Miracle-dz/UniFAR-FTUs huggingface dataset:
Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012

AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004? 2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.
Role of RNA Biogenesis Factors in the Processing and Transport of Human Telomerase RNA

Telomerase RNA has long been considered to be a noncoding component of telomerase. However, the expression of the telomerase RNA gene is not always associated with telomerase activity. The existence of distinct TERC gene expression products possessing different functions were demonstrated recently. During biogenesis, hTR is processed by distinct pathways and localized in different cell compartments, depending on whether it functions as a telomerase complex component or facilitates antistress activities as a noncoding RNA, in which case it is either processed in the mitochondria or translated. In order to identify the factors responsible for the appearance and localization of the exact isoform of hTR, we investigated the roles of the factors regulating transcription DSIF (Spt5) and NELF-E; exosome-attracting factors ZCCHC7, ZCCHC8, and ZFC3H1; ARS2, which attracts processing and transport factors; and transport factor PHAX during the biogenesis of hTR. The data obtained revealed that ZFC3H1 participates in hTR biogenesis via pathways related to the polyadenylated RNA degradation mechanism. The data revealed essential differences that are important for understanding hTR biogenesis and that are interesting for further investigations of new, therapeutically significant targets.
DC fault ride through operation of a full-bridge MMC converter

In recent years the growth of renewable energy has encouraged the development of HVDC grids. One challenge of building HVDC grids is the power converter response to DC side faults. The full-bridge Modular Multilevel Converter (MMC) is a desired power converter topology which is used in HVDC grids due to its scalability, modularity and capability of blocking DC side faults. Post fault operation of the full-bridge MMC requires the control of power flow, the energy of each sub-module capacitor and the elimination of circulating harmonic current to reduce power loss while DC line-to-ground or DC line-to-line faults exist. This thesis presents a post fault operation method for a full-bridge MMC in order to transmit partial power after a DC line-to-ground fault and provides reactive power after DC line-to-line fault. Simulated results are provide from a point-to-point HVDC system which consists of two eleven-level full-bridge MMC.
Antimicrobial Effects of L-Chg10-Teixobactin against Enterococcus faecalis In Vitro

Objective: Teixobactin and its analogues are a new class of antibiotics that have no detectable bacterial resistance. This study was designed to determine the antibacterial and antibiofilm activities of a novel teixobactin analogue, L-Chg10-teixobactin, against two strains of Enterococcus faecalis (E. faecalis). Materials and Methods: The efficacy of L-Chg10-teixobactin against two strains of E. faecalis (ATCC 29212 and 47077) was determined using Clinical and Laboratory Standards Institute methods. L-Chg10-teixobactin was prepared at a stock concentration of 1 mg/mL in 5% DMSO. The minimum inhibitory concentration (MIC) was calculated using a two-fold serial broth dilution method, utilizing a 96-well plate. The minimum bactericidal concentration (MBC) was determined by plating the bacteria onto agar to define the concentration that resulted in 99.9% of bacterial death. Ampicillin was used as the control. The effect of L-Chg10-teixobactin on the inhibition of ATCC 47077 strain biofilm formation was determined by measuring the minimum biofilm inhibitory concentration (MBIC) using the safranin assay, while the eradication of the preformed biofilm was determined by measuring the minimum biofilm eradication concentration (MBEC) using the XTT assay. For nonlinear data, the log dose–response curve was plotted to calculate the optimum concentration using Excel (version 16.51, Microsoft® excel. 2021, Microsoft Corporation, Reymond, WA, USA). The data are presented as mean ± standard deviation (SD). Results: The MIC and MBC values of L-Chg10-teixobactin against both strains of E. faecalis were 0.8 μg/mL. The MIC of ampicillin was 1.25 μg/mL for ATCC 29212 and ranged from 1.25 to 5 μg/mL for ATCC 47077. The MBC of ampicillin for ATCC 29212 and ATCC 47077 was 10 and 20 μg/mL, respectively. The MIC and MBC of ampicillin were much higher compared with those of L-Chg10-teixobactin. The MBEC80 of L-Chg10-teixobactin was 4.60 μg/mL for ATCC 47077, which was much lower than that of ampicillin (20 μg/mL). Conclusions: L-Chg10-teixobactin demonstrated potent antibacterial and antibiofilm effects against E. faecalis, suggesting its potential role an effective antibacterial and antibiofilm agent in endodontic treatment.
Enhancing the Performance of Liquid State Machine with Time-Division Sampling and Reservoir Reconstructing

