Ongoing Pursuit Research Articles

Self-supported bimetallic iron-nickel sulfide nanosheets for efficient alkaline electrocatalytic oxygen evolution

The ongoing pursuit of cost-effective approaches for synthesizing transition metal sulfide heterostructure oxygen evolution electrocatalysts, with the objective of optimizing active site exposure and stabilizing spatial framework, remains a significant challenge. In this study, self-supported bimetallic iron-nickel sulfide (Fe1-xS-NiS/NF) nanosheet heterostructures were successfully fabricated in situ on nickel foam through the direct sulfurization of bimetallic carbonate precursors. The effects of sulfurization temperature and Fe content on the oxygen evolution reaction (OER) performance of the catalyst are investigated, and the best conditions are found to be 350 °C and 2 mmol, respectively. As expected, the optimized catalyst demonstrates remarkable OER performance in an alkaline solution with low overpotentials of 235 mV and 333 mV at high current densities of 50 mA cm−2 and 100 mA cm−2, respectively. Furthermore, the catalyst shows long-term stability lasting for 35 h at 60 mA cm−2 with a negligible shift in the polarization curve observed even after 2000 cyclic voltammetry cycles, while also exhibiting good structural preservation. The current study has the potential to offer valuable insights into the fabrication of electrocatalysts based on metal sulfide heterostructures.

Revisiting Database Indexing for Parallel and Accelerated Computing: A Comprehensive Study and Novel Approaches

While the importance of indexing strategies for optimizing query performance in database systems is widely acknowledged, the impact of rapidly evolving hardware architectures on indexing techniques has been an underexplored area. As modern computing systems increasingly leverage parallel processing capabilities, multi-core CPUs, and specialized hardware accelerators, traditional indexing approaches may not fully capitalize on these advancements. This comprehensive experimental study investigates the effects of hardware-conscious indexing strategies tailored for contemporary and emerging hardware platforms. Through rigorous experimentation on a real-world database environment using the industry-standard TPC-H benchmark, this research evaluates the performance implications of indexing techniques specifically designed to exploit parallelism, vectorization, and hardware-accelerated operations. By examining approaches such as cache-conscious B-Tree variants, SIMD-optimized hash indexes, and GPU-accelerated spatial indexing, the study provides valuable insights into the potential performance gains and trade-offs associated with these hardware-aware indexing methods. The findings reveal that hardware-conscious indexing strategies can significantly outperform their traditional counterparts, particularly in data-intensive workloads and large-scale database deployments. Our experiments show improvements ranging from 32.4% to 48.6% in query execution time, depending on the specific technique and hardware configuration. However, the study also highlights the complexity of implementing and tuning these techniques, as they often require intricate code optimizations and a deep understanding of the underlying hardware architecture. Additionally, this research explores the potential of machine learning-based indexing approaches, including reinforcement learning for index selection and neural network-based index advisors. While these techniques show promise, with performance improvements of up to 48.6% in certain scenarios, their effectiveness varies across different query types and data distributions. By offering a comprehensive analysis and practical recommendations, this research contributes to the ongoing pursuit of database performance optimization in the era of heterogeneous computing. The findings inform database administrators, developers, and system architects on effective indexing practices tailored for modern hardware, while also paving the way for future research into adaptive indexing techniques that can dynamically leverage hardware capabilities based on workload characteristics and resource availability.

Oligandrin from Croton oligandrus (Euphorbiaceae) exhibits anti-breast cancer activity through immune-boosting mechanisms: In vitro and in vivo study

