Miracle-dz/UniFAR-FTUs huggingface dataset:
City, Street and Citizen: The Measure of the Ordinary

How can we learn from a multicultural society if we don’t know how to recognise it? The contemporary city is more than ever a space for the intense convergence of diverse individuals who shift in and out of its urban terrains. The city street is perhaps the most prosaic of the city’s public parts, allowing us a view of the very ordinary practices of life and livelihoods. By attending to the expressions of conviviality and contestation, ‘City, Street and Citizen’ offers an alternative notion of ‘multiculturalism’ away from the ideological frame of nation, and away from the moral imperative of community. This book offers to the reader an account of the lived realities of allegiance, participation and belonging from the base of a multi-ethnic street in south London. ‘City, Street and Citizen’ focuses on the question of whether local life is significant for how individuals develop skills to live with urban change and cultural and ethnic diversity. To animate this question, Hall has turned to a city street and its dimensions of regularity and propinquity to explore interactions in the small shop spaces along the Walworth Road. The city street constitutes exchange, and as such it provides us with a useful space to consider the broader social and political significance of contact in the day-to-day life of multicultural cities. Grounded in an ethnographic approach, this book will be of interest to academics and students in the fields of sociology, global urbanisation, migration and ethnicity as well as being relevant to politicians, policy makers, urban designers and architects involved in cultural diversity, public space and street based economies.
Task 1 : Coupling Low-Voltage Microgrids into Mid-Voltage Distribution Systems

This report presents results of the first two stages of the project, i.e. algorithm development and simulation model development. A hierarchical control architecture is proposed to maximize the real power export to mid-voltage (MV) distribution network by coupling low-voltage (LV) microgrids. At the same time, reactive power is dispatched coordinatively so that voltage regulatory constraints are satisfied. Two levels of optimization problems are solved to designate set points for each microsource controller: 1) the state at the point of common coupling (PCC) is determined by each microgrid controller in a decentralized fashion, 2) set points for microsources within a microgrid are calculated in the microgrid controller in a centralized way. Corresponding simulation model is developed in MATLAB R © Simulink R © with SimPowerSystems toolbox. Simulation results show that the algorithm developed can maintain system stability, while simultaneously achieving the goal of maximizing real power export under voltage regulation constraints. Response of the system under disturbances proves the robustness of the hierarchical control system. Index Terms Distributed optimization, capacity estimation, weak network.
Evolution of pore fluid pressures in a stimulated geothermal reservoir inferred from earthquake focal mechanisms

This paper proposes an inversion method to estimate the evolution of pore fluid pressure fields from earthquake focal mechanism solutions. Application of the method to induced seismicity in the Basel enhanced geothermal system in Switzerland shows the evolution of pore fluid pressure in response to fluid injection experiments. The pore fluid pressure in the reservoir was less than the minimum principal stress at each depth, indicating that hydraulic fracturing did not occur during the stimulation. This suggests that seismic events may play an important role in promoting the development of permeable channels, particularly southeast of the borehole where the largest seismic event (Mw 2.95) occurred. This is not directly related to a drastic decrease in fault strength at the hypocenter but rather to positive feedback between permeability enhancement and elastic/poroelastic stress loading from slipping interfaces.
Extremes of the ENSO phenomenon and Indian summer monsoon rainfall

Characterizing every year during the 120 year interval 1871-1990 as a year of El Nino (EN), or Southern Oscillation minimum (SO), or equatorial eastern Pacific sea-surface temperature (SST) warm (W) or cold (C) episode or none (non-events), the corresponding summer monsoon rainfall departures for all India and for the 29 meteorological subdivisions were examined. The best relationship for droughts was with unambiguous ENSOW (El Nino year with SO and W near the middle of the calendar year) and for floods with C (cold SST). The droughts were generally widespread, although Assam and Bengal might have had normal rainfall or even floods when other subdivisions had droughts. In some ENSOW years when all India rainfall was normal, the rainfall in subdivisions was either normal or mixed (droughts in some subdivisions, floods in others). However, droughts and floods occurred during other types of events also, and ENSOW or C were neither sufficient nor necessary. Some floods and droughts were associated with incorrect type (floods during El Nino, etc.), and some occurred during non-events, indicating that factors unrelated to EN, or SO, or W, or C may be more influential in some years.
(Topological) modular forms with level structures: decompositions and duality

The present article studies decompositions of vector bundles on the moduli stack of elliptic curves that are pushforwards of vector bundles on moduli of elliptic curves with level structure. These imply decomposition results for rings of modular forms and also for topological modular forms. We give explicit formulas for these decompositions and also apply them to equivariant topological modular forms. Moreover, we study the dualizing sheaf on $\overline{\mathcal{M}}_1(n)$ and characterize the numbers $n$ such that $Tmf_1(n)$ is Anderson self-dual.
Assessing wildlife value orientations in China: an exploration of the concepts and methodology.

