Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency-Tunable Bandpass Filters with Constant Absolute Bandwidth and Improved Linearity

This paper presents a frequency-tunable bandpass fllter with constant absolute bandwidth and improved linearity. The proposed resonator is composed of an open-ended transmission line with back-to-back varactor diodes loaded at one end. The back-to-back varactor diodes are used to enhance the linearity of the fllter, which is better than that of the single varactor counterparts. A mixed electric and magnetic coupling scheme is utilized to control the overall coupling coe-cients so that the absolute bandwidth can be kept constant when the frequency is tuned. For validation, two frequency-tuning fllters with 30-MHz and 44-MHz absolute bandwidth are implemented. The experimental and simulated results are presented to verify the proposed design.
Affect and Learning : a computational analysis

In this thesis we have studied the influence of emotion on learning. We have used computational modelling techniques to do so, more specifically, the reinforcement learning paradigm. Emotion is modelled as artificial affect, a measure that denotes the positiveness versus negativeness of a situation to an artificial agent in a reinforcement learning setting. We have done a range of different experiments to study the effect of affect on learning, including the effect on learning if affect is used to control the exploration behaviour of the agent and the effect on learning when affect is communicated by a human (though real-time analysis of that human’s facial expressions) to a simulated robot. We conclude that affect is a useful concept to consider in adaptive agents that learn based on reinforcement learning and that in some cases affect can indeed help the learning process. Further, affective modelling in this way can help understand the psychological processes that underlie influences of affect on cognition. Finally, we have developed a formal notation for a specific type of emotion theory, i.e., cognitive appraisal theory.
Style-based abstractions for human motion classification

This paper presents an approach to motion analysis for robotics in which a quantitative definition of “style of motion” is used to classify movements. In particular, we present a method for generating a “best match” signal for empirical data via a two stage optimal control formulation. The first stage consists of the generation of trajectories that mimic empirical data. In the second stage, an inverse problem is solved in order to obtain the “stylistic parameters” that best recreate the empirical data. This method is amenable to human motion analysis in that it not only produces a matching trajectory but, in doing so, classifies its quality. This classification allows for the production of additional trajectories, between any two endpoints, in the same style as the empirical reference data. The method not only enables robotic mimicry of human style but can also provide insights into genres of stylized movement, equipping cyberphysical systems with a deeper interpretation of human movement.
Uygulamaya Dayalı Öğretim Teknolojileri ve Materyal Tasarımı Becerileri Ölçeği Geliştirme

Bu calismada Uygulamaya Dayali Ogretim Teknolojileri ve Materyal Tasarimi Becerileri Olcegi gelistirilmistir. Olcekteki maddeler ders kitabi ve literatur taramasi ile olusturulmus ve alan uzmanlarinin yer aldigi Delphi degerlendirme yontemi ile degerlendirilmistir. Olcek 1595 kisi uzerinde denenmistir. Sonucta elde edilen 39 maddelik olcegin guvenilir ve gecerli bir olcek oldugu bulunmustur.
Surgical tool segmentation using a hybrid deep CNN-RNN auto encoder-decoder

Surgical tool segmentation is used for detection, tracking and pose estimation of the tools in the vicinity of surgical scenes. It is considered as an essential task in surgical phase recognition and flow identification. Surgical flow identification is an unresolved task in the domain of context-aware surgical systems, which is used extensively on computer assisted intervention (CAI). CAI is used for staff assignment, automated guidance during intervention, surgical alert systems, automatic indexing of surgical video databases and optimisation of the real-time scheduling of operating room. Semantic segmentation is used for accurate delineation of surgical tools from the background. In semantic segmentation, each label is assigned to a class as a tool or a background. In this presented work, we applied a hybrid method utilising both recurrent and convolutional networks to achieve higher accuracy of surgical tools segmentation. The proposed method is trained and tested using a public dataset MICCAI 2016 Endoscopic Vision Challenge Robotic Instruments dataset "EndoVis". We achieved better performance using the proposed method compared to state-of-the-art methods on the same dataset for benchmarking. We achieved a balanced accuracy of 93.3% and Jaccard index of 82.7%.
Protein-Flavonoid Interaction Studies by a Taylor Dispersion Surface Plasmon Resonance (SPR) Technique: A Novel Method to Assess Biomolecular Interactions

