bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning Diagnosis of Peritonsillar Abscess
Authors: Wilson Michael B. , Ali S. Ahmed , Kovatch Kevin J. , Smith Josh D. , Hoff Paul T.
Published: August 2019

Peritonsillar abscess (PTA) is a difficult diagnosis to make clinically, with clinical examination of even otolaryngologists showing poor sensitivity and specificity. Machine learning is a form of artificial intelligence that “learns” from data to make predictions. We developed a machine learning classifier to predict the diagnosis of PTA based on patient symptoms. We retrospectively collected clinical data and symptomatology from 916 patients who underwent attempted needle aspiration for PTA. Machine learning classifiers were trained on a subset of the data to predict the presence or absence of purulence on attempted aspiration. The performance of the model was evaluated on a holdout set. The accuracy of the top‐performing algorithm, the artificial neural network, was 72.3%. Artificial neural networks can use patient symptoms to exceed human ability to predict PTA in patients with clinical suspicion for PTA. Similar models can assist medical decision making for clinicians who have suspicion of PTA.
A sampling-based multi-tree fusion algorithm for frontier detection
Authors: Qiao Wenchuan , Fang Zheng , Si Bailu
Published: August 2019

Autonomous exploration is a key step toward real robotic autonomy. Among various approaches for autonomous exploration, frontier-based methods are most commonly used. One efficient method of frontier detection exploits the idea of the rapidly-exploring random tree and uses tree edges to search for frontiers. However, this method usually needs to consume a lot of memory resources and searches for frontiers slowly in the environments where random trees are not easy to grow (unfavorable environments). In this article, a sampling-based multi-tree fusion algorithm for frontier detection is proposed. Firstly, the random tree’s growing and storage rules are changed so that the disadvantage of its slow growing under unfavorable environments is overcome. Secondly, a block structure is proposed to judge whether tree nodes in a block play a decisive role in frontier detection, so that a large number of redundant tree nodes can be deleted. Finally, two random trees with different growing rules are fused to speed up frontier detection. Experimental results in both simulated and real environments demonstrate that our algorithm for frontier detection consumes fewer memory resources and shows better performances in unfavorable environments.
Real‐life data of direct anticoagulant use, bleeding risk and venous thromboembolism recurrence in chronic thromboembolic pulmonary hypertension patients: an observational retrospective study
Authors: Sena Sert , Bulent Mutlu , Derya Kocakaya , Deniz Kaptan , Halil Ataş , Okan Erdogan , Bedrettin Yıldızeli
Published: August 2019

Introduction

Lifelong anticoagulation is the cornerstone of the chronic thromboembolic pulmonary hypertension (CTEPH) treatment regardless of the additional pulmonary endarterectomy, balloon pulmonary angioplasty, or medical treatment alone. Aim of this study was to evaluate the rate of oral anticoagulant preferences and document direct oral anticoagulants’ (DOACs’) safety, efficacy in the CTEPH population.

Methods

Patients’ demographic data obtained from database between September 2011 and April 2018. In‐hospital events, death, venous thromboembolism (VTE) recurrence, bleeding events and anticoagulant therapy transition were recorded.

Results

We reviewed 501 CTEPH patients who observed 9.0 ± 8.5 years. All‐cause death, all bleeding, recurrent VTE was observed in 15.6%, 31% and 12%. Forty‐one patients (8.2%) were diagnosed as inoperable. Of all, 15.2% of operable patients remained as residual. All‐cause mortality rates were 13.8% (57 pts.) in the warfarin group as compared with 9.7% (13 pts.) in rivaroxaban group (HR: 1.61, 95% CI, 0.89–2.99; p: 0.11). Higher bleeding events occurred with warfarin group (27.1%) as compared with rivaroxaban (24.6%; HR: 1.28, 95% CI, 0.86–1.88; p: 0.22). Major bleeding was significantly higher with warfarin group (HR: 1.94, 95% CI, 1.05–3.62; p: 0.03). Subgroup analysis of all‐cause death revealed that this significance dominated by the rate of death according to bleeding events; warfarin versus those seen with rivaroxaban (4.85% vs. 2.2%; HR: 4.75, 95% CI: 1.12–20.16; p = 0.03). The rate of recurrent VTE was found 8.9% in the rivaroxaban group, 10.9% in warfarin group (HR: 1.21, 95% CI, 0.64–2.23; p: 0.55).

Conclusion

DOACs could be a safe and effective alternative for lifelong anticoagulant therapy in CTEPH patients. Rivaroxaban produced similar rates of thromboembolism and non‐relevant bleeding compared to those associated with warfarin. The main difference was found with major bleeding that it was mainly associated with the death rate according to major bleeding. Using DOACs might be a more reasonable way to prevent bleeding events without increasing thromboembolic risk.
Visibility of the hilar lymph nodes using advanced virtual monoenergetic low-keV images for preoperative evaluation of lung cancer
Authors: Sekiguchi Tomoya , Ozawa Yoshiyuki , Hara Masaki , Nakagawa Motoo , Goto Taeko , Shibamoto Yuta
Published: August 2019

Objective:

The purpose of our study was to evaluate the visibility of the hilar lymph nodes (LNs) using advanced virtual monoenergetic low-keV images compared with early-phase contrast-enhanced CT.

