Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of ultrasound in the detection of cervical lymph node metastases in clinically N0 squamous cell carcinoma of the head and neck

Abstract Nodal involvement is the most important prognostic factor in head and neck squamous cell carcinoma (HNSCC) of mucosal origin. The presence of a single ipsilateral or contralateral metastatic node reduces survival by 50% and bilateral disease by a further 50%. The management of N+ HNSCC is relatively clear-cut. By contrast, the investigation and treatment of patients with clinically N0 disease is controversial. Most institutions electively treat the neck with surgery or radiotherapy because the risk of occult metastases is over 20%, even though it will be unnecessary in the majority of cases. In this situation the main purpose of staging would be to assess those nodes that are not going to be removed. However, the optimal management of the clinically N0 neck remains controversial and there is growing interest in a more conservative approach. Research is now directed toward finding a method of staging sensitive enough to bring the risk of occult metastases below 20%. High spatial resolution, ease of multiplanar scanning, power Doppler and the ability to perform guided fine-needle aspiration for cytology give ultrasound (US) an advantage over other imaging techniques.
Human papillomavirus infection and risk of lung cancer in never-smokers and women: an ‘adaptive’ meta-analysis

OBJECTIVES: The incidence of lung cancer in Koreans is increasing in women and in both men and women with a never-smoking history. Human papillomavirus (HPV) infection has been suggested as a modifiable risk factor of lung cancer in never-smokers and women (LCNSW). This systematic review (SR) aimed to evaluate an association between HPV infection and lung cancer risk in LCNSW. METHODS: Based on a prior SR and some expert reviews, we identified refereed, cited, or related articles using the PubMed and Scopus databases. All case-control studies that reported the odds ratio of HPV infection in LCNSW were selected. An estimate of the summary odds ratio (SOR) with 95% confidence intervals (CI) was calculated. RESULTS: A total of four case-control studies were included. The fixed-effect model was applied because of homogeneity (I-squared=0.0%). The SORs in women and in never-smokers were 5.32 (95% CI, 1.75 to 16.17) and 4.78 (2.25 to 10.15) respectively. CONCLUSIONS: These results showed a significant effect of HPV infection in LCNSW. It is evident that developing a preventive plan against LCNSW may be necessary.
An Environment Recognition Algorithm Based on Weighted Cloud Classifier

Environment recognition is a necessary prerequisite for behavioral decision and intelligent control of intelligent vehicle. In order to improve the surrounding environment recognition ability of intelligent vehicles, a weighted cloud classifier is constructed to recognize the content of image captured by vehicle camera. By researching the image texture characters, several cloud classifiers are trained based on the first and second order statistical characteristics of texture to identify the image content preliminarily. Then the cloud models are combined with adaboost algorithm to construct a weighted cloud classifier. Experiment results show that through weight optimization, the weighted classifier can realize multi-target recognition, and achieve good results in the recognition of vehicle, road, lane line and other targets. The weighted cloud classifier will play an important role in improving the environment recognition and behavioral decision capacity of intelligent vehicle.
Design of a multiblock general regression neural network for wind speed prediction in Algeria

In this work, we investigate a new design of a multiblock general regression neural network applied to wind speed prediction in Algeria. The idea in our proposed method is to minimize the error of the prediction for wind speed in such a way as to minimize the quantity of training samples used, and thus to reduce the costs related to the training sample collection. For this reason, we propose to select the most significant sample among a large number of training samples by using multiblock general regression neural network (MBGRNN). This paper presents experimental results on six different real wind speed measurement stations in Algeria namely, Alger, Djelfa, Bechar, Oran, Sétif and In Aménas. The wind speed data covers a period of ten years between 2001 and 2010.
Wireless Sensor Network Applications in Low Power Circuits

