Miracle-dz/UniFAR-FTUs huggingface dataset:
Q‐ball imaging

Magnetic resonance diffusion tensor imaging (DTI) provides a powerful tool for mapping neural histoarchitecture in vivo. However, DTI can only resolve a single fiber orientation within each imaging voxel due to the constraints of the tensor model. For example, DTI cannot resolve fibers crossing, bending, or twisting within an individual voxel. Intravoxel fiber crossing can be resolved using q‐space diffusion imaging, but q‐space imaging requires large pulsed field gradients and time‐intensive sampling. It is also possible to resolve intravoxel fiber crossing using mixture model decomposition of the high angular resolution diffusion imaging (HARDI) signal, but mixture modeling requires a model of the underlying diffusion process.
Indistinguishability Obfuscation for Turing Machines with Unbounded Memory

We show how to build indistinguishability obfuscation (iO) for Turing Machines where the overhead is polynomial in the security parameter λ, machine description |M| and input size |x| (with only a negligible correctness error). In particular, we avoid growing polynomially with the maximum space of a computation. Our construction is based on iO for circuits, one way functions and injective pseudo random generators. Our results are based on new "selective enforcement" techniques. Here we first create a primitive called positional accumulators that allows for a small commitment to a much larger storage. The commitment is unconditionally sound for a select piece of the storage. This primitive serves as an "iO-friendly" tool that allows us to make two different programs equivalent at different stages of a proof. The pieces of storage that are selected depend on what hybrid stage we are at in a proof. We first build up our enforcement ideas in a simpler context of "message hiding encodings" and work our way up to indistinguishability obfuscation.
Renin-angiotensin-aldosterone system in the elderly: rational use of aliskiren in managing hypertension

The overall purpose of hypertension treatment is 2-fold. First, patients often have symptoms that are related to their high blood pressure and although subtle in many instances may be improved dramatically by blood pressure control. The main reason for blood pressure treatment, however, is to reduce the burden of cardiovascular complications and end organ damage related to the condition. This may be considered the ultimate goal of blood pressure treatment. In this respect, actual blood pressure measurements may be seen as surrogate end points as the organ protective effects of two antihypertensive agents may differ significantly even though their blood pressure lowering effects are similar. Thus beta-blockers, once seen as first-line treatment of hypertension for most patients, now are considered as third- or fourthline agents according to the latest NICE guidelines (National Institute for Health and Clinical Excellence, www.nice.org.uk/CG034). On the other hand, agents that inhibit the activity of the renin-angiotensin-aldosterone system (RAAS) system are being established as safe, effective and end organ protective in numerous clinical trials, resulting in their general acceptance as first-line treatment in most patients with stage 2 hypertension. This shift in emphasis from beta-blockers and thiazide diuretics is supported by numerous clinical trials and has proven safe and well tolerated by patients. The impact of this paradigm shift will have to be established in future long-term randomized clinical trials. The optimal combination treatment with respect to end organ protection has yet to be determined. Most combinations will include either a RAAS active agent and calcium channel blocker or two separate RAAS active agents working at different levels of the cascade. In this respect direct renin inhibitors and angiotensin receptor blockers seem particularly promising but the concept awaits evaluation in upcoming randomized clinical trials. Although safety data from the randomized clinical trials to date have been promising, we still lack data on the long-term effect of aliskiren on mortality and there still are patient groups where the safety of aliskiren is unexplored.
Use of Computation-Unit Integrated Memories in High-Level Synthesis

