Miracle-dz/UniFAR-FTUs huggingface dataset:
COST-EFFECTIVE EMISSION CONTROLS FOR COAL-FIRED POWER PLANTS

Integrated environmental control (IEC) concepts involving combined SO2/NOx. removal processes in combination with pre-combustion and combustion control methods offer significant potential for more cost-effective emissions control for coal-fired power plants. IEC system designs involving three advanced flue gas treatment processes in conjunction with conventional and advanced coal cleaning technologies to achieve overall reductions of 90 percent for both SO2 and NOx are compared to a conventional pulverized coal plant design using currently available technology. A new computer modeling framework is used to characterize key uncertainties, and to evaluate overall performance and cost probabilistically using Monte Carlo methods. Results indicate that several IEC systems currently under development offer a good chance of reducing environmental control costs by 20 to 30 percent, although improvements in currently commercial technology are likely to offset some of the gains expected from advanced process designs.
Unstable shoes and rehabilitation

foot measurements shows high variability in basic foot measurements within length classes (Figure 2). Only a few shoe producers have been producing shoes in various widths of the same model and size. The results show that one width per size can fit maximum 50% of the population. Three widths per size have to be produced to fit 95% of the population. A low correlation between foot width and foot height was observed. This means that a wide foot is not necessarily also a high foot, or the opposite, a narrow foot is not necessarily also a low foot. This fact has to be considered when designing multi width lasts. So far multi width lasts have been scaled by the same factor in width and height, which does not make sense according to the results of this study. A very low correlation between foot length and foot height is also noticeable. This analysis shows small differences in characteristic foot dimensions between the European nations. The difference in the regression lines of the nations with the narrowest and the widest feet is less than the difference between the two last widths. According to this analysis there is no need to produce different widths of the same shoe model for different European nations. Discussion and conclusion
Ultra-stable Oscillators: Limits of GNSS Coherent Integration

Oscillators are indispensable hardware components of many RF circuits and wireless systems whose precision has continuously increased in the last few decades. The development of such ultra-stable oscillators has motivated the design of reliable techniques for assessing their performance. Global Navigation Satellite Systems (GNSSs) provide an extremely accurate frequency reference, indispensable for precise positioning. This reference is freely available to the user and therefore can be used for assessing the oscillator performance. In this work a wide set of high quality oscillators, manufactured by the Swiss companies Oscilloquartz, Fordahl and Micro Crystal, has been analyzed by using the GPS signal as frequency reference. GPS L1 samples have been collected using a front-end driven by the oscillator under test, post-processed and analyzed by custom developed software. Several frequency errors, such as Doppler frequency and bit transitions have been removed possibly leaving only the errors induced by the local and satellite’s oscillators. Perfect frequency sources would have led to an accumulated power linearly growing with the integration time. The appearance of artifacts and the saturation of the accumulated power reveal the limits of the considered oscillators. If the local oscillator is ultra-precise, extremely long coherent integrations are possible allowing indoor positioning. More specifically coherent integrations longer than one minute have been obtained and used for indoor location in the context of Assisted GPS under attenuated signal conditions of up to 45 dB.
Investigation of fault modes of voltage-fed inverter system for induction motor drive

The authors describe a systematic investigation into the various fault modes of a voltage-fed pulse-width-modulated (PWM) inverter system for induction motor drives. All the fault modes were identified, and a preliminary mathematical analysis was made for the key fault types-namely, input supply single line to ground fault, rectifier diode short circuit, inverter transistor base drive open, and inverter transistor short circuit conditions. The predicted fault performances were substantiated by a simulation study. The study was used to determine stresses in power circuit components and to evaluate satisfactory postfault steady-state operating regions. The results are equally useful for better protection system design and easy fault diagnosis. <<ETX>>
Using the 3T architecture for tracking Shuttle RMS procedures

Describes the use of a three-tiered robot control software architecture, known as 3T, as the software framework for automating the job of NASA flight controllers as they track procedures executed by on-orbit astronauts. The project discussed focuses on automating the procedures relating to the Shuttle's Remote Manipulator System and is a pathfinder project for the automation of other Shuttle operations. The RMS Assistant system is designed to track the expected steps of the crew as they carry out RMS operations, detecting malfunctions in the RMS system from failures or improper configurations as well as improper or incomplete procedures by the crew. In this regard, it is a "flight controller in a box". Moving the flight controller functions on-orbit is part of a larger program of downsizing general Space Shuttle operations. The 3T architecture was designed for intelligent autonomous robots, but has an added capability that allows for variable autonomy to include full teleoperation. In that mode, the software acts as a monitoring system, and thus provides an "assistant" framework now and accommodates more autonomous operations in the future.
Protective Effect of Panax ginseng on osteoporosis in Ovariectomized Female Guinea-pigs