The wildlife value orientation (WVO) construct has been used to describe deeply-held beliefs about how humans should relate to wildlife. As part of a larger effort to test the usefulness of the WVO construct across cultures, we conducted pilot testing of the construct in China. Sixteen mixed-method interviews were conducted in five cities/towns in China. Participants included individuals from both rural and urban areas with equal numbers of men and women. Interviews employed a 30-to-60-minute series of semi-structured, open-ended questions followed by 45 quantitative questionnaire items. The qualitative data were analyzed using open coding methods. The interrater reliability and inter-method-reliability of the initial conceptualization of WVO dimensions was analyzed, based on which a reconceptualization was developed and used to guide a secondary analysis. The results as well as the strengths and weaknesses of the qualitative and quantitative methods were discussed.
A Model-Based Deep Learning Approach for Self-Learning in Smart Production Systems

In this research, we discuss the impact of combining model-based deep learning and game theory in dynamic games to develop a sample-efficient self-learning methodology for smart production systems. We propose a novel approach, namely Model-Based Game Theory (MBGT), by incorporating model-based deep learning into a successful self-learning strategy of State-based Potential Games. Most of the advanced self-learning approaches are established based on machine learning and artificial intelligence, including reinforcement learning and game-theoretical method. However, because of the iterative behaviour during the learning processes, the learning processes are almost impossible to be conducted directly in a real-world manufacturing environment. One potential approach is to conduct the learning processes using the digital representation of the systems, e.g. the digital twin or simulation. Nonetheless, such representations in industrial settings are not always available and developing a digital representation of a complex system is immensely challenging. Hence, this problem can be solved through model-based learning, in which deep learning models are trained to predict the dynamics of the systems with a small margin of error. Then, the trained models are deployed as virtual environments for the learning processes of the GT-based control policies, instead of learning in the real world. In this study, we implement MBGT to a bulk good system and thoroughly analyse the performances between training in the real system and virtual environment, which eventually turn out to be positive effects.
Qualitative Analysis for Validating IEC 62443-4-2 Requirements in DevSecOps

Validation of conformance to cybersecurity standards for industrial automation and control systems is an expensive and time consuming process which can delay the time to market. It is therefore crucial to introduce conformance validation stages into the continuous integration/continuous delivery pipeline of products. However, designing such conformance validation in an automated fashion is a highly non-trivial task that requires expert knowledge and depends upon available security tools, ease of integration into the DevOps pipeline, as well as support for IT and OT interfaces and protocols.This paper addresses the aforementioned problem focusing on the automated validation of ISA/IEC 62443-4-2 standard component requirements. We present an extensive qualitative analysis of the standard requirements and the current tooling landscape to perform validation. Our analysis demonstrates the coverage established by the currently available tools and sheds light on current gaps to achieve full automation and coverage. Furthermore, we showcase for every component requirement where in the CI/CD pipeline stage it is recommended to test it and the tools to do so.
The geography of distance education - bibliographic characteristics of a journal network

The publication of the results of research in distance education in peer-reviewed journals is an important means of communication, dissemination, discourse and reporting of practice in the field. This study is an attempt at analyzing the relationships and influences among these journals. It is based upon a sample of 1416 scholarly articles published over six years in the 12 most widely cited international distance education journals. The bibliographic description and network analysis help us to investigate the structure and patterns of information exchange within the field of distance education research. The analysis of this citation network and the similarities in citation patterns reveals a clear core/periphery structure among distance education journals. The results of this analysis help us to understand the regional, international, impact and influence factors related to publication in these journals and across the field.
Integrated Production Quality and Security Analysis

Production monitoring aims at detecting critical changes regarding production quality and information security of complex Cyber-Physical-Production-Systems. However, identifying the scope of asset properties to monitor is often challenging due to the multi-disciplinary relationships between production quality and security aspects. Therefore, focused production security monitoring requires modeling and analyzing the assets and properties that have an impact on production quality. This paper introduces the Production Quality+Security (PQS) approach to represent and integrate the quality and security expert knowledge required for analyzing production effects and their influencing asset properties as a foundation for monitoring changes to these properties. In a feasibility study, we evaluated PQS with a CPPS for automotive production. The study results indicate PQS to provide an effective and efficient knowledge representation for the integrated analysis of production quality risks and security monitoring parameters.
Digital Twin for Machine-Learning-based Vehicle CO2 Emissions Concentration Prediction in Embedded System

