Miracle-dz/UniFAR-FTUs huggingface dataset:
Regularised dynamic optimal transportation of electric vehicles over networks considering strategic charging pricing

A dynamic optimal transport problem of electric vehicles (EVs) over a network is investigated. The EVs are considered to be transported from their initial locations to the destination nodes for charging purposes. In our framework, the operators of charging stations are strategic, and each of them designs their charging pricing optimally to maximise the revenue. Since EVs play an essential role as power loads at the charging stations, the designed transport strategy by the EV operator has an impact on the market energy price which in turn influences the charging prices. Therefore, to design an efficient transport plan, the EV operator needs to take into account its influence on the charging pricing and the market energy price due to their complex interplay. To achieve this goal, a unified framework is proposed for optimal EV transportation by considering factors including the delay, charging cost, and real-time social demand of EVs over a finite-time horizon. The balanced dynamic optimal transport strategy is enabled through a combined quadratic and entropic regularisation. To compute the equilibrium pricing for all charging stations, an iterative particle-swarm optimisation scheme is designed which addresses a high-dimensional nonlinear optimisation problem. Finally, case studies are used to illustrate and corroborate the obtained results.
Number plate recognition on vehicle using YOLO - Darknet

Character recognition is one of the steps in the number plate recognition system. Character recognition is done to get text character data. The method used is YOLOv3 (You Only Look Once), and Darknet-53 is used as a feature extractor. In this study, the data used were number plate images derived from the extraction and cropping of motorized vehicle videos that had been taken using cellphones and cameras. Testing is done with two different models, namely the model obtained with additional preprocessing data and the model obtained without any preprocessing data. Data preprocessing is done to improve the quality of the number plate image. Testing is done on an uninterrupted number plate image dataset and a number plate image dataset with interference and a reduction of color intensity (brightness) in the image. For the model obtained from the data without preprocessing, the highest number plate recognition accuracy obtained is 80%, and the character recognition accuracy is 97.1%. Meanwhile, for the model obtained from preprocessing data, the highest number plate recognition accuracy obtained was 88%, and the character recognition accuracy was 98.2%.
KylinX: Simplified Virtualization Architecture for Specialized Virtual Appliances with Strong Isolation

ion. The success of these relaxations on picoprocess inspires our dynamic KylinX extension to Unikernel. Containers and picoprocesses tend to have a large TCB, since the LibOSs often contain unused features. In contrast, KylinX and other Unikernels leverage the virtual hardware abstraction (e.g., event channels and shared memory) safely exposed by the hypervisor to simplify their implementation and follow the minimalism philosophy [45] to link an application only against requisite libraries to improve not only efficiency but also security. Dune [43] leverages Intel VT-x [87] to provide a process (rather than a machine) abstraction to isolate processes and access privileged hardware features. It augments UNIX processes with isolation and enhances the performance by allowing them to access privileged CPU features. Going one step further, IX [44] incorporates virtual devices into the Dune process model and achieves high throughput and low latency for networked systems. lwCs [68] provides independent units of protection, privilege, and execution states within a process. These designs have realized some similar properties of KylinX; for example, access to (virtual) hardware features while providing the process abstraction. Dune and IX achieve this in a way different from Unikernel LibOSs by augmenting processes, and they have essentially implemented a hypervisor. Compared to these techniques, KylinX runs directly on Xen (a type-1 hypervisor), which naturally provides strong isolation and allows KylinX to focus on the flexibility and efficiency issues. Further, leveraging hardware support (e.g., MMU virtualization required by Dune) for process isolation in a libOS not only introduces a duplicate scheduler and memory management, but also complicates conventional management functionalities (like live migration) across platforms, because hardware vendors (Intel and AMD) have incompatible MMU virtualization support [85]. Haven [42], SCONE [37], Ryoan [58], and Graphene-SGX [86] leverage hardware protection of Intel SGX [17] to achieve shielded execution in processes against attacks from malicious operating systems and hypervisors. These studies are orthogonal to KylinX and thus could be incorporated into KylinX. For instance, we may put a pVM into the trusted enclave for strong confidentiality.
Concepts and methods for assessing solute dynamics in stream ecosystems

