Miracle-dz/UniFAR-FTUs huggingface dataset:
Zero-Sleep-Leakage Flip-Flop Circuit With Conditional-Storing Memristor Retention Latch

In this paper, two new zero-sleep-leakage flip-flop (F-F) circuits are proposed to make the sleep leakage literally zero. At the sleep-in time, the F-F's data are transferred to memristor retention latch; thus, the F-F can be completely cutoff from the external power supply saving the energy leak during the sleep time. The conditional storing circuit in the F-F (type-2) can reduce switching power by 87% in storing the data than the F-F (type-1). And, the crossover time of the F-F (type-2) is shortened by 97% than the F-F (type-1).
The Relationship between Particulate Pollution Levels in Australian Cities, Meteorology, and Landscape Fire Activity Detected from MODIS Hotspots

Smoke from bushfires is an emerging issue for fire managers because of increasing evidence for its public health effects. Development of forecasting models to predict future pollution levels based on the relationship between bushfire activity and current pollution levels would be a useful management tool. As a first step, we use daily thermal anomalies detected by the MODIS Active Fire Product (referred to as “hotspots”), pollution concentrations, and meteorological data for the years 2002 to 2008, to examine the statistical relationship between fire activity in the landscapes and pollution levels around Perth and Sydney, two large Australian cities. Resultant models were statistically significant, but differed in their goodness of fit and the distance at which the strength of the relationship was strongest. For Sydney, a univariate model for hotspot activity within 100 km explained 24% of variation in pollution levels, and the best model including atmospheric variables explained 56% of variation. For Perth, the best radius was 400 km, explaining only 7% of variation, while the model including atmospheric variables explained 31% of the variation. Pollution was higher when the atmosphere was more stable and in the presence of on-shore winds, whereas there was no effect of wind blowing from the fires toward the pollution monitors. Our analysis shows there is a good prospect for developing region-specific forecasting tools combining hotspot fire activity with meteorological data.
A New Architecture for H.264 Variable Block Size Motion Estimation

In an H.264 video encoder, motion estimation (ME) is the most time-consuming component. Several fast ME algorithms have been proposed to reduce the complexity of integer pixel ME (IME) computation, but few of them considered IME and fractional pixel ME (FME) together. Given the possibility of performance improvement through designing both IME and FME at the same time, a new hardware architecture is proposed for variable block size motion estimation with full search at 1/4 pixel accuracy. With the search range (SR) of [-20, +19] in both horizontal and vertical direction, the new architecture will save more than 50% computation time compared with full search algorithm (FS), while the cost is 50% increase of the sum of absolute differences (SAD) in average. The hardware implementation can achieve real-time operation at a frequency of 15 MHz for CIF format frame at 30 Hz.
CONVEX: Similarity-Based Algorithms for Forecasting Group Behavior

A proposed framework for predicting a group's behavior associates two vectors with that group. The context vector tracks aspects of the environment in which the group functions; the action vector tracks the group's previous actions. Given a set of past behaviors consisting of a pair of these vectors and given a query context vector, the goal is to predict the associated action vector. To achieve this goal, two families of algorithms employ vector similarity. CONVEXk _NN algorithms use k-nearest neighbors in high-dimensional metric spaces; CONVEXMerge algorithms look at linear combinations of distances of the query vector from context vectors. Compared to past prediction algorithms, these algorithms are extremely fast. Moreover, experiments on real-world data sets show that the algorithms are highly accurate, predicting actions with well over 95-percent accuracy.
Revised response criteria for malignant lymphoma.

