Miracle-dz/UniFAR-FTUs huggingface dataset:
CCL2 Is Associated with a Faster Rate of Cognitive Decline during Early Stages of Alzheimer's Disease

Chemokine (C-C motif) receptor 2 (CCR2)-signaling can mediate accumulation of microglia at sites affected by neuroinflammation. CCR2 and its main ligand CCL2 (MCP-1) might also be involved in the altered metabolism of beta-amyloid (Aβ) underlying Alzheimer's disease (AD). We therefore measured the levels of CCL2 and three other CCR2 ligands, i.e. CCL11 (eotaxin), CCL13 (MCP-4) and CCL26 (eotaxin-3), in the cerebrospinal fluid (CSF) and plasma of 30 controls and 119 patients with mild cognitive impairment (MCI) at baseline. During clinical follow-up 52 MCI patients were clinically stable for five years, 47 developed AD (i.e. cases with prodromal AD at baseline) and 20 developed other dementias. Only CSF CCL26 was statistically significantly elevated in patients with prodromal AD when compared to controls (p = 0.002). However, in patients with prodromal AD, the CCL2 levels in CSF at baseline correlated with a faster cognitive decline during follow-up (r s = 0.42, p = 0.004). Furthermore, prodromal AD patients in the highest tertile of CSF CCL2 exhibited a significantly faster cognitive decline (p<0.001) and developed AD dementia within a shorter time period (p<0.003) compared to those in the lowest tertile. Finally, in the entire MCI cohort, CSF CCL2 could be combined with CSF Tau, P-tau and Aβ42 to predict both future conversion to AD and the rate of cognitive decline. If these results are corroborated in future studies, CCL2 in CSF could be a candidate biomarker for prediction of future disease progression rate in prodromal AD. Moreover, CCR2-related signaling pathways might be new therapeutic targets for therapies aiming at slowing down the disease progression rate of AD.
Serum Biochemistry in Four Siberian Husky Puppies with Swimming Puppy Syndrome

Complete blood counts and blood chemistry in four Siberian husky puppies diagnosed with swimming puppy syndrome were compared with four healthy Siberian husky puppies. Only serum creatine kinase in affected puppies was significantly (P < 0.01) higher than in normal puppies. Although serum creatine kinase level cannot be used for diagnosis of this disease, it could serve as a tool for prognosis of the disease after treatment.
High-level Information Fusion: An Overview

Data and information fusion (DIF) involves a process of combining data from multiple inputs (from one or more sources such as sensors and textual reports). 1 The aim is to obtain information that is better (more useful and meaningful) than that would be derived from each of the sources individually (that is, without fusing). DIF is emerging as an important field of multidisciplinary study [113, 316]. This is due to increase in data and information flow, as well as improvement in communication, computing and sensor technology. The first applications of DIF techniques were in the military arena [177, 179, 455]. The use of DIF techniques for problem-solving has extended to many non-military applications in the commercial and industrial sectors [177, 179, 199, 228]. In general, data and information fusion can provide enhancement to the outcomes of processes for solving various application problems. Some advantages of carrying out DIF include [316]: 2 improvement in the accuracy of data, as well as reduction in uncertainty and ambiguity within data, and 2 improvement in situation awareness (SAW) and inference that lead to better decision making.
Extreme population subdivision throughout a continuous range: phylogeography of Batrachoseps attenuatus (Caudata: Plethodontidae) in western North America

