ethicalabs/Research-Intent-Collab huggingface dataset:
Impact of Different Treatment Modalities for Localized Prostate Cancer on Patient-Reported Quality of Life Outcomes in an Asian Cohort

Abstract                 Background  This study aimed to provide a long-term comparison of patient-reported functional outcomes (PROs) across various treatments for localized PCa over five years in an Asian population. Methods  This was a prospective study involving 866 patients with PCa who were undergoing treatment, including active surveillance (AS)(n = 126), radical prostatectomy (RP) (n = 332), radiation therapy (RT) (n = 339) and focal therapy (FT)(n = 69). Patients were required to complete the EPIC-26 questionnaire at baseline and annually for 5 years, and were followed up until the most recent completion of the questionnaire, loss to follow-up, or death. Longitudinal functional outcomes were analyzed using linear mixed-effects models; the model included fixed effects for treatment modality, time, a treatment×time interaction, and clinically relevant covariates, including age, BMI, Charlson Comorbidity Index, and AUA risk group classification. Results  Over a median follow-up of 42.81months, RP resulted in the worst outcome in urinary continence (mean difference: −19, 95%CI: −24 to − 14; P &lt; 0.001) and sexual function mean difference: −22, 95%CI: −26 to − 17; P &lt; 0.001) in the first year, as compared to AS. RT was associated with an early decline in bowel function and hormonal dysfunction, which was most severe at 1–3 years, but both functions had recovered afterwards. FT preserved function in most domains, with no significant differences in sexual function compared to AS beyond 1 year. Conclusion  Different treatment modalities (AS, RP, RT, FT) resulted in distinct functional outcomes profiles.
Scientists’ Views about Public Engagement and Science Communication in the Context of Climate Change

Scientists who study issues such as climate change are often called on by both their colleagues and broader society to share what they know and why it matters. Many are willing to do so—and do it well—but others are either unwilling or may communicate without clear goals or in ways that may fail to achieve their goals. There are several central topics involved in the study of scientists as communicators. First, it is important to understand the evolving arguments behind why scientists are being called on to get involved in public engagement about contentious issues such as climate change. Second, it is also useful to consider the factors that social science suggests actually lead scientists to communicate about scientific issues. Last, it is important to consider what scientists are trying to achieve through their communication activities, and to consider to what extent we have evidence about whether scientists are achieving their desired goals.
Longitudinal quality of life measurement in colorectal cancer survivorship: a scoping review of patient-reported outcome measures (PROMs)

Abstract                                        Purpose                     This study aimed to identify the Patient-Reported Outcome Measures (PROMs) used to assess health-related quality of life (HRQoL) in colorectal cancer (CRC) survivors over time, examining the specific HRQoL domains assessed by PROMs, and exploring PROM use across interventions, age groups, settings, and survivorship phases.                                                           Methods                     PubMed, Embase, CINAHL, and PsycINFO were systematically searched for studies published between January 2005 and March 2025. Eligible studies focused on survivors with local or locally advanced CRC, where HRQoL was assessed at least at two timepoints (&lt; 2 years and 5 + years post-diagnosis) using either a comprehensive PROM or two or more PROMs covering different domains and reported outcomes. Studies were screened independently by two reviewers.                                                           Results                     The review included 21 articles representing 15 unique studies. Disease-specific PROMs predominated, commonly supplemented with generic instruments. Measurement timing and domain coverage varied widely. Physical health and symptom domains such as bowel function, fatigue, and pain were consistently assessed, whereas psychosocial constructs such as fear of cancer recurrence, financial strain, and social reintegration were less frequently captured. Temporal mapping of PROMs revealed strong emphasis on acute recovery within 2 years and limited long-term monitoring beyond 5 years.                                                           Conclusions                     PROM use in CRC survivorship research remains fragmented. Harmonisation of measures, survivor involvement in PROM development, and longitudinal implementation are essential next steps to generate comparable, patient-centred, and policy-relevant evidence that supports long-term survivorship care.                                                           Scoping review registration                                            This protocol has been registered prospectively with the Open Science Framework (OSF)                       https://osf.io/a9rf7                       .                                                                                Implications for cancer survivors                     More consistent and long-term use of PROMs in follow-up care can help identify late treatment effects and under-recognised survivorship issues.
An Integrated View of the One-Health Movement: The Oneness of Human HealthReview of: One Health—People, Animals, and the Environment; AtlasRonald M. and MaloyStanley (ed.); (2014). American Society for Microbiology Press, Washington, DC. 318 pages.

