Miracle-dz/UniFAR-FTUs huggingface dataset:
Nanostructuring of Biosensing Electrodes with Nanodiamonds for Antibody Immobilization

While chemical vapor deposition of diamond films is currently cost prohibitive for biosensor construction, in this paper, we show that sonication-assisted nanostructuring of biosensing electrodes with nanodiamonds (NDs) allows harnessing the hydrolytic stability of the diamond biofunctionalization chemistry for real-time continuous sensing, while improving the detector sensitivity and stability. We find that the higher surface coverages were important for improved bacterial capture and can be achieved through proper choice of solvent, ND concentration, and seeding time. A mixture of methanol and dimethyl sulfoxide provides the highest surface coverage (33.6 ± 3.4%) for the NDs with positive zeta-potential, compared to dilutions of dimethyl sulfoxide with acetone, ethanol, isopropyl alcohol, or water. Through impedance spectroscopy of ND-seeded interdigitated electrodes (IDEs), we found that the ND seeds serve as electrically conductive islands only a few nanometers apart. Also we show that the seeded NDs are amply hydrogenated to be decorated with antibodies using the UV-alkene chemistry, and higher bacterial captures can be obtained compared to our previously reported work with diamond films. When sensing bacteria from 106 cfu/mL E. coliO157:H7, the resistance to charge transfer at the IDEs decreased by ∼38.8%, which is nearly 1.5 times better than that reported previously using redox probes. Further in the case of 108 cfu/mL E. coliO157:H7, the charge transfer resistance changed by ∼46%, which is similar to the magnitude of improvement reported using magnetic nanoparticle-based sample enrichment prior to impedance detection. Thus ND seeding allows impedance biosensing in low conductivity solutions with competitive sensitivity.
Correlated Tag Learning in Topic Model

It is natural to expect that the documents in a corpus will be correlated, and these correlations are reflected by not only the words but also the observed tags in each document. Most previous works model this type of corpus, which are called the semi-structured corpus, without considering the correlations among the tags. In this work, we develop a Correlated Tag Learning (CTL) model for semi-structured corpora based on the topic model to enable the construction of the correlation graph among tags via a logistic normal participation process. For the inference of the CTL model, we devise a variational inference algorithm to approximate the posterior. In experiments, we visualize the tag correlation graph generated by the CTL model on the DBLP corpus and for the tasks of document retrieval and classification, the correlation graph among tags is helpful to improve the generalization performance compared with the state-of-the-art baselines.
Energy aware multi-path and multi-SPEED routing protocol in wireless sensor networks

Wireless sensor networks are limited in energy. Any routing protocol used in wireless sensor networks should take into consideration the time sensitive nature of the traffic in such networks, along with the amount of energy left for each sensor. In this paper we present an energy aware packet delivery mechanism for probabilistic Quality of Service (QoS) guarantee in wireless sensor networks. Each node takes routing decisions based on geographic progress towards the destination sink, required end-to-end total reaching probability, delay at the candidate forwarding node and residual energy. The simulation results demonstrate that the proposed protocol effectively improves the energy usage efficiency of the sensor nodes, maximizing the lifetime of the entire sensor network, while keeping guaranteed QoS.
Computationally Sound Compositional Logic for Security Protocols

We have been developing a cryptographically sound formal logic for proving protocol security properties without explicitly reasoning about probability, asymptotic complexity, or the actions of a malicious attacker. The approach rests on a probabilistic, polynomial-time semantics for a protocol security logic that was originally developed using nondeterministic symbolic semantics. This workshop presentation will discuss ways in which the computational semantics lead to different reasoning methods and report our progress to date in several directions. One significant difference between the symbolic and computational settings results from the computational difference between efficiently recognizing and efficiently producing a value. Among the more recent developments are a compositional method for proving cryptographically sound properties of key exchange protocols, and some work on secrecy properties that illustrates the computational interpretation of inductive properties of protocol roles.
Generic and Polymorphic Graph Transformations-Supporting the Definition of Visual Languages

In this paper we present a graph transformation based approa ch f r the specification of reusable and extensible visual language de finitions. It is based on the graph transformation language and environment PROGRES. We will see that PROGRES in its current form is not yet well-pr epared for the construction of reusable and extensible specification f ragments despite of the fact that a powerful package concept has been added rat her recently. Therefore, we will propose some additional extensions whic h combine the functional programming language concept of parametric pol ym rphism with the object-oriented concept of generic classes.
Development of a physiological signals enhanced teleoperation strategy

