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1. Analyzing and Assessing Dynamic Behavior of a Physical Supply and Demand System for Sustainable Water Management under a Semi-Arid Environment

   https://doi.org/10.3390/w14121939  

   Mashaly, Ahmed F. ; Fernald, Alexander G. ( June 2022 , Water)

   The extensive interest in sustainable water management reflects the extent to which the global water landscape has changed in the past twenty years, which is a natural development of changes in water resources and an increase in the level of imbalance between water supply and demand. In this paper, a simulation model based on system dynamics (SD) methodology was developed to aid sustainable water management efforts in a semi-arid region. Six policy scenarios were used to study, analyze, and assess water management trends in the Southeast region of New Mexico, USA. The modeling process included two phases: calibration (2000–2015) and future prediction (2016–2050). Several statistical criteria were applied to assess the developed model performance. The findings revealed that the simulated outputs were in excellent agreement with the historical data, indicating accurate model simulation. The SD model’s determination coefficients ranged from 0.9288 to 0.9936 and the index of agreement values ranged from 0.9397 to 0.9958. Findings for the business-as-usual scenario indicated that total water withdrawals and total population will continue to rise, whereas groundwater storage, agricultural consumptive water use, and total consumptive water use will decrease over the simulated period. Sensitivity analysis using Monte Carlo simulation indicated that cultivated irrigated land change is the most influential parameter affecting groundwater storage, water supply storage change (total withdrawals), agricultural consumptive water use, and total consumptive water use. The changes occurring in the agricultural cultivated area had a great influence on controlling the groundwater system. Overall, the results showed that our SD model has been successful in capturing the system’s dynamic behavior, and confirmed its capability in modeling water management issues for policy and decision makers under semi-arid conditions. 

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2. A Spatially Detailed and Economically Complete Blue Water Footprint of the United States

   https://doi.org/10.5194/hess-2017-650  

   Rushforth, Richard R. ; Ruddell, Benjamin L. ( January 2017 , Hydrology and Earth System Sciences Discussions)

   This paper quantifies and maps a spatially detailed and economically complete blue water footprint for the United States, utilizing the National Water Economy Database version 1.1 (NWED). NWED utilizes multiple mesoscale federal data resources from the United States Geological Survey (USGS), the United States Department of Agriculture (USDA), the U.S. Energy Information Administration (EIA), the U.S. Department of Transportation (USDOT), the U.S. Department of Energy (USDOE), and the U.S. Bureau of Labor Statistics (BLS) to quantify water use, economic trade, and commodity flows to construct this water footprint. Results corroborate previous studies in both the magnitude of the U.S. water footprint (F) and in the observed pattern of virtual water flows. The median water footprint (F_CUMed) of the U.S. is 181 966 Mm³ (F_Withdrawal: 400 844 Mm³; F_CUMax: 222 144 Mm³; F_CUMin: 61 117 Mm³) and the median per capita water footprint (F'_CUMed) of the U.S. is 589 m³ capita^−1 (F'_Withdrawal: 1298 m³ capita^−1; F'_CUMax: 720 m³ capita^−1; F'_CUMin: 198 m³ capita^−1). The U.S. hydro-economic network is centered on cities and is dominated by the local and regional scales. Approximately (58 %) of U.S. water consumption is for the direct and indirect use by cities. Further, the water footprint of agriculture and livestock is 93 % of the total U.S. water footprint, and is dominated by irrigated agriculture in the Western U.S. The water footprint of the industrial, domestic, and power economic sectors is centered on population centers, while the water footprint of the mining sector is highly dependent on the location of mineral resources. Owing to uncertainty in consumptive use coefficients alone, the mesoscale blue water footprint uncertainty ranges from 63 % to over 99 % depending on location. Harmonized region-specific, economic sector-specific consumption coefficients are necessary to reduce water footprint uncertainties and to better understand the human economy's water use impact on the hydrosphere. 

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3. Systematic review: Wearable remote monitoring to detect nonalcohol/nonnicotine‐related substance use disorder symptoms

   https://doi.org/10.1111/ajad.13341  

   Oesterle, Tyler S. ; Karpyak, Victor M. ; Coombes, Brandon J. ; Athreya, Arjun P. ; Breitinger, Scott A. ; Correa da Costa, Sabrina ; Dana) Gerberi, Danielle J. ( November 2022 , The American Journal on Addictions)

