bluuebunny/crossref_metadata_2025 huggingface dataset:
Endoscopic Ultrasound-Guided Hepaticogastrostomy With Lumen-Apposing Metal Stent for Management of Pyogenic Liver Abscess
Authors: Desai Aditi , Manvar Amar , Ho Sammy
Published: September 2019

A 45-year-old man presented with abdominal pain, fever with chills, nonproductive cough, mild pleurisy, and anorexia. Computed tomography scan showed a heterogeneously enhancing mass in the left hepatic lobe with leukocytosis and elevated C-reactive protein. Interval growth of the lesion was noted on magnetic resonance imaging obtained several days after admission. Given the clinical suspicion for pyogenic liver abscess and favorable location in the left hepatic lobe, endoscopic ultrasound-guided drainage was pursued. The patient underwent endoscopic ultrasound-guided hepaticogastrostomy with a lumen-apposing metal stent. His symptoms gradually abated after procedure. Radiographic resolution of the abscess was noted 1 week after stent placement, and the stent was subsequently removed. He had no clinical or radiographic evidence of recurrence at 1-month follow-up.
Budd-Chiari Syndrome in a Patient With Simultaneous Diagnosis of Hepatic Sarcoidosis and Nodular Regenerative Hyperplasia
Authors: Odah Tarek , Al-Khazraji Ahmed , Idriss Rajab , Morrow Matthew , Curry Michael P.
Published: September 2019

Budd-Chiari syndrome (BCS) is a rare vascular disorder characterized by an obstruction of the hepatic venous outflow. Nodular regenerative hyperplasia (NRH) may develop as a result of an underlying autoimmune disease such as hepatic sarcoidosis. Only a few case reports have described cases with either NRH or hepatic sarcoidosis associated with BCS. We present a 42-year-old man presenting with BCS and signs of portal hypertension who was found to have an underlying pathological diagnosis of both hepatic sarcoidosis and NRH and who was successfully treated with a transjugular intrahepatic portosystemic shunt.
Sigmoid Neovagina: A Case Presentation and Pathological Review of Intestinal Transfer
Authors: Long Amanda , Leroy Kyley , Wong Patricia
Published: September 2019

Intestinal vaginoplasty, first described in 1904, has more recently become a popular mechanism for gender-affirming surgery in the United States. We present the case of a transgender female patient with retained foreign bodies in her neovagina, which required endoscopic therapy, provide a brief review of the literature, and discuss the potential long-term complications that can arise from a neovagina after intestinal transfer. It is important that gastroenterologists have awareness and recognition of these issues, as surgical reconstruction using intestinal segments for transgender patients becomes more common.
Use of Tofacitinib for the Treatment of Arthritis Associated With Ulcerative Colitis
Authors: Wang Wenfei , Cleveland Noa Krugliak , Ollech Jacob , Rubin David T.
Published: September 2019

Tofacitinib is a Janus kinase 1–3 inhibitor initially approved for the treatment of rheumatoid arthritis and now approved for the treatment of moderately to severely active ulcerative colitis (UC). We present the case of a patient with UC and seronegative inflammatory arthritis in whom arthritis progressed while on vedolizumab and was successfully treated with tofacitinib. This case provides insight into the use of tofacitinib for the treatment of UC and a concomitant extraintestinal manifestation of joint involvement.
Ekstraksi Zat Warna Dari Daun Jambu Biji Australia (Psidium Guajava L)
Authors: Haryadi Ichwan , Hidayati Nur
Published: September 2019

Abstrak Daun jambu biji Australia (Psidium guajava l) yang berwarna merah kecoklatan memiliki potensi sebagai zat warna alami karena daun jambu biji Australia mengandung senyawa tanin yang berwarna kecoklatan. Penelitian ini dilakukan untuk memperoleh zat warna alami dari daun jambu biji Australia dan juga untuk mengkaji pengaruh jenis pelarut dan metode ekstraksi terhadap kualitas dan rendemen zat warna yang dihasilkan. Variasi jenis pelarut meliputi larutan alkohol, asam asetat, asam klorida, sodium hidroksida, dan air netral biasa. Sedangkan metode yang digunakan adalah cara maserasi konvensional dan berbantuan gelombang ultrasonik. Larutan ekstrak daun jambu biji Australia diukur absorbansinya menggunakan spektrofotometer UV-Vis dengan panjang gelombang 525 nm. Nilai absorbansi larutan ekstrak tertinggi ditunjukkan oleh larutan dengan menggunakan larutan alkohol dan sodium hidroksida dengan metode maserasi berbantuan gelombang ultrasonik, yaitu sebesar 2,205 dan diatas 3. Sedangkan rendemen tertinggi dihasilkan dengan metode konvensional dan menggunakan pelarut alkohol sebanyak 5.1%. Kata kunci : daun jambu australia; maserasi; ultrasonifikasi; zat warna alami
Comparison of detection percentage and morphology of myocardial bridge between conventional coronary angiography and coronary CT angiography
Authors: Eftekhar-Vaghefi Seyed Hassan , Pourhoseini Somayeh , Movahedi Maryam , Hooshmand Shohre , Ostovan Mohammad Ali , Dehghani Pooyan , Ostovan Nikan
Published: September 2019

