstrated the adaptability and efficiency of C. vulgaris in degrading crude oil components under mixotrophic conditions up to a level of 1%, while S. quadricauda showed similar capabilities at a concentration of 0.5%.

Liquid fertilizers produced by microwave-assisted acid hydrolysis of livestock and poultry wastes and their effects on hot pepper cultivation.

Liquid fertilizers (LFs) produced by microwave-assisted acid hydrolysis of livestock and poultry wastes were applied to potted hot pepper (Capsicum annuum L.) to evaluate their potential to be used as amino acid LFs. A preliminary experiment was conducted to determine the optimum acid-hydrolysis conditions for producing LFs from a mixture of pig hair and faeces (P) and another mixture of chicken feathers and faeces (C). Two LFs were produced under the optimum acid-hydrolysis conditions (acidification by sulphuric acid (7.5 mol L-1) in a microwave (200 W) for 90 minutes), and a commercial amino acid LF (Guo Guang (GG)) was used for comparison. P, C and GG fertilizers were tested in potted hot pepper cultivation at two doses, whereas no fertilizer application served as the control (CK). P and C fertilizers significantly increased the fruit yield compared with GG fertilizer, particularly at the higher dose. Moreover, the treatments improved the fruit vitamin C and soluble sugar contents in the order of C > P > GG compared with CK. These results could be attributed to more types of amino acids in C fertilizer than in P and GG fertilizers. The results also indicated that the prepared fertilizers could significantly increase the shoot and root dry weight, soil available nitrogen and phosphorus contents and nitrogen, phosphorus, and potassium (NPK) uptake by plants compared with CK. In conclusion, microwave-assisted acid hydrolysis could effectively convert unusable wastes into valuable fertilizers comparable or even superior to commercial fertilizers.

Providing multimedia information to children and young people increases recruitment to trials: pre-planned meta-analysis of SWATs.

BACKGROUND: Randomised controlled trials are often beset by problems with poor recruitment and retention. Information to support decisions on trial participation is usually provided as printed participant information sheets (PIS), which are often long, technical, and unappealing. Multimedia information (MMI), including animations and videos, may be a valuable alternative or complement to a PIS. The Trials Engagement in Children and Adolescents (TRECA) study compared MMI to PIS to investigate the effects on participant recruitment, retention, and quality of decision-making. METHODS: We undertook six SWATs (Study Within A Trial) within a series of host trials recruiting children and young people. Potential participants in the host trials were randomly allocated to receive MMI-only, PIS-only, or combined MMI + PIS. We recorded the rates of recruitment and retention (varying between 6 and 26 weeks post-randomisation) in each host trial. Potential participants approached about each host trial were asked to complete a nine-item Decision-Making Questionnaire (DMQ) to indicate their evaluation of the information and their reasons for participation/non-participation. Odds ratios were calculated and combined in a meta-analysis. RESULTS: Data from 3/6 SWATs for which it was possible were combined in a meta-analysis (n = 1758). Potential participants allocated to MMI-only were more likely to be recruited to the host trial than those allocated to PIS-only (OR 1.54; 95% CI 1.05, 2.28; p = 0.03). Those allocated to combined MMI + PIS compared to PIS-only were no more likely to be recruited to the host trial (OR = 0.89; 95% CI 0.53, 1.50; p = 0.67). Providing MMI rather than PIS did not impact on DMQ scores. Once children and young people had been recruited to host trials, their trial retention rates did not differ according to intervention allocation. CONCLUSIONS: Providing MMI-only increased the trial recruitment rate compared to PIS-only but did not affect DMQ scores. Combined MMI + PIS instead of PIS had no effect on recruitment or retention. MMIs are a useful tool for trial recruitment in children and young people, and they could reduce trial recruitment periods.

Unveiling antibacterial and antioxidant activities of zinc phosphate-based nanosheets synthesized by Aspergillus fumigatus and its application in sustainable decolorization of textile wastewater.

