This study aims to determine the relationship between arm muscle strength and underhand serving skills in volleyball among students at SMK Negeri 3 Kota Kupang. This study uses a quantitative approach with a correlational method. The study population consisted of 22 students who participated in volleyball extracurricular activities, and the entire population was sampled using total sampling technique. Data collection techniques were carried out through tests and measurements, namely push-up tests to measure arm muscle strength and standard volleyball underhand serve tests to measure students' underhand serve skills. The data obtained were analysed using Pearson Product Moment correlation analysis techniques after meeting the analysis prerequisites. The results showed a correlation coefficient of r = -0.222 with a significance value of p = 0.321 (p > 0.05). These findings indicate that there is no significant relationship between arm muscle strength and underhand serving skills in students at SMK Negeri 3 Kota Kupang. Thus, it can be concluded that underhand serving skills in volleyball are not only influenced by arm muscle strength but are more determined by other factors such as technical mastery, movement coordination, and timing in serving.

3D phenotyping refers to the quantitative characterization of a plant’s structural and morphological traits in three-dimensional space, allowing for a detailed analysis of plant architecture and growth patterns. In recent years, rapid advancements in non-destructive, high-throughput 3D imaging technologies have enabled the precise measurement of these traits. Initially focused on single-plant traits under controlled conditions, the field has now expanded towards robust applications in real-world field environments, enabling large-scale analyses of plant canopies and complex structures. This study focuses on the recent advancements in 3D crop phenotyping using point cloud technologies. It compares sensor technology and its application in controlled environments (Chamber-Crop Phenotyping, CCP) and field conditions (Field-Crop Phenotyping, FCP). Technologies such as Multiview stereo (MVS) reconstruction, LiDAR, and laser triangulation have enhanced plant phenomics by enabling high-throughput, non-destructive measurements of key traits such as canopy structure, leaf area, and stem diameter. This review highlights the strengths of the CCP, where environmental variables and flexibility are tightly controlled, facilitating precise trait measurement, and contrasts it with the challenges of the FCP, where unpredictable factors, such as occlusion, wind, light variability, and terrain complexity, complicate data acquisition. Various sensor platforms, including ground-based robotic systems and unmanned aerial vehicles (UAVs), have been discussed regarding their ability to overcome occlusion and limited sensor range in real-world conditions. The need to transition these technologies from laboratory environments to real-world agricultural applications is emphasized, highlighting their potential to improve crop management and plant breeding through accurate phenotypic trait extraction. Finally, current research gaps and future directions for integrating advanced sensor platforms and analytical techniques in both CCP and FCP settings are identified, emphasizing the need to enhance the scalability and robustness of 3D phenotyping for field applications.

Candesartan cilexetil is an angiotensin II receptor blocker commonly prescribed for the management of hypertension. Accurate and reliable analytical methods are essential to ensure its quality, safety, and efficacy in pharmaceutical formulations. Various analytical techniques, including spectrophotometric and chromatographic methods, have been reported for the estimation of candesartan cilexetil. This article provides a concise overview of hypertension, antihypertensive therapy, candesartan cilexetil, general analytical methods, and a summarized literature review of reported analytical techniques. The review highlights the diversity of existing methods and emphasizes the importance of systematic and reliable analytical approaches for routine quality control.

ABSTRACT The rising incidence of amphetamine misuse, particularly in the context of attention deficit hyperactivity disorder treatment, underscores the urgent need for sensitive and effective detection methods. This review examines innovative nanomaterial‐based approaches for AMP detection, emphasizing their advantages over conventional analytical techniques. Various nanomaterials, including carbon nanotubes, graphene and metal nanoparticles, have been utilized to enhance the sensitivity and selectivity of detection methods such as electrochemical sensors, surface‐enhanced Raman spectroscopy and fluorescence‐based assays. The distinctive properties of nanomaterials, including high surface area, conductivity and biocompatibility, enable the development of rapid and reliable detection systems. This paper discusses recent advancements in nanomaterial synthesis, functionalization and integration into detection platforms, along with the challenges and future directions in this field. By harnessing the potential of nanotechnology, these innovative approaches aim to improve the accuracy and efficiency of amphetamine detection, thereby enhancing the monitoring and management of substance abuse, particularly in individuals with attention deficit hyperactivity disorder.

