ethicalabs/Research-Intent-Collab huggingface dataset:
Additive manufacturing and radio frequency filters : A case study on 3D-printing processes, postprocessing and silver coating methods

Additive manufacturing (AM) is an attractive way to shorten development time, reduce product weight and allow the manufacturing of more complex products than by conventional manufacturing processes. The problem arises when the previous traditional manufacturing requirements need to be fulfilled by AM as well as the volume production capability. This investigation is done together with Ericsson to evaluate the possibilities of the different AM technologies, post-processing methods and silver coating processes to guarantee the specifications of radiofrequency (RF) filters. Here, minimal RF signal insertion losses are targeted. Since insertion losses are dependent on surface roughness, surface smoothness is sought as well. Ericsson simulation software uses correction factors to account for surface roughness, however there are some inconsistencies between the simulated and actual surface roughness that is allowed in the parts. In AM parts, surface roughness is not easy to control since it depends on parameters related to feedstock, process and machine properties. Commonly, most AM components do not comply with requirements of lower surface roughness values. Therefore, parts need to be smoothened before silver plated; this step is necessary to ensure the electrical conductivity in this specific application. These finishing processes add costs to the final product and increase time to market. Firstly, a comprehensive study was carried out to better understand the landscape of AM technologies, postprocessing and silver coating methods. Secondly, the different processes are assessed with the help of selection matrices, considering the products requirements. The components to print are two RF filters with different shapes and dimensions but similar requirements. The CAD design is modified depending on each AM process and directly affects the results. Afterwards, the design of an experimental plan is carried out; the number of samples of each part comparing AM technologies, feedstock, different suppliers (3D printing and post-processing) is obtained. Due to budget and time restrictions, the parts were printed using Multi Jet Fusion and Selective Laser Melting processes. After printing, tolerances and surface roughness were measured. This thesis results in the selection of suitable AM technologies and post-processing methods for RF filters. For MJF printed cavities at 0˚, 30˚ and 90˚ orientation, the best results for this application are obtained at 30˚ providing a good balance between sharp detail and smooth surfaces. In the case of SLM, waveguides are printed at 0˚ and 30˚. 30˚ waveguides present lower surface roughness values than the 0˚ ones as inner support material is needed at 0˚ orientation. SLM cavities were printed at 30˚ in seek of asymmetry between faces, resulting in higher surface roughness in the downfacing face.
Climate resilience in Trento: understanding vulnerabilities and empowering adaptive resources

The impacts of climate change are causing environmental, social and economic damages and are making the planet less liveable. In addition to temperature increases and precipitation changes, climate changes increase the frequency of extreme events such as floods, heat waves and water scarcity. It is evident that actions and decisions both at the global and local level need to be taken. Impacts in the urban environment are intensified by microclimatic phenomena (e.g. Urban Heat Islands) resulting from human lifestyles, morphology and materials used in cities. They are further exacerbated by population growth in urban areas. The paper reports the first results of the study carried out in Trento, a town of 117’000 inhabitants located in the Adige Valley. It investigates the impacts of climate change in its urban environment and focuses on the possibilities of making the town more resilient, through a solid knowledge of the vulnerabilities and the capacity of developing further the opportunities already present in the territory. In recent years, Trento joined European programs such as the “Covenant of Mayors” and launched projects to find solutions to the afore-mentioned challenges and traced scenarios for the future decades: a general decrease in total rainfall accompanied by an increase of precipitation maxima and a significant increase of temperatures are envisaged, leading to vulnerabilities to people and ecosystems, especially in the densest residential areas. The aim of the paper is to show a series of design practices and tests, involving the Municipality and local Research Institutes, seeking to integrate the urban components with the elements of Green and Blue Infrastructure, in order to improve local microclimate and the valorization of spaces. The guidelines provided promote the creation of multifunctional spaces and aim to define replicable solutions that contribute both to mitigation and adaptation to climate changes.
IMPLEMENTING CLINICAL GUIDELINES IN THE TREATMENT OF DIABETES MELLITUS IN  GENERAL PRACTICE

