Miracle-dz/UniFAR-FTUs huggingface dataset:
Sweeper's Algorithm and its Application on Image Clustering

Using Two Dimensional Hybrid Cellular Automata (2-D HCA) rules image shifting, image copying, zooming in and out, thickening and thinning of an image etc. were possible and reported in [8]. A new searching algorithm called Sweeper’s algorithm was proposed on binary images using 2D HCA and was the basis for solving various problems like migration of initially distributed organisms in a space towards a single point destination, density classification problem of CA etc. [9]. Due to the wide scope of Sweeper’s algorithm it was mentioned in [8] that the problem areas that can be solved by this algorithm are text and image compression, informed search in Artificial Intelligence, clustering problem, Cryptography, and pattern classification etc. Here in this paper we have taken up the challenge and tried to solve the clustering problem using Sweeper’s algorithm. Basically our study is based on various color images consisting of the combinations of Red, Green, and Blue (RGB) colors as well as selecting different destination points in the search space. First we have taken red color and one of the two color from blue or green as cluster points and took it as input and by applying Sweeper’s algorithm we found two cluster regions one with red color and other with blue or green color. Subsequently we took all the three (RGB) color as input and by applying the algorithm we found three clusters. We took one color between red, blue, green and some other color like magenta, cyan, yellow etc. as input and found different clusters. We have also studied the intersection region of different colors using this algorithm and found interesting color patterns.
Current status of percutaneous ventricular assist devices for cardiogenic shock

Purpose of review Percutaneous ventricular assist devices (pVADs) are being increasingly used in patients with cardiogenic shock. They offer a means of instituting rapid and adequate cardiac support in patients with cardiogenic shock unresponsive to inotropes/vasopressors and intraaortic balloon pumps (IABPs). However, there is considerable debate on the appropriate use of these devices given the difficulty of conducting randomized trials in patients with cardiogenic shock, lack of clear guidelines on indications, device selection, and cost-effective care of patients implanted with these devices. Recent findings Several centers have recently reported data on the use of these devices for cardiogenic shock in a variety of different settings, including myocardial ischemia and its complications, high-risk percutaneous coronary intervention, myocarditis, and refractory arrhythmias. Recent randomized trials have compared the use of IABP with different pVADs evaluating hemodynamic outcomes as well as short-term mortality. Summary We review the current evidence on the use of pVADs (Tandemheart pVAD, Impella, percutaneous extracorporeal membrane oxygenation), their indications, relative merits, and adverse effects, and discuss the current approach to the appropriate use of pVADs in patients with cardiogenic shock. We also propose an algorithm for device selection tailored to each patient's needs based on severity of cardiogenic shock, amount of support needed, and the overall clinical scenario.
Security in Cognitive Radio Networks

While bringing the potential for solving the spectrum underutilization problem using methods such as dynamic and opportunistic spectrum access, Cognitive Radios (CRs) also bring a set of security issues and potential breaches that have to be addressed. These issues come out mainly from the two important capabilities implemented within CRs: their cognition ability and reconfigurability. This chapter will focus on identifying, presenting and classifying the main potential security attacks and vulnerabilities, as well as proposing appropriate counter-measures and solutions for them. These will be supplemented by simulation results and metrics, with the intention of estimating the efficiency of each of the observed attacks and its counter-measure. The presented simulations are performed in the proprietary C/C++ and Matlab/Simulink simulators. nSHIELD is a major ongoing European embedded systems security-related project, which will be used to demonstrate the practicability of the potential implementation of the proposed countermeasures and solutions for the discussed security problems and issues. Security in Cognitive Radio Networks
Adaptive Approach for DSR and OLSR Routing Protocols using Optimal Probabilistic Logical Key Hierarchy in MANET

