Miracle-dz/UniFAR-FTUs huggingface dataset:
Synergies Between Intrinsic and Synaptic Plasticity Mechanisms

We propose a model of intrinsic plasticity for a continuous activation model neuron based on information theory. We then show how intrinsic and synaptic plasticity mechanisms interact and allow the neuron to discover heavy-tailed directions in the input. We also demonstrate that intrinsic plasticity may be an alternative explanation for the sliding threshold postulated in the BCM theory of synaptic plasticity. We present a theoretical analysis of the interaction of intrinsic plasticity with different Hebbian learning rules for the case of clustered inputs. Finally, we perform experiments on the bars problem, a popular nonlinear independent component analysis problem.
Robot-mediated mixed gesture imitation skill training for young children with ASD

Autism Spectrum Disorder (ASD) impacts 1 in 68 children in the U.S. with tremendous consequent cost in terms of care and treatment. Evidence suggests that early intervention is critical for optimal treatment results. Robots have been shown to have great potential to attract attention of children with ASD and can facilitate early interventions on core deficits. In this paper, we propose a robotic platform that mediates imitation skill training for young children with ASD. Imitation skills are considered to be one of the most important skill deficits in children with ASD, which has a profound impact on social communication. While a few previous works have provided methods for single gesture imitation training, the current paper extends the training to incorporate mixed gestures consisting of multiple single gestures during intervention. A preliminary user study showed that the proposed robotic system was able to stimulate mixed gesture imitation in young children with ASD with promising gesture recognition accuracy.
Detecting Violence in Video using Subclasses

This paper attacks the challenging problem of violence detection in videos. Different from existing works focusing on combining multi-modal features, we go one step further by adding and exploiting subclasses visually related to violence. We enrich the MediaEval 2015 violence dataset by manually labeling violence videos with respect to the subclasses. Such fine-grained annotations not only help understand what have impeded previous efforts on learning to fuse the multi-modal features, but also enhance the generalization ability of the learned fusion to novel test data. The new subclass based solution, with AP of 0.303 and P100 of 0.55 on the MediaEval 2015 test set, outperforms the state-of-the-art. Notice that our solution does not require fine-grained annotations on the test set, so it can be directly applied on novel and fully unlabeled videos. Interestingly, our study shows that motion related features (MBH, HOG and HOF), though being essential part in previous systems, are seemingly dispensable. Data is available at http://lixirong.net/datasets/mm2016vsd
Fine‐needle aspiration cytology of salivary glands: Diagnostic pitfalls—revisited

Fine needle aspiration cytology (FNAC) of salivary gland lesions is a safe, effective diagnostic technique. Several amply illustrated reviews are available in the English literature. The reported diagnostic accuracy varies between 86% to 98%. The sensitivity ranges from 62% to 97.6% and specificity is higher from 94.3% to 100%. In this present study, we have analyzed 172 cases of salivary gland aspirates and the histopathological diagnosis was available in 45 cases. There was discordance in cytological and histopathological diagnosis in nine cases. Five cases had discrepancies in benign versus malignant diagnosis with four cases being false negative. The errors in these FNA diagnoses were due to sampling error, observational error and interpretational error. Therefore, this study illustrates high diagnostic accuracy of FNAC in salivary gland lesions and shows that FNAC offers valuable information that allows the planning of subsequent patient management. Diagn. Cytopathol. 2006;34:580–584. © 2006 Wiley‐Liss, Inc.
Loss of Photic Entrainment and Altered Free-Running Circadian Rhythms in math5−/− Mice