A stream solute workshop was held February 1-5,1989, at The University of Mississippi with the goals of 1) suggesting a conceptual model for stream solute studies that integrates physical, chemical, and biological processes, and 2) identifying advantages and limitations of various methods for studying solute transport and exchanges. Solute dynamics refers to the spatial and temporal patterns of transport and transfers of materials that are chemically dissolved in water. Solute trans- port and exchange processes can be described by solute transport equations that relate solute concentration to advection, dispersion, groundwater and tributary inputs, transient storage zones, and biotic and abiotic transformations. Studies can be based on these model equations even if a full simulation of a particular system is not attempted. Although no common methodological approach can serve every investigation of solute dynamics, experimental approaches represent a range from greatest control and least realism to least control and greatest realism. The model parameters describe processes that can be investigated in laboratory, chamber, and flume experiments designed to reduce confounding experimental variables. Whole-stream studies, particularly solute injection experi- ments, provide estimates of solute transfer to and from the water column and can be used to calibrate the simulation models. Transport and transfer models can link experimental results obtained at different scales and increase the opportunity for inter-site comparisons and the extrapolation of results between laboratory, chamber, flume, and whole-stream studies.
An Investigation upon Industry 4.0 and Society 5.0 within the Context of Sustainable Development Goals

In the literature, quite limited research exists on the subject of Society 5.0. The present study examined the existence of Society 5.0 and the effectiveness of Industry 4.0 and evaluated the efficiency of United Nations Development Goals (SDGs) in this process, especially in Turkey. The research was carried out based on data obtained through a survey form with 30 questions which was conducted with 335 academicians working at Kafkas University. The data were analyzed by means of exploratory factor analysis with the SPSS program, confirmatory factor analysis with AMOS, and structural equation modeling with Smart PLS. The analysis results indicated that SDG9, SDG10, SDG11, SDG12, SDG13, and SDG14 had a low influence (i.e., R2: 0.172) on the application of Industry 4.0 and Society 5.0. Moreover, it was observed that the participants were heavily affected by order of the day and gave responses to the questions with that impact. The study also revealed that Turkey did not have a leading philosophy in the field of Society 5.0 and Industry 4.0 and made progress by concentrating on out-dated processes.
Energy-Efficient Ultra-Dense Network Using LSTM-based Deep Neural Networks

As a means to achieve thousand-fold throughput improvements of future wireless communications, ultra-dense network (UDN) where a large number of small cells are densely deployed on top of the macro cells has received great deal of attention in recent years. While UDN offers number of benefits, intensive deployment of small cells may pose a serious concern in the energy consumption. Over the years, to reduce the energy consumption of UDN, an approach that turns off the lightly loaded base stations (BSs) has been proposed. However, determining the proper on/off modes of BSs is a challenging problem due to the huge computational overhead and inefficiency caused by the delayed decision. An aim of this paper is to propose a deep neural network (DNN)-based framework to achieve reduction of energy consumption in UDN. By exploiting the long short-term memory (LSTM) to extract the temporally correlated features from the channel information and the feedforward network to make BS on/off mode decision, we can control the on/off modes of BSs, thereby achieving a considerable reduction of the cumulative energy consumption. From the extensive simulations, we demonstrate that the proposed technique is effective in reducing the energy consumption of UDN.
Investigating Physical Interaction With Digital Data Through the Materialization of Email Handling

Adopting a re-materialization approach, we designed and implemented an everyday interactive artifact that enables an individual to monitor and establish the reconfirmation time of email data. This device represents a new means of handling and interacting with email. To investigate the value of the materialization of email data through a daily interactive object, Maili, we conducted a 1-month field study with five participants in their work environments. The results showed that applying physicality to email handling helped to increase accessibility to and interest in the data, as well as in the reconfirmation function of email. Results also indicated the value of combining non-digital (the tray) with digital functions. By presenting the process of using the dematerialized data, our findings offer new insights into how we can materialize digital information in everyday tangible artifacts.
Experimental demonstration of high‐concentration photovoltaics on a parabolic trough using tracking secondary optics

A new approach to high‐concentration photovoltaics (HCPV) based on a parabolic trough primary concentrator is presented. The design diverges from the standard HCPV arrangement of a two‐axis tracking point‐focus concentrator, and rather employs a simpler parabolic trough primary concentrator to reduce cost. To break the 2D limit of concentration, and bring the system into the realm of HCPV, the system employs an array of rotating secondary concentrators is arranged along the focal line of the parabolic trough. The resulting line‐to‐point (LTP) focus geometry allows the system to achieve a geometric concentration of 590×, yet still maintains the advantages of having a linear trough primary concentrator, namely manufacturability, economy, and scalability. A full‐scale prototype of the system was constructed in Biasca, Switzerland. During on‐sun tests a flux concentration of 364 suns was measured at the exit of the secondary concentrator, the highest reported concentration for any parabolic‐trough‐based system. Moreover, the system reached a peak efficiency of 20.2%, the highest measured solar‐to‐DC efficiency for a parabolic trough‐based solar collector. Long‐term performance is estimated by means of a coupled optical‐electrical model validated vis‐à‐vis the experimental results. This work serves as an experimental proof‐of‐concept for high‐concentration trough‐based collectors, thereby opening new avenues for reducing the cost of HCPV systems. Copyright © 2016 John Wiley & Sons, Ltd.
Evaluating remote sensing indices as potential productivity and stand quality indicators for Pinus radiata plantations