Objectives: To evaluate the implementation of clinical guidelines  for diabetes mellitus in general practice with a specific computer-based  clinical decision support system (CDSS) as part of the intervention.Methods: Randomized study with health center as unit. General  practice in Sør- and Nord-Trøndelag counties in Norway, 380,000  inhabitants. Seventeen health centers with 24 doctors and 499 patients with  diabetes mellitus were in the intervention group and 12 health centers with 29  doctors and 535 patients were in the control group. Main outcome measures were  group differences in fractions of patients without registrations (process  evaluation) and mean group differences for the same variables (patient outcome  evaluation).Results: Statistically significant group differences were  experienced for fractions of patients without registration of cigarette  smoking (intervention group, 82.6%; control group 94.5%), body mass index  (78.2% vs. 93.0%), and sufficient registrations for calculation of risk score  for myocardial infarction (91.1% vs. 98.3%); all during 18 months. Large  center variations were shown for all variables. The only statistically  significant group difference was −2.3 mm Hg (95% CI, −3.8,  −0.8) in diastolic blood pressure in favor of the intervention group.  Statistically insignificant differences in favor of the intervention group  were HbA1c, −0.1% (95% CI, −0.4, 0.1), systolic blood pressure,  −1.2 mm Hg (95% CI, −4.4, 2.0). Statistically insignificant  differences in favor of the control group were fractions of smokers, +3.0%  (95% CI, −4.0, 10.0), body mass index, +0.3 kg/m2 (95%  CI, −0.8, 1.4), risk score in female +0.1 (95% CI, −5.1, 5.2), and  risk score in male +2.6 (95% CI, −14.2, 19.5).Conclusions: Implementation of clinical guidelines for diabetes  mellitus in general practice, by means of a CDSS and several procedures for  implementation, did not result in a clinically significant change in  doctors' behavior or in patient outcome.
THE ROLE OF INTERNATIONAL TRANSPORT LOGISTICS IN OPTIMIZING TRANSPORT INFRASTRUCTURE ARCHITECTURES

Nowadays, transport infrastructure is a crucial component of any social and economic system. The arrangement of infrastructure is a top priority in economic activity due to the globalization of international logistics. This study aims to comprehensively analyse the transport infrastructure system regarding architectural objects. It also seeks to identify the main issues of the management paradigm in the industry and options for solving them. The research employed general scientific methods of cognition, including logical and structural analysis, comparison, theoretical modelling, abstraction, induction, and deduction, as well as statistical methods, specification, generalization, and formalization. The article examines innovative approaches to developing transport infrastructure in the international logistics system. The authors analysed the main issues, challenges, and achievements of managing the architectural component of transport infrastructure. The paper concludes that the effective use of transport infrastructure capabilities is essential for increasing the productivity of economic processes. The authors also identified the position and role of architectural objects in the international logistics system.
Photonic perceptron based on a Kerr microcomb for high-speed, scalable, optical neural networks

Abstract                   Optical artificial neural networks (ONNs)—analog computing hardware tailored for machine learning—have significant potential for achieving ultra‐high computing speed and energy efficiency. A new approach to architectures for ONNs based on integrated Kerr microcomb sources that is programmable, highly scalable, and capable of reaching ultra‐high speeds is proposed here. The building block of the ONN—a single neuron perceptron—is experimentally demonstrated that reaches a high single‐unit throughput speed of 11.9 Giga‐FLOPS at 8 bits per FLOP, corresponding to 95.2 Gbps, achieved by mapping synapses onto 49 wavelengths of a microcomb. The perceptron is tested on simple standard benchmark datasets—handwritten‐digit recognition and cancer‐cell detection—achieving over 90% and 85% accuracy, respectively. This performance is a direct result of the record low wavelength spacing (49 GHz) for a coherent integrated microcomb source, which results in an unprecedented number of wavelengths for neuromorphic optics. Finally, an approach to scaling the perceptron to a deep learning network is proposed using the same single microcomb device and standard off‐the‐shelf telecommunications technology, for high‐throughput operation involving full matrix multiplication for applications such as real‐time massive data processing for unmanned vehicles and aircraft tracking.
AlphaFold 2, but not AlphaFold 3, predicts confident but unrealistic β-solenoid structures for repeat proteins

Abstract                 AlphaFold 2 has revolutionised protein structure prediction but, like any new tool, its performance on specific classes of targets, especially those potentially under- represented in its training data, merits attention. Prompted by a highly confident prediction for a biologically meaningless, scrambled repeat sequence, we assessed AF2 performance on sequences comprised perfect repeats of random sequences of different lengths. AF2 frequently folds such sequences into β-solenoids which, while ascribed high confidence, contain unusual and implausible features such as internally stacked and uncompensated charged residues. A number of sequences confidently predicted as β-solenoids are predicted by other advanced methods as intrinsically disordered. The instability of some predictions is demonstrated by Molecular Dynamics. Importantly, other Deep Learning-based structure prediction tools predict different structures or β-solenoids with much lower confidence suggesting that AF2 alone has an unreasonable tendency to predict confident but unrealistic β-solenoids for perfect repeat sequences. The potential implications for structure prediction of natural (near-)perfect sequence repeat proteins are also explored.
Uncertainty Analysis in Fault Tree Models with Dependent Basic Events

