Miracle-dz/UniFAR-FTUs huggingface dataset:
Immunotherapy in mucosal melanoma: a case report and review of the literature

Background Mucosal melanoma is a rare form of melanoma presenting variably as sores or unexplained bleeding located mainly in the head and neck region, anorectal region or female genital tract. Mucosal melanoma is usually diagnosed at an advanced stage and is characterized by an aggressive behavior. Surgery represents the mainstay of treatment for early stage melanomas, but for advanced disease there have been until recently very limited treatment options. Ipilimumab, a human monoclonal antibody directed against the cytotoxic T lymphocyte antigen 4, was the first treatment modality to demonstrate survival benefit in advanced malignant melanoma. Method Description of a new case and review of the literature. Results We present here a patient with mucosal melanoma with aggressive biological behavior and documented late response to ipilimumab. Conclusions Ipilimumab represents an effective treatment option in selected patients with mucosal melanoma.
Eccentric training in Achilles tendinopathy: is it harmful to tendon microcirculation?

Background: Eccentric training has been shown to reduce pain and gain function in patients with chronic Achilles tendinopathy. However, currently no data are available regarding any potential adverse effects of an eccentric training intervention on Achilles tendon microcirculation. Methods: 59 patients (49 (12) years; body mass index 27 (5); 49 mid-portion, 10 chronic insertional tendinopathy) with 64 symptomatic (54 mid-portion, 10 insertional) Achilles tendons were prospectively enrolled. Baseline tendon microcirculation at four distinct tendon positions from the insertion to the proximal mid-portion area was assessed using a laser Doppler system for capillary blood flow, tissue oxygen saturation and postcapillary venous filling pressure. A 12-week daily painful home-based eccentric training regimen was initiated (3×15 repetitions per tendon and day). Results: Achilles tendon capillary blood flow was significantly reduced at the insertion (by 35%, p = 0.008) and the distal mid-portion area (by 45%, p = 0.015) at 2 mm and by 22% (p = 0.007) and 13% (p = 0.122) at 8 mm tissue depths, respectively. Achilles tendon oxygen saturation was not decreased after the 12-week eccentric training regimen throughout the insertion to the proximal mid-portion area (insertion 72 (13) vs 73 (10), proximal mid-portion 63 (13) vs 62 (11), both NS). Achilles tendon postcapillary venous filling pressures were significantly reduced at the insertion (51 (16) vs 41 (19), p = 0.001) and the distal mid-portion (36 (13) vs 32 (12), p = 0.037) at 2 mm and at the insertion at 8 mm (63 (19) vs 51 (13), p = 0.0001). Pain was reduced from 5.4 (2.1) to 3.6 (2.4; p = 0.001) in the mid-portion and from 6 (2.5) to 3.2 (2.7; p = 0.002) in the insertional tendinopathy group. No Achilles tendon rupture or any interruption during the eccentric training was noted among the 59 patients. Conclusion: Daily eccentric training for Achilles tendinopathy is a safe and easy measure, with beneficial effects on the microcirculatory tendon levels without any evident adverse effects in both mid-portion and insertional Achilles tendinopathy.
Multi-Input RNAi-Based Logic Circuit for Identification of Specific Cancer Cells

A synthetic biomolecular circuit identifies abnormal cell states by the integration of multiple endogenous microRNA inputs. Engineered biological systems that integrate multi-input sensing, sophisticated information processing, and precisely regulated actuation in living cells could be useful in a variety of applications. For example, anticancer therapies could be engineered to detect and respond to complex cellular conditions in individual cells with high specificity. Here, we show a scalable transcriptional/posttranscriptional synthetic regulatory circuit—a cell-type “classifier”—that senses expression levels of a customizable set of endogenous microRNAs and triggers a cellular response only if the expression levels match a predetermined profile of interest. We demonstrate that a HeLa cancer cell classifier selectively identifies HeLa cells and triggers apoptosis without affecting non-HeLa cell types. This approach also provides a general platform for programmed responses to other complex cell states.
Scaling the Aspect Ratio of Nanoscale Closely Packed Silicon Vias by MacEtch: Kinetics of Carrier Generation and Mass Transport

Metal‐assisted chemical etching (MacEtch) has shown tremendous success as an anisotropic wet etching method to produce ultrahigh aspect ratio semiconductor nanowire arrays, where a metal mesh pattern serves as the catalyst. However, producing vertical via arrays using MacEtch, which requires a pattern of discrete metal disks as the catalyst, has often been challenging because of the detouring of individual catalyst disks off the vertical path while descending, especially at submicron scales. Here, the realization of ordered, vertical, and high aspect ratio silicon via arrays by MacEtch is reported, with diameters scaled from 900 all the way down to sub‐100 nm. Systematic variation of the diameter and pitch of the metal catalyst pattern and the etching solution composition allows the extraction of a physical model that, for the first time, clearly reveals the roles of the two fundamental kinetic mechanisms in MacEtch, carrier generation and mass transport. Ordered submicron diameter silicon via arrays with record aspect ratio are produced, which can directly impact the through‐silicon‐via technology, high density storage, photonic crystal membrane, and other related applications.
Analysis of passive charge balancing for safe current-mode neural stimulation