Review of             :             One Health—People, Animals, and the Environment             ; Ronald M. Atlas and Stanley Maloy (ed.); (2014). American Society for Microbiology Press, Washington, DC. 318 pages.
Evaluation of the Success of HRIS (Human Resource Information System) using the Delone Mclean Approach and Technology Acceptance Model (Case Study At PT. Anugerah Pharmindo Lestari)

Information systems play a significant role in today's business world, enabling companies to achieve innovation and competitiveness advantages. By using information systems, companies can enhance their efficiency, effectiveness, and productivity. This has led many companies to start implementing human resource information systems. PT. Anugerah Pharmindo Lestari (APL), a company operating in the healthcare service distribution sector, has been using HRIS since 2020. However, no evaluation has been conducted, serving as the basis for the necessity of this research. The objective is to understand the influence of system quality, information quality, and user experience on user satisfaction through perceived usefulness. The research employs a qualitative approach, targeting the entire population of 73 HRIS admins at PT. APL, all of whom are included in the sample. Data is collected through interviews and questionnaire distribution. The research concludes that the system quality directly does not support perceived usefulness and user satisfaction. Information quality cannot form perceived usefulness but can shape user satisfaction. User experience can shape perceived usefulness and user satisfaction. However, perceived usefulness cannot moderate impact of system quality, information quality, and user experience to satisfaction.
LASSO Principal Component Averaging -- a fully automated approach for point forecast pooling

This paper develops a novel, fully automated forecast averaging scheme, which combines LASSO estimation method with Principal Component Averaging (PCA). LASSO-PCA (LPCA) explores a pool of predictions based on a single model but calibrated to windows of different sizes. It uses information criteria to select tuning parameters and hence reduces the impact of researchers' at hock decisions. The method is applied to average predictions of hourly day-ahead electricity prices over 650 point forecasts obtained with various lengths of calibration windows. It is evaluated on four European and American markets with almost two and a half year of out-of-sample period and compared to other semi- and fully automated methods, such as simple mean, AW/WAW, LASSO and PCA. The results indicate that the LASSO averaging is very efficient in terms of forecast error reduction, whereas PCA method is robust to the selection of the specification parameter. LPCA inherits the advantages of both methods and outperforms other approaches in terms of MAE, remaining insensitive the the choice of a tuning parameter.
Artificial bee colonies for continuous optimization: Experimental analysis and improvements

The artificial bee colony (ABC) algorithm is a recent class of swarm intelligence algorithms that is loosely inspired by the foraging behavior of honeybee swarms. It was introduced in 2005 using continuous optimization problems as an example application. Similar to what has happened with other swarm intelligence techniques, after the initial proposal, several researchers have studied variants of the original algorithm. Unfortunately, often these variants have been tested under different experimental conditions and different fine-tuning efforts for the algorithm parameters. In this article, we review various variants of the original ABC algorithm and experimentally study nine ABC algorithms under two settings: either using the original parameter settings as proposed by the authors, or using an automatic algorithm configuration tool using a same tuning effort for each algorithm. We also study the effect of adding local search to the ABC algorithms. Our experimental results show that local search can improve considerably the performance of several ABC variants and that it reduces strongly the performance differences between the studied ABC variants. We also show that the best ABC variants are competitive with recent state-of-the-art algorithms on the benchmark set we used, which establishes ABC algorithms as serious competitors in continuous optimization. © 2013 Springer Science+Business Media New York.
Serum MicroRNA Signatures Identified in a Genome-Wide Serum MicroRNA Expression Profiling Predict Survival of Non–Small-Cell Lung Cancer

Purpose Recent findings that human serum contains stably expressed microRNA (miRNA) have revealed a great potential of serum miRNA signature as disease fingerprints to predict survival. We used genome-wide serum miRNA expression analysis to investigate the role of serum miRNA in predicting prognosis of non–small-cell lung cancer (NSCLC). Patients and Methods To control disease heterogeneity, we used patients with stages I to IIIa lung adenocarcinoma and squamous cell carcinoma, who were treated with both operation and adjuvant chemotherapies. In the discovery stage, Solexa sequencing followed by individual quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) assays was used to test the difference in levels of serum miRNAs between 30 patients with longer survival (alive and mean survival time, 49.54 months) and 30 patients with shorter survival matched by age, sex, and stage (dead and mean survival time, 9.54 months). The detected serum miRNAs then were validated in 243 patients (randomly classified into two subgroups: n = 120 for the training set, and n = 123 for the testing set). Results Eleven serum miRNAs were found to be altered more than five-fold by Solexa sequencing between longer-survival and shorter-survival groups, and levels of four miRNAs (ie, miR-486, miR-30d, miR-1 and miR-499) were significantly associated with overall survival. The four-miRNA signature also was consistently an independent predictor of overall survival for both training and testing samples. Conclusion The four-miRNA signature from the serum may serve as a noninvasive predictor for the overall survival of NSCLC.
Monitoring the human rights to water and sanitation: an analysis of policy in Pacific island countries

