Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards an Operational Concept for Advanced Nuclear Power Plants

Advanced nuclear power plants currently being designed are characterized by structural, functional and operational features that are uncommon in the current generation of plants worldwide. Due to the long worldwide hiatus in the development of new nuclear power plants most of these issues and the implications of new operational concepts have never been evaluated in detail. This paper is a summary of the results a four-year project at the Idaho National Laboratory to develop a systematic process to analyze the operational requirements of new plants. The paper describes a method to produce reliable information for the design of robust and resilient systems that allow dynamic collaboration between operators and plant systems. It also provides examples of the application of this method to the development of an operational concept for advanced nuclear power plants, with examples from sodium fast reactors (SFRs).
Resource allocation for cellular device‐to‐device‐aided vehicle‐to‐everything networks with partial channel state information

In Vehicle‐to‐Everything (V2X), cellular Device‐to‐Device (D2D) communication can not only enhance system capacity and spectral utilization but also reduce the traffic load and communication delay. However, due to the fast variations of the channel state information (CSI) caused by high mobility of vehicles, the accurate CSI is difficult to be obtained in real‐time. In this paper, different from other previous researches that are subject to the perfect CSI, a more realistic channel state model is adopted that only the partial CSI of the communication links is available. Then we study the joint power allocation and spectrum sharing problem to maximize the total weighted ergodic capacity of all vehicular links, namely, Vehicle‐to‐Infrastructure (V2I) links and Vehicle‐to‐Vehicle (V2V) links. Meanwhile, the transmission reliability guarantees the quality of service (QoS) requirements of V2I and V2V. Since the formulated problem is a nonconvex mixed integer nonlinear programming (MINLP) problem, we first derive the strategy for obtaining the optimal solution of power allocation under arbitrary weighted factor and quantify different cases of feasible regions. Then we propose a two‐stage algorithm to complete the optimal resource allocation in polynomial time. Moreover, we further propose a low‐complexity spectrum sharing method based on the principles of Gale‐Shapley mechanism. The simulation results show that the proposed algorithms outperform the other baseline schemes significantly, and the low‐complexity scheme can effectively achieve a tradeoff between performance and complexity.
Perception of Pharmacy Teachers About Their Roles and Current Practice at Governmental Universities in Sudan

Background Pharmacy educator has a number of roles and responsibilities, an information provider, clinical trainer, role model on-the-job, formal teaching settings, course planner and resource material creator, student assessor, and curriculum evaluator. Objective This study aimed to assess the perception and commitment of pharmacy teachers in Sudanese governmental universities about their roles and educational responsibilities. Materials and Methods Descriptive cross-sectional study was conducted at governmental pharmacy colleges in Sudan from November 2020 to July 2021. Data were collected using an online self-administered questionnaire adapted from the Association for Medical Education in Europe (AMEE) Guide No. 20. Data were analyzed using Statistical Package for Social Sciences (SPSS) version 26 and Microsoft Excel version 16. Results Out of 125 participants, 61.6% were female and 65.6% were lecturers. Approximately half of them had less than five years’ experience. The most important role perceived and the highest committed one was a lecturer in the classroom setting. Only half of the participants had good perceptions and commitment regarding teachers’ roles. Age, designation, and continuous professional development were significantly associated with participants’ commitment. Also, a significant association was found between the perception and practice of the participants. Conclusion Only half of pharmacy educators were found to have a good perception and good commitment regarding their role as teachers.
Application of Lean Six Sigma Methodology in Software Continuous Integration

Lean Six Sigma (LSS) is an effective methodology that aims to maximize shareholder value by improving quality, efficiency, customer satisfaction and costs. Continuous integration is the software engineering practice of rapid and automated development and testing. A case study presented in this paper demonstrates how LSS tools help software R&D teams to improve product quality and reduce development cost. The define, measure, analyze, improve and control (DMAIC) methodology is applied to develop an action plan to achieve continuous integration at an anonymous software R&D organization's LSS Green Belt project. The LSS implementation has had a significant impact on the financial performance of the organization. It is showed that the package continuous integration (PCI) success ratio (3 months average) increased from 27% to 74%, meanwhile an operational saving of approximately 56.87K Euro was reported from this project. Finally, some key success factors that are critical to the implementation of an effective Green Belt program are examined, and managerial implications are provided.
Bone metastases in non-small cell lung cancer: a narrative review

