Miracle-dz/UniFAR-FTUs huggingface dataset:
Magnetic ground state and Fermi surface of bcc

Using spin-spiral technique within the full potential linearized augmented-plane-waves (LAPW) electronic structure method, we investigate the magnon spectrum and Néel temperature of bcc Eu. Ground state corresponding to an incommensurate spin spiral is obtained in agreement with experiment and previous calculations. We demonstrate that the magnetic coupling is primarily through the intra-atomic f −s and f −d exchange and Ruderman-Kittel-Kasuya-Yosida mechanism. We show that the existence of this spin spiral is closely connected to a nesting feature of the Fermi surface, which was not noticed before.
AN EXAMINATION OF AN INTENSE WEST-EAST ORIENTED LAKE-EFFECT SNOW BAND OVER SOUTHEAST LOWER MICHIGAN

On several occasions each year, an intense west-east oriented lake-effect snow band develops over lake Michigan, and extends east for a distance of over 200 km, affecting areas in southeast lower Michigan that are usually east of the traditional lower Michigan "snow belt". Localized snow accumulations of 50 to 150 mm (2 to 6 in.) frequently occur over southeast Michigan in these events. Radiosonde observations associated with seven sample cases are presented, indicating that these bands typically occur under conditions that are known to be favorable for lake-effect snow; i.e., a lake surface / 850-mb temperature difference greater than or equal to 13°C, limited low-level directional wind shear, ample low-level moisture, and an inversion height of at least 1 km. A more detailed case study from one of these events is also presented. It is shown that an intense snow band evolved in association with the development of a strong lower-tropospheric convergence zone across southern lower Michigan. It is hypothesized that the band formed when westerly wind around the southern end of Lake Michigan acquired a strong ageostrophic flow component resulting from ground-produced frictional effects in the shallow, cold airmass southeast of the lake, and also due in part to an isallobaric contribution that naturally occurs over southern Michigan whenever a cold westerly flow traverses Lake Michigan. This subsequently resulted in a significant lake-induced frontogenetic process, with enhanced convergence and upward vertical motion developing along a boundary between the shallow, stable, strongly sheared airmass southeast of the lake, and a more well-mixed airmass directly downwind of the lake. Additionally, an examination of NCAR / Penn State MM5 numerical weather prediction model forecasts for this event indicated that the MM5 was able to simulate the relatively narrow convergence zone associated with the snow band. However, model difficulties with the forecast thermal structure of the lowertroposphere resulted in significant errors with the forecast placement of the band. Nonetheless, it is suggested that there is much potential value to be gained from a local model in predicting the development and trends of certain features that may be critical to formation of these significant weather phenomena. 'Current affiliation, NOAA/National Weather Service Office, State College, PA
Perron ’ s Method for Viscosity Solutions Associated with Piecewise-Deterministic Processes

where $¥nabla u$ is the gradient of $u$ and $Q(¥cdot, x)$ is a probability measure. The applications for (0.1) considered here are dynamic programming equations associated with the control of piecewise-deterministic (PD) processes. A $¥mathrm{P}¥mathrm{D}$ process follows deterministic dynamics between random jumps, and is determined by its three “local characteristics”: (i) a continuous vector field $g$ , which determines the flow
Negative Impedance Technique for Wide Dynamic Range in Radar Systems

Radar receiver must be able to detect all targets that appears in the designed maximum range, these targets echo signals will have different power levels according to the radar cross section changing, the jamming, and the clutter, this paper proposes a new technique for increasing the wide dynamic range of the radar receiver in order to detect all the signals power levels, this technique based on using time varying gain amplifier (TVGA) for achieving compensation of the power loss due to range, and then using an adaptive sweep optimization (ASO) technique for increasing the linear rejoin of the time varying gain amplifier, the simulation was done using matlab, it shows that intermodulation ratio (IMR) was improved for the time varying gain amplifier electronic circuit, the comparison results with the old methods shows that the probability of detection for the radar was increased using the new technique (ASO/TVGA), for more validation the radar system was tested by detecting three targets at different ranges. Key-Words: Adaptive Sweep; Amplifier; Detection; Linearity, Time Varying.
Structural and Functional Basis of PP 5 Ser / Thr Phosphatase Substrate Specificity

