This article examines how large enterprise organizations can reliably create 0-to-1 products under structural constraints such as multi-layer governance, legacy operating models, and uncertainty in market selection. The study focuses on one specific contribution developed by the author: a data-driven mapping tool embedded in a market expansion platform for de-novo growth and acquisition screening. The novelty of the article lies in combining research on opportunity framing, experimentation discipline, governance design, and innovation structures with an applied product case in which multi-source market data were converted into a visual decision system for location prioritization. The aim is to identify enterprise practices that increase the probability of launching a first viable product while preserving strategic alignment and decision quality. The material base combines recent peer-reviewed literature with an analytical reconstruction of the product work on a mapping platform that integrated reimbursement signals, patient-segmentation data, media-efficiency indicators, and market restrictions into a unified scoring logic. Methods include comparative analysis, analytical synthesis, and conceptual modeling. The results show that enterprise 0-to-1 success improves when opportunity selection is treated as a productized decision system rather than a one-time strategic exercise. The article is relevant for product leaders designing internal decision platforms, growth tools, and other data-intensive products inside large organizations.
The COVID-19 pandemic catalyzed a global expansion of digital surveillance systems, transforming emergency health technologies into long-term governance tools. This paper critically examines the normalization of surveillance in post-pandemic society through a sociological lens, with a particular focus on India. Drawing exclusively from secondary data, it analyzes how surveillance infrastructures—such as contact tracing apps, biometric monitoring, and AI-based public surveillance—have reconfigured state–citizen relations, reinforced social inequalities, and reshaped the meaning of citizenship in the digital age. The study engages with key sociological theories, including Foucault’s governmentality, Zuboff’s surveillance capitalism, and Lyon’s concept of the surveillance society, to explore how technological control has been embedded into everyday life. The findings underscore that surveillance is not merely a technical phenomenon but a deeply social institution that reproduces power, marginality, and exclusion. The paper concludes with a set of policy recommendations aimed at promoting rights-based, participatory, and ethically grounded digital governance.
Premium grade in frozen fish is decided in the hours between landing and the moment a batch leaves the freezer, and the conditions of those hours change when a seasonal plant reaches peak volume. The quality literature measures freezing and frozen storage under steady conditions: a fixed freezing rate, a programmed storage temperature, a planned number of thaw cycles. A processing plant at the height of a salmon run does not operate that way. Arrival rate, queue length, chamber turnaround and door traffic all move at once, and they move the product's thermal history with them. This review proposes a break-point taxonomy for that regime. Five points at which cold chain integrity fails under load are mapped onto the quality-loss mechanism dominant at each, the indicator that makes the loss measurable, and the class of control that holds it. Twenty-nine sources published between 2015 and 2026 are cited, thirteen examined in full text. The penalty for the slower or less controlled route is large and consistent: mean ice crystal cross-sectional area of 939.6 µm² under air freezing against 86.5 µm² under immersion freezing at -40 °C, end-of-storage drip loss of 15.17% at -20 °C against 9.09% at -40 °C, and predicted remaining shelf life falling from 391 to 204 days across a four-stage warming chain. The review closes with a comparative matrix of control practice families and five named gaps, each with a first step.
The crisis of climate change today is a global issue in the 21st century. In developing countries as well as others around the globe, the challenge is for countries to develop their economies while simultaneously decreasing their GHG (greenhouse gas) emissions. Pakistan is one of the least polluters of all the countries of the world whose contribution to global GHGs is less than 1%, but unfortunately Pakistan is one of the countries that is most sensitive to climate change phenomena such as rising average atmospheric temperatures, floods, droughts, glacier shrinkage, and, most importantly, energy supply insecurity. Energy transition towards renewable energy, industrial modernization, policy reforms, transportation electrification, and climate finance have been addressed in this research study as critical parameters for assessing Pakistan's journey toward decarbonization and achieving net-zero emissions. The study examines Pakistan's emissions profile, energy consumption patterns across different sectors, the vast potential of renewable energy, and the country's climate change commitments under global agreements. The report further highlights obstacles created by inadequate and ineffective institutions, financial constraints, and the lack of appropriate technology to combat climate change. In recent years, total GHG emissions in Pakistan increased from 606 MtCO2e in 2021 to 609 MtCO2e in 2022, while fossil fuel-related GHG-CO2 emissions increased from more than 200 MtCO2e in 2021 to more than 204 MtCO2e in 2022. The study demonstrates that Pakistan has enormous renewable energy potential which, if harnessed through solar and wind energy, could revolutionize the country's energy sector. To achieve the long-term aspiration of "Net Zero," a holistic and time-bound approach, coupled with energy-efficient industrial development and climate finance support through global policy and regulatory frameworks, is essential.
