Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical applications of diffusion‐weighted magnetic resonance imaging in diagnosis of renal lesions – a systematic review

Diffusion‐weighted magnetic resonance imaging (DW‐MRI) is an established technique to detect the changes of the diffusion of water in biological tissues and reflect the pathophysiological process on the molecular level. It is a promising non‐invasive imaging modality in detection of microstructural and functional changes in pathologies of kidney. To systematically review the research advancement of the DW‐MRI in diagnosis of renal lesions, a systematic literature search was performed up to 8 October 2014 using the MEDLINE/PubMed and Embase databases for articles reporting on DW‐MRI in diagnosis of renal lesions. Only articles with full data about DW‐MRI application with potential implication in solving usually encountered clinical challenges about renal lesions were finally examined. The clinical application of DW‐MRI allows a better understanding of some pathologic conditions of the kidney including renal insufficiency, renal artery stenosis, ureteral obstruction, foetal kidney disease, hydronephrosis and pyonephrosis. In addition, DW‐MRI can also provide clinicians with the information of function evaluation of renal allograft and curative effect assessment of renal tumour. In summary, performance of renal DW‐MRI, presuming that measurements are high quality, will further boost this modality, particularly for early detection of diffusion renal conditions, as well as more accurate characterization of renal lesions.
Neural Agrin Induces Ectopic Postsynaptic Specializations in Innervated Muscle Fibers

Neural agrin, in the absence of a nerve terminal, can induce the activity-resistant expression of acetylcholine receptor (AChR) subunit genes and the clustering of synapse-specific adult-type AChR channels in nonsynaptic regions of adult skeletal muscle fibers. Here we show that, when expression plasmids for neural agrin are injected into the extrasynaptic region of innervated muscle fibers, the following components of the postsynaptic apparatus are aggregated and colocalized with ectopic agrin-induced AChR clusters: laminin-β2, MuSK, phosphotyrosine-containing proteins, β-dystroglycan, utrophin, and rapsyn. These components have been implicated to play a role in the differentiation of neuromuscular junctions. Furthermore, ErbB2 and ErbB3, which are thought to be involved in the regulation of neurally induced AChR subunit gene expression, were colocalized with agrin-induced AChR aggregates at ectopic nerve-free sites. The postsynaptic muscle membrane also contained a high concentration of voltage-gated Na+ channels as well as deep, basal lamina-containing invaginations comparable to the secondary synaptic folds of normal endplates. The ability to induce AChR aggregationin vivo was not observed in experiments with a muscle-specific agrin isoform. Thus, a motor neuron-specific agrin isoform is sufficient to induce a full ectopic postsynaptic apparatus in muscle fibers kept electrically active at their original endplate sites.
Traffic Allocation for Low-Latency Multi-Hop Networks With Buffers

For buffer-aided tandem networks consisting of relay nodes and multiple channels per hop, we consider two traffic allocation schemes, namely local allocation and global allocation, and investigate the end-to-end latency of a file transfer. We formulate the problem for generic multi-hop queuing systems and subsequently derive closed-form expressions of the end-to-end latency. We quantify the advantages of the global allocation scheme relative to its local allocation counterpart, and we conduct an asymptotic analysis on the performance gain when the number of channels in each hops increases to infinity. The traffic allocations and the analytical delay performance are validated through simulations. Furthermore, taking a specific two-hop network with millimeter-wave (mm-wave) as an example, we derive lower bounds on the average end-to-end latency, where Nakagami- $m$ fading is considered. Numerical results demonstrate that, compared with the local allocation scheme, the advantage of global allocation grows as the number of relay nodes increases, at the expense of higher complexity that linearly increases with the number of relay nodes. It is also demonstrated that a proper deployment of relay nodes in a linear mm-wave network plays an important role in reducing the average end-to-end latency, and the average latency decays as the mm-wave channels become more deterministic. These findings provide insights for designing multi-hop mm-wave networks with low end-to-end latency.
Semi-supervised Non-negative Patch Alignment Framework

Non-negative matrix factorization (NMF) learns the latent semantic space more direct and reliable than the latent semantic indexing (LSI) and the spectral clustering methods, thus performs well in document clustering. Recently, semi-supervised NMF such as N2S2L, CNMF and unsupervised method such as GNMF significantly improve the face recognition performance, but they are designed for classification. In this paper, we combine both geometric structure and label information with NMF under the non-negative patch alignment framework (NPAF) to form SS-NPAF. Due to this combination, it greatly improves the clustering performance. To optimize SS-NPAF, we apply the well-known projected gradient method to overcome the slow convergence problem of the mostly used multiplicative update rule. Experimental results on two popular document datasets, i.e., Reuters21578 and TDT-2, show that SS-NPAF outperforms the representative SS-NMF algorithms.
Moving to Universal Coverage? Trends in the Burden of Out-Of-Pocket Payments for Health Care across Social Groups in India, 1999–2000 to 2011–12

