ethicalabs/Research-Intent-Collab huggingface dataset:
Investigation of grounding accidents in the bay of İzmir with the application of root cause analysis

City of Izmir as the third largest city of Turkey, is the opening gate of Anatolia to the world through Aegean Sea. The city with its great volume of cargo capacity plays crucial role both in international and domestic sea trade. The Port of Alsancak located at the inner part of the bay is the largest seaport of Aegean Region in terms of annual loading capacity. The main objective of this research is to find the root-causes of accidents that have resulted in the groundings in Bay of Izmir. To do this, the Root Cause Analysis methodology was carried out on the accidental data provided by Turkish Main Search and Rescue Coordination Center (TMSRCC). Between 2001 and 2016, a total of 24 ships grounded at the entrance of Yenikale due to shallow water conditions, which is regarded as the riskiest point in terms of groundings. In this study, the Fault Tree Analysis (FTA) method which is the one of the most preferred root cause analysis methods was used. As a result, it was found that equipment failures and geographical factors are the main reasons of grounding accidents in Bay of Izmir. In order to eliminate these causes, necessary precautions have been offered and suggestions for further studies have been made.
Exploring study profiles of Computer Science students with Social Network Analysis

Information technology is widely adapted in all levels of education. The extensive information resources facilitate enhanced human capacity and the social environment to support learning. In particular, Social Network Analysis (SNA) has been broadly used in teaching and learning practices. In this paper, we perform community detection analysis to identify the learning behavior profiles of undergraduate computer science students in a Nordic university. The social network was created using 273 responses to an online survey. The students themselves provided their social connections at the university, and node attributes were created based on responses to questions regarding Educational Values, Goals Orientation, Self-efficacy, and the university teaching methods. We analyze the biggest communities to identify the factors that characterize the learning strategy and preferences of undergraduate computer science students.
Molecular Dynamics Simulations of Sodium Dodecyl Sulfate Micelles in Water—The Effect of the Force Field

Molecular dynamic (MD) simulations of preassembled sodium dodecyl sulfate (SDS) micelles are carried out using three versions of GROMOS, as well as CHARMM36, OPLS-AA, and OPLS-UA force fields at different aggregation numbers and box sizes. The differences among force fields have little effect on the overall micelle structure of small aggregates of size 60 or 100, but for micelles of an aggregation number of 300 or higher, bicelle structures with ordered tails, rather than the more realistic rodlike or cylindrical micelles with disordered tails, occur when using versions of GROMOS45A3 or the OPLS-AA force fields that are adapted to model the sulfate head group atoms using methods given in the literature. We find that the Lennard-Jones (L-J) parameters for the sodium ions and the ionic oxygens of the SDS head group, as well as the water model, control the transition to bicelles, regardless of other L-J parameters. A closer binding of the sodium ions to the head group ionic oxygens screens the electrostatic repulsions more strongly, resulting in condensation of SDS head groups, leading to unphysical bicelles for GROMOS45A3 or the OPLS-AA force fields, when the aggregation number is large. A telltale sign that the sodium-oxygen interaction is too strong shows up in high nearest neighbor peaks (height >8 and height >20 for micelles with 60 and 100 surfactants, respectively) in the radial distribution functions (RDFs) of sodium ions to ionic oxygens. In the 100-surfactant micelles, the high RDF peak is accompanied by "crystal-like" layering of sodium ions onto the surface of the micelle. The distance between the sodium ions and micelle also depends on the number of waters binding to sodium ions in the presence of surfactant head groups, which depends on both the sodium ion and water models, and for the same sodium model increases as the water model is changed in the order: TIP4P, SPC/E, SPC, and TIP3P.
A Pharmacogenetic Prediction Model of Progression‐Free Survival in Breast Cancer using Genome‐Wide Genotyping Data from <scp>CALGB</scp> 40502 (Alliance)

Genome‐wide genotyping data are increasingly available for pharmacogenetic association studies, but application of these data for development of prediction models is limited. Prediction methods, such as elastic net regularization, have recently been applied to genetic studies but only limitedly to pharmacogenetic outcomes. An elastic net was applied to a pharmacogenetic study of progression‐free survival (PFS) of 468 patients with advanced breast cancer in a clinical trial of paclitaxel, nab‐paclitaxel, and ixabepilone. A final model included 13 single nucleotide polymorphisms (SNPs) in addition to clinical covariates (prior taxane status, hormone receptor status, disease‐free interval, and presence of visceral metastases) with an area under the curve (AUC) integrated over time of 0.81, an increase compared to an AUC of 0.64 for a model with clinical covariates alone. This model may be of value in predicting PFS with microtubule targeting agents and may inform reverse translational studies to understand differential response to these drugs.
Nanomedicine-Driven Advances: Enhancing Checkpoint Inhibition and CAR-T Therapies in Cancer Immunotherapy