As the CMOS technology continues to scale down into the nano-scale regime, robustness of the circuit with respect to process variation and soft error are becoming major obstacles for circuit designers. Storage elements (SRAM, flip-flops) are particularly vulnerable to process variation and soft errors. Thus, in this work, we have focused on storage elements to improve the yield loss in SRAM due to process variations and to design a soft error tolerant flip-flop. SRAMs are particularly vulnerable to failures due to process variation resulting in reduced yield. The main problem with SRAM is the conflicting requirements for read stability and writes ability. In this work, we propose designs to overcome conflicting trade-off between read and write stability. Furthermore, new SRAM cells, namely 11TSRAM, PMOS access transistor SRAM, are proposed with capability of working at near threshold voltages, properly. The effect of body-biasing on SRAM cell is explored to show improvements from body-biasing in sub-threshold regions. Results show at least 30% improvement in read noise margin for proposed SRAM cells while write margin is improved. Furthermore, to overcome short channel effect, different candidate transistor structures have been investigated to replace the bulk MOSFETs. Among them, FINFET is considered to be a promising candidate for scaled CMOS devices in sub-22-nm technology nodes. In this work, by introducing a new device, the read and write stability for SRAM is improved by 20% and 9% respectively, while performance is improved by 56%compared to conventional designs. we study the double-gate FINFET SRAM technology-circuit design space to understand the interplay of device short-channel-effect (SCE), SRAM area, access time, soft error immunity, stability under process variations and leakage. Several Flip-Flop designs are designed to reduce power in DSP applications. Simulation results show 40% improvement in total power saving for some DSP applications such as FIR filters and other DSP applications. Design challenges in submicron CMOS technology are investigated in details for sub-threshold designs for wireless sensor network applications. In this work different CMOS model such as ST Microelectronic, TSMC and IBM models are used for different application.
Speech recognition and enhancement by a nonstationary AR HMM with gain adaptation under unknown noise

A gain-adapted speech recognition in unknown noise is developed in time domain. The noise is assumed to be the colored noise. The nonstationary autoregressive (NAR) hidden Markov model (HMM) used to model clean speeches. The nonstationary AR is modeled by polynomial functions with a linear combination of M known basis functions. Enhancement using multiple Kalman filters is performed for the gain contour of speech and estimation of noise model when only the noisy signal is available.
Keratin 8/18 Modulation of Protein Kinase C-mediated Integrin-dependent Adhesion and Migration of Liver Epithelial Cells

Hepatocyte and hepatoma cell IFs are made solely of keratins 8/18 (K8/K18). Cell adhesion and migration involve integrin interactions with focal adhesion kinase (FAK) and protein kinase C (PKC). Here we report a new regulatory function for K8/K18 IFs in the PKC-mediated integrin/FAK-dependent adhesion and migration of simple epithelial cells.
Reinforcement learning of multiple tasks using parametric bias

We propose a reinforcement learning system designed to learn multiple different continuous state-action-space tasks. The system has been tested on a family of space-searching task akin to Morris water maze, but with obstacles. While exploring a task, the agent builds its internal model of the environment and approximates a state value function. For learning multiple tasks, we use a parametric bias switching mechanism in which the value of the parametric bias layer identifies the task for the agent. Each task has a specific parametric bias vector, and during training the vectors self-organize to reflect the structure of relationships between tasks in the task set. This mapping of the task set to parametric bias space can later be used to generate novel behaviors of the agent.
MPT0B169, a New Antitubulin Agent, Inhibits Bcr-Abl Expression and Induces Mitochondrion-Mediated Apoptosis in Nonresistant and Imatinib-Resistant Chronic Myeloid Leukemia Cells

