Insufficient Capacity Research Articles

Application of Immobilized Microorganism Gel Beads in Black-Odor Water with High Nitrogen and Phosphorus Removal Performance

Black-odor water, which is caused by the excessive accumulation of nitrogen and phosphorus in water, is a significant problem. Immobilized microorganisms are considered to be an effective technical solution, but there are still many key parameters to be determined, such as organic matter dissolution, insufficient stability, and insufficient phosphorus removal capacity, among other problems. In this study, the optimum raw material ratios of immobilized microorganism gel beads were determined by means of a response surface experiment. The optimal ratio of raw materials was 5% polyvinyl alcohol (PVA), 1% sodium alginate (SA), and 6% bacterial powder. In addition, the nitrogen and phosphorus removal performance of the materials was improved by loading inorganic compounds, such as 0.5 wt.% zeolite, 0.5 wt.% iron powder, and 0.2 wt.% activated carbon. Tolerance analysis determined that these gel beads could maintain a good performance in a series of harsh environments, such as during intense agitation, at high temperatures, and at low pH values, etc. The total nitrogen (TN), ammonia nitrogen (NH3-N), and phosphorus (TP) removal efficiencies were 88.9%, 90%, and 95%.

Preparation of CS coated graded ordered porous ZrO2 implantable drug carrier

ZrO2 is bioceramic known for its excellent chemical stability and biocompatibility. Porous ZrO2, with its large surface area, has attracted considerable attention in the field of orthopedic implant drug delivery. However, the shortcomings of poor bioactivity and insufficient drug loading capacity in traditionally prepared porous ZrO2 limit its application. In this paper, graded ordered porous ZrO2 with interconnected open pores was prepared by colloid crystal templating, which exhibited large specific surface area and excellent slow-release properties. Then, it was surface-coated with chitosan (CS) possessing bioactivity and strong adsorption capacity. Factors affecting microscopic morphology, drug loading and slow-release properties of this composite were systematically investigated using ibuprofen (IBU) as a drug model. Results showed that graded ordered porous ZrO2 significantly enhanced drug loading capacity compared to normal ordered porous ZrO2, reaching 125.66 mg/g. Additionally, surface coating modification of the composite by CS significantly affected IBU loading capacity. By regulating process parameters such as CS concentration and coating time, high-efficiency loading of IBU was realized and drug loading capacity reached up to 194.17 mg/g. In vitro drug simulation experiments showed that CS coating effectively controlled the initial burst release of IBU and prolonged the effective release time; maximum cumulative release rate reached 93.7 %. This study provides a new idea for implantable drug sustained-release systems, which may better meet medical needs.

Integration of deep neutral network modeling and LC-MS-based pseudo-targeted metabolomics to discriminate easily confused ginseng species

Metabolomics covers a wide range of applications in life sciences, biomedicine, and phytology. Data acquisition (to achieve high coverage and efficiency) and analysis (to pursue good classification) are two key segments involved in metabolomics workflows. Various chemometric approaches utilizing either pattern recognition or machine learning have been employed to separate different groups. However, insufficient feature extraction, inappropriate feature selection, overfitting, or underfitting lead to an insufficient capacity to discriminate plants that are often easily confused. Using two ginseng varieties, namely Panax japonicus and P. japonicus var. major, containing the similar ginsenosides, we integrated pseudo-targeted metabolomics and deep neural network (DNN) modeling to achieve accurate species differentiation. A pseudo-targeted metabolomics approach was optimized through data acquisition mode, ion pairs generation, comparison between multiple reaction monitoring (MRM) and scheduled MRM, and chromatographic elution gradient. In total, 1980 ion pairs were monitored within 23 min, allowing for the most comprehensive ginseng metabolome analysis. The established DNN model demonstrated excellent classification performance (in terms of accuracy, precision, recall, F1 score, area under the curve, and receiver operating characteristic) using the entire metabolome data and feature-selection dataset, exhibiting superior advantages over random forest (RF), support vector machine (SVM), extreme gradient boosting (XGBoost), and multilayer perceptron (MLP). Moreover, DNNs were advantageous for automated feature learning, nonlinear modeling, adaptability, and generalization. This study confirmed practicality of the established strategy for efficient metabolomics data analysis and reliable classification performance even when using small-volume samples. This established approach holds promise for plant metabolomics and is not limited to ginseng.

