Miracle-dz/UniFAR-FTUs huggingface dataset:
Discretely Coding Semantic Rank Orders for Supervised Image Hashing

Learning to hash has been recognized to accomplish highly efficient storage and retrieval for large-scale visual data. Particularly, ranking-based hashing techniques have recently attracted broad research attention because ranking accuracy among the retrieved data is well explored and their objective is more applicable to realistic search tasks. However, directly optimizing discrete hash codes without continuous-relaxations on a nonlinear ranking objective is infeasible by either traditional optimization methods or even recent discrete hashing algorithms. To address this challenging issue, in this paper, we introduce a novel supervised hashing method, dubbed Discrete Semantic Ranking Hashing (DSeRH), which aims to directly embed semantic rank orders into binary codes. In DSeRH, a generalized Adaptive Discrete Minimization (ADM) approach is proposed to discretely optimize binary codes with the quadratic nonlinear ranking objective in an iterative manner and is guaranteed to converge quickly. Additionally, instead of using 0/1 independent labels to form rank orders as in previous works, we generate the listwise rank orders from the high-level semantic word embeddings which can quantitatively capture the intrinsic correlation between different categories. We evaluate our DSeRH, coupled with both linear and deep convolutional neural network (CNN) hash functions, on three image datasets, i.e., CIFAR-10, SUN397 and ImageNet100, and the results manifest that DSeRH can outperform the state-of-the-art ranking-based hashing methods.
Impaired awareness of motor intention in functional neurological disorder: implications for voluntary and functional movement

Background Functional neurological disorders (FNDs), also known as conversion disorder, are unexplained neurological symptoms unrelated to a neurological cause. The disorder is common, yet poorly understood. The symptoms are experienced as involuntary but have similarities to voluntary processes. Here we studied intention awareness in FND. Method A total of 26 FND patients and 25 healthy volunteers participated in this functional magnetic resonance study using Libet's clock. Results FND is characterized by delayed awareness of the intention to move relative to the movement itself. The reporting of intention was more precise, suggesting that these findings are reliable and unrelated to non-specific attentional deficits. That these findings were more prominent with aberrant positive functional movement symptoms rather than negative symptoms may be relevant to impairments in timing for an inhibitory veto process. Attention towards intention relative to movement was associated with lower right inferior parietal cortex activity in FND, a region early in the processing of intention. During rest, aberrant functional connectivity was observed with the right inferior parietal cortex and other motor intention regions. Conclusions The results converge with observations of low inferior parietal activity comparing involuntary with voluntary movement in FND, emphasizing core deficiencies in intention. Heightened precision of this impaired intention is consistent with Bayesian theories of impaired top-down priors that might influence the sense of involuntariness. A primary impairment in voluntary motor intention at an early processing stage might explain clinical observations of slowed effortful voluntary movement, heightened self-directed attention and underlie functional movements. These findings further suggest novel therapeutic targets.
A Versatile New Model of Chemically Induced Chronic Colitis Using an Outbred Murine Strain