Objective: To investigate the protective effect of Panax ginseng on osteoporosis in guinea-pigs induced by ovariectomy. Methods: Six-month-old 36 SPF non-pregnant female guinea-pigs, were divided into four groups randomly: sham-operated group (Sham), blank model group (Model), recommended dose of Panax ginseng group (RD) and Maximum dose of Panax ginseng group (MD), 9 guinea-pigs in each group. Guinea-pigs models of osteoporosis were prepared by ovariectomized (OVX), except Sham group. 2 weeks later, OVX guinea-pigs were administered gavage with Panax ginseng powder twice daily for 100 days, RD group with 2.5mg/100gBW, MD group with 5mg/100 gBW. Sham and Model group were given with the same dose of saline, all the gavage dose were 3mL. The serum of guinea-pigs were obtained to measure the electrolytes ions, serum Ca, Mg, P, to measure serum bone metabolism indexes BALP, OC, TRACP-5b, BMD and BMC. Results: Compared with Model group, the level of serum Ca, P decreased in the Panax ginseng groups, but the level of Mgincreased (P<0.05), the statistics difference in MD group was significant (P<0.01). The influence of serum BALP, OC, and TRACP-5b: compared with Model group, the Panax ginseng groups had statistical differences (P<0.05), with the dose correlated positively. Compared with Model group, the index values of BMD and BMC of the Panax ginseng groups were significantly Maximum (P<0.05), there was a dosedependent difference with drug intervention. Conclusion: Panax ginseng can inhibit bone loss, decrease bone turnover rate, and improve the osteoporosis with dose-dependent effect.
Prediction Deviants with Varying Degrees Induce Separable Error-related EEG Features

Error-related potential (ErrP) usually emerges in the brain when human perceives errors and is believed to be a promising signal for optimizing brain-computer interface (BCI) system. However, most of the ErrP studies only focus on how to distinguish the correct and wrong conditions, which is not enough for the BCI application in real scenarios. Therefore, it is necessary to study the ErrPs induced by the prediction deviants with varying degrees, concurrently test the separability of such EEG features. To this end, electroencephalogram (EEG) data of twelve healthy subjects were recorded when they participated in a direction prediction experiment. There are three prediction -deviant conditions in it, i.e., correct prediction, 90°deviant, 180° deviant. Event-related potential and inter-trial coherence were analyzed. Consequently, the error-related negativity (ERN) and N450 component in FCZ were significantly modulated by the degrees of prediction deviants, especially in the low-frequency band (<13Hz). Moreover, single-trial classification was adopted to test the separability of these features; the averaged accuracies between any two conditions were 87.75%, 85.25%, 64.79%. This study demonstrates the prediction deviants with varying degrees can induce separable ErrP features, which provide a deeper understanding of the ErrP signatures for developing BCIs.
The Group Jump Rope Orchestra: an interactive system to present a sense of togetherness

“ The Group Jump Rope Orchestra” is an interactive system to present a sense of togetherness of participants by using a virtual reality technology. Participants of this system can perform an orchestra music by jumping a virtual rope that is projected onto their front screen and onto the floor. As the number of participants increases, the orchestra becomes grander.
Abnormal EEG Complexity and Alpha Oscillation of Resting State in Chronic Stroke Patients

A valid evaluation of neurological functions after stroke may improve clinical decision-making. The aim of this study was to compare the performance of EEG-related indexes in differentiating stroke patients from control participants, and to investigate pathological EEG changes after chronic stroke. 20 stroke and 13 healthy participants were recruited, and spontaneous EEG signals were recorded during the resting state. EEG rhythms and complexity were calculated based on Fast Fourier Transform and the fuzzy approximate entropy (fApEn) algorithm. The results showed a significant difference of alpha rhythm (p = 0.019) and fApEn (p = 0.003) of EEG signals from brain area among ipsilesional, contralesion hemisphere of stroke patients and corresponding brain hemisphere of healthy participants. EEG fApEn had the best classification accuracy (84.85%), sensitivity (85.00%), and specificity (84.62%) among these EEG-related indexes. Our study provides a potential method to evaluate alterations in the properties of the injured brain, which help us to understand neurological change in chronic strokes.
“Assessment of lymph node status in cases of metastatic malignancy by frozen section and imprint cytology”

