Miracle-dz/UniFAR-FTUs huggingface dataset:
An Application of State Estimation to Short-Term Load Forecasting, Part I: Forecasting Modeling

A precise short-term forecasting method for estimating the status of systems is required for on-line real-time control of complex power systems. In this paper, some state estimation type modelings of load forecasting are introduced, and a few practical problems for applying state estimation are discussed. In [11] the identification algorithms of the covariance matrices of system and observation noise are developed using observed data series, and their experimental results by simulation model are discussed. Results show that forecasting error by the developed method is quickly converged to minimum error of the ideal state estimation with previously known noise properties.
Event and Entity Coreference Across Five Languages: Effects of Context and Referring Expression

Current work on coreference focuses primarily on entities, often leaving unanalysed the use of anaphors to corefer with antecedents such as events and textual segments. Moreover, the anaphoric forms that speakers use for entity and event coreference are not mutually exclusive. This ambiguity has been the subject of work in English, with evidence of a split between comprehenders’ preferential interpretation of personal versus demonstrative pronouns. In addition, comprehenders are shown to be sensitive to antecedent complexity and aspectual status, two verb-driven cues that signal how an event is being portrayed. Here we extend this work via a comparison across five languages (English, French, German, Italian, and Spanish). With a story-continuation experiment, we test how different referring expressions corefer with entity and event antecedents and whether verbal features such as argument structure and aspect influence this choice. Our results show widely consistent, not categorical biases across languages: entity coreference is favoured for personal pronouns and event coreference for demonstratives. Antecedent complexity increases the rate at which anaphors are taken to corefer with an event antecedent, as does portraying an event as completed though the latter does not reach significance. Lastly, we report a comparison of the same referring expressions to refer to entity and event antecedents in a trilingual parallel corpus annotated with coreference. Together, the results provide a first crosslingual picture of coreference preferences beyond the restricted entity-only patterns targeted by most existing work on coreference. The five languages are all shown to allow gradable use of pronouns for entity and event coreference, with biases that align with existing generalizations about the link between prominence and the use of reduced referring expressions. The studies also show the feasibility of manipulating targeted verbdriven cues across multiple languages to support crosslingual comparisons.
Apotential role for psilocybin in the treatment of obsessive-compulsive disorder

The recent revivification of interest in the therapeutic use of psychedelics has had a particular focus on mood disorders and addiction, although there is reason to think these drugs may be effective more widely. After outlining pertinent aspects of psilocybin and obsessive-compulsive disorder (OCD), the current review summarizes the evidence indicating that there may be a role for psilocybin in the treatment of OCD, as well as highlighting a range of potential therapeutic mechanisms that reflect the action of psilocybin on brain function. Although the current evidence is limited, that multiple signals point in directions consistent with treatment potential, alongside the psychological and physiological safety of clinically administered psilocybin, support the expansion of research, both in animal models and in further randomized controlled trials, to properly investigate this potential.
Probabilistic wind power forecasts using local quantile regression

Wind power forecasts are in various ways valuable for users in decision-making processes. However, most forecasts are deterministic, and hence possibly important information about uncertainty is not available. Complete information about future production can be obtained by using probabilistic forecasts, and this article demonstrates how such forecasts can be created by means of local quantile regression. The approach has several advantages, such as no distributional assumptions and flexible inclusion of predictive information. In addition, it can be shown that, for some purposes, forecasts in terms of quantiles provide the type of information required to make optimal economic decisions. The methodology is applied to data from a wind farm in Norway. Copyright © 2004 John Wiley & Sons, Ltd.
An analytical model for the determination of resonance frequencies of perforated beams

In this paper, we develop closed expressions for the equivalent bending and shear stiffness of beams with regular square perforations, and apply them to the problem of determining the resonance frequencies of slender, regularly perforated clamped–clamped beams, which are of interest in the development of MEMS resonant devices. We prove that, depending on the perforation size, the Euler–Bernoulli equation or the more complex shear equation needs to be used to obtain accurate values for these frequencies. Extensive finite element method simulations are used to validate the proposed model over the full practical range of possible hole sizes. An experimental verification of the model is also presented.
Design and construction of hardware and software for autonomous observations of Transient Luminous Events

Transient luminous events (TLE) are phenomena which are currently on the rise in terms of sightings. However, there is no widespread uniform method of their observation and subsequent image processing. Therefore, our project focuses on the design and construction of hardware that can record TLE. It consists of a low gain, colour, CMOS camera with a bright, wide lens connected to a small, power-efficient single board computer. The project also includes writing software to control the hardware. The software decides whether to capture or not and at what orientation there is the biggest chance to capture a TLE. The software can process and classify the created photos based on deep neural networks. As a final product, we have developed the whole apparatus from a hardware and software point of view and installed it at the Astronomical Observatory at Kolonica Saddle in Slovakia, Central Europe. The plan for the future is to make similar apparatuses to spread the observation network.
Facilities Management and Changing Professional Boundaries

