Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of One-forms on P-adic Analytic Spaces.

Among the many differences between classical and p-adic objects, those related to differential equations occupy a special place. For example, a closed p-adic analytic one-form defined on a simply-connected domain does not necessarily have a primitive in the class of analytic functions. In the early 1980s, Robert Coleman discovered a way to construct primitives of analytic one-forms on certain smooth p-adic analytic curves in a bigger class of functions. Since then, there have been several attempts to generalize his ideas to smooth p-adic analytic spaces of higher dimension, but the spaces considered were invariably associated with algebraic varieties. This book aims to show that every smooth p-adic analytic space is provided with a sheaf of functions that includes all analytic ones and satisfies a uniqueness property. It also contains local primitives of all closed one-forms with coefficients in the sheaf that, in the case considered by Coleman, coincide with those he constructed. In consequence, one constructs a parallel transport of local solutions of a unipotent differential equation and an integral of a closed one-form along a path so that both depend nontrivially on the homotopy class of the path. Both the author's previous results on geometric properties of smooth p-adic analytic spaces and the theory of isocrystals are further developed in this book, which is aimed at graduate students and mathematicians working in the areas of non-Archimedean analytic geometry, number theory, and algebraic geometry.
Improved Lagrange Nonlinear Programming Neural Networks for Inequality Constraints

By redefining multiplier associated with inequality constraint as a positive definite function of the originally-defined multiplier, u2 j ,i = 1,2, ----, m, say, the nonnegative constraints imposed on inequality constraints in Karush-Kuhn-Tucker necessary conditions are removed completely. Hence it is no longer necessary to convert inequality constraints into equality constraints by slack variables in order to reuse those results concerned only with equality constraints. Utilizing this technique, improved Lagrange nonlinear programming neural networks are devised, which handle inequality constraints directly without adding slack variables. Then the local stability of the proposed Lagrange neural networks is analyzed rigourously with Liapunov's first approximation principle, and its convergence is discussed deeply with LaSalle's invariance principle. Finally, an illustrative example shows that the proposed neural networks can effectively solve the nonlinear programming problems.
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons

This paper explores the computational consequences of simultaneous intrinsic and synaptic plasticity in individual model neurons. It proposes a new intrinsic plasticity mechanism for a continuous activation model neuron based on low order moments of the neuron's firing rate distribution. The goal of the intrinsic plasticity mechanism is to enforce a sparse distribution of the neuron's activity level. In conjunction with Hebbian learning at the neuron's synapses, the neuron is shown to discover sparse directions in the input.
A Model for User Trust in Cloud Computing

Cloud has proved to be a suitable choice for providing computing and storage resources especially for small and medium sized businesses in recent years. The “pay per usage” cost model, on demand computing, large scale storage resource with easy access, and freeing users from managing and maintaining resources are among the important factors that have made cloud an attractive choice for such services. The issue of low trust on cloud computing is an obstacle, one of the major obstacle to its pervasive deployment, particularly in case of critical data storage on the provider’s datacenter. This paper presents a model for trust in cloud computing, accounting for important elements which shape the users trust and a way of evaluating each element’s importance.
A Senior Project-Based Multiphase Motor Drive System Development

Adjustable-speed drives based on multiphase motors are of significant interest for safety-critical applications that necessitate wide fault-tolerant capabilities and high system reliability. Although multiphase machines are based on the same conceptual theory as three-phase machines, most undergraduate electrical machines and electric drives courses do not cover this topic. Setting aside the analysis challenges addressed in state-of-the-art literature, undergraduate electrical machines and power electronics courses are a good opportunity for students to understand the main concepts underlying such electric drive systems. This paper presents an adjustable-speed multiphase drive system senior project for electrical engineering undergraduate students that addresses their attainment of the course's learning outcomes. Eight of the course's students were assigned to build the multiphase variable-speed motor drive system. From a pedagogical point of view, this paper describes the methodology of using a senior project to engage students through experiential learning of electric drive systems, which span disciplines such as electrical machines, control, power electronics, and electronics. Students acquire both technical skills and soft skills, which are evaluated through various assessment activities. A number of lessons for future work have been drawn from the experience of applying this project-based learning approach.
Extending MapReduce across Clouds with BStream

