ethicalabs/Research-Intent-Collab huggingface dataset:
Hydrological and ecological controls on dissolved carbon concentrations in groundwater and carbon export to surface waters in a temperate pine forest watershed

Abstract. Export of soil carbon to superficial water through the drainage of groundwater is a significant but poorly documented component of the continental carbon budget. We monitored the concentrations of dissolved organic and inorganic carbon (DOC and DIC) in groundwaters and first order streams of a small temperate, forested and sandy watershed where hydrology occurs exclusively through drainage (no surface runoff). The studied watershed was also implemented for continuous measurements of groundwater table, precipitation, evapotranspiration, river discharge, and net ecosystem exchanges of sensible and latent heat fluxes as well as CO2. On a monthly basis, we found a good consistency between precipitation and the sum of evapotranspiration, drainage and groundwater storage. DOC and DIC temporary storage in groundwater and export to streams varied drastically during the hydrological cycle, the residence times of these two carbon forms varying from one month to several years. DOC concentrations in groundwater and streams were maximal at high water table and high stream discharge, when the water table reached the superficial organic rich layer of the soil. A large fraction of this winter DOC maximum was temporarily stored and further mineralized to DIC in the groundwater and only about 15 % was exported to streams during winter periods. In contrast, DIC, which was present in majority in the form of dissolved CO2 in groundwater and streams, was apparently diluted at high water table: DIC concentrations were maximum at low water table and low discharge in late summer and maximum pCO2 in groundwater corresponded to the late summer period of heterotrophic conditions (i.e., Reco &gt; GPP). Groundwater DIC peaked in late summer and was followed by a rapid loss of excess CO2 from stream surface to the atmosphere. Overall, mean carbon export was 7.5 g C m−2 yr−1 (50 % as DOC and 50 % as DIC) and represented only 1.5 % of the NEE. About 65 % of the DIC exported from groundwaters returned to the atmosphere in the form of CO2 in first order streams.
Training a Hidden Markov Model with a Bayesian Spiking Neural Network

It is of some interest to understand how statistically based mechanisms for signal processing might be integrated with biologically motivated mechanisms such as neural networks. This paper explores a novel hybrid approach for classifying segments of sequential data, such as individual spoken works. The approach combines a hidden Markov model (HMM) with a spiking neural network (SNN). The HMM, consisting of states and transitions, forms a fixed backbone with nonadaptive transition probabilities. The SNN, however, implements a biologically based Bayesian computation that derives from the spike timing-dependent plasticity (STDP) learning rule. The emission (observation) probabilities of the HMM are represented in the SNN and trained with the STDP rule. A separate SNN, each with the same architecture, is associated with each of the states of the HMM. Because of the STDP training, each SNN implements an expectation maximization algorithm to learn the emission probabilities for one HMM state. The model was studied on synthesized spike-train data and also on spoken word data. Preliminary results suggest its performance compares favorably with other biologically motivated approaches. Because of the model's uniqueness and initial promise, it warrants further study. It provides some new ideas on how the brain might implement the equivalent of an HMM in a neural circuit.
Abstract 2807: Distinctive microbiome signatures in colorectal cancer: A comparative metagenomic analysis

Abstract                The human gut microbiome is increasingly recognized for its role in colorectal cancer (CRC) pathogenesis. This study aims to delineate the microbiome characteristics of CRC patients compared to healthy individuals, using a comprehensive metagenomic approach.                We utilized a cohort of 80 CRC patients and an equal number of matched healthy controls. Fecal samples were collected and subjected to in-depth metagenomic sequencing, targeting both structural and functional profiles of the microbiome. Data analysis involved advanced bioinformatics techniques. Key observations were subsequently validated in an independent cohort to bolster the findings.                Our analysis revealed significant alterations in the microbiome composition of CRC patients versus healthy individuals. Notably, there was an increased prevalence of pathogenic bacteria, such as Bacteroides Vulgatus in CRC patients. These bacteria are implicated in promoting inflammation and carcinogenesis. Conversely, there was a noticeable depletion of beneficial microbes like Lactobacillus in the CRC group. Functionally, the microbiome in CRC patients was characterized by enriched pathways related to DNA repair, cell cycle control, and metabolism pathways like Citrate cycle and Galactose metabolism. Validation in an independent cohort confirmed these distinctive microbiomic patterns.                Our study provides compelling evidence of altered microbiome landscapes in CRC patients, highlighting potential roles in disease development and progression. These findings pave the way for further investigation into microbiome-based diagnostics and therapeutic interventions in colorectal cancer.                Citation Format: Ziqi Chen, Bei Ning Nie, Bin Luo, Ziliang Wang, Xinyi Wang. Distinctive microbiome signatures in colorectal cancer: A comparative metagenomic analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2807.
Noise analysis for sampling mixers using stochastic differential equations

