Miracle-dz/UniFAR-FTUs huggingface dataset:
Microgrids-Based Approach for Voltage Control in Distribution Systems by an Efficient Sensitivity Analysis Method

High levels of renewable energy sources (RESs) in distribution networks have led to complex operational needs. The management of the network in microgrids (MGs) allows the implementation of effective and innovative management strategies. We propose a hybrid control strategy to maintain voltage levels within the operational limits using the RESs reactive and active power outputs. The proposed regulation strategy considers different MGs that are managed by different owners, who contribute to regulating the voltage on the distribution systems. In order to obtain an effective regulation, each MG can collaborate with the others. In the first instance, voltage is regulated inside MG using available distributed generation resources in correspondence of the bus of over/undervoltage is detected (stage 1). Next, more MGs can contribute to alleviating the problem involving other distributed generation resources (stage 2). The control method is based on sensitivity analysis, which allows selecting the appropriate distributed resources: we propose also a new method of calculating the sensitivity coefficients for radial and meshed networks. We demonstrate the effectiveness and the robustness of the proposed voltage control scheme using comparisons and representative studies by extensive simulations on two test networks performed by the proposed methodology. The results demonstrate the effectiveness of the control actions and the used algorithm.
A fundamental investigation of scaling up turbulent liquid-phase vortex reactor using experimentally validated CFD models

The velocity field in a macro-scale multi-inlet vortex reactor used in the Flash Nanoprecipitation process for producing functional nanoparticles was investigated using stereoscopic particle image velocimetry. Based on the experimental data, a simple model was proposed to describe the average velocity field within the reactor. In the model, the axial and azimuthal velocities could be well described by the combination of two co-flowing batchelor vortices. In this model, six dimensionless coefficients are identified by non-linear curve fitting, and their dependence on Reynolds number can be linearly described. This simple model is able to accurately predict the mean velocity field within the confined turbulent swirling flow based purely on Reynolds number.
A Multimodal Multilevel Neuroimaging Model for Investigating Brain Connectome Development

Abstract Recent advancements of multimodal neuroimaging such as functional MRI (fMRI) and diffusion MRI (dMRI) offers unprecedented opportunities to understand brain development. Most existing neurodevelopmental studies focus on using a single imaging modality to study microstructure or neural activations in localized brain regions. The developmental changes of brain network architecture in childhood and adolescence are not well understood. Our study made use of dMRI and resting-state fMRI imaging data sets from Philadelphia Neurodevelopmental Cohort (PNC) study to characterize developmental changes in both structural as well as functional brain connectomes. A multimodal multilevel model (MMM) is developed and implemented in PNC study to investigate brain maturation in both white matter structural connection and intrinsic functional connection. MMM addresses several major challenges in multimodal connectivity analysis. First, by using a first-level data generative model for observed measures and a second-level latent network modeling, MMM effectively infers underlying connection states from noisy imaging-based connectivity measurements. Second, MMM models the interplay between the structural and functional connections to capture the relationship between different brain connectomes. Third, MMM incorporates covariate effects in the network modeling to investigate network heterogeneity across subpopoulations. Finally, by using a module-wise parameterization based on brain network topology, MMM is scalable to whole-brain connectomics. MMM analysis of the PNC study generates new insights in neurodevelopment during adolescence including revealing the majority of the white fiber connectivity growth are related to the cognitive networks where the most significant increase is found between the default mode and the executive control network with a 15% increase in the probability of structural connections. We also uncover functional connectome development mainly derived from global functional integration rather than direct anatomical connections. To the best of our knowledge, these findings have not been reported in the literature using multimodal connectomics. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.
Simulation-based optimization of pump scheduling for drinking water distribution systems

Efficient Water Distribution Systems (WDSs) are crucial for modern society. Their operation requires large amounts of energy with significant financial impact for the utility providers. Existing solution methods are often oversimplified and can only solve the problem for very small, schematic networks. This article studies a pumping scheduling problem for WDSs in which, besides scheduling the operation of pumps over a planning horizon, several constraints regarding hydraulic properties are considered. The goal is to provide a pumping plan of minimum cost that satisfies all demand and respects operational and hydraulic constraints. This work proposes a nonlinear and non-convex formulation as well as a high-performance heuristic. The physical hydraulic behaviour is ensured via hydraulic simulation software. The present method significantly improved the best solutions for several benchmark instances by up to 17%. The solutions also reduce the energy consumed during peak periods, when the electrical grid is most strained.
Healthy relationship education programmes for young people: systematic review of outcomes

