Miracle-dz/UniFAR-FTUs huggingface dataset:
MR enteroclysis in the diagnosis of small-bowel neoplasms.

PURPOSE To evaluate the diagnostic accuracy and interobserver variance of magnetic resonance (MR) enteroclysis in the diagnosis of small-bowel neoplasms, with small-bowel endoscopy, surgery, histopathologic analysis, and follow-up serving as standards of reference, and to identify MR enteroclysis characteristics capable of enabling discrimination between benign and malignant small-bowel neoplasms. MATERIALS AND METHODS This study was performed in accordance with the guidelines of the institutional review board, and the requirement for informed consent was waived. MR enteroclysis studies of 91 patients (43 women, 48 men; age range, 18-83 years) were retrospectively evaluated by two radiologists blinded to clinical details. Only studies explicitly performed to investigate or exclude the presence of small-bowel neoplasms were included. Radiologic findings were compared with findings of double-balloon endoscopy (n = 45), surgery (n = 18), esophagogastroduodenoscopy (n = 3), ileocolonoscopy (n = 2), autopsy (n = 2), and clinical follow-up for more than 18 months (n = 21). Efficacy parameters were calculated with 95% confidence intervals. Tumor characteristics were compared with the Student t test and the Fisher exact test. RESULTS Readers 1 and 2 interpreted 31 and 33 studies, respectively, as depicting a small-bowel neoplasm and 19 and 17 studies, respectively, as depicting small-bowel malignancy. In 32 patients, the presence of small-bowel neoplasm was confirmed. In 19 of these patients, the neoplasm was malignant. Sensitivity and specificity in the diagnosis of small-bowel neoplasms was 0.91 and 0.95, respectively, for reader 1 and 0.94 and 0.97, respectively, for reader 2; the kappa value was 0.95. Factors associated with malignancy were the presence of longer solitary nonpedunculated lesions, mesenteric fat infiltration, and enlarged mesenteric lymph nodes. CONCLUSION Eighty-six of 91 studies were correctly interpreted, resulting in an overall diagnostic accuracy of 0.95 for MR enteroclysis in the detection of small-bowel neoplasms. SUPPLEMENTAL MATERIAL http://radiology.rsna. org/lookup/suppl/doi:10.1148/radiol.09090828/-/DC1.
TCP, XCP and RCP in Wireless mesh networks: An evaluation study

TCP is the most widely used congestion protocol in the Internet. However, TCP has some limitations, even in the wired world, such as not providing high utilizations in high bandwidth-delay product networks, and introducing high load and overhead in the network. Due to these limitations, several congestion protocols have been proposed. Some of the most known and recent protocols developed to provide faster and lighter congestion control are eXplicit Control Protocol (XCP) and Rate Control Protocol (RCP). These protocols have been proposed essentially to work in wired networks and environments; however, there are already new versions of XCP for wireless networks. Since these protocols have a large acceptation on the research field, and simultaneously,Wireless mesh networks (WMN) are in undergoing rapid progress, it is important to evaluate how XCP and RCP behave in these networks, as compared to TCP. This paper presents an evaluation study of TCP, XCP and RCP in WMNs, studying different WMN scenarios. Surprisingly, the results show that TCP is more efficient in mesh scenarios, being more fair and stable than XCP and RCP. To obtain the available network capacity, both XCP and RCP need that all nodes in the network cooperate, which increases network overhead, and reduces performance and fairness. Moreover, their capacity evaluation is not accurate in wireless networks.
Learning Concept Hierarchies through Probabilistic Topic Modeling

With the advent of semantic web, various tools and techniques have been introduced for presenting and organizing knowledge. Concept hierarchies are one such technique which gained significant attention due to its usefulness in creating domain ontologies that are considered as an integral part of semantic web. Automated concept hierarchy learning algorithms focus on extracting relevant concepts from unstructured text corpus and connect them together by identifying some potential relations exist between them. In this paper, we propose a novel approach for identifying relevant concepts from plain text and then learns hierarchy of concepts by exploiting subsumption relation between them. To start with, we model topics using a probabilistic topic model and then make use of some lightweight linguistic process to extract semantically rich concepts. Then we connect concepts by identifying an "is-a" relationship between pair of concepts. The proposed method is completely unsupervised and there is no need for a domain specific training corpus for concept extraction and learning. Experiments on large and real-world text corpora such as BBC News dataset and Reuters News corpus shows that the proposed method outperforms some of the existing methods for concept extraction and efficient concept hierarchy learning is possible if the overall task is guided by a probabilistic topic modeling algorithm.
i-vector Based Speaker Recognition on Short Utterances