AimRecent developments in cancer research indicate that cancer is a manifestation of immune system dysfunction. Many natural anticancer agents developed recently possess immune-modulatory properties. In our ongoing pursuit of anticancer alternatives, we evaluated the immune-modulatory potential of oligandrin, an ent-pimarane type diterpenoid from Croton oligatrus. Methodswe assessed on Breast cancer patients’ peripheral blood mononuclear cells (PBMCs) were isolated to assess the effect of oligandrin (0.5, 1, 10, 100, 200 mg/mL) in vitro using the Ficoll-histopaque density centrifugation method. The parameters that were assessed included, PBMC viability and cytokine (IL-6, IL-12, IL-10, EGF, TNF-α, INF-γ) production. In vivo, we chemically induced breast cancer using DMBA (50 mg/kg BW) in Wistar rats, then treated them with oligandrin (1 mg/kg BW) or standards (tamoxifen 3.3 mg/kg; letrozole 1 mg/kg) for 20 weeks. The parameters that were evaluated included, tumor burden, volume, incidence, histopathology, antioxidant, and inflammatory status. ResultsOligandrin (1, 10, 100 and 200 μg/mL) significantly increased (p < 0.05) PBMC cell number 24 h after incubation. In vivo, it induced 62.5 % tumor incidence reduction compared to DMBA rats (100 %). Oligandrin significantly protected (p < 0.001) rats against increased tumor burden, mass and volume, which was accompanied by a significant antioxidant effect [increment of GSH (p < 0.01) and SOD (p < 0.001)]. Oligandrin prevented high-grade adenocarcinomas according to SBR stratification and significantly reduced pro-inflammatory cytokine levels (IL-6, IL-12) while increasing anti-inflammatory cytokine levels (INF-γ). ConclusionOligandrin is reported for the first time to protect against breast cancer onset and this effect seems to be at least in part attributable to its immune-boosting capacity.

Isoreticular Covalent Organic Pillars: Engineered Nanotubular Hosts for Tailored Molecular Recognition.

In the realm of nanoscale materials design, achieving precise control over the dimensions of nanotubular architectures poses a substantial challenge. In our ongoing pursuit, we have successfully engineered a novel class of single-molecule nanotubes─isoreticular covalent organic pillars (iCOPs)─by stacking formylated macrocycles through multiple dynamic covalent imine bonds, guided by principles of reticular chemistry. Our strategic selection of rigid diamine linkers has facilitated the synthesis of a diverse array of iCOPs, each retaining a homologous structure yet offering distinct cavity shapes influenced by the linker choice. Notably, three of these iCOP variants feature continuous one-dimensional channels, exhibiting length-dependent host-guest interactions with α,ω-dibromoalkanes, and each presenting a distinct critical guest alkyl chain length threshold for efficient guest encapsulation. This newfound capability not only provides a platform for tailoring nanotubular structures with precision, but also opens new avenues for innovative applications in molecular recognition and the purification of complex mixtures.

A Review on Image Steganography Techniques

In contemporary times, the exploration of digital multimedia has transformed it into a reliable medium for secure communication. Steganography, the art of concealed communication through mediums like images, has emerged as a pivotal approach, countered by the opposing method of steganalysis for detecting embedded data. This review delves into diverse methodologies examined by researchers, elucidating the primary objective of image steganography—to safeguard data messages from illicit access. The essence lies in discreetly transferring embedded secure data to the target destination without detection by unauthorized users. While various carrier file formats can be employed, digital images, owing to their widespread use on the global Internet, become the preferred medium. The realm of steganographic methodologies encompasses a broad spectrum, varying in complexity, each with its distinct strengths and weaknesses. This exploration underscores the dynamic landscape of image steganography, affirming the ongoing pursuit of effective methods to protect information from unauthorized access through covert channels. The review article provides an overview of various methodologies employed by researchers in the field of image steganography. It emphasizes the significance of using digital images as carrier files due to their prevalence on the worldwide Internet. The content acknowledges the complexity of steganographic methods and highlights that each method has its own strengths and weaknesses. Overall, the discussion underscores the importance of exploring and analyzing these methodologies to enhance the effectiveness of image steganography in secure communication.

Catalytic Applications in the Production of Hydrotreated Vegetable Oil (HVO) as a Renewable Fuel: A Review

The significance and challenges of hydrotreatment processes for vegetable oils have recently become apparent, encompassing various reactions like decarbonylation, decarboxylation, and hydrogenation. Heterogeneous noble or transition metal catalysts play a crucial role in these reactions, offering high selectivity in removing oxygen and yielding desired hydrocarbons. Notably, both sulphided and non-sulphided catalysts exhibit effectiveness, with the latter gaining attention due to health and toxicity concerns associated with sulphiding agents. Nickel-based catalysts, such as NiP and NiC, demonstrate specific properties and tendencies in deoxygenation reactions, while palladium supported on activated carbon catalysts shows superior activity in hydrodeoxygenation. Comparisons between the performances of different catalysts in various hydrotreatment processes underscore the need for tailored approaches. Transition metal phosphides (TMP) emerge as promising catalysts due to their cost-effectiveness and environmental friendliness. Ultimately, there is an ongoing pursuit of efficient catalysts and the importance of further advancements in catalysis for the future of vegetable oil hydrotreatment.

