Asset Management Transformation in Energy Companies: Integration of ISO 55001, Balanced Scorecard, and SWOT Analysis for Competitive Advantage

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Asset management is a strategic component in ensuring the sustainability and operational efficiency of electric energy companies, especially in facing the challenges of increasing demand and the need for reliable electricity services. This article examines the implementation of ISO 55001 as a structured asset management system framework, with a Balanced Scorecard (BSC) approach as an integrated performance measurement tool from four perspectives: financial, customer, internal business processes, and learning and growth. The research was conducted at an electric energy provider organization, by analyzing Key Performance Indicators data for 2022–2023. The results of the BSC measurement show positive trends, such as increasing ROI, EBITDA Margin, Customer Satisfaction Index, and human capital readiness, but also reveal weaknesses such as the still high ratio of power outages and Equivalent Forced Outage Rate (EFOR). SWOT analysis is used to identify internal factors (strength and weakness) and external factors (opportunity and threat). Quantitative SWOT results show that the company is in quadrant I (aggressive strategy), with internal strengths and external opportunities dominating. Based on these findings, alternative strategies are formulated that are adjusted to each BSC perspective and ISO 55001 pillars (Cost, Performance, Risk). Strategies include optimizing asset life cycles, reducing maintenance costs, increasing distribution system reliability, and developing Human Resource capabilities. The integration of ISO 55001 and BSC has been proven to provide a holistic approach in designing data-based and risk-based strategies. These findings not only provide theoretical contributions to the development of modern asset management systems, but are also practically relevant for corporate policy makers in improving the efficiency, reliability, and competitiveness of organizations in the energy sector.

EryC PCR assay as DIVA tool for Bovine Brucellosis

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The present study focuses on differential identification of vaccinated and infected animals of brucellosis (DIVA) by EryC PCR assay. Clinical specimen (400) comprising of 200 (162 blood, 27 milk, 10 vaginal swab and one tissue) samples from vaccinated and 200 (51 blood and 149 milk) samples from unvaccinated cattle. These samples were collected from four different regions of Maharashtra. The RBPT recorded overall prevalence of 39.9% (85/213) with 50.98% (26/51) in unvaccinated animals and 36.41% (59/162) in vaccinated animals. According to MRT results, the overall percent positivity observed was 58.5% (103/176) with vaccinated animals showing a 74.07% positivity (20/27) and unvaccinated animals showing 55.70% positivity (83/149).

A sum of 199 clinical samples (85 blood, 103 milk, 10 vaginal swab and one tissue sample) subjected to differentiate vaccine strain and wild strains of B. abortus,by targeting deletion of 702bp. The EryC PCR assay generated amplicon in 57 clinical samples i.e. 28.64% (19 from vaccinated and 38 from unvaccinated animals) of them found positive by EryC PCR. 16 samples from vaccinated animals amplified amplicon of 1257bp and only three samples showed amplicon of 555bp. Eight samples from unvaccinated animals amplified amplicon of 1257bp, 30 milk samples from unvaccinated animals generated amplicon of 555bp suggesting infection is due to vaccine strain.

 

Lung Disease Classification Using Transfer Learning on Chest X-ray Images

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Lung diseases remain a significant global health concern, necessitating the development of rapid and accurate diagnostic methods. While previous research has shown the promise of deep learning models, particularly transfer learning with architectures such as ResNet and VGG, limitations persist in evaluation scope, class imbalance handling, and model interpretability. This study proposes an enhanced deep learning framework for multi-label classification of thoracic diseases using chest X-ray images, addressing these gaps through comprehensive evaluation metrics, advanced data augmentation, and explainable AI (XAI) techniques. The NIH ChestX-ray14 dataset is utilized, with class imbalance mitigated via synthetic minority oversampling and weighted focal loss. Multiple state-of-the-art CNN architectures, including EfficientNet and ResNet variants, are benchmarked using precision, recall, F1 Score, AUC, and accuracy. Moreover, Gradient-weighted Class Activation Mapping (Grad-CAM) is integrated to visualize pathological regions, improving clinical interpretability. The offered framework can perform better in all assessment criteria, achieving an AUC of 0.91 with EfficientNet-B0, and provides interpretable outputs critical for deployment in real-world diagnostic settings. This work advances automated radiological diagnosis by addressing key methodological shortcomings and offers a reliable, explainable solution for lung disease detection.

