Miracle-dz/UniFAR-FTUs huggingface dataset:
Glyco-Platelets with Controlled Morphologies via Crystallization-Driven Self-Assembly and Their Shape-Dependent Interplay with Macrophages.

Two-dimensional (2D) materials are of great significance to the materials community as a result of their high surface area and controllable surface properties. However, controlled preparation of biodegradable 2D structures with biological activity is difficult. In this work we demonstrate that by careful selection of building block structures and assembly conditions it is possible to use crystallization-driven self-assembly (CDSA) to assemble well-defined 2D nanostructures from poly(l-lactide) (PLLA)-based diblock glycopolymers. 1D glyco-cylinders and 2D diamond-shaped glyco-platelets are produced, where the underlying formation mechanism is revealed by dissipative particle dynamics simulations. Furthermore, we demonstrate that assembly of the polymers under mild degradation provides a straightforward route to hollow-cored platelets, a morphology that has previously proven laborious to access. The well-defined sizes and shapes of the glyco-platelets allow us to investigate macrophage activation efficiency and demonstrate clear size and shape effects, pointing toward potential applications in immunology.
Neural Network-based Multilingual Translation Models

Statistical machine learning usually requires extensive corpora for training. In the case of Machine Translation (MT) these corpora consist of large amounts of parallel texts in the chosen source and target languages. Since acquiring corpora is usually time-consuming and expensive, especially in the case of exotic language pairs such as VietnameseIndonesian, a third pivot language is sometimes used for a pipelined translation. I.e. a source language will be translated into the pivot language rst, with the result nally being translated into the actual target language. However, in a straightforward pipelining systems like this the second MT system will tend to reinforce errors made by the rst, leading to an overall poor translation quality. In this work we attempt to transfer the idea of pipelining to the model level and combine this approach with an interlingua representation of language, leading to a multilingual neural network based discriminative word lexicon (NNDWL). These models are trained on various language pairs and are capable of translating between languages even without having seen any sample sentences from that speci c pair. Our proposed multilingual architecture was able to outperform a simple pipelined unilingual NNDWL. Compared to unilingual NNDWL, which used translated sentences from source to intermediate language as input, the multilingual counterpart resulted in similar translation quality. If only the intrinsic objective function is considered, the error rates were even nearly identical. This approach allows for translation between rarely looked-at languages without having to train a dedicated MT system for the speci c pair. Moreover, using such a simple model, the system is already capable of generating a translation fairly quickly. In future works, we would like to adapt the concept to more complex models, in order to improve the overall translation quality. In addition, the system could be extended via additional languages and input modals, forcing the model to learn abstract or interlingua representation from the input data .
Evaluation of the Structure-Function Relationship in Glaucoma Using a Novel Method for Estimating the Number of Retinal Ganglion Cells in the Human Retina.

PURPOSE We developed a simple method for estimating the number of retinal ganglion cells (RGCs) in the human retina using optical coherence tomography (OCT), compared it to a previous approach, and demonstrated its potential for furthering our understanding of the structure-function relationship in glaucoma. METHODS Swept-source (ss) OCT data and 10-2 visual fields (VFs) were obtained from 43 eyes of 36 healthy controls, and 50 eyes of 50 glaucoma patients and suspects. Using estimates of RGC density from the literature and relatively few assumptions, estimates of the number of RGCs in the macula were obtained based on ssOCT-derived RGC layer thickness measurements. RESULTS The RGC estimates were in general agreement with previously published values derived from histology, whereas a prior method based on VF sensitivity did not agree as well with histological data and had significantly higher (P = 0.001) and more variable (P < 0.001) RGC estimates than the new method based on ssOCT. However, the RGC estimates of the new approach were not zero for extreme VF losses, suggesting that a residual, non-RGC contribution needs to be added. Finally, the new ssOCT-derived RGC estimates were significantly (P < 0.001 to P = 0.018) related to VF sensitivity (Spearman's ρ = 0.26-0.47), and, in contrast to claims made in prior studies, statistically significant RGC loss did not occur more often than statistically significant visual loss. CONCLUSIONS The novel method for estimating RGCs yields values that are closer to histological estimates than prior methods, while relying on considerably fewer assumptions. Although the value added for clinical applications is yet to be determined, this approach is useful for assessing the structure-function relationship in glaucoma.
Empirical Valuation of Relationship between Freight Index and Economic Performance

