During the COVID-19 pandemic, Aotearoa followed an elimination strategy followed by a mitigation strategy, which saw high success and kept health impact low. However, there were inequities in health outcomes, notably that Māori and Pacific Peoples had lower vaccine coverage and experienced higher age-standardised rates of hospitalisation and death. Models provide predictions of disease spread and burden, which can effectively inform policy, but are often less good at including inequities/heterogeneity. Despite the differences in health outcomes, most models have not explicitly considered ethnic heterogeneities as factors. We developed such a model to investigate the first Omicron wave of the COVID-19 pandemic in Aotearoa, which was the first widespread community transmission of SARS-CoV-2. We analysed three models for contact patterns within and between ethnicities: proportionate, assortative, and unconstrained mixing, which were fit using ethnicity-specific data on reported cases and spatially disaggregated population counts. We found that Māori, Pacific, and Asian transmission rates were between 1.08-2.46, 1.50-3.89, and 0.80-0.92 times the European rates, respectively. We then f
Previous pandemics, including influenza pandemics and Covid-19, have disproportionately impacted Māori and Pacific populations in Aotearoa New Zealand. The reasons for this are multi-faceted, including differences in socioeconomic deprivation, housing conditions and household size, vaccination rates, access to healthcare, and prevalence of pre-existing health conditions. Many mathematical models that were used to inform the response to the Covid-19 pandemic did not explicitly include ethnicity or other socioeconomic variables. This limited their ability to predict, understand and mitigate inequitable impacts of the pandemic. Here, we extend a model that was developed during the Covid-19 pandemic to support the public health response by stratifying the population into four ethnicity groups: Māori, Pacific, Asian and European/other. We include three ethnicity-specific components in the model: vaccination rates, clinical severity parameters, and contact patterns. We compare model results to ethnicity-specific data on Covid-19 cases, hospital admissions and deaths between 1 January 2022 and 30 June 2023, under different model scenarios in which these ethnicity-specific components are p
This is the writeup of lectures delivered in Asian Pacific introductory school on superstring and the related topics in Beijing (2006) and the expanded version of these lectures in the 3rd summer school on strings, fields and holography in Nanjing (2023). It intends to give a historical as well as a pedagogical account of the development in finding the 1/2 BPS extended string solitons in the early stage of the so-called second string revolution before which those objects were thought to be unrelated to strings. Non-susy solutions which are related to brane/anti brane systems or non-BPS systems are also discussed.
The forecast accuracy of machine learning (ML) weather prediction models is improving rapidly, leading many to speak of a "second revolution in weather forecasting". With numerous methods being developed and limited physical guarantees offered by ML models, there is a critical need for a comprehensive evaluation of these emerging techniques. While this need has been partly fulfilled by benchmark datasets, they provide little information on rare and impactful extreme events or on compound impact metrics, for which model accuracy might degrade due to misrepresented dependencies between variables. To address these issues, we compare ML weather prediction models (GraphCast, PanguWeather, and FourCastNet) and ECMWF's high-resolution forecast system (HRES) in three case studies: the 2021 Pacific Northwest heatwave, the 2023 South Asian humid heatwave, and the North American winter storm in 2021. We find that ML weather prediction models locally achieve similar accuracy to HRES on the record-shattering Pacific Northwest heatwave but underperform when aggregated over space and time. However, they forecast the compound winter storm substantially better. We also highlight structural differen
Breast Cancer is a major disease affecting women's health in the United States with incidence and prevalence dominant among younger women and the Black race. We analyzed the association between breast cancer characteristics with age and race and how survival months and age differ in racial groups. Using the Surveillance, Epidemiology, and End Results (SEER) datasets we performed a logistic regression to examine significant predictors that affect survival month. There were 3414 whites, 291 Blacks, and 320 Others (American Indian/AK Native, Asian/Pacific Islander) in the sample. We found significant associations between racial groups and ages with significant differences in age between Blacks and Whites, and Whites and Others. Patients with a breast cancer tumor in grades 1 and 2 have higher survival months (by 1.49% and 0.49%) respectively.