Considers the relationship between the emerging facilities management discipline and the existing building‐related professions. Defines facilities management and argues that it is impossible for the facilities manager to become expert in every area of responsibility. Facilities management must help to integrate the work of specialists in the many distinct areas involved. Discusses the issue of co‐ordinated professional qualifications.
A COMPARATIVE STUDY OF YOLO AND SSD OBJECT DETECTION ALGORITHMS

: Object detection is one of the most important and challenging branches of computer vision, which has been widely applied in people’s life, such as monitoring security, autonomous vehicle driving and so on, with the purpose of locating instances of semantic objects of a certain class. In order to understand the main development status of object detection pipeline, thoroughly and deeply, in this survey, we first examine the existing methods of typical detection models and describe the benchmark datasets. This project describes the role of deep learning techniques based on convolutional neural network for object detection. Deep learning techniques for state-of-the-art object detection systems are assessed in this project. A computer views all types of visual media as an array of numerical values. As a consequence, they require image processing algorithms to inspect contents of images. This project compares two major object detection algorithms: Single Shot Detection (SSD) and You Only Look Once (YOLO) to find the fastest and most efficient of the two. In this comparative analysis, using the COCO (Common Object in Context) dataset, the performance of these two algorithms is evaluated and their strengths and limitations are analysed based on parameters such as accuracy, precision and speed. From the analysis of results, it can be concluded that in an identical testing environment, YOLO-v3 performs better than SSD.
AN ANALYSIS THE MEAT PRODUCTION AND CONSUMPTION PATTERN: A CASE STUDY OF BALOCHISTAN SELECTED DISTRICTS

In order to explore the production and consumption pattern of red meat three districts namely, Killa Saifullah, Pishin and Jaffarabad of Balochistan were selected randomly.300 hundred respondents were selected. Well-structured questionnaire was used. Cronbach's Alpha program was 0.84. to 0. 81.Chi-Square test was applied and the p-value was considered significant at p<0.01. Results revealed more than (53%) of the respondents fell into the age group of 36 to 45. While most (44%) of the respondents were acquainted with religious schooling. More than half (55%) of the respondents belonged from married categories. Chi-Square technique about the production and consumption pattern of red meat based on (p ≤0.01) was used. Highly statistically variations were observed regarding the production and consumption pattern as district-wise. Based on the results following recommendation has been developed. Government should be encouraging the new emerging technologies in the livestock sector and livestock farmers should adopt different methods and Pak. Journal of Int’L Affairs, Vol 4, Issue 3 (2021) An Analysis the Meat Production and . 770 approaches for animal breeding so as to increase the livestock production. Government should promote the integrated livestock approaches and system within terms of real practices shape and mode.
In the Trenches of the Solar-stellar Connection. V. High-resolution Ultraviolet and X-Ray Observations of Sun-like Stars: The Curious Case of Procyon

A joint X-ray (0.2–2 keV) and ultraviolet (1150–3000 Å) time-domain study has been carried out on three nearby bright late-type stars, bracketing the Sun in properties. Alpha Cen A (HD 128620: G2 V) is a near twin to the Sun, although slightly more massive and luminous, slightly metal-rich, but older. Alpha Cen B (HD 128621: K1 V) is cooler than the Sun, somewhat less massive and lower in luminosity. Procyon (HD 61421: F5 IV–V) is hotter, more massive and more luminous than the Sun, half the age, but more evolved. Stellar observations were from Chandra X-ray Observatory and Hubble Space Telescope (HST). The Sun provided a benchmark through high-energy spectral scans from solar irradiance satellites and novel high-dispersion full-disk profiles of key UV species—Mg ii, C ii, and Si iv—from the Interface Region Imaging Spectrograph. Procyon’s flux history was strikingly constant at all wavelengths, in contrast to the other three cycling-dynamo stars. Procyon also displays a strong subcoronal (T ∼ 1 × 105 K) emission excess, relative to chromospheric Mg ii (T ≲ 104 K), although its X-rays (T ∼ 2 MK) appear to be more normal. At the same time, the odd sub-Gaussian shapes, and redshifts, of the subgiant’s “hot lines” (such as Si iv and C iv) are remarkably similar to the solar counterparts (and α Cen AB). This suggests a Sun-like origin, namely a supergranulation network supplied by magnetic flux from a noncycling “local dynamo. ”
A Finite Element Modelling Investigation of Lower Leg Injuries

