Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential White Matter Connectivity in Early Mild Cognitive Impairment According to CSF Biomarkers

Mild cognitive impairment (MCI) is a heterogeneous group and certain MCI subsets eventually convert to dementia. Cerebrospinal fluid (CSF) biomarkers are known to predict this conversion. We sought evidence for the differences in white matter connectivity between early amnestic MCI (EMCI) subgroups according to a CSF phosphorylated tau181p/amyloid beta1–42 ratio of 0.10. From the Alzheimer's Disease Neuroimaging Initiative database, 16 high-ratio, 25 low-ratio EMCI patients, and 20 normal controls with diffusion tensor images and CSF profiles were included. Compared to the high-ratio group, radial diffusivity significantly increased in both sides of the corpus callosum and the superior and inferior longitudinal fasciculus in the low-ratio group. In widespread white matter skeleton regions, the low-ratio group showed significantly increased mean, axial, and radial diffusivity compared to normal controls. However, the high-ratio group showed no differences when compared to the normal group. In conclusion, our study revealed that there were significant differences in white matter connectivity between EMCI subgroups according to CSF phosphorylated tau181p/amyloid beta1–42ratios.
Husserl's Crisis of the European Sciences and Transcendental Phenomenology: An Introduction

Preface Introduction: Husserl's life and writings 1. Husserl's Crisis: an unfinished masterpiece 2. Galileo's revolution and the origins of modern science 3. The Crisis in psychology 4. Rethinking tradition: Husserl on history 5. Husserl's problematical concept of the life-world 6. Phenomenology as transcendental philosophy 7. The ongoing influence of Husserl's Crisis.
Low complexity direction of arrival (DoA) estimation for 2D massive MIMO systems

Mobile data traffic is expected to almost double every year from 2012 to 2016. In order to address the challenge, “massive MIMO” has been proposed as one of the enabling technologies to significantly increase the spectral-efficiency of a wireless system. In “massive MIMO” systems, a base station will rely on the uplink sounding signals from mobile stations to figure out the channel knowledge to perform MIMO beam-forming. Accordingly, direction-of-arrival estimation at the base station becomes crucial for “massive MIMO” systems to realize the predicted capacity gains. In this paper, we study DoA estimation for two-dimensional (2D) “massive MIMO” systems in mobile wireless systems. To be specific, we derive the Cramer-Rao lower bound for 2D “massive MIMO” systems and introduce a low complexity direction-of-arrival estimation algorithm to jointly estimate elevation and azimuth angles of the arrived signals based on unitary transformation. Results suggest that the dimension of the antenna array at the base station plays an important role in the estimation performance. It is also found that azimuth estimation is more vulnerable compared to elevation estimation. These insights will be useful for designing practical “massive MIMO” systems in future mobile wireless communications.
Calcineurin inhibition enhances motor neuron survival following injury

The immunosuppressive agents cyclosporin A (CsA) and FK‐506 have previously been shown to exhibit neurotrophic and neuroprotective properties in vivo. Given that significant clinical expertise exists for both drugs, they represent an attractive starting point for treatment of acute neural injuries. One putative mechanism for neuroprotection by these drugs relates to inhibition of calcineurin activity. However each drug–immunophilin complex can potentially influence additional signal transduction pathways. Furthermore, several non‐immunosuppressive immunophilin ligands have been described as possessing neuroprotective properties, suggesting that neuroprotection may be separable from calcineurin inhibition. In the present study, we examined the mechanism of this neuroprotection in facial motor neurons following axotomy‐induced injury. Similar to previous studies in rats, CsA and FK‐506 enhanced motor neuron survival in mice following acute injury. To examine the mechanism responsible for neuroprotection by these agents, pharmacologic inhibitors of several potential alternate signalling pathways (17‐(allylamino)‐17‐demethoxygeldanamycin, rapamycin, cypermethrin) were evaluated with respect to neuroprotection. Of these, only cypermethrin, a direct calcineurin inhibitor not previously associated with neuronal survival properties, was observed to significantly enhance motor neuron survival following injury. The results demonstrate for the first time that direct inhibition of calcineurin is neuroprotective in vivo. These data support a model in which calcineurin inhibition promotes neuronal survival, distinct from effects upon neurite outgrowth.
A Network Traffic Classification Method Using Support Vector Machine with Feature Weighted-degree

