ethicalabs/Research-Intent-Collab huggingface dataset:
Fundamental interactions involving neutrons and neutrinos: reactor-based studies led by the Petersburg Nuclear Physics Institute (National Research Center "Kurchatov Institute") [PNPI (NRC KI)]

Neutrons of very low energy ( eV), commonly known as ultracold, are unique in that they can be stored in material and magnetic traps, thus enhancing methodical opportunities to conduct precision experiments and to probe the fundamentals of physics. One of the central problems of physics, of direct relevance to the formation of the Universe, is the violation of time invariance. Experiments searching for the nonzero neutron electric dipole moment serve as a time invariance test, and the use of ultracold neutrons provides very high measurement precision. Precision neutron lifetime measurements using ultracold neutrons are extremely important for checking ideas on the early formation of the Universe. This paper discusses problems that arise in studies using ultracold neutrons. Also discussed are the currently highly topical problem of sterile neutrinos and the search for reactor antineutrino oscillations at distances of 6–12 meters from the reactor core. The field reviewed is being investigated at multiple facilities globally. The present paper mainly concentrates on the results of PNPI-led studies at WWR-M PNPI (Gatchina), ILL (Grenoble), and SM-3 (Dimitrovgrad) reactors, and also covers the results obtained during preparation for research at the PIK reactor which is under construction.
Watering down human rights ? A healthy environment for the rights to water and sanitation

Global Challenges ; No. 11(2022), Article 9
Synthesis, Structure, and Electrochemistry of Sm-Modified LiMn2O4 Cathode Materials for Lithium-Ion Batteries

Spinel lithium manganese oxide and a series of Sm/LiMn2O4 spinels with different Sm additive contents (x = 0.02%, 0.05%) were prepared for the first time via a coprecipitation method for rechargeable lithium-ion batteries. X-ray diffraction (XRD), scanning electron microscopy (SEM), energy-dispersive analysis of x-rays (EDAX), infrared (IR), and electron spin resonance spectral studies as well as various electrochemical measurements were used to examine the structural and electrochemical characteristics of LiMn2−xSmxO4 (x = 0.00%, 0.02%, 0.05%). XRD and SEM studies confirmed the nano materials size for all prepared spinels. From cyclic voltammetry studies, in terms of peak splitting, electrochemical active surface area, and intensity of the peaks, the LiMn1.98Sm0.02O4 sample possesses better electrochemical performance compared with the LiMn1.95Sm0.05O4 sample. Hence, limited addition of a rare-earth dopant is preferable to obtain better efficiency. Direct-current (DC) electrical conductivity measurements indicated that these samples are semiconducting and their activation energies decrease with increasing rare-earth Sm3+ content.
A tale of two systems—Nurses practice environment, well being, perceived quality of care and patient safety in private and public hospitals in South Africa: A questionnaire survey

To examine the practice environment, nurse reported quality of care and patient safety, and nurse workforce outcomes in medical and surgical units in private and public hospitals in South Africa (SA), and determine the association of modifiable features of the hospital such as the practice environment and patient to nurse workloads on these outcomes.Cross-sectional survey of nurses.Nurses were surveyed in medical and surgical units of 55 private hospitals and 7 public national referral hospitals in SA. A total of 1187 nurses completed the survey.Practice environment, patient to nurse workloads, nurse reported quality of care and patient safety, and nurse workforce outcomes including burnout, job satisfaction and intention to leave.On a national level, more than half, 54.4% (634/1166) of nurses intend to leave their hospital within the next year due to job dissatisfaction and 52.3% (600/1148) rate their practice environment as poor or fair, while almost half, 45.8% (538/1174) report high levels of burnout and 44.9% (517/1152) are not confident that management will resolve patient problems. Public hospital nurses report more negative outcomes than private hospital nurses. Some 71% (320/451) of public hospital nurses rate their practice environment as poor/fair, 62.9% (281/447) are not confident management will resolve patient problems, and 59% (272/461) intend to leave their hospital within the next year due to job dissatisfaction. On a national level, more favourable practice environments are significantly associated with more positive nurse reported quality of care, and nurse workforce outcomes. This is true for private and public hospitals. Patient to nurse workloads are also significantly associated with more positive nurse reported quality of care and patient safety, and nurse workforce outcomes, but primarily in public hospitals.Improving the practice environment, including patient to nurse ratios holds promise for retaining a qualified and committed nurse workforce and may benefit patients in terms of better quality care.
Public communication of science and university extension (public engagement): researchers' perspectives from a qualitative study