1. Institute of Structural and Molecular Biology, University College London and Birkbeck College, Biological Sciences, Malet Street, London, WC1E 7HX, UK. 2. Department of Urology, SUNY Upstate Medical University, 750 East Adams St., Syracuse, NY 13210, USA. 3. Department of Biochemistry & Molecular Biology, SUNY Upstate Medical University, 750 East Adams St., Syracuse, NY 13210, USA. 4. Cancer Research Institute, SUNY Upstate Medical University, 750 East Adams St., Syracuse, NY 13210, USA. † Present address: Medical Research Council Genome Damage and Stability Centre, School of life Sciences, University of Sussex, Brighton, UK. ‡ Present address: Section of Structural Biology, The Institute of Cancer Research, Chester Beatty Laboratories, 237 Fulham Road, London, SW3 6JB, UK.
Transformative Learning in Nursing: A Guide for Nurse Educators

Transformative Learning Theory offers a uniquely inclusive methodology across all levels of nursing education for educators and students focused on common nursing arenas and situations. This is the only book to present practical, innovative strategies for novice and experienced nurse educators to apply Transformative Learning Theory in various curricula, courses, and learning situations. Geared for adult and returning students, the text addresses common learning issues from both learner and teacher perspectives, enabling educators and students to apply Transformative Learning to evaluate their own authentic transformation throughout their careers. Key Features: Offers a uniquely inclusive theory and methodology "Transformative Learning Theory" across degree levels for educators and students Includes practical learning strategies and activities for a broad nursing curriculum Addresses the needs of novice nurse educators with clinical, but limited pedagogical, expertise and experienced nurse educators seeking new frameworks and techniques Provides direct application for classroom, online, or hybrid learning environments Covers all aspects of simulation Designed for graduate nursing education courses
A multilocus perspective on the worldwide population structure of common dolphins ( genus Delphinus )

Common dolphins (genus Delphinus) presently comprise two species and four subspecies: the short-beaked common dolphin, D. delphis delphis Linnaeus, 1758 distributed in temperate waters of the Atlantic and Pacific Oceans; D. delphis ponticus Barabash, 1935 restricted to the Black Sea; the long-beaked common dolphin, D. capensis capensis Gray, 1828 distributed in nearshore sub-tropical and temperate waters of the Southern Atlantic and Pacific Oceans; and D. capensis tropicalis van Bree, 1971 distributed in the Indian Ocean. These species were initially described based on morphological data, with mitochondrial DNA and AFLPs also supporting the distinction between short-beaked and long-beaked populations in the Northeast Pacific. However, more recent analysis on a global scale using mitochondrial DNA has revealed some level of discordance between morphology and genetics. In this report we will present preliminary results from a multilocus analysis (including mitochondrial DNA, microsatellites and nuclear loci) aimed at clarifying the population structure and taxonomy of common dolphins.
An instrumental electrode model for solving electrical impedance tomography forward problems

An instrumental electrode model (IEM) capable of describing the performance of electrical impedance tomography (EIT) systems in the MHz frequency range has been proposed. Compared with the commonly used Complete Electrode Model (CEM), which assumes ideal front-end interfaces, the proposed model considers the effects of non-ideal components in the front-end circuits. This introduces an extra boundary condition in the forward model and offers a more accurate modelling for EIT systems. We have demonstrated its performance using simple geometry structures and compared the results with the CEM and full Maxwell methods. The IEM can provide a significantly more accurate approximation than the CEM in the MHz frequency range, where the full Maxwell methods are favoured over the quasi-static approximation. The improved electrode model will facilitate the future characterization and front-end design of real-world EIT systems.
Session 1 pBAb : Ultrasound Contrast Agents and Passive Cavitation Mapping of High Intensity Focused Ultrasound Lesion Formation 1 pBAb 1 . Acoustic characterization and modeling of polylactic acid-encapsulated contrast microbubbles

