Miracle-dz/UniFAR-FTUs huggingface dataset:
The regulation of the homeostasis and regeneration of peripheral nerve is distinct from the CNS and independent of a stem cell population

ABSTRACT Peripheral nerves are highly regenerative, in contrast to the poor regenerative capabilities of the central nervous system (CNS). Here, we show that adult peripheral nerve is a more quiescent tissue than the CNS, yet all cell types within a peripheral nerve proliferate efficiently following injury. Moreover, whereas oligodendrocytes are produced throughout life from a precursor pool, we find that the corresponding cell of the peripheral nervous system, the myelinating Schwann cell (mSC), does not turn over in the adult. However, following injury, all mSCs can dedifferentiate to the proliferating progenitor-like Schwann cells (SCs) that orchestrate the regenerative response. Lineage analysis shows that these newly migratory, progenitor-like cells redifferentiate to form new tissue at the injury site and maintain their lineage, but can switch to become a non-myelinating SC. In contrast, increased plasticity is observed during tumourigenesis. These findings show that peripheral nerves have a distinct mechanism for maintaining homeostasis and can regenerate without the need for an additional stem cell population. This article has an associated ‘The people behind the papers’ interview. Highlighted Article: Lineage analysis and long-term labelling studies show that peripheral nerve regeneration is underpinned by the proliferative plasticity of mature cells rather than the activation of a stem cell population.
An exploration into the efficacy of public warning signs: A zoo case study

Unauthorised feeding and touching of the animals by visitors to zoos and wildlife parks pose serious threats to the health of both animals and visitors alike. We tested the efficacy of four different “do not feed” signs designed to prevent zoo visitors from feeding a group of meerkats. Signs consisted of one of two different written messages and imagery of either a pair of watching human eyes, or meerkat pawprints as a control. Covert observation of visitor behaviour in the presence and absence of the signs was analysed. Visitors were significantly less likely to feed the meerkats when signs were present, than when they were absent. The effect of the signs was specific to the targeted behaviour in that feeding was reduced, but attempts to touch the meerkats increased with the presence of the signs. We did not find that the presence of watching eyes or the different wording on the signs affected the likelihood of visitors feeding the meerkats. We also examined factors that influenced the likelihood of visitors attending to the signs. We found that children were more likely to attend to signs than adults which has important implications for the design of such signs. Together our findings show that signs are effective in reducing the unwanted behaviours they target but may also result in displacement of these negative behaviours and that children are more likely to attend to these signs than adults.
The Effect of Manufacturing Agglomeration on Haze Pollution in China

Based on panel data on 285 Chinese cities from 2003 to 2012, we use a dynamic spatial panel model to empirically analyze the effect of manufacturing agglomeration on haze pollution. The results show that when economic development levels, population, technological levels, industrial structure, transportation, foreign direct investment, and greening levels are stable, manufacturing agglomeration significantly aggravates haze pollution. However, region-specific analysis reveals that the effects of manufacturing agglomeration on inter-regional haze pollution depends on the region: the effect of manufacturing agglomeration on haze pollution is the largest in the Western region, followed by the Central region, and is the least in the Eastern region. Based on the above conclusions, we put forward several specific suggestions, such as giving full play to the technology and knowledge spillover effects of manufacturing agglomeration, guiding manufacturing agglomerations in a scientific and rational way, accelerating the transformation and upgrading of manufacturing industries in agglomeration regions.
Post traumatic stress symptoms in parents of children with cancer: A mediation model

Abstract Objective: Caregivers of pediatric cancer patients are at risk for posttraumatic stress symptoms (PTSS). Previous literature has identified caregiver illness uncertainty as a predictor of PTSS, yet little is known about the mechanism by which illness uncertainty may affect PTSS. Rumination, or perseverations about the cause and consequences of an event, has been related to posttraumtic stress disorder in other populations. However, limited research of this relationship exists for pediatric cancer caregivers. Further, no studies have evaluated rumination in relation to illness uncertainty. The current study examined rumination in relation to illness uncertainty and PTSS in caregivers with children actively receiving treatment for cancer. It was hypothesized that rumination would be related to illness uncertainty and would mediate the relationship between illness uncertainty and PTSS. Methods: Caregivers (N = 59) completed the Parent Perception of Uncertainty Scale, Ruminative Responses Scale, and the Impact of Event Scale-Revised. Results: illness uncertainty was identified as a significant predictor of rumination (B = 0.148, p = .015), and rumination was a significant predictor of PTSS (B = 1.83, p < .001). Biased-corrected bootstrap regression analysis revealed that rumination mediated the relationship between illness uncertainty and PTSS (R2 = 0.53, p < .001). Conclusions: Rumination was identified as a mediator between the relationship of illness uncertainty and PTSS. These findings underscore the importance of rumination in caregivers of children with cancer, as a potential construct for identifying caregivers at risk of PTSS, and as a possible mechanism for targeted intervention.
Proteomic Analysis of Baboon Cerebral Artery Reveals Potential Pathways of Damage by Prenatal Alcohol Exposure*