Public Communication of Science (CPC) can be understood as a strategic dimension of university life. This study investigates how researchers from the Institute of Physics at the Federal University of Uberlândia, in Minas Gerais (Brazil), perceive and practice CPC, highlighting institutional tensions, institutional initiatives, and the role of university mechanisms. Based on interviews with nine professors and seven postgraduate students, results indicate a clear recognition of CPC’s social relevance. However, participation remains irregular and reactive, alongside a lack of awareness regarding existing institutional initiatives. We advocate for an institutional ecosystem that strengthens engagement and the social role of the university.
A Comparative Evaluation Between Two Design Solutions for an Information Dashboard

This study is a software usability design case about information presentation in a software dash­board. The dashboard is supposed to present system information about an enterprise resource planning system. The study aims to evaluate if the intended users of the dash­board prefer a list-based or an object-based presentation of the information and why. It also investigates if the possi­bility to get familiar with the prototype affects the evaluation’s result. The study was performed using parallel prototypes and evaluation with users. The use of parallel prototypes is a rather unexplored area. Likewise, little research has been done in the area of how user experience changes over time. Two prototypes were created, presenting the same information in two different design solutions, one list-based, and one object-based. The prototypes were evaluated with ten presumptive users, with respect to usability. The evaluation consisted of two parts, one quantitative and one qualita­tive. Half of the respondents got a chance to get familiar with the list-based prototype, and half the object-based prototype, after which they evaluated both sequentially. The result of the evaluation showed that seven out of ten respondents preferred the list-based prototype. The two primary reasons were that they are more used to the list-based concept from their work, and that the list-based prototype presented all information about an application at once. In the object-based prototype the user had to make a request for each type of information, which opened up in a new pop-up window. The primary reason that three of the ten respondents preferred the object-based prototype was that it had a more modern look, and gave a cleaner impression since it only presented the information the respondent was interested in at each point in time. The result also implied that the possibility to get familiar with the prototype by testing it for a couple of days affected the result. Eight out of ten respondents preferred the prototype they got familiar to, and the only ones that liked or preferred the object-based prototype were those who had gotten familiar with it.   The results of the study support the results of the existing research done by Dow et al. (2010) on the use of parallel prototypes, i.e. creating several prototypes in parallel, and conform with the results of the research of Karapanos et al. (2009) on how user experience changes over time. Some other interesting information that emerged from the study was that all but one of the respondents thought that the prototype they got familiar with had an acceptable level of usability. The study also validated that all respondents are positive to use a dashboard in their work, and that the presented information was enough for a first version of the dashboard. It also validated that the different groups of users would use the dashboard differently, and therefore are in need of slightly different information.
Deep Learning for Galaxy Morphology Classification in Large-Scale Surveys

In this thesis, the deep learning techniques and their applications are explored on the classification of the galaxy morphologies in the large-scale surveys of astronomical data. The dataset used in this study is derived from the Sloan Digital Sky Survey (SDSS) which is the combination of photometric and spectroscopic data across five spectral bands. This research thesis uses a robust framework for automating the galaxy classification and the dataset uses 500,000 records with comprehensive attribute listing. These attributes include the astronomical coordinates, photometric measurements, observational details, and class labels (galaxy, star, quasar). The methodology involved in this research report includes a detailed data preparation, data cleaning, normalization, and transformation. This is done so that a better and optimized model can be trained and developed. The evaluation for such models used in this report is conducted by the traditional evaluation metrics like accuracy, precision, recall, F1-score, and confusion matrices. Resultant models are comprehensive and show the accuracy of classifying relevant galaxies into their respective morphological categories. This report also shows the key findings to be data augmentation and class imbalance, which are addressed to achieve even better classification accuracies across different galaxy types
INTEGRATED PROCESS MODELING AND EXPERIMENTAL ANALYSIS FOR OPTIMIZING CONTINUOUS MANUFACTURE OF DRUG SUBSTANCE CARBAMAZEPINE