Probing perfection: The relentless art of meddling for pulmonary airway segmentation from HRCT via a human-AI collaboration based active learning method

In the realm of pulmonary tracheal segmentation, the scarcity of annotated data stands as a prevalent pain point in most medical segmentation endeavors. Concurrently, most Deep Learning (DL) methodologies employed in this domain invariably grapple with other dual challenges: the inherent opacity of ‘black box’ models and the ongoing pursuit of performance enhancement. In response to these intertwined challenges, the core concept of our Human-Computer Interaction (HCI) based learning models (RS_UNet, LC_UNet, UUNet and WD_UNet) hinge on the versatile combination of diverse query strategies and an array of deep learning models. We train four HCI models based on the initial training dataset and sequentially repeat the following steps 1–4: (1) Query Strategy: Our proposed HCI models selects those samples which contribute the most additional representative information when labeled in each iteration of the query strategy (showing the names and sequence numbers of the samples to be annotated). Additionally, in this phase, the model selects the unlabeled samples with the greatest predictive disparity by calculating the Wasserstein Distance, Least Confidence, Entropy Sampling, and Random Sampling. (2) Central line correction: The selected samples in previous stage are then used for domain expert correction of the system-generated tracheal central lines in each training round. (3) Update training dataset: When domain experts are involved in each epoch of the DL model's training iterations, they update the training dataset with greater precision after each epoch, thereby enhancing the trustworthiness of the ‘black box’ DL model and improving the performance of models. (4) Model training: Proposed HCI model is trained using the updated training dataset and an enhanced version of existing UNet.Experimental results validate the effectiveness of this Human-Computer Interaction-based approaches, demonstrating that our proposed WD-UNet, LC-UNet, UUNet, RS-UNet achieve comparable or even superior performance than the state-of-the-art DL models, such as WD-UNet with only 15 %–35 % of the training data, leading to substantial reductions (65 %–85 % reduction of annotation effort) in physician annotation time.

Sustainable Synthesis of Guanidine Derivatives and Computational Assessment of their Antidiabetic Efficacy.

Type 2 Diabetes Mellitus (T2DM) represents a significant and pressing worldwide health concern, necessitating the quest for enhanced antidiabetic pharmaceuticals. Guanidine derivatives, notably metformin and buformin, have emerged as pivotal therapeutic agents for T2DM management. The present study introduces an efficient one-pot synthesis method for the production of symmetrical guanidine compounds. This synthesis involves the reaction of isothiocyanates with secondary amines, employing an environmentally friendly and recyclable reagent, tetrabutylphosphonium tribromide (TBPTB). A comprehensive assessment of the biological activity of the synthesized guanidine compounds, specifically in the context of T2DM, has been rigorously conducted. Additionally, computational analyses have unveiled their substantial potential as promising antidiabetic agents. Results highlight the relevance of these compounds in the ongoing pursuit of novel therapeutic solutions for T2DM.</p>.

Theoretical framework and inference for fitting extreme data through the modified Weibull distribution in a first-failure censored progressive approach

The importance of biomedical physical data is underscored by its crucial role in advancing our comprehension of human health, unraveling the mechanisms underlying diseases, and facilitating the development of innovative medical treatments and interventions. This data serves as a fundamental resource, empowering researchers, healthcare professionals, and scientists to make informed decisions, pioneer research, and ultimately enhance global healthcare quality and individual well-being. It forms a cornerstone in the ongoing pursuit of medical progress and improved healthcare outcomes. This article aims to tackle challenges in estimating unknown parameters and reliability measures related to the modified Weibull distribution when applied to censored progressive biomedical data from the initial failure occurrence. In this context, the article proposes both classical and Bayesian techniques to derive estimates for unknown parameters, survival, and failure rate functions. Bayesian estimates are computed considering both asymmetric and symmetric loss functions. The Markov chain Monte Carlo method is employed to obtain these Bayesian estimates and their corresponding highest posterior density credible intervals. Due to the inherent complexity of these estimators, which cannot be theoretically compared, a simulation study is conducted to evaluate the performance of various estimation procedures. Additionally, a range of optimization criteria is utilized to identify the most effective progressive control strategies. Lastly, the article presents a medical application to illustrate the effectiveness of the proposed estimators. Numerical findings indicate that Bayesian estimates outperform other estimation methods by achieving minimal root mean square errors and narrower interval lengths.

