Search Results (23)

The global transition towards clean energy sources is becoming essential to reduce reliance on conventional fuels and mitigate carbon emissions. In the future, the clean energy storage landscape, green hydrogen, and green ammonia (powered by renewable energy sources) are emerging as key players. This study explores the prospectives and feasibility of producing and storing offshore green hydrogen and green ammonia. The potential power output of Hornsea one and Hornsea two winds farms in the United Kingdom was calculated using real wind data. The usable electricity from the Hornsea one wind farm was 5.83 TWh/year, and from the Hornsea two wind farm, it was 6.44 TWh/year, harnessed to three different scenarios for the production and storage of green ammonia and green hydrogen. Scenario 1 fulfil the requirement of green hydrogen storage for flexible ammonia production but consumes more energy for green hydrogen compression. Scenario 2 does not offer any hydrogen storage which is not favourable in terms of flexibility and market demand. Scenario 3 offers both, a direct routed supply of produced hydrogen for green ammonia synthesis and a storage facility for green hydrogen storage. Detailed mathematical calculations and sensitivity analysis was performed based on the total energy available to find out the energy storage capacity in terms of the mass of green hydrogen and green ammonia produced. Sensitivity analysis in the case of scenario 3 was conducted to determine the optimal percentage of green hydrogen going to the storage facility. Based on the cost evaluation of three different presented scenarios, the levelized cost of hydrogen (LCOH) is between USD 5.30 and 5.97/kg, and the levelized cost of ammonia (LCOA) is between USD 984.16 and USD 1197.11/tonne. These prices are lower compared to the current UK market. The study finds scenario 3 as the most appropriate way in terms of compression energy savings, flexibility for the production and storage capacity that depends upon the supply and demand of these green fuels in the market, and a feasible amount of green hydrogen storage. Full article

The Simultaneous Localization and Mapping (SLAM) scanner is an easy and portable Light Detection and Ranging (LiDAR) data acquisition device. Its main output is a 3D point cloud covering the scanned scene. Regarding the importance of accuracy in the survey domain, this paper aims to assess the accuracy of two SLAM scanners: the NavVis VLX and the BLK2GO scanner. This assessment is conducted for both outdoor and indoor environments. In this context, two types of reference data were used: the total station (TS) and the static scanner Z+F Imager 5016. To carry out the assessment, four comparisons were tested: cloud-to-cloud, cloud-to-mesh, mesh-to-mesh, and edge detection board assessment. However, the results of the assessments confirmed that the accuracy of indoor SLAM scanner measurements (5 mm) was greater than that of outdoor ones (between 10 mm and 60 mm). Moreover, the comparison of cloud-to-cloud provided the best accuracy regarding direct accuracy measurement without manipulations. Finally, based on the high accuracy, scanning speed, flexibility, and the accuracy differences between tested cases, it was confirmed that SLAM scanners are effective tools for data acquisition. Full article

Chemically stable two-dimensional nanostructured graphene with huge surface area, high electrical conductivity and mechanical excellence has gained significant research attention in the past two decades. Its excellent characteristics make graphene one of the important materials in various applications such as environmental and energy storage devices. Graphene no doubt has been a top priority among the carbon nanomaterials owing to its structure and properties. However, the functionalization of graphene leads to various nanocomposites where its properties are tailored to be suited for various applications with more performance, environmental friendliness, efficiency, durability and cost effectiveness. Graphene nanocomposites are said to exhibit more surface area, conductivity, power conversion efficiency and other characteristics in energy devices like supercapacitors. This review was aimed to present some of the applications of graphene-based nanocomposites in energy conversion devices like supercapacitors and Li-ion batteries and some of the environmental applications. It was observed that the performance of supercapacitors was obstructed due to restacking and agglomeration of graphene layers. This was addressed by combining MO (metal oxide) or CP (conducting polymer) with graphene as material for electrodes. Electrodes with CP or MO/graphene composites are summarized. Heterogeneous catalysts were of environmental concern in recent years. In this context, graphene-based nanocomposites gained significance due to expansion in structural diversity. A minimum overview is presented in this paper in terms of structural aspects and properties of GO/rGO-based materials used in supercapacitors and environmental applications like dye removal. Continuous efforts towards synthesis of productive graphene-based nanocomposites might lead to significant output in applications related to environment and energy sectors. Full article