Electropolishing is an essential process for the surface treatment of metallic materials. To determine the appropriate replacement timing of electropolishing solutions for their efficient use and improved productivity, it is important to periodically analyze the amounts of dissolved metals in the solutions. However, these solutions are typically highly corrosive, and on-site analytical techniques that can be easily applied at production sites have not yet been established. In this study, we demonstrated microvolume liquid analysis using low-energy laser-induced breakdown spectroscopy (LIBS) combined with a porous silicon substrate fabricated by metal-assisted etching (metal-assisted chemical etching) and a non-contact gas-blowing pretreatment. In the analysis of electropolishing solutions used for niobium superconducting cavities and stainless steel products, emission lines of niobium and of iron and chromium were successfully detected after blowing the respective microdroplet samples on porous silicon, and linear correlations were observed between the spectral line intensity and the polished amounts. The present results provide a basis for future on-site application of LIBS to highly corrosive electropolishing solutions in the metal finishing industry.

This study aims to explore Fadwa Tuqan's religious expression by examining the relationship between the Qur'an and the poem “Awhamun Fiy Zaitun” through Julia Kristeva's intertextual approach. The focus of this study is on how the poet expresses her religiosity in her poetry. The method used is a descriptive, qualitative method with content analysis techniques designed for library research. The data are analyzed to identify patterns of intertextuality, expressed as intertextual principles, that connect the two texts: poetry and the Qur’an. The results of this study found that Fadwa Tuqan absorbed elements of the Qur'an into the poem “Awhamun Fiy Zaitun” through the principles of dominant transformation, modification, expansion, defamiliarization, existence and excerpts so that the symbol زيتون became the basis for the title of this poem. This reflects the expression of religiosity as a Muslim in Palestine who makes the Qur'an the source of her religiosity. Overall, this study provides insight into the creative relationship between sacred texts and Tuqan's poetry. The implications enrich modern Arabic literature as a metaphysical dialogue with God and provide a theoretical and practical contribution to the study of Palestinian poetry.

The study investigated the impact of credit risk management on the profitability of commercial banks in Ethiopia. The research adopted explanatory research design and a quantitative approach were employed. It used descriptive and inferential statistical analyses techniques. The population of this study includes 31 commercial banks that are working in Ethiopia, from which a purposive sample of ten leading banks were selected on the basis of their branch network and operational age. The study is panel from the period between 2013 and 2023. The Random effects Generalized Least Squares model was utilized as panel data regression analysis to test the impact of credit risk management factors on bank performance. The regression result shows that Non-Performing Loans were found to have a significant negative impact on bank profitability, which implies that a high level of non-performing loans decreases bank profitability, emphasizing the importance of effective credit risk management. Conversely, and contrary to conventional assumptions, both a higher Loan to Total Asset Ratio and Loan to Deposit Ratio were unexpectedly associated with decreased profitability, suggesting an optimal threshold for lending activity exists beyond which excessive loan expansion introduces detrimental liquidity and credit risks. In alignment with established financial principles, Capital Adequacy significantly enhanced bank performance, underscoring its crucial role in providing essential buffers against losses, maintaining stability, and fostering stakeholder confidence for sustainable returns. Bank size as measured by total assets is positively related to better performance but insignificance effect on it.

