Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Vascular Perturbations in an Aβ-Injected Animal Model and in AD Brain

The validity of amyloid-β peptide (Aβ 1-42) intrahippocampal injection, as an animal model of Alzheimer's disease (AD), has previously been considered in terms of inflammatory reactivity and neuronal damage. In this work, we have extended the testing of the animal model to vasculature by comparison of selected properties of microvessels in vivo with those in human AD brain tissue. The injection of Aβ 1-42, relative to control PBS (phosphate buffered saline), increased the mean number of microvessels and diminished the mean length of microvessels in the molecular layer of dentate gyrus. The animal model showed Aβ 1-42, but not PBS, injection was associated with abnormalities in morphology of microvessels which were characterized as looping, fragmented, knob-like, uneven, and constricted. In particular, numbers of constricted microvessels, defined as vessels with diameters less than 3 μm, were considerably enhanced for Aβ 1-42, compared to PBS, injection. In comparison, human AD brain demonstrated an elevated number of microvessels with a diminished mean length relative to nondemented (ND) brain. Additionally, microvessel perturbations in AD brain showed a similar pattern of morphological abnormalities to those observed in Aβ 1-42-injected rat hippocampus. Constricted microvessels were a prominent feature of AD brain but were rarely observed in ND tissue. These results provide the first evidence that a peptide-injection animal model exhibits a commonality in perturbations of microvessels compared with those evident in AD brain.
Age and Vascular Burden Determinants of Cortical Hemodynamics Underlying Verbal Fluency

Background Aging processes and several vascular burden factors have been shown to increase the risk of dementia including Alzheimer's disease. While pathological alterations in dementia precede diagnosis by many years, reorganization of brain processing might temporarily delay cognitive decline. We hypothesized that in healthy elderly individuals both age-related neural and vascular factors known to be related to the development of dementia impact functional cortical hemodynamics during increased cognitive demands. Methods Vascular burden factors and cortical functional hemodynamics during verbal fluency were assessed in 1052 non-demented elderly individuals (51 to 83 years; cross-sectional data of the longitudinal TREND study) using functional near-infrared spectroscopy (fNIRS). The prediction of functional hemodynamic responses by age in multiple regressions and the impact of single and cumulative vascular burden factors including hypertension, diabetes, obesity, smoking and atherosclerosis were investigated. Results Replicating and extending previous findings we could show that increasing age predicted functional hemodynamics to be increased in right prefrontal and bilateral parietal cortex, and decreased in bilateral inferior frontal junction during phonological fluency. Cumulative vascular burden factors, with hypertension in particular, decreased left inferior frontal junction hemodynamic responses during phonological fluency. However, age and vascular burden factors showed no statistical interaction on functional hemodynamics. Conclusion Based on these findings, one might hypothesize that increased fronto-parietal processing may represent age-related compensatory reorganization during increased cognitive demands. Vascular burden factors, such as hypertension, may contribute to regional cerebral hypoperfusion. These neural and vascular hemodynamic determinants should be investigated longitudinally and combined with other markers to advance the prediction of future cognitive decline and dementia.
Clustering Distributed Time Series in Sensor Networks

Event detection is a critical task in sensor networks, especially for environmental monitoring applications. Traditional solutions to event detection are based on analyzing one-shot data points, which might incur a high false alarm rate because sensor data is inherently unreliable and noisy. To address this issue, we propose a novel Distributed Single-pass Incremental Clustering (DSIC) technique to cluster the time series obtained at sensor nodes based on their underlying trends. In order to achieve scalability and energy-efficiency, our DSIC technique uses a hierarchical structure of sensor networks as the underlying infrastructure. The algorithm first compresses the time series produced at individual sensor nodes into a compact representation using Haar wavelet transform, and then, based on dynamic time warping distances, hierarchically groups the approximate time series into a global clustering model in an incremental manner. Experimental results on both real data and synthetic data demonstrate that our DSIC algorithm is accurate, energy-efficient and robust with respect to network topology changes.
An Implied Loss Model

In this paper we present a model which is, by construction, consistent with observed market quotes for standard CDO tranches. The model is closely related to implied tree methods which can be used for valuing exotic equity derivatives consistent with observed market quotes for vanilla European call and put options. Rather than modelling default events for each name in the basket, the total basket loss is modelled directly and calibrated to CDO prices by construction. The proposed model has multiple important uses. First, the model can be used as a tool for avoiding arbitrage opportunities when pricing standard CDO tranches. This is a problem which is hard to solve when using the market standard Base Correlation approach in combination with interpolation and extrapolation rules. As a result the proposed model can be used to determine an arbitrage free distribution for portfolio losses for all maturities, which can subsequently be used as input to the more complex HJM type models which have recently become popular. Second, it provides us with a straightforward method for valuing Forward Starting CDOs, FDOs, consistently with observed market quotes on CDO tranches. A number of tests have been performed which have shown that the model performs well for pricing FDOs, when compared to a number of different factor copula models. Moreover, even under the assumption of heterogeneity of the basket in terms of recovery rates, the performance of the model is still impressive. Apart from performance tests, some additional tests have been presented in this paper, which show that the limited amount of market data still leads to a large amount of uncertainty in FDO prices. Finally forward Base Correlation skews implied by the model are considered and these are found to be rather stable. JEL Classification: G13
Mapping of Hierarchical Activation in the Visual Cortex