Currently, the network traffic classification has two important problems, which are low accuracy and high computation complexity. In order to solve these problems, a novel network traffic classification method using support vector machine with feature weighted-degree (FWD-SVM) is proposed in this study. Our method can efficiently reduce the influence on the sample distribution, relative properties, and redundancy. Through reducing the training time of traffic classification machine and the predicting time of unknown samples,our method speeds up computation performance. Using support vector machine with feature weighted-degree, our method improves the stability and the accuracy of classification. The experimental results demonstrate that the proposed method not only can greatly reduce the computation complexity, but also has higher classified accuracy. Subject Categories and Descriptors C.2. 1 [Network Architecture and Design]: Network topology General Terms Support Vector Machines, Network Traffic, Network Classification
Multiple window time-frequency distribution and coherence of EEG using Slepian sequences and Hermite functions

Multiple window (MW) time-frequency analysis (TFA) is a newly developed technique to estimate a time-varying spectrum for random nonstationary signals with low bias and variance. In this paper, the authors describe the application of MW-TFA techniques to electroencephalogram (EEG) and compare the results with those of the conventional spectrogram. They find that the MW-TFA provides them with not only low bias and variance time-frequency (TF) distribution for EEG but also TF coherence estimation between a single realization of EEG recorded from two sites. They also compare the performance of the MW-TFA using two sets of windows, Slepian sequences, and Hermite functions. If care is taken in matching the two windows, the authors find no noticeable difference in the resulting TF representations.
Color, texture and shape descriptor fusion with Bayesian network classifier for automatic image annotation

Due to the large amounts of multimedia data prevalent on the Web, Some images presents textural motifs while others may be recognized with colors or shapes of their content. The use of descriptors based on one’s features extraction method, such as color or texture or shape, for automatic image annotation are not efficient in some situations or in absence of the chosen type. The proposed approach is to use a fusion of some efficient color, texture and shape descriptors with Bayesian networks classifier to allow automatic annotation of different image types. This document provides an automatic image annotation that merges some descriptors in a parallel manner to have a vector that represents the various types of image characteristics. This allows increasing the rate and accuracy of the annotation system. The Texture, color histograms, and Legendre moments, are used and merged respectively together in parallel as color, texture and shape features extraction methods, with Bayesian network classifier, to annotate the image content with the appropriate keywords. The accuracy of the proposed approach is supported by the good experimental results obtained from ETH-80 databases.
Maximum and entropic repulsion for a Gaussian membrane model in the critical dimension

We consider the real-valued centered Gaussian field on the four-dimensional integer lattice, whose covariance matrix is given by the Green's function of the discrete Bilaplacian. This is interpreted as a model for a semi-flexible membrane. d = 4 is the critical dimension for this model. We discuss the effect of a hard wall on the membrane, via a multiscale analysis of the maximum of the field. We use analytic and probabilistic tools to describe the correlation structure of the field.
Context information based initial cell search for millimeter wave 5G cellular networks

Millimeter wave (mmWave) communication is envisioned as a cornerstone to fulfill the data rate requirements for fifth generation (5G) cellular networks. In mmWave communication, beamforming is considered as a key technology to combat the high path-loss, and unlike in conventional microwave communication, beamforming may be necessary even during initial access/cell search. Among the proposed beamforming schemes for initial cell search, analog beamforming is a power efficient approach but suffers from its inherent search delay during initial access. In this work, we argue that analog beamforming can still be a viable choice when context information about mmWave base stations (BS) is available at the mobile station (MS). We then study how the performance of analog beamforming degrades in case of angular errors in the available context information. Finally, we present an analog beamforming receiver architecture that uses multiple arrays of Phase Shifters and a single RF chain to combat the effect of angular errors, showing that it can achieve the same performance as hybrid beamforming.
(1 + εΒ)-spanner constructions for general graphs