Chronic myeloid leukemia (CML) is a clonal disorder of hematopoietic stem/progenitor cells that is caused by the Bcr-Abl oncoprotein. Clinical resistance to the Bcr-Abl inhibitor imatinib is a critical problem in treating CML. This study investigated the antitumor effect and mechanism of MPT0B169, a new antitubulin agent, in K562 CML cells and their derived imatinib-resistant cells, IMR2 and IMR3. IMR2 and IMR3 cells showed complete resistance to imatinib-induced growth inhibition and apoptosis. Resistance involved ERK1/2 overactivation and MDR1 overexpression. MPT0B169 inhibited the growth of K562, IMR2, and IMR3 cells in a dose- and time-dependent manner. MPT0B169 substantially inhibited the mRNA and protein levels of Bcr-Abl, followed by its downstream pathways including Akt, ERK1/2, and STAT3 in these cells. MPT0B169 treatment resulted in a decrease in the polymer form of tubulin according to Western blot analysis. It triggered cell cycle arrest at the G2/M phase before apoptosis, which was related to the upregulation of the mitotic marker MPM2 and the cyclin B1 level, and a change in the phosphorylation of Cdk1. MPT0B169 induced apoptosis in nonresistant and imatinib-resistant cells via a mitochondrion-mediated caspase pathway. Further study showed that the agent led to a decrease in the antiapoptotic proteins Bcl-2, Bcl-xL, and Mcl-1 and an increase in the apoptotic protein Bax. Taken together, our results suggest that MPT0B169 might be a promising agent for overcoming imatinib resistance in CML cells.
Remote tracking of nonholonomic mobile robots via networked predictive control

This paper considers the remote tracking problem of a nonholonomic mobile robot under the situation of constant communication delay in both the feedback and forward channels. A tracking controller in the discrete-time domain for the case of ideal network conditions is used, and then, based on above tracking controller, a networked predictive controller as well as an algorithm for dealing with constant communication delay are proposed. Simulation results verify the realizability and effectiveness of the proposed algorithm.
Cluster-based Medium Access Scheme for VANETs

In recent years research on active safety systems with the main focus on environment sensing has been done. Therefore vehicles are equipped with sensors which record information about the nearby traffic situation and possible hazards. For anticipatory driving additional information outside of the range of the sensors' area needs to be collected. This can be done by introducing data transfer between vehicles, which allows to gather data of a larger area and therefore improves the anticipatory capabilities of the system. One main aspect in the data exchange between vehicles is the organization of the access to the medium. It has to be able to cope with all the problems of mobile ad-hoc networks. Especially the hidden station problem is an important factor in vehicular ad-hoc networks (VANETs). But also the high density of nodes, high dynamics and a limited data rate require a fair and efficient access to the medium. In this paper we present a medium access scheme for vehicular ad-hoc networks which is based on clustering of the vehicles. Thus the effect of hidden stations can be minimized, which leads to a more reliable data transfer than IEEE 802.11 based systems can provide.
Minimizing Communication Costs of Distributed Local Computation ∗

A valuation algebra offers a suitable framework to represent knowledge and information. Based on this framework, several algorithms to process knowledge and pooled under the name local computation were mapped out in recent years. This paper proposes an extension of the valuation algebra framework that allows to express the costs of transmitting valuations between network hosts. Based on this model, we estimate the total computation costs caused by the local computation architectures and observe under which constraints these costs can be minimized. Once a sufficient condition is identified, we present an efficient algorithm to solve the minimization problem concretely.
Learning to Detect Hedges and their Scope Using CRF

Detecting speculative assertions is essential to distinguish the facts from uncertain information for biomedical text. This paper describes a system to detect hedge cues and their scope using CRF model. HCDic feature is presented to improve the system performance of detecting hedge cues on BioScope corpus. The feature can make use of cross-domain resources.
Characterization of Two New Aminopeptidases in Escherichia coli

ABSTRACT Two genes in the Escherichia coli genome, ypdE and ypdF, have been cloned and expressed, and their products have been purified. YpdF is shown to be a metalloenzyme with Xaa-Pro aminopeptidase activity and limited methionine aminopeptidase activity. Genes homologous to ypdF are widely distributed in bacterial species. The unique feature in the sequences of the products of these genes is a conserved C-terminal domain and a variable N-terminal domain. Full or partial deletion of the N terminus in YpdF leads to the loss of enzymatic activity. The conserved C-terminal domain is homologous to that of the methionyl aminopeptidase (encoded by map) in E. coli. However, YpdF and Map differ in their preference for the amino acid next to the initial methionine in the peptide substrates. The implication of this difference is discussed. ypdE is the immediate downstream gene of ypdF, and its start codon overlaps with the stop codon of ypdF by 1 base. YpdE is shown to be a metalloaminopeptidase and has a broad exoaminopeptidase activity.
Characterization of Left Ventricular Activation in Patients With Heart Failure and Left Bundle-Branch Block