Today, batch processing frameworks like Hadoop MapReduce are difficult to scale to multiple clouds due to latencies involved in inter-cloud data transfer and synchronization overheads during shuffle-phase. This inhibits the MapReduce framework from guaranteeing performance at variable load surges without over-provisioning in the internal cloud (IC). We propose BStream, a cloud bursting framework for MapReduce that couples stream-processing in the external cloud (EC) with Hadoop in the internal cloud (IC). Stream processing in EC enables pipelined uploading, processing and downloading of data to minimize network latencies. We use this framework to meet job deadlines. BStream uses an analytical model to minimize the usage of EC. We propose different checkpointing strategies that overlap output transfer with input transfer/processing and simultaneously reduce the computation involved in merging the results from EC and IC. Checkpointing further reduces job completion time. We experimentally compare BStream with other related works and illustrate performance benefits due to stream processing and checkpointing strategies in EC. Lastly, we characterize the operational regime of BStream.
Markerless Motion Capture for Humans in Video

This proposal concerns automating the motion capture of humans. Motion capture is defined as “The creation of a 3D representation of a live performance” in the book Understanding Motion Capture for Computer Animation and Video Games by Alberto Menache [20]. Specifically, we propose to develop a new framework for human motion capture based on recent advances in Bayesian object detection and tracking. Motion capture of humans is a key operation in film and game production, and is also useful for medical applications, ergonomics, and virtual reality. At present it is an expensive process, requiring special equipment and much user intervention. The proposal is to investigate new, state of the art, methods in tracking and object detection to obviate the need for specialized environments or equipment.
Automated database design for large-scale scientific applications

The need for large-scale scientific data management is today more pressing than ever, as modern sciences need to store and process terabyte-scale data volumes. Traditional systems, relying on filesystems and custom data access and processing code do not scale for multi-terabyte datasets. Therefore, supporting today's data-driven sciences requires the development of new data management capabilities. This Ph.D dissertation develops techniques that allow modern Database Management Systems (DBMS) to efficiently handle large scientific datasets. Several recent successful DBMS deployments target applications like astronomy, that manage collections of objects or observations (e.g. galaxies, spectra) and can easily store their data in a commercial relational DBMS. Query performance for such systems critically depends on the database physical design, the organization of database structures such as indexes and tables. This dissertation develops algorithms and tools for automating the physical design process. Our tools allow databases to tune themselves, providing efficient query execution in the presence of large data volumes and complex query workloads. For more complex applications dealing with multidimensional and time-varying data, standard relational DBMS are inadequate. Efficiently supporting such applications requires the development of novel indexing and query processing techniques. This dissertation develops an indexing technique for unstructured tetrahedral meshes, a multidimensional data organization used in finite element analysis applications. Our technique outperforms existing multidimensional indexing techniques and has the advantage that can easily be integrated with standard DBMS, providing existing systems with the ability to handle spatial data with minor modifications.
Senti-LSSVM: Sentiment-Oriented Multi-Relation Extraction with Latent Structural SVM

Extracting instances of sentiment-oriented relations from user-generated web documents is important for online marketing analysis. Unlike previous work, we formulate this extraction task as a structured prediction problem and design the corresponding inference as an integer linear program. Our latent structural SVM based model can learn from training corpora that do not contain explicit annotations of sentiment-bearing expressions, and it can simultaneously recognize instances of both binary (polarity) and ternary (comparative) relations with regard to entity mentions of interest. The empirical evaluation shows that our approach significantly outperforms state-of-the-art systems across domains (cameras and movies) and across genres (reviews and forum posts). The gold standard corpus that we built will also be a valuable resource for the community.
THE IMMUNOGLOBULINS OF MICE