In the background of ongoing health sector reforms in India, the paper investigates the magnitude and trends in out-of-pocket and catastrophic payments for key population sub-groups. Data from three rounds of nationally representative consumer expenditure surveys (1999–2000, 2004–05 and 2011–12) were pooled to assess changes over time in a range of out-of-pocket -related outcome indicators for the poorest 20% households, scheduled caste and tribe households and Muslims households relative to their better-off/majority religion counterparts. Our results suggest that the poorest 20% of households experienced a decline in the proportion reporting any OOP for inpatient care relative to the top 20% and Muslim households saw an increase in the proportion reporting any inpatient OOP relative to non-Muslim households during 2000-2012. The change in the proportion of Muslim households or SC/ST households reporting any OOP for outpatient care was similar to that for their respective more advantaged counterparts; but the poorest 20% of households experienced a faster increase in the proportion reporting any OOP for outpatient care than their top 20% counterparts. SC/ST, Muslim and the poorest 20% of households experienced as faster increase in the share of outpatient OOP in total household spending relative to their advantaged counterparts. We conclude that the financial burden of out of pocket spending increased faster among the disadvantaged groups relative to their more advantaged counterparts. Although the poorest 20% saw a relative decline in OOP spending on inpatient care as a share of household spending, this is likely the result of foregoing inpatient care, than of accessing benefits from the recent expansion of cashless publicly financed insurance schemes for inpatient care. Our results highlight the need to explore the reasons underlying the lack of effectiveness of existing public health financing programs and public sector health services in reaching less-advantaged castes and religious minorities.
A Crypto-Based Approach to Privacy-Preserving Collaborative Data Mining

To conduct data mining, we often need to collect data from various parties. Privacy concerns may prevent the parties from directly sharing the data and some types of information about the data. How multiple parties collaboratively conduct data mining without breaching data privacy presents a challenge. In this paper, we propose a formal definition of privacy, develop a solution for privacy-preserving k-nearest neighbor classification which is one of data mining tasks, and show that our solution preserves data privacy according to our definition
PHD filters for nonstandard targets, I: Extended targets

The probability hypothesis density (PHD) and cardinalized PHD (CPHD) filters were introduced in 2000 and 2006, respectively, as approximations of the full multitarget Bayes detection and tracking filter. Both filters are based on the “standard” multitarget measurement model that underlies most multitarget tracking theory. This paper is one of a series of theoretical studies that address PHD and CPHD filters for nonstandard multitarget measurement models. In this paper I derive the measurement-update equations for a PHD filter that presumes a Poisson model for extended targets due to Gilholm, Godsill, Maskell, and Salmond.
Step by Step: Investigating Foot Gesture Interaction

A promising new way of interacting with computing devices is by using our feet. Foot interaction has the potential of being an intuitive, easy to use and enjoyable way of interaction. However, there are very few guidelines for using foot interaction, or specifically foot gestures. In this research we conduct a user elicitation study for foot interaction on a horizontal surface to produce user-defined gesture sets for actions taken from two domains -- typical GUI actions and avatar controls. We analyze how foot gestures differentiate from hand gestures, point out foot gesture properties and discuss general observations.
SIMBICON: simple biped locomotion control

Physics-based simulation and control of biped locomotion is difficult because bipeds are unstable, underactuated, high-dimensional dynamical systems. We develop a simple control strategy that can be used to generate a large variety of gaits and styles in real-time, including walking in all directions (forwards, backwards, sideways, turning), running, skipping, and hopping. Controllers can be authored using a small number of parameters, or their construction can be informed by motion capture data. The controllers are applied to 2D and 3D physically-simulated character models. Their robustness is demonstrated with respect to pushes in all directions, unexpected steps and slopes, and unexpected variations in kinematic and dynamic parameters. Direct transitions between controllers are demonstrated as well as parameterized control of changes in direction and speed. Feedback-error learning is applied to learn predictive torque models, which allows for the low-gain control that typifies many natural motions as well as producing smoother simulated motion.
Instructional Practices in Early Elementary School Written Expression: Teacher Beliefs, Instructional Strategies and Decision Making