The article examines the methodological transition from the use of standard accuracy metrics to risk-oriented modelling in the design of hybrid intelligent systems embedded in a management and control loop. The relevance of the approach stems from the fact that, in real processes, the quality of a solution is determined by the probability of undesired events, the magnitude of their consequences, and the speed of error detection and reversibility in the operational environment. The aim of the work is to translate the evaluation of intelligent models from the plane of numerical indicators into the language of systemic risk associated with people, infrastructure, and organisational procedures. The scientific novelty lies in integrating cost-sensitive error assessment, class imbalance analysis, and data shifts with an architectural description of hybrid (neuro-symbolic) systems, in which risk is distributed along the entire chain: data – model – rules – human – action. Accuracy metrics are proposed to be treated as particular input characteristics within a more general scheme for managing undesired events, defined by loss functions, barrier architecture, traceability, explainability, and controlled degradation modes. It is shown that, under class imbalance, label defects, and drifting data, the choice of metric and thresholds becomes a methodological decision that directly influences actual damage rather than a technical detail of the experiment. A conclusion is formulated on the necessity of shifting acceptance criteria from maximising aggregated metrics to constraining expected loss and ensuring risk controllability at the level of the hybrid system as a whole. The article is intended for researchers and engineers developing and deploying risk-sensitive intelligent systems in safety-critical and regulated domains.
The article examines the standardization of APIs and security protocols in the integration of banking payment solutions with retail partner infrastructure. The aim of the study is to systematize architectural, procedural, and security approaches that govern the boundary between banking payment platforms and retailer systems. The relevance of the topic stems from the growth of embedded finance, co-branded card programmes, and partner-facing banking platforms, where integration failures may affect revenue, trust, auditability, and regulatory exposure. The novelty of the article lies in the proposed core-and-periphery model, which separates the standardized banking core from the controlled customization zone of retail partners. The main findings show that mature integration architectures require OpenAPI-based contracts, TLS 1.3, mTLS, OAuth 2.x, OpenID Connect, FAPI profiles, JWS, JWE, ISO 20022, PCI DSS, ISO/IEC 27001, and NIST-aligned API security practices. The study concludes that scalable partner onboarding depends on reusable artifacts, certification gates, unified observability, SLOs, incident runbooks, and coordinated release governance. The article will be useful for researchers, banking architects, API security specialists, payment platform teams, and retail partners involved in embedded finance integrations.
With the advancement of industrialization, new energy vehicles (NEVs) have become crucial for mitigating air pollution and global warming, and the thermal management system (TMS) has emerged as a key component affecting vehicle safety, performance, and comfort. For battery electric vehicles (BEVs), the TMS has evolved from a set of decentralized auxiliary circuits into a vehicle-level energy dispatch hub. This paper examines the heat generation mechanisms, key components, and refrigerant/coolant paths of the battery, motor/drive, and cabin air conditioning subsystems, and compares the integrated architectures of Tesla, Xiaomi, and BYD. The analysis shows that integration, intelligent control, and working fluid substitution are the main optimization directions. Integration strategies include centralized octovalve, discrete multi-valve, and direct-cooling/direct-heating schemes. Intelligent control is moving from PID to model predictive control and reinforcement learning, while the natural refrigerants R290 and R744 offer advantages in wide-temperature adaptability and low-temperature performance, respectively. In addition, immersion cooling, composite phase-change materials, digital twins, and predictive thermal management are extending optimization from hardware and algorithms to materials, cloud, and life-cycle management. Ultimately, the future competitiveness of TMS will rely on unifying structural integration, intelligent control, and refrigerant switching into a coherent engineering system under the constraints of wide-temperature-range adaptation, high-performance chip cooling, and environmental regulations.