In this paper, we describe the design, implementation, and installation of a digital twin version of a physical CO2 monitoring system with the aim of democratizing access to affordable CO2 emission measuring and enabling the creation of effective pollutant reduction strategies. The presented digital twin acts as a replacement that enables the measuring of CO2 emissions without the use of a physical sensor. The exhibited work is specifically designed to be installed on a low-powered Micro Controller Unit (MCU), enabling its accessibility to a broader base of users. To this end, an optimized Artificial Neural Network (ANN) model was trained to be capable of predicting CO2 emission concentrations with 87.15% accuracy when performing on the MCU. The ANN model is the result of a compound optimization technique that enhances the speed and accuracy of the model while reducing its computational complexity. The results outline that the implementation of the digital twin is 86.4% less expensive than its physical CO2 counterpart, whilst still providing highly accurate and reliable data.
On the Core and Harsanyi Extensions of the Almost Positive Games

In the paper, we study interconnections between the cores and other solutions of the Harsanyi extensions of almost positive cooperative games. A short and elementary proof is given establishing that the cores of Aubin extensions of the games mentioned above consist of their Shapley vectors. The proposed approach is based on a generalization of the classical notion of a balanced cover of the grand coalition to the case of fuzzy coalitions. This generalization allows us to expand the concept of a balanced ordinary cooperative game in situations where fuzzy blocking makes sense. In the preceding papers of the author it was shown that enlarging blocking capabilities by means of fuzzy coalitions doesn't prevent reasonable utilization of the linear programming methods (proved by O.N.Bondareva and L.S.Shapley to be very efficient in case of ordinary cooperative games). In particular, a criterion for the fuzzy game to have unblockable imputation turned out to be rather useful in clarifying some properties of Harsanyi extensions considered in the paper. One more example of the relevant application of the criterion mentioned is the main result of this work relating to the accessibility of core-imputations of the almost positive game via an appropriate fuzzy domination. Here we take into account, as well, a close correlation between the cores and superdifferentials of fuzzy cooperative games, mentioned by J.-P.Aubin.
Novel Non-Isolated High Step-Up DC-DC Converter Topologies for Electric Vehicles

This paper presents three new non-isolated high step-up converters (NI-HSC) for electric vehicle charging applications. Higher duty ratios increase the overall gain of the step-up converter. However, this increases voltage and current stresses in the switching devices. This paper proposes three soft-switched high step-up converters (SS-HSC) improved with auxiliary cells, to reduce the switching losses and to improve the overall efficiency. The auxiliary cell provides soft-switching of the main MOSFETs. The zero voltage switching (ZVS) is achieved for all the MOSFETs during turn-on. Zero current switching (ZCS) turn-off is obtained for one main switch and the auxiliary switch. Principles of operation and simulation results are presented to evaluate the theoretical analysis. The designed converter systems are simulated with 100 V input voltage at 6 kW to obtain 600 V output voltage.
A role-based Metric to determine the Quality of Simulation Models

With the progressive development of digital twins, simulation models are becoming increasingly important. They are already a central artefact in the entire systems engineering and are becoming an substantial part of the delivery, either a virtual or a real product, itself. In contrast to physical components, whose quality requirements are defined very precisely in terms of detailed specifications, this is rarely the case with simulation models. On the one hand, this is due to the novelty of simulation models as an independent good and, on the other hand, to the fact that there are no comprehensively defined quality criteria for simulation models. The authors address this problem and present a role-based metric for objectively determining the quality of simulation models. In addition to the quality-relevant attributes, a role concept is presented that enables the seamless application of the metric. The objective is for the quality level to be specified on a transparent and measurable basis and can thus become part of the business in automation technology.
of clinical breast examination in a breast cancer surveillance program for women with

Objective : To assess the sensitivity and specificity of clinical breast examination for detecting breast cancer in asymptomatic women with predisposing germline mutations enrolled in a cancer risk management program that includes radiologic screening. Design, setting : Retrospective, longitudinal cohort study of women with BRCA1/2 mutations who attended the Breast and Ovarian Cancer Risk Management Clinic at the
LiDAR data augmentation by interpolation on spherical range image

LiDAR sensors are used for mapping tasks, LiDAR odometry or 3D environment reconstruction. Several of them count with a high number of vertical layers, which increase their price and prevents research groups from carrying out experiments and scientific advances. In this paper, we propose a method for augmenting point cloud data by bilinear interpolation in a Spherical Range Image. Our method improves others on the state-of-the-art by means of standard deviation filtering of the newly generated layers. The system operates at a frequency greater than 10 Hz for data interpolation up to 20 times. In addition, we present two applications for our approach such as LiDAR odometry and LiDAR-Camera fusion, obtaining better results than others that do not apply data augmentation. Finally we make available to the scientific community a package development on ROS (Robot Operating System). The code is available at https://github.com/EPVelasco/lidar-camera-fusion
Voltage Offset Compensation in CMOS OTAs: Novel Approaches for Temperature Drift Improvement