Many university teacher training programs do not provide future teachers with training regarding written expression instruction (Gilbert & Graham, 2010), leading to teachers lacking foundational teaching strategies for instructing written expression. This article focuses on the practical teaching experiences of seven early elementary school teachers instructing written expression. These experiences are examined through a phenomenological approach with a constructivist framework. Each participant completed two audio recorded semi-structured interviews and one classroom observation. Four major themes emerged from the transcripts, observations and artifacts gathered. Two of the themes include subthemes. The teachers reported primarily learning to instruct written expression through personal experience and the experience of colleagues, rather than from teacher training programs. Through this research, teachers described reliance on training while already working as elementary school educators and reliance on same grade-level colleagues to improve their own skills at instructing written expression. Additionally, some participants reported not realizing the limited knowledge that they had regarding written expression until they were already teachers. Furthermore, the participants indicated reliance on cues from their own students to determine the knowledge students have more heavily than using objective, research based tools. Written expression skills are important for early elementary school students in order for them to be able to express themselves, communicate with others, and to demonstrate their knowledge in a variety of academic subjects. In addition, early writing skills are valuable to allow students to build more complex skills in the future.
Relationship Between Left Ventricular Structural and Metabolic Remodeling in Type 2 Diabetes

Concentric left ventricular (LV) remodeling is associated with adverse cardiovascular events and is frequently observed in patients with type 2 diabetes mellitus (T2DM). Despite this, the cause of concentric remodeling in diabetes per se is unclear, but it may be related to cardiac steatosis and impaired myocardial energetics. Thus, we investigated the relationship between myocardial metabolic changes and LV remodeling in T2DM. Forty-six nonhypertensive patients with T2DM and 20 matched control subjects underwent cardiovascular magnetic resonance to assess LV remodeling (LV mass–to–LV end diastolic volume ratio), function, tissue characterization before and after contrast using T1 mapping, and 1H and 31P magnetic resonance spectroscopy for myocardial triglyceride content (MTG) and phosphocreatine-to-ATP ratio, respectively. When compared with BMI- and blood pressure–matched control subjects, subjects with diabetes were associated with concentric LV remodeling, higher MTG, impaired myocardial energetics, and impaired systolic strain indicating a subtle contractile dysfunction. Importantly, cardiac steatosis independently predicted concentric remodeling and systolic strain. Extracellular volume fraction was unchanged, indicating the absence of fibrosis. In conclusion, cardiac steatosis may contribute to concentric remodeling and contractile dysfunction of the LV in diabetes. Because cardiac steatosis is modifiable, strategies aimed at reducing MTG may be beneficial in reversing concentric remodeling and improving contractile function in the hearts of patients with diabetes.
Highly Accurate Mandarin Tone Classification In The Absence of Pitch Information

A deep neural network (DNN) classiﬁer based only on 40 mel-frequency cepstral coefﬁcients (MFCCs) achieved 29.99 % frame error rate (FER) and 16.86 % segment error rate (SER) in recognizing ﬁve tonal categories in Mandarin Chinese broadcast news. With the addition of sub-band autocorrelation change detection (SACD) pitch-class features [1], the classiﬁer scored 27.58 % FER and 15.56 % SER. These results are substantially better than the best previously reported results on broadcast news tone clas-siﬁcation [2] and are also better than a human listener achieved in categorizing test stimuli created by amplitude-and frequency-modulating complex tones to match the extracted F 0 and amplitude parameters [3]. The same DNN architecture scored substantially worse when trained and tested with SACD pitch-class parameters alone: 39.22 % FER and 24.89 % SER. RAPT F 0 estimates are worse yet: 44.37 % FER and 27.28 % SER. The 40 MFCC parameters do not encode F 0 in any obvious way and attempts to predict SACD or other pitch features from them work badly. These surprising results raise difﬁcult questions for theories of Chinese tone.
Flexible Turn-Taking for Spoken Dialogue Systems

Most of the research on spoken dialogue systems so far has focused either on higher levels of dialogue or on speech understanding. In contrast, the lowlevel interactional aspects of conversation such as turn-taking have been essentially ignored, leading builders of practical systems to resort to simple pause detection-based methods to handle turn-taking. In a preliminary study based on the Let’s Go bus information system, I found that such methods lead to interaction failures and potentially to complete dialogue breakdowns for a significant proportion of the dialogues with real-world users. In addition, a comparison of conversational rhythm in successful dialogues showed that even when speech recognition is not a major obstacle to communication, systems perform very differently and much less efficiently than human speakers. To address these issues, I propose an approach that relies on two innovations over current dialogue systems. First, it features a new event-driven system architecture that allows real-time processing of conversation, which I implemented in the Olympus/RavenClaw spoken dialogue framework. In addition to the dialogue manager and the traditional understanding and generation modules, a new module, the interaction manager, is in charge of dynamically monitoring and managing low-level interaction phenomena. The second component of the proposed approach is the turn-taking model used by the interaction manager. Inspired by mobile robotics and autonomous agent research, the model is composed of a set of sensors that provide information about the world, a set of actions that the system can take, and an action selection mechanism. Although I will explore different such mechanisms, Reinforcement Learning appears to be an appropriate framework for learning turn-taking behavior. The last expected contribution of this thesis is in the form of an evaluation framework for turn-taking in spoken dialogue systems. This important aspect of the proposed work will include a study of various local and global metrics of turn-taking and dialogue, along with the design and validation of composite metrics. All the theoretical findings and models proposed in this thesis will be grounded and validated in real world applications including Let’s Go and other RavenClaw-based dialogue systems.
Ion Channel Expression in the Developing Enteric Nervous System

