Miracle-dz/UniFAR-FTUs huggingface dataset:
Cytology of "significant" breast ductal proliferations.

OBJECTIVE To determine the usefulness of fine needle aspiration cytology in diagnosing breast ductal proliferations that fall short of invasive cancer (hyperplasia, atypia and in situ carcinoma). STUDY DESIGN This study was a comparison of the cytomorphology and histomorphology of 30 palpable breast lesions in which an initial fine needle aspiration diagnosis of ductal hyperplasia or atypia was based on available criteria. RESULTS Among six patients, a cytologic diagnosis of mild hyperplasia, based on monolayered cell sheets, was confirmed in five. Fourteen cytologic reports of moderate hyperplasia, based on three-dimensional cell clusters, cell overlap and sublumens, were confirmed in 12. A cytomorphologic diagnosis of atypical ductal hyperplasia was rejected in four of seven patients. Three cases of marked cytologic atypia were diagnosed histopathologically as ductal carcinoma in situ. CONCLUSION In breast aspirates, three-dimensional ductal cell clusters, a swirling pattern of growth, sublumens, cell dyscohesion and conspicuous nuclear overlap indicate moderate ductal hyperplasia. Ductal atypia should be diagnosed only on such nuclear features as anisonucleosis, irregular nuclear membranes, clumped chromatin and eosinophilic macronucleoli. Cytologists should highlight those features which are important to diagnose breast proliferations as "significant" from the viewpoint of progressing to invasive cancer and not attempt too fine a classification of these lesions.
Reduced Serotonin Transporter Availability Decreases Prefrontal Control of the Amygdala

After a threatening event, the risk of developing social psychopathologies is increased in short-allele (s) carriers of the serotonin transporter gene. The amygdala becomes overresponsive to emotional stimuli, an effect that could be driven by local hypersensitivity or by reduced prefrontal regulation. This study distinguishes between these two hypotheses by using dynamic causal modeling of fMRI data acquired in a preselected cohort of human s-carriers and homozygous long-allele carriers. Increased amygdala activity in s-carriers originates from reduced prefrontal inhibitory regulation when social emotional behavior needs to be controlled, suggesting a mechanism for increased vulnerability to psychopathologies.
A generic homogenization model for magnetoelectric multiferroics

A generic homogenization modeling framework which incorporates crystallographic domain features is introduced and computationally implemented for magnetoelectric multiferroics of all symmetries. The homogenization, mathematically applicable to heterogeneous media with contrasts in physical properties, replaces the heterogeneity of the multiferroics by an equivalent effective medium with uniform physical characteristics. A statistically representative unit-cell is proposed to encompass all forms of multiferroics and their composites in bulk. The variational formulation of the coupled magneto-electromechanical problem reveals the nature of interaction between mechanical, electrical, and magnetic fields of a multiferroic at a microscopic scale with high resolution. Furthermore, the mathematical homogenization theory of the multiferroic is implemented in finite element method by solving the coupled equilibrium electrical, magnetic, and mechanical fields. A “multiferroic finite element” is conceived for this purpose. The model is applied to a two-phase multiferroic magnetoelectric composite to demonstrate its validity by characterizing the equivalent physical properties.
An active approach to consolidating TCP and ABR flow control

The active network paradigm no longer views data as passive but as a program, or a parameter to a program in the network elements. Active networks provide a framework for network management computations to be performed within the network elements. In this paper, we consider the available bit rate service (ABR) as an active networked service. In this study, we use the transmission control protocol (TCP) protocol data unit (PDU) to control the TCP and ABR source buffers. We demonstrate that the performance of TCP is improved by injecting, at the switch, duplicate acknowledgements which throttle TCP and yet maintain existing TCP and ABR dynamics.
Cornea Expression of Toll-Like Receptor 4 Contributes to Corneal Inflammation in Experimental Dry Eye Disease

METHODS. Seven to 8-week-old female C57BL/6 mice were housed in a controlled environment chamber and administered scopolamine to induce experimental DED. Mice received intravenous TLR4 inhibitor (Eritoran) to block systemic TLR4mediated activity. The expression of TLR4 by the corneal epithelium and stroma was evaluated using real-time polymerase chain reaction and flow cytometry. Corneal fluorescein staining (CFS) was performed to evaluate clinical disease severity. The corneal expression of proinflammatory cytokines (IL-1b, IL-6, TNF, and CCL2), corneal infiltration of CD11bþ antigen-presenting cells, and lymph node frequency of mature MHC-II CD11bþ cells were assessed.
Mexiletine and Lidocaine Suppress the Excitability of Dorsal Horn Neurons