This invited paper introduces novel approaches for trimming the voltage offset of CMOS operational amplifiers and comparators. The presented methods can be applied either to a one-time trimming during production testing, or via periodic calibration during circuit operation. The primary focus of this paper is to optimize the temperature drift of the trimmed and untrimmed offset voltage, VOS. The paper discusses various approaches to achieve this goal, including a) constant current injection, b) MOS physical size programming, and c) tail offset voltage trimming. Furthermore, the paper introduces new techniques that enhance temperature drift performance: d) temperature compensated current offset injection, e) temperature compensated active load trimming, f) constant-resistance tail offset voltage trimming, and g) series input-referred voltage generator. Additionally, the paper introduces the concept of transconductance temperature characteristic dumping, which has the potential to improve the residual temperature drift of the OTA. Simulation in 130nm CMOS demonstrating the effectiveness of the presented methods are provided.
Computational development of aryl sulfone compounds as potential NNRTIs

Human immunodeficiency virus (HIV) attacks the host’s immune system and affects millions of people globally. Due to the high mutation rate of HIV, it is of great importance that novel drugs are found to combat new strains. Non-nucleoside reverse transcriptase inhibitors (NNRTIs) are allosteric inhibitors that bind to the HIV reverse transcriptase and prevent replication. Indolyl aryl sulfones (IAS) and IAS derivatives have been found to be highly effective against mutant strains of HIV-1 reverse transcriptase. Here, we analyzed molecules designed using aryl sulfone scaffolds paired to cyclic compounds (that have previously been found to be beneficial groups for NNRTIs) as potential NNRTIs through the computational design and docking of 100 novel NNRTI candidates. Moreover, we explored the specific combinations of functional groups and aryl sulfones that resulted in the NNRTI candidates with the strongest binding affinity while testing all compounds for carcinogenicity. We hypothesized that the combination of an IAS scaffold and pyrimidine would produce the compounds with the best binding affinity. Our hypothesis was correct as the series of molecules with an IAS scaffold and pyrimidine exhibited the best average binding affinity. Additionally, this study found 32 molecules designed in this procedure with higher or equal binding affinities to the previously successful IAS derivative 5-bromo-3-[(3,5-dimethylphenyl)sulfonyl]indole-2-carboxyamide when docked to HIV-1 reverse transcriptase. These findings contribute to the search for novel NNRTIs as well as expanding knowledge regarding the characteristics of the NNRTI pharmacophore.
N′-[(E)-1-(3-Fluorophenyl)ethylidene]formohydrazide

In the title compound, C9H9FN2O, the dihedral angle between the fluorobenzene ring and the mean plane of the side chain is 15.59 (14)°. In the crystal, the molecules form inversion dimers linked by pairs of N—H⋯O hydrogen bonds, resulting in R 2 2(8) loops. These dimers are reinforced by C—H⋯O interactions.
The Journal of Values-Based Leadership The Journal of Values-Based Leadership

This paper reviews the current literature of management to indicate how transformational leaders contribute to organisational knowledge by building an effective culture. The paper is based on a review of leadership theories, organisational knowledge, organisational culture and the integration of concepts from the knowledge-based view of the firm. This review also indicates that to develop organisational knowledge transformational leaders act as change agents who influence organisational culture which can in turn mediate the relationship between transformational leadership and organisational knowledge.
Special Section on ADME Databases-Minireview Overview of Current Herb – Drug Interaction Databases

An HERB – Drug Interaction (HDI) database is a structured data collection method for HDI information extracted from scattered literatures for quick retrieval. Our review summarized the ten currently available HDI databases, including those databases comprising HDI on the market. A detailed comparison on the scope of mono-graphs, including the nature of content extracted from the original literature and user interfaces of these databases, was performed, and the number of references of fifty popular herbs in each HDI database was counted and presented in a heatmap to give users an intuitive understanding of the focuses of different HDI databases. Since it is well known that the development and maintenance of databases need continuous investment of capital and manpower, the sustainability of these databases was also reviewed and compared. Recently, artificial intelligence (AI) technologies, especially Natural Language Processing (NLP), have been applied to screen specific topics from massive articles and automatically identify the names of drugs and herbs in the literature. However, its application on the labor-intensive extraction and evaluation of HDI-related experimental conditions and results from literature remains limited due to the scarcity of these HDI data and the lack of well-established annotated datasets for these specific NLP recognition tasks. In view of the difficulties faced by current HDI databases and potential expansion of AI applicationin HDI database development, we propose a standardized format for data reporting and use of Concept Unique Identifier (CUI) for medical terms in the literature to accelerate the structured data collection.