Biodegradable polymers like Polylactic acid hold potential for better stability and control over encapsulation properties of ultrasound contrast microbubbles. We report here several interesting acoustic properties of air-filled PLA shelled microbubbles through both in vitro experiments and mathematical modeling. Attenuation measurements with PLA microbubbles (average diameter 1.9 micrometer), indicated a resonance frequency of 2.5-3 MHz, which, in contrary to other encapsulated microbubbles, is lower than the resonance frequency of a free bubble of similar size. Pressure dependent scattering measurements at two different excitation frequencies (2.25 and 3 MHz) show strongly non-linear behavior with distinct second and subharmonic responses. Subharmonic responses are registered above a relatively low generation threshold of 100-150 kPa. To investigate the underlying mechanisms we utilized several preexisting interfacial models describing encapsulated bubble dynamics. The attenuation data was utilized to determine the interfacial rheological properties of the encapsulation for each of these models. The model predictions are then compared with scattered nonlinear-suband second harmonic-responses. Our studies indicate that the extremely low surface elasticity (around 0.01 N/m) and reduced surface tension (0.01-0.03 N/m) along with the polydispersity of the bubble suspension play a critical role in determining the acoustic properties of PLA microbubbles.
Exploring Links between Mother and Infant through Human Milk Diurnal Melatonin Rhythm in Human Milk and Association of Maternal Diet and BMI with Infant Gut Bacteria

A comprehensive overview of the scientific efforts towards understanding the beneficial effects of breastfeeding on infants, mothers and societies has been collected. Of particular interest are the mechanisms which change the human milk composition dynamically over the lactation period, day and feed. Two potential links between mother and infant through human milk were investigated: diurnal Melatonin rhythm in human milk and association of maternal diet and BMI with infant gut bacteria. A pilot study was designed to find a feasible way of monitoring human milk Melatonin levels. I decided to use a commercial ELISA kit designed for human serum and plasma. The human milk Melatonin concentration curve peaked at 11 pg mL between 2 and 5 am. During daytime, the Melatonin level dropped below the ELISA detection limit (1.6 pg mL ). The diurnal rhythm was clearly detectable, making this procedure feasible for the purpose of correlating human milk Melatonin and infant sleep behaviour. In the longitudinal study Sleep Behavior and Gut Microbiota in Healthy Infants, maternal diet was monitored with a self-reported Food Frequency Questionnaire and infant gut bacteria were analysed by 16S rRNA gene analysis. I was not able to find any correlation between maternal food intake and their breastfed infants’ gut bacteria. There was a small effect of maternal BMI on Actinobacteria (rPearson = .18) and the Bacteroides-Prevotella group (rPearson = -.18). For further investigation we need to look into the link between maternal diet and breast milk composition.
The Tyranny of the Single-Minded: Guns, Environment, and Abortion

Abstract We study how electoral incentives affect policy choices on secondary issues, which only minorities of voters care intensely about. We develop a model in which office and policy-motivated politicians vote in favor of or against regulations on these issues. We derive conditions under which politicians flip-flop, voting according to their policy preferences at the beginning of their terms but in line with the preferences of single-issue minorities as they approach reelection. To assess the evidence, we study U.S. senators' votes on gun control, the environment, and reproductive rights. In line with the model's predictions, we find that election proximity has a pro-gun effect on Democratic senators and a pro-environment effect on Republican senators; these effects arise for senators who are not retiring, do not hold safe seats, and represent states where the single-issue minority is of intermediate size. Also in line with our theory, election proximity does not affect votes on reproductive rights due to the presence of single-issue minorities on both sides.
Soundslike – Automatic content-based music annotation and recommendation for large databases