Competing Claims of Caliphal Legitimacy: Al-Tamaghrouti’s Rihla and the Moroccan-Ottoman Early Modern Diplomatic Landscape

This article explores al-Tamaghrouti’s Rihla, Al-Nafhah al-Miskia fi al-Sifarah al-Turkiyah [The Fragrant Breeze in the Turkish Embassy], to illuminate his engagement with the spiritual and temporal legitimacy of caliphal claims in the early modern Islamicate Mediterranean. It argues that Moroccan embassies to the Sublime Porte were arenas where claims to temporal and spiritual superiority played themselves out in the form of competing caliphal symbolism. When situated within Sultan Ahmad al-Mansur’s caliphal vision, Al-Tamaghrouti’s account reveals a discursive landscape marked by contrasting claims to the superiority of the Moroccan normative order. His Rihla vividly captures the double-bind challenges faced by al-Mansur’s Morocco in the sixteenth century: Iberian imperialism and Ottoman expansionism. I resituate the insight that dynamic interactions among various Muslim-Christian universalistic principles maintained a paradoxical longevity of peaceful relations (Windler 2018) within the rubric of Muslim-Muslim relations to explore how different universalistic ideologies interact within inter-imperial/religious Muslim relations, particularly in the context of diplomatic engagements and political interactions. Al-Tamaghrouti drew on various spiritual and temporal motifs to construe a space of hermeneutic ambiguity whereby Sultan al-Mansur’s claims to universal caliphal leadership not only fulfills Mahdist qualities but transcends them, construing a discursive field in which al-Mansur emerges as a leader who transcends prophetic norms. By analyzing the interplay of power, religion, and diplomacy in al-Tamaghrouti’s travelogue, we gain a deeper understanding of the intricacies of statecraft and the ongoing pursuit of legitimacy in the Islamic world.

Effect of Adding Oil Palm (Elaeis guineensis Jacq.) Mesocarp Fibers to Cement Composites

The construction industry's ongoing pursuit of eco-friendly materials has led to extensive research into fiber cement composites (FCC), particularly those utilizing natural fibers such as oil palm (Elaeis guineensis Jacq.) mesocarp fiber (OPMF) from Peru. This study examined the physical, mechanical, and chemical effects of adding different proportions of OPMF (0, 3, 6, and 9%) in manufacturing FCCs. This addition resulted in reduced values regarding density, porosity, and modulus of rupture, as well as in increased moisture content and thickness reduction. The FCC containing 3% OPMF exhibited the most favorable performance thanks to its higher density and its lower water absorption and porosity when compared to the control board (0%-OPMF). Micro-images revealed minor microcracks and interfacial gaps, indicative of debonding, which compromises the properties of the FCC. Furthermore, an infrared spectrum analysis demonstrated an increase in hydroxyl group vibrations with an increased fiber proportion.

«Право на город»: Кронштадт глазами горожан

The article examines the social space of modern Kronstadt, a small historical town within the boundaries of St. Petersburg, whose residents still claim to preserve a special collective identity. The work is based on materials collected during interviews with locals in the spring of 2021. Kronstadt’s social space is characterized and described as an assemblage in which heterogeneous forces interact, thereby determining the prospects for the town’s development — both in terms of urban economy and the perception of the townspeople. There are four main elements of the current urban identity— or four components of the “Kronstadt palimpsest”: first, the townspeople’s perception of the town’s status and resource position within the hierarchy of St. Petersburg’s urban environment. Second, the determination of the administrative and “natural” boundaries of the town on the territory of Kotlin Island. Third, the ranking of neighborhoods based on the degree of prestige, along with the folklorization of “disadvantaged” zones. And fourth, the attitude toward the influx of tourists and the perception of “strangers” by local residents, as well as the division of city attractions into “ceremonial” and “personal” ones. It is concluded that the townspeople’s ongoing pursuit of the “right to the city”, based on the history, geographical location of the settlement, and their own ideas about the preferred urban way of life, largely determines the uniqueness of the Kronstadt assemblage. This sets this small town apart from the array of satellite towns around Russian megacities.

