Miracle-dz/UniFAR-FTUs huggingface dataset:
Polymeric vesicles in biomedical applications

Polymeric vesicles, or polymersomes, are nano- to micrometre sized polymeric capsules with a bilayered membrane. Applications of these vesicles are foreseen in nanomedicine, in vivo imaging and drug delivery. These applications put many restrictions on the choice of polymer, the size and the surface of the vesicle. In this respect much can be learned and translated to polymersome science from lines of research with a longer history of practical knowledge such as liposomal formulation and polymer drug conjugation. The dimensions of a vesicle, such as size and shape can be controlled for polymersomes and will influence the in vivo circulation time. The surface can be adjusted to induce stealth character, or chemically modified to introduce targeting moieties. And last but not least the choice of block copolymers—the building blocks of a polymersome—can introduce features like biocompatibility, inherent or induced permeability and triggered release. In this review we will discuss the recent advances in polymersome science with regard to biomedical applications and will specifically address the abovementioned features which affect their biological behaviour.
A novel flat DCN architecture adopting low radix optical packet switches

We investigate the performance of a novel flat data center network (DCN) architecture based on distributed buffer-less optical packet switches and fast flow control. Scalability of the novel DCN is assessed by numerical simulation with OMNeT++ discrete event simulator for medium and large size data centers. The simulation results reports an end-to-end latency of less than 8µs (including retransmission), a packet loss <10 -8 and >9Tb/s average network throughput for load of 0.4 and DCN up to 100,000 servers, which therefore provided a promising solution apart from the prevalent electrical data center architectures.
The IWSLT 2018 Evaluation Campaign

The International Workshop of Spoken Language Translation (IWSLT) 2018 Evaluation Campaign featured two tasks: low-resource machine translation and speech translation. In the first task, manually transcribed speech had to be translated from Basque to English. Since this translation direction is a under-resourced language pair, participants were encouraged to use additional parallel data from related languages. In the second task, participants had to translate English audio into German text with a full speech-translation system. In the baseline condition, participants were free to use composite architectures, while in the end-to-end condition they were restricted to use a single model for the task. This year, eight research groups took part in the low-resource machine translation task and nine in the speech translation task.
Fabrication and Performance of Silicon-Embedded Permanent-Magnet

This paper focuses on the design, fabrication, and characterization of silicon-packaged permanent-magnet (PM) microgenerators. The use of silicon packaging favors fine control on shape and dimensions in batch fabrication and provides a path toward high rotational speeds (∼1 Mr/min), a requirement for ultimate compactness of microgenerators. The successful silicon packaging of these microgenerators consisted of three essential elements: 1) a winding scheme allowing both nonplanar fabrication and through-wafer interconnects; 2) laminations built into the silicon for enhanced electrical performance; and 3) a balancing scheme for the heavy PM rotor to ensure its maximum performance. The devices were fabricated using bonded silicon wafers, integrated magnetics, and an electroplated metal. The mechanical strength of the 12-mm-diameter silicon-packaged PM rotors was evaluated at high rotational speeds using an external spindle drive. Speeds up to 200 000 r/min were achieved prior to a mechanical rotor failure. The generators were electrically characterized, and an output power in excess of 1 W across a resistive load of 0.32 Ω was measured at a maximum speed. A 225% power increase was also experimentally determined due to the addition of a laminated stator back iron. [2009-0151]
Microbial compositionof chlorinated ethene-degrading cultures dominated byDehalococcoides

