Miracle-dz/UniFAR-FTUs huggingface dataset:
Selective Impairment in Frequency Discrimination in a Mouse Model of Tinnitus

Tinnitus is an auditory disorder, which affects millions of Americans, including active duty service members and veterans. It is manifested by a phantom sound that is commonly restricted to a specific frequency range. Because tinnitus is associated with hearing deficits, understanding how tinnitus affects hearing perception is important for guiding therapies to improve the quality of life in this vast group of patients. In a rodent model of tinnitus, prolonged exposure to a tone leads to a selective decrease in gap detection in specific frequency bands. However, whether and how hearing acuity is affected for sounds within and outside those frequency bands is not well understood. We induced tinnitus in mice by prolonged exposure to a loud mid-range tone, and behaviorally assayed whether mice exhibited a change in frequency discrimination acuity for tones embedded within the mid-frequency range and high-frequency range at 1, 4, and 8 weeks post-exposure. A subset of tone-exposed mice exhibited tinnitus-like symptoms, as demonstrated by selective deficits in gap detection, which were restricted to the high frequency range. These mice exhibited impaired frequency discrimination both for tones in the mid-frequency range and high-frequency range. The remaining tone exposed mice, which did not demonstrate behavioral evidence of tinnitus, showed temporary deficits in frequency discrimination for tones in the mid-frequency range, while control mice remained unimpaired. Our findings reveal that the high frequency-specific deficits in gap detection, indicative of tinnitus, are associated with impairments in frequency discrimination at the frequency of the presumed tinnitus.
Static and Dynamic Robust PCA via Low-Rank + Sparse Matrix Decomposition: A Review

Principal Components Analysis (PCA) is one of the most widely used dimension reduction techniques. Robust PCA (RPCA) refers to the problem of PCA when the data may be corrupted by outliers. Recent work by Candes, Wright, Li, and Ma defined RPCA as a problem of decomposing a given data matrix into the sum of a low-rank matrix (true data) and a sparse matrix (outliers). The column space of the low-rank matrix then gives the PCA solution. This simple definition has lead to a large amount of interesting new work on provably correct, fast, and practically useful solutions to the RPCA problem. More recently, the dynamic (time-varying) version of the RPCA problem has been studied and a series of provably correct, fast, and memory efficient tracking solutions have been proposed. Dynamic RPCA (or robust subspace tracking) is the problem of tracking data lying in a (slowly) changing subspace while being robust to sparse outliers. This article provides an exhaustive review of the last decade of literature on RPCA and its dynamic counterpart (robust subspace tracking), along with describing their theoretical guarantees, discussing the pros and cons of various approaches, and providing empirical comparisons of performance and speed.
Prophylaxis with levofloxacin: impact on bacterial susceptibility and epidemiology in a hematopoietic stem cell transplant unit

Background The emergence of resistance has been demonstrated in cancer treatment centers where prophylaxis with fluoroquinolone is used. Objective Considering the importance of epidemiological monitoring as a strategy in choosing protocols involving antibiotics, this study aimed to evaluate the emergence of quinolone resistance and changes in the local epidemiology in a hematopoietic stem cell transplant service. Methods For this study, 60 positive cultures before the prophylactic use of levofloxacin (period A: 2007-2008) and 118 cultures after starting the use of prophylactic levofloxacin (period B: 2010-2011) were evaluated. Results Resistance increased for all the different types of bacteria isolated (from 46.0% to 76.5%; p-value = 0.0002). Among Gram-negative bacteria, resistance increased from 21.4% to 60.7% (p-value = 0.0163) and among Gram-positive bacteria, it increased from 55.6% to 82.9% (p-value = 0.0025). The use of levofloxacin increased from 19.44 defined daily doses per 1,000 patient-days in period A to 166.64 in period B. The use of broad spectrum antibiotics remained unchanged. Considering bacteria associated with infection, 72 and 76 were isolated in periods A and B, respectively. There was a reduction in the rate of Gram-negative bacteria in cultures associated with infection (3.81 vs. 2.00 cultures/1,000 patient-days; p-value = 0.008). Conclusion The study of prophylaxis with levofloxacin demonstrated that there was a decrease in infections by Gram-negative bacteria; however, bacterial resistance increased, even though the use of broad-spectrum antibiotics remained unchanged. Constant monitoring of local epidemiology combined with research on clinical outcomes is needed to evaluate the effectiveness of prophylaxis. © 2014 Associação Brasileira de Hematologia, Hemoterapia e Terapia Celular. All rights reserved.
Continuing medical education effect on clinical outcomes: effectiveness of continuing medical education: American College of Chest Physicians Evidence-Based Educational Guidelines.

