Miracle-dz/UniFAR-FTUs huggingface dataset:
Gravitational waves from 3D MHD core collapse simulations

We present the gravitational wave analyses from rotating (model s15g) and nearly non-rotating (model s15h) 3D MHD core collapse supernova simulations at bounce and during the first couple of ten milliseconds afterwards. The simulations are launched from 15 M� progenitor models stemming from stellar-evolution calculations. Gravity is implemented by a spherically symmetric effective general relativistic potential. The input physics uses the Lattimer-Swesty equation of state for hot, dense matter and a neutrino parametrisation scheme that is accurate until the first few ms after bounce. The 3D simulations allow us to study features already known from 2D simulations, as well as nonaxisymmetric effects. In agreement with recent results, we find only type I gravitational wave signals at core bounce. In the later stage of the simulations, one of our models (s15g) shows nonaxisymmetric gravitational wave emission caused by a low T/|W| dynamical instability, while the other model radiates gravitational waves due to a convective instability in the protoneutron star. The total energy released in gravitational waves within the considered time intervals is 1.52 × 10 −7 M� (s15g) and 4.72 × 10 −10 M� (s15h). Both core collapse simulations indicate that corresponding events in our Galaxy would be detectable either by the LIGO or Advanced LIGO detector.
Research on Initial Alignment and Self-Calibration of Rotary Strapdown Inertial Navigation Systems

The errors of inertial sensors affect the navigation accuracy of the strapdown inertial navigation system (SINS) and are accumulated over time in nature. In order to continuously maintain the high navigation accuracy of vehicles for a long time period, an initial alignment and self-calibration is necessary after the SINS starts. Additionally, the observability analysis is one of the key techniques during the initial alignment and self-calibration process. For marine systems, the observability of inertial sensor errors is extremely low, as their motion states are always slow. Therefore, studying the rotating SINS is urgent. Since traditional analysis methods have their limitations, the global observation analysis method was used in this paper. On the basis of this method, the relationship between the observability and the kinestate of the rotating SINS has been established. After the discussion about the factors that affect the observability in detail, the design principle of the initial alignment and self-calibration rotating scheme, which is appropriate for marine systems, id proposed. With the proposed principle, a novel initial alignment and self-calibration method, named the eight-position rotating scheme, is designed. Simulations and experiments are carried out to verify its performance. The results have shown that compared with other rotating schemes and the static state, the estimated accuracy of the eight-position scheme rotating about axes x and y was the best, and the position error was significantly reduced with this new rotating scheme. The feasibility and effectiveness of the proposed design principle and the rotating scheme were verified.
Performance evaluation of IRIS recognition algorithms using neural network classifier

Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus it is the most promising for high security environments. Hence numbers of IRIS recognition algorithms are proposed, such as ICA (independent component analysis), SVD (singular value decomposition), Characterizing key local variation etc. which extracts iris features and competitive learning mechanism to recognize iris pattern.
Conductive Nanocrystalline Cellulose Polymer Composite Film as a Novel Mediator in Biosensor Applications

Recent biosensors using the glucose oxidase enzyme to detect glucose (“blood sugar”) were made with intrinsic conducting polymers such as poly pyrrole (PPY) to mediate the reaction. PPY coated electrodes were difficult to employ via eletropolymerization because PPY is only soluble in solvents that are potentially damaging to the enzyme. Nano crystalline cellulose – poly pyrrole (NCC-PPY) colloid circumvents this by forming natural, enzyme compatible and hydrophilic films that can be mechanically bound to the electrodes and the colloids are easy to disperse. NCC-PPY was used in this study as mediator to investigate its use in biosensor applications. Using the NCC-PPY film casted on microfabricated interdigitated electrodes, a glucose biosensor with sensitivity factor of 20 was achieved. As a mediator, NCC-PPY showed enhanced catalysis with no enzyme inactivation and a total current of 2mA. Enhanced sensitivity was attributed to the combination of resistance changes of doped PPY, redox mediation of the reaction and compatibility of the cellulose with the enzyme
Expression of the Minor Isoform Pea Ferredoxin in Tobacco Alters Photosynthetic Electron Partitioning and Enhances Cyclic Electron Flow1[W]