Introduction: Myocardial bridge (MB) is a congenital anomaly in which a segment of a coronary artery is surrounded by myocardium. In our study, we want to use conventional coronary angiography (CCA) to describe morphologic characteristics of MB (unidentified or identified) in the patients with documented evidence of MB in coronary computed tomography angiography (CCTA). Methods: The present study was designed as cross-sectional and was conducted on 47 patients with documented evidence of MB in CCTA, who were referred to Nemazee and Faghihi hospitals for performing coronary angiography during a one year period. We compared the morphologic characteristics of tunneled segments, which were missed at CCA (unidentified), and the tunneled segments which were identified with CCA. Results: In sum, MB was found in 16 (34%) patients at CCA (identified), and it was not found in 31 (66%) patients (unidentified) based on compression sign. No significant correlation was found between the percentage of systolic compression and the length and depth of the tunneled segment in identified group (r=0.73, P = 0.18; r=1.09, P = 0.15; respectively). Degree of atherosclerotic plaque formation (diameter stenosis, percentage) (mean, 0.25 (25%) ±0.29; range, 0-0.98) of the tunneled segments in unidentified group was significantly more than the same degree (mean, 0.07 (7%) ±0.13; range, 0-0.41) of the identified group (P = 0.03). The measurement of the trapezoid area under the tunneled segment with this formula [(MB length+ intramyocardial segment) ×depth/2] had significant relation with systolic compression (r=0.304, P = 0.03) and defined the cut-off value of 250 mm2 as the value of significant difference in detecting myocardial bridging with CCA. Conclusion: Our results showed that in most of identified MBs in CCA the tunneled segment area was equal and more than 250 mm2. In addition, the degree of atherosclerotic plaque of the tunneled segments at CCA was significantly more in unidentified group.
Better treatment option in chronic superficial femoral artery occlusive disease: comparison of methods (meta-analysis)
Authors: Starodubtsev Vladimir , Karpenko Andrey , Lenko Evgeniy , Ignatenko Pavel
Published: September 2019

Introduction: The objective is to evaluate the frequency of primary obstruction events (PrO) during one-year follow-up after performing excisional atherectomy with the SilverHawk/TurboHawk atherectomy device (S/TH) or remote superficial femoral artery endarterectomy (RSFAE) in patients with the chronic superficial femoral artery occlusive disease (СSFAOD). Methods: We included all randomized clinical trials (RCTs) and not-RCTs concerning the treatment of patients with СSFAOD after S/TH and RSFAE without duration. Results: Twenty-nine items (1990-2017) were discovered; 27 articles on the levels of evidence were included in qualitative synthesis; 9 studies (meta-analysis) were included in quantitative synthesis. The results of 2762 patients’ treatment were summed up in our analysis (1422 patients S/TH; 1340 patients RSFAE). All included reports were at low risk of bias. According to the criterion "frequency of PrO" during one-year follow-up, the pooled Hazard Ratios indicate significant favours of S/TH if compared it with RSFAE (HR= 0.66 (0.57 to 0.76, P < 0.00001), I2 = 9%). Conclusion: Our study showed that S/TH with the SpiderFX device (distal embolic protection) are safe and effective treatment option for short lesion (<15 cm) in patients with СSFAOD. The usage of S/TH methods significantly reduced number of PrO if compared it with RSFAE. In long-segment lesion (>15 cm) in patients with СSFAOD, RSFAE may be considered better than an endovascular procedure. But still it is necessary to conduct well-planned randomized studies to determine effectiveness and safety of the compared methods (S/TH and RSFAE) in patients with long-segment lesion (>15 cm).
Keeping Pace: A Practitioner-Focused Review of Pacing Strategies in Running
Authors: Pryor J. Luke , Johnson Evan C. , Yoder Hillary A. , Looney David P.
Published: September 2019

The purposeful distribution of speed, power, or energy is termed as the pacing or pacing strategy and is recognized as a key determinant in optimal run performance. There is no agreement on the best pacing strategy for all runners and race types. Thus, the challenge posed to runners and practitioners is pacing strategy selection and in-race adherence. This review briefly discusses pacing strategy types and selection considerations. More importantly, we overview factors influencing pacing and translate key findings from research into useable evidence-based recommendations for pacing strategy preparation and adherence during competition.
Rapid Memory Reactivation at Movie Event Boundaries Promotes Episodic Encoding
Authors: Silva Marta , Baldassano Christopher , Fuentemilla Lluís
Published: September 2019

Segmentation of continuous experience into discrete events is driven by rapid fluctuations in encoding stability at context shifts (i.e., event boundaries), yet the mechanisms underlying the online formation of event memories are poorly understood. We investigated the neural per-time point spatial similarity patterns of the scalp electrophysiological (EEG) activity of 30 human participants (male and female) watching a 50 min movie and found that event boundaries triggered the rapid reinstatement of the just-encoded movie event EEG patterns. We also found that the onset of memory reinstatement at boundary onset was accompanied by a left-lateralized anterior negative ERP effect, which likely reflects the detection of a shift in the narrative structure of the movie. A data-driven approach based on Hidden Markov modeling allowed us to detect event boundaries as shifts between stable patterns of brain EEG activity during encoding, and to identify their reactivation during a free recall task. These results provide the first neurophysiological underpinnings for how the memory systems segment a continuous long stream of experience into episodic events.