Low‐vagility species with deep evolutionary histories are key to our understanding of the biogeographical history of geologically complex areas, such as the west coast of North America. We present a detailed study of the phylogeography of the salamander Batrachoseps attenuatus (Caudata: Plethodontidae) using sequences of the mitochondrial gene cob from 178 individuals sampled from throughout the species’ range. Sequences of three other mitochondrial genes (16S, cox1, nad4) and a nuclear gene (RAG‐1) were used to investigate the deeper evolutionary history of the species. We found high levels of genetic diversity and deep divergences within a mostly continuous distribution, with five genetically well‐differentiated and geographically structured mitochondrial DNA clades. Significant association between geographical and genetic distances within these clades suggests demographic stability, whereas Fu's FS tests suggest demographic expansions in three of them. Mantel tests identify two biogeographical barriers, the San Andreas Fault and the Sacramento–San Joaquin Delta, as important in the diversification of lineages. The timing of the main splitting events between intraspecific lineages was estimated by applying relaxed molecular clock methods combining several mutation rates and a fossil calibration. The earliest splitting events are old (Pliocene/Miocene), with more recent (Pleistocene) subdivisions in some clades. Disjunct populations distributed along the western foothills of the Sierra Nevada colonized this area relatively recently from a single refugium east of San Francisco Bay. The combination of fine‐scale, comprehensive sampling with phylogenetic, historical demographic and hypothesis‐based tests allowed delineation of a complex biogeographical scenario with general implications for the study of codistributed taxa.
A Selective Approach to Improve the Performance of UWB Image Transmission System over Indoor Fading Channels

A selective approach is proposed to improve the performance of Time-Hopping (TH) PPM UWB image transmission system over indoor fading channels. We divided the image information into key information and secondary information. In the proposed approach, key information is transmitted with good channel condition, secondary information otherwise. The threshold of channel condition can be derived from the CDF of indoor fading distribution. Simulation has been conducted to show the improvement. The PSNR (Peak Signal to Noise Ratio) of selective transmission system has a gain of almost 9 dB over non-selective system.
On the robustness of empirical likelihood ratio confidence intervals for location

The authors examine the robustness of empirical likelihood ratio (ELR) confidence intervals for the mean and M‐estimate of location. They show that the ELR interval for the mean has an asymptotic breakdown point of zero. They also give a formula for computing the breakdown point of the ELR interval for M‐estimate. Through a numerical study, they further examine the relative advantages of the ELR interval to the commonly used confidence intervals based on the asymptotic distribution of the M‐estimate.
ICAP-1, a Novel β1 Integrin Cytoplasmic Domain–associated Protein, Binds to a Conserved and Functionally Important NPXY Sequence Motif of β1 Integrin

The cytoplasmic domains of integrins are essential for cell adhesion. We report identification of a novel protein, ICAP-1 (integrin cytoplasmic domain– associated protein-1), which binds to the β 1 integrin cytoplasmic domain. The interaction between ICAP-1 and β1 integrins is highly specific, as demonstrated by the lack of interaction between ICAP-1 and the cytoplasmic domains of other β integrins, and requires a conserved and functionally important NPXY sequence motif found in the COOH-terminal region of the β1 integrin cytoplasmic domain. Mutational studies reveal that Asn and Tyr of the NPXY motif and a Val residue located NH2-terminal to this motif are critical for the ICAP-1 binding. Two isoforms of ICAP-1, a 200–amino acid protein (ICAP-1α) and a shorter 150–amino acid protein (ICAP-1β), derived from alternatively spliced mRNA, are expressed in most cells. ICAP-1α is a phosphoprotein and the extent of its phosphorylation is regulated by the cell–matrix interaction. First, an enhancement of ICAP-1α phosphorylation is observed when cells were plated on fibronectin-coated but not on nonspecific poly-l-lysine–coated surface. Second, the expression of a constitutively activated RhoA protein that disrupts the cell–matrix interaction results in dephosphorylation of ICAP-1α. The regulation of ICAP-1α phosphorylation by the cell–matrix interaction suggests an important role of ICAP-1 during integrin-dependent cell adhesion.
Fusion Based Holistic Road Scene Understanding

This paper addresses the problem of holistic road scene understanding based on the integration of visual and range data. To achieve the grand goal, we propose an approach that jointly tackles object-level image segmentation and semantic region labeling within a conditional random field (CRF) framework. Specifically, we first generate semantic object hypotheses by clustering 3D points, learning their prior appearance models, and using a deep learning method for reasoning their semantic categories. The learned priors, together with spatial and geometric contexts, are incorporated in CRF. With this formulation, visual and range data are fused thoroughly, and moreover, the coupled segmentation and semantic labeling problem can be inferred via Graph Cuts. Our approach is validated on the challenging KITTI dataset that contains diverse complicated road scenarios. Both quantitative and qualitative evaluations demonstrate its effectiveness.
A probabilistic model of emphysema based on granulometry analysis