A liquid biopsy-based assay for classifying breast cancer from benign nodule.

e12572 Background: Breast cancer (BRCA) ranks as the most frequently diagnosed non-skin cancer and stands as the second leading cause of cancer-related mortality in women in the United States. Globally, 2.3 million women were diagnosed with breast cancer in 2020, resulting in 685,000 deaths. Therefore, accurate classification of breast cancer could contribute to immediate treatment and improve outcomes for individuals diagnosed with breast cancer. Our study introduces an ensemble model utilizing the distinctive characteristics of cell-free DNA (cfDNA) fragmentation from whole genome sequencing (WGS) for the classification of BRCA and benign nodule. Methods: The study cohort consisted of 214 individuals diagnosed with breast cancer (BRCA) and 211 individuals with benign breast nodule. Employing whole-genome sequencing (WGS), we subjected plasma samples from all participants to comprehensive fragmentomic profiling. Three fragmentomic features: copy number variation (CNV), fragmentation size coverage (FSC), and fragmentation size distribution (FSD), were utilized by machine learning algorithms. An ensemble model integrated results from each algorithm then generated a cancer score ranging from 0 to 1 for each sample. The model was trained exclusively using the training cohort and the model’s performance was assessed in the independent validation cohort. Results: Our ensemble model demonstrated a sensitivity of 80.2% and a specificity of 95.3% in training cohort, with an AUC of 0.966. In the validation cohort, the model maintained its effectiveness, with a sensitivity of 73.6%, a specificity of 89.3% supported by an AUC of 0.919. Notably, the model showed various predictive ability across different stages of breast cancer. In the training cohort, it exhibited a sensitivity of 76.4% for Stage I, 81.8% for Stage II, and 88.9% for Stage III, indicating superior predictive power at advanced progression levels. Additionally, the model demonstrated a consistent sensitivity of 75% for Stage I in the validation cohort, affirming its reliable performance across independent datasets. When stratified by molecular subtypes, the model showed relatively lower scores and sensitivity BRCA with HR+/HER2+, compared to HR-/HER2+ and HR+/HER2- subgroups, as well as Triple-Negative Breast Cancer. Finally, the model generated unbiased predictions across various histology subtypes, accurately discerning ductal carcinoma and other BRCA histology subtypes in training and validation cohorts. Conclusions: The ensemble model that leverages non-invasive liquid biopsy-based assay for the accurate classification of BRCA and benign nodule provides a critical opportunity for effective intervention for cancer patients. This approach, facilitating swift and appropriate treatments, and optimizing the allocation of healthcare resources, underscores its significance in the ongoing pursuit of enhancing breast cancer care and outcomes.

Nano‐enhanced epoxy sandwich composites: Investigating mechanical properties for future aircraft construction

AbstractThe aviation sector is continually seeking ways to reduce the weight of aircraft structures without compromising their mechanical integrity. Lightweight materials, such as advanced epoxy sandwich composites with hybrid nanostructures, have the potential to significantly contribute to fuel efficiency, thereby addressing environmental concerns and operational costs. This research investigates the mechanical properties of hybrid sandwich polymer composites filled with silica nanoparticles (SNiPs). Epoxy isocyanate (PU) foam sandwich composites were fabricated with kevlar fiber, carbon fiber, and glass fiber, constructed by alternating inclined interply bidirectional fiber and foam layers. SNiPs were introduced into the composite system at varying percentages, such as 0, 2, 4, and 6 wt%. The study employs a systematic approach, incorporating experimental testing, to assess key mechanical parameters, including tensile strength, flexural strength, and shear strength. The test results indicate that the incorporation of SNiPs improved the mechanical properties of the composites, leading to enhanced strength, toughness, and modulus of elasticity. Incorporation of composite laminates with 4 wt% SiNPs resulted in improved three‐point bending, tensile, shear, and torsional strengths, with maximum values of ca. 64, ca. 5, ca. 2 MPa, and ca. 22 Nm, respectively. The findings contribute to the ongoing pursuit of materials that can meet the stringent demands of modern aviation, ultimately paving the way for advancements in aircraft construction and design.

