Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene Coexpression and Evolutionary Conservation Analysis of the Human Preimplantation Embryos

Evolutionary developmental biology (EVO-DEVO) tries to decode evolutionary constraints on the stages of embryonic development. Two models—the “funnel-like” model and the “hourglass” model—have been proposed by investigators to illustrate the fluctuation of selective pressure on these stages. However, selective indices of stages corresponding to mammalian preimplantation embryonic development (PED) were undetected in previous studies. Based on single cell RNA sequencing of stages during human PED, we used coexpression method to identify gene modules activated in each of these stages. Through measuring the evolutionary indices of gene modules belonging to each stage, we observed change pattern of selective constraints on PED for the first time. The selective pressure decreases from the zygote stage to the 4-cell stage and increases at the 8-cell stage and then decreases again from 8-cell stage to the late blastocyst stages. Previous EVO-DEVO studies concerning the whole embryo development neglected the fluctuation of selective pressure in these earlier stages, and the fluctuation was potentially correlated with events of earlier stages, such as zygote genome activation (ZGA). Such oscillation in an earlier stage would further affect models of the evolutionary constraints on whole embryo development. Therefore, these earlier stages should be measured intensively in future EVO-DEVO studies.
Virtual reconstruction and representation of an archaeological terracotta statue

This paper describes the virtual reconstruction of a late fifteenth century terracotta statue. The proposed solution was adopted during the restoration process when it was not possible to get back the fragments from the missing parts that were lost during the burial period. The archaeological statue that has been called “Crist del Fossar”, according to its morphology and provenance, was found severely damaged, as it appeared highly fragmented with dull and age-worn edges. The restoration was assisted by means of an automatic reassembly technique that operates on digital models of fragments. This technique considers the best alignments between themselves (without the need to manipulate the original ones) and leads the reassembly and adhesion processes of the fragments. The statue will be part of a temporary exhibition at the Museu de Prehistòria de València where visitors would be able to appreciate the restoration of the few fragments that have been conserved and will be able to explore the virtual reconstruction of the entire statue through an immersive 3D interactive visualization.
Mobile Crowd Sensing Networks Technology

With the explosive popularization of the wireless mobile terminal devices, the combination of mobile sensing and crowdsourcing brings about a novel sensing paradigm of Internet of Things (IoT). By means of analyzing the data collected from mobile terminal, the crowd sensing can sense user’s situation intelligently and provide personalized service. It summarizes the latest researches both at home and aboard, introduces the state of art in mobile crowd sensing from four aspects, namely, the data processing, the motivation mechanism, the crowd sensing applications and the platforms, and also puts forward our opinions in respect of the abovementioned research fields.
The Use of Sentence Similarity as a Semantic Relevance Metric for Question Answering

An algorithm for calculating semantic similarity between sentences using a variety of linguistic information is presented and applied to the problem of Question Answering. This semantic similarity measure is used in order to determine the semantic relevance of an answer in respect to a question. The algorithm is evaluated against the TREC Question Answering test-bed and is shown to be useful in determining possible answers to a question. Not all linguistic information is shown to be useful, however, and a ni n- depth analysis shows that certain sentence features are more important than others in determining relevance.
A phone-dependent confidence measure for utterance rejection

An acoustic confidence measure for acceptance/rejection of recognition hypotheses for continuous speech utterances is proposed. This measure is useful for rejecting utterances that are out of domain, or contain out-of-vocabulary words or speech disfluencies. A phone-based approach is implemented so that a single global threshold can be applied to hypothesis rejection for any word sequence. Phone confidence is computed for each frame of speech as the posterior phone probability given the acoustic observation. Word sequence confidence is evaluated as the average phone confidence, either by weighting all frames equally or by normalizing by phone duration. The confidence measure is tested on a database of spoken company names. When normalized by phone duration, it achieves, in some cases with less computational expense, rejection performance comparable to a baseline system implementing a common filler-model approach. When all frames are equally weighted, performance is substantially poorer.
Preparation of Pure and Stable Chitosan Nanofibers by Electrospinning in the Presence of Poly(ethylene oxide)