Murine colitis models are crucial tools for understanding intestinal homeostasis and inflammation. However, most current models utilize a highly inbred strain of mice, and often only one sex is employed to limit bias. This targeted approach, which in itself is biased, means that murine genetic diversity and sex-related differences are ignored, making it even more difficult to extend findings to humans, who are highly heterogeneous. Furthermore, most models do not examine the chronic form of colitis, an important fact taking into account the chronic nature of the inflammatory bowel diseases (IBD). Here, we attempted to create a more realistic murine colitis model by addressing these three issues. Using chemically induced chronic colon inflammation in an outbred strain of mice (RjOrl:SWISS [CD-1]), we (i) mimicked the relapsing nature of the disease, (ii) better represented normal genetic variability, and (iii) employed both female and male mice. Colitis was induced by intrarectal administration of dinitrobenzene sulfonic acid (DNBS). After a recovery period and 3 days before the mice were euthanized, colitis was reactivated by a second administration of DNBS. Protocol length was 24 days. Colitis severity was assessed using body mass, macroscopic scores, and histological scores. Myeloperoxidase (MPO) activity, cytokine levels, and lymphocyte populations were also characterized. Our results show that the intrarectal administration of DNBS effectively causes colitis in both female and male CD-1 mice in a dose-dependent manner, as reflected by loss of body mass, macroscopic scores and histological scores. Furthermore, colon cytokine levels and mesenteric lymph node characteristics indicate that this model involves immune system activation. Although some variables were sex-specific, most of the results support including both females and males in the model. Our ultimate goal is to make this model available to researchers for testing candidate anti-inflammatory agents, such as classical or next-generation probiotics; we also aim for the results to be more easily transferrable to human trials.
Study on Elastic Modulus of Rust by the Cyclic Low-compression Test / Bestimmung des Elastizitätsmoduls von Rost mit Hilfe einer zyklischen Belastung mit niedriger Druckspannung

After steel corrosion initiates, the volume of rust is larger than the original steel, inducing an internal pressure on the surrounding confining concrete to crack the cover. Therefore, the rust is one of the most influential factors during the concrete cracking process due to corrosion. This paper aims to find out the mechanical behavior of rust, which can be used in the corrosion induced cracking model. Four types of rust samples collected from different natural environments were investigated in this model. X-ray diffraction is used for differentiating the major chemical compositions of the rust samples. The cyclic low-compression test shows that the constitutive model of rust layer can be expressed as a power function. The elastic modulus of rust considering the influence of the area (calculated from the traced profile of the rust flake) of samples is also proposed. The results of this study show that physical mechanical behavior of the rust samples collected from the different natural environments are similar; the moduli of rust samples decrease with the increase of their area, however, the elastic modulus of rust tends to be constant when the area of the sample is larger than 460 mm2, which is around 102 MPa. This value can be applied to the analysis of the concrete cover cracking due to reinforcement corrosion, which enables the prediction of the concrete cover cracking rationally.
Simultaneous Assessment of Cardiomyocyte DNA Synthesis and Ploidy: A Method to Assist Quantification of Cardiomyocyte Regeneration and Turnover

Although it is accepted that the heart has a limited potential to regenerate cardiomyocytes following injury and that low levels of cardiomyocyte turnover occur during normal ageing, quantification of these events remains challenging. This is in part due to the rarity of the process and the fact that multiple cellular sources contribute to myocardial maintenance. Furthermore, DNA duplication within cardiomyocytes often leads to a polyploid cardiomyocyte and only rarely leads to new cardiomyocytes by cellular division. In order to accurately quantify cardiomyocyte turnover discrimination between these processes is essential. The protocol described here employs long term nucleoside labeling in order to label all nuclei which have arisen as a result of DNA replication and cardiomyocyte nuclei identified by utilizing nuclei isolation and subsequent PCM1 immunolabeling. Together this allows the accurate and sensitive identification of the nucleoside labeling of the cardiomyocyte nuclei population. Furthermore, 4′,6-diamidino-2-phenylindole labeling and analysis of nuclei ploidy, enables the discrimination of neo-cardiomyocyte nuclei from nuclei which have incorporated nucleoside during polyploidization. Although this method cannot control for cardiomyocyte binucleation, it allows a rapid and robust quantification of neo-cardiomyocyte nuclei while accounting for polyploidization. This method has a number of downstream applications including assessing the potential therapeutics to enhance cardiomyocyte regeneration or investigating the effects of cardiac disease on cardiomyocyte turnover and ploidy. This technique is also compatible with additional downstream immunohistological techniques, allowing quantification of nucleoside incorporation in all cardiac cell types.
A Low-Jitter and Low-Reference-Spur Ring-VCO-Based Switched-Loop Filter PLL Using a Fast Phase-Error Correction Technique

