Miracle-dz/UniFAR-FTUs huggingface dataset:
The Stigma of Voice-Hearing Experiences: Religiousness and Voice-Hearing Contents Matter

Extensive research confirms that people with psychotic disorders suffer high levels of social stigma on average. However, psychotic-like experiences show incredible diversity and cannot reasonably be understood as a monolithic category. It is plausible that voice-hearing experiences with benign content might elicit less stigma than those with negative content, and researchers have hypothesized that culturally or theologically consistent voice-hearing experiences might elicit no stigma at all. The present study evaluated these hypotheses by testing how voice-hearing experiences that varied in terms of valence and the presence or absence of religious content affected stigma responses (i.e., perceived dangerousness and desired social distance) among people who were high or low in religiousness. Participants read vignettes describing two people who hear voices: one with positive content (complimentary, supportive) and the other negative (insulting, homicidal). Via random assignment, half read vignettes that attributed the voice to Abraham Lincoln whereas the other half read vignettes that replaced the words Abraham Lincoln with the word God. Results suggested that different voice-hearing contents elicited different levels of stigma. More religious participants perceived God-hearers to be less dangerous and desired particularly low levels of social distance from people who were described as hearing the voice of God saying positive things. Religiousness was associated with decreased stigma only in the context of specific voice-hearing experiences, lending support to the hypothesis that the stigma of voice-hearing experiences is determined as a simultaneous function of the contents of the experiences and the cultural context within which they are embedded.
Rate Control for Scalable Multimedia Applications in Network-on-Chips

Network-on-Chip (NoC) architectures are emerged as a promising solution to the lack of scalability in Multi-Processor Systems-on-Chips (MPSoCs). With the explosive growth in the usage of multimedia applications, it is expected that NoC serves as a multimedia server supportingmulti-class services. This paper addresses rate control problem for applications with scalable multimedia services in Network-on-Chip architectures. Scalable multimedia applications are relying on multi-class services which use layered encoding schemes. We formulate the rate control for multimedia with multi-class services using the optimization approach. This allows us to devise an iterative rate control algorithm as the solution to the optimization problem. The rate control algorithm can be implemented using a controller with low computational overhead. The validity of the obtained expressions is demonstrated by comparing results predicted by the analytical model against those attained through extensive simulation experiments.
Fetal Hemoglobin Inducers from the Natural World: A Novel Approach for Identification of Drugs for the Treatment of β-Thalassemia and Sickle-Cell Anemia

The objective of this review is to present examples of lead compounds identified from biological material (fungi, plant extracts and agro-industry material) and of possible interest in the field of a pharmacological approach to the therapy of β-thalassemia using molecules able to stimulate production of fetal hemoglobin (HbF) in adults. Concerning the employment of HbF inducers as potential drugs for pharmacological treatment of β-thalassemia, the following conclusions can be reached: (i) this therapeutic approach is reasonable, on the basis of the clinical parameters exhibited by hereditary persistence of fetal hemoglobin patients, (ii) clinical trials (even if still limited) employing HbF inducers were effective in ameliorating the symptoms of β-thalassemia patients, (iii) good correlation of in vivo and in vitro results of HbF synthesis and γ-globin mRNA accumulation indicates that in vitro testing might be predictive of in vivo responses and (iv) combined use of different inducers might be useful to maximize HbF, both in vitro and in vivo. In this review, we present three examples of HbF inducers from the natural world: (i) angelicin and linear psoralens, contained in plant extracts from Angelica arcangelica and Aegle marmelos, (ii) resveratrol, a polyphenol found in grapes and several plant extracts and (iii) rapamycin, isolated from Streptomyces hygroscopicus.
Performance analysis of audio streaming in secure wireless access network

