Articles

Decentralized control loops are widely credited with improving system resilience, on the reasoning that removing a central point of coordination also removes a central point of vulnerability. This article separates two properties that applied literature on decentralized architecture routinely conflates: bounded fault tolerance, the capacity of a control architecture to remain stable when an individual loop or node is switched off or corrupted in isolation, and network-level resilience, the capacity to recover from correlated disturbances such as communication loss, targeted compromise, or cascading propagation across dependency chains. Reviewing control-theoretic stability results alongside consensus and infrastructure-resilience research shows that the first property follows from specific, testable structural conditions: a steady-state gain condition in one case, a minimum-neighbor redundancy count in another. These conditions come in different strengths depending on whether the disturbance is benign disconnection or active compromise, a distinction the second property depends on and that decentralization leaves for the designer to resolve. The analysis concludes that a resilience claim attached to a decentralized control loop is a claim about a specific structural parameter matched to a stated disturbance model, a parameter whose verification requires evidence beyond the topology itself.

Conventional SCADA-based water utility control relies on hydraulic models recalibrated through discrete campaigns spaced months to years apart, leaving controllers to act on models that degrade silently between updates. This paper specifies and evaluates a framework that couples a gradient-calibrated hydraulic digital twin to a hierarchically decomposed reinforcement learning controller, coordinating production, transmission, and distribution decisions through Lagrangian relaxation of inter-tier coupling constraints. A differentiable hydraulic solver updates pipe roughness, demand allocation, and valve loss parameters through exact gradients of the prediction residual within a rolling 24-hour window, while a temporal fusion transformer propagates quantile demand forecasts into a risk-sensitive reward term. Evaluated on a 2,400-node benchmark network against a rule-based SCADA baseline across thirty replicated simulation runs, the framework reduced specific energy consumption from 0.58 to 0.40–0.42 kWh/m³, demand forecast error from 14.7% to 4.0–5.0% MAPE, anomaly detection latency from 4.3 hours to 0.3–0.5 hours, treatment dosing error from ±15% to ±4%, and non-revenue water from 32.1% to 21–22%. Lagrangian decomposition reduced joint action-space cardinality from a multiplicative to an additive function of per-tier size, yielding an approximately two-orders-of-magnitude reduction in effective search space for the tested topology. Parameter identifiability under sensor coverage sparser than the benchmark configuration remains untested and bounds the framework's applicability to deployments matching the assumed instrumentation density.

Knowledge work teams operating under variable demand face a class of delivery failure that single-layer governance models cannot prevent: structural overload injected at the commitment-formation boundary, invisible to execution-layer metrics, and amplified by cognitive fragmentation that standard workflow instruments do not register. This article examines the architectural conditions under which knowledge work control systems reduce cognitive load and improve delivery predictability. Through a grouped analytical review of empirical and theoretical literature on WIP-limit governance, team cognitive load, and observability-driven telemetry, the article identifies a shared structural limitation across all three bodies of research: none models the coupling between commitment formation, execution mode, and cognitive context as a single governed system. Drawing on control systems theory, queueing dynamics, and cognitive psychology, the article argues that delivery predictability degrades not from execution inefficiency but from the absence of cross-loop coupling rules that prevent obligation surplus, flow degradation, and cognitive fragmentation from reinforcing one another. The three-loop flow architecture comprising a Commit Loop with capacity-bounded intake, a Delivery Loop with explicit Normal, Overload, and Recovery operating modes, and a Cognition Loop enforcing context-capacity constraints through a Context Token Protocol is identified as a structural response to the documented failure modes of existing frameworks. The analytical contribution is a precise specification of the boundary conditions under which WIP-limit Kanban, team-topology design, and DORA-type telemetry each remain adequate, and the condition under which none of them does.

