Ateneo de Manila University

Lifeline utility networks have been studied extensively within the domain of network reliability due to the prevalence of natural hazards. The reliability of these networks is typically investigated through graphs that retain their structural characteristics. This paper introduces novel connectivity-based reliability measures tailored for stochastic graphs with designated source vertices and failure-probability-weighted edges. In particular, the per-vertex path survival reliability quantifies the average survival likelihood of single-source paths from a vertex to any source. A consolidated per-graph reliability measure is also presented, incorporating graph density and the shortest distance to a source as regulating elements for network comparison. To highlight the advantages of the proposed reliability measures, a theoretical discussion of their key properties is presented, along with a comparison against standard reliability measurements. The proposal is further accompanied by an efficient calculation procedure utilizing the zero-suppressed binary decision diagram, constructed through the frontier-based search, to compactly represent all single-source paths. Finally, the path survival reliabilities are calculated for a set of real-world networks and demonstrated to provide practical insights.

The genus Diaporthe consists of several species that cause diseases in various plant species. This genus comprises 13 species complexes based on multi-loci phylogenetic analyses with 832 accepted or presumed species. Plant pathogenic Diaporthe species are widely distributed where their host plants thrive well. For instance, the blight pathogen D. vexans is commonly found in eggplant-growing regions. Rain splashes and wind easily disperse spores of Diaporthe species. Diaporthe infects various agronomic and horticultural crops, leading to various diseases, including dieback, damping off, root and fruit rot, stem canker, leaf lesions, necrotic lesions, and wilting. Among the most important species with economic importance are D. vexans, D. helianthi, D. phaseolorum, and D. citri. Diseases caused by Diaporthe species may be addressed by a combination of strategies (integrated disease management) that reduces the pathogen inoculum, kills the pathogen, or increases the plant’s resistance to the disease. Control strategies include pruning dead branches in the case of D. citri on citrus, use of potential biological control agents, planting of less susceptible varieties, and using synthetic pesticides that have been shown to provide reasonable disease control. With its biology, importance in crop production, host range, and lack of complete control, disease-causing Diaporthe species are significant impediments to achieving our food security goal.

Primal world beliefs (“primals”) capture understanding of general characteristics of the world, such as whether the world is Good and Enticing. Children (N=1215, 50% girls), mothers, and fathers from Colombia, Italy, Jordan, Kenya, Philippines, Sweden, Thailand, and United States reported neighborhood danger, socioeconomic status, parental warmth, harsh parenting, psychological control, and autonomy granting from ages 8 to 16 years. At age 22 years, original child participants reported their primal world beliefs. Parental warmth during childhood and adolescence significantly predicted Good, Safe, and Enticing world beliefs, but other experiences were only weakly related to primals. We did not find that primals are strongly related to intuitive aspects of the materiality of childhood experiences, which suggests future directions for understanding the origins of primals.

Background The transition towards Universal Health Coverage (UHC) in a devolved healthcare system such as the Philippines is beset by health workforce issues considering that it is among the world’s leading source countries for health workers. This study aims to document health workforce issues and recommended practices in the implementation of UHC in the Philippines. Methods We conducted focus group discussions and key informant interviews with health policymakers and UHC implementers in the national, regional, and local levels. Participants included local chief executives, healthcare facility administrators, and healthcare providers at tertiary, secondary, and primary levels, as well as patients. We transcribed and translated the focus group discussions and key informant interviews and analyzed it thematically. Results Workforce factors at entry, current employment, and exit hinder the implementation of UHC. Factors at entry include: poor preparation of graduates in school for implementing UHC; difficulty in recruitment due to restrictive government hiring policies; and government budget caps for personnel services. Factors at the current employment include: poor working conditions; uncompetitive salaries; lack of trained personnel for financial management; exorbitant fees for trainings; lack of job security for nationally deployed personnel; and lack of integration of some barangay health workers and community health volunteers. Factors at exit include the pull of migration overseas and poor crisis management. Some recommended practices to recruit and retain health workforce include scholarships and return service programs; free tuition for dependents of health workers; opportunities for postgraduate degrees and specialist training overseas, and onboarding UHC training for new hires. Conclusions To address the health workforce issues hindering the effective implementation of UHC in the Philippines, there is a need for reforms in the country’s healthcare sector and beyond. Specifically, there is a need to revisit the country’s Local Government Code, integrate further health professions education institutions and healthcare facilities, implement reforms in its basic, higher, and health education, and the civil service, revisit training costs, and training programs for specialists, and design and implement more sustainable and equitable bilateral labor agreements to keep health workforce in the Philippines and engage them as partners for optimal implementation of UHC in the country.