Advances in the Internet and multimedia technologies have spurred many research efforts in Internet-based multimedia access system. In this paper, we presented such a model and framework for delivering real-time traffics to a wireless access network over public Internet protocol (IP) backbone network. We have presented a performance analysis of audio streaming when IP tunneling network using generic route encapsulation (GRE) along with Internet protocol security (IPSec) is implemented. The impacts on performance, with particular attention to Quality of Service (QoS) characteristics have been evaluated through a series of experiments. In this paper, the effects of a compression scheme based on compressed real-time transport protocol (CRTP) and resource reservation protocol (RSVP) are analyzed when delivering real-time traffics to the wireless access network through secured IP network.
Standardized Follow-up of Patients with Symptomatic Knee Osteoarthritis Treated with a Single Intra-articular Injection of a Combination of Cross-Linked Hyaluronic Acid and Mannitol

Objectives The objective of this study is to obtain pilot data from daily practice conditions of a viscosupplement made of a cross-linked high-molecular-weight hyaluronic acid (HA) combined with mannitol in patients with knee osteoarthritis (KOA). Methods The data of 40 consecutive patients, 29 women and 11 men, who were prospectively followed up for 6 months, using a standardized procedure, were retrospectively analyzed. All patients have received a single intra-articular injection of H Anox-M-XL (4.4 mL), viscosupplement made of a cross-linked HA (16 mg/mL) + mannitol (35 mg/mL), in the target knee. The primary outcome was safety. The secondary end points included 3- and 6-month change in the WOMAC pain (0–50) and WOMAC total (0–240) and patient's global assessment (PGA). Patient's self-assessment of treatment efficacy (0–3) and analgesic consumption were obtained at months 3 and 6. An intent-to-treat analysis was performed. Results Mean (SD) age was 60.7 (13.9) years, and mean BMI was 28.6 (5.0). Kellgren–Lawrence radiological grade was I/II and III/IV in 13 and 27 of the subjects, respectively. The average WOMAC pain and WOMAC total scores at baseline were 21.5 (9.8) and 89.9 (42.8), respectively. Thirty-nine patients completed the follow-up. HAnox-M-XL was well tolerated; two patients experienced knee pain after injection, which resolved within three days. No treatment-related severe adverse event was reported. Mean (SD) variations in WOMAC pain and WOMAC total scores were –8.2 (8.9) and –38.4 (35.6), respectively, at month 6 (P = 0.001). PGA decreased from 5.5 (2.0) to 3.0 (2.2) (P = 0.006). Efficacy was rated as good or very good in 76.9% of the cases. Most of the regular analgesics users decreased their consumption. Conclusion Treatment with one injection of 4.4 mL HAnox-M-XL is effective to alleviate KOA symptoms over six months, without safety concern. Controlled trials are needed to confirm these pilot data.
M.sc. Mathematical Finance

Leasing, as a financial instrument, has become an interesting emerging factor in the tremendous leasing market today. Motivated by this exciting development in the new world of international business, I am presenting this essay to introduce many aspects of this attractive yet complex issue. Firstly, this essay describes a general introduction to financial leasing, including its advantages and different kinds of credit risks. Structure of the leasing market and a comparison of financial leasing and purchasing are briefly mentioned. Two major focuses of this essay are the pricing of leasing contracts and leasing credit risks. More specifically, I will discuss how to value the leasing contracts via a real-option approach by establishing the equilibrium conditions and lease rates of any term. Applying the same idea, pricing a forward lease rate can also be deduced. Regarding leasing with credit risks, the determination of equilibrium lease rates is subjected to the possibility of default risks. This concept is also discussed in detail. Moreover, with support of real data, the current leasing industry in China is discussed with real applications in the telecommunication industry. The influence of banks participating as the leasing organization and leasing strategy for banks are two concepts presented as a conclusion to this essay as they relate to the current leasing situation in China. ii Contents Abstract ii Contents iii Acknowledgements v 1 Introduction 1
Glial Cell Line-Derived Neurotrophic Factor Alters Axon Schwann Cell Units and Promotes Myelination in Unmyelinated Nerve Fibers

