Miracle-dz/UniFAR-FTUs huggingface dataset:
The Object-Oriented Politics of Stadium Sustainability: A Case Study of SC Freiburg

Sport stadia are political objects that carry an environmental cost. The purpose of this research is to add to previous literature by theorizing the political process of stadium construction in a way that accounts for how environmental issues are introduced into the political process and, therefore, offers a more accurate lens through which to interpret how sustainable stadia are constructed. We conducted a case study of SC Freiburg’s carbon-neutral stadium construction process to theorize the object-oriented politics of sport facility construction. SC Freiburg is a German football club, playing in the Bundesliga. To examine the case, we employed a key informant interview and document analysis using Nexis Uni searches, local newspaper articles, official city documents, and social media websites. The case study of SC Freiburg’s carbon neutral stadium construction process showed that environmental concerns were included through a political process that incorporated the interests of a diverse public of human and nonhuman actors (while excluding some actors whose interests could not be reconciled) to produce a sustainable matter of fact. Additionally, we propose a pragmatic definition of stadium sustainability and suggest that environmental activists should make sure that both human and nonhuman actors with sustainability concerns are included in the stadium’s material public.
The Nature and Articulation of Ethical Codes on Tailings Management in South Africa

It is well recognized that the mining industry in South Africa is highly rated for its substantial contribution to the country’s economic growth, including employment and infrastructural development. It is also known that mining and ore processing activities potentially pose a severe threat to public health and environmental well-being, in the way operations are carried out, mine wastes are disposed of (in dumps), local communities are relocated, mine management and the mining community, in general, perceive established environmental standards and etiquette. This paper examines ethical practices and norms in the South African mining industry, with particular reference to the management of tailings dams. We analyse the modes of articulation of the country’s regulatory instruments for tailings management, and review the corporate social responsibility (CSR) approach of leading mining companies. Despite decades of research and resulting recommendations on tailings management, it is concluded that the current legislations are largely ineffective, that the level of adherence by mine management and the mining community is low, and that the mechanisms for compliance monitoring is weak. New perspectives on legislative issues for unsolved problems in tailings handling are put forward, and directions for future research, indicated.
Polar Coding For Forward Error Correction In Space Communications With LDPC Comparisons

With the surging development of optical telecommunicationsfor space applications, the importance of errorcorrection has become more apparent than ever. Specifically,the exploration of forward error correction code (FEC) methodologieswill be instrumental in developing the standards foroptical communications in space. Despite the widespread useof low-density parity-check (LDPC) codes, alternate FEC codessuch as polar codes have shown immense promise in assistingspace communications error correction with their ability tobypass the error floors that plague LDPC codes. Extremelypromising techniques including cyclic redundancy checks (CRC),successive cancellation (SC), and successive cancellation lists(SCL) that assist polar coding in achieving the Shannon limitin a timely manner are evaluated. MATLAB simulations areconducted with AWGN and burst noise to test each technique'sability to handle noise typically encountered in space and eachtechnique's ability to correct unexpected errors. Results ofsimulations for different rates and message lengths are alsoreported to determine each technique's ability to handle largedata volumes and fix errors. Similar simulations are conductedfor LDPC codes with additional tests for convolutional and nointerleavers. Finally, a discussion regarding the future ability ofpolar codes to satisfy current missions in the place of, or inconjunction with, LDPC codes along with the merits of eachFEC technique's ability to process data efficiently and handledata while maintaining adequate performance will be provided.Preliminary recommendations will be made for each technique'seffectiveness for GEO related missions along with discussionsregarding each technique's ability to fit within the CCSDS standards for optical communications.
Redundancy Removed Dual-Tree Discrete Wavelet Transform to Construct Compact Representations for Automated Seizure Detection

With the development of pervasive sensing and machine learning technologies, automated epileptic seizure detection based on electroencephalogram (EEG) signals has provided tremendous support for the lives of epileptic patients. Discrete wavelet transform (DWT) is an effective method for time-frequency analysis of EEG and has been used for seizure detection in daily healthcare monitoring systems. However, the shift variance, the lack of directionality and the substantial aliasing, limit the effects of DWT in some applications. Dual-tree discrete wavelet transform (DTDWT) can overcome those drawbacks but may increase information redundancy. For classification tasks with small dataset sizes, such redundancy can greatly reduce learning efficiency and model performance. In this work, we proposed a novel redundancy removed DTDWT (RR-DTDWT) framework for automated seizure detection. Energy and modified multi-scale entropy (MMSE) features in a dual tree wavelet domain were extracted to construct a complete picture of mental states. To the best of our knowledge, this is the first study to employ MMSE as an indicator of epileptic seizures. Moreover, a compact EEG representation can be obtained after removing useless information redundancy (redundancy between wavelet trees, adjacent channels and entropy scales) by a general auto-weighted feature selection framework via global redundancy minimization (AGRM). Through validation on Bonn and CHB-MIT databases, the proposed RR-DTDWT method can achieve better performance than previous studies.
MEASURING THE IMPACT OF DATA QUALITY IN A CORPORATE DECISION-SUPPORT SYSTEM