Background and Objective Bone metastases are common in patients with non-small cell lung cancer (NSCLC) and remain a significant source of morbidity, mortality, and diminished quality of life, despite the considerable progress made in the overall management of patients with metastatic NSCLC over the last decade. Understanding the molecular pathogenesis of bone metastases is critical to improving survival, preserving function, and managing symptoms in this patient population. The objective of our review is to provide a comprehensive review of the pathophysiology, clinical presentation, management, and factors predicting the development and prognosis of patients with NSCLC with bone metastases. Methods An online electronic search was performed on PubMed and Google Scholar of all English-language literature using combinations of the following keywords: bone metastases, non-small cell lung cancer, pathophysiology, skeletal related events, response to therapy, predictive factors, and immunotherapy. Bibliographies of identified papers were reviewed for additional articles of interest. Observational cohort, retrospective studies, randomized controlled trials (RCTs), meta-analyses, and review articles were examined for this review. Key Content and Findings Bone metastases in lung cancer patients remain a common occurrence, impacting morbidity, mortality, and quality of life. Patients with skeletal related events (SREs) have worse prognosis. There is data supporting use of bisphosphonates and/or denosumab, and these should be considered in all patients with bone metastases. Novel studies comparing the genomic alterations of skeletal metastases and primary tumors are needed. As therapy for patients with advanced disease evolves, more studies are needed to evaluate the interplay between immunotherapy and bone metastases, and in determining the response to treatment in bone. Conclusions Predicting development and progression of bone metastases could allow earlier and targeted therapy in patients with bone metastases. Predicting and evaluating response to conventional chemotherapy and immune checkpoint inhibitors in NSCLC patients with bone metastases remains an unmet need and merits further study.
Entrepreneurship and Peacebuilding: A Review and Synthesis

Entrepreneurship is the dominant form of enterprise in conflict-affected settings, yet little is known about the role of entrepreneurship in peacebuilding. In response, this article undertakes a review of entrepreneurship in conflict-affected regions to integrate research from business and management with research from political science, international relations, and parallel domains. Three views of entrepreneurship emerge—the destructive view, economic view, and social cohesion view—showing how entrepreneurship can concurrently create conflict but also potentially generate peace. The article identifies new avenues for pro-peace entrepreneurship: namely, through personal transformation, social contributions, inclusive interactions, conflict trigger removal, intergroup policy persuasion, and acting as legal champions. This article also discusses several pathways forward for business-for-peace research alongside additional implications for the deployment of business-based support programs in conflict settings.
Optimal Network Protocol Selection for Competing Flows via Online Learning

Today’s Internet must support applications with increasingly dynamic and heterogeneous connectivity requirements, such as video streaming and the Internet of Things. Yet current network management practices generally rely on pre-specified network configurations, which may not be able to cope with dynamic application needs. Moreover, even the best-specified policies will find it difficult to cover all possible scenarios, given applications’ increasing heterogeneity and dynamic network conditions, e.g., on volatile wireless links. In this work, we instead propose a model-free learning approach to find the optimal network policies for current network flow requirements. This approach is attractive as comprehensive models do not exist for how different policy choices affect flow performance under changing network conditions. However, it can raise new challenges for online learning algorithms: policy configurations can affect the performance of multiple flows sharing the same network resources, and this performance coupling limits the scalability and optimality of existing online learning algorithms. In this work, we extend multi-armed bandit frameworks to propose new online learning algorithms for protocol selection with provably sublinear regret under certain conditions. We validate the optimality and scalability of our algorithms through data-driven simulations and testbed experiments. (An extended abstract of this work was accepted by IEEE ICNP as a short paper Zhang et al. (2019)).
Proficiency of allocentric and egocentric wayfinding: a comparison of schoolchildren with young adults and older adults

Abstract Wayfinding skills decay in old age, more so for wayfinding in an allocentric than an egocentric reference frame. This study investigates whether wayfinding deficits of schoolchildren mimic those of older adults. Schoolchildren were tested on two wayfinding tasks: one could only be mastered in an allocentric, and the other only in an egocentric reference frame. The results were compared with those from a previous study of young and older adults who had been tested on the same two wayfinding tasks. It was found that wayfinding performance improved somewhat from school age to young adulthood and that this improvement proceeded more or less in parallel for the allocentric and the egocentric tasks. It was further found that wayfinding performance decayed from young to older adulthood and that this decay was more dramatic for the allocentric than for the egocentric task. This pattern of findings does not support the hypothesis that the wayfinding performance of schoolchildren mimics that of older adults.
Rock mass fracture maps prediction based on spatiotemporal image sequence modeling