Flavonoids are common polyphenolic compounds widely distributed in fruits and vegetables. These pigments have important pharmacological relevance because emerging research suggests possible anti-cancer and anti-inflammatory properties as well other beneficial health effects. These compounds are relatively hydrophobic molecules, suggesting the role of blood transport proteins in their delivery to tissues. In this study, we assess the binding interactions of four flavonoids (kaempferol, luteolin, quercetin, and resveratrol) with human serum albumin (HSA), the most abundant protein in the blood, and with glutathione S-transferase pi isoform-1 (GSTP1), an enzyme with well-characterized hydrophobic binding sites that plays an important role in detoxification of xenobiotics with reduced glutathione, using a novel Taylor dispersion surface plasmon resonance (SPR) technique. For the first time, HSA sites revealed a high-affinity binding site for flavonoid interactions. Out of the four flavonoids that we examined, quercetin and kaempferol showed the strongest equilibrium binding affinities (KD) of 63 ± 0.03 nM and 37 ± 0.07 nM, respectively. GSTP1 displayed lower affinities in the micromolar range towards all of the flavonoids tested. The interactions of flavonoids with HSA and GSTP1 were studied successfully using this novel SPR assay method. The new method is compatible with both kinetic and equilibrium analyses.
S-matrix equivalence restored

The canonical transformation that maps light-cone Yang-Mills theory to a Lagrangian description of the MHV rules is non-local, consequently the two sets of fields do not necessarily generate the same S-matrix. By deriving a new recursion relation for the canonical transformation expansion coefficients, we find a direct map between these coefficients and tree level light-cone diagrams. We use this to show that, at least up to one-loop with dimensionally regularised MHV vertices, the only difference is the omission of the one-loop amplitudes in which all gluons have positive helicity.
Decisional support for young people who self-harm: protocol for a feasibility trial

Introduction Self-harm is common in adolescents, and it is the strongest predictor of suicide. Young people who self-harm are often unsure of how and where to get help. Decision aids (DAs) have been shown to help with decisional conflict where there is uncertainty around different options. We have developed an online DA to support young people in help-seeking for self-harm. A feasibility trial will examine the acceptability of the online intervention and the ability to recruit and follow-up participants within a school setting. Methods and analysis In this parallel arm, single-blind feasibility trial, 60 participants aged 12–18 years who have self-harmed in the past 12 months, will be randomised to either (1) a group receiving the online DA or (2) a control group receiving general information about feelings and emotions. Both groups will complete measures assessing decision-making and help-seeking behaviour. The school counsellor will be notified of any participants who have been randomised to ensure safeguarding for the young person. Participants in both groups will be followed up at 4 weeks, and the measures will be repeated. Qualitative interviews will be conducted with a subset of participants to explore their views and experiences of the DA and of participation in the study. Ethics and dissemination Ethical approval was granted by King's College London (KCL) College Research Ethics Committee. Results of this study will help to clarify if we can recruit and administer an online decisional support intervention within a school setting for young people who self-harm. The study will inform the design and implementation of a larger randomised controlled trial to test the effectiveness of the DA. Dissemination of the study findings will target publication in peer-reviewed journals of general and special interest. The funder will be sent a report outlining the major findings of the study. Trial registration number ISRCTN11230559.
Group Dieting, the Stigma of Obesity, and Overweight Adolescents