Neural activity in the VC is hierarchical, and activation due to stimuli at one area leads to corresponding activity in specified regions of another area [1]. This can be illustrated by viewing the activation in voxels of each region over a given period of time using fMRI data. It has been shown that the signals for vision pass through the first area, V1, before entering other areas such as V2, and there is a mirrored image of the VC on each side of the brain, which we will refer to as RV1, RV2 and LV1, LV2 (we will treat these as separate regions of interest, ROIs, in our mapping). In addition, we ignore any possible cross-wiring between hemispheres in these regions. Given the hierarchical processing of information from the stimulus to V1 and then to V2, our intent is to build a model to confidently predict mappings between these regions. In the process, we also build a model to predict V1 from the stimulus.
Accounting for calibration uncertainty in phylogenetic estimation of evolutionary divergence times.

The estimation of phylogenetic divergence times from sequence data is an important component of many molecular evolutionary studies. There is now a general appreciation that the procedure of divergence dating is considerably more complex than that initially described in the 1960s by Zuckerkandl and Pauling (1962, 1965). In particular, there has been much critical attention toward the assumption of a global molecular clock, resulting in the development of increasingly sophisticated techniques for inferring divergence times from sequence data. In response to the documentation of widespread departures from clocklike behavior, a variety of local- and relaxed-clock methods have been proposed and implemented. Local-clock methods permit different molecular clocks in different parts of the phylogenetic tree, thereby retaining the advantages of the classical molecular clock while casting off the restrictive assumption of a single, global rate of substitution (Rambaut and Bromham 1998; Yoder and Yang 2000).
Grounded Semantic Composition for Visual Scenes

We present a visually-grounded language understanding model based on a study of how people verbally describe objects in scenes. The emphasis of the model is on the combination of individual word meanings to produce meanings for complex referring expressions. The model has been implemented, and it is able to understand a broad range of spatial referring expressions. We describe our implementation of word level visually-grounded semantics and their embedding in a compositional parsing framework. The implemented system selects the correct referents in response to natural language expressions for a large percentage of test cases. In an analysis of the system's successes and failures we reveal how visual context influences the semantics of utterances and propose future extensions to the model that take such context into account.
Oral furosemide‐induced natriuresis: a potential method for identifying cirrhotic patients with refractory ascites

To the Editor: We read with considerable interest the paper by Salerno et al . (1) regarding the definition, pathogenesis and therapy of refractory ascites in cirrhotic patients. The authors proposed that ‘according to the International Ascites Club, refractory ascites is defined as ascites that cannot be mobilized or whose early recurrence after paracentesis cannot be satisfactorily prevented by medical therapy’, and can be divided into diuretic-resistant and diuretic-intractable ascites. However, this proposed definition is rather vague and requires several, frequently tough, clinical evaluations before definite characterization of refractory ascites. For this definition, ascites requires a prolonged, preferably in-hospital, observation to optimize the diet and the diuretic therapy using stepwise increases in diuretics until the maximal doses mentioned by the authors are reached. Moreover, apart from the shortage in hospital beds representing a major problem, trials with diuretics might induce complications including hyponatraemia, renal failure or hepatic encephalopathy requiring further hospitalization with a cost burden. Therefore, a practical, quick and accurate test to define refractory ascites appears to be mandatory to overcome this significant problem. In this respect, Spahr et al . (2) showed that cirrhotic patients with refractory ascites can be identified easily and quickly by measuring urinary sodium excretion after an 80 mg i.v. furosemide injection. A cut-off value of 50 mEq of urinary sodium during the following 8 h allowed them to discriminate between cirrhotic patients with responsive ascites and those with refractory ascites; the test was performed after 3 days without diuretics and patients were on an 80 mEq sodium/day dosage. Using the same protocol (2), we evaluated the comparable effect of a single 80 mg i.v. furosemide infusion and a single 80 and 160 mg oral furosemide dosage on urinary sodium excretion over 8 h in cirrhotic patients with ascites (3). The 80 mg i.v. furosemide infusion induced natriuresis lower than 50 mEq/8 h in 30% of our patients, thereby indicating the presence of refractory ascites; this test induced natriuresis above 50 mEq/8 h in the rest (70%) of the patients, indicating the presence of responsive ascites. An identical profile was also obtained by introducing the 80 or 160 mg oral furosemide test (3). Thus, oral furosemine appears to be a non-invasive, easy and quick test for refractory ascites identification. Therefore, it is important to know whether the authors considered the aforementioned data that provide practical implications for the identification and management of cirrhotic ascites.
Toll-like receptor 10 is involved in induction of innate immune responses to influenza virus infection

