Miracle-dz/UniFAR-FTUs huggingface dataset:
Initialization of Iterative Refinement Clustering Algorithms

Iterative refinement clustering algorithms (e.g. K-Means, EM) converge to one of numerous local minima. It is known that they are especially sensitive to initial conditions. We present a procedure for computing a refined starting condition from a given initial one that is based on an efficient technique for estimating the modes of a distribution. The refined initial starting condition leads to convergence to "better" local minima. The procedure is applicable to a wide class of clustering algorithms for both discrete and continuous data. We demonstrate the application of this method to the Expectation Maximization (EM) clustering algorithm and show that refined initial points indeed lead to improved solutions. Refinement run time is considerably lower than the time required to cluster the full database. The method is scalable and can be coupled with a scalable clustering algorithm to address the large-scale clustering in data mining.
Monitoring the effects of doxorubicin on 3D-spheroid tumor cells in real-time

Recently, increasing numbers of cell culture experiments with 3D spheroids presented better correlating results in vivo than traditional 2D cell culture systems. 3D spheroids could offer a simple and highly reproducible model that would exhibit many characteristics of natural tissue, such as the production of extracellular matrix. In this paper numerous cell lines were screened and selected depending on their ability to form and maintain a spherical shape. The effects of increasing concentrations of doxorubicin (DXR) on the integrity and viability of the selected spheroids were then measured at regular intervals and in real-time. In total 12 cell lines, adenocarcinomic alveolar basal epithelial (A549), muscle (C2C12), prostate (DU145), testis (F9), pituitary epithelial-like (GH3), cervical cancer (HeLa), HeLa contaminant (HEp2), embryo (NIH3T3), embryo (PA317), neuroblastoma (SH-SY5Y), osteosarcoma U2OS, and embryonic kidney cells (293T), were screened. Out of the 12, 8 cell lines, NIH3T3, C2C12, 293T, SH-SY5Y, A549, HeLa, PA317, and U2OS formed regular spheroids and the effects of DXR on these structures were measured at regular intervals. Finally, 5 cell lines, A549, HeLa, SH-SY5Y, U2OS, and 293T, were selected for real-time monitoring and the effects of DXR treatment on their behavior were continuously recorded for 5 days. A potential correlation regarding the effects of DXR on spheroid viability and ATP production was measured on days 1, 3, and 5. Cytotoxicity of DXR seemed to occur after endocytosis, since the cellular activities and ATP productions were still viable after 1 day of the treatment in all spheroids, except SH-SY5Y. Both cellular activity and ATP production were halted 3 and 5 days from the start of the treatment in all spheroids. All cell lines maintained their spheroid shape, except SHSY-5, which behaved in an unpredictable manner when exposed to toxic concentrations of DXR. Cytotoxic effects of DXR towards SH-SY5Y seemed to cause degradation of the extracellular matrix, since all cells were dismantled from the spheroid upon cell death. On the other hand, 293T spheroids revealed retarded cellular activity and ATP productions upon DXR treatment throughout the experiment. Since 293T was the embryonic kidney cells, the fast clearance or neutralizations could have made them resistant towards DXR. In conclusion, the same degree of sensitivity from the 2D system did not translate to a 3D culture system, resulting in higher IC50 values than the 2D system. The varying sensitivities and tolerances to drugs could be better understood with a 3D cell culture system.
Malignant glaucoma.

My interest in malignant glaucoma stems from my practice in association with Dr. Paul A. Chandler and our work in cooperation with Dr. W. Morton Grant, and I am speaking not as an individual but as a member of a team of three. A review of our files revealed 66 patients with some form of malignant glaucoma in one br both eyes. Of these 66 patients, 32 had typical full-blown phakic malignant glaucoma, and the remaining 34 included aphakic cases, some with a milder and more transient form of the disease, as well as some with complex ocular pathology in which malignant glaucoma was included as one of several diagnoses.
A Symmetry-Based Method to Infer Structural Brain Networks from Probabilistic Tractography Data