The index method is significant among the individual methods of scientific research. This work intends to develop ways to analyze the usage of transport indices as indicators of the character of market activity in logistical infrastructure at different levels. Transport indices only developed in the past decade; nevertheless, they have already developed a large degree of diversity. This makes systematization, classification, and identification of their distinguishing features all necessary. By their nature, freight indices are largely similar to stock market indices, in that they both show the average changes in some observed phenomenon, and that they both aim to describe the general changes in a process involving many factors. The authors propose a transport index classification with freight indices set aside in a separate group, depending on their intended applications and possible uses. As a result, based on the empirical analysis of the transport index and the stock market index, the level of interconnection between logistical infrastructure and market activity in the Russian economy has been defined, by applying the GARCH model. On the other hand, applying this methodology to the USA’s statistical transport index and stock market index gave no results. This once again confirms the necessity of setting freight indices aside in a separate group, as well as the futility of performing analytical procedures with statistically heterogeneous indexes.
Mouse models of Machado-Joseph disease and other polyglutamine spinocerebellar ataxias

SummaryMachado-Joseph disease (MJD), also called spinocerebellar ataxia type 3, is caused by mutant ataxin-3 with a polyglutamine expansion. Although there is no treatment available at present to cure or delay the onset of MJD, mouse models have been generated to facilitate the development of a therapy. In this review, the published reports on mouse models of MJD and other polyglutamine spinocerebellar ataxias are compared. Based on these studies, the following approaches will be discussed as candidate treatments for MJD: 1) interfering with the formation of the mutant ataxin-3 cleavage fragment and possibly aggregate or inclusions, 2) reducing the disease protein nuclear localization, and 3) decreasing mutant ataxin-3 expression in neurons.
Robustness in Mechanism Design and Contracting

This review summarizes a nascent body of theoretical research on design of incentives when the environment is not fully known to the designer and offers some general lessons from the work so far. These recent models based on uncertainty and robustness offer an additional set of tools in the toolkit, complementary to more traditional, fully Bayesian modeling approaches, and broaden the range of problems that can be studied. The kinds of insights that such models can offer, and the methodological and technical challenges that they confront, broadly parallel those of traditional approaches.
The Reparative Abilities of Menstrual Stem Cells Modulate the Wound Matrix Signals and Improve Cutaneous Regeneration

Considerable advances have been made toward understanding the cellular and molecular mechanism of wound healing, however, treatments for chronic wounds remain elusive. Emerging concepts utilizing mesenchymal stem cells (MSCs) from umbilical cord, adipose tissue and bone marrow have shown therapeutical advantages for wound healing. Based on this positive outcome, efforts to determine the optimal sources for MSCs are required in order to improve their migratory, angiogenic, immunomodulatory, and reparative abilities. An alternative source suitable for repetitive, non-invasive collection of MSCs is from the menstrual fluid (MenSCs), displaying a major practical advantage over other sources. This study aims to compare the biological functions and the transcriptomic pattern of MenSCs with umbilical cord MSCs in conditions resembling the wound microenvironment. Consequently, we correlate the specific gene expression signature from MenSCs with changes of the wound matrix signals in vivo. The direct comparison revealed a superior clonogenic and migratory potential of MenSCs as well as a beneficial effect of their secretome on human dermal fibroblast migration in vitro. Furthermore, MenSCs showed increased immunomodulatory properties, inhibiting T-cell proliferation in co-culture. We further, investigated the expression of selected genes involved in wound repair (growth factors, cytokines, chemokines, AMPs, MMPs) and found considerably higher expression levels in MenSCs (ANGPT1 1.5-fold; PDGFA 1.8-fold; PDGFB 791-fold; MMP3 21.6-fold; ELN 13.4-fold; and MMP10 9.2-fold). This difference became more pronounced under a pro-inflammatory stimulation, resembling wound bed conditions. Locally applied in a murine excisional wound splinting model, MenSCs showed a significantly improved wound closure after 14 days, as well as enhanced neovascularization, compared to the untreated group. Interestingly, analysis of excised wound tissue revealed a significantly higher expression of VEGF (1.42-fold) among other factors, translating an important conversion of the matrix signals in the wound site. Furthermore, histological analysis of the wound tissue from MenSCs-treated group displayed a more mature robust vascular network and a genuinely higher collagen content confirming the pro-angiogenic and reparative effect of MenSCs treatment. In conclusion, the superior clonogenicity, immunosuppressive and migration potential in combination with specific paracrine signature of MenSCs, resulted in an enhanced wound healing and cutaneous regeneration process.
A Cost-Efficient Real-Time 25 Mb/s System for LED-UOWC: Design, Channel Coding, FPGA Implementation, and Characterization

In this paper, we experimentally demonstrate a cost-efficient real-time field programmable gate array (FPGA)-based system for underwater optical wireless communication (UOWC) at a data rate up to 25 Mb/s over a 10 m underwater channel. The transmitter of the system employs a commercial blue LED as a modulation light source and an FPGA unit for transmitter baseband signal processing, and an avalanche photo diode cascaded with an FPGA unit for receiver baseband signal processing at the receiver side. We also suggest a simplified system model to characterize underwater optical link. Three types of hard-decision forward error correction codes are introduced to investigate the impact on the receiver sensitivity in long distance transmission cases. By adding additional link attenuation, we experimentally measure the attenuation coefficients for different water conditions. Based on the measured results, the achievable link distance for clear ocean water is estimated up to 118 m at the transmitted electrical power of 30 dBm. The proposed UOWC system takes both implementation complexity and cost into consideration and also provides a significant guidance to the future real-time high-speed underwater optical communications.
Voltage sharing scheme for series-connected power semiconductors