A manual indexing of large music libraries is both tedious and costly, that is why a lot of music datasets are incomplete or wrongly annotated. An automatic content-based annotation and recommendation system for music recordings is independent of originally available metadata. It allows for generating an objective metadata that can complement manual expert annotations. These metadata can be effectively used for navigation and search in large music databases of broadcasting stations, streaming services, or online music archives. Automatically determined similar music pieces can serve for user-centered playlist creation and recommendation. In this paper we propose a combined approach to automatic music annotation and similarity search based on musically relevant low-level and mid-level descriptors. First, we use machine learning to infer the high-level metadata categories like genre, emotion, and perceived tempo. These descriptors are then used for similarity search. The similarity criteria can be individually weighted and adapted specifically to specific user requirements and musical facets as rhythm or harmony. The proposed method on music annotation is evaluated on an expert-annotated dataset reaching average accuracies of 60% to 90%, depending on a metadata category. An evaluation for the music recommendation is conducted for different similarity criteria showing good results for rhythm and tempo similarity with precision of 0.51 and 0.71 respectively.
Effect of Different Ethanol Concentrations , Using Different Extraction Techniques , on the Antioxidant Capacity of Lebanese Eryngium creticum

This study aims to investigate the effects of different percentages of ethanol (40%, 80%, and 100%) and extraction times (2h, 4h, 12h for reflux), by using conventional (maceration and reflux) and nonconventional (microwave assisted extraction) extraction techniques, on the bioactive phenolic compounds and the antioxidant activity of the Lebanese Eryngium creticum. The quantification of these extracts showed that this plant is rich in secondary metabolites. Moreover, the nonconventional microwave assisted extraction technique was more effective (1.718 g of extract compared to the other used methods) along with a reduced extraction time and less used solvent. The antioxidant activity was evaluated using the DPPH radical scavenging assay and ferric reducing antioxidant power. Results showed that extracts, using 40% ethanol, possessed the highest iron chelating activity (87.92%). On the other hand, the extracts had the highest DPPH scavenging activity (89.92%) after using 80% ethanol. All these results prove that E. creticum is a good source of different antioxidant and bioactive compounds. Keyword: Eryngium creticum; ethanol-water binary solvent; antioxidant activity; extraction conditions.
TRANSFORMATIONS , ENACTMENTS AND DISTRUST IN PROMOTING MULTIPLICITY IN DESIGN PROCESS

Our research aims to develop an approach to technology design that will support relational nature of human agency, i.e. the human capacity for action. To this end, we developed six design qualities to be integrated into design process. In this paper, we report on two exploratory design workshops, in which we aimed to promote one of these qualities, multiplicity. In addition, the focus of the workshops was upon various forms of togetherness between humans and technologies. The two workshops involved various activities in which participants could create connections with other participants, various materials and technologies. We explain the very different ways in which different sets of participants translated our design inscriptions in each workshop. We discuss three important effects that we observed: transformation of workshop space, enactments of technology, and distrust of design process.
Neuroprotective profile of mulberry leaf extract in focal cerebral ischemia model in rats Sheeba

The cerebral ischemia causes severe degree of oxidative stress as a result of reperfusion injury. An attempt has been made to analyze the preventive and curative potential of mulberry leaf extract, in focal cerebral ischemia model in rat, as it is rich source of novel chemicals possessing antioxidant and neuroprotective properties. The aqueous extract (MLE-AR-14) pre-treatment one hour prior to ischemia significantly (65%) prevented the ischemic cerebral damage. It also tended to revert the behavioral deficit caused due to brain damage. The biochemical markers of oxidative stress MDA and GSH were also significantly altered towards basal levels. The most important and exciting finding is the effectiveness of MLE-AR-14 administration after six hours post cerebral injury. The extract at a dose of 100 mg/kg p.o. caused reduction in cerebral infarct by 54% indicating its curative potential in cerebral stroke. The oxidative end product MDA was reduced by 42 % and the level of GSH was elevated by 54% on post-treatment. Thus, it seems that MLE-AR-14 has a potent neuroprotective profile and also has modulatory effect on cellular and biomolecular processes in preventing redox status to arrest apoptotic and necrotic processes underlying focal cerebral ischemia, as evidenced by histological parameters. The post-ischemic efficacy of the extract suggests that it may be clinically exploited in cerebral stroke.
Spatial and temporal organization of RecA in the Escherichia coli 1 DNA-damage response 2

