ethicalabs/Research-Intent-Collab huggingface dataset:
Optimal Radius for Connectivity in Duty-Cycled Wireless Sensor Networks

We investigate the condition on transmission radius needed to achieve connectivity in duty-cycled wireless sensor networks (briefly, DC-WSN). First, we settle a conjecture of Das et. al. (2012) and prove that the connectivity condition on Random Geometric Graphs (RGG), given by Gupta and Kumar (1989), can be used to derive a weak sufficient condition to achieve connectivity in DC-WSN. To find a stronger result, we define a new vertex-based random connection model which is of independent interest. Following a proof technique of Penrose (1991) we prove that when the density of the nodes approaches infinity then a finite component of size greater than 1 exists with probability 0 in this model. We use this result to obtain an optimal condition on node transmission radius which is both necessary and sufficient to achieve connectivity and is hence optimal. The optimality of such a radius is also tested via simulation for two specific duty-cycle schemes, called the contiguous and the random selection duty-cycle scheme. Finally, we design a minimum-radius duty-cycling scheme that achieves connectivity with a transmission radius arbitrarily close to the one required in Random Geometric Graphs. The overhead in this case is that we have to spend some time computing the schedule.
Corporate social responsibility and financial reporting quality: the role of board gender diversity

Purpose This study aims to investigate the impact of corporate social responsibility (CSR) on financial reporting quality (FRQ). In addition, the role of board gender diversity (BGD) in the CSR–FRQ relationship is investigated.  Design/methodology/approach The study’s sample includes 135 nonfinancial Pakistan Stock Exchange-listed companies from 2010 to 2022. A multidimensional financial method is used to evaluate the firm’s CSR participation. FRQ is measured using the accrual-based model proposed by Jones (1991) and the accrual-quality-based model offered by Dechow et al. (1995). BGD is the proportion of female directors to total directors on the board. The fixed effect estimation model is employed in this investigation. Furthermore, the system-generalized approach of the moment estimation technique is employed to assess the robustness of the results. Moreover, a firm’s participation in CSR activities can be measured using a CSR index to ensure the reliability of the results.  Findings Empirical results demonstrate that firms with higher CSR engagements have higher FRQ, which supports the stakeholder perspective of CSR. Furthermore, this favorable association is more vital for organizations with more gender diversity on their boards.  Practical implications The study’s findings give policymakers, business managers, regulators and investors a better understanding of the impact of firm engagement in CSR-related activities on FRQ in Pakistani enterprises and the role of greater gender diversity in the board in this CSR–FRQ relationship.  Originality/value Little research in the literature examines the impact of CSR on FRQ. To the best of the authors’ knowledge, this is the first study in an emerging market to empirically assess this association and investigate the function of BGD in this previously unknown relationship.
A Bounded Degree Lasserre Hierarchy with SOCP Relaxations for Global Polynomial Optimization and Applications

In this paper, we propose a new convergent conic programming hierarchy of relaxations involving both semi-definite cone and second-order cone constraints for solving nonconvex polynomial optimization problems to global optimality. The significance of this hierarchy is that the size and number of the semi-definite and second-order cone constraints of the relaxations are fixed and independent of the step or level of the approximation in the hierarchy. Using the Krivine-Stengle's certificate of positivity in real algebraic geometry, we establish the convergence of the hierarchy of relaxations, extending the very recent so-called bounded degree Lasserre hierarchy. In particular, we also provide a convergent bounded degree second-order cone programming (SOCP) hierarchy for solving polynomial optimization problems. We then present finite convergence at step one of the SOCP hierarchy for two classes of polynomial optimization problems: a subclass of convex polynomial optimization problems where the objective and constraint functions are SOCP-convex polynomials, defined in terms of specially structured sum of squares polynomials, and a class of polynomial optimization problems, involving polynomials with essentially non-positive coefficients. In the case of one-step convergence for problems with SOCP-convex polynomials, we show how a global solution is recovered from the relaxation via Jensen's inequality of SOCP-convex polynomials. As an application, we derive a corresponding convergent conic linear programming hierarchy for conic-convex semi-algebraic programs. Whenever the semi-algebraic set of the conic-convex program is described by convex polynomial inequalities, we show further that the values of the relaxation problems converge to the common value of the convex program and its Lagrangian dual under a constraint qualification.
Building Global Relationships: Open Educational Resources and Collaborative Online International Learning Courses

Using open educational resources (OERs) in collaborative online international learning (COIL) courses provides students and faculty the opportunity to share content, enhance knowledge, and develop intercultural competence across geopolitical and other boundaries. Faculty perceptions at the research site regarding benefits and challenges of using OER are consistent with positive findings of other OER research that validate its potential. This case study describes experiences of two college courses taught with different international partners. It shares the journey of co-planning, implementing, and revising assignments highlighting OER instructional materials. Technology and accessibility considerations influence the curricular decisions for each course. They demonstrate how the timely availability of relevant OER content can be particularly impactful for international learning environments like COIL. The article underscores the faculty-librarian-instructional designer collaboration throughout the project and offers suggestions for future study.
Using Crowdsourcing for Multi-label Biomedical Compound Figure Annotation

