Miracle-dz/UniFAR-FTUs huggingface dataset:
Event Driven Modeling and Characterization of the Second Order Voltage Switched Charge Pump PLL

The charge pump phase locked loop (CP-PLL) is widely used subsystem in modern mixed-signal electronic systems that are utilized in digital and wireless applications such as clock generation, synchronization and frequency synthesis. In the classical mode, the combination of a current switched charge pump and a digital phase and frequency detector (CP-PFD) circuits produces an ideal pulse width modulated constant current during one sampling period, which permits a suitable transient performance. Nevertheless, many commercially used CP-PLL chips (e.g., 4046 family) have a voltage switched charge pump (VSCP) because the design of the constant voltage source is easier than the constant current generator and it is a low cost solution. However, the VSCP delivers a non-constant pump current, which varies during one sampling period related to the electrical load of the loop filter (LF). This effect results in a varying gain of the control system affecting significantly its tracking ability. Furthermore, due to its hybrid structure, the simulation of the CP-PLL at high frequencies is challenging and the analysis of its transient characteristics during its non-linear acquisition procedure is not easy. In this paper, a first ever exact and nonlinear model based on the phase equations of the second order voltage switched charge pump phase locked loop (VSCP-PLL) is established by using an event driven (ED) technique. This exact model is then simplified by using a step-wise quasi-constant current approximation during one sampling period to obtain the analytical phase equations. The derived ED-model is validated at transistor level simulations using 130 nm CMOS process. Furthermore, some typical nonlinear features of the VSCP-PLL are explored and the developed ED-models are compared with the quasi-time-continuous (QTC) theory.
Effect of Different Auxin Concentrations on Virginia Creeper (Parthenocissus quinquefolia) Rooting

Parthenocissus plant is one of the most attractive outdoor deciduous vines; provides deep green cover to most any object, rapidly climbing by means of tendrils and adhesive disks, can be espaliered against a wall and provides great visual appeal during winter when the leaves have fallen. Rooting the cutting of this plant is difficult without using a rooting hormone, so the present research project was investigated to find out the optimum auxin (NAA) hormone concentration on rooting of this plant. Six treatments (0, 1000, 2000, 3000, 4000 and 5000 ppm NAA) were used in a completely randomized design (CRD) with four replicates. Results showed that in most cases cuttings treated with 1000 ppm NAA produced the best results or results which are not significantly different from the higher concentrations of NAA, so it's better to save in using the auxin hormone and use the lowest concentration in rooting the parthenocissus hard wood cuttings.
Transcriptional Regulation of the Yeast DnaJ Homologue SIS1(*)

The Saccharomyces cerevisiae SIS1 gene encodes an essential heat shock protein with similarity to the Escherichia coli DnaJ protein. In sis1-85 and sis1-86 mutants, the sis1 RNA is induced to high levels at room temperature and without heat shock. The presence of wild type SIS1 in the sis1-85 mutant represses the overexpression of SIS1-85 protein. Furthermore, overexpression of wild type SIS1 reduces the β-galactosidase activity expressed from a SIS1:lacZ fusion. These results suggest that SIS1 negatively regulates its own expression. The autoregulation of SIS1 transcription is mediated through a 39-base pair cis-element containing the SIS1 heat shock element plus additional flanking sequences on one side. Although SIS1 transcription is constitutive, it is transiently induced upon heat shock. In addition, SIS1 transcription is regulated by SSA (a class of HSP70 proteins) function. The elevated transcription of SIS1 in ssa1 ssa2 mutants is mediated solely through the SIS1 heat shock element. Therefore, the SIS1 autoregulatory element is different from the SSA-responsive element, suggesting that the mechanism involved in autoregulation of SIS1 is distinct from regulation of SIS1 by SSA proteins.
On the logspace shortest path problem

In this paper, we reduce the logspace shortest path problem to biconnected graphs; in particular, we present a logspace shortest path algorithm for general graphs which uses a logspace shortest path oracle for biconnected graphs. We also present a linear time logspace shortest path algorithm for graphs with bounded vertex degree and biconnected component size, which does not rely on an oracle. The asymptotic timespace product of this algorithm is the best possible among all shortest path algorithms.
Ontology for Multi-surface Interaction

Digital computation is a powerful source of functional support. However, it has been confined to the augmentation of single objects only. In this article, we are interested in the combination of physicality with computation in the context of multiple objects. We propose the notion of multi-surface interaction as a unifying paradigm for reasoning about both emerging distributed UI’s and known interaction techniques such as GUIs, tangible UIs, and manipulable UIs. Multi-surface interaction is expressed within an ontology that shows how our concepts feed into the design of sound foundational software for the development of ubiquitous user interfaces.
Partially Parallel MR Spectroscopic Imaging of Gliomas at 3T