This dissertation presents a comprehensive study on the continuous manufacture (CM) of the drug substance (DS) carbamazepine (CBZ), a widely used anti-epileptic medication, aimed at enhancing process efficiency and product quality. The research progresses through a series of investigations, beginning with the development of kinetic models for CBZ synthesis from iminostilbene via two different synthetic routes using urea and potassium cyanate across various reactor setups, including batch and continuous flow systems. Discrepancies between batch and continuous models, particularly in yield prediction and impurity formation, are thoroughly examined and addressed through adjustments in reactant addition methods and system designs. This demonstrates the value of mechanistic modeling, a tool that has been undervalued in recent research particularly for its ability to compare between batch and continuous systems. Subsequently, the research delves into the crystallization processes, employing a population balance model (PBM) to study CBZ polymorph form III crystal formation, highlighting the influence of seed crystal size distribution on product crystal quality. It also provides novel strategies for modeling the evolution of crystal size distribution (CSD) due to nucleation and growth and evaluates the robustness of these strategies as seed CSD varies. Lastly, the scope is expanded to a holistic view of the integrated synthesis and crystallization process presenting one of the first studies of a complete DS CM system and emphasizing the development of a robust Quality-by-Control (QbC) framework. This includes the implementation of in-line Raman spectroscopy for real-time concentration monitoring, an active feedback level control system, dynamic modeling of impurity partitioning for enhancing disturbance mitigation across the CM process, and a retrograde design strategy that optimizes the upstream synthesis based on downstream purification capabilities/limitations. Through all these contributions, the dissertation aims to advance the modernization of continuous manufacturing practices in the pharmaceutical industry and promotes a shift towards more adaptive and controlled production environments.
The United Nations Security Council Reform: A Critical Approach

Utilizing Critical Theory, through its neo-Gramscian and Frankfurt School dimensions, as the theoretical framework, this study aims to explain how the institutions, such as the United Nations, of an international system transform together with the structure – the international system. More specifically our aim is to explain the lack of transformation of only one body, the Security Council, of that specific institution, the United Nations. Analyzing the press releases of the United Nations General Assembly in 1996, 1997, 2000, and 2006 and examining 337 statements from the Member States through Critical Theory to be able understand and explain how and why it hasn’t been possible to reform, or transform, the United Nations Security Council in the last 14 years since the establishment of the Open-Ended Working Group as a group to particularly deal with the question of reform. The analysis suggests that the current debates in the United Nations concerning the reform of the Security Council is unable to produce a successful transformation of that body because it is not possible for an institution to finalize its own transformation independent from that of the structure as a whole.
A Measurement of the Cosmic Microwave Background Gravitational Lensing Potential and its Power Spectrum from 500 Square Degrees of SPTpol Data

Weak gravitational lensing by large-scale structure in the universe causes deflections in the paths of cosmic microwave background (CMB) photons. This effect introduces statistical anisotropy in the observed CMB temperature and polarization fields. The signature of lensing can be used to reconstruct the projected gravitational lensing potential with a quadratic estimator technique; this provides a measure of the integrated mass distribution out to the surface of last scattering, sourced primarily from redshifts between 0.1 and 5. The power spectrum of the lensing potential encodes information about the geometry of the universe and the growth of structure and can be used to place constraints on the sum of neutrino masses and dark energy. High signal-to-noise mass maps from CMB lensing are also powerful for cross-correlating with other tracers of large-scale structure and for delensing the CMB in search for primordial gravitational waves. This thesis describes a high signal-to-noise reconstruction of the CMB gravitational lensing potential and a measurement of its power spectrum using data from 500 \sqdeg of sky observed between 2012 and 2015 with the polarization-sensitive receiver SPTpol, installed on the South Pole Telescope (SPT). We find the ratio of the lensing spectrum to a theoretical $\Lambda$CDM model to be $A_{\rm \mv}=0.94 \pm 0.05 {\rm\, (stat.)} \pm 0.04 {\rm\, (sys.)}$. This measurement represents a $17.1 \sigma$ constraint on the lensing amplitude and a $41 \sigma$ detection of lensing effects.
Joint Multi-User Communication and Sensing Exploiting Both Signal and Environment Sparsity

As a potential technology feature for 6G wireless networks, the idea of sensing-communication integration requires the system not only to complete reliable multi-user communication but also to achieve accurate environment sensing. In this paper, we consider such a joint communication and sensing (JCAS) scenario, in which multiple users use the sparse code multiple access (SCMA) scheme to communicate with the wireless access point (AP). Part of the user signals are scattered by the environment object and reflected by an intelligent reflective surface (IRS) before they arrive at the AP. We exploit the sparsity of both the structured user signals and the unstructured environment and propose an iterative and incremental joint multi-user communication and environment sensing scheme, in which the two processes, i.e., multi-user information detection and environment object detection, interweave with each other thanks to their intrinsic mutual dependence. The proposed algorithm is sliding-window based and also graph based, which can keep on sensing the environment as long as there are illuminating user signals. The trade-off relationship between the key system parameters is analyzed, and the simulation result validates the convergence and effectiveness of the proposed algorithm.
Intergenerational occupational justice: Ethically reflecting on climate crisis