The enteric nervous system arises from neural crest-derived cells (ENCCs) that migrate caudally along the embryonic gut. The expression of ion channels by ENCCs in embryonic mice was investigated using a PCR-based array, RT-PCR and immunohistochemistry. Many ion channels, including chloride, calcium, potassium and sodium channels were already expressed by ENCCs at E11.5. There was an increase in the expression of numerous ion channel genes between E11.5 and E14.5, which coincides with ENCC migration and the first extension of neurites by enteric neurons. Previous studies have shown that a variety of ion channels regulates neurite extension and migration of many cell types. Pharmacological inhibition of a range of chloride or calcium channels had no effect on ENCC migration in cultured explants or neuritogenesis in vitro. The non-selective potassium channel inhibitors, TEA and 4-AP, retarded ENCC migration and neuritogenesis, but only at concentrations that also resulted in cell death. In summary, a large range of ion channels is expressed while ENCCs are colonizing the gut, but we found no evidence that ENCC migration or neuritogenesis requires chloride, calcium or potassium channel activity. Many of the ion channels are likely to be involved in the development of electrical excitability of enteric neurons.
Deletion of Genes Encoding Arginase Improves Use of “Heavy” Isotope-Labeled Arginine for Mass Spectrometry in Fission Yeast

The use of “heavy” isotope-labeled arginine for stable isotope labeling by amino acids in cell culture (SILAC) mass spectrometry in the fission yeast Schizosaccharomyces pombe is hindered by the fact that under normal conditions, arginine is extensively catabolized in vivo, resulting in the appearance of “heavy”-isotope label in several other amino acids, most notably proline, but also glutamate, glutamine and lysine. This “arginine conversion problem” significantly impairs quantification of mass spectra. Previously, we developed a method to prevent arginine conversion in fission yeast SILAC, based on deletion of genes involved in arginine catabolism. Here we show that although this method is indeed successful when 13C6-arginine (Arg-6) is used for labeling, it is less successful when 13C6 15N4-arginine (Arg-10), a theoretically preferable label, is used. In particular, we find that with this method, “heavy”-isotope label derived from Arg-10 is observed in amino acids other than arginine, indicating metabolic conversion of Arg-10. Arg-10 conversion, which severely complicates both MS and MS/MS analysis, is further confirmed by the presence of 13C5 15N2-arginine (Arg-7) in arginine-containing peptides from Arg-10-labeled cells. We describe how all of the problems associated with the use of Arg-10 can be overcome by a simple modification of our original method. We show that simultaneous deletion of the fission yeast arginase genes car1+ and aru1+ prevents virtually all of the arginine conversion that would otherwise result from the use of Arg-10. This solution should enable a wider use of heavy isotope-labeled amino acids in fission yeast SILAC.
Analyzing Attack Trees using Generalized Stochastic Petri Nets

In recent years, attack trees have been developed to describe processes by which malicious users attempt to exploit or break computer software and/or networks. Attack trees are a way of decomposing, visualizing, and determining the cost or likeliness of attacks. Similarly, Petri nets (PNs) are graphical representations of a system or process used for modeling, formal analysis, and design verification. PNs are easy to build and simulate using a myriad of available tools. There are a number of subclasses of PNs, including colored, timed, stochastic, etc. This paper focuses on the use of generalized stochastic PNs (GSPNs) to model and analyze attack trees with the ultimate goal of automating the analysis using simulation tools. The results of this simulation and analysis can be used to further refine the attack tree or to develop countermeasures
Effect of Thermal Processing and Maceration on the Antioxidant Activity of White Beans

Phenolic compounds, which naturally occur in beans, are known to have antioxidant activity, which may be partially lost during the processing of this legume. This study evaluated the effect of thermal processing and maceration on the phenolic acid and flavonoids profile and content and on the antioxidant activity of white beans. According to the results obtained from the 2,2-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) method, there were no significant differences among treatment groups analysed. When was using 1,1-diphenyl-2-pycrylhydrazyl method (DPPH), beans cooked without maceration present the higher antioxidant activity, and raw beans the lower. The phenolic acids found in greater amounts were gallic acid and chlorogenic acid. Kaempferol was only detected in the soaked and cooked samples; catechin and kaempferol-3-rutinoside were found in the highest concentrations. Quercetin and kaempferol-3-glucoside were not affected by the cooking process, either with or without maceration. In general, the heat treatment increased the antioxidant activity.