Miracle-dz/UniFAR-FTUs huggingface dataset:
Antibody mediated immune responses induced by intranasal immunization with rTgPGAM2 in association with adjuvants in mice

Objective To investigate the mucosal immune responses induced by intranasal immunization with rTgPGAM2 in association with adjuvants in mice.Methods Forty-eight 6-week-old BALB/c mice were randomly divided into six groups,with eight mice in each group.The mice in immunized groups were immunized intranasally three times with 500 IU IL-2,1 000 IU IFN-γ,30 μg rTgPGAM2,30 μg rTgPGAM2 plus 500 IU IL-2,or 30 μg rTgPGAM2 plus 1 000 IU IFN-γ. Mice were immunized 3 times,with a respite of 14 d after the 1st and 2nd immunization and a respite of 7 d after the 2nd and 3rd immunization.Control mice were administered 20 μl PBS.All animals were sacrificed on day 14 after the third immunization.The levels of IgA and IgG in sera and sIgA in nasopharynx washes,vaginal washes,and intestinal washes were detected using ELISA.Results The groups administered rTgPGAM2 plus IL-2 and rTgPGAM2 plus IFN-γ had markedly higher levels of IgA and IgG in sera compared to the PBS group(F= 18.653 and 8.853,P0.05). Immunized groups had significantly higher levels(F=6.670 and 7.288,P0.05) of sIgA in nasopharynx washes and vaginal washes compared to the control group.The groups administered rTgPGAM2 plus IL-2 group and rTgPGAM2 plus IFN-γ had significantly higher levels of sIgA in intestinal washes compared to the PBS group(F=4.557,P0.05). Conclusion Antibody-mediated immune responses were induced in mice by intranasal immunization with rTgPGAM2 alone or with adjuvant.rTgPGAM2 plus IL-2 induced the greatest antibody response.
Cannabis and Cognitive Functioning: Author's acknowledgements

Is the cognitive function of long-term regular cannabis users impaired, and if so, what is the nature of this impairment? This timely and well-argued volume provides an extensive and comprehensive critical review of the literature relevant to cannabis and cognitive functioning, examining the evidence in the light of important recent findings on the pharmacology and neuropsychology of cannabis. Her conclusion, that long-term cannabis use produces subtle but enduring impairment in memory, attention and the organization and integration of complex information, will be of compelling interest to a wide range of clinicians, researchers and policy makers.
Un análisis del proceso de aprendizaje social en animales no humanos: situaciones apetitivas versus aversivas* An Analysis of Social Learning Process in No Human Animals: Appetitive Versus Aversive Settings

a b s t R a C t This paper attempts to identify whether the components involved in different processes of social learning, both imitative and non imitative, evaluated in appetitive contexts can be identified in an aversive context. This identification will allow us to appraise the goodness and/or limitations of the concepts and their heuristic value. The paper begins with the definitions of learning, individual learning and social learning, followed by the definition of the different processes of social learning in appetitive contexts, with emphasis in conceptual and experimental difficulties. Then, the definition of the different processes of social learning in aversive context is proposed and the paper concludes with a discussion about differences and similarities in both contexts.
Assessment on Early Impairment of Left Ventricular Myocardial Systolic Function in Patients With Rheumatoid Arthritis by Speckle Tracking Strain Imaging

Objective: To assess the early impairment of left ventricular(LV) myocardial systolic function in patients with rheumatoid arthritis(RA) by speckle tracking strain imaging.Methods: Our work included two groups,RA group,n=25 patients,and Control group,n=25 healthy subjects from normal physical examination.Standard echo and speckle tracking strain imaging were conducted to analyze and compare the LV systolic peak longitudinal strain with strain rate from apical 4-chamber,2-chamber and 3-chamber views and LV systolic peak circumferential strain with strain rate from short axis views at mitral valve,papillary and apical levels between two groups.Results: There were no statistic differences observed by standard echo and tissue Doppler imaging between two groups.Compared with Control group,RA group showed reduced apical longitudinal strain of 4-chamber and 2-chamber,P0.05,while all short axis circumferential strain and strain rate were increased,P0.01. The apical longitudinal strain of 4-chamber and 2-chamber were positively related with disease duration(r=0.372 and r=0.308,P0.05 respectively). The apical short axis circumferential strain was negatively related with disease duration(r=-0.435,P0.01). Conclusion: RA patients may have abnormal LV systolic function as reduced peak longitudinal strain even they have normal result by standard echo examination.Speckle tracking strain imaging is an effective method for detecting the early LV systolic dysfunction in RA patients.
Mobilität nach der beruflichen Ausbildung: Eine empirische Studie für Westdeutschland

