ethicalabs/Research-Intent-Collab huggingface dataset:
Promoting and Enhancing Sustainable Livelihood Options as an Adaptive Strategy to Reduce Vulnerability and Increase Resilience to Climate Change Impact in the Central Himalaya

In the rural landscape of the central Himalaya, livelihoods of the people depend heavily on agriculture, animal husbandry and forestry sectors and they are inextricably connected with each other. The role of forest goods and services in sustaining the productivity of the agriculture and animal husbandry is immense. The central Himalayan region has a number of characteristics that increase the region’s vulnerability to climate change impacts. Higher population and poverty, coupled with low resilience to climate risks, make the region highly vulnerable to climate change. Livelihoods of majority of the poor/marginal and traditional societies are heavily dependent on natural resources particularly in the hilly region. Changes in the availability of the resources, accentuated by climate risks, are expected to have far-reaching implications. These risks could undermine the gains made in poverty reduction and livelihoods and impede progress towards meeting the desired national development goals. International Panel on Climate Change (IPCC) has confirmed that we are now locked into inevitable changes in climate system. Changes on climate such as mean temperature, increased frequency and intensity of extreme weather events as well as changes in precipitation pattern, sea level rise and glaciers retreat have been projected. Although there is a lack of certainty in predicting and quantifying climate change impacts on socio-economic systems, it is well known that climate change impacts threaten a major dimension of human well being, namely food security. These climate change related risks threaten approximately 70 % of the rural people largely dependent on rain-fed agriculture in the central Himalaya. For the rural poor, human security is synonymous with food security. Extreme droughts or untimely heavy rains have often led not only to loss of life, but also an exacerbation of poverty conditions through the degradation of the natural resource base, leading to increase in poverty particularly in low income groups. Hence, low income group or poor people are the most vulnerable to the impacts of climate change.
Design Concepts for an Outage Control Center Information Dashboard

The nuclear industry, and the business world in general, is facing a rapidly increasing amount of data to be dealt with on a daily basis. In the last two decades, the steady improvement of data storage devices and means to create and collect data along the way influenced the manner in which we deal with information. Most data is still stored without filtering and refinement for later use. Many functions at a nuclear power plant generate vast amounts of data, with scheduled and unscheduled outages being a prime example of a source of some of the most complex data sets at the plant. To make matters worse, modern information and communications technology is making it possible to collect and store data faster than our ability to use it for making decisions. However, in most applications, especially outages, raw data has no value in itself; instead, managers, engineers and other specialists want to extract the information contained in it. The complexity and sheer volume of data could lead to information overload, resulting in getting lost in data that may be irrelevant to the task at hand, processed in an inappropriate way, or presented in an ineffective way. To prevent information overload,more » many data sources are ignored so production opportunities are lost because utilities lack the ability to deal with the enormous data volumes properly. Decision-makers are often confronted with large amounts of disparate, conflicting and dynamic information, which are available from multiple heterogeneous sources. Information and communication technologies alone will not solve this problem. Utilities need effective methods to exploit and use the hidden opportunities and knowledge residing in unexplored data resources. Superior performance before, during and after outages depends upon the right information being available at the right time to the right people. Acquisition of raw data is the easy part; instead, it is the ability to use advanced analytical, data processing and data visualization methods to turn the data into reliable information and comprehensible, actionable information. Techniques like data mining, filtering and analysis only work reliably for well-defined and well-understood problems. The path from data to decision is more complex. The ability to communicate knowledge during outages and emergent issues is crucial. This paper presents an approach to turn the unused data into an opportunity: applying principles from semiotics, human factors and visual analytics to transform the traditional way of processing outage data into media that will improve the collective situation awareness, knowledge, decisions, actions and overall performance of the entire outage team, and also support the reliability, quality and overall effectiveness of maintenance work. The application of the proposed visualization methods will become the medium of a semi-automated analytical process where humans and machines cooperate using their respective, distinct capabilities for the most effective results.« less
Phase Transitions, Patterns and Statistical Mechanics of Front Propagation in a Dynamic Random Impurity Model for Strip, Unusual Trees and Other Geometries