Methods:

Dual energy contrast-enhanced CT was performed for pre-operative evaluation of lung cancer at 20 and 60 s after administration of contrast media in 50 patients (32 males and 18 females; mean age, 69 years). Five kinds of images (A: 20 s/120 kV; B: 60 s/40 keV; C: 60 s/50 keV; D: 60 s/120 kV; E: 60 s/100 kV) were reconstructed. We measured the CT number of the bilateral main pulmonary arteries (PAs), pulmonary veins (PVs) and hilar LNs, and evaluated the differences in CT number (Hounsfield units, HUs) between the PA/PV and LNs (PA–LN and PV–LN contrast). Artifacts from the superior vena cava (SVC) were also evaluated.

Results:

The mean PA–LN contrast (HU) was 415 in image group A, 299 in B, 180 in C, 80 in D, and 100 in E. The mean PV–LN contrasts in each group were 306, 287, 177, 78, and 99, respectively. Image group B showed the second highest PA–LN contrast following image group A. There was no significant difference in the PV–LN contrast between image groups A and B. The PA–LN and PV–LN contrasts of image groups B and C were significantly higher than those of E. SVC artifacts were lower in the delayed-phase images (Group B–E) than in Group A.

Conclusion:

To evaluate the hilar LNs with a single image series, advanced virtual monoenergetic 40-keV imaging at the delayed 60-s phase seems to be the most valuable.

Advances in knowledge:

Advanced virtual monoenergetic image is useful for evaluation of both hilar LNs and tumors in the delayed phase without artifact derived from the streak artifact from dense contrast media in the SVC.
Development and implementation of a dynamically updated big data intelligence platform from electronic health records for nasopharyngeal carcinoma research
Authors: Lin Li , Liang Wei , Li Chao-Feng , Huang Xiao-Dan , Lv Jia-Wei , Peng Hao , Wang Bing-Yi , Zhu Bo-Wei , Sun Ying
Published: August 2019

Objective:

To develop a big data intelligence platform for secondary use of electronic health records (EHRs) data to facilitate research for nasopharyngeal cancer (NPC).

Methods:

This project was launched in 2015 and carried out by the cooperation of an academic cancer centre and a technology company. Patients diagnosed with NPC at Sun Yat-sen University Cancer Centre since January 2008 were included in the platform. Standard data elements were established to defined 981 variables for the platform. For each patient, data from 13 EHRs systems were extracted, integrated, structurized and normalized. Eight functional modules were constructed for the platform to facilitate the investigators to identify eligible patients, establish research projects, conduct statistical analysis, track the follow-up, search literature, etc.

Results:

From January 2008 to December 2018, 54,703 patients diagnosed with NPC were included. Of these patients, 39,058 (71.4%) were male, and 15,645 (28.6%) were female; median age was 47 (interquartile range, 39–55) years. Of 981 variables, 341 were obtained from data structurization and normalization, of which 68 were generated by interacting multiple data sources via well-defined logical rules. The average precision rate, recall rate and F-measure for 341 variables were 0.97 ± 0.024, 0.92 ± 0.030, and 0.94 ± 0.027 respectively. The platform is regularly updated every seven days to include new patients and add new data for existing patients. Up to now, eight big data-driven retrospective studies have been published from the platform.

Conclusion:

Our big data intelligence platform demonstrates the feasibility of integrating EHRs data of routine healthcare, and offers an important perspective on real-world study of NPC. The continued efforts may be focus on data sharing among multiple hospitals and publicly releasing of data files.

Advances in knowledge:

Our big data intelligence platform is the first disease-specific data platform for NPC research. It incorporates comprehensive EHRs data from routine healthcare, which can facilitate real-world study of NPC in risk stratification, decision-making and comorbidities management.
Chronic obstructive pulmonary disease's impact on mental health
Authors: Bostock-Cox Beverley
Published: August 2019

Beverley Bostock-Cox explains why nurses need to consider the mental effects of the condition
New media use among young Batswana – on concerns, consequences and the educational factor
Authors: Storm-Mathisen Ardis
Published: August 2019

Based on a multi-methodological fieldwork, conducted in Gaborone and a village in Botswana in 2015/16, this article discusses how new media is used as part of young people’s everyday practices and with what consequences. The findings show that Batswana attach high significance to personal media but use it more for social than direct income-generating activities, with little effect on their core life concerns. People’s uses of personal media have, however, significantly changed the practical processes around how concerns can be handled, and on their socio-economic consequences. The dynamics by which personal media uses indirectly generate new outcomes are discussed using four cases that exemplify variations within the most ardent new media user group in Botswana, the young adults in the capital. The analysis highlights how mobility, social capital and – not least – education are important and interlinked factors in the social mechanisms that produce different outcomes of media use.
Pan-Africanism as a laughing matter: (Funny) expressions of African identity on Twitter
Authors: Cheruiyot David , Uppal Charu
Published: August 2019