Two subclasses of mouse 7S γ2-globulins are identified, and are designated γ2a- and γ2b-globulins. They are distinguished from 7S γ1-globulins, γ1A (β2A)-globulins, and γ1M-globulins of mouse serum. Antibody activity was detected among the γ2a-globulins and γ2b-globulins of hyperimmune mouse serum. γ2a- and γ2b-myeloma proteins were identified. The genetically determined isoantigen, Iga-1, was present on γ2a-myeloma proteins, but not on γ2b-myeloma proteins. These findings indicate a complexity among the 7S γ2-globulins which must be taken into account in structural, functional, and genetic studies of immunoglobulins.
Terahertz-regime realization and optical characterization of two-dimensional photonic crystal waveguides on a silicon-on-insulator (SOI) substrate

A terahertz-scale two-dimensional photonic-crystal waveguide based on a silicon-on-insulator was fabricated, and the optical transmission spectrum was measured. Terahertz beam propagation characteristics were observed using a thermal imaging camera, with incident light in the 10.1-10. 7μm range. The measured transmission spectrum was in very good agreement with a three-dimensional finite-difference time-domain calculation.
Keyboard-Card Menus: A New Presentation of Non-Standard Shortcuts

Keyboard-card menus" are a new type of menu system in which poten- tially hundreds of menu items are arranged in sets of keyboard patterns that are de- signed to be navigated using only a computer keyboard's character keys, for fast access. In selecting items from these menus, novice users physically rehearse the same actions that an expert would use. We describe these menus and their potential applications in further detail, along with a study comparing keyboard-card menus' presentation of what are effectively shortcuts with a presentation of these same shortcuts that uses dropdown menus. The data from our study shows that keyboard-card menus have significant advantages over dropdown menus in making the transition to expert use faster.
Polymer Photovoltaic Cells

1Introduction Polymer photovoltaic cells (PPVCs) have attracted much attention recently because of its easy fabrication, low cost and possibility to make flexible devices[1]. PPVC is composed of a conjugated polymer/C60blend layer (photosensitive layer) sandwiched between a transparent ITO electrode and a metal electrode.When a light through ITO electrode irradiates on the photosensitive layer, the photons with appropriate energy will be absorbed by the conjugated polymer (CP) and excitons (electron-hole pair) are produced. The excitons move to the interface of CP/C60 where the electrons transfer to the LUMO of C60 and holes leave on the HOMO of the CP. The separated electrons migrate through the C60 network to and are collected by the metal electrode, and the holes migrate through the CP network to and are collected by the ITO electrode, so that the photocurrent and photovoltage are attained.
A unified framework for external wrench estimation, interaction control and collision reflexes for flying robots

Flying in unknown environments can lead to unwanted collisions with the environment. If not being accounted for, these may cause serious damage to the robot and/or its environment. Fast and robust collision detection combined with safe reaction is therefore essential in this context. Deliberate physical interaction may also be required in some applications. The robot can then switch into an interaction mode when contact occurs. The control loop must also be designed with interaction in mind. To implement these mechanisms, knowledge of environmental interaction forces is required. In principle, they may be measured or estimated. In this paper, we present a novel model-based method for external wrench estimation in flying robots. The estimation is based on proprioceptive sensors and the robot's dynamics model only. Using this estimate, we also design admittance and impedance controllers for sensitive and robust physical interaction. We also investigate the performance of our collision detection and reaction schemes in order to guarantee collision safety. Upon collision, we determine the collision location and normal located on the robot's geometric model. The method relies on the complete wrench information provided by our scheme. This allows applications such as tactile environment mapping.
The Emerging Role of Branched-Chain Amino Acids in Insulin Resistance and Metabolism