Health information systems are a key building block of a well‐functioning health system and are a vital component in the implementation of universal health coverage. The Philippines's current transition toward universal health coverage had attendant health information system reforms, such as the establishment of the country's National Health Data Repository and the Health Sector Enterprise Architecture. However, many issues remain in this transition, such as insufficient investments in health information systems, poor reliability of health information systems, technical support delays, data quality issues, and cybersecurity issues. We recommend making health data portable throughout the health system while adhering to data privacy laws, investing in internet connectivity, information technology, and capacity building for human resources, and improving implementation of current policies and guidelines to fully harness the potential of health information systems in making universal health coverage a reality in the Philippines.

This article reviews the state of anti-corruption efforts in the Philippines by outlining a typology of corruption and evaluating the country’s progress on these different fronts. Notwithstanding recent gains, the country appears stuck in its anti-corruption efforts. While reforms have managed to advance economic growth, corruption nevertheless continues to undermine private sector investments in key economic sectors and geographic regions associated with high poverty, as well as weakens public goods provision. Corruption de facto erodes the inclusivity of economic growth gains, which eventually contributes to imbalanced growth and inequality. Policy responses, therefore, need to consider the multi-faceted nature and implications of corruption and address its root causes. Reforms to improve competition in the economic and political spheres could help address some of the underlying features of rent-seeking behaviour and corruption. Given how these reforms run into deep political economy issues, a clear theory of change is necessary, touching on both the market economy and the political system.

Organizational theory has developed in numerous directions that have been difficult to integrate. This review synthesizes them into seven perspectives, with theories focused within and beyond the organization (i.e., intra‐ and extra‐organizational dynamics). It proposes the acronym SCRIPTS: structure, culture, relations, institutions, professions, transformation, and social conflict. Within organizations, structure focuses on theories of bureaucracy, management, routines, and decision‐making while culture focuses on shared values, identity, climate, and sensemaking. Relations involve studies of interpersonal and interorganizational networks. Institutions focus on the macro‐dynamics of fields and isomorphism, and micro‐dynamics of entrepreneurship and inhabited institutions. Professions refer to psychological factors shaping individual performance and sociological factors shaping work and occupations. Transformation involves episodic and gradual changes within organizations and across society. Social conflict involves power and competition, with key theories focused on gendered, racialized, and global inequalities. This paper introduces theories and concepts in the study of organizations by grouping similar perspectives, highlighting their domains within or beyond the organization, and underscoring their utility for researchers and leaders.

The thermal properties of starch/PVOH formulations gelatinized with glycerol, cross-linked with boric acid, incorporated with clay and loaded with 2 wt%, 4 wt%, and 7 wt% sayote fibers were investigated. The FTIR spectra, SEM micrographs, DSC, and TGA results revealed a successful blending in starch/PVOH (50/50) and starch/PVOH (65/35) fomulations with glycerol as plasticizer and boric acid as cross-linking agent. Plasticized and cross-linked starch/PVOH reinforced with clay and varying amounts of sayote fiber suggest more inter- and intra- molecular hydrogen bonding interactions, making the composite more crystalline and thermally stable. The SEM micrographs showed a smoother surface with the addition of boric acid and a more orderly woven surface with 2 wt% sayote fiber loading. DSC thermograms reveal that the formulations were compatible and had good blending interactions, since the experimental enthalpies of melting were higher than their theoretical values. The addition of sayote fiber increased the thermal stability of starch/PVOH composite blends and prevented the re-crystallization of starch. TGA curves showed that the addition of sayote fibers formed stronger blends that delayed the degradation of the composite. The starch/PVOH (50/50) and starch/PVOH (65/35) composite blends were more crystalline and thermally stable at 2 wt% to 4 wt% sayote fiber loading.