Mammalian free-running circadian rhythms are entrained to the external light/dark cycle by photic signaling to the suprachiasmatic nuclei via the retinohypothalamic tract (RHT). We investigated the circadian entrainment and clock properties ofmath5−/− mutant mice.math5 is a critical regulator of retinal ganglion cell development; math5−/− mice show severe optic nerve hypoplasia. By anterograde cholera toxin B tracing, we find that math5−/− mice do not develop an identifiable RHT pathway. This appears to be attributable to agenesis or dysgenesis of the majority of RHT-projecting retinal ganglion cells. math5−/− mice display free-running circadian rhythms with a period ∼1 hr longer than B6/129 controls (24.43 ± 0.10 vs 23.62 ± 0.19 hr;p < 0.00001). The free-running period of heterozygote mice is indistinguishable from that of controls.math5−/− mice show no entrainment to light/dark cycles, whereas heterozygote mice show normal entrainment to both 12 hr light/dark cycles and to a 1 hr skeletal photoperiod.math5−/− mice show reduced ability to entrain their rhythms to the nonphotic time cue of restricted running wheel access but demonstrate both free-running behavior and entrained anticipation of wheel unlocking in these conditions, suggesting the presence of a second diurnal oscillatory system inmath5−/− animals. These results demonstrate that retinal ganglion cell input is not necessary for the development of a free-running circadian timekeeping system in the suprachiasmatic nucleus but is important for both photic entrainment and determination of the free-running period.
The molecular understanding of cancer: from the unspeakable illness to a curable disease

The beginning of our understanding of the molecular basis of cancer and the discovery in the 1980s of cancer associated genes, oncogenes, and tumour suppressor genes has led to cancer becoming a treatable condition rather than an unspeakable disease. In 1971, the then USA President, Richard Nixon, declared ‘war against cancer’ with a far too optimistic perspective of winning in just a few years. This tactic failed because our knowledge of the disease was still very limited and even its origin—viral or due to exposure to external agents—was still highly debated. A better understanding of the cause(s) of the origin of cancer led to its definition as a genetic disease at the somatic level and heralded a new era for molecular diagnosis and the development of more mechanistic evidence-based, targeted cancer therapies. However, the initial positive results were soon overshadowed by a major limitation of targeted agents, namely resistance mechanisms, which still represent an obstacle for the full eradication of the disease. More recently, effective therapeutic approaches have been developed in the field of ‘immunotherapy’. The combination of novel therapies will hopefully result in effective cancer growth control and make the disease ‘chronic’. The launch of the ‘Moonshot Cancer Program’ by President Barack Obama aims to significantly reduce cancer deaths in the next decade—let us see.
Distributed Charging Control in Broadband Wireless Power Transfer Networks

Wireless power transfer (WPT) technology provides a cost-effective solution to achieve a sustainable energy supply in wireless networks, where WPT-enabled energy nodes (ENs) can charge wireless devices (WDs) remotely without interruption to the use. However, in a heterogeneous WPT network with distributed ENs and WDs, some WDs may quickly deplete their batteries due to the lack of timely wireless power supply by the ENs, thus resulting in short network operating lifetime. In this paper, we exploit frequency diversity in a broadband WPT network and study the distributed charging control by ENs to maximize network lifetime. In particular, we propose a practical voting-based distributed charging control framework, where each WD simply estimates the broadband channel, casts its votes for some strong sub-channels, and sends to the ENs along with its battery state information, based on which the ENs independently allocate their transmit power over the sub-channels without the need of centralized control. Under this framework, we aim to design lifetime-maximizing power allocation and efficient voting-based feedback methods. Toward this end, we first derive the general expression of the expected lifetime of a WPT network and draw the general design principles for lifetime-maximizing charging control. Based on the analysis, we then propose a distributed charging control protocol with voting-based feedback, where the power allocated to sub-channels at each EN is a function of the weighted sum vote received from all WDs. Besides, the number of votes cast by a WD and the weight of each vote are related to its current battery state. Simulation results show that the proposed distributed charging control protocol could significantly increase the network lifetime under stringent transmit power constraint in a broadband WPT network. Reciprocally, it also consumes lower transmit power to achieve nearly perpetual network operation.
Kernel Conditional Random Fields: Representation, Clique Selection, and Semi-Supervised Learning

there are long range interactions between regions of the protein chain that are not necessarily consecutive in the primary sequence. Our experimental results indicate that KCRFs and semi-supervised kernels have the potential to lead to progress on this problem, where the state of the art has been based on heuristic "sliding window" methods. However, our results also suggest that the improvement due to semi-supervised learning is hindered by the lack of a good similarity measure with which to construct the graph. The construction of an effective graph is a challenge that may best be tackled by biologists and machine learning researchers working together.
Gastrointestinal Stromal Tumors : challenges in diagnosis and treatment

Background: Gastrointestinal stromal tumors (GIST) are considered the most common mesenchymal neoplasms of the digestive system. They originate from the interstitial cells of Cajal and one of their major characteristics is the over expression of KIT protein Tyrosine Kinase,and they have both diagnostic and therapeutic dilemma.The aim of this study is to present the challenges encountered in the diagnosis and treatment of GIST cases in our facility, Saudi German hospital Riyadh Saudia Arabia during the past 10 years and compare the results obtained with that of other oncology centers.Patients & Methods: This study is a retrospective study of cases with GIST that were diagnosed and treated in our center during the past 10 years. These studies include clinical characteristics,target therapy, imaging techniques, histopathology, immunohistochemistry, surgical techniques and prognosis of such cases. Results: thirty two patients were diagnosed as having GIST (24 males/8 females)with a mean age 62 years (31-83 years). Diagnosis was made preoperatively in 22 patients (69%) and intraoperatively with histopatholgical confirmation in ten patients (31%). The site of the tumor was detected in the stomach in twelve cases (37.5%),two in duodenum (6.25%), ten in small intestine (31.25%), two in mesentery (6.25%), four in colon (12.5%) and two rectal GIST (6.25%). The main presentation of the disease was anemia, GIT bleeding and abdominal mass. Twenty eight patients were considered resectable and they were operated upon (87.5%) and in four patients (12.5%) neadjuvant therapy was started with favorable response in two cases and poor response in the other two with advanced GIST. All patients received Imatinib as adjuvant therapy. Mean follow up period was 33 months (4-54 months). Conclusion: GIST is a challenging malignant tumor that requires a multidisciplinary approach in a highly specialized facility seeking the best management and prognosis.
The impact of intermediate-term alcohol abstinence on memory retrieval and suppression

Background: The nature of episodic memory deficit in intermediate-term abstinence from alcohol in alcohol dependence (AD) is not yet clarified. Deficits in inhibitory control are commonly reported in substance use disorders. However, much less is known about cognitive control suppressing interference from memory. The Think/No-think (TNT) paradigm is a well established method to investigate inhibition of associative memory retrieval. Methods: Thirty-six unmedicated patients with AD and 36 healthy controls (HCs) performed the TNT task. Thirty image–word pairs were trained up to a predefined accuracy level. Cued recall was examined in three conditions: Think (T) for items instructed to-be-remembered, No-think (NT) assessing the ability to suppress retrieval and Baseline (B) for general relational memory. Premorbid IQ, clinical variables and impulsivity measures were quantified. Results: AD patients had a significantly increased demand for training. Baseline memory abilities and effect of practice on retrieval were not markedly different between the groups. We found a significant main effect of group (HC vs. AD) × condition (B, T, and NT) and a significant difference in mean NT–B scores for the two groups. Discussion: AD and HC groups did not differ essentially in their baseline memory abilities. Also, the instruction to focus on retrieval improved episodic memory performance in both groups. Crucially, control participants were able to suppress relational words in the NT condition supporting the critical effect of cognitive control processes over inhibition of retrieval. In contrast to this, the ability of AD patients to suppress retrieval was found to be impaired.
Consistent environmental modeling by use of occupancy grid maps, digital road maps, and multi-object tracking

Occupancy grid mapping, street topology estimation, and object tracking are basic modules of vehicular environmental perception systems. For the sake of expandability and adaptability, this contribution proposes a hierarchical modular environmental perception architecture (HMEP). It limits the interactivity between individual basic modules. In a combination module, the consistency between occupancy grid cells and object tracks is evaluated. This allows to distinguish between static and dynamic parts of the environment in a postprocessing step. Efficient algorithms for implementation of the combination module are provided and an evaluation based on simulation and real data is presented.
Improving the performance of log-structured file systems with adaptive block rearrangement

Log-Structured File System (LFS) is famous for its optimization for write performance. Because of its append-only nature, garbage collection is needed to reclaim the space occupied by the obsolete data. The cleaning overhead could significantly decrease the performance of file system. However, traditional cleaning policies do not consider the storage location where the valid data in the cleaned segments should be placed and rewritten to. In this paper, we propose a new method called R-LFS to dynamically reorganize data in disk to approximate the organ pipe heuristic that can place data in disk optimally. Basically, frequently accessed data are dynamically clustered and placed toward the center of disk, whereas less accessed data are moved and placed toward the edges of disk to reduce disk seek time. The essence of R-LFS is that R-LFS takes advantage of the chance of data reorganization during segment cleaning and data writing, no extra overhead is incurred for this data reorganization. Besides, because hot data and cold data are in nature separately clustered under R-LFS, cleaning overhead can be substantially reduced as well. Performance evaluation under both trace-driven simulation and practical implementation on NetBSD/LFS shows that R-LFS can effectively improve the performance of LFS.
Accounting for Biases in Black-Scholes

Prices of currency options commonly differ from the Black-Scholes formula along two dimensions: implied volatilities vary by strike price (volatility smiles) and maturity (implied volatility of at-the-money options increases, on average, with maturity). We account for both using Gram-Charlier expansions to approximate the conditional distribution of the logarithm of the price of the underlying security. In this setting, volatility is approximately a quadratic function of moneyness, a result we use to infer skewness and kurtosis from volatility smiles. Evidence suggests that both kurtosis in currency prices and biases in Black-Scholes option prices decline with maturity.
Unternehmungsnetzwerke : Konstitution und Strukturation

Perspektive und Gegenstand Systemische Rationalisierung: der industriesoziologische Netzwerkansatz Netzwerk und Struktur: der strukturelle Netzwerkansatz Strukturation von Unternehmungsnetzwerken: der strukturationstheoretische Netzwerkansatz Reflexive Vernetzung: die aktuelle Form moderner Vernetzung.
Iterative modulo scheduling: an algorithm for software pipelining loops

Modulo scheduling is a framework within which a wide variety of algorithms and heuristics may be defined for software pipelining innermost loops. This paper presents a practical algorithm, iterative modulo scheduling, that is capable of dealing with realistic machine models. This paper also characterizes the algorithm in terms of the quality of the generated schedules as well the computational expense incurred.
A Framework for Relationship Pattern Languages

A relationship pattern is an abstraction of a recurring need when establishing relationships among information elements in specific contexts. By developing or leveraging a relationship pattern, modelers can solve a class of problems once and describe many relationship types at once. We have developed a framework for specifying relationship patterns and pattern languages (sets of patterns) in both modeling-language-independent and modeling-language-specific ways. We describe this framework both informally and formally. We provide examples of some commonly observed relationship patterns and show how to use them in ER with the help of a relationship pattern language called Exemplar. We also provide notes on using relationship patterns in UML.
Journal of Graph Algorithms and Applications on the Approximability of Comparing Genomes with Duplicates 20 Angibaud Et Al. Approximability of Comparing Genomes with Duplicates

A central problem in comparative genomics consists in computing a (dis-)similarity measure between two genomes, e.g. in order to construct a phylogenetic tree. A large number of such measures has been proposed in the recent past: number of reversals, number of breakpoints, number of common or conserved intervals etc. In their initial definitions, all these measures suppose that genomes contain no duplicates. However, we now know that genes can be duplicated within the same genome. One possible approach to overcome this difficulty is to establish a one-to-one correspondence (i.e. a matching) between genes of both genomes, where the correspondence is chosen in order to optimize the studied measure. Then, after a gene relabeling according to this matching and a deletion of the unmatched signed genes, two genomes without duplicates are obtained and the measure can be computed. In this paper, we are interested in three measures (number of break-points, number of common intervals and number of conserved intervals) and three models of matching (exemplar, intermediate and maximum matching models). We prove that, for each model and each measure M, computing a matching between two genomes that optimizes M is APX–hard. We show that this result remains true even for two genomes G1 and G2 such that G1 contains no duplicates and no gene of G2 appears more than twice. Therefore, our results extend those of [7, 10, 13]. Besides, in order to evaluate the possible existence of approximation algorithms concerning the number of breakpoints, we also study the complexity of the following decision problem: is there an exemplarization (resp. an intermediate matching, a maximum matching) that induces no break-point ? In particular, we extend a result of [13] by proving the problem to be NP–complete in the exemplar model for a new class of instances, we note that the problems are equivalent in the intermediate and the ex-emplar models and we show that the problem is in P in the maximum matching model. Finally, we focus on a fourth measure, closely related to the number of breakpoints: the number of adjacencies, for which we give several constant ratio approximation algorithms in the maximum matching model, in the case where genomes contain the same number of duplications of each gene.
Optimizing Graph Algorithms on Pregel-like Systems

We study the problem of implementing graph algorithms efficiently on Pregel-like systems, which can be surprisingly challenging. Standard graph algorithms in this setting can incur unnecessary inefficiencies such as slow convergence or high communication or computation cost, typically due to structural properties of the input graphs such as large diameters or skew in component sizes. We describe several optimization techniques to address these inefficiencies. Our most general technique is based on the idea of performing some serial computation on a tiny fraction of the input graph, complementing Pregel's vertex-centric parallelism. We base our study on thorough implementations of several fundamental graph algorithms, some of which have, to the best of our knowledge, not been implemented on Pregel-like systems before. The algorithms and optimizations we describe are fully implemented in our open-source Pregel implementation. We present detailed experiments showing that our optimization techniques improve runtime significantly on a variety of very large graph datasets.
Cross‐sectional and longitudinal multimodal structural imaging in prodromal Huntington's disease

Diffusivity in white‐matter tracts is abnormal throughout the brain in cross‐sectional studies of prodromal Huntington's disease. To date, longitudinal changes have not been observed. The present study investigated cross‐sectional and longitudinal changes in white‐matter diffusivity in relationship to the phase of prodromal Huntington's progression, and compared them with changes in brain volumes and clinical variables that track disease progression.
Cytotoxic Effect of Alcohol on Liver Cells and Fibroblasts in Vitro

Cultures of liver cells (Chang) and of fibroblasts (3T6) were exposed to media containing a range of concentrations of ethanol. At the end of a standard period of time the number of viable cells was determined. As the concentration of ethanol increased over 0.25 per cent v/v liver cell survival decreased progressively. Fibroblast survival decreased progressively at ethanol concentrations over 0.50 per cent v/v. This indicates that ethanol is more toxic to liver cells than to fibroblasts. Certain alcoholic beverages, particularly brandy, were found to be more toxic than pure ethanol.
CSN 5 Isopeptidase Activity Links COP 9 Signalosome Activation to Breast Cancer Progression

CSN5 has been implicated as a candidate oncogene in human breast cancers by genetic linkage with activation of the poorprognosis, wound response gene expression signature. CSN5 is a subunit of the eight-protein COP9 signalosome, a signaling complex with multiple biochemical activities; the mechanism of CSN5 action in cancer development remains poorly understood. Here, we show that CSN5 isopeptidase activity is essential for breast epithelial transformation and progression. Amplification of CSN5 is required for transformation of primary human breast epithelial cells by defined oncogenes. The transforming effects of CSN5 require CSN subunits for assembly of the full COP9 signalosome and the isopeptidase activity of CSN5, which potentiates the transcriptional activity of MYC. Transgenic inhibition of CSN5 isopeptidase activity blocks breast cancer progression evoked by MYC and RAS in vivo . These results highlight CSN5 isopeptidase activity in breast cancer progression, suggesting it as a therapeutic target in aggressive human breast cancers. [Cancer Res 2008; 68(2):506–15]