Global Strategy Group

During the coronavirus disease 2019 (COVID-19) outbreak, negative-pressure rooms were implemented to isolate high-risk COVID-19 patients. This study compared pneumonia patient outcomes before and after their implementation, focusing on in-hospital mortality as the primary outcome. We conducted a retrospective cohort study of adult pneumonia patients admitted to a tertiary hospital in Northern Thailand, excluding those with trauma-related illness, out-of-hospital cardiac arrest/in-hospital cardiac arrest, or incomplete data. The primary outcome was in-hospital mortality, and the outcomes were door-to-first doctor contact time, door-to-antibiotic time, emergency department (ED) length of stay (LOS), intensive care unit (ICU) admission, and 30-day mortality. Data from 220 pneumonia patients (104 pre-pandemic, 116 pandemic) were analyzed. Of these, 58.6% were elderly males with comorbidities like hypertension and diabetes. Door-to-first doctor contact time was longer during the pandemic (median, 1 vs. 0 minutes; P<0.001), as was ED LOS (median, 5.9 vs. 4.1 hours; P<0.001). Door-to-antibiotic time was also longer in unadjusted comparisons (median, 60.0 vs 36.5 minutes; P<0.001), but the difference was attenuated and not statistically significant after adjustment (adjusted mean difference, 14.2 minutes; P=0.071). No significant differences in in-hospital mortality, 30-day mortality, or ICU admissions were observed. Negative-pressure rooms led to increased door-to-doctor contact time and ED LOS during COVID-19, although without significant differences in mortality. These findings highlight the need to improve ED workflows for future pandemic preparedness.

The process of Timor-Leste's independence from Indonesia has not only shaped the dynamics of the XXI century global landscape. Still, it has also been a historical reality influenced by internal and external factors, notably Australian support - a traditional middle power. However, the achievement of Timor-Leste's independence has challenged Australia's relations with Indonesia. Despite being the least developed country in Southeast Asia and grappling with economic struggles, Timor-Leste aspires to overcome these hurdles after 19 years of independence and build a prosperous and robust nation, as outlined in the Timor-Leste Strategic Development Plan extending until 2030. The paper aims to evaluate the issues of Timor-Leste in the twenty-first century, considering geopolitical conditions, post-independence impacts, and issues related to international integration.

This paper investigates the complementarity between business training and timely access to financial capital for small and medium enterprises (SMEs) in Kenya. All participants in the business support program we study are offered training. One-third of participants are offered loans immediately after training ( Concurrent Loan group), one-third are offered loans six weeks after training ( Delayed Loan group), and the remaining third are offered loans after another four weeks ( Control group). While a long time lag may reduce knowledge retention and application among SMEs, concurrent access to loans and associated business spending may divert the entrepreneurs’ attention away from improving business practices. We find evidence for the latter in both intention-to-treat and treatment-on-the-treated estimates. While SMEs in both Control and Delayed Loan groups improve their business practices, SMEs in the Concurrent Loan group who take loans do not improve their practices at all. Moreover, entrepreneurs who take loans spend less time on their businesses and experience declines in their business revenue. • Providing loans immediately after business training reduces improvements in business practices for small and medium enterprises. • A delayed access to loans after training helps entrepreneurs to focus on implementing training lessons. • Access to loans reduces the time treated entrepreneurs spend on their businesses and lowers business performance.

Enterprises face sustained pressure to improve service delivery speed, quality, and cost while managing workforce constraints and rising service complexity. Traditional rule-based automation improves efficiency at isolated task levels but fails to scale across end-to-end service operations. This paper examines how AI enabled service automation transforms operational service delivery by reducing manual effort, increasing throughput, and reallocating human capacity toward higher value activities. A reference architecture is presented that integrates intelligent intake, machine learning driven decision engines, workflow orchestration, and human in the loop governance. A quantitative productivity measurement model links automation coverage to service throughput, cycle time reduction, backlog stabilization, and effective full time equivalent capacity release. Enterprise service scenarios across IT operations, customer support, and shared services are evaluated to demonstrate measurable productivity gains. Results indicate that organizations adopting AI enabled service automation achieve significant reductions in manual touchpoints while improving service reliability, workforce utilization, and operational resilience.

ABSTRACT BackgroundThe United States (U.S.) Food and Drug Administration (FDA) conducts Good Clinical Practice (GCP) inspections to evaluate regulatory compliance, assess clinical trial conduct, and verify data integrity in support of marketing applications. To date, there has been no comprehensive assessment of the geographic distribution or extent of such inspections conducted during the marketing application review. MethodsWe conducted a retrospective analysis of FDA GCP inspection records involving clinical investigators (CIs), sponsors, and contract research organizations (CROs) associated with marketing applications submitted during fiscal years 2016 to 2018. ResultsA total of 1,275 GCP inspections were performed in support of 347 marketing applications during the study period. Inspections covered CIs (86%), sponsors (10%), and CROs (4%). On average, three CIs were inspected for each application. Most CI inspections (63%) were conducted within the U.S., with the remainder primarily in Europe. Of the 347 applications, 36% had sponsor inspections and 15% CRO inspections; the majority of these were conducted in the U.S. (&amp;gt;80%). Approximately 4% of U.S.-based and 2% of non-U.S.-based CIs were inspected. CI inspections covered about 10% of enrolled trial participants overall (14% U.S. vs. 8% non-U.S.) and included review of approximately 5% of source records (8% U.S. vs. 3% non-U.S.). ConclusionsWhile the total number of inspections and source records reviewed varied by year, the distribution of inspection types, participant coverage, and source document review percentages remained consistent. Most inspections were conducted in the U.S., where CI inspections also covered a higher proportion of participants and source data.

Solar technologies have been associated with private and social returns, but their technological potential often remains unachieved because of persistently low demand for high-quality products. In a randomized field experiment in Senegal, we assess the potential of three types of quality signaling to increase demand for high-quality solar lamps. We find no effect on demand when consumers are offered a money-back guarantee but increased demand with a third-party certification or warranty, consistent with the notion that consumers are uncertain about product durability rather than their utility. However, despite the higher willingness to pay, the prices they would pay are still well below market prices for the average household, suggesting that reducing information asymmetries alone is insufficient to encourage wider adoption. Surprisingly, we also find that the effective quality signals in our setting stimulate demand for low-quality products by creating product-class effects among those least familiar with the product. • Quality signals have the potential to increase demand for off-grid solar technology. • Money-back guarantee has no effect on the demand for high-quality solar lamp. • Third-party certification and 2-year warranty increase willingness to pay by 12–14 %. • Effective quality signals also stimulate demand for uncertified low-quality product.

Abstract Farmer seed purchase patterns historically drive end‐use quality into a subordinate position to yield enhancement and protection in hard red winter (HRW) wheat ( Triticum aestivum L.) breeding programs. Evolving consumer food purchase decisions could conceivably swing this priority pendulum back near the center. ‘Paradox’ (Reg. no. CV‐1223; PI 705146), ‘Breadbox’ (Reg. no. CV‐1221; PI 705144), and ‘Firebox’ (Reg. no. CV‐1222; PI 705145) HRW wheat cultivars were developed with magnified dough strength as the first breeding priority and released in 2023. Our objectives herein were to document their novel rheology relative to contemporary HRW wheat, determine correlated changes in agronomic performance, and assess Paradox's potential as a strengthening component in bread flour blends. Marker‐assisted backcrossing with Glu‐B1al as the molecular target was conducted through the BC 2 F 2 generation, from which experimental lines OK15MASBx7 ARS 8–29 (Paradox), OK15MASBx7 ARS 8–20 (Breadbox), and OK15DMASBx7 ARS 6–8 (Firebox) were derived via conventional inbreeding or doubled haploidization. Relative to the HRW controls, Paradox and Breadbox produced a sevenfold greater peak time and fourfold greater stability time, whereas changes in Firebox were more moderate but still superior to the HRW controls. None of the cultivars was diminished for agronomic or milling characteristics, and their novel dough strength was unrelated to grain protein concentration. All three cultivars have entered non‐commoditized supply chains as ingredient flour intended for products requiring more gluten strength, including many formulations for pan bread.

The paper explores the impact of artificial intelligence (AI) on data licensing practices, particularly in the financial services. The authors discuss the rapid emergence of the technology and the resulting pressures on the data providers and looks to answer the question of whether existing data licensing frameworks need a fundamental re-think or can be adapted or maintained. The scope of the paper includes examining the use of market data in the financial markets, highlighting the complexities. The reader can expect to take away a good understanding three distinct types of data licensing (individual, application and redistribution) and the principles underpinning them giving ‘real’ examples to help with that understanding. The paper then goes on to discuss the relationship between AI technologies and the long-established data licensing practices and how at the heart of everything is the use case or how the authors refer to it as the ‘what not the how’. This article is also included in The Business &amp; Management Collection which can be accessed at https://hstalks.com/business/.