A low-jitter and low-reference-spur ring-type voltage-controlled oscillator (VCO)-based switched-loop filter (SLF) phase-locked loop (PLL) is presented. To enhance the capability of suppressing jitter of a VCO, we propose a fast phase-error correction (FPEC) technique that emulates the phase-realignment mechanism of an injection-locked clock multiplier. By the proposed FPEC technique, accumulated jitter of a VCO can be removed intensively in a short interval, thereby suppressing jitter dramatically. Based on a PLL topology having an intrinsic integrator in a VCO, the proposed architecture can also achieve a low reference spur despite a high multiplication factor (i.e., 64). This paper also presents the selective frequency-tuning technique used in the VCO that helps the proposed architecture further suppress the level of reference spur. The proposed PLL was fabricated in a 65-nm CMOS process. The measured rms jitter integrated from 1 kHz to 80 MHz and the reference spur of the output signal with a 3.008-GHz frequency were 357 fs and −71 dBc, respectively. The total active area was 0.047 mm2, and the power consumption was 4.6 mW.
Bio-inspired meta-learning for active exploration during non-stationary multi-armed bandit tasks

Fast adaptation to changes in the environment requires agents (animals, robots and simulated artefacts) to be able to dynamically tune an exploration-exploitation trade-off during learning. This trade-off usually determines a fixed proportion of exploitative choices (i.e. choice of the action that subjectively appears as best at a given moment) relative to exploratory choices (i.e. testing other actions that now appear worst but may turn out promising later). Rather than using a fixed proportion, non-stationary multi-armed bandit methods in the field of machine learning have proven that principles such as exploring actions that have not been tested for a long time can lead to performance closer to optimal — bounded regret. In parallel, researches in active exploration in the fields of robot learning and computational neuroscience of learning and decision-making have proposed alternative solutions such as transiently increasing exploration in response to drops in average performance, or attributing exploration bonuses specifically to actions associated with high uncertainty in order to gain information when choosing them. In this work, we compare different methods from machine learning, computational neuroscience and robot learning on a set of non-stationary stochastic multi-armed bandit tasks: abrupt shifts; best bandit becomes worst one and vice versa; multiple shifting frequencies. We find that different methods are appropriate in different scenarios. We propose a new hybrid method combining bio-inspired meta-learning, kalman filter and exploration bonuses and show that it outperforms other methods in these scenarios.
Molecular Epidemiology of Viral Hemorrhagic Septicemia Virus in the Great Lakes Region

G gene Viral hemorrhagic septicemia virus (VHSV) is considered by many nations and international organizations to be one of the most important viral pathogens of finfish (Office International des Epizooties 2007). For several decades following its initial characterization in the 1950s, VHSV was thought to be limited to Europe where it was regarded as an endemic pathogen of freshwater fish that was especially problematic for farmed rainbow trout, an introduced species (Wolf 1988; Smail 1999). Subsequently, it was shown that VHSV was present among many species of marine and anadromous fishes in both the Pacific and Atlantic Oceans where it has been associated with substantial mortality among both wild and cultured fish (Meyers and Winton 1995; Skall et al. 2005).
DEFORMED SYSTEMS FOR CONTEXTUAL TEXT RECOGNITION Javier

A fuzzy method for incorporating the contextual constraints into a text recognition system is presented here. The method takes as input all the internal result that an Isolated Character Classifier (ICC) computes for an input letter, instead of an unique output character. The internal result is handled here as a fuzzy set which is then processed by a Deformed System. Such a Deformed System represents a dictionary of legal words, and it is actually a Finite Automaton which has been modified for accepting as input no single symbols but fuzzy sets. Several tests have been carried out in a Text Recognition System and the obtained results show the suitability of the method.
Action Recognition Using 3D Histograms of Texture and A Multi-Class Boosting Classifier

Human action recognition is an important yet challenging task. This paper presents a low-cost descriptor called 3D histograms of texture (3DHoTs) to extract discriminant features from a sequence of depth maps. 3DHoTs are derived from projecting depth frames onto three orthogonal Cartesian planes, i.e., the frontal, side, and top planes, and thus compactly characterize the salient information of a specific action, on which texture features are calculated to represent the action. Besides this fast feature descriptor, a new multi-class boosting classifier (MBC) is also proposed to efficiently exploit different kinds of features in a unified framework for action classification. Compared with the existing boosting frameworks, we add a new multi-class constraint into the objective function, which helps to maintain a better margin distribution by maximizing the mean of margin, whereas still minimizing the variance of margin. Experiments on the MSRAction3D, MSRGesture3D, MSRActivity3D, and UTD-MHAD data sets demonstrate that the proposed system combining 3DHoTs and MBC is superior to the state of the art.
Polymeric Carriers - The Influence of Body Fluid Compounds on a Drug Local Release

The release of a model compound (cyanocobalamin) from the core-shell structure of drug carrier was considered. Mass transfer was described by the classical equation describing a diffusion mass flow. The presence of compounds found in body fluids on the diffusional mass stream was investigated. It has been shown that high molecular weight compounds unable to penetrate the carrier surface form on the carrier surface a layer that slightly slows the drug release. Slowing down also occurs in the case of counter-current transport of soluble organic components. However, the salts (particularly NaCl) present in body fluids, probably due to the emerging osmotic pressure, significantly accelerate the transport of the released drug. In order to prevent this phenomenon, salts at the concentrations equal to their concentrations in the fluid surrounding the carrier should be placed into the carrier.
Partial Hash Update via Hamming Subspace Learning

Hashing technique has become an effective method for information retrieval due to the fast calculation of the Hamming distance. However, with the continuous growth of data coming from the Internet, the online update of hashing on the massive social data becomes very time-consuming. To alleviate this issue, in this paper, we propose a novel updating technique for hashing methods, namely Hamming Subspace Learning (HSL). The motivation of HSL is to generate a low-dimensional Hamming subspace from a high-dimensional Hamming space by selecting representative hash functions. Through HSL, we aim to improve the speed of updating binary codes for all samples. We present a method for Hamming subspace learning based on greedy selection strategy and the Distribution Preserving Hamming Subspace learning (DHSL) algorithm by designing a novel loss function. The experimental results demonstrate that the HSL is effective to improve the speed of online updating and the performance of hashing algorithm.
Coding to Mitigate Video Disruption during Wireless Access Switching

We propose a coding-based solution to mitigate the disruption during switching from unicast to broadcast wireless channels while streaming live video to mobile devices. Our solution, based on unequal error protection principles, takes advantage of side information about the switching time available at the encoder. In particular, we present a method to distribute error protection unequally among the input packets based on their temporal position in the video stream and on the switching time distribution. We implement our proposed encoder and decoder in Matlab and compare the proposed scheme to LT codes and to the naive approach of not using coding at all. Our experiments indicate that our approach results in approximately $8$\% improvement over plain LT coding and about $20$\% improvement over a no coding approach.
A sentiment-based item description approach for kNN collaborative filtering

In this paper, we propose an approach based on sentiment analysis to describe items in a neighborhood-based collaborative filtering model. We use unstructured users' reviews to produce a vector-based representation that considers the overall sentiment of those reviews towards specific features. We propose and compare two different techniques to obtain and score such features from textual content, namely term-based and aspect-based feature extraction. Finally, our proposal is compared against structured metadata under the same recommendation algorithm, whose results show a significant improvement over the baselines.
Comparison of the c‐MET gene amplification between primary tumor and metastatic lymph nodes in non‐small cell lung cancer

c‐MET has recently been identified as a promising novel target in non‐small cell lung cancer (NSCLC). We detected the consistency of c‐MET gene amplification in metastatic lymph nodes and tumor tissues of NSCLC patients and discuss the clinical application value of c‐MET gene amplification in metastatic lymph nodes.
On the design of the 5-DoF finger-wearable cutaneous haptic device