Information analysis or retrieval for images in the biomedical literature needs to deal with a large amount of compound figures (figures containing several subfigures), as they constitute probably more than half of all images in repositories such as PubMed Central, which was the data set used for the task. The ImageCLEFmed benchmark proposed among other tasks in 2015 and 2016 a multi-label classification task, which aims at evaluating the automatic classification of figures into 30 image types. This task was based on compound figures and thus the figures were distributed to participants as compound figures but also in a separated form. Therefore, the generation of a gold standard was required, so that algorithms of participants can be evaluated and compared. This work presents the process carried out to generate the multi-labels of \(\sim \,2650\) compound figures using a crowdsourcing approach. Automatic algorithms to separate compound figures into subfigures were used and the results were then validated or corrected via crowdsourcing. The image types (MR, CT, X–ray, ...) were also annotated by crowdsourcing including detailed quality control. Quality control is necessary to insure quality of the annotated data as much as possible. \(\sim \,625\) h were invested with a cost of \(\sim \,870\$\).
Edge-CloudBlock-6G: Adopting AI Technology for Intelligent Spectrum Access and Secure Hybrid Beam forming in mmWave Massive MIMO Assisted Cognitive Radio based IoCV Environment

Cognitive Radio Network (CRN), as a key technology to improve utilization of radio spectrum and spectrum sensing with Internet of Connected Vehicles (IoCV) which can significantly facilitate vehicle management and route planning to encounter the issues in reliable communication and spectrum access. Though, it faces issues such as high sensing delay, packet loss rate, latency and high throughput. In this proposed work, the existing issues are encountered through edge based Cognitive Radio Network (CRN) in Multi Input Multi Output (MIMO) using 6G (6GCRN-MIMO). Firstly, all Primary Users (PUs), Secondary Users (SUs)and pedestrians are authenticated using cloud based blockchain in order to increase security. The clustering is performed for management of network using modified K‐Means (MKM) algorithm and clustering is performed through entry of authenticated users with consideration of several metrics. The intersection safety information is provided over the proposed network for reduction of collision in intersection using Improved Naive Bayes(INB) algorithm. Spectrum sensing and spectrum handoff are performed using Efficient Capsule Network (E-CapsNet) algorithm when PU is inactive while SU is selecting optimal channel through various metrics for reduction of spectrum scarcity. The ERSU is used to collect and store the environment data to perform the secure routing process using Red Fox Optimization (RFO) algorithm. Hybrid beamforming is performed to enhance reliable communication with Asynchronous Advantage Actor Critic Learning (A3CL) method. The proposed approach is simulated by using SUMO and OMNET ++ and validated by comparing it with existing approaches in terms of spectrum efficiency, spectrum sensing and QoS. The results proved that the proposed approach achieved finest performance while compared to existing approaches.
Magnetic relaxation and magnetization field dependence measurements in La0.5Ca0.5MnO3

We reported a systematic change in the average magnetic relaxation rate, after the application and removal of a 5 T magnetic field, in a polycrystalline sample of La0.5Ca0.5MnO3. Magnetic relaxation measurements and magnetization versus field curves were taken from 10 K to 160 K. The long time behavior of the relaxation curves was approximately logarithmic in all cases. Keywords: Charge Ordering, Relaxation, Magnetic measurements
Additional file 4: of Toward the precision breast cancer survival prediction utilizing combined whole genome-wide expression and somatic mutation analysis

The comparison of mutation rates for top mutated genes and 14 pathway genes. The mutation rates for 15 different gene sets, including one top-35-mutated gene set and 14 pathway-based gene sets. The genes in each set were ordered by their mutation rates. (PDF 36Â kb)
SeeingGAN: Galactic image deblurring with deep learning for better morphological classification of galaxies

11 pages, 8 figures
Applying Principles From Aviation Safety Investigations to Root Cause Analysis of a Critical Incident During a Simulated Emergency

Summary Statement           Safety investigations in aviation aim to identify potential root causes. They use structured techniques to analyze information from flight data and cockpit voice recorders. Full-scale medical simulations using audiovisual recordings provide similar possibilities. During a simulated cardiac arrest, an incident related to use of the defibrillator (automated external defibrillator) occurred with emergency medical services (EMS) providers. Treatment interventions and dialogs during the incident were extracted from audiovisual recordings and transferred into a transcript of events.           Knowing indicated treatment measures, the team adhered to automated external defibrillator voice prompts rather than follow their own assessment. Cardiopulmonary resuscitation was on hold for 72% of the time. Time to first defibrillation was delayed by 2:17 minutes. Transcript allowed us to identify faulty decision-making, loss of leadership, and automation bias as possible root causes. Use of RCA methodology during medical simulation improves understanding of critical incidents and can contribute to training of EMS personnel and education of instructors.
Correcting Misperceptions about Ethno-Racial Discrimination: The Limits of Evidence-Based Awareness Raising to Promote Support for Equal-Treatment Policies