Recent progress in diffusion MRI and tractography algorithms as well as the launch of the Human Connectome Project (HCP)1 have provided brain research with an abundance of structural connectivity data. In this work, we describe and evaluate a method that can infer the structural brain network that interconnects a given set of Regions of Interest (ROIs) from probabilistic tractography data. The proposed method, referred to as Minimum Asymmetry Network Inference Algorithm (MANIA), does not determine the connectivity between two ROIs based on an arbitrary connectivity threshold. Instead, we exploit a basic limitation of the tractography process: the observed streamlines from a source to a target do not provide any information about the polarity of the underlying white matter, and so if there are some fibers connecting two voxels (or two ROIs) X and Y, tractography should be able in principle to follow this connection in both directions, from X to Y and from Y to X. We leverage this limitation to formulate the network inference process as an optimization problem that minimizes the (appropriately normalized) asymmetry of the observed network. We evaluate the proposed method using both the FiberCup dataset and based on a noise model that randomly corrupts the observed connectivity of synthetic networks. As a case-study, we apply MANIA on diffusion MRI data from 28 healthy subjects to infer the structural network between 18 corticolimbic ROIs that are associated with various neuropsychiatric conditions including depression, anxiety and addiction.
A Low Patch-Rank Interpretation of Texture

We propose a novel cartoon-texture separation model using a sparse low-rank decomposition. Our texture model connects the separate ideas of robust principal component analysis (PCA) [E. J. Candes, X. Li, Y. Ma, and J. Wright, J. ACM, 58 (2011), 11], nonlocal methods [A. Buades, B. Coll, and J.-M. Morel, Multiscale Model. Simul. , 4 (2005), pp. 490--530], [A. Buades, B. Coll, and J.-M. Morel, Numer. Math., 105 (2006), pp. 1--34], [G. Gilboa and S. Osher, Multiscale Model. Simul. , 6 (2007), pp. 595--630], [G. Gilboa and S. Osher, Multiscale Model. Simul. , 7 (2008), pp. 1005--1028], and cartoon-texture decompositions in an interesting way, taking advantage of each of these methodologies. We define our texture norm using the nuclear norm applied to patches in the image, interpreting the texture patches to be low-rank. In particular, this norm is easier to implement than many of the weak function space norms in the literature and is computationally faster than nonlocal methods since there is no explicit weight .
Microbial Diversity in a Hydrocarbon- and Chlorinated-Solvent-Contaminated Aquifer Undergoing Intrinsic Bioremediation

ABSTRACT A culture-independent molecular phylogenetic approach was used to survey constituents of microbial communities associated with an aquifer contaminated with hydrocarbons (mainly jet fuel) and chlorinated solvents undergoing intrinsic bioremediation. Samples were obtained from three redox zones: methanogenic, methanogenic-sulfate reducing, and iron or sulfate reducing. Small-subunit rRNA genes were amplified directly from aquifer material DNA by PCR with universally conserved or Bacteria- orArchaea-specific primers and were cloned. A total of 812 clones were screened by restriction fragment length polymorphisms (RFLP), approximately 50% of which were unique. All RFLP types that occurred more than once in the libraries, as well as many of the unique types, were sequenced. A total of 104 (94 bacterial and 10 archaeal) sequence types were determined. Of the 94 bacterial sequence types, 10 have no phylogenetic association with known taxonomic divisions and are phylogenetically grouped in six novel division level groups (candidate divisions WS1 to WS6); 21 belong to four recently described candidate divisions with no cultivated representatives (OP5, OP8, OP10, and OP11); and 63 are phylogenetically associated with 10 well-recognized divisions. The physiology of two particularly abundant sequence types obtained from the methanogenic zone could be inferred from their phylogenetic association with groups of microorganisms with a consistent phenotype. One of these sequence types is associated with the genus Syntrophus; Syntrophus spp. produce energy from the anaerobic oxidation of organic acids, with the production of acetate and hydrogen. The organism represented by the other sequence type is closely related to Methanosaetaspp. , which are known to be capable of energy generation only through aceticlastic methanogenesis. We hypothesize, therefore, that the terminal step of hydrocarbon degradation in the methanogenic zone of the aquifer is aceticlastic methanogenesis and that the microorganisms represented by these two sequence types occur in syntrophic association.
Computer-aided tumor detection in endoscopic video using color wavelet features