The community composition of microbial cultures degrading tetrachloroethene (PCE), trichloroethene (TCE), cis-1,2-dichloroethene (cDCE) and vinyl chloride (VC) to ethene was studied. A combination of PCR-denaturing gradient gel electrophoresis (PCR-DGGE) and 16S rRNA gene sequence analysis revealed that all cultures contained Dehalococcoides populations, but that the populations of other organisms varied widely. Based on the sequences of cloned 16S rRNA genes, real-time PCR methods were developed for several of these phylotypes affiliated with the putative dechlorinators Sulfurospirillum and Geobacter, the putative methanogens Methanomethylovorans, Methanomicrobiales, Methanosaeta and Methanosarcina, the putative acetogens Acetobacterium, Spirochaetes, and Sporomusa, and the putative fermenters Bacteroidetes, Syntrophus, and Syntrophobacter. These novel quantitative PCR methods were then used to estimate relative abundances of each phylotype in several individual cultures maintained on each chlorinated ethene. Dehalococcoides populations were the dominant phylotypes assayed in most KB-1 cultures, agreeing with the DGGE and cloning results. A Geobacter phylotype was also strongly represented in most PCE and TCE cultures, but not in cDCE or VC cultures, suggesting a possible role for this organism as a PCE-to-cDCE dechlorinator. The Sulfurospirillum phylotype was estimated to comprise a minor fraction of 16S rRNA gene copies and did not appear to have an important role in dechlorination.
Robust Finite-Time H∞ Filtering for Discrete-Time Markov Jump Stochastic Systems

This study is concerned with the problem of finite-time H∞ filter design for uncertain discrete-time Markov Jump stochastic systems. Our attention is focused on the design of mode-dependent H∞ filter to ensure the finite-time stability of the filtering error system and preserve a prescribed H∞ performance level for all admissible uncertainties. Sufficient conditions of filtering design for the system under consideration are developed and the corresponding filter parameters can be achieved in terms of linear matrix inequalities (LMI). Finally, a numerical example is provided to illustrate the validity of the proposed method.
Effect Of Nd Doping On The Phase Diagram Of (Sm1-Yndy)0.52Sr0.48mno3

We have performed dc magnetization measurements on (Sm1-yNdy)0.52Sr0.48MnO3 (0 ≤ y ≤ 1) single crystals to study the nature of ferromagnetic to paramagnetic phase transition. For y = 0, ferromagnetic transition is first-order along with a discontinuous change in magnetization at TC (110 K) with the presence of thermal hysteresis. With increasing Nd doping (y), TC increases while thermal hysteresis starts to decrease which eventually vanishes at around y = 0.4, suggesting that first-order ferromagnetic transition becomes second-order in nature at that Nd concentration. The variation of TC with y has been explained in terms of the average A-site cation radius and quenched disorder.
Effect of GAN augmented dataset size on deep learning-based ultrasound bone segmentation model training

Recently, ultrasound imaging is increasingly being used as intra-operative imaging modality in osteolytic bone surgery due to its cost-eﬀectiveness and radiation-free nature. Deep learning approaches have shown remarkable success in segmenting bone surface from ultrasound images. However, limited training dataset size has always hindered the success of deep learning approaches, which is especially evident in ultrasound bone segmentation since there is no publicly available quality dataset. To resolve the issue, in addition to standard data augmentation approaches, generative adversarial networks (GANs) have recently been used for generating augmented training samples. Although the addition of the generative approach in data augmentation is observed to have a positive eﬀect on deep learning architecture’s performance, the question about the eﬀect of using a multi-fold of GAN generated training dataset remains unanswered. In this work, we have generated 14 fold of GAN-augmented training dataset and evaluated the performance of the network for successively increased dataset size. Our test results show that although the use of the GAN-augmented training dataset in addition to standard augmentation approaches helps perform the network better, the addition of multi-fold GAN-augmented datasets has no noticeable performance gain.
The Impact of Genre-awareness Raising in the EFL Essay Writing Classes on Their First Language Writing

The current study tends to investigate whether the genre-awareness raising in the EFL essay writing classes will affect the EFL learner’s L1 essay writing. There have been 40 undergraduate junior students in two EFL classes who have all been passing a course in Essay Writing at the Islamic Azad University – Islamshahr. They have been homogenized by performing a TOEFL proficiency test and have been asked to write a composition both in English and Persian on a specified topic at the beginning of the class as a pretest. They have all attended 8 sessions of treatment to raise their awareness of the genre structure of a 5-paragraph essay in English. Then, a post-test similar to the pre-test has been administered. The T-test run between the pretests and post-tests in English and Persian indicates the fact that the EFL learners’ essay writing has improved regarding the genre structure of their 5-paragraph essays (sig. = .006, p< .01 & sig. = .032, p<.05). The correlation between the English and Persian post-tests (0.85), on the other hand, demonstrates a high relationship between the two variables. Since there has been no other variables involved in the improvement of the EFL learners’ use of genre structures in their Persian essays – mostly based on the subjects’ negligence of such structures in their pre-test in their native language, we can conclude that the genre-awareness writing process in English essay writing has significantly influenced the EFL learners’ Persian essay writing. That is, unlike other features of a foreign language, the genre structures as a sort of IDFs are transferable from one language to another through awareness raising.
Assessing the globally averaged sea level budget on seasonal to interannual timescales