Anti-progressive collapse performance and design method of novel T-stub connections

To address the insufficient anti-collapse capacity of T-stub connections due to premature failure, this study proposes a novel T-stub connection (NTC) by adding four V-shaped laminated plates. Monotonic loading tests are conducted on the T-stub web and V-shaped laminated plate to analyze the influence of geometric parameters on their deformation and load-bearing capacity. The working mechanism of NTC is investigated through the validated numerical models by analyzing the failure mode, impact force history, deformation pattern, internal force development, and energy dissipation. The research results indicate that, compared to the T-stub connection, the NTC exhibits two-phase failure characteristics, which begin with the fracture of the bolt-hole in the T-stub web, followed by the gradual straightening and eventual fracture of the V-shaped laminated plates. NTC undergoes three stages under impact loads: peak, oscillation, and platform stages. The addition of V-shaped laminated plates enhances the ductility of NTC by 93 %−130 % and its energy dissipation capacity by 189 %−235 %. This significant enhancement in deformation and energy dissipation capabilities can be attributed to the addition of the V-shaped laminated plates. The deformation and bearing capacity calculation formulas for both the T-stub web and V-shaped laminated plate are provided. Additionally, a design method for NTC is proposed based on theoretical analysis, and its rationality is verified through numerical examples involving three different sets of beam and column sections.

Telementoring to Strengthen Child and Youth Mental Health Care Capacity in Primary Care Providers: Session Duration and Learning Outcomes.

Primary care providers (PCPs) report insufficient capacity for child and youth mental health care (CYMH). The telementoring program Project ECHO (Extension for Community Healthcare Outcomes) can build capacity, but 75- to 120-minute sessions are a participation barrier. Using a Lean health care paradigm, we designed a 60-minute session, and compared self-reported CYMH capacity strengthening (10 constructs) and satisfaction between 60- and 90-minute sessions. Pre-post (n = 139) and post-cycle (n = 146) survey data were analyzed using generalized linear mixed-effects logistic regression. Capacity strengthening was demonstrated when analyzing both groups together (all Ps ≤ .002). Session duration did not affect capacity strengthening for 9/10 constructs (all Ps > .05), but medication management development was higher with 90-minute sessions (P = .002). Satisfaction was high in both groups. The 60-minute ECHO CYMH sessions can be used without negative learning outcomes, but more mentoring may be needed to build capacity for psychopharmacologic treatment.

Spatial-frequency parallel subsampling for distributed compressive sensing in ultrasonic imaging inspection

To address the problem of the high hardware requirements and insufficient data storage capacity in current ultrasonic imaging testing, a novel approach is developed using a programmable device, which combines spatial-frequency parallel subsampling with the distributed compressive sensing simultaneous orthogonal matching pursuit (DCS-SOMP) algorithm to achieve fast and high-quality ultrasonic imaging inspection with a small amount of subsampled data. The spatial sparse measurement method was employed to achieve spatial subsampling and minimize the count of signals. Additionally, frequency subsampling was utilized to significantly reduce the data volume of time-domain signals while ensuring signal quality by truncating the primary testing frequency components. The subsampled data was then reconstructed using distributed compressive sensing (DCS) for multi-channel data reconstruction. The experiment of ultrasonic scanning imaging was conducted on a carbon steel specimen containing six transverse through-holes with a diameter of Ф1.5 mm at different depths. The ultrasonic signals were acquired using the spatial-frequency parallel subsampling method, and subsequently reconstructed using the DCS-SOMP algorithm. The results show that the proposed method achieves comparable image quality to that obtained with complete data, using only 1/8 of the complete data, while accurately locating and quantifying defects.