SIGNIFICANCE OF STATEMENTMemory for specific episodic events are the building blocks of our autobiographical memory. However, it is still unclear how the memory systems structure the unfolding experience into discrete event units that can be understood and remembered at the long-term. Here, we show that the detection of context shifts, or event boundaries, during a 50 min movie viewing triggers the rapid memory reactivation of the just-encoded event to promote its successful encoding into long-term memory. By finding that memory reactivation, a neural mechanism critical for episodic memory formation and consolidation, takes place under these ecologically valid experimental circumstances, our results provide valuable insights into how the brain shapes the ongoing experience into episodic memories in the real-life.
Altered Dynamics of Canonical Feedback Inhibition Predicts Increased Burst Transmission in Chronic Epilepsy
Authors: Pothmann Leonie , Klos Christian , Braganza Oliver , Schmidt Sarah , Horno Oihane , Memmesheimer Raoul-Martin , Beck Heinz
Published: September 2019

Inhibitory interneurons, organized into canonical feedforward and feedback motifs, play a key role in controlling normal and pathological neuronal activity. We demonstrate prominent quantitative changes in the dynamics of feedback inhibition in a rat model of chronic epilepsy (male Wistar rats). Systematic interneuron recordings revealed a large decrease in intrinsic excitability of basket cells and oriens-lacunosum moleculare interneurons in epileptic animals. Additionally, the temporal dynamics of interneuron recruitment by recurrent feedback excitation were strongly altered, resulting in a profound loss of initial feedback inhibition during synchronous CA1 pyramidal activity. Biophysically constrained models of the complete feedback circuit motifs of normal and epileptic animals revealed that, as a consequence of altered feedback inhibition, burst activity arising in CA3 is more strongly converted to a CA1 output. This suggests that altered dynamics of feedback inhibition promote the transmission of epileptiform bursts to hippocampal projection areas.

SIGNIFICANCE STATEMENTWe quantitatively characterized changes of the CA1 feedback inhibitory circuit in a model of chronic temporal lobe epilepsy. This study shows, for the first time, that dynamic recruitment of inhibition in feedback circuits is altered and establishes the cellular mechanisms for this change. Computational modeling revealed that the observed changes are likely to systematically alter CA1 input-output properties leading to (1) increased seizure propagation through CA1 and (2) altered computation of synchronous CA3 input.
Gluco-metabolic effects of oral and intravenous alcohol administration in men
Authors: Lanng Amalie R , Gasbjerg Lærke S , Bergmann Natasha C , Bergmann Sigrid , Helsted Mads M , Gillum Matthew P , Hartmann Bolette , Holst Jens J , Vilsbøll Tina , Knop Filip K
Published: September 2019

Background

Ingestion of the calorically dense compound alcohol may cause metabolic disturbances including hypoglycaemia, hepatic steatosis and insulin resistance, but the underlying mechanisms are uncertain. The gastrointestinal tract is well recognised as a major influencer on glucose, protein and lipid metabolism, but its role in alcohol metabolism remains unclear.

Objective

To examine the effects of oral and intravenous alcohol, respectively, on plasma concentrations of several gluco-regulatory hormones including serum/plasma insulin, C-peptide, glucagon, glucose-dependent insulinotropic polypeptide (GIP), glucagon-like peptide 1 (GLP-1) and fibroblast growth factor 21 (FGF21).

Design and methods

In a double-blinded, randomised, crossover design, we subjected 12 healthy men to intragastric ethanol infusion (IGEI) and an isoethanolaemic intravenous ethanol infusion (IVEI) (0.7 g alcohol per kg body weight), respectively, on two separate experimental days.

Results

Isoethanolaemia during the two alcohol administration forms was obtained (P = 0.38). During both interventions, plasma glucose peaked after ~30 min and thereafter fell below baseline concentrations. GIP and GLP-1 concentrations were unaffected by the two interventions. Insulin concentrations were unaffected by IGEI but decreased during IVEI. C-peptide, insulin secretion rate and glucagon concentrations were lowered similarly during IGEI and IVEI. FGF21 concentrations increased dramatically (nine-fold) and similarly during IGEI and IVEI.

Conclusions

Alcohol does not seem to affect the secretion of incretin hormones but decreased insulin and glucagon secretion independently of gut-derived factors. IGEI as well as IVEI potently stimulate FGF21 secretion indicating a gut-independent effect of alcohol on FGF21 secretion in humans.
Increased risk of thyroid disease in Danish women with polycystic ovary syndrome: a cohort study
Authors: Glintborg Dorte , Rubin Katrine Hass , Nybo Mads , Abrahamsen Bo , Andersen Marianne
Published: September 2019

Aim

To investigate risk of thyroid disease in Danish women with PCOS.

Design

National register-based study on women with PCOS in Denmark. 18,476 women had a diagnosis of PCOS in the Danish National Patient Register. PCOS Odense University Hospital (PCOS OUH, n = 1146) was an embedded cohort of women with PCOS and clinical and biochemical examination. Three age-matched controls were included for each woman with PCOS (n = 54,757). The main outcome measures were thyroid disease (hypothyroidism, Graves’ disease, goiter, thyroiditis) according to hospital diagnosis codes and/or inferred from filled medicine prescriptions. Associations between baseline TSH and development of cardio-metabolic disease was examined in PCOS OUH.