We present an approach to the detection of tumors in colonoscopic video. It is based on a new color feature extraction scheme to represent the different regions in the frame sequence. This scheme is built on the wavelet decomposition. The features named as color wavelet covariance (CWC) are based on the covariances of second-order textural measures and an optimum subset of them is proposed after the application of a selection algorithm. The proposed approach is supported by a linear discriminant analysis (LDA) procedure for the characterization of the image regions along the video frames. The whole methodology has been applied on real data sets of color colonoscopic videos. The performance in the detection of abnormal colonic regions corresponding to adenomatous polyps has been estimated high, reaching 97% specificity and 90% sensitivity.
The Effects of Neuregulin on Cardiac Myosin Light Chain Kinase Gene-Ablated Hearts

Background Activation of ErbB2/4 receptor tyrosine kinases in cardiomyocytes by neuregulin treatment is associated with improvement in cardiac function, supporting its use in human patients with heart failure despite the lack of a specific mechanism. Neuregulin infusion in rodents increases cardiac myosin light chain kinase (cMLCK) expression and cardiac myosin regulatory light chain (RLC) phosphorylation which may improve actin-myosin interactions for contraction. We generated a cMLCK knockout mouse to test the hypothesis that cMLCK is necessary for neuregulin-induced improvement in cardiac function by increasing RLC phosphorylation. Principal Findings The cMLCK knockout mice have attenuated RLC phosphorylation and decreased cardiac performance measured as fractional shortening. Neuregulin infusion for seven days in wildtype mice increased cardiac cMLCK protein expression and RLC phosphorylation while increasing Akt phosphorylation and decreasing phospholamban phosphorylation. There was no change in fractional shortening. In contrast, neuregulin infusion in cMLCK knockout animals increased cardiac performance in the absence of cMLCK without increasing RLC phosphorylation. In addition, CaMKII signaling appeared to be enhanced in neuregulin-treated knockout mice. Conclusions Thus, Neuregulin may improve cardiac performance in the failing heart without increasing cMLCK and RLC phosphorylation by activating other signaling pathways.
Joint estimation of DOA and speech based on EM beamforming

In this paper, we propose a multi-microphone joint optimal estimation of the direction of arrival (DOA) and the source speech signal through newly introduced EM beamforming. This produces a posterior PDF for the DOA, based only on the reliable speech spectrum. By maximizing over the posterior PDF of the DOA, we achieve maximum a posteriori DOA estimation. After convergence, the estimated source spectrum through weighted sum in the Bayesian sense is a maximum likelihood estimate (MLE). This is a sufficient statistic for minimum mean square error (MMSE) optimal estimation using a subsequent single channel MMSE filter.
Quality of life after pulmonary embolism: validation of the PEmb‐QoL Questionnaire

Summary. Background: Even though quality of life (QoL) has become a key component of medical care, there is no instrument available that specifically measures QoL after pulmonary embolism (PE). Recently, the Pulmonary Embolism Quality of Life (PEmb‐QoL) Questionnaire has been developed to address this gap. Objective: To evaluate the validity of the PEmb‐QoL questionnaire. Methods: We distributed the PEmb‐QoL questionnaire and the Short Form‐36 (SF‐36) questionnaire twice among consecutive subjects with a history of objectively confirmed acute PE. Internal consistency reliability, test‐retest reliability, convergent validity and criterion validity, and correlations between the PEmb‐QoL and clinical patient characteristics were assessed using standard‐scale construction techniques. Results: Ninety participants completed the questionnaires twice. Internal consistency was adequate (Cronbach’s α 0.62–0.94), as well as test‐retest reliability (intra‐class correlation coefficients: 0.78–0.94). Furthermore, correlation between the PEmb‐QoL questionnaire and the SF‐36 questionnaire supported convergent validity. Age, obesity, cardiopulmonary comorbidity, centrally located PE and a family history of venous thromboembolism were shown to be independent determinants of disease‐specific QoL. Conclusion: The PEmb‐QoL questionnaire is a reliable instrument to specifically assess QoL following PE, which is helpful in the identification of patients with decreased QoL following acute PE.
Rapid and simple assay for the determination of tripeptidyl peptidase and palmitoyl protein thioesterase activities in dried blood spots.