The benefit of decision support systems (DSS) is in practice frequently impaired by the processing of unsure and erratic data [1]. We present an experience of u sing Cadral, a business DSS developed at our depart ment, for processing applications received by the adminis tration of Family Benefits in Luxembourg. To better adapt to the operational context [2], Cadral includ es informative tools that help the user take into a ccount the quality of the data when modeling the knowledge of the system.
Assessing OpenStreetMap Completeness for Management of Natural Disaster by Means of Remote Sensing: A Case Study of Three Small Island States (Haiti, Dominica and St. Lucia)

Over the last few decades, many countries, especially islands in the Caribbean, have been challenged by the devastating consequences of natural disasters, which pose a significant threat to human health and safety. Timely information related to the distribution of vulnerable population and critical infrastructure is key for effective disaster relief. OpenStreetMap (OSM) has repeatedly been shown to be highly suitable for disaster mapping and management. However, large portions of the world, including countries exposed to natural disasters, remain incompletely mapped. In this study, we propose a methodology that relies on remotely sensed measurements (e.g., Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-2 and Sentinel-1) and derived classification schemes (e.g., forest and built-up land cover) to predict the completeness of OSM building footprints in three small island states (Haiti, Dominica and St. Lucia). We find that the combinatorial effects of these predictors explain up to 94% of the variation of the completeness of OSM building footprints. Our study extends the existing literature by demonstrating how remotely sensed measurements could be leveraged to evaluate the completeness of the OSM database, especially in countries with high risk of natural disasters. Identifying areas that lack coverage of OSM features could help prioritize mapping efforts, especially in areas vulnerable to natural hazards and where current data gaps pose an obstacle to timely and evidence-based disaster risk management.
Effects of soft robotic gloves on rehabilitation outcomes in individuals with sensorimotor hand impairments: a systematic review

For individuals with hand hemiparesis following a stroke, rehabilitation strategies are predominantly founded on the principles of neuroplasticity and automaticity [1] to regain optimal hand-related functional abilities and facilitate participation in everyday activities. Such an approach requires to engage these individuals into meaningful activity-specific exercises and to repeat those intensively on a daily basis. Adhering to these principles [2] remains challenging in clinical practice for rehabilitation professionals, especially given various time and productivity constraints. To overcome this challenge, the development of soft robotic gloves to facilitate hand rehabilitation have progressed substantially in the last decade. Moreover, these soft robotic gloves are foreseen as promising rehabilitation intervention to potentiate the effects of conventional rehabilitation interventions and are now about to transition into clinical practice, although their effects remain uncertain given the paucity of evidence. In this context, this review aims to map evidence on the effects of the different rehabilitation interventions using a soft robotic device for sensorimotor hand impairments and, whenever possible, the satisfaction related to their use.
Neutralisation and contrast preservation

This paper studies the contextual variation in the voicing properties of three-consonant clusters (CC#C) in Hungarian. We investigate the velar–alveolar stop clusters /kt/ and /ɡd/, and the alveolar fricative–stop clusters /st/ and /zd/ in potentially voicing-neutralising and assimilating contexts. We show that in these contexts, regressive voicing assimilation in Hungarian is categorical, but partially contrast preserving, and that stops and fricatives are not affected in the same way. Fricatives resist voicing before a voiced obstruent and are devoiced utterance-finally. This is a phonetically unfavourable position, therefore other duration-related cues step up to prevent complete laryngeal neutralisation.
Physics-Based Signal Processing Approaches for Underwater Acoustic Sensing

Email: zurkl@uw.edu Introduction The undersea world is an important and fascinating domain, but it is also a very challenging environment for sensing. The dominant modality for underwater sensing is acoustics because electromagnetic and optical waves attenuate quickly in seawater. Fortunately, many sources of interest to humans, such as biologics (whales, dolphins, fishes) and man-made vehicles (submarines, ships), have distinct acoustic signatures that can be detected passively or actively. Sound radiated in the lower part of the acoustic band (i.e., 100s of hertz or below) can travel over fairly long distances, and these signals can be detected at significant ranges. However, the propagation over these distances can change the acoustic signature appreciably due to the physics of the underwater propagation, which introduces phenomena such as refraction and reflected multipaths.
Categorization of the Condition of Railway Embankments Using a Multi-Attribute Utility Theory