Robust speaker verification on short utterances remains a key consideration when deploying automatic speaker recognition, as many real world applications often have access to only limited duration speech data. This paper explores how the recent technologies focused around total variability modeling behave when training and testing utterance lengths are reduced. Results are presented which provide a comparison of Joint Factor Analysis (JFA) and i-vector based systems including various compensation techniques; Within-Class Covariance Normalization (WCCN), LDA, Scatter Difference Nuisance Attribute Projection (SDNAP) and Gaussian Probabilistic Linear Discriminant Analysis (GPLDA). Speaker verification performance for utterances with as little as 2 sec of data taken from the NIST Speaker Recognition Evaluations are presented to provide a clearer picture of the current performance characteristics of these techniques in short utterance conditions.
A Generic Framework for Modeling Brain Deformation as a Constrained Parametric Optimization Problem to Aid Non-diffeomorphic Image Registration in Brain Tumor Imaging

Summary Objectives: In the present paper a novel computational framework for modeling tumor induced brain deformation as a biophysical prior for non-rigid image registration is described. More precisely, we aim at providing a generic building block for non-rigid image registration that can be used to resolve inherent irregularities in non-diffeomorphic registration problems that naturally arise in serial and cross-population brain tumor imaging studies due to the presence (or progression) of pathology. Methods: The model for the description of brain cancer dynamics on a tissue level is based on an initial boundary value problem (IBVP). The IBVP follows the accepted assumption that the progression of primary brain tumors on a tissue level is governed by proliferation and migration of cancerous cells into surrounding healthy tissue. The model of tumor induced brain deformation is phrased as a parametric, constrained optimization problem. As a basis of comparison and to demonstrate generalizability additional soft constraints (penalties) are considered. A backtracking line search is implemented in conjunction with a limited memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) method in order to handle the numerically delicate log-barrier strategy for confining volume change. Results: Numerical experiments are performed to test the flexible control of the computed deformation patterns in terms of varying model parameters. The results are qualitatively and quantitatively related to patterns in patient individual magnetic resonance imaging data. Conclusions: Numerical experiments demonstrate the flexible control of the computed deformation patterns. This in turn strongly suggests that the model can be adapted to patient individual imaging patterns of brain tumors. Qualitative and quantitative comparison of the computed cancer profiles to patterns in medical imaging data of an exemplary patient demonstrates plausibility. The designed optimization problem is based on computational tools widely used in non-rigid image registration, which in turn makes the model generally applicable for integration into non-rigid image registration algorithms.
Arithmetic with measurements on dynamically-typed object-oriented languages

In physics, like in other sciences, formulas are specified using explicit measurements, that is, a number with its unit. The first step to determine the validity of a physics formula's evaluation is to verify that the unit of the result corresponds with the prospective unit. In software development, physics, financial and other sciences formulas are programmed using mathematical expressions based only on numbers, being the units of these numbers implicitly given by the semantics of the program or assumed by the programmer's knowledge. Consequently, it is common that errors result from operating with values expressed in different units, e.g., dividing a quantity of years by a quantity of months, without obtaining any type of indication or objection to this error from the system. In this report, we discuss our experience designing and implementing a model that solves this problem reifying the concept of measurement, unit and their arithmetic. Our model relieves the programmer from the arduous task of verifying the validity of the arithmetic expressions regarding units, delegating that responsibility to the system, thereby, diminishing the errors introduced by the incorrect use of values expressed in different units. We also show that having implemented this model with a dynamically typed language simplified its programming and increased its reusability.
Competing Streams at the Cocktail Party: Exploring the Mechanisms of Attention and Temporal Integration