We have reported novel solid-cancer treatment modality of nano-thermal ablation therapy using two medical devices of 100kHz electromagnetic field radiator and heat-generating nanoparticles of MCL particle [1]. External 100kHz electromagnetic field radiation induced heat generation of MCL particle in tumor tissue and caused tumor specific cytotoxicity and blood vessel disruption [1]. MCL particle was designed to be about 100nm diameter and to move within tumor tissue by composing heat-generating magnetite (Fe₃O₄) with neutral and cationic lipids [1]. However, concerning 100kHz radiator, rational concept of its performance and specification was not fully discussed. Purpose of this seminar is to describe significance of 100kHz magnetic flux density for rational designing, specification and usage of the radiator, referring to our unpublished data during 2004~2025. At first, our calibration method of 100kHz magnetic flux density was shown, and then its application to density distribution analysis of our radiators HTS-5010H and Hi-Heater 5010 was described. And, based on density distribution profile of Hi-Heater 5010 radiator, effective density at tumor locus in the standard treatment condition of the therapy was confirmed 15mT. Based on the recorded data of clinical research using HTS-5010H radiator, safety radiation condition toward groin, breast, thigh, neck, chest and arm were shown with density distribution in patient bodies. With all respect, quoting MFH^®300F (100kHz) radiator [2], availability of three types radiators for various target cancers was discussed on the basis of effective tumor density and mitigation of normal tissue heating. According to Design Control Guidance of medical device [3], design process of the radiator was exemplified by drafted documents of design input and output.

C-phycocyanin (C-PC) is a high-value pigment–protein in Spirulina biomass whose thermolability makes it vulnerable to degradation during post-harvest drying, yet freeze-drying—the gold-standard preservation method—remains prohibitively energy-intensive for large-scale production. This study investigated whether controlled-humidity air drying can preserve C-PC content and its antioxidant functionality in dried biomass comparably to freeze-drying. Wet Spirulina biomass (25 g fresh weight) was dried under nine factorial combinations of temperature (25, 40, and 60°C) and relative humidity (20, 30, and 40%) using a temperature–humidity chamber, with freeze-drying (FD) as the reference. C-PC was extracted, quantified spectrophotometrically along with allophycocyanin and chlorophyll, and its purity index (A₆₂₀/A₂₈₀) and antioxidant activity (DPPH radical scavenging, IC₅₀, and ascorbic acid equivalent antioxidant capacity) were determined. Statistical analyses included one-way ANOVA with Tukey's post-hoc test and partial Pearson correlation. Air drying at 25°C yielded C-PC contents of 184.39 - 194.72 mg g^-1 DW (98 - 104% of the FD reference, 188.11 mg g^-1 DW) with food-grade purity indices of 0.95 - 1.00, whereas drying at 40°C and 60°C reduced C-PC to 76 - 85% and 58 - 63% of the FD value, respectively. Partial correlation analysis identified temperature as the dominant determinant of C-PC loss (Pearson r = -0.90 to -1.00), while relative humidity exerted a secondary, modulatory influence. The 25°C air-dried C-PC retained 86 - 87% of the antioxidant capacity of a commercial C-PC reference standard, approaching the 94% retention achieved by freeze-drying. These findings demonstrate that controlled-humidity air drying at 25°C and 20 - 30% relative humidity effectively preserves both C-PC yield and bioactivity at levels comparable to freeze-drying, offering a potential scalable and low-cost drying alternative for the Spirulina nutraceutical industry

Background: Sleep deprivation is increasingly prevalent among young adults due to academic, occupational, and social demands, making them susceptible to circadian disruption. Executive functioning—encompassing working memory, inhibitory control, and cognitive flexibility is essential for academic and professional success. This meta-analysis quantifies the effect of sleep deprivation on executive functioning in healthy young adults. Practical Implications: These findings highlight the need for evidence-based interventions such as university-level sleep education programs, flexible academic scheduling, and workplace policies promoting adequate sleep to optimize cognitive performance and productivity among young adults. Methods: Following PRISMA 2020 guidelines, PubMed, Scopus, PsycINFO, and Web of Science were searched (January 2000–March 2024) for studies assessing acute (<6 hours sleep or ≥24 hours total deprivation) or chronic (<6 hours/night over multiple days) sleep deprivation in young adults. Outcomes included validated executive function tests (e.g., Stroop, N-Back). Random-effects meta-analysis (Hedges’ g) was conducted using R (version 4.3.2) with metafor/meta packages. Heterogeneity (I², Q-test), sensitivity (leave-one-out), and publication bias (funnel plot, Egger’s test) were evaluated. Results: Out of 2,478 screened studies, 39 met inclusion criteria (n=4,578). Sleep deprivation had a moderate-to-large detrimental effect on executive functioning (Hedges’ g = -0.62, 95% CI [-0.78, -0.45], p<0.001). Subdomain analysis revealed greatest impairment in working memory (g = -0.71), followed by inhibitory control (g = -0.59) and cognitive flexibility (g = -0.49) (all p<0.001). Moderate heterogeneity was present (I² = 58%), with results robust to sensitivity analysis. Egger’s test indicated no significant publication bias (p=0.22). Interpretation: Sleep deprivation significantly impairs executive functioning in young adults, especially working memory. Interventions improve sleep may enhance cognitive performance and should be integrated into public health strategies and educational policies. Future research should assess chronic restriction and individual vulnerability factors.