An <italic>(α,Β)</italic>-spanner of a graph <italic>G</italic> is a subgraph <italic>H</italic> such that <italic>d_H(u,w)\le &agr\cdot d_G(u,w)+&Bgr</italic> for every pair of vertices <italic>u,w</italic>, where <italic>d_{G'}(u,w)</italic> denotes the distance between two vertices <italic>u</italic> and <italic>v</italic> in <italic>G'</italic>. It is known that every graph <italic>G</italic> has a polynomially constructible <italic>(2&kgr;-1,0)</italic>-spanner (a.k.a. <italic>multiplicative</italic> <italic>(2&kgr;-1)</italic>-spanner) of size <italic>O(n^{1+1/&kgr})</italic> for every integer <italic>&kgr\ge 1</italic>, and a polynomially constructible <italic>(1,2)</italic>-spanner (a.k.a. <italic>additive</italic> 2-spanner) of size <italic>\tO(n^{3/2})</italic>. This paper explores hybrid spanner constructions (involving both multiplicative and additive factors) for general graphs and shows that the multiplicative factor can be made <italic>arbitrarily close to 1</italic> while keeping the spanner size arbitrarily close to <italic>O(n)</italic>, at the cost of allowing the additive term to be a sufficiently large constant. More formally, we show that for any constant <italic>&egr, &dgr > 0</italic> there exists a constant <italic>&Bgr = &Bgr(&egr, &dgr)</italic> such that for every <italic>n</italic>-vertex graph <italic>G</italic> there is an efficiently constructible <italic>(1+ &egr, &Bgr)</italic>-spanner of size <italic>O(n^{1 + &dgr})<italic>. It follows that for any constant <italic>&egr, &dgr > 0</italic> there exists a constant <italic>&Bgr(&egr, &dgr)</italic> such that for any <italic>n</italic>-vertex graph <italic>G = (V,E)</italic> there exists an efficiently constructible subgraph <italic>(V,H)</italic> with <italic>O(n^{1 +&dgr})</italic> edges such that <italic>d_H(u,w) \le (1 + &egr) d_G(u,w) </italic> for every pair of vertices.
Different degrees of explicitness in intentional artifacts: studying user goals in a large search query log

On the web, search engines represent a primary instrument through which users exercise their intent. Understanding the specific goals users express in search queries could improve our theoretical knowledge about strategies for search goal formulation and search behavior, and could equip search engine providers with better descriptions of users' information needs. However, the degree to which goals are explicitly expressed in search queries can be suspected to exhibit considerable variety, which poses a series of challenges for researchers and search engine providers. This paper introduces a novel perspective on analyzing user goals in search query logs by proposing to study different degrees of intentional explicitness. To explore the implications of this perspective, we studied two different degrees of explicitness of user goals in the AOL search query log containing more than 20 million queries. Our results suggest that different degrees of intentional explicitness represent an orthogonal dimension to existing search query categories and that understanding these different degrees is essential for effective search. The overall contribution of this paper is the elaboration of a set of theoretical arguments and empirical evidence that makes a strong case for further studies of different degrees of intentional explicitness in search query logs.
A central role for the mammalian target of rapamycin in LPS-induced anorexia in mice.