Government monitoring of water and sanitation services is a critical step in realising the human rights to water and sanitation (HRWS). In this study we investigated the national water and sanitation policies of 13 Pacific island countries (PICs) to understand how they envision monitoring the water and sanitation service delivery dimensions put forth by the HRWS framework. In particular, we analysed the policies for fundamental aspects of good monitoring governance and sought to learn how strongly monitoring of each service delivery dimension was represented in the policies. We found that delineation of roles and responsibilities and defined information flows are generally underdeveloped, and that the policies tend to give precedence to monitoring the service delivery dimensions of availability, quality, and sustainability over accessibility, affordability, acceptability, and equality. Donors have considerable influence on which dimensions receive the most emphasis in the policies. If realisation of the HRWS is to be effectively supported in PICs, PIC governments and supporting donors must continue to refine national policy to clarify aspects of good monitoring governance and to be more inclusive of monitoring a wider range of service delivery dimensions.
Where does the heliospheric modulation of galactic cosmic rays start?

Abstract   The long outstanding question of where the heliospheric (solar) modulation of galactic cosmic rays actually begins, in terms of spatial position, as well as at what high kinetic energy, can now be answered. Both answers are possible by using the results of an advanced numerical model, together with appropriate observations. Voyager 1 has been exploring the outskirts of the heliosphere and is presently entering what can be called the very local interstellar medium. It has been generally expected, and accepted, that once the heliopause is crossed, the local interstellar spectrum (LIS) should be measured  in situ  by the Voyager spacecraft. However, we show that this may not be the case and that modulation effects on galactic cosmic rays can persist well beyond the heliopause. For example, proton observations at 100 MeV close to the heliopause can be lower by     ∼    25% to 40% than the LIS, depending on solar modulation conditions. It is also illustrated quantitatively that significant solar modulation diminishes above     ∼    50 GeV at Earth. It is found that cosmic ray observations above this energy contain less that     5  %     solar modulation effects and should therefore reflect the LIS for galactic cosmic rays. Input spectra, in other words the very LIS, for solar modulation models are now constrained by  in situ  observations and can therefore not any longer be treated arbitrarily. It is also possible for the first time to determine the lower limit of the very LIS from a few MeV/nuc to very high energies.
IMPLEMENTATION OF ROOT CAUSE ANALYSIS METHOD TO INVESTIGATE FAILURE OF FRONT WALL TUBE BOILER

Root cause analysis is a method that observes all of the possible causes that make the system or components fail. This research is implemented such a method to investigate the failed front wall tube on the boiler. The purpose of this research is to find out the main cause of failure on the front wall tube to avoid a similar problem in the future.  Considering all aspects that have the potential to be the main cause of failure, therefore, many tests and examinations are done, including visual tests, fractography, metallography, chemical analysis, hardness test, SEM, and EDS analysis.  Examination result on the fracture surface shows two bulges on a tube and some longitudinal cracks spread on bulges outside the surface area. At the same time, the thick scale is also found on the inside surface of these bulges. Moreover, microstructure and hardness changes are also found in this area.  From the analysis of all test result that obtained it is concluded that the main cause of failure is the presence of scales which reduce heat transfer so that local overheating occurred.  Consequently, its tensile strength in this area is decreased, and finally, the tube could not support operational pressure and deformed to make a bulge.
Deep Biological Pathway Informed Pathology-Genomic Multimodal Survival Prediction