PURPOSE Standardized response criteria are needed to interpret and compare clinical trials and for approval of new therapeutic agents by regulatory agencies. METHODS The International Working Group response criteria (Cheson et al, J Clin Oncol 17:1244, 1999) were widely adopted, but required reassessment because of identified limitations and the increased use of [18F]fluorodeoxyglucose-positron emission tomography (PET), immunohistochemistry (IHC), and flow cytometry. The International Harmonization Project was convened to provide updated recommendations. RESULTS New guidelines are presented incorporating PET, IHC, and flow cytometry for definitions of response in non-Hodgkin's and Hodgkin's lymphoma. Standardized definitions of end points are provided. CONCLUSION We hope that these guidelines will be adopted widely by study groups, pharmaceutical and biotechnology companies, and regulatory agencies to facilitate the development of new and more effective therapies to improve the outcome of patients with lymphoma.
Conductor: enabling and understanding cross-device interaction

The proliferation of inexpensive connected devices has created a situation where a person, at any given moment, is surrounded by interactive computers. Despite this fact, there are very few means by which a user may take advantage of this large number of screens. We present Conductor, a prototype framework which serves as an exemplar for the construction of cross-device applications. We present a series of interaction methods by which users can easily share information, chain tasks across devices, and manage sessions across devices. We also present a cross-device usage scenario which utilizes several cross-device applications built within our prototype framework. We also describe a user study, which helped us to understand how users will take advantage of a large number of devices in support of performance of a sense making task.
Screening of lysyl oxidase (LOX) and lysyl oxidase like (LOXL) enzyme expression and activity in preterm prelabor rupture of fetal membranes

Abstract Objective: Lysyl oxidase (LOX) and LOX like enzymes (LOXL1–4) physiologically remodel extracellular matrix and pathologically contribute to cellular senescence under oxidative stress (OS). We characterized LOX and LOXL expressions and activity in human fetal membranes. Methods: Human fetal membranes from women with uncomplicated pregnancies at term, preterm birth with intact membranes (PTB) or preterm prelabor rupture of membranes (pPROM), and in vitro fetal membranes stimulated with water-soluble cigarette smoke extract (CSE), an OS inducer, were analyzed by real-time PCR and immunohistochemistry for LOX and LOXL (1–4) expression and localization. LOX activity was measured by fluorometric assay. Results: LOX gene expression was ∼2.5-fold higher in fetal membranes from pPROM compared to PTB and term (P=0.02). LOX and LOXL1, 2 and 4 were localized to both amniotic and chorionic cells, whereas LOXL3 was limited to chorion. LOX and LOXL isoform expressions were not different between CSE treated and untreated groups, while LOX activity was increased in the presence of an antioxidant (P=0.02). Conclusions: Increase of LOX expression in pPROM, an OS-related disease, and the apparent inhibition of LOX activity by CSE restored by antioxidant treatment suggest that reactive oxygen species might influence LOX-mediated tissue remodeling in fetal membranes. Balanced antioxidant supplementation during pregnancy may reduce the risk of pPROM by increasing LOX activity.
Solving 0-1 knapsack problems by a discrete binary version of cuckoo search algorithm

Cuckoo search (CS) is one of the most recent population-based meta-heuristics. CS algorithm is based on the cuckoo's behaviour and the mechanism of Levy flights. Unfortunately, the standard CS algorithm is proposed only for continuous optimisation problems. In this paper, we propose a discrete binary cuckoo search (BCS) algorithm in order to deal with binary optimisation problems. To get binary solutions, we have used a sigmoid function similar to that used in the binary particle swarm optimisation algorithm. Computational results on some knapsack problem instances and multidimensional knapsack problem instances show the effectiveness of the proposed algorithm and its ability to achieve good quality solutions.
Development of antibiotic resistance in Pseudomonas aeruginosa during two decades of antipseudomonal treatment at the Danish CF Center