Effective time management is a critical factor in the successful delivery of construction projects. In the construction industry, project schedules are closely linked to workforce productivity, operational efficiency, and site safety. When projects are subjected to schedule pressures, workers may be compelled to accelerate tasks, overlook safety procedures, or operate under stressful conditions, thereby increasing the risk of accidents and injuries. This research investigates the impact of time management practices on safety performance in construction projects. It explores the role of scheduling techniques such as the Critical Path Method (CPM) and the Program Evaluation and Review Technique (PERT) in promoting safer project execution through enhanced coordination, monitoring, and resource allocation. Using secondary data from project management literature and scheduling-based Health, Safety, and Environment (HSE) planning studies, the research analyzes the relationship between project timelines and safety outcomes. The findings indicate that effective scheduling enhances safety awareness, reduces unsafe behaviors, and supports the successful implementation of HSE measures. The research concludes that incorporating safety considerations into project schedules is essential for minimizing workplace hazards and improving overall project performance.
The production and service has rapid change during past decade, which brings significant impacts to customer participating in such activity. This rapid development stimulates producers and customers simultaneously efforts in co-creation process for enhancing value of products and services. Co-creation is recognized as a resource integration process involving firms, suppliers, and customers that are guided business ecosystem. Through co-creation processes, the participators share their resources and knowledge during collaborative activities and interactions, termed co-creation practices. The study develops a contingency framework on how the service implementation drives co-creation in generating firm performance. We employ 127 service-oriented firm as our empirical analysis. Results indicate two service implementation activities (service quality and service innovation) that affect value co-creation. The value co-creation plays mediating role between service implementation and firms performance.
This article revisits and reanalyzes survey data originally collected for a 2013 doctoral dissertation on work competence and customer satisfaction in selected sports and fitness centers in Cebu City, Philippines. The purpose is not to describe the current state of the fitness industry, but to extract management implications from a legacy dataset and to place the findings in dialogue with recent research on fitness service quality, customer experience, and sport management competencies. A mixed-method approach combining quantitative and qualitative procedures was used to analyze data from 23 professionals and 35 customers across five fitness centers and sport clubs. Work competence was examined through core competencies and service quality, while customer satisfaction was assessed through quality of personnel, programs, and facilities. Results showed that both professionals and customers rated work competence as very good, and customers reported a very satisfied overall level of satisfaction. No significant relationships were found between demographic profiles and work competence or satisfaction. However, customers’ perceived work competence was positively associated with customer satisfaction. The difference between professionals’ self-assessment and customers’ evaluation of work competence was not statistically significant. The findings suggest that professional competence, communication, service responsiveness, program assessment, and customer-centered service design remain important managerial priorities for fitness service organizations.
The article examines the transformation of large language models from a single-query, single-response regime to a multi-agent configuration, in which a single external stimulus generates a tree of dependent calls to the model, and analyzes the specific constraints on scaling inference. The relevance of the study is determined by the proliferation of LLM-based agents and the growing share of workloads in which not the total number of tokens but the cadence of short iterations is decisive. The objective is to identify causal bottlenecks that determine throughput and tail latencies during the concurrent operation of multiple autonomous executors. On the basis of an analytic–synthetic review of 11 sources, a framework is proposed that shifts the unit of analysis from an individual response to a chain of dependent micro-steps, interpreted as competing job classes. The scientific contribution consists of systematizing the role of the KV cache as a dynamic scarce resource, introducing the phenomenon of contextual inflation, and linking these effects to batching policies, service fairness, distributed inference, and step routing across models of different sizes. It is shown that bottlenecks in multi-agent systems shift from arithmetic performance to memory, attention-state management, stopping discipline, and context engineering, while tail and network latencies take on the character of cascading lockups; the necessity of role-dependent token budgets and carefully designed eviction and state-folding strategies is substantiated. The article is intended for researchers and engineers developing LLM-based multi-agent systems and the infrastructure for their operation.
This article examines architectural mechanisms for preserving architectural consistency and system knowledge context during the transition to generative-oriented software development. The study adopts an analytical synthesis of recent empirical and review research, treating generative development as a system-level architectural process rather than a model-centric activity. The analysis builds on recent studies on the use of language models in architecturally significant engineering processes, as well as on approaches to explicit knowledge representation, architectural decision capture, and process-level governance of software development. It is shown that the risks of architectural degradation in generative development are driven not so much by the quality of individual generation outputs as by the absence of mechanisms for maintaining architectural invariants and causal relationships between requirements, decisions, and their implementation. The reviewed empirical evidence suggests that preserving repository-level architectural context improves the functional correctness of automatically generated artifacts; however, this effect does not extend to the level of system decomposition and inter-service interactions. Special attention is given to interpreting architectural consistency as a cross-cutting property of the development process, shaped by the interaction of external knowledge representations, architectural decision capture mechanisms, and managed process control loops. It is shown that none of these mechanisms in isolation ensures stable preservation of architectural integrity in generative development. The article may be of interest to researchers and practitioners in the fields of software architecture, architectural knowledge management, and the industrial application of generative technologies.