The integration of multi-modal data, such as pathological images and genomic data, is essential for understanding cancer heterogeneity and complexity for personalized treatments, as well as for enhancing survival predictions. Despite the progress made in integrating pathology and genomic data, most existing methods cannot mine the complex inter-modality relations thoroughly. Additionally, identifying explainable features from these models that govern preclinical discovery and clinical prediction is crucial for cancer diagnosis, prognosis, and therapeutic response studies. We propose PONET- a novel biological pathway-informed pathology-genomic deep model that integrates pathological images and genomic data not only to improve survival prediction but also to identify genes and pathways that cause different survival rates in patients. Empirical results on six of The Cancer Genome Atlas (TCGA) datasets show that our proposed method achieves superior predictive performance and reveals meaningful biological interpretations. The proposed method establishes insight into how to train biologically informed deep networks on multimodal biomedical data which will have general applicability for understanding diseases and predicting response and resistance to treatment.
Serverless Computing som Function-as-a-Service : Skillnader i prestanda mellan GCP, Azure och AWS

Digitaliseringen går allt snabbare för att fylla det behov som det moderna samhälletkräver så behövs inte bara en digital arbetskraft, det behövs även en infrastruktur sommöjliggör en snabbare digital utveckling. Samtidigt har cloud computing och molnleverantörer blivit en alltmer integrerad del av mjukvaruutvecklingen. Ett ytterligare abstraktionslager som fått mer popularitet och uppmärksamhet de senaste åren är serverless computing. Serverless computing innebär ett abstraktionslager som moln-leverantörer tillhandahåller för att ta bort ansvaret för drift och skalbarhet av servrar. Denna studie konstruerar ett ramverk för en benchmark av prestanda för serverless infrastruktur på tre av de största moln-leverantörerna. Ramverket bygger på en grey box implementering av en rekursiv algoritm för att beräkna det 45:e numret i en Fibonacci-serie i Python, Java och NodeJS. Detta görs på moln-plattformarna Google Cloud Platform, Amazon Web Services och Microsoft Azure. Syftet är att se huruvida det finns skillnader i exekveringstid och minnesåtgång för den givna algoritmen på de tre plattformarna i respektive programmeringsspråk. Studien visar att det finns statistiskt signifikanta skillnader mellan både exekveringstid och minnesåtgång, för alla kodspråken på de tre plattformarna. Störst skillnad är det på NodeJS, följt av Java och sist Python. På aggregerad nivå är det större skillnad för minnesåtgång gentemot exekveringstid.
Health Technology Assessment With Diminishing Returns to Health: The Generalized Risk-Adjusted Cost-Effectiveness (GRACE) Approach

Cost-effectiveness analysis (CEA) embeds an assumption at odds with most economic analysis-that of constant returns to health in the creation of happiness (utility). We aim to reconcile it with the bulk of economic theory.We generalize the traditional CEA approach, allow diminishing returns to health, and align CEA with the rest of the health economics literature.This simple change has far-reaching implications for the practice of CEA. First, optimal cost-effectiveness thresholds should systematically rise for more severe diseases and fall for milder ones. We provide formulae for estimating how these thresholds vary with health-related quality of life (QoL) in the sick state. Practitioners can also use our approach to account for treatment outcome uncertainty. Holding average benefits fixed, risk-averse consumers value interventions more when they reduce outcome uncertainty ('insurance value') and/or when they provide a chance at positively skewed outcomes ('value of hope'). Finally, we provide a coherent way to combine improvements in QoL and life expectancy (LE) when people have diminishing returns to QoL.This new approach obviates the need for increasingly prevalent and ad hoc exceptions to CEA for end-of-life care, rare disease, and very severe disease (eg, cancer). Our methods also show that the value of improving QoL for disabled people is greater than for comparable non-disabled people, thus resolving an ongoing and mathematically legitimate objection to CEA raised by advocates for disabled people. Our Generalized Risk-Adjusted Cost-Effectiveness (GRACE) approach helps align HTA practice with realistic preferences for health and risk.
Investigative Root Cause Analysis for Land Free Urban Microgrid Farm for Food, Water, and Energy

Many urban farms are designed to be indoors or use traditional soil or energy generation techniques. Microgrids provide local electricity to a small network of users with power storage. Few urban farms and microgrids are designed and engineered to draw energy from extreme weather events producing electricity and water. The paper examines the feasibility of a self-sufficient, adaptive small-scale microgrid farm harnessing power from multiple renewable energy (solar and wind) and rainwater collection techniques while producing food. This study’s objective is to conduct an investigative Root Cause Analysis of an outdoor hydroponic system named Pangea. The study findings suggest an outdoor hydroponic system shares many defects from exposure to shifts in climatic conditions to poor engineering and design. The concept and technological aspect of this work can be transferred to commercial, large-scale greenhouse.