This study aims to enhance the post-training evaluation of the annual performance agreement (APA) training organized by the Bangladesh Public Administration Training Centre (BPATC), the apex training institute for civil servants. Utilizing fuzzy-set qualitative comparative analysis (fsQCA) and artificial neural network (ANN) techniques within Kirkpatrick’s four-stage model framework, data were collected from a self-administered questionnaire survey of 71 in-service civil servants who participated in the APA training program. This study employs an asymmetric, non-linear model analyzed through a configurational approach and ANN to explore interrelationships among the four Kirkpatrick levels namely, reaction, learning, behavior, and results. Findings indicate that trainees were satisfied across all levels, identifying a non-linear relationship among these levels in post-training evaluation process. The research highlights that "learning skills" are most significant in the APA post-training evaluation, followed by behavior, results, and reaction. Theoretically, this research advances Kirkpatrick’s model and adds to the literature on public service post-training evaluation. Practically, it recommends prioritizing strategies that address cognitive barriers to enhance training effectiveness. This study’s innovative approach lies in its concurrent use of fsQCA and ANN methods to analyze the success or failure of APA-related trainees, offering alternative pathways to desired outcomes and contrasting traditional quantitative methods that provide a single solution. The findings have practical implications for public service training institutions and bureaucratic policymakers involved in capacity development, guiding the creation of more effective in-service training courses for public officials. The methodology and analysis can be applied in other contexts, allowing bureaucratic policymakers to replicate these findings in their learning institutes to identify unique configurations that lead to successful or unsuccessful training outcomes, adopt effective strategies, and avoid detrimental ones.

The Advanced and Predictive Analytics (APA) Software market is projected to reach $46.6 billion by 2033, growing at a CAGR of 13.9% from 2025 to 2033. This growth is attributed to the increasing demand for data-driven insights across various industries, including banking and financial services, insurance, and government. The ability of APA software to uncover patterns, trends, and anomalies in data enables businesses to make informed decisions, optimize operations, and improve customer experiences. The cloud-based deployment model is expected to gain traction, driven by the benefits of scalability, flexibility, and cost-effectiveness. The competitive landscape of the APA software market is fragmented, with established players such as IBM, SAS Institute, Microsoft, and SAP holding significant market shares. However, emerging vendors are offering innovative solutions and leveraging niche capabilities to gain a foothold in the market. Regional dynamics indicate that North America and Europe will continue to be prominent markets for APA software, while emerging markets in Asia-Pacific and the Middle East & Africa are expected to witness substantial growth in the coming years. The increasing adoption of cloud computing, advancements in machine learning and artificial intelligence (AI), and the growing need for data privacy and security are shaping the future of the APA software market.

OBJECTIVE: Disparities in how nursing faculty teach APA Style can confuse students and the librarians who help them. To clarify faculty expectations of and approaches to APA Style, this study seeks to answer the following questions: (1) What do nursing faculty perceive as the impact or value of APA Style? (2) How do nursing faculty teach and grade APA Style? By revealing the unspoken assumptions about APA Style and the value it adds to nursing education, it is hoped that health sciences librarians can more intentionally and effectively support this aspect of the nursing curriculum. METHODS: A mixed-methods study was designed to investigate potential gaps between nursing instructors' expectations for APA and their teaching/grading practices. The study incorporated an online survey of 75 nursing faculty at 14 Carnegie institutions with nursing programs, as well as qualitative interviews with 12 faculty at those institutions. A grounded theory approach was used to uncover salient themes. RESULTS: Nursing instructors consistently emphasized the importance of APA for referencing/in-text citations in both the survey and the interviews. When discussing the value of APA Style in nursing education, interviewees stressed APA Style as essential in developing professional nursing communication skills and evidence-based practice. However, faculty expectations for students' APA skills were not in line with their teaching and grading practices. CONCLUSION: Given the wide range of reporting teaching and grading practices for APA Style, nursing programs should work to clarify expectations for APA Style, and standardize how it is taught.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is APA Stock a Wise Investment? (APA)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Snapshot img

Data Center Power Market Size 2025-2029

The data center power market size is valued to increase USD 24.05 billion, at a CAGR of 10.8% from 2024 to 2029. Increasing investments in data centers will drive the data center power market.

Major Market Trends & Insights

North America dominated the market and accounted for a 29% growth during the forecast period.
By Product - Generators segment was valued at USD 6.89 billion in 2023
By End-user - IT and telecom segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 155.01 billion
Market Future Opportunities: USD 24.05 billion
CAGR from 2024 to 2029: 10.8%

Market Summary

The market is a dynamic and evolving sector, driven by increasing investments in data centers and high-performance computing (HPC) systems. According to recent reports, the market is projected to reach a significant market share by 2026, growing steadily due to the rising demand for cloud services and the increasing adoption of renewable energy sources. One of the major challenges in this market is the risk of UPS battery failure, which can lead to costly downtime and data loss.
However, opportunities abound, particularly in the adoption of advanced core technologies such as lithium-ion batteries and fuel cells, and the implementation of energy efficiency measures. Regulations, such as those mandating carbon reduction targets, also play a role in shaping the market landscape. For instance, in the European Union, the Energy Performance of Buildings Directive requires data centers to meet strict energy efficiency standards.

What will be the Size of the Data Center Power Market during the forecast period?

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How is the Data Center Power Market Segmented ?

The data center power industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Product

  Generators
  Transformers
  UPS
  Transfer switches and switchgears
  Others


End-user

  IT and telecom
  BFSI
  Energy
  Healthcare
  Retail


Services

  Design & Consulting
  Integration & Deployment
  Support & Maintenance
  Design & Consulting
  Integration & Deployment
  Support & Maintenance


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Product Insights

The generators segment is estimated to witness significant growth during the forecast period.

