Miracle-dz/UniFAR-FTUs huggingface dataset:
A Channel Stress-Profile-Based Compact Model for Threshold Voltage Prediction of Uniaxial Strained HKMG nMOS Transistors

In this paper, a physics-based compact model for the longitudinal and transverse stress profile in the channel of an uniaxially strained bulk MOS transistor is presented. The stress in the channel of a MOS transistor is not uniform and this nonuniform stress distribution results in higher average channel stress with reduction in the gate length. The developed model accurately predicts the average channel stress for different stress liners and transistor dimensions like gate length, gate height, and spacer width. The modeled average stress is then used to calculate the strain induced threshold voltage shift in HKMG nMOS transistors for different stress liners (fixed transistor dimensions) and for different transistor dimensions (fixed stress liner). The accuracy of the model is verified by comparing the threshold voltage shift with the experimental data obtained from the transistors fabricated in the 28 nm HKMG CMOS technology.
Periocular recognition: Analysis of performance degradation factors

Among the available biometric traits such as face, iris and fingerprint, there is an active research being carried out in the direction of unconstrained biometrics. Periocular recognition has proved its effectiveness and is regarded as complementary to iris recognition. The main objectives of this paper are three-fold: 1) to announce the availability of periocular dataset, which has a variability in terms of scale change (due to camera-subject distance), pose variation and non-uniform illumination; 2) to investigate the performance of periocular recognition methods with the presence of various degradation factors; 3) propose a new initialization strategy for the definition of the periocular region-of-interest (ROI), based on the geometric mean of eye corners. Our experiments confirm that performance can be consistently improved by this initialization method, when compared to the classical technique.
Microbial and Animal Rhodopsins: Structures, Functions, and Molecular Mechanisms

Organisms of all domains of life use photoreceptor proteins to sense and respond to light. The light-sensitivity of photoreceptor proteins arises from bound chromophores such as retinal in retinylidene proteins, bilin in biliproteins, and flavin in flavoproteins. Rhodopsins found in Eukaryotes, Bacteria, and Archaea consist of opsin apoproteins and a covalently linked retinal which is employed to absorb photons for energy conversion or the initiation of intra- or intercellular signaling.1 Both functions are important for organisms to survive and to adapt to the environment. While lower organisms utilize the family of microbial rhodopsins for both purposes, animals solely use a different family of rhodopsins, a specialized subset of G-protein-coupled receptors (GPCRs). 1,2 Animal rhodopsins, for example, are employed in visual and nonvisual phototransduction, in the maintenance of the circadian clock and as photoisomerases.3,4 While sharing practically no sequence similarity, microbial and animal rhodopsins, also termed type-I and type-II rhodopsins, respectively, share a common architecture of seven transmembrane α-helices (TM) with the N- and C-terminus facing out- and inside of the cell, respectively (Figure ​(Figure11). 1,5 Retinal is attached by a Schiff base linkage to the e-amino group of a lysine side chain in the middle of TM7 (Figures ​(Figures11 and ​and2). 2). The retinal Schiff base (RSB) is protonated (RSBH+) in most cases, and changes in protonation state are integral to the signaling or transport activity of rhodopsins. Figure 1 Topology of the retinal proteins. (A) These membrane proteins contain seven α-helices (typically denoted helix A to G in microbial opsins and TM1 to 7 in the animal opsins) spanning the lipid bilayer. The N-terminus faces the outside of the cell .
Modeling and adaptation of stochastic driver-behavior model with application to car following

In this paper, we present our recently developed stochastic driver-behavior model based on Gaussian mixture model (GMM) framework. The proposed driver-behavior modeling is employed to anticipate car-following behavior in terms of pedal control operations in response to the observable driving signals, such as the own vehicle velocity and the following distance to the leading vehicle. In addition, the proposed driver modeling allows adaptation scheme to enhance the model capability to better represent particular driving characteristics of interest (i.e., individual driving style) from the observed driving data themselves. Validation and comparison of the proposed driver-behavior models on realistic car-following data of several drivers showed the promising results. Furthermore, the adapted driver models showed consistent improvement over the unadapted driver models in both short-term and long-term predictions.
Mitochondrial Dysfunction in Parkinson's Disease

Parkinson's disease (PD) is a progressive, neurodegenerative condition that has increasingly been linked with mitochondrial dysfunction and inhibition of the electron transport chain. This inhibition leads to the generation of reactive oxygen species and depletion of cellular energy levels, which can consequently cause cellular damage and death mediated by oxidative stress and excitotoxicity. A number of genes that have been shown to have links with inherited forms of PD encode mitochondrial proteins or proteins implicated in mitochondrial dysfunction, supporting the central involvement of mitochondria in PD. This involvement is corroborated by reports that environmental toxins that inhibit the mitochondrial respiratory chain have been shown to be associated with PD. This paper aims to illustrate the considerable body of evidence linking mitochondrial dysfunction with neuronal cell death in the substantia nigra pars compacta (SNpc) of PD patients and to highlight the important need for further research in this area.
Optimization of tele-immersion codes

As computational power increases, tele-immersive applications are an emerging trend. These applications make extensive demands on computational resources through their heavy use of real-time 3D reconstruction algorithms. Since computer vision developers do not necessarily have parallel programming expertise, it is important to give them the tools and capabilities to naturally express computer vision algorithms, yet retain high efficiency by exploiting modern GPU and large-scale multi-core platforms. In this paper, we describe our optimization efforts for a tele-immersion application by tuning it for GPU and multi-core platforms. Additionally, we introduce a method to obtain portability, high performance, and increase programmer productivity.
Temporal Coherence in Image-Based Visual Hull Rendering

Image-based visual hull rendering is a method for generating depth maps of a desired viewpoint from a set of silhouette images captured by calibrated cameras. It does not compute a view-independent data representation, such as a voxel grid or a mesh, which makes it particularly efficient for dynamic scenes. When users are captured, the scene is usually dynamic, but does not change rapidly because people move smoothly within a subsecond time frame. Exploiting this temporal coherence to avoid redundant calculations is challenging because of the lack of an explicit data representation. This paper analyzes the image-based visual hull algorithm to find intermediate information that stays valid over time and is, therefore, worth to make explicit. We then derive methods that exploit this information to improve the rendering performance. Our methods reduce the execution time by up to 25 percent. When the user's motions are very slow, reductions of up to 50 percent are achieved.
Targeting mTOR for the treatment of AML. New agents and new directions

Despite recent advances in the field, the treatment of patients with acute myeloid leukemia (AML) remains challenging and difficult. Although chemotherapeutic agents induce remissions in a large number of patients, many of them eventually relapse and die. A major goal for the development of new approaches for the treatment of AML is to enhance the antileukemic effects of standard chemotherapeutics and to design effective combinations targeting non-overlapping cellular pathways. The PI3K/Akt/mTOR signaling pathway plays a critical role in survival and growth of malignant cells and its targeting has been the focus of extensive work and research efforts over the last two decades. It now appears possible that a major limitation of the first generation of mTOR inhibitors can be overcome by a new class of catalytic inhibitors of mTOR. There is emerging evidence that such compounds target both TORC1 and TORC2 and elicit much more potent responses against early leukemic precursors in vitro. In addition, recent studies have shown that combinations of such agents with cytarabine result in enhanced antileukemic responses in vitro, raising the prospect and potential of use of these agents in combination regimens for the treatment of AML.
Improving control precision and motion adaptiveness for surgical robot with recurrent neural network

Surgical robot research is driven by the desire of improving surgical outcomes. This paper proposed a Recurrent Neural Network based controller to address two problems: 1) improving control precision, 2) increasing adaptiveness for robot motion (explained in Section I). RNN was adopted in this work mainly because 1) the problem formulation naturally matches RNN structure, 2) RNN has advantages as an biologically inspired method. The proposed method was explained in detail and analysis shows that the proposed method is able to dynamically regulate outputs to increase the adaptiveness and the control precision. This paper uses Raven II surgical robot as an example to show the application of the proposed method, and the numeral simulation results from the proposed method and three other controllers show that the proposed method has improved precision, improved high robustness against noise and increased movement smoothness, and it keeps the manipulator links as far away as possible from physical boundaries, which potentially increases surgical safety and leads to improved surgical outcomes.
Cap-Independent Translational Enhancement of Turnip Crinkle Virus Genomic and Subgenomic RNAs

ABSTRACT The presence of translational control elements and cap structures has not been carefully investigated for members of theCarmovirus genus, a group of small icosahedral plant viruses with positive-sense RNA genomes. In this study, we examined both the 5′ and 3′ untranslated regions (UTRs) of the turnip crinkle carmovirus (TCV) genomic RNA (4 kb) as well as the 5′ UTR of the coat protein subgenomic RNA (1.45 kb) for their roles in translational regulation. All three UTRs enhanced translation of the firefly luciferase reporter gene to different extents. Optimal translational efficiency was achieved when mRNAs contained both 5′ and 3′ UTRs. The synergistic effect due to the 5′-3′ cooperation was at least fourfold greater than the sum of the contributions of the individual UTRs. The observed translational enhancement of TCV mRNAs occurred in a cap-independent manner, a result consistent with the demonstration, using a cap-specific antibody, that the 5′ end of the TCV genomic RNA was uncapped. Finally, the translational enhancement activity within the 5′ UTR of 1.45-kb subgenomic RNA was shown to be important for the translation of coat protein in protoplasts and for virulent infection in Arabidopsis plants.
Playing vs. Nonplaying Aerobic Training in Tennis: Physiological and Performance Outcomes

This study compared the effects of playing and nonplaying high intensity intermittent training (HIIT) on physiological demands and tennis stroke performance in young tennis players. Eleven competitive male players (13.4 ± 1.3 years) completed both a playing and nonplaying HIIT session of equal distance, in random order. During each HIIT session, heart rate (HR), blood lactate, and ratings of perceived exertion (RPE) were monitored. Before and after each HIIT session, the velocity and accuracy of the serve, and forehand and backhand strokes were evaluated. The results demonstrated that both HIIT sessions achieved an average HR greater than 90% HRmax. The physiological demands (average HR) were greater during the playing session compared to the nonplaying session, despite similar lactate concentrations and a lower RPE. The results also indicate a reduction in shot velocity after both HIIT sessions; however, the playing HIIT session had a more deleterious effect on stroke accuracy. These findings suggest that 1) both HIIT sessions may be sufficient to develop maximal aerobic power, 2) playing HIIT sessions provide a greater physiological demand with a lower RPE, and 3) playing HIIT has a greater deleterious effect on stroke performance, and in particular on the accuracy component of the ground stroke performance, and should be incorporated appropriately into a periodization program in young male tennis players.
Exploring user engagement in online news interactions

This paper describes a qualitative study of online news reading and browsing. Thirty people participated in a quasi-experimental study in which they were asked to browse a news website and select three stories to discuss at a social gathering. Semi-structured interviews were conducted post-task to understand participants' perceptions of what makes online news reading and browsing engaging or non-engaging. Findings as presented within the experience-based framework of user engagement and demonstrate the complexity of users' interactions with information content and systems in online news environments. This study extends the model of user engagement and contributes new insights into user's experience in casual-leisure settings, such as online news, which has implications for other information domains.
Optimization of the replica molding process of PDMS using pennate diatoms

Biomimetic fabrication of nanostructured materials has recently attracted the attention of researchers as a cost-effective and easily applicable method of nanotexturing. Different techniques and materials have been used in order to replicate natural patterns, among which polydimethylsiloxane (PDMS Sylgard 184®) was recently used to replicate the micro- and nanoscale patterns from centric diatoms. In this paper, we test the reproducibility and precision of this approach using various morphologically different diatom species trying to optimize the molding parameters. The optimization process is focused on immobilization of diatoms on the glass support, which serves as a master for templating, as well as on the parameters of PDMS fabrication such as the ratio of the curing agent and elastomer, use of vacuum, curing time and temperature. The results indicate that higher ratios of curing agent and elastomer, longer curing time and lower temperature are the most favorable conditions to obtain negative diatom replicas of good quality with features of 50 nm. Although this method can give very precise results producing high-resolution molds with all micro- and nanostructures replicated, we revealed some limitations regarding the size and morphology of the species used. These results indicate that large round and flat diatom species seem to be more suitable for the cast molding.
Importance of Eco-Friendly OLED Lighting

The importance of artificial light has long been recognized as it extends the day. Copious corporations and academic institutions are investing cosmic treasures in tracking down the advanced artificial lighting applications with a vision towards energy efficient and eco-friendly solid state lighting. In this regard, organic light-emitting diodes (OLEDs) are going to change the human lifestyle, by offering a promising avenue to develop future energy saving solid-state lighting sources because of their intrinsic characteristics such as low driving voltage, high resolution, high brightness, large viewing angle, large color gamut, high contrast, less weight and size, efficiency etc., there by dictating their ability to reach the pinnacle in the field of flat panel displays and solid state lighting sources. With the goal towards future application, many design strategies like synthesis of novel materials, well judged anatomy of device configuration, development of refined and low cost fabrication techniques have been put forward to achieve high efficiency, good color stability and quality lighting. Practical applications, which enrich the ideas of the specialists in this field to develop new routes for future research development of OLEDs are enumerated and illustrated by specific examples. This chapter also integrates the novel approaches for energy efficient and eco-friendly solid state lighting as well as the limitations and global haphazards of currently used lighting systems. The current state of the art, ongoing challenges and future perspectives of this research frontier to reduce the driving voltage, minimization of degradation issues, enhance their life time are illustrated. Review on the status and future outlook of these OLEDs strongly reveals their emergence in the next few years.
Onset of ductility and brittleness in silicon nanowires mediated by dislocation nucleation

Most studies show that materials at the nano-scale have different mechanical properties than in the bulk state. Semiconductors like silicon and germanium are brittle in the bulk state, but when their size is reduced to the nano-scale they appear to be ductile. Under tensile loading, we performed molecular dynamics simulations on silicon crystalline nanowires of different lengths. We present the details of the obtained mechanisms that led to ductility and brittleness. In the case of ductility, dislocation nucleation was observed with a signature of surface step formation on the surface and in the case of brittleness a cavity was formed after the distinct formation of a wedge-like shape on the surface. Interestingly, a common mechanism taking place behind ductility and brittleness is dislocation nucleation. We believe that the observed mechanisms reveal interesting information for understanding and explaining the size dependent brittle to ductile transition.
On Path diagrams and Stirling permutations

Any ordinary permutation $\tau\in S_n$ of size $n$, written as a word $\tau=\tau_1. \tau_n$, can be locally classified according to the relative order of $\tau_j$ to its neighbours. This gives rise to four local order types called peaks (or maxima), valleys (or minima), double rises and double falls. By the correspondence between permutations and binary increasing trees the classification of permutations according to local types corresponds to a classification of binary increasing trees according to nodes types. Moreover, by the bijection between permutations, binary increasing trees and suitably defined path diagrams one can obtain continued fraction representations of the ordinary generating function of local types. The aim of this work is to introduce the notion of local types in $k$-Stirling permutations, to relate these local types with nodes types in $(k+1)$-ary increasing trees and to obtain a bijection with suitably defined path diagrams. Furthermore, we also present a path diagram representation of a related tree family called plane-oriented recursive trees, and the discuss the relation with ternary increasing trees.
Getting the balance right: Established and emerging therapies for major depressive disorders

Major depressive disorder (MDD) is a common and serious illness of our times, associated with monoamine deficiency in the brain. Moreover, increased levels of cortisol, possibly caused by stress, may be related to depression. In the treatment of MDD, the use of older antidepressants such as monoamine oxidase inhibitors and tricyclic antidepressants is decreasing rapidly, mainly due to their adverse effect profiles. In contrast, the use of serotonin reuptake inhibitors and newer antidepressants, which have dual modes of action such as inhibition of the serotonin and noradrenaline or dopamine reuptake, is increasing. Novel antidepressants have additive modes of action such as agomelatine, a potent agonist of melatonin receptors. Drugs in development for treatment of MDD include triple reuptake inhibitors, dual-acting serotonin reuptake inhibitors and histamine antagonists, and many more. Newer antidepressants have similar efficacy and in general good tolerability profiles. Nevertheless, compliance with treatment for MDD is poor and may contribute to treatment failure. Despite the broad spectrum of available antidepressants, there are still at least 30% of depressive patients who do not benefit from treatment. Therefore, new approaches in drug development are necessary and, according to current research developments, the future of antidepressant treatment may be promising.
The Protective Effect of Alpha 7 Nicotinic Acetylcholine Receptor Activation on Critical Illness and Its Mechanism

Critical illnesses and injuries are recognized as major threats to human health, and they are usually accompanied by uncontrolled inflammation and dysfunction of immune response. The alpha 7 nicotinic acetylcholine receptor (α7nAchR), which is a primary receptor of cholinergic anti-inflammatory pathway (CAP), exhibits great benefits for critical ill conditions. It is composed of 5 identical α7 subunits that form a central pore with high permeability for calcium. This putative structure is closely associated with its functional states. Activated α7nAChR exhibits extensive anti-inflammatory and immune modulatory reactions, including lowered pro-inflammatory cytokines levels, decreased expressions of chemokines as well as adhesion molecules, and altered differentiation and activation of immune cells, which are important in maintaining immune homeostasis. Well understanding of the effects and mechanisms of α7nAChR will be of great value in exploring effective targets for treating critical diseases.
Damping Optimization on Magnetorheological Grease Isolator of Floating Slab Track

The bearings with variable damping characteristics are very important for floating slab track (FST) to restrain vibration in low frequency. A model with single degree of freedom of FST is built. Based on analyzing the characteristic of the magnetorheological grease (MRG) materials, a MRG isolator is proposed to instead of passive bearings of FST. For attenuating the vertical vibration, the method of adaptive particle swarm optimization (PSO) with variable inertial parameter is proposed to adjust the damping. The results simulated in MATLAB show that MRG isolators with the adaptive PSO algorithm can optimize damping at different excitations effectively and conspicuously decrease the low frequency vibration energy of FST.