wireless network with Ad hoc nature consists of mobile nodes which facilitates a fundamental architecture for communication without the support of traditional steady and fixed-positioned routers. However, the architecture must preserve communicating routes and the hosts have mobile nature and they have their restricted transmission range. There are various protocols for controlling the routing in the mobility environment. In MANET, the mobile nodes can perform the roles of both hosts and routers. Various MANET applications use for Military strategic communications and Disaster recovery mostly depended on secure node communication. For Secure Communication we use several Logical Hierarchy key protocol in Mobile Ad-hoc Network. But group key administration looks many problems because of unreliable media, less energy resources, mobile node failure. In this paper we analysis new logical key with Optimal Probabilistic Technique. In this key all node shaped in tree structure. OPLKH decreases the rekey cost and routing energy consumption in Mobile ad hoc network. In simulation we calculated the no. of rekeys cost, total energy consumption at server, key generation of energy consumption.
Coordination of Myeloid Differentiation with Reduced Cell Cycle Progression by PU.1 Induction of MicroRNAs Targeting Cell Cycle Regulators and Lipid Anabolism

ABSTRACT During macrophage development, myeloid progenitor cells undergo terminal differentiation coordinated with reduced cell cycle progression. Differentiation of macrophages from myeloid progenitors is accompanied by increased expression of the E26 transformation-specific transcription factor PU.1. Reduced PU.1 expression leads to increased proliferation and impaired differentiation of myeloid progenitor cells. It is not understood how PU.1 coordinates macrophage differentiation with reduced cell cycle progression. In this study, we utilized cultured PU.1-inducible myeloid cells to perform genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) analysis coupled with gene expression analysis to determine targets of PU.1 that may be involved in regulating cell cycle progression. We found that genes encoding cell cycle regulators and enzymes involved in lipid anabolism were directly and inducibly bound by PU.1 although their steady-state mRNA transcript levels were reduced. Inhibition of lipid anabolism was sufficient to reduce cell cycle progression in these cells. Induction of PU.1 reduced expression of E2f1, an important activator of genes involved in cell cycle and lipid anabolism, indirectly through microRNA 223. Next-generation sequencing identified microRNAs validated as targeting cell cycle and lipid anabolism for downregulation. These results suggest that PU.1 coordinates cell cycle progression with differentiation through induction of microRNAs targeting cell cycle regulators and lipid anabolism.
A moth brain learns to read MNIST

We seek to characterize the learning tools (ie algorithmic components) used in biological neural networks, in order to port them to the machine learning context. In particular we address the regime of very few training samples. The Moth Olfactory Network is among the simplest biological neural systems that can learn. We assigned a computational model of the Moth Olfactory Network the task of classifying the MNIST digits. The moth brain successfully learned to read given very few training samples (1 to 20 samples per class). In this few-samples regime the moth brain substantially outperformed standard ML methods such as Nearest-neighbors, SVM, and CNN. Our experiments elucidate biological mechanisms for fast learning that rely on cascaded networks, competitive inhibition, sparsity, and Hebbian plasticity. These biological algorithmic components represent a novel, alternative toolkit for building neural nets that may offer a valuable complement to standard neural nets.
Total Body Irradiation in the “Hematopoietic” Dose Range Induces Substantial Intestinal Injury in Non-Human Primates