The Effects of Phenytoin on Thyroid Function Tests: A Case Mimicking Central Hypothyroidism

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Introduction: Phenytoin, a widely used antiepileptic, can alter thyroid hormone metabolism and laboratory assays, potentially mimicking central hypothyroidism.

Case Presentation: A 75-year-old woman on long-term phenytoin presented with nonspecific symptoms and thyroid function tests showing low free T4 with a normal TSH. Workup revealed no evidence of pituitary disease. Elevated phenytoin levels and the absence of clinical hypothyroid features suggested phenytoin-induced assay interference or altered metabolism.

Conclusion: In patients on chronic phenytoin therapy, discordant thyroid function tests may not indicate true hypothyroidism but rather drug-induced changes. Clinical correlation is essential before initiating unnecessary treatment.

Time to Normalization of Thyroid Function Tests and Associated Factors Among Thyrotoxic Patients at Saint Paul’s Hospital Millennium Medical College Endocrine Clinic, Addis Ababa, Ethiopia, 2024

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Background: Thyrotoxicosis is characterized by excessively high tissue thyroid hormone levels. Untreated or inadequately managed thyrotoxicosis can lead to various complications. Understanding factors influencing the time to achieve thyroid function normalization is essential for improving treatment outcomes and patient care.

Objectives: This study aimed to assess the median time to normalization of thyroid function tests and identify factors associated with delayed euthyroidism among thyrotoxic patients attending the Endocrine Clinic at St. Paul’s Hospital Millennium Medical College, Addis Ababa, Ethiopia, in 2023.

Methods: A hospital-based retrospective cohort study was conducted involving 181 patients diagnosed with thyrotoxicosis who attended the adult Endocrine Clinic from April 2023 to January 2024. Data were collected using a structured questionnaire and entered into EpiData version 7.1, then exported to STATA version 15 for analysis. Descriptive statistics summarized continuous variables as mean ± SD or median with interquartile range, and categorical variables as frequencies and percentages. The association between independent variables and time to euthyroidism was analyzed using Cox proportional hazards regression, with the log-rank test employed to compare median times across groups. Adjusted hazard ratios (AHR) with 95% confidence intervals (CI) were reported to quantify the strength of associations.

Results: Approximately 61% of patients achieved euthyroidism, with a median time of 7 months (Interquartile Range: 3–13 months). Factors significantly associated with delayed normalization included use of Propylthiouracil (AHR = 0.33; 95% CI: 0.12–0.89), poor medication adherence (AHR = 0.24; 95% CI: 0.13–0.42), higher baseline pulse rate (AHR = 0.97; 95% CI: 0.95–0.99), and elevated baseline free thyroxin levels (AHR = 0.99; 95% CI: 0.98–0.995).

Conclusion: Although more than half of the patients attained euthyroidism, the process took longer than expected. High baseline FT4 levels, elevated pulse rate, non-adherence to medication, and the use of PTU as the anti-thyroid drug delayed the achievement of euthyroidism. Patients with thyrotoxicosis require attentive and continuous monitoring until thyroid function normalizes to prevent complications.

The Impact of Psychological Capital and Leader-Member Exchange on Employee Productivity: A Systematic Literature Review

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Employee productivity is a key indicator in assessing the effectiveness and efficiency of individual performance in achieving organizational goals. Achieving optimal productivity is influenced by various factors, including individual psychological aspects and interpersonal relationships within the workplace, thereby requiring support from company management. This study aims to analyze the influence of psychological capital and leader-member exchange on employee productivity at Company, located in East Jakarta. This company is a multinational manufacturing company in the consumer health sector that produces various healthcare products for both domestic and international markets. The sampling in this study was conducted using a stratified random sampling technique, involving 131 respondents, consisting of both permanent and non-permanent employees directly recruited directly by the company. The research instrument utilized a questionnaire with a 5-point Likert scale, and data were collected through an online survey method. Data analysis was performed using the Structural Equation Modeling–Partial Least Squares (SEM-PLS) approach with the SmartPLS software. The results of the analysis indicate that all proposed hypotheses are supported, suggesting significant relationships among the variables. Psychological capital was found to have a positive influence on employee productivity, as did leader-member exchange. These findings offer practical implications for company management, highlighting the importance of fostering employees’ positive psychological conditions and maintaining high-quality superior-subordinate relationships to sustainably enhance productivity.