In general, two types of dependence need to be considered when estimating the probability of the top event (TE) of a fault tree (FT): “objective” dependence between the (random) occurrences of different basic events (BEs) in the FT and “state‐of‐knowledge” (epistemic) dependence between estimates of the epistemically uncertain probabilities of some BEs of the FT model. In this article, we study the effects on the TE probability of objective and epistemic dependences. The well‐known Frèchet bounds and the distribution envelope determination (DEnv) method are used to model all kinds of (possibly unknown) objective and epistemic dependences, respectively. For exemplification, the analyses are carried out on a FT with six BEs. Results show that both types of dependence significantly affect the TE probability; however, the effects of epistemic dependence are likely to be overwhelmed by those of objective dependence (if present).
Internet Health Promotion and Behavior Change Theory: An Integrated Model Applied to Internet Interventions to Enhance Prevention and Early Detection

This paper is the study of the theoretical models of mental health promotion and behavior change. It presents the Integrated Model of Health Promotion and Behavior Change theory as it applies to Internet Self-Help to show how the Internet by Case Identification through the screening recruitment strategy enhances prevention and early intervention in mild to moderate depression in the high-prevalence target group of 18-24 year University students. It found that early detection can be facilitated most cost-effectively through case identification by targeted population screening of at-risk groups. It shows, using the conceptual and transtheoretical models of behavior change, how such strategies lead to a decrease in the incidence, severity and longevity of depression. Early detection through case identification gives help that is personalized, widely accessible, can help a large proportion of the community and may lead to a decrease in health care costs.
Erratum to “The Lateral Trigger Probability function for the Ultra-High Energy Cosmic Ray Showers detected by the Pierre Auger Observatory” [Astroparticle Physics 35 (2011) 266–276]

Not Available
DEVELOPMENT OF A SIMULATION MODEL AND SOFTWARE FOR OPTIMIZING ENTERPRISE TRANSPORT LOGISTICS

The article is devoted to the development of a simulation model and software for optimizing the transport and logistics processes of an enterprise. The relevance of the topic is due to the need to increase the efficiency of freight transport management under conditions of uncertainty and limited resources. Traditional route planning methods often do not take into account the multi-criteria nature of the choice and do not allow assessing the influence of the human factor. The subject of the study is the processes of formalization, simulation modeling and software implementation of decision support algorithms in logistics. The purpose of the study is to create a simulation model of the transport department’s activities and a web application for multi-criteria route optimization. The research objectives include: classification of models; development of a simulation model in the AnyLogic environment; justification of the choice of technology stack; development of a mathematical model for estimating travel time and cost, taking into account the synergistic effect; creation of a software product with route visualization and Pareto analysis. The practical significance of the work lies in the creation of a tool that reduces time and financial costs for cargo delivery, increases the validity of route selection and automates reporting. The implementation of developed software and transport monitoring systems ensures not only real-time visibility of shipments, but also provides an analytical framework for decision-making. This ultimately leads to a reduction in logistics costs and increased customer loyalty through improved on-time delivery performance. Thus, the digitalization of a company’s transport logistics management enables a shift from reactive management (responding to problems) to proactive management (preventing problems).
Isotopic and trace element geochemistry of the Seligdar magnesiocarbonatites (South Yakutia, Russia): Insights regarding the mantle evolution beneath the Aldan-Stanovoy shield

Abstract   The Paleoproterozoic Seligdar magnesiocarbonatite intrusion of the Aldan-Stanovoy shield in Russia underwent extensive postmagmatic hydrothermal alteration and metamorphic events. This study comprises new isotopic (Sr, Nd, C and O) data, whole-rock major and trace element compositions and trace element characteristics of the major minerals to gain a better understanding of the source and the formation process of the carbonatites. The Seligdar carbonatites have high concentrations of P2O5 (up to 18 wt%) and low concentrations of Na, K, Sr and Ba. The chondrite-normalized REE patterns of these carbonatites display significant enrichments of LREE relative to HREE with an average La/Ybcn ratio of 95. Hydrothermal and metamorphic overprints changed the trace element characteristics of the carbonatites and their minerals. These alteration processes were responsible for Sr loss and the shifting of the Sr isotopic compositions towards more radiogenic values. The altered carbonatites are further characterized by distinct 18O- and 13C-enrichments compared to the primary igneous carbonatites. The alteration most likely resulted from both the percolation of crustal-derived hydrothermal fluids and subsequent metamorphic processes accompanied by interaction with limestone-derived CO2. The narrow range of negative eNd(T) values indicates that the Seligdar carbonatites are dominated by a homogenous enriched mantle source component that was separated from the depleted mantle during the Archean.
Corporate Social Responsibility in Islamic Culture. Case Study: Islamic Reporting Initiative