In this paper, we have developed a teleoperation method with novel features, such that the human operator could manipulate the telerobot using both physical and physiological means. Physiological studies have shown that our central neural system (CNS) is able to adapt muscle force, stiffness and damping to perform different tasks under various environments. However, there has been very little research in the robotics communities to incorporate human motor skills of muscle force, stiffness and damping adaptation into teleoperation. As a matter of fact, muscle activities regulated by CNS can be represented by surface electromyography (sEMG) measured by electrodes attached on the skin of human limbs. Therefore, sEMG based teleimpedance control has been recently developed to transfer the variable stiffness from human operator to a robot for flexible manipulation [1], [2], [3]. In this paper, we have developed a personalised variable gain control, whereas the control gain is set according to muscle activation extracted from sEMG signals, and force feedback is employed such that human operator is able to sense the circumstance in a haptic manner and to adapt muscle contraction subconsciously as if they are directly interacting with the environment. The proposed method enables an operator to adjust tracking speed and stiffness of the telerobot easily on the fly, and thus greatly improves a user's manipulation ability for delicate tasks, especially in the presence of motion amplification and varying payload on the telerobot. The effectiveness of the proposed approach has been tested and confirmed by comparative experiments, in which a 7-DOF (degrees of freedom) robotic arm of Baxter® robot is employed.
NEMO5: Predicting MoS2 heterojunctions

Molybdenum disulfide (MoS2) is a promising 2D material since it has a finite band gap, and its electronic band structure depends on the layer thickness. The tunability of the gate voltage on band alignment of different MoS2 layers is analyzed. For this purpose, the multipurpose nanodevice simulation tool NEMO5 was altered by several new features: electronic bandstructure calculations in maximally localized Wannier function (MLWF) representation and self-consistent charge calculations with subatomic electrostatic resolution.
Development of an IP-Free Biotechnology Platform for Constitutive Production of HPV16 L1 Capsid Protein Using the Pichia pastoris PGK1 Promoter

The human papillomavirus (HPV) L1 major capsid protein, which forms the basis of the currently available vaccines against cervical cancer, self-assembles into virus-like particles (VLPs) when expressed heterologously. We report the development of a biotechnology platform for HPV16 L1 protein expression based on the constitutive PGK1 promoter (PPGK1) from the methylotrophic yeast Pichia pastoris. The L1 gene was cloned under regulation of PPGK1 into pPGKΔ3 expression vector to achieve intracellular expression. In parallel, secretion of the L1 protein was obtained through the use of an alternative vector called pPGKΔ3α, in which a codon optimized α-factor signal sequence was inserted. We devised a work-flow based on the detection of the L1 protein by dot blot, colony blot, and western blot to classify the positive clones. Finally, intracellular HPV VLPs assembly was demonstrated for the first time in yeast cells. This study opens up perspectives for the establishment of an innovative platform for the production of HPV VLPs or other viral antigens for vaccination purposes, based on constitutive expression in P. pastoris.
HDR image noise estimation for denoising tone mapped images

Tone mapping operators are designed to compress the dynamic range of high dynamic range (HDR) images while preserving the perceived image brightness, but they often enhance image noise in the process, specially in low-light conditions. We propose a method for reducing noise in images created by any tone mapping operator. Our approach leverages the noise distribution of the HDR image to guide the range kernel of a cross bilateral filter that is used to denoise the tone mapped image. When the noise distribution is unknown, we use a new method to automatically estimate it assuming that the HDR image was produced as an average of multiple exposures taken in RAW or JPEG compressed format. Our method performs quantitatively better than existing denoising methods applied on either the original HDR or the tone-mapped images directly, and a user study confirms that it produces visually preferable results.
Limited Stability of Microcystins in Oligopeptide Compositions of Microcystis aeruginosa (Cyanobacteria): Implications in the Definition of Chemotypes

The occurrence of diverse oligopeptides in cyanobacteria, including the cyanotoxins microcystins, has been recently used to classify individual clones into sub-specific oligopeptide chemotypes, whose composition and dynamics modulate microcystin concentrations in cyanobacterial blooms. Cyanobacterial chemotyping allows the study of the ecology of chemotypical subpopulations, which have been shown to possess dissimilar ecological traits. However, the stability of chemotypes under changing abiotic conditions is usually assumed and has not been assessed in detail. We monitored oligopeptide patterns of three strains of Microcystis aeruginosa under different nutrient and light conditions. MALDI-TOF MS revealed alterations in the microcystins signatures under N and P poor conditions and high light intensities (150 and 400 μmol photons m−2s−1). Variations in the general oligopeptide composition were caused by a gradual disappearance of microcystins with low relative intensity signals from the fingerprint. The extent of such variations seems to be closely related to physiological stress caused by treatments. Under identical clonal compositions, alterations in the oligopeptide fingerprint may be misinterpreted as apparent shifts in chemotype succession. We discuss the nature of such variations, as well as the consequent implications in the use of cyanobacterial chemotyping in studies at the subpopulation level and propose new guidance for the definition of chemotypes as a consistent subpopulation marker.
Global shape processing in human visual cortex