Frequent consumption of aflatoxins-contaminated spices has been linked to serious adverse health effects among consumers. The likelihood of exposure to these toxins is influenced by the level of public awareness. Controlling aflatoxins contamination throughout the food chain is critical for public health. This study aimed to assess the handling practices and awareness of aflatoxin contamination among micro- and small-scale spice processors. A total of 60 processors from 4 districts of two regions of Tanzania were interviewed. The results showed that while 56.7% of interviewed processors were aware of aflatoxin contamination in spices primarily through training (38.3%) and mass media (30%). However, there were still misconceptions regarding the causes and effects of aflatoxins to human health. It was observed that, poor drying and storage practices, inadequate monitoring of processors aggravated the situation. Nonetheless, all interviewed processors expressed willingness to participate in training programs to ensure quality and safety along the chain. The study findings underscore the necessity for targeted interventions to reduce aflatoxin risks in the spice value chain. These should include strengthened food safety inspections and enforcement, as well as tailored training and support for micro and small-scale spice processors. Enhancing their knowledge and ability to adopt proper handling, drying and storage practices is critical for enhancing food safety and safeguarding public health.

Background: Tobacco endgame, defined as elimination of commercial tobacco sales The U.S. tobacco control landscape is a complex, adaptive system shaped by diverse stakeholders, evolving products and regulations, shifting social norms, and the strategic countermeasures of a powerful industry. Managing such complexity requires more than isolated interventions—it demands a coordinated, enterprise-wide approach that accounts for dynamic interactions, feedback loops, and emergent risks. Objective: Drawing on complex systems thinking, Zachman enterprise architecture model, and public health best practices, we conceptualize tobacco control as an evolving enterprise progressing through six interconnected phases: (1) Conception & Initiation, (2) Policy & System Design, (3) Implementation & Operation, (4) Evaluation & Adaptation, (5) Consolidation & Endgame Transition, and (6) Sustainment or Sunset. Each phase incorporates governance structures, performance benchmarks, and transition criteria designed to manage interdependence and reduce systemic vulnerabilities. Results: The lifecycle framing emphasizes how tobacco control in the U.S. can evolve as a complex, adaptive enterprise—integrating public health objectives with legal, operational, and cultural change processes. This model supports strategic sequencing, cross-sector alignment, and risk mitigation against emergent industry tactics, enabling a resilient and measurable pathway to the endgame. Conclusions: Seeing tobacco control as a complex enterprise that operates under a lifecycle model may offer a roadmap for achieving and sustaining the tobacco endgame. Using this approach may enhance policy coherence, resource efficiency, and adaptability, ensuring tobacco endgame is achieved.

Avian influenza is a very lethal disease caused by influenza viruses that normally circulate among birds, and contains well-known subtypes are A(H5N1) and A(H7N9). Human infection is rare and occurs through close contact with infected poultry, therefore, confirming a history of such contact is important. The same treatment as for seasonal influenza is recommended, such as the neuraminidase inhibitors, cap endonuclease inhibitors, and RNA polymerase inhibitor. The avian influenza patients are regulated by the Infectious Diseases Control Law in Japan, we should manage the avian influenza appropriately.

Background: Mechanical low back pain (MLBP) is a leading cause of disability worldwide, with well-established risk factors such as obesity, occupational ergonomics, and core muscle strength. However, the role of pes planus (flat foot) as a contributing factor remains underrecognized. This study aims to investigate the association between flat foot and MLBP using Clarke’s angle as an objective measure of foot posture. Methods: A case-control study was conducted in South Timor Tengah Regency, East Nusa Tenggara, Indonesia, from December 2024 to February 2025. Fifty patients diagnosed with MLBP and 50 healthy controls were enrolled. Foot type assessment was performed using Clarke’s angle, with a cutoff of ≤30° indicating flat foot. Pain severity in the LBP group was recorded using the Numerical Rating Scale (NRS). Statistical analysis was conducted using chi-square and independent t-tests, with significance set at p < 0.05. Results: Flat foot was significantly more prevalent in the LBP group (58%) than in the control group (18%) (p = 0.000; OR: 6.29, 95% CI: 2.52-15.69), indicating that individuals with flat feet are over six times more likely to experience MLBP. No significant differences were observed between the groups regarding BMI, age, or gender. Conclusion: These findings suggest that flat foot is an independent risk factor for MLBP, likely due to altered spinal biomechanics and compensatory postural changes. Clinicians should consider foot posture assessments in MLBP patients and explore targeted interventions, such as orthotic support, to mitigate symptoms.