High-level synthesis (HLS) of memory-intensive applications has featured several innovations in terms of enhancements made to the basic memory organization and data layout. However, increasing performance and energy demands faced by application-specific integrated circuits (ASICs) are forcing designers to alter the fundamental architectural template of the HLS output, namely, a controller datapath associated with a memory subsystem (monolithic, partitioned, etc.). An architectural template for the HLS output that consists of a controller-datapath circuit associated with a memory subsystem into which computation units have been integrated is proposed. The enhanced memory subsystem is called computation-unit integrated memory (CIM). A CIM offers higher memory bandwidth (relative to what is offered through the system bus) to computation units present locally within it and reduces the overall communication between the memory subsystem and the controller datapath, thus providing a template highly suitable for deriving efficient implementations of memory-intensive applications. This paper addresses the challenge of providing a systematic synthesis framework for a CIM-based architecture. This framework can analyze the various tradeoffs involved in selecting suitable operations in a behavior for execution using a CIM and generate a high-performance low-overhead implementation. Efficient data reuse of register files have also been fully exploited to further improve system performance. Experiments with several behaviors indicate that an average performance improvement of 2.02times(a maximum of 2.70times) is possible with very low area overheads. The energy-delay product improves by an average of 2.5times(maximum of 3.8times)
A Pathway Separate from the Central Channel through the Nuclear Pore Complex for Inorganic Ions and Small Macromolecules*

Nuclear pore complexes (NPCs) are supramolecular nanomachines that mediate the exchange of macromolecules and inorganic ions between the nucleus and the cytosol. Although there is no doubt that large cargo is transported through the centrally located channel, the route of ions and small molecules remains debatable. We thus tested the hypothesis that there are two separate pathways by imaging NPCs using atomic force microscopy, NPC electrical conductivity measurements, and macromolecule permeability assays. Our data indicate a spatial separation between the active transport of macromolecules through the central channel and the passive transport of ions and small macromolecules through the pore periphery.
Cav1.2 and Cav1.3 Are Differentially Coupled to Glucagon-Like Peptide-1 Potentiation of Glucose-Stimulated Insulin Secretion in the Pancreatic β-Cell Line INS-1

The incretin peptides, glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1), potentiate glucose-stimulated insulin secretion (GSIS) and β-cell proliferation and differentiation. Ca2+ influx via voltage-gated L-type Ca2+ channels is required for GLP-1 and GIP potentiation of GSIS. We investigated the role of the L-type Ca2+ channels Cav1.2 and Cav1.3 in mediating GLP-1- and GIP-stimulated events in INS-1 cells and INS-1 cell lines expressing dihydropyridine-insensitive (DHPi) mutants of either Cav1.2 or Cav1.3. Cav1.3/DHPi channels supported full potentiation of GSIS by GLP-1 (50 nM) compared with untransfected INS-1 cells. However, GLP-1-potentiated GSIS mediated by Cav1.2/DHPi channels was markedly reduced compared with untransfected INS-1 cells. In contrast, GIP (10 nM) potentiation of GSIS mediated by both Cav1.2/DHPi and Cav1.3/DHPi channels was similar to that observed in untransfected INS-1 cells. Disruption of intracellular Ca2+ release with thapsigargin, ryanodine, or 2-aminoethyldiphenylborate and inhibition of protein kinase A (PKA) or protein kinase C (PKC) significantly reduced GLP-1 potentiation of GSIS by Cav1.3/DHPi channels and by endogenous L-type channels in INS-1 cells, but not by Cav1.2/DHPi channels. Inhibition of glucose-stimulated phospholipase C activity with 1-(6-((17b-3-methoxyestra-1,3,5(10)-trien-17-yl)amino)hexyl)-1H-pyrrole-2,5-dione (U73122) did not inhibit potentiation of GSIS by GLP-1 in INS-1 cells. In contrast, wortmannin, an inhibitor of phosphatidylinositol 3-kinase, and 2′-amino-3′-methoxyflavone (PD98059), an inhibitor of mitogen-activated protein kinase/extracellular signal-regulated kinase (ERK) kinase, both markedly inhibited GLP-1 potentiation of GSIS by endogenous channels in INS-1 cells and Cav1.3/DHPi channels, but not by Cav1.2/DHPi channels. Thus, Cav1.3 is preferentially coupled to GLP-1 potentiation of GSIS in INS-1 cells via a mechanism that requires intact intracellular Ca2+ stores, PKA and PKC activity, and activation of ERK1/2.
Impact of missing data mechanism on the estimate of change: a case study on cognitive function and polypharmacy among older persons

