Miracle-dz/UniFAR-FTUs huggingface dataset:
Collateral Projections from the Lateral Parabrachial Nucleus to the Central Amygdaloid Nucleus and the Ventral Tegmental Area in the Rat

Lateral parabrachial nucleus (LPB) is a critical region in the integration and transmission of peripheral nociceptive information. The parabrachio‐amygdaloid (P‐Amy) pathway and parabrachio‐ventral tegmental area (P‐VTA) pathway is thought to be significant in regulation of pain‐related negative emotions. In present study, retrograde tract tracers Fluoro‐gold (FG) and tetramethylrhodramine‐dextran (TMR) were stereotaxically injected into the right central amygdaloid nucleus (CeA) and right VTA, respectively. Then, part of these rats were performed with the spare nerve injury (SNI) in the controlateral side of FG and TMR injection. Afterwards, double‐ or triple‐immunofluorescent histochemistry was used to examine FG/TMR double‐ and FG/TMR/FOS or FG/TMR/CGRP triple‐labeled neurons in the LPB. The results showed that all of FG, TMR single‐ and FG/TMR double‐labeled neurons were distributed in the LPB bilaterally with an ipsilateral predominance. The proportion of FG/TMR double‐labeled neurons to the total number of FG‐ and TMR‐labeled neurons was 10.78% and 13.07%, respectively. Nearly all of the FG/TMR double‐labeled neurons (92.67%) showed calcitonin gene‐related peptide (CGRP) immunopositive. On the other hand, in the SNI rats, about 89.49% and 77.87% of FG‐ and TMR‐labeled neurons were FG/FOS‐ and TMR/FOS‐positive neurons; about 93.33% of the FG/TMR double‐labeled neurons were FOS‐LI. Our results suggest that the part of CGRP immunopositive neurons in the LPB send projection fibers to both the CeA and VTA by the way of axon collaterals, which are activated by the nociceptive stimulation in the SNI condition, and may play an important role in the transmission of peripheral nociceptive information. Anat Rec, 302:1178–1186, 2019. © 2018 The Authors. The Anatomical Record published by Wiley Periodicals, Inc. on behalf of American Association of Anatomists.
Exchange Protein Directly Activated by cAMP Modulates Ebola Virus Uptake into Vascular Endothelial Cells

Members of the family Filoviridae, including Ebola virus (EBOV) and Marburg virus (MARV), cause severe hemorrhagic fever in humans and nonhuman primates. Given their high lethality, a comprehensive understanding of filoviral pathogenesis is urgently needed. In the present studies, we revealed that the exchange protein directly activated by cAMP 1 (EPAC1) gene deletion protects vasculature in ex vivo explants from EBOV infection. Importantly, pharmacological inhibition of EPAC1 using EPAC-specific inhibitors (ESIs) mimicked the EPAC1 knockout phenotype in the ex vivo model. ESI treatment dramatically decreased EBOV infectivity in both ex vivo vasculature and in vitro vascular endothelial cells (ECs). Furthermore, postexposure protection of ECs against EBOV infection was conferred using ESIs. Protective efficacy of ESIs in ECs was observed also in MARV infection. Additional studies using a vesicular stomatitis virus pseudotype that expresses EBOV glycoprotein (EGP-VSV) confirmed that ESIs reduced infection in ECs. Ultrastructural studies suggested that ESIs blocked EGP-VSV internalization via inhibition of macropinocytosis. The inactivation of EPAC1 affects the early stage of viral entry after viral binding to the cell surface, but before early endosome formation, in a phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-dependent manner. Our study delineated a new critical role of EPAC1 during EBOV uptake into ECs.
Camera Orientation Estimation in Natural Scenes Using Semantic Cues

Camera orientation estimation in natural scenes has recently been approached by several methods, which rely mainly on matching a single modality – edges or horizon lines with 3D digital elevation models. In contrast to previous works, our new image to model matching scheme is based on a fusion of multiple modalities and is designed to be naturally extensible with different cues. In this paper, we use semantic segments and edges. To our knowledge, we are the first to consider using semantic segments jointly with edges for alignment with digital elevation model. We show that high-level features, such as semantic segments, complement the low-level edge information and together help to estimate the camera orientation more robustly compared to methods relying solely on edges or horizon lines. In a series of experiments, we show that segment boundaries tend to be imprecise and important information for matching is encoded in the segment area and a coarse shape. Intuitively, semantic segments encode low frequency information as opposed to edges, which encode high frequencies. Our experiments exhibit that semantic segments and edges are complementary, improving camera orientation estimation reliability when used together. We demonstrate that our method combining semantic and edge features is able to reach state-of-the-art performance on three datasets.
In vitro evaluation of the antitumor effect of bismuth lipophilic nanoparticles (BisBAL NPs) on breast cancer cells

Aim The objective of this study was to evaluate the antitumor activity of lipophilic bismuth nanoparticles (BisBAL NPs) on breast cancer cells. Materials and methods The effect of varying concentrations of BisBAL NPs was evaluated on human MCF-7 breast cancer cells and on MCF-10A fibrocystic mammary epitheliocytes as noncancer control cells. Cell viability was evaluated with the MTT assay, plasma membrane integrity was analyzed with the calcein AM assay, genotoxicity with the comet assay, and apoptosis with the Annexin V/7-AAD assay. Results BisBAL NPs were spherical in shape (average diameter, 28 nm) and agglomerated into dense electronic clusters. BisBAL NP induced a dose-dependent growth inhibition. Most importantly, growth inhibition was higher for MCF-7 cells than for MCF-10A cells. At 1 µM BisBAL NP, MCF-7 growth inhibition was 51%, while it was 11% for MCF-10A; at 25 µM BisBAL NP, the growth inhibition was 81% for MCF-7 and 24% for MCF-10A. With respect to mechanisms of action, a 24-hour exposure of 10 and 100 µM BisBAL NP caused loss of cell membrane integrity and fragmentation of tumor cell DNA. BisBAL NPs at 10 µM were genotoxic to and caused apoptosis of breast cancer cells. Conclusion BisBAL NP-induced growth inhibition is dose dependent, and breast cancer cells are more vulnerable than noncancer breast cells. The mechanism of action of BisBAL NPs may include loss of plasma membrane integrity and a genotoxic effect on the genomic DNA of breast cancer cells.
Learning Useful Representations Through Stacked Self-Organizing Maps

In this work we explore an original strategy for building deep networks, based on stacking layers of Self-Organizing Maps (SOM) with finite weights. We aim to show that our approach, with enough hidden variables, is capable to represents any “soft” distribution over the visible variables, where “soft” means that the distribution does not contain any probabilities of 1 or 0. The algorithm compute the model one layer at a time. The first layer receives the input observations and compute a probability of membership for each observation and each neuron. These probabilities become the input of the second layer, which compute a new set of probabilities, and so on. The number of neurons decrease in each layer after the first. The proposed algorithm is experimentally tested on artificial and real data-sets. The effect of the added hidden layers for the representation of data structure is experimentally demonstrated.
Comparison of the effects of debriefing methods on psychomotor skills, self-confidence, and satisfaction in novice nursing students: A quasi-experimental study

Oral debriefing (OD) and video-assisted debriefing (VAD) are commonly used debriefing methods, with no evidence of superiority of one to another. The present study aimed to compare the effects of OD and VAD on the development of learning outcomes in nursing students. This is a quasi-experimental study. A total of 50 first-year nursing students participated in this study. Participants in the control group participated in OD and those in the intervention group took part in VAD. Debriefing improved psychomotor skills, self-confidence, and student satisfaction in both groups. There was no statistically significant difference between OD and VAD in the study outcomes. Both OD and VAD methods have significantly positive impact on simulation outcomes and can increase preparedness of nursing students before entering the clinical settings. Given the widespread use of simulation, more studies are needed to evaluate different methods of debriefing to optimize the usefulness of simulation-based learning.
Exponential Family Restricted Boltzmann Machines and Annealed Importance Sampling

In this paper, we investigate restricted Boltzmann machines (RBMs) from the exponential family perspective, en-abling the visible units to follow any suitable distributions from the exponential family. We derive a unified view to compute the free energy function for exponential family RBMs (exp-RBMs). Based on that, annealed important sampling (AIS) is generalized to the entire exponential family, allowing for estimating the log-partition function and log-likelihood. Our experiments on a document processing task demonstrate that the generalized free energy functions and AIS estimation perform well in helping capture useful knowledge from the data; the estimated log-partition functions are stable. The appropriate instances of exp-RBMs can generate novel and meaningful samples and can be applied to classification tasks.
THU Face Database for Real-Time Automatic Video Scoring Model

With the rapid development of electronic techniques, the Internet video services have already covered billions of users and become the mainstream media and major marketing channel in recent years. Along with the increasing importance of video, peoples interest in video have becoming far more important and influential. Still, there is no real-time video evaluation system reflect people’s interest Meter. This paper aims at build a facial video database providing standardized test video sequences, which is also an open database for any research related to facial expression and interest meter. Furthermore, Backpropagation (BP) neural network and Self organizing Feature Map (SOFM) neural network are used to establish the video scoring model. Our database contains over 1000 videos from 82 subjects, each frame of which is processed into a recognized facial expression. Simulation results show that the accuracy of our automatic video method can reach 85.6% based on our facial video database. Free examples can be downloaded at http://www.facedbv2. com.
A Big-Bang Big-Crunch Type-2 Fuzzy Logic System for Generating Interpretable Models in Workforce Optimization

Efficient utilization of resources (engineers) is critical to optimal service delivery in service-based industries, such as water, electricity or telecom companies. One of the ways in which efficiency can be improved is by optimizing the geographic area in which the engineers operate. This process is known as Work Area (WA) optimization and it is a sub-domain of workforce optimization.In previous attempts to tackle the work area optimization problem, various machine learning algorithms have been proposed to optimize the work areas. However, they don’t provide much insight into when and which WAs must be optimized. This is an important question, as optimizing a WA which is already optimum can lead to a loss in efficiency as the engineers can take time to adjust to the new WA.This paper presents a Type-2 Fuzzy Logic System (FLS) which has been optimized by the Big-Bang Big-Crunch approach to allow maximizing the model interpretability and allow good prediction for the future performance of WAs. We can then use these predictions to determine which WAs must be optimized.We compare the proposed type-2 FLS model against a type-1 counterpart, a stacked autoencoder deep neural network and single hidden layer neural network.The results show that the proposed type-2 FLS provides a highly interpretable model which predicts the future performance of WAs with a reasonable error rate. In addition, it also provides the necessary insight into which parameters of the WA determine the future performance. This allows answering the question of when and which WAs must be optimized.
Timing the Origin of Cryptococcus gattii sensu stricto, Southeastern United States

We conducted molecular clock analysis of whole-genome sequences from a set of autochthonous isolates of Cryptococcus gattii sensu stricto from the southeastern United States. Our analysis indicates that C. gattii arrived in the southeastern United States approximately 9,000–19,000 years ago, long before its arrival in the Pacific Northwest.
Exploring Textual and Speech information in Dialogue Act Classification with Speaker Domain Adaptation

In spite of the recent success of Dialogue Act (DA) classification, the majority of prior works focus on text-based classification with oracle transcriptions, i.e. human transcriptions, instead of Automatic Speech Recognition (ASR)’s transcriptions. In spoken dialog systems, however, the agent would only have access to noisy ASR transcriptions, which may further suffer performance degradation due to domain shift. In this paper, we explore the effectiveness of using both acoustic and textual signals, either oracle or ASR transcriptions, and investigate speaker domain adaptation for DA classification. Our multimodal model proves to be superior to the unimodal models, particularly when the oracle transcriptions are not available. We also propose an effective method for speaker domain adaptation, which achieves competitive results.
Roll Back Mechanism in Multi Version Locking in Distributed Database

In the distributed database multiple sites are interconnected to provide a resource sharing environment. The different sites at each site coexist in order to access the resources. Concurrency control methods are adopted to control the simultaneous execution of multiple transactions. In this paper we investigate multi version locking protocol in distributed environment. Multi version database has the potential to significantly increase the amount of concurrency in transaction processing as they can avoid read write conflict by completing the read requests with older versions of data while the write operation is in progress. In this paper we have presented a detailed review of multi version locking algorithm. We look into the extent to which they endow with the increase in the level of concurrency. We have given an improvement on the algorithm proposed by wang to prevent the rollback situation. We have not imposed any restriction on the waiting of the transaction to prevent rollback as discussed by wang rather we have suggested that check point based mechanism and proper re-sequencing of the transaction can be done to prevent the rollback of the transaction in multi version locking.
Development of transplant immunosuppressive agents – considerations in the use of animal models

ABSTRACT Introduction: The development of all immunosuppressant agents to date has involved the experimental use of large and small animal models. Over the last half-century, immunosuppressive drugs have extended the lives of transplant patients worldwide. However, the use of animal models in the development of these drugs is not perfect, and this has brought to light a number of issues including idiosyncratic reactions that are found in animal models but not in humans. The 2006 highly publicized case of the ‘elephant man’ TGN 1412 drug trial highlights the importance of being cogent of the limitations of animal models. Areas covered: This review covers the utility and limitations of the use of animal models for the development of immunosuppressant agents. This includes both large and small animal models, particularly rodent models in the transplant setting. Expert opinion: The use of animal models represents a critical stage in the development of immunosuppressive drugs. Limitations include physiological differences to humans; this is especially true of immunologically naïve lab rodents with small memory cell populations. Toxic drug levels may differ widely between species. Animal models are also costly and raise ethical concerns. However, there is currently no way to recreate the complex environment of the human immune system purely in vitro.
Doubly Label Consistent Autoencoder: Accounting User and Item Metadata in Recommender Systems

Recent studies have experimentally shown that autoencoder based formulations for collaborative filtering can outperform other approaches. However, prior studies in this area, were either based on only ratings information; and at most accounted for either user or item metadata but not both. The metadata was appended to the ratings and just passed on as inputs. This is the most that can be done in the standard neural network based autoencoder formulation. However, collaborative filtering is a highly under-determined problem, therefore being able to utilize maximum information will naturally boost results. Previous autoencoder based formulations either had to leave out user metadata or item metadata. This is the first work, that proposes to modify the autoencoder to account for both user and item metadata. Results using explicit metadata (e.g. age, gender, occupation for users and genre for movies) and implicit metadata (neighborhood information) on our proposed formulation improves upon the state-of -the-art techniques considerably.
Heme metabolism as a therapeutic target against protozoan parasites