The disadvantages experienced by minorities and the lack of societal remedies for them are widely believed to be partly attributable to mainstream-majority citizens’ limited awareness of the hardships encountered by minorities. This study investigates whether informing citizens about field experiments on ethno-racial discrimination increases their recognition of the issue and support for equal-treatment policies. Based on the assumption that citizens require assistance to comprehend the significance of field-experimental evidence, the study tests three types of framing: a scientist framing the evidence as credible, a lawyer emphasizing the legal breach, or a minority expressing personal grief. The results indicate that citizens are generally aware of discrimination against ethno-racial minorities and even tend to overperceive its extent. Furthermore, communicating field-experimental results corrects and converges misperceptions but does not change recognition of the problem or support for equal-treatment policies, regardless of the framing or initial misperception. Only combining priming, correction, and framing temporarily increases recognition and donations to minority support groups, but not support for equal-treatment policies. These findings suggest evidence-based awareness campaigns have limited immediate success in promoting policy support. Citizens may donate to acknowledge minority hardships but hesitate to endorse policies that could affect their group’s privileged position.
The Stem Cell Niche Should be a Key Issue for Cell Therapy in Regenerative Medicine

Recent advances in stem cell research have highlighted the role played by such cells and their environment (the stem cell niche) in tissue renewal and homeostasis. The control and regulation of stem cells and their niche are remaining challenges for cell therapy and regenerative medicine on several tissues and organs. These advances are important for both, the basic knowledge of stem cell regulation, and their practical translational applications into clinical medicine. This article is primarily concerned with the mesenchymal stem cells (MSCs) and it reviews the current aspects of their own niche. We discuss on the need for a deeper understanding of the identity of this cell type and its microenvironment in order to improve the effectiveness of any cell therapy for regenerative medicine. Ex vivo reproduction of the conditions of the natural stem cell niche, when necessary, would provide success to tissue engineering. The first challenge of regenerative medicine is to find cells able to replace and/or repair the lost function of tissues and organs by disease or aging and the trophic and immunomodulatory effects recently found for MSCs open up for new opportunities. If MSCs are pericytes, as it has been proposed, perhaps it may explain the ubiquity of these cells and their possible role in miscellaneous repairs throughout the body opening for new chances for extensive tissue repair.
Improve Deep Learning with Unsupervised Objective

We propose a novel approach capable of embedding the unsupervised objective into hidden layers of the deep neural network (DNN) for preserving important unsupervised information. To this end, we exploit a very simple yet effective unsupervised method, i.e. principal component analysis (PCA), to generate the unsupervised “label" for the latent layers of DNN. Each latent layer of DNN can then be supervised not just by the class label, but also by the unsupervised “label" so that the intrinsic structure information of data can be learned and embedded. Compared with traditional methods which combine supervised and unsupervised learning, our proposed model avoids the needs for layer-wise pre-training and complicated model learning e.g. in deep autoencoder. We show that the resulting model achieves state-of-the-art performance in both face and handwriting data simply with learning of unsupervised “labels".
Decolonizing Human Rights Law in Global Health - the Impacts of Intellectual Property Law on Access to Essential Medicines: A Perspective from the COVID-19 Pandemic

AbstractThe global impacts of COVID-19 have been calamitous, unleashing widespread human suffering and exacerbating health crises, all while worsening pre-existing inequalities and transgressing fundamental human rights. Despite earnest pleas from the United Nations and developing nations for an equitable distribution of COVID-19 vaccines, these appeals were largely unheeded. Instead, major pharmaceutical manufacturers and high-income countries (HICs) had maintained a stranglehold on vaccine technology through the safeguarding of intellectual property rights (IPRs), leading to exorbitant pricing and preferential distribution to affluent regions. This vaccine hoarding has left low- and middle-income countries (LMICs) with delayed and insufficient supplies, endangering the lives of the most vulnerable. The stringent enforcement of IPRs mechanisms, rather than aligning with international human rights obligations, has further marginalised the right to life, health, and access to vaccines and medicines, particularly in LMICs. This study ardently advocates for a policy shift that promotes the decolonisation of human rights in the context of IPRs and global health law.
Humanitarian Intervention and The Responsibility to Protect After 9/11