The residual cholesterol inflammation index (RCII) integrates residual cholesterol and C-reactive protein to assess for metabolic and inflammatory risk. We explored the link between the RCII and long-term risk of heart failure (HF) development in the United States. Data from the National Health and Nutrition Examination Survey were inspected, and 6027 participants aged 45 years and older were included. Natural log-transformed residual cholesterol inflammation index (ln RCII) values were used to classify participants into quartiles. The association between RCII and HF risk was examined, and potential covariates were controlled for using subgroup analyses, restricted cubic spline curves, subject work characteristic curve analysis techniques, and logistic regression models. The Q4 group (ln RCII > 14.82) was older, had an elevated body mass index, and a notably increased occurrence of diabetes, hypertension, and HF than the low ln RCII group (P < .05). Corrected logistic regression showed a higher HF in the Q4 group compared to the Q1 group (P < .05). HF risk increased by 36% (P < .001), 34% (P < .001), and 22% (P = .009) for every unit increase in ln RCII, indicating an independent positive correlation between RCII and HF risk. Restricted cubic spline regression confirmed a linear relationship (nonlinear P > .05). The receiver operating characteristic curve area under the curve was 0.59 (P < .05). Subgroup analyses revealed significant moderating associations for smoking status (interaction P = .034), stronger predictive validity of ln RCII among nonsmokers (P = .0014), no significant associations among smokers (P = .2375), and consistent positive associations for other subgroups. Elevated RCII levels are predictive of HF risk and are linked to an increased risk of HF in middle-aged and older populations.

Purpose Driven by the exponential growth in the online engagement of consumers, it has become essential for brands to promote their products and services through online influencer marketing (OIM) campaigns. OIM stems from the integrated marketing communications (IMC) theory, and in addition to the benefits, OIM campaigns pose certain challenges for brands. Therefore, this study identifies and prioritizes the OIM challenges from the lens of the IMC theory. Design/methodology/approach The author examined the literature and identified 12 challenges in the context of the IMC theory. Following the collection of feedback from 22 industry professionals, the highlighted challenges were ranked using a unique causal impact analysis technique called the grey influence analysis (GINA). Findings The study revealed that negative brand association risk, influencer authenticity and credibility assessment, cost and return-on-investment management, and campaign performance management are the most influential individual OIM challenges. Whereas a collective categorical analysis revealed that the challenges pertaining to audience-centered and channel-centered IMC pillars are the most significant. Research limitations/implications The study focused on OIM campaigns in general, rather than any specific industry. Consequently, the findings may not be replicable in specialized industries. Practical implications The study’s findings could help marketing managers boost OIM campaign execution in line with the IMC by focusing on brand alignment, credibility evaluation, and performance accountability of online influencers. The study encourages ethical and transparent influencer practices through a responsible online communication system. Originality/value As one of the first applications of GINA in OIM, this study broadens its scope to the wider domains of digital marketing and branding.

Raman spectroscopy has shown great promise in classifying biomedical samples. While conventional spectral analysis techniques have been employed to extract meaningful patterns from Raman data, emerging developments in machine learning (ML) offer new opportunities to advance the field. We employed Raman spectroscopy (RS) to analyze hippocampal tissue sections from rats subjected to chronic constriction injury (CCI) exposed to Cannabidiol (CBD) vapor versus Sham controls. Through examination of spectral features in the Raman data, we detected distinct molecular bond signatures indicative of changes in key biomolecules, including proteins, lipids, and nucleic acids. These signatures offer insights into CBD vapor-induced biochemical alterations in the hippocampus and have potential relevance to neuropathic pain mechanisms linked to CCI. Our Raman-based approach enabled us to capture information about biochemical modifications in the hippocampal region exposed to CBD vapes. We applied supervised machine learning (ML) models (Random Forest, SVM) to classify Raman spectra obtained from the brain tissues. The machine learning algorithms effectively captured patterns in the spectral data, enabling us to accurately differentiate between treated and control groups. Our models achieved high classification performance, showing that CBD vapor exposure induces distinct biochemical alterations in brain tissue detectable via Raman spectroscopy. Our results support the use of ML as a powerful tool for spectral analysis in complex biological systems.