ABSTRACT The quality of romantic relationships is associated with mental health and wellbeing throughout the life course. A number of programmes have been developed to support young people in navigating healthy relationships, and a larger role for relationship education was recently formalised in statutory guidance in England. This study aimed to systematically review the evidence base for relationship education programmes. Evaluations of relationship education programmes for young people, including charting of outcome domains and measures, were reviewed, followed by a focussed synthesis of data from studies that included outcome domains of relevance to healthy relationships. Thirty-six studies of seven programmes were found that focussed on one or more outcomes relating to healthy relationship skills, knowledge and attitudes, none of which were assessed as high quality. All evaluated programmes were developed in the US, and only one evaluation was conducted in the UK. The evaluations had a diverse set of outcome domains and outcome measures, few had longitudinal measures. No evidence was found for young people’s involvement in programme or evaluation development. High-quality longitudinal evaluations and a core set of validated outcome measures are needed. This research also highlights the need to co-create programmes with young people, teachers and relationship experts that are feasible, acceptable and integrated into a mental health-informed curriculum
The Impact Of Mental Transformation Training Across Levels Of Automation On Spatial Awareness In Human-robot Interaction

objects places greater demand on the ability to mentally picture an abstract object, rotate the object, and picture the object again in a different perspective (Kass, Ahlers, & Dugger, 1998; Willis & Schaie, 1988). Accordingly, recent approaches to mental rotation training have attempted to remove either the unfamiliarity or abstract nature of the object that must be mentally rotated. For instance, success has been shown when training with a familiar or concrete
Assessing the Invasion Risk of Humulus scandens Using Ensemble Species Distribution Modeling and Habitat Connectivity Analysis

Given the rapid spread of invasive alien plant species in Europe and limited information regarding their distribution and dispersion patterns, we analyzed the invasive risk of Humulus scandens, a species with an increased invasive potential. We collected occurrence records from Romania within an EU funded project and literature data, in order to perform an ensemble distribution model. Environmental variables varied from downscaled topoclimatic continuous entries to categorical ones, such as soil class, texture, or land use. Results showed potential core areas of the species within the study region. By inverting the probability output of the models, we have created a resistance surface which helped us model its dispersion patterns. Further, we assessed the probability of invasion for each resulted corridor using the species dispersion ecology and created an invasion risk map. H. scandens is highly influenced by milder climates and areas with constant flooding events, thus we found that the Tisa basin and its tributaries can be under a high invasion risk, spreading through the entire catchment, in Central, Western, and Northern Romania, towards the Eastern Carpathians. The Danube acted as a dispersion corridor for major river systems in southern Romania, but the dispersion capability of the species dropped in steppe areas with higher aridity and limited water course network. This approach is useful for creating adequate action plans in relation to invasive alien plant species, and should urgently be regarded, as results show a potentially large distribution of H. scandens across entire water catchment areas, with devastating effects on natural ecosystems.
Intrinsically disordered N-terminal domain (NTD) of p53 interacts with mitochondrial PTP regulator Cyclophilin D

Mitochondrial permeability transition pore (mPTP) plays crucial roles in cell death in a variety of diseases, including ischemia/reperfusion injury in heart attack and stroke, neurodegenerative conditions, and cancer. To date, cyclophilin D is the only confirmed component of mPTP. Under stress, p53 can translocate into mitochondria and interact with CypD, triggering necrosis and cell growth arrest. However, the molecular details of p53/CypD interaction are still poorly understood. Previously, several studies reported that p53 interacts with CypD through its DNA-binding domain (DBD). However, using surface plasmon resonance (SPR), we found that full-length p53 (FLp53) binds to CypD with KD of ~1 μM, while both NTD-DBD and NTD bind to CypD at ~10 μM KD (Fig. 1C and 1D). Thus, instead of DBD, NTD is the major CypD binding site on p53. NMR titration and MD simulation revealed that NTD binds CypD with broad and dynamic interfaces dominated by electrostatic interactions. NTD 20-70 was further identified as the minimal binding region for CypD interaction, and two NTD fragments, D1 (residues 22-44) and D2 (58-70), can each bind CypD with mM affinity. Our detailed biophysical characterization of the dynamic interface between NTD and CypD provides novel insights on the p53-dependent mPTP opening and drug discovery targeting NTD/CypD interface in diseases.
Enabling Location-based Services using Wearable and Handheld

Smartphones, or more general handhelds, which are commonly used for indoor localization purposes, are not a viable option in places where people do not carry them all the time, e.g., home and oﬃce. Alternatively using wearable devices brings along limitations in regards to power supply, processing capability and availability of sensors, which prevents the adoption of many common handheld localization solutions. In this work a distributed localization system is presented, using wearable and handheld jointly, to address these drawbacks. Using only a magnetometer, an accelerometer, and Bluetooth radio, localization is performed by means of a particle ﬁlter. In addition, a smart handoﬀ mechanism is presented, which uses the wearable only when it is necessary, thus reduces energy consumption on the wearable without aﬀecting the desired location accuracy. Evaluating the system with ten participants, a localization accuracy of 90.31% in an indoor environment spanning about 320 square meters was achieved.
SARS-CoV-2 Mutations and COVID-19 Clinical Outcome: Mutation Global Frequency Dynamics and Structural Modulation Hold the Key