A detailed finite element (FE) model has been developed of the human lower leg in order to investigate the mechanisms that cause severe ankle injuries in frontal impacts. Predictions from the model have been validated against the results from two separate sets of subinjurious and injurious post mortem human subjects (PMHS) tests. The model correlated well against the test results and it was estimated that a predicted von Mises stress of 120 MPa correlates to a predicted risk of injury to the calcaneus and talus bones in the model. A series of predictive model runs were also carried out to investigate the influence that environmental and subject variations have on the predicted injury risk of the ankle. The set-up of all these model runs were based on sled impact tests in which PMHS legs were mounted on a sled rig with the feet resting on a heel and mid-foot pad. The environmental investigations included model runs with and without the heel pad and loading the foot in eversion and a neutral position. Subject variations investigated the influence that the stiffness of the ligaments joining the mid-foot to the hind-foot have on the predicted injury risk. Without the heel pad there was considerable dorsiflexion of the foot and a predicted increased injury risk to the neck of the talus and a reduced injury risk to the calcaneus. Loading the foot in eversion it was predicted that the greatest injury risk was to the lateral aspect of the talus where the lateral malleolus of the fibula articulates with the talus. Increasing the ligament stiffness reduced the shearing motion in the joints between the mid-foot and the hind-foot and there was an increased injury risk to the neck of the talus.
Deep learning based models to study the effect of glaucoma genes on angle dysgenesis in-vivo

Abstract Objective: To predict the presence of Angle Dysgenesis on Anterior Segment Optical Coherence Tomography (ADoA) using deep learning and to correlate ADoA with mutations in known glaucoma genes. Design: A cross-sectional observational study. Participants: Eight hundred, high definition anterior segment optical coherence tomography (ASOCT) B-scans were included, out of which 340 images (One scan per eye) were used to build the machine learning (ML) model and the rest were used for validation of ADoA. Out of 340 images, 170 scans included PCG (n=27), JOAG (n=86) and POAG (n=57) eyes and the rest were controls. The genetic validation dataset consisted of another 393 images of patients with known mutations compared with 320 images of healthy controls Methods: ADoA was defined as the absence of Schlemm's canal(SC), the presence of extensive hyper-reflectivity over the region of trabecular meshwork or a hyper-reflective membrane (HM) over the region of the trabecular meshwork. Deep learning was used to classify a given ASOCT image as either having angle dysgenesis or not. ADoA was then specifically looked for, on ASOCT images of patients with mutations in the known genes for glaucoma (MYOC, CYP1B1, FOXC1 and LTBP2). Main Outcome measures: Using Deep learning to identify ADoA in patients with known gene mutations. Results: Our three optimized deep learning models showed an accuracy > 95%, specificity >97% and sensitivity >96% in detecting angle dysgenesis on ASOCT in the internal test dataset. The area under receiver operating characteristic (AUROC) curve, based on the external validation cohort were 0.91 (95% CI, 0.88 to 0.95), 0.80 (95% CI, 0.75 to 0.86) and 0.86 (95% CI, 0.80 to 0.91) for the three models. Amongst the patients with known gene mutations, ADoA was observed among all the patients with MYOC mutations, as it was also observed among those with CYP1B1, FOXC1 and with LTBP2 mutations compared to only 5% of those healthy controls (with no glaucoma mutations). Conclusions: Three deep learning models were developed for a consensus-based outcome to objectively identify ADoA among glaucoma patients. All patients with MYOC mutations had ADoA as predicted by the models.
Learning and teaching technology options

Education should play an important role in improving European Union (EU) status in the context of stagnated GDP growth, very high unemployment rates, and an aging workforce. Although educational technology is expected to contribute to improving education in the EU, compelling evidence of the benefits of technology on education remains elusive. In the current Network Society, the relevant question is not if governments should invest in educational technology but how governments should allocate funding in order to add more value to the educational system through technology. Educational technology encompasses a wide array of technologies and methodologies that are shaped by stakeholders’ behaviours and affected by contextual factors that, if adequately mixed, can contribute to students and teachers better achieving their goals. Such a wide and complex task cannot be addressed by a simple and single intervention. Comprehensive on-going policies are required, covering technology, methodology, economic and regulatory aspects; in addition, such policies are dependent on strong stakeholder engagement. This is a new process where we must learn by doing; therefore, carefully assessing the results of the different interventions is crucial to ensuring success. The following topics are analysed in this report: emerging educational technologies, new ways of teaching and learning fostered by those technologies, the role of different educational stakeholders, and other contextual considerations. Based on the analysis, and taking into account the challenges facing Europe, several policy options are proposed and assessed. We expect that this report will support EU policy-makers to define educational technology policies to adequately respond to the needs of the EU. STOA Science and Technology Options Assessment Learning and teaching technologies options
Theoretical aspects of control of synchronous reluctance machines