ABSTRACTA dynamic random impurity model is studied lor describing the evolution of an advancing interface through a multiphase random medium containing mobile impurities. A short range repulsion between the Iront and the impurities leads to an aggregation process along the front, and to the trapping of aggregates behind the front. The patterns of trapped impurities are found to be self-organized. Some theoretical treatment is performed through a transfer matrix technique in various geometries: trees with loops instead of branches, chains of squares and triangles joined by vertices. Arguments are given for applications of such concepts, techniques and models in various cases: chemistry, biology, trafic, sociology, economy,…
Clinical Pharmacists vs. Antimicrobial Resistance: Evidence-Based Strategies and Stewardship Impact in Modern Healthcare: A Review

Background: Antimicrobial resistance (AMR) has been a significant problem to human health as antibiotics are misused and overused. Due to antimicrobial stewardship programs (ASPs), the emergence of antimicrobial resistance is hindering the performance of healthcare systems, and clinical pharmacists have become a necessity in these programs. Objectives: This review discusses the changing role of clinical pharmacists in the fight against AMR through evidence-based methods. Methods: Various strategies were reviewed including drug optimization, de-escalation, intravenous-to-oral conversions, therapeutic drug monitoring, and educating prescribers. The role of clinical pharmacists as part of multidisciplinary teams performing evidence-based interventions in real-time was emphasized. Results: Intervention by pharmacists has been shown to significantly reduce inappropriate antibiotic use, hospital-acquired infections, resistance patterns, and healthcare expenditures, while improving patient outcomes and compliance with stewardship procedures. Additionally, their role in surveillance, audit-feedback systems, and policy development enhances the clinical effectiveness of ASPs in both hospital and community-based settings. Conclusion: Challenges to the implementation of clinical pharmacist-led ASP initiatives such as limited resources, interprofessional barriers, and specialized training still exist. Nonetheless, the strategic integration of clinical pharmacist initiatives into ASPs is possibly the sustainable path forward to maintaining optimal antibiotic efficacy. This review emphasizes the importance of expanding pharmacist roles, promoting ongoing training, and promoting interprofessional collaboration to mitigate the global threat posed by AMR. Keywords: Clinical pharmacists, Antimicrobial resistance (AMR), Antimicrobial stewardship (AMS), Evidence-based interventions, Drug optimization, Healthcare-associated infections
Mapping chromatin remodelling in glioblastoma identifies epigenetic regulation of key molecular pathways and novel druggable targets

Abstract                 Analysis of chromatin remodelling in neoplastic stem cells as compared to ontogenetically related neural stem cells, reveals multifactorial epigenetic regulation of signalling pathways known to contribute to glioblastoma development. It also identifies novel epigenetically regulated druggable target genes on a patient-specific level, including SMOX and GABBR2 which could be further developed for future translational approaches to more effectively treat this neoplasm.
Central bank digital currencies

Advances in technology and digitalisation are widespread and affect all facets of life, including jobs, education and social interactions. Electronic devices and high-speed networks have become practically ubiquitous, leading to the rise of the modern, digital consumer, who is positively inclined towards mobile and online platforms and is increasingly the driving force of consumption. The need for speed, convenience, round-the-clock availability and an enhanced user experience has led to significant changes in the payments space. These include the emergence of non-bank payment service providers, private cryptocurrencies and real time gross settlement (RTGS) enhancements. These changes have prompted many central banks to study the possibility of a central bank digital currency (CBDC) as a payment token and the impact it could have on their economies. Electronic central bank-based currencies have been in place for decades. They are in the form of banknotes and serve as reserve balances that banks and participating financial institutions maintain with central banks. The latter are used for interbank settlements. CBDC is a potential new form of money, issued digitally by the central bank and intended to serve as legal tender. Given that these are government-issued legal tender, CBDCs will need to be backed by government debt. This paper aims to provide an understanding of the concept of CBDCs, the case for and against CBDCs and the CBDC experiments worldwide that explore central bank investigations around CBDC usage.
Energy density functional in nuclear physics