Summary: Characterization of ferredoxin overexpressor transplastomic tobacco plants provides new evidence about the different roles of this protein and the effect of this feature on the regulation of the photosynthetic electron flow to produce alternative electron partitioning between linear and cyclic flow. Ferredoxins (Fds) are ferrosulfoproteins that function as low-potential electron carriers in plants. The Fd family is composed of several isoforms that share high sequence homology but differ in functional characteristics. In leaves, at least two isoforms conduct linear and cyclic photosynthetic electron transport around photosystem I, and mounting evidence suggests the existence of at least partial division of duties between these isoforms. To evaluate the contribution of different kinds of Fds to the control of electron fluxes along the photosynthetic electron transport chain, we overexpressed a minor pea (Pisum sativum) Fd isoform (PsFd1) in tobacco (Nicotiana tabacum) plants. The transplastomic OeFd1 plants exhibited variegated leaves and retarded growth and developmental rates. Photosynthetic studies of these plants indicated a reduction in carbon dioxide assimilation rates, photosystem II photochemistry, and linear electron flow. However, the plants showed an increase in nonphotochemical quenching, better control of excitation pressure at photosystem II, and no evidence of photoinhibition, implying a better dynamic regulation to remove excess energy from the photosynthetic electron transport chain. Finally, analysis of P700 redox status during illumination confirmed that the minor pea Fd isoform promotes enhanced cyclic flow around photosystem I. The two novel features of this work are: (1) that Fd levels achieved in transplastomic plants promote an alternative electron partitioning even under greenhouse light growth conditions, a situation that is exacerbated at higher light intensity measurements; and (2) that an alternative, minor Fd isoform has been overexpressed in plants, giving new evidence of labor division among Fd isoforms.
A Modified H-Bridge Single Phase Multilevel Grid Connected Inverter for Photovoltaic System

This paper proposes a modified H-Bridge single-phase multilevel-level grid-connected inverter for photovoltaic systems, with a novel pulse width-modulated (PWM) control scheme. Three reference signals that are identical to each other with an offset that is equivalent to the amplitude of the triangular carrier signal were used to generate the PWM signals. The inverter is capable of producing seven levels of output-voltage levels (Vdc, 2Vdc/3, Vdc/3, 0,−Vdc,−2Vdc/3,−Vdc/3) from the dc supply voltage. In this paper a new nine level inverter with reduced number of switches is proposed and Matlab /Simulink results are presented. Keywords—Grid connected, modulation index, multilevel inverter, photovoltaic(PV) system, pulse width-modulated (PWM).
Experimental Study of Process Parameters through Dissimilar Form of Electrodes in EDM Machining

Electrical discharge machining (EDM) is a well-established machining option for manufacturing geometrically complex or hard material parts that are extremely difficult-to-machine by conventional machining processes. In recent years, EDM researchers have explored a number of ways to improve the sparking efficiency including some unique experimental concepts that depart from the EDM traditional sparking phenomenon. Despite a range of different approaches, this new research shares the same objectives of achieving more efficient metal removal coupled with a reduction in tool wear and improved surface quality. This paper reviews and based on review findings the research work carried out to improve performance measures, optimizing the process variables, monitoring and control the sparking process, simplifying the electrode design and manufacture. From the experiment, it has been witnessed that current was the most significant parameter followed by pulse on time and the least significant was the pulse off time for the Material removal rate and tool wear rate.
Inclusion of regular and linear languages in group languages

is the free monoid over Σ and e is the identity inG. The problem of determining whether a context-free language is subset of a grouplanguage is discussed. Polynomial algorithms are presented for testing whether aregular language, or a linear language is included in a group language. A few ﬁnitesets are built, such that each of them is included in the group language L(G) if andonly if the respective context-free language is included in L(G).
Approximate Testing Equivalence Based on Time, Probability, and Observed Behavior