The contributions of this paper are the result of a thematic review conducted on some of the most relevant scientific contributions and policy guidelines about women’s perception of safety while walking in public spaces. The first part of the review focused on 23 scientific references revolving around the keywords “gender”, “safety” and “walkability”. This led to the establishment of three main Safety Factors: (i) Spatial Features (space characteristics/morphological features); (ii) City Use (traces of behavior and presence of city users); and (iii) Hotspots (safe havens and no-go areas); further resulting in 19 sub-factors. The second part of the review covered a collection of 20 reports and 10 guidelines focused on diverse geographical scales, areas of interest and target audiences, as well as data collection methods. This involved the selection of multiple case studies, which are also presented, thus maintaining a geographically diverse sample. As part of the scientific research project “STEP UP—Walkability for Women in Milan”, the outputs of the proposed thematic review will be exploited to help identify challenging areas of Milan (Italy), as samples of analysis to develop a set of policy recommendations to enhance the level of walkability for women. Full article

The Clonogenic Survival Assay (CSA) is a fundamental tool employed to assess cell survival and proliferative potential in cancer research. Despite its importance, CSA faces limitations, primarily its time- and labor-intensive nature and its binary output. To overcome these limitations and enhance CSA’s utility, several approaches have been developed, focusing on increasing the throughput. However, achieving both high-content and high-throughput analyses simultaneously has remained a challenge. In this paper, we introduce LeGO-CSA, an extension of the classical CSA that employs the imaging of cell nuclei barcoded with fluorescent lentiviral gene ontology markers, enabling both high-content and high-throughput analysis. To validate our approach, we contrasted it with results from a classical assay and conducted a proof-of-concept screen of small-molecule inhibitors targeting various pathways relevant to cancer treatment. Notably, our results indicate that the classical CSA may underestimate clonogenicity and unveil intriguing aspects of clonal cell growth. We demonstrate the potential of LeGO-CSA to offer a robust approach for assessing cell survival and proliferation with enhanced precision and throughput, with promising implications for accelerating drug discovery and contributing to a more comprehensive understanding of cellular behavior in cancer. Full article

Teaching translation in higher education has undeniably been impacted by the innovations brought about by machine translation (MT), more particularly neural machine translation (NMT). This influence has become significantly more noticeable in recent years, as NMT technology progresses hand in hand with artificial intelligence. A case study supported by a questionnaire conducted among translation students (bachelor’s and master’s programmes at ISCAP) probed the degree of student satisfaction with CAT tools and revealed that they favour the use of MT in their translation practices, focusing their work on post-editing tasks rather than exploring other translation strategies and complementary resources. Although MT cannot be disregarded in translation programmes, as machine-generated translations make up an increasingly larger amount of a professional translator’s output, the widespread use of MT by students poses new challenges to translators’ training, since it becomes more difficult to assess students’ level of proficiency. Translation teachers must not only adapt their classroom strategies to accommodate these current translation strategies (NMT) but also, as intended by this study, find new, adequate methods of training and assessing students that go beyond regular translation assignments while still ensuring that students acquire the proper translation competence. Thus, as the use of NMT makes it considerably more challenging to assess a student’s level of translation competence, it is necessary to introduce other activities that not only allow students to acquire and develop their translation competence as defined in the EMT (European Masters in Translation) framework but also enable teachers to assess students more objectively. Hence, this article foregrounds a set of activities usually regarded as “indirect tasks” for technical translation courses that hopefully results in the development of student translation skills and competence, as well as provides more insights for teachers on how to more objectively assess students. It is possible, then, to conclude that these activities, such as different types of paraphrasing and error-detection tasks, may have the potential to encourage creative thinking and problem-solving strategies, giving teachers more resources to assess students’ level of translation competence. Full article

