Miracle-dz/UniFAR-FTUs huggingface dataset:
Age-progressive volcanism of the Oregon High Lava Plains: Overview and evaluation of tectonic models

The High Lava Plains province of central and southeastern Oregon is a Late Tertiary to Quaternary bimodal volcanic province characterized by age-progressive rhyolites and widespread basaltic volcanism. The age-progressive trend co-originates with the Yellowstone–Snake River Plain trend along the axis of middle Miocene flood basalt vents of the Columbia River and the Steens basalts. Although the Yellowstone trend has an azimuth consistent with plate motion, the High Lava Plains trend is at ~120° off of this direction. This relationship complicates the mantle plume model for the origin of the Yellowstone melting anomaly. Many models have been proposed for the origin of the High Lava Plains, mostly linking the province to the Yellowstone system. I summarize the geology of the High Lava Plains, review models for the origin of the province, evaluate several fundamental aspects of these models, and present my current view of the origin of the High Lava Plains. My analysis disproves the propagating fault zone model for ageprogressive volcanism and suggests a role for the westward sublithospheric flow of material from under the craton. I conclude that rather than disproving the plume model for the Yellowstone system, the High Lava Plains may be best understood in the context of plume-related processes.
Shifting trends in wilderness recreational use.

Wilderness recreational use grew rapidly during most of the post World War II era, but growth has slowed or reversed recently. National park backcountry use began declining in the 1970’s and national forest use slowed or declined in the 1980’s in many areas. Reasons are unclear, but an aging population and changing interests are the most Apparent causes. This change has implications for wilderness allocation and management.
Multi-view Collaborative Gaussian Process Dynamical Systems

Gaussian process dynamical systems (GPDSs) have shown their eﬀectiveness in many tasks of machine learning. However, when they address multi-view data, current GPDSs do not explicitly model the dependence between private and shared latent variables. Instead, they introduce structurally and intrinsically discrete segmentation in the latent space. In this paper, we propose the multi-view collaborative Gaussian process dynamical systems (McGPDSs) model, which assumes that the private latent variable for each view is controlled by its dynamical prior and the shared latent variable. The relevance between private and shared latent variables can be automatically learned by optimization in the Bayesian framework. The model is capable of learning an eﬀective latent representation and generating novel data of one view given data of the other view. We evaluate our model on two-view data sets, and our model obtains better performance compared with the state-of-the-art multi-view GPDSs.
MINERAL STATUS OF SOILS, WATER, FEEDS AND FODDERS OF DAIRY ANIMALS IN MAHABOOBNAGAR DISTRICT OF ANDHRA PRADESH

A survey was conducted to evaluate the mineral status of dairy animals of Mahaboobnagar district of Andhra pradesh. Four villages were selected for the survey that truly represented the animal husbandry practices of the district. The soils in the surveyed villages were adequate in Ca, Mg, Mn, Fe and Co, while deficient in P. About 32.5 % samples had Cu and Zn levels below the critical level. The supply of minerals from water was negligible. The dry and green roughages on average were deficient to marginally adequate in Ca (0.20  0.46 %), adequatein Mg (0.19  0.36 %), Co (0.20  0.30 ppm), reasonable in Mn (24.78  155.74 ppm) and quite excess in Fe (103.3  525.8 ppm), while deficient in Cu (1.52  9.91 ppm) and P (0.12  0.32 %). The dry roughages were deficient in Zn (16.98  30.28 ppm), while greens were adequate. The brans were rich in P, Fe, Mn and Co; moderate in Cu, Zn and Mg, while maize grain was deficient in most of the minerals except P, Fe and Co. Ragi straw and horse gram were good sources of Ca. The dairy animals in the district were in short supply of P, Cu and Zn, which needs strategic supplementation.
HEAVY ION FUSION ACCELERATOR RESEARCH (HIFAR)