BACKGROUND: Spinal sensitization and facilitatory processes in dorsal horn neurons after nerve injury alter spinal outflow leading to enhanced pain perception and chronic pain syndromes. Clinically used Na+ channel blockers at doses which do not block conduction can relieve such chronic pain. Although much attention has been paid to their effect upon afferents, less work has been done with their effect on the excitability of central sensory neurons. Thus, we investigated the effects of the Na+ channel blockers mexiletine and lidocaine on sensory spinal dorsal horn neurons. METHODS: Patch-clamp recordings were directly performed in visualized neurons of the substantia gelatinosa in the spinal cord of young rats to investigate the effect of mexiletine and lidocaine in different types of dorsal horn neurons (tonically firing, adapting-firing, and single spike neurons). RESULTS: All three different types of neurons responded dose-dependently to mexiletine and lidocaine. Both local anesthetics reversibly inhibited Na+ and K+ currents. The half-maximal inhibitory concentration for Na+ conductance block was 89 ± 2 or 54 ± 6 &mgr;M and for delayed-rectifier K+ conductance block was 582 ± 36 or 398 ± 14 &mgr;M for lidocaine and mexiletine, respectively. The inhibition of Na+ and K+ currents consecutively altered the properties of single action potentials and reduced the firing rate of tonically firing and adapting-firing neurons. CONCLUSIONS: In clinically relevant concentrations, lidocaine and mexiletine reduced the excitability of sensory dorsal horn neurons via a blockade of Na+ and K+ channels. Our work confirms that, in addition to the peripheral effects of lidocaine and mexiletine, modulation of voltage-gated ion channels in the central nervous system contributes to the antinociceptive effects of these drugs used in pain therapy.
Risk Potentiality of Frontline Radiotherapy Associated Cataract in Primary Ocular Adnexal Mucosa-associated Lymphoid Tissue Lymphoma

Purpose To elucidate risk potentiality of frontline radiotherapy associated cataracts in primary ocular adnexal mucosa-associated lymphoid tissue lymphoma (OAML). Methods Data from eight consecutive patients of 41 total OAML patients who had undergone cataract surgery after frontline radiotherapy were analyzed. Results The median patient age was 46 years (range, 36 to 69 years). The median total radiation dose was 3,780 cGy (range, 3,060 to 4,500 cGy), and the mean duration from radiation irradiation to cataract surgery was 36.60 ± 8.93 months. Preoperative lens opacification was primarily at the posterior lens subcapsule, and best-corrected visual acuity (BCVA) was 0.43 ± 0.21. Patients underwent the phacoemulsification surgical procedure with posterior chamber intraocular lens insertion. The average BCVA improved to 0.90 ± 0.14 after cataract surgery. Two patients underwent posterior continuous curvilinear capsulorhexis, and one had posterior capsule rupture. For posterior capsule opacification (PCO), three patients received Nd:YAG laser posterior capsulotomy after the initial surgery, and one patient is currently under consideration for laser posterior capsulotomy. Conclusions Radiotherapy increased posterior subcapsule opacification at a relatively young age in primary OAML. Phacoemulsification was a manageable procedure without severe complications, and final visual outcomes were good. However, because after-cataracts progressed earlier than did senile cataracts, close follow-up should be considered for PCO management.
An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.
A new de-blurring technique for license plate images with robust length estimation

Recognizing a license plate clearly while seeing a surveillance camera snapshot is often important in cases where the troublemaker vehicle(s) have to be identified. In many real world situations, these images are blurred due to fast motion of the vehicle and cannot be recognized by the human eye. For this kind of blurring, the kernel involved can be said to be a linear uniform convolution described by its angle and length. We propose a new de-blurring technique in this paper to parametrically estimate the kernel as accurately as possible with emphasis on the length estimation process. We use a technique which employs Hough transform in estimating the kernel angle. To accurately estimate the kernel length, a novel approach using the cepstral transform is introduced. We compare the de-blurred results obtained using our scheme with those of other recently introduced blind de-blurring techniques. The comparisons corroborate that our scheme can remove a large blur from the image captured by the camera to recover vital semantic information about the license plate.
A Bayesian Wilcoxon signed-rank test based on the Dirichlet process