BACKGROUND: The development of an environment-friendly nanomaterial with promising antimicrobial and antioxidant properties is highly desirable. The decolorization potentiality of toxic dyes using nanoparticles is a progressively serious worldwide issue. METHODS: The successful biosynthesis of zinc nanoparticles based on phosphates (ZnP-nps) was performed using the extracellular secretions of Aspergillus fumigatus. The antibacterial activity of the biosynthetic ZnP-nps was investigated against Gram-negative bacteria and Gram-positive bacteria using the agar diffusion assay method. The antioxidant property for the biosynthetic nanomaterial was evaluated by DPPH and H2O2 radical scavenging assay. RESULTS: Remarkable antibacterial and antiradical scavenging activities of ZnP-nps were observed in a dose-dependent manner. The minimum inhibitory concentration (MIC) for Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli was 25 µg/ml, however, the MIC for Bacillus subtilis was 12.5 µg/ml. The maximum adsorptive performance of nanomaterial was respectively achieved at initial dye concentration of 200 mg/L and 150 mg/L using methylene blue (MB) and methyl orange (MO), where sorbent dosages were 0.5 g for MB and 0.75 g for MB; pH was 8.0 for MB and 4.0 for MO; temperature was 30 °C; contact time was 120 min. The experimental data was better obeyed with Langmuir's isotherm and pseudo-second-order kinetic model (R2 > 0.999). The maximum adsorption capacity (qmax) of MB and MO dyes on nanomaterial were 178.25 mg/g and 50.10 mg/g, respectively. The regenerated nanomaterial, respectively, persist > 90% and 60% for MB and MO after 6 successive cycles. The adsorption capacity of the prepared zinc phosphate nanosheets crystal toward MB and MO, in the present study, was comparable/superior with other previously engineered adsorbents. CONCLUSIONS: Based on the above results, the biosynthesized ZnP-nanosheets are promising nanomaterial for their application in sustainable dye decolorization processes and they can be employed in controlling different pathogenic bacteria with a potential application as antiradical scavenging agent. Up to our knowledge, this is probably the first study conducted on the green synthesis of ZnP-nanosheets by filamentous fungus and its significant in sustainable dye decolorization.

Unsteady ternary hybrid-nanofluid flow over an expanding/shrinking cylinder with multiple slips: a Yamada-Ota model implementation.

The primary objective of this investigation is to examine the thermal state of an unsteady ternary hybrid-nanofluid flow over an expanding/shrinking cylinder. The influence of radiation along with a non-uniform thermal source/sink is taken into account to expedite heat distribution. Multiple slips are considered at the cylinder interface. The mathematical model is simplified by incorporating appropriate transformations. A numerical solution is obtained using the bvp4c algorithm. The flow characteristics and behavior of the trihybrid nanoliquid exhibit significant changes when the cylinder expands or contracts. The effects of various emerging parameters are analyzed using graphical representations. The velocity field shows an opposite trend when the unsteadiness and mass transfer parameters are increased. The thermal field improves with higher values of the non-uniform source/sink parameter but deteriorates with an increase in the thermal slip parameter. The drag force increases with higher values of the unsteadiness parameter, while it decreases with amplified values of the mass suction and velocity slip parameters. A strong correlation is observed with previous studies which validates and strengthens the credibility of the present analysis.

Nanocatalysts as fast and powerful medical intervention: Bridging cochlear implant therapies and advanced modelling using Hidden Markov Models (HMMs) for effective treatment of inner ear infections.

As human population growth and waste from technologically advanced industries threaten to destabilise our delicate ecological equilibrium, the global spotlight intensifies on environmental contamination and climate-related changes. These challenges extend beyond our external environment and have significant effects on our internal ecosystems. The inner ear, which is responsible for balance and auditory perception, is a prime example. When these sensory mechanisms are impaired, disorders such as deafness can develop. Traditional treatment methods, including systemic antibiotics, are frequently ineffective due to inadequate inner ear penetration. Conventional techniques for administering substances to the inner ear fail to obtain adequate concentrations as well. In this context, cochlear implants laden with nanocatalysts emerge as a promising strategy for the targeted treatment of inner ear infections. Coated with biocompatible nanoparticles containing specific nanocatalysts, these implants can degrade or neutralise contaminants linked to inner ear infections. This method enables the controlled release of nanocatalysts directly at the infection site, thereby maximising therapeutic efficacy and minimising adverse effects. In vivo and in vitro studies have demonstrated that these implants are effective at eliminating infections, reducing inflammation, and fostering tissue regeneration in the ear. This study investigates the application of hidden Markov models (HMMs) to nanocatalyst-loaded cochlear implants. The HMM is trained on surgical phases in order to accurately identify the various phases associated with implant utilisation. This facilitates the precision placement of surgical instruments within the ear, with a location accuracy between 91% and 95% and a standard deviation between 1% and 5% for both sites. In conclusion, nanocatalysts serve as potent medicinal instruments, bridging cochlear implant therapies and advanced modelling utilising hidden Markov models for the effective treatment of inner ear infections. Cochlear implants loaded with nanocatalysts offer a promising method to combat inner ear infections and enhance patient outcomes by addressing the limitations of conventional treatments.

Effect and mechanism of nano-materials on plant resistance to cadmium toxicity: A review.