Fundamentals of energy density functional in nuclear physics are presented. Much attention is paid to a mathematically rigorous treatment of deriving the energy density functional. The specific features of the density functional used in studying many-nucleon systems, which is quite different from that used in many-electron systems, are also shown. The intended audience are physicists, chemists and mathematicians. In particular those who will start to study the density functional theory are intended.
Correction: Community concerns about genetic discrimination in life insurance persist in Australia: A survey of consumers offered genetic testing

Correction to: European Journal of Human Geneticshttps://doi.org/10.1038/s41431-023-01373-1, published online 11 May 2023 In the sentence beginning ‘When asked about regulation of the use of genetic test results…’ in this article, the value ‘91%’ should have been ‘88%’. The original article has been corrected.
Additional file 3 of Beyond coverage: a qualitative study exploring the perceived impact of Gabon’s health insurance plan on access to and quality of prenatal care

Additional file 3. Framework for non-participant observation
Validation of an mRNA vaccine platform expressing eGFP and development of a recombinant Streptococcus gordonii as live vaccine vector

Thesis project involved the development of an mRNA and a recombinant Streptococcus gordonii vaccine model. The mRNA vaccine was produced starting from the design of a DNA plasmid template encoding for the enhanced Green Fluorescent Protein (eGFP) (Chapter 2). The mRNA was transcribed, modified and complexed with a delivery system. The vaccine complex obtained was evaluated for the transfection efficiency and the protein expression in two mammalian cell lines: HeLa cells and C2C12 cells. The expression of the protein was already detectable 1 hour after transfection in both cell lines, with an increase after 6h and 12h respectively. Observation at inverted microscope showed a progressive detachment of the transfected cells from the surface of the wells, indicating a possible cell death after transfection. In addition, it was observed that cell death occurs massively only when the mRNA-lipofectamine complex is transfected, but not when mRNA or lipofectamine alone is transfected, suggesting a direct correlation with the expression of the heterologous protein. These results led us to investigate cell death phenomenon by analyzing with annexin V and propidium iodide. Obtained results confirmed the cell death, whereas phagocytosis assays revealed that transfected cells were more efficiently engulfed by macrophage like THP-1 cell respect the untreated ones, suggesting a possible immunogenic action of the cells expressing the heterologous protein. The second part of this thesis (Chapter 3) describes the development of a Streptococus gordonii strain expressing the hemagglutinin subunit HA1 of influenza A/Puerto Rico 8/1934 for vaccination purposes. For the construction of the vaccine vector, the previously established host-vector system for heterologous gene expression in S. gordonii was used. A synthetic DNA encoding for the HA1 subunit (PR8) was custom synthesized and cloned into pSMB55 shuttle vector for the construction of emm6::ha1(PR8) gene fusion, that was subsequently PCR amplified and transformed into S. gordonii GP1295 recipient strain. The obtain recombinant clone, TP484C2, was first sequenced to confirm chromosomal integration of the genetic construct and then used for M6-HA1(PR8) protein expression analysis performed by western blot and flow cytometry assay, that confirmed the heterologous protein expression at bacterial surface. Preliminary data obtained through these studies provide basis for future in vivo studies on heterologous immunization strategy using both, mRNA vaccine and recombinant Streptococcus gordonii. Lastly, Chapter 4 aimed to briefly describe the methodology learnt in my in-company period in VisMederi Group in Siena.
The Iraq War and the Responsibility to Protect: Uses, Abuses and Consequences for the Future of Humanitarian Intervention