Insulin is required for maintenance of glucose homeostasis. Despite the importance of insulin sensitivity to metabolic health, the mechanisms that induce insulin resistance remain unclear. Branched-chain amino acids (BCAAs) belong to the essential amino acids, which are both direct and indirect nutrient signals. Even though BCAAs have been reported to improve metabolic health, an increased BCAA plasma level is associated with a high risk of metabolic disorder and future insulin resistance, or type 2 diabetes mellitus (T2DM). The activation of mammalian target of rapamycin complex 1 (mTORC1) by BCAAs has been suggested to cause insulin resistance. In addition, defective BCAA oxidative metabolism might occur in obesity, leading to a further accumulation of BCAAs and toxic intermediates. This review provides the current understanding of the mechanism of BCAA-induced mTORC1 activation, as well as the effect of mTOR activation on metabolic health in terms of insulin sensitivity. Furthermore, the effects of impaired BCAA metabolism will be discussed in detail.
How “suspicious” is that nodule? Review of “suspicious” Afirma gene expression classifier in high risk thyroid nodules

The Afirma gene expression classifier (GEC) is being increasingly utilized to confirm the benign nature of indeterminate FNA cytology results thus avoiding unnecessary surgical procedures. However the “suspicious” result of the Afirma GEC does not classify these indeterminate nodules further in determining appropriate management. This study investigated the outcome of the thyroid nodules deemed to be “suspicious” by the Afirma GEC in a high risk population.
Association of Oxidative DNA Damage and C-Reactive Protein in Women at Risk for Cardiovascular Disease

Objective—The aim of the current study was to examine the relationship between clinical markers of inflammation and 8-oxo-7,8-dihydro-2′deoxyguanosine (8-oxodG), an oxidative stress marker, in middle-aged women drawn from the HANDLS study, a longitudinal epidemiological study. Methods and Results—We examined commonly assayed markers of inflammation, the DNA base adduct 8-oxodG, a marker of oxidative stress, and cardiovascular risk factors in a cohort of women matched on age and race in 3 groups (n=39 per group) who had low (<3 mg/L) high-sensitivity C-reactive protein (hsCRP), mid (>3–20 mg/L), and high (>20 mg/L) hsCRP. We found a significant relationship between hsCRP level and the oxidative stress marker, 8-oxodG. 8-oxodG was positively correlated with systolic blood pressure, pulse pressure, and interleukin-23. hsCRP was associated with obesity variables, high-density lipoprotein, serum insulin levels, interleukin-12p70 and intracellular adhesion molecule-1. Incubation of primary human endothelial cells with hsCRP generated reactive oxygen species in vitro. Furthermore, hsCRP specifically induced DNA base lesions, but not other forms of DNA damage, including single and double strand breaks. Conclusion—These data suggest that in women 8-oxodG is associated with hsCRP and is independently related to select cardiovascular risk factors. Our data in women suggest that hsCRP may contribute to cardiovascular disease by increasing oxidative stress.
Moisture Effects on PVD and DCP Measurements

This study deals with the experimental investigation of the effects of moisture and density on the elastic moduli and strength of four subgrade soils generally representing the range of road conditions in Minnesota. The testing approach involved i) reduced-scale simulation of field compaction, ii) field-type testing on prismatic soil volumes, and iii) element testing on cylindrical soil specimens. The field-type testing included: i) the GeoGauge, ii) the PRIMA 100 device, iii) the modified light weight deflectometer (LWD) device, iv) the portable vibratory deflectometer (PVD) and v) the Dynamic Cone Penetrometer (DCP). To compare the Young's modulus values stemming from the field-type and laboratory experiments, cylindrical specimens were extracted from the prismatic soil volumes and tested for the resilient modulus (M sub r), small-strain Young's modulus using bender elements. The results reveal that both moisture and density have a measurable effect on the elastic modulus and strength of all four soils. On the element testing side, the small strain estimates from the bender element tests were in good agreement with the resilient modulus values. In the context of field testing, there was significant scatter of the estimated Young's moduli depending upon the particular testing device.
Mercaptopurine therapy intolerance and heterozygosity at the thiopurine S-methyltransferase gene locus.