Longitudinal studies typically suffer from incompleteness of data. Attrition is a major problem in studies of older persons since participants may die during the study or are too frail to participate in follow-up examinations. Attrition is typically related to an individual’s health; therefore, ignoring it may lead to too optimistic inferences, for example, about cognitive decline or changes in polypharmacy. The objective of this study is to compare the estimates of level and slope of change in 1) cognitive function and 2) number of drugs in use between the assumptions of ignorable and non-ignorable missingness. This study demonstrates the usefulness of latent variable modeling framework. The results suggest that when the missing data mechanism is not known, it is preferable to conduct analyses both under ignorable and non-ignorable missing data assumptions.
A Research on Supplier Assessment Indices System of Green Purchasing

With the worse environment for human survival and the limited resource, enterprises are forced to improve their environmental management to enhance their competitiveness. The level of purchasing management can affect not only enterprises’ economic performance, but environmental performance. This study developed a questionnaire on the basis of the literatures at present and did a survey among Chinese manufacture enterprises. Through factor analysis by SPSS, the main factors for green suppliers’ assessment are identified. Analysis on data results are followed by conclusion based on the theory of innovation diffusion. The limitations in this study are also pointed in the end.
The medial parietal occipital areas in the macaque monkey

Abstract The number, location, extent, and functional properties of the cortical areas that occupy the medial parieto-occipital cortex (mPOC) have been, and still is, a matter of scientific debate. The mPOC is a convoluted region of the brain that presents a high level of individual variability, and the fact that many areas of mPOC are located within very deep sulci further limits the possibility to investigate their anatomo-functional properties. In the present review, we summarize the location and extent of mPOC areas in the macaque brain as obtained by architectural, connectional, and functional data. The different approaches lead to a subdivision of mPOC that includes areas V2, V3, V6, V6Av, and V6Ad. Extrastriate areas V2 and V3 occupy the posterior wall of the parieto-occipital sulcus (POs). The fundus of POs and the ventralmost part of the anterior wall of the sulcus are occupied by a retinotopically organized visual area, called V6, which represents the contralateral part of the visual field and emphasizes its periphery. The remaining part of the anterior wall of POs is occupied by two areas, V6Av and V6Ad, which contain visual as well as arm reaching neurons. Our analyses suggest that areas V6 and V6Av, together, occupy the cortical territory previously described as area PO. Functionally, area V6 is a motion area particularly sensitive to the real motion of objects in the animal's field of view, while V6Av and V6Ad are visuomotor areas likely involved in the visual guidance of arm movement and object prehension.
Green Synthesis and Characterization of Gold Nanoparticles Using Onion ( Allium cepa ) Extract

In the present research program, cost effective and environment friendly gold nanoparticless were synthesized using the onion (Allium cepa) extract as the reducing agent. The nanoparticless were characterized using UV-visble, XRD, and SEM, TEM methods. The absorption peak at 540 nm was found to be broaden with increase in time indicating the polydispersity nature of the nanoparticles. The XRD results suggested that the crystallization of the bio-organic phase occurs on the surface of the gold nanoparticles or vice versa. The broadening of peaks in the XRD patterns was attributed to particle size effects. The internalization of nanoparticles within cells could occur via processes including phagocytosis, fluid-phase endocytosis and receptor mediated endocytosis.
Specifying Viewpoint and Information Need with Affective Metaphors: A System Demonstration of the Metaphor-Magnet Web App/Service

Metaphors pervade our language because they are elastic enough to allow a speaker to express an affective viewpoint on a topic without committing to a specific meaning. This balance of expressiveness and indeterminism means that metaphors are just as useful for eliciting information as they are for conveying information. We explore here, via a demonstration of a system for metaphor interpretation and generation called Metaphor Magnet, the practical uses of metaphor as a basis for formulating affective information queries. We also consider the kinds of deep and shallow stereotypical knowledge that are needed for such a system, and demonstrate how they can be acquired from corpora and the web.
Inflammation induced by mast cell deficiency rather than the loss of interstitial cells of Cajal causes smooth muscle dysfunction in W/Wv mice