Results

The median (quartiles) age at inclusion was 29 (23–35) years and follow-up duration was 11.1 (6.9–16.0) years. The hazard ratio (95% CI) for thyroid disease development was 2.5 (2.3–2.7) (P < 0.001). The event rate of thyroid disease was 6.0 per 1000 patient-years in PCOS Denmark versus 2.4 per 1000 patient-years in controls (P < 0.001). Women in PCOS OUH with TSH ≥2.5 mIU/L (n = 133) had higher BMI (median 29 vs 27 kg/m2), wider waist, higher triglycerides and free testosterone by the time of PCOS diagnosis compared to women in PCOS OUH with TSH <2.5 mIU/L (n = 588). Baseline TSH did not predict later development of cardio-metabolic diseases in PCOS OUH.

Conclusions

The event rate of thyroid disease was significantly and substantially higher in women with PCOS compared to controls.
FOXL2 antagonises the male developmental pathway in embryonic chicken gonads
Authors: Major Andrew T , Ayers Katie L , Chue Justin , Roeszler Kelly N , Smith Craig A
Published: September 2019

FOXL2 is a conserved transcription factor with a central role in ovarian development and function. Studies in humans and mice indicate that the main role of FOXL2 is in the postnatal ovary, namely folliculogenesis. To shed light on the function and evolution of FOXL2 in the female gonad, we examined its role in embryonic avian gonads, using in ovo overexpression and knockdown. FOXL2 mRNA and protein are expressed female specifically in the embryonic chicken gonad, just prior to the onset of sexual differentiation. FOXL2 is expressed in the medullary cord cells, in the same cell type as aromatase (CYP19A1). In addition, later in development, expression also becomes localised in a subset of cortical cells, distinct from those expressing oestrogen receptor alpha. Misexpression of FOXL2 in the male chicken embryonic gonad suppresses the testis developmental pathway, abolishing local expression of the male pathway genes SOX9, DMRT1 and AMH and repressing Sertoli cell development. Conversely, knockdown of FOXL2 expression allows ectopic activation of SOX9 in female gonads. However, misexpression of FOXL2 alone was insufficient to activate aromatase expression in male gonads, while FOXL2 knockdown did not affect aromatase expression in females. These results indicate that FOXL2 plays an important role in embryonic differentiation of the avian ovary via antagonism of SOX9, but may be dispensable for aromatase activation at embryonic stages. The data suggest that FOXL2 has different roles in different species, more central for embryonic ovarian differentiation in egg-laying vertebrates.
Risk Factors for the Development of Esophagorespiratory Fistula in Esophageal Cancer
Authors: Paul Gregor , Bohle Wolfram , Zoller Wolfram
Published: September 2019

Background and Aims: The development of esophagorespiratory fistula (ERF) in esophageal cancer (EC) is a devastating complication, leading to poor survival rates and low quality of life. Goal of this study was to identify risk factors leading to fistula formation in esophageal cancer. Methods: We identified 47 patients with malignant ERF formation in EC in a period of 10 years. Clinical characteristics were compared by univariable analysis to 47 randomly selected patients with EC, but without ERF. A case-control study was conducted for patients with squamous cell carcinoma (SCC) and ERF matching in a 1:2 fashion for primary tumor localization. Results: Identifiable risk factors in EC patients were histology of SCC (P-value < 0.001), former or current smoking status (P = 0.002) and primary tumor localization in the proximal esophagus (P < 0.001). The "hot spot" for ERF formation was tumor growth 20-25cm distal to dental arch. An additional risk factor in SCC patients was age. Patients with ERF formation in SCC were younger than patients without ERF (median 63 vs. 67 years, P = 0.02). No difference in the rate of fistula formation was seen between esophagectomy and definitive chemoradiation, but the latter developed ERF earlier in the course of the disease (237 vs. 596.5 days, P = 0.01). Conclusion: Patients with proximal SCC of the esophagus and a smoking history, as well as young patients with SCC should be closely monitored for ERF formation.
Combination of non-invasive fibrosis tests: a solution for the prediction of advanced fibrosis in non-alcoholic fatty liver disease?
Authors: Lupşor-Platon Monica
Published: September 2019

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Efficient separation of five flavonoids from Oxytropis falcata bunge by high-speed counter-current chromatography and their anticancer activity
Authors: Chen Chen , Liu Fengqin , Zhao Jingyang , Chen Tao , Li Yulin , Zhang Dejun
Published: September 2019

