HydroPy (v1.0): a new global hydrology model written in Python

Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components and their past evolution as well as potential future development under various scenarios. While GHMs have been part of the hydrologist's toolbox for several decades, the models are continuously being developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance, and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge; however, they can – at least to some extent – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similarly to MPI-HM and thus conclude the successful transition from MPI-HM to HydroPy.

California Wildfire Exposure, Vulnerability, and Mental Health: Who gets to recover and who does not?

One of the various aftereffects of persistent climate change is an upsurge in the frequency, severity, and effect of wildfires on the wellbeing of suffering communities. The destruction and wreckage of one's home, properties, and the surrounding neighborhood, as well as the threat to one's psychological safety and the safety of loved ones, can have long-term effects on survivors' mental health. The central goal of this study, therefore, is threefold. Firstly, identify the significant qualitative and quantitative studies that examine the impacts of wildfire on mental health. This study mainly focuses on studies that capture the effects of wildfire, smoke, and air quality in California and how that affected the local communities based on their vulnerability determinants. Secondly, the study examines both types of studies to find common grounds regarding the most vulnerable population and their mental health, their ability to seek professional help, and barriers to the road to recovery. Finally, this study provides evidence-based strategies for including more vulnerable members of society in receiving sufficient and timely psychological care to recover from PTSD, trauma, distress, and hopelessness. Migrant farmworkers, particularly younger female Hispanic and indigenous workers, suffer from the wildfire's long-term stress, PTSD, depression, and emotional distress. Furthermore, the continued COVID-19 deepens the gap, social stigma, and barriers to receiving sufficient mental health care to recover and rehabilitate traumatic wildfire exposure. A localized mental healthcare support system based on equity, with flexible infrastructure and greater accessibility, promises to be more efficient and advantageous for underrepresented and vulnerable individuals seeking mental health treatment and quick recovery.

IoMT, Edge Computing, Blockchain, and Deep Learning for Next Generation Healthcare Systems (Preprint)

UNSTRUCTURED Processing medical data, diagnosing diseases, determining the best possible medical centers or physicians, and recommending the more effective remedies or drugs in the earliest time are the most important challenges to deploy intelligent systems for healthcare purposes. Hence, utilization of the Internet of Medical Things (IoMT) with Edge Computing (EC) technology will result in a strong network to aggregate the healthcare data more reliably and solve the aforementioned challenges. However, the administration of the millions of individuals with a wide variety of physical or mental disorders is another challenge associated with the use of such Artificial Intelligence-based platforms, especially when it comes to a large number of insurance conditions and companies. Furthermore, although the EC-based platforms can increase the security of the data, there are still vulnerable to face some cyber-attacks. Thus, the privacy of sensitive personal information of patients should be considered. Blockchain is a suitable option to overcome the problems associated with medical documentation and administration of patient’s affairs using smart contracts. An EC-based platform based on blockchain to improve the weaknesses of conventional smart healthcare systems is rendered in this research. The proposed platform takes the advantage of both EC and blockchain in the terms of speed, security, accuracy, and bandwidth. It should be noted that this method could be utilized as a flexible infrastructure for the next generation healthcare systems using any kind of crypto network like Bitcoin, Ethereum, Cardano, etc.

HydroPy (v1.0): A new global hydrology model written in Python

Global hydrological models (GHMs) are a useful tool in the assessment of the land surface water balance. They are used to further the understanding of interactions between water balance components as well as their past evolution and potential future development under various scenarios. While GHMs are a part of the Hydrologist's toolbox since several decades, the models are continuously developed. In our study, we present the HydroPy model, a revised version of an established GHM, the Max-Planck Institute for Meteorology's Hydrology Model (MPI-HM). Being rewritten in Python, the new model requires much less effort in maintenance and due to its flexible infrastructure, new processes can be easily implemented. Besides providing a thorough documentation of the processes currently implemented in HydroPy, we demonstrate the skill of the model in simulating the land surface water balance. We find that evapotranspiration is reproduced realistically for the majority of the land surface but is underestimated in the tropics. The simulated river discharge correlates well with observations. Biases are evident for the annual accumulated discharge, however they can – at least to some part – be attributed to discrepancies between the meteorological model forcing data and the observations. Finally, we show that HydroPy performs very similar to MPI-HM and, thus, conclude the successful transition from MPI-HM to HydroPy.