The term “religious hybrids” refers to religious individuals who seek groundedness in a particular religious tradition but consciously or unconsciously mix in other factors such as culture or different religions. Thus, religious individuals often experience conflict between their lived faith and their affiliated religion’s doctrines, leading to guilt and the deterioration of mental health. In confronting such complexities resulting from religious hybridity, Raimundo Panikkar’s intra-religious dialogue is considered appropriate, given that such dialogue within oneself considers the deepening of one’s faith through the encounter with various religions. Within this context, this study proposes a philosophically modified see-judge-act framework to assist religious hybrids and pastoral care workers in coping with the precarious condition resulting from religious hybridity. In elaborating this proposal, the paper is comprised of five parts. The first part elaborates on the see-judge-act framework and its effectiveness in pastoral care. Second, the discussion covers the “see” aspect of religious hybridity. In this part, the characteristics of hybrid religious identities are identified. Third, the “judge” part pertains to Albert Camus’s philosophical anthropology, focusing on the absurdity of the human condition and the concept of rebellion. Then, Panikkar’s idea of intra-religious dialogue is elaborated. The fourth part of the study presents the “act” aspect: a rebellious intra-religious dialogue as an adaptive coping strategy. Lastly, given the intended scope, the study concludes with future directions for research.

Importance Approximately 29.9 million cancer cases and 15.3 million deaths are anticipated by 2040 globally, necessitating cancer system strengthening. A greater understanding of health system factors that can be leveraged to improve cancer control may guide health system planning. Objective To evaluate predictors of improved cancer outcomes globally. Design, Setting, and Participants This pan-cancer ecological study used the most recent available national health system metrics and cancer statistics, spanning the breadth of global income levels across 185 countries. Estimates of age-standardized mortality to incidence ratios were derived from GLOBOCAN 2022 for patients with cancer of all ages. The analysis took place on November 27, 2024. Main Outcomes and Measures Health spending as a percent of gross domestic product (GDP), physicians per 1000 population, nurses and midwives per 1000 population, surgical workforce per 1000 population, GDP per capita, Universal Health Coverage (UHC) service coverage index, availability of pathology services, human development index, gender inequality index (GII), radiotherapy centers per 1000 population, and out-of-pocket expenditure as percentage of current health expenditure were collected. The association between the mortality to incidence ratio (MIR) and each metric was evaluated using univariable linear regressions (α = .0045), which were used to construct multivariable models (α = .05). Variation inflation factor allowed exclusion of variables with significant multicollinearity. R ² measured goodness of fit. Results On univariable analysis, all metrics were significantly associated with MIR of cancer ( P < .001 for all), including UHC index (β, −0.0076 [95% CI, −0.0083 to −0.0068]), GDP per capita (β, −5.10 × 10 ⁻⁶ [95% CI, −5.75 × 10 ⁻⁶ to −4.46 × 10 ⁻⁶ ]), clinical and workforce capacity, radiotherapy capacity (β, −88.25 [95% CI, −100.43 to −76.06]), and gender inequality index (β, 0.63 [95% CI, 0.57-0.70]). After including metrics significant on univariable analysis and correcting for multicollinearity, on multivariable analysis, greater UHC index and GDP per capita were independently associated with lower (improved) MIR for cancer. The multivariable model had R ² of 0.87. On multivariable analysis stratified by sex, greater UHC index and greater GDP per capita were independently associated with improved MIR for all cancers. R ² for the multivariable models was 0.87 for females and 0.85 for males. Conclusions This study found that global health system metrics related to progress toward universal health care, greater health care spending and GDP per capita, strengthened clinical workforce and capacity, and increased gender equity were associated with improved pan-cancer outcomes at a population level on univariable analysis. The degree of UHC and GDP per capita were independently associated with improved cancer outcomes in multivariable models with good explanatory power. These exploratory findings merit further validation and may guide health system planning and prioritization.