Electrospinning was employed to obtain chitosan nanofibers from blends of chitosans (CS) and poly(ethylene oxide) (PEO). Blends of chitosan (MW (weight-average molecular weight) = 102 kg/mol) and PEO (M (molecular weight) = 1000 kg/mol) were selected to optimize the electrospinning process parameters. The PEO powder was solubilized into chitosan solution at different weight ratios in 0.5 M acetic acid. The physicochemical changes of the nanofibers were determined by scanning electron microscopy (SEM), swelling capacity, and nuclear magnetic resonance (NMR) spectroscopy. For stabilization, the produced nanofibers were neutralized with K2CO3 in water or 70% ethanol/30% water as solvent. Subsequently, repeated washings with pure water were performed to extract PEO, potassium acetate and carbonate salts formed in the course of chitosan nanofiber purification. The increase of PEO content in the blend from 20 to 40 w% exhibited bead-free fibers with average diameters 85 ± 19 and 147 ± 28 nm, respectively. Their NMR analysis proved that PEO and the salts were nearly completely removed from the nanostructure of chitosan, demonstrating that the adopted strategy is successful for producing pure chitosan nanofibers. In addition, the nanofibers obtained after neutralization in ethanol-aqueous solution has better structural stability, at least for six months in aqueous solutions (phosphate buffer (PBS) or water).
Grapevine leafroll-associated virus 3

Grapevine leafroll disease (GLD) is one of the most important grapevine viral diseases affecting grapevines worldwide. The impact on vine health, crop yield, and quality is difficult to assess due to a high number of variables, but significant economic losses are consistently reported over the lifespan of a vineyard if intervention strategies are not implemented. Several viruses from the family Closteroviridae are associated with GLD. However, Grapevine leafroll-associated virus 3 (GLRaV-3), the type species for the genus Ampelovirus, is regarded as the most important causative agent. Here we provide a general overview on various aspects of GLRaV-3, with an emphasis on the latest advances in the characterization of the genome. The full genome of several isolates have recently been sequenced and annotated, revealing the existence of several genetic variants. The classification of these variants, based on their genome sequence, will be discussed and a guideline is presented to facilitate future comparative studies. The characterization of sgRNAs produced during the infection cycle of GLRaV-3 has given some insight into the replication strategy and the putative functionality of the ORFs. The latest nucleotide sequence based molecular diagnostic techniques were shown to be more sensitive than conventional serological assays and although ELISA is not as sensitive it remains valuable for high-throughput screening and complementary to molecular diagnostics. The application of next-generation sequencing is proving to be a valuable tool to study the complexity of viral infection as well as plant pathogen interaction. Next-generation sequencing data can provide information regarding disease complexes, variants of viral species, and abundance of particular viruses. This information can be used to develop more accurate diagnostic assays. Reliable virus screening in support of robust grapevine certification programs remains the cornerstone of GLD management.
Uncertainty aware grasping and tactile exploration

The perception of the surrounding world depends on noisy sensors which introduce uncertainty. When we develop algorithms for grasping with robotic hands it is not enough to assume the best estimate of the environment - if there is a measure of uncertainty we need to account for it. This paper presents a control law which augments a grasp controller with the ability to prefer known or unseen regions of an object; this leads to the introduction of two motion primitives: an explorative and exploitative grasp. We integrate this control law in a framework for iterative grasping and implement a tactile exploration scenario. The experimental results confirm that using the notion of uncertainty in the control loop yields better models and does it faster than an uninformed controller.
Cluster based self-organization management protocols for wireless sensor networks

This study proposes a scheme for self-organization management protocols of higher-level nodes to contest member nodes with multi-hop form hierarchical clusters, introduce the "20/80 rule" for determining the ratio of headers to member nodes, and develop a new cluster-based routing protocol that integrates the inter-cluster on-demand routing and the intra-cluster table-driven routing applied in the sensor networks for further consumer applications.
Comparative Study of Queen-MAC , TC-MAC and OD-MAC Protocols in Wireless Sensor Networks

Abstract— Wireless sensor networks(WSNs) have become a leading solution in many important applications such as intrusion detection, target tracking, industrial automation, smart building and so on MAC protocol of wireless sensor network research is the key problem. From the basic ideas, the paper introduces three MAC protocols i.e. Queen-MAC, TC-MAC and OD-MAC protocol in detail, which are analyzed and compared based on performance parameters, and finally summarizes the problems of MAC protocols and possible research direction in future combined with the current research status.
Recourse in Kidney Exchange Programs

We introduce the problem of selecting patient-donor pairs in a kidney exchange program to undergo a crossmatch test, and we model this selection problem as a two-stage stochastic integer programming problem. The optimal solutions of this new formulation yield a larger expected number of realized transplants than previous approaches based on internal recourse or subset recourse. We settle the computational complexity of the selection problem by showing that it remains NP-hard even for maximum cycle length equal to two. Furthermore, we investigate to what extent different algorithmic approaches, including one based on Benders decomposition, are able to solve instances of the model. We empirically investigate the computational efficiency of this approach by solving randomly generated instances and study the corresponding running times as a function of maximum cycle length, and of the presence of nondirected donors. Summary of Contribution: This paper deals with an important and very complex issue linked to the optimization of transplant matchings in kidney exchange programs, namely, the inherent uncertainty in the assessment of compatibility between donors and recipients of transplants. Although this issue has previously received some attention in the optimization literature, most attempts to date have focused on applying recourse to solutions selected within restricted spaces. The present paper explicitly formulates the maximization of the expected number of transplants as a two-stage stochastic integer programming problem. The formulation turns out to be computationally difficulty, both from a theoretical and from a numerical perspective. Different algorithmic approaches are proposed and tested experimentally for its solution. The quality of the kidney exchanges produced by these algorithms compares favorably with that of earlier models.
Saccade-related EEG signals by ICA algorithms

Saccade-related electroencephalogram (EEG) signals have been the subject of application oriented research by our group toward developing a brain computer interface (BCI). Our goal is to develop novel BCI based on eye movements system employing EEG signals online. Most of the analysis of the saccade-related EEG data has been performed using ensemble averaging approaches. In signal processing method for BCI, raw EEG signals are analyzed. In ensemble averaging method which is major EEG analysis is not suitable for processing raw EEG signals. In order to process raw EEG data, we use independent component analysis. This paper presents extraction rate of saccade-related EEG signals by four ICA algorithms and six window size. As results of extracting rate focused on ICA algorithm, The JADE and Fast ICA have good results. As you know, calculation time in Fast ICA is faster than calculation time in JADE. Therefore, in this case, Fast ICA is best in order to extract saccade-related ICs. Next, we focus on extracting rate in each windows. The windows not including EEG signals after saccade and the windows which has small window size is good extracting rate.
PROBABILITY OF IMMINENT FAILURE AS A ROUTING METRIC IN A HIGH-MOBILITY WIRELESS AD HOC NETWORK

The current duration of a link in a mobile wireless ad hoc network (MANET) has important information to offer with respect to its stability. Unlike location or signal strength methods, life measurements implicitly includes the effects of true propagation mechanisms, mobility space geometry, power control mechanisms and other phenomena that are ignored or simplistically modeled in the methods mentioned above. Consequently, the information contained in the current duration of the links can be used to enhance the accuracy of these methods. Furthermore, under high mobility conditions and in the absence of any resources for location and signal strength measurements, this information can also be used alone to obtain new routing metrics to enhance the performance of routing algorithms in a MANET. One such metric is the probability of imminent failure, which can also be used to predict route failures with relatively high accuracy. Here we modify DSR to use this metric, improving the efficiency by reducing the routing overhead.
Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science.
Pre-Existing T- and B-Cell Defects in One Progressive Multifocal Leukoencephalopathy Patient

Progressive multifocal leukoencephalopathy (PML) usually occurs in patients with severe immunosuppression, hematological malignancies, chronic inflammatory conditions or receiving organ transplant. Recently, PML has also been observed in patients treated with monoclonal antibodies. By taking advantage of the availability of samples from a multiple sclerosis (MS) patient treated with natalizumab, the antibody anti-α4 integrin, who developed PML and was monitored starting before therapy initiation, we investigated the fate of T and B lymphocytes in the onset of PML. Real-time PCR was used to measure new T- and B-cell production by means of T-cell receptor excision circle (TREC) and K-deleting recombination excision circle (KREC) analysis and to quantify transcripts for CD34, terminal-deoxynucleotidyltransferase, and V pre-B lymphocyte gene 1. T- and B-cell subsets and T-cell heterogeneity were measured by flow cytometry and spectratyping. The data were compared to those of untreated and natalizumab-treated MS patients and healthy donors. Before therapy, a patient who developed PML had a low TREC and KREC number; TRECs remained low, while KRECs and pre-B lymphocyte gene 1 transcripts peaked at 6 months of therapy and then decreased at PML diagnosis. Flow cytometry confirmed the deficient number of newly produced T lymphocytes, counterbalanced by an increase in TEMRA cells. The percentage of naive B cells increased by approximately 70% after 6 months of therapy, but B lymphocyte number remained low for the entire treatment period. T-cell heterogeneity and immunoglobulins were reduced. Although performed in a single patient, all results showed that an immune deficit, together with an increase in newly produced B cells a few months after therapy initiation, may predispose the patient to PML. These findings indicate the TREC/KREC assay is a potential tool to identify patients at risk of developing PML and may provide insights into the immunological involvement of monoclonal antibody-associated therapies.
Robot Motion