Current amplification of heavy ion beams is an integral feature of the induction linac approach to heavy ion fusion. As part of the Heavy Ion Fusion Accelerator Research program at LBL we have been studying the evolution of the transverse emittance of ion beams while they are undergoing current amplification, achieved by longitudinal bunch compression and acceleration. Experiments arc conducted on MBE-4, a icir beam Cs + induction linac. The space-charge dominated bcuns of MBE-4 are focused by electrostatic quadruples while they arc accelerated from nominally 200 keV up to - 1 MeV by 24 accelerating gaps. Initially the beams have currents of typically 4 mA to 10 mA per beam. Early experimental results showed a growth of the normalized emittance by a factor of 2 while the beam current was amplified by up to 9 times its initial value. We will discuss the results of recent experiments in which a mild bunch length compression rate, more typical of that required by s fusion driver, has shown that the normalized emittance can be maintained at its injection value (0.03 nun-mi) during acceleration.
Complementarity of ungulate-mediated dispersal processes in different sites across Europe

Animals are frequent and efficient vectors of plant dispersal, either via external (epizoochory) or internal (endozoochory) mechanism. Among the animal vectors, ungulates have been proven to be effective dispersers of seeds in numerous studies. In this study, we aim to assess the taxonomic and functional complementarity either (1) between dispersal modes (endozoochory – epizoochory) or (2) between dispersal vectors (Cervus elaphus – Sus scrofa). Data from our COSTAUD project are combined with data extracted on previous studies for analysis. Non-parametric comparison tests, correlation tests and Principal Component Analysis were perfomed on this data. We found a slight overlap in dispersed species between dispersal modes, and also between ungulate vectors. We also found clear associations of functional traits to a dispersal mode or to an ungulate vector. First, light demanding plant species living in open spaces, with and high seed bank longevity and round diaspores are more likely to be dispersed via endozoochory. Contrarily, plant species realeased at great height, have long shape and appendages are more likely to be dispersed via epizoochory. Furthermore, wild boar is more likely to disperse species with pulp. The results also suggest a complementarity between dispersal modes and vectors with red deer being a more efficient disperser via endozoochory, and wild boar for epizoochory.
THE EFFECT OF PERCEIVED EASE OF USE, PERCEIVED USEFULNESS, AND TRUST ON INTENTION TO USE OF MOBILE BANKING

This study aims to determine the effect of perceived ease of use on the intention to use mobile banking, perceived usefulness on the intention to use mobile banking, and trust on the intention to use mobile banking, as well as the combined effect of perceived ease of use, perceived usefulness, and trust on the intention to use mobile banking among students of the Accounting Department of the State University of Jakarta, class of 2019. The population for this study comprised 179 students. Stratified Random Sampling was conducted with specific criteria, resulting in a sample of 124 students. This research is guided by the TAM (Technology Acceptance Model) Theory. The study reveals that perceived ease of use has a negative and insignificant effect on the intention to use mobile banking, thus rejecting H1. However, perceived usefulness have a positive and significant effect on the intention to use mobile banking, supporting H2. Trust also has a positive and significant effect on the intention to use mobile banking, validating H3. Furthermore, perceived ease, perceived usefulness, and trust collectively have a positive and significant effect on the intention to use mobile banking, confirming H4.
Estimation of Mycobacterium avium subspecies paratuberculosis in the first mass screening of human populace in Mathura region of South Uttar Pradesh

Bio-heap of Mycobacterium avium subspecies paratuberculosi s (MAP) was estimated in the first mass screening of human population in Mathura region of South Uttar Pradesh . 48,919 samples were collected between December, 2010 and March, 2013 from Pathology laboratories, 26,390 were screened by indigenous ELISA kit, IS 900 blood and stool PCR, IS 1311 PCR_RE and stool microscopy. From 23,196 serum samples screened by indigenous ELISA, 34.0% were positive for MAP infection (Mathura - 35.4% and Agra 14.2%). Percent prevalence of MAP infection was 28.3, 41.8, 37.4, 29.5, 41.1, 40.7, 42.5, 36.5 and 51.2 in patients suspected for diabetes, liver disorders, anaemia, thyroid, tuberculosis, typhoid, abdominal disorders, inflammatory illness and ion imbalance, respectively. 3093 blood samples screened by IS900 PCR, 8.4% were positive (Mathura - 9.2% and Agra -7.9%). Percent prevalence of MAP was 4.8, 7.0, 20.0, 4.9, 17.8, 7.6 and 12.7 in patients suspected for diabetic, liver disorder, skin disorders, anaemia, Malaria, typhoid and apparently normal individuals, respectively. 101 stool samples screened by microscopy, 5.9% were positive and of these 2.9% were confirmed by IS 900 PCR. IS 1311 PCR_RE bio-typing showed ‘Indian Bison Type’ was the most prevalent biotype. The study indicated large scale exposure of human population to MAP in the Mathura region of South Uttar Pradesh and ‘Indian Bison Type’ biotype was most prevalent.
Investor Sentiment and the Mean-variance Relation