Dynamic voltage-sharing schemes have been investigated which allow high-voltage power-semiconductor devices, such as thyristors, IGCTs, IGBTs or power MOSFETs, to be series connected in strings and switched, as simply in high-voltage applications, as when used as single devices. The circuits have many of the advantages of simply using RC or RCD snubbers, including being easily applicable to both low- and high-side switches. However, because the snubber capacitors are not fully discharged their associated reset current and power-losses are minimized. To illustrate the principle of operation experimentally, a string of three series-connected power MOSFETs switching 100 A from 330 V has been used to obtain practical waveforms. The schemes are discussed and illustrated, using SPICE simulation results. The new, relatively simple voltage-sharing schemes are much easier to design and optimize than recently reported active gate-control and regenerative-snubber methods, allow very rapid turn-on and turn-off switching, and give composite-device switches a usable voltage rating similar to the aggregated voltage ratings of the string.
Can 'Time-Invariant' Hedges Estimated from Time-Varying Hedge Models Outperform Time-Invariant Hedges Even During Period of Financial Crisis? An Empirical Investigation of Indian Futures Market

The real test of effectiveness of hedge models and its consistency happens when markets are turbulent and during extreme events. This study is, therefore, an attempt to explore Indian futures market for hedging by equity holders in general as well as in period of recent financial crisis. We have estimated effectiveness of the optimal hedge ratio based on HKM [Herbst, Kare and Marshall (1993)] methodology with benchmark model JSE [Johnson (1960), Stein (1961) and Ederington (1979)] methodology for futures. Hedge ratio based on HKM methodology is a time-variant whereas hedge ratio based on JSE methodology is a constant and time-invariant. To bring the comparison of hedge effectiveness on equal level (from transaction cost point of view), time-varying hedge ratio estimated based on HKM methodology are made “time-invariant” and then Bases using the hedge ratios are estimated. For empirical validation of the Effectiveness of the optimal hedge ratios and their stability in normal as well in the period of financial crisis, the study of S&P Nifty Index {National Stock Exchange of India (NSE) – 50 Index and its futures is conducted using daily data for the year 2005 (representing normal period) and January, 2007 to June,2009 (representing turbulent time period) based on the value of volatility index. Results suggest that hedge using HKM model is more effective than that of hedge based on JSE model. The results are statistically significant at 95% confidence level. An additional contribution of this study is to help the hedger to decide “when” to re-balance the hedge.
The Effect of a Textured Insole on Symmetry of Turning

Turning while walking is a common daily activity. Individuals with unilateral impairment frequently perform turns asymmetrically. The purpose of the study was to investigate the effect of a discomfort-inducing textured insole on symmetry of turning. Nine healthy individuals performed turns to the right while walking with no insole, immediately after the insole was inserted in the right shoe, and after walking for six minutes with the insole. The duration of turning, displacements of pelvic markers, and perceived level of discomfort were evaluated. Utilizing the insole was associated with the increased level of perceived discomfort (p < 0.05). Moreover, using the insole was linked to changes in the displacement of two pelvic markers and larger asymmetry index while turning immediately after the insole was inserted in the right shoe as compared to no insole condition (p < 0.05). The duration of right turning increased immediately after the insole was inserted (p < 0.05) and after walking with the insole for six minutes. The results indicate that the textured insole creates asymmetry of turning in healthy individuals. The outcome provides a background for future studies focused on using a textured insole to minimize the asymmetry of turning commonly seen in individuals with unilateral impairment.
Modeling of a negative ion source I . Gas kinetics and dynamics in the expansion region

The vibrational population distribution of the electronic ground state of H2 in the expansion region of a negative ion source is investigated using a kinetic Monte Carlo model. Operative conditions are referred to the inductively coupled plasma radio frequency negative ion source developed at IPP-Garching. The different excitation and relaxation processes are discussed, both bulk and surface contributions. In particular, due to the relatively high plasma density, the relevant role of direct low energy electron-impact excitation, surface Auger neutralization and vibration-translation deactivation is recovered. Results of the present model will be used as input data for the neutral source model in the extraction region. * corresponding author: taccogna@ipp.mpg. de
Relationship between Emotional Labor and Intrinsic Job Satisfaction: The Moderating Role of Gender

