For more than two decades, global malaria reports have presented an encouraging narrative: expanding programme coverage, billions invested, and steady declines in mortality. Yet those who spend their evenings beside light traps and breeding sites often see a more complicated reality. Beneath the reassuring graphs lies a persistent operational question: Are we winning the fight against malaria, or are we simply becoming better at reporting progress while our ability to measure it remains uncertain? The 2025 Africa Malaria Progress Report captured this tension candidly, noting that "behind the figures lies a stark truth: we remain off-course and the 'perfect storm' of threats has intensified." I argue that the problem confronting malaria control today is not merely financial or clinical. Rather, it is structural. Modern malaria programmes rely overwhelmingly on two tools: Long-lasting insecticidal nets and indoor residual spraying. Both interventions have saved countless lives, but neither was ever designed to carry the entire burden of vector control indefinitely. Under sustained pressure, mosquito populations are responding exactly as evolutionary biology predicts: Through increasing insecticide resistance and shifts in feeding and resting behaviour that circumvent indoor interventions. At the same time, new ecological challenges, including climate change and the expansion of Anopheles stephensi into African urban environments, are adding complexity to already strained systems. Equally troubling is the fragmentation of malaria control across numerous institutions, funding streams, and implementation structures that often operate in parallel rather than as a unified system. Re-establishing integrated vector management by combining surveillance, larval source management, environmental control, and targeted adult mosquito control interventions under coordinated national programmes may offer a more resilient path forward. Mosquitoes respond to pressure. Successful malaria programmes must learn to do the same.
Over the past decade, U-Net has been the dominant architecture in medical image segmentation, leading to the development of thousands of U-shaped variants. Despite its widespread adoption, there is still no comprehensive benchmark to systematically evaluate their performance and utility, largely because of insufficient statistical validation and limited consideration of efficiency and generalization across diverse datasets. To bridge this gap, we present U-Bench, the first large-scale, statistically rigorous 2D benchmark that evaluates 100 U-Net variants across 28 datasets and 10 imaging modalities. Our contributions are threefold: (1) Comprehensive Evaluation: U-Bench evaluates models along three key dimensions: statistical robustness, zero-shot generalization, and computational efficiency. We introduce a novel metric, U-Score, which jointly captures the performance-efficiency trade-off, offering a deployment-oriented perspective on model progress. (2) Systematic Analysis and Model Selection Guidance: We summarize key findings from the large-scale evaluation and systematically analyze the impact of dataset characteristics and architectural paradigms on model performance. Based on these insights, we propose a model advisor agent to guide researchers in selecting the most suitable models for specific datasets and tasks. (3) Public Availability: We provide all code, models, protocols, and weights, enabling the community to reproduce our results and extend the benchmark with future methods. In summary, U-Bench not only exposes gaps in previous evaluations but also establishes a foundation for fair, reproducible, and practically relevant benchmarking in the next decade of U-Net-based segmentation models. The weights, datasets, and results will be released after the acceptance.
The purpose of this paper is to examine the impact of financial literacy and Personality traits on retirement planning strategy among full-time employee in Indonesia. This study applies a quantitative approach and the data were collected through online survey and compose of 358 respondents of full-time employess in Indonesia. The study reveals that age, income, and openness significantly related to pursuing active planning retirement strategy. Financial knowledge and behavior do not significantly affect the intention to pursue any retirement planning strategy. We expect this study to contribute into significant implication for Goverment, financial practitioners advisor, financial services authority (OJK) & Banking regulations include an individual worker. Earlier research on retirement planning focused on financial characteristics of the individual separately from the individual’s subjective norms (age, income, dependents, personality traits). This study combine those factors and see how each factor influences the final retirement planning strategies
Based on clinical evidence, medication resistance poses a significant challenge to the treatment of cancer. It causes the disease to become uncontrollable and raises death rates. Drug resistance arises from a variety of causes, but a change in the inherited makeup of tumor cells is typically the root reason. The ability to modify the genome is growing with the recent discovery of clustered regularly interspaced short palindromic repeats (CRISPR)/associated (Cas)9 technology, which may be helpful in reducing drug resistance. Owing to its exceptional accuracy and efficiency, the CRISPR/Cas 9 system has been used to investigate the relevant roles of cancer-causing genes, create animal models of tumors, and identify potential therapeutic targets. As a result, it has emerged as the go-to technique for therapeutic gene editing. Utilizing CRISPR/Cas 9 technologies in the treatment of different diseases is growing. Because oncogene regulation differs from normal gene regulation, the CRISPR/Cas 9 system offers efficient methods for oncogene elimination, interference with expression, and modification of activity, all of which can effectively impede the growth of tumors. This article discusses the potential of the CRISPR/Cas9 system to identify resistance targets in drug-resistant breast cancer and reverse resistance gene alterations. Furthermore, the difficulties that prevent this technology from being clinically applicable and emphasize the CRISPR/Cas9 systems are discussed. The CRISPR/Cas9 system will be a crucial component of personalized medicine and is anticipated to have a significant impact on reducing drug resistance in cancer therapy.