This paper examines the effects of investor sentiment on the mean-variance relation. Behind the well-known ambiguous relation between the mean and variance, the relation is significantly positive in the low sentiment periods and close-to-zero in the high sentiment periods. The results are robust for four volatility models. The empirical findings are consistent with economic intuitions. In the low sentiment periods, the price is damped down and the mean of return is pushed up. The market price is a compromise between rational traders and irrational traders. Hence the stocks are undervalued but irrational traders still believe that the stocks are overvalued. Rational investors invest more in stocks and irrational ones invest less. The ratio of the mean to the variance must be higher, which attracts more wealth of rational investors. Vice verse, the relation is lower in the high sentiment periods. We propose a general equilibrium model to formalize these intuitions. Furthermore, our empirical results show that the market’s reaction to volatility is not homogenous through time but depends on investor sentiment. The whole market cares more about volatility when sentiment is low and less when sentiment is high. Besides the evidence from the mean-variance relation, the finding is confirmed by the empirical results of the return-innovation relation. The relation between the returns and the volatility innovations are much more negative in the low sentiment periods.
Impact of various blends of natural issue as developing media on seed germination, survival, growth, biomass and performance of Arizona cypress and Medite cypress

The present research was carried out to determine the influence of different combinations of organic matter as growing media on seed germination, survival, growth, biomass and performance of needle-leaved Arizona cypress ( Cupressus arizonica var arizonica Greene) and Medite cypress ( C. sempervirens var. horizantalis (Mill.) Gord) seedlings in Koloudeh nursery, located in Amol city (North of Iran). Seeds were sown in plastic pots as randomized completely block design (RCBD) with four replications at four different soil treatments, including: T1) nursery common soil (control), T2) control soil: cattle manure (5:1), T3) control soil: decomposed litter (5:1), T4) control soil: cattle manure: decomposed litter (5:1:1). The results after one year showed that seedlings of both species grown on T4 obtained better germination percent, survival, shoot height, collar diameter, seedling vigor index and Quality Index (QI). Greatest relative growth rate (RGR) of height and diameter were achieved on organic matter treatments. In most of the studied attributes, response of C. arizonica was better than C. sempervirens , showing the different biological requirements of these species. From the study, it is concluded that the increased of soil nutrient can be useful in seedling production of both species.
Effect of salicylic acid application in two basil cultivars submitted to water deficit

(SA) is a plant hormone that plays an important role in response to environmental stresses, including water deprivation stress. Basil ( Ocimum basilicum L.) is a plant sensitive to water stress and its cultivation can be strongly affected by prolonged periods of drought. Thus, the objective of our study was to evaluate the possible attenuating role of AS in response to water stress in two basil cultivars. The experiment was conducted in a greenhouse of the Federal University of Agreste of Pernambuco ( Universidade Federal do Agreste de Pernambuco ). The experimental design was completely randomized, with eight treatments, being two varieties of basil (purple and green), two forms of application of SA (with and without application) and two forms of irrigation (irrigated and without irrigation). The concentration of salicylic acid used was 2mM and its application was exogenous. As for the results, it was observed a reduction of 15.7% of the dry mass of the aerial part of the basil plants when submitted to water deficit in relation to the irrigated plants. Significant differences were observed in the photosynthetic rate of the two varieties of basil when exposed to SA. These results suggest that the use of SA at the concentration of 2mM contributed positively to the growth of basil plants submitted to water stress as well as to irrigated plants.
Sciadopitysin attenuates paraquat induced renal toxicity by modulating Nrf2/Keap-1 pathway in male albino rats

