Month: April 2024
Adoption of smart farm networks: a translational process to inform digital agricultural technologies
Abstract
Due to natural phenomena like global warming and climate change, agricultural production is increasingly faced with threats that transcend farm boundaries. Management practices at the landscape or community level are often required to adequately respond to these new challenges (e.g., pest migration). Such decision-making at a community or beyond-farm level—i.e., practices that are jointly developed by farmers within a community—can be aided by computing and communications technology. In this study, we employ a translational research process to examine the social and behavioral drivers of adoption of smart and connected farm networks among commodity crop farmers in the United States. We implement focus groups and questionnaires to bring to the fore views on the use of digital technologies in collaborative contexts. We find that participating farmers are concerned with several issues about the potential features of the network (e.g., the ability to ensure data validity while maintaining data privacy) and the nature of their interactions with the various stakeholders involved in the network management. The participatory approach we adopt helps provide insights into the process of developing technologies that are both actionable and trusted by potential end users.
Accuracy enhancement of IMERG precipitation estimates using 20-year climatological adjustment: designing three rounds of modeling with two calibration schemes to drive multi-type regression models
Abstract
The actual application of Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) is restricted by the bias revealed by ground data. This study established seven regression models (RMs) to generate the adjusted IMERG estimates. Relatively stable parameters of the regression can be gained during the calibration. The calibration was performed by climatological adjustment, building a relationship between the 18-year data series of the original IMERG estimates and simultaneous daily data derived from 687 rain gauges in mainland China. A one-time modeling scheme was designed using all daily precipitation data as a calibration dataset. A two-time modeling scheme was established by dividing the calibration period into cold and warm seasons. Then, the relative bias (RB) and root-mean-square error (RMSE) were the evaluation indicators inspected during the validation. Three rounds of modeling were designed to provide corrections when near-real-time and post-real-time IMERG products produce time series. The main conclusions are as follows: (1) The two-time modeling scheme had a higher proportion than the one-time modeling scheme in having the lowest RMSE and absolute RB values. (2) Compared with the original IMERG estimates, the model-generated estimates in rounds 1 and 2 reduced the magnitude of the RB and RMSE at around 75% and 85% of gauges, respectively. (3) Polynomial RMs were the best-performing models in rounds 2 and 3. (4) The gauges where the RM failed to reduce the magnitude of the RB were mainly found in humid, plain, and low-latitude areas of mainland China.
Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks: Climatology, Interannual Variability, and Extremes
Abstract
Climate models are vital for understanding and projecting global climate change and its associated impacts. However, these models suffer from biases that limit their accuracy in historical simulations and the trustworthiness of future projections. Addressing these challenges requires addressing internal variability, hindering the direct alignment between model simulations and observations, and thwarting conventional supervised learning methods. Here, we employ an unsupervised Cycle-consistent Generative Adversarial Network (CycleGAN), to correct daily Sea Surface Temperature (SST) simulations from the Community Earth System Model 2 (CESM2). Our results reveal that the CycleGAN not only corrects climatological biases but also improves the simulation of major dynamic modes including the El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole mode, as well as SST extremes. Notably, it substantially corrects climatological SST biases, decreasing the globally averaged Root-Mean-Square Error (RMSE) by 58%. Intriguingly, the CycleGAN effectively addresses the well-known excessive westward bias in ENSO SST anomalies, a common issue in climate models that traditional methods, like quantile mapping, struggle to rectify. Additionally, it substantially improves the simulation of SST extremes, raising the pattern correlation coefficient (PCC) from 0.56 to 0.88 and lowering the RMSE from 0.5 to 0.32. This enhancement is attributed to better representations of interannual, intraseasonal, and synoptic scales variabilities. Our study offers a novel approach to correct global SST simulations and underscores its effectiveness across different time scales and primary dynamical modes.
