Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-Temporal Decomposition and Coordination for Distributed Load Restoration in AC/DC Hybrid System

A new spatio-temporal decomposition and coordination scheme is proposed for load restoration in an AC/DC hybrid transmission system. First, the framework of spatio-temporal decomposition is built for load restoration, the decoupled variables and spatial and temporal coordinators are defined, as well as two interactive blocks. Furthermore, the spatio-temporal decomposed models of subsystems and HVDC links are constructed considering security constraints and HVDC operation characteristics. Finally, a new hierarchical overlapping coordination based analytical target cascading (HOC_ATC) algorithm is developed to coordinate the decomposed models by iterative calculations between subsystems and coordinators, as well as the two interactive blocks. The proposed distributed scheme maintains independent operations of subsystems, and handles the multi-step restoration process by iteratively calculating single-step models. The developed HOC_ATC algorithm provides tractable and efficient computation for the HVDC model incorporated load restoration optimization. The effectiveness of the proposed method is validated using two IEEE test systems, showing improved computational efficiency and better convergence ability.
Modeling Submarket Effect for Real Estate Hedonic Valuation: A Probabilistic Approach

It is critical for urban planners and real estate developers to understand how the built environment and house characteristics are valued in housing market. However, this problem is challenging because of the existence of the submarket effect resulted from the heterogeneity nature of city. In this paper, we propose a probabilistic approach to residential property hedonic valuation problem modeling the full scope of submarket effect based on built environment and house characteristics. Specifically, we introduce a latent variable representing housing submarket and model both of the submarket criteria and hedonic price model(HPM) into a Bayesian network. Utilizing the probabilistic dependencies in the Bayesian network, our model is able to capture the full scope of the submarket effect. Furthermore, to analyze the relationship among the discovered submarkets, we propose a probabilistic hierarchical clustering method to infer the hierarchical structure of housing market. In particular, we perform Bayesian hypothesis testings to find the most similar submarkets and agglomerate submarkets step-by-step, thus revealing the hierarchical structure of housing market. Finally, we conduct comprehensive experiments in the housing market of Nanjing which is a metropolis in eastern China. The experimental results demonstrate the effectiveness of our proposed modeling method.
Nucleic Acid-Based Therapy: Development of a Nonviral-Based Delivery Approach

Gene therapy returns to the center stage of medicine to treat patients with diseases that are unable to be cured with the conventional therapeutic strategies. This development is due to various reasons, including vector development and significant achievement in next- generation sequencing. Among the various methodologies of gene therapy, nucleic acid-based therapy has been considered to be promising in various diseases. The development of delivery methods to target cells in vivo , however, remains critical. These include viral vector-based and nonviral vector-based gene delivery methods as well as physical approaches such as hydrodynamic gene delivery (HGD). HGD is a simple and effective in vivo gene transfer method for the functional analysis of therapeutic genes and regula-tory elements in small animals. Moreover, this chapter outlines the principle of HGD, gene expression studies in rodents, and recent advances in clinical application of HGD and provides future perspectives in developing a safe and efficient method for nucleic acid- based therapy.
Proportional-Derivative Voltage Control With Active Damping for DC/DC Boost Converters via Current Sensorless Approach

This brief presents an advanced proportional-derivative (PD) voltage control mechanism for DC/DC boost converters suffering from the parameter and load variations. The proposed controller eliminates the requirement for current feedback by designing the first-order observer estimating the voltage derivative without the use of converter parameters, which corresponds to the first contribution. As another contribution, a specific feedback gain structure for PD-loop and the active damping component guarantees the first-order closed-loop transfer function from the reference to the output voltage by the stable pole-zero cancellation. A prototype bi-directional 3-kW boost converter experimentally validates the closed-loop performance of the proposed technique.
Transformational Leadership Qualities Among Students Within Doctoral Higher Education Leadership Programs