Remarkable progress has been made over the past few years on the performance of Spiking Neural Network (SNN), which is mostly driven by its biological features and used for pattern classification. However, the existing works on SNNs are challenged by high network complexity and training cost. As motivated by neuromorphic computation and certain features of human brains, Liquid State Machine (LSM) is put forward as a particular form of SNNs. LSMs are characterized by its short-term memory and lightweight computing, which is mostly contributed by its recurrently and randomly connected structure. In this paper, we proposed an improved LSM model on speech recognition using two promising techniques: time-division sampling and reservoir reconstruction. First, we proposed that dividing the output state from the liquid layer through multiple time windows, this approach is proven to explore more detailed input signal information. Second, the reconstructed structure of LSMs is investigated to extend the classification ability of LSMs, and two kinds of topologies of LSMs are served on the basis of parallel assembled liquids and a hub topology. FSDD and N-TIDIGITS datasets are used to demonstrate the performance improvement of proposed methods. Specifically, the classification accuracy of FSDD and N-TIDIGITS are 92%, 87%, respectively.
Strengthening Australia’s Chemical Regulation

Humans are exposed to a myriad of chemicals every day, some of which have been established to have deleterious effects on human health. Regulatory frameworks play a vital role in safeguarding human health through the management of chemicals and their risks. For this review, we focused on agricultural and veterinary (Agvet) chemicals and industrial chemicals, which are regulated, respectively, by the Australian Pesticides and Veterinary Medicines Authority (APVMA), and the Australian Industrial Chemicals Introduction Scheme (AICIS). The current frameworks have been considered fragmented, inefficient, and most importantly, unsafe in prioritizing human health. We evaluated these frameworks, identified gaps, and suggested improvements that would help bring chemical regulation in Australia in line with comparative regulations in the EU, US, and Canada. Several weaknesses in the Australian frameworks include the lack of a national program to monitor chemical residues, slow pace in conducting chemical reviews, inconsistent risk management across states and territories, a paucity of research efforts on human health impacts, and inadequate framework assessment systems. Recommendations for Australia include establishing a national surveillance and chemical residue monitoring system, harmonizing risk assessment and management across jurisdictions, improving chemical review efficiency, and developing regular performance review mechanisms to ensure that human health is protected.
Effects of Tea Treatments against High-Fat Diet-Induced Disorder by Regulating Lipid Metabolism and the Gut Microbiota

High-fat diet (HFD) may induce changes of metabolism and gut microbiota changes, and these changes are susceptible to diet adjustments such as tea treatment. However, the treatment effects may vary among different types of tea. In this study, we evaluated the effects of six types of tea on glucose and lipid metabolism and gut microbiota in HFD mice. We established HFD mouse model by 12 weeks feed with 60% fat diet, then treated with teas for six weeks. Here, we showed that treatment with different types of tea can inhibit weight gain and insulin resistance though different ways. Green tea regulated lipid metabolism by regulating the expression of adenosine 5′-monophosphate-activated protein kinase (AMPK) and carnitine palmitoyltransferase-I (CPT-1). The effect of dark tea and white tea in reducing liver weight seemed to be related to activities of acetyl-CoA carboxylase (ACC). Yellow tea exhibited the best anti-inflammatory and antioxidant effects and effects of recovering the disorder of model mouse microbiota. The decrease in blood sugar and the upregulation of gluconeogenesis-related enzymes seemed to be related to the decrement of unclassified Lachnospiraceae. These different effects may result from the unique chemical compositions contained by different types of tea, which can regulate different lipid and glucose metabolism-related proteins. Despite variations in its compositions and metabolic reactions, tea is a potent antiobesity and hypoglycemic agent.
Global profiling of lysine succinylation in human lungs

The lysine succinylation (Ksucc) is involved in many core energy metabolism pathways and affects the metabolic process in mitochondria, making this modification highly valuable for studying diseases related to mitochondrial disorders. In this paper, we used liquid chromatography with tandem mass spectrometry (LC‐MS/MS) to perform the first global profiling of succinylation in human lungs under normal physiological conditions. Using an MS‐based platform, we identified 1485 Ksucc sites in 568 proteins. We then compared these sites with those previously identified in human succinylome studies to investigate specific succinylated proteins and identify their possible functions in the lung and to explore the substrate preferences of succinylation modifiers in different cell lines and at different subcellular localizations. Our work expands the succinylation database and supplementary materials on the human succinylome and will thus help in further study of the function of Ksucc and regulation under related physiological and pathological conditions.
WINDMILLS DETECTION USING DEEP LEARNING ON SENTINEL SATELLITE IMAGES