Natalie Allon was one of the pioneers in the sociological analysis of obesity and dieting, and a consistent voice on the topic in the 1970s. Her contributions to the study of the obese are reviewed in this paper. As an ethnographer who used participant observation and unstructured interviewing to examine organized dieting groups, she provided insight into the structure and function of these groups. She showed how group dieting was a form of religious ritual for the participants, as well as performing the latent function of providing social support. Her analysis of the stigma of obesity examined stigmatization of fatness in four areas: as sin, as disease, as crime, and as ugliness. Work on overweight adolescents showed that they had problems in social interaction. Because obesity often served as the exclusive focus of interaction, it overwhelmed others with mixed emotions, it clashed with positive attributes of a person, and it was an uncertain predictor of joint activity. Negative self image and a mixture.
Deterministic sampling and range counting in geometric data streams

We present memory-efficient deterministic algorithms for constructing ∈-nets and ∈-approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their approximation factors. We show how our deterministic samples can be used to answer approximate online iceberg geometric queries on data streams. We use these techniques to approximate several robust statistics of geometric data streams, including Tukey depth, simplicial depth, regression depth, the Thiel-Sen estimator, and the least median of squares. Our algorithms use only a polylogarithmic amount of memory, provided the desired approximation factors are inverse-polylogarithmic. We also include a lower bound for non-iceberg geometric queries.
Optimization of Number of Mesh Routers in WMNs Using WMN-SA System Considering Uniform Distribution for Different Number of Mesh Clients

One of the key advantages of Wireless Mesh Networks (WMNs) is their importance for providing cost-efficient broadband connectivity. There are issues for achieving the network connectivity and user coverage, which are related with the node placement problem. In this work, we consider the router node placement problem in WMNs. We want to find the optimal distribution of router nodes in order to provide the best network connectivity and user coverage in a set of uniformly distributed clients. From the simulation results, we conclude that, when the number of mesh clients is small, a small number of mesh routers are needed in order to optimize the size of Giant Component (GC) and number of covered mesh clients (NCMC). However, some of mesh routers can not cover the clients. On the other hand, when the number of mesh clients is big, many mesh routers are needed to optimize the GC and the NCMC. In this case, a mesh router can cover more than one mesh clients.
Complete Genome Assembly of Enterococcus faecalis 29212, a Laboratory Reference Strain

ABSTRACT Enterococcus faecalis is a nonmotile Gram-positive coccus, found both as a commensal organism in healthy humans and animals and as a causative agent of multiple diseases, in particular endocarditis. We sequenced the genome of E. faecalis ATCC 29212, a commonly used reference strain in laboratory studies, to complete “finished” annotated assembly (3 Mb).
Host-Synthesized Secondary Compounds Influence the In Vitro Interactions between Fungal Endophytes of Maize

ABSTRACT Maize produces a suite of allelopathic secondary metabolites, the benzoxazinoids. 2,4-Dihydroxy-7-methoxy-2H-1,4-benzoxazin-3-one and 2,4-dihydroxy-2H-1,4-benzoxazin-3-one reside as glucosides in plant tissue and spontaneously degrade to 6-methoxy-2-benzoxazolinone (MBOA) and 2-benzoxazolinone (BOA) upon plant cell disruption. Several maize-associated fungi in the genus Fusarium can metabolize MBOA and BOA. BOA tolerance levels in 10 species of Fusarium and in the maize endophytes Nigrospora oryzae, Acremonium zeae, and Periconia macrospinosa were characterized. BOA tolerance ranged from 0.25 to 1.10 mg/ml among species. The influence of substrate alteration by one species on the subsequent growth of another species was assessed in the presence and absence of BOA. The colony area of the secondary colonizer in heterospecific interactions was compared to that in autospecific interactions (one isolate follows itself). In the presence of BOA, four of six secondary colonizers had greater growth (facilitation) when primary colonizers had higher BOA tolerance than the secondary colonizer. When the primary colonizer had lower tolerance than the secondary, three of six secondary colonizers were inhibited (competition) and three not significantly affected. In BOA-free medium, the number of isolates that were facilitated or inhibited was the same regardless of the tolerance level of the primary colonizer. Two of six secondary colonizers were facilitated, two inhibited, and two not significantly affected. This study provides some support for facilitation in stressful conditions under the Menge-Sutherland model. The results are not consistent with the corresponding prediction of competition in the absence of stress. The hypothesis drawn from these data is that in the presence of a toxin, fungal species that detoxify their substrate can enhance the colonization rate of less tolerant fungi.
An efficient codebook design in SDCHMM for mobile communication environments