We propose a cube-type cutaneous haptic device that can be mounted on the user's fingertip and display 5-DoF (degree-of-freedom) touch/pressure to the fingerpad when manipulating objects in remote or simulated environments. For practical usability and high wearability/portability, we mainly aim to realize the haptic device having high-force multi-DoF functionality with compact and lightweight structure. To achieve the aim, multi-DoF miniature compliant mechanisms are designed and applied to the device as motion guides: a 3-DoF tip-tilt mechanism and a planar 2-DoF XY mechanism for displaying touch/pressure and shearing force, respectively. To reduce the overall size of the device, the two complaint mechanisms are designed with a flat structure and they are stacked in series. And as the actuators suitable for the compact wearable devices, the SMA (shape memory alloy) actuators well known as solid-state smart actuators are considered due to its high energy density (force-to-weight ratio) characteristics. The proposed haptic device is fabricated as a polymeric functional prototype with 3-dimensional printer. And the working performances of the device such as output displacement, force, and frequency response characteristic are experimentally evaluated.
THE STUDY ON THE MODIFICATION OF NEW MATERIAL USED FOR HIGH SLIP AND SPECIAL THREEPHASE ASYNCHRONOUS MOTOR ROTORS

It will be a break through in the new electric material field that study and develop a kind of new electric material of the low cost, high resistivity, good mechanical property use for high slip and special threephase asynchronous motor rotors, to replace traditional rotor aluminum. The purpose of this studying is reducing the costs of motors, raising quality of motors and increasing economic profit. This study will use Al 25%Si alloy to the motor rotors by the experimental method, and make synthetic experiment of the modification that is a key link of this material applying. Through study some modification method with P, RE, P and RE composite, P Cu, P Cu and Na composite, the results of modification are showed: synthetic effect of modification with P Cu and Na composite is better than other modification methods. And final conclusions are obtained: the resistivity is affected by the twofold result of modification of primary silicon and eutectic silicon; the tensile strength is affected mainly by the size and shape of primary silicon; the percentage elongation is affected mainly by the morphology of eutectic structure; the modification of new electrical material Al 25%Si alloy used for rotors with P Cu and Na composite make the resistivity is high, mechanical property is better and synthetic results are best.
PREFORMULATION STUDY OF BUCCOADHESIVE MONOLAYERED TABLETS OF CARVEDILOL .

The purpose of this research work was to establish mucoadhesive buccal tablets of carvedilol in the forms of monolayered tablets. The tablets were prepared using Sodium methyl cellulose (NaMC ) , sodium alginate and Methocel K15M as bioadhesive polymers to impart mucoadhesion. Buccal tablets were evaluated by different parameters such as weig ht uniformity, content uniformity, thickness, hardness, surface pH, swelling index, ex vivo mucoadhesive strength, In-vitro drug release, and I nvitro drug permeation. The present study concludes that mucoadhesive buccal tablets of carvedilol can be a good way to bypass the extensive hepatic first-pa ss metabolism and to improve the bio availability o f carvedilol.
Generic architecture of a social media-driven intervention support system for smart cities

With the growing adoption of Internet and mobile technology, the information exchange via social media has greatly influenced both government and corporate operations. Social Media has not only become a platform for mere entertainment and communication but a great source of innovation for public services. While millions of users generate data on these social media platforms everyday, the challenge is to effectively extract and analyze information from the big social data in a productive manner for improving public services of future smart and connected communities. In this paper, we propose a novel approach of creating an Intervention Support System (ISS) interface for public services of a city to easily and effectively monitor attitude trends of public for topics of interest (e.g., a cleanliness awareness campaign), while hiding all the complex functionality of collecting, processing, and mining big user-generated data from social media. We first discuss the generic architecture of ISS and its various components, followed by demonstrating the efficacy of the proposed architecture via an application design to identify intervention targets on social networks for supporting public campaigns against the key societal crisis of gender-based violence. We conclude with the challenges, limitations, and future work direction to effectively assist future smart city services via big data analytics approaches.