Using a wide range of excitements by service staff indicates the important role of emotional labor in such jobs, which affect their job satisfaction. This study examines the relationship between emotional labor and intrinsic job satisfaction among salespersons. The study is a descriptive study of correlation type and field survey. A population consisted of 248 salespersons working in seven chain stores were selected through simple sampling. Data collection tools are standard questionnaires whose validity and reliability have been confirmed. Obtained data were analyzed using descriptive and inferential statistics tests and structural equation modeling and regression analysis. The findings of the research indicate that there is a significant difference between the level of emotional labor, surface acting and deep acting between women and men. There is also direct relationship between emotional labor and intrinsic job satisfaction. Additionally, the effect of gender moderator on the relationship between emotional labor and intrinsic job satisfaction was confirmed.
Prediction of Domestic Hot Water Temperature in a District Heating Network

With the fourth generation of district heating networks in sight, opportunities are rising for better services and optimized planning of energy production. Indeed, the more intensive data collection is expected to allow for load prediction, customer profiling, etc. In this context, our work aims at a better understanding of customer profiles from the captured data. Given the variety of households, such profiles are difficult to capture. This study explores the possibility to predict domestic hot water (DHW) usage. Such prediction is made challenging due to the presence of two components in the signal, the first one bound to the physical properties of the DHW distribution system, the second one bound to the human patterns related to DHW consumption. Our contributions include (1) the analysis of recurrent neural network architectures based on GRU, (2) the inclusion of state-based labels inferred in an unsupervised way to simulate domain knowledge, (3) the comparison of different features. Results show that the physical contribution in the signal can be forecasted successfully across households. On the contrary, the stochastic “human” component is harder to predict and would need further research, either by improving the modelling or by including alternate signals.
Fuzzy Spectral Hierarchical Communities in Evolving Political Contribution Networks

A valuable tool for analyzing social networks is partitioning the complex graphs based on dense sub-networks, usually referred to as communities. This partitioning can discover groups who have similar attributes or behaviors. Using a previously developed method for creating hierarchical fuzzy communities using spectral clustering, these communities are evaluated in a temporal network and tracked through time to evaluate community change. This method is tested on a real world political network based on campaign finance contributions, and it is shown how communities change over time at multiple levels of the hierarchy.
English to Hindi Machine Translation System

This paper presents an overview of the English to Hindi Machine Translation System using Rule-based translation system. Rule-based Machine Translation system translates a language into another language using linguistic information like dictionary and grammars and by following the semantic and syntactic rules of each language. Communication between people from different linguistic backgrounds still poses as a major problem. Hindi is one of the most popular and used languages in India but English even though being a universal language is not known by many Indians. The aim of this translation system is to provide a platform to do the translation which will enhance the well-learned society of Indians without the barrier of language.
Performance of Cascaded Diode Bridge Integrated H-Bridge 13 Level Multilevel Inverter

Cascaded H-bridge (CBH) Multi Level Inverter (MLI) holds the benefits in the availability of isolated DC links. This topology of CHBMLI is being frequent at usage in the renewable applications. To avoid the switching loss, the main purpose of MLIs lies in the usage of switches. Henceforth, to cope up with the problem, the number of switches is compulsorily increased for the higher level. This paper presents the performance of Two Cell Cascaded Diode Bridge Integrated H-Bridge Multilevel Inverter having thirteen levels. The technique used is based on obtaining the pulses by comparing the sine wave with constant dc source of variable amplitude. With this technique we reduced the frequency of PWM signal and therefore reduce the switching loss of power switches and harmonic components. MATLAB simulation results of this technique shows that THD are reduced to minimum value.
A Data-Driven Approach to Smooth Pitch Correction for Singing Voice in Pop Music

In this paper, we present a machine-learning approach to pitch correction for voice in a karaoke setting, where the vocals and accompaniment are on separate tracks and time-aligned. The network takes as input the time-frequency representation of the two tracks and predicts the amount of pitch-shifting in cents required to make the voice sound in-tune with the accompaniment. It is trained on examples of semi-professional singing. The proposed approach differs from existing real-time pitch correction methods by replacing pitch tracking and mapping to a discrete set of notes---for example, the twelve classes of the equal-tempered scale---with learning a correction that is continuous both in frequency and in time directly from the harmonics of the vocal and accompaniment tracks. A Recurrent Neural Network (RNN) model provides a correction that takes context into account, preserving expressive pitch bending and vibrato. This method can be extended into unsupervised pitch correction of a vocal performance---popularly referred to as autotuning.
Feedback Model Makes Changes in Education

Among the many tactical interventions to support school districts quest for No Child Left Behind (NCLB) compliance, the Strategic Schooling model has proven to be effective in several school districts throughout California, including Fresno, Berkeley, parts of northern and southern California. This tactical intervention promotes the concepts of identifying target students, providing feedback andusing the skill and know-how.