In diesem Beitrag wird die Dauer der Betriebszugehorigkeit eines Jugendlichen im Anschlus an eine Berufsausbildung im dualen System untersucht. Auf der Basis einer Stichprobe von 4.627 Ausbildungsabsolventen wird gezeigt, das die Betriebszugehorigkeitsdauer sowohl von Merkmalen das Ausbildungsbetriebes als auch von denen des Auszubildenden sowie der gesamtwirtschaftlichen Situation bestimmt wird. In Betrieben mit hohen Nettoausbildungskosten herrschen langere Betriebszugehorigkeitsdauern vor. Des weiteren wird die Bereitschaft von Betrieben zur "Ausbildung uber Bedarf" festgestellt. Eine erhohte Ausbildungsbereitschaft, etwa in der Zeit einer angespannten Situation auf dem Arbeitsmarkt fur Jugendliche Mitte der achtziger Jahre, fuhrt jedoch zu geringeren Ubernahmequoten. Gleichzeitig hemmt der Uberschus an Ausbildungsabsolventen in dieser Zeit die Mobilitat der jungen Fachkrafte. Neben einer Bestimmung der Einflusfaktoren auf das Mobilitatsverhaltens von Ausbildungsabsolventen, leistet diese Untersuchung somit einen Beitrag zur Erklarung der Ausbildungsbereitschaft von Betrieben.
Lower Leg MRI Features in Axonal Charcot-Marie-Tooth Patients with MFN2 Mutations

Department of Neurology, Yonsei University College of Medicine, Seoul; Department of Neurology, Konkuk University College of Medicine, Seoul; Department of Neurology, Kyung Hee University East-West Neo Medical Center, Seoul; Department of Diagnostic Radiology, Hanyang University, College of Medicine, Kuri; Department of Biological Science, Kongju National University, Gongju; Department of Neurology, Ewha Womans University College of Medicine, Seoul, Korea
Measuring Cocaine Use by Hair Analysis among Criminally-Involved Youth

The study examined the utility of hair analysis for determining the prevalence of cocaine use in a high-risk population. Personal interviews and scalp hair specimens were obtained from 121 male youths who had been in jail in New York City and were followed-up in the community after their release. Using the standard cutoff, 51% of the hair specimens were classified positive for cocaine at a mean concentration of 87.6 nanograms per 10 milligrams of hair. Using the detection limit of the test, 67% were positive for cocaine. Only 23% of the youths reported any use of cocaine or crack during the previous 3 months and only 36% reported any lifetime use, indicating a substantial rate of underreporting. Associations were found between cocaine in hair and several behavioral variables: number of prior arrests (p=.08, trend), rearrest after release from jail (p<.05), not continuing education (p<.01), and no legal employment (p<.01). Hair analysis is a promising new epidemiological tool for obtaining more valid measures of illicit drug use in difficult-to-study populations.
Dinâmica de corpos lúteos em protocolos com redução da dose de FSH na superovulação em ovelhas