Bacterial lipopolysaccharide (LPS), also known as endotoxin, induces profound anorexia. However, the LPS-provoked pro-inflammatory signaling cascades and the neural mechanisms underlying the development of anorexia are not clear. Mammalian target of rapamycin (mTOR) is a key regulator of metabolism, cell growth, and protein synthesis. This study aimed to determine whether the mTOR pathway is involved in LPS-induced anorexia. Effects of LPS on hypothalamic gene/protein expression in mice were measured by RT-PCR or western blotting analysis. To determine whether inhibition of mTOR signaling could attenuate LPS-induced anorexia, we administered an i.c. v. injection of rapamycin, an mTOR inhibitor, on LPS-treated male mice. In this study, we showed that LPS stimulates the mTOR signaling pathway through the enhanced phosphorylation of mTOR(Ser2448) and p70S6K(Thr389). We also showed that LPS administration increased the phosphorylation of FOXO1(Ser256), the p65 subunit of nuclear factor kappa B (P<0.05), and FOXO1/3a(Thr) (24) (/) (32) (P<0.01). Blocking the mTOR pathway significantly attenuated the LPS-induced anorexia by decreasing the phosphorylation of p70S6K(Thr389), FOXO1(Ser256), and FOXO1/3a(Thr) (24) (/) (32). These results suggest promising approaches for the prevention and treatment of LPS-induced anorexia.
Towards micro-groupware: Supporting Small Group Activities Around Assistive Technology

Assistive technology (AT) aims at compensating for motor, sensory or cognitive functional limitations of its users. Severely disabled users typically need to rely on family and caregivers to setup and manage the technology they need to use on a daily basis. We propose a conceptual blueprint for an assistive technology micro-groupware platform for users with severe motor limitations. Stakeholders can address the definition of roles and forms of participation for a small group of people with situation-dependent configuration tasks at different levels and dimensions.
A classification approach to finding buildings in large scale aerial photographs

Automatic building extraction remains an open research problem in digital photogrammetry. While many algorithms are proposed for building extraction, none of these solve the problem completely. One of their limitations is in the initial detection of the presence or absence of a building in the image region. One approach to the initial detection of buildings is to cast the problem as one of classification, where the image is divided into patches that either contain or do not contain a building. Support Vector Machines (SVMs) are a relatively new classification tool that appear well suited to this task. They are closely related to other machine learning techniques such as neural networks but have a stronger base in statistical theory and produce a generalised solution to the classification problem, using the principles of structural risk minimisation.
Strategic Decision Making Processes: Extending Theory to an English University Strategic Decision Making Processes: Cases from an English University

A wide variety of factors influence the quality of strategic decisions. This research considers one such influence, the Strategic Decision Making process. It explores whether previous theoretical propositions hold in quite different organisations in a very different business environment, namely a University in England. The research examines how a strategic problem was addressed. Interviews with the Top Management Team, supported by documentary evidence, are content analysed for the relevance of the propositions in this new environment. Two cases of decision making, relating to the same problem, in a single university suggest that the propositions are indeed relevant.
Autoethnography as a Transformative Research Method

Autoethnography is a qualitative, transformative research method because it changes time, requires vulnerability, fosters empathy, embodies creativity and innovation, eliminates boundaries, honors subjectivity, and provides therapeutic benefits. This article discusses these seven lenses using select passages from “Jesus Christ and Reese's Peanut Butter Cups: A Narrative on Homosexual Identity, Spirituality, and Human Development” (an unpublished manuscript) written in 2013. Keywords: autoethnography, reflexivity, transformative, qualitative research, education The Journey Begins: Falling Into Autoethnography Several months ago I began a journey. The journey was a personal adventure into my subconscious in an effort to understand and find closure with certain traumatic events from my past, but what started out as a simple story quickly became a full-fledged research project centered around embodied writing, performance, and autoethnography. The final product later came to be known as “Jesus Christ and Reese's TM Peanut Butter Cups: A Narrative on Homosexual Identity, Spirituality, and Human Development” (“JCRPBC”; Custer, 2013). At first, the method I chose to use for this article was foreign to me, but as I immersed myself in the existing literature and reflected upon my style of writing, I came to know and embrace autoethnography. Autoethnography is a style of autobiographical writing and qualitative research that explores an individual’s unique life experiences in relationship to social and cultural institutions. Carolyn Ellis in the Handbook of Autoethnography describes this powerful qualitative method eloquently. … autoethnography is not simply a way of knowing about the world; it has become a way of being in the world, one that requires living consciously, emotionally, reflexively. It asks that we not only examine our lives but also consider how and why we think, act, and feel as we do. Autoethnography requires that we observe ourselves observing, that we interrogate what we think and believe, and that we challenge our own assumptions, asking over and over if we have penetrated as many layers of our own defenses, fears, and insecurities as our project requires. It asks that we rethink and revise our lives, making conscious decisions about who and how we want to be. And in the process, it seeks a story that is hopeful, where authors ultimately write themselves as survivors of the story they are living. (Jones, 2013, p. 10) The process of autoethnography can uncover many different feelings within the writer. It can be joyful, sad, revealing, exciting, and occasionally painful. Diana Raab (2013) writes, “Because many autoethnographical studies relate to painful experiences, the researcher may encounter difficult moments during the course of the research and writing” (p. 14). Not only does an individual have to face their own pain, often times they are exposed to the pain and anguish of other people who have experienced similar circumstances. It is not an easy task to
The Crystal Structures of the Ferric and Ferrous Forms of the Heme Complex of HmuO, a Heme Oxygenase of Corynebacterium diphtheriae*