Background—Conventional activation mapping in the dilated human left ventricle (LV) with left bundle-branch block (LBBB) morphology is incomplete given the limited number of recording sites that may be collected in a reasonable time and given the lack of precision in marking specific anatomic locations. Methods and Results—We studied LV activation sequences in 24 patients with heart failure and LBBB QRS morphology with simultaneous application of 3D contact and noncontact mapping during intrinsic rhythm and asynchronous pacing. Approximately one third of the patients with typical LBBB QRS morphology had normal transseptal activation time and a slightly prolonged or near-normal LV endocardial activation time. A “U-shaped” activation wave front was present in 23 patients because of a line of block that was located anteriorly (n=12), laterally (n=8), and inferiorly (n=3). Patients with a lateral line of block had significantly shorter QRS (P <0.003) and transseptal durations (P <0.001) and a longer distance from the LV breakthrough site to line of block (P <0.03). Functional behavior of the line of block was demonstrated by a change in its location during asynchronous ventricular pacing at different sites and cycle lengths. Conclusions—A U-shaped conduction pattern is imposed on the LV activation sequence by a transmural functional line of block located between the LV septum and the lateral wall with a prolonged activation time. Assessment of functional block is facilitated by noncontact mapping, which may be useful for identifying and targeting specific locations that are optimal for successful cardiac resynchronization therapy.
Psychometric performance of the NEI VFQ-25 in visually normal Latinos: the Los Angeles Latino Eye Study.

PURPOSE To characterize the psychometric performance of the National Eye Institute 25-item Visual Function Questionnaire (NEI VFQ-25) in visually normal Latinos (Mexican Americans). METHODS The Los Angeles Latino Eye Study (LALES) is a population-based study to assess the prevalence of eye disease and self-reported visual functioning in Latinos aged 40 or more years. Self-reported visual functioning was assessed by using English and Spanish versions of the NEI VFQ-25. Psychometric properties of the NEI VFQ-25, including internal consistency of the subscales and the individual items, were assessed through the Multi-trait Analysis Program-Revised (MAP-R) analysis. Adjusted mean and median subscale scores were compared between English and Spanish speakers to identify any systematic differences. RESULTS Of the 1917 participants from two census tracts, 1171 participants with no visual impairment were included in this analysis. The mean age of the participants was 52.3 years, 57% of the participants were female, and 67.5% of the participants were Spanish speaking. Median scores for Spanish-speaking participants were significantly lower than those of the English-speaking participants on four subscales: Ocular Pain, General Vision, Vision-Specific Mental Health, and General Health (P < 0.05). Internal consistency for three of eight measurable subscales for the study group was poor (Cronbach alpha < 0.6). CONCLUSIONS This study reveals psychometric inconsistencies in the NEI VFQ-25 when administered to visually normal Latinos. The difference in mean subscale scores between Spanish and English speakers must be integrated into the development of population norms of visual function. Further detailed psychometric evaluation is needed to determine the validity of this instrument in Latino populations.
A molecular understanding of the dynamic mechanism of aquaporin osmosis

AQPs (aquaporins), the rapid water channels of cells, play a key role in maintaining osmotic equilibrium of cells. In this paper, we reported the dynamic mechanism of AQP osmosis at the molecular level. A theoretical model based on molecular dynamics was carried out and verified by the published experimental data. The reflection coefficients ({\sigma}) of neutral molecules are mainly decided by their relative size with AQPs, and increase with a third power up to a constant value 1. This model also indicated that the reflection coefficient of a complete impermeable solute can be smaller than 1. The H+ concentration of solution can influence the driving force of the AQPs by changing the equivalent diameters of vestibules surrounded by loops with abundant polar amino acids. In this way, pH of solution can regulate water permeability of AQPs. Therefore, an AQP may not only work as a switch to open or close, but as a rapid response molecular valve to control its water flow. The vestibules can prevent the channel blockage of AQPs by a primary screening before their constriction region. This model also provides a prediction tool to the structure of AQPs by the {\sigma}s of special solutes. The puzzling variance between {\sigma} to erythrocytes AQP1 and {\sigma} to oocytes-expressing AQP1 was also explained.
Probabilistic inversion of a terrestrial ecosystem model: Analysis of uncertainty in parameter estimation and model prediction