Concrete is the most important material used in many construction applications. The multistorey buildings are constructed of ordinary concrete, steel and other materials and are subjected to heavy loads requiring heavy construction and may not be cost effective. But the structural lightweight concrete produced using lightweight aggregates may reduce the dead load of the structure, so now a days it is used in construction of multistorey buildings. Concrete is considered as light weight concrete which has density of less than 2000 kg/m3. In this research, a G+10 multistorey plan irregular building is analysed with structural lightweight concrete using perlite as a fine aggregate and normal weight concrete using the Response Spectrum Method under different seismic zones and Time History Method for Bhuj earthquake. The parameters like storey displacement, storey drift, storey shear and overturning moments are considered and the results of NWC and SLWC buildings are compared. From the results obtained it is observed that seismic damages are considerably reduced in structural lightweight concrete buildings as compared to normal weight concrete buildings.
This research presents an integrated real-time geotechnical monitoring framework for the Diamer Basha Dam Project, combining UAV photogrammetry, GNSS networks, total station surveys, GIS-based deformation mapping, and geotechnical instrumentation (piezometers, inclinometers, extensometers, and crack meters). The research assesses excavation-induced deformation, blasting impacts, groundwater pressure fluctuations, and slope stability under complex geological conditions. Results show that the integrated approach enhances deformation prediction, improves slope safety evaluation, and supports effective risk management during the construction of large RCC dam projects.
The article examines risk-based qualification of dual-use refrigerated incubators using temperature bracketing and verification embedded into equipment lifecycle management. The relevance of the work stems from the need to simultaneously satisfy increasingly stringent GxP regulatory expectations and the demand for operational leanness in laboratory infrastructure, where the traditional V-model of validation results in an excessive volume of mapping activities. The objective of the study is to develop a scientifically justified qualification scheme that, with a minimal number of tests, enables reliable extrapolation of results between boundary and intermediate setpoints. The novelty of the approach lies in integrating engineering data on the thermal behavior of the incubator with the ASTM E2500 methodology and quality risk management principles, as well as in introducing the concept of dynamic qualification, which treats recovery rate as a critical quality attribute. Based on mapping at +5.0 °C and +57.5 °C using 15 calibrated data loggers, a performance envelope is established within which intermediate modes can reasonably be regarded as qualified; acceptance criteria, sensor placement schemes, and the logic of risk-based monitoring within the lifecycle framework are substantiated. The article is intended for validation and quality specialists, equipment engineers, authors of GxP laboratory procedures, and regulatory inspectors.
This study investigated the mentoring practices of Small and Medium Enterprises (SMEs) in Villa de Bacolor, Pampanga, and assessed their impact on organizational productivity, operability, and employee attributes. Mentoring was recognized as a strategic tool for enhancing SME resilience and competitiveness; however, limited studies had explored its structured impact within this region. Using a descriptive-correlational design as outlined by Creswell (2019), data were collected from 678 respondents (315 mentors and 363 mentees) drawn from a population of 8,158 individuals. This approach facilitated an analysis of mentoring practices and their relationship with SME productivity outcomes. Findings revealed that mentoring practices, particularly structured modules, mentor expertise, and consistent mentoring frequency, significantly enhanced strategic planning, market efficiency, operational processes, and financial productivity. Weighted mean scores demonstrated high satisfaction with mentoring across these dimensions. However, challenges were noted in areas such as adaptability to rapidly changing market conditions and sustaining the long-term benefits of mentoring programs. These challenges underscored the need for more dynamic mentoring strategies and ongoing support mechanisms to address evolving SME needs. The study highlighted the importance of structured, expert-led, and relationship-focused mentoring for SMEs, recommending tailored modules, regular mentor training, and continuous evaluation to address existing gaps. A strategic mentoring framework was proposed to sustain productivity gains and promote SME growth. Overall, mentoring was affirmed as a critical factor in enhancing productivity, adaptability, and competitiveness, positioning it as an essential component for SME development and economic contributions in Bacolor, Pampanga.