Significance Toll-like receptors (TLRs) play key roles in innate immune recognition of pathogens leading to the activation of innate host defenses and sometimes to immunopathology. In humans, there are 10 identified TLR members, designated TLRs 1–10. Of those, TLR10 remains the only one without a defined ligand or function. We now provide previously unidentified evidence that TLR10 plays a role in innate immune responses following influenza viral infection. Influenza viruses are subtyped on the hemagglutinin (H) and neuraminidase (N) proteins. Compared with seasonal influenza virus H1N1, the highly pathogenic avian influenza virus H5N1 is a more potent inducer of TLR10 expression. Given the importance of innate immune sensing receptors in host defense and pathogenesis, evidence of a functional role for TLR10 in influenza infection suggests that this receptor probably plays a role in a range of other viral and perhaps other microbial diseases. Toll-like receptors (TLRs) play key roles in innate immune recognition of pathogen-associated molecular patterns of invading microbes. Among the 10 TLR family members identified in humans, TLR10 remains an orphan receptor without known agonist or function. TLR10 is a pseudogene in mice and mouse models are noninformative in this regard. Using influenza virus infection in primary human peripheral blood monocyte-derived macrophages and a human monocytic cell line, we now provide previously unidentified evidence that TLR10 plays a role in innate immune responses following viral infection. Influenza virus infection increased TLR10 expression and TLR10 contributed to innate immune sensing of viral infection leading to cytokine induction, including proinflammatory cytokines and interferons. TLR10 induction is more pronounced following infection with highly pathogenic avian influenza H5N1 virus compared with a low pathogenic H1N1 virus. Induction of TLR10 by virus infection requires active virus replication and de novo protein synthesis. Culture supernatants of virus-infected cells modestly up-regulate TLR10 expression in nonvirus-infected cells. Signaling via TLR10 was activated by the functional RNA–protein complex of influenza virus leading to robust induction of cytokine expression. Taken together, our findings identify TLR10 as an important innate immune sensor of viral infection and its role in innate immune defense and immunopathology following viral and bacterial pathogens deserves attention.
Sensitivity Analysis for the Inverted Siphon in a Long Distance Water Transfer Project: An Integrated System Modeling Perspective

Long distance water diversion projects are developed to alleviate the conflicts between supply and demand of water resources across different watersheds. However, the significant scale water diversion projects bring new challenges for the water supply security. This paper presents the flood risk of inverted siphon structure which is used for crossing transversally in the water diversion project through sensitivity analysis. Soboĺ and regionalized sensitivity analysis are used to investigate the sensitive parameters of the integrated model and the sensitive range of the parameters, respectively. The integrated system model consists of the hydrologic model, the sediment transport model and the siphon hydraulic model to determine the flood overtopping duration and volume, which are used to quantify flood risk in this study. The flood overtopping duration and volume indicators are used to quantify flood risk in the sensitivity analysis. The South to North Water Diversion Project in China is used as a case study. The results show the mean rainfall and roughness coefficient of the pipe are the most sensitive parameters in the integrated models, while the sensitive range of these two parameters are distinct. The sensitivity analysis of the inverted siphon provides an insight into the significant contributions to the flood risk. The analysis can provide the guidance for the system operation security.
Commutators which commute with one factor

Let A and B be n × n matrices, let C = ABA−1B−1 be the multiplicative commutator of A and B, and assume AC = CA. Olga Taussky (1961) examined the structure of A and B for the case where A and B are unitary. Marcus and Thompson (1966) generalized her results to the case where A and C are assumed normal. We look at this problem for general A, with particular attention to the cases where A is diagonalizable or nonderogatory. Now let [A,B] = AB − BA be the additive commutator of A and B and assume A commutes with [A,B]. The finitedimensional version of a theorem of Putnam tells us that if A is normal, then A and B commute. We show that the same conclusion holds when A is diagonalizable. If A is nonderogatory, then A and B can be simultaneously triangularized.
Randomized external-memory algorithms for some geometric problems