Emphysema is associated with the destruction of lung parenchyma, resulting in abnormal enlargement of airspaces. Accurate quantification of emphysema is required for a better understanding of the disease as well as for the assessment of drugs and treatments. In the present study, a novel method for emphysema characterization from histological lung images is proposed. Elastase-induced mice were used to simulate the effect of emphysema on the lungs. A database composed of 50 normal and 50 emphysematous lung patches of size 512 x 512 pixels was used in our experiments. The purpose is to automatically identify those patches containing emphysematous tissue. The proposed approach is based on the use of granulometry analysis, which provides the pattern spectrum describing the distribution of airspaces in the lung region under evaluation. The profile of the spectrum was summarized by a set of statistical features. A logistic regression model was then used to estimate the probability for a patch to be emphysematous from this feature set. An accuracy of 87% was achieved by our method in the classification between normal and emphysematous samples. This result shows the utility of our granulometry-based method to quantify the lesions due to emphysema.
Development of a dynamic symbiotic network planner and application to a living lab testbed

The concept of symbiotic networks is introduced as a way to improve the use of available resources and infrastructure and the overall performance of co-located wireless networks. An existing wireless network planning tool is extended with a symbiotic feature, which is able to create a new (symbiotic) network out of the different coexisting networks. This symbiotic planning tool is applied to a living lab testbed network in Ghent, Belgium. Feedback about reception quality at the testbed nodes is continuously given to the tool and the internal propagation prediction models are adapted accordingly in order to improve the accuracy of the network planning. The concept of this dynamic symbiotic network planner are presented.
Context-Based Semantic Approach to Ontology Creation of Maritime Information in Chinese

The term “maritime affairs” means in general the shipping (Maritime Services) and all things related to the sea, such as navigation, shipbuilding, surveying, maritime law, and processing the maritime accidents (including the navigation and berthing incidents). And the 71 percents of the earth’s surface is covered with ocean, while the shipping is a low-cost, high-volume, long-distance transport. With the explosive growth of information and globalization, it highlights the importance of collecting the maritime information and digging out the useful information. To create a professional and systematic maritime ontology, it will enhance the efficiency and accuracy of excavation. Considering the lack of context-semantics for the constructing Chinese ontology, the paper proposed a new method which combines with context-semantics. This paper will be divided into four stages. The first stage is extracting the terminology of special area, the second is relationship definition, then ontology creation and the last is ontology evaluation and. On the first stage, it introduced Xtracts algorithms to extract compound words, which can integrate context-semantic into ontology construction.
Real-time multi-tasking in software synthesis for information processing systems

Software synthesis is a new approach which focuses on the support of embedded systems without the use of operating systems. Compared to traditional design practices, a better utilization of the available time and hardware resources can be achieved, because the static information provided by the system specification is fully exploited and an application-specific solution is automatically generated. On-going research on a software synthesis approach for real-time information processing systems is presented which starts from a concurrent process system specification and tries to automate the mapping of this description to a single processor. An internal representation model which is well-suited for the support of concurrency and timing constraints is proposed, together with flexible execution models for multi-tasking with real-time constraints. The method is illustrated on a personal terminal receiver demodulator for mobile satellite communication.
Bayesian ranking of biochemical system models