Before the 2003 Iraq war, the political leadership of the United States and United Kingdom had to sell the case for war to their people and the world. This was attempted through a number of speeches that employed rhetorical justifications for the war. Two prominent justifications used during this period involved the employment of security and humanitarian narratives. The security narrative focused on claims regarding Iraq's undermining of international law, possession of weapons of mass destruction and threat to the world. The humanitarian narrative revolved around claims about human suffering in Iraq and the need to liberate its people. While it is widely assumed that security is the dominant casus belli in the post-9/11 world, there is much evidence to suggest that the humanitarian justifications that played a critical role in the military interventions of the 1990s were still important after 9/11. The use of humanitarian justifications for the Iraq war clearly has implications for the ‘responsibility t...
Synthesis and Electrochemistry Characteristics of Layered Li[Li&lt;sub&gt;(1/3-x)&lt;/sub&gt;Mn&lt;sub&gt;(2/3-x)&lt;/sub&gt;Ni&lt;sub&gt;x&lt;/sub&gt;Co&lt;sub&gt;x&lt;/sub&gt;]O&lt;sub&gt;2&lt;/sub&gt; (x = 0.1, 0.15, 0.2, 0.22, 0.25) Cathode Materials for Lithium Secondary Batteries

Li[Li(1/3-x)Mn(2/3-x)NixCox]O2 (x=0.1, 0.15, 0.2, 0.22, 0.25) compounds were synthesized and studied by the X-ray diffraction method and electrochemical techniques. The XRD analysis showed that these compounds could be classified as the α-NaFeO2 structure type. Both a and c parameters decreased linearly, while c/a increased with the increase of Ni and Co content. The first discharge capacity increases with increasing lithium content at the 3a sites in the Li[Li(1/3-x)Mn(2/3-x)NixCox]O2. A Li[Li0.23Mn0.57Ni0.1Co0.1]O2 electrode delivers discharge capacities of 238 mAh/g at C/10 between 4.6V and 2.5V.
Can low-cost sensors (LCS) enhance air quality monitoring for personal pollution exposure assessment?

Abstract                Laboratory and field assessments of low-cost sensors (LCS) are essential for ensuring the accuracy of PM2.5 measurements collected by citizens in air quality campaigns. Evaluation of Sensirion SPS30 (LCS SPS30) in controlled laboratory setting showed a coefficient of determination (R                   2) ranging from 0.81–0.99 and a root mean square error (RMSE) from 0.81–61.72 μg m−3, at average concentration of 21.5 μg m−3. In contrast, co-location assessment at an average concentration of 9 μg m−3 resulted in R                   2 of 0.5 and a RMSE of 6.82 μg m−3. The results demonstrated that the sensor met micro-environmental monitoring standards (accuracy &lt; 25%) and United States Environmental Protection Agency's performance criteria (RMSE ≤ 7 μg m−3, R                   2 &gt; 0.7) only at relative humidity (RH) levels below 60%, emphasising its strong sensitivity to RH and the need for RH-dependent data corrections. The observed underestimation or overestimation of PM2.5 readings was primarily attributed to variations in particle composition and concentration. Despite accuracy variations, LCSs can effectively capture spatiotemporal urban air quality patterns and identify pollution hotspots in community monitoring, particularly in low-pollution environments. In a citizen-led PM2.5 monitoring campaign in Maribor, Slovenia, the lowest concentrations were recorded at 15:00 (2.9 μg m−3), while the highest occurred during the morning rush-hour (4.8 μg m−3), likely attributed to the planetary boundary layer’s impact on atmospheric particulate dispersion. Spatial analysis revealed that hotspots clustered near intersections, where vehicle waiting time is the longest.
A Tutorial about Random Neural Networks in Supervised Learning

Random Neural Networks (RNNs) are a class of Neural Networks (NNs) that can also be seen as a specific type of queuing network. They have been successfully used in several domains during the last 25 years, as queuing networks to analyze the performance of resource sharing in many engineering areas, as learning tools and in combinatorial optimization, where they are seen as neural systems, and also as models of neurological aspects of living beings. In this article we focus on their learning capabilities, and more specifically, we present a practical guide for using the RNN to solve supervised learning problems. We give a general description of these models using almost indistinctly the terminology of Queuing Theory and the neural one. We present the standard learning procedures used by RNNs, adapted from similar well-established improvements in the standard NN field. We describe in particular a set of learning algorithms covering techniques based on the use of first order and, then, of second order derivatives. We also discuss some issues related to these objects and present new perspectives about their use in supervised learning problems. The tutorial describes their most relevant applications, and also provides a large bibliography.
INTELLIGENT DISTRIBUTED DYNAMIC FOG COMPUTING FRAMEWORK