One of the major obstacles of MOTE is occurrence of failures in superovulation, and one reason may be the high dose of FSH, which can promote premature regression of the corpus luteum and therefore ineffective response to superovulation. The aim of the present study was to evaluate the effect of exogenous FSH dose in superstimulatory treatment on development dynamic and function of corpora lutea in embryo donor ewes. Twenty-nine Santa Inês ewes were submitted to estrus synchronization with an intravaginal progesterone device (CIDR), which was inserted on Day 0 and was remain until the Day 8. At the same time the beginning of the protocol and intravaginal device withdrawal was administered an analog of PGF2α. The gonadotropin treatment was commenced 48 hours before the CIDR withdrawal (D6), when females are randomly divided into three groups according to the total dose of exogenous porcine FSH: G200 (control, n = 9) 200 mg of FSH ; G133 (n = 10) 133 mg FSH; and G100 (n = 10) 100 mg of FSH. The total doses were administered in 8 to applications at 12 hour intervals (20, 20, 15, 15, 10, 10, 5 and 5% FSHp). In D6 (1st application FSH), females also received 300 IU of eCG. Evaluations ultrasound mode-B and Doppler were performed during the luteogênese period (D11) until the corresponding day of videolaparoscopy (D15), in order to follow the development of luteal structures (dimensions), evaluate the contents of the artery blood flow ovarian (VPS, EDV, RI and PI), and macroscopically evaluate the characteristics of the formed corpora lutea and classify them as normal or subnormal (premature regression) by laparoscopy. Statistical analysis was performed using the software R®, the level of significance was set at p <0.05. The superovulated sheep with 100 and 133 mg of FSH showed a gradual increase in the diameter of corpora lutea with passage of postovulation days (p <0.001), by contrast, the animals receiving treatment 200 mg of FSH showed increased diameter between 11 and 13 and decreased in 14 and 15 (p <0.001). The sheep exposed to superstimulatory treatment with 200 mg of FSH presented higher RPCL (49,03) in relation to the groups treated with 100 and 133 mg of FSH (p <0.001). The VDF was higher in superovulated sheep with 133 mg of FSH one day after the ovulation (D11) than in the superovulation 100 mg of FSH (p = 0.029). The IR was higher in superovulated sheep with 200 mg of superovulated that when 100 mg of FSH (p = 0.02). And the IP was higher in 14 and 15 than in the remaining days (p <0.01). The conclusion is that ultrasound is a powerful tool for tracking the luteal dynamics superstimulated sheep and minor exogenous FSH doses were sufficient for efficient superovulatory response in sheep, providing lower cost for the gonadotrophin treatment of female donors embryos.
Effect of intragastric resveratrol on the activity of the myeloperoxidase and cytochrome C oxidase in inflammatory reaction after the spinal cord injury in rats

Objective To investigate the effect of intragastric resveratrol on the activity of the myeloperoxidase( MPO) and cytochrome C oxidase( CCO) in inflammatory reaction after the spinal cord injury in rats. Methods A total of 96 adult male Sprague-Daw ley rats,w hich were selected from February 2008 to February 2012 in the Animal Department of People's Hospital of Wuhan University,were randomly divided into 4 groups. The model of moderate spinal cord injury was established according to Allen's technique. Rats were fed w ith resveratrol( 100 mg / kg) or methylprednisolone sodium( MPSS,100 mg / kg) through the tube. At the 8thh,the 1std,the 3rdd,and the 7thd after the spinal cord injury,the changes of MPO and CCO activity were observed using colorimetry and compared betw een the tw o groups. Results The difference of the activity of MPO and CCO betw een the tw o groups was significant at the 8thh,the 1std,the 3rdd,and the 7thd after the spinal cord injury( P 0. 01), indicating an protective effect of resveratrol on nerve cells after the spinal cord injury. Moreover,the difference of the effect betw een the resveratrol group and the MPSS group was observed at the 1std after the spinal cord injury( P 0. 01). Conclusion Resveratrol can protect the nerval cells after the spinal cord injury by inhibiting the activity of MPO and improving the activity of CCO.
ESRGAN+ : Further Improving Enhanced Super-Resolution Generative Adversarial Network

Enhanced Super-Resolution Generative Adversarial Network (ESRGAN) is a perceptual-driven approach for single image super-resolution that is able to produce photorealistic images. Despite the visual quality of these generated images, there is still room for improvement. In this fashion, the model is extended to further improve the perceptual quality of the images. We have designed a network architecture with a novel basic block to replace the one used by the original ESRGAN. Moreover, we introduce noise inputs to the generator network in order to exploit stochastic variation. The resulting images present more realistic textures.
A Fixation-Based 360° Benchmark Dataset For Salient Object Detection