Processing of complex acoustic scenes depends critically on the temporal integration of sensory information as sounds evolve naturally over time. It has been previously speculated that this process is guided by both innate mechanisms of temporal processing in the auditory system, as well as top-down mechanisms of attention and possibly other schema-based processes. In an effort to unravel the neural underpinnings of these processes and their role in scene analysis, we combine magnetoencephalography (MEG) with behavioral measures in humans in the context of polyrhythmic tone sequences. While maintaining unchanged sensory input, we manipulate subjects' attention to one of two competing rhythmic streams in the same sequence. The results reveal that the neural representation of the attended rhythm is significantly enhanced in both its steady-state power and spatial phase coherence relative to its unattended state, closely correlating with its perceptual detectability for each listener. Interestingly, the data reveal a differential efficiency of rhythmic rates of the order of few hertz during the streaming process, closely following known neural and behavioral measures of temporal modulation sensitivity in the auditory system. These findings establish a direct link between known temporal modulation tuning in the auditory system (particularly at the level of auditory cortex) and the temporal integration of perceptual features in a complex acoustic scene, while mediated by processes of attention.
Sequential Regression: A Neodescriptive Approach to Multicollinearity

Classical regression analysis uses partial coefficients to measure the influences of some variables (regressors) on another variable (regressand). However, a descriptive point of view shows that these coefficients are very bad measures of influence. Their interpretation as an average change of the regressand is only valid if the regressors are weakly correlated, and they are useless when the degree of multicollinearity is high. Despite these obvious flaws there is a lack of alternative ideas to measure influences. On that score this paper proposes two new coefficients of influence: (1) A supplementary coefficient measures the additional influence of a regressor when certain variables are already taken into account. (2) A particular coefficient, which is a mean of certain supplementary coefficients, allocates the influence of a regressor within the collective influence of all regressors. Both new coefficients can directly be interpreted as average changes of the regressand
Markets with Many More Agents than Commodities: Aumann's "Hidden" Assumption

Abstract We address a question posed by J.-F. Mertens and show that, indeed, R. J. Aumann's classical existence and equivalence theorems depend on there being “many more agents than commodities. ” We show that for an arbitrary atomless measure space of agents there is a fixed non-separable infinite dimensional commodity space in which one can construct an economy that satisfies all the standard assumptions but which has no equilibrium, a core allocation that is not Walrasian, and a Pareto efficient allocation that is not a valuation equilibrium. We identify the source of the failure as the requirement that allocations be strongly measurable. Our main example is set in a commodity–measure space pair that displays an “acute scarcity” of strongly measurable allocations—where strong measurability necessitates that consumer choices be closely correlated no matter the prevailing prices. This makes the core large since there may not be any strongly measurable improvements even though there are many weakly measurable strict improvements. Moreover, at some prices the aggregate demand correspondence is empty since disaggregated demand has no strongly measurable selections, though it does have weakly measurable selections. We note that our example can be constructed in any vector space whose dimension is greater than the cardinality of the continuum—that is, whenever there are at least as many commodities as agents . We also prove a positive core equivalence result for economies in non-separable commodity spaces. Journal of Economic Literature Classification Numbers: C62, C71, D41, D50.
Effects of Aerobic Exercise on Premenopausal Sex Hormone Levels: Results of the WISER Study, a Randomized Clinical Trial in Healthy, Sedentary, Eumenorrheic Women