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had an enormous burden on the healthcare system worldwide as a consequence of its new emerging variants of concern (VOCs) since late 2019. Elucidating viral genome characteristics and its influence on disease severity and clinical outcome has been one of the crucial aspects toward pandemic management. Genomic surveillance holds the key to identify the spectrum of mutations vis-à-vis disease outcome. Here, in our study, we performed a comprehensive analysis of the mutation distribution among the coronavirus disease 2019 (COVID-19) recovered and mortality patients. In addition to the clinical data analysis, the significant mutations within the two groups were analyzed for their global presence in an effort to understand the temporal dynamics of the mutations globally in comparison with our cohort. Interestingly, we found that all the mutations within the recovered patients showed significantly low global presence, indicating the possibility of regional pool of mutations and the absence of preferential selection by the virus during the course of the pandemic. In addition, we found the mutation S194L to have the most significant occurrence in the mortality group, suggesting its role toward a severe disease progression. Also, we discovered three mutations within the mortality patients with a high cohort and global distribution, which later became a part of variants of interest (VOIs)/VOCs, suggesting its significant role in enhancing viral characteristics. To understand the possible mechanism, we performed molecular dynamics (MD) simulations of nucleocapsid mutations, S194L and S194*, from the mortality and recovered patients, respectively, to examine its impacts on protein structure and stability. Importantly, we observed the mutation S194* within the recovered to be comparatively unstable, hence showing a low global frequency, as we observed. Thus, our study provides integrative insights about the clinical features, mutations significantly associated with the two different clinical outcomes, its global presence, and its possible effects at the structural level to understand the role of mutations in driving the COVID-19 pandemic.
Unconventional energy sources: Safety impacts, opportunities, and economic challenges

ABSTRACT Unconventional hydrocarbon applications have been growing rapidly in recent years. Unconventional oil can be produced from oil sands, oil shale, extra heavy oil, gas to liquids (GTL), and other liquids. Conventional fossil energy will not be enough to meet the continuously increasing need for energy in the future. In this case, renewable energy sources will become important. Conventional oil sources are currently preferred because they are less expensive than unconventional sources. New technologies are being developed to reduce unconventional oil production costs.
Internet Access Possibilities in Bluetooth Low Energy Sensors

The purpose of this Master Thesis is to evaluate different solutions that enable Internet access to Bluetooth Low Energy sensor networks as well as provide an example implementation using one of the solutions evaluated. Three distinct solutions are observed from a set of attributes and applied to three different use cases of Bluetooth Low Energy sensor networks. The solutions evaluated are the HTTP Proxy Service, the GATT REST API, and 6LoWPAN applied to Bluetooth Low Energy devices. The new Bluetooth Mesh technology is also introduced and assessed for how it may affect the future of the three evaluated solutions and the Bluetooth enabled Internet of Things paradigm as a whole. A simplified version of the HTTP Proxy Service is implemented in a u-blox ODIN-W2 gateway device allowing HTTP messages to be sent via Bluetooth Low Energy. All three solutions are shown to have discrete means of controlling the flow of information in the networks, as well as varying in both complexity and security, proving each solution to excel for one of the three use cases assessed.
HDAC Inhibitor Sodium Butyrate Attenuates the DNA Repair in Transformed but Not in Normal Fibroblasts

Many cancer therapy strategies cause DNA damage leading to the death of tumor cells. The DNA damage response (DDR) modulators are considered as promising candidates for use in combination therapy to enhance the efficacy of DNA-damage-mediated cancer treatment. The inhibitors of histone deacetylases (HDACis) exhibit selective antiproliferative effects against transformed and tumor cells and could enhance tumor cell sensitivity to genotoxic agents, which is partly attributed to their ability to interfere with DDR. Using the comet assay and host-cell reactivation of transcription, as well as γH2AX staining, we have shown that sodium butyrate inhibited DNA double-strand break (DSB) repair of both endo- and exogenous DNA in transformed but not in normal cells. According to our data, the dysregulation of the key repair proteins, especially the phosphorylated Mre11 pool decrease, is the cause of DNA repair impairment in transformed cells. The inability of HDACis to obstruct DSB repair in normal cells shown in this work demonstrates the advantages of HDACis in combination therapy with genotoxic agents to selectively enhance their cytotoxic activity in cancer cells.
The battle of the game consoles: Utilizing Chernoff faces in modelling competitive dynamics between MNCs