Background: Electronic cigarette (e-cigarette) use and vaping tobacco have increased rapidly worldwide, raising concerns about their health effects, social acceptability, and regulatory challenges. In many countries, e-cigarettes are more commonly used by individuals from higher socioeconomic status (SES) backgrounds, who, in theory, should have greater knowledge about e-cigarettes and their associated risks. However, it remains unclear why a group with more knowledge about e-cigarette risks would also hold more positive attitudes toward vaping and exhibit higher usage rates — a phenomenon that may represent a knowledge-behavior paradox. Understanding this paradox, along with the complex relationships between e-cigarette knowledge, attitudes, and behaviors, is critical for informing effective public health interventions, campaigns, social media messaging, and regulatory policies. Objectives: This study aimed to evaluate the complex relationship between SES, e-cigarette knowledge, pro-vaping attitudes, and e-cigarette use. Methods: The SMOKES Study (Study of Measurement of Knowledge and Examination of Support for Tobacco Control Policies) used a multi-center, cross-sectional design, collecting data from 2,403 college and university students across 15 provinces in Iran (covering nearly half of the country's provinces). The survey measured family income, age, sex, ethnicity, e-cigarette use, knowledge, and attitudes. Structural Equation Modeling (SEM) was employed to examine the interrelations between SES, knowledge, attitudes, and behavior, while adjusting for age, sex, and ethnic minority status. Results: SEM analysis confirmed the hypothesized paradox. Although greater knowledge about e-cigarettes was linked to less favorable attitudes toward vaping and lower use, pro-vaping attitudes emerged as the strongest predictor of vaping behavior, while knowledge played a weaker protective role. Notably, individuals with higher SES simultaneously showed higher knowledge and, paradoxically, more pro-e-cigarette attitudes and greater usage. Female students and ethnic minority students reported higher correct knowledge and lower pro-vaping attitudes and use. Although age and higher family income were associated with more favorable attitudes, they did not directly predict vaping behavior. These results suggest that for higher SES individuals, poor knowledge is not the main driver of e-cigarette use; rather, their pro-e-cigarette attitudes, which seem to outweigh the influence of knowledge, play a key role. Conclusions: Although individuals from higher SES backgrounds report greater correct knowledge about e-cigarettes, this knowledge does not necessarily translate into reduced positive attitudes or lower usage. This study highlights the complexity of these paradoxical effects and suggests that public health strategies need to go beyond simple education and knowledge-based interventions. Targeted approaches should address industry messaging, challenge misconceptions, and strengthen regulatory efforts to reduce e-cigarette use among young adults, including those from higher SES backgrounds.

Background: Tobacco control policies are implemented globally to reduce tobacco-related morbidity and mortality. Emerging evidence suggests that individual tobacco use may influence the level of support for these policies. However, the extent to which personal use affects policy endorsement remains underexplored, particularly among young adults in academic settings. Aims: This study aimed to examine whether college students who use tobacco exhibit lower support for tobacco control policies compared to their non-user counterparts. Methods: We conducted a multi-center, cross-sectional study involving 2403 college students from various provinces in Iran. Tobacco use was ascertained based on self-reported consumption of cigarettes, electronic cigarettes, and hookah. Attitudes toward tobacco control policies were evaluated using a structured survey instrument, and comparative analyses were performed to assess differences in policy support between tobacco users and non-users. Results: The analysis revealed that tobacco users demonstrated significantly lower support for tobacco control policies compared to non-users. This association was consistently observed across users of cigarettes, electronic cigarettes, and hookah, suggesting a systematic pattern irrespective of the type of tobacco product used. Conclusion: These findings indicated a clear association between tobacco use and reduced endorsement of tobacco control policies among Iranian college students. These results have potential implications for public health policy, emphasizing the importance of addressing individual tobacco use behaviors in the development and implementation of tobacco control strategies. Further research is needed to elucidate the underlying mechanisms of this relationship.