Cancer immunotherapy has revolutionized oncological treatment, offering patients improved survival and quality of life. However, tumor heterogeneity, immune evasion, and treatment toxicity hinder its full potential. Nanomedicine provides innovative solutions to these challenges by enhancing immunotherapeutic strategies' efficacy, specificity, and safety. This review explores current advances in the application of nanomaterials in cancer immunotherapy, focusing on their role in personalized approaches, multifunctional therapeutic modalities, biocompatibility considerations, and enhancement of the enhanced permeability and retention (EPR) effect. Critical developments in bioinspired and stimuli-responsive nanotechnologies are discussed, emphasizing their ability to modulate the tumor microenvironment (TME), improve drug delivery, and facilitate combination therapies. The review also addresses translational challenges, regulatory considerations, and clinical advancements, highlighting examples from recent clinical trials and emerging technologies. Personalized nanomedicine enables the design of tailored therapeutic agents targeting tumors, reducing off-target effects and maximizing therapeutic efficacy. Multifunctional nanomaterials facilitate synergistic effects when combining photothermal, photodynamic, chemotherapeutic, and immunotherapeutic modalities. While promising, toxicity, biodegradability, and long-term safety issues necessitate standardized evaluation protocols for clinical translation. Advancements in stimuli-responsive nanomaterials and immune checkpoint inhibitors contribute to developing next-generation cancer immunotherapies with improved outcomes. This review provides a comprehensive overview of nanomedicine's current landscape, challenges, and future perspectives in cancer immunotherapy, advocating for further research to address the existing gaps and optimize clinical applications.
Brexit and the United Nations Security Council: Declining British Influence?

The United Kingdom's decision to leave the European Union has ramifications beyond the UK and the EU. This article analyses the impact of the Brexit referendum on the UK's political capital in the United Nations Security Council; a dimension of Brexit that has received little attention thus far. Drawing on extensive elite interviews we show that the UK has considerable political capital in the Council, where it is seen as one of the most effective actors, but the reputational costs of Brexit are tarnishing this image. With case-studies on the UK's role in Somalia and Yemen we show how the UK has been able to further its interests with dual roles in the EU and Security Council, and the risks posed by tensions between trade and human rights after Brexit. We also analyse what it takes to be influential within the Security Council and argue that more attention should be paid to the practices of diplomacy. Influence is gained via penholding, strong diplomatic skill and a well-regarded UN permanent representative. The UK accrues political capital as a leader on the humanitarian and human rights side of the Council's agenda, but this reputation is at risk as it exits the EU.
Repurposing NGO data for better research outcomes: a scoping review of the use and secondary analysis of NGO data in health policy and systems research

Abstract                 Background                 Non-governmental organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas, including the evaluation of health policy and programmes.                                Methods                 A scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytical approach provided a comprehensive overview and descriptive analyses of the studies that (1) used data produced or collected by or about NGOs; (2) performed secondary analysis of the NGO data (beyond the use of an NGO report as a supporting reference); and (3) analysed NGO-collected clinical data.                                Results                 Of the 156 studies that performed secondary analysis of NGO-produced or collected data, 64% (n = 100) used NGO-produced reports (mostly to a limited extent, as a contextual reference or to critique NGO activities) and 8% (n = 13) analysed NGO-collected clinical data. Of these studies, 55% (n = 86) investigated service delivery research topics and 48% (n = 51) were undertaken in developing countries and 17% (n = 27) in both developing and developed countries. NGOs were authors or co-authors of 26% of the studies. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), albeit with some limitations such as inconsistent and missing data.                                Conclusion                 We found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics such as conflict-affected areas. NGO–academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. The use of NGO data use could enable relevant and timely research in the areas of programme evaluation and health policy and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries.
Investigating Cultural Alignment of Large Language Models

ACL 2024 (Main)
Decision on the election to the judicial function and its review by Constitutional Court