At the Danish CF Center patients with chronic Pseudomonas aeruginosa lung infection were treated 3–4 times a year (from 1976) with a 2‐week intravenous antipseudomonal course which included preferentially an aminoglycoside and a β‐lactam antibiotic. We investigated the development of antibiotic resistance in P. aeruginosa strains isolated from Danish CF patients over a period of 18 years by testing the in vitro efficacy of carbenicillin, piperacillin, ceftazidime, tobramycin and ciprofloxacin against P. aeruginosa strains collected in 1973 (51 strains), 1980 (80 strains), 1985 (58 strains), and 1991 (100 strains). All the strains were screened and assayed semiquantitively for β‐lactamase activity by use of nitrocefin. We found a significant (p<0.005) increase in the MIC values of the P. aeruginosa strains against piperacillin and ceftazidime. However, no significant correlation was found between the MIC and the number of antipseudomonal courses of antibiotics. The proportion of resistant in vivo selected P. aeruginosa strains, presumed to be stably derepressed producers of chromosomal β lactamase, also increased significantly during the period studied. Our results confirm that the β lactamase production is an important mechanism of antibiotic resistance in P. aeruginosa.
Analysis of blocking probability for distributed lightpath establishment in WDM optical networks

In this paper, we analyze the blocking probability of distributed lightpath establishment in wavelength-routed WDM networks by studying the two basic methods: destination-initiated reservation (DIR) and source-initiated reservation (SIR). We discuss three basic types of connection blocking: 1) blocking due to insufficient network capacity; 2) blocking due to outdated information; and 3) blocking due to over-reservation. It is shown that the proposed models are highly accurate for both the DIR and the SIR methods, in both the regular and irregular network topologies, under the whole range of traffic loads.
AUTOMATIC MUSIC TAGGING BY LOW-RANK REPRESENTATION Yannis Panagakis and

A novel multi-label annotation method is proposed and applied to music tagging. Each music recording is represented by its auditory temporal modulations (ATMs). Given a set of training music recordings represented by the tag-music recording matrix having zero-one (indicator) vectors of the tags associated with each recording in its columns along with the matrix of the ATM representations in its columns, a low-rank weight matrix is sought, such that the tag-music recording matrix is expressed as the product of the weight matrix and the matrix of the ATM representations plus an error matrix. Clearly, such a weight matrix captures the relationships between the labels (i.e., tags) and the audio features. It can be derived by solving a convex nuclear norm minimization problem, if the tag-music recording matrix and the matrix of the ATM representations are assumed to be jointly low-rank. Having found the weight matrix, the annotation vector for labeling any test music recording can be obtained by multiplying the weight matrix with its ATM representation. The just outlined method is referred to as low-rank representation based multilabel annotation (LRRMA). The LRRMA outperforms the state-ofthe-art auto-tagging systems, when applied to the CAL500 dataset in a 5-fold cross-validation experimental protocol.
Structural health monitoring of plastic components with piezoelectric sensors

Due to the material changes of components from metal to plastic or composite materials, the structural health monitoring finds more and more interest in the industrial fields. The reason is that these materials are more vulnerable to damage or impacts which cannot be optically detected. In this contribution we present a method to analyze the structure of plastic components with piezo-electrical sensors and actuators. The components are stimulated by actuators, and sensors capture the injected vibrations. These signals are decomposed into Intrinsic Mode Functions to compute statistical features. A Fuzzy-Pattern-Classifier is applied to detect structural modifications at the components under test.
A transparent framework based on accessing bridge and mobile app for protecting database privacy with PKI

With the popularity of cloud computing, database outsourcing has been adopted by many companies. However, database owners may not 100% trust their database service providers. As a result, database privacy becomes a key issue for protecting data from the database service providers. Many researches have been conducted to address this issue, but few of them considered the simultaneous transparent support of existing DBMSs (Database Management Systems), applications and RADTs (Rapid Application Development Tools). A transparent framework based on accessing bridge and mobile app for protecting database privacy with PKI (Public Key Infrastructure) is, therefore, proposed to fill the blank. The framework uses PKI as its security base and encrypts sensitive data with data owners' public keys to protect data privacy. Mobile app is used to control private key and decrypt data, so that accessing sensitive data is completely controlled by data owners in a secure and independent channel. Accessing bridge utilizes database accessing middleware standard to transparently support existing DBMSs, applications and RADTs. This paper presents the framework, analyzes its transparency and security, and evaluates its performance via experiments.
Synthesis, characterization, and biological activity of poly(arginine)‐derived cancer‐targeting peptides in HepG2 liver cancer cells