BACKGROUND Patients with acute lymphoblastic leukemia are often treated with 6-mercaptopurine, and those with homozygous deficiency in thiopurine S-methyltransferase (TPMT) enzyme activity have an extreme sensitivity to this drug as a result of the accumulation of higher cellular concentrations of thioguanine nucleotides. We studied the metabolism, dose requirements, and tolerance of 6-mercaptopurine among patients with different TPMT phenotypes. METHODS We compared, by use of statistical modeling, 6-mercaptopurine pharmacology and tolerance in 180 patients who achieved remission on St. Jude Children's Research Hospital Protocol Total XII composed of weekly methotrexate (40 mg/m(2)) and daily oral 6-mercaptopurine (75 mg/m(2)) given for 2.5 years, interrupted every 6 weeks during the first year for treatment with either high-dose methotrexate or teniposide plus cytarabine. Statistical tests were two-sided. RESULTS Erythrocyte concentrations of thioguanine nucleotides (pmol/8 x 10(8) erythrocytes) were inversely related to TPMT enzyme activity (P<.01), with averages (+/- standard deviations) of 417 (+/-179), 963 (+/-752), and 3565 (+/-1282) in TPMT homozygous wild-type (n = 161), heterozygous (n = 17), and homozygous-deficient (n = 2) patients, respectively. There was complete concordance between TPMT genotype and phenotype in a subset of 28 patients for whom TPMT genotype was determined. There were no sex differences in thioguanine nucleotide concentrations (P =.24), TPMT enzyme activity (P =.22), or average weekly prescribed dose of 6-mercaptopurine (P=.49). The cumulative incidence of 6-mercaptopurine dose reductions due to toxicity was highest among patients homozygous for mutant TPMT (100%), intermediate among heterozygous patients (35%), and lowest among wild-type patients (7%) (P<.001), with average (+/- standard deviation) final weekly 6-mercaptopurine doses of 72 (+/-60), 449 (+/-160), and 528 (+/-90) mg/m(2), respectively. Lowering doses of 6-mercaptopurine in TPMT heterozygotes and in deficient patients allowed administration of full protocol doses of other chemotherapy while maintaining high thioguanine nucleotide concentrations. CONCLUSION We conclude that genetic polymorphism in TPMT is an important determinant of mercaptopurine toxicity, even among patients who are heterozygous for this trait.
Body Weight, Metabolic Dysfunction, and Risk of Type 2 Diabetes in Patients at High Risk for Cardiovascular Events or With Manifest Cardiovascular Disease: A Cohort Study

OBJECTIVE To quantify the role of BMI and metabolic dysfunction in the risk of development of type 2 diabetes in patients at high risk or with manifest vascular disease. RESEARCH DESIGN AND METHODS A total of 6,997 patients participating in the prospective Secondary Manifestations of ARTerial disease (SMART) cohort study were classified according to BMI and metabolic dysfunction, defined as three or more of the modified National Cholesterol Education Program (NCEP) metabolic syndrome criteria (waist circumference replaced by hs-CRP ≥2 mg/L). Risk of type 2 diabetes (assessed with biannually questionnaires) was estimated with Cox proportional hazards analysis. RESULTS During a median follow-up of 6.0 years (interquartile range 3.1–9.1 years), 519 patients developed type 2 diabetes (incidence rate 12/1,000 person-years). In the absence of metabolic dysfunction (≤2 NCEP criteria), adiposity increased the risk of type 2 diabetes compared with normal-weight patients (HR 2.5 [95% CI 1.5–4.2] for overweight and HR 4.3 [95% CI 2.2–8.6] for obese patients). In the presence of metabolic dysfunction (≥3 NCEP criteria), an increased risk of type 2 diabetes was observed in patients with normal weight (HR 4.7 [95% CI 2.8–7.8]), overweight (HR 8.5 [95% CI 5.5–13.4]), and obesity (HR 16.3 [95% CI 10.4–25.6]) compared with normal-weight patients without metabolic dysfunction. CONCLUSIONS Adiposity, even in the absence of metabolic dysfunction, is a risk factor for type 2 diabetes. Moreover, presence of metabolic dysfunction increases the risk of type 2 diabetes in all BMI categories. This supports the assessment of adiposity and metabolic dysfunction in patients with vascular disease or at high risk for cardiovascular events.