The Influence of Financial Literacy and Cashless Payment on Consumptive Behavior of Generation Z in Jakarta

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The increasing adoption of digital financial services has significantly reshaped consumption patterns, particularly among Generation Z who are native to digital environments. Despite rising national financial literacy levels, the gap between knowledge and actual financial behavior persists. This study examines the effect of financial literacy and cashless payment on the consumptive behavior of Generation Z in the DKI Jakarta region. A quantitative approach was employed with purposive sampling, involving 130 respondents. Data were collected using structured questionnaires and analyzed using multiple linear regression in SPSS. The results reveal that financial literacy has a significant negative effect on consumptive behavior, while cashless payment has a significant positive effect. Moreover, both variables jointly influence consumer behavior significantly. These findings highlight the paradox of financial awareness coexisting with increasing consumption risks due to frictionless payment systems. The study suggests that educational initiatives should not only focus on enhancing financial knowledge but also promote behavioral control when using digital financial tools.

Ventricular Septal Defect Posterior to Acute Myocardial Infarction

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We present the case of an 84-year-old woman who arrived at our unit with chest pain of cardiac origin, a Wellens type A pattern on the electrocardiogram, and on physical examination, a holosystolic murmur at the tricuspid and mitral areas radiating to the right parasternal border—a finding suggestive of ventricular septal defect. She was admitted to the Coronary Care Unit for continuous monitoring. Transthoracic echocardiography revealed rupture of the interventricular septum, along with an image compatible with a dissecting interventricular hematoma. These findings confirmed the presence of a left-to-right shunt. This case highlights the essential role of echocardiography in the early detection of mechanical complications following acute myocardial infarction, and underscores the complexity of managing post-infarction septal rupture in elderly patients.

Building Customer Loyalty in B2B Logistics: The Interplay of Trust, Perceived Risk, and Perceived Value in Indonesia’s Trucking Industry

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This research analyzes the determinants of customer loyalty in Indonesia’s B2B logistics industry, particularly in the trucking sector, focusing on trust, perceived risk, and perceived value. Adopting a quantitative approach, this study samples businesses that use trucking services and examines how the mentioned variables influence enduring customer loyalty. Using comprehensive industry theoretical models, we prepared a structured questionnaire and subsequently collected data from many firms spanning multiple industries that depended on trucking logistics. The research employs advanced statistical methods such as factor analysis and SEM to evaluate the relationships between the key constructs trust, perceived risk, perceived value, and customer loyalty. The findings underscore the role of perceived value as the foremost predictor of customer loyalty; trust only affects loyalty indirectly through its impact on perceived value. The findings suggest that perceived risk should be accepted in high choice or digitized markets, implying organizations need more emphasis on trust and its actual outcome. The study demonstrates that strategically managing perceptions of trust, risk, and value is critical for enhancing.

The Effect of Environmental Management System, Green Investment, Company Size, Profitability, and Public Accounting Firm Reputation on Carbon Emission Disclosure in Energy Sector Companies Listed on the IDX in the Period 2019-2023

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This research aims to investigate and empirically prove the impact of environmental management systems, green investment, company size, profitability, and public accounting firms’ reputations on carbon emission disclosure. The study’s population consists of companies in the energy industry listed on the IDX between 2019 and 2023. We selected the study sample using a census sampling approach that yielded 219 observations. We used the Eviews 12 software for panel data regression analysis as our data analysis method. According to the study’s findings, carbon emission disclosure is positively and significantly impacted by environmental management systems and company size but not by green investment, profitability, and public accounting firms’ reputations.