BACKGROUND As opportunities for quality improvement become more visible, educational planners, health services researchers, and policymakers search for strategies that lead to better clinical outcomes. Continuing medical education (CME) is one such strategy, but the impact of CME is poorly defined in relation to clinical outcomes, and efforts to standardize definitions of clinical outcomes are in varied stages of development. METHODS The Johns Hopkins University Evidence-based Practice Center conducted a systematic review of the effectiveness of CME for the Agency for Health Care Research and Quality. From the review, 37 studies were used by the guideline panel to answer questions about improvement in clinical outcomes. Recommendations were made using the American College of Chest Physicians guideline grading system. RESULTS Multiple media, multiple techniques of instruction, and multiple exposures to content are suggested to meet instructional objectives intended to improve clinical outcomes. CONCLUSIONS There are models to describe and guide the planning and evaluation of CME, and there are models to measure quality of care. Research and practice of CME must be defined in relation to guideline implementation and quality improvement and other interventions and systems intended to improve or measure clinical outcomes. Further research is required to identify the qualities essential for measuring causal linkages thought to exist among CME, physician behavior, and clinical outcomes.
Application of Virtual Patients in Undergraduate Dental Education

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More effective drugs lead to harder selective sweeps in the evolution of drug resistance in HIV-1

In the early days of HIV treatment, drug resistance occurred rapidly and predictably in all patients, but under modern treatments, resistance arises slowly, if at all. The probability of resistance should be controlled by the rate of generation of resistance mutations. If many adaptive mutations arise simultaneously, then adaptation proceeds by soft selective sweeps in which multiple adaptive mutations spread concomitantly, but if adaptive mutations occur rarely in the population, then a single adaptive mutation should spread alone in a hard selective sweep. Here, we use 6717 HIV-1 consensus sequences from patients treated with first-line therapies between 1989 and 2013 to confirm that the transition from fast to slow evolution of drug resistance was indeed accompanied with the expected transition from soft to hard selective sweeps. This suggests more generally that evolution proceeds via hard sweeps if resistance is unlikely and via soft sweeps if it is likely. DOI: http://dx.doi. org/10.7554/eLife.10670. 001
Imperfect Secrecy in Wiretap Channel II

In a point-to-point communication system, which consists of a sender, a receiver, and a set of noiseless channels, the sender wishes to transmit a private message to the receiver through the channels, which may be eavesdropped by a wiretapper. The set of wiretap sets is arbitrary. The wiretapper can access any one but not more than one wiretap set. From each wiretap set, the wiretapper can obtain some partial information about the private message, which is measured by the equivocation of the message given the symbols obtained by the wiretapper. The security strategy is to encode the message with some random key at the sender. Only the message is required to be recovered at the receiver. Under this setting, we define an achievable rate tuple consisting of the size of the message, the size of the key, and the equivocation for each wiretap set. We first prove a tight rate region when both the message and the key are required to be recovered at the receiver. Then, we extend the result to the general case when only the message is required to be recovered at the receiver. Moreover, we show that even if stochastic encoding is employed at the sender, the message rate cannot be increased.
Realistic Transformation of Facial and Vocal Smiles in Real-Time Audiovisual Streams

Research in affective computing and cognitive science has shown the importance of emotional facial and vocal expressions during human-computer and human-human interactions. But, while models exist to control the display and interactive dynamics of emotional expressions, such as smiles, in embodied agents, these techniques can not be applied to video interactions between humans. In this work, we propose an audiovisual smile transformation algorithm able to manipulate an incoming video stream in real-time to parametrically control the amount of smile seen on the user's face and heard in their voice, while preserving other characteristics such as the user's identity or the timing and content of the interaction. The transformation is composed of separate audio and visual pipelines, both based on a warping technique informed by real-time detection of audio and visual landmarks. Taken together, these two parts constitute a unique audiovisual algorithm which, in addition to providing simultaneous real-time transformations of a real person's face and voice, allows to investigate the integration of both modalities of smiles in real-world social interactions.
Hydroalcoholic extract of Zataria multiflora mitigates cisplatin-induced oxidative stress, apoptosis and hepatotoxicity in mice