Oxytropis falcata Bunge, known as the “king of herbs” in Tibetan medicine, is used for treatment of hyperpyrexia, pain, wounds, inflammation, and anthrax. However, it is difficult to efficiently isolate compounds with high purity from O. falcata because of the complexity of traditional Tibetan medicines. In this study, the 80% ethanol elution fraction from extract by AB-8 macroporous resin column chromatography was demonstrated to have anticancer activity on human hepatoma SMMC-7721 cells in vitro. Then, a high-speed counter-current chromatography (HSCCC) method was successfully established for separation of compounds by using hexane–ethyl acetate–methanol–water (10:4:10:10, v/v/v/v) as the solvent system. Five flavonoids (7-hydroxyflavonone [1], 5,7-dihydroxy-4′-methoxy flavonol [2], 5,7-dihydroxyflavanone [3], 2′,4′-dihydroxychalcone [4], and 2′,4′-dihydroxydihydrochalcone [5]) were obtained in one-step separation with purities of 97.7%, 98.1%, 98.3%, 99.0%, and 98.3%, respectively. Finally, anticancer activities against the growth of SMMC-7721 cells of 5 flavonoids were confirmed. The IC50 values of the separated compounds were 213.45 μg/mL, 197.74 μg/mL, 375.16 μg/mL, 17.44 μg/mL, and 136.83 μg/mL in 24 h, respectively. The present study provided a basis for further development and utilization of this medicinal herb as a source of a new potential anticancer agent.
The Problem of Living Standards and Quality of Life in the Age of Digitalization
Authors: Korshunov Gennady , Kroitor Svetlana
Published: September 2019

The authors substantiate the relevance of the study of the processes of digitalization of modern society. They show that the main factor of transformation in all spheres is information technology, which is the driver of the next industrial revolution. The researchers prove that at the current stage of social development the level of ICT development is one of the key indicators of the competitiveness of national economies. The article presents a number of examples of developed and developing countries where programs and strategies for the development of digital economies are already being implemented. The authors review similar programs and projects implemented in Belarus, analyze the experience of the Belarusian state in the development of infrastructure conditions and the legal framework on the way to the creation of an IT-country. The thesis that the process of digitalization of the economy, society and the state, on the one hand, opens up Windows of opportunity and growth for economic and social actors; on the other hand, it leads to the emergence of new, as yet unexplored, risks and threats. The advantages of sociological science as a tool to explore these new opportunities and risks based on the assessment and expectations of the population are shown. The sociological concepts "standard of living" and "quality of life" are considered and compared, the authors offer their interpretations of these notions. They prove that modern rapidly digitizing communities have access to the latest technologies and the ability to use them become powerful factors affecting the living standards and quality of life of individuals. The scientists investigate a number of contradictions preventing improvement of quality of life in the conditions of increasing digitalization of social processes, namely: unevenness of development of ICT in different spheres of activity of society and higher rates of development of technologies in comparison with the speed of their development by the population. On the base of analysis of statistical information and sociological research data the authors point out the factors reducing the digital readiness of the population including insufficient computer and digital literacy of the population, psychological conservatism, fear of facing threats to information security, lack of confidence in the usefulness and practical applicability of new knowledge. The researchers also formulate prospects of further research within the given problematics.
Migration Tenets of Main Socio-Demographic Groups of the Population of Belarus: Sociological Analysis
Authors: Artyukhin Mikchail , Pushkevich Sergey , Shurok Ella
Published: September 2019

The article deals with the migration of the population as a socio-economic, socio-political and sociocultural phenomenon. The authors carry out the analysis of the migration situation in Belarus and define its ambiguous character. The researchers show that starting from 2016 negative trends began to manifest themselves increasingly in the external migration of the population of Belarus. As a result of the collapse of the main migration indicators, the coefficient of compensation for natural loss of the population due to the positive migration balance fell sharply: in 2017 it amounted to only 23.1 %. The paper demonstrates that the need for multidimensional knowledge of the socioeconomic mechanisms of migration in the context of modern threats to national security has led to the demand for sociological research in the field of migration. This is especially true for studies that determine the main characteristics and typology of migration behavior of the main socio-demographic groups. The article presents the results of monitoring sociological research conducted by Institute of Sociology of the National Academy of Sciences of Belarus for the period 2010–2018. The data of these studies indicate a fairly high level of potential external migration of the population of the Republic of Belarus. To the greatest extent, migration activity is a characteristic of young age respondents. In this regard, the authors conclude that the increasing importance of migration in the political, economic and demographic development of society determines the need to develop adequate challenges of the state migration policy and socioeconomic mechanisms for the effective regulation of migration processes.
Factors Influencing Problem-Based Learning: Students’ and Teachers’ Perspectives
Authors: Charoensakulchai Sakarn , Kantiwong Anupong , Piyaraj Phunlerd
Published: September 2019

This article was migrated. The article was not marked as recommended. Aim : Problem-based learning(PBL) is a widely accepted teaching and learningmethod being used in most accredited medical schools. Phramongkutklao College of Medicine routinely utilized this powerful method. This paper involves the use of problem-based learning in teaching malaria sessionduring parasitology course. From our experience, there is a number of contributing factor to the success of PBL.The objective of this study is to critically explore students and teachers' perspectives on factors influencing PBL at our institution. Methods : A cross-sectional study was performed on 204 medical students and 25 medical educators. Demographic data and perceptions toward PBL were obtained using electronic standardized questionnaire in 5 score rating scale. The questions were divided into 6 categories: objective and content, stress and anxiety, teachers' role, group work attitude, self-preparation and self-assessment. Independent T-test was used to compare means between students' and teachers' perspectives. Exploratory factor analysis (EFA) was used to explore loading factor of each factor. Results : The Cronbach's alpha revealed that the questionnaire was generally reliable (0.78). Objective and content (p-value 0.003), students' preparation (p-value 0.005) and student assessment (p-value 0.026) had significantly different view between students and teachers while the other topics shared parallel view by both groups. In addition, student assessment (λ = 0.84), student's preparation (λ = 0.83) and attitudes in group work (λ = 0.82) have high impact over PBL. Conclusions : It can be concluded that, both students and teachers had generally good attitude toward PBL. We concluded that good attitude and preparation in problem-based learning session from both students and teachers are vital to good quality and successfulness in implementation of problem-based learning.
Feature Sampling Based Unsupervised Semantic Clustering for Real Web Multi-View Content
Authors: Gong Xiaolong , Huang Linpeng , Wang Fuwei
Published: September 2019