We show that the well-known random incremental constructlon of Clarkson and Shor [14] can be adapted via gradations to provide efficient external-memory algorithms for some geomctric problems. In particular, as the main result, we obtain an optimal randomized algorithm for the problem of computing the trapezoidal decomposition determined by a set of N line scgmcnts in the plane with K pairwise intersections, that requires G($$ logMjB Q + 5) expected disk accesses (I/OS), where M is the size of the available internal memory and B is the size of the block transfer. The approach is sufficiently general to obtain algorithms for the problems of 2-d and 3-d convex hulls, 2-d abstract Voronoi diagrams and batched point location in a planar subdivision, which require an optimal expected number of I/OS and are olmplcr than the ones previously known. The results extend to a external-memory model with multiple disks.
Adaptive OFDM Techniques With One-Bit-Per-Subcarrier Channel-State Feedback

In the orthogonal frequency-division multiplexing (OFDM) scheme, some subcarriers may be subject to a deep fading. Adaptive techniques can be applied to mitigate this effect if the channel-state information (CSI) is available at the transmitter. In this paper, we study the performance of an OFDM-based communication system whose transmitter has only one bit of CSI per subcarrier, obtained through a low-rate feedback. Three adaptive approaches are considered to exploit such a CSI feedback: adaptive subcarrier selection; adaptive power allocation (APA); and adaptive modulation selection (AMS). Under the conditions of a constant raw data rate and perfect feedback channel, the performance of these approaches are analyzed and compared in terms of raw bit-error rate. It is shown that one-bit CSI feedback can greatly enhance the system performance. Moreover, imperfections of the feedback channel are considered, and their impact on the performance of these techniques is studied. It is shown that by exploiting the knowledge that the feedback channel is imperfect, the performance of the APA and AMS techniques can be substantially improved
Zero-Shot Recognition via Direct Classifier Learning with Transferred Samples and Pseudo Labels

As an interesting and emerging topic, zero-shot recognition (ZSR) makes it possible to train a recognition model by specifying the category's attributes when there are no labeled exemplars available. The fundamental idea for ZSR is to transfer knowledge from the abundant labeled data in different but related source classes via the class attributes. Conventional ZSR approaches adopt a two-step strategy in test stage, where the samples are projected into the attribute space in the first step, and then the recognition is carried out based on considering the relationship between samples and classes in the attribute space. Due to this intermediate transformation, information loss is unavoidable, thus degrading the performance of the overall system. Rather than following this two-step strategy, in this paper, we propose a novel one-step approach that is able to perform ZSR in the original feature space by using directly trained classifiers. To tackle the problem that no labeled samples of target classes are available, we propose to assign pseudo labels to samples based on the reliability and diversity, which in turn will be used to train the classifiers. Moreover, we adopt a robust SVM that accounts for the unreliability of pseudo labels. Extensive experiments on four datasets demonstrate consistent performance gains of our approach over the state-of-the-art two-step ZSR approaches.
A Novel FNP-Pose Estimation for Three-Dimensional Face Recognition using DPCA Under Facial Expression

This paper presents an efficient 3D face recognition algorithm with facial expression. The proposed algorithm describes a novel FNP (fast nose points)-pose estimation which is the Triangle-based four point method to estimate the pose of three-dimensional (3-D) face, (i.e. the 3-D shape). Firstly, we find the specific points using Angle comparison Trace. Secondly, from this triangle we calculate weight point of triangle which is used for translation and compensate the rotation of 3D test facial image. Finally, Depth PCA is employed for 3D face recognition where it performs PCA on a 2D x-y axis and takes into account the depth information from 3D Vertices and Face entries. 2D texture information is mapped corresponding to each point at centre of vertices and segment 2-by-2 around this point. The proposed algorithm allows the use of fast iterative algorithm to compute the 3-D facial pose and 3D face recognition that best fits the data. The algorithm has been tested with 3D database and obtained results provide a high level of robustness and accurate recognition.
Automated Multi-Tier System Design for Service Availability

Creating a cost-effective large-scale multi-tier Enterprise service requires judicious selection and configuration of infrastructure elements and mechanisms. The minimum cost solution that satisfies business requirements for service availability and performance should be identified. Emerging self-managed computing utility environments demand an automated solution to this problem. This solution must be integrated with the utility controller, which typically virtualizes resources for services, thus hiding from them information about the characteristics of the underlying physical infrastructure. In this paper, we present AVED, our initial version of an engine that automatically designs a cost-effective service infrastructure which will meet the service’s availability requirements. AVED explores a design space consisting of multiple combinations of hardware/software configurations presenting various tradeoffs among cost, availability, and performance. We illustrate that AVED generates a complete picture of the cost-availability tradeoff for the infrastructure design. We also describe how AVED can be integrated with utility computing environments to improve the automation of service lifecycles.