ethicalabs/Research-Intent-Collab huggingface dataset:
CUGUV: A Benchmark Dataset for Promoting Large-Scale Urban Village Mapping with Deep Learning Models

Delineating the extent of urban villages (UVs) is crucial for effective urban planning and management, as well as for providing targeted policy and financial support. Unlike field surveys, the interpretation of satellite imagery provides an efficient, near real-time, and objective means of mapping UV. However, current research efforts predominantly concentrate on individual cities, resulting in a scarcity of interpretable UV maps for numerous other cities. This gap in availability not only hinders public awareness of the distribution and evolution of UV but also limits the reliability and transferability of models due to the insufficient number and diversity of samples. To address this issue, we developed CUGUV, a benchmark dataset that includes a diverse collection of thousands of UV samples, carefully curated from 15 major cities across various geographical regions in China. The dataset can be accessed through this link: https://doi.org/10.6084/m9.figshare.26198093 . This dataset can serve as a foundation for evaluating and improving the robustness and transferability of models. Subsequently, we present an innovative framework that effectively integrates and learns from multiple data sources to better address the cross-city UV mapping task. Tests show that the proposed models achieve over 92% in overall accuracy, precision, and F1-scores, outperforming state-of-the-art models. This highlights the effectiveness of both the proposed dataset and model. This presented dataset and model bolsters our capability to better understand and accurately model these complex and diverse phenomena, ultimately leading to a notable improvement in the performance of large-scale UV mapping.
Proposal and detailed theoretical analysis on a photonic neural network with optically pumped Spin-VCSEL spiking neurons

Abstract                A dual-layer photonic spiking neural network (PSNN) was constructed, where multiple optically pumped spin vertical-cavity surface-emitting lasers (Spin-VCSELs) were proposed as spiking neurons. Based on a detailed theoretical analysis of leaky integrate-and-fire (LIF) and refractory period characteristics of Spin-VCSEL neurons, the training and testing performance for the studied PSNN was evaluated using two standard pattern classification tasks (Iris dataset, simple digit recognition). The results showed that, by selecting appropriate parameters such as frequency detuning and number of pre-synaptic neurons, etc., higher training/testing accuracies beyond 90% can be obtained. When compared with traditional electrically pumped VCSEL, a threshold reduction of up to 50% can be achieved under nanosecond scale spin relaxation time and circular polarization optical pumping, the feasibility of realizing high accuracy (88%) pattern classification near the reduced threshold was also verified. Therefore, optically pumped Spin-VCSEL neurons can become a valuable new choice for high-performance PSNN with reduced power consumption.
Climate Change Vulnerability and Adaptation Pathways:   Stakeholders’ Synergies in Building Climate Resilience   in the Semi-arid Area of Central Tanzania

This article examines the perceived effect of climate change on cereal crop production and the responses of various stakeholders aimed at enhancing the resilience of smallholder farmers in semi-arid areas of central Tanzania. A total of 366 household heads, 28 participants in focus group discussions (FGDs), and 8 key informants from Bahi and Kongwa districts in Dodoma, Tanzania, were involved in this study. Both quantitative and qualitative data were gathered through a structured interview schedule, FGDs, in-depth interviews, and documentary reviews. Descriptive statistics and content analysis were used to analyse quantitative and qualitative data, respectively. The findings indicate that smallholder farmers in the study area have noted declining crop yields for maize, bulrush millet, and sorghum; a decline that is associated with the changing climate. In response to these effects, the farmers have employed various adaptive measures, including the use of improved seeds, changes in planting dates, intercropping, adjustments in farm size, out-migration, and changes in land-use practices. However, they have faced various challenges in implementing these measures, specifically low income levels, high prices of agricultural inputs, and limited soft loans. In response, government institutions, the private sector, and non-governmental organisations have provided support to strengthen their adaptive capacity through supplying agricultural inputs, awareness creation on viable adaptive strategies, and providing support on livelihood options through non-farm activities. The study recommends the need to strengthen this support in this and other similar areas so as to increase smallholder farmers’ resilience to withstand the adverse effects of climate change.
The moderating role of Lean Six Sigma practices on quality management practices and quality performance in medical device manufacturing industry

PurposeThe purpose of this paper is to explore the moderating role of Lean Six Sigma (LSS) practices in explaining the relationship between quality management practices (QMPs) and quality performance.Design/methodology/approachPartial least square-based structural equation modeling (PLS-SEM) was used to empirically examine the moderating effect of LSS practices on QMPs and quality performance in Malaysian medical device manufacturing companies.FindingsFindings revealed that both QMPs and LSS practices have a significant and positive effect on quality performance. Furthermore, LSS practices served as a substitute for moderating the positive relationship between QMPs and quality performance in such a way that the relationship becomes weaker as LSS practices increase.Originality/valueLSS is acknowledged as the most well-known hybrid methodology; however, due to its relative newness, it has not been studied in great detail. Unlike previous studies, this paper argued that Lean and Six Sigma practices are distinct from its predecessor TQM practices; moreover, both Lean and Six Sigma practices do not need to substitute QM/TQM practices instead of complimenting the QMPs. In addition, this study adds to the growing body of QM literature by empirically examine the effect of LSS practices in moderating the relationship between QMPs and quality performance.
Moving beyond Consent for Citizen Science in Big Data Health Research