In the current economic climate, it is crucial to optimize the use of all resources regarding railway infrastructure maintenance. In this paper, a multi-attribute decision support framework is applied to categorize railway embankments in order to prioritize maintenance activities. The paper describes a methodology to first determine the current condition of embankments using a combination of ground penetrating radar (GPR) surveys, visual inspection, and historical data about maintenance activities. These attributes are then used for the development of a multi-attribute utility theory model, which can be used as a support for decision making process for maintenance planning. The methodology is demonstrated for the categorization of 181 km of railway embankments in Croatia.
Light automation for aircraft fuselage assembly

ABSTRACT The ever-growing need to improve manufacturing processes has led recently to an increase in the number of automation solutions used to assemble aircraft structural elements. A process of interest to this industry is the alignment of fuselage sections, which is currently done either manually or by complex, expensive automated systems. The manual method introduces a significant production delay and most automated systems have limited flexibility. This article presents an integration solution implemented in an alternative low-cost, high-flexibility alignment robotic cell. The performance of an optical coordinate measuring machine (CMM) as feedback source for the adaptive control of a conventional industrial manipulator is assessed. Laser interferometry readings are used as reference. The contribution of the work lies in the execution of experiments based on the EN ISO 9283 standard (Manipulating industrial robots - performance criteria and related test methods) to determine the adequacy of the commercial off-the-shelf system to the tolerances and requirements of the fuselage alignment process at hand. The optimal configuration of the integrated system attained the nominal alignment position with an average accuracy of 0.16mm and $0.004^\circ$ , partially meeting the required tolerances, and the obtained values are nearly 16x better compared to a baseline, open-loop manipulator. These results serve as reference for the aerospace industry in the development of the next generation of tools and automated assembly processes.
Rural care Registered Nurses' interpretation of health literacy and its effect on patient care

The purpose of this phenomenological qualitative study was to describe rural care Registered Nurses’ interpretation of health literacy and its effect on patient care. Individuals who do not understand their disease and have poor management skills are at risk for low health literacy. The consequences of limited health literacy are poor healthcare outcomes and higher healthcare costs. Implications from this study are useful in educating practicing Registered Nurses in the development of the necessary skills to empower patients to actively participate in their healthcare. Education about health literacy should begin in grades Kindergarten through 12, with the primary focus being on the development a personal definition of health and wellness. A phenomenological lens was used to examine the data collected in this study. Interviews were conducted with Registered Nurses working in a rural acute care setting. Data analysis was conducted according to Moustakas’s (1994), Van Kaam Method. The following themes emerged: health literacy, relationships, participatory decision-making, and empowerment. Findings from this study revealed that rural care Registered Nurses had limited knowledge of health literacy and were not aware of available health literacy assessment tools. Most of the participants in this study utilized nurse developed tools which assessed the literacy level of patients instead of health literacy and thus influenced their relationships with their patients. The majority of participants did not have an understanding of the essential relationship that exists between a patient’s health literacy and the patient’s participation in their own healthcare. There were limited examples that nurses were encouraging their patients to engage in
From Research to Industry: A Quantitative and Qualitative Analysis of Science-Technology Transferences and Emergence Patterns in Bioremediation

This article uses text mining techniques to determine the time lag of knowledge transfer between research activity and technology development in bioremediation, complementing these with advanced visualization techniques in order to extract patterns that could be of interest for decision making in this field. The emergence patterns in this field have been identified and a method based on subject-action-object (SAO) semantic structure is proposed for characterizing such patterns, using 2-word tuples. Our results show that technology developments in heavy metal bioremediation swiftly follow scientific advances, as opposed to developments in bioremediation of organic chemical components. The science mapping reveals three distinct areas: 1) heavy metal remediation and phytoremediation; 2) aerobic and anaerobic remediation of chemical elements; and 3) bioremediation techniques for treating specific contamination sources such as oil. The emergence analysis points at activities involving energy recovery by bioremediation, and shows an increasing amount of technologies involving specific strains of microorganisms, which could gain significant traction in this field in an estimated time horizon of ten years. Our SAO approach, tested on the data sample corresponding to these strains, proves to be useful for characterizing the emerging technologies when applied to instrumental concepts.
Wideband 28-nm CMOS Variable-Gain Amplifier

This paper discusses a wideband variable-gain amplifier (VGA) implemented in a 28-nm FDSOI CMOS technology. This VGA employs optimal-biasing and differential large-signal pre-distortion linearizations that operate over all gain settings and over its frequency range. The 0.4-to-4-GHz VGA, which consists of its core circuit and an output buffer, exhibits a wideband gain ranging from 4.6 to 12 dB in 1-dB steps and an input return loss higher than 10 dB while demonstrating a worst-case IM3 of −54 dBm across the gain range at ~0-dBm output power and noise figures from 3 to 5.9 dB at 12 dB gain. The VGA and buffer consume 15 mA and 60 mA from a 1.5 V supply, respectively. The total chip area, including the bond pads, is ${1\times 1\,\text {mm}^{2}}$ .
A Typical Distributed Generation Scenario Reduction Method Based on an Improved Clustering Algorithm