Speech recognition systems require too much memory to run and are too slow for mass application. In order to overcome these constraints and make speech recognition systems suitable for mobile devices, we propose efﬁcient codebook construction method for subspace distribution clustering hidden markov modeling (SDCHMM). The output probability of mixture Gaussians is more sensitive to quantization error of mean vectors than that of variance vectors. Therefore we propose a new subspace deﬁnition which minimizes quantization error of mean vectors ﬁrst. Next, we split mixture Gaussians into mean and variance vectors and construct separate codebooks using modiﬁed Bhattacharyya distance measure. In experiments using RM database, proposed method decreases 24.5% relative word error rate compared with general SDCHMM without use of extra memory.
YaeT (Omp85) affects the assembly of lipid‐dependent and lipid‐independent outer membrane proteins of Escherichia coli

The Omp85 family of proteins has been found in all Gram‐negative bacteria and even several eukaryotic organisms. The previously uncharacterized Escherichia coli member of this family is YaeT. The results of this study, consistent with previous Omp85 studies, show that the yaeT gene encodes for an essential cellular function. Direct examinations of the outer membrane fraction and protein assembly revealed that cells depleted for YaeT are severely defective in the biogenesis of outer membrane proteins (OMPs). Interestingly, assemblies of the two distinct groups of OMPs that follow either SurA‐ and lipopolysaccharide‐dependent (OmpF/C) or ‐independent (TolC) folding pathways were affected, suggesting that YaeT may act as a general OMP assembly factor. Depletion of cells for YaeT led to the accumulation of OMPs in the fraction enriched for periplasm, thus indicating that YaeT facilitates the insertion of soluble assembly intermediates from the periplasm to the outer membrane. Our data suggest that YaeT's role in the assembly of OMPs is not mediated through a role in lipid biogenesis, as debated for Omp85 in Neisseria, thus advocating a conserved OMP assembly function of Omp85 homologues.
Comparative Assessment of Scoring Functions on a Diverse Test Set

Scoring functions are widely applied to the evaluation of protein-ligand binding in structure-based drug design. We have conducted a comparative assessment of 16 popular scoring functions implemented in main-stream commercial software or released by academic research groups. A set of 195 diverse protein-ligand complexes with high-resolution crystal structures and reliable binding constants were selected through a systematic nonredundant sampling of the PDBbind database and used as the primary test set in our study. All scoring functions were evaluated in three aspects, that is, "docking power", "ranking power", and "scoring power", and all evaluations were independent from the context of molecular docking or virtual screening. As for "docking power", six scoring functions, including GOLD::ASP, DS::PLP1, DrugScore(PDB), GlideScore-SP, DS::LigScore, and GOLD::ChemScore, achieved success rates over 70% when the acceptance cutoff was root-mean-square deviation < 2.0 A. Combining these scoring functions into consensus scoring schemes improved the success rates to 80% or even higher. As for "ranking power" and "scoring power", the top four scoring functions on the primary test set were X-Score, DrugScore(CSD), DS::PLP, and SYBYL::ChemScore. They were able to correctly rank the protein-ligand complexes containing the same type of protein with success rates around 50%. Correlation coefficients between the experimental binding constants and the binding scores computed by these scoring functions ranged from 0.545 to 0.644. Besides the primary test set, each scoring function was also tested on four additional test sets, each consisting of a certain number of protein-ligand complexes containing one particular type of protein. Our study serves as an updated benchmark for evaluating the general performance of today's scoring functions. Our results indicate that no single scoring function consistently outperforms others in all three aspects. Thus, it is important in practice to choose the appropriate scoring functions for different purposes.
Threshold-based multicast for continuous media delivery