Charge balancing has been often considered as one of the most critical requirement for neural stimulation circuits. Over the years several solutions have been proposed to precisely balance the charge transferred to the tissue during anodic and cathodic phases. Elaborate dynamic current sources/sinks with improved matching, and feedback loops have been proposed with a penalty on circuit complexity, area or power consumption. Here we review the dominant assumptions in safe stimulation protocols, and derive mathematical models to determine the effectiveness of passive charge balancing in a typical application scenario.
Mindfulness and Health Behaviour : Examining the roles of attention regulation and decentering

This chapter examines how mindfulness interventions affect health behaviour through attention regulation and decentering. Specifically, mindfulness may be effective to the degree that attention training increases one’s ability to accurately detect temptation cues, to direct attention in ways that support self-control, and to monitor one’s behaviour. In addition, the decentering component of mindfulness allows one to view the reward simulations that lead to desire as mere mental events, making tempting stimuli less inherently attractive, and thus preventing impulses and cravings. This analysis is illustrated with research on eating, smoking, and drinking, and may contribute to a more detailed understanding of mindfulness mechanisms and support their most effective application. You created this PDF from an application that is not licensed to print to novaPDF printer (http://www.novapdf.com)
Electroencephalography Source Connectivity: Aiming for High Resolution of Brain Networks in Time and Space

The human brain is a large-scale network the function of which depends on dynamic interactions between spatially distributed regions. In the rapidly evolving field of network neuroscience, two unresolved challenges hold the promise of potential breakthroughs. First, functional brain networks should be identified using noninvasive and easy-to-use neuroimaging techniques. Second, the time-space resolution of these techniques should be good enough to assess the dynamics of the identified networks. Emerging evidence suggests that the electroencephalography (EEG) source-connectivity method may offer solutions to both issues, provided that scalp EEG signals are appropriately processed. Therefore, this technique's performance strongly depends on signal processing that involves various methods, such as preprocessing approaches, inverse solutions, statistical couplings between signals, and network science.
Signaling Pathways and Cellular Mechanisms Regulating Mossy Fiber Sprouting in the Development of Epilepsy

The sprouting of hippocampal dentate granule cell axons, termed mossy fibers, into the dentate inner molecular layer is one of the most consistent findings in tissue from patients with mesial temporal lobe epilepsy. Decades of research in animal models have revealed that mossy fiber sprouting creates de novo recurrent excitatory connections in the hippocampus, fueling speculation that the pathology may drive temporal lobe epileptogenesis. Conducting definitive experiments to test this hypothesis, however, has been challenging due to the difficulty of dissociating this sprouting from the many other changes occurring during epileptogenesis. The field has been largely driven, therefore, by correlative data. Recently, the development of powerful transgenic mouse technologies and the discovery of novel drug targets has provided new tools to assess the role of mossy fiber sprouting in epilepsy. We can now selectively manipulate hippocampal granule cells in rodent epilepsy models, providing new insights into the granule cell subpopulations that participate in mossy fiber sprouting. The cellular pathways regulating this sprouting are also coming to light, providing new targets for pharmacological intervention. Surprisingly, many investigators have found that blocking mossy fiber sprouting has no effect on seizure occurrence, while seizure frequency can be reduced by treatments that have no effect on this sprouting. These results raise new questions about the role of mossy fiber sprouting in epilepsy. Here, we will review these findings with particular regard to the contributions of new granule cells to mossy fiber sprouting and the regulation of this sprouting by the mTOR signaling pathway.
A Domain Partition-Based Trust Model for Unreliable Clouds

Cloud computing has become an important scientific computing and commercial application paradigm. Many computing resources and data exist in clouds, and face various trust issues. Malicious providers may provide poor services to users, while malicious users may give good providers unfaithful trust evaluations. Hence, it is important to detect these malicious nodes that can be providers and users. Current studies on trust management do not sufficiently address the issues of minimizing trust management overhead and maximizing the ability to detect malicious nodes. This paper proposes a new trust model and related algorithm to decrease trust management overhead and improve malicious node detection ability based on domain partition. Partitioning nodes into domains is helpful for decreasing the overhead of trust management in terms of trust storage and computation. Domain and cross-domain sliding-windows are proposed and utilized to store the most recent trust values. Then, an algorithm is designed to compute domain and cross-domain trust values for nodes, and a filter procedure is adopted to remove malicious trust evaluations and malicious nodes from a domain. Simulation results show that the proposed model and algorithm outperform two updated methods, i.e., one based on fuzzy mathematics and another based on authenticated trust and reputation calculation and management, in terms of speed and accuracy of trust computation and malicious node detection.
Towards Deeper Generative Architectures for GANs using Dense connections

In this paper, we present the result of adopting skip connections and dense layers, previously used in image classification tasks, in the Fisher GAN implementation. We have experimented with different numbers of layers and inserting these connections in different sections of the network. Our findings suggests that networks implemented with the connections produce better images than the baseline, and the number of connections added has only slight effect on the result.
Cross-media Multi-level Alignment with Relation Attention Network

With the rapid growth of multimedia data, such as image and text, it is a highly challenging problem to effectively correlate and retrieve the data of different media types. Naturally, when correlating an image with textual description, people focus on not only the alignment between discriminative image regions and key words, but also the relations lying in the visual and textual context. Relation understanding is essential for cross-media correlation learning, which is ignored by prior cross-media retrieval works. To address the above issue, we propose Cross-media Relation Attention Network (CRAN) with multi-level alignment. First, we propose visual-language relation attention model to explore both fine-grained patches and their relations of different media types. We aim to not only exploit cross-media fine-grained local information, but also capture the intrinsic relation information, which can provide complementary hints for correlation learning. Second, we propose cross-media multi-level alignment to explore global, local and relation alignments across different media types, which can mutually boost to learn more precise cross-media correlation. We conduct experiments on 2 cross-media datasets, and compare with 10 state-of-the-art methods to verify the effectiveness of proposed approach.
How the Community Became More Than the Curriculum: Participant Experiences In #RHIZO14

The paper outlines participant experiences in a rhizomatic MOOC, #rhizo14. We begin with a brief outline of the structure of the course before presenting our five participant narratives to illustrate our beliefs that, for us, the #rhizo14 community became more than the curriculum. We then discuss some of the common themes in our narratives: the role that the Facebook group held in fostering our feelings of community, how the diversity of voices in the course promoted learning and engagement of group members, the formation of sub-communities with diverse interests, and the flexibility of participation that the course encouraged. While acknowledging the partiality of our narratives, we conclude that the emphasis in #rhizo14 on contribution and creation rather than content mastery encouraged a sense of "eventedness" (shared experience), which allowed our community to thrive.
Precise Box Score: Extract More Information from Datasets to Improve the Performance of Face Detection

For the training of face detection network based on R-CNN framework, anchors are assigned to be positive samples if intersection-over-unions (IoUs) with ground-truth are higher than the first threshold(such as 0.7); and to be negative samples if their IoUs are lower than the second threshold(such as 0.3). And the face detection model is trained by the above labels. However, anchors with IoU between first threshold and second threshold are not used. We propose a novel training strategy, Precise Box Score(PBS), to train object detection models. The proposed training strategy uses the anchors with IoUs between the first and second threshold, which can consistently improve the performance of face detection. Our proposed training strategy extracts more information from datasets, making better utilization of existing datasets. What's more, we also introduce a simple but effective model compression method(SEMCM), which can boost the performance of face detectors further. Experimental results show that the performance of face detection network can consistently be improved based on our proposed scheme.
Treatment of sialorrhea with glycopyrrolate: A double-blind, dose-ranging study.

OBJECTIVE To determine the safety and efficacy of glycopyrrolate in the treatment of developmentally disabled children with sialorrhea. DESIGN Placebo-controlled, double-blind, crossover dose-ranging study. SETTING Outpatient facilities in 2 pediatric hospitals. PATIENTS Thirty-nine children with both developmental disabilities and excessive and bothersome sialorrhea. MAIN OUTCOME MEASURES Parent and investigator evaluation of change in sialorrhea and adverse effects. RESULTS Glycopyrrolate in doses of 0.10 mg/kg per dose is effective at controlling sialorrhea. Even at low doses, 20% of children may exhibit adverse effects severe enough to require discontinuation. CONCLUSIONS Glycopyrrolate is effective in the control of excessive sialorrhea in children with developmental disabilities. Approximately 20% of children given glycopyrrolate may experience substantial adverse effects, enough to require discontinuation of medication. Arch Pediatr Adolesc Med. 2000;154:1214-1218.
Our use, misuse, and abandonment of a concept: Whither habitat?

Summary The foundational concept of habitat lies at the very root of the entire science of ecology, but inaccurate use of the term compromises scientific rigor and communication among scientists and nonscientists. In 1997, Hall, Krausman & Morrison showed that ‘habitat’ was used correctly in only 55% of articles. We ask whether use of the term has been more accurate since their plea for standardization and whether use varies across the broader range of journals and taxa in the contemporary literature (1998–2012). We searched contemporary literature for ‘habitat’ and habitat‐related terms, ranking usage as either correct or incorrect, following a simplified version of Hall et al.'s definitions. We used generalized linear models to compare use of the term in contemporary literature with the papers reviewed by Hall et al. and to test the effects of taxa, journal impact in the contemporary articles and effects due to authors that cited Hall et al. Use of the term ‘habitat’ has not improved; it was still only used correctly about 55% of the time in the contemporary data. Proportionately more correct uses occurred in articles that focused on animals compared to ones that included plants, and papers that cited Hall et al. did use the term correctly more often. However, journal impact had no effect. Some habitat terms are more likely to be misused than others, notably ‘habitat type’, usually used to refer to vegetation type, and ‘suitable habitat’ or ‘unsuitable habitat’, which are either redundant or nonsensical by definition. Inaccurate and inconsistent use of the term can lead to (1) misinterpretation of scientific findings; (2) inefficient use of conservation resources; (3) ineffective identification and prioritization of protected areas; (4) limited comparability among studies; and (5) miscommunication of science‐based findings. Correct usage would improve communication with scientists and nonscientists, thereby benefiting conservation efforts, and ecology as a science.
Defending Malicious Script Attacks Using Machine Learning Classifiers

The web application has become a primary target for cyber criminals by injecting malware especially JavaScript to perform malicious activities for impersonation. Thus, it becomes an imperative to detect such malicious code in real time before any malicious activity is performed. This study proposes an efficient method of detecting previously unknown malicious java scripts using an interceptor at the client side by classifying the key features of the malicious code. Feature subset was obtained by using wrapper method for dimensionality reduction. Supervised machine learning classifiers were used on the dataset for achieving high accuracy. Experimental results show that our method can efficiently classify malicious code from benign code with promising results.
Exploring Relationships Between Random Physical Events and Mass Human Attention: Asking for Whom the Bell Tolls

Exploratory study of the outputs of continuously operating truly random number generators (RNG) located around the world indicated that the largest daily change in variance in the year 2001 occurred on an unprecedented day in United States history, September 11, 2001. Calculation of correlations between all possible pairs of RNG outputs on a per-day basis showed that the largest daily average correlation also took place on September 11. Comparison of daily RNG correlations for 250 days that made headline news in 2001 according to a commercial news service vs. similar measures for 115 non- eventful days showed a larger average RNG correlation on days with major news events (p 5 0.011). More generally, the correlation between an objective metric of daily news vs. the daily average RNG correlation was significantly positive (p 5 0.001). Potential environmental artifacts were examined and found to be implausible explanations for these results. One interpretation of these findings is that mind-matter interaction effects previously observed only in focused laboratory studies may be detectable outside the laboratory, potentially at a global scale.
Effect of Gestational and Lactational Exposure to DEHP, DINP, and DEP on Intestinal Morphology, Disaccharidases, and Alkaline Phosphatase in Rats during Postnatal Development

Abstract Introduction The diesters of 1,2-benzenedicarboxylic acid (phthalic acid), commonly known as phthalates, are used primarily as plasticizers of polyvinyl chloride and as additives in consumer and personal care products. Objective This study was designed to evaluate the impact of in utero and postnatal exposure to diisononyl phthalate (DINP), diethylhexyl phthalate (DEHP), and diethyl phthalate (DEP) on gut maturation in a Wistar rat model. Materials and Methods Pregnant females were gavaged from day 8 of gestation through postnatal day (pd) 30 with 0 (vehicle control), DEHP (380 mg/kg/d), DINP (380 mg/kg/d), or DEP (800 mg/kg/d) dissolved in corn oil. Intestinal samples have been collected at 0, 7, 14, 21, and 30 pd for histological and biochemical analysis. The mitotic index has been evaluated based on the expression of Ki-67 antigen. Results All tested phthalate treatments have significantly decreased the body as well as the organ's weight (p < 0.001). DINP exposure resulted in severe villous atrophy, while DEHP treated group was characterized by lymphoepithelial lesions. In addition, a significant decrease of the Ki-67 proliferation index was observed in the youngest rats (0 and 7 days) upon the various treatments (p < 0.0001), whereas at day 30, an increased numbers of Ki-67 positive cells were observed in DEHP and DEP but bot DINP group. Lactase and sucrase activities were inhibited by DEP in contrast to DINP and DEHP which increased enzymes activity (p < 0.05). Conclusion Our results suggest that exposure to phthalates during gestational and lactational phases negatively impacts the development of the small intestine.