The article addresses the question which consequences the war on terrorism has for the practice of and thinking about humanitarian intervention. The discussions about the legality and legitimacy of humanitarian intervention reached their peak after the NATO bombardments against the Federal Republic of Yugoslavia to protect the Albanians in Kosovo in 1999. The terrorist attacks of 9/11, which led to the war on terrorism, however, changed the focus of attention. The central question for international lawyers is no longer whether states may use force to protect human rights, but whether the use of force in anticipatory self-defence is allowed under international law in view of new security threats. After describing humanitarian intervention after the end of the Cold War, the impact of the war on terrorism on the protection of human rights is analysed. Although some authors think that the war on terrorism can coincide with the protection of human rights, the present author is more pessimistic. Subsequently the concept of the responsibility to protect is discussed. The author concludes that this concept is less revolutionary as some authors claim it to be. Most importantly, it does not provide a legal justification for the use of force to protect human rights without permission of the Security Council. The last section of the article therefore investigates whether the principle of necessity can serve as a potential legal justification for an intervention for human protection purposes without Security Council authorization.
GREGoR: Accelerating Genomics for Rare Diseases

Rare diseases are collectively common, affecting approximately one in twenty individuals worldwide. In recent years, rapid progress has been made in rare disease diagnostics due to advances in DNA sequencing, development of new computational and experimental approaches to prioritize genes and genetic variants, and increased global exchange of clinical and genetic data. However, more than half of individuals suspected to have a rare disease lack a genetic diagnosis. The Genomics Research to Elucidate the Genetics of Rare Diseases (GREGoR) Consortium was initiated to study thousands of challenging rare disease cases and families and apply, standardize, and evaluate emerging genomics technologies and analytics to accelerate their adoption in clinical practice. Further, all data generated, currently representing ~7500 individuals from ~3000 families, is rapidly made available to researchers worldwide via the Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) to catalyze global efforts to develop approaches for genetic diagnoses in rare diseases (https://gregorconsortium.org/data). The majority of these families have undergone prior clinical genetic testing but remained unsolved, with most being exome-negative. Here, we describe the collaborative research framework, datasets, and discoveries comprising GREGoR that will provide foundational resources and substrates for the future of rare disease genomics.
Virtual Reality Robotic Surgical Simulation: An Analysis of Gynecology Trainees

To analyze the learning curves of gynecology trainees on several virtual reality da Vinci Skills Simulator exercises.Prospective cohort pilot study.Academic hospital-based gynecology training program.Novice robotic surgeons from a gynecology training program.Novice robotic surgeons from an academic gynecology training program completed 10 repetitions of 4 exercises on the da Vinci Skills Simulator: matchboard, ring and rail, suture sponge, and energy switching. Performance metrics measured included time to completion, economy of instrument movement, excessive force, collisions, master workspace range, missed targets, misapplied energy, critical errors, and overall score. Statistical analyses were conducted to define the learning curve for trainees and the optimal number of repetitions for each exercise.A total of 34 participants were enrolled, of which 9 were medical students, 22 were residents, and 3 were fellows. There was a significant improvement in performance between the 1st and 10th repetitions across multiple metrics for all exercises. Senior trainees performed the suture exercise significantly faster than the junior trainees during the first and last repetitions (p = 0.004 and p = 0.003, respectively). However, the performance gap between seniors and juniors narrowed significantly by the 10th repetition. The mean number of repetitions required to achieve performance plateau ranged from 6.4 to 9.3.Virtual reality robotic simulation improves ability through repetition at all levels of training. Further, a performance plateau may exist during a single training session. Larger studies are needed to further define the most high-yield simulator exercises, the ideal number of repetitions, and recommended intervals between training sessions to improve operative performance.
Food and nutrition security: Towards the full realisation of human rights

The challenges involved in the realisation of the human right to adequate food and nutrition (HRtAFN), and of food and nutrition sovereignty and security in African countries and in Brazil, comprise different elements - but also share several similarities. While there has been evidence of a significant reduction in hunger and malnutrition worldwide, it is observed that this phenomenon has not occurred at the same pace in sub-Saharan Africa and in some regions of Brazil. At the same time, there has been a rapid increase in the rates of overweight, obesity and related illnesses, such as diabetes, cardiac disease, various types of cancer, etc. [...]
Data Reduction Techniques in Wireless Sensor Networks With Internet of Things

Since they are used in an array of real-life uses, wireless sensor equipment in Internet of Things (IoT) systems will be among the biggest prolific sources of big data on the connection. The huge quantity of data collected from sensing equipment increases transmission overhead, reducing the short lifespan of IoT sensing equipment. As a result, it is required to cleanse and reduce the sensed information in order to cut transmission costs and conserve power on sensing equipment. A Data Reduction and Cleansing Technique (DRCT) for power consumption in IoT-based wireless sensor networks (WSNs) is suggested in this research. This method depends on 2 levels of data cleansing and reduction: sensing and aggregation.