Paraquat (PQ) is a herbicide that has the potential to instigate nephrotoxicity in animals and human. Sciadopitysin (SPS) is a biflavonoid that is extracted from Taxus cuspidate and displays diverse biological activities including anti-oxidant, anti-inflammatory and anti-apoptotic. Therefore, the present investigation was designed to evaluate the mitigative potential of SPS against PQ prompted renal toxicity in albino rats. 48 male albino rats were divided into 4 groups, such as control group, PQ treated group (5 mgkg -1 ), PQ + SPS co-treated group (5 mgkg -1 and 2 mgkg -1 respectively) and only SPS treated group (2 mgkg -1 ). The exposure of PQ significantly reduced Nrf-2 as well as anti-oxidant enzymes expression, while increasing Keap-1 expression. Moreover, anti-oxidant enzymes such as, glutathione reductase (GSR), superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT), glutathione-S-transferase (GST), heme oxygenase-1 (HO-1) and glutathione (GSH) activities were decreased. However, in PQ-treated rats malondialdehyde (MDA) and reactive oxygen species (ROS) contents were significantly increased. PQ exposure also increased the serum level of urea, urinary protein, urobilinogen and creatinine while decreased creatinine clearance and albumin protein levels. Moreover, KIM-1 and NGAL levels were also increased in PQ exposed rats. Additionally, inflammatory indices including nuclear factor kappa-B (NF-κB), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α) interleukin-1β (IL-1β) and cyclooxygenase-2 (COX-2) activity were increased in PQ administrated rats. Besides, it escalated the Bax and Caspase-3 expression. Contrarily, a substantial decrease was observed in anti-apoptotic marker, Bcl-2 expression. The exposure of PQ also induced significant histopathological damages in renal tissues. Nevertheless, SPS supplementation recovered all these damages due to its anti-apoptotic, anti-oxidant and anti-inflammatory nature.
A STUDY ON PROFESSIONAL DEVELOPMENT NEEDS OF EFL TEACHERS AT SOME UPPER SECONDARY SCHOOLS IN THE CENTRAL AREA OF VIETNAM

This study aims to investigate the needs of professional development (PD) of EFL teachers at some upper secondary schools in the central area of Vietnam and the ways they would like to carry out their professional development acitivities. The partiticipants included sixty EFL upper secondary school teachers who had teaching experience ranging from 2-30 years and their ages ranged from 23 to over 50. The data were collected by means of a questionnaire and an interview protocol. The findings show that most of the upper secondary school EFL teachers perceived PD as a process that helped them to develop new skills, stay up-to-date on current trends, and advance their career. In particular, participation in a network of teachers was considered to be the most common PD activity needed by all the participants. They also stated that taking part in PD activities served the need of understanding more about the cultures of English - speaking countries in order to convey the lessons to students more accurately and lively. Besides, the results indicate that the need to know how to select appropriate materials and the ways to adapt them contributed to EFL teachers’ PD. From the findings, implications for administrators and teachers are put foward for EFL teachers to realize their needs for improvement.
The Multi-Scale Coupled Model: a New Framework Capturing Wind Farm-Atmosphere Interaction and Global Blockage Effects