This study focuses on a novel humidity sensor composed of graphene-oxide (GO)-supported MoTe₂ nanosheets. Conductive Ag electrodes were formed on PET substrates by inkjet printing. A thin film of GO-MoTe₂ was deposited on the Ag electrode used for adsorbing humidity. The experiment’s results demonstrate that MoTe₂ are attached to GO nanosheets uniformly and tightly. The capacitive output of the sensors with various ratios of GO/MoTe₂ has been tested for different levels of humidity (11.3–97.3%RH) at room temperature (25 °C). As a consequence, the obtained hybrid film exhibits superior sensitivity (94.12 pF/%RH). The structural integrity and interaction of different components were discussed to afford the prominent humidity sensitivity performance. Under the bending condition, the output curve of the sensor has no obvious fluctuation. This work provides a low-cost way to build flexible humidity sensors with high-performance in environmental monitoring and healthcare. Full article

Fabrizio Romano’s sizeable social media followings and role as influencer–sports journalist warrant attention. Romano, known for his catchphrase ‘Here We Go’, specialises in football transfers and produces multi-platform content. This study investigates how Romano’s Twitter practice informs professional understandings of sports journalism. A content and textual analysis (n = 494) was conducted of one month of Romano’s tweets and replies. Tweets were categorised according to markers of sports journalism practice. Results show Romano is professionalising sports journalism on social media and subverting understandings of personal branding through favouring objective news over subjective opinion and focusing on the professional rather than the personal. Romano’s transfer news prioritises major European football clubs, which is consistent with the trajectory of sports journalism on digital platforms. Play-by-play commentary is a minor aspect of Romano’s Twitter output, which contributes to the debate on the significance of game coverage to contemporary sports journalism. Tweets did not mention the human rights issues surrounding the World Cup starting in Qatar, even though this was a key talking point. This finding suggests that the normative assumption that sports journalists should scrutinise power and/or highlight social injustice does not always apply to all practitioners in all contexts, particularly where ultra-specialist settings are concerned. Full article

A smart sensing platform based on a triboelectric nanogenerator (TENG) possesses various advantages such as self-powering, convenience, real-time and biocompatibility. However, the detection limit of the TENG-based sensor is required to be improved. In this study, a high performance TENG-based glucose sensor was proposed by using the Ti₃C₂T_x (MXene)/graphene oxide (GO) composite electrode. The MXene and GO nanosheets are popular 2D materials which possessed high conductivity and a rich surface functional group. The MXene/GO thin films were prepared through electrostatic self-assembly technology, which can effectively impede the agglomeration of two nanoflakes. The as-prepared MXene/GO film presented outstanding mechanical property. To figure out the relationship between the nanostructure of MXene/GO film and the TENG, a series of MXene/GO-based TENG with different GO sizes was characterized. As a result, the TENG with 400 nm GO demonstrated the highest output performance. Subsequently, the optimized TENG was used in glucose detection application without the assistance of a glucose enzyme. This simple and flexible TENG shows promising potential in biosensors and non-invasive health monitoring. Full article

The GTP-binding protein-coupled receptors (GPCRs) play important roles in physiology and neuronal signaling. More than a thousand genes, excluding the olfactory receptors, have been identified that encode these integral membrane proteins. Their pharmacological and functional properties make them fascinating targets for drug development, since various disease states can be treated and overcome by pharmacologically addressing these receptors and/or their downstream interacting partners. The activation of the GPCRs typically causes transient changes in the intracellular second messenger concentrations as well as in membrane conductance. In contrast to ion channel-mediated electrical signaling which results in spontaneous cellular responses, the GPCR-mediated metabotropic signals operate at a different time scale. Here we have studied the kinetics of two common GPCR-induced signaling pathways: (a) Ca²⁺ release from intracellular stores and (b) cyclic adenosine monophosphate (cAMP) production. The latter was monitored via the activation of cyclic nucleotide-gated (CNG) ion channels causing Ca²⁺ influx into the cell. Genetically modified and stably transfected cell lines were established and used in stopped-flow experiments to uncover the individual steps of the reaction cascades. Using two homologous biogenic amine receptors, either coupling to G_o/q or G_s proteins, allowed us to determine the time between receptor activation and signal output. With ~350 ms, the release of Ca²⁺ from intracellular stores was much faster than cAMP-mediated Ca²⁺ entry through CNG channels (~6 s). The measurements with caged compounds suggest that this difference is due to turnover numbers of the GPCR downstream effectors rather than the different reaction cascades, per se. Full article