Abstract. Automatic detection of objects from Earth Observation images is still a challenge for researchers. This paper aims at extracting automatically windmills on mid-resolution images (10-meter resolution), based on Sentinel satellite products. Sentinel-2 optical images are obvious candidates for our study. At 10-meter resolution, a windmill is represented with only a few pixels. We also start to consider Synthetic Aperture Radar (SAR) Sentinel-1 images but no particular windmill radar response on GRD (Ground Range Multi-look Detected) products seemed to be relevant.Considering the maturity of deep learning techniques for object detection in computer vision, we explore the use of deep neural networks for windmill detection on remote sensing images. For that purpose, we had to create the training data sets but we took advantage of the availability of many Sentinel images and of the use of automated labelling as the objects are georeferenced. The proposed approach relies on the U-Net framework, reformulating our problem of object detection in terms of semantic segmentation. We trained several neural networks on different data sets emanating from different countries. That enabled us to measure the performance of detection within a country but also across two countries (training on a country and predicting on another country). The results show the ability of detection of such small objects with respect to the resolution and we obtain various levels of performances depending on the trained and test data sets.
Electrostatic Discharge Simulation Using a GPU-Accelerated DGTD Solver Targeting Modern Graphics Processors

The presence of graphics processors (GPUs) in supercomputers constantly increased in the past decade. Finite-difference time-domain (FDTD) and discontinuous Galerkin time-domain (DGTD) are traditionally used on GPUs for their scalability; however, the limitations of past hardware required particular care in the implementation to obtain good performance. In this work, we discuss an implementation of DGTD for Maxwell’s equations on modern GPUs, and we assess its performance on the simulation of an electrostatic discharge.
Embedding Local Quality Measures in Minutiae-Based Biometric Recognition

Degradation in data quality is still a main source of errors in the modern biometric recognition systems. However, the data quality can be embedded in the recognition methods at global and local levels to build more accurate biometric systems. Local quality measures represent the quality of local parts within a biometric sample. They are either combined into a global quality measure or directly embedded into the recognition techniques. Minutiae-based comparison is the main and the most common technique used for fingerprint recognition and high-resolution palmprint recognition in various security and forensic applications. The focus of this thesis is mainly on direct incorporation of the local quality measures into the state-of-the-art minutiae-based recognition methods, particularly those based on Minutiae Cylinder-Code (MCC). Firstly, we introduce cylinder quality measures as a new type of local quality measures associated with the local minutiae descriptors. Then, we propose several methods for incorporating such local quality measures into the biometric systems, in order to improve their recognition performance. Among them is a novel and efficient quality-based consolidation method for embedding minutiae quality and cylinder quality measures in MCC based comparison methods. We also propose a supervised embedding method based on a binary classification model, which requires labeled minutiae for training. Finally, we apply a variant of the proposed consolidation method for the challenging case of latent fingerprint and palmprint identification with embedded subjective and objective minutiae quality.
Use of Low Melting Point Metals and Alloys (Tm < 420 °C) as Phase Change Materials: A Review

Phase Change Materials (PCMs) are materials that release or absorb sufficient latent heat at a constant temperature or a relatively narrow temperature range during their solid/liquid transformation to be used for heating or cooling purposes. Although the use of PCMs has increased significantly in recent years, their major applications are limited to Latent Heat Storage (LHS) applications, especially in solar energy systems and buildings. PCMs can be classified according to their composition, working temperature and application. Metallic PCMs appear to be the best alternative to salts and organic materials due to their high conductivity, high latent heat storage capacity and wide-ranging phase change temperature, i.e., melting temperature and chemical compatibility with their containers. This paper reviews the latest achievements in the field of low-melting point metallic PCMs (LMPM-PCMs), i.e., those with melting temperatures of less than 420 °C, based on Zn, Ga, Bi, In and Sn. Pure LMPM-PCMs, alloy LMPM-PCMs and Miscibility Gap Alloy (MGA) LMPM-PCMs are considered. Criteria for the selection of PCMs and their containers are evaluated. The physical properties and chemical stability of metallic PCMs, as well as their applications, are listed, and new application potentials are presented or suggested. In particular, the novel application of metallic PCMs in casting design is demonstrated and suggested.
Volumetric Analysis of Hearing-Related Structures of Brain in Children with GJB2-Related Congenital Deafness

Background: Children with non-syndromic hereditary sensorineural hearing loss (SNHL) provide an opportunity to explore the impact of hearing on brain development. Objective: This study investigates volumetric differences of key hearing-related structures in children with gap junction protein beta 2 GJB2-related SNHL compared to controls. Materials and methods: Ninety-four children with SNHL (n = 15) or normal hearing (n = 79) were studied using automated volumetric segmentation. Heschl’s gyrus (HG), anterior HG (aHG), planum temporale (PT), medial geniculate nucleus (MGN), and nucleus accumbens (NA) were analyzed relative to total brain volume (TBV) at two different age groups: (1) 7–12 months and (2) 13 months–18 years. Two-sided t-tests were used to evaluate differences between groups. Differences were considered significant if p < 0.007. Results: Significantly smaller aHG-to-TBV ratios were found in 13-month-to-18-year-old patients (p < 0.0055). HG-, PT-, MGN-, and NA-to-TBV ratios were smaller in the same age group, without reaching a significant level. Conversely, HG- and NA-to-TBV were larger in the younger age group. No significant differences were found between the groups for age and TBV. Conclusions: In this exploratory volumetric analysis of key hearing-related structures, we observed age-related changes in volume in children with GJB2-related SNHL.
Numerical characterisation of multi-layered CPW directional couplers