Glial cell line-derived neurotrophic factor (GDNF) plays an important role in the development and maintenance of a subset of dorsal root ganglion sensory neurons. We administered high-dose exogenous recombinant human GDNF (rhGDNF) daily to adult rats to examine its effect on unmyelinated axon–Schwann cell units in intact peripheral nerves. In rhGDNF-treated animals, there was a dramatic proliferation in the Schwann cells of unmyelinated fibers, which resulted in the segregation of many unmyelinated axons into a 1:1 relationship with Schwann cells and myelination of normally unmyelinated small axons. This study demonstrates that the administration of high doses of a growth factor to adult rats can change the phenotype of nerve fibers from unmyelinated to myelinated.
Better Shepherding Behaviors Using Improved Shepherd Locomotion Graduate Student Mentor

Flocking behavior is very common in nature, and there have been ongoing research efforts to simulate such behavior in computer animations and robotics applications. Shepherding is one type of flocking behavior in which an outside agent guides or shepherds the members of the flock. Simulating this shepherding behavior is interesting because of its commonality in nature. A sheep dog guiding a flock of sheep, cowboys driving a herd of cattle, a predator hunting a group of its prey, and a flock of geese following a mother goose are all examples of shepherding behaviors found in nature. Currently, little work has been done on simulating these types of behaviors. In this work, we investigate ways to improve existent methods of simulating singleagent shepherding behaviors. We define the locomotion of a shepherd, and we explore methods of increasing the efficiency of a shepherd in herding a flock from a start to a goal position.
On-line exact shortest distance query processing

Shortest-path query processing not only serves as a long established routine for numerous applications in the past but also is of increasing popularity to support novel graph applications in very large databases nowadays. For a large graph, there is the new scenario to query intensively against arbitrary nodes, asking to quickly return node distance or even shortest paths. And traditional main memory algorithms and shortest paths materialization become inadequate. We are interested in graph labelings to encode the underlying graphs and assign labels to nodes to support efficient query processing. Surprisingly, the existing work of this category mainly emphasizes on reachability query processing, while no sufficient effort has been given to distance labelings to support querying exact shortest distances between nodes. Distance labelings must be developed on the graph in whole to correctly retain node distance information. It makes many existing methods to be inapplicable. We focus on fast computing distance-aware 2-hop covers, which can encode the all-pairs shortest paths of a graph in O(|V|·|E|1/2) space. Our approach exploits strongly connected components collapsing and graph partitioning to gain speed, while it can overcome the challenges in correctly retaining node distance information and appropriately encoding all-pairs shortest paths with small overhead. Furthermore, our approach avoids pre-computing all-pairs shortest paths, which can be prohibitive over large graphs. We conducted extensive performance studies, and confirm the efficiency of our proposed new approaches.
A lattice Boltzmann model for natural convection in cavities

We study a multiple relaxation time lattice Boltzmann model for natural convection with moment–based boundary conditions. The unknown primary variables of the algorithm at a boundary are found by imposing conditions directly upon hydrodynamic moments, which are then translated into conditions for the discrete velocity distribution functions. The method is formulated so that it is consistent with the second–order implementation of the discrete velocity Boltzmann equations for fluid flow and temperature. Natural convection in square cavities is studied for Rayleigh numbers ranging from 103 to 106. An excellent agreement with benchmark data is observed and the flow fields are shown to converge with second order accuracy.
Octave spanning spectra and pulse compression by nondegenerate cascaded four-wave mixing: 2D simulation and experiment

We present a theoretical model and respective numerical simulation of cascaded four-wave mixing of femtosecond pulses in bulk chi(3) media, evidencing the importance of two-dimensional interaction geometries in the efficient generation of frequency-converted beams, and in agreement with the experimental results in terms spectral and spatial distribution and efficiency, demonstrating compression without the need of complex amplitude or phase control.
Super-Interpolation With Edge-Orientation-Based Mapping Kernels for Low Complex  $2\times $  Upscaling