Background: Menthol-flavored tobacco products are disproportionately used in low-income African American communities, a result of decades of targeted marketing and systemic inequities. Menthol use has been associated with lower quit rates, often compounded by factors such as lower trust in healthcare systems, reduced access to cessation programs, and other structural barriers. Despite this, few studies have systematically examined the explanatory mechanisms that might clarify why menthol-flavored tobacco is linked to poorer cessation outcomes among participants in tobacco cessation programs. Aims: This study aimed to investigate the potential mechanisms by which menthol tobacco use is associated with lower quit rates across three types of smoking cessation interventions. Methods: Participants were randomized into one of three smoking cessation interventions: in-person (CEASE), self-help, or online/hybrid programs. Smoking abstinence was assessed three months post-intervention as the primary outcome. Secondary analyses explored whether demographic, socioeconomic, or behavioral factors mediated the association between menthol use and quit rates across the intervention arms. Results: Menthol tobacco use was significantly associated with lower quit rates (p < 0.01). This association was not explained by demographic, socioeconomic, health, or addiction-related factors. While menthol use was associated with lower education and employment levels, demographic characteristics, physical or mental health, or addiction did not explain the effect of menthol on tobacco cessation. These findings suggest that the lower quit rates observed among menthol users cannot be attributed to any third factors assessed in this study. Conclusions: Menthol tobacco use independently predicts lower quit rates, and the mechanisms behind this disparity remain unclear. The consistent findings across different intervention types highlight the need for further research to uncover the underlying pathways and to design targeted strategies to improve cessation outcomes for menthol users.

Background: Tobacco use remains disproportionately high among low-income and racial-ethnic minority populations. The CEASE program, with its self-help, hybrid/online, and in-person modalities, has demonstrated efficacy in promoting tobacco cessation. However, predictors of successful cessation among participants in these groups remain unclear. Objective: To identify baseline predictors of successful tobacco cessation among low-income and racial-ethnic minority participants in the CEASE program, with a focus on demographic, socioeconomic, behavioral, and psychosocial factors. Methods: Participants were allocated into three intervention arms: self-help, CEASE hybrid/online, and CEASE in-person. Baseline characteristics, including demographics (e.g., age, gender), socioeconomic status (e.g., education, employment), substance use profiles (e.g., cigarette packs per week, use of other tobacco products, menthol tobacco use), physical health (e.g., general health, number of cardiometabolic risk conditions), mental health (e.g., depressive symptoms, perceived stress), perceived social support, and nicotine dependence, were analyzed as potential predictors of cessation success. Multivariable logistic regression models were used to identify factors associated with successful quitting, controlling for the study arm. Results: In addition to the study arm, gender, baseline depression, cardiometabolic conditions, tobacco flavor, and the use of other tobacco products were significant predictors of quit success. Individuals receiving in-person interventions had significantly higher odds of quitting (AOR = 3.79, p < 0.05). Women were significantly less likely to quit compared to men (AOR = 0.24, p < 0.01). Participants with a greater number of cardiometabolic risk conditions were more likely to quit (AOR = 1.93, p < 0.05), while those with higher levels of depression had lower odds of quitting (AOR = 0.61, p < 0.05). Menthol tobacco users were also less likely to quit (AOR = 0.10, p < 0.05). Interestingly, individuals who used other forms of tobacco in addition to cigarettes had increased odds of quitting (AOR = 2.86, p < 0.05). No other factors, including demographic variables (e.g., age), socioeconomic status (e.g., education, marital status), substance use profiles (e.g., cigarette packs per week, NRT use), or nicotine dependence, were significant predictors of cessation success. Conclusion: Baseline self-reported anxiety/depression and depressive symptoms play a critical role in reducing the likelihood of successful tobacco cessation among low-income and racial-ethnic minority participants in the CEASE program. These findings underscore the importance of addressing mental health challenges as part of tobacco cessation interventions to enhance their efficacy. Future research should explore targeted strategies for integrating mental health support into cessation programs to improve outcomes for underserved populations.