This paper proposes a novel wafer-level vacuum packaged electric field microsensor (EFM) featuring a high quality factor, low driving voltage, low noise, and low power consumption. The silicon-on-insulator (SOI) conductive handle layer was innovatively used as the sensing channel to transmit the external electric field to the surface of the sensitive structure, and the vacuum packaging was realized through anodic bonding between the SOI and glass-on-silicon (GOS). The fabrication process was designed and successfully realized, featured with a simplified process and highly efficient batch manufacturing, and the final chip size was only 5 × 5 mm. A theoretical model for the packaged device was set up. The influence of key parameters in the packaging structure on the output characteristics of the microsensor was analyzed on the basis of the proposed model. Experiments were conducted on the wafer-level vacuum-packaged EFM to characterize its performance. Experimental results show that, under the condition of applying 5 V DC driving voltage, the required AC driving voltage of the sensor was only 0.05 V_P, and the feedthrough was only 4.2 mV. The quality factor was higher than 5000 and was maintained with no drop in the 50-day test. The vacuum in the chamber of the sensor was about 10 Pa. A sensitivity of 0.16 mV/(kV/m) was achieved within the electrostatic field range of 0–50 kV/m. The linearity of the microsensor was 1.62%, and the uncertainty was 4.42%. Full article

In the past, planning to develop an electricity generation capacity supply of consumable load, an acceptable level of reliability, and minimum cost has played significant roles. Due to technological development in energy and the support of energy policymakers to make the most of these clean and cheap resources, a significant amount of research has been conducted to make the most of such energy. Constraints such as low capacity, output power uncertainty, and sustainability problems have made using distributed energy sources costly and complex. Theoretically, capacity development planning in a power system is part of macro-energy planning. It is generally based on specific development policies in each country’s national interest. In addition to being economical, the purpose of this planning was to find the best capacity development plan commensurate with the amount of consumption so that the development plan does not go beyond the permissible limits of reliability, environmental issues, and other constraints. On the other hand, due to the considerable growth of divided production, especially energy sources, it is essential to use microgrids. Accordingly, in this research study, in the process of solving the problem of planning and providing load growth by the distributed generation units to maximize reliability and minimize investment costs, the creation of smaller networks was investigated. To optimize zoning, the weighted graph theory method, in which the weight of the edges is the apparent power passing through the lines, was adopted. In addition, reactive power reliability was included in the calculations to improve the economic aspects. Probabilistic modeling for the presence of renewable resources was employed to bring the model to reality. Since the above problem is very complex, a Seagull-based algorithm and chaos theory were utilized to solve this matter. Finally, the suggested method for the sample system is discussed in different scenarios, indicating an improvement in the system’s performance. According to the numerical results, the NSGA, SPEA, and MOPSO have mean values of 68.3%, 50.2%, and 48.3%, which are covered by the proposed optimization algorithm. Full article

Economy and parsimony in the consumption of energy resources are becoming a part of common sense in practically all countries, although the effective implementation of energy efficiency policies still has a long way to go. The energy demand for residential buildings is one of the most significant energy sinks. We focus our analysis on one of the most energy-consuming systems of residential buildings located in regions of tropical climate, which are cooling systems. We evaluate to which degree the integration of thermal energy storage (TES) and photovoltaic (PV) systems helps to approach an annual net zero energy building (NZEB) configuration, aiming to find a feasible solution in the direction of energy efficiency in buildings. To conduct the simulations, an Energy Efficiency Analysis Framework (EEAF) is proposed. A literature review unveiled a potential knowledge gap about the optimization of the ASHRAE operational modes (full storage load, load leveled, and demand limiting) for air conditioning/TES sets using PV connected to the grid. A hypothetical building was configured with detailed loads and occupation profiles to simulate different configurations of air conditioning associated with TES and a PV array. Using TRNSYS software, a set of scenarios was simulated, and their outputs are analyzed in a life cycle perspective using life cycle costing (LCC). The modeling and simulation of different scenarios allowed for identifying the most economic configurations from a life cycle perspective, within a safe range of operability considering the energy efficiency and consequently the sustainability aspects of the buildings. The EEAF also supports other profiles, such as those in which the occupancy of residential buildings during the day is increased due to significant changes in people’s habits, when working and studying in home office mode, for example. These changes in habits should bring a growing interest in the adoption of solar energy for real-time use in residential buildings. The results can be used as premises for the initial design or planning retrofits of buildings, aiming at the annual net zero energy balance. Full article