The Bayesian probability inversion and a Markov chain Monte Carlo (MCMC) technique were applied to a terrestrial ecosystem model to analyze uncertainties of estimated carbon (C) transfer coefficients and simulated C pool sizes. This study used six data sets of soil respiration, woody biomass, foliage biomass, litterfall, C content in the litter layers, and C content in mineral soil measured under both ambient CO2 (350 ppm) and elevated CO2 (550 ppm) plots from 1996 to 2000 at the Duke Forest Free‐Air CO2 Experiment (FACE) site. A Metropolis‐Hastings algorithm was employed to construct a posterior probability density function (PPDF) of C transfer coefficients on the basis of prior information of model parameters, model structure, and the six data sets. The constructed PPDFs indicated that the transfer coefficients from pools of nonwoody biomass, woody biomass, and structural litter were well constrained by the six data sets under both ambient and elevated CO2. The data sets also gave moderate information to the transfer coefficient from the slow soil C pool. However, the transfer coefficients from pools of metabolic litter, microbe, and passive soil C were poorly constrained. The poorly constrained parameters were attributable to either the lack of experimental data or the mismatch of timescales between the available data and the parameters to be estimated. Cumulative distribution functions were constructed for simulated C pool sizes on the basis of the six data sets, showing that on average the ecosystem would store 16,616 g C m−2 at elevated CO2 by the year 2010, significantly higher than 13,426 g C m−2 at ambient CO2 with 95% confidence. This study shows that the combination of a Bayesian approach and MCMC inversion technique is an effective method to synthesize information from various sources for assessment of ecosystem responses to elevated CO2.
Proteomic analysis of γ‐butyrolactone‐treated mouse thalamus reveals dysregulated proteins upon absence seizure

Absence seizure has been of interest because the symptom is related to sensory processing. However, the mechanism that causes the disease is not understood yet. To better understand the molecular mechanism related to the disease progress at protein level, we performed proteomic studies using the thalamus of mice for which absence seizure was induced by γ‐butyrolactone (GBL). Differential proteome expression between GBL‐treated mice and control mice was examined by fluorescence 2D difference gel electrophoresis (DIGE) at three different time points (5, 10, and 30 min) after GBL‐administration. We identified 16 proteins differentially expressed by >1.4‐fold at any of the three time points. All proteins besides the serine protease inhibitor EIA were down‐regulated in absence seizure‐induced mice. The down‐regulated proteins can be classified into five groups by their biological functions: cytoskeleton rearrangement, neuroprotection, neurotransmitter secretion, calcium binding, and metabolism. The maximum level of change was reached by 10 min after GBL‐treatment, with the expression level returning back to the original at 30 min when mice were awakened from absence seizure thereby demonstrating the proteomic response is reversible. Our results suggest that absence seizures are associated with restricted functional sets of proteins, whose down‐regulation may interfere with general function of neuronal cells.
A cooperative game-theory model for bandwidth allocation in multi-hop wireless networks

The use of multi-hop wireless networks is extensive and growing. Such networks often have no single administrative authority. As such, they are best modeled by game theory. Existing approaches to this problem have focused on competitive game-theory analysis. In this paper we study the problem from the perspective of cooperative game theory. We assume that nodes wish to maximize their individual utility and cooperate solely for the purpose of increasing that utility. By assuming that the utility of a node is equal to its bandwidth, and by adopting the KS-Raiffa solution to cooperation, we are able to compute the fair bandwidth allocation in two-hop wireless networks. We then generalize these results to arbitrary multi-hop wireless networks. By assuming that any node can perform denial-of-service attack on the network, we are able to prove that Raiffa cooperation will result in temporal fairness in the network. Our results suggest that the ideal MAC for a wireless network will be one based on KS-Raiffa solution.