The author presents a theoretical performance analysis of several control strategies for synchronous reluctance machines which are being fed from a current controlled inverter. The three main control strategies considered have as their objectives to allow maximum rated torque, maximum rate of change of torque and maximum power factor, respectively, from the machine. These control strategies are investigated to determine their limitations and inter-relationships. A technique for 'field weakened' control of the machine is developed. It is shown that the rate of change of torque performance of the control strategies based on constant current angle is poor at lower angular velocities. A control strategy based on having constant current in the most inductive axis of the machine is shown to give better performance under these conditions, and a technique for moving between control strategies is developed. >
Development of design rainfalls: A review

Design rainfalls are essential parameters in designing and assessing combined and stormwater sewers and are still used today. They create idealized intensity profiles with statistically determined parameters. Their gradual development is based on the development of computer technology, measuring instruments, and measurement campaigns’ progress. However, climate change is causing changes in precipitation events’ characteristics, so it is important to focus on reassessing them and adapting to current conditions. The paper summarizes the knowledge about the development of design rains to reveal their potential for the future.
Genetic identity of mint cultivars after in vitro conservation, assessed by ISSR primers

The species of the genus Mentha have been known since ancient times and have significant value in the pharmaceutical, cosmetic and food industries, as well as in medicine. For the widespread use of mint, including in a variety of breeding programs, and the preservation of genetic diversity, effective methods of maintaining cultivars and collection samples are required. Thanks to the development of biotechnological methods, in particular, the creation of slow-growing collections, are now actively used as an effective alternative to field collections. It is known that the cultivation of tissues and organs on artificial culture media can cause somaclonal variability. The purpose of this work is to study the effect of in vitro storage at 4-6°C without illumination after 3 and 4 in vitro conservation cycles on the genetic stability of three cultivars of mint Azhurnaya, Bergamotnaya and Zagrava using ISSR primers. 1 cycle: 1 year of in vitro conservation, microcutting and 2 subcultures of regrowth in a culture room. After conservation, the number of viable explants was 70.0-82.1%. Callus formation at the base of the shoots was not observed in any of the cultivars. After 3 and 4 cycles of in vitro conservation, genetic stability was assessed using 11 ISSR primers. It was found that all three mint genotypes showed full compliance (length and number of amplicons) with the profiles of control samples for all studied markers. It was also found that the markers used by ISSR are highly informative for mint cultivars.
CHARACTERISTICS OF PHOTOVOLTAIC MODULES IN VARIOUS CONFIGURATIONS FOR PARTIAL SHADING CONDITIONS

Partial shading conditions (PSCs) can cause a significant reduction in energy output in photovoltaic (PV) systems. This paper recounts the characteristics of PV in various condition of PCSs. The compared PV characteristics involve voltage, current, generated power, fill factor, mismatching loss, and efficiency. Six configurations of the PV system are used in this research namely Series-Parallel (SP), Honey Comb (HC), Total Cross Tied (TCT), Bridge Linked Honey Comb (BLHC), Bridge Linked Total Cross Tied (BLTCT), and Series-Parallel Total Cross Tied (SPTCT). The PSCs are considered uniform, short and narrow, long and narrow, long and wide, short and wide, and corner. The result indicates that TCT configuration is the best configuration among others then followed by the BLHC, BLTCT, SPTCT, HC, and SP configurations.
Application of partial least squares near-infrared spectral classification in diabetic identification

In order to identify the diabetic patients by using tongue near-infrared (NIR) spectrum，a spectral classification model of the NIR reflectivity of the tongue tip is proposed, based on the partial least square (PLS) method. 39sample data of tongue tip’s NIR spectra are harvested from healthy people and diabetic patients , respectively. After pretreatment of the reflectivity, the spectral data are set as the independent variable matrix, and information of classification as the dependent variables matrix, Samples were divided into two groups，i.e. 53 samples as calibration set and 25 as prediction set，then the PLS is used to build the classification model The constructed modelfrom the 53 samples has the correlation of 0.9614 and the root mean square error of cross-validation (RMSECV) of 0.1387. The predictions for the 25 samples have the correlation of 0.9146 and the RMSECV of 0.2122. The experimental result shows that the PLS method can achieve good classification on features of healthy people and diabetic patients.
Aspects of Computer Simulation of Liquid-Fueled Combustors

An existing ''discrete droplet'' model of liquid sprays has been extended to include a stochastic representation of turbulent dispersion effects. Applications to simple test cases, including the dispersion of single particles, produce reasonable agreement. However, two further applications involving volatile and combusting sprays show that the turbulent dispersion effects are small in comparison to those due to uncertainties about the initial conditions of the spray.