Consent has been the cornerstone of personal data privacy regime. This notion is premised on the liberal tenets of individual autonomy, freedom of choice and rationality. More important, consent is only meaningful if data subjects are fully informed and parties are of equal bargaining power. Under orthodox framework, it is believed that privacy can be waived by consent.   The above concern is particularly pertinent to citizen science in health and medical research, in which the nature of research is often data intensive with serious implication for individual’s privacy and other interests. Although there is no standard definition for citizen science, it includes generally the gathering and volunteering of data by non-professionals, the participation of non-experts in analysis and scientific experimentation, and public input into research and project. Citizens become experimenters, stakeholders, purveyors of data, research participants or even partners. Consent from citizen scientists is indispensable as it is a constitutive element for self-determination and self-empowerment for participants. Furthermore, consent from data subjects determines the responsibility and accountability of data users. Yet with the advancement of data mining and big data technologies, risks and harm of subsequent data use may not be known at the time of data collection. Progress of research often extends beyond the existing data. Namely, researchers of existing team or even third parties can match data sets to re-identify individuals. Furthermore, big data technology use and transfer of data for other unforeseen purposes maybe outside the control of the original research team. In other words, consent becomes problematic in citizen science in big data era. The model that one can fully specify the terms in notice and consent has become an illusion.   Is consent still valid? Should it still be one of the critical criteria in citizen science health research which are collaborative and contributory by nature? With a focus on the issue of consent and privacy protection, this study will analyze not only the traditional informed consent model but also the alternative models of “open consent”, “portable consent,” “dynamic consent,” and “meta consent.” Facing the challenges that big data and citizen science pose to personal data protection and privacy, this paper explores the legal, social and ethical concerns behind the concept of consent. It argues that we need to move beyond the consent paradigm and take into account a much broader context of harm and risk assessment. Ultimately, what lies behind consent are the entailing values of autonomy, fairness and propriety in the name of research.
Privacy-Aware Sequential Learning

In settings like vaccination registries, individuals act after observing others, and the resulting public records can expose private information. We study privacy-preserving sequential learning, where agents add endogenous noise to their reported actions to conceal private signals. Efficient social learning relies on information flow, seemingly in conflict with privacy. Surprisingly, with continuous signals and a fixed privacy budget $(ε)$, the optimal randomization strategy balances privacy and accuracy, accelerating learning to $Θ_ε(\log n)$, faster than the nonprivate $Θ(\sqrt{\log n})$ rate. In the nonprivate baseline, the expected time to the first correct action and the number of incorrect actions diverge; under privacy with sufficiently small $ε$, both are finite. Privacy helps because, under the false state, agents more often receive signals contradicting the majority; randomization then asymmetrically amplifies the log-likelihood ratio, enhancing aggregation. In heterogeneous populations, an order-optimal $Θ(\sqrt{n})$ rate is achievable when a subset of agents have low privacy budgets. With binary signals, however, privacy reduces informativeness and impairs learning relative to the nonprivate baseline, though the dependence on $ε$ is nonmonotone. Our results show how privacy reshapes information dynamics and inform the design of platforms and policies.
Descriptive literature review of human resource information systems (HRIS) adoption issues in the health sector, South Africa

No organisation is ever static. For several reasons, each organisation reviews its aims and objectives from time to time. These reasons may be internally or externally driven. They could also be politically, economically and or socially motivated. Research has established that most of the attempts at bringing about change are based on the needs of employees and customers. Essentially, for the purposes of better management of employees and customers, human resource information systems (HRIS) are touted as the panacea for effective and efficient health sector service delivery. Focusing on South Africa, this paper used the descriptive literature review method to determine HRIS adoption issues within the health sector of South Africa. As an important sector in any growing economy, the health sector in our view benefits from a constant review of its mission. Within the context of South Africa, substantial emphasis is yet to be placed on health sector effectiveness. Elsewhere, in other regions and continents, research on HRIS adoption within the health sector suggests that its adoption is problematic but useful. The South African health sector is yet to fully embrace this technology and as a result is suffering from employee dissatisfaction, brain drain, and general maladministration. Investment in HRIS research is therefore instructive especially within the context of South Africa. What we have found through this review is that investing in HRIS is crucial; however, it requires thorough consideration for its funding, infrastructural support, and skilled manpower among others.
International treaty and international custom as sources of international law: determination and interrelation