MOTIVATION There often are many alternative models of a biochemical system. Distinguishing models and finding the most suitable ones is an important challenge in Systems Biology, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Bayes factors are employed as a measure of evidential preference for one model over another. Marginal likelihood is a key component of Bayes factors, however computing the marginal likelihood is a difficult problem, as it involves integration of nonlinear functions in multidimensional space. There are a number of methods available to compute the marginal likelihood approximately. A detailed investigation of such methods is required to find ones that perform appropriately for biochemical modelling. RESULTS We assess four methods for estimation of the marginal likelihoods required for computing Bayes factors. The Prior Arithmetic Mean estimator, the Posterior Harmonic Mean estimator, the Annealed Importance Sampling and the Annealing-Melting Integration methods are investigated and compared on a typical case study in Systems Biology. This allows us to understand the stability of the analysis results and make reliable judgements in uncertain context. We investigate the variance of Bayes factor estimates, and highlight the stability of the Annealed Importance Sampling and the Annealing-Melting Integration methods for the purposes of comparing nonlinear models. AVAILABILITY Models used in this study are available in SBML format as the supplementary material to this article.
Learning to acquire whole-body humanoid CoM movements to achieve dynamic tasks

This paper presents a novel approach to acquire dynamic whole-body movements on humanoid robots focused on learning a control policy for the center of mass. A policy-gradient method is used to acquire a CoM movement as a control policy for achieving a desired dynamic task. A CoM-Jacobian-based redundancy resolution is then used to compute angular velocities for all joints in order to achieve a whole-body movement consistent with the CoM movement acquired through learning. To demonstrate the effectiveness of our method, we apply it in simulation to the learning of a strong punching movement on the Fujitsu humanoid robot, Hoap-2.
Detecting Hate, Offensive, and Regular Speech in Short Comments

The freedom of expression provided by the Internet also favors malicious groups that propagate contents of hate, recruit new members, and threaten users. In this context, we propose a new approach for hate speech identification based on Information Theory quantifiers (entropy and divergence) to represent documents. As a differential of our approach, we capture weighted information of words, rather than just their frequency in documents. The results show that our approach overperforms techniques that use data representation, such as TF-IDF and unigrams combined to text classifiers, achieving an F1-score of 86%, 84% e 96% for classifying hate, offensive, and regular speech classes, respectively. Compared to the baselines, our proposal is a win-win solution that improves efficacy (F1-score) and efficiency (by reducing the dimension of the feature vector). The proposed solution is up to 2.27 times faster than the baseline.
STRONG CONVERGENCE THEOREMS FOR EQUILIBRIUM PROBLEMS AND FIXED POINT PROBLEMS OF STRICT PSEUDO-CONTRACTION MAPPINGS

The purpose of this paper is to introduce an iterative scheme for finding a common element of the set of solutions of an equilibrium problem and the set of fixed points of a k strict pseudo-contraction non-self mapping in Hilbert space. By the viscosity approximation algorithms, under suitable con- ditions , some strong convergence theorems for approximating to this common elements are proved. The results presented in the paper extend and improve some recent results of Marino and Xu (G.Marino,H.K.Xu, Weak and strong convergence theorems for k strict pseudo-contractions in Hilbert spaces, J. Math. Anal. Appl. 329 (2007) 336-349), Zhou (H.Zhou, Convergence theorems of fixed Points for k strict pseudo-contractions in Hilbert spaces, Nonlinear Anal. 69 (2008) 456-462), Takahashi and Takahashi (S. Takahashi, W. Taka- hashi, Viscosity approximation methods for equilibrium problems and fixed point problems in Hilbert spaces, J. Math. Anal. Appl. 331 (2007) 506- 515), Ceng,Homidan,etc (L. C. Ceng, S.A.Homidan, Q.H.Ansari, J. C. Yao, An iterative scheme for equilibrium problems and fixed point problems of strict pseudo-contraction mappings, J. Comput. Appl. Math. 223 (2009) 967-974).
Nano-Based Optical Chemical Sensors

The development of nanoscale materials for optical chemical sensing applications has emerged as one of the most important research areas of interest over the past decades. Nanomaterials exhibit highly tunable size- and shape-dependent chemical and physical properties, show unique surface chemistry, thermal and electrical properties, high surface area and large pore volume per mass unit area. Because of their unique and advantageous features they can help to improve sensitivity, response time and detection limit of sensors. In this review, recently developed photoluminescence-based optical chemical nanosensors are presented. Some future trends of the nanomaterial-based optical chemical sensors are given.
Performance evaluation of packet classification on FPGA-based TCAM emulation architectures