Characterization of Unintended Conducted Emissions (UCE) from electronic devices is important when diagnosing electromagnetic interference, performing nonintrusive load monitoring (NILM) of power systems, and monitoring electronic device health, among other applications. Prior work has demonstrated that UCE analysis can serve as a diagnostic tool for energy efficiency investigations and detailed load analysis. While explaining the feature selection of deep networks with certainty is often not fully comprehensive, or in other applications, quite lacking, additional tools/methods for further corroboration and confirmation can help further the understanding of the researcher. This is true especially in the subject application of the study in this paper. Often the focus of such efforts is the selected features themselves, and there is not as much understanding gained about the noise in the collected data. If selected feature and noise characteristics are known, it can be used to further shape the design of the deep network or associated preprocessing. This is additionally difficult when the available data are limited, as in the case which the authors investigated in this study. Here, the authors present a novel work (which is a proposed complementary portion of the overall solution to the deep network classification explainability problem for this application) by applying a systematic progression of preprocessing and a deep neural network (ResNet architecture) to classify UCE data obtained via current transformers. By using a methodical application of preprocessing techniques prior to a deep classifier, hypotheses can be produced concerning what features the deep network deems important relative to what it perceives as noise. For instance, it is hypothesized in this particular study as a result of execution of the proposed method and periodic inspection of the classifier output that the UCE spectral features are relatively close to each other or to the interferers, as systematically reducing the beta parameter of the Kaiser window produced progressively better classification performance, but only to a point, as going below the Beta of eight produced decreased classifier performance, as well as the hypothesis that further spectral feature resolution was not as important to the classifier as rejection of the leakage from a spectrally distant interference. This can be very important in unpredictable low-FNR applications, where knowing the difference between features and noise is difficult. As a side-benefit, much was learned regarding the best preprocessing to use with the selected deep network for the UCE collected from these low power consumer devices obtained via current transformers. Baseline rectangular windowed FFT preprocessing provided a 62% classification increase versus using raw samples. After performing a more optimal preprocessing, more than 90% classification accuracy was achieved across 18 low-power consumer devices for scenarios in which the in-band features-to-noise ratio (FNR) was very poor. Full article

Finding an ideal sampling design is a crucial stage in detailed soil mapping to assure reasonable accuracy of resulting soil property maps. This study aimed to evaluate the influence of sampling designs and sample sizes on the quality of soil apparent electrical conductivity (ECa) maps from an electromagnetic sensor survey. Twenty-six (26) parallel transects were gathered in a 72-ha plot in Southeastern Brazil. Soil ECa measurements using an on-the-go electromagnetic induction sensor were taken every second using sensor vertical orientation. Two approaches were used to reduce the sample size and simulate kriging interpolations of soil ECa. Firstly, the number of transect lines was reduced by increasing the distance between them; thus, 26 transects with 40 m spacing; 13 with 80 m; 7 with 150 m; and 4 with 300 m. Secondly, random point selection and Douglas-Peucker algorithms were used to derive four reduced datasets by removing 25, 50, 75, and 95% of the points from the ECa survey dataset. Soil ECa was interpolated at 5 m output spatial resolution using ordinary kriging and the four datasets from each simulation (a total of twelve datasets). Map uncertainty was assessed by root mean square error and mean error metrics from 400 random samples previously selected for external map validation. Maps were evaluated on their uncertainty and spatial structure of variation. The transect elimination approach showed that maps produced with transect spacing up to 150 m could preserve the spatial structure of ECa variations. Douglas-Peucker results showed lower nugget values than random point simulations for all selected sample densities, except for a 95% point reduction. The soil ECa maps derived from the 75% reduced dataset (by random sampling or Douglas-Peucker) or from 13 transect lines (80 m spacing) showed reasonable accuracy (RMSE of validation circa 0.7) relative to the map interpolated from all survey points (RMSE of 0.5), suggesting that transect spacing of 80 m and reading intervals greater than one second can be used for improving the efficiency of on-the-go soil ECa surveys. Full article