The initial hypothesis suggested that the interstitial cells of Cajal (ICC) played an essential role in mediating enteric neuronal input to smooth muscle cells. Much information for this hypothesis came from studies in W/Wv mice lacking ICC. However, mast cells, which play critical roles in regulating inflammation in their microenvironment, are also absent in W/Wv mice. We tested the hypothesis that the depletion of mast cells in W/Wv mice generates inflammation in fundus muscularis externa (ME) that impairs smooth muscle reactivity to Ach, independent of the depletion of ICC. We performed experiments on the fundus ME from wild type (WT) and W/Wv mice before and after reconstitution of mast cells by bone marrow transplant. We found that mast cell deficiency in W/Wv mice significantly increased COX-2 and iNOS expression and decreased smooth muscle reactivity to Ach. Mast cell reconstitution or concurrent blockade of COX-2 and iNOS restored smooth muscle contractility without affecting the suppression of c-kit in W/Wv mice. The expression of nNOS and ChAT were suppressed in W/Wv mice; mast cell reconstitution did not restore them. We conclude that innate inflammation induced by mast cell deficiency in W/Wv mice impairs smooth muscle contractility independent of ICC deficiency. The impairment of smooth muscle contractility and the suppression of the enzymes regulating the synthesis of Ach and NO in W/Wv mice need to be considered in evaluating the role of ICC in regulating smooth muscle and enteric neuronal function in W/Wv mice.
Identifying and Analyzing Judgment Opinions

In this paper, we introduce a methodology for analyzing judgment opinions. We define a judgment opinion as consisting of a valence, a holder, and a topic. We decompose the task of opinion analysis into four parts: 1) recognizing the opinion; 2) identifying the valence; 3) identifying the holder; and 4) identifying the topic. In this paper, we address the first three parts and evaluate our methodology using both intrinsic and extrinsic measures.
ZnO Nanoparticles Synthesised by mechanochemical processing

Some characterization and microstructural features of mechanochemicaly milled ZnO powders are presented in this study. It is shown that the application of mechanochemical ZnO nanoparticles is a simple technique for preparation of nanocrystalline powders. Synthesised powders are analyzed by X-ray diffraction, scanning electron microscopy (SEM), transmission electron microscope (TEM) and Brunauer-Emmett-Teller (BET).
Phased array system consisting of unit pattern reconfigurable Square Loop Antennas

A 2×2 array of pattern adaptive Square Loop Antennas (SLA) is presented. The antenna generates off-boresight tilted beams (14.4dBi at θ<sub>max</sub> =32°) in four different quadrant of Φ<sub>max</sub>=45°, Φ<sub>max</sub>=135°, Φ<sub>max</sub>=225° and Φ<sub>max</sub>=315°, when four of its feeding ports are excited by proper phases. The antenna also provides both circularly and linearly polarized axial beams (13.6dBi) when all the 16 feeding ports are excited simultaneously with specific phases. These five distinct patterns enable systems to offer high gain coverage in both off-boresight and boresight directions.
Bridging the gap between RFID/EPC concepts, technological requirements and supply chain e-business processes

Supply chain pressures have caused some firms to reexamine their processes. In doing so, firms are exploring emerging technology such as RFID to enable seamless exchange of information within their supply chain. While RFID promised to "revolutionize" the way business processes are managed today, the impact and benefits of the technology are still unclear and ambiguous concepts such as "intelligent products", "smart supply chains" or "the internet of things" are still creating confusion within potential adopters. In this paper an attempt is made to (i) clarify the ambiguity surrounding RFID vs. other AIDC and IOS technologies such as the EPC Network (ii) specify the technology readiness & IT related requirements of actual and emerging applications, and (iii) propose a framework to highlight how the technology can be used to support RFID/EPC enabled ecommerce processes and support practitioners and academicians in assessing the impact of RFID on electronic supply chain business processes.
A Novel Image-centric Approach Towards Direct Volume Rendering