Magnetic resonance spectroscopic imaging (MRSI) has been used to more accurately diagnose, localize, and assess progression and treatment response for gliomas. The main limitation of the MRSI is the long data acquisition times. A current approach is to reduce the amount of k-space data sampled by limiting the data acquisition to a central elliptical portion of k-space. This study investigated the feasibility of reducing the data acquisition time further for the MRSI data using two parallel imaging techniques and investigating the relative performance of sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA)
Exact Post-Selection Inference for Changepoint Detection and Other Generalized Lasso Problems

We study tools for inference conditioned on model selection events that are defined by the generalized lasso regularization path. The generalized lasso estimate is given by the solution of a penalized least squares regression problem, where the penalty is the l1 norm of a matrix D times the coefficient vector. The generalized lasso path collects these estimates for a range of penalty parameter ({\lambda}) values. Leveraging a sequential characterization of this path from Tibshirani & Taylor (2011), and recent advances in post-selection inference from Lee et al. (2016), Tibshirani et al. (2016), we develop exact hypothesis tests and confidence intervals for linear contrasts of the underlying mean vector, conditioned on any model selection event along the generalized lasso path (assuming Gaussian errors in the observations). By inspecting specific choices of D, we obtain post-selection tests and confidence intervals for specific cases of generalized lasso estimates, such as the fused lasso, trend filtering, and the graph fused lasso. In the fused lasso case, the underlying coordinates of the mean are assigned a linear ordering, and our framework allows us to test selectively chosen breakpoints or changepoints in these mean coordinates. This is an interesting and well-studied problem with broad applications, our framework applied to the trend filtering and graph fused lasso serves several applications as well. Aside from the development of selective inference tools, we describe several practical aspects of our methods such as valid post-processing of generalized estimates before performing inference in order to improve power, and problem-specific visualization aids that may be given to the data analyst for he/she to choose linear contrasts to be tested. Many examples, both from simulated and real data sources, are presented to examine the empirical properties of our inference methods.
Empathy-Based Conservation: An Interdisciplinary Approach to Conservation Policy and Decision-Making

Introduction In the late 20 th century, neuroscientists in Italy discovered a neuron in the brain capable of mentally mimicking the emotions derived from the actions of others (Rizzolatti and Craighero, 2004). It is the process that makes your elbow ache when someone else knocks their elbow on the counter or the uncontrollable smile that creeps up when someone smiles at you. No questions asked, people intuitively sense what others are feeling. The old school of thought was that humans deduced through logic and reason the actions of others and interpreted the emotions through a rational process (Carew et al, 2008). As neuroscience progresses, they have discovered more and more about how much people rely on their emotions to interact with others and make decisions. The mirror neurons in our brains allow us to make judgments about situations without being completely conscious of them. But when those emotions become conscience, it is often referred to as the act of empathizing with someone or, more simply put, walking in the other person's shoes. What could this have to do with conservation? The choices people make to recycle, reduce consumption, and reuse everyday products often comes not because of our rationalization of the activity through scientific fact, but because we are empathizing with someone or something. People have changed their conservation behavior due to feelings for the plight of penguins losing their arctic habitat, someone in another country not having access to the same comforts they enjoy, or a neighbor downstream drinking polluted water. They also choose to abide by the laws of game wardens when hunting to make sure population levels are sustainable and enter into agreements such as the Conservation Reserve Program to make habitat for animals and promote ecosystem health. Regardless of what side of the fence they sit on, people make all sorts of decisions based on emotions, whether they empathize with their future great-grand children or the animals themselves. It seems like common sense that we are, at base, emotional beings. Most economic theories, however, are not based on such an irrational means of making choices. Those neoclassical economic theories rely on the assumption that we are all rational, self-interested beings that will always act in a way to maximize profit or utility. This is a dangerous assumption since it literally controls the formulas on which the U.S. economy bases growth, price, and prosperity. So if the …
Cross-modal individual recognition in domestic horses (Equus caballus) extends to familiar humans

It has recently been shown that some non-human animals can cross-modally recognize members of their own taxon. What is unclear is just how plastic this recognition system can be. In this study, we investigate whether an animal, the domestic horse, is capable of spontaneous cross-modal recognition of individuals from a morphologically very different species. We also provide the first insights into how cross-modal identity information is processed by examining whether there are hemispheric biases in this important social skill. In our preferential looking paradigm, subjects were presented with two people and playbacks of their voices to determine whether they were able to match the voice with the person. When presented with familiar handlers subjects could match the specific familiar person with the correct familiar voice. Horses were significantly better at performing the matching task when the congruent person was standing on their right, indicating marked hemispheric specialization (left hemisphere bias) in this ability. These results are the first to demonstrate that cross-modal recognition in animals can extend to individuals from phylogenetically very distant species. They also indicate that processes governed by the left hemisphere are central to the cross-modal matching of visual and auditory information from familiar individuals in a naturalistic setting.
Optimal parameter estimation for model-based quantization