TRANSFORMATIONAL LEADERSHIP QUALITIES AMONG STUDENTS WITHIN DOCTORAL HIGHER EDUCATION LEADERSHIP PROGRAMS Joshua Lee Howell Old Dominion University, 2020 Director: Dr. Dennis E. Gregory Transformational Leadership Qualities Among Students Within Doctoral Higher Education Leadership Programs is a mixed-method study utilizing program evaluation of course descriptions and transformational leadership fostering activities, interviews with program chairs surrounding transformational leadership fostering activities, and completion of the Multifactor Leadership Questionnaire (MLQ-5xTM) survey results from doctoral higher education students and their programs within the Commonwealth of Virginia. Researchers in the field of Higher Education and Leadership indicated that Transformational Leadership was more apt for college and university presidency, that doctoral degrees were more preferable for college and university presidency, and as doctoral higher education programs provide students with curriculum geared toward college and university leadership training, these programs may be seen as a training ground for the nation’s future college and university presidents. Transformational Leadership is defined as “an exceptional form of influence that moves followers to accomplish more than what is usually expected of them. It is a process that often incorporates charismatic and visionary leadership” (Northouse, 2016, p. 161). This study aimed to address not only current Transformational Leadership measurement of doctoral higher education students through the MLQ-5xTM, but also how their corresponding programs are seen by program chairs in charge of these programs, and how the programs are described through program websites. This study investigated the only five public doctoral higher education programs in the Commonwealth of Virginia and surveyed a total of thirty students across these programs. These individuals self-rated using the MLQ-5x and were peer-rated by colleagues to enhance validity of results. Themes surrounding how these programs are administered were collected, and findings suggest that while students are in fact above average regarding transformational leadership, there is no correlation between student transformational leadership scores and program offerings.
Wnt activator FOXB2 drives prostate cancer neuroendocrine differentiation

The Wnt signaling pathway is of paramount importance for development and disease. However, the tissue-specific regulation of Wnt pathway activity remains incompletely understood. Here we identify FOXB2, an uncharacterized forkhead box family transcription factor, as a potent activator of Wnt signaling in normal and cancer cells. Mechanistically, FOXB2 induces the non-classical Wnt ligand WNT7B, which increases TCF/LEF-dependent transcription without activating LRP6 or β-catenin. Proximity ligation and RNA interference identified YAP1, JUN, and DDX5 as transcriptional co-regulators required for FOXB2-dependent Wnt activation. Although FOXB2 expression is limited in adults, it is induced in select cancers, particularly advanced prostate cancer. RNA-seq data analysis suggests that FOXB2/WNT7B expression in prostate cancer is associated with a transcriptional program that favors neuronal differentiation and decreases recurrence-free survival. Consistently, FOXB2 is induced during neuroendocrine transformation of LNCaP prostate carcinoma cells, and conversely, FOXB2 overexpression is sufficient to induce their differentiation. Our results suggest that FOXB2 is a tissue-specific Wnt enhancer that promotes prostate cancer malignant transformation.
Teacher-child interaction initiated with children’s questions

This paper presents a round of research conducted with the aim of determining the characteristics of interaction situations involving pre-schoolers and their teachers and initiated with children? s questions. Insight into the existing body of research shows that there is a lack of similar studies, which address the cognitive side of such situations, but where the social aspect is neglected. Systematic observation was used to describe interaction situations in preschools initiated by children aged three to six years asking teachers questions. Qualitative and quantitative data analysis was performed, indicating consistency between the type of the child? s question, the teacher? s answer and the course of the interaction. After children receive answers to their questions requesting new information (cognitive questions) or those intended to create conditions necessary for particular activities (action-related questions), interaction ends. On the other hand, children ask so-called social questions for the sake of interaction, and it depends on the teacher? s reply whether they will develop. Another finding suggests that children? s questions are not automatically welcome at just any moment, especially if they go beyond the limits of the teacher guided activity in progress at the time the question is asked. The research findings afford remarkable insight into how preschool teachers with their different adequate responses and behaviours can support children? s development and learning in children- initiated interaction situations.
Response of lentil to high temperature under variable water supply and carbon dioxide enrichment

Lentil (Lens culinaris Medik.) production in arable, Mediterranean-type climates is limited by heat waves and unreliable rainfall. Under climate change scenarios, increased atmospheric carbon dioxide (CO2) concentration will increase plant growth; however, the net effect of increasing occurrence and intensity of heat waves and drought is unclear. This study tested the response of combined acute high temperature (>32°C) at the early pod-filling stage and (i) crop-available soil water, and (ii) elevated CO2 on three lentil genotypes in two experiments. The three lentil genotypes selected were commercial cultivar PBA Bolt and two landraces sourced from the Australian Grains Genebank, AGG 71457 and AGG 73838. High soil-water availability (0.42 Mg m–3) throughout the growing season increased yield by 28% compared with low soil-water availability (0.35 Mg m–3). Across contrasting water treatments, there was no difference in patterns of crop response to high temperature during the early pod-filling phase (5 days at 42°C daytime, 25°C night), where yields were reduced by 45%. A significant interaction between high temperature response and genotype was observed, where reduction in grain number was higher for AGG 73838 (0.20% per degree-hour >32°C) than for AGG 71457 (0.07% per degree-hour >32°C) or PBA Bolt (0.10% per degree-hour >32°C). For heat and CO2 effects, there was no significant interaction between high temperature (3 days at 38°C daytime, ambient night temperature) and CO2 treatment on yield components. There was, however, an overall trend of increased biomass, grain number and yield due to elevated CO2. Although non-limiting soil water did not reduce the impact of high temperature in this study, the range in response across genotypes to high temperature supports opportunity for increased adaptation of lentil toward increasing yield stability under effects of climate change.
Nepotism vs. Intergenerational Transmission of Human Capital in Academia (1088--1800)