   Abstract Background and Objectives Substance use disorders (SUDs) are chronic relapsing diseases characterized by significant morbidity and mortality. Phenomenologically, patients with SUDs present with a repeating cycle of intoxication, withdrawal, and craving, significantly impacting their diagnosis and treatment. There is a need for better identification and monitoring of these disease states. Remote monitoring chronic illness with wearable devices offers a passive, unobtrusive, constant physiological data assessment. We evaluate the current evidence base for remote monitoring of nonalcohol, nonnicotine SUDs. Methods We performed a systematic, comprehensive literature review and screened 1942 papers. Results We found 15 studies that focused mainly on the intoxication stage of SUD. These studies used wearable sensors measuring several physiological parameters (ECG, HR, O 2 , Accelerometer, EDA, temperature) and implemented study‐specific algorithms to evaluate the data. Discussion and Conclusions Studies were extracted, organized, and analyzed based on the three SUD disease states. The sample sizes were relatively small, focused primarily on the intoxication stage, had low monitoring compliance, and required significant computational power preventing “real‐time” results. Cardiovascular data was the most consistently valuable data in the predictive algorithms. This review demonstrates that there is currently insufficient evidence to support remote monitoring of SUDs through wearable devices. Scientific Significance This is the first systematic review to show the available data on wearable remote monitoring of SUD symptoms in each stage of the disease cycle. This clinically relevant approach demonstrates what we know and do not know about the remote monitoring of SUDs within disease states. 

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4. JRmGRN: joint reconstruction of multiple gene regulatory networks with common hub genes using data from multiple tissues or conditions

   https://doi.org/10.1093/bioinformatics/bty354  

   Deng, Wenping ; Zhang, Kui ; Liu, Sanzhen ; Zhao, Patrick X. ; Xu, Shizhong ; Wei, Hairong ; Birol, ed., Inanc ( April 2018 , Bioinformatics)

   Joint reconstruction of multiple gene regulatory networks (GRNs) using gene expression data from multiple tissues/conditions is very important for understanding common and tissue/condition-specific regulation. However, there are currently no computational models and methods available for directly constructing such multiple GRNs that not only share some common hub genes but also possess tissue/condition-specific regulatory edges.

   In this paper, we proposed a new graphic Gaussian model for joint reconstruction of multiple gene regulatory networks (JRmGRN), which highlighted hub genes, using gene expression data from several tissues/conditions. Under the framework of Gaussian graphical model, JRmGRN method constructs the GRNs through maximizing a penalized log likelihood function. We formulated it as a convex optimization problem, and then solved it with an alternating direction method of multipliers (ADMM) algorithm. The performance of JRmGRN was first evaluated with synthetic data and the results showed that JRmGRN outperformed several other methods for reconstruction of GRNs. We also applied our method to real Arabidopsis thaliana RNA-seq data from two light regime conditions in comparison with other methods, and both common hub genes and some conditions-specific hub genes were identified with higher accuracy and precision.

   JRmGRN is available as a R program from: https://github.com/wenpingd.

   Supplementary data are available at Bioinformatics online.

    

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5. Field experiments have enhanced our understanding of drought impacts on terrestrial ecosystems—But where do we go from here?

   https://doi.org/10.1111/1365-2435.14460  

   Knapp, Alan K. ; Condon, Kathleen V. ; Folks, Christine C. ; Sturchio, Matthew A. ; Griffin‐Nolan, Robert J. ; Kannenberg, Steven A. ; Gill, Amy S. ; Hajek, Olivia L. ; Siggers, J. Alexander ; Smith, Melinda D. ( October 2023 , Functional Ecology)

   We review results from field experiments that simulate drought, an ecologically impactful global change threat that is predicted to increase in magnitude, extent, duration and frequency. Our goal is to address, from primarily an ecosystem perspective, the questions ‘What have we learned from drought experiments?’ and ‘Where do we go from here?’.

   Drought experiments are among the most numerous climate change manipulations and have been deployed across a wide range of biomes, although most are conducted in short‐statured, water‐limited ecosystems. Collectively, these experiments have enabled ecologists to quantify the negative responses to drought that occur for most aspects of ecosystem structure and function. Multiple meta‐analyses of responses have also enabled comparisons of relative effect sizes of drought across hundreds of sites, particularly for carbon cycle metrics. Overall, drought experiments have provided strong evidence that ecosystem sensitivity to drought increases with aridity, but that plant traits associated with aridity are not necessarily predictive of drought resistance. There is also intriguing evidence that as drought magnitude or duration increases to extreme levels, plant strategies may shift from drought tolerance to drought escape/avoidance.

   We highlight three areas where more drought experiments are needed to advance our understanding. First, because drought is intensifying in multiple ways, experiments are needed that address alterations in drought magnitude versus duration, timing and/or frequency (individually and interactively). Second, drivers of drought may be shifting—from precipitation deficits to rising atmospheric demand for water—and disentangling how ecosystems respond to changes in hydrological ‘supply versus demand’ is critical for understanding drought impacts in the future. Finally, more attention should be focussed on post‐drought recovery periods since legacies of drought can affect ecosystem functioning much longer than the drought itself.

   We conclude with a call for a fundamental shift in the focus of drought experiments from those designed primarily as ‘response experiments’, quantifying the magnitude of change in ecosystem structure and function, to more ‘mechanistic experiments’—those that explicitly manipulate ecological processes or attributes thought to underpin drought responses.

   Read the freePlain Language Summaryfor this article on the Journal blog.

    

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