Importance The Rohingya displaced population in Bangladesh is the largest stateless population in the world. Infectious diseases, such as gastroenteritis, respiratory infections, and fever, are among the major health problems the Rohingya population has faced. Although associations between gastroenteritis and air temperature have been reported in various regions, no study has yet been carried out among the displaced populations. Objectives To evaluate the association between air temperature and risk of gastroenteritis among the forcibly displaced Rohingya population in refugee camps in Bangladesh. Design, Setting, and Participants In this cross-sectional study, daily time series data derived from facility-based case reports were collected in 2 clinics organized by the UNHCR (United Nations High Commissioner for Refugees) in Kutupalong and Nayapara registered camps from January 1, 2019, to December 31, 2021. Statistical analysis was conducted from April 2023 to September 2024. Exposure Hourly 2-m air temperature from ERA5-Land by the European Centre for Medium-Range Weather Forecasts. Main Outcomes and Measures The daily number of gastroenteritis cases recorded in the camp clinics was the main outcome measure. Nonlinear lagged associations between daily temperature and gastroenteritis cases were modeled using a quasi-Poisson generalized linear model to account for overdispersion coupled with a distributed lag nonlinear model including a maximum 21-day lag. Covariates from the literature were adjusted in the model. Results A total of 33 280 gastroenteritis cases (95% among individuals aged ≥5 years; 71% female) were recorded in Kutupalong and 31 165 gastroenteritis cases (99% among individuals aged ≥5 years; 67% female) were recorded in Nayapara. Further examination revealed a potential U-shaped curve in Kutupalong with minimum risk temperature (MRT) set at 26 °C. Cumulative relative risk (RR) at the 10th percentile temperature (21.1 °C) was 2.31 (95% CI, 1.18-4.65), while RR at 90th percentile temperature (28.5 °C) was 1.78 (95% CI, 1.24-2.56) relative to MRT. In Nayapara, a nearly linear risk increase was observed with decreasing temperature. Cumulative RR at the 10th percentile temperature (21 °C) was 1.32 (95% CI, 0.78-2.24), while the RR at the 90th percentile temperature (28.3 °C) was 0.75 (95% CI, 0.56-0.99). Lagged effects were delayed in nature. In Kutupalong, cold temperatures (10th percentile) were associated with statistically significant gastroenteritis risks at approximately 15 to 20 days (range: RR, 1.06 [95% CI, 1.00-1.13] to RR, 1.10 [95% CI, 1.00-1.21]). In Nayapara, gastroenteritis risks were correspondingly higher at longer lags (lag, 18 days; RR, 1.05 [95% CI, 1.00-1.10]). Conclusions and Relevance In this cross-sectional study of the Rohingya displaced population in Bangladesh, cold temperatures were associated with an increase in the risk of gastroenteritis. It is important to understand the association of climatic factors with the health of displaced communities, whose population is expected to grow in the future.

Long COVID, where symptoms persist after recovering from COVID-19, can affect cognitive functions like language. However, little is known about its impact on children’s language skills, especially across different school levels. This study investigated the impact of long COVID on language proficiency among 1244 children (Asian; 53.5% boys) from kindergartens (N = 408, Mage = 4.42 ± 1.26 years), primary schools (N = 547, Mage = 9.69 ± 1.96 years), and secondary schools (N = 289, Mage = 14.97 ± 1.85 years) in Hong Kong. Language proficiency was assessed using the Language Experience and Proficiency Questionnaire (LEAP-Q), which measured speaking, listening, reading, and writing in both Chinese and English. Participants were categorized into three groups: long COVID, recovered from COVID-19, and no history of COVID-19. One-way and two-way ANOVAs were used to analyze the differences in language proficiency across these groups and school levels. Children with long COVID symptoms exhibited significantly lower overall language proficiency, particularly in speaking and listening, compared to those in the recovered and no-COVID groups. The effect was more pronounced among primary and secondary students, with secondary school students showing the most substantial deficits. No significant differences were found between the recovered and no-COVID groups. The results suggest that long COVID might have detrimental effects on children’s linguistic proficiency. The language development of older students who suffered from long COVID could benefit from receiving targeted educational and therapeutic interventions.