Discontinuities in rock mass are the characteristic challenge of rock tunnel engineering projects, which have a vital impact on rock mass exposures' mechanical and hydrological characteristics. There is a growing demand for predicting the fracture maps during tunnel excavation to ensure a smooth tunnel excavation process. The computer vision measurement of fractures in the tunnel surface is a current hot spot, but the traditional statistical analysis methods for fractures are still mainstream. This paper uses a novel perspective of the time‐space sequence to explain the continuously exposed rock mass during tunneling. A spatial‐aware recurrent neural network is proposed, which takes the historical fracture maps as the input to predict the unexcavated part. The experimental results suggest that the proposed model produces reliable performance and is superior to the other two state‐of‐the‐art deep learning models. Moreover, the test on the site rock tunnel data suggested promising results for fracture map predictions.
Optimization of planar strongly coupled wireless power transfer system for biomedical applications

Strongly coupled four‐coil wireless power transfer (WPT) system is presented in this letter. Conformal architecture is used for both transmitter (TX) and receiver (RX) coils. Thus, a high mutual coupling coefficient is achieved between the coplanar coils. Furthermore, the quality factors of primary and secondary coils are improved. The proposed WPT system features a compact structure for biomedical applications and provides a measured efficiency greater than 79% when the distance between the TX and RX is 10 mm at a resonance frequency of 13.56 MHz. The designed system is also simulated for 10 mm human tissue medium using HFSS, which generates a power transfer efficiency of 55.1%. The simulated results are also verified by experimentation. © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:1861–1866, 2016
Surrogate modeling and optimization for the unequal diameter radial diffuser of stratified thermal energy storage tanks

Stratified thermal energy storage (TES) tanks are widely used in thermal power plants to enhance the electric power peak load shifting capability and integrate high renewable energy shares. In this study, a data‐driven surrogate modeling and optimization study of the unequal diameter radial diffuser previously proposed by the present authors is conducted. First, based on the orthogonal experimental design, numerical experiments are performed to generate the performance database. Then, the database is used to establish the data‐driven surrogate model via the support vector machine. Subsequently, the single‐objective optimization and multiobjective optimization of an unequal diameter radial diffuser are conducted using the genetic algorithm. For the single‐objective optimization, the optimal thermocline thickness is 0.829 m when the diameter ratio of the long baffle and the tank is 0.426, the diameter ratio of the short baffle and the long baffle is 0.823, and the distance between the two baffles is 228.51 mm. For multiobjective optimization, the obtained Pareto optimal solutions are obtained. Under the premise of maintaining excellent thermal stratification, the selected Point C can reduce the steel cost by 88.1%. The research results are helpful for designing efficient and economical unequal diameter radial diffusers for TES tanks.
DEEP LEARNING BASED NON-ITERATIVE SOLUTION TO THE INVERSE PROBLEM IN MICROWAVE IMAGING

|A deep learning-based approach in conjugation with Fourier Diﬀraction Theorem (FDT) is proposed in this paper to solve the inverse scattering problem arising in microwave imaging. The proposed methodology is adept in generating a permittivity mapping of the object in less than a second and hence has the potential for real-time imaging. The reconstruction of the dielectric permittivity from the measured scattered (cid:12)eld values is done in a single step as against that by a long iterative procedure employed by conventional numerical methods. The proposed technique proceeds in two stages; with the initial estimate of the contrast function being generated by the FDT in the (cid:12)rst stage. This initial pro(cid:12)le is fed to a trained U-net to reconstruct the (cid:12)nal dielectric permittivities of the scatterer in the second stage. The capability of the proposed method is compared with other works in the recent literature using the Root Mean Square Error (RMSE). The proposed method generates an RMSE of 0.0672 in comparison to similar deep learning methods like Back Propagation-Direct Sampling Method (BP-DSM) and Subspace-Based Variational Born Iterative Method (SVBIM), which produce error values 0.1070 and 0.0813 in the case of simulation (using Austria Pro(cid:12)le). The RMSE level while reconstructing the experimental data (FoamDielExt experimental database) is 0.0922 for the proposed method as against 0.1631 and 0.1037 for BP-DSM and SVBIM, respectively.
Learning-outcomes-based assessments at universities of applied sciences in the Netherlands: perceptions of business lecturers