The solid‐phase synthesis, structural characterization, and biological evaluation of a small library of cancer‐targeting peptides have been determined in HepG2 hepatoblastoma cells. These peptides are based on the highly specific Pep42 motif, which has been shown to target the glucose‐regulated protein 78 receptors overexpressed and exclusively localized on the cell surface of tumors. In this study, Pep42 was designed to contain varying lengths (3–12) of poly(arginine) sequences to assess their influence on peptide structure and biology. Peptides were effectively synthesized by 9‐fluorenylmethoxycarbonyl‐based solid‐phase peptide synthesis, in which the use of a poly(ethylene glycol) resin provided good yields (14–46%) and crude purities >95% as analyzed by liquid chromatography–mass spectrometry. Peptide structure and biophysical properties were investigated using circular dichroism spectroscopy. Interestingly, peptides displayed secondary structures that were contingent on solvent and length of the poly(arginine) sequences. Peptides exhibited helical and turn conformations, while retaining significant thermal stability. Structure–activity relationship studies conducted by flow cytometry and confocal microscopy revealed that the poly(arginine) derived Pep42 sequences maintained glucose‐regulated protein 78 binding on HepG2 cells while exhibiting cell translocation activity that was contingent on the length of the poly(arginine) strand. In single dose (0.15 mM) and dose‐response (0–1.5 mM) cell viability assays, peptides were found to be nontoxic in human HepG2 liver cancer cells, illustrating their potential as safe cancer‐targeting delivery agents. Copyright © 2014 European Peptide Society and John Wiley & Sons, Ltd.
Face Recognition System Using Multiple Face Model of Hybrid Fourier Feature Under Uncontrolled Illumination Variation

The authors present a robust face recognition system for large-scale data sets taken under uncontrolled illumination variations. The proposed face recognition system consists of a novel illumination-insensitive preprocessing method, a hybrid Fourier-based facial feature extraction, and a score fusion scheme. First, in the preprocessing stage, a face image is transformed into an illumination-insensitive image, called an “integral normalized gradient image,” by normalizing and integrating the smoothed gradients of a facial image. Then, for feature extraction of complementary classifiers, multiple face models based upon hybrid Fourier features are applied. The hybrid Fourier features are extracted from different Fourier domains in different frequency bandwidths, and then each feature is individually classified by linear discriminant analysis. In addition, multiple face models are generated by plural normalized face images that have different eye distances. Finally, to combine scores from multiple complementary classifiers, a log likelihood ratio-based score fusion scheme is applied. The proposed system using the face recognition grand challenge (FRGC) experimental protocols is evaluated; FRGC is a large available data set. Experimental results on the FRGC version 2.0 data sets have shown that the proposed method shows an average of 81.49% verification rate on 2-D face images under various environmental variations such as illumination changes, expression changes, and time elapses.
Interplay Between Grip and Vision in the Monkey Medial Parietal Lobe

We aimed at understanding the relative contribution of visual information and hand shaping to the neuronal activity of medial posterior parietal area V6A, a newly added area in the monkey cortical grasping circuit. Two Macaca fascicularis performed a Reach-to-Grasp task in the dark and in the light, grasping objects of different shapes. We found that V6A contains Visual cells, activated only during grasping in the light; Motor neurons, equally activated during grasping in the dark and in the light; Visuomotor cells, differently activated while grasping in the dark and in the light. Visual, Motor, and Visuomotor neurons were moderately or highly selective during grasping, whereas they reduced their selectivity during object observation without performing grasping. The use of the same experimental design employed in the dorsolateral grasping area AIP by other authors allowed us to compare the grasp-related properties of V6A and AIP. From these data and from the literature a frame emerges with many similarities between medial grasping area V6A and lateral grasping area AIP: both areas update and control prehension, with V6A less sensitive than AIP to fine visual details of the objects to be grasped, but more involved in coordinating reaching and grasping.
YODA: Young and newcOmer Developer Assistant