We address optimal model estimation for model-based vector quantization for both the constrained resolution (CR) and constrained entropy (CE) cases. To this purpose we derive under high-rate (HR) theory assumptions the rate-distortion (RD) relations for these two quantization scenarios assuming a Gaussian model. Based on the RD relations we show that the maximum likelihood (ML) criterion leads to optimal performance for CE quantization, but not for CR quantization. We introduce a new model estimation criterion for CR quantization that is optimal (under HR theory assumptions) in terms of the RD relation. Our experiments confirm that the proposed criterion for model identification outperforms the ML criterion for a range of conditions.
Learning from Pairwise Marginal Independencies

We consider graphs that represent pairwise marginal independencies amongst a set of variables (for instance, the zero entries of a covariance matrix for normal data). We characterize the directed acyclic graphs (DAGs) that faithfully explain a given set of independencies, and derive algorithms to efficiently enumerate such structures. Our results map out the space of faithful causal models for a given set of pairwise marginal independence relations. This allows us to show the extent to which causal inference is possible without using conditional independence tests.
Current status and impact of CMV prevention following pediatric organ transplantation

Cytomegalovirus (CMV) is arguably the most important opportunistic viral infection affecting transplant recipients. The effects of this virus may be manifested by direct end-organ disease (1) and indirectly through interaction with the immune system and with other opportunistic pathogens (2). The direct effects are well described and include a variety of diseases, including pneumonitis, hepatitis, enteritis, and the CMV syndrome among other entities (1). The indirect effects of CMV are less clearly defined and in many situations, the relative contribution of CMV to the particular clinical syndrome is inconsistent (3). These entities include, but are not limited to allograft rejection, bronchiolitis obliterans, vanishing bile ducts, cardiac vasculopathy, glomerulovasculopathy, invasive fungal infections, and Epstein-Barr virus-related posttransplant lymphoproliferative disorder (PTLD).
Prehypertension and the risk of stroke

Objective: In this meta-analysis, we sought to evaluate the association between prehypertension and the risk of stroke. Methods: We searched PubMed and EMBASE databases for studies with data on prehypertension and stroke. Two independent reviewers assessed the reports and extracted data. Prospective studies were included if they reported multivariate-adjusted relative risks (RRs) with 95% confidence intervals (CIs) for the associations between stroke and prehypertension or its 2 subranges (low-range prehypertension: 120–129/80–84 mm Hg; high-range prehypertension: 130–139/85–89 mm Hg). We conducted subgroup analyses according to blood pressure ranges, stroke type, endpoint, age, sex, ethnicity, and study characteristics. Results: Pooled data included the results of 762,393 participants from 19 prospective cohort studies. Prehypertension increased the risk of stroke (RR 1.66; 95% CI 1.51–1.81) compared with optimal blood pressure (<120/80 mm Hg). In the secondary outcome analyses, even low-range prehypertension increased the risk of stroke (RR 1.44; 95% CI 1.27–1.63), and the risk was greater for high-range prehypertension (RR 1.95; 95% CI 1.73–2.21). The RR was higher with high-range than with low-range prehypertension (p < 0.001). There were no significant differences in any of the subgroup analyses (all p > 0.05). Conclusions: After adjusting for multiple cardiovascular risk factors, prehypertension is associated with stroke morbidity. Although the increased risk is largely driven by high-range prehypertension, the risk is also increased in people with low-range prehypertension.
Unsupervised Clustering : A Fast Scalable Method forLarge Datasets

Fast and eeective unsupervised clustering is a fundamental tool in unsupervised learning. Here is a new method to explore large datasets that enjoys many favorable properties. It is fast and eeective, and produces a hierarchical structure on the underlying dataset, without using a training set. It also yields auxiliary information on the signiicance of the diierent attributes.
Genetic map construction with R / qtl

Genetic map construction remains an important prerequisite for quantitative trait loci analysis in organisms for which genomic sequence is not available. Surprisingly little has been written about the construction of genetic maps, particularly regarding the many practical issues involved. We provide an overview of the process, including a description of the key facilities in the R/qtl software. The process is illustrated through simulated data on an F2 intercross derived from two inbred strains. email : broman@wisc.edu
Comparing object alignment algorithms with appearance variation: Forward-additive vs inverse-composition