Crystal structures of the ferric and ferrous heme complexes of HmuO, a 24-kDa heme oxygenase of Corynebacterium diphtheriae, have been refined to 1.4 and 1.5 Å resolution, respectively. The HmuO structures show that the heme group is closely sandwiched between the proximal and distal helices. The imidazole group of His-20 is the proximal heme ligand, which closely eclipses the β- and δ-meso axis of the porphyrin ring. A long range hydrogen bonding network is present, connecting the iron-bound water ligand to the solvent water molecule. This enables proton transfer from the solvent to the catalytic site, where the oxygen activation occurs. In comparison to the ferric complex, the proximal and distal helices move closer to the heme plane in the ferrous complex. Together with the kinked distal helix, this movement leaves only the α-meso carbon atom accessible to the iron-bound dioxygen. The heme pocket architecture is responsible for stabilization of the ferric hydroperoxo-active intermediate by preventing premature heterolytic O-O bond cleavage. This allows the enzyme to oxygenate selectively at the α-meso carbon in HmuO catalysis.
Reliability and Validity of a Substance Craving Scale: Testing Invariance across Substances

Craving for alcohol or drugs has been studied for many years by scholars and clinicians in an effort to improve the efficiency of substance abuse treatment across individuals and settings. The reduction of craving has been conceptualized as a target of intervention in addiction treatment programs and post treatment relapse prevention programs. The purpose of this research was to develop a substance craving scale that is reliable and valid for use across substance use disorders. The scale was examined via the Rasch model, an item response theory model that provides the analysis of data through use of a single, difficulty parameter. To date, there has been no Rasch analysis conducted of a substance craving scale that assesses cravings for all substances. The current Substance Craving Scale was developed based on several of the prior validated, drug-specific scales that are used to measure substance craving. An additional craving item, used on the National Longitudinal Alcohol Epidemiologic Survey and a key basis of the DSM-V decision to add craving as a criterion, was also included in the final scale. Analysis of the data employed both Rasch and traditional test theory techniques. The measure was analyzed with a Rasch dichotomous model with Winsteps statistical software, and other techniques used SPSS statistical software. Analyses were performed to provide summary statistics of the data, to determine item fit, dimensionality of the measure, reliability, validity, and differential item functioning (DIF) for substance of choice. The results showed that all but one item on the measure were appropriate based on a preliminary item analysis, and the final psychometric analyses were conducted on the revised 11-item scale. The craving scale was found to be unidimensional, reliable for research purposes, and showed evidence of validity of construct. Most importantly, there was no significant differential item functioning by substance of choice. Several items were discussed regarding their theoretical importance, and the validity and reliability of the scale were critiqued. Limitations of the study included homogeneity of the sample, hence reliability and validity of the Substance Craving Scale should be replicated in different samples, especially for those individuals entering substance treatment.