Social media has become a critical tool for journalists to disseminate their work, engage with their audience, and connect with sources. Unfortunately, journalists also regularly endure significant online harassment on social media platforms, ranging from personal attacks to doxxing to threats of physical harm. In this paper, we seek to understand how to make social media usable for journalists who face constant digital harassment. To begin, we conduct a set of need-finding interviews with Asian American and Pacific Islander journalists to understand where existing platform tools and newsroom resources fall short in adequately protecting journalists, especially those of marginalized identities. We map journalists' unmet needs to concrete design goals, which we use to build PressProtect, an interface that provides journalists greater agency when engaging with readers on Twitter/X. Through user testing with eight journalists, we evaluate PressProtect and find that participants felt it effectively protected them against harassment and could also generalize to serve other visible and vulnerable groups. We conclude with a discussion of our findings and recommendations for social platfor
This study explores the mechanisms behind anomalous positive and negative rainfall events in the southeastern United States (SEUS), emphasizing the interplay between upper-level large-scale atmospheric teleconnections and the lower-level North Atlantic Subtropical High (NASH). Through a novel conditional weather regime analysis of geopotential height at both lower and upper levels across the Pacific-North America-Atlantic region, we identify distinct clusters representing persistent and recurring circulation patterns originating from the Pacific and Atlantic Oceans. Our analysis of lower-level conditional weather regimes reveals two distinct phases of the NASH that influence rainfall patterns in the SEUS region. In one phase, the weakening and eastward shift of the NASH's northern boundary reduces the central low-level jet, enhances cyclonic circulation, and increases rainfall in the SEUS. In the other phase, the excessive latent heating associated with enhanced SEUS rainfall triggers a wave train pattern that strengthens the intensity of NASH. Conversely, the opposite conditions apply during anomalous negative rainfall events. Additionally, the upper-level conditional weather regi
This paper computes composite indicators of corporate social responsibility (CSR) from an efficiency perspective for food and beverage manufacturing firms in various world regions over the period from 2011 to 2018. From a methodological perspective, we extend the measurement of composite indicators within data envelopment analysis, allowing for the non-convexities of the production set and for the appropriate comparison of indicators between groups of firms. From an empirical point of view, we contribute by comparing the efficiency in CSR practices of food and beverage companies across regions of Europe, the United States and Canada, and Asia Pacific. The study reveals differences in CSR efficiency between food and beverage firms in the regions considered, with USA and Canadian firms tending to perform best, followed by European firms, and Asian Pacific firms achieving the worst efficiency results. The study also shows that regional catching up in performance occurred over the analyzed period.
Intraseasonal variations of the South Asian Summer Monsoon (SASM) contain alternating extreme rainfall (active) and low rainfall (break) phases impacting agriculture and economies. Their timing and spatial location are dominated by the Boreal Summer Intraseasonal Oscillation (BSISO), a quasi-periodic movement of convective precipitation from the equatorial Indian Ocean to the Western Pacific. However, observed deviations from the BSISO's canonical north-eastward propagation are poorly understood. Utilizing climate networks to characterize how active phases propagate within the SASM domain and using clustering analysis, we reveal three distinct modes of BSISO propagation: north-eastward, eastward-blocked, and stationary. We further show that Pacific sea surface temperatures modulate the modes - with El Niño- (La Niña-) like conditions favoring the stationary (eastward-blocked) - by changing local zonal and meridional overturning circulations and the BSISO Kelvin wave component. Using these insights, we demonstrate the potential for early warning signals of extreme rainfall until four weeks in advance.