A common problem that affects object alignment algorithms is when they have to deal with objects with unseen intra-class appearance variation. Several variants based on gradient-decent algorithms, such as the Lucas-Kanade (or forward-additive) and inverse-compositional algorithms, have been proposed to deal with this issue by solving for both alignment and appearance simultaneously. In , Baker and Matthews showed that without appearance variation, the inverse-compositional (IC) algorithm was theoretically and empirically equivalent to the forward-additive (FA) algorithm, whilst achieving significant improvement in computational efficiency. With appearance variation, it would be intuitive that a similar benefit of the IC algorithm would be experienced over the FA counterpart. However, to date no such comparison has been performed. In this paper we remedy this situation by performing such a comparison. In this comparison we show that the two algorithms are not equivalent due to the inclusion of the appearance variation parameters. Through a number of experiments on the MultiPIE face database, we show that we can gain greater refinement using the FA algorithm due to it being a truer solution than the IC approach.
Correlated Flicker Noise and Hole Mobility Characteristics of ( 110 ) / < 110 > Uniaxially Strained SiGe

Hole mobility and flicker noise characteristics of uniaxially strained (110)/<110> Si0.75Ge0. 25 pFINFETs (SSGOI0.25) are investigated in this letter. Equivalent gate referred flicker noise in SSGOI0.25 is dominated by correlated number and mobility fluctuation in the low bias regime and Hooge mobility flucutation in the high bias regime. The extracted Hooge parameter in SSGOI0.25 and in Si pFINFETs is 10 -5 and 10, respectively. Lower value of Hooge parameter in SSGOI0.25 pFINFETs is attributed to improved phonon limited mobility compared to the SOI pFINFETs. SSGOI0.25FINFETs are found to exhibit the lowest equivalent gate referred flicker noise among any non-planar devices reported till date.
Higher Chow groups and etale cohomology

The main purpose of the present paper is to relate the higher Chow groups of varieties over an algebraically closed field introduced by S.Bloch [B1] to etale cohomology. We follow the approach suggested by the auther in 1987 during the Lumini conference on algebraic K-theory. The first and most important step in this direction was done in [SV1], where singular cohomology of any qfh-sheaf were computed in terms of Ext-groups. The difficulty in the application of the results of [SV1] to higher Chow groups lies in the fact that a priori higher Chow are not defined as singular homology of a sheaf. To overcome this difficulty we prove that for an affine varietie X higher Chow groups CH (X,n) of codimension i ≤ dimX may be computed using equidimensional cycles only(this is done in the first two sections of the paper). In section 3 we generalize this result to all quasiprojective varieties over a field of characteristic zero. Together with the main theorem of [SV1] this result shows that for an equidimensional quasiprojective variety X over an algebraically closed field F of characteristic zero the higher Chow groups of codimension d = dimX with finite coefficients Z/m are dual to Ext∗qfh(z0(X),Z/m), where z0(X) is the qfh-sheaf of equidimensional cycles of relative dimension zero, introduced and studied in [SV2]. The above Ext-groups are easy to compute and in this way we come to the following main result
Degraded Compound Multi-Receiver Wiretap Channels

We study the degraded compound multi-receiver wiretap channel (DCMRWC). DCMRWC consists of two groups of users and a group of eavesdroppers, where, if we pick an arbitrary user from each group of users and an arbitrary eavesdropper, they satisfy a certain Markov chain. We study two different communication scenarios for this channel. In the first scenario, the transmitter wants to send a confidential message to users in the first (stronger) group and a different confidential message to users in the second (weaker) group, where both messages need to be kept confidential from the eavesdroppers. For this scenario, we assume that there is only one eavesdropper. We obtain the secrecy capacity region for the discrete memoryless channel model, the parallel channel model, and the Gaussian parallel channel model. For the Gaussian multiple-input multiple-output (MIMO) channel model, we obtain the secrecy capacity region when there is only one user in the second group. In the second scenario we study, the transmitter sends a confidential message to users in the first group which needs to be kept confidential from the second group of users and the eavesdroppers. Moreover, the transmitter sends a different confidential message to users in the second group which needs to be kept confidential only from the eavesdroppers. For this scenario, we do not put any restriction on the number of eavesdroppers. As in the first scenario, we obtain the secrecy capacity region for the discrete memoryless channel model, the parallel channel model, and the Gaussian parallel channel model. For the Gaussian MIMO channel model, we establish the secrecy capacity region when there is only one user in the second group.
Real time visual SLAM for underwater robotic inspection

This paper addresses the development of an underwater visual navigation system for a Remotely Operated Vehicle (ROV) based on Real-Time Simultaneous Localization and Mapping method using natural landmarks. Our proposed approach was tested in an indoor tank, where field experiments were performed to obtain 3D vehicle (VIDEORAY Pro3 ROV) trajectory, and results validated using an external stereo vision “ground-truth” system.