Several application domains require formal but flexible approaches to the comparison problem. Different process models that cannot be related by behavioral equivalences should be compared via a quantitative notion of similarity, which is usually achieved through approximation of some equivalence. While in the literature the classical equivalence subject to approximation is bisimulation, in this paper we propose a novel approach based on testing equivalence. As a step towards flexibility and usability, we study different relaxations taking into account orthogonal aspects of the process observations: execution time, event probability, and observed behavior. In this unifying framework, both interpretation of the measures and decidability of the verification algorithms are discussed.
Biochemical and molecular epidemiology of human cancer: indicators of carcinogen exposure, DNA damage, and genetic predisposition.

The primary goal of biochemical and molecular epidemiology is to identify individuals at high cancer risk by obtaining evidence of high exposure to carcinogens, leading to pathobiological lesions in target cells, and/or increased oncogenic susceptibility due to either inherited or acquired host factors. This emerging and multidisciplinary area of cancer research combines epidemiological and laboratory approaches. Because DNA is considered to be an important target for modification by mutagens and carcinogens, damage to DNA can be used as an internal, molecular dosimeter of carcinogen exposure. The reactive species of these carcinogens may directly bind to DNA to form adducts and may indirectly cause secondary DNA lesions, e.g., via induction of free radicals and aldehydes. Highly sensitive and specific methods have been developed to measure the minute amounts of DNA lesions and DNA repair products found in biological specimens from humans exposed to carcinogens. For example, DNA adducts have been measured in cells and tissues from people occupationally exposed to carcinogenic polycyclic aromatic hydrocarbons. Antibodies recognizing carcinogen-DNA adducts have also been detected in human sera. Inherited predisposition to cancer has been revealed by recent advances in molecular genetics, including restriction-fragment-length polymorphism. For example, the hypothesis that rare alleles of the Ha-ras proto-oncogene are associated with an increased risk of lung cancer is currently being tested. These approaches afford the potential of biochemical and molecular epidemiology to predict disease risk for individual persons, instead of for populations, and before the onset of clinically evident disease.
Solving large instances of the RSA problem in flexgrid elastic optical networks

We present an optimization procedure that mixes advanced large-scale optimization methods and heuristics to solve large instances (with over 1.7 million integer variables) of the routing and spectrum allocation (RSA) problem - a basic optimization problem in flexgrid elastic optical networks. We formulate the problem as a mixed-integer program for which we develop a branch-and-price algorithm enhanced with such techniques as problem relaxations and cuts for improving lower bounds (LBs) for the optimal objective value, and an RSA heuristic for improving the upper bounds. All these elements are combined into an effective optimization procedure. The results of numerical experiments run on network topologies of different dimensions and with large demand sets show that the algorithm performs well and can be applied to the problem instances that are difficult to solve using commercial solvers such as CPLEX.
Simulated Physician Learning Program Improves Glucose Control in Adults With Diabetes

OBJECTIVE Inexpensive and standardized methods to deliver medical education to primary care physicians (PCPs) are desirable. Our objective was to assess the impact of an individualized simulated learning intervention on diabetes care provided by PCPs. RESEARCH DESIGN AND METHODS Eleven clinics with 41 consenting PCPs in a Minnesota medical group were randomized to receive or not receive the learning intervention. Each intervention PCP was assigned 12 simulated type 2 diabetes cases that took about 15 min each to complete. Cases were designed to remedy specific physician deficits found in their electronic medical record observed practice patterns. General linear mixed models that accommodated the cluster randomized study design were used to assess patient-level change from preintervention to 12-month postintervention of A1C, blood pressure, and LDL cholesterol. The relationship between the study arm and the total of intervention and patient health care costs was also analyzed. RESULTS Intervention clinic patients with baseline A1C ≥7% significantly improved glycemic control at the last postintervention A1C measurement, intervention effect of −0.19% mean A1C (P = 0.034) and +6.7% in A1C <7% goal achievement (P = 0.0099). Costs trended lower, with the cost per patient −$71 (SE = 142, P = 0.63) relative to nonintervention clinic patients. The intervention did not significantly improve blood pressure or LDL control. Models adjusting for age, sex, and comorbidity showed similar results. PCPs reported high satisfaction. CONCLUSIONS A brief individualized case-based simulated learning intervention for PCPs led to modest but significant glucose control improvement in adults with type 2 diabetes without increasing costs.
Unsupervised Information Extraction with Distributional Prior Knowledge

We address the task of automatic discovery of information extraction template from a given text collection. Our approach clusters candidate slot fillers to identify meaningful template slots. We propose a generative model that incorporates distributional prior knowledge to help distribute candidates in a document into appropriate slots. Empirical results suggest that the proposed prior can bring substantial improvements to our task as compared to a K-means baseline and a Gaussian mixture model baseline. Specifically, the proposed prior has shown to be effective when coupled with discriminative features of the candidates.
Quantum Queries for Testing Distributions

We consider probability distributions given in the form of an oracle f : [n]→ [m] that we can query. Here the probability Pf (j) of an outcome j ∈ [m] is the fraction of the domain that is mapped to j by f . We give quantum algorithms for testing whether two such distributions are identical or at least -far in L1-norm. Recently, Bravyi, Hassidim, and Harrow showed that if Pf and Pg are both unknown (i.e., given by oracles f and g), then this testing can be done in roughly √ m quantum queries. We consider the case where the second distribution is known, and show that testing can be done with roughly m quantum queries, which is essentially optimal. In contrast, it is known that classical testing algorithms need about m queries in the unknown-unknown case and about √ m queries in the known-unknown case. Our results can also be used to reduce the query complexity of graph isomorphism testers with quantum oracle access.
Horizontally Scalable Submodular Maximization

A variety of large-scale machine learning problems can be cast as instances of constrained submodular maximization. Existing approaches for distributed submodular maximization have a critical drawback: The capacity - number of instances that can fit in memory - must grow with the data set size. In practice, while one can provision many machines, the capacity of each machine is limited by physical constraints. We propose a truly scalable approach for distributed submodular maximization under fixed capacity. The proposed framework applies to a broad class of algorithms and constraints and provides theoretical guarantees on the approximation factor for any available capacity. We empirically evaluate the proposed algorithm on a variety of data sets and demonstrate that it achieves performance competitive with the centralized greedy solution.
Quantifying computational security subject to source constraints, guesswork and inscrutability

Guesswork forms the mathematical framework for quantifying computational security subject to brute-force determination by query. In this paper, we consider guesswork subject to a per-symbol Shannon entropy budget. We introduce inscrutability rate as the asymptotic rate of increase in the exponential number of guesses required of an adversary to determine one or more secret strings. We prove that the inscrutability rate of any string-source supported on a finite alphabet χ, if it exists, lies between the per-symbol Shannon entropy constraint and log |χ|. We further prove that the inscrutability rate of any finite-order Markov string-source with hidden statistics remains the same as the unhidden case, i.e., the asymptotic value of hiding the statistics per each symbol is vanishing. On the other hand, we show that there exists a string-source that achieves the upper limit on the inscrutability rate, i.e., log |χ|, under the same Shannon entropy budget.
Epidemiology and Treatment of Kaposi’s Sarcoma in HIV-1 Infected Individuals in a Poor Resource Setting