We analyze three different sources of noise in a sampling mixer working at radio frequency (RF) or intermediate frequency. External RF and intrinsic noise are analyzed using conventional frequency domain methods. External local oscillator (LO) noise is analyzed in the time domain by solving a stochastic differential equation. We are able to take into account the time varying aspect of the LO noise coupling, and show that LO noise becomes important at high frequencies. An analytical expression for LO noise is obtained, which can be used to guide mixer design. LO noise is in addition to LO jitter, which should be combined with noise analysis to give a complete picture.
Role of Professional Women in Conflict Resolution and Peace Building in Niger Delta Region of Nigeria

Oil and gas activities in Southern part of Nigeria have exposed the region to environmental degradation and social vices. This problem has caused conflicts among stakeholders (government, community, companies, institutions, individuals), which has led to community clashes. These conflicts have resulted to the loss of lives and properties. They are also responsible for youth restiveness, low level of women empowerment and lack of peaceful coexistence in the region. This makes the promotion of understanding and dialogue to be a prime issue in the management of conflict, community peace and security. Professional women belong to professional bodies that spread into all works of life; academia, government, industry, legal institution, health sector, financial institutions, NGOs, security sector.  This paper discussed issues on causes of conflict in Niger Delta, what roles should professional women play in attaining peace, global examples of professional women in conflict resolution, role of professional women in Niger Delta, way in which women engage in conflict resolution and challenges women face in conflict resolution and peace building. The paper concluded that time has come for everybody to be aware of gender equality and involvement in conflict resolution and peace building. Professional women need to intensify effort in achieving this.
Fog Function: Serverless Fog Computing for Data Intensive IoT Services

Fog computing can support IoT services with fast response time and low bandwidth usage by moving computation from the cloud to edge devices. However, existing fog computing frameworks have limited flexibility to support dynamic service composition with a data-oriented approach. Function-as-a-Service (FaaS) is a promising programming model for fog computing to enhance flexibility, but the current event- or topic-based design of function triggering and the separation of data management and function execution result in inefficiency for data-intensive IoT services. To achieve both flexibility and efficiency, we propose a data-centric programming model called Fog Function and also introduce its underlying orchestration mechanism that leverages three types of contexts: data context, system context, and usage context. Moreover, we showcase a concrete use case for smart parking where Fog Function allows service developers to easily model their service logic with reduced learning efforts compared to a static service topology. Our performance evaluation results show that the Fog Function can be scaled to hundreds of fog nodes. Fog Function can improve system efficiency by saving 95% of the internal data traffic over cloud function and it can reduce service latency by 30% over edge function.
Bangladesh&amp;#39;s Approach towards International Criminal Law: A Case Study of International Crimes Tribunal Bangladesh

The International Crimes Tribunal Bangladesh that has been found by the Bangladeshi Government to try war crimes during India Pakistan war of 1971. The tribunal is violating the fair trial rights as guaranteed by Constitution, the International Covenant on Civil and Political Rights and International Humanitarian Law and the standard of the International Crimes Tribunal Bangladesh is far below than that setup by The International Criminal Tribunal for the former Yugoslavia, the International Criminal Tribunal for Rwanda and the International Criminal Court. These irregularities imply serious concern over the proceedings of the said tribunal. Study seeks to describe the International Law about war crimes particularly with respect to fair trial provisions and it compare the proceedings of the Bangladeshi tribunal with the other internationally recognized tribunals.
Neural Database Systems: Exploring Machine Learning-Based Indexing and Query Optimization Beyond Traditional Architectures

Could machine learning models serve as database systems themselves? The theoretical appeal is compelling: neural networks could learn data distributions, predict query results, and adapt to workloads automatically. However, current machine learning models fundamentally cannot replace database systems due to their probabilistic nature, inability to guarantee lossless data storage, and lack of ACID compliance. Despite this limitation, ML offers unprecedented opportunities for revolutionizing specific database components. This paper first examines why ML cannot replace databases entirely, then explores novel applications where ML can dramatically enhance database systems. We propose several innovative approaches including adaptive neural hash tables, reinforcement learning-based query planners, and predictive caching mechanisms that achieve 2-10x performance improvements while maintaining data integrity through hybrid architectures. Our unique contributions include workload-aware neural indexing, self-tuning buffer management, and intelligent storage tiering—approaches that no existing system has fully explored.
Information-theoretic approach to readout-error mitigation for quantum computers

Matched the published version
Reflections on Direct Access to the African Court on Human and Peoples’ Rights: A Cul De Sac?