Одним из направлений развития сетей связи 5G и сетей связи 2030 является интегрирование в сеть распределенных вычислительных структур, таких как системы пограничных и туманных вычислений (Fog), которые призваны выполнить децентрализацию вычислительной части сетей. В связи с этим необходимо исследовать и определить принципы предоставления услуг на основе распределенной вычислительной инфраструктуры, в том числе в условиях ограниченности ресурсов отдельно взятых составных частей (Fog-устройства). Предлагается новый фреймворк распределенной динамической вычислительной системы туманных вычислений на основе микросервисного архитектурного подхода к реализации, развертыванию и миграции программного обеспечения предоставляемых услуг. Исследуется типовая архитектура микросервисного подхода и ее имплементация в туманные вычисления, а также рассматриваются два алгоритма: алгоритм K-средних для нахождения центра пользовательской нагрузки и алгоритм роевой оптимизации для определения устройства тумана с необходимыми характеристиками для последующей миграции микросервиса.                                                                                             One of the directions of 5G and 2030 communications networks development is the network-integrated distributed structures, such as edge computing (MEC) and Fog computing, which are designed to decentralize the computing part of networks. In this regard, it is necessary to investigate and determine the principles of providing services based on a distributed computing infrastructure, including in conditions of limited resources of individual components (Fog devices). This article proposes a new framework for a distributed dynamic computing system of fog computing based on a microservice architectural approach to the implementation, deployment, and software migration of the services. The article examines the typical architecture of the microservice approach and its implementation in fog computing, and also investigates two algorithms: K-means for finding the center of user load, swarm optimization (PSO) to determine the fog device with the necessary characteristics for the subsequent migration of the microservice.
Modeling the Brazilian Cerrado land use change highlights the need to account for private property sizes for biodiversity conservation

AbstractSimulating future land use changes can be an important tool to support decision-making, especially in areas that are experiencing rapid anthropogenic pressure, such as the Cerrado–Brazilian savanna. Here we used a spatially-explicit model to identify the main drivers of native vegetation loss in the Cerrado and then extrapolate this loss for 2050 and 2070. We also analyzed the role of property size in complex Brazilian environmental laws in determining different outcomes of these projections. Our results show that distance to rivers, roads, and cities, agricultural potential, permanent and annual crop agriculture, and cattle led to observed/historical loss of vegetation, while protected areas  prevented such loss. Assuming full adoption of the current Forest Code, the Cerrado may lose 26.5 million ha (± 11.8 95% C.I.) of native vegetation by 2050 and 30.6 million ha (± 12.8 95% C.I.) by 2070, and this loss shall occur mainly within large properties. In terms of reconciling conservation and agricultural production, we recommend that public policies focus primarily on large farms, such as protecting 30% of the area of properties larger than 2500 ha, which would avoid a loss of more than 4.1 million hectares of native vegetation, corresponding to 13% of the predicted loss by 2070.
Aplikasi Human Resource Information System (HRIS) pada Azwa Production Jakarta

Azwa Production merupakan perusahaan yang berjalan dibidang event organizer, percetakan, dan penjualan produk-produk kebutuhan kantor dengan desain dan produk yang ditentukan langsung  oleh client. Pada perusahaan tersebut masih menggunakan sistem yang masih konvensional menggunakan aplikasi pengolah angka dan pengolah kata sederhana untuk mengolah data-data pegawainya.  Dari permasalahan tersebut peneliti ingin merancang sistem pengolahan data pegawai pada perusahaan tersebut sehingga dapat membantu perusahaan dalam mengelola, serta menyimpan data-data tersebut dengan aman di database. Dengan menggunakan metode pendekatan deskriptif peneliti mengumpulkan data dengan cara observasi, peninjauan kepustakaan, dan wawancara. Hasil dari penelitian ini adalah memudahkan perusahaan dalam mengelola dan menyimpan data pegawainya.