The non-human primate has been a useful model for studies of human acute radiation syndrome (ARS). However, to date structural changes in various parts of the intestine after total body irradiation (TBI) have not been systematically studied in this model. Here we report on our current study of TBI-induced intestinal structural injury in the non-human primate after doses typically associated with hematopoietic ARS. Twenty-four non-human primates were divided into three groups: sham-irradiated control group; and total body cobalt-60 (60Co) 6.7 Gy gamma-irradiated group; and total body 60Co 7.4 Gy gamma-irradiated group. After animals were euthanized at day 4, 7 and 12 postirradiation, sections of small intestine (duodenum, proximal jejunum, distal jejunum and ileum) were collected and fixed in 10% formalin. The intestinal mucosal surface length, villus height and crypt depths were assessed by computer-assisted image analysis. Plasma citrulline levels were determined using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Total bone marrow cells were counted and hematopoietic stem/progenitor cells in bone marrow were analyzed by flow cytometer. Histopathologically, all segments exhibited conspicuous disappearance of plicae circulares and prominent atrophy of crypts and villi. Intestinal mucosal surface length was significantly decreased in all intestinal segments on day 4, 7 and 12 after irradiation (P < 0.02–P < 0.001). Villus height was significantly reduced in all segments on day 4 and 7 (P = 0.02–0.005), whereas it had recovered by day 12 (P > 0.05). Crypt depth was also significantly reduced in all segments on day 4, 7 and 12 after irradiation (P < 0.04–P < 0.001). Plasma citrulline levels were dramatically reduced after irradiation, consistent with intestinal mucosal injury. Both 6.7 and 7.4 Gy TBI reduced total number of bone marrow cells. And further analysis showed that the number and function of CD45+CD34+ hematopoietic stem/progenitors in bone marrow decreased significantly. In summary, TBI in the hematopoietic ARS dose range induces substantial intestinal injury in all segments of the small bowel. These findings underscore the importance of maintaining the mucosal barrier that separates the gut microbiome from the body's interior after TBI.
An Ecohistory of Health: The Role of ‘Healthy Cities’

Throughout history, there has been a continuous and ongoing conflict over the ways to perceive reality. It has been said that the Industrial Revolution proved the superiority of the linear, objective, rational, and reductionist models over the holistic, systems view. Its great success, it is claimed, comes from finding the simple causative agent of the problem, removing it, and permitting individuals and society to go on with life. Thus all models of education and medical treatment in the post-Tnodern era are linear. The results in medicine and health are well known. This has enabled us, or so it is claimed, to lengthen life spans, reduce suffering, diminish illness, and improve the well-being of people and the quality of their lives. I write this with tongue in cheek, knowing, as Thomas McKeown ~ and others have pointed out, that these so-called improvements have come not only because of the scientific achievements of medicine but also from changes in the standard of living. An alternate view, expressed in modern terminology, deals with co~nplexity, inquiring systems, and even chaos. There are many aspects of life processes that we do not understand and thus have little ability to control. We are forced to look at organized complexity in a different manner. In my case, quite reverentially and with awe. How can such simple things as movement, perception, and reality be so complex?
Identification of Surface Protein Biomarkers of Listeria monocytogenes via Bioinformatics and Antibody-Based Protein Detection Tools

ABSTRACT The Gram-positive bacterium Listeria monocytogenes causes a significant percentage of the fatalities among foodborne illnesses in humans. Surface proteins specifically expressed in a wide range of L. monocytogenes serotypes under selective enrichment culture conditions could serve as potential biomarkers for detection and isolation of this pathogen via antibody-based methods. Our study aimed to identify such biomarkers. Interrogation of the L. monocytogenes serotype 4b strain F2365 genome identified 130 putative or known surface proteins. The homologues of four surface proteins, LMOf2365_0578, LMOf2365_0581, LMOf2365_0639, and LMOf2365_2117, were assessed as biomarkers due to the presence of conserved regions among strains of L. monocytogenes which are variable among other Listeria species. Rabbit polyclonal antibodies against the four recombinant proteins revealed the expression of only LMOf2365_0639 on the surface of serotype 4b strain LI0521 cells despite PCR detection of mRNA transcripts for all four proteins in the organism. Three of 35 monoclonal antibodies (MAbs) to LMOf2365_0639, MAbs M3643, M3644, and M3651, specifically recognized 42 (91.3%) of 46 L. monocytogenes lineage I and II isolates grown in nonselective brain heart infusion medium. While M3644 and M3651 reacted with 14 to 15 (82.4 to 88.2%) of 17 L. monocytogenes lineage I and II isolates, M3643 reacted with 22 (91.7%) of 24 lineage I, II, and III isolates grown in selective enrichment media (UVM1, modified Fraser, Palcam, and UVM2 media). The three MAbs exhibited only weak reactivities (the optical densities at 414 nm were close to the cutoff value) to some other Listeria species grown in selective enrichment media. Collectively, the data indicate the potential of LMOf2365_0639 as a surface biomarker of L. monocytogenes, with the aid of specific MAbs, for pathogen detection, identification, and isolation in clinical, environmental, and food samples. IMPORTANCE L. monocytogenes is traditionally divided into at least 12 serotypes. Currently, there are no monoclonal antibodies (MAbs) available that are capable of binding to the surface of L. monocytogenes strains representing all 12 serotypes. Such antibodies would be useful and are needed for the development of methods to detect and isolate L. monocytogenes from food samples. In our study, we aimed to identify surface proteins that possess regions of well-conserved amino acid sequences among various serotypes and then to employ them as antigen targets (biomarkers) for the development of MAbs. Through bioinformatics and protein expression analysis, we identified one of the four putative surface protein candidates, LMOf2365_0639, encoded by the genome of the L. monocytogenes serotype 4b strain F2365, as a useful surface biomarker. Extensive assessment of 35 MAbs raised against LMOf2365_0639 in our study revealed three MAbs (M3643, M3644, and M3651) that recognized a wide range of L. monocytogenes isolates.
Gene Expression Analysis to Assess the Relevance of Rodent Models to Human Lung Injury

&NA; The relevance of animal models to human diseases is an area of intense scientific debate. The degree to which mouse models of lung injury recapitulate human lung injury has never been assessed. Integrating data from both human and animal expression studies allows for increased statistical power and identification of conserved differential gene expression across organisms and conditions. We sought comprehensive integration of gene expression data in experimental acute lung injury (ALI) in rodents compared with humans. We performed two separate gene expression multicohort analyses to determine differential gene expression in experimental animal and human lung injury. We used correlational and pathway analyses combined with external in vitro gene expression data to identify both potential drivers of underlying inflammation and therapeutic drug candidates. We identified 21 animal lung tissue datasets and three human lung injury bronchoalveolar lavage datasets. We show that the metasignatures of animal and human experimental ALI are significantly correlated despite these widely varying experimental conditions. The gene expression changes among mice and rats across diverse injury models (ozone, ventilator‐induced lung injury, LPS) are significantly correlated with human models of lung injury (Pearson r = 0.33‐0.45, P < 1E−16). Neutrophil signatures are enriched in both animal and human lung injury. Predicted therapeutic targets, peptide ligand signatures, and pathway analyses are also all highly overlapping. Gene expression changes are similar in animal and human experimental ALI, and provide several physiologic and therapeutic insights to the disease.
Investigation of Non-Orthogonal Multiple Access Techniques for Future Cellular Networks

There is an expected explosion in the number of users which will be connected to future wireless networks with the continued expansion of the Internet of Things. New technologies are needed in order to keep up with this connectivity demand. Non-orthogonal multiple access (NOMA) is one technology which seeks to improve spectral efficiency and allow for more connected users. NOMA seeks to overload resources in order to allow more users to access the same time and frequency resource blocks. There have been various proposals on how to realize NOMA in the network, including power domain non-orthogonal multiple access (PD-NOMA), interleave division multiple access(IDMA), and sparse code multiple access (SCMA). This paper investigates these three proposals and simulates them in the uplink setting in order to analyze their performance and compare them. Advantages and disadvantages for each technique are discussed with an emphasis on practical considerations.
Whole exome sequencing to identify genetic markers for trastuzumab‐induced cardiotoxicity