The research described in this thesis used a combination of neuroimaging, brain stimulation and psychophysical methods to explore the representation of global shape in human visual cortex. Global shape processing mechanisms integrate over local orientation information to form an abstracted representation of an object’s shape; an important processing step for accurate object recognition in the complex visual scenes of everyday life. This thesis presents evidence for a global shape processing stream in human lateral occipital cortex comprising brain areas LO1, LO2 and object-selective lateral occipital complex (LOC). First, brain responses to shape were shown to be more global and less dependent on task in LO2 compared to LO1. Second, a global shape aftereffect was used to demonstrate that global representations of object shape are formed by a series of integrative mechanisms, where each successive mechanism integrates over outputs from the preceding mechanisms to form increasingly global shape representations. Third, brain stimulation was used to determine whether area LO2 is causally important for global shape adaptation and shape discriminations, however brain stimulation had no effect on shape perceptions meaning conclusions about a causal role for LO2 in global shape processing could not be drawn. Finally, neural tuning to radial frequency, one possible dimension of a representational shape space, was modelled using Gaussian neural modelling. Tuning towards radial frequencies that are processed globally was localised to lateral occipital cortex, and shifted from local to global frequencies in LO2 and LOC. Overall, this thesis provides novel contributions to the current understanding of how the analysis of an object’s shape facilitates object recognition, and the nature and locus of global shape representations in the human brain.
Surface wave tomography: global membrane waves and adjoint methods

SUMMARY We implement the wave equation on a spherical membrane, with a finite-difference algorithm that accounts for finite-frequency effects in the smooth-Earth approximation, and use the resulting ‘membrane waves’ as an analogue for surface wave propagation in the Earth. In this formulation, we derive fully numerical 2-D sensitivity kernels for phase anomaly measurements, and employ them in a preliminary tomographic application. To speed up the computation of kernels, so that it is practical to formulate the inverse problem also with respect to a laterally heterogeneous starting model, we calculate them via the adjoint method, based on backpropagation, and parallelize our software on a Linux cluster. Our method is a step forward from ray theory, as it surpasses the inherent infinite-frequency approximation. It differs from analytical Born theory in that it does not involve a far-field approximation, and accounts, in principle, for non-linear effects like multiple scattering and wave front healing. It is much cheaper than the more accurate, fully 3-D numerical solution of the Earth’s equations of motion, which has not yet been applied to large-scale tomography. Our tomographic results and trade-off analysis are compatible with those found in the ray- and analytical-Born-theory approaches.
Mental rotation performance in soccer players and gymnasts in an object-based mental rotation task

In this study, the effect of motor expertise on an object-based mental rotation task was investigated. 60 males and 60 females (40 soccer players, 40 gymnasts, and 40 non-athletes, equivalent males and females in each group) solved a psychometric mental rotation task with both cube and human figures. The results revealed that all participants had a higher mental rotation accuracy for human figures compared to cubed figures, that the gender difference was reduced with human figures, and that gymnasts demonstrated a better mental rotation performance than non-athletes. The results are discussed against the background of the existing literature on motor experts, mental rotation performance as well as the importance of the testing situation and the test construction.
AN ENERGY-EFFICIENT MAXIMIZATION BASED PATH SELECTION AND RESOURCE ALLOCATION SCHEME IN OFDMA-BASED TWO-HOP RELAY CELLULAR NETWORKS

In this paper, we investigate the energy efficiency problem in downlink transmission of the OFDMA-based two-hop relay cellular networks. Most of the researches on energy efficiency focus on the transmission in traditional cellular system, especially for the uplink transmission. Our objective is to maximize the system energy efficiency for the downlink transmission of the two-hop relay cellular system. We consider both the circuit power and transmission power consumption, and propose a two-step suboptimal path selection and subchannel allocation scheme to maximize the system energy efficiency. The simulation results show that our proposed scheme have good performance in energy efficiency.
Adaptation to Vocal Expressions Reveals Multistep Perception of Auditory Emotion