In this paper, we propose and evaluate the performance of a continuous media delivery technique, called threshold-based multicast. Similar to patching, threshold-based multicast allows two clients that request the same video to share a channel without having to delay the earlier request. It ensures sharing by permitting the client with the later arrival time to join an ongoing multicast session initiated for the earlier request. However, threshold-based multicast does not allow a later arriving client to always join an ongoing multicast session. If it has been some time since the ongoing multicast session was started, a new multicast session is initiated. That is, a threshold is used to control the frequency at which new multicast sessions are started. We derive the optimal threshold that minimizes the server bandwidth required. Our analytical result shows that threshold-based multicast significantly reduces the server bandwidth requirement. Furthermore, we perform a simulation study demonstrating the performance gain of continuous media delivery by threshold-based multicast.
Repeat-pass interferometry using a fixed-receiver and ERS-2/ENVISAT as transmitters of opportunity

The presented work discusses the processing of repeat-pass interferometric data acquired with SABRINA (SAR Bistatic Receiver for INterferometric Applications), where the receiver is fixed and the baseline is due to the two different satellite orbits. The paper addresses the particularities of bistatic interferometry like the coregistration of the images and the decorrelation factors affecting the interferometric phase. Theoretical developments are complemented with the first repeat-pass results. The characteristics of the scene and the 35 days temporal baseline have caused the interferogram to be severely affected by the temporal decorrelation. This first result opens the discussion of what kind of targets are seen in a bistatic geometry and which of them can be coherent along time.
Channel-Optimized Quantization With Soft-Decision Demodulation for Space&#8211;Time Orthogonal Block-Coded Channels

We introduce three soft-decision demodulation channel-optimized vector quantizers (COVQs) to transmit analog sources over space-time orthogonal block (STOB)-coded flat Rayleigh fading channels with binary phase-shift keying (BPSK) modulation. One main objective is to judiciously utilize the soft information of the STOB-coded channel in the design of the vector quantizers while keeping a low system complexity. To meet this objective, we introduce a simple space-time decoding structure that consists of a space-time soft detector, followed by a linear combiner and a scalar uniform quantizer with resolution q. The concatenation of the space-time encoder/modulator, fading channel, and space-time receiver can be described by a binary-input, 2q-output discrete memoryless channel (DMC). The scalar uniform quantizer is chosen so that the capacity of the equivalent DMC is maximized to fully exploit and capture the system's soft information by the DMC. We next determine the statistics of the DMC in closed form and use them to design three COVQ schemes with various degrees of knowledge of the channel noise power and fading coefficients at the transmitter and/or receiver. The performance of each quantization scheme is evaluated for memoryless Gaussian and Gauss-Markov sources and various STOB codes, and the benefits of each scheme is illustrated as a function of the antenna-diversity and soft-decision resolution q. Comparisons to traditional coding schemes, which perform separate source and channel coding operations, are also provided
A non-commutative Positivstellensatz on isometries

A symmetric non-commutative polynomial p when evalu- ated at a tuple of operators on a flnite dimensional, real Hilbert space H has a value which is a symmetric operator. We show that any such polynomial which takes positive semideflnite values on the variety Z of spherical isometries is represented as a sum of squares of polynomials plus a residual part vanishing on Z. Here by spherical isometries we mean tuples A =( A 1;A2;:::;An) of operators on H such that A T A1 + :::+A TAn =I: This observation improves prior theorems known only for strictly pos- itive polynomials. It is known that for commutative polynomials the result is false.
ObjectMinutiae: Fingerprinting for Object Authentication

In this work, we present \emph{ObjectMinutiae}, which is a framework for authenticating different objects or materials via extracting and matching their fingerprints. Unlike biometrics fingerprinting processes, which use patterns such as ridge ending and bifurcation points as the interest points, our work applies stereo photometric techniques for reconstructing objects' local image regions that contain the surface texture information. The interest points of the recovered image regions can be detected and described by state-of-the-art computer vision algorithms. Together with dimension reduction and hashing techniques, our proposed system is able to perform object verification using compact image features. With neutral and different torturing conditions, preliminary results on multiple types of papers support the use of our framework for practical object authentication tasks.