Proteome analysis was performed to determine whether fetal alcohol exposure during mid-pregnancy would evoke changes in protein profile of fetal cerebral artery in baboons. We detected that levels of 238 proteins differed significantly between control and alcohol-exposed fetuses. Proteins of metabolic pathways represented one of the major targets of alcohol. The differences were detected near term, long after alcohol exposure took place. Our findings point at novel targets of alcohol within developing brain vessels. Graphical Abstract Highlights We studied mid-pregnancy alcohol exposure and baboon fetal cerebral artery. 238 proteins differed between control and alcohol-exposed fetuses near-term. Proteins of metabolic pathways represented one of the major targets of alcohol. Alcohol effect on the development of fetal brain vessels is persistent. Alcohol is one of the most widely misused substances in the world. Alcohol consumption by pregnant women often results in an array of fetal developmental abnormalities, but the damage to the fetus by alcohol remains poorly understood. The limited knowledge regarding the molecular targets of alcohol in the developing fetus constitutes one of the major obstacles in developing effective pharmacological interventions that could prevent fetal damage after alcohol consumption by pregnant women. The fetal cerebral artery is emerging as an important mediator of fetal cerebral damage by maternal alcohol drinking. In the present work, we conduct proteomics analysis of cerebral (basilar) artery lysates of near-term fetal baboons to search for protein targets of fetal alcohol exposure. Our study demonstrates that 3 episodes of binge alcohol exposure during the second trimester-equivalent of human pregnancy are sufficient to render profound changes in fetal cerebral artery proteome. These changes persisted, as they were detected in near-term fetuses. In particular, the relative abundance of 238 proteins differed significantly between control and alcohol-exposed fetuses. Enrichment analysis pointed at the group of metabolic activity proteins as a major class targeted by alcohol. Western blotting confirmed upregulation of the aldehyde dehydrogenase 6 family member A1 (ALDH6A1) in cerebral artery lysates from alcohol-exposed fetuses. This upregulation translated to greater ALDH activity of cerebral artery lysate of near-term fetuses following prenatal alcohol exposure when compared with controls.
Proceedings of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with ACM Conference on Recommender Systems (RecSys 2016), Boston, MA, USA, September 16, 2016

Privacy issues are an undying obstacle to the adoption of recommender systems, because recommender systems critically rely on their users to disclose information about themselves. While there exist several technical solutions to reduce the exposure of such personal information (e.g. client-side personalization, homomorphic encryption, k-anonymity), the concept of privacy is an inherently human attitude associated with the collection, distribution and use of disclosed data, and this disclosure itself is also a human behavior. This talk discusses one particular human-centric solution to reduce users’ privacy concerns in using recommender systems: User-Tailored Privacy. User-Tailored Privacy is an approach to privacy that measures users’ privacy-related characteristics and behaviors, uses this as input to model their privacy preferences, and then provides them with adaptive privacy decision support. In effect, it takes the decision-supporting functionality of recommender systems, and applies it to users’ privacy decisions. The talk will revolve around the implementation and evaluation of User-Tailored Privacy in an interactive, demographics-based recommender system that gives healthy living advice. This system personalizes its recommendations based on the answer to a broad array of questions that range from innocuous (e.g. age, gender) to very sensitive (e.g. religion, sexual activity, household income, and savings). The system asks these questions in a sequential order, and recommendations are adapted to the user’s answers on the fly. User-Tailored Privacy is implemented in the form of adaptive request orders that prioritize questions that are likely to benefit the recommender, but skips questions that the user is likely to deem too sensitive to answer. I will present the outcomes of a user experiment with 672 participants that tested several means of ordering the recommendations.
Fast Separation of Direct and Global Components of a Scene Using High Frequency Illumination

We present fast methods for separating the direct and global illumination components of a scene measured by a camera and illuminated by a light source. In theory, the separation can be done with just two images taken with a high frequency binary illumination pattern and its complement. In practice, a larger number of images are used to overcome the optical and resolution limitations of the camera and the source. The approach does not require the material properties of objects and media in the scene to be known. However, we require that the illumination frequency is high enough to adequately sample the global components received by scene points. We present separation results for scenes that include complex interreflections, subsurface scattering and volumetric scattering. Several variants of the separation approach are also described. When a sinusoidal illumination pattern is used with different phase shifts, the separation can be done using just three images. When the computed images are of lower resolution than the source and the camera, smoothness constraints are used to perform the separation using a single image. Finally, in the case of a static scene that is lit by a simple point source, such as the sun, a moving occluder and a video camera can be used to do the separation. We also show several simple examples of how novel images of a scene can be computed from the separation results.
FloWaveNet : A Generative Flow for Raw Audio