The increasing threat of microbial infections on surfaces has created a critical demand for effective antimicrobial textiles. This research addresses this need by fabricating a nanocomposite textile with antimicrobial functionality, incorporating cobalt oxide nanoparticles (Co₃O₄ NPs) synthesized through an eco-friendly and cost-efficient method utilizing okra fruit (OF) extract. In the initial phase, the produced cobalt oxide nanoparticles underwent characterization using appropriate analytical techniques such as scanning electron microscopy-energy dispersive x-ray spectroscopy (SEM-EDX), Fourier transform infrared spectroscopy (FTIR), x-ray diffraction (XRD), transmission electron microscopy (TEM), Zeta potential and dynamic light scattering (DLS) technique. The results showed that a homogeneous shape with a rod-like structure in the diameter range from 4 to 11 nm. spectroscopy revealed a distinct absorption band at 551 cm⁻¹, which corresponds to the stretching vibrations of the cobalt–oxygen (Co–O) bond. OF-Co₃O₄ nanoparticles (NPs), at 200 μL, exhibited notable antibacterial activity, forming inhibition zones measuring 27 mm against S. aureus and 24 mm against E. coli. Following antimicrobial assessment, cotton fabrics were impregnated with an OF-Co₃O₄ NP solution at a concentration of 1000 µg/mL. At this dosage, the treated fabrics demonstrated strong antibacterial properties, reducing bacterial growth by 81.8% for S. aureus and 76.5% for E. coli. KEY WORDS: Cobalt oxide nanoparticles, Phyto-synthesis, Antibacterial, Medical textiles Bull. Chem. Soc. Ethiop. 2026, 40(3), 641-654. DOI: https://dx.doi.org/10.4314/bcse.v40i3.11

Occurrence and spatial distribution of emerging organic contaminants in the coastal and deep Red Sea sediments utilizing liquid chromatography tandem high resolution mass spectrometry.

In the last 60 years, the broad spectrum of activity of nitroimidazole derivatives against anaerobic bacteria, parasites, and protozoa has permitted their use as the first choice of treatment for many infectious diseases. New compounds are needed to overcome the acquired resistance of bacteria and parasites. This work aimed to investigate 4- and 5-nitroimidazole derivatives in terms of the contribution of the position of the nitro group, along with that of different substituents, on their chemical, structural, and biological properties. Copper (II) coordination compounds with these derivatives were synthesized and characterized by analytical and spectroscopical techniques. Their structural properties and their intra- and intermolecular interactions were analyzed from single crystal X-ray diffraction studies. Theoretical calculations allowed for explaining the lability in solution of the copper (II) coordination compounds with the 4-nitroimidazole derivatives. The potential antimicrobial activity against anaerobic periodontal and opportunistic aerobic bacteria, including E. coli , S. aureus , S. mutans , and P. gingivalis , was evaluated. It is noteworthy that the position of the nitro group in the heterocycle drives their coordination behavior toward the metal ions, the geometry of the copper (II) atom in the complexes, and their stability in solution, thus affecting their biological activity.

Purpose This research investigates the interplay between technology adaptation and macropolicies (MP) on the sustainability of supply chains in the steel industry in Iran. The sector holds significant importance for economic growth and environmental sustainability, making it a crucial area of investigation. The aim of the study is to provide supply chain executives and policymakers helpful knowledge to improve sustainability initiatives. Design/Methodology/Approach A quantitative research approach was utilized, employing a structured survey distributed to 160 industry experts. Regression analysis, path modeling and bootstrapping techniques were utilized to examine the mediating role of industry-specific challenges (ISC) in sustainable supply chain management (SSCM). Findings The results suggest that technological adaptation and MP significantly impact SSCM. However, the relationship is mediated by ISC, demonstrating that achieving sustainability objectives involves tackling supply-demand fluctuations, ecological impact and data inefficiencies. Practical implications This study offers actionable recommendations for policymakers and steel industry leaders to enhance sustainability through targeted regulations, improved data management strategies and the adaptation of emerging technologies. Originality/Value This study contributes to the literature by providing a sector-specific analysis of sustainability in industrial supply chains, particularly in a developing economy context. Particularly, it offers novel perspectives on how emerging economies might improve supply chain sustainability by highlighting the interplay of political, technological and industry-specific issues.