The paper explores the review of decisions on the election to judicial functions. The candidate may file an appeal on the decision on the election to the judicial function to the Constitutional Court within 15 days from the day of the publication of the decision in the Official Gazette of the Republic of Serbia, which excludes the right to submit a constitutional appeal. Appeal to the Constitutional Court suspends the enforcement of the decision, which means that the elected candidate cannot take office before the appeal is decided. The scope of the Constitutional Court review has been limited to proper execution of powers by the High Judicial Council, following procedure provided for in the Law on Judges and the quality of reasoning in decisions on the election to the judicial function. So far, all appeals submitted to the Constitutional Court have been dismissed as manifestly ill-founded.
Structural Reliability Analysis and Quantitative Risk Assessment for Optimizing Cost of Offshore Structural Integrity Management and Life Extension Programme without Air Diving Operation

Abstract                Offshore platforms in Gulf of Thailand have been aging and reaching their end of service life. To safely operate in aging platforms beyond their original intended service life, all possible operation risks need to be assessed through design review, condition assessment, inspection strategy and technique for the platform life extension stage. Qualitative or Semi-quantitative risk assessment was generally utilized by adopting scoring rule based on the condition assessment through inspection data/anomalies. A general subsea inspection campaign requested a costly additional air diving campaign for ACFM for joints with low fatigue life without a consideration of past inspection results. In practice, the routine inspection should be arranged in such a way that the operation risk meets the as-low-as practically possible (ALARP) criteria and yet minimize the cost, time and resources required for inspection. A quantitative risk assessment (QRA) and structural reliability analysis (SRA) are applied within PTTEP to evaluate and predict platform's risk development through time dependent probability of system failure. Inspection strategy including interval (when), locations (where), and suitable equipment and technique (how) are quantitatively incorporated into a mathematical model. The system probability of failure incorporating the system degradation is evaluated and inspection is triggered when the risk exceeds the allowable threshold. A complementary statistical decision model to evaluate the suitable inspection interval considered cost of failure, loss of production, and inspection is also employed. Results of quantitative method shows that the inspection interval can be prolonged, particularly, for well-designed and well-maintained platforms with reducing demand of additional air diving campaign. For most platform with relatively low to moderate consequences of failure, the inspection interval can be extended up until 10 years with routine general visual inspection (GVI), Flooded Member Detection (FMD) operated by remotely operated vehicle (ROV), provided that no significant anomalies are reported during the entire platform life cycle.                In Summary, the approaches minimize the demand for additional air diving operation leading a reduction in additional cost, operational risk, and carbon footprint at least 250MT. The offshore structural integrity management and life extension programme for platform after service life by QRA is considered as new leveraged paradigm and delivers the cutting-edge integrity management programme leading to the most optimized operational cost with philosophy of safety and sustainability.
AutoML-Based Neural Architecture Search for Object Recognition in Satellite Imagery

Advancements in optical satellite hardware and lowered costs for satellite launches raised the high demand for geospatial intelligence. The object recognition problem in multi-spectral satellite imagery carries dataset properties unique to this problem. Perspective distortion, resolution variability, data spectrality, and other features make it difficult for a specific human-invented neural network to perform well on a dispersed type of scenery, ranging data quality, and different objects. UNET, MACU, and other manually designed network architectures deliver high-performance results for accuracy and prediction speed in large objects. However, once trained on different datasets, the performance drops and requires manual recalibration or further configuration testing to adjust the neural network architecture. To solve these issues, AutoML-based techniques can be employed. In this paper, we focus on Neural Architecture Search that is capable of obtaining a well-performing network configuration without human manual intervention. Firstly, we conducted detailed testing on the top four performing neural networks for object recognition in satellite imagery to compare their performance: FastFCN, DeepLabv3, UNET, and MACU. Then we applied and further developed a Neural Architecture Search technique for the best-performing manually designed MACU by optimizing a search space at the artificial neuron cellular level of the network. Several NAS-MACU versions were explored and evaluated. Our developed AutoML process generated a NAS-MACU neural network that produced better performance compared with MACU, especially in a low-information intensity environment. The experimental investigation was performed on our annotated and updated publicly available satellite imagery dataset. We can state that the application of the Neural Architecture Search procedure has the capability to be applied across various datasets and object recognition problems within the remote sensing research field.
Human Resource Information System (Hris): Navigating The Implementation, Challenges, And Benefits