Abstract About ten years ago, concerns were expressed about quality and standards in some universities of applied sciences (UAS) in the Netherlands. In response, a HBO report outlined a series of measures to improve the quality of assessment practices in UAS. This study provides recent analysis of lecturer perceptions of assessments of UAS with a view to exploring how these recommendations have become embedded in the assessment cultures of UAS. The qualitative study with 19 participants teaching at ten different UAS, reveals strong evidence of a staff knowledge gap around outcomes-based assessment.
Sensitivity Analysis and Optimization of Multibody Systems

Multibody dynamics simulations are currently widely accepted as valuable means for dynamic performance analysis of mechanical systems. The evolution of theoretical and computational aspects of the multibody dynamics discipline make it conducive these days for other types of applications, in addition to pure simulations. One very important such application is design optimization for multibody systems. Sensitivity analysis of multibody system dynamics, which is performed before optimization or in parallel, is essential for optimization. Current sensitivity approaches have limitations in terms of efficiently performing sensitivity analysis for complex systems with respect to multiple design parameters. Thus, we bring new contributions to the state-of-the-art in analytical sensitivity approaches in this study. A direct differentiation method is developed for multibody dynamic models that employ Maggi’s formulation. An adjoint variable method is developed for explicit and implicit first order Maggi’s formulations, second order Maggi’s formulation, and first and second order penalty formulations. The resulting sensitivities are employed to perform optimization of different multibody systems case studies. The collection of benchmark problems includes a five-bar mechanism, a full vehicle model, and a passive dynamic robot. The fivebar mechanism is used to test and validate the sensitivity approaches derived in this paper by comparing them with other sensitivity approaches. The full vehicle system is used to demonstrate the capability of the adjoint variable method based on the penalty formulation to perform sensitivity analysis and optimization for large and complex multibody systems with respect to multiple design parameters with high efficiency. In addition, a new multibody dynamics software library MBSVT (Multibody Systems at Virginia Tech) is developed in Fortran 2003, with forward kinematics and dynamics, sensitivity analysis, and optimization capabilities. Several different contact and friction models, which can be used to model point contact and surface contact, are developed and included in MBSVT. Finally, this study employs reference point coordinates and the penalty formulation to perform dynamic analysis for the passive dynamic robot, simplifying the modeling stage and making the robotic system more stable. The passive dynamic robot is also used to test and validate all the point contact and surface contact models developed in MBSVT.
HTB: A Very Effective Method to Protect Web Servers Against BREACH Attack to HTTPs

BREACH is a side-channel attack to HTTPs that allows an attacker to obtain victims’ credentials under certain conditions. An attacker with a privileged position on the network can guess character by character a secret session key just by analyzing the size of the responses returned by the server over HTTPs and encrypted. Heal the Breach (HTB) is the proposed technique to mitigate BREACH attack by randomly changing the size of server responses through a modified gzip library. The attacker needs a precision of one byte in the size of the responses to be able to determine if a guess character is part of the secret token. Since the modified gzip library introduces randomness in the size of the response, BREACH becomes ineffective. The only way to circumvent this protection is to make several requests and compute the average size of the response, which minimizes the random effect. Mathematical and experimental results show that, for a random variation of the size from 1 to 10 bytes, an attacker needs to analyze 500 times more packages to obtain enough accuracy and surpass this mitigation. However, if the number of requests increases it is easier to isolate and block the attack using standard Intrusion Detection Systems (IDS). Compared to other mitigations, the approach presented in this paper is very effective, easy to implement for all websites hosted in the server, and produces a negligible increase in normal traffic.
Oral Health Policy in Latin America: Challenges for Better Implementation

Background: Oral health is considered an important public policy. This study aimed to understand which barriers and facilitator occurs during the implementation of oral health programs/policies. Methods: A qualitative study was conducted within personal interviews with decision-makers, at the political, technical, and academic levels. Data were transcribed and analyzed using Maxqda®. Results: The formation of dentists with an emphasis on the public service proved to be a critical knot, also the population´s lack of knowledge about their rights was mentioned. In Chile and Colombia, one of the main facilitators was the previous existence of oral health programs. As barrier, the lack of systematization of epidemiological data. In Brazil, the main facilitators were many dentists available and the political will of politicians to include oral health as public. Managers unprepared to work in public service was one of the main barriers. Conclusions: During the development and implementation of public policies several factors are encountered, it can be concluded that human resources are fundamental elements for the functioning of public service, besides the interest of the managers and politicians for the inclusion of this theme in the political agenda of the country.