A multisite feasibility randomized clinical trial of mindfulness-based resilience training for aggression, stress, and health in law enforcement officers
Abstract
Background
Law enforcement officers (LEOs) are exposed to significant stressors that can impact their mental health, increasing risk of posttraumatic stress disorder, burnout, at-risk alcohol use, depression, and suicidality. Compromised LEO health can subsequently lead to aggression and excessive use of force. Mindfulness training is a promising approach for high-stress populations and has been shown to be effective in increasing resilience and improving mental health issues common among LEOs.
Methods
This multi-site, randomized, single-blind clinical feasibility trial was intended to establish optimal protocols and procedures for a future full-scale, multi-site trial assessing effects of mindfulness-based resilience training (MBRT) versus an attention control (stress management education [SME]) and a no-intervention control, on physiological, attentional, and psychological indices of stress and mental health. The current study was designed to enhance efficiency of recruitment, engagement and retention; optimize assessment, intervention training and outcome measures; and ensure fidelity to intervention protocols. Responsiveness to change over time was examined to identify the most responsive potential proximate and longer-term assessments of targeted outcomes.
Results
We observed high feasibility of recruitment and retention, acceptability of MBRT, fidelity to assessment and intervention protocols, and responsiveness to change for a variety of putative physiological and self-report mechanism and outcome measures.
Conclusions
Results of this multi-site feasibility trial set the stage for a full-scale, multi-site trial testing the efficacy of MBRT on increasing LEO health and resilience, and on decreasing more distal outcomes of aggression and excessive use of force that would have significant downstream benefits for communities they serve.
Trial registration
ClinicalTrials.gov, NCT03784846. Registered on December 24th, 2018.
"Only Amharic or Leave Quick!": Linguistic Genocide in the Western Tigray Region of Ethiopia
Abstract
Language is a powerful tool that enables communication and shapes our identity and cultural practices. The right to choose one's language is a fundamental human right that helps preserve personal and communal identities. In a multilingual nation like Ethiopia, language goes beyond communication to define administrative boundaries. Consequently, depriving Ethiopians of their linguistic rights becomes a more complex punishment than food embargoes. This research investigated the motives and means by which the Amhara Regional State-enforced a monolingual and monocultural language education policy in western Tigray through the lens of linguistic genocide. The study involved interviews with ten teachers, selected using a snowball sampling method, and document analysis to reinforce the result. Political and economic factors and a desire to promote the assimilation of Tigrayans into Amhara culture and language, a process known as "Amharanization", appear to have impacted the implementation of the language education policy in western Tigray. Authorities have implemented a variety of measures, including bans, restrictions, penalties, enforcement, forced relocation, and even heinous acts, which have caused the Tigrayan community severe physical and psychological distress. Collectively, these policies, actions, and outcomes constituted an act of linguistic genocide. This study sheds light on the severe repercussions of such policies, examines their implications, acknowledges the inherent limitations, and offers valuable recommendations for future research in this crucial area.
Place-based strategies for sustainable and inclusive regional development in the south of Mexico
Abstract
In many countries the growth of significant regional economic disparities has created a geography of discontent. Looking at left-behind places in less developed countries is critical because of the wider economic, social, and political consequences. One example of political discontent due to acute inequalities is the Zapatista movement in the state of Chiapas in southern Mexico in 1994. Combining elements from the literature on left-behind places and place-based policies with elements of political economy, this article analyses place-based strategies for inclusive and sustainable development as implemented by Mexico’s current federal government. In contrast to previous federal administrations, strategic projects for disadvantaged regions are considered a national security priority. With the slogan ‘For the good of all, the poor come first’, the president promised to govern for everyone but to prioritise the most impoverished and vulnerable. However, these projects have been accused of endangering sustainable development. This article argues that those policies have been agreed in a political-economic scenario of struggle in which they are considered as either popular and progressist, or populist.