The objective of the present research was to evaluate the use of several spectral vegetation indices (SVIs), including NDVI, SAVI, SR and RSR, obtained from Landsat 7 images, as potential predictors of forest productivity of radiata pine stands. We aimed to evaluate relationships between the variations in stand volume and SVIs over time and the effect of early weed control on stand growth response. We evaluated a large-scale silviculture experiment located at the Central Valley of Chile, since its establishment until 12 years of age, where weed control showed to be the major silvicultural response. Forest inventory measurements were made annually and local equations were used to estimate stand volume. Significant and highly significant correlation was found among SVI ́s and stand productivity parameters. The best relationship was found between NDVI and stand cumulative volume (R-adj=0.92, p-value < 0.0001, RMSE= 0.03), but SR and RSR were able to better track productivity and the major weed control effect on stand volume growth over time. SVIs’ coefficient of variation estimates were correlated with estimates of stand productivity variability but no significant relationships were established to provide an index of stand quality due to the sensor spatial resolution and plot sizes. SVIs may serve as important tools to monitor forest growth and high-resolution imagery may provide valuable estimates of stand variability for inventory assessment or as a support tool for growth and yield models.
Mineral Uptake Rates and Yield Coefficients of the Green Microalgae Scenedesmus Dimorphus

The need for renewable sources of energy has become critical as fossil fuel resources, which include oil, coal, and natural gas, are known to contribute to climate change and will eventually be depleted. Biofuels that originate from the fat of plants, animals, microalgae, and bacteria are an attractive alternative. Microalgae, in particular, are strong candidates for biofuel production since they have a high growth rate and lipid content (up to 50% in some species). The goal of this research was to optimize 3NBBM+V recipe (Bold Basal Medium with 3-fold Nitrogen and Vitamins) in an effort of reducing the amount of nutrients used in growing the green microalgae Scenedesmus dimorphus, and hence lower the cost of cultivation. Three runs were carried out on a 5L bioreactor in batch mode. The average growth rate of S. dimorphus was 0.17 ± 0.03 days. Inductively Coupled Plasma was utilized to monitor substrate concentration with time in the bioreactor which allowed the determination of yield coefficients in gdw biomass/g substrate for magnesium (253±50), calcium (341±84), potassium (61±15), phosphorous (60±13), and iron (5807±3000). These yields were utilized to calculate the optimal starting substrate concentration in the media in mg/L for magnesium (4.3±0.3), calcium (3.2±0.2), potassium (18±1), phosphorous (18±1), and iron (0.19±0.015). The
Research on Security Verification Mechanism of Perception Layer Terminal of Power Internet of Things Based on Device Operation Fingerprint

Integrating the Internet of things technology into the power grid is a major development trend in the future, which can effectively improve the overall performance of the existing power grid. However, due to the traditional Internet of things mainly uses the form of digital password for security protection, due to the low security problems, there are great hidden dangers to the operation of the equipment. For this reason, this paper proposes a security verification mechanism for the perception layer terminal of the power Internet of things based on the device operation fingerprint. In this paper, the biometric fingerprint identification technology and Internet of things architecture are deeply studied, and the fingerprint identification algorithm process and steps are analyzed in detail, and the processing time of each step is compared. In order to improve the comprehensive performance of the security verification of the perception layer terminal of the Internet of things, according to the actual security requirements of the power Internet of things, combined with the biometric fingerprint identification technology, a new security verification system is established. In this paper, the security mechanism of RFID system is adopted, and the performance of fingerprint image filtering is improved by optimizing calculation method and simplifying algorithm. By improving the identity authentication mode and optimizing the data encryption transmission mechanism, the security protection performance of the perception layer of the power Internet of things is further improved. In the simulation test, the system identification accuracy rate of this paper reaches 99.75%, and the software implementation efficiency test results are good, which shows that the system in this paper has high security protection performance, and can meet the current security protection needs of the power Internet of things.
Indirect determination of leucogen in leucogen tablets by flow injection spectrophotomertry

The hydrolysis product of leucogen in alkaline medium was determined by spectrophotometry at 300nm. The method was used to determine leucogen indirectly by flow injection spectrophotometry. The linear range is 0.01～0.2 mg/mL and the recovery is 100 0%～102 0%.
Energy aware adaptive resource management model for software-defined networking-based service provider networks