Background: It is hypothesized that exercise can lead to a decrease in breast cancer risk through several hormonal and nonhormonal mechanisms. The WISER (Women In Steady Exercise Research) study investigated the effects of aerobic exercise on premenopausal sex hormone levels. Methods: Three hundred ninety-one sedentary, healthy, young eumenorrheic women were randomized either into an exercise intervention of 30 minutes of aerobic exercise 5 times a week for approximately 16 weeks (n = 212) or into a control group (n = 179). Serum levels of estradiol, estrone sulfate, testosterone, and sex hormone–binding globulin (SHBG), all in the midfollicular phase, and of progesterone, in the midluteal phase, were measured at baseline and at the end of the 16-week period. Results: Compared with the controls (n = 153), exercisers (n = 166) experienced significant increases in aerobic fitness, lean body mass, and decreases in percent body fat. There were no significant changes in body weight and menstrual cycle length between or within groups. Progesterone decreased significantly in exercisers; however, this reduction was similar to that of the control group. No significant changes between or within groups were found for any of the other sex hormones or SHBG. Conclusions: In premenopausal women, 16 weeks of 150 minutes per week of moderate aerobic exercise in young women did not significantly alter sex hormone or SHBG levels. Impact: Any favorable effects that moderate aerobic exercise without an associated weight change may have on breast cancer risk in premenopausal women are unlikely to be a consequence of changes in levels of sex hormones or SHBG. Cancer Epidemiol Biomarkers Prev; 20(6); 1098–106. ©2011 AACR.
An investigative study on motifs extracted features on real time big-data signals

In last decade, temporal medical data analysis is considered as core data samples in technological processing and research. However, a practical scenario of processing is unachieved. In this paper, the authors have projected a diagnosis of real time heart signals under motifs features over the Electro Cardio Graphic (ECG) and Phono Cardio Graphic (PCG) datasets. A combination of local motif patters for ECG datasets and Featured signal patters under PCG dataset with feed machine learning techniques is appended. A case study is performed on real time digital datasets of Electrocardiogram and Phonocardiogram. The selective outcome of study is constructive in comparison with raw temporal data processing techniques.
A Holistic Approach to Risk for Early Kidney Injury in Indigenous Youth With Type 2 Diabetes: A Proof of Concept Paper From the iCARE Cohort

Background: Indigenous youth with type 2 diabetes (T2D) are disproportionately affected by early onset albuminuria and are at high risk of kidney failure in early adulthood. Traditional biological approaches have failed to fully explain the renal morbidity seen in this population. The improving renal Complications in Adolescents with type 2 diabetes through REsearch cohort (iCARE) study was therefore designed in collaboration with patients, to more holistically evaluate risk factors for renal morbidity. We hypothesize that both biological factors and mental health influence renal outcomes, mediated via inflammatory pathways. Objective: The objective of this study was to evaluate the iCARE analytic framework which evaluates relationships between biological factors, mental health, inflammation, and albuminuria utilizing a structural equation modeling (SEM) approach. Methods: The first 187 youth with T2D (10-25 years) from the Manitoba iCARE cohort are presented here to evaluate our theoretical and analytic framework. An SEM was chosen to evaluate the statistical significance of proposed associations. The primary outcome was a nonorthostatic urine albumin:creatinine ratio ≥2 mg/mmol. Main exposures (ie, latent factors) included psychological health (distress, perceived stress, positive mental health and resilience), hypertension (24 hour monitored), and inflammatory markers (C-reactive protein [CRP], erythrocyte sedimentation rate [ESR], fibrinogen). Hemoglobin A1c (HbA1c) and duration of diabetes were covariates. Results: Within the initial cohort (median age = 15 years, duration of diabetes = 2.3 years, 66.8% female), 30.5% (n = 57) had nonorthostatic albuminuria (ALB), and the majority of ALB was persistent (confirmed in 2/3 samples over a 6-month period; n = 47). Youth with ALB had higher HbA1c (10.9% vs 8.9%; P < .001), more hypertension (94.2% vs 78·2%; P = .02), longer duration of diabetes (3.4 vs 2.4 years; P = .01), higher distress (9.2 vs 7.3; P = .02), and stress scores (28.7 vs 26.4; P = .03), and elevated inflammatory markers (CRP: 4.9 vs 3.1 mg/L; P = .01, fibrinogen: 3.7 vs 3.3 µmol/L; P = .02). Factors directly associated with ALB in the SEM were hypertension (0.28; P = .001), inflammation (0.41; P < .001), and HbA1c (0.50; P < .001). Psychological health was independently associated with inflammation (−0.20; P < .001) but not directly associated with ALB. Conclusions: Albuminuria is highly prevalent in Indigenous youth with T2D. This preliminary analysis supports a theoretical framework linking glycemic control, hypertension, and inflammation, potentially mediated by psychological factors with albuminuria. These data support the need for more holistic models of evaluation and care for youth with T2D and multifactorial interventions to prevent complications.
Calsyntenin-1 mediates axonal transport of the amyloid precursor protein and regulates Aβ production