With the advent of ultrahigh-definition (UHD) video services, super-resolution (SR) techniques are often required to generate high-resolution (HR) images from low-resolution (LR) images, such as HD images. To generate such HR images and a video of UHD resolutions in limited computing devices with hardware and software, low complex but excellent SR methods are particularly required. In this paper, we present a novel and fast SR method, called super-interpolation (SI), by unifying an interpolation step and a quality-enhancement step. The proposed SI method utilizes edge-orientation (EO)-based pre-learned kernels, which inherits the simplicity of interpolation and the quality enhancement of SR. It performs SR directly from the initial resolution of an input image to the target resolution of an up-scaled output image without requiring any intermediate interpolated image. The proposed SI method involves offline training and online up-scaling phases. In the offline training phase, training LR image patches are clustered based on their edge orientations into different EO classes for which class-dependent linear mapping functions are learned between training LR and HR image patches. In up-scaling phase, an HR output image patch for each LR input image patch is generated by applying an appropriate linear mapping function selected based on the EO of LR input image patch. Our proposed SI method is intensively compared with the ten state-of-the-art SR methods for common image sets and many HD/UHD images. The experimental results show that the SI method yields the smallest running time and requires relatively small hardware resources. It outperforms the six state-of-the-art methods in average (peak signal-to-noise ratio) PSNR/(structural similarity) SSIM, and exhibits competitive or somewhat lower PSNR/SSIM performance compared with the others.
Spectroscopy of Giant Stars in the Pyxis Globular Cluster

The Pyxis globular cluster is a recently discovered globular cluster that lies in the outer halo (Rgc∼40 kpc) of the Milky Way. Pyxis lies along one of the proposed orbital planes of the Large Magellanic Cloud (LMC), and it has been proposed to be a detached LMC globular cluster captured by the Milky Way. We present the first measurement of the radial velocity of the Pyxis globular cluster based on spectra of six Pyxis giant stars. The mean heliocentric radial velocity is ∼36 km s−1, and the corresponding velocity of Pyxis with respect to a stationary observer at the position of the Sun is ∼−191 km s−1. This radial velocity is a large enough fraction of the cluster’s expected total space velocity—assuming that it is bound to the Milky Way—that it allows strict limits to be placed on the range of permissible transverse velocities that Pyxis could have in the case that it still shares or nearly shares an orbital pole with the LMC. We can rule out that Pyxis is on a near circular orbit if it is Magellanic debris, but we cannot rule out an eccentric orbit associated with the LMC. We have calculated the range of allowed proper motions for the Pyxis globular cluster that result in the cluster having an orbital pole within 15° of the present orbital pole of the LMC and that are consistent with our measured radial velocity, but verification of the tidal capture hypothesis must await proper motion measurement from the Space Interferometry Mission or Hubble Space Telescope. A spectroscopic metallicity estimate of [Fe/H ] = -1.4 ± 0.1 is determined for Pyxis from several spectra of its brightest giant; this is consistent with photometric determinations of the cluster metallicity from isochrone fitting.
Efficiently communicating map updates with the pose graph

Robot mapping is a task that can benefit a lot from cooperative multi-robot systems. In multi-robot simultaneous localization and mapping (SLAM), it becomes very important how efficiently a given map can be shared among the robot team. To this end, the recently proposed pose graph map representation is used, adapted for use in a particle filter based mapping algorithm, and compared to the standard occupancy grid representation. Through analysis of corner cases as well as experiments with real robot data, the two map representations are thoroughly compared. It is shown that the pose graph representation allows for much more efficient communication of map updates than the standard occupancy grid.
Vibrating needle insertion for trajectory optimization

Minimally invasive percutaneous medical procedures are widely accepted in current clinical practice. However, with current technologies, the procedures are challenging and a high level of expertise is required to perform them successfully. In many of these procedures, the needle and the tissue deforms and displaces substantially as the needle is advanced to its target. This paper presents a novel approach to reduce the tissue displacement and the needle insertion trajectory error by combining a vibrating mode with continuous low velocity needle insertion mode. And a new way to modeling this vibrating insertion is proposed. Through theoretical analysis, the tissue and needle equative rigidity can be greatly improved. Preliminary experimental results verify that the deformation error can be greatly reduced if suitable kinetic parameters are being chosen.
Homocysteine levels and risk of hip fracture in postmenopausal women.