Introduction: Dissemination of cancers most commonly occurs by the lymphatic route and is generally favoured by carcinomas. The best achievable goal of any surgical procedure is removal of all the affected tissue and leave behind healthy tissue which is entirely free of any malignant cells. Though histopathological examination is gold standard, it is time consuming and cannot be implemented as an intraoperative diagnostic tool. The present study utilises frozen section analysis and touch imprint cytology as intraoperative tools and analyses their diagnostic accuracy to detect lymph node metastasis in comparison with routine histopathology in epithelial malignancies. Aim: To evaluate the efficacy of intraoperative diagnosis by touch imprint cytology and frozen section analysis for the assessment of metastatic lymph node deposits. Materials and methods: Total 76 cases of primary malignancy with suspicious metastatic lymph nodes were investigated. Metastatic nodes were subjected to frozen section and European Journal of Molecular & Clinical Medicine ISSN 2515-8260 Volume 7, Issue 2, 202
Patient-specific modeling of the volume of tissue activated (VTA) is associated with clinical outcome of DBS in patients with an obsessive-compulsive disorder

Deep brain stimulation (DBS) promises to treat an increasing number of neurological and psychiatric disorders. DBS outcome is directly a factor of optimal targeting of the relevant brain structures. Computational models can help to interpret a patient’s outcome by predicting the volume of tissue activated (VTA) around DBS electrode contacts. Here we report results of a preliminary study of DBS in two patients with obsessive-compulsive disorder and show that VTA predictions, which are based on patient-specific volume conductor models, correlate with clinical outcome. Our results suggest that patient specific VTA calculation can help inform device programing to maximize therapeutic effects and minimize side effects.Clinical Relevance— Patient-specific modeling of the volume of activated tissue can predict clinical outcomes and thus, can help to optimize DBS device programing to maximize therapeutic effects.
sEMG-Based Hand Movement Regression by Prediction of Joint Angles With Recurrent Neural Networks

This work takes a step towards a better biosignal based hand gesture recognition by investigating the strategies for a reliable prediction of hand joint angles. Those strategies are especially important for medical applications in order to achieve e.g. good acceptance of hand prostheses among amputees. A recurrent neural network with a small footprint is deployed to estimate the joint positions from surface electromyography data measured at the forearm. As the predictions are expected to be not smooth, different post processing methods and a regularisation term for the objective function of the network are proposed. The experiments were conducted on publicly available databases. The results reveal that both post processing strategies and regularisation have a positive impact on the results with a maximal relative improvement of 6.13 %. On the one hand post processing strategies introduce an additional delay, consequently, the improvement is analysed in context of the caused delay. On the other hand the regularisation strategy does not cause a delay and can be adjusted easily to cope with different ground truths or compensate for certain problems in the hand tracking.
Gaussian-Mixture Modelling of A-Mode Radiofrequency Scans for the Measurement of Arterial Wall Thickness

Measurement of arterial wall thickness is an integral component of vascular properties and health assessment. State-of-the-art automated or semi-automated techniques are majorly applicable to B-mode images and are not available for entry-level in-expensive devices. Considering this, we have earlier developed and validated an image-free (A-mode) ultrasound device, ARTSENS® for the evaluation of vascular properties. In this work, we present a novel gaussian-mixture modeling-based method to measure arterial wall thickness from A-mode frames, which is readily deployable to the existing technology. The method’s performance was assessed based on systematic simulations and controlled phantom experiments. Simulations revealed that the method could be confidently applied to A-mode frames with above-moderate SNR (>15 dB). When applied to A-mode frames acquired from the flow-phantom setup (SNR > 25 dB), the mean error was limited to (2 ± 1%), and RMSE was 19 μm, on comparison with B-mode measurements. The measured and reference wall thickness strongly agreed with each other (r = 0.88, insignificant mean bias = 7 μm, p = 0.16). The proposed method was capable of performing real-time measurements.
A Novel Approach to Decode Covert Spatial Attention Using SSVEP and Single-Frequency Phase-Coded Stimuli

This paper investigates for the first time the use of single-frequency phase-coded stimuli to detect covert visuo-spatial attention (CVSA) with steady-state visual evoked potentials (SSVEP). Two 15Hz pattern-onset stimulations were encoded with opposite phases and simultaneously presented on a LCD monitor. The effects of attending each stimulus on the amplitudes and phases of the evoked SSVEPs across the visual cortex are explored. A real-time CVSA classification experiment was simulated offline with 9 BCI-naive subjects, achieving an average classification accuracy of 88.4 ± 8% SE. Our results are, to our knowledge, the first report that CVSA can be decoded with SSVEP using single-frequency phase-coded stimuli. This opens opportunities for attention-tracking applications with largely increased number of targets.
An analysis of social accountability and transparency interventions’s influence of educational services