Стаття присвячена питанням співвідношення міжнародного договору та міжнародного звичаю, їх детермінації і взаємозв’язку. Оскільки міжнародний договір і міжнародний звичай є основними та найбільш поширеними джерелами сучасного міжнародного права, аналіз їх співвідношення є досить актуальним. Міжнародні договори та міжнародні звичаї підлягають постійному застосуванню суб’єктами між- народного права (державами та міжнародними організаціями), що вимагає оптимізації та пошуків ефективних механізмів вдосконалення у сучасних міжнародних відносинах, обумовлюючи акту- альність дослідження цих основних джерел міжнародного права. Здійснюється аналіз важливої для теорії і практики міжнародного права, особливо для пробле- матики джерел міжнародного права, Резолюції Генеральної Асамблеї ООН A/RES/73/203 від 20 грудня 2018 року «Виявлення норм міжнародного звичаєвого права». Результати даного дослідження свідчать, що міжнародний договір відрізняється від міжнародного звичаю своєю специфікою, особливістю об’єкта правового регулювання, формою закріплення і знач- ною перевагою договорів за своєю кількістю в сучасному міжнародному праві. Міжнародний договір виникає і формується як результат переговорів і плідної роботи суб’єктів міжнародного права над правилами, взаємними права та обов’язками з тих чи інших питань співробітництва. Міжнародні до- говори мають конкретні найменування і чітко встановлений предмет правового регулювання. Зазначається, що міжнародний звичай формується внаслідок практики діяльності суб’єктів між- народного права в ході історичного процесу міжнародних відносин. Правова природа міжнарод- ного звичаю є погоджувальною з боку суб’єктів міжнародного права, насамперед, держав і міжна- родних організацій. Зроблено висновок, що в процесі переходу від виникнення міжнародного звичаю до прийняття міжнародного договору, звичаї допомагають заповнювати прогалини в міжнародному праві. Також є можливим і зворотній процес, тоді коли міжнародні договори набувають широкого застосування і характеру міжнародного звичаю, наприклад міжнародно-правові договори у сфері захисту прав людини, які в подальшому набули загальної практики.
HOW SHOULD WE REPORT CORPORATE SOCIAL RESPONSIBILITY? THE CASE UPM.

Corporate Social Responsibility (CSR) reporting is similar in traditional financial accounting in the sense that it gives an account of the doings of a company over a given period of time, traditionally a year. This report is usually available to the general public, however, it differs from traditional financial accounting in that even a publicly listed company is not obligated to produce such a report. Currently, CSR reporting is still based on voluntary service. This research has been conducted due to the rising importance – or trend – of Corporate Social Reporting in order to assess how to properly report a company's doings in order to produce the maximum value for both the company and its stakeholders.  In order to analyze such, the action-based method was used. First, the Global Reporting Initiative framework is briefly described, after what the case study begins. A series of interviews were conducted with executives at the international pulp and paper company UPM Kymmene, in order to determine how suitable their current reports are and how to possibly improve future ones. As a result of the research, the thesis comes to the conclusion that there is not a single way to properly report CSR, but rather a multitude of different ways in which companies can properly report such, and, thus, both create value for their stakeholders, and the company itself. As a conclusion, the paper explains that reporting depends on many different factors, such as time, strategy, audience, industry, etc. Like any exploratory study this thesis aims at revealing possible leads for further research. Further research on this same topic could potentially focus on analyzing proper ways to report CSR in different companies in order to confirm whether reporting methods are indeed a variable or not. Asiasanat:Stakeholders;CSR;CR;Corporate Responsibility;Corporate Social Responsibility;GRI;Global Reporting Initiative;UPM Kymmene;Case Study
Phase transitions and fluctuations in classical statistical mechanics

It is shown that allowance for fluctuations leads to the appearance of additional terms in the Hamiltonian of the system and in the thermodynamic parameters of the substance. As a result, it becomes possible to describe the critical phenomena and phase transitions of liquid–vapor within classical statistical mechanics (without taking into account fluctuations, this is impossible).
Indigenous People’s Land Rights in Post-Soeharto Indonesia

Abstract One of the challenges during the democratic transition from the New Order regime to the Reformasi era was advancing the idea of an agrarian transition to reconcile structural inequalities regarding land ownership. However, this transition was unfortunately not accompanied by a rearrangement of land ownership to allow the practice of land-grabbing inherited from the New Order regime to persist in contemporary Indonesia. This article examines the reasons behind the failure of the agrarian transition in Indonesia, by focusing on case studies in Tegalrejo Village, Malang Regency and the Pamona indigenous peoples, Poso Regency. We argue that the modus operandi of land-grabbing practices is highly dependent on state power and weak protection of communal land rights. By explaining these two factors, this article provides recommendations to strengthen the community’s position in dealing with land-grabbing practices by limiting the power of the state and encouraging land reform aimed at securing community land rights.
Deep learning observables in computational fluid dynamics