Objective: To examine racial/ethnic differences in the associations of family socioeconomic status (SES), neighborhood SES, and inhibitory control with body mass index (BMI) in 9-10-year-old children using data from the Adolescent Brain Cognitive Development (ABCD) study. Methods: This cross-sectional study included a diverse sample of children aged 9-10 years, representing non-Latino White, Black, Latino, Asian, and Other racial/ethnic groups. BMI was the primary outcome. Key predictors were family SES, neighborhood SES, and inhibitory control. Multivariable regression models were stratified by race/ethnicity to identify group-specific associations. Results: Race/ethnic groups differed in psychosocial correlates of childhood BMI at age 9 and 10. Among non-Latino White children, higher family income (B = -0.086, p < 0.001), higher parental education (B = -0.069, p < 0.001), and living in a married household (B = -0.079, p < 0.001) were associated with lower BMI. Additionally, the presence of healthy food options in the zip code (B = -0.030, p = 0.032) was linked to lower BMI, while lack of planning (B = 0.032, p = 0.030) was associated with higher BMI. For non-Latino Black children, positive urgency (B = -0.068, p = 0.022) was negatively associated with BMI, while other factors such as family SES and neighborhood SES did not show significant associations. For Latino children, higher family income (B = -0.093, p = 0.001) and parental education (B = -0.099, p < 0.001) were associated with lower BMI. In this group, male gender (B = 0.043, p = 0.033) was associated with higher BMI. Among Asian children, higher family income (B = -0.199, p = 0.006) and parental education (B = -0.144, p = 0.037) were significantly associated with lower BMI. For children in the "Other" racial/ethnic category, higher family income (B = -0.101, p = 0.023), living in a married household (B = -0.076, p = 0.026), and higher median income in the zip code (B = -0.083, p = 0.013) were associated with lower BMI. In this group, male children had lower BMI compared to females (B = -0.089, p = 0.001). Conclusion: The findings highlight substantial racial/ethnic differences in the psychosocial and socioeconomic correlates of BMI in children. There is a need for tailored interventions that target social determinants of childhood high BMI. One size does not fit all.

Background: Low socioeconomic status (SES) has been linked to higher rates of tobacco and marijuana use initiation; however, the contributions of environmental and neurocognitive factors remain underexplored. This study investigates a potential pathway connecting low SES, fine particulate matter (PM2.5) exposure, brain functional connectivity, and inhibitory control to increased tobacco and marijuana use initiation among adolescents. Objectives: To examine the mediating roles of PM2.5 exposure, resting-state functional connectivity between the right pallidum and the ventral attention network (P-VAN rsFC), and inhibitory control in the relationship between low SES and tobacco and marijuana use initiation. Methods: Data were drawn from the Adolescent Brain Cognitive Development (ABCD) study to assess associations between baseline SES, baseline PM2.5 exposure (based on zip code), baseline P-VAN rsFC, baseline inhibitory control, and subsequent tobacco and marijuana use initiation. Mediation models were used to determine whether PM2.5 exposure and changes in P-VAN rsFC act as pathways linking low SES to diminished inhibitory control and subsequent substance use initiation. Results: Low SES was associated with higher PM2.5 exposure, which, in turn, was linked to alterations in P-VAN rsFC. These alterations were correlated with lower inhibitory control, which significantly predicted tobacco and marijuana use initiation over time. Inhibitory control partially mediated the relationship between low SES and substance use initiation, indicating a complex pathway influenced by environmental and neurocognitive factors. Conclusions: This study identifies a potential mechanism linking low SES to tobacco and marijuana use initiation through environmental and neurobiological pathways. Understanding how PM2.5 exposure and neurofunctional connectivity impact inhibitory control can provide valuable insights for developing targeted interventions to reduce substance use among adolescents in low SES environments.

Active Pharmaceutical Ingredients (APIs) serve as the cornerstone of pharmaceutical development, driving therapeutic efficacy and safety in drug formulations. This article provides a comprehensive overview of the lifecycle of APIs, starting from their discovery and development, through to manufacturing processes and regulatory oversight. The development of APIs begins with intensive research and discovery efforts, where medicinal chemists and pharmacologists identify and optimize potential compounds through computational modelling, high-throughput screening, and structure-activity relationship studies. Promising candidates undergo rigorous preclinical testing to assess pharmacological properties, safety profiles, and potential adverse effects in animal models. Upon successful preclinical outcomes, APIs progress to clinical trials, involving phases of testing in human subjects to evaluate efficacy, dosage regimens, and safety profiles under controlled conditions. Clinical trial data are meticulously analyzed to support regulatory submissions, demonstrating the API's therapeutic benefits and safety for eventual patient use. Manufacturing APIs involves complex chemical synthesis or biotechnological methods, ensuring precise control over reaction conditions, purity, and yield. The scale-up from laboratory synthesis to industrial production demands adherence to Good Manufacturing Practices (GMP), where stringent quality control measures verify consistency, potency, and stability throughout production batches. Regulatory oversight by authorities such as the Food and Drug Administration (FDA) in the United States and the European Medicines Agency (EMA) in Europe ensures that APIs meet stringent standards of safety, efficacy, and quality before market approval. Manufacturers must submit comprehensive Chemistry, Manufacturing, and Controls (CMC) data, detailing manufacturing processes, analytical methods, and stability studies to support regulatory filings.