Kaposi’s sarcoma was first described in 1872 by Moritz Kaposi, a Vienna-based Hungarian dermatologist, as a rare multifocal angioproliferative tumour involving blood and lymphatic vessels in elderly men of Jewish origin (Kaposi, 1872). Before the AIDS epidemic three clinico-epidemiological forms with similar histological features have been described. The classic Kaposi’s sarcoma (KS) originally described by Kaposi is primarily a skin disease with a chronic indolent course that can sometimes regress spontaneously (Kaposi, 1872). Most of the cases occurred in elderly men of Mediterranean and Jewish origin. The African-endemic KS is seen in the indigenous population of sub-Saharan Africa (Franceschi & Geddes, 1995). It is also seen more commonly among male patients, but differs from the classic form in that it may affect a younger population and is more likely to spread to visceral organs and lymphatics. In addition, it has a variable clinical presentation ranging from a benign disease with few skin lesions to a widely disseminated disease associated with high morbidity and mortality (Franceschi & Geddes, 1995; Taylor et al 1971). Kaposi’s sarcoma seen in patients as a result of immunosuppression complicating organ transplantation may have chronic or progressive course and spontaneous remission after discontinuation of immunosuppressive therapy is observed in the majority of patients (Penn, 1979). The first description of AIDS-associated Kaposi’s sarcoma (AAKS) was in 1981, when Friedman-Kien et al (1981) reported some previously healthy young homosexual men with Kaposi's sarcoma involving lymph nodes, viscera, and mucosa as well as skin. This was associated with life-threatening opportunistic infections and a profound defect in cellmediated immunity. This aggressive and frequently fatal form of Kaposi's sarcoma is the most common cancer in patients with HIV infection (Schwartz, 2004). Before the discovery and widespread use of highly active antiretroviral therapy (HAART) KS was over 20,000 times more common in AIDS patients than the general population (Engels et al 2006). However, several studies showed that HAART reduced the incidence of KS in high income countries (.Franceschi et al, 2008; Pipkin et al, 2011; Simard et al, 2011). The cumulative incidence of Kaposi sarcoma declined from 14.3% during 1980 to 1989, to 6.7% during 1990
Effect of Graphene Nanoplatelets Fillers on Mechanical Properties and Microstructure of Cast Aluminum Matrix Composites

Recently, many studies on the production of graphite/graphene reinforced aluminum-matrix composites using different fabrication methods, such as powder or semi-powder method, have been performed. However, cast aluminum/graphite or aluminum/graphene composites have not been widely investigated and the research on this production method mainly focuses on 3D graphite particle reinforcements. In this study, the use of a 2D graphene structure, i.e. graphene nanoplatelets (GNPs), in the production of cast Al/GNP composites is investigated. Graphene nanoplatelets reinforced cast aluminum matrix composites were produced using aluminum alloy as matrix material and different graphene nanoplatelets contents. Specimens were cast into a heated rectangular steel mold, the temperature of which was 100°C. All specimens underwent tensile and bending tests as well as hardness measurements and microstructural investigation. Ultimate Tensile Strength (UTS) was considerably increased, simultaneously with a slight decrease of elongation at break, in the case of 0.1 wt% graphene nanoplatelets addition. Regarding bending performance, a slight increase was observed as well. The flexural behavior for 0.1 wt% graphene nanoplatelets addition was exactly the same with the matrix material. The graphene nanoplatelets content found to affect both the surface and the chemical composition of the interdendritic region. After 0.1 wt%, further increase of the wt% graphene nanoplatelets content lead to formation of aluminum carbides (Al4C3) at the grain boundaries, with a consequent drop on the mechanical performance of the Al/GNPs composite.
IMPACT OF CONSTELLATION DESIGN ON DOPPLER-RATE BASED MT POSITIONING FOR SATELLITE-UMTS

User position information is an important factor for achieving efficient operation of global wireless networks. It reduces the signalling load generated as a normal consequence of service provision. The basic constellation parameters that should be optimised in the design of the satellite segment of third generation wireless telecommunication networks (i.e., S-UMTS) to provide fast and accurate user location using a positioning technique based on time delay, Doppler shift and Doppler-rate measurements are discussed and analysed. In particular, orbit altitude, angle between planes and satellite spacing that provide the highest possible accuracy are derived from the simulation results presented in this paper.