Packet classification techniques are continuously challenged as network bandwidth increases and new services are deployed. Ternary Content Addressable Memories (TCAMs) have traditionally been used for scenarios requiring high-speed packet processing. However, TCAM-based classification suffers from high power consumption and clock rate limitations. Among several proposed solutions, TCAM emulation through RAM has emerged as a more flexible and energy-efficient strategy. On the other hand, Field-Programmable Gate Array (FPGA) devices have been evolving providing not only abundant logical resources but also an increasing number of integrated RAM blocks. This paper investigates performance and trade-offs related to TCAM emulation in FPGAs. In particular, we analyze the impact of encoding different key ranges on rules for different configurations in terms of the search key length and the number of rules. To validate and evaluate actual performance, we report and discuss results of real implementations on FPGA devices. Our work shows that classification rates above 300Mpps for both large keys and rule sets can be implemented with only a few megabits of RAM when considering up to medium size range matching intervals.
Heterogeneous Nuclear Ribonucleoprotein L Is a Subunit of Human KMT3a/Set2 Complex Required for H3 Lys-36 Trimethylation Activity in Vivo*

The presence of histone H3 lysine 36 methylation (H3K36me) correlates with actively transcribed genes. In yeast, histone H3K36me mediated by KMT3 (also known as Set2) recruits a histone deacetylase complex, Rpd3s, to ensure the fidelity of transcription initiation. We report the purification of human KMT3a (also known as HYPB or hSet2) complex and the identification of a novel, higher eukaryotic specific subunit, heterogeneous nuclear ribonucleoprotein L (HnRNP-L). Interestingly, although KMT3a has intrinsic activity in vitro, HnRNP-L is essential in vivo. Moreover, KMT3a generates mono-, di-, and trimethylated products in vitro, but RNA interference against KMT3a or HnRNP-L down-regulates exclusively the H3K36me3 mark in vivo.
DME interference analysis in aeronautical LTE networks

In the last decade, the aeronautical authorities expressed their need to develop a new aeronautical wireless communication system. The L-band Digital Aeronautical Communication System (L-DACS) is a candidate of the future system and orthogonal frequency-division multiplexing (OFDM) will be sued for it. Meanwhile, the Distance Measuring Equipment (DME) is also working in the aeronautical L-band. In our paper, taking LTE for example which is the prospective technology for aeronautical radio communications, we establish an aeronautical LTE communication link model and study the DME impact on it through analyzing the coexistence scenario between them. This article adopts the Monte-Carlo simulation method to perform the co-existing interference study and results show that how the performance of the aeronautical LTE system is affected. It can be very significant to provide reference for specific aeronautical LTE network deployment in practice and evaluating interferences with other aeronautical radio communication systems.
Keyframe-based real-time camera tracking

We present a novel keyframe selection and recognition method for robust markerless real-time camera tracking. Our system contains an offline module to select features from a group of reference images and an online module to match them to the input live video in order to quickly estimate the camera pose. The main contribution lies in constructing an optimal set of keyframes from the input reference images, which are required to approximately cover the entire space and at the same time minimize the content redundancy amongst the selected frames. This strategy not only greatly saves the computation, but also helps significantly reduce the number of repeated features so as to improve the camera tracking quality. Our system also employs a parallel-computing scheme with multi-CPU hardware architecture. Experimental results show that our method dramatically enhances the computation efficiency and eliminates the jittering artifacts.
Near-Optimal Trajectory Planning of a Spherical Mobile Robot for Environment Exploration

Spherical mobile robot has the characteristics of compact structure and agile motion and is promising to be used in unmanned environment. Designed for environment exploration, a spherical mobile robot BHQ-2 was briefly introduced. The kinematic equation of BHQ-2 was established and its controllability was proved with controllable Lie algebra. Based on the Ritz approximation theory, the near-optimal trajectory of BHQ-2 was planned with the Gauss-Newton algorithm. Simulation results and experimental results of the spherical mobile robot to plan trajectory with the method were presented.