Neuronal ceroid lipofuscinoses constitute a group of at least eight inherited, progressive encephalopathies that are characterized by lipofuscin-like inclusions in various tissues and that have recently been classified as CLN1 to CLN8 according to their genetic defects (1). A form with mostly infantile manifestation (CLN1) and the classical late infantile form (CLN2) are caused by deficiencies of the lysosomal enzymes palmitoyl protein thioesterase 1 (PPT1) and tripeptidyl peptidase 1 (TPP1), respectively. The basic defects underlying the other forms are still ill-defined or unknown. To date, more than 30 mutations have been reported in the PPT1 and TPP1 genes, rendering molecular genetic analysis impractical as a primary means of diagnosis. Electron microscopy of characteristic cellular inclusions remains an important diagnostic method, but it is also tedious and not readily available. Enzymatic assays based on fluorescent substrates have recently been reported for PPT1 (2) and TPP1(3). These assays can also be used with isolated leukocytes. However, because few laboratories are experienced in diagnosing these rare disorders, blood samples must be sent to specialized centers by expensive express mail services to avoid loss of enzymatic activity. In our experience, samples for this kind of study frequently arrive in poor condition. As an alternative to the use of leukocytes, methods for determining several lysosomal enzymes from dried blood spots (DBS) have recently been described (4). DBS are also used routinely for enzyme measurements within newborn-screening programs for the detection of biotinidase and galactose-uridyltransferase deficiencies in neonates. DBS require only minute amounts of blood, are easy to …
A Scientometric Study on Graphene and Related Graphene- Based Materials in Medicine

Here we carried out a scientometric analysis of scientific literature published referred to the use of graphene and graphene-based materials. We found that in the last 15 years, more than 1200 issues have been produced, with an H -index of 67 cited 2647 times. The countries that have a larger production, in terms of number of issues published, are China, the United States, South Korea, India, and Iran, and the most relevant subject categories in which they are indexed are materials science, chemistry, science and tech- nology, physics, and engineering, while the biological and medical specialties seem to be actually not deeply involved.
Interference management in OFDMA femtocell networks: issues and approaches

One of the effective techniques of improving the coverage and enhancing the capacity and data rate in cellular wireless networks is to reduce the cell size (i.e., cell splitting) and transmission distances. Therefore, the concept of deploying femtocells over macrocell has recently attracted growing interests in academia, industry, and standardization forums. Various technical challenges towards mass deployment of femtocells have been addressed in recent literature. Interference mitigation between neighboring femtocells and between the femtocell and macrocell is considered to be one of the major challenges in femtocell networks because femtocells share the same licensed frequency spectrum with macrocell. Further, the conventional radio resource management techniques for hierarchical cellular system is not suitable for femtocell networks since the positions of the femtocells are random depending on the users' service requirement. In this article, we provide a survey of the different state-of-the-art approaches for interference and resource management in orthogonal frequency-division multiple access (OFDMA)-based femtocell networks. A qualitative comparison among the different approaches is provided. To this end, open challenges in designing interference management schemes for OFDMA femtocell networks are discussed.
LDPC code design for binary-input binary-output Z interference channels