Individuals and NGOs can directly access the African Court on Human and Peoples’ Rights if the state against which a case has been filed has made an optional declaration granting this access. Alternatively, they can access the Court if the African Commission on Human and Peoples’ Rights refers communications to it. However, two main barriers have riddled this structure. One, the few states that had made the optional declaration have begun to rapidly withdraw from it. Two, the African Commission, which was expected to mitigate such a situation where few states are making the optional declaration, is hardly referring cases to the Court. This paper examines these two barriers in tandem. It argues that if this status quo is sustained, then, sooner rather than later, this path treaded may lead the African human rights system to a cul-de-sac – back to a one tier system, composed of an accessible Commission and a Court inaccessible to both individuals and NGOs. Drawing lessons from the European and Inter-American Human Rights system, it recommends preventing this eventuality by amending the African Commission’s 2020 Rules of Procedure to provide for a default procedure of referral of cases from the Commission to the Court.
Excessive Editing of Selfies on Social Media: The Illusion of Sustainability in Mental Health among Female Adolescents

The advent of social media has transformed how female adolescents perceive and present themselves, leading many to engage in excessive editing of their selfies. This practice is often seen as a means to boost their mental well-being by enhancing their self-image. However, this reliance on edited images may create a false sense of sustainability regarding their mental health. This study aims to explore the relationship between excessive selfie editing on social media and appearance-related anxiety in female adolescents. Employing a quantitative descriptive correlational design, the research involved 150 high school students, selected through a snowball sampling method, to examine the connection between their photo editing behaviors and psychological outcomes. Two validated instruments were utilized for data collection: the Selfie Editing Behavior Scale and the Appearance Anxiety Scale. Results indicated a significant positive correlation between the frequency of selfie editing and the levels of appearance anxiety experienced by the participants. These findings suggest that while adolescents may seek satisfaction through image enhancement, such practices can exacerbate insecurities and adversely affect their mental health over time.
Principles of Law Governing Detention at International Criminal Tribunals

In this chapter, it is argued that the ‘contextual margins of appreciation’ and the discretionary powers vested in the tribunals’ detention authorities as identified in Chap. 3 are subject to a number of principles that underlie and constitute the core elements of the law governing detention at the international criminal tribunals. This requires first defining the notion of ‘legal principles’. Following this, a number of legal principles are distilled from the different sources of the tribunals’ detention law and from their case law. The resulting list of principles is not meant to be an exhaustive one.
How Evaluation Choices Distort the Outcome of Generative Drug Discovery

"How to evaluate the de novo designs proposed by a generative model?" Despite the transformative potential of generative deep learning in drug discovery, this seemingly simple question has no clear answer. The absence of standardized guidelines challenges both the benchmarking of generative approaches and the selection of molecules for prospective studies. In this work, we take a fresh - critical and constructive - perspective on de novo design evaluation. By training chemical language models, we analyze approximately 1 billion molecule designs and discover principles consistent across different neural networks and datasets. We uncover a key confounder: the size of the generated molecular library significantly impacts evaluation outcomes, often leading to misleading model comparisons. We find increasing the number of designs as a remedy and propose new and compute-efficient metrics to compute at large-scale. We also identify critical pitfalls in commonly used metrics - such as uniqueness and distributional similarity - that can distort assessments of generative performance. To address these issues, we propose new and refined strategies for reliable model comparison and design evaluation. Furthermore, when examining molecule selection and sampling strategies, our findings reveal the constraints to diversify the generated libraries and draw new parallels and distinctions between deep learning and drug discovery. We anticipate our findings to help reshape evaluation pipelines in generative drug discovery, paving the way for more reliable and reproducible generative modeling approaches.
Object detection and distance measurement with computer vision