Bayesian methods are ubiquitous in machine learning. Nevertheless, the analysis of empirical results is typically performed by frequentist tests. This implies dealing with null hypothesis significance tests and p-values, even though the shortcomings of such methods are well known. We propose a nonparametric Bayesian version of the Wilcoxon signed-rank test using a Dirichlet process (DP) based prior. We address in two different ways the problem of how to choose the infinite dimensional parameter that characterizes the DP. The proposed test has all the traditional strengths of the Bayesian approach; for instance, unlike the frequentist tests, it allows verifying the null hypothesis, not only rejecting it, and taking decisions which minimize the expected loss. Moreover, one of the solutions proposed to model the infinite-dimensional parameter of the DP allows isolating instances in which the traditional frequentist test is guessing at random. We show results dealing with the comparison of two classifiers using real and simulated data.
A Review of Medication Reconciliation Issues and Experiences with Clinical Staff and Information Systems

Summary Medication reconciliation was developed to reduce medical mistakes and injuries through a process of creating and comparing a current medication list from independent patient information sources, and resolving discrepancies. The structure and clinician assignments of medication reconciliation varies between institutions, but usually includes physicians, nurses and pharmacists. The Joint Commission has recognized the value of medication reconciliation and mandated implementation in 2006; however, a variety of issues have prevented simple, easy, and universal implementation. This review references issues related to the development and the implementation of medication reconciliation including: – the need of a system or standard for accurate drug identification to create a definitive ‘gold standard’ patient medication list, – identifying stakeholders of medication reconciliation within the institution and contrasting staff interest and participation with institutional resources, – observations and opportunities of integrating medication reconciliation with the electronic patient health record, and – summarizing a series of institutions experiences developing and implementing medication reconciliation. Last, as medication reconciliation becomes a regular process within medical centers, key concepts for effective implementation are discussed.
Automatic Spatially-Aware Fashion Concept Discovery

This paper proposes an automatic spatially-aware concept discovery approach using weakly labeled image-text data from shopping websites. We first fine-tune GoogleNet by jointly modeling clothing images and their corresponding descriptions in a visual-semantic embedding space. Then, for each attribute (word), we generate its spatiallyaware representation by combining its semantic word vector representation with its spatial representation derived from the convolutional maps of the fine-tuned network. The resulting spatially-aware representations are further used to cluster attributes into multiple groups to form spatiallyaware concepts (e.g., the neckline concept might consist of attributes like v-neck, round-neck, etc). Finally, we decompose the visual-semantic embedding space into multiple concept-specific subspaces, which facilitates structured browsing and attribute-feedback product retrieval by exploiting multimodal linguistic regularities. We conducted extensive experiments on our newly collected Fashion200K dataset, and results on clustering quality evaluation and attribute-feedback product retrieval task demonstrate the effectiveness of our automatically discovered spatially-aware concepts.
The Potential of NanoCellulose in the Packaging Field: A Review

Nanocellulose has potential applications across several industrial sectors and allows the development of innovative materials, as well as the enhancement of conventional materials properties. The nanocellulose particles can be utilized as fillers, in composites manufacture, as coating and as self‐standing thin films, achieving always very interesting and promising properties. Very few of the several reviews that recently appeared on this topic in the scientific literature, however, summarized the potential of cellulose in nanoform specifically for the packaging field rather focusing on different aspects, ranging from the chemistry and the morphology of nanocellulose particles to the preparation methods, the industrial applications and the patents released. In the present review, the remarkable chemical and physical properties of nanocellulose are introduced and discussed with specific reference to the packaging needs. First, the cellulose resources and structure are introduced, then the process methods to reach the nanoscale, the corresponding morphologies and nomenclatures are summarized, mentioning also the possible chemical modifications of nanocellulose and, finally, its practical and potential applications for packaging materials, especially food packaging materials, are tentatively proposed and discussed. Although the review might not cover every aspect on nanocellulose, yet the key points, particularly those related to safety and biodegradability issues, are regarded and considered. Copyright © 2015 John Wiley & Sons, Ltd.
Instruction-level test methodology for CPU core self-testing

TIS is an instruction-level methodology for processor core self-testing that enhances instruction set of a CPU with test instructions. Since the functionality of test instructions is the same as the NOP instruction, NOP instructions can be replaced with test instructions. Online testing can be accomplished without any performance penalty. TIS tests different parts of the processor and detects stuck-at faults. This method can be employed in offline and online testing of single-cycle, multicycle and pipelined processors. But, TIS is more appropriate for online testing of pipelined architectures in which NOP instructions are frequently executed because of data, control and structural hazards. Running test instructions instead of these NOP instructions, TIS utilizes the time that is otherwise wasted by NOPs. In this article, two different implementations of TIS are presented. One implementation employs a dedicated hardware modules for test vector generation, while the other is a software-based approach that reads test vectors from memory. These two approaches are implemented on a pipelined processor core and their area overheads are compared. To demonstrate the appropriateness of the TIS test technique, several programs are executed and fault coverage results are presented.
Intrinsic Epigenetic Regulation of the D4Z4 Macrosatellite Repeat in a Transgenic Mouse Model for FSHD