Service restoration in distribution systems considering priority customers and microgrids

Service restoration (SR) consists of automatically generating and executing a plan to restore the service in healthy zones using the least number of maneuvers after detecting and isolating a permanent fault in the distribution system zone. This component is essential to self-healing functionality in smart grids and allows customers to reconnect quickly to the distribution grid after a power outage. Distributed generation (DG) supports the distribution network when there is insufficient capacity to restore all zones out of service or supply the loads locally through microgrids. The power supply must be restored to the highest priority customers in case of partial restoration. Also, most research works use simplified or linearized models to propose restoration algorithms. This paper proposes a complete AC formulation for the service restoration problem in distribution systems considering network reconfiguration (NR), the integration of distributed generation (DG), and priority customers (PCs) into the solution. The optimization problem is solved by a centralized algorithm based on combining the Differential Evolution (DE) and Continuous Population-Based Incremental Learning (PBILc) metaheuristics techniques. Simulation results are presented for three case studies in which the IEEE 33-bus distribution system is tested for different fault scenarios. The numerical results show the robustness and efficiency of the proposed algorithm.

Predicting the roadway width of forest roads by means of airborne laser scanning

Modern forestry relies on an extensive network of well-maintained forest roads. However, the trafficability of forest roads can be limited by poor construction or by insufficient load-bearing capacity caused by, for example, weather conditions. In all forestry operations, the forest roads should be able to support heavy vehicles during the transport of roundwood and harvesting machinery, so logistics must be carefully planned to ensure good road trafficability. To facilitate this planning, it is necessary to know the various characteristics of the forest road in terms of its width, structure and load-bearing capacity. Obtaining such information using remote sensing data would be beneficial. In this study, we used airborne laser scanning (ALS) data to assess the width of the roadway on forest roads. We developed several algorithms that were used to assess roadway width based on the cross-sectional data (derived with ALS) of the roads in 8-m long segments. The ALS echoes within the segments were classified into 20 cm wide strips which the algorithms then analyzed in a stepwise manner. Both height and intensity information from the ALS data were utilized. The algorithm results were then used as predictors in linear models to predict the roadway width. The main focus was on the road level, i.e., aggregated values from 25 different roads were used in model fitting. In terms of root mean square error (RMSE) values, accuracies of approximately 20–30 cm (or 7–10 %) were obtained for the predicted roadway widths with a separate validation data. This level of accuracy can be considered adequate given the characteristics of the ALS data used in the modelling. The results indicate that the presented approach has potential for practical applications to predict the width attributes of forest roads.

Comprehensive performance analysis and optimization for PEMFC-heat pump combined system considering dual heat source

Traditional proton exchange membrane fuel cell (PEMFC) systems face the challenges of strong thermal–electrical coupling and insufficient heating capacity. This study proposes a PEMFC–heat pump combined system considering dual heat source, which effectively utilizes fuel cell waste heat and environmental heat to achieve significant improvements in thermal–electrical decoupling and heating capacity. Energy, economic, and environmental analysis models were established, and the effects of key parameters on the combined system were systematically analyzed, followed by multi-objective optimization. Results show that the PEMFC current density has the largest effect on the heating capacity, while the heat flow ratio exerts the strongest influence on economic performance. The minimum pollutant emissions are achieved when wind power is adopted for hydrogen production. Under an ambient temperature of 248.15 K, the combined system increases the heating capacity by 12.8 % and reduces the levelized cost of energy and greenhouse gas emissions by 7.85 % and 15.9 %, respectively. The optimal solution presents a strong nonlinear relationship with the PEMFC current density and condenser undercooling, the heat flow ratio is close to the upper limit (0.99), and the operating temperature is close to the lower limit (333.4 K). These findings provide innovative thermoelectric decoupling and efficient energy supply solutions for PEMFC systems and have important implications for accelerating the low-carbon transition of regional energy systems.

Dilemmas and Breakthroughs in the Application of the Principle of Common but Differentiated Responsibilities in the Context of COP28

The 28th Conference of the Parties to the United Nations Framework Convention on Climate Change (UNFCCC) to be held in Dubai, UAE, in 2023 has reached the “UAE Consensus”, which symbolizes that the principle of common but differentiated responsibilities has entered into a new stage, presenting a new pattern of flexibility, procedure and dynamism. However, the problems that still exist in the Conference mean that the principle of common but differentiated responsibilities is still in the process of being realized, and there are still dilemmas such as uncertainty about the legal attributes of the principle, the lack of a specific system to ensure its implementation, and the insufficient capacity of developing countries in terms of financial and technical support. Based on the above, we would like to put forward some suggestions for improving the application of the principle of common but differentiated responsibilities in China: firstly, the status of the principle should be clarified; secondly, a system should be set up to ensure its implementation; and lastly, the provisions on capacity-building for developing countries in terms of financial support and technical assistance should be fine-tuned. Under the current situation, guaranteeing the realization of the principle of common but differentiated responsibilities will be of great significance to the containment and improvement of global climate change.

Exploring cognitive load through neuropsychological features: an analysis using fNIRS-eye tracking.

Cognition is crucial to brain function, and accurately classifying cognitive load is essential for understanding the psychological processes across tasks. This paper innovatively combines functional near-infrared spectroscopy (fNIRS) with eye tracking technology to delve into the classification of cognitive load at the neurocognitive level. This integration overcomes the limitations of a single modality, addressing challenges such as feature selection, high dimensionality, and insufficient sample capacity. We employ fNIRS-eye tracking technology to collect neural activity and eye tracking data during various cognitive tasks, followed by preprocessing. Using the maximum relevance minimum redundancy algorithm, we extract the most relevant features and evaluate their impact on the classification task. We evaluate the classification performance by building models (naive Bayes, support vector machine, K-nearest neighbors, and random forest) and employing cross-validation. The results demonstrate the effectiveness of fNIRS-eye tracking, the maximum relevance minimum redundancy algorithm, and machine learning techniques in discriminating cognitive load levels. This study emphasizes the impact of the number of features on performance, highlighting the need for an optimal feature set to improve accuracy. These findings advance our understanding of neuroscientific features related to cognitive load, propelling neural psychology research to deeper levels and holding significant implications for future cognitive science.

Soil conservation and water conservation services and trade-offs following the land consolidation project: a case study of Yan’an city, China

The Loess Plateau is an important region for soil and water conservation and ecological construction in China. Exploring the spatio-temporal variations in soil conservation and water conservation services and their relationships in Loess Plateau under the background of land consolidation projects is of great significance for ecological protection and quality development in the Yellow River Basin. Taking Yan’an city as the research area, this paper used the InVEST model to quantitatively evaluated spatio-temporal variation characteristics and trade-off/synergy relationship of the soil conservation and water conservation services from 2010 to 2018. According to the implementation data, the relationship between the gully control and land consolidation (GCLC) project in various counties of Yan’an city and soil conservation and water conservation service was analyzed. The results showed that the total amount of soil conservation services in Yan’an City were 4.07 × 106 t and 3.75 × 106 t in 2010 and 2018 with a decrease of 7.76%, and with low spatial clustering characteristic. The total amount of water conservation services were 2.01 × 1010 mm and 2.03 × 1010 mm in 2010 and 2018 with a increase of 0.56%, and with high spatial clustering characteristic. There is a synergistic relationship between soil conservation and water conservation services in most area of Yan’an city. From 2010 to 2018, the effect of the GCLC projects on soil conservation and water conservation services in Yan’an city is not significant. The GCLC project can effectively alleviate the situation of sharp decline of cultivated land area and insufficient food production capacity.

Can global health security frameworks measure One Health implementation in West Africa?A mixed-methods study

BackgroundThe 2014 outbreak of the Ebola virus disease highlighted the importance of overhauling and transforming healthcare systems in West Africa to improve the ability of individual countries to deal with infectious diseases. As part of this effort, in November 2016 the West African Health Organization (WAHO) began the process of institutionalizing the One Health (OH) approach to health security across the Economic Community of West African States (ECOWAS). The lack of clear metrics and evaluation frameworks to measure the progress of OH implementation in West Africa has been reported as a challenge. Therefore, this study sought to assess and explore whether the existing metrics of global health security frameworks can measure the successful implementation of OH activities, evaluate the progress made since 2016, and identify key areas for improvement in the region.MethodThe study employed predetermined keywords to select indicators from the International Health Regulations (IHR) Monitoring Frameworks, specifically the State Party Self-Assessment Annual Report (SPAR) and Joint External Evaluation (JEE), deemed relevant to the OH approach. In addition, the COVID-19 performance index scores (severity and recovery) for June 2022 were extracted from the Global COVID-19 Index (GCI). The GCI Recovery Index evaluated the major recovery parameters reported daily to indicate how a country performed on the path to recovery from the COVID-19 pandemic compared to other countries. National documents were also analyzed using categorical variables to assess the performance status of OH platforms across implementing countries. A quantitative analysis of these indicators was conducted and supplemented with qualitative data gathered through interviews with key stakeholders. Between March and April 2022, we conducted 18 key informant interviews with purposively selected representatives from regional governmental agencies and international multilateral agencies, including ECOWAS member states. Interviews were conducted online, transcribed, and analysed following the tenets of thematic analysis.ResultsOur quantitative analysis revealed no significant association between the implementation status of OH activities and any of the selected indicators from SPAR and JEE. The descriptive analysis of the JEE scores at the country level revealed that countries with existing OH platforms scored relatively higher on the selected JEE indicators than other countries in the pre-implementation stage. OH implementation status did not significantly affect COVID-19 recovery and severity indices. The qualitative findings with relevant stakeholders revealed noteworthy challenges related to insufficient human capacity, inadequate coordination, and a lack of government funding for the sustainability of OH initiatives. Nonetheless, countries in the ECOWAS region are making progress toward the integration of OH into their health security systems.ConclusionStandardized metrics were used to assess the implementation and efficacy of OH systems in the ECOWAS region. Current indicators for monitoring global health security frameworks lack specificity and fail to comprehensively capture essential OH components, particularly at the sub-national level. To ensure consistency and effectiveness across countries, OH implementation metrics that align with global frameworks such as IHR should be developed.

Linear Active Disturbance Rejection Control for Flexible Excitation System of Pumped Storage Units

The role of pumped storage in global energy structure transformation is becoming increasingly prominent. This article introduces a flexible excitation system based on fully controlled device converters into pumped storage units (PSUs). It can address the issues of insufficient excitation capacity and limited stability associated with traditional thyristor excitation systems. The study focuses on linear active disturbance rejection control (LADRC) for the flexible excitation control system of pumped storage units and utilizes intelligent optimization algorithms to optimize the controller parameters. This addresses the inherent problem of traditional PID controllers, which are unable to alleviate the trade-off between response speed and overshoot. At the same time, the robustness and anti-interference of the control system are improved, effectively enhancing the performance of the pumped storage flexible excitation control system. Simulation verifies the feasibility and superiority of the proposed method.

A multi-scale attributes fusion model for travel mode identification using GPS trajectories

ABSTRACT Travel mode recognition is a key issue in urban planning and transportation research. While traditional travel surveys use manual data collection and have limited coverage, poor timeliness, and insufficient sample capacity, recent advancements in Global Positioning System (GPS) technology allow large-scale data collection and offer novel opportunities to enhance travel mode recognition. However, existing studies often neglect regular differences and changes in motion states across different travel modes and fail to fully integrate multi-scale spatio-temporal features, which limits the accurate classification of travel modes. To fill this gap, this study proposes a multi-scale spatio-temporal attribute fusion (MSAF) model for precise travel mode identification using solely GPS trajectories without altering their sampling rate. The MSAF model segments GPS trajectories into various temporal and spatial scales, extracting local motion states and spatial features at multiple scales. The spatio-temporal feature extraction module is constructed to extract local motion states and capture spatio-temporal dependencies. Additionally, the model incorporates a multi-scale feature fusion module, which effectively combines features of various scales through a series of fusion techniques to obtain a comprehensive representation, enabling automatic and accurate travel mode identification. Experiments on real-world datasets, including the GeoLife Trajectories dataset and the Sussex-Huawei Locomotion-Transportation (SHL) dataset, demonstrate the effectiveness of the MSAF model, achieving a competitive accuracy of 95.16% and 91.70%. This represents an improvement of 2.50% to 7.95% and 0.8% to 6.62% over several state-of-the-art baselines, effectively addressing sample imbalance challenges. Moreover, the experiments demonstrate the significant role of multiscale feature fusion in improving model performance.

Advancement of Bioenergy Technology in South Africa

South Africa has been experiencing an energy crisis since 2007 and continues to the present. This has resulted in load-shedding (action to interrupt electricity supply to avoid excessive load on the generating plant). One way to address this problem is to further explore the potential and contribution of bioenergy through research conducted and implementing energy reports. Therefore, the study aims to provide the state of bioenergy and its contribution to the country’s economic sector and to enhance the replacement of fossil fuels with bioenergy resources and technology. A total blackout of 15,913 h has been experienced since 2014, according to the weekly system status report released by ESKOM. The power utility (Eskom) responsible for power generation and utility has attributed this problem to insufficient generation and capacity. Based on this, the country is embarking on solving this problem. Although the country is dominated by coal (fossil fuel), constituting 73.8% of the total energy supply, this poses a serious environmental risk and health hazard. Renewable energy is considered an alternative energy source, and its introduction and implementation look promising in reducing and solving the current energy crisis. With abundant renewable energy potential, representing 8.7% of the total energy supply, around 85% is bioenergy. This review’s findings revealed that bioenergy contributed mainly towards heat, and fuels admit other energy sources, which is recommended. Therefore, its deployment on a large scale is promising and possible. This study will guide and further encourage the deployment of bioenergy projects in South Africa.

School health and nutrition services for children and adolescents in Tanzania: A review of policies and programmes.

School health and nutrition programmes are effective strategies to address the health problems among school-going children and adolescents. We examined the policy environments, successesand bottlenecks associated with school health and nutrition programmes in Tanzania. We used the 'policy triangle framework' to examine 22 national and regional school health and nutrition policies and programmes in Tanzania. We also interviewed 16 key informants to gain further insights into school health and nutrition programmes. Several school health and nutrition policies in Tanzania outline the basic elements of school-based health and nutrition services. Yet, these documents neither recognise vulnerable groups, recommend age-appropriate strategies to address children's and adolescents' varied and transient needs, nor provide a framework for implementing and tracking recommended activities. In these documents, underweight and infectious diseases, including humanimmunodeficiency virus/acquired immunodeficiency syndrome, are frequently identified as major concerns of young people, with little or no consideration of social determinants. Diverse strategies including school feeding, water and sanitation services, health and nutrition educationand promotion of healthy behaviours are identified. In doing so, these documents adequately define the roles and responsibilities of all government actors, but young people and their guardians are not actively engaged in design and implementation. Additionally, there are several challenges to implementing these policies including budgetary constraints, limited resources, a lack of inter-sectoral coordinationand insufficient capacity within targeted schools. To improve the health and nutritional status of school-going children and adolescents in Tanzania, adequate budgets, strengthened coordination and implementation efforts, the development of school-based stakeholders' capacity, as well as the involvement of all other stakeholders, including adolescents, are imperative.

Study on debris flow discharge characteristics of check dam spillway

After a check dam is filled with sediment, the debris flow will flow out from the spillway. Insufficient discharge capacity of the spillway can lead to debris flow scouring the dam's shoulder and foundation. Therefore, it is necessary to study the discharge capacity of the spillway. It is of great importance for further optimizing the structural design of the check dam. This article analyzes discharge characteristics of debris flow of a spillway through a series of flume experiments. According to the motion states, it can be divided into five stages: contact stage of the spillway, flushing and climbing stage, increasing and reflux stage, stable discharge stage, and final discharge stage. We analyzed the influencing factors of the discharge capacity, including the type of spillway, bulk density of debris flow, scale of debris flow, flume gradient, and effective opening width of the spillway. Furthermore, we derived a calculation formula of discharge for the spillway based on Bernoulli's principle. Finally, we considered the influence of the ratio of flow area and Froude number to the discharge coefficient and established a calculation method of discharge. Consequently, we compared the calculated results with the measured results and found them to be in good agreement. Our research results provide a quantitative calculation method for the design of spillways and energy dissipation and erosion prevention projects under check dams, which is beneficial for improving engineering value and for better serving disaster prevention and reduction efforts.

Seismic Assessment of an Old Historical Unreinforced Masonry Power House Building

Abstract Design of unreinforced masonry buildings is a major concern in seismically active zones in Nepal. The ChandraJyoti Jalvidhyut Power House, a historical landmark in Nepal, represents the nation’s pioneering effort in hydropower generation and signifies its rich cultural heritage. This study comprehensively assesses the structural assessment and seismic performance deficiencies of the ChandraJyoti Jalvidhyut Power House. Material tests on bricks with the individual properties and behaviour of construction materials were done. Utilizing a finite element model in DIANA software V 10.5, the structure’s response under pushover loading conditions is simulated, providing insights into its structural behaviour. Additionally, fragility curves are developed to correlate earthquake intensity with the probability of damage, offering essential information for preservation strategies and seismic risk mitigation. The compressive strength test of bricks, with a value of 9.6 MPa, falls short of the 10 MPa minimum requirement specified by NBC 203:2015, indicating insufficient load-bearing capacity. The building’s pushover analysis shows that the longitudinal direction experiences higher lateral forces (base shear of 945.87 kN) and greater drift ratios exceeding 0.4%, which increases the likelihood of cracks compared to the transverse direction (base shear of 826.77 kN). The analysis also highlights significant nonlinear behavior in both directions, with maximum roof displacements of 35.18 mm (transverse) and 34.4 mm (longitudinal), reflecting the impact of structural irregularities.

PUBLIC ADMINISTRATION REFORM: AN IMPETUS FOR GOOD GOVERNANCE AND POLITICAL SECURITY IN NIGERIA

Over the last decade, the Nigerian government has undertaken a wide ranging policy, institutional, and legal initiatives to enhance the country’s public service delivery. Despite these efforts, the nation has grappled with a myriad of issues that still undermine good governance and political security. These challenges include weak institutional capacity, corruption, poor leadership, inadequate public service delivery, political instability, limited resources, poor infrastructure, and a shortage of skilled human resources. This paper examines the strategies and mechanisms employed by public administrators in Nigeria to enhance good governance and political security, analyses the impact of effective public administration on political stability and security and identifies the challenges affecting the implementation of good governance principles through public administration in Nigeria. The study has adopted the New Public Management Theory proposed by Hood in 1991 and relied on secondary data. Findings from the study show that Nigerian public administration has undergone a series of reforms to enhance good governance and political security through various strategies and mechanisms such as capacity building, international cooperation, and ethical conduct. The study also reveals that corruption and lack of accountability, bureaucratic bottlenecks and insufficient capacity among others have been identified as challenges of the implementation of good governance principles in Nigeria. The paper recommends that the encouragement and promotion of transparency and accountability be given top priority; citizen participation should also be encouraged in the planning and decision-making process; empowering local governments through the allocation of adequate resources to foster political security. The paper also recommends the establishment of a proper recruitment base to promote professionalism and meritocracy in the public service.