Costus afer, a known medicinal plant used in the removal of total monocyclic aromatic hydrocarbon (TMAH) in crude oil-contaminated soil add to the list of plant that has the potential to restore the soil quality. This study investigated the potential of Costus afer plant at various ages (7, 14, 21, 28, 35, and 42 days old) to biodegrade crude oil-contaminated soil. The group-balanced block design (GBBD) was used in establishing the experiment. TMAH was quantified by the standard method, according to USEPA method using gas chromatography-mass spectrometry (GC-MS). The contamination of 48kg of sandy loam soil was simulated by mixing 0.5, 1.0, and 1.5L of Bonny-Light crude oil with the soil in three separate vessels to achieve conditions of low (C₁), medium(C₂), and high(C₃) contamination, respectively. An additional vessel with medium-level contaminated soil but no treatment (C₄) served as the control. The Costus afer plants were nursed and transplanted at the stated ages to each vessel except the control. Controlled irrigation was applied, and the setups were housed to shield them from rainfall. After 90 days of treatment, results showed that the 7 days old Costus afer plants produced the highest amount of TMAH reduction of 96.5, 39.8, and 32.1%, for C₁, C₂ and C₃, respectively, while the control (C₄) was 9.45%. Furthermore, the sequence of TMAH reduction by the plants was 7 days old, 14 days old, 21 days old, 28 days old, 35 days old, and 42 days old. Thus, in addition to its medicinal value, Costus afer plant also has the potential to biodegrade TMAH in crude oil-contaminated sandy loam soil.

PLCs, or programmable logic controllers, are essential parts of contemporary industrial automation systems and are responsible for managing and keeping an eye on a variety of operations. PLC reliability is critical to maintaining industrial systems' continuous and secure operation. A wide range of reliability strategies were used to improve the reliability of Programmable Logic Controllers, and this article methodically looks at them all. The evaluation classified PLC reliability techniques into Root Cause Analysis (RCA), Reliability Centered Maintenance (RCM), Hazard analysis (HA), Reliability block diagram (RBD), Fault tree analysis (FTA), Physics of failure (PoF) and FMEA/FMECA, after thoroughly reviewing the body of literature. The proportion of reviewed papers using either RCA, RCM, FMEA/FMECA, FTA, RBD, RCM, PoF, or Hazard analysis to increase the reliability of PLCs showed that RCA, which makes up 20% of the publications reviewed, has been used the most to increase the reliability of the PLC, followed by HA, RCM, RBD, FTA, and PoF, which account for 17%, 16%, 16%,13%, 10%, and 8% of the articles reviewed, respectively. The paper discusses new developments and trends in PLC reliability, such as the application of machine learning (ML) and artificial intelligence (AI) to fault detection and predictive maintenance.

The control of processes is made smooth and effective by Programmable Logic Controllers (PLCs), which are essential to industrial automation. The assessment of PLCs' reliability is crucial since more and more sectors depend on them for crucial tasks. In-depth reviews of the components necessary to evaluate PLC system reliability are presented in this study. To ensure a robust review, the review first clarifies the basic concepts of reliability, highlighting the significance of system uptime and the ramifications of failures in industrial settings. Next, it examined the different elements that go into a PLC's overall reliability, such as availability, testability, and (maintenance and maintainability). The percentage of the reviewed papers that employed (maintenance and maintainability), testability, or availability to improve the reliability of PLC systems showed that, availability and (maintenance and maintainability) has been employed the most for enhancing system reliability, accounting for 32% each of publications analyzed, followed by testability, accounting for 28% respectively. The scatter chart that depicts the progression of reliability components from 2010 to 2023 also explained that the use of availability and (maintenance and maintainability) was increasing. This upward trend can be explained by the fact that repairable systems are heavily reliant on availability, whereas (maintenance and maintainability) tend to avoid unnecessary equipment breakdown and testability, which ensures the ease with which the functionality of any system or component can be ascertained with the required level of precision.