In this work, a new Co(II) complex, abbreviated as [Co(L)(bipy)(H2O)2]n (1) was prepared using cobalt(II) acetate tetrahydrate, 2-((2'-carboxybenzyl)oxy)benzoic acid (H2L), and 2,2'-bipyridine (bipy) ligands in a mixture solution of ethanol and water (v: v = 3: 1). The structure of the complex (1) was analyzed by elemental analysis (EA), infrared (IR) spectroscopy, ultraviolet-visible (UV-Vis) spectroscopy, thermogravimetric analysis (TG), and single-crystal X-ray diffraction techniques. The complex (1) crystallizes in the monoclinic space group C2/c, featuring a distorted octahedral [CoO₄N₂] coordination sphere, by two oxygen atoms from the carboxylate groups of two 2-((2'-carboxybenzyl)oxy)benzoate (L) ligands, two oxygen atoms from coordinated water molecules, and two nitrogen atoms (N1 and N2) from a single 2,2'-bipyridine (bipy) ligand. Bridging carboxylate ligands (L) form a 1D chain, which extends into a 2D layer via π-π interactions of the 2,2'-bipyridine ligands (bipy). The DFT calculations of the complex (1) indicates that the HOMO is predominantly distributed on the oxygen and nitrogen atoms bonded to Co(II) ion, but the LUMO is mainly localized around distributed in the six-membered carbon ring adjacent to the Co(II) ion. Electrostatic potential calculation of the complex (1) shows that the regions with higher electrostatic potential are mainly located on the aromatic ring, whilst the lower electrostatic potential regions are primarily located near the oxygen and nitrogen atoms. The electrochemical behavior of the complex (1) was investigated in acetonitrile and 1mol·L⁻¹ sulfuric acid. In ACN/TBATFB, the complex (1) exhibits a well-defined, predominantly reversible Co(III)/Co(II) redox couple, indicating good electrochemical stability, whereas in 1mol·L⁻¹ H₂SO₄, a significantly different redox response with enhanced anodic currents and a prominent oxidation peak is observed, arising from the synergistic effect of ligand protonation-oxidation processes and the metal-centered Co(III)/Co(II) redox couple under acidic conditions. The cytotoxicity of the complex (1) and CoCl₂ was evaluated against L02, PANC-1, and MCF7 cell lines using the MTT assay. The complex (1) exhibited lower IC₅₀ values and higher selectivity for cancer cells than CoCl₂, attributable to improved cellular uptake and ROS-mediated oxidative stress, whereas free Co²⁺, which stimulated cell proliferation at low concentrations, the complex (1) showed no growth-inducing effect, highlighting its potential as a cobalt-based anticancer agent.

This study reports the synthesis and biological evaluation of four novel N-acetyl-derived heterocyclic compounds, namely 2-((1-acetyl-3-substituted-5-oxo-1,5-dihydro-4H-1,2,4-triazol-4-yl)iminomethyl)-phenyl-naphthalene-2-sulfonates. The compounds were synthesized via acetylation reactions using acetic anhydride and were fully characterized by IR, 1H NMR, 1 3C NMR, elemental analysis, and HR-MS techniques. The anticancer activities of the synthesized compounds were evaluated in the concentration range of 1.563-200µM against HepG2 (hepatocellular carcinoma) and U87 (glioblastoma) cell lines, showing significant cytotoxic effects. Enzyme inhibition assays demonstrated potent inhibitory activities against α-glucosidase, α-amylase, acetylcholinesterase (AChE), and glutathione S-transferase (GST), with IC50 values ranging from 1.4 to 2.9µM. Molecular docking studies, performed using DFT-optimized geometries, supported the experimental findings and revealed strong and specific interactions with the target proteins. Among the studied derivatives, compound 2a exhibited the highest affinity toward α-glucosidase, 2d showed superior binding to α-amylase and AChE, while 2c demonstrated enhanced interaction with GST. Compound 2b displayed promising anticancer potential, forming stable complexes with proteins associated with the HepG2 and U87 cell lines.