Many datasets contain personally identifiable information, or PII, which poses privacy risks to individuals. PII masking is commonly used to redact personal information such as names, addresses, and phone numbers from text data. Most modern PII masking pipelines involve machine learning algorithms. However, these systems may vary in performance, such that individuals from particular demographic groups bear a higher risk for having their personal information exposed. In this paper, we evaluate the performance of three off-the-shelf PII masking systems on name detection and redaction. We generate data using names and templates from the customer service domain. We find that an open-source RoBERTa-based system shows fewer disparities than the commercial models we test. However, all systems demonstrate significant differences in error rate based on demographics. In particular, the highest error rates occurred for names associated with Black and Asian/Pacific Islander individuals.
We analyze international co-authorship relations in the Social Science Citation Index 2011 using all citable items in the DVD-version of this index. Network statistics indicate four groups of nations: (i) an Asian-Pacific one to which all Anglo-Saxon nations (including the UK and Ireland) are attributed; (ii) a continental European one including also the Latin-American countries; (iii) the Scandinavian nations; and (iv) a community of African nations. Within the EU-28 (including Croatia), eleven of the EU-15 states have dominant positions. Collapsing the EU-28 into a single node leads to a bi-polar structure between the US and EU-28; China is part of the US-pole. We develop an information-theoretical test to distinguish whether international collaborations or domestic collaborations prevail; the results are mixed, but the international dimension is more important than the national one in the aggregated sets (this was found in both SSCI and SCI). In France, however, the national distribution is more important than the international one, while the reverse is true for most European nations in the core group (UK, Germany, the Netherlands, etc.). Decomposition of the USA in terms of sta
The Asian-pacific region is the major international tourism demand market in the world, and its tourism demand is deeply affected by various factors. Previous studies have shown that different market factors influence the tourism market demand at different timescales. Accordingly, the decomposition ensemble learning approach is proposed to analyze the impact of different market factors on market demand, and the potential advantages of the proposed method on forecasting tourism demand in the Asia-pacific region are further explored. This study carefully explores the multi-scale relationship between tourist destinations and the major source countries, by decomposing the corresponding monthly tourist arrivals with noise-assisted multivariate empirical mode decomposition. With the China and Malaysia as case studies, their respective empirical results show that decomposition ensemble approach significantly better than the benchmarks which include statistical model, machine learning and deep learning model, in terms of the level forecasting accuracy and directional forecasting accuracy.
At night, the car projects its turn signals onto the road to alert other road users
Researchers have developed a compact quantum detector that makes terahertz radiation much easier to detect。 A specially designed metasurface funnels incoming energy into tiny active regions, greatly strengthening the electrical signal produced。 The approach boosted efficiency by roughly 20 times compared to earlier designs and could pave the way fo
The waiver "serves the public interest by promoting a second large satellite broadband constellation
A long-overlooked organ may hold surprising clues to healthy aging and cancer survival。 Researchers at Mass General Brigham used AI to analyze CT scans from tens of thousands of adults and found that people with healthier thymuses—a small immune-system organ once thought to become largely irrelevant after childhood—lived longer and had substantiall
NASA’s futuristic X-59 jet is about to face its biggest challenge yet: breaking the sound barrier for the first time。 After a successful series of test flights that pushed the aircraft to near-supersonic speeds, engineers are preparing to fly it faster than Mach 1 and eventually up to Mach 1。6 at 60,000 feet
A decades-old mystery about Saturn has finally been solved thanks to the James Webb Space Telescope。 Scientists discovered that Saturn’s changing “rotation rate” was never caused by the planet speeding up or slowing down, but by powerful winds high in its atmosphere。 Webb’s unprecedented observations revealed that Saturn’s northern lights actively
Scientists have uncovered unexpected quantum complexity inside cobalt, a metal long thought to be fully understood。 Advanced measurements revealed a dense network of topological electronic states that remain robust at room temperature。 These states enable extremely fast electron behavior and can be switched or controlled using magnetism
There are more than a quarter of a million V2G-capable GM EVs on the roads already