Service provider networks (SPNs) seek to implement the resource management mechanisms called load balancing and energy saving to satisfy today's networking demands. Software ‐ defined networking (SDN) allows SPNs to perform agile and efficient networking operations. It is still an open issue on how to implement these resource management mechanisms in SDN ‐ based SPNs. An energy ‐ aware adaptive resource management model (ERM) for SDN ‐ based SPNs is proposed. Load balancing aims to distribute overall network traffic volume as fairly as possible among available links. Energy ‐ saving aims to turn off as many network devices and links as possible. Unlike the works in the literature, our model utilises the trade ‐ off between load balancing and energy efficiency. To do so, the controller establishes paths among edge pairs. The controller aggregates traffic load between edge pairs to as few links as possible based on a pre-defined load level. Then, unused network elements switch to sleep mode. In the case of load balancing, the controller distributes traffic load among active network resources. Experimental results show that ERM can successfully increase both energy ‐ saving and resource utilization even under heavy traffic loads.
Gender Differences in Knowledge, Use, and Collection of Wild Edible Plants in Three Spanish Areas

Many ethnobotanical studies have shown differences in the knowledge and practices held by men and women. Using ethnographic fieldwork, a survey, and secondary data from three different areas in Spain, this study shows a geographical pattern in women’s and men’s relations with wild edible plants. In the case studies from Southern Spain, Donana, and Sierra Morena Extremena, women gather less wild edible plants than men, while in the Central Spain case study, Sierra Norte de Madrid, the difference is less marked. We explain this difference through the construction and distribution of agrarian spaces, particularly with regards to land tenure type and urban centers size. In the southern cases, large agrarian properties are more prevalent than in Sierra Norte de Madrid, where common lands and small and medium properties predominate. Additionally, in Donana, big urban agro-towns dominate, whereas in Sierra Norte de Madrid and Sierra Morena Extremena little towns are the norm. Overall, our study suggests that gendered differences in the use of natural resources are better understood if contextualized in a large socioecological context.
Kognitive Remediation und soziales Kompetenztraining bei Schizophrenie

Viele schizophren Erkrankte haben auch nach Abklingen von akuten Krankheitsepisoden Probleme bei der Alltagsgestaltung, die sie als sehr belastend erleben. Eine Beeinträchtigung der psychosozialen Funktionsfähigkeitmit Isolation und sozialem Rückzug ist bei schizophren erkrankten Menschen seit vielen Jahrzehnten beschrieben und auch heute noch Teil der Diagnosekriterien von Schizophrenie im DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Version 5).
Seismic Evaluation of Existing Building Structures in the City of Madiun using Pushover Analysis

This paper presented the seismic evaluation of the existing building structure in Madiun city. The selected building analysis is Parkir Building of Pasar Besar Madiun city that located at Panglima Sudirman street Madiun city Indonesia. The structural system of this building is Moment Resisting Frame (MRF). The building structure is reinforced concrete. Seismic load calculation use equivalent static load analysis base on Seismic Resistance Design Standart for Building Structures (SNI 1726:2012). Pushover analysis of this building use software ETABS version 9.00. Aim of this research to know the performance level of this bulding. The pushover analysis is a relatively simple tool for Performance Based Seismic Evaluation (PBSE).
Serum Level of Uromodulin as an Early Predictor Marker of Kidney Disorders

BACKGROUND: Metabolic diseases are known to be risk factors of kidney injury. The glycoprotein Uromodulin Tamm-Horsfall protein is a biochemical marker specifically synthesized and secreted by kidney tubular epithelial cells. AIM: The study aimed to use novel biochemical parameters to predict early changes in renal functions and to use natural food supplements to help in the prevention and management of such conditions. METHODS: Crossover studies comparing two interventions trials. Subjects: Seventy obese females were included in this study. They were divided in two groups, first group (34 women) with mean age 45.82 ± 1.51 and mean body mass index (BMI) 35.65 ± 0.68 kg/m2, and second group (36 women) with mean age 49.80 ± 2.27, and mean BMI 37.67 ± 1.59. Intervention: All participants have followed a low caloric balanced regimen (1000–1200 Kcal/day) of the each groups consumed a different specific nutritional supplement composed mainly of whole grains and herbs. All patients were monitored clinically, anthropometrically, dietary 24 h recall and biochemically. RESULTS: After intervention all the recorded anthropometric parameters showed significant decreases at p ≤ 0.05–0.01. The serum uromodulin (sUMOD) increased significantly after intervention in both groups the increments were 15.56 and 9.37%. Numerically creatinine and urea decreased, while creatinine clearance increased. CONCLUSION: Data revealed the importance of using dietary therapy composed of hypocaloric diet with supplements made from whole grains and special herbs in management of obesity and its metabolic disorders. sUMOD proved to be an accurate biochemical marker that showed the kidneys’ response to the management in comparison to using usual diagnostic markers.