The growth in the number and size of wind energy projects in the last decade has revealed structural limitations in the current approach adopted by the wind industry to assess potential wind farm sites. These limitations are the result of neglecting the mutual interaction of large wind farms and the thermally-stratified atmospheric boundary layer. While currently available analytical models are sufficiently accurate to conduct site assessments for isolated rotors or small wind turbine clusters, the wind farm’s interaction with the atmosphere cannot be neglected for large-size arrays. Specifically, the wind farm displaces 5 the boundary layer vertically, triggering atmospheric gravity waves that induce large-scale horizontal pressure gradients. These perturbations in pressure alter the velocity field at the turbine locations, ultimately affecting global wind farm power production. The implication of such dynamics can also produce an extended blockage region upstream of the first turbines and a favorable pressure gradient inside the wind farm. In this paper, we present the multi-scale coupled (MSC) model, a novel approach that allows the simultaneous prediction of micro-scale effects occurring at the wind turbine scale, such as individual wake 10 interactions and rotor induction, and meso-scale phenomena occurring at the wind farm scale and larger, such as atmospheric gravity waves. This is achieved by evaluating wake models on a spatially-heterogeneous background velocity field obtained from a reduced-order meso-scale model. The MSC model is validated against two large-eddy simulations (LES) with similar average inflow velocity profiles and a different capping inversion strength, so that two distinct interfacial gravity wave regimes are produced, i.e. subcritical and supercritical. Interfacial waves can produce high blockage in the first case, as they are allowed 15 to propagate upstream. Conversely, in the supercritical regime their propagation speed is less than their advection velocity and upstream blockage is only operated by internal waves. The MSC model not only proves to successfully capture both local induction and global blockage effects in the two regimes, but also captures wind farm gravity-wave interaction, underestimating wind farm power by about only 2 % compared with the LES results. Conversely, wake models alone, even if combined with a local induction model, cannot distinguish between differences in thermal stratification, and are affected by a first-row over-20 prediction bias that leads to a consistent overestimation of the wind farm power by 13 % to 20 %
Online Non-stochastic Control with Partial Feedback

Online control with non-stochastic disturbances and adversarially chosen convex cost functions, referred to as online non-stochastic control , has recently attracted increasing attention. We study online non-stochastic control with partial feedback , where learners can only access partially observed states and partially informed (bandit) costs. The problem setting arises naturally in real-world decision-making applications and strictly generalizes exceptional cases studied disparately by previous works. We propose the ﬁrst online algorithm for this problem, with an (cid:101) O ( T 3 / 4 ) regret competing with the best policy in hindsight, where T denotes the time horizon and the (cid:101) O ( · )-notation omits the poly-logarithmic factors in T . To further enhance the algorithms’ robustness to changing environments, we then design a novel method with a two-layer structure to optimize the dynamic regret , a more challenging measure that competes with time-varying policies. Our method is based on the online ensemble framework by treating the controller above as the base learner. On top of that, we design two diﬀerent meta-combiners to simultaneously handle the unknown variation of environments and the memory issue arising from the online control. We prove that the two resulting algorithms enjoy (cid:101) O ( T 3 / 4 (1 + P T ) 1 / 2 ) and (cid:101) O ( T 3 / 4 (1 + P T ) 1 / 4 + T 5 / 6 ) dynamic regret respectively, where P T measures the environmental non-stationarity. Our results are further extended to unknown transition matrices. Finally, empirical studies in both synthetic linear and simulated nonlinear tasks validate our method’s eﬀectiveness, thus supporting the theoretical ﬁndings.
Sustainable Development And Financial Inclusion In Sub-Saharan Africa: Empirical Evidence From Panel Vector Error Correction Model (Vecm)

Financial inclusion has been identified as an essential tool for sustainable development in Sub-Saharan Africa (SSA). The low level of financial inclusion in SSA has been attributed to various factors such as low income, high level of poverty, low literacy rate, and inadequate infrastructure. This research investigates the long-run and short-run relationships between financial inclusion and sustainable development in SSA using a panel vector error correction model (VECM) regression method. The study uses cross-sectional data from 48 countries in SSA, covering the period from 2000 to 2021. The model considers the number of Bank branches per 100,000 adults, automated teller machines (ATMs) (per 100,000 adults), and borrowers from commercial banks (per 100,000 adults) as proxies of financial inclusion, while the sustainable development is proxied by human development index (HDI). In addition, the model controls for the influence of GDP per capita and health expenditure. The regression results show that financial inclusion has a positive and statistically significant association with the level of sustainable development in the SSA region. In the long run, a 1% increase in financial inclusion is associated with a 0.62% increase in sustainable development, while the short-run Wald test indicates that each of lagged values of all independent variables jointly Granger causes changes in HDI, suggesting that financial inclusion variables help predict short-run deviation in HDI. This study's findings reveal significant