We argue that the waning of nepotism in academia bolstered scientific production in pre-industrial Europe. We build a database of families of scholars (1088-1800), measure their scientific output, and develop a general method to disentangle nepotism from inherited human capital -two determinants of occupational persistence. This requires jointly addressing measurement error in human capital proxies and sample selection bias arising from nepotism. Our method exploits multi-generation correlations together with parent-child distributional differences to identify the structural parameters of a first-order Markov process of human capital transmission with nepotism. We find an intergenerational human capital elasticity of 0.59, higher than that suggested by parent-child elasticities, yet lower than multi-generation estimates ignoring nepotism. On average, 16 percent of scholars' sons achieved their position because of nepotism. Nepotism was lower in science than in law and in Protestant than in Catholic institutions, and declined during the Scientific Revolution and the Enlightenment---two periods of buoyant scientific advancement.
Strategic Network Slicing Management in Radio Access Networks

Network slicing might radically change the relations among different actors of the telecommunications ecosystem, where new players, active in different markets, could benefit of tailored connectivity services based on different business strategies. We argue that for fully exploiting the opportunities offered by network slicing, dynamic sharing of resources is crucial not only for efficiency and cost savings, but also for enabling a resource negotiation that can unleash the potential of new business relations. We develop an automated mechanism that allows tenants to take strategic decisions to optimize the management of their slices based on their instantaneous demands and model their interaction as in marketplace. We integrate our solution, based on game theory, on a 3GPP calibrated system level simulator, where a slice-aware scheduler enforces the tenants’ decisions at the Nash Equilibrium (NE). We compare our proposal with a static baseline, that assigns a fixed share of resources to each slice, and show that, by dynamically trading resources in the market, tenants achieve lower costs, and, therefore, higher profits. We provide an algorithmic implementation that guarantees the convergence to a single NE and test the computational complexity of our algorithm to an increasing number of slices in the system.
Evaluating the influence of federal prescribed fire regimes in east Texas on white-tailed deer body condition and antler size

The physiological impacts of Federal prescribed burn regimes on white-tailed deer (Odocoileus virginianus) body weight and antler size was investigated in east Texas National Forests. Burn history was provided by the U.S. Department of Agriculture, Forest Service, National Forests and Grasslands in Texas. Many State wildlife management areas overlapped the National Forest boundaries; therefore, the burn histories were used in combination with Texas Parks and Wildlife Department deer harvest records to investigate the relationships between white-tailed deer physical attributes and prescribed fire. Deer antler beam and inside mean spread were significantly greater at 2 years post-burn than at less than 1 year post-burn. These results indicate that frequent prescribed fire is physiologically beneficial to white-tailed deer.
THE EFFICIENCY OF PREPARED BIOFERTILIZER FROM LOCAL ISOLATE OF BRADYRHIZOBIUM SP ON GROWTH AND YIELD OF MUNGBEAN PLANT

Bradyrhizbium sp. was isolated from 40 legumes roots and soil samples collected from various agricultural areas of Iraq by growing them on yeast extract mannitol agar (YEMA) and identification based on culture and microscopic characteristics, biochemical and physiological test and PCR technology. A split plot experiment was carried out to study the effect of biofertilizer prepared from this isolate on the growth and yield of mungbean plant in sterile and non-sterile soil. The results showed a significant increases in all studied growth and yield traits due to biofertilization. The increase percentage for the biofertilized treatments was 159.35% and 266.66% compare to the non-fertilized treatments in the number and dry weight of nodules, respectively. The increase in dry weight of root and vegetative part were 114.28% and 86.57% respectively , while the increase in the nitrogen concentration in the vegetative part was 16.94%. The results showed that the biofertilized treatment was significantly superior in number of plant pods, total yield and protein % in seeds compare with non-biofertilized, the percentage increase was 49.44%, 90.59% and 16.86% respectively. As for sterilization, the results showed no significant differences between sterilized and non-sterile soil in all growth and yield parameters of mungbean plant. The effect of interaction was significant, the biofertilized and sterilized treatment gave the highest value for all studied traits except the concentration of nitrogen in the vegetative part.
End-to-End Motion Classification Using Smartwatch Sensor Data