Many large scale problems in computational fluid dynamics such as uncertainty quantification, Bayesian inversion, data assimilation and PDE constrained optimization are considered very challenging computationally as they require a large number of expensive (forward) numerical solutions of the corresponding PDEs. We propose a machine learning algorithm, based on deep artificial neural networks, that predicts the underlying \emph{input parameters to observable} map from a few training samples (computed realizations of this map). By a judicious combination of theoretical arguments and empirical observations, we find suitable network architectures and training hyperparameters that result in robust and efficient neural network approximations of the parameters to observable map. Numerical experiments are presented to demonstrate low prediction errors for the trained network networks, even when the network has been trained with a few samples, at a computational cost which is several orders of magnitude lower than the underlying PDE solver.   Moreover, we combine the proposed deep learning algorithm with Monte Carlo (MC) and Quasi-Monte Carlo (QMC) methods to efficiently compute uncertainty propagation for nonlinear PDEs. Under the assumption that the underlying neural networks generalize well, we prove that the deep learning MC and QMC algorithms are guaranteed to be faster than the baseline (quasi-) Monte Carlo methods. Numerical experiments demonstrating one to two orders of magnitude speed up over baseline QMC and MC algorithms, for the intricate problem of computing probability distributions of the observable, are also presented.
Les projets EQUAL, retour sur une expérimentation : la construction de la lutte contre les discriminations ethno-raciales « à la française »

En pratique, l'action publique de lutte contre les discriminations en France a été principalement constituée – en dehors de l'instauration de la Haute autorité de lutte contre les discriminations et pour l'égalité (HALDE) fin 2004 – par deux dispositifs : le Programme d'initiative communautaire EQUAL (PIC EQUAL) et les « Plans territoriaux de lutte contre les discriminations raciales à l'emploi » (PLCD) mis en place par la DIV (Division interministérielle à la ville). Ces deux dispositifs, tous deux lancés en 2001, avaient en commun de porter sur les discriminations raciales à l'emploi. Cette communication porte sur les projets EQUAL qui concentrèrent de 2001 à 2004 l'essentiel de l'intervention publique en matière de lutte contre les discriminations tant en termes de dispositifs que de moyens alloués.Cette communication fait retour sur l’expérimentation qu’a constituée le PIC EQUAL pour montrer les incidences de ces projets sur les caractéristiques de l’action publique française de lutte contre les discriminations. Elle montre que les projets EQUAL ont dessiné une action publique de lutte contre les discriminations française délocalisée et fortement outillée faute d'être idéologisée.
Incorporating Personality Trait Measures in Behavioral Assessment

Articles by Collins and Thompson, Staats, and Williams and Thompson have taken different tracks, but all advocate the integration of "personality" measures with behavioral assessment. This article addresses several issues that have hindered such integration. First, many traits are poorly defined, inconsistently applied, and excessively molar. The concept of trait communicates a useful idea -that there are meaningful consistencies in behavior across situations. However, the concepts of personality and personality traits are superfluous. They are imbued with semantic imprecision, redundancy, and unwanted psychodynamic and causal connotations. Also, trait measures are insensitive to the dynamic aspects of behavior. Finally, personality assessment questionnaires are frequently used in behavioral assessment but most often for client or subject selection and molar therapy outcome evaluation. The goal of research in this area should be to determine the persons, situations, purposes, particular traits, and measurement methods affecting the utility of trait measures in behavioral assessment.
An Appraisal of the Application of the Principle of Complementarity in the Functioning of the African Commission on Human and Peoples’ Rights and the African Court on Human and Peoples’ Rights Within the African Human Rights System

The principle of complementarity is a very vital principle in international law. The principle of complementarity promotes respect for national sovereignty, encourages domestic accountability, prevents impunity, ensures efficient allocation of resources, and strengthens international-domestic cooperation. This article examines or makes an appraisal on the application of the principle of complementarity in the functioning of the African Human Rights Commission and the African Human Rights Court system. The study uses a qualitative research methodology, employing primary data sources from vital conventions like the Rome Statute, African Charter on Human and Peoples’ Rights, and a host of others. Secondary data came from textbooks, journal articles, reports, and newspapers. The study is underpinned or anchored by the natural law theory and the functional theory. The findings in the study reveals blatantly like that the principle of complementarity is crucial to the African human rights system, fostering a cooperative and mutually reinforcing relationship between the Commission and the Court but however, its effectiveness in practice has been characterized by variability, with both successful instances and significant challenges. And as result of this, there is need to enhance cooperation between the commission and the court, increase awareness and visibility, develop clear guidelines and to improve access to the court.