UPF1-Mediated RNA Decay—Danse Macabre in a Cloud

Nonsense-mediated RNA decay (NMD) is the prototype example of a whole family of RNA decay pathways that unfold around a common central effector protein called UPF1. While NMD in yeast appears to be a linear pathway, NMD in higher eukaryotes is a multifaceted phenomenon with high variability with respect to substrate RNAs, degradation efficiency, effector proteins and decay-triggering RNA features. Despite increasing knowledge of the mechanistic details, it seems ever more difficult to define NMD and to clearly distinguish it from a growing list of other UPF1-mediated RNA decay pathways (UMDs). With a focus on mammalian NMD, we here critically examine the prevailing NMD models and the gaps and inconsistencies in these models. By exploring the minimal requirements for NMD and other UMDs, we try to elucidate whether they are separate and definable pathways, or rather variations of the same phenomenon. Finally, we suggest that the operating principle of the UPF1-mediated decay family could be considered similar to that of a computing cloud providing a flexible infrastructure with rapid elasticity and dynamic access according to specific user needs.

Challenges of Confidentiality and Security in Mobile Cloud Computing and Protective Measures

Mobile Cloud Computing (MCC) has a significant potential to provide scalability, reliability, extra battery life, and additional storage capacity. Due to the flexible infrastructure and simplicity of access, cloud computing has become widespread. Energy consumption and execution time have also considerably enhanced by shifting the execution of resources consuming tasks that bring the benefit to mobile users. However, security and privacy is the major barrier to this growing trend of computing aptitude. Noteworthy efforts have already been made by the academic and research organizations to build secure computing infrastructures but various challenges are stay alive in security procedure of MCC. This manuscript provides a broad analysis of confidentiality and security challenges in mobile cloud computing and also discusses how to overcome these loopholes.

Software-Defined Network Security

The future networks are expected to lead a hyper-connected society with the promise of high social and economic value. The goal is to solve today's network problems and provide satisfactory security. Thus, the future networks require a flexible infrastructure that is secure against cyberattacks. Software defined networking (SDN) can be considered as one of the building blocks of upcoming networking technologies. In this chapter, first, the limitations of today's networks are presented. Then, solutions to secure the networks with SDN components are given. This concept is referred to as “SDN for Security.” While SDN facilitates securing networks in general, it introduces additional challenges, mainly, the vulnerabilities of the SDN components such as the controller have to be addressed. Security for SDN aims at securing SDN assets and is discussed in the sequel. After reading this chapter, readers will obtain a comprehensive overview of the limitations of traditional networks, such as how SDN overcomes those limitations and the security issues thereof.

A Review and Classification of Assisted Living Systems

Europe’s social agenda for the “active elderly” is based upon a series of programs that provide a flexible infrastructure for their lives so that they are motivated, engaged in lifelong learning, and contributing to society. Economically speaking, Europe must engage in active aging research in order to avoid unsustainable health costs, and ambient assisted living (AAL) systems provide a platform for the elderly to remain living independently. This paper reviews research conducted within the area of AAL, and offers a taxonomy within which such systems may be classified. This classification distinguishes itself from others in that it categorises AAL systems in a top-down fashion, with the most important categories placed immediately to the left. In this paper, each section is explored further, and AAL systems are the focus. Entire AAL systems still cannot be fully evaluated, but their constituent technical parts can be assessed. The activities of daily living (ADLs) component was given further priority due to its potential for system evaluation, based on its ability to recognise ADLs with reasonable accuracy.