Miracle-dz/UniFAR-FTUs huggingface dataset:
Multitone Jamming Rejection of Frequency Hopped OFDM Systems in Wireless Channels

This work considers the bit error rate (BER) performance of orthogonal frequency division multiplexing (OFDM) frequency hopping (FH) systems in the presence of Multitone jamming (MTJ) and multipath fading. Analytical and simulation results confirmed that optimum jamming strategies require channel and signal power side information. Moreover, the common assumption that the jamming tones and subcarriers frequencies are identical can be quite inaccurate at low signal-to-jamming power ratios (SJR), particularly for small number of jamming tones.
Coordinated regulation of multiple flagellar motors by the Escherichia coli chemotaxis system

Escherichia coli cells swim toward a favorable environment by chemotaxis. The chemotaxis system regulates the swimming behavior of the bacteria by controlling the rotational direction of their flagellar motors. Extracellular stimuli sensed by chemoreceptors are transduced to an intracellular signal molecule, phosphorylated CheY (CheY-P), that switches the rotational direction of the flagellar motors from counterclockwise (CCW) to clockwise (CW) or from CW to CCW. Many studies have focused on identifying the proteins involved in the chemotaxis system, and findings on the structures and intracellular localizations of these proteins have largely elucidated the molecular pathway. On the other hand, quantitative evaluations of the chemotaxis system, including the process of intracellular signaling by the propagation of CheY-P and the rotational switching of flagellar motor by binding of CheY-P molecules, are still uncertain. For instance, scientific consensus has held that the flagellar motors of an E. coli cell switch rotational direction asynchronously. However, recent work shows that the rotational switching of any two different motors on a single E. coli cell is highly coordinated; a sub-second switching delay between motors is clearly correlated with the relative distance of each motor from the chemoreceptor patch located at one pole of the cell. In this review of previous studies and our recent findings, we discuss the regulatory mechanism of the multiple flagellar motors on an individual E. coli cell and the intracellular signaling process that can be inferred from this coordinated switching.
Two different motor systems are needed to generate human speech

Vocalizations such as mews and cries in cats or crying and laughter in humans are examples of expression of emotions. These vocalizations are generated by the emotional motor system, in which the mesencephalic periaqueductal gray (PAG) plays a central role, as demonstrated by the fact that lesions in the PAG lead to complete mutism in cats, monkeys, as well as in humans. The PAG receives strong projections from higher limbic regions and from the anterior cingulate, insula, and orbitofrontal cortical areas. In turn, the PAG has strong access to the caudal medullary nucleus retroambiguus (NRA). The NRA is the only cell group that has direct access to the motoneurons involved in vocalization, i.e., the motoneuronal cell groups innervating soft palate, pharynx, and larynx as well as diaphragm, intercostal, abdominal, and pelvic floor muscles. Together they determine the intraabdominal, intrathoracic, and subglottic pressure, control of which is necessary for generating vocalization. Only humans can speak, because, via the lateral component of the volitional or somatic motor system, they are able to modulate vocalization into words and sentences. For this modulation they use their motor cortex, which, via its corticobulbar fibers, has direct access to the motoneurons innervating the muscles of face, mouth, tongue, larynx, and pharynx. In conclusion, humans generate speech by activating two motor systems. They generate vocalization by activating the prefrontal‐PAG‐NRA‐motoneuronal pathway, and, at the same time, they modulate this vocalization into words and sentences by activating the corticobulbar fibers to the face, mouth, tongue, larynx, and pharynx motoneurons. J. Comp. Neurol. 524:1558–1577, 2016. © 2015 Wiley Periodicals, Inc.
Trajectory extraction for abnormal behavior detection in public area

Surveillance system to improve safety and security is a major demand for the management and control of public area. Crowd management and control system requires a situation recognition technique which can predict accidents and provide alarms to the monitoring personnel. In this paper, we propose an abnormal behavior detection technique by using trajectory extraction of moving objects in video. Abnormal behavior includes running persons. The proposed abnormal behavior detection system separates background and foreground using Gaussian mixture model. And then, foreground image is used to generate the trajectories of moving objects using a Kanade-Lucas-Tomasi algorithm of the optical flow method. In addition, noise removal step is added to improve the accuracy of the created trajectory. From the trajectory of moving objects information, such as length, pixel, coordinate and moving degree is extracted. As the result of the estimation of abnormal behavior, objects' behavior is configured and analyzed based on a priori specified scenarios, such as running persons. In the results, proposed system is able to detect the abnormal behavior in public area.
Proteomic Profiling of Plasmodium Sporozoite Maturation Identifies New Proteins Essential for Parasite Development and Infectivity

Plasmodium falciparum sporozoites that develop and mature inside an Anopheles mosquito initiate a malaria infection in humans. Here we report the first proteomic comparison of different parasite stages from the mosquito—early and late oocysts containing midgut sporozoites, and the mature, infectious salivary gland sporozoites. Despite the morphological similarity between midgut and salivary gland sporozoites, their proteomes are markedly different, in agreement with their increase in hepatocyte infectivity. The different sporozoite proteomes contain a large number of stage specific proteins whose annotation suggest an involvement in sporozoite maturation, motility, infection of the human host and associated metabolic adjustments. Analyses of proteins identified in the P. falciparum sporozoite proteomes by orthologous gene disruption in the rodent malaria parasite, P. berghei, revealed three previously uncharacterized Plasmodium proteins that appear to be essential for sporozoite development at distinct points of maturation in the mosquito. This study sheds light on the development and maturation of the malaria parasite in an Anopheles mosquito and also identifies proteins that may be essential for sporozoite infectivity to humans.
Does imaging-guided selection of patients with ischemic heart failure for high risk revascularization improve identification of those with the highest clinical benefit?: Imaging-guided selection of patients with ischemic heart failure for high-risk revascularization improves identification of those 

65-year-old man presented to his local emergency department with rapid atrial fibrillation and acute pulmonary edema. This patient had a history of hypertension, and 2 months before this presentation, he developed progressive exertional dyspnea. The patient deteriorated in the emergency department and went into cardiogenic shock. Emergent coronary angiography revealed diffuse 3-vessel disease: a 99% proximal left anterior descending coronary artery lesion, 90% mid-right coronary artery lesion, occluded large first marginal branch, and diffuse severe disease of the left circumflex coronary artery. The initial ejection fraction (EF) on echocardiography was 15%, with mild mitral regurgitation and an estimated pulmonary artery pressure of 55 mm Hg. The patient stabilized with an intraaortic balloon pump and intensive care unit management; however, because of the diffuse nature of the disease, he was not believed to be a surgical candidate. He was transferred to another tertiary-care facility for consideration of cardiac transplantation. As part of this evaluation, a PET viability study was done that demonstrated a significant area of perfusion-metabolism mismatch in the entire anteriolateral wall. Less than 1% of the myocardium was scar, and 28% was defined as hibernating (Figure 1). Response by Velazquez on p 270 The results of the viability test were pivotal in the decision to perform coronary artery bypass graft (CABG) surgery in a patient who otherwise would not have had surgery. Approximately 2 months after his initial presentation, the patient had a 4-vessel CABG. His predischarge echocardiogram demonstrated an EF of 25%. Six months after surgery, the patient was clinically stable with New York Heart class II functional symptoms and an EF of 45%.
A Gabor Wavelet Transformation-Based Texture Images Classification Algorithm

In this paper, we introduce a texture image classification algorithm based on Gabor wavelet transform. Using Gabor wavelet transform, image is decomposed into sub-bands images in multiresolution and multi-direction, and we extract texture feature from all sub-bands images. Then the algorithm groups feature image into clusters by the k near neighbor algorithm. The experimental results on dataset Brodatz showed that the proposed algorithm can achieve an ideal accuracy rate and excellent classification effect.
Parallelized Dilate Algorithm for Remote Sensing Image

As an important algorithm, dilate algorithm can give us more connective view of a remote sensing image which has broken lines or objects. However, with the technological progress of satellite sensor, the resolution of remote sensing image has been increasing and its data quantities become very large. This would lead to the decrease of algorithm running speed or cannot obtain a result in limited memory or time. To solve this problem, our research proposed a parallelized dilate algorithm for remote sensing Image based on MPI and MP. Experiments show that our method runs faster than traditional single-process algorithm.
Segmentation and classification of colon glands with deep convolutional neural networks and total variation regularization

Segmentation of histopathology sections is a necessary preprocessing step for digital pathology. Due to the large variability of biological tissue, machine learning techniques have shown superior performance over conventional image processing methods. Here we present our deep neural network-based approach for segmentation and classification of glands in tissue of benign and malignant colorectal cancer, which was developed to participate in the GlaS@MICCAI2015 colon gland segmentation challenge. We use two distinct deep convolutional neural networks (CNN) for pixel-wise classification of Hematoxylin-Eosin stained images. While the first classifier separates glands from background, the second classifier identifies gland-separating structures. In a subsequent step, a figure-ground segmentation based on weighted total variation produces the final segmentation result by regularizing the CNN predictions. We present both quantitative and qualitative segmentation results on the recently released and publicly available Warwick-QU colon adenocarcinoma dataset associated with the GlaS@MICCAI2015 challenge and compare our approach to the simultaneously developed other approaches that participated in the same challenge. On two test sets, we demonstrate our segmentation performance and show that we achieve a tissue classification accuracy of 98% and 95%, making use of the inherent capability of our system to distinguish between benign and malignant tissue. Our results show that deep learning approaches can yield highly accurate and reproducible results for biomedical image analysis, with the potential to significantly improve the quality and speed of medical diagnoses.
A Probabilistic Approach to Fault Diagnosis in Linear Lightware Networks

The application of probabilistic reasoning to fault diagnosis in linear lightwave networks (LLNs) is investigated. The LLN inference model is represented by a Bayesian network (or causal network). An inference algorithm is proposed that is capable of conducting fault diagnosis (inference) with incomplete evidence and on an interactive basis. Two belief updating algorithms are presented which are used by the inference algorithm for performing fault diagnosis. The first belief updating algorithm is a simplified version of the one proposed by Pearl (1988) for singly connected inference models. The second belief updating algorithm applies to multiply connected inference models and is more general than the first. The authors also introduce a t-fault diagnosis system and an adaptive diagnosis system to further reduce the computational complexity of the fault diagnosis process. >
Characterization of RNA synthesis during a one-step growth curve and of the replication mechanism of bovine viral diarrhoea virus.

The noncytopathic Australian bovine viral diarrhoea virus (BVDV) Trangie isolate was used to establish a one-step growth curve and to investigate previously uncharacterized aspects of pestivirus replication. The eclipse phase was found to be approximately 8 to 10 h and the first appearance of viral antigen assayed by immunofluorescence occurred around 6 h post-infection (p.i.). Both positive- and negative-sense virus RNAs were first detected at 4 h p.i. by Northern blot hybridization using strand-specific RNA probes generated by in vitro transcription from cDNA cloned from the NS3 region. The ratio of positive- to negative-sense virus RNA changed from 2:1 at 4 h p.i. to 10:1 at 12 h p.i. and thereafter. The kinetics of synthesis showed that the rate of synthesis of positive-strand viral RNA increased rapidly from 6 h p.i. , whereas the rate of synthesis of the negative-strand remained constant. The copy number of genomic RNA determined by Northern blot hybridization analysis was estimated to be 1.5 x 10(4) copies per cell, 16 to 24 h p.i. Viral RNA species that were thought to represent replicative intermediate (RI) and replicative forms (RF) were detected after electrophoretic separation by urea-PAGE. Confirmation of the identity of the RI and RF was obtained using LiCl precipitation and RNase A digestion of [3H]uridine-labelled RNA. Pulse-chase labelling of BVDV-infected cells was consistent with synthesis of nascent BVDV RNA through an RI derived by strand displacement from an RF template and thus the synthesis of BVDV RNA is likely to be similar to the model proposed for flavivirus replication.
Increasing the energy efficiency of TLS systems using intermediate checkpointing

With the advent of Chip Multiprocessors (CMPs), improving performance relies on the programmers/compilers to expose thread level parallelism to the underlying hardware. However, this is a difficult and error-prone process for the programmers, while state of the art compiler techniques are unable to provide significant benefits for many classes of applications. An alternative is offered by systems that support Thread Level Speculation (TLS), which relieve the programmer and compiler from checking for thread dependences and instead use the hardware to enforce them. Unfortunately, TLS suffers from power inefficency because data misspeculations cause threads to roll back to the beginning of the speculative task. For this reason intermediate check-pointing of TLS threads has been proposed. When a violation does occur, we now have to roll back to a checkpoint before the violating instruction and not to the start of the task. However, previous work omits study of the microarchitectural details and implementation issues that are essential for effective checkpointing. In this paper we study checkpointing on a state-of-the art TLS system. We systematically study the costs associated with checkpointing and analyze the tradeoffs. We also propose changes to the TLS mechanism to allow effective checkpointing. Further, we establish the need for accurately identifying points in execution that are appropriate for checkpointing and analyze various techniques for doing so in terms of both effectiveness and viability. We propose program counter based and hybrid predictors and show that they outperform previous proposals. Placing checkpoints based on dependence predictors results in power improvements while maintaining the performance advantage of TLS. The checkpointing system proposed achieves an energy saving of up to 14%, with an average of 7% over normal TLS execution.
Active Role of the Interdomain Linker of AraC

ABSTRACT Mutations in the interdomain linker of the gene for the AraC regulatory protein of Escherichia coli that severely interfere with the protein's ability either to repress or to activate transcription have been found. These mutations have relatively small effects on the dimerization domain's ability to bind arabinose or to dimerize the protein or on the DNA-binding domain's affinity for a single DNA half-site. The linker mutations, however, dramatically change the affinity of AraC for binding to two direct-repeat DNA half-sites. Less dramatically, the induction-deficient linker variants also display altered DNA sequence selectivity. These results show that changing the sequence of the interdomain linker can profoundly affect the dimerization domain–DNA-binding domain interactions in AraC. The smaller effects on the functions of the individual domains could be the direct result of the linker alterations but more likely are the indirect result of the altered dimerization domain–DNA-binding domain interactions. In summary, the linker does not simply function as a passive and flexible connector between the domains of AraC but, instead, is more directly involved in the protein's dimerization domain–DNA-binding domain interactions.
Linking Marketing and Engineering Product Design Decisions via Analytical Target Cascading

Firms design products that appeal to consumers and are feasible to produce. The resulting marketing and engineering design goals are driven by consumer preferences and engineering capabilities, two issues that conveniently are addressed in isolation from one another. This convenient isolation, however, typically will not result in optimal product decisions when the two problems are interrelated. A method new to the marketing community, analytical target cascading (ATC), is adopted here to explore such interrelationships and to formalize the process of coordinating marketing and engineering design problems in a way that is proven to yield the joint optimal solution. The ATC model is built atop well-established marketing methodologies, such as conjoint, discrete choice modeling and demand forecasting. The method is demonstrated in the design of dial-readout household scales, using real conjoint choice data and a parametric engineering product design model. Results indicate that the most profitable achievable product can fall short of predictions based on marketing alone but well ahead of what engineering may produce based on original marketing target specifications. A number of extensions can be accomplished readily using techniques from the extant marketing and design optimization literature.
Combining Supervised and Semi-Supervised Learning in the Design of a New Identifier for NPPs Transients

This study introduces a new identifier for nuclear power plants (NPPs) transients. The proposed identifier performs its function in two steps. First, the transient is identified by the previously developed supervised classifier combining ARIMA model and EBP algorithm. In the second step, the patterns of unknown transients are fed to the identifier based on the semi-supervised learning (SSL). The transductive support vector machine (TSVM) as a semi-supervised algorithm is trained by the labeled data of transients to predict some unlabeled data. The labeled and newly predicted data is then used to train the TSVM for another portion of unlabeled data. Training and prediction is continued until the change of targets is less than a desired value. The last targets (i.e., the final predicted for unlabeled data) identify the type of unknown transient. To analyze the ability of the proposed identifier, Bushehr nuclear power plant (BNPP) transients are examined. Results show good performance of the proposed identifier. Noticeable advantages are: clustering of unknown transients by labeled and unlabeled data, transductive approach of identifier without need to cluster all data, and sole dependency of identifier on sign of output signal due to the modular networks. Recognition of transient based on similarity of its statistical properties to the reference one, more robustness against noisy data, and improvement balance between memorization and generalization are other advantages of the identifier.
Amelioration of diet-induced steatohepatitis in mice following combined therapy with ASO-Fsp27 and fenofibrate[S]

Nonalcoholic fatty liver disease (NAFLD) is the leading cause of chronic liver disease. NAFLD progresses from benign steatosis to steatohepatitis (NASH) to cirrhosis and is linked to hepatocellular carcinoma. No targeted treatment is currently approved for NAFLD/NASH. We previously showed that fat-specific protein 27 (FSP27), a lipid droplet-associated protein that controls triglyceride turnover in the hepatocyte, is required for fasting- and diet-induced triglyceride accumulation in the liver. However, silencing Fsp27 with antisense oligonucleotides (ASOs) did not improve hepatosteatosis in genetic nor nutritional mouse models of obesity. Herein, we tested the therapeutic potential of ASO-Fsp27 when used in combination with the PPARα agonist fenofibrate. C57BL/6 mice were fed a high-trans-fat, high-cholesterol, high-fructose diet for eight weeks to establish NASH, then kept on diet for six additional weeks while dosed with ASOs and fenofibrate, alone or in combination. Data show that ASO-Fsp27 and fenofibrate synergize to promote resistance to diet-induced obesity and hypertriglyceridemia and to reverse hepatic steatosis, inflammation, oxidative stress, and fibrosis. This multifactorial improvement of liver disease noted when combining both drugs suggests that a course of treatment that includes both reduced FSP27 activity and activation of PPARα could provide therapeutic benefit to patients with NAFLD/NASH.
Random Polymer Models

Random Polymer Models and Their Applications The Homogeneous Pinning Model Weakly Inhomogeneous Models The Free Energy of Disordered Polymer Chains Disordered Pinning Models: The Phase Diagram Disordered Copolymers and Selective Interfaces: The Phase Diagram The Localized Phase of Disordered Polymers The Delocalized Phase of Disordered Polymers Numerical Algorithms and Computations.