Analysis of smart devices’ sensor data for the classification of human activities has become increasingly targeted by industry and motion research. With the popularization of smartwatches, this data becomes available to everyone. The user’s data from accelerometers and gyroscopes is conventionally analyzed as a multivariate time series to obtain reliable information about the user’s activity at a specific moment. Due to the particular sampling rate instabilities of each device, previous approaches mainly work with feature extraction methods to generalize the information independently of the gear, which requires a lot of time and expertise. To overcome this problem, we present an end-to-end model for activity classification based on convolutional neural networks of different dimensions without extensive feature extraction. The data preprocessing is not computationally intensive and the model can deal with the irregularities of the data. By representing the input as twofold – both, interpolated 1D time series and encoded time series as images with the help of Gramian Angular Summation Fields – the use of computer vision techniques is enabled. In addition, an online prediction is possible and the accuracy is comparable to feature extraction approaches. The model is validated with random 10-fold and leave-one-user-out cross-validation showing improvement regarding the generalization of the task.
Distinct Regulation of Bioenergetics and Translation by Group I mGluR and NMDAR

Neuronal activity is responsible for large energy consumption within the brain. However, the cellular mechanisms draining ATP upon the arrival of a stimulus are yet to be explored systematically at the post-synapse. Here we provide evidence that a significant fraction of ATP is consumed upon glutamate stimulation to energize the mGluR-induced protein synthesis. We find that both mGluR and NMDAR alter protein synthesis and ATP consumption with distinct kinetics at the synaptic-dendritic compartments. While mGluR activation leads to a rapid and sustained reduction in the neuronal ATP level, NMDAR activation has no immediate impact on the same. ATP consumption correlates inversely to the kinetics of protein synthesis for both the receptors. We observe a persistent elevation in protein synthesis within 5 minutes of mGluR activation and robust inhibition of the same within 2 minutes of NMDAR activation, assessed by the phosphorylation status of eEF2 and metabolic labeling. However, a delayed protein synthesis-dependent ATP expenditure ensues after 15 minutes of NMDAR activation. We identify a central role for AMPK in this correlation between protein synthesis and ATP consumption. AMPK is dephosphorylated and inhibited upon mGluR activation while it was rapidly phosphorylated upon NMDAR activation. Perturbing AMPK activity disrupts the receptor-specific modulations of eEF2 phosphorylation and protein synthesis. Therefore, our observations suggest that the glutamate receptors required modulating the AMPK-eEF2 signaling axis to alter neuronal protein synthesis and bioenergetics. Short Summary Stimulation of glutamate receptors induces robust protein synthesis within cortical neurons and consumes a significantly large fraction of cellular ATP. Glutamate receptors viz. mGlulR and NMDAR modulate AMPK-eEF2 signaling uniquely leading to the dynamic regulation of protein synthesis and bioenergetics. Key Highlights Protein synthesis following glutamate receptor activation is responsible for the bulk of the activity-induced ATP consumption in cortical neurons. mGluR and NMDAR regulate protein synthesis with distinct kinetics and dictate the subsequent impacts over neuronal ATP level. Dynamic modulation of AMPK and eEF2 phosphorylation is key to create unique temporal features of receptor-specific protein synthesis and bioenergetics.
PlncRNADB: A Repository of Plant lncRNAs and lncRNA-RBP Protein Interactions

Long noncoding RNAs (lncRNAs) are endogenous noncoding RNAs, arbitrarily longer than 200 nucleotides, that play critical roles in diverse biological processes. LncRNAs exist in different genomes ranging from animals to plants. PlncRNADB is a searchable database of lncRNA sequences and annotation in plants. We built a pipeline for lncRNA prediction in plants, providing a convenient utility for users to quickly distinguish potential noncoding RNAs from protein-coding transcripts. More than five thousand lncRNAs are collected from four plant species (Arabidopsis thaliana, Arabidopsis lyrata, Populus trichocarpa and Zea mays) in PlncRNADB. Moreover, our database provides the relationship between lncRNAs and various RNA-binding proteins (RBPs), which can be displayed through a user-friendly web interface. PlncRNADB can serve as a reference database to investigate the lncRNAs and their interaction with RNA-binding proteins in plants. The PlncRNADB is freely available at http://bis.zju. edu.cn/PlncRNADB/.
Fire behavior and filter plugging during a postulated solvent fire in the extraction process of a nuclear fuel reprocessing plant

A solvent fire in the extraction process of a fuel reprocessing plant is postulated. Because of the high concentration of fission products and large amount of nuclear fuel materials in the extraction process, it is necessary to demonstrate that these radioactive materials can be confined by the air ventilation system during a solvent fire. Large-scale tests are performed in a fire/filter facility to evaluate the effectiveness of a ventilation system including high-efficiency particulate air (HEPA) filters to confine radioactive materials. It is demonstrated that the integrity of the filters in the ventilation factor of HEPA filters for smoke particles, which might contain radioactive materials, is sufficiently high during a postulated solvent fire.