[1] Analysis of ocean temperature and salinity data from profiling floats along with satellite measurements of sea surface height and the time variable gravity field are used to investigate the causes of global mean sea level rise between mid-2003 and mid-2007. The observed interannual and seasonal fluctuations in sea level can be explained as the sum of a mass component and a steric (or density related) component to within the error bounds of each observing system. During most of 2005, seasonally adjusted sea level was approximately 5 mm higher than in 2004 owing primarily to a sudden increase in ocean mass in late 2004 and early 2005, with a negligible contribution from steric variability. Despite excellent agreement of seasonal and interannual sea level variability, the 4-year trends do not agree, suggesting that systematic long-period errors remain in one or more of these observing systems.
Eikonal Scattering and Asymptotic Superluminality of Massless Higher Spins

We consider scattering of massless higher-spin particles in the eikonal regime in four dimensions. By demanding the absence of asymptotic superluminality, corresponding to positivity of the eikonal phase, we place constraints on the possible cubic couplings which can appear in the theory. The cubic couplings come in two types: lower-derivative non-abelian vertices, and higher-derivative abelian vertices made out of gauge-invariant curvature tensors. We find that the abelian couplings between massless higher spins lead to an asymptotic time advance for certain choices of polarizations, indicating that these couplings should be absent unless new states come in at the scale suppressing the derivatives in these couplings. A subset of non-abelian cubic couplings are consistent with eikonal positivity, but are ruled out by consistency of the four-particle amplitude away from the eikonal limit. The eikonal constraints are therefore complementary to the four-particle test, ruling out even trivial cubic curvature couplings in any theory with a finite number of massless higher spins and no new physics at the scale suppressing derivatives in these vertices.
' s response to reviews Title : Mobility and cognition are associated with wellbeing and health related quality of life among older adults

Thank you for the insightful comments from the Editorial Team and the Reviewers. We have been diligent in incorporating the reviewers’ and editorial team comments. These suggestions are addressed in the ‘Response to Reviewers’ document. These revisions are highlighted using the ‘Track Changes’ function in Microsoft Word. We also attached a clean version of the manuscript with ‘Track Changes’ accepted.
AN ADAPTIVE VISCOSITY E–SCHEME FOR DEGENERATE CONSERVATION AND BALANCE LAWS

An adaptive E–scheme for degenerate, viscous balance laws is presented. Taking into account natural diffusion, numerical viscosity is locally reduced to a minimum. Numerical experiments demonstrate the improved accuracy of the adaptive scheme. Explicit and implicit three–point E–schemes are monotone, TVD and nonlinearly stable. A high–resolution version of the adaptive E–scheme is derived and tested in experiments. The latter is not necessarily monotone, but TVD.
SOUNDSCAPE EMOTION RECOGNITION VIA DEEP LEARNING

Deep learning has proven very effective in image and audio classification tasks. Is it possible to improve the performance of emotion recognition tasks based on deep learning approaches? We introduce the strength of deep learning in the context of soundscape emotion recognition (SER). To the best of our knowledge, this is the first study to use deep learning for SER. The main aims are to evaluate the performance of the Convolutional Neural Network (CNN) trained from scratch, the Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN) trained from scratch, the CNN trained through supervised fine-tuning, the Support Vector Machines for Regression (SVR), and the combination of CNN and SVR (Transfer Learning) for predicting the perceived emotion of sound-scape recordings. The results show that deep learning is a promising approach for improving the performance for SER. Moreover, the fine-tuned VGG-like audio classification model outperforms the other deep-learning frameworks regarding predicting valence. The best performance of predicting arousal is obtained by the CNN trained from scratch. Finally, we analyze the performance of predicting perceived emotion for soundscape recordings in each of Schafer's soundscape categories.
LIFE-THREATENING HYPERNATREMIA IN A 22-YEAR-OLD MAN WITH CONCURRENT DIABETIC KETOACIDOSIS AND HYPEROSMOLAR HYPERGLYCEMIC STATE

Van Phan1, Vien Phan2, Thai Truong3, Phillip Tran4, Andre Outon5 From 1Resident, 5Internist, Department of Medicine, NYC Health + Hospitals/Jacobi, New York, USA, 2Researcher, Department of Internal Medicine, Kansai Medical University, Osaka, Japan, 3Resident, Department of Medicine, University of Medicine and Pharmacy, Ho Chi Minh City, Vietnam, 4Cardiologist, Department of Cardiovascular, Yavapai Regional Medical Center, Prescott, Arizona, USA Correspondence to: Van Phan, Jacobi Medical Center, 1400 Pellham Parkway South, Bronx, New York 10461, USA. E-mail:tuongvanmd@gmail.com Received 21 March 2020 Initial Review 06 April 2020 Accepted 21 April 2020
Real-Time Recommendation of Diverse Related

News articles typically drive a lot of traffic in the form of comments posted by users on a news site. Such usergenerated content tends to carry additional information such as entities and sentiment. In general, when articles are recommended to users, only popularity (e.g., most shared and most commented), recency, and sometimes (manual) editors’ picks (based on daily hot topics), are considered. We formalize a novel recommendation problem where the goal is to find the closest most diverse articles to the one the user is currently browsing. Our diversity measure incorporates entities and sentiment extracted from comments. Given the realtime nature of our recommendations, we explore the applicability of nearest neighbor algorithms to solve the problem. Our user study on real opinion articles from aljazeera.net and reuters.com validates the use of entities and sentiment extracted from articles and their comments to achieve news diversity when compared to content-based diversity. Finally, our performance experiments show the real-time feasibility of our solution.
Dynamic and Temporal Answer Set Programming on Linear Finite Traces

The logical foundations of Answer Set Programming (ASP; (Lifschitz, 1999)) rest upon the logic of Here-and-There (HT; (Heyting, 1930)), or more precisely its equilibrium models (Pearce, 1997) that correspond to stable models semantics (Gelfond and Lifschitz, 1988). For deﬁning extensions to ASP from ﬁrm logical principles, it has thus become good practice to ﬁrst elaborate upon equilibrium models for an extended HT setting in order to consider after-wards the respective language fragments of that setting that are well suited in the context of logic programming. This avenue was also followed in (Cabalar and Vega, 2007), which gave rise to the temporal extension of HT called Temporal Here-and-There (THT) and its non-monotonic counterpart Temporal Equilibrium Logic (TEL (Aguado et al., 2013)). More precisely, TEL builds upon an extension of the logic of HT with Linear Temporal Logic (LTL; (Pnueli, 1977)) sharing the syntax of the latter. This results in an expressive non-monotonic modal logic, which extends traditional temporal logic programming approaches (Cabalar, Di ´ eguez, and Vidal, 2015) to the general syntax of LTL and possesses a computational complexity beyond LTL (Bozzelli and Pearce, 2015). As in LTL, a model in TEL is an inﬁnite sequence of states, called a trace . These inﬁnite traces are convenient for describ-ing formal properties of reactive systems and, as in LTL, can be processed by model checking techniques based on automata construction (Cabalar Demri, 2011; Cabalar Di ´ eguez, However, the usual temporal reasoning problems treated in the ASP literature are simulation, explanation and planning under the assumption of a ﬁnite narrative. In that sense, temporal approaches based on ﬁnite traces (Baier McIlraith,
ANALYSIS OF THE IMPACT ON THE SURROUNDING LOADS FOR THE APPLICATION OF SHUNT ACTIVE POWER FILTER

The industrial field not only includes diode rectifier with smoothing inductor, thyristor rectifier, and diode rectifier with smoothing dc capacitor loads, but also contains reactive compensation capacitors and passive filters. The application of Shunt Active Power Filter (SAPF) in this field may cause significant harmonic pollution to the systems. This paper analyzes the harmonic characteristics before and after SAPF put into operation for a given nonlinear load, reveals the series and parallel resonance between the equivalent capacitance (the voltage-type harmonic source, reactive compensation capacitors and passive filters) and system inductance(line inductors and the leakage inductors of transformers or motors) may be excited for the frequency conversion effect, and analyzes the harmonic voltage propagation and the harmonic voltage and current magnification by using transmission line theory. Then, two-type methods are proposed to deal with the problems by this paper, i.e. to modify the topology/parameters so as to change the resonant frequency of the system; while the other is to improve and change SAPF’s compensation bandwidth to be a selective or limited one. Furthermore, a virtual-harmonicresistance based active damping method is also proposed for the harmonic-resonance suppression. They all can suppress the harmonic current effectively, while guarantee the load-side current without significant enlargement. Simulation results validate the feasibility of the schemes proposed by this paper.
Sugars, organic acids, minerals and lipids in jabuticaba

O objetivo deste trabalho foi determinar a composicao dos acucares, acidos orgânicos e minerais do fruto inteiro e fracoes (casca, polpa e semente) dos genotipos de jabuticabeira Paulista (Plinia cauliflora) e Sabara (P. jaboticaba), assim como a composicao do oleo das cascas e sementes. As frutas apresentaram elevados teores de acucares totais, destacando-se a frutose, seguida de glicose e sacarose. No genotipo Paulista, foram encontrados teores mais elevados de acucares totais e redutores na polpa e na casca, o que nao foi observado ao comparar os frutos inteiros dos dois genotipos. Foram encontrados cinco acidos orgânicos na seguinte ordem quantitativa: acido citrico > acido succinico > acido malico > acido oxalico > acido acetico. Potassio foi o mineral mais abundante encontrado. A fruta mostrou tambem ser rica em magnesio, fosforo, calcio e cobre. O oleo das sementes mostrou ter praticamente a mesma constituicao do oleo extraido das cascas, e os compostos majoritarios foram um fitosterol nao identificado, os acidos palmitico, linoleico e oleico e o esqualeno.
Aalborg Universitet A mixed methods exploration of intensive care unit nurses ’ perception of handling oxygen therapy to critically ill patients

Objectives: Nurses handle supplementary oxygen to intensive care unit patients as part of their daily practise. To secure patients of optimal and safe care, knowledge of nurses’ perception of this practise, including influencing factors for adjusting oxygenation levels is essential. This study aimed to explore intensive care nurses’ perception of handling oxygenation and of factors that govern and influence this practise. Research methodology/design: A mixed methods approach was applied comprising six focus group interviews, conducted in February/March 2017, leading to construction of a questionnaire distributed to 535 ICU nurses in September 2017. Following a process of content analysis, the findings were discussed against Gittell’s framework for relational coordination. Setting: Intensive care units in rural, urban and university hospital settings. Main outcome: A deeper understanding of nurses’ perception of handling oxygenation to patients in the intensive care unit. Findings and results: Findings are presented through the categories Treatment Guidance, Nursing Practise, Knowledge and Competences and Inter-professional Collaboration. Conclusion: Nurses’ practise of handling supplementary oxygen therapy to the intensive care patient is influenced by day-by-day physician prescribed upper and lower limits for pO2 and pCO2, by nurses’ understanding of the individual clinical patient situation and by knowledge of pros and cons in relation to oxygen therapy including observational and clinical assessment expertise. Establishing working environments in the intensive care unit setting based on mutual interand intra-professional respect may contribute to enhance safe and high quality patient care. 2018 The Authors. Published by Elsevier Ltd. This is anopenaccess article under the CCBY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Implications for clinical practice Explicit and written treatment guidelines and shared goals for oxygen treatment is needed to support correct supplementary oxygen supply and avoid day-by-day changes and risk of oxygen overload. Nurses’ every day practise handling oxygen should rely on treatment guidelines and nurses’ professional clinical assessment. If future research provides evidence for a more restrictive approach for oxygen supplements to the critically ill patient, it is of vital importance that nurses as well as physicians are thoroughly educated and trained, preferably together to reach high levels of shared knowledge and to serve as a basis for respectful inter-professional collaboration.