This paper presents a numerical characterisation of two 3 dB multi-layered CPW directional couplers, which were fabricated at King's College London. The quasi-TEM models of the couplers are studied with the help of a 2-dimensional finite element program. The characteristic impedances for both couplers obtained are in a good agreement with the values measured in the experiment.
Managing Sustainable Consumption: Shaping the Customer Journey with Focus on Sustainability in the Food Industry

As consumer awareness surrounding impacts of the climate crisis continues to be a notable threat, businesses are searching for new models to make their sustainability profile even better. As a result, the implementation of a company’s sustainability vision following the SDGs has to be linked closely to the integration of customers into strategic action. One success factor is the management of customers over their entire life cycle. The Customer Journey serves as a model to systematise this approach, by designing touchpoints throughout the purchasing process in order to motivate consumers to act sustainably. Based on behaviour models, the authors develop recommendations for the food industry to design a sustainable Customer Journey that helps to reduce the percentage of consumers reporting positive attitudes to sustainable products while not exhibiting corresponding behaviour.
Adopting a Companion Dog Helps Veterans with Posttraumatic Stress Disorder in a Pilot Randomized Trial

Despite significant treatment advances, many military veterans continue to suffer from posttraumatic stress disorder (PTSD) and associated symptoms, suggesting a need for new interventions. This pilot trial examined the change in psychological symptoms of 19 veterans in treatment for PTSD who were randomized either to adopt a dog immediately from a Humane Society shelter (n = 9) or to a three-month waitlist followed by dog adoption (n = 10). The dogs were companion dogs, not service animals. The investigators analyzed quantitative assessments using mixed regression models with repeated measures. All veterans also participated in periodic semi-structured interviews. The study results showed companion dog adoption to be a feasible adjunctive intervention that helped improve PTSD and depressive symptoms for most participants. These findings suggest that this is a promising approach that is worthy of further study.
Design of the Threshold-Controllable Memristor Emulator Based on NDR Characteristics

Due to the high manufacturing cost of memristors, an equivalent emulator has been employed as one of the mainstream approaches of memristor research. A threshold-type memristor emulator based on negative differential resistance (NDR) characteristics is proposed, with the core part being the R-HBT network composed of transistors. The advantage of the NDR-based memristor emulator is the controllable threshold, where the state of the memristor can be changed by setting the control voltage, which makes the memristor circuit design more flexible. The operation frequency of the memristor emulator is about 250 kHz. The experimental results prove the feasibility and correctness of the threshold-controllable memristor emulator circuit.
Tailoring of Multisource Deposition Conditions towards Required Chemical Composition of Thin Films

The model to tailor the required chemical composition of thin films fabricated via multisource deposition, exploiting basic physicochemical constants of source materials, is developed. The model is experimentally verified for the two-source depositions of chalcogenide thin films from Ga–Sb–Te system (tie-lines GaSb–GaTe and GaSb–Te). The thin films are deposited by radiofrequency magnetron sputtering using GaSb, GaTe, and Te targets. Prepared thin films are characterized by means of energy dispersive X-ray analysis coupled with a scanning electron microscope to determine the chemical composition and by variable angle spectroscopic ellipsometry to establish film thickness. Good agreement between results of calculations and experimentally determined compositions of the co-deposited thin films is achieved for both the above-mentioned tie-lines. Moreover, in spite of all the applied simplifications, the proposed model is robust to be generally used for studies where the influence of thin film composition on their properties is investigated.
Continuous User Identification

The objective of this work has been to investigate the possibility of implementing a Continuous Identification system using Behavioural Biometrics, taking advantage of the high acceptability and low cost offered by this method. The Behavioural Biometrics chosen for this work is Keystroke Dynamics. Continuous Identification is proposed to be performed after a user is locked out in a Continuous Authentication system, utilizing the same keystroke dynamics. Three features were considered when extracting the keystroke dynamics: duration, latency, and relative frequency of each keystroke action. The data was also categorized with respect to software context. Two distance metrics, namely Manhattan and Euclidean, were implemented and compared both via a Mean To Mean and via a One To Mean method. Two score fusion methods were utilized: weighted average mean with fixed weights and with variable weights. The analysis also included the effect of different data chunk sizes, simulating the number of actions before a user is locked out. Th best results obtained was rank-1 identification accuracy rate of 60% after 50 actions and 72% after 1000 actions, when using duration-latency combination, with no categorization, Mean To Mean comparison, and Manhattan Distance. This setting was then applied on the results from a Continuous Authentication system. To the best of our knowledge, this work is the first to address Continuous Identification based on Behavioural Biometrics.