Fixation prediction (FP) in panoramic contents has been widely investigated along with the booming trend of virtual reality (VR) applications. However, another issue within the field of visual saliency, salient object detection (SOD), has been seldom explored in 360° or omnidirectional) images due to the lack of datasets representative of real scenes with pixel-level annotations. Toward this end, we collect 107 equirectangular panoramas with challenging scenes and multiple object classes. Based on the consistency between FP and explicit saliency judgements, we further manually annotate 1,165 salient objects over the collected images with precise masks under the guidance of real human eye fixation maps. Six state-of-the-art SOD models are then benchmarked on the proposed fixation-based 360° image dataset (F-360iSOD), by applying a multiple cubic projection-based fine-tuning method. Experimental results show a limitation of the current methods when used for SOD in panoramic images, which indicates the proposed dataset is challenging. Key issues for 360° SOD is also discussed. The proposed dataset is available at https://github.com/PanoAsh/F-360iSOD.
Complexity, Stability Properties Of Mixed Games And Dynamic Algorithms, And 'Learning' In The Sharing Economy.

The Sharing Economy (which includes Airbnb, Apple, Alibaba, Uber, WeWork, Ebay, Didi Chuxing, Amazon) blossomed across the world, triggered structural changes in industries and significantly affected international capital flows primarily by disobeying a wide variety of statutes and laws in many countries. They also illegally reduced and changing the nature of competition in many industries often to the detriment of social welfare. This article develops new dynamic pricing models for the SEOs and derives some stability properties of mixed games and dynamic algorithms which eliminate antitrust liability and also reduce deadweight losses, greed, Regret and GPS manipulation. The new dynamic pricing models contravene the Myerson Satterthwaite Impossibility Theorem.
Adaptive Large Neighborhood Search for Circle Bin Packing Problem

We address a new variant of packing problem called the circle bin packing problem (CBPP), which is to find a dense packing of circle items to multiple square bins so as to minimize the number of used bins. To this end, we propose an adaptive large neighborhood search (ALNS) algorithm, which uses our Greedy Algorithm with Corner Occupying Action (GACOA) to construct an initial layout. The greedy solution is usually in a local optimum trap, and ALNS enables multiple neighborhood search that depends on the stochastic annealing schedule to avoid getting stuck in local minimum traps. Specifically, ALNS perturbs the current layout to jump out of a local optimum by iteratively reassigns some circles and accepts the new layout with some probability during the search. The acceptance probability is adjusted adaptively using simulated annealing that fine-tunes the search direction in order to reach the global optimum. We benchmark computational results against GACOA in heterogeneous instances. ALNS always outperforms GACOA in improving the objective function, and in several cases, there is a significant reduction on the number of bins used in the packing.
Deep Depth Prior for Multi-View Stereo

It was recently shown that the structure of convolutional neural networks induces a strong prior favoring natural color images, a phenomena referred to as a deep image prior (DIP), which can be an effective regularizer in inverse problems such as image denoising, inpainting etc. In this paper, we investigate a similar idea for depth images, which we call a deep depth prior. Specifically, given a color image and a noisy and incomplete target depth map from the same viewpoint, we optimize a randomly initialized CNN model to reconstruct an RGB-D image where the depth channel gets restored by virtue of using the network structure as a prior. We propose using deep depth priors for refining and inpainting noisy depth maps within a multi-view stereo pipeline. We optimize the network parameters to minimize two losses 1) a RGB-D reconstruction loss based on the noisy depth map and 2) a multi-view photoconsistency-based loss, which is computed using images from a geometrically calibrated camera from nearby viewpoints. Our quantitative and qualitative evaluation shows that our refined depth maps are more accurate and complete, and after fusion, produces dense 3D models of higher quality.
Wide-Area Measurement System-Based Low Frequency Oscillation Damping Control Through Reinforcement Learning