Insights into the novel Enterococcus faecalis phage: A comprehensive genome analysis.

Enterococcus faecalis, a Gram-positive bacterium, poses a significant clinical challenge owing to its intrinsic resistance to a broad spectrum of antibiotics, warranting urgent exploration of innovative therapeutic strategies. This study investigated the viability of phage therapy as an alternative intervention for antibiotic-resistant E. faecalis, with a specific emphasis on the comprehensive genomic analysis of bacteriophage SAM-E.f 12. The investigation involved whole-genome sequencing of SAM-E.f 12 using Illumina technology, resulting in a robust dataset for detailed genomic characterization. Bioinformatics analyses were employed to predict genes and assign functional annotations. The bacteriophage SAM-E.f 12, which belongs to the Siphoviridae family, exhibited substantial potential, with a burst size of 5.7 PFU/infected cells and a latent period of 20 min. Host range determination experiments demonstrated its effectiveness against clinical E. faecalis strains, positioning SAM-E.f 12 as a precise therapeutic agent. Stability assays underscore resilience across diverse environmental conditions. This study provides a comprehensive understanding of SAM-E.f 12 genomic composition, lytic lifecycle parameters, and practical applications, particularly its efficacy in murine wound models. These results emphasize the promising role of phage therapy, specifically its targeted approach against antibiotic-resistant E. faecalis strains. The nuanced insights derived from this research will contribute to the ongoing pursuit of efficacious phage therapies and offer valuable implications for addressing the clinical challenges associated with E. faecalis infections.

A comprehensive exploration of PPS/MgO@MoS2 core–shell composites for enhanced thermal and mechanical performance

The growing worldwide energy crisis and environmental issues have prompted the exploration of sustainable alternatives across different sectors, such as the automotive realm. Electric vehicles (EVs) have surfaced as a practical substitute for traditional fossil fuel-driven vehicles, with their efficacy being contingent upon the weight of the vehicle. In this investigation, we present polyphenylene sulfide (PPS) as an advanced engineering plastic, boasting exceptional resistance to high temperatures and chemical stability. Its versatility makes it suitable for a range of applications within the automotive industry. However, the thermal conductivity of PPS is lower than those of other engineering plastics. Therefore, a novel core–shell structure comprising magnesium oxide (MgO) and molybdenum sulfide (MoS2) was fabricated to enhance the thermal and mechanical properties. The core–shell structure was elucidated via a comprehensive analysis using various techniques. Furthermore, the PPS/MgO@MoS2/PA composites were synthesized to address the challenges associated with high filler ratios. Tensile strength evaluations and thermal conductivity assessments confirmed the effectiveness of the proposed materials for diverse engineering applications, particularly in EVs. Additionally, surface treatments with polyformaldehyde and (3-aminopropyl)triethoxysilane (PA) improved the adhesion with the PPS matrix, which enhanced the mechanical tensile strength to 90 MPa. As the filler ratio increased, the MgO@MoS2 core–shell achieved a high through-plane heat conductivity of 4.07 W/m·K, which is 22 times compared to pristine PPS. Hence, this study provides valuable insights into the ongoing pursuit of sustainable automotive solutions by addressing the critical issues of energy efficiency, environmental impact, and materials science.

Submarine Maneuvering Performance Analysis: a Study of the Effect of Different Rudder Angle Settings on the Turning Dynamics of SUBOFF Submarine

In the ongoing pursuit of bolstering maritime military capabilities, the optimization and augmentation of submarine performance stand as pivotal objectives within the realm of strategic naval power. Given the exacting operational standards required for submarines to execute vital missions like reconnaissance, stealthy attacks, and tracking, this study leverages Computational Fluid Dynamics (CFD) simulation technology to meticulously analyze and evaluate submarine maneuverability under various rudder angle configurations. Through a thorough examination of a spectrum of simulation results, this study unveils the critical determinants influencing submarine maneuverability and proposes corresponding optimization strategies. The outcomes not only furnish a robust scientific foundation for enhancing submarine maneuvering capabilities but also offer valuable technical insights for advancing overall submarine operational efficacy. The discoveries of this study bear significant practical significance and applicability, guiding submarine design endeavors and fortifying tactical responsiveness in intricate maritime settings.