The article is dedicated to the explanation of architectural patterns that shape distributed energy management systems implemented through programmable logic controllers. Relevance is determined by the rapid spread of distributed renewable generation, storage units, and supervisory platforms across distributed energy sites, where stable operation increasingly depends on how heterogeneous components are coordinated rather than on the performance of any single device. Novelty lies in the interpretation of PLC-based energy management as a layered control environment in which signal validation, semantic normalization, communication mediation, mode logic, and predictive adjustment are structurally interconnected. The work describes the internal organization of these architectures and studies how control functions are redistributed between field devices, PLC loops, gateways, supervisory systems, and analytical layers. Special attention is given to interoperability under protocol fragmentation, export-limiting behavior, and the separation of control-critical data from telemetry streams. The work sets itself the goal of explaining how such architectures preserve stability under variability and partial degradation. Analytical review, comparative interpretation, conceptual grouping, and synthesis are used to solve this task. The conclusion describes the structural conditions of resilient design. The article will be useful for automation engineers, system integrators, and researchers working with hybrid distributed energy infrastructures.
Real-time financial decision systems depend on machine learning models that change after release because input data, customer behavior, and portfolio risk move faster than traditional model governance cycles. This article examines continuous integration and delivery for models used in credit, fraud, eligibility, and limit decisions. The aim is to build an analytical framework for CI/CD in financial machine learning without presenting experimental claims. The study draws on ten recent sources on MLOps, data quality, concept drift, non-traditional credit data, and AI risk governance. Comparative source analysis, conceptual synthesis, classification, and analytical generalization guide the work. The results define three requirements: controlled pipeline promotion for code, data, features, and model artifacts; monitoring that separates data failures from model deterioration; and release governance that connects automation with audit evidence. Practitioners can use the framework to design model promotion, rollback, threshold review, and real-time trace logging for financial decision services under supervisory oversight.
The adoption of new technologies and the use of Information and Communication Technology (ICT) are now recognized as a major contributor to change in the education sector because of its capacity to improve classroom instruction, increase learners' involvement and optimize learners' learning outcomes. Giftedness can, however, be felt differently across different contexts. The effective use of ICT in schools suffers from major challenges in the form of geographical isolation, mountainous topography, unstable electricity, limited internet connectivity and socio-economic constraints in GIBALT. The focus of this research is to examine the level of integration of ICT in public schools of Gilgit-Baltistan especially in Skardu and Ghanche districts. Skardu is relatively more urbanized and well connected, whereas, Ghanche is relatively more constrained due to its isolation and rurality. This research involves both qualitative and quantitative approaches where quantitative data are obtained using survey method and qualitative data using interviews and focus group discussion methods. The research explores the influence of ICT on teaching and learning processes and factors that can either hinder or facilitate this process. The expected outcome will provide guidance for policy makers, school administration, and educational leaders in developing infrastructure, training teachers, and creating an ICT strategy based on leadership. There is currently a gap in literature concerning the role of ICTs in remote and mountainous schools and the use of ICTs in education remains debatable.
This study examined the impact of the oil crisis on the lives and academic experiences of business students at the Nueva Ecija University of Science and Technology (NEUST) – Atate Campus, Palayan City, Nueva Ecija. It focused on students enrolled in the Bachelor of Science in Business Administration (BSBA) and Bachelor of Science in Entrepreneurship (BS Entrep) programs under the College of Management and Business Technology. The study aimed to determine the effects of the oil crisis in terms of transportation expenses, daily living expenses, financial stress, attendance, concentration, and academic performance, as well as the coping strategies employed by students. A quantitative descriptive research design was utilized, with data collected from 201 randomly selected respondents using a structured questionnaire with a four-point Likert scale. The findings revealed that students strongly agree that the oil crisis significantly affects their transportation expenses, daily living expenses, and financial stress. Meanwhile, the impact on attendance, concentration, and academic performance was found to be moderate. Students coped with these challenges by budgeting their allowance, reducing non-essential expenses, and seeking alternative transportation. The study recommends the implementation of support interventions to help students manage the challenges brought about by the oil crisis.