With the development of computer and robotic technology, it becomes more and more common for robots to do hard, regular work for human. The appearance of robots has already changed humanity’s daily life and improved the efficiency of industry production. Among different kinds of robot applications, object detection and distance measurement are especially important for industry production. Like quality examination, product sorting and dimension measurement. These robots in these applications are programmable, high speed and high efficiency. To do object detection and distance measurement, deep learning and time of flight camera are widely used in industry. Engineers have already spent a lot of time doing related research. However, it is not easy and cheap to implement these methods. Deep learning needs so much computing power and industrial cameras are very expensive. Hence, in this report, the aim is to explore some easy ways to do object detection and distance measurement for some easy application in single background. To achieve this goal, some external sensors are necessary. Later the report will explain the theoretical basis and the experimental results of these two different ways. Then there will be a short discussion about the future development, which can improve the efficiency of these two methods covered in the report.
The Role of the United Nations, the African Union and Africa's Sub-Regional Organizations in Dealing with Africa's Human Rights Problems: Connecting Humanitarian Intervention and the Responsibility to Protect

AbstractThis article examines the basis for humanitarian intervention (HI) in the United Nations Charter, the African Union (AU) Charter and in a number of African sub-regional institutions. It traces the historical development of HI and argues that, while the right to HI emerged more than 100 years ago, that right also emerges from the Genocide Convention. The article argues that this treaty connects HI to the developing norm of the responsibility to protect (R2P) and examines the extent to which R2P is garnering wider support around the world. It focuses on the UN, and the various AU and sub-regional institutions and instruments that sanction HI. It assesses whether intervention can be authorized even in the absence of a UN Security Council mandate and examines the principles, application and interrelationship of R2P and HI in the African context. It traces the use of these norms in Africa, including in the various sub-regional structures, and evaluates the AU's political will and capability to deal with conflict and human rights abuse.
Action learning workshops for scientists: science communication for public engagement skills for the VLIR-Teams Active Parks research group

Universities and funding agencies are increasingly expecting research teams to include initiatives promoting public engagement, which often require public science communication. However, developing science communication skills can be challenging for researchers due to the limited availability of training opportunities. This practice insight documents the experiences of researchers participating in action-learning science communication workshops developed for the VLIR-Teams Active Parks research group in Cuenca, Ecuador. Through learning activities, researchers developed interdisciplinary science communication skills, including self-reflexivity, crafting speeches, and content creation for social media, to effectively communicate their study's outcomes on public park usage to stakeholders and various community audiences. The workshops proved effective in building public engagement skills and developing self-reflexivity, enabling researchers to create impactful, audience-centered initiatives that fostered meaningful connections with the community.
Appointment of Judges: A Key Issue of Judicial Independence

This comment emphasises the importance of the mechanisms for appointment of judges in maintaining judicial independence and public confidence in the judiciary. It argues that the power of appointment of judges should not be vested exclusively in the executive government. The paper examines the basic nature of the principal mechanisms for appointment of judges operating in different countries of the world. Particularly, it analyses the main strengths and weaknesses of the elective system of judicial selection and the system of appointing judges through parliamentary approval, consultation with the judiciary and legal profession and an independent commission. It concludes that the appointment of judges by using an independent commission may be considered an acceptable and effective mechanism for judicial appointments.
The impact of workplace relationships on nurse-reported quality of care and patient safety in the North West Province

Background There is a well-established relationship between the quality of workplace interactions among nurses, physicians, their managers, and nurse colleagues, and the subsequent improvement in patient outcomes. However, despite the growing body of research on this topic in developed countries, there remains a notable paucity of literature exploring these dynamics in developing countries.   Aim To investigate the impact of workplace relationships on nurse-reported quality of care and patient safety.   Design This study applied a cross-sectional survey design   Method A multiphase sampling method was applied. Purposive sampling was used to select the province, health sector and hospitals (n = 3). All-inclusive sampling was applied to in-patient units of the selected hospitals and nursing staff in those units (n = 236). Data was collected in April 2021, using validated instruments.   Results Nurse manager ability, leadership, and support was not experienced as positively contributing to the practice environment and had the most impact on quality of care and patient safety. Collegial nurse-physician relationships were experienced as contributing positively to the practice environment, and had the most impact on adverse events, namely medication errors, patient falls after admission and healthcare-associated infections. Increased exposure to COVID-19 patients resulted in more positive perceptions of nurses regarding collegial nurse-physician relationships. The most common perpetrators of workplace violence were supervisors/managers, followed by nursing colleagues. On average participants experience more personal workplace violence than physical workplace violence. Personal workplace violence had more effect on quality of care, patient safety, and adverse events than physical workplace violence.   Conclusion Positive workplace relationships or collegiality, especially nurse-manager relationships, appear to have the most impact on nurse-perceived quality of care and patient safety, followed by nurse-physician relationships, and then workplace violence.   Relevance to clinical practice The focus of education interventions should be on developing leadership, and recruiting and retaining relationship-focused leaders since leaders have the greatest impact on nurse-reported quality of care and patient safety.