Pan-Africanism, a concept that attempts to capture the essence of being an African, needs to be reconsidered in the age of social media. In this article, we examine how Twitter users negotiate the question of African identity through humorous hashtagdriven conversations. We specifically question whether a new kind of Pan-Africanism is emerging on Africa’s Twitterverse through the use of a popular hashtag in 2015, #IfAfricaWasABar. In our analysis of tweets linked to #IfAfricaWasABar, we conclude that Twitter provides temporary solidarity by engaging users in humorous exchanges regarding the sociocultural, political and economic issues that define the African continental condition today.
Remaking Winnetou, reconfiguring German fantasies of Indianer and the Wild West in the Post-Reunification Era
Authors: Loock Kathleen
Published: August 2019

This article argues that the 2016 television remake of Winnetou reconfigures German fantasies of Native Americans (Indianer) and the Wild West in the post-reunification era. The remake raises questions about the historically constructed meanings and the appropriateness of Winnetou in Germany today, presenting an occasion to probe processes of German nation building and their continued – and increasingly controversial – reliance on metaphorical meanings of “Indianness”. Taking a cultural studies approach, the article develops a theoretical framework around remaking, generationing, and cultural memory, and examines the remake against the background of Germany’s still ongoing inner reunification and Native American claims to self-representation.
Defining the new speaker: theoretical perspectives and learner trajectories
Authors: Jaffe Alexandra
Published: August 2019

This article addresses the concept of the new speaker from both a theoretical/definitional perspective and from the standpoint of a situated, ethnographic analysis. The more general and theoretical focus addresses some of the presuppositions and entailments of the new speaker concept, both as an “on-the-ground” concept that gets operationalized by social actors and as an analytical category used by researchers. In particular, it considers how the new speaker concept elucidates criteria in relation to which minority language-speaking communities of practice are conceptualized and enacted. The ethnographic focus, on Corsican adult language classrooms, explores how new-speakerness is invoked implicitly in Corsica, where the term “new speaker” itself is not in circulation, but is a target of language planning strategies. This ethnographic research reveals complex identity and language ideological issues that are raised about the legitimacy, authority and authenticity of Corsican language learners in a sociolinguistic context in which both formal/institutional and informal/social use of the minority language is quite restricted.
Sociolinguistic vitality of Manx after extreme language shift: authenticity without traditional native speakers
Authors: Ó hIfearnáin Tadhg
Published: August 2019

This article draws on sociolinguistic fieldwork among speakers of one of Europe's smallest indigenous language communities, a speaker group which persists after the loss of all of its “traditional speakers” within living memory. The extreme language shift experienced by Manx has not led to loss of the language as a spoken and literary medium due to the efforts of significant numbers of language activists and enthusiasts over several generations, from before the loss of the traditional language community to the present. Their actions have resulted in significant linguistic institutionalisation and a rapidly expanding number of speakers of various abilities, some of whom form a new “speaker community”. It discusses the constructions of linguistic authenticity and alternative models for the revival speaker, showing how core groups of speakers have been bestowed with authenticity by the wider non-speaker population, for whom linguists' interest in language endangerment and language death are not primary concerns. The article shows how speakers appropriate and are accorded forms of authority and legitimacy in the absence of traditional native speakers.
Neofalantes as an active minority: understanding language practices and motivations for change amongst new speakers of Galician
Authors: O'Rourke Bernadette , Ramallo Fernando
Published: August 2019

In this article we use Moscovici's (1976) notion of active minorities as a framework to explain the linguistic practices and motivations behind linguistic change amongst new speakers of Galician. Revitalization policies since the 1980s brought about changes in the symbolic and economic value of Galician on the linguistic market. However, this has not been significant enough to change the rules of social mobility and Spanish has continued to be the language of prestige. Despite this, neofalantes ‘new speakers of Galician’ have opted for linguistic change and engage in the process of majority language displacement. We argue that this displacement can at least in part be explained by a move away from functionalist models of language contact and shift and towards an understanding of these processes from a language conflict perspective. This allows us to explain the practices of neofalantes as not simply deviations from the sociolinguistic “status quo” but as reactions to it and as proponents of social change. To explore the behavioural styles and practices of neofalantes as an active minority, we analyse the discourses which emerge from discussion groups involving twelve new speakers of Galician about their sociolinguistic practices.
Evaluating public opinion towards robots: a mixed-method approach
Authors: Operto Stefania
Published: August 2019

The article presents the results of some research conducted in Italy on the perception of robots. The study was carried out as part of a project arranged by the School of Robotics (Scuola di Robotica) in 2017/2018 and involved around 700 Italian citizens belonging to different social groups. Data collection used mixed methods: surveys, focus groups, interviews, and participatory workshops. The results were compared with surveys conducted in Europe by the Eurobarometer.

