Miracle-dz/UniFAR-FTUs huggingface dataset:
Self-Organized Data-Energy-Aware Clustering and Routing for Wireless Sensor Networks

In this paper we propose a clustering and routingscheme for wireless sensor networks based on a self-organizing approach. The aim of thisapproach is for nodes to perform an integrated emergent task (data gathering and reporting to the sink) by simply following rules based on their individual local environment. Clusterhead election is also performed in a distributed manner and is based on sensorfs relative residual energy and the relative amount of information that they need to send to the sink. Hence nodes are assumed to possess variable data sizes across the network. In the scheme clusters are formed, and decide on their roles in the data gathering and routing procedure. Clusters at theedge of the network identify themselves and become in charge of initiating the routing of data, whilst intermediate clusters await data from higher clusters from the edge of the network for further aggregation and forwarding towards the sink. Simulation results show that the clustering scheme is able to reduce the total amount of energy used up by the network and efficiently routedata back to the sink.
Relay selection for MIMO two-way relay networks with spatial multiplexing

Relay selection strategies help to improve spectral and energy efficiencies, to enhance transmission robustness, or to reduce latency in cooperative networks. A novel relay selection strategy, which maximizes the overall achievable sum rate, is proposed and analyzed for multiple-input multiple-output (MIMO) amplify-and-forward two-way relay networks with spatial multiplexing. Interestingly, this strategy amounts to maximizing the minimum of the determinant of the Wishart matrices from the relays to the two user nodes. The performance of this strategy is investigated by deriving the average sum rate approximations in closed-form. Our analysis and numerical results reveal that the proposed relay selection scheme provides substantial sum rate improvements.
A recapitulative three-dimensional model of breast carcinoma requires perfusion for multi-week growth

Breast carcinomas are complex, three-dimensional tissues composed of cancer epithelial cells and stromal components, including fibroblasts and extracellular matrix. In vitro models that more faithfully recapitulate this dimensionality and stromal microenvironment should more accurately elucidate the processes driving carcinogenesis, tumor progression, and therapeutic response. Herein, novel in vitro breast carcinoma surrogates, distinguished by a relevant dimensionality and stromal microenvironment, are described and characterized. A perfusion bioreactor system was used to deliver medium to surrogates containing engineered microchannels and the effects of perfusion, medium composition, and the method of cell incorporation and density of initial cell seeding on the growth and morphology of surrogates were assessed. Perfused surrogates demonstrated significantly greater cell density and proliferation and were more histologically recapitulative of human breast carcinoma than surrogates maintained without perfusion. Although other parameters of the surrogate system, such as medium composition and cell seeding density, affected cell growth, perfusion was the most influential parameter.
Femoral pseudoaneurysms post-cardiac catheterization surgically treated: evolution and prognosis.

OBJECTIVES To analyze the postoperative complications of patients who have undergone surgical repair of femoral pseudoaneurysm after cardiac catheterization. DESIGN Prospective study. MATERIALS Cardiovascular risk factors, related to surgery and cardiac catheterization were collected prospectively in 79 patients from 2003 to 2006 in Valladolid University Hospital. The indications of surgery included necrosis of adjacent soft tissue, rapid growth, infection, bleeding, hemodynamic instability or failure of the percutaneous treatment (US-guided compression and US-guided percutaneous thrombin injection). METHODS Patient and management related predictors for 30-day outcome were analyzed. RESULTS Fifty-six patients (56/79, 71%) experienced some type of postoperative complication, the most frequent being the need for a transfusion. Infection (15/79, 19%) and dehiscence of the surgical wound (10/79, 12.7%) were the other two most common complications. The mortality related to the intervention was 3.8% (3/79). The mean hospital stay was 32.5 days (+/-28.4 days). Significant risk factors in logistic regression model were gender (P=0.023, OR=9.66), 70 years old (P=0.049, OR=0.15) and the concurrent use of anticoagulation or antiplatelet therapy after the cardiac catheterization (P=0.005, OR=0.03). CONCLUSION Patients who undergo surgical treatment of femoral pseudoaneurysm post-cardiac catheterization experience a high postoperative morbidity and hospital stay. Factors such as female gender, age over 70 years and treatment with anticoagulants or antiplatelets increase the postoperative morbidity. A seasonal influence was appreciated, with a higher frequency during the summer period.
Thymoquinone Inhibits Murine Leukemia WEHI-3 Cells In Vivo and In Vitro

Background Thymoquinone is an active ingredient isolated from Nigella sativa (Black Seed). This study aimed to evaluate the in vitro and in vivo anti-leukemic effects of thymoquinone on WEHI-3 cells. Methodology/Principal Findings The cytotoxic effect of thymoquinone was assessed using an MTT assay, while the inhibitory effect of thymoquinone on murine WEHI-3 cell growth was due to the induction of apoptosis, as evidenced by chromatin condensation dye, Hoechst 33342 and acridine orange/propidium iodide fluorescent staining. In addition, Annexin V staining for early apoptosis was performed using flowcytometric analysis. Apoptosis was found to be associated with the cell cycle arrest at the S phase. Expression of Bax, Bcl2 and HSP 70 proteins were observed by western blotting. The effects of thymoquinone on BALB/c mice injected with WEHI-3 cells were indicated by the decrease in the body, spleen and liver weights of the animal, as compared to the control. Conclusion Thymoquinone promoted natural killer cell activities. This compound showed high toxicity against WEHI-3 cell line which was confirmed by an increase of the early apoptosis, followed by up-regulation of the anti-apoptotic protein, Bcl2, and down-regulation of the apoptotic protein, Bax. On the other hand, high reduction of the spleen and liver weight, and significant histopathology study of spleen and liver confirmed that thymoquinone inhibited WEHI-3 growth in the BALB/c mice. Results from this study highlight the potential of thymoquinone to be developed as an anti-leukemic agent.
Image-Mediated Learning for Zero-Shot Cross-Lingual Document Retrieval

We propose an image-mediated learning approach for cross-lingual document retrieval where no or only a few parallel corpora are available. Using the images in image-text documents of each language as the hub, we derive a common semantic subspace bridging two languages by means of generalized canonical correlation analysis. For the purpose of evaluation, we create and release a new document dataset consisting of three types of data (English text, Japanese text, and images). Our approach substantially enhances retrieval accuracy in zero-shot and few-shot scenarios where text-to-text examples are scarce.
Probabilistic random field based method for annotated machine printed documents preprocessing

Today, the convenience of search, both on the personal computer hard disk and on the web, is essentially limited to machine-printed text documents and images because of the poor accuracy of handwriting recognizers. The proposed research will advance the state-of-the-art in realizing search of hand-annotated documents. We will primarily target machine-printed documents which have been annotated by hand by multiple writers in an office/collaborative environment. In applications where the annotations are action instructions (such as, “make 4 copies”, “remove Figure X” etc.) we can envision the proposed system serving as the front end of an OCR-based NLP module. We expect that the techniques developed in this dissertation will be also useful for retrieval of pages from material in languages for which accurate OCRs do not exist. The main research task proposed is that of segmenting handwritten text, machine printed text, noise or overlapped text, sometimes referred to as the task of ”ink separation”. Prior techniques primarily use histogram thresholding and analysis of the connectivity of strokes. These algorithms, although effective, rely on heuristic rules of spatial constraints, and are not scalable across applications. We have developed a system that is composed by three parts: the binariztion of document images (focus on hand-held devices captured documents), a boosted tree classifier to perform the initial classification which is followed by a Markov random field (MRF) based approach to re-label the initial segments based on their statistical dependencies within a neighborhood. The MRF based binarization will provide a reliable binarized document image for segmentation even with bad illumination. The boost tree will allow dividing the training data set into several small clusters and use a simple classifier to solve the initial labeling at the cluster (homogeneous) levels. The overlapped text will be further separated using a MRF based method. The isolated handwritten textual blocks will be indexed (unsupervised) based on writing instrument, style, ink color, etc. as being possible indicators of different writers. We have shown the ability to selectively remove the annotations belonging to a particular writer and allow the end user of the system to view an unmarked document even though the original document image is marked up. This feature will be accomplished by intelligent document restoration whereby the removal of overlapping strokes does not damage the underlying machine-printed text. We have performed experiments on a large document dataset and report results.
Tangible Windows

We are stuck in a world where our digital life is confined into virtual windows that clutter computer screens everywhere. Tangible Windows allow you to break out of this prison by pushing windows into the real world. Instead of interacting with your applications through virtual rectangles, you can hold them in your hands, embed them in your environment, and take them with you. Tangible Windows employ a new set of operations that allow applications to move freely between them. We have implemented a working prototype of a Tangible Windows Systems and evaluated it by comparing it with a common desktop computer in a user study. All participants commended the system and prefer it over the desktop computer to some extend. Author
The kernel proportionate NLMS algorithm

In this paper, the kernel proportionate normalized least mean square algorithm (KPNLMS) is proposed. The proportionate factors are used in order to increase the convergence speed and the tracking abilities of the kernel normalized least mean square (KNLMS) adaptive algorithm. We confirm the effectiveness of the proposed algorithm for nonlinear system identification and forward prediction using computer simulations.
3D shape retrieval using point bidirectional features

In this paper, we describe a novel 3D shape retrieval method based on new features. The features are extracted for 3D points based on a 2D attribute space which consists of two bidirectional 3D shape attributes, one of which along the shape surface direction and the other along the shape content direction perpendicular to the former. We define this features as Point Bidirectional Features (PBFs), which can reflect not only the global shape but also the local content. For simplicity, we choose the geodesic distance (GD) and the shape diameter function (SDF) to construct PBFs. Given a database of 3D shapes and a query shape, the proposed retrieval method adopts a shape similarity measurement based on 3D points matching with PBFs to decide which is the most similar shape from the database. To reduce cost of computation and feature storage, a shape simplification algorithm is integrated into this method. Additionally, a simple but effective point correspondence mechanism with K-Nearest Neighbor (KNN) assignment is designed for this retrieval method. Experimental results demonstrate the effectiveness of the proposed features and method.
The Protein Kinase A Regulatory Subunit R1A (Prkar1a) Plays Critical Roles in Peripheral Nerve Development

Signaling through cAMP has been implicated in Schwann cell (SC) proliferation and myelination, but the signaling pathway components downstream of cAMP required for SC function remain unknown. Protein kinase A (PKA) is a potential downstream effector of cAMP. Here, we induced loss of Prkar1a, the gene encoding the type 1A regulatory subunit of PKA, in SC to study its role in nerve development; loss of Prkar1a is predicted to elevate PKA activity. Conditional Prkar1a knock-out in mouse SC (Prkar1a-SCKO) resulted in a dramatic and persistent axonal sorting defect, and unexpectedly decreased SC proliferation in Prkar1a-SCKO nerves in vivo. Effects were cell autonomous as they were recapitulated in vitro in Prkar1a-SCKO SC, which showed elevated PKA activity. In the few SCs sorted into 1:1 relationships with axons in vivo, SC myelination was premature in Prkar1a-SCKO nerves, correlating with global increase in the cAMP-regulated transcription factor Oct-6 and expression of myelin basic protein. These data reveal a previously unknown role of PKA in axon sorting, an unexpected inhibitory role of PKA on SC cell proliferation in vivo and define the importance of Prkar1a in peripheral nerve development.
Stimulus affective valence reverses spatial compatibility effect

In spatial compatibility tasks, the Reaction Time to right-side stimuli is shorter for right key responses (compatible condition) than for left key responses (incompatible condition) and vice-versa for left-side stimuli. Similar results have been found when the stimulus location is not relevant for response selection, such as in the Simon task. The Simon effect is the difference between the reaction times for non-corresponding and corresponding conditions. The Simon effect and its variants may be modulated by using emotional stimuli. However, until now, no work has studied how the affective valence of a stimulus influences spatial compatibility effects along the horizontal dimension. The present study investigated this issue by using small lateralized figures of soccer team players as stimuli. In the experiment, a compatible or incompatible response was chosen according to the team shirt. In one block, for the Favorite team, the volunteers had to press the key on the same side as the stimulus hemifield but the opposite-side key for the Rival team. In the other block, a reverse code had to be used. Fourteen right-handed volunteers were tested. Mean reaction times were subjected to analysis of variance with the following variables: Preference (Favorite/Rival), Hemifield (Left/Right), and Response Key (Left/Right). A three-way interaction was found (F1,13 = 6.60, p = .023), showing that the spatial compatibility effects depended on Preference. The Favorite team player elicited the usual spatial compatibility pattern, but for the Rival team player, the reverse effect was found, with incompatible responses being faster than compatible responses. We propose that this modulation may result from approach/avoidance reactions to the Favorite and Rival teams, respectively. Moreover, we suggest as a corollary that the classic spatial compatibility task is a powerful tool for investigating approach/avoidance effects.
Scheduling, worrying, and stepping up: Working parents' strategies for providing care to middle-school children

The thirty working parents interviewed for this study offer three unique strategies for raising teenagers ages 12 to 14 years old. This study draws on the literature on care and on parents’ perceptions of their teenagers’ needs, on their own abilities to perform the necessary caring tasks, and on their appraisals of their spouses’ commitments to caring for their teenagers. Rather than produce strategies that are based on negotiations with family members, parents in this study tended to develop their own individual strategies when confronted with a set of problems in caring for young teenagers, principle among these is the contested nature of teenagers’ need for care—contested by the educational institution, by employers, by spouses and teenagers themselves. We conclude by suggesting that these parents’ strategies lead to unequal divisions of physical and emotional care that are shaped by gender, race and institutional intransigence.
Transient patterns in the assembly of vernal pool plant communities.

Community assembly theory asserts that the contemporary composition of ecological communities may depend critically on events that occur during the formation of the community; a phenomenon termed "historical contingence. " We tested key aspects of this theory using plant communities in over 200 experimentally created vernal pools at a field site in central California, USA. The experiment was initiated in 1999 with construction of vernal pool basins into which different seeding treatments were imposed to evaluate the effects of dispersal limitation, order of colonization ("priority effects"), and frequency of colonization on plant community composition. We tracked the abundance and distribution of five focal species for seven years following seeding and observed strong but transient effects of seeding, as well as order and frequency of colonization. All five species occurred with higher frequency in seeded pools vs. unseeded control pools, demonstrating dispersal limitation. Three of four species exerted strong priority effects, with much higher abundance in pools in which they were seeded first compared to pools in which they were seeded in the second year of the study, one year after other species were seeded. We tested for effects of frequency of colonization using one species, the endangered Lasthenia conjugens, and observed much higher abundance in frequently vs. infrequently seeded pools for the first four years following seeding. Finally, we observed that the strength of priority effects varied significantly with water depth for one of the species groups, which demonstrates that abiotic context can strongly influence species interactions. We conclude that several aspects of historical contingence play key roles in the early formation of vernal pool plant communities. But we also observed reversals in community trajectories, suggesting that in this system historical effects may be lost within a decade.
Similarity quantification analysis to detect suffering fetus

To characterize a dynamical system, a number of descriptors or invariants can be used. Here we proposed to review and generalize the analysis of recurrence by introducing the concept of similarity. In this study, we showed that it was possible to distinguish the fetal heart rate of healthy from suffering fetus using the similarities of a time series, while the analysis of recurrence does not allowed it.
Coordinated Transmit and Receive Processing with Adaptive Multi-Stream Selection

In this paper, we propose an adaptive coordinated Tx-Rx beamforming scheme for inter-user interference cancellation, when a base station (BS) communicates with multiple users that each has multiple receive antennas. The conventional coordinated Tx-Rx beamforming scheme transmits a fixed number of data streams for each user regardless of the instantaneous channel states, that is, all the users, no matter they are with ill-conditioned or well-conditioned channels, have the same number of data streams. However, in the proposed adaptive coordinated Tx-Rx beamforming scheme, we adaptively select the number of streams per user to solve the inefficient problem of the conventional coordinated Tx-Rx beamforming scheme. As a result, the BER performance is improved. Simulation results show that the proposed algorithm outperforms the conventional co-ordinated Tx-Rx beamforming algorithm by 2.5dB at a target BER of 10-2.
Evolutive neural fuzzy filtering: real time constrains

In this paper, we describe the evolutive neural fuzzy filtering properties with real time conditions, giving the principles of its operation based on a back propagation fuzzy neural net, which adaptively choose and emit a decision according with the reference signal changes in order to loop the correct new conditions for a process. This work is an approach about the evolutive neural fuzzy digital filters (ENFDF). This filter using the neural fuzzy mechanism select the best parameter values into the knowledge base (KB), actualizing the filter weights to give a good enough answers with respect to the reference signal in natural linguistic sense. Additionally, the filtering architecture includes a decision making stage using an inference into its structure to deduce the filter decisions in accordance with the previous and actual filter answer in order to updates the new decision with respect to the new reference system conditions. This process requires that all of its states bound into ENFDF time limit as a real time system, considering the Nyquist and Shannon criteria. In this paper, we characterize the membership functions building the knowledge base in a probabilistic way with respect to the rules set inference to describe the reference system and the inference to deduce the new filter decision, performing the ENFDF. Moreover, the paper describes in schematic sense the neural net architecture with the decision-making stages in order to integrate the filtering stages as an evolutive system. The results expressed in formal sense using the concepts into the paper references. Finally, we present the simulation of the ENFDF operation using the Matlab© software. The paper has eight sections conformed as follows: 1. Introduction, 2. Filtering conditions, 3. Neural net description, 4. Rule base strategy, 5. Real time scheme, 6. Simulations, 7.Conclusion and References.
Efficient Large-Scale Similarity Search Using Matrix Factorization

We consider the image retrieval problem of finding the images in a dataset that are most similar to a query image. Our goal is to reduce the number of vector operations and memory for performing a search without sacrificing accuracy of the returned images. We adopt a group testing formulation and design the decoding architecture using either dictionary learning or eigendecomposition. The latter is a plausible option for small-to-medium sized problems with high-dimensional global image descriptors, whereas dictionary learning is applicable in large-scale scenarios. We evaluate our approach for global descriptors obtained from both SIFT and CNN features. Experiments with standard image search benchmarks, including the Yahoo100M dataset comprising 100 million images, show that our method gives comparable (and sometimes superior) accuracy compared to exhaustive search while requiring only 10% of the vector operations and memory. Moreover, for the same search complexity, our method gives significantly better accuracy compared to approaches based on dimensionality reduction or locality sensitive hashing.