Transfer Function (TF) generation is a fundamental problem in Direct Volume Rendering (DVR). A TF maps voxels to color and opacity values to reveal inner structures. Existing TF tools are complex and unintuitive for the users who are more likely to be medical professionals than computer scientists. In this paper, we propose a novel image-centric method for TF generation where instead of complex tools, the user directly manipulates volume data to generate DVR. The user's work is further simplified by presenting only the most informative volume slices for selection. Based on the selected parts, the voxels are classified using our novel Sparse Nonparametric Support Vector Machine classifier, which combines both local and near-global distributional information of the training data. The voxel classes are mapped to aesthetically pleasing and distinguishable color and opacity values using harmonic colors. Experimental results on several benchmark datasets and a detailed user survey show the effectiveness of the proposed method.
Pervasive EEG diagnosis of depression using Deep Belief Network with three-electrodes EEG collector

According to the World Health Organization, it is predicted that in 2020, depression will become the second largest illness threatening the health of mankind. In order to alleviate the worldwide damage caused by depression, a portable and accurate diagnosing technique is the most essential. This research uses three-electrode pervasive EEG collector to collect EEG data from Fp1, Fp2, and Fpz as locations of scalp electrodes, since these locations are closely related to emotions, and uncovered by hair. Special designed experiment has been conducted and totally 178 subjects' EEG data have been collected. Then the research uses KNN (k-Nearest Neighbor), SVM (Support Vector Machine), ANN (Artificial Neuro Network) and DBN (Deep Belief Network) to analyze the data. The results show DBN performed better than traditional methods using shallow algorithms. Moreover, the results suggested the absolute power of beta wave is a valid characteristic, which could be used for detection of depression. The accuracy reached 78.24% using the combination of DBN and the absolute power of beta wave. This research proves the feasibility of smaller-size pervasive system for depression diagnosis.
Fitness Costs of Mutation Rate Adaption and its Application to Optimization of Dynamic Objective Functions

Evolutionary algorithms can be used to solve complex optimization tasks. However, adequate parameterization is crucial for efficient optimization. Evolutionary adaptation of mutation rates provides a solution to the problem of finding suitable mutation rate settings. However, evolution of low mutation rates may lead to premature convergence. In nature, mutation rate control coevolves with other functional units in a genome, and it is constrained because mutation rate control requires energy and resources. This principle can be captured by an abstract concept of fitness cost associated mutation rate adaptation, which can be generically applied in evolutionary algorithms. Application of this principle can be useful for addressing problems of premature convergence. This contribution explores applications of this concept within the context of dynamic fitness landscapes. It is shown that fitness costs for mutation rate adaptation is no less advantageous in dynamic fitness landscapes than in static ones, and that interesting synergies can arise in conjunction with dynamics in multimodal fitness landscapes.
Performance comparison between k-tuple distance and four model-based distances in phylogenetic tree reconstruction

Phylogenetic tree reconstruction requires construction of a multiple sequence alignment (MSA) from sequences. Computationally, it is difficult to achieve an optimal MSA for many sequences. Moreover, even if an optimal MSA is obtained, it may not be the true MSA that reflects the evolutionary history of the underlying sequences. Therefore, errors can be introduced during MSA construction which in turn affects the subsequent phylogenetic tree construction. In order to circumvent this issue, we extend the application of the k-tuple distance to phylogenetic tree reconstruction. The k-tuple distance between two sequences is the sum of the differences in frequency, over all possible tuples of length k, between the sequences and can be estimated without MSAs. It has been traditionally used to build a fast ‘guide tree’ to assist the construction of MSAs. Using the 1470 simulated sets of sequences generated under different evolutionary scenarios, the neighbor-joining trees and BioNJ trees, we compared the performance of the k-tuple distance with four commonly used distance estimators including Jukes–Cantor, Kimura, F84 and Tamura–Nei. These four distance estimators fall into the category of model-based distance estimators, as each of them takes account of a specific substitution model in order to compute the distance between a pair of already aligned sequences. Results show that trees constructed from the k-tuple distance are more accurate than those from other distances most time; when the divergence between underlying sequences is high, the tree accuracy could be twice or higher using the k-tuple distance than other estimators. Furthermore, as the k-tuple distance voids the need for constructing an MSA, it can save tremendous amount of time for phylogenetic tree reconstructions when the data include a large number of sequences.