Aqueous zinc ion batteries have emerged as promising candidates for next-generation energy storage systems due to their inherent advantages of cost-effectiveness, operational safety, and environmental compatibility. Nevertheless, critical challenges including zinc dendrite formation, parasitic corrosion reactions, hydrogen evolution, and unsatisfactory Zn2+ diffusion kinetics still hinder their commercial viability. To address these limitations systematically, recent research efforts have focused on developing comprehensive mechanistic analyses through advanced characterization methodologies. This review presents a critical evaluation of state-of-the-art analytical techniques for investigating aqueous zinc ion batteries, encompassing fundamental principles, operational protocols, and practical applications across various research scenarios, thereby establishing a robust methodological framework for future studies. The discussion commences with an examination of conventional characterization approaches that provide essential baseline information regarding electrode morphology and electrochemical behavior. Subsequently, we introduced in situ analytical platforms combining three-dimensional visualization techniques, multimodal spectroscopic characterization, and dynamic electrochemical monitoring systems. These advanced operando characterization tools enable real-time observation of interfacial evolution and transient reaction processes, offering unprecedented insights into battery failure mechanisms at multiple scales.

Youth street violence known as klitih has become a persistent social problem in the Special Region of Yogyakarta, while access to structured and comprehensive official crime data remains limited. Online news portals frequently report klitih incidents and provide contextual information that can potentially support empirical crime analysis, yet such data are rarely utilized in systematic academic studies. This study aims to utilize online news articles as an alternative data source to identify patterns of youth criminality related to klitih in Yogyakarta, focusing on spatial distribution, temporal trends, and characteristics of actors and instruments involved. A quantitative descriptive approach was employed, using web scraping techniques to automatically collect relevant online news articles from a national news portal. The unit of analysis consisted of news articles reporting klitih incidents within the Yogyakarta region during a defined observation period. The collected data were pre-processed and analyzed using descriptive analytical techniques, including frequency analysis, categorical distribution, and temporal trend analysis. The results indicate that klitih incidents are predominantly concentrated in urban areas, occur mainly during nighttime and early morning hours, and involve youth actors using easily accessible instruments. These findings demonstrate that online news data can serve as a reliable alternative source for capturing empirical patterns of youth criminality and support data-driven approaches in criminological studies.

The Grama Sabha represents a foundational mechanism of participatory democracy within India’s Panchayati Raj framework, enabling direct interaction between citizens and elected representatives in local governance. While its constitutional mandate underscores inclusive deliberation and accountability, empirical evidence on the nature and depth of elected representatives’ participation remains limited. This study undertakes a computational analysis of participation patterns of elected representatives in Grama Sabha meetings across Gram Panchayats in Karnataka. Primary data were collected through a structured survey administered to 384 elected representatives, capturing participation across sixteen analytically defined dimensions, including attendance regularity, procedural awareness, agenda engagement, financial oversight, grievance handling, inclusiveness, conflict management, and post-meeting follow-up. Quantitative and descriptive analytical techniques were employed to identify participation trends and performance differentials across dimensions. The findings indicate relatively strong engagement in terms of attendance and awareness of institutional roles, while revealing notable deficiencies in inclusive consultation practices, conflict resolution, and systematic monitoring of resolutions. By integrating computational techniques with participatory governance analysis, the study contributes empirical insights into the functioning of Grama Sabhas and highlights critical areas for institutional strengthening. The paper concludes with policy-oriented recommendations aimed at enhancing the effectiveness of Grama Sabhas as instruments of grassroots democracy in Karnataka.

The development of socio-religious dynamics in Indonesia today faces the challenge of polarization between religious radicalism and liberalism that has the potential to undermine the foundations of moderate Islam. This research aims to comprehensively describe the strategic role of Ahlussunnah wal Jama'ah (Aswaja) in building a moderate Islamic civilization through theological, institutional, and cultural pillars. The method used is a qualitative approach with an analytical descriptive design, which utilizes content analysis techniques against credible national and international scientific literature in the last ten years. The results of the study show that Aswaja functions as a theological instrument through the principles of tawasuth, tawazun, i'tidal, and tasamuh which are filters for extreme ideologies. Institutionally, Aswaja values are transformed into habitus in Islamic boarding schools and universities to ensure inclusive social behavior. In conclusion, the cultural flexibility of Aswaja through the rules of al-muhafadzah 'ala al-qadim as-shalih allows Islam to remain relevant in the face of digital disruption and the post-truth era. The sustainability of moderate civilization is highly dependent on the resilience of the thinking methodology (manhaj al-fikr) and the strategy of digitizing Aswaja values in the future