In recent years, distributed generation (DG) technology has developed rapidly. Renewable energy, represented by wind energy and solar energy, has been widely studied and utilized. In order to give full play to the advantages of distributed generation and to meet the challenges of DG access to the power grid, the multi-scenario analysis method commonly used in DG optimal allocation method is studied in this paper. In order to solve the problems that may arise from using large-scale scenes in the planning of DG considering uncertainties by using multi-scene analysis method, the cluster analysis method suitable for large-scale scene reduction in scene reduction method is introduced firstly, and then an improved clustering algorithm is proposed. The validity of the scene reduction method is tested, and the feasibility of the reduction method is verified. Finally, the method mentioned in this paper is compared with other commonly used methods through IEEE-33 node system.
Pattern Reconfigurable Rectenna With Omni-Directional/Directional Radiation Modes for MPT With Multiple Transmitting Antennas

A pattern reconfigurable rectenna, consisting of a pattern reconfigurable receiving antenna and a low-/medium-power rectifying circuit, is proposed for microwave power transmission with multiple transmitting antennas. By controlling the states of p-i-n switch groups, the receiving antenna can work at one omni-directional mode and eight directional modes with flattened wide main beams for the arbitrary direction of incoming waves. In order to achieve good impedance matching at different modes, where the received power fluctuates severely, a complex impedance compression network (CICN) is introduced to the rectifying circuit. Since the proposed rectenna has a versatile structure, it can be used for multiple transmitting antennas in conformity with the incoming waves’ direction.
Range-Adaptive Wireless Power Transfer Based on Differential Coupling Using Multiple Bidirectional Coils

Wireless power transfer systems using coupled magnetic resonances are susceptible to the transfer distance variation between the transmitter (Tx) and receiver (Rx) since the coupling between Tx and Rx is highly position dependent. Once the transfer distance deviates from the optimum one, the coupling will be either excessive or weak, which results in power transfer efficiency (PTE) degradation. This article presents a Tx structure consisting of multiple subcoils oriented in opposite directions to keep the coupling relatively constant over an extensive range of transfer distances. The proposed design can achieve a PTE of 88–70% with a transfer distance varying from 0 to 70 mm and a PTE of 85–60% with a misalignment of 0–80 mm at a 40 mm transfer distance. The radius of the Tx and Rx is 84.6 and 45.1 mm, respectively. The measured PTE of the proposed design is better than 70% with a 0–50 mm transfer distance while the misalignment changing from 0 to 50 mm. The proposed system is much less sensitive to the transfer distance variation than the convention system and has a great potential for wireless charging applications.
Cellulases Production by a Trichoderma sp. Using Food Manufacturing Wastes

The cost of cellulase enzymes is a main contributor to the operational cost of a biorefinery producing ethanol from lignocellulosic material. Therefore, onsite production of enzymes using low-value substrates might be an option to make a bio-based facility more economical, while improving environmental sustainability. Food manufacturing wastes (FMWs), such as olive mill solids, tomato pomace, and grape pomace, are some of the main wastes produced by the food industry in Chile. FMWs are mostly composed of lignocellulosic material, which is primarily made of cellulose. A fungal strain obtained from olive stones was identified as a Trichoderma sp. and characterized by molecular and morphological techniques. This strain was able to grow on three FMWs in both liquid and solid cultures. In liquid cultures, cellulase and β-glucosidase activities from the culture supernatants were quantified. Identification of extracellular proteins using mass spectrometry revealed the presence of endoglucanases, exoglucanases, and β-glucosidases. Cellulase production from agroindustrial residues could be an excellent opportunity to utilize FMWs as well as decrease enzyme production costs in biorefinery processes.
Energy Optimization by Software Prefetching for Task Granularity in GPU-Based Embedded Systems

Energy saving and optimization play an increasingly important role in industrial electronic systems. A heterogeneous embedded system is composed of a general-purpose central processing unit with an enhanced module of graphics processing units (GPU). This article explores the effective strategies of task granularity and software prefetching for energy optimization. In this article, we propose a novel energy optimization model for GPU-based embedded systems by harnessing a communication-based pipeline spatial and temporal relation. We analyze the characteristics of a multiple thread execution of parallel GPUs. We present an effective algorithm for the dynamic power optimization with the adaptively adjusted distance of software prefetching. The experimental results show that the dynamic energy consumption can be saved by 22.1% and 21.8%, respectively, under two prefetching strategies (register and shared memory) without loss of performance. We demonstrate the effectiveness of the proposed methods for energy saving and consumption reduction of performance driven computing in industrial scenarios.