In this paper, we explore code optimization for two-user discrete memoryless interference channels (DMICs) wherein the inputs and outputs of the channel are from a finite alphabet. For encoding, we employ irregular low-density parity-check (LDPC) codes combined with non-linear trellis codes (NLTCs) to satisfy the desired distribution of zeros and ones in the transmitted codewords. At the receiver sides, we adopt BCJR algorithm based decoders to compute the symbol-by-symbol log-likelihood ratios (LLRs) of LDPC coded bits to be fed to message passing decoders. As a specific example, we consider the binary-input binary-output Z interference channel (BIBO ZIC) for which the transmitted and received signals are binary and one of the receivers is interference free. For a specific example of a BIBO ZIC, we examine the Han-Kobayashi inner bound on the achievable rate pairs and show that with a simple scheme of sending the messages as private one can achieve the sum-capacity of the channel. We also perform code optimization and demonstrate that the jointly optimized codes outperform the optimal single user codes with time sharing.
N′-(3-Chlorobenzylidene)-4-hydroxybenzohydrazide

The molecule of the title compound, C14H11ClN2O2 adopts an E conformation of the azomethine double bond and the dihedral angle between the benzene rings is 38.96 (13)°. In the crystal, molecules are linked by N—H⋯O and O—H⋯O (with the ketone O atom as acceptor) and C—H⋯O (with the hydroxy O atom as acceptor) hydrogen bonds, forming a three-dimensional network.
Impact of Computational Theory of Language Understanding for Development of Neural Network Model 牧野 貴樹 MAKINO Takaki † ‡ ( PY ) 合原 一幸 AIHARA Kazuyuki

This paper shows how the computational theory of language understanding can affect the design of language-understanding neural networks. We propose some basic properties of a computational theory of language understanding, and we show that the generalizability requirement in the property forces us to face with the feature binding problem. Based on the advantage of the temporal-coding, we discuss the necessity of global phase control for language understanding. We also show simulation results with a simple neural network model for sentence understanding on the bases of the theory.
Dynamic Modeling and Control for SPMSMs With Internal Turn Short Fault

A dynamic model for a faulted surface-mount permanent magnet synchronous motor (SPMSM) is derived using a deformed flux model. In reflecting the internal turn short into the dynamics, the variations in inductance and back EMF term were considered. Then, the faulted model was transformed into the two synchronous dq-models: one for the positive sequence and the other for the negative sequence. Also, a torque equation, which shows the relation between the ripple and the negative sequence current, is derived. The negative sequence current should be suppressed to eliminate the torque ripple. The dual current controller is utilized for this purpose: in the dual controller, the positive and negative sequences are controlled separately in their own synchronous frames. Notch filters are utilized in each synchronous frame to extract positive or negative sequence component. Experiments were performed with an SPMSM specially designed to make an internal turn short artificially. The experimental results coincide well with the corresponding simulation results, and exhibit a strength of the dual current controller in suppressing the negative sequence current.
Distributed Model Predictive Control of timed continuous Petri nets

In this paper we focus on distributed control of timed continuous Petri nets (TCPN). We assume that subsystems are connected by places modeling buffers. The problem we handle here is to drive all the subsystems to their desired final states, which is similar to the classical set-point control problem in general continuous-state systems. We first propose a centralized MPC controller, in which asymptotic stability is guaranteed by means of adding constraints to force the state trajectory to be inside an interior convex subset of the reachability space. Then, we apply this controller to a distributed setting, and for this aim we use a particular strategy to maintain the positiveness of the markings of buffer places. We prove that, by using the proposed algorithm, the desired final states of all subsystems can be reached in finite time (even if at different time instants). In our method, no high level coordinator is needed and only limited communication occurs among neighboring subsystems.
An Assertions-Based Approach to Verifying the Absence Property Pattern

Temporal properties are very common in various classes of systems, including information systems and security policies. This paper investigates two verification methods, proof and model checking, for one of the most frequent patterns of temporal property, the absence pattern. We explore two model-based specification techniques, B and Alloy, because of their adequacy for easily specifying systems with complex data structures, like information systems. We propose a first-order, assertion-based, sound and complete strategy to verify the absence pattern. This enables the proof of the absence pattern using conventional first-order provers. We show that the use of assertions significantly increases the size of the models that can be checked, when compared to traditional LTL model checking techniques. The approach is illustrated throughout a case study.