Real web datasets are often associated with multiple views such as long and short commentaries, users preference and so on. However, with the rapid growth of user generated texts, each view of the dataset has a large feature space and leads to the computational challenge during matrix decomposition process. In this paper, we propose a novel multi-view clustering algorithm based on the non-negative matrix factorization that attempts to use feature sampling strategy in order to reduce the complexity during the iteration process. In particular, our method exploits unsupervised semantic information in the learning process to capture the intrinsic similarity through a graph regularization. Moreover, we use Hilbert Schmidt Independence Criterion (HSIC) to explore the unsupervised semantic diversity information among multi-view contents of one web item. The overall objective is to minimize the loss function of multi-view non-negative matrix factorization that combines with an intra-semantic similarity graph regularizer and an inter-semantic diversity term. Compared with some state-of-the-art methods, we demonstrate the effectiveness of our proposed method on a large real-world dataset Doucom and the other three smaller datasets.
Play as You Like: Timbre-Enhanced Multi-Modal Music Style Transfer
Authors: Lu Chien-Yu , Xue Min-Xin , Chang Chia-Che , Lee Che-Rung , Su Li
Published: September 2019

Style transfer of polyphonic music recordings is a challenging task when considering the modeling of diverse, imaginative, and reasonable music pieces in the style different from their original one. To achieve this, learning stable multi-modal representations for both domain-variant (i.e., style) and domaininvariant (i.e., content) information of music in an unsupervised manner is critical. In this paper, we propose an unsupervised music style transfer method without the need for parallel data. Besides, to characterize the multi-modal distribution of music pieces, we employ the Multi-modal Unsupervised Image-to-Image Translation (MUNIT) framework in the proposed system. This allows one to generate diverse outputs from the learned latent distributions representing contents and styles. Moreover, to better capture the granularity of sound, such as the perceptual dimensions of timbre and the nuance in instrument-specific performance, cognitively plausible features including mel-frequency cepstral coefficients (MFCC), spectral difference, and spectral envelope, are combined with the widely-used mel-spectrogram into a timbreenhanced multi-channel input representation. The Relativistic average Generative Adversarial Networks (RaGAN) is also utilized to achieve fast convergence and high stability. We conduct experiments on bilateral style transfer tasks among three different genres, namely piano solo, guitar solo, and string quartet. Results demonstrate the advantages of the proposed method in music style transfer with improved sound quality and in allowing users to manipulate the output.
Pathological Evidence Exploration in Deep Retinal Image Diagnosis
Authors: Niu Yuhao , Gu Lin , Lu Feng , Lv Feifan , Wang Zongji , Sato Imari , Zhang Zijian , Xiao Yangyan , Dai Xunzhang , Cheng Tingting
Published: September 2019

Though deep learning has shown successful performance in classifying the label and severity stage of certain disease, most of them give few evidence on how to make prediction. Here, we propose to exploit the interpretability of deep learning application in medical diagnosis. Inspired by Koch’s Postulates, a well-known strategy in medical research to identify the property of pathogen, we define a pathological descriptor that can be extracted from the activated neurons of a diabetic retinopathy detector. To visualize the symptom and feature encoded in this descriptor, we propose a GAN based method to synthesize pathological retinal image given the descriptor and a binary vessel segmentation. Besides, with this descriptor, we can arbitrarily manipulate the position and quantity of lesions. As verified by a panel of 5 licensed ophthalmologists, our synthesized images carry the symptoms that are directly related to diabetic retinopathy diagnosis. The panel survey also shows that our generated images is both qualitatively and quantitatively superior to existing methods.
Building Causal Graphs from Medical Literature and Electronic Medical Records
Authors: Nordon Galia , Koren Gideon , Shalev Varda , Kimelfeld Benny , Shalit Uri , Radinsky Kira
Published: September 2019

Large repositories of medical data, such as Electronic Medical Record (EMR) data, are recognized as promising sources for knowledge discovery. Effective analysis of such repositories often necessitate a thorough understanding of dependencies in the data. For example, if the patient age is ignored, then one might wrongly conclude a causal relationship between cataract and hypertension. Such confounding variables are often identified by causal graphs, where variables are connected by causal relationships. Current approaches to automatically building such graphs are based on text analysis over medical literature; yet, the result is typically a large graph of low precision. There are statistical methods for constructing causal graphs from observational data, but they are less suitable for dealing with a large number of covariates, which is the case in EMR data. Consequently, confounding variables are often identified by medical domain experts via a manual, expensive, and time-consuming process.