Most modern text-to-speech architectures use a WaveNet vocoder for synthesizing high-fidelity waveform audio, but there have been limitations, such as high inference time, in its practical application due to its ancestral sampling scheme. The recently suggested Parallel WaveNet and ClariNet have achieved real-time audio synthesis capability by incorporating inverse autoregressive flow for parallel sampling. However, these approaches require a two-stage training pipeline with a well-trained teacher network and can only produce natural sound by using probability distillation along with auxiliary loss terms. We propose FloWaveNet, a flow-based generative model for raw audio synthesis. FloWaveNet requires only a single-stage training procedure and a single maximum likelihood loss, without any additional auxiliary terms, and it is inherently parallel due to the characteristics of generative flow. The model can efficiently sample raw audio in real-time, with clarity comparable to previous two-stage parallel models. The code and samples for all models, including our FloWaveNet, are publicly available.
Frequent value locality and value-centric data cache design

By studying the behavior of programs in the SPECint95 suite we observed that six out of eight programs exhibit a new kind of value locality, the frequent value locality, according to which a few values appear very frequently in memory locations and are therefore involved in a large fraction of memory accesses. In these six programs ten distinct values occupy over 50% of all memory locations and on an average account for nearly 50% of all memory accesses during program execution. This observation holds for smaller blocks of consecutive memory locations and the set of frequent values remains quite stable over the execution of the program.In the six benchmarks with frequent value locality, on an average 50% of all cache misses occur during the reading or writing of the ten most frequently accessed values. We propose a new data cache structure, the frequent value cache (FVC), which employs a value-centric approach to caching data locations for exploiting the frequent value locality phenomenon. FVC is a small direct-mapped cache which is dedicated to holding only frequently occurring values. The value-centric nature of FVC enables us to store data in a compressed form where the compression is achieved by encoding the frequent values using a few bits. Moreover this simple compression scheme preserves the random access to data values in a cache line.Our experiments demonstrate that by augmenting a direct mapped cache (DMC) with a direct mapped FVC of size no more than 3 Kbytes we can obtain reductions in miss rates ranging from 1% to 68%. In fact we observed that higher reductions in miss rates can be achieved by augmenting a DMC with a small FVC as opposed to doubling the size of DMC for the 124.m88ksim and 134.perl benchmarks.
A cognitive approach for effective coding and transmission of 3D video

Future multimedia applications will rely on the transmission of 3D video contents within heterogeneous fruition scenarios, and as a matter of fact, the reliable delivery of 3D video signals proves to be a crucial issue in such communications. To this purpose, multimedia communication experts have been designing cross-layer strategies to improve the quality of the perceived 3D experience. This article presents a new cross-layer strategy, called Cognitive Source Coding (CSC), that defines a new 3D video system able to identify the different elements of the 3D scene and choose the most appropriate coding strategy.
APE: Archetypal-Prototypal Embeddings for Audio Classification

Archetypal analysis deals with representing data points using archetypes, which capture the boundary of the data. Prototypal analysis deals with representing data points using prototypes, which capture the average behaviour of the data. Utilising these two complementary representations, we propose a simple, fixed-length representation for audio signals. We employ a well-studied method for determining archetypes, and utilise Gaussian mixture modelling to represent prototypes. Archetypes and prototypes are concatenated and utilised within a dictionary learning framework. Time-frequency representations of audio signals are projected on these dictionaries, under simplex constraints, to obtain the proposed archetypal prototypal embedding or APE. Experimental results on the tasks of bioacoustic classification and acoustic scene classification demonstrate the effectiveness of the APE representation for audio classification.
Thermal-Aware Synthesis of 5G Base Station Antenna Arrays: An Overview and a Sparsity-Based Approach

Heat removal capabilities and radiation performances of several sparse antenna array topologies are studied for cooling enhancement in 5G millimeter-wave base station antennas. Both electromagnetic (EM) and thermal aspects are jointly considered for the first time in array layout optimization, and a novel connection between layout sparsity and thermal management is presented. Two types of active electronically scanned arrays (AESAs), based on the traditional and planar approaches, are examined. Thermal management in AESAs is discussed, with a focus on cooling challenges at millimeter waves. Being relatively low cost and low profile while supporting flexible beamforming, passively cooled planar AESAs with fanless CPU coolers are proposed, for the first time, to be used in 5G base stations. Additional cooling for such arrays is achieved by increasing the inter-element distances in the layout. Linear irregular arrays, spiral arrays, thinned arrays, circular ring arrays, and heat sink antenna arrays are revisited with a critical discussion on their EM and thermal performance. The results are compared with regular and square layouts that are used as benchmarks throughout this paper.
Microfluidic-Based 3D Engineered Microvascular Networks and Their Applications in Vascularized Microtumor Models