Abstract Neglected tropical diseases caused by protozoan parasites affect the life of millions of people worldwide, causing mortality, morbidity and high economic and social burden. The search for new drug targets and therapeutic strategies to fight these pathogens are necessary, since many current drugs have limited effects, cause severe side effects and their use has resulted in pathogen resistance. Heme (iron protoporphyrin IX) is a ubiquitous molecule important in many biological processes, including the homeostasis, growth and development of human pathogens such as trypanosomatids (Trypanosoma cruzi, Trypanosoma brucei and Leishmania spp.) and Plasmodium spp. In this review, several chemotherapy approaches and strategies are discussed that target heme transport, catabolism, crystallization and hemeproteins.
A new species of Hypoprepia from the mountains of central Arizona (Lepidoptera, Erebidae, Arctiinae, Lithosiini)

Abstract A new firefly-mimicking lichen moth of the genus Hypoprepia, H.lampyroides Palting & Ferguson, sp. n. , is described from the mountains of east-central Arizona and the Sierra Madre Occidental of Mexico. Hypoprepia Hübner, 1831 is a North American genus of lithosiine tiger moths, previously consisting of five species: H.fucosa Hübner, 1831 and H.miniata (Kirby, 1837), both of eastern and central North America; H.cadaverosa Strecker, 1878 from the Rocky Mountains into New Mexico and west Texas; H.inculta H. Edwards, 1882, a widespread western USA species and H.muelleri Dyar, 1907 from the vicinity of Mexico City. The latter is herein synonymized under H.inculta (= H.muellerisyn. n.), resulting in the total number of taxa in the genus unchanged at five.
Managing the cervical spine in multiple myeloma patients

Discuss the relevant literature on surgical and nonsurgical treatments for multiple myeloma (MM) and their complementary effects on overall treatment. Existing surgical algorithms designed for neoplasia of the spine may not suit the management of spinal myeloma. Less than a fifth of metastatic, including myelomatous lesions, occur in the cervical spine but have a poorer prognosis and surgery in this area carries a higher morbidity. With the advances of chemotherapy, early access to radiotherapy, early orthosis management, and high definition imaging, including CT and MRI, surgical indications in MM have changed. Medical decompression (or oncolysis), including in the presence of neurological deficit and orthotic stabilization, are proving viable nonsurgical options to manage MM. A key to decision making is the assessment and monitoring of biomechanical spinal stability as part of a multidisciplinary approach.
On the Impact of Semantic Transparency on Understanding and Reviewing Social Goal Models

Context: i* is one of the most influential languages in the Requirements Engineering research community. Perhaps due to its complexity and low adoption in industry, it became a natural candidate for studies aiming at improving its concrete syntax and the stakeholders' ability to correctly interpret i* models. Objectives: We evaluate the impact of semantic transparency on understanding and reviewing i* models, in the presence of a language key. Methods: We performed a quasi-experiment comparing the standard i* concrete syntax with an alternative that has an increased semantic transparency. We asked 57 novice participants to perform understanding and reviewing tasks on i* models, and measured their accuracy, speed and ease, using metrics of task success, time and effort, collected with eye-tracking and participants' feedback. Results: We found no evidence of improved accuracy or speed attributable to the alternative concrete syntax. Although participants' perceived ease was similar, they devoted significantly less visual effort to the model and the provided language key, when using the alternative concrete syntax. Conclusions: The context provided by the model and language key may mitigate the i* symbol recognition deficit reported in previous works. However, the alternative concrete syntax required a significantly lower visual effort.
Adversarials -1: Defending by Attacking

Although neural networks are very successful in the domain of image processing, they are vulnerable to adversarial images-slightly perturbed images, which a human cannot distin- guish from the original image. However, for the neural network, the perturbation leads to a different classification of the image.A lot of research was done on adversarial attacks, and on defenses against those attacks. In this paper, we propose a new defense by applying adversarial attacks to adversarial images. The new type of adversarial images is called $\mathrm {a}\mathrm {d}\mathrm {v}^{-1}$ and by observing the properties of the different transitions-from original to adversarial images, and from adversarial to $\mathrm {a}\mathrm {d}\mathrm {v}^{-1}$ images-we are able to detect adversarial images with a high accuracy, even for unknown attacks. Furthermore we are able to identify the attack, used to create the adversarial image in the first place. Regarding classification, depending on the used attack, our approach reaches correct classification accuracies, comparable to other defenses.