The aim of this paper is to explore the state of the art of Corporate Social Responsibility in Islamic culture. This topic is interesting not because CSR is a new concept, but because some corporate sustainability reporting values developed in Western Countries, as GRI Standard, are not focused in Islamic values and beliefs. In fact, Sustainable Development is not a new concept, but it is embedded in the fundamental codes of conduct in Islamic Societies and Laws through Shari’ah. The objectives are: a) a literature review of Islamic CSR b) a qualitative comparative analysis between Islamic CSR (ICSR) and conventional CSR c) a documental analysis of the Islamic network that implements CSR strategies, policies and practices in Islamic Societies (IRI- Islamic Reporting Initiatives) supported by an ad-hoc interview held with an IRI’s Staff member. The conclusion of this research discusses the perspective of Islamic view in sustainability reporting by incorporating the concept of Tawhid which provides a holistic guidance based on Islamic beliefs, values and concepts and, in specific, the main differences between western and Islamic Corporate Sustainability Reporting perspective. The finding of the paper is to be useful to integrate and develop sustainable strategies for Islamic companies.
Message Passing and Combinatorial Optimization

Graphical models use the intuitive and well-studied methods of graph theory to implicitly represent dependencies between variables in large systems. They can model the global behaviour of a complex system by specifying only local factors. This thesis studies inference in discrete graphical models from an algebraic perspective and the ways inference can be used to express and approximate NP-hard combinatorial problems.   We investigate the complexity and reducibility of various inference problems, in part by organizing them in an inference hierarchy. We then investigate tractable approximations for a subset of these problems using distributive law in the form of message passing. The quality of the resulting message passing procedure, called Belief Propagation (BP), depends on the influence of loops in the graphical model. We contribute to three classes of approximations that improve BP for loopy graphs A) loop correction techniques; B) survey propagation, another message passing technique that surpasses BP in some settings; and C) hybrid methods that interpolate between deterministic message passing and Markov Chain Monte Carlo inference.   We then review the existing message passing solutions and provide novel graphical models and inference techniques for combinatorial problems under three broad classes: A) constraint satisfaction problems such as satisfiability, coloring, packing, set / clique-cover and dominating / independent set and their optimization counterparts; B) clustering problems such as hierarchical clustering, K-median, K-clustering, K-center and modularity optimization; C) problems over permutations including assignment, graph morphisms and alignment, finding symmetries and traveling salesman problem. In many cases we show that message passing is able to find solutions that are either near optimal or favourably compare with today's state-of-the-art approaches.
Isotopic (O, Sr, Nd) and trace element geochemistry of the Laouni layered intrusions (Pan-African belt, Hoggar, Algeria): evidence for post-collisional tholeiitic magmas variably contaminated by continental crust

info:eu-repo/semantics/published
Stabilizer quantum error correction with quantum bus computation

4 pages, 5 figures
Selection Bias in Hybrid Randomized Controlled Trials using External Controls: A Simulation Study

Hybrid randomized controlled trials (hybrid RCTs) integrate external control data, such as historical or concurrent data, with data from randomized trials. While numerous frequentist and Bayesian methods, such as the test-then-pool and Meta-Analytic-Predictive prior, have been developed to account for potential disagreement between the external control and randomized data, they cannot ensure strict type I error rate control. However, these methods can reduce biases stemming from systematic differences between external controls and trial data. A critical yet underexplored issue in hybrid RCTs is the prespecification of external data to be used in analysis.   The validity of statistical conclusions in hybrid RCTs depends on the assumption that external control selection is independent of historical trials outcomes. In practice, historical data may be accessible during the planning stage, potentially influencing important decisions, such as which historical datasets to include or the sample size of the prospective part of the hybrid trial, thus introducing bias. Such data-driven design choices can be an additional source of bias, which can occur even when historical and prospective controls are exchangeable.   Through a simulation study, we quantify the biases introduced by outcome-dependent selection of historical controls in hybrid RCTs using both Bayesian and frequentist approaches, and discuss potential strategies to mitigate this bias. Our scenarios consider variability and time trends in the historical studies, distributional shifts between historical and prospective control groups, sample sizes and allocation ratios, as well as the number of studies included. The impact of different rules for selecting external controls is demonstrated using a clinical trial example.
Leadership Styles and Organizational Commitment with Mediation of Organizational Citizenship Behavior among Bahraini Managers

This study explores the role of organizational citizenship behavioras a mediating variable to the relationship between leadership styles and organizational commitment among Bahraini managers. Organizational citizenship behaviorwas in debate regards it is positive and negative consequences through the literature, most ofthe studies support the conclusion of organizational commitment that leads to organizational citizenship behavior, other studies support the opposite. However, the mediating relationship of organizational citizenship behaviorsbetween leadership styles and organizational commitment is not developed by previous studies.Therefore, the use of the mediating variable gives more insight into the relationship between the dependent and independent variables and contributes to the clarity of conclusions. This study found thatleadership presentsa positive significant relationship with organizational commitment and organizational citizenshipbehavior, and organizational citizenship behavior positively and significantly affects organizationalcommitment and partially mediates the relationship between the two variables