We devise a novel resummation prescription based on the method of finite-part integration [Galapon EA. 2017 Proc. R. Soc A 473, 20160567. (doi:10.1098/rspa.2016.0567)] to perform a constrained extrapolation of the divergent weak-field perturbative expansion for the Heisenberg–Euler Lagrangian to the non-perturbative strong magnetic and electric field regimes. In the latter case, the prescription allowed us to reconstruct the non-perturbative imaginary part from a finite collection of the real expansion coefficients. We also demonstrate the utility of the various equivalent representations of Hadamard’s finite part in deriving the exact closed form for the Heisenberg–Euler Lagrangian from the non-perturbative integral representation.

While numerous studies have explored the impact of bias correction on climate projections of precipitation and temperature, few have investigated the influence of these corrected climate outputs on the estimation of drought characteristics. In response to this gap, this study aims to quantify and compare meteorological drought characteristics derived from climate simulation datasets with and without bias correction. We conducted our investigation using downscaled data of six Coordinated Regional Climate Downscaling Experiment-Southeast Asia (CORDEX-SEA) experiments for the period 1976 to 2005, with Quantile Mapping (QM) being employed as our bias correction (BC) technique. The drought characteristics examined in this study are frequency, duration, severity, intensity, and geographical extent, utilizing the 12-month Standardized Precipitation Evapotranspiration Index (SPEI). We performed univariate cross-validation QM BC for both precipitation and temperature at a grid-cell wide, demonstrating comparable performances for both the training (1976–1995) and testing (1996–2005) periods. The drought characteristics analysis was conducted for the entire temporal dataset (1976–2005) to utilize over 30 years of data for drought computation. Compared to the reference drought characteristics derived from APHRODITE, the drought characteristics from both the uncorrected and bias-corrected models show a similar pattern in the distribution of relative differences, with moderately lower differences for the models with bias correction, particularly in mainland Southeast Asia, except for the Myanmar region. Additionally, the application of QM showed moderate improvements in determining drought intensity and geographical extent. However, the implementation of QM only resulted in marginal improvements for drought duration and severity and did not perform well in reproducing the number of drought events. We further demonstrated that the effectiveness of bias correction on drought characteristics variation across topographies and land covers, with considerable improvement observed in low-elevation and grassland/arable land regions. To this end, this study provides a new perspective on the added value of bias correction techniques in climate change projections for drought indicator computation.

Modeling the brain dependence network is central to understanding underlying neural mechanisms such as perception, action, and memory. In this study, we present a broad range of statistical methods for analyzing dependence in a brain network. Leveraging a combination of classical and cutting-edge approaches, we analyze multivariate hippocampal local field potential (LFP) time series data concentrating on the encoding of nonspatial olfactory information in rats. We present the strengths and limitations of each method in capturing neural dynamics and connectivity. Our analysis begins with exploratory techniques, including correlation, partial correlation, spectral matrices, and coherence, to establish foundational connectivity insights. We then investigate advanced methods such as Granger causality (GC), robust canonical coherence analysis, spectral transfer entropy (STE), and wavelet coherence to capture dynamic and nonlinear interactions. Additionally, we investigate the utility of topological data analysis (TDA) to extract multi-scale topological features and explore deep learning-based canonical correlation frameworks for connectivity modeling. This comprehensive approach offers an introduction to the state-of-the-art techniques for the analysis of dependence networks, emphasizing the unique strengths of various methodologies, addressing computational challenges, and paving the way for future research.