Understanding the mechanisms that control processing of the amyloid precursor protein (APP) to produce amyloid-β (Aβ) peptide represents a key area of Alzheimer's disease research. Here, we show that siRNA-mediated loss of calsyntenin-1 in cultured neurons alters APP processing to increase production of Aβ. We also show that calsyntenin-1 is reduced in Alzheimer's disease brains and that the extent of this reduction correlates with increased Aβ levels. Calsyntenin-1 is a ligand for kinesin-1 light chains and APP is transported through axons on kinesin-1 molecular motors. Defects in axonal transport are an early pathological feature in Alzheimer's disease and defective APP transport is known to increase Aβ production. We show that calsyntenin-1 and APP are co-transported through axons and that siRNA-induced loss of calsyntenin-1 markedly disrupts axonal transport of APP. Thus, perturbation to axonal transport of APP on calsyntenin-1 containing carriers induces alterations to APP processing that increase production of Aβ. Together, our findings suggest that disruption of calsyntenin-1-associated axonal transport of APP is a pathogenic mechanism in Alzheimer's disease.
Spilogale gracilis

CONTEXT AND CONTENT. Order Carnivora, family Mephitidae, genus Spilogale (Dragoo and Honeycutt 1997). Traditionally, skunks of the genera Spilogale, Conepatus, and Mephitis were included in the family Mustelidae, subfamily Mephitinae, but Dragoo and Honeycutt (1997), based on analyses of mitochrondrial DNA (mtDNA) sequences, found that these genera plus the stinkbadgers (Mydaus) formed a clade separate from other mustelids. Thus, they placed members of the clade in a separate family. At various times, spotted skunks in western North America were treated as specifically distinct (Davis and Schmidly 1994; Hall and Kelson 1952, 1959; Jones et al. 1992; Kinlaw 1995) and at other times gracilis was considered a subspecies of S. putorius (Hall 1981; Ramirez-Pulido et al. 1996; Seton 1929; Van Gelder 1959; Wozencraft 1993). Hall and Kelson (1952) suggested that proof of intergradation between eastern and western forms ultimately would be found. Later they (Hall and Kelson 1959:929) claimed that "Most workers are of the opinion that the genus Spilogale is monotypic, or has, at most, 2 or 3 species. " Nevertheless, they cited no references in support of their contention. In the most recent morphologic and morphometric treatment of the genus Spilogale, Van Gelder (1959) recognized only 2 species: S. putorius and S. pygmaea. Based on specimens from southern Texas, deemed intermediate between smaller animals with more extensive white to the west and larger, blacker individuals to the east, he subsumed S. gracilis, and all of its former subspecies, into S. putorius. He did not find evidence of intergradation between eastern and western populations through the remainder of the midsection of the continent (Van Gelder 1959:251, figure 4). Subsequently, eastern and western spotted skunks were determined to have bacula of different shape and size (Mead 1966) and to be reproductively isolated temporally (Mead 1968b), creating justification for recognition of S. gracilis as a distinct species. Based on analyses of cytochrome b and a region of the mtDNA Dloop, separation of S. gracilis and S. putorius as distinct species was supported (Dragoo et al. 1993). The latter authors suggested (Dragoo et al. 1993:264) that "if there is gene flow between the eastern and the western forms in the United States it is probably occurring via Central American forms. " Herein, we review information available on spotted skunks (other than S. pygmaea and S. angustifrons sensu Hall and Kelson 1959) in the Rocky Mountains and westward not considered by Kinlaw (1995). Hall and Kelson (1959) included 10 subspecies in S. gracilis. Hall (1981) acknowledged Van Gelder's (1959) recognition of only 7 races in the same geographic region, but he retained the delineation between western and eastern forms on the range map (Hall 1981:1016, map 518) from Hall and Kelson's (1959) treatment of the genus. He placed all 7 within S. putorius. These races, herein considered subspecies of S. gracilis, are as follows: