Miracle-dz/UniFAR-FTUs huggingface dataset:
Extremely Low-Threshold Current Density InGaAs/AlGaAs Quantum-Well Lasers on Silicon

An InGaAs/AlGaAs quantum-well laser structure was grown on a silicon substrate by adopting a three-step grown thin (1.8 μm) and simple buffer layer. The whole structure was grown by metalorganic chemical vapor deposition. The material quality was characterized by transmission electron microscopy, photoluminescence spectra, and electrochemical capacitance-voltage profiler. It shows that the threading dislocation density and interface roughness are effectively reduced, and the active region's optical properties grown on a silicon substrate are comparable to that grown on a GaAs substrate. Broad stripe lasers have also been fabricated. The cavity length and stripe width are 1 mm and 15 μm, respectively. An extremely low-threshold current density of 313 A/cm2 has been achieved under pulsed condition at room temperature. Meanwhile, the laser can operate under continuous wave condition at the temperature of 240 K. The above results make us more confident for realizing better performance of Si-based III-V semiconductor lasers by further improvement of the material growth method.
Annotation de vidéos par paires rares de concepts

La detection d'un concept visuel dans les videos est une tâche difficile, specialement pour les concepts rares ou pour ceux dont il est complique de decrire visuellement. Cette question devient encore plus difficile quand on veut detecter une paire de concepts au lieu d'un seul. En effet, plus le nombre de concepts presents dans une scene video est grand, plus cette derniere est complexe visuellement, et donc la difficulte de lui trouver une description specifique s'accroit encore plus. Deux directions principales peuvent eˆtre suivies pour tacler ce probleme: 1) detecter chaque concept separement et combiner ensuite les predictions de leurs detecteurs correspondants d'une maniere similaire a celle utilisee souvent en recherche d'information, ou 2) considerer le couple comme un nouveau concept et generer un classifieur supervise pour ce nouveau concept en inferant de nouvelles annotations a partir de celles des deux concepts formant la paire. Chacune de ces approches a ses avantages et ses inconvenients. Le probleme majeur de la deuxieme methode est la necessite d'un ensemble de donnees annotees, surtout pour la classe positive. S'il y a des concepts rares, cette rarete s'accroit encore plus pour les paires formees de leurs combinaisons. D'une autre part, il peut y avoir deux concepts assez frequents mais il est tres rare qu'ils occurrent conjointement dans un meˆme document. Certains travaux de l'etat de l'art ont propose de palier ce probleme en recoltant des exemples representatifs des classes etudiees du web, mais cette tâche reste couˆteuse en temps et argent. Nous avons compare les deux types d'approches sans recourir a des ressources externes. Notre evaluation a ete realisee dans le cadre de la sous-tâche "detection de paire de concepts" de la tâche d'indexation semantique (SIN) de TRECVID 2013, et les resultats ont revele que pour le cas des videos, si on n'utilise pas de ressources d'information externes, les approches qui fusionnent les resultats des deux detecteurs sont plus performantes, contrairement a ce qui a ete montre dans des travaux anterieurs pour le cas des images fixes. La performance des methodes decrites depasse celle du meilleur resultat officiel de la campagne d'evaluation precedemment citee, de 9% en termes de gain relatif sur la precision moyenne (MAP).
Path Planning in an Environment with Static and Dynamic Obstacles Using Genetic Algorithm: A Simplified Search Space Approach

This paper discusses a novel step by step path planning method which uses genetic algorithm (GA) to find the feasible and suitable paths in an environment with static and dynamic obstacles. To increase the speed of calculations, dimension of the search space is reduced by developing a new method to represent the environment. This representation method is based on detecting the corners of circumferential polygons of all obstacles as representatives of the environment. Each individual (or path) is a subsequence of these points including the start and destination points as the first and last genes in the sequence. Thus, each individual will be of a variable length. If an individual represents a path which passes over some obstacles, it will be unfeasible; otherwise it represents a feasible path. To produce new generations, four evolutionary operators are defined. The goal is to find a short feasible path, which clearly is not unique. In addition, using a step by step path planning approach and updating the representation of the environment at each step will result in a robust performance of the algorithm in two dimensional (2D) static and dynamic environments.
Alternative Splicing at C Terminus of CaV1.4 Calcium Channel Modulates Calcium-dependent Inactivation, Activation Potential, and Current Density

Background: Alternative splicing diversifies calcium channel structure to change channel properties. Results: Extensive C-terminal alternative splicing generates channels differing in activation potential and voltage- and calcium-dependent inactivation properties. Conclusion: Diversification of channel function through altered structure is fine-tuned by alternative splicing. Significance: CaV1.4 C-terminal splice variations recapitulate some aspects of native photoreceptor calcium currents. The CaV1.4 voltage-gated calcium channel is predominantly expressed in the retina, and mutations to this channel have been associated with human congenital stationary night blindness type-2. The L-type CaV1.4 channel displays distinct properties such as absence of calcium-dependent inactivation (CDI) and slow voltage-dependent inactivation (VDI) due to the presence of an autoinhibitory domain (inhibitor of CDI) in the distal C terminus. We hypothesized that native CaV1.4 is subjected to extensive alternative splicing, much like the other voltage-gated calcium channels, and employed the transcript scanning method to identify alternatively spliced exons within the CaV1.4 transcripts isolated from the human retina. In total, we identified 19 alternative splice variations, of which 16 variations have not been previously reported. Characterization of the C terminus alternatively spliced exons using whole-cell patch clamp electrophysiology revealed a splice variant that exhibits robust CDI. This splice variant arose from the splicing of a novel alternate exon (43*) that can be found in 13.6% of the full-length transcripts screened. Inclusion of exon 43* inserts a stop codon that truncates half the C terminus. The CaV1.4 43* channel exhibited robust CDI, a larger current density, a hyperpolarized shift in activation potential by ∼10 mV, and a slower VDI. Through deletional experiments, we showed that the inhibitor of CDI was responsible for modulating channel activation and VDI, in addition to CDI. Calcium currents in the photoreceptors were observed to exhibit CDI and are more negatively activated as compared with currents elicited from heterologously expressed full-length CaV1.4. Naturally occurring alternative splice variants may in part contribute to the properties of the native CaV1.4 channels.
Peer-to-Peer Human-Robot Interaction for Space Exploration

NASA has embarked on a long-term program to develop human-robot systems for sustained, affordable space exploration. To support this mission, we are working to improve human-robot interaction and performance on planetary surfaces. Rather than building robots that function as glorified tools, our focus is to enable humans and robots to work as partners and peers. In this paper. we describe our approach, which includes contextual dialogue, cognitive modeling, and metrics-based field testing.
Amphibian neural crest cell migration on purified extracellular matrix components: a chondroitin sulfate proteoglycan inhibits locomotion on fibronectin substrates

The ability of purified extracellular matrix components to promote the initial migration of amphibian neural crest (NC) cells was quantitatively investigated in vitro. NC cells migrated avidly on fibronectin (FN), displaying progressively more extensive dispersion at increasing amounts of material incorporated in the substrate. In contrast, dispersion on laminin substrates was optimal at low protein concentrations but strongly reduced at high concentrations. NC cells were unable to migrate on substrates containing a high molecular mass chondroitin sulfate proteoglycan (ChSP). When proteolytic peptides, representing isolated functional domains of the FN molecule, were tested as potential migration substrates, the cell binding region of the molecule (105 kD) was found to be as active as the intact FN. A 31- kD heparin-binding fragment also stimulated NC cell migration, whereas NC cells dispersed to a markedly lower extent on the isolated collagen- binding domain (40 kD), or the latter domain linked to the NH2-terminal part of the FN molecule. Migration on the intact FN was partially inhibited by antibodies directed against the 105- and 31-kD fragments, respectively; dispersion was further decreased when the antibodies were used in combination. Addition of the ChSP to the culture medium dramatically perturbed NC cell migration on substrates of FN, as well as of 105- or 31-kD fragments. However, preincubation of isolated cells or substrates with ChSP followed by washing did not affect NC cell movement. The use of substrates consisting of different relative amounts of ChSP and the 105-kD peptide revealed that ChSP counteracted the motility-promoting activity of the 105-kD FN fragment in a concentration-dependent manner also when bound to the substrate. Our results indicate that NC cell migration on FN involves two separate domains of the molecule, and that ChSP can modulate the migratory behavior of NC cells moving along FN-rich pathways and may therefore influence directionally and subsequent localization of NC cells in the embryo.
Changing Model Behavior at Test-Time Using Reinforcement Learning

Machine learning models are often used at test-time subject to constraints and trade-offs not present at training-time. For example, a computer vision model operating on an embedded device may need to perform real-time inference, or a translation model operating on a cell phone may wish to bound its average compute time in order to be power-efficient. In this work we describe a mixture-of-experts model and show how to change its test-time resource-usage on a per-input basis using reinforcement learning. We test our method on a small MNIST-based example.
Coronal loop seismology using damping of standing kink oscillations by mode coupling

Context. Kink oscillations of solar coronal loops are frequently observed to be strongly damped. The damping can be explained by mode coupling on the condition that loops have a finite inhomogeneous layer between the higher density core and lower density background. The damping rate depends on the loop density contrast ratio and inhomogeneous layer width. Aims. The theoretical description for mode coupling of kink waves has been extended to include the initial Gaussian damping regime in addition to the exponential asymptotic state. Observation of these damping regimes would provide information about the structuring of the coronal loop and so provide a seismological tool. Methods. We consider three examples of standing kink oscillations observed by the Atmospheric Imaging Assembly (AIA) of the Solar Dynamics Observatory (SDO) for which the general damping profile (Gaussian and exponential regimes) can be fitted. Determining the Gaussian and exponential damping times allows us to perform seismological inversions for the loop density contrast ratio and the inhomogeneous layer width normalised to the loop radius. The layer width and loop minor radius are found separately by comparing the observed loop intensity profile with forward modelling based on our seismological results. Results. The seismological method which allows the density contrast ratio and inhomogeneous layer width to be simultaneously determined from the kink mode damping profile has been applied to observational data for the first time. This allows the internal and external Alfven speeds to be calculated, and estimates for the magnetic field strength can be dramatically improved using the given plasma density. Conclusions. The kink mode damping rate can be used as a powerful diagnostic tool to determine the coronal loop density profile. This information can be used for further calculations such as the magnetic field strength or phase mixing rate.
An integrated approach for visual analysis of a multisource moving objects knowledge base

We present an integrated and multidisciplinary approach for analyzing the behavior of moving objects. The results originate from an ongoing research of four different partners from the Dutch Poseidon project (Embedded Systems Institute (2007)), which aims to develop new methods for Maritime Safety and Security (MSS) systems to monitor vessel traffic in coastal areas. Our architecture enables an operator to visually test hypotheses about vessels with time-dependent sensor data and on-demand external knowledge. The system includes the following components: abstraction and simulation of trajectory sensor data, fusion of multiple heterogenous data sources, reasoning, and visual analysis of the combined data sources. We start by extracting segments of consistent movement from simulated or real-world trajectory data, which we store as instances of the Simple Event Model (SEM), an event ontology represented in the Resource Description Framework (RDF). Next, we add data from the web about vessels and geography to enrich the sensor data. This additional information is integrated with the representation of the vessels (actors) and places in SEM. The enriched trajectory data are stored in a knowledge base, which can be further annotated by reasoning and is queried by a visual analytics tool to search for spatiotemporal patterns. Although our approach is dedicated to MSS systems, we expect it to be useful in other domains.
From Heroes' Groves to Parks of Peace: Landscapes of remembrance, protest and peace

The public space surrounding war memorials and military monuments has always been important in the iconography of remembrance. In the 19th century these spaces often took the form of garden cemeteries and memorial plantations; after the First World War large tracts of former battlefield were preserved as sacred spaces which were essential to the process of ritual pilgrimage. After 1945 there was a considerable shift in the landscapes of war: memorial schemes more often took a pragmatic and utilitarian form, and desolated cities such as Hiroshima (and to a lesser extent Dresden and Coventry) became the cornerstone for anti-war movements in the late 1950s and 1960s. This period saw the emergence of a symbolic landscape of protest, which often co-existed uncomfortably as a place of tourism. Through a study of such sites the various types of 'peace landscape' are analysed, from environmental schemes such as trans-border parks to political interventions in the form of peace gardens. In the final section a recent design competition for a peace park in Turkey is examined and compared with similar complex environments in the US and Northern Ireland.
Field of research : Dilute Bose-Einstein condensates , ultracold quantum gases

Research group: Quantum Computing and Devices (QCD) Contact person: Prof. Mikko Möttönen (mikko.mottonen@aalto.fi) Field of research: Dilute Bose-Einstein condensates, ultracold quantum gases Project title: Quantum knots Project instructor: M.Sc. Tuomas Ollikainen, M.Sc. Konstantiv Tiurev Site of research: Aalto University, QCD Labs, Otaniemi Website Click here! Level of student: applications from all students are welcome (also for people applying for a Mater’s or PhD thesis project) Introduction
A computer aided diagnosis ‘CAD’ for brain glioma exploration

Manual analysis of brain glioma tumor lacks accuracy and is time consuming. Thus, to avoid human error, this paper presents an automatic and accurate computer aided diagnosis (CAD) system for brain glioma exploration on magnetic resonance imaging. A preprocessing approach was proposed to eliminate extra-cerebral features. Tumor and even its edema was automatically extracted by a fast distribution matching algorithm. Then, we realize a 3D reconstruction for brain tumor glioma and its edema in order to classify glioma tumor based on their radiologic appearance. As discussed with clinicians, the experimental results showed that the proposed computer aided diagnosis for brain glioma tumor achieves a good agreement. Thus, the proposed tool facilitates and speeds up the analysis of data and supports decision making.
Secure Capacity Region for Erasure Broadcast Channels with Feedback

We formulate and study a cryptographic problem relevant to wireless: a sender, Alice, wants to transmit private messages to two receivers, Bob and Calvin, using unreliable wireless broadcast transmissions and short public feedback from Bob and Calvin. We ask, at what rates can we broadcast the private messages if we also provide (information-theoretic) unconditional security guarantees that Bob and Calvin do not learn each-other's message? We characterize the largest transmission rates to the two receivers, for any protocol that provides unconditional security guarantees. We design a protocol that operates at any rate-pair within the above region, uses very simple interactions and operations, and is robust to misbehaving users.
Distinct sets of αβ TCRs confer similar recognition of tumor antigen NY-ESO-1157–165 by interacting with its central Met/Trp residues

Naturally acquired immune responses against human cancers often include CD8+ T cells specific for the cancer testis antigen NY-ESO-1. Here, we studied T cell receptor (TCR) primary structure and function of 605 HLA-A*0201/NY-ESO-1157–165-specific CD8 T cell clones derived from five melanoma patients. We show that an important proportion of tumor-reactive T cells preferentially use TCR AV3S1/BV8S2 chains, with remarkably conserved CDR3 amino acid motifs and lengths in both chains. All remaining T cell clones belong to two additional sets expressing BV1 or BV13 TCRs, associated with α-chains with highly diverse VJ usage, CDR3 amino acid sequence, and length. Yet, all T cell clonotypes recognize tumor antigen with similar functional avidity. Two residues, Met-160 and Trp-161, located in the middle region of the NY-ESO-1157–165 peptide, are critical for recognition by most of the T cell clonotypes. Collectively, our data show that a large number of αβ TCRs, belonging to three distinct sets (AVx/BV1, AV3/BV8, AVx/BV13) bind pMHC with equal antigen sensitivity and recognize the same peptide motif. Finally, this in-depth study of recognition of a self-antigen suggests that in part similar biophysical mechanisms shape TCR repertoires toward foreign and self-antigens.
Towards vegetation species discrimination by using data-driven descriptors