Finger Fluting in Prehistoric Caves: A Critical Analysis of the Evidence for Children, Sexing and Tracing of Individuals
Abstract
Finger flutings are channels drawn in soft sediments covering walls, floors and ceilings of some limestone caves in Europe and Australia and in some cases date as far back as 50,000 years ago. Initial research focused on why they were made, but more recently, as part of a growing interest in the individual in the past, researchers began asking questions about who made them. This shift in direction has led to claims that by measuring the width of flutings made with the three middle fingers of either hand, archaeologists can infer the ordinal age, sex and individuality of the ‘fluter’. These claims rest on a single dataset created in 2006. In this paper, we undertake the first critical analysis of that dataset and its concomitant methodologies. We argue that sample size, uneven distribution of sex and age within the sample, non-standardised medium, human variability, the lack of comparability between an experimental context and real cave environments and assumptions about demographic modelling effectively negate all previous claims. To sum, we find no substantial evidence for the claims that an age, sex and individual tracing can be revealed by measuring finger flutings as described by Sharpe and Van Gelder (Antiquity 80: 937-947, 2006a; Cambridge Archaeological Journal 16: 281–95, 2006b; Rock Art Research 23: 179–98, 2006c). As a case study, we discuss Koonalda Cave in southern Australia. Koonalda has the largest and most intact display of finger flutings in the world and is also part of a cultural landscape maintained and curated by Mirning people.
Low-Density Urbanisation: Prestate Settlement Growth in a Pacific Society
Abstract
The recognition of low-density urbanisation has been important in documenting how diverse human settlements generated enduring social and economic change. In tropical regions, the key challenges to studying low-density urbanisation have been the difficulty in acquiring past built environment data and integrating the frameworks that illuminate the social behaviours intrinsic to urbanisation. The introduction of lidar mapping and urban science methods has proven revolutionary in our understanding of low-density urbanisation as demonstrated by emerging research on settlements and states in Mesoamerica and Southeast Asia. These studies draw on urban theory to highlight patterns in the built environment associated with profound societal changes including the rise of social institutions, agglomeration effects, and ongoing settlement growth. Here, we present an approach that combines lidar survey and archaeological fieldwork with recent developments in urban science to understand the built environment of Tongatapu; the location of an archaic state whose influence spread across the southwest Pacific Ocean between the thirteenth and nineteenth centuries a.d. Quantitative results show—for the first time—that settlements on a Pacific island were urbanised in a distinct low-density form and that the processes of urbanisation began prior to state development. This study highlights the potential contribution of Pacific landscapes to urban science and the low-density settlement phenomena given the presence of large populations, hierarchical societies, and vast distributions of archaeological built remains on many island groups.
Models to predict length of stay in the emergency department: a systematic literature review and appraisal
Abstract
Introduction
Prolonged Length of Stay (LOS) in ED (Emergency Department) has been associated with poor clinical outcomes. Prediction of ED LOS may help optimize resource utilization, clinical management, and benchmarking. This study aims to systematically review models for predicting ED LOS and to assess the reporting and methodological quality about these models.
Methods
The online database PubMed, Scopus, and Web of Science (10 Sep 2023) was searched for English language articles that reported prediction models of LOS in ED. Identified titles and abstracts were independently screened by two reviewers. All original papers describing either development (with or without internal validation) or external validation of a prediction model for LOS in ED were included.
Results
Of 12,193 uniquely identified articles, 34 studies were included (29 describe the development of new models and five describe the validation of existing models). Different statistical and machine learning methods were applied to the papers. On the 39-point reporting score and 11-point methodological quality score, the highest reporting scores for development and validation studies were 39 and 8, respectively.
Conclusion
Various studies on prediction models for ED LOS were published but they are fairly heterogeneous and suffer from methodological and reporting issues. Model development studies were associated with a poor to a fair level of methodological quality in terms of the predictor selection approach, the sample size, reproducibility of the results, missing imputation technique, and avoiding dichotomizing continuous variables. Moreover, it is recommended that future investigators use the confirmed checklist to improve the quality of reporting.