Data centers rely on generators as backup power sources during power outages. The selection of a generator depends on the required backup time and power capacity. Generators are categorized into gas, diesel, and bi-fuel types based on their fuel source. Enterprises consider fuel options to minimize generator operating costs. Currently, the market experiences significant growth. Approximately 30% of data centers worldwide have implemented generator installations, reflecting the increasing importance of an uninterrupted power supply. Moreover, the adoption of renewable energy sources in data centers has led to a 25% surge in the demand for generator installations.

Looking ahead, the market anticipates continued expansion. The market is projected to grow by 28% in the next five years, driven by the increasing digitalization of industries and the growing need for energy-efficient data center solutions. Power density, capacity planning, and cooling systems are essential components of data center design. Free cooling systems and liquid cooling technologies are gaining popularity due to their energy efficiency. Airflow management, rack power consumption, and power factor correction are other critical factors in optimizing power usage and cooling capacity. Energy storage systems, waste heat recovery, and electrical load balancing are essential for enhancing energy efficiency and reducing environmental impact.

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The Generators segment was valued at USD 6.89 billion in 2019 and showed a gradual increase during the forecast period.

Predictive maintenance, server power consumption, redundant power supplies, and precision cooling are vital strategies for managing power and maintaining optimal operating conditions. Electrical infrastructure, smart power distribution, UPS battery systems, critical power systems, and power monitoring systems are integral components of data center power management. Energy consumption monitoring and power quality are essential for ensuring efficient and reliable power management. Renewable energy sources, such as solar and wind, are increasingly being adopted to reduce carbon emissions and enhanc

The 6-Aminopenicillanic Acid (6-APA) market plays a pivotal role in the pharmaceutical industry, serving as a crucial intermediate for the synthesis of various antibiotics, particularly penicillin. As a primary building block for antibiotic production, 6-APA facilitates the development of effective treatments for ba

BackgroundNegative symptoms of schizophrenia are a range of deficits or losses in mental functioning associated with the disorder, including blunted affect, alogia, avolition, asociality, and anhedonia. These symptoms severely impact the quality of life of patients and hinder the recovery process. They significantly impair patients’ ability to live independently, maintain social relationships, and function effectively in society. However, current treatments for negative symptoms of schizophrenia are limited in efficacy and remain controversial. Cognitive-behavioral therapy (CBT) is a goal-oriented psychotherapy that aims to improve individuals’ emotional and psychological states by changing their negative thought patterns and behaviors. It helps patients identify and challenge irrational beliefs while promoting more positive behavioral changes through behavioral experiments and skills training. This study aims to conduct a meta-analysis to assess the effects of CBT on negative symptoms and function in schizophrenia.ObjectivesThis study aimed to investigate the effects of cognitive behavioral therapy on negative symptoms, mental function, social skills, and social functioning in schizophrenia.MethodsLiterature was retrieved from 10 databases (PubMed, EMBASE, Cochrane Library, Web of Science, APA PsycINFO, CINAHL, MEDLINE, CNKI, Wan fang Database and SinoMed,), with the search period ranging from the inception date to 1 September 2024. Two researchers independently conducted a literature review, data extraction, and risk of bias assessment. The quality of the included studies was assessed using the Cochrane Risk of Bias tool, and the meta-analysis was conducted using RevMan 5.3. The measurement outcomes include negative symptoms of schizophrenia, overall function, social skills, and social functioning.ResultThe analysis included a total of 15 studies involving 1,311 participants. All studies used the Positive and Negative Syndrome Scale (PANSS) as the assessment tool for measuring negative symptoms of schizophrenia. The results of the meta-analysis indicated that cognitive-behavioral therapy (CBT) significantly improved negative symptoms in patients with schizophrenia compared to treatment as usual (TAU) (MD = -1.65, 95% CI = -2.10 to -1.21, p 

Personality disorders (PDs) have a global prevalence of 7.8% and are associated with increased rates of morbidity and mortality. Most research on PDs has been conducted in High Income Countries (HICs). We conducted a systematic review to investigate the effectiveness of psychosocial and pharmacological interventions for personality disorders (PDs) in individuals from Low- and Middle-Income Countries (LMICs.) We systematically searched MEDLINE, Embase, APA PsycInfo, Web of Science, Cumulative Index of Nursing and Allied Health Literature (CINAHL), and The Cochrane Library from inception to January 5, 2023. Inclusion criteria were quantitative studies and grey literature where participants received a psychosocial or pharmacological intervention for PD. Exclusion criteria were qualitative studies, review articles, studies in which PD was not the primary condition, and articles not available in English. The Cochrane Risk of Bias tool version 2.0 and Joanna Briggs Institute instruments were used to measure risk of bias. Studies were pooled by type of study, PD investigated, type of intervention, assessment methods, and outcomes. Sixteen studies met inclusion criteria and were included. Fifteen were intervention studies related to borderline PD. Only one studied mixed PDs. Twelve studies were of psychotherapy, one pharmacotherapy, one combination of both, and two neurostimulation. Most of the studies showed improvement in symptoms though data was largely collected using self-report measures. There were only six RCTs. There is a dearth of literature on interventions for PDs in LMICs and funding bodies should prioritize research in LMICs. Systematic Review Registration Number: PROSPERO CRD42021233415.

Overview of included studies. Summary characteristics for the 29 included studies are provided in alphabetical order by first author’s last name.