The microvasculature plays a critical role in human physiology and is closely associated to various human diseases. By combining advanced microfluidic-based techniques, the engineered 3D microvascular network model provides a precise and reproducible platform to study the microvasculature in vitro, which is an essential and primary component to engineer organ-on-chips and achieve greater biological relevance. In this review, we discuss current strategies to engineer microvessels in vitro, which can be broadly classified into endothelial cell lining-based methods, vasculogenesis and angiogenesis-based methods, and hybrid methods. By closely simulating relevant factors found in vivo such as biomechanical, biochemical, and biological microenvironment, it is possible to create more accurate organ-specific models, including both healthy and pathological vascularized microtissue with their respective vascular barrier properties. We further discuss the integration of tumor cells/spheroids into the engineered microvascular to model the vascularized microtumor tissue, and their potential application in the study of cancer metastasis and anti-cancer drug screening. Finally, we conclude with our commentaries on current progress and future perspective of on-chip vascularization techniques for fundamental and clinical/translational research.
Ultrafast optogenetic stimulation of the auditory pathway by targeting‐optimized Chronos

Optogenetic tools, providing non‐invasive control over selected cells, have the potential to revolutionize sensory prostheses for humans. Optogenetic stimulation of spiral ganglion neurons (SGNs) in the ear provides a future alternative to electrical stimulation used in cochlear implants. However, most channelrhodopsins do not support the high temporal fidelity pertinent to auditory coding because they require milliseconds to close after light‐off. Here, we biophysically characterized the fast channelrhodopsin Chronos and revealed a deactivation time constant of less than a millisecond at body temperature. In order to enhance neural expression, we improved its trafficking to the plasma membrane (Chronos‐ES/TS). Following efficient transduction of SGNs using early postnatal injection of the adeno‐associated virus AAV‐PHP.B into the mouse cochlea, fiber‐based optical stimulation elicited optical auditory brainstem responses (oABR) with minimal latencies of 1 ms, thresholds of 5 μJ and 100 μs per pulse, and sizable amplitudes even at 1,000 Hz of stimulation. Recordings from single SGNs demonstrated good temporal precision of light‐evoked spiking. In conclusion, efficient virus‐mediated expression of targeting‐optimized Chronos‐ES/TS achieves ultrafast optogenetic control of neurons.
Ensuring Memory Consistency in Heterogeneous Systems Based on Access Mode Declarations

Running a program on disjoint memory spaces requires to address memory consistency issues and to perform transfers so that the program always accesses the right data. Several approaches exist to ensure the consistency of the memory accessed, we are interested here in the verification of a declarative approach where each component of a computation is annotated with an access mode declaring which part of the memory is read or written by the component. The programming framework uses the component annotations to guarantee the validity of the memory accesses. This is the mechanism used in VectorPU, a C++ library for programming CPU-GPU heterogeneous systems and this article proves the correctness of the software cache-coherence mechanism used in the library. Beyond the scope of VectorPU, this article can be considered as a simple and effective formalisation of memory consistency mechanisms based on the explicit declaration of the effect of each component on each memory space.
A Survey of Person Name Disambiguation on the Web

Person name disambiguation on the Web (PNDW) consists of grouping the Web pages retrieved by a search engine when a person’s name is queried according to the individuals they refer to. This problem is of interest to the research community because Internet users often search for information about people on search engines, and also because people’s names are a very ambiguous type of named entity. In addition, the Web domain presents several challenges for natural language processing and information retrieval methods. In this paper, we classify PNDW systems according to their main characteristics: 1) features used to identify different individuals with the same name; 2) mathematical models used to represent the search results; 3) clustering algorithms used to group the Web pages; 4) methods used to address the impact of Web pages from social networking sites; and 5) methods used to deal with the multilingual nature of the Web. Also, we present the data sets most widely used to evaluate PNDW systems. Finally, we analyze the results obtained by the best PNDW systems in the literature.
Sheffield Submissions for the WMT18 Quality Estimation Shared Task

In this paper we present the University of Sheffield submissions for the WMT18 Quality Estimation shared task. We discuss our submissions to all four sub-tasks, where ours is the only team to participate in all language pairs and variations (37 combinations). Our systems show competitive results and outperform the baseline in nearly all cases.