The International Heat Stress Genotype Experiment for modeling wheat response to heat: field experiments and AgMIP-Wheat multi-model simulations

The data set contains a portion of the International Heat Stress Genotype Experiment (IHSGE) data used in the AgMIP-Wheat project to analyze the uncertainty of 30 wheat crop models and quantify the impact of heat on global wheat yield productivity. It includes two spring wheat cultivars grown during two consecutive winter cropping cycles at hot, irrigated, and low latitude sites in Mexico (Ciudad Obregon and Tlaltizapan), Egypt (Aswan), India (Dharwar), the Sudan (Wad Medani), and Bangladesh (Dinajpur). Experiments in Mexico included normal (November-December) and late (January-March) sowing dates. Data include local daily weather data, soil characteristics and initial soil conditions, crop measurements (anthesis and maturity dates, anthesis and final total above ground biomass, final grain yields and yields components), and cultivar information. Simulations include both daily in-season and end-of-season results from 30 wheat models

The value of standards for health datasets in artificial intelligence-based applications

Artificial intelligence as a medical device is increasingly being applied to healthcare for diagnosis, risk stratification and resource allocation. However, a growing body of evidence has highlighted the risk of algorithmic bias, which may perpetuate existing health inequity. This problem arises in part because of systemic inequalities in dataset curation, unequal opportunity to participate in research and inequalities of access. This study aims to explore existing standards, frameworks and best practices for ensuring adequate data diversity in health datasets. Exploring the body of existing literature and expert views is an important step towards the development of consensus-based guidelines. The study comprises two parts: a systematic review of existing standards, frameworks and best practices for healthcare datasets; and a survey and thematic analysis of stakeholder views of bias, health equity and best practices for artificial intelligence as a medical device. We found that the need for dataset diversity was well described in literature, and experts generally favored the development of a robust set of guidelines, but there were mixed views about how these could be implemented practically. The outputs of this study will be used to inform the development of standards for transparency of data diversity in health datasets (the STANDING Together initiative)

Heritagization of the Camino to Finisterre

This chapter focuses on one of the objectives of the Finisterre route research project: to compare the concept of heritage conveyed in regional and municipal heritage policies with that of other local actors. The ethnographic studies carried out in the villages and towns with pilgrim hostels show that there is a gap between the two concepts. This chapter deals with two aspects of the disparity. Firstly, some politicians construct a sophisticated discourse on heritage regarding the Camino de Santiago, which contrasts with the lack of a term to name ‘heritage’ at a local level. The second aspect is related to the concept of heritage itself. Politicians and heritage managers have a limited concept of heritage, and therefore they dedicate their heritage policies and funding to building restoration and maintenance of the route itself. On the other hand, the local residents’ idea of heritage is broader, and includes cultural practices such as festivals and religious celebrations as well as other elements of heritage that are more difficult to catalogue, such as ‘continuing to work the land,’ ‘the rural landscape,’ or ‘our local water supplies.’ In addition, this chapter analyses various levels of conflict around heritage and the Camino.Peer reviewe

Costs Associated with Low Birth Weight in a Rural Area of Southern Mozambique

BACKGROUND: Low Birth Weight (LBW) is prevalent in low-income countries. Even though the economic evaluation of interventions to reduce this burden is essential to guide health policies, data on costs associated with LBW are scarce. This study aims to estimate the costs to the health system and to the household and the Disability Adjusted Life Years (DALYs) arising from infant deaths associated with LBW in Southern Mozambique. METHODS AND FINDINGS: Costs incurred by the households were collected through exit surveys. Health system costs were gathered from data obtained onsite and from published information. DALYs due to death of LBW babies were based on local estimates of prevalence of LBW (12%), very low birth weight (VLBW) (1%) and of case fatality rates compared to non-LBW weight babies [for LBW (12%) and VLBW (80%)]. Costs associated with LBW excess morbidity were calculated on the incremental number of hospital admissions in LBW babies compared to non-LBW weight babies. Direct and indirect household costs for routine health care were 24.12 US$(CI 95$ (CI 95% 6.33; 10.72). Of the 3,322 live births that occurred in one year in the study area, health system costs associated to LBW (routine health care and excess morbidity) and DALYs were 169,957.61 US$ (CI 95% 144,900.00; 195,500.00) and 2,746.06, respectively. CONCLUSIONS: This first cost evaluation of LBW in a low-income country shows that reducing the prevalence of LBW would translate into important cost savings to the health system and the household. These results are of relevance for similar settings and should serve to promote interventions aimed at improving maternal care

Tackling algorithmic bias and promoting transparency in health datasets: the STANDING Together consensus recommendations