We present a novel approach for automatically constructing causal graphs between medical conditions. The first part is a novel graph-based method to better capture causal relationships implied by medical literature, especially in the presence of multiple causal factors. Yet even after using these advanced text-analysis methods, the text data still contains many weak or uncertain causal connections. Therefore, we construct a second graph for these terms based on an EMR repository of over 1.5M patients. We combine the two graphs, leaving only edges that have both medical-text-based and observational evidence. We examine several strategies to carry out our approach, and compare the precision of the resulting graphs using medical experts. Our results show a significant improvement in the precision of any of our methods compared to the state of the art.
The Kelly Growth Optimal Portfolio with Ensemble Learning
Authors: Shen Weiwei , Wang Bin , Pu Jian , Wang Jun
Published: September 2019

As a competitive alternative to the Markowitz mean-variance portfolio, the Kelly growth optimal portfolio has drawn sufficient attention in investment science. While the growth optimal portfolio is theoretically guaranteed to dominate any other portfolio with probability 1 in the long run, it practically tends to be highly risky in the short term. Moreover, empirical analysis and performance enhancement studies under practical settings are surprisingly short. In particular, how to handle the challenging but realistic condition with insufficient training data has barely been investigated. In order to fill voids, especially grappling with the difficulty from small samples, in this paper, we propose a growth optimal portfolio strategy equipped with ensemble learning. We synergically leverage the bootstrap aggregating algorithm and the random subspace method into portfolio construction to mitigate estimation error. We analyze the behavior and hyperparameter selection of the proposed strategy by simulation, and then corroborate its effectiveness by comparing its out-of-sample performance with those of 10 competing strategies on four datasets. Experimental results lucidly confirm that the new strategy has superiority in extensive evaluation criteria.
PerformanceNet: Score-to-Audio Music Generation with Multi-Band Convolutional Residual Network
Authors: Wang Bryan , Yang Yi-Hsuan
Published: September 2019

Music creation is typically composed of two parts: composing the musical score, and then performing the score with instruments to make sounds. While recent work has made much progress in automatic music generation in the symbolic domain, few attempts have been made to build an AI model that can render realistic music audio from musical scores. Directly synthesizing audio with sound sample libraries often leads to mechanical and deadpan results, since musical scores do not contain performance-level information, such as subtle changes in timing and dynamics. Moreover, while the task may sound like a text-to-speech synthesis problem, there are fundamental differences since music audio has rich polyphonic sounds. To build such an AI performer, we propose in this paper a deep convolutional model that learns in an end-to-end manner the score-to-audio mapping between a symbolic representation of music called the pianorolls and an audio representation of music called the spectrograms. The model consists of two subnets: the ContourNet, which uses a U-Net structure to learn the correspondence between pianorolls and spectrograms and to give an initial result; and the TextureNet, which further uses a multi-band residual network to refine the result by adding the spectral texture of overtones and timbre. We train the model to generate music clips of the violin, cello, and flute, with a dataset of moderate size. We also present the result of a user study that shows our model achieves higher mean opinion score (MOS) in naturalness and emotional expressivity than a WaveNet-based model and two off-the-shelf synthesizers. We open our source code at https://github.com/bwang514/PerformanceNet
Private Model Compression via Knowledge Distillation
Authors: Wang Ji , Bao Weidong , Sun Lichao , Zhu Xiaomin , Cao Bokai , Yu Philip S.
Published: September 2019

The soaring demand for intelligent mobile applications calls for deploying powerful deep neural networks (DNNs) on mobile devices. However, the outstanding performance of DNNs notoriously relies on increasingly complex models, which in turn is associated with an increase in computational expense far surpassing mobile devices’ capacity. What is worse, app service providers need to collect and utilize a large volume of users’ data, which contain sensitive information, to build the sophisticated DNN models. Directly deploying these models on public mobile devices presents prohibitive privacy risk. To benefit from the on-device deep learning without the capacity and privacy concerns, we design a private model compression framework RONA. Following the knowledge distillation paradigm, we jointly use hint learning, distillation learning, and self learning to train a compact and fast neural network. The knowledge distilled from the cumbersome model is adaptively bounded and carefully perturbed to enforce differential privacy. We further propose an elegant query sample selection method to reduce the number of queries and control the privacy loss. A series of empirical evaluations as well as the implementation on an Android mobile device show that RONA can not only compress cumbersome models efficiently but also provide a strong privacy guarantee. For example, on SVHN, when a meaningful (9.83,10−6)-differential privacy is guaranteed, the compact model trained by RONA can obtain 20× compression ratio and 19× speed-up with merely 0.97% accuracy loss.
On Strength Adjustment for MCTS-Based Programs
Authors: Wu I-Chen , Wu Ti-Rong , Liu An-Jen , Guei Hung , Wei Tinghan
Published: September 2019