Cisplatin (CP), as an anticancer drug, causes hepatotoxicity. Zataria multiflora Boiss (ZM), as a herbal medicine, has antioxidant property and decrease oxidative stress-induced toxicity and side effects. This study investigated the effects of hydroalcoholic extract of ZM against cisplatin-induced hepatotoxicity. In this experimental study, thirty-two male mice were randomly divided into four groups (8/group). The control group; ZM group was received ZM (200 mg/kg) during 7 days by gavage; CP group was received CP (10 mg/kg) intraperitoneally in 5th day of study; ZM + CP group. Serum biochemical [alanine aminotransferases (ALT), aspartate aminotransferase (AST) and alkaline phosphatase (ALP)], tissue biochemical [malondialdehyde (MDA), protein carbonyl (PC) and glutathione (GSH) content], histopathological and immunohistochemical assays were examined to determine hepatotoxicity. CP caused significant increase in ALT, AST and ALP, oxidative stress (increased of MDA, PC and decreased of GSH in liver tissues), histological changes (hepatocellular degeneration, necrosis, inflammatory cell infiltration, congestion, sinusoidal dilatation). ZM significantly mitigated the toxic effects of CP on the liver tissue and oxidative stress (p<0.01 and p<0.05, respectively). Furthermore, CP increased caspase-3 immunoreactivity (apoptosis) (21.85 ± 6.81) and ZM administration significantly reduced immunoreactivity of caspase-3 compared with CP-treated mice (10.66 ± 3.23). The findings of this study showed that the ZM as a potential antioxidant compound and with scavenging free radicals, hepatic injury and suppression of caspase-3 expression attenuated the hepatotoxicity induced cisplatin.
Profile metacognitive awareness of biology education students in microbiology course

Metacognitive ability refers to self-cognitive awareness and the process of how cognitive works and how to manage them. The lack of metacognitive ability causes students to get less able to use appropriate learning strategies that will affect the cognitive abilities. This study aims to determine the profile of metacognitive awareness of students of the microbiology course and the relationship between metacognitive awareness and the ability to understand the concept of microbiology. The subjects of the study were 28 students who took microbiology courses at Educational Institutions and Teachers in West Java. The metacognitive data awareness was collected using the Metacognitive Awareness Inventory (MAI) and the understanding ability measured by multiple choice test. Data were analyzed using descriptive statistics. The conclusion shows that students metacognitive ability in the microbiology course is still low. The percentage of student’s metacognitive ability criterion showed less indication (32%), enough (43%), good (25%). There is a relationship between the metacognitive awareness criteria and the ability to understand the basic concepts of microbiology. Students who have less and enough metacognitive awareness criteria obtained understanding ability score lower than the good criteria.
Human Pose Estimation with Parsing Induced Learner

Human pose estimation still faces various difficulties in challenging scenarios. Human parsing, as a closely related task, can provide valuable cues for better pose estimation, which however has not been fully exploited. In this paper, we propose a novel Parsing Induced Learner to exploit parsing information to effectively assist pose estimation by learning to fast adapt the base pose estimation model. The proposed Parsing Induced Learner is composed of a parsing encoder and a pose model parameter adapter, which together learn to predict dynamic parameters of the pose model to extract complementary useful features for more accurate pose estimation. Comprehensive experiments on benchmarks LIP and extended PASCAL-Person-Part show that the proposed Parsing Induced Learner can improve performance of both single- and multi-person pose estimation to new state-of-the-art. Cross-dataset experiments also show that the proposed Parsing Induced Learner from LIP dataset can accelerate learning of a human pose estimation model on MPII benchmark in addition to achieving outperforming performance.
Overview of Current Challenges in Self-Pierce Riveting of Lightweight Materials

This paper shows an overview of different analyses regarding current challenges at self-pierce riveting with solid rivets as well as semi-tubular rivets of lightweight materials like aluminum die casting, carbon fiber reinforced plastic and 7xxx series aluminum alloy. The joining process analyses will demonstrate the cause and the development as well as the influence on joint quality of individual joining process-induced defects. In addition, methods are described how these imperfections can be avoided or reduced.
Multiple Granularity Group Interaction Prediction

Most human activity analysis works (i.e., recognition or prediction) only focus on a single granularity, i.e., either modelling global motion based on the coarse level movement such as human trajectories or forecasting future detailed action based on body parts' movement such as skeleton motion. In contrast, in this work, we propose a multi-granularity interaction prediction network which integrates both global motion and detailed local action. Built on a bidirectional LSTM network, the proposed method possesses between granularities links which encourage feature sharing as well as cross-feature consistency between both global and local granularity (e.g., trajectory or local action), and in turn predict long-term global location and local dynamics of each individual. We validate our method on several public datasets with promising performance.
Representing and Learning High Dimensional Data with the Optimal Transport Map from a Probabilistic Viewpoint