Mentoring project newcomers is a crucial activity in software projects, and requires to identify people having good communication and teaching skills, other than high expertise on specific technical topics. In this demo we present Yoda (Young and newcOmer Developer Assistant), an Eclipse plugin that identifies and recommends mentors for newcomers joining a software project. Yoda mines developers' communication (e.g., mailing lists) and project versioning systems to identify mentors using an approach inspired to what ArnetMiner does when mining advisor/student relations. Then, it recommends appropriate mentors based on the specific expertise required by the newcomer. The demo shows Yoda in action, illustrating how the tool is able to identify and visualize mentoring relations in a project, and suggest appropriate mentors for a developer who is going to work on certain source code files, or on a given topic. Demo URL: http://youtu.be/4yrbYT-LAXA.
Relationship extraction from biomedical literature using Maximum Entropy based on rich features

Relation extraction is the detection and classification of interactions between named entities. Recently, a lot of studies have focused on the relation extraction from biomedical literatures. Although various approaches have been applied on this area, most methods are either pre-requires biomedical lexicons or parsing templates which are not suitable for complexities of biomedical literatures. In this paper, applying existing lexicons, we propose a Maximum Entropy method based on rich features to extract the interactions between the disease and treatment. This task is a multi-class biomedical relationship extraction. Experiment results show that the proposed method can achieve a comparable performance with the state-of-the-art generative biomedical relation extraction methods on multi-class disease-treatment interaction extraction.
The effect of jitter noise on binary input intersymbol interference channel capacity

The effect of signal dependent jitter noise on channel capacity is investigated. Upper and lower bounds on capacity are computed numerically for channels with a mix of signal dependent jitter noise and additive white Gaussian noise. The resulting bounds allow for comparison of potential coding gain for differing amounts of jitter noise and varying code rates. The comparison provides insight into the effect jitter noise has on channel capacity and shows that in some cases there is significantly more coding gain possible when the noise is predominantly jitter noise.
Design of airborne radome using Swastika-shaped metamaterial-element based FSS

This paper presents a novel Swastika-shaped metamaterial structure which exhibits metamaterial behavior (μ- and ε-negative) in distinct frequency ranges. The EM analysis of metamaterial (MTM) structure is carried out using transmission line transfer matrix method and validated with full-wave method based software package. The proposed structure is observed to exhibit bandpass frequency selective characteristics with very good transmission efficiency in the frequency range of 8.5 GHz–10.3 GHz. Further, a planar multilayered radome wall configuration is designed which consists of a thick Arlon layer embedded with Swastika-shaped MTM FSS as the middle layer backed by two thin quartz-based laminations on each side. Further, the thickness of radome wall is optimized sector wise in view of airborne radome applications.
Area optimized CMOS layouts of a 50 Gb/s low power 4:1 multiplexer

In this work, novel layouts of a 4:1 CMOS transmission gate multiplexer are presented. The proposed layouts are realized by following the design rules for 45 nm and 90 nm CMOS processes, with a supply voltage of 1.2 V. Both layouts are designed using two different routing strategies - using only one metal layer, and using two metal layers. The power dissipation and area are noted and compared in all four cases. It is observed that layouts utilizing two metal layers have reduced area but augmented cost of fabrication. The multiplexer layout, using two metal layers for routing, generates an output bit rate as high as 50 Gb/s, without any erroneous bit, in case of 90 nm technology and occupies an area of 8.91 μm2; dissipating 55.966 μW of power. The output bit rate remains same for 45 nm process, with zero bit error, a power consumption of 33.713 μW and an area of 2.45 μm2. The multiplexer continues to operate till 60 Gbps with a BER of 1/8. The areas occupied by these layouts are the lowest encountered in the authors' literature survey.