Italy is an interesting context for this type of study for the density of robots, for the growth trends of robotics compared to other countries and for the relationships between industry and the labor market. The results of the research show that the attitudes and expectations of Italians towards robots are complex, multidimensional and contradictory: on the one hand, the interviewees positively value the growing presence of robots, on the other, they show fears about the spread of robotics in society. Robots, especially those designed to interact with humans, are part of a large system influenced by social, cultural and environmental factors in which actors move with different expectations and needs. The presence of a significant degree of differentiation between the responses of the different socio-demographic categories confirms the importance of investigating these issues, in order to reduce the distance that persists between researchers and scientists and the impact of technology on society. Furthermore, robotics is often narrated with myths and legends that have no correspondence in reality; since robots will interact more fully with humans, the human-robot interaction process and the bias integrated into the technology must be carefully studied to avoid the risks of confirmatory bias.
Prediction of toxicity of secondary metabolites
Authors: Hernández-Alvarado Ricardo Bruno , Madariaga-Mazón Abraham , Martinez-Mayorga Karina
Published: August 2019

The prediction of toxicological endpoints has gained broad acceptance; it is widely applied in early stages of drug discovery as well as for impurities obtained in the production of generic or equivalent products. In this work, we describe methodologies for the prediction of toxicological endpoints compounds, with a particular focus on secondary metabolites. Case studies include toxicity prediction of natural compound databases with anti-diabetic, anti-malaria and anti-HIV properties.
Conformations and interactions comparison between R- and S-methadone in wild type CYP2B6, 2D6 and 3A4
Authors: Kamal Nik Nur Syazana Bt Nik Mohamed , Lim Theam Soon , Ismail Rusli , Choong Yee Siew
Published: August 2019

Methadone is a morphine-substitute drug in methadone maintenance treatment (MMT) program to treat patients with opioid dependency. However, the methadone clinical effects are depending on the methadone metabolism rates that vary among the patients with genetic polymorphism of cytochrome P450s (CYPs). Our previous study showed methadone has different binding affinity due to the polymorphisms in CYP2B6, CYP2D6 and CYP3A4 that could contribute to the methadone metabolism rate. In this work, the conformation and interactions of R- and S-methadone in wild type CYP2B6, CYP2D6 and CYP3A4 were further studied in order to understand behaviour of R- and S-methadone at the CYP binding site. Clustering analysis showed that the conformation of R- and S-methadone in CYP2B6 are most stable, thus could lead to a higher efficiency of methadone metabolism. The conformation fluctuation of methadone in CYP2D6 could due to relatively smaller binding pocket compared with CYP2B6 and CYP3A4. The binding sites volumes of the studied CYPs were also found to be increased upon the binding with methadone. Therefore, this might contributed to the interactions of both R- and S-methadone in CYPs were mainly by hydrophobic contacts, van der Waals and electrostatic interactions. In the future, should an inhibitor for CYP is to be designed to prolong the prolonged opioid effect, the inhibitor should cater for single CYP isozyme as this study observed the behavioural differences of methadone in CYP isozymes.

Graphical Abstract:
Sic vita est: Visual representation in painting of the conceptual metaphor LIFE IS A JOURNEY
Authors: Poppi Fabio , Kravanja Peter
Published: August 2019

This article analyzes how the conceptualization LIFE IS A JOURNEY is conveyed within a series of paintings ranging from the fifteenth century to the twentieth century. While the previous research on visual metaphor generally aims to describe how the domains of metaphorical conceptualization interact or discusses the rhetorical effect that visual metaphor is able to induce, this article takes a historical perspective in order to identify the main conceptual aspects shared by the paintings under consideration. It is proposed that the concept of a JOURNEY is associated with a PURPOSIVE ACTIVITY that involves the start of the journey and its termination as two qualitatively different moments that are faced as a collective/shared experience and that are inspired by some human wish. This article also shows how the conceptual potential of metaphor tends to maintain a coherent representation although the paintings represent different historical sensitivities and artistic approaches.
A Comparison of Half and Quarter Space Penetration into Granular Media
Authors: Guzman Ivan L. , Iskander Magued , Bless Stephan
Published: August 2019

In this study, two experimental techniques are compared for the purpose of visualizing projectile penetration at speeds ranging between 60 and 150 m/s into granular media. The two techniques are half space penetration into a transparent synthetic soil surrogate and quarter space penetration of an opaque natural sand and transparent soil surrogate against an observation window. In both techniques a pneumatic projectile accelerator was employed to launch the projectiles, and high-speed imagery was employed to visualize the penetration events unintrusively. Transparency in transparent targets was achieved by saturating angular fused quartz with a refractive index matched pore fluid made of sucrose. Comparison of both techniques suggests that their results are complimentary. In particular, the terminal depth of penetration is not significantly inhibited by shooting in quarter space. Additionally, both techniques permitted visualizing distinct dilation zones ahead and around penetration. Each technique offers a number of distinct advantages. In particular, half space penetration reduces the possibility of projectile diversion and is much safer, whereas quarter space penetration allows for visualizing penetration into opaque targets at a finer scale than that achieved in half space penetration.
Concurrent Medial Prefrontal Cortex and Dorsal Hippocampal Activity Is Required for Estradiol-Mediated Effects on Object Memory and Spatial Memory Consolidation
Authors: Carney Rosalind S.E.
Published: August 2019

Highlighted Research Paper:Chemogenetic Suppression of Medial Prefrontal-Dorsal Hippocampal Interactions Prevents Estrogenic Enhancement of Memory Consolidation in Female Mice by, Jennifer J. Tuscher, Lisa R. Taxier, Jayson C. Schalk, Jacqueline M. Haertel, and Karyn M. Frick.
Predicting Longitudinal Traits Derived from High-Throughput Phenomics in Contrasting Environments Using Genomic Legendre Polynomials and B-Splines
Authors: Momen Mehdi , Campbell Malachy T , Walia Harkamal , Morota Gota
Published: August 2019

Recent advancements in phenomics coupled with increased output from sequencing technologies can create the platform needed to rapidly increase abiotic stress tolerance of crops, which increasingly face productivity challenges due to climate change. In particular, high-throughput phenotyping (HTP) enables researchers to generate large-scale data with temporal resolution. Recently, a random regression model (RRM) was used to model a longitudinal rice projected shoot area (PSA) dataset in an optimal growth environment. However, the utility of RRM is still unknown for phenotypic trajectories obtained from stress environments. Here, we sought to apply RRM to forecast the rice PSA in control and water-limited conditions under various longitudinal cross-validation scenarios. To this end, genomic Legendre polynomials and B-spline basis functions were used to capture PSA trajectories. Prediction accuracy declined slightly for the water-limited plants compared to control plants. Overall, RRM delivered reasonable prediction performance and yielded better prediction than the baseline multi-trait model. The difference between the results obtained using Legendre polynomials and that using B-splines was small; however, the former yielded a higher prediction accuracy. Prediction accuracy for forecasting the last five time points was highest when the entire trajectory from earlier growth stages was used to train the basis functions. Our results suggested that it was possible to decrease phenotyping frequency by only phenotyping every other day in order to reduce costs while minimizing the loss of prediction accuracy. This is the first study showing that RRM could be used to model changes in growth over time under abiotic stress conditions.
Utilization of Tissue Ploidy Level Variation in de Novo Transcriptome Assembly of Pinus sylvestris
Authors: Ojeda Dario I , Mattila Tiina M , Ruttink Tom , Kujala Sonja T , Kärkkäinen Katri , Verta Jukka-Pekka , Pyhäjärvi Tanja
Published: August 2019

Compared to angiosperms, gymnosperms lag behind in the availability of assembled and annotated genomes. Most genomic analyses in gymnosperms, especially conifer tree species, rely on the use of de novo assembled transcriptomes. However, the level of allelic redundancy and transcript fragmentation in these assembled transcriptomes, and their effect on downstream applications have not been fully investigated. Here, we assessed three assembly strategies for short-reads data, including the utility of haploid megagametophyte tissue during de novo assembly as single-allele guides, for six individuals and five different tissues in Pinus sylvestris. We then contrasted haploid and diploid tissue genotype calls obtained from the assembled transcriptomes to evaluate the extent of paralog mapping. The use of the haploid tissue during assembly increased its completeness without reducing the number of assembled transcripts. Our results suggest that current strategies that rely on available genomic resources as guidance to minimize allelic redundancy are less effective than the application of strategies that cluster redundant assembled transcripts. The strategy yielding the lowest levels of allelic redundancy among the assembled transcriptomes assessed here was the generation of SuperTranscripts with Lace followed by CD-HIT clustering. However, we still observed some levels of heterozygosity (multiple gene fragments per transcript reflecting allelic redundancy) in this assembled transcriptome on the haploid tissue, indicating that further filtering is required before using these assemblies for downstream applications. We discuss the influence of allelic redundancy when these reference transcriptomes are used to select regions for probe design of exome capture baits and for estimation of population genetic diversity.
GROWTH PERFORMANCE, BIOCHEMICAL BLOOD PARAMETERS AND MEAT QUALITY OF RAINBOW TROUT (ONCORHYNCHUS MYKISS W.) FED WITH CNICUS BENEDICTUS L. EXTRACT
Authors: Koshinski R. , Velichkova K. , Sirakov I. , Stoyanova S.
Published: August 2019

Aquaculture development is influenced by various environmental factors and nutrition with herbal additives can affect the growth in aquaculture and to improve indicators such as digestibility, nutrition effectiveness and food taste. The purpose of this study was to trace growth performance, meat quality and biochemical blood parameters (glucose, urea, creatinine, total protein, albumin, ASAT, ALAT, Ca, P, Mg, triglycerides, cholesterol) of rainbow trout (Oncorhynchus mykiss W.) fed with additive blessed thistle (Cnicus benedictus L.) extract. To achieve the objective a control group (no added) and an experimental (with added 1363 mg.kg-1 of blessed thistle extract) option, each with a two repetition, were set in a recirculating system in the Aquaculture Base of the Faculty of Agriculture at the Trakia University. Forty specimens from the fish species rainbow trout with an average weight of fish 13.32+3.07 g (control) and 13.33+2.58 g (experimental) in good health condition were placed in each tank and cultivated for 60 days. At the end of the experiment were calculated average final weight, specific growth rates, feed conversion ratio, meat quality and blood parameters. Trout from the experimental group, fed with supplement had with 8.52% higher average final weight compared to the parameter value of fish from control (P<0.001). The blood biochemical parameters ASAT and ALAT in control variant were higher with 27.4% and 44% respectively, compare to values of this parameter of fish from the experimental (P>0.05). Experimental fish fed with additive blessed thistle have a higher electrolytes level of magnesium (Mg) with 5.26% compared to control group (P>0.05). The protein content in the fish of the control group and experimental were of close value, but not statistically proven. The blessed thistle supplementation in the diet led to lower the lipid content in the fillets of the rainbow trout with 19.7% compare to values of this parameter of fish from control group and was statistically proven (P<0.05). This result shows that fish fed with the supplement are more useful and dietetic in their quality as human food. Rainbow trout fed with blessed thistle supplement have better growth performance and blood parameters.
The ‘Late Avar reform’ and the ‘long eighth century’: A tale of the hesitation between structural transformation and the persistent nomadic traditions (7th to 9th century AD)
Authors: Szenthe Gergely
Published: August 2019

Research on late antique and early medieval economic and social processes during the past three decades called for, and enabled, a fresh look at the history of the ‘Late Avar period’ of the Carpathian Basin, corresponding exactly to the ‘long eighth century’ of the Mediterranean and European world. This paper offers a rather sketchy new model, alongside raising questions and framing a research programme focusing on social and economic historical processes. Therefore, using the archaeological evidence as a solid foundation, I have proposed a set of research hypotheses as starting points for regional and micro-regional studies.
Dinamika Pengembangan Kurikulum Pendidikan Agama Islam di Madrasah (Studi Multi-Situs di Kabupaten Jombang)
Authors: Umam Khoirul
Published: August 2019

Dalam konteks dinamika pengembangan kurikulum di Indonesia, kurikulum PAI masih menghadapi berbagai masalah dalam pengembangannya. Hal ini disebabkan perbedaan status kepemilikan sekolah, lingkungan sekolah, dan sumber daya manusia yang tersedia. Penelitian ini bertujuan untuk menganalisa  permasalahan penerapan pengembangan, konstruksi, serta faktor-faktor pendukung dan penghambat kurikulum PAI di MTs Salafiyah Syafi’iyah Tebuireng, MTs Ar-Rahman Nglaban, MTsN Plandi Diwek, dan MTsN Tambakberas Jombang. Penelitian ini menggunakan penelitian lapangan dengan studi multi-situs pada empat lembaga yang berbeda di Kabupaten Jombang. Hasil penelitian menunjukkan bahwa konstruksi kurikulum dari keempat madrasah tersebut menitikberatkan pada Subject Centered Design, yang berfokus pada mata pelajaran. Sedangkan faktor-faktor penentu yang paling dominan adalah sumber daya manusia dan sarana prasarana. Perbandingan model konstruksi kurikulum di empat madrasah tersebut terletak pada esensi dan kedalaman materi. Dari data keempat madrasah tersebut, maka collaborrative curriculum menjadi pilihan desain ulang kurikulum yang dinilai ideal dan dapat diterapkan.
Pendidikan Moral melalui Pembelajaran Kitab Alfiyah ibn Malik di Pondok Pesantren Langitan Tuban
Authors: Muhid Abdul , Asnawi Asnawi , S. A. P. Rangga Sa’adillah
Published: August 2019

Kitab Alfiyah of Muhammad bin Abdillah bin Malik al-Andalusi or known as Ibnu Malik is famous for resource of Arabic grammar. It is uncommon to find discourse of the kitab apart from the Arabic grammar. It is the fact that moral values are the other side of its contents, implicitly live in the stanzas. Philosophical worldview makes possible to uncover the moral values, then to interpret it, and to internalize it throung learning activities. This article describes the moral contents, internalization methods, and reflection of the internalization towards santri in Pondok Pesantren Langitan Tuban.  With naturalistic paradigm, data were collected through interview, observation, and documentation. Findings shows that moral internalization in the kitab Alfiyah Ibn Malik learning activities was going through modelling, rewards, punishment, building habits, and indoctrination. In addition, author finds 31 moral values within stanzas in the kitab and 12 reflective behaviors by santri.
Madrasah Diniyah Sebagai Pola Diseminasi Islam Moderat di Pesantren Mahasiswa Darussalam Keputih Surabaya
Authors: Mukaffa Zumrotul
Published: August 2019

Tulisan ini mencoba mengurai peran penting Madrasah Diniyah dibawah naungan Pesantren Darussalam Keputih yang berada di lingkungan Institut Teknologi Sepuluh November (ITS) Surabaya di tengah-tengah maraknya gerakan Islam transnasional di dalam kampus. Pengelola menyadari sepenuhnya arti penting diseminasi tata nilai Islam moderat dan menempatkan Madrasah Diniyah sebagai struktur mediasi dalam membiakkan nilai-nilai toleransi dan menolak formalisasi khilafah dalam bingkai Negara Kesatuan Republik Indonesia. Para santri tidak hanya belajar kitab-kitab berdasarkan jenjang kelas masing-masing, melainkan juga mendalami gagasan besar Islam moderat di tanah air. Pendalaman dilakukan dengan cara menghubungkan pengetahuan santri dengan website WIKI ASWAJA dan ASWAJA NU yang dikelola oleh Pusat Kajian Aswaja PWNU Jawa Timur. Isu-isu mutakhir, seperti khilafah dan Islam Nusantara yang dipublikasikan oleh website didiskusikan dengan metode bandongan-muhawarah dengan melibatkan seluruh santri-mahasiswa. Keberhasilan Madrasah Diniyah Takmiliyah di pesantren Darussalam sebagai struktur mediasi ditandai oleh kemampuannya mengembangkan diskursus tandingan terhadap gerakan-gerakan Islam transnasional di lingkungan kampus.
Program Penalaran Islam Indonesia dan Gerakan Kontra-Radikalisme
Authors: Mas'ud Ali , Jazil Saiful , Subty Taufik , Fahmi Muhammad
Published: August 2019

Artikel ini mendeskripsikan urgensi pelaksanaan program penalaran Islam Indonesia (PPII) sebagai penguatan materi PAI yang rahmatan lil ‘alamin dan gerakan kontra radikalisme di UIN Sunan Ampel Surabaya. Data dikumpulkan dengan observasi, wawancara, dan dokumentasi. Hasil penelitian menunjukkan bahwa PPII membangun landasan keislaman berdasarkan Teologi Islam Kontekstual, Ekspresi Sufistik, Hukum Islam Kontesktual, Metodologi Hukum Islam, dan Genealogi Peradaban Islam Indonesia. Dengan demikian, perilaku Islam rahmatan lil ‘alamin, akhlaqul karimah, dan nalar keislaman dapat terinternalisasi ke dalam disiplin keilmuan yang dipelajari mahasiswa. Melihat geliat gerakan keagamaan Islam yang radikal semakin berani menampilkan diri di publik, PPII menempati peran penting dalam gerakan kontra radikalisme. Materi-materi dalam PPII sinergis dengan materi PAI dengan pendekatan penalaran rasional-empiris yang secara epistemologis identik dengan pendekatan Burhani.
Heterogeneous Transfer Learning via Deep Matrix Completion with Adversarial Kernel Embedding
Authors: Li Haoliang , Pan Sinno Jialin , Wan Renjie , Kot Alex C.
Published: August 2019

Heterogeneous Transfer Learning (HTL) aims to solve transfer learning problems where a source domain and a target domain are of heterogeneous types of features. Most existing HTL approaches either explicitly learn feature mappings between the heterogeneous domains or implicitly reconstruct heterogeneous cross-domain features based on matrix completion techniques. In this paper, we propose a new HTL method based on a deep matrix completion framework, where kernel embedding of distributions is trained in an adversarial manner for learning heterogeneous features across domains. We conduct extensive experiments on two different vision tasks to demonstrate the effectiveness of our proposed method compared with a number of baseline methods.
Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering
Authors: Li Xiangpeng , Song Jingkuan , Gao Lianli , Liu Xianglong , Huang Wenbing , He Xiangnan , Gan Chuang
Published: August 2019

Most of the recent progresses on visual question answering are based on recurrent neural networks (RNNs) with attention. Despite the success, these models are often timeconsuming and having difficulties in modeling long range dependencies due to the sequential nature of RNNs. We propose a new architecture, Positional Self-Attention with Coattention (PSAC), which does not require RNNs for video question answering. Specifically, inspired by the success of self-attention in machine translation task, we propose a Positional Self-Attention to calculate the response at each position by attending to all positions within the same sequence, and then add representations of absolute positions. Therefore, PSAC can exploit the global dependencies of question and temporal information in the video, and make the process of question and video encoding executed in parallel. Furthermore, in addition to attending to the video features relevant to the given questions (i.e., video attention), we utilize the co-attention mechanism by simultaneously modeling “what words to listen to” (question attention). To the best of our knowledge, this is the first work of replacing RNNs with selfattention for the task of visual question answering. Experimental results of four tasks on the benchmark dataset show that our model significantly outperforms the state-of-the-art on three tasks and attains comparable result on the Count task. Our model requires less computation time and achieves better performance compared with the RNNs-based methods. Additional ablation study demonstrates the effect of each component of our proposed model.
Angular Triplet-Center Loss for Multi-View 3D Shape Retrieval
Authors: Li Zhaoqun , Xu Cheng , Leng Biao
Published: August 2019

How to obtain the desirable representation of a 3D shape, which is discriminative across categories and polymerized within classes, is a significant challenge in 3D shape retrieval. Most existing 3D shape retrieval methods focus on capturing strong discriminative shape representation with softmax loss for the classification task, while the shape feature learning with metric loss is neglected for 3D shape retrieval. In this paper, we address this problem based on the intuition that the cosine distance of shape embeddings should be close enough within the same class and far away across categories. Since most of 3D shape retrieval tasks use cosine distance of shape features for measuring shape similarity, we propose a novel metric loss named angular triplet-center loss, which directly optimizes the cosine distances between the features. It inherits the triplet-center loss property to achieve larger inter-class distance and smaller intra-class distance simultaneously. Unlike previous metric loss utilized in 3D shape retrieval methods, where Euclidean distance is adopted and the margin design is difficult, the proposed method is more convenient to train feature embeddings and more suitable for 3D shape retrieval. Moreover, the angle margin is adopted to replace the cosine margin in order to provide more explicit discriminative constraints on an embedding space. Extensive experimental results on two popular 3D object retrieval benchmarks, ModelNet40 and ShapeNetCore 55, demonstrate the effectiveness of our proposed loss, and our method has achieved state-ofthe-art results on various 3D shape datasets.
Towards Optimal Discrete Online Hashing with Balanced Similarity
Authors: Lin Mingbao , Ji Rongrong , Liu Hong , Sun Xiaoshuai , Wu Yongjian , Wu Yunsheng
Published: August 2019

When facing large-scale image datasets, online hashing serves as a promising solution for online retrieval and prediction tasks. It encodes the online streaming data into compact binary codes, and simultaneously updates the hash functions to renew codes of the existing dataset. To this end, the existing methods update hash functions solely based on the new data batch, without investigating the correlation between such new data and the existing dataset. In addition, existing works update the hash functions using a relaxation process in its corresponding approximated continuous space. And it remains as an open problem to directly apply discrete optimizations in online hashing. In this paper, we propose a novel supervised online hashing method, termed Balanced Similarity for Online Discrete Hashing (BSODH), to solve the above problems in a unified framework. BSODH employs a well-designed hashing algorithm to preserve the similarity between the streaming data and the existing dataset via an asymmetric graph regularization. We further identify the “data-imbalance” problem brought by the constructed asymmetric graph, which restricts the application of discrete optimization in our problem. Therefore, a novel balanced similarity is further proposed, which uses two equilibrium factors to balance the similar and dissimilar weights and eventually enables the usage of discrete optimizations. Extensive experiments conducted on three widely-used benchmarks demonstrate the advantages of the proposed method over the stateof-the-art methods.
Learning Neural Bag-of-Matrix-Summarization with Riemannian Network
Authors: Liu Hong , Li Jie , Wu Yongjian , Ji Rongrong
Published: August 2019

Symmetric positive defined (SPD) matrix has attracted increasing research focus in image/video analysis, which merits in capturing the Riemannian geometry in its structured 2D feature representation. However, computation in the vector space on SPD matrices cannot capture the geometric properties, which corrupts the classification performance. To this end, Riemannian based deep network has become a promising solution for SPD matrix classification, because of its excellence in performing non-linear learning over SPD matrix. Besides, Riemannian metric learning typically adopts a kNN classifier that cannot be extended to large-scale datasets, which limits its application in many time-efficient scenarios. In this paper, we propose a Bag-of-Matrix-Summarization (BoMS) method to be combined with Riemannian network, which handles the above issues towards highly efficient and scalable SPD feature representation. Our key innovation lies in the idea of summarizing data in a Riemannian geometric space instead of the vector space. First, the whole training set is compressed with a small number of matrix features to ensure high scalability. Second, given such a compressed set, a constant-length vector representation is extracted by efficiently measuring the distribution variations between the summarized data and the latent feature of the Riemannian network. Finally, the proposed BoMS descriptor is integrated into the Riemannian network, upon which the whole framework is end-to-end trained via matrix back-propagation. Experiments on four different classification tasks demonstrate the superior performance of the proposed method over the state-of-the-art methods.
Weakly Supervised Scene Parsing with Point-Based Distance Metric Learning
Authors: Qian Rui , Wei Yunchao , Shi Honghui , Li Jiachen , Liu Jiaying , Huang Thomas
Published: August 2019

Semantic scene parsing is suffering from the fact that pixellevel annotations are hard to be collected. To tackle this issue, we propose a Point-based Distance Metric Learning (PDML) in this paper. PDML does not require dense annotated masks and only leverages several labeled points that are much easier to obtain to guide the training process. Concretely, we leverage semantic relationship among the annotated points by encouraging the feature representations of the intra- and intercategory points to keep consistent, i.e. points within the same category should have more similar feature representations compared to those from different categories. We formulate such a characteristic into a simple distance metric loss, which collaborates with the point-wise cross-entropy loss to optimize the deep neural networks. Furthermore, to fully exploit the limited annotations, distance metric learning is conducted across different training images instead of simply adopting an image-dependent manner. We conduct extensive experiments on two challenging scene parsing benchmarks of PASCALContext and ADE 20K to validate the effectiveness of our PDML, and competitive mIoU scores are achieved.
Backbone Cannot Be Trained at Once: Rolling Back to Pre-Trained Network for Person Re-Identification
Authors: Ro Youngmin , Choi Jongwon , Jo Dae Ung , Heo Byeongho , Lim Jongin , Choi Jin Young
Published: August 2019

In person re-identification (ReID) task, because of its shortage of trainable dataset, it is common to utilize fine-tuning method using a classification network pre-trained on a large dataset. However, it is relatively difficult to sufficiently finetune the low-level layers of the network due to the gradient vanishing problem. In this work, we propose a novel fine-tuning strategy that allows low-level layers to be sufficiently trained by rolling back the weights of high-level layers to their initial pre-trained weights. Our strategy alleviates the problem of gradient vanishing in low-level layers and robustly trains the low-level layers to fit the ReID dataset, thereby increasing the performance of ReID tasks. The improved performance of the proposed strategy is validated via several experiments. Furthermore, without any addons such as pose estimation or segmentation, our strategy exhibits state-of-the-art performance using only vanilla deep convolutional neural network architecture.
Miles and Memories
Authors: Nekhlyudov Larissa
Published: August 2019

An internist describes preparing to run a marathon in memory of her mother and the injury that prevented her from completing the race. Her perspective on this setback was shaped by her own loss and memories of patients whose lives were interrupted by cancer, reminding us that a cancer diagnosis comes without preparation and without choosing. While more cancer patients are surviving, there are still those whose life journeys end much too soon.