Abstract—In this paper, we analyse the use of Convolutional Neural Networks (CNNs or ConvNets) to discriminate vegetation species with few labelled samples. To the best of our knowledge, this is the first work dedicated to the investigation of the use of deep features in such task. The experimental evaluation demonstrate that deep features significantly outperform wellknown feature extraction techniques. The achieved results also show that it is possible to learn and classify vegetation patterns even with few samples. This makes the use of our approach feasible for real-world mapping applications, where it is often difficult to obtain large training sets.
A -68.5 dB IM3 Low-Voltage CMOS Transconductor with Wide Tuning Range

SUMMARY A CMOS transconductor for multi-mode application is presented. The transconductor includes a voltage-to-current converter and a current multiplier. Voltage-to-current conversion employs linear region MOS transistors, and the conversion features high linearity over a wide input swing range. The current multiplier, which operates in the weak inversion region, provides a wide transconductance tuning range without degrading the linearity. The transconductor was designed and fabricated in the TSMC 0.18-μm CMOS process. The results show the transconductance tuning ratio of 23 and the IM3 performance of −68.5 dB.
Identification of seizure onset zone using automatically detected spike and high-frequency oscillation in human intracranial EEG

High frequency oscillations (HFOs) have been considered as reliable biomarkers for seizure onset zone (SOZ) that may potentially benefit the presurgical evaluation in epilepsy surgery. By applying an automatic technique, we explored the spatial characteristics of ripples (80-250 Hz), fast ripples (250-500 Hz) and spikes using human iEEG data recorded in 5 patients with refractory temporal epilepsy, and related our results to clinician-identified SOZ. Fast ripples, which generally appeared within the spiking regions, reached 100% of specificity when used for SOZ approximation, whereas spikes showed highest sensitivity of 92%. Our results indicate that the information of HFOs and spikes can be fused together to better understand the pathophysiology of the disease. Automatic detectors can be used efficiently to identify different types of neural activities, and thus facilitate the accurate delineation of SOZ.
In vivo Imaging of Kurtosis Tensor Eigenvalues in the Brain at 3 T

Background Diffusion tensor imaging (DTI), a gaussian anisotropic diffusion model, provides mean diffusivity (MD) and fractional anisotropy (FA) metrics that describe diffusion in brain tissue (white and gray matter). However, the widely recognized non-gaussian diffusion behavior in tissue has motivated higher order schemes (q-ball, HARDI, DSI) to accurately describe the tissue structure. In generalized DTI, higher order tensors are invoked to represent the orientational diffusion profile [1-3]. Diffusional kurtosis imaging (DKI) measures the displacement non-gaussianity or “kurtosis” [4,5]. The directionally averaged mean kurtosis (MK) has been shown to be a potentially valuable disease marker in such illnesses as Alzheimer’s and ADHD [6,7]. Recent work has also used kurtosis projections along the diffusion tensor [8], and the kurtosis tensor has been used to estimate the full orientation distribution function (ODF) [9]. Another strategy, analogous to the principal diffusivities of the diffusion tensor, is to seek eigenvalues/tensors/vectors of the kurtosis tensor as its characteristic features. Though this is challenging for a rank-4 object, there are mathematical prescriptions for deriving such parameters [10,11]. The present study employed spectral decomposition [10] of the diffusion kurtosis tensor, in order to understand the kurtosis variation in the brain and supplement tractography techniques. Methods Scans were performed on a healthy volunteer in a full body Siemens Tim Trio 3 T scanner with a 12-channel head coil. DKI data used a twice-refocused bipolar diffusion gradient EPI sequence (2 x 2 x 2.5 mm resolution, 100 x 100 matrix, 50 slices, iPat = 2, 64 directions, b = 0 (11 avgs.) ,1000, 2000 s/mm (2 avgs ea.)) Analysis was performed using code written in Igor Pro. For each direction n , apparent diffusion (D ( n )) and apparent kurtosis (K( n )) were extracted:
Dynamic path planning of mobile robot mounted range sensors and single CCD camera

This paper treats a trajectory tracking control of a mobile robot by a single CCD camera and range sensors. First, the mobile robot detects the obstacle based on information of both the image and the distance. And then, from the obstacle information, the mobile robot generates a trajectory to avoid the obstacle. Finally, the usefulness of our proposed methods is demonstrated through experiment.