Lithium‐Mediated Nitrogen Reduction for Ammonia Synthesis: Reviewing the Gap between Continuous Electrolytic Cells and Stepwise Processes through Galvanic Li─N2 Cells

AbstractElectrochemical N2 reduction reaction (E‐NRR) has recently gained increasing interest within the scientific community, due to the ongoing energy crisis and pursuit of process sustainability. In this scenario, emerging lithium‐mediated (Li‐m) strategies are obtaining promising Faradaic efficiency (FE) and NH3 production rate values. In this work, the Li‐m scenarios are classified and explained toward a more sustainable process. Continuous processes, with a lithium salt and a proton donor in an electrolytic cell, are analyzed and compared with stepwise pathways. Different parameters are summarized in relation to the system stability, for which the importance of a tailored solid electrolyte interphase (SEI) layer emerged. Among stepwise processes, the thermochemical direct nitridation of lithium is discussed together with the recently developed Galvanic Li─N2 cell strategy.

Current advances in cancer treatment: A comprehensive review of therapeutic strategies and emerging innovations

Cancer stands as a pressing global health crisis, claiming one in every six lives across the world. The treatment of cancer has evolved into a remarkably intricate endeavour. In recent years, there have been significant advancements in the field of cancer treatment, alongside the longstanding methods of surgery, chemotherapy, and radiotherapy. In the realm of oncology, there has been a surge of innovative treatments, encompassing stem cell therapy, targeted therapy, ablation therapy, nanoparticles, natural antioxidants, radionics, chemo dynamic therapy, sonodynamic therapy, and ferroptosis-based therapy. Contemporary oncology is predominantly dedicated to the progression of cancer nanomedicines, with notable promise found in stem cell therapy, offering the potential to rejuvenate and mend afflicted tissues at both primary and metastatic cancer sites. Nanoparticles have ushered in new avenues for both diagnosis and treatment. Targeted therapy presents a groundbreaking strategy that hinders the proliferation and dissemination of particular cancer cells, while minimizing harm to healthy ones. Ablation therapy, characterized by its minimally invasive nature, enables the elimination of cancer using methods like controlled burning or freezing, eliminating the necessity for open surgery. In the ongoing pursuit of improved cancer therapies, numerous innovative technologies are currently undergoing clinical trials, and some have already gained approval. This review provides a comprehensive update on the recent advancements and breakthroughs in the realm of cancer treatment.

NUMERICAL HEAT TRANSFER ENHANCEMENT OF SOLAR RECEIVER TUBE OF PARABOLIC TROUGH COLLECTOR USING FIBERFRAX 140 COATED WITH AL 2O 3

Parabolic trough collectors (PTCs) play a vital role in solar-thermal energy conversion, with the absorber tube being central to heat collection efficiency. This study investigates the potential for improving heat transfer within the PTC absorber tube using Fiberfrax 140 coated with Al 2O 3 as a novel reflector material. The research is driven by the ongoing pursuit of enhanced PTC performance. A standard modeling approach was employed, utilizing Computational Fluid Dynamics (CFD) analysis with SolidWorks Flow Simulation software, coupled with solar simulations to assess collector performance under varying conditions. Environmental parameters of Bauchi such as temperature, humidity, and wind speed were sourced from the Nigerian Meteorological Agency (NiMet). Optimization techniques were implemented to establish the optimal design configuration. The optimal design parameters were determined as a focal length of 700mm and a rim angle of 90°. Simulations were conducted daily from 8:00 AM to 5:00 PM, encompassing the period of January to June. A mass flow rate of 0.2 kg/s, informed by existing literature, was employed in the simulations. The results indicate improved collector performance throughout the simulated period, with peak thermal efficiency ranging from70%to82%.