In this paper, we propose a generative model in the space of diffeomorphic deformation maps. More precisely, we utilize the Kantarovich-Wasserstein metric and accompanying geometry to represent an image as a deformation from templates. Moreover, we incorporate a probabilistic viewpoint by assuming that each image is locally generated from a reference image. We capture the local structure by modelling the tangent planes at reference images. Once basis vectors for each tangent plane are learned via probabilistic PCA, we can sample a local coordinate, that can be inverted back to image space exactly. With experiments using 4 different datasets, we show that the generative tangent plane model in the optimal transport (OT) manifold can be learned with small numbers of images and can be used to create infinitely many 'unseen' images. In addition, the Bayesian classification accompanied with the probabilist modeling of the tangent planes shows improved accuracy over that done in the image space. Combining the results of our experiments supports our claim that certain datasets can be better represented with the Kantarovich-Wasserstein metric. We envision that the proposed method could be a practical solution to learning and representing data that is generated with templates in situatons where only limited numbers of data points are available.
Adaptive Control with Unknown Parameters in Reference Input

In this paper, model reference adaptive control problem is considered with reference input dependent upon the unknown parameters of the system. Due to the uncertainty in the reference input, conventional linear-in-parameters adaptive controller cannot achieve the control objective without enforcing persistent excitation (PE). A new technique is presented for introducing an excitation signal and regulating its magnitude, dependent upon the convergence of the output tracking and parameter errors. Intelligent excitation ensures parameter convergence similar to conventional PE, but initiates only when necessary. As a result, the regulated output tracks the unknown reference input. Simulations illustrate the theoretical findings
Metastatic Breast Lobular Carcinoma Involving Tamoxifen-Associated Endometrial Polyps: Report of Two Cases and Review of Tamoxifen-Associated Polypoid Uterine Lesions

Two cases of lobular breast carcinoma metastatic to an endometrial polyp are described. Both patients had been treated with tamoxifen and presented with abnormal uterine bleeding. Histology of endometrial biopsy in both cases showed typical tamoxifen-associated endometrial polyps with focal subtle stromal infiltration by metastatic lobular breast carcinoma. This was confirmed by positive immunohistochemical staining with cytokeratin epithelial markers. Metastatic breast carcinoma may rarely involve tamoxifen-associated endometrial polyps. Because primary endometrial carcinomas may also arise within tamoxifen polyps, these should be extensively sampled. We briefly review polypoid uterine lesions that may occur secondary to tamoxifen therapy.
PENGEMBANGAN MEDIA PEMBELAJARAN UNTUK MENINGKATKAN HASIL BELAJAR SISWA

Media pembelajaran adalah adalah alat yang dapat membantu proses belajar mengajar sehingga makna pesan yang disampaikan menjadi lebih jelas dan tujuan pendidikan atau pembelajaran dapat tercapai dengan efektif dan efisien. Hasil belajar adalah hasil yang diberikan kepada siswa berupa penilaian setelah mengikuti proses pembelajaran dengan menilai pengetahuan, sikap, ketrampilan pada diri siswa dengan adanya perubahan tingkah laku. Media pembelajaran berfungsi sebagai salah satu sumber belajar bagi siswa untuk memperoleh pesan dan informasi yang berikan oleh guru sehingga materi pembelajaran dapat lebih meningkat dan membentuk pengetahuan bagi siswa.Manfaat dari media pembelajaran, pertama, memberikan pedoman bagi guru untuk mencapai tujuan pembelajaran sehingga dapat menjelaskan materi pembelajaran dengan urutan yang sistematis dan membantu dalam penyajian materi yang menarik untuk meningkatkan kualitas pembelajaran, kedua, dapat meningkatkan motivasi dan minat belajara siswa sehingga siswa dapat berpikir dan menganalisis materi pelajaran yang diberikan oleh guru dengan baik dengan situasi belajar yang menyenangkan dan siswa dapat memahami materi pelajaran dengan mudah.Yang dapat meningkatkan hasil belajar siswa dengan adanya media pembelajaran: proses belajar mengajar menjadi mudah dan menarik sehingga siswa dapat mengerti dan memahami pelajaran dengan mudah, efisiensi belajar siswa dapat meningkat karena sesuai dengan tujuan pembelajaran, membantu konsentrasi belajar siswa karena media pembelajaran yang menarik dan sesuai dengan kebutuhan siswa, meningkatkan motivasi belajar siswa karena perhatian siswa terhadap pelajaran dapat meningkat, memberikan pengalaman menyeluruh dalam belajar sehingga siswa dapat memahami secara nyata dari materi yang diberikan lebih mengerti materi secara keseluruhan, siswa terlibat dalam proses pembelajaran sehingga siswa aktif mengikuti dan terlibat dalam proses pembelajaran dan siswa memiliki kesempatan melakukan kreativitas dan mengembangkan potensi yang dimiliki. Kata Kunci : Media Pembelajaran dan Hasil Belajar Siswa