\ua9 2025 World Health OrganizationWithout careful dissection of the ways in which biases can be encoded into artificial intelligence (AI) health technologies, there is a risk of perpetuating existing health inequalities at scale. One major source of bias is the data that underpins such technologies. The STANDING Together recommendations aim to encourage transparency regarding limitations of health datasets and proactive evaluation of their effect across population groups. Draft recommendation items were informed by a systematic review and stakeholder survey. The recommendations were developed using a Delphi approach, supplemented by a public consultation and international interview study. Overall, more than 350 representatives from 58 countries provided input into this initiative. 194 Delphi participants from 25 countries voted and provided comments on 32 candidate items across three electronic survey rounds and one in-person consensus meeting. The 29 STANDING Together consensus recommendations are presented here in two parts. Recommendations for Documentation of Health Datasets provide guidance for dataset curators to enable transparency around data composition and limitations. Recommendations for Use of Health Datasets aim to enable identification and mitigation of algorithmic biases that might exacerbate health inequalities. These recommendations are intended to prompt proactive inquiry rather than acting as a checklist. We hope to raise awareness that no dataset is free of limitations, so transparent communication of data limitations should be perceived as valuable, and absence of this information as a limitation. We hope that adoption of the STANDING Together recommendations by stakeholders across the AI health technology lifecycle will enable everyone in society to benefit from technologies which are safe and effective

The Blood Pressure "Uncertainty Range" – a pragmatic approach to overcome current diagnostic uncertainties (II)

A tremendous amount of scientific evidence regarding the physiology and physiopathology of high blood pressure combined with a sophisticated therapeutic arsenal is at the disposal of the medical community to counteract the overall public health burden of hypertension. Ample evidence has also been gathered from a multitude of large-scale randomized trials indicating the beneficial effects of current treatment strategies in terms of reduced hypertension-related morbidity and mortality. In spite of these impressive advances and, deeply disappointingly from a public health perspective, the real picture of hypertension management is overshadowed by widespread diagnostic inaccuracies (underdiagnosis, overdiagnosis) as well as by treatment failures generated by undertreatment, overtreatment, and misuse of medications. The scientific, medical and patient communities as well as decision-makers worldwide are striving for greatest possible health gains from available resources. A seemingly well-crystallised reasoning is that comprehensive strategic approaches must not only target hypertension as a pathological entity, but rather, take into account the wider environment in which hypertension is a major risk factor for cardiovascular disease carrying a great deal of our inheritance, and its interplay in the constellation of other, well-known, modifiable risk factors, i.e., attention is to be switched from one's "blood pressure level" to one's absolute cardiovascular risk and its determinants. Likewise, a risk/benefit assessment in each individual case is required in order to achieve best possible results. Nevertheless, it is of paramount importance to insure generalizability of ABPM use in clinical practice with the aim of improving the accuracy of a first diagnosis for both individual treatment and clinical research purposes. Widespread adoption of the method requires quick adjustment of current guidelines, development of appropriate technology infrastructure and training of staff (i.e., education, decision support, and information systems for practitioners and patients). Progress can be achieved in a few years, or in the next 25 years

Lack of observational evidence for quantum structure of space-time at Plank scales

It has been noted (Lieu & Hillmann, 2002) that the cumulative affect of Planck-scale phenomenology, or the structure of space-time at extremely small scales, can be lead to the loss of phase of radiation emitted at large distances from the observer. We elaborate on such an approach and demonstrate that such an effect would lead to an apparent blurring of distant point-sources. Evidence of the diffraction pattern from the HST observations of SN 1994D and the unresolved appearance of a Hubble Deep Field galaxy at z=5.34 lead us to put stringent limits on the effects of Planck-scale phenomenology.Comment: 12 pages, 3 figures, accepter for ApJ

Outcomes research in the development and evaluation of practice guidelines

BACKGROUND: Practice guidelines have been developed in response to the observation that variations exist in clinical medicine that are not related to variations in the clinical presentation and severity of the disease. Despite their widespread use, however, practice guideline evaluation lacks a rigorous scientific methodology to support its development and application. DISCUSSION: Firstly, we review the major epidemiological foundations of practice guideline development. Secondly, we propose a chronic disease epidemiological model in which practice patterns are viewed as the exposure and outcomes of interest such as quality or cost are viewed as the disease. Sources of selection, information, confounding and temporal trend bias are identified and discussed. SUMMARY: The proposed methodological framework for outcomes research to evaluate practice guidelines reflects the selection, information and confounding biases inherent in its observational nature which must be accounted for in both the design and the analysis phases of any outcomes research study