Facioscapulohumeral dystrophy (FSHD) is a progressive muscular dystrophy caused by decreased epigenetic repression of the D4Z4 macrosatellite repeats and ectopic expression of DUX4, a retrogene encoding a germline transcription factor encoded in each repeat. Unaffected individuals generally have more than 10 repeats arrayed in the subtelomeric region of chromosome 4, whereas the most common form of FSHD (FSHD1) is caused by a contraction of the array to fewer than 10 repeats, associated with decreased epigenetic repression and variegated expression of DUX4 in skeletal muscle. We have generated transgenic mice carrying D4Z4 arrays from an FSHD1 allele and from a control allele. These mice recapitulate important epigenetic and DUX4 expression attributes seen in patients and controls, respectively, including high DUX4 expression levels in the germline, (incomplete) epigenetic repression in somatic tissue, and FSHD–specific variegated DUX4 expression in sporadic muscle nuclei associated with D4Z4 chromatin relaxation. In addition we show that DUX4 is able to activate similar functional gene groups in mouse muscle cells as it does in human muscle cells. These transgenic mice therefore represent a valuable animal model for FSHD and will be a useful resource to study the molecular mechanisms underlying FSHD and to test new therapeutic intervention strategies.
Effect of natural products on diabetes associated neurological disorders

Abstract Diabetes mellitus, a metabolic disorder, is associated with neurological complications such as depression, anxiety, hypolocomotion, cognitive dysfunction, phobias, anorexia, stroke, pain, etc. Traditional system of medicine is long known for its efficient management of diabetes. The current review discusses the scope of some common medicinal herbs as well as secondary metabolites with a special focus on diabetes-mediated central nervous system complications. Literatures suggest that natural products reduce diabetes-mediated neurological complications partly by reducing oxidative stress and/or inflammation or apoptosis in certain brain regions. Natural products are known to modulate diabetes-mediated alterations in the level of acetylcholinesterase, choline acetyltransferase, monoamine oxidase, serotonin receptors, muscarinic receptors, insulin receptor, nerve growth factor, brain-derived neurotrophic factor, and neuropeptide in brain. Further, there are several natural products reported to manage diabetic complications with unknown mechanism. In conclusion, medicinal plants or their secondary metabolites have a wide scope and possess therapeutic potential to effectively manage neurological complications associated with chronic diabetes.
Network Analyses in Plant Pathogens

Even in the age of big data in Biology, studying the connections between the biological processes and the molecular mechanisms behind them is a challenging task. Systems biology arose as a transversal discipline between biology, chemistry, computer science, mathematics, and physics to facilitate the elucidation of such connections. A scenario, where the application of systems biology constitutes a very powerful tool, is the study of interactions between hosts and pathogens using network approaches. Interactions between pathogenic bacteria and their hosts, both in agricultural and human health contexts are of great interest to researchers worldwide. Large amounts of data have been generated in the last few years within this area of research. However, studies have been relatively limited to simple interactions. This has left great amounts of data that remain to be utilized. Here, we review the main techniques in network analysis and their complementary experimental assays used to investigate bacterial-plant interactions. Other host-pathogen interactions are presented in those cases where few or no examples of plant pathogens exist. Furthermore, we present key results that have been obtained with these techniques and how these can help in the design of new strategies to control bacterial pathogens. The review comprises metabolic simulation, protein-protein interactions, regulatory control of gene expression, host-pathogen modeling, and genome evolution in bacteria. The aim of this review is to offer scientists working on plant-pathogen interactions basic concepts around network biology, as well as an array of techniques that will be useful for a better and more complete interpretation of their data.
Linear Equations with Ordered Data

Following a recently considered generalization of linear equations to unordered data vectors, we perform a further generalization to ordered data vectors. These generalized equations naturally appear in the analysis of vector addition systems (or Petri nets) extended with ordered data. We show that nonnegative-integer solvability of linear equations is computationally equivalent (up to an exponential blowup) with the reachability problem for (plain) vector addition systems. This high complexity is surprising, and contrasts with NP-completeness for unordered data vectors. Also surprisingly, we achieve polynomial time complexity of the solvability problem when the nonnegative-integer restriction on solutions is dropped.