Although trastuzumab‐induced cardiotoxicity is an important determinant to limit the use of this drug, the molecular mechanism of risk for this toxicity is not well understood. To identify genetic variants determining the risk of trastuzumab‐induced cardiotoxicity, we carried out whole exome sequencing of germline DNA samples from 9 patients with trastuzumab‐induced cardiotoxicity, and conducted a case‐control association study of 2258 genetic variants between 9 cases (with trastuzumab‐induced cardiotoxicity) and general Japanese population controls registered in the Human Genetic Variation Database (HGVD). The top variant which showed the lowest P‐value in the screening study was rs139503277 in PHD Finger Protein 3 (Pmin = .00012, odds ratio [OR] = 51.23). To further validate the result of screening study, we carried out a replication study of 10 variants showing Pmin < . 001 in the screening study using 234 independent patients treated with trastuzumab, including 10 cases and 224 controls (without trastuzumab‐induced cardiotoxicity). In the replication study, we observed that three variants had an effect in the same direction as in the screening study (rs78272919 in exon 2 of Keratin 15, rs5762940 in exon 2 of zinc and ring finger 3, and rs139944387 in exon 44 of Eyes shut homologs [EYS]). A combined result of the screening and the replication studies suggested an association of a locus on chromosome 6q12 with trastuzumab‐induced cardiotoxicity (rs139944387 in EYS, combined Pmin = .00056, OR = 13.73). This finding provides new insights into personalized trastuzumab therapy for patients with human epidermal growth factor receptor 2 (HER2)‐positive cancer.
Observations and insights into Pb-assisted stress corrosion cracking of alloy 600 steam generator tubes

Pb-assisted stress-corrosion cracking (PbSCC) of Alloy 600 steam-generator tubing in high-temperature-water service and laboratory tests were studied by analytical transmission electron microscopy of cross-sectioned samples. Examinations of pulled tubes from many pressurized water reactors revealed lead in cracks from 11 of 17 samples. Comparisons of the degraded intergranular structures with ones produced in simple laboratory tests with PbO in near-neutral AVT water showed that the PbSCC characteristics in service tubing could be reproduced without complex chemistries and heat-flow conditions that can occur during plant operation. Observations of intergranular and transgranular cracks promoted by Pb in the test samples also provided new insights into the mechanisms of PbSCC in mill-annealed and thermally treated Alloy 600.
Sparse imputation for noise robust speech recognition using soft masks

In previous work we introduced a new missing data imputation method for ASR, dubbed sparse imputation. We showed that the method is capable of maintaining good recognition accuracies even at very low SNRs provided the number of mask estimation errors is sufficiently low. Especially at low SNRs, however, mask estimation is difficult and errors are unavoidable. In this paper, we try to reduce the impact of mask estimation errors by making soft decisions, i.e., estimating the probability that a feature is reliable. Using an isolated digit recognition task (using the AURORA-2 database), we demonstrate that using soft masks in our sparse imputation approach yields a substantial increase in recognition accuracy, most notably at low SNRs.
Knowledge Transfer from Weakly Labeled Audio Using Convolutional Neural Network for Sound Events and Scenes

In this work we propose approaches to effectively transfer knowledge from weakly labeled web audio data. We first describe a convolutional neural network (CNN) based framework for sound event detection and classification using weakly labeled audio data. Our model trains efficiently from audios of variable lengths; hence, it is well suited for transfer learning. We then propose methods to learn representations using this model which can be effectively used for solving the target task. We study both transductive and inductive transfer learning tasks, showing the effectiveness of our methods for both domain and task adaptation. We show that the learned representations using the proposed CNN model generalizes well enough to reach human level accuracy on ESC-50 sound events dataset and sets state of art results on this dataset. We further use them for acoustic scene classification task and once again show that our proposed approaches suit well for this task as well. We also show that our methods are helpful in capturing semantic meanings and relations as well. Moreover, in this process we also set state-of-art results on Audioset dataset using balanced training set.
Differential evolution with self-adaptive mutation scaling factor

Throughout the past few decades, a variant of differential evolution (DE) algorithms have been introduced with a competitive performance on complex optimization problems. However, the DE superiority is highly dependent on its control parameters and the search operators (i.e., mutation and crossover schemes). Therefore, to obtain the optimal performance, tuning the parameters is essential. In this paper, the DE algorithm is proposed that uses a new designed mutation scaling factor to dynamically adapt the movement of the individuals in the search space toward the optimal value during the evolutionary process. The numerical experiments are conducted on thirty CEC 2014 benchmark functions on four different dimensions; 10, 30, 50, and 100. The obtained results demonstrate that the proposed algorithm is highly competitive and shows better performance than the classical DE algorithm.