BACKGROUND Recent studies suggest that high homocysteine levels are associated with an increased risk of fractures. Homocysteine levels are known to be influenced by vitamin B and folate supply or status, and poor renal function can result in higher levels independent of nutritional adequacy. OBJECTIVE The aim of the study was to determine the associations between fasting homocysteine levels and incident hip fractures, and the effects of other factors on hip fracture risk. DESIGN We conducted a case-control study in the Women's Health Initiative Observational Study, a study of postmenopausal women (n = 93,676) recruited in the United States. We selected 400 incident cases of hip fracture and 400 controls matched on age, ethnicity, and blood draw date among women not on osteoporosis therapies. Outcome measures included physician-adjudicated, incident hip fractures. Baseline lifestyle and nutritional questionnaires were performed. RESULTS The risk of hip fracture increased 1.38-fold [95% confidence interval (CI), 1.14, 1.66] for each sd increase in serum homocysteine level after adjustment for fracture risk factors. This association was not affected by adjustment for dietary folate, B6, or B12 intake, but it diminished after adjustment for cystatin-C level (odds ratio, 1.08; 95% CI, 0.66-1.79), a measure of renal function not affected by muscle mass. Among women in the highest quartile of homocysteine and cystatin-C compared to those without elevations in either biomarker, the risk of hip fracture was substantially elevated (odds ratio, 2.8; 95% CI, 1.61-4.87). CONCLUSIONS This study indicates that high homocysteine levels are associated with an increased risk of hip fracture, which could be accounted for by poor renal function.
Human Activity Recognition by Means of Online Semi-supervised Learning

Human activity recognition (HAR) is a reasonably recent field of study for the computer science community. It aims at automatically analysing ongoing events and extract their context from the captured data. The detection of human activities, such as walking, running, falling, or even cycling, allows for several heterogeneous applications, from surveillance systems to patient monitoring systems. Despite being a particularly active field of study in the past years, HAR still leaves many strategies left to explore and key aspects left to address. There are two main approaches in terms of data extraction: Video and sensors. The sensor approach is, however, the most promising, due to its extreme portability and unobtrusiveness. Most sensor-based HAR systems are trained in a static dataset with Supervised Learning techniques, generating a classification model with a relatively low error rate. However, these systems commonly ignore one of HAR's challenges, the difference of input signals produced by different people when doing the same activities. Consequently, as a user's movements drift from the generic, the system error increases. The activity classification method should therefore be able to generate adapted results for each different user. This article exhibits and discloses an under explored approach to this problem: By means of Online Semi-supervised Learning, An incremental technique capable of adapting the classification model to the user of the application by continuously updating it as the data from the user's own specific input signals arrives. This is possible due to the nature of Semi-supervised learning, which trains on both labeled and unlabeled data, making it possible to keep learning even after reaching its final user, without the need of any manual input.
Face Recognition Using Two-Dimensional Discriminant Locality Preserving Projections

One of the key issues of face recognition is to extract the features of face images, and a new method of feature extraction, two-dimensional discriminate locality preserving projections (2D-DLPP), is proposed. 2D-DLPP benefits from three techniques, i.e., locality preserving projections (LPP), image based projection and discriminant analysis. Firstly, LPP is an effective feature extraction method that optimally preserves the local structure of the samples. Secondly, compared to vector based projection, image based projection can reduce the complexity of algorithm, avoid the small sample size problem and give more spatial structural information of image. Finally, discriminant analysis applied in 2D-DLPP can improve recognition performance by maximizing the interpersonal distance and minimizing the intrapersonal distance. Experiments are performed to test and evaluate the algorithm using the ORL and the Yale face databases. The Experimental results show that 2D-DLPP has better face recognition performance than other methods.