The human voice carries speech as well as important nonlinguistic signals that influence our social interactions. Among these cues that impact our behavior and communication with other people is the perceived emotional state of the speaker. A theoretical framework for the neural processing stages of emotional prosody has suggested that auditory emotion is perceived in multiple steps (Schirmer and Kotz, 2006) involving low-level auditory analysis and integration of the acoustic information followed by higher-level cognition. Empirical evidence for this multistep processing chain, however, is still sparse. We examined this question using functional magnetic resonance imaging and a continuous carry-over design (Aguirre, 2007) to measure brain activity while volunteers listened to non-speech-affective vocalizations morphed on a continuum between anger and fear. Analyses dissociated neuronal adaptation effects induced by similarity in perceived emotional content between consecutive stimuli from those induced by their acoustic similarity. We found that bilateral voice-sensitive auditory regions as well as right amygdala coded the physical difference between consecutive stimuli. In contrast, activity in bilateral anterior insulae, medial superior frontal cortex, precuneus, and subcortical regions such as bilateral hippocampi depended predominantly on the perceptual difference between morphs. Our results suggest that the processing of vocal affect recognition is a multistep process involving largely distinct neural networks. Amygdala and auditory areas predominantly code emotion-related acoustic information while more anterior insular and prefrontal regions respond to the abstract, cognitive representation of vocal affect.
Dropouts in Swiss vocational education and the effect of training companies’ trainee selection methods

Abstract In the Swiss vocational education system, which is often called a ‘Dual System’, trainees enter into an apprenticeship contract with a training company. On average, 25% of those contracts are terminated prematurely (PCT). This article examines the relationship between training companies’ selection methods and PCTs. The investigation is based on a quantitative study with a cross-sectional design and on qualitative interviews. Trainers and operations managers (N = 335) of Swiss training companies for cooks and painters were surveyed. Half of the companies have been affected by a PCT in the past and the other half have not. The findings indicate that a certain amount of the explained variance between companies with and without reported PCTs can be explained by the companies’ selection process. Companies that were affected by a PCT use a job interview and a company visit significantly less often in their selection process than companies without a PCT.
Differences in the Number of Intrinsically Disordered Regions between Yeast Duplicated Proteins, and Their Relationship with Functional Divergence

Background Intrinsically disordered regions are enriched in short interaction motifs that play a critical role in many protein-protein interactions. Since new short interaction motifs may easily evolve, they have the potential to rapidly change protein interactions and cellular signaling. In this work we examined the dynamics of gain and loss of intrinsically disordered regions in duplicated proteins to inspect if changes after genome duplication can create functional divergence. For this purpose we used Saccharomyces cerevisiae and the outgroup species Lachancea kluyveri. Principal Findings We find that genes duplicated as part of a genome duplication (ohnologs) are significantly more intrinsically disordered than singletons (p<2.2e-16, Wilcoxon), reflecting a preference for retaining intrinsically disordered proteins in duplicate. In addition, there have been marked changes in the extent of intrinsic disorder following duplication. A large number of duplicated genes have more intrinsic disorder than their L. kluyveri ortholog (29% for duplicates versus 25% for singletons) and an even greater number have less intrinsic disorder than the L. kluyveri ortholog (37% for duplicates versus 25% for singletons). Finally, we show that the number of physical interactions is significantly greater in the more intrinsically disordered ohnolog of a pair (p = 0.003, Wilcoxon). Conclusion This work shows that intrinsic disorder gain and loss in a protein is a mechanism by which a genome can also diverge and innovate. The higher number of interactors for proteins that have gained intrinsic disorder compared with their duplicates may reflect the acquisition of new interaction partners or new functional roles.
Calculation and Visualization of Range of Motion of Hip Joint from MRI

Femoro-Acetabular Impingement (FAI) is a hip joint disease which affects and impairs the range of hip motion during performing activities of daily living, jogging, walking, or climbing stairs due to bony abnormalities of the joint. In this research we introduce a motion simulation and visualization system which helps surgeons to analyze range of hip motions as well as to have a better communication with patients. We evaluate the maximum motion that the joint can achieve from its bony structure if the muscle and other connective tissues are perfectly trained. These goals are achieved by presenting three dimensional (3D) visualizations of motions envelopes by examining maximum possible rotation of the digital hip bones through computer-based simulation. Our computer-based simulation system estimates, analyzes and visualizes the maximum hip range of motion (ROM) for the constructed 3D bone models (femur and pelvis) that are extracted from Magnetic Resonance Images (MRI) after segmenting the bones. These tasks are accomplished first by calculating Hip Joint Center (HJC) which is center of rotation of femoral head followed by simulating hip motions with examining impingement between the femur and the acetabulum using a collision detection system. Six primary plane motions (flexion extension, abduction adduction and internal external rotation) as well as various combinations of these motions and six successive movements are simulated and analyzed along with 3D visualization of estimated range of these motions. Our system by 3D visualization of motions envelopes will provide a platform to understand quicker and better the effect of bony morphology of the hip joint on the possible ROM.