This thesis reviews the research on multimarket competition and competitive dynamics, and contributes to the literature by examining how competition can be modeled in the global game consoles market between Microsoft Xbox 360 and Sony PlayStation 3. The empirical study is conducted by collecting data with the method of structured content analysis. The data is analyzed with quantitative methods. Specifically, I suggest that the visual statistical method of Chernoff faces can be used to help to counter some of the statistical issues related to data analysis. This thesis includes a theoretical contribution in the form of a conceptual framework of competitive behavior between a rival multinational firm dyad. Additionally the thesis addresses the methodology of competitive dynamic modeling. The empirical case suggests that the two game console manufacturers Sony and Microsoft compete with each other aggressively, concentrating especially on service and signaling actions. Although the first mover Microsoft has been more aggressive, Sony has been gaining on in sales volume, and the market is currently quite equally shared between the two companies. The future of the two game console giants depends on how well they can keep up with the forces of creative destruction in their hypercompetitive environment. The managers in the multinational firms should consider the competitive dynamics with their main competitors closely in order to ensure the success of the firms in the long term.
Breast Cancer Recognition Using Saliency-Based Spiking Neural Network

The spiking neural networks (SNNs) use event-driven signals to encode physical information for neural computation. SNN takes the spiking neuron as the basic unit. It modulates the process of nerve cells from receiving stimuli to firing spikes. Therefore, SNN is more biologically plausible. Although the SNN has more characteristics of biological neurons, SNN is rarely used for medical image recognition due to its poor performance. In this paper, a reservoir spiking neural network is used for breast cancer image recognition. Due to the difficulties of extracting the lesion features in medical images, a salient feature extraction method is used in image recognition. The salient feature extraction network is composed of spiking convolution layers, which can effectively extract the features of lesions. Two temporal encoding manners, namely, linear time encoding and entropy-based time encoding methods, are used to encode the input patterns. Readout neurons use the ReSuMe algorithm for training, and the Fruit Fly Optimization Algorithm (FOA) is employed to optimize the network architecture to further improve the reservoir SNN performance. Three modality datasets are used to verify the effectiveness of the proposed method. The results show an accuracy of 97.44% for the BreastMNIST database. The classification accuracy is 98.27% on the mini-MIAS database. And the overall accuracy is 95.83% for the BreaKHis database by using the saliency feature extraction, entropy-based time encoding, and network optimization.
LESSON STUDY IMPLEMENTATION OF INDONESIAN LANGUAGE LEARNING AT GRADE VII.5 MTsN LUBUK BUAYA PADANG

PELAKSANAAN LESSON STUDY DALAM PEMBELAJARAN BAHASA INDONESIA SISWA KELAS VII.5 MTsN LUBUK BUAYA PADANG Abstract This research started from less efectivity on learning teacher meet in religion ministry in Padang. The less teacher who available in each grade and there is no professional team of lesson study made learning less efficiense. This research intended to describe the implementation of plan, do and see lesson study in learning Indonesian at grade VII.5 MTsN Lubuk Padang. Further observer understands to the duties and responsibilities of classroom management by model’s teacher. Based on these findings it could be concluded that the implementation of lesson study still needs improvement in order to get better learning in the classroom. Keywords: lesson study implementation , learning , strateg y Abstrak Penelitian ini dimulai dari kurangnya efektifitas pertemuan pembelajaran guru dalam pelayanan agama di Padang. Semakin sedikit guru yang tersedia di setiap kelas dan belum adanya tim profesional lesson study agar kegiatan pembelajaran lebih efisien. Penelitian ini dimaksudkan untuk menggambarkan pelaksanaan rencana, lakukan dan lihat dalam lesson study dalam pembelajaran bahasa Indonesia di kelas VII.5 MTsN Lubuk Padang. Selanjutnya pengamat memahami tugas dan tanggung jawab pengelolaan kelas oleh guru model. Berdasarkan temuan tersebut dapat disimpulkan bahwa pelaksanaan lesson study masih perlu perbaikan untuk mendapatkan pembelajaran yang lebih baik di kelas. Kata Kunci : pelaksanaan lesson study , pembelajaran , strateg i
Open and short U‐shaped microstrip resonators for second‐order single‐ or dual‐bandstop filter design

Single‐ and dual‐band bandstop filters with U‐shaped resonators are proposed. First, short and open U‐shaped resonators are coupled to a main transmission line to obtain second‐order stopband performance with two transmission zeros in the stop band and two reflection zeros in the passband. In contrast to traditional second‐order bandstop filters, the two different resonators are coupled to both sides of the microstrip line so that the commonly used quarter wavelength distance between resonators is eliminated. Secondly, open and short U‐shaped stepped impedance resonators are employed to obtain dual‐band bandstop filters in a compact size. Both filters are prototyped and measured. Good agreement between simulated and measured results demonstrates the reliability of the design method. © 2017 Wiley Periodicals, Inc. Microwave Opt Technol Lett 59:1362–1365, 2017