Cadmium (Cd), one of the most toxic heavy metals, has been extensively studied by environmental scientists because of its detrimental effects on plants, animals, and humans. Increased industrial activity has led to environmental contamination with Cd. Cadmium can enter the food chain and pose a potential human health risk. Therefore, reducing the accumulation of Cd in plant species and enhancing their detoxification abilities are crucial for remediating heavy metal pollution in contaminated areas. One innovative technique is nano-phytoremediation, which employs nanomaterials ranging from 1 to 100 nm in size to mitigate the accumulation and detrimental effects of Cd on plants. Although extensive research has been conducted on using nanomaterials to mitigate Cd toxicity in plants, it is important to note that the mechanism of action varies depending on factors such as plant species, level of Cd concentration, and type of nanomaterials employed. This review aimed to consolidate and organize existing data, providing a comprehensive overview of the effects and mechanisms of nanomaterials in enhancing plant resistance to Cd. In particular, its deep excavation the mechanisms of detoxification heavy metals of nanomaterials by plants, including regulating Cd uptake and distribution, enhancing antioxidant capacity, regulating gene expression, and regulating physiological metabolism. In addition, this study provides insights into future research directions in this field.

Underwater Wireless Sensor Networks with RSSI-Based Advanced Efficiency-Driven Localization and Unprecedented Accuracy.

Deep-sea object localization by underwater acoustic sensor networks is a current research topic in the field of underwater communication and navigation. To find a deep-sea object using underwater wireless sensor networks (UWSNs), the sensors must first detect the signals sent by the object. The sensor readings are then used to approximate the object's position. A lot of parameters influence localization accuracy, including the number and location of sensors, the quality of received signals, and the algorithm used for localization. To determine position, the angle of arrival (AOA), time difference of arrival (TDoA), and received signal strength indicator (RSSI) are used. The UWSN requires precise and efficient localization algorithms because of the changing underwater environment. Time and position are required for sensor data, especially if the sensor is aware of its surroundings. This study describes a critical localization strategy for accomplishing this goal. Using beacon nodes, arrival distance validates sensor localization. We account for the fact that sensor nodes are not in perfect temporal sync and that sound speed changes based on the medium (water, air, etc.) in this section. Our simulations show that our system can achieve high localization accuracy by accounting for temporal synchronisation, measuring mean localization errors, and forecasting their variation. The suggested system localization has a lower mean estimation error (MEE) while using RSSI. This suggests that measurements based on RSSI provide more precision and accuracy during localization.

Artificial Intelligence Based Approach for Classification of Human Activities Using MEMS Sensors Data.

The integration of Micro Electronic Mechanical Systems (MEMS) sensor technology in smartphones has greatly improved the capability for Human Activity Recognition (HAR). By utilizing Machine Learning (ML) techniques and data from these sensors, various human motion activities can be classified. This study performed experiments and compiled a large dataset of nine daily activities, including Laying Down, Stationary, Walking, Brisk Walking, Running, Stairs-Up, Stairs-Down, Squatting, and Cycling. Several ML models, such as Decision Tree Classifier, Random Forest Classifier, K Neighbors Classifier, Multinomial Logistic Regression, Gaussian Naive Bayes, and Support Vector Machine, were trained on sensor data collected from accelerometer, gyroscope, and magnetometer embedded in smartphones and wearable devices. The highest test accuracy of 95% was achieved using the random forest algorithm. Additionally, a custom-built Bidirectional Long-Short-Term Memory (Bi-LSTM) model, a type of Recurrent Neural Network (RNN), was proposed and yielded an improved test accuracy of 98.1%. This approach differs from traditional algorithmic-based human activity detection used in current wearable technologies, resulting in improved accuracy.

Compact UWB MIMO Antenna for 5G Millimeter-Wave Applications.

This paper presents a printed multiple-input multiple-output (MIMO) antenna with the advantages of compact size, good MIMO diversity performance and simple geometry for fifth-generation (5G) millimeter-wave (mm-Wave) applications. The antenna offers a novel Ultra-Wide Band (UWB) operation from 25 to 50 GHz, using a Defective Ground Structure (DGS) technology. Firstly, its compact size makes it suitable for integrating different telecommunication devices for various applications, with a prototype fabricated having a total size of 33 mm × 33 mm × 0.233 mm. Second, the mutual coupling between the individual elements severely impacts the diversity properties of the MIMO antenna system. An effective technique of orthogonally positioning the antenna elements to each other increased their isolation; thus, the MIMO system provides the best diversity performance. The performance of the proposed MIMO antenna was investigated in terms of S-parameters and MIMO diversity parameters to ensure its suitability for future 5G mm-Wave applications. Finally, the proposed work was verified by measurements and exhibited a good match between simulated and measured results. It achieves UWB, high isolation, low mutual coupling, and good MIMO diversity performance, making it a good candidate and seamlessly housed in 5G mm-Wave applications.