The current climate crisis is linked to the negative impacts of human occupations, as enacted historically and currently, on the world’s ecosystems. Such impacts raise the questions: Are all occupa...
Integrating forest biodiversity conservation and restoration ecology principles to recover natural forest ecosystems

Effective conservation of forest biodiversity and effective forest restoration are two of the biggest challenges facing forest managers globally. I present four general principles to guide strategies aimed at meeting these challenges: (1) protect and restore populations of key species and their habitats, (2) conserve and restore key attributes of stand structural complexity, (3) maintain and restore natural patterns of landscape heterogeneity, and (4) maintain and restore key ecological processes. The complexity associated with these principles is that how they will be practically implemented on the ground will invariably be ecosystem specific as what constitutes stand structural complexity or landscape heterogeneity will vary between ecosystems. Here I demonstrate the practical application of the four general principles in a detailed case study of conservation and restoration in the Mountain Ash (Eucalyptus regnans) forests of the Central Highlands of Victoria, south-eastern Australia. These forests are characterized by declining species, loss of key elements of stand structural, loss of old growth forest, altered patterns of landscape heterogeneity, and altered ecosystem processes. I highlight how altered management practices in Mountain Ash forests that are guided by our four general principles can help conserve existing biodiversity and underpin effective forest restoration. Consideration of our general principles also can identify policy deficiencies that need to be addressed to enhance restoration and biodiversity conservation.
Point estimation for adaptive trial designs I: a methodological review

Recent FDA guidance on adaptive clinical trial designs defines bias as "a systematic tendency for the estimate of treatment effect to deviate from its true value", and states that it is desirable to obtain and report estimates of treatment effects that reduce or remove this bias. The conventional end-of-trial point estimates of the treatment effects are prone to bias in many adaptive designs, because they do not take into account the potential and realised trial adaptations. While much of the methodological developments on adaptive designs have tended to focus on control of type I error rates and power considerations, in contrast the question of biased estimation has received relatively less attention. This paper is the first in a two-part series that studies the issue of potential bias in point estimation for adaptive trials. Part I provides a comprehensive review of the methods to remove or reduce the potential bias in point estimation of treatment effects for adaptive designs, while part II illustrates how to implement these in practice and proposes a set of guidelines for trial statisticians. The methods reviewed in this paper can be broadly classified into unbiased and bias-reduced estimation, and we also provide a classification of estimators by the type of adaptive design. We compare the proposed methods, highlight available software and code, and discuss potential methodological gaps in the literature.
Energy reconstruction of hadron-initiated showers of ultra-high energy cosmic rays

The current methods to determine the primary energy of ultra-high energy cosmic rays (UHECRs) are different when dealing with hadron or photon primaries. The current experiments combine two different techniques, an array of surface detectors and fluorescence telescopes. The latter allow an almost calorimetric measurement of the primary energy. Thus, hadron-initiated showers detected by both type of detectors are used to calibrate the energy estimator from the surface array (usually the interpolated signal at a certain distance from the shower core S(r0)) with the primary energy. On the other hand, this calibration is not feasible when searching for photon primaries since no high energy photon has been unambiguously detected so far. Therefore, pure Monte Carlo parametrizations are used instead. In this work, we present a new method to determine the primary energy of hadron-induced showers in a hybrid experiment based on a technique previously developed for photon primaries. It consists on a set of calibration curves that relate the surface energy estimator, S(r0), and the depth of maximum development of the shower, Xmax, obtained from the fluorescence telescopes. Then, the primary energy can be determined from pure surface information since S(r0) and the zenith angle of the incoming shower are only needed. Considering a mixed sample of ultra-high energy proton and iron primaries and taking into account the reconstruction uncertainties and shower to shower fluctuations, we demonstrate that the primary energy may be determined with a systematic uncertainty below 1% and resolution around 16% in the energy range from 10^{18.5} to 10^{19.6} eV. Several array geometries, the shape of the energy error distributions and the uncertainties due to the unknown composition of the primary flux have been analyzed as well.
Book Recommendation System Using Collaborative Filtering

Due to the extreme expansion of digital book platforms, users are having trouble finding relevant books because of the enormous amount of information. Recommendation systems are beneficial against this complication as they offer recommendations based on what users are interested in. Good reads data is used to implement and analyze a collaborative filtering approach to item-based recommendation on a big data environment, resulting in an improved book recommendation system. This system utilizes user-based and item-based collaborative filtering and aims at refining the accuracy of the recommendations by implementing Singular Value Decomposition (SVD) and cosine similarity.  INDEX TERMS: : Recommendation System, Collaborative Filtering, Book Recommendation, SVD, Flask Web Application