16 The RecA protein orchestrates the cellular response to DNA damage via its multiple roles in 17 the bacterial SOS response. Lack of tools that provide unambiguous access to the various 18 RecA states within the cell have prevented understanding of the spatial and temporal 19 changes in RecA structure/function that underlie control of the damage response. Here, we 20
Automatic Native Language Identification Using Novel Acoustic and Prosodic Feature Selection Strategies

We consider the problem of automatic identification of native language (L1) of non-native English (L2) speakers from eleven L1 backgrounds. Analyzing the influence of each L1 pronunciation variabilities on L2 pronunciation, different sets of linguistic units are chosen to compute supra-segmental features by considering the acoustic and prosodic variations within and across these sets. Using these features, we implement a multi-class classifier comprising 55 binary (one versus another) support vector machine (SVM) classifiers. We select optimal set of features for each binary classifier using two feature selection strategies (FSSs) based on Fisher discriminant ratio (FDR). The first strategy considers the features that maximizes the each binary classifier performance. However, the second strategy selects the features by maximizing a multi-class classifier performance for which an algorithm is proposed. Experiments are performed on the ETS corpus of non-native spoken English, comprising 4099 files. When the proposed features along with FSSs are used, the unweighted average recall (UAR) on the test set for each selection strategy is found to be 1.3% and 2.1% (absolute) higher compared to using all features; as well as 3.0% and 3.8% higher than the baseline technique respectively.
Higgs mass prediction in the MSSM at three-loop level in a pure DR context

The impact of the three-loop effects of order α t α 2 s on the mass of the light CP -even Higgs boson in the MSSM is studied in a pure DR context. For this purpose, we imple-ment the results of Kantet al.(JHEP 08:104, 2010) into the C++ module Himalaya and link it to FlexibleSUSY , a Mathematica and C++ package to create spectrum generators for BSM models. The three-loop result is compared to the ﬁxed-order two-loop calculations of the original FlexibleSUSY and of FeynHiggs , as well as to the result basedonan EFT approach.Asidefromtheexpectedreduction of the renormalization scale dependence with respect to the lower-order results, we ﬁnd that the three-loop contributions signiﬁcantly reduce the difference from the EFT prediction in the TeV-region of the SUSY scale M S . Himalaya can be linked also to other two-loop DR codes, thus allowing for the elevation of these codes to the three-loop level.
Classification of Parkinson ’ s disease Machines and neural networks

Parkinson's disease (PD) is a chronic and progressive movement disorder, meaning that symptoms continue and worsen over time. The diagnosis of Parkinson is challenging because currently none of the clinical tests have been proven to help in diagnosis. In this paper, the main purpose was to classify the PD people (sick) and non-PD people (healthy). Recently the machine learning methods based diagnosis of medical diseases has taken a great deal of attention. The Support Vector Machine (SVM) and the Neural Network (NN) learning methods are used as base classifiers. The support vector machine is a novel type of learning machine, based on statistical learning theory, which contains radial basis function (RBF) as special cases. 100% / 80% accuracies are reported. ic, Scientific research on vocal recordings of patients that suffer from Parkinson’s disease are not abundant. The data set used in this study was collected by Little et al. (2009) who used support vector machine techniques to distinguish between the people who have normal vocal signals and who suffer from Parkinson’s disease. They achieve a classification accuracy of 91.4% but they single class true positive rates. This is noteworthy because of the highly imbalanced sick to healthy ratio (3:1) data class distribution of the Parkinson’s disease data set (Freddie and Koker, 2011). In previous studies in which the possib an ‘‘intelligent’’ stimulator (Cassidy et al., 2002; Gasson et al., 2005) by analysing the STN LFP signals was first documented, different types of artificial neural network such as Multiple Layer Perceptrons (Pan et al., 2007) and Radial Basis Function Networks (Wu, Warwick, Ma, Burgess, et al., 2010; Wu, Warwick, Ma, Gasson, et al., 2010) were used to ‘‘predict’’ PD tremor based on LFP signals. Initial results showed that both RBN and MLP could be used as classifiers to obtain reasonab do not report