This research examines the implementation, perceived obstacles, and benefits of HR information systems (HRIS), while also offering suggestions for the effective implementation of HRIS within organisations. The study conducted a comprehensive literature review from reputable academic research sources such as ScienceDirect, Google Scholar, and Bing. The focus was on analysing HRIS, implementation challenges and benefits, and recommendations on ways to efficiently implement HRIS within organisations. Findings of the study highlight significant obstacles that hinder HRIS implementation within organisations. However, the study also recognises the benefits associated with HRIS implementation in organisations, which can ultimately enhance the efficiency and effectiveness of HRM practices. Based on a thorough examination of these factors, the research also provides best practices for successfully integrating and utilising HRIS within organisations.
Numerical Simulations in Cosmology III: Dark Matter Halos

Lecture at the Summer School "Relativistic Cosmology: Theory and Observations", Italy, Como, May 2000. AASTeX and natbib
Additional file 3 of Mixotrophic chemosynthesis in a deep-sea anemone from hydrothermal vents in the Pescadero Basin, Gulf of California

Additional file 3: Figure S1. Phylogenetic relationships of the SUP05 group, based on 16S rRNA. A. SUP05 cluster, based on 16S rRNA. Taxa shown in green are known symbionts of marine invertebrates. * &gt; 70% support (using the Jukes Kantor model). Additional taxa were included according to Petersen et al. 2012; Glaubitz et al. 2013; Shah et al. 2019. Inset. Shows SUP05 amplicons recovered from Ostiactis pearseae, surrounding seawater samples, and Bathymodiolus mussels from the Costa Rica margin Jaco Scar seep sites (SG, unpublished).
Macroscopic modelling of radio emission from ultra-high-energy-cosmic-ray-induced air showers

De aarde wordt dagelijks vanuit de ruimte gebombardeerd door kosmische deeltjes met extreem hoge energieën. Tijdens botsingen in onze atmosfeer ontstaat een lawine van secundaire deeltjes, typisch een miljoen tot een miljard in aantal, welke met de snelheid van het licht richting aarde beweegt. Een netto elektron overschot in combinatie met de afbuiging van elektronen en positronen in het aardmagneetveld geeft aanleiding tot een elektrische stroom in de deeltjes lawine. In het proefschrift wordt de uitgezonden radio straling beschreven die is geïnduceerd door de tijdsvariatie van deze stroom waarbij relativistische effecten in rekening worden genomen. Met name relativistische “Cherenkov” effecten door de eindige luchtdichtheid in onze atmosfeer zijn van cruciaal belang voor een realistische beschrijving van de radio-emissie. Voor het modelleren van de emissie is een computerprogramma ontwikkeld, die publiekelijk verkrijgbaar is. De berekening maakt gebruik van realistische Monte-Carlo simulaties om de stroom- en ladingsverdeling in de deeltjes lawine te verkrijgen. Deze worden vervolgens gebruikt om de radio straling te berekenen. Resultaten van de simulaties laten zien dat het uitgezonden radio signaal goed gebruikt kan worden om de massa van het oorspronkelijke kosmische deeltje te bepalen. Dit geeft de mogelijkheid om de belangrijke vraag over hun oorsprong te beantwoorden. Tevens worden de resultaten van de berekeningen met data vergeleken wat een sterke aanwijzing geeft voor emissie door het netto elektron overschot. Dit is de eerste keer dat dit wordt aangetoond in een natuurlijk proces.
Digital phenotyping correlations in larger mental health samples: analysis and replication

Background      Smartphones can facilitate patients completing surveys and collecting sensor data to gain insight into their mental health conditions. However, the utility of sensor data is still being explored. Prior studies have reported a wide range of correlations between passive data and survey scores.              Aims      To explore correlations in a large data-set collected with the mindLAMP app. Additionally, we explored whether passive data features could be used in models to predict survey results.              Method      Participants were asked to complete daily and weekly mental health surveys. After screening for data quality, our sample included 147 college student participants and 270 weeks of data. We examined correlations between six weekly surveys and 13 metrics derived from passive data features. Finally, we trained logistic regression models to predict survey scores from passive data with and without daily surveys.              Results      Similar to other large studies, our correlations were lower than prior reports from smaller studies. We found that the most useful features came from GPS, call, and sleep duration data. Logistic regression models performed poorly with only passive data, but when daily survey scores were included, performance greatly increased.              Conclusions      Although passive data alone may not provide enough information to predict survey scores, augmenting this data with short daily surveys can improve performance. Therefore, it may be that passive data can be used to refine survey score predictions and clinical utility may be derived from the combination of active and passive data.