Accountability and transparency have a very important impact on the delivery and quality of education services, because the release of data can put pressure on schools’ results and citizens can make reference based on the data. The purpose of this essay is to analyse whether various interventions have a positive impact on education. This essay adopted the method of case studies, selected different intervention actions were used in different countries to analyse. The results show that all of these interventions have positive effects on educational services, but each intervention has its own disadvantages. The effectiveness of accountability and transparency is likely to be maximized when multiple interventions are carried out simultaneously.
FLNA Deficiency

FLNA deficiency is associated with a phenotypic spectrum that includes FLNA-related periventricular nodular heterotopia (Huttenlocher syndrome), congenital heart disease (patent ductus arteriosus, atrial and ventricular septal defects), valvular dystrophy, dilation and rupture of the thoracic aortic, pulmonary disease (pulmonary hypertension, alveolar hypoplasia, emphysema, asthma, chronic bronchitis), gastrointestinal dysmotility and obstruction, joint hypermobility, and macrothrombocytopenia.
Intelligent materials in future electronics

With the increasing demand for higher speed and performance of computers, a new concept of electron devices is indispensable for future electronics. Devices with intelligent materials meet such a demand and can simplify electronics, so that a system made of the devices can perform more complex functions close to those for the human brain and organisms. Intelligent materials are distinct from conventional materials in their characteristics, and they have the potential to become a dominant electronic-material in the future because of their various built-in functions. In this paper an important concept in the design of intelligent materials, called k-space engineering, is introduced. The k-space engineering, which manipulates the band structure of an existing material, is promising for future electron devices. >
Smart load management of plug-in electric vehicles in distribution and residential networks with charging stations for peak shaving and loss minimisation considering voltage regulation

New smart load management (SLM) approach for the coordination of multiple plug-in electric vehicle (PEV) chargers in distribution feeders is proposed. PEVs are growing in popularity as a low emission and efficient mode of transport against petroleum-based vehicles. PEV chargers represent sizeable and unpredictable loads, which can detrimentally impact the performance of distribution grids. Utilities are concerned about the potential overloads, stresses, voltage deviations and power losses that may occur in distribution systems from domestic PEV charging activity as well as from newly emerging charging stations. Therefore this study proposes a new SLM control strategy for coordinating PEV charging based on peak demand shaving, improving voltage profile and minimising power losses. Furthermore, the developed SLM approach takes into consideration the PEV owner preferred charging time zones based on a priority selection scheme. The impact of PEV charging stations and typical daily residential loading patterns are also considered. Simulation results are presented to demonstrate the significant performance improvement offered by SLM for a 1200 node test system topology consisting of several low-voltage residential networks populated with PEVs.
Research Integration Framework of Organizational Identity Change and Strategic Change in Subversive Situation

At present, the economy is developing rapidly, and the environment in which the organization is located is more and more highly dynamic, uncertain and even subversive, in order to maintain a sustainable competitive advantage, enterprises must carry out organizational strategic changes. The premise of successful strategic change is the realization of organizational identity change, and the change of organizational identity will also trigger the strategic change of an organization. This paper will explain the relationship between strategic change and organizational identity change, and summarize the subversive situations that lead to organizational identity change and strategic change.
Mathema cal model and math-heuris c for the aircra recovery problem

Recebido: 19 de novembro de 2019 Aceito para publicação: 1 de maio de 2020 Publicado: 22 de novembro de 2021 Editor de área: Li Weigang ABSTRACT The aircraft recovery problem (ARP) arises when unexpected events such as storms, airport closures, and unscheduled aircraft maintenance cause delays and/or flight cancellations, dismantling the original aircraft schedule. This work initially presents a mathematical model for the recovery of an airline schedule. Given the NP-Hard nature of the problem, the mathematical model cannot solve large instances. It has led to the development of a two-part math-heuristic: a mixed-integer programming network flow model to obtain a new schedule with minimum flight cancellations and delays; and an integer linear programming model to minimize flight aircraft exchanges from the original schedule. Applications of the heuristic to instances with up to 470 flights presented, in less than one minute of processing, results differing less than 0.5% from the optimal results, which allows to conclude that the heuristic qualifies for application to real cases of considerable size.
Isolating Transcutaneous Spinal Cord Stimulation Artifact to Identify Motor Response during Walking

The objective of this investigation was to demonstrate the applicability of a custom-developed EMD-Notch filtering algorithm to isolate the scTS-induced artifact from sEMG signals during walking in an individual with motor-incomplete SCI. Overall, the EMD-Notch filtering algorithm provides an effective approach to isolate the scTS artifact, extract the sEMG data, and further study the modulation of the spinal neuronal networks during dynamic activities.Clinical Relevance— This investigation will help with the modification of individualized scTS parameters to achieve task-specific neuromodulatory effects.