This paper proposes an approach to strength adjustment for MCTS-based game-playing programs. In this approach, we use a softmax policy with a strength index z to choose moves. Most importantly, we filter low quality moves by excluding those that have a lower simulation count than a pre-defined threshold ratio of the maximum simulation count. We perform a theoretical analysis, reaching the result that the adjusted policy is guaranteed to choose moves exceeding a lower bound in strength by using a threshold ratio. The approach is applied to the Go program ELF OpenGo. The experiment results show that z is highly correlated to the empirical strength; namely, given a threshold ratio 0.1, z is linearly related to the Elo rating with regression error 47.95 Elo where −2≤z
≤2. Meanwhile, the covered strength range is about 800 Elo ratings in the interval of z in [−2,2]. With the ease of strength adjustment using z, we present two methods to adjust strength and predict opponents’ strengths dynamically. To our knowledge, this result is state-of-the-art in terms of the range of strengths in Elo rating while maintaining a controllable relationship between the strength and a strength index.
MetaStyle: Three-Way Trade-off among Speed, Flexibility, and Quality in Neural Style Transfer
Authors: Zhang Chi , Zhu Yixin , Zhu Song-Chun
Published: September 2019

An unprecedented booming has been witnessed in the research area of artistic style transfer ever since Gatys et al. introduced the neural method. One of the remaining challenges is to balance a trade-off among three critical aspects—speed, flexibility, and quality: (i) the vanilla optimization-based algorithm produces impressive results for arbitrary styles, but is unsatisfyingly slow due to its iterative nature, (ii) the fast approximation methods based on feed-forward neural networks generate satisfactory artistic effects but bound to only a limited number of styles, and (iii) feature-matching methods like AdaIN achieve arbitrary style transfer in a real-time manner but at a cost of the compromised quality. We find it considerably difficult to balance the trade-off well merely using a single feed-forward step and ask, instead, whether there exists an algorithm that could adapt quickly to any style, while the adapted model maintains high efficiency and good image quality. Motivated by this idea, we propose a novel method, coined MetaStyle, which formulates the neural style transfer as a bilevel optimization problem and combines learning with only a few post-processing update steps to adapt to a fast approximation model with satisfying artistic effects, comparable to the optimization-based methods for an arbitrary style. The qualitative and quantitative analysis in the experiments demonstrates that the proposed approach achieves high-quality arbitrary artistic style transfer effectively, with a good trade-off among speed, flexibility, and quality.
Y2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences
Authors: Han Zhizhong , Shang Mingyang , Wang Xiyang , Liu Yu-Shen , Zwicker Matthias
Published: September 2019

Jointly learning representations of 3D shapes and text is crucial to support tasks such as cross-modal retrieval or shape captioning. A recent method employs 3D voxels to represent 3D shapes, but this limits the approach to low resolutions due to the computational cost caused by the cubic complexity of 3D voxels. Hence the method suffers from a lack of detailed geometry. To resolve this issue, we propose Y2Seq2Seq, a view-based model, to learn cross-modal representations by joint reconstruction and prediction of view and word sequences. Specifically, the network architecture of Y2Seq2Seq bridges the semantic meaning embedded in the two modalities by two coupled “Y” like sequence-tosequence (Seq2Seq) structures. In addition, our novel hierarchical constraints further increase the discriminability of the cross-modal representations by employing more detailed discriminative information. Experimental results on cross-modal retrieval and 3D shape captioning show that Y2Seq2Seq outperforms the state-of-the-art methods.
MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons
Authors: Zhang Malu , Wu Jibin , Chua Yansong , Luo Xiaoling , Pan Zihan , Liu Dan , Li Haizhou
Published: September 2019

One of the long-standing questions in biology and machine learning is how neural networks may learn important features from the input activities with a delayed feedback, commonly known as the temporal credit-assignment problem. The aggregate-label learning is proposed to resolve this problem by matching the spike count of a neuron with the magnitude of a feedback signal. However, the existing threshold-driven aggregate-label learning algorithms are computationally intensive, resulting in relatively low learning efficiency hence limiting their usability in practical applications. In order to address these limitations, we propose a novel membrane-potential driven aggregate-label learning algorithm, namely MPD-AL. With this algorithm, the easiest modifiable time instant is identified from membrane potential traces of the neuron, and guild the synaptic adaptation based on the presynaptic neurons’ contribution at this time instant. The experimental results demonstrate that the proposed algorithm enables the neurons to generate the desired number of spikes, and to detect useful clues embedded within unrelated spiking activities and background noise with a better learning efficiency over the state-of-the-art TDP1 and Multi-Spike Tempotron algorithms. Furthermore, we propose a data-driven dynamic decoding scheme for practical classification tasks, of which the aggregate labels are hard to define. This scheme effectively improves the classification accuracy of the aggregate-label learning algorithms as demonstrated on a speech recognition task.
Scalable Recollections for Continual Lifelong Learning
Authors: Riemer Matthew , Klinger Tim , Bouneffouf Djallel , Franceschini Michele
Published: September 2019

Given the recent success of Deep Learning applied to a variety of single tasks, it is natural to consider more human-realistic settings. Perhaps the most difficult of these settings is that of continual lifelong learning, where the model must learn online over a continuous stream of non-stationary data. A successful continual lifelong learning system must have three key capabilities: it must learn and adapt over time, it must not forget what it has learned, and it must be efficient in both training time and memory. Recent techniques have focused their efforts primarily on the first two capabilities while questions of efficiency remain largely unexplored. In this paper, we consider the problem of efficient and effective storage of experiences over very large time-frames. In particular we consider the case where typical experiences are O(n) bits and memories are limited to O(k) bits for k