Ensuring the stability of power systems is gaining more attention today than ever before due to the rapid growth of uncertainties in load and increased renewable energy penetration. Lately, wide-area measurement system (WAMS)-based centralized controlling techniques are offering flexibility and more robust control to keep the system stable. WAMS-based controlling techniques, however, face pressing challenges of irregular delays in long-distance communication channels and subsequent responses of equipment to control actions. This paper presents an innovative control strategy for damping down low-frequency oscillations in transmission systems. The method uses a reinforcement learning technique to overcome the challenges of communication delays and other non-linearity in wide-area damping control. It models the traditional problem of oscillation damping control as a novel faster exploration-based deep deterministic policy gradient (DDPG-S). An effective reward function is designed to capture necessary features of oscillations enabling timely damping of such oscillations, even under various kinds of uncertainties. A detailed analysis and a systematically designed numerical validation are presented to prove feasibility, scalability, interpretability, and comparative performance of the modelled low-frequency oscillation damping controller. The benefit of the technique is that stability is ensured even when uncertainties of load and generation are on the rise.
You Foot the Bill! Attacking NFC With Passive Relays

Imagine when you line up in a store, the person in front of you can make you pay her bill by using a passive wearable device that forces a scan of your credit card or mobile phones without your awareness. An important assumption of today’s near-field communication (NFC)-enabled cards is the limited communication range between the commercial reader and the NFC cards. Previous approaches effectively used mobile phones and active relays to break the range limit of NFC propagation for the NFC attack. However, these approaches require a power supply and protocol modification when mobile phones or active relays transmit NFC signals. We propose ReCoil, a system that uses passive relays to attack NFC-enabled mobile phones or cards by expanding the communication range of NFC to 49.6 cm, an obvious improvement over its intended commercial distance. ReCoil is a magnetically coupled resonant wireless power transfer system, which optimizes the energy transfer by searching the optimal geometry parameters. Specifically, we first narrow down the feasible area reasonably and design the ReCoil-greedy algorithm such that the relays absorb the maximum energy from the reader. In order to reroute the signal to pass over the surface of the human body, we then design a half waistband by carefully analyzing the impact of the distance and orientation between two coils on the mutual inductance. Then, three more coils are added to the system to keep enlarging the communication range. Finally, extensive experiment results validate our analysis, showing that our passive relays consisting of common copper wires and tunable capacitors can expand the range of NFC to 49.6 centimeters.
Isometry theorem of Cartan-Hadamard manifold

Cartan-Hadamard manifold is a simply connected Riemannian manifold with non-positive sectional curvature. In this article, we have proved that a Cartan-Hadamard manifold satisfying steady gradient Ricci soliton with the integral condition of potential function is isometric to the Euclidean space. Next we have proved a compactness theorem for gradient shrinking Ricci soliton satisfying some scalar curvature condition. Finally, we have showed that a gradient expanding Ricci soliton with linear volume growth and positive potential function is an Einstein manifold.
An Approach for Time-aware Domain-based Social Influence Prediction

Online Social Networks(OSNs) have established virtual platforms enabling people to express their opinions, interests and thoughts in a variety of contexts and domains, allowing legitimate users as well as spammers and other untrustworthy users to publish and spread their content. Hence, the concept of social trust has attracted the attention of information processors/data scientists and information consumers/business firms. One of the main reasons for acquiring the value of Social Big Data (SBD) is to provide frameworks and methodologies using which the credibility of OSNs users can be evaluated. These approaches should be scalable to accommodate large-scale social data. Hence, there is a need for well comprehending of social trust to improve and expand the analysis process and inferring the credibility of SBD. Given the exposed environment's settings and fewer limitations related to OSNs, the medium allows legitimate and genuine users as well as spammers and other low trustworthy users to publish and spread their content. Hence, this paper presents an approach incorporates semantic analysis and machine learning modules to measure and predict users' trustworthiness in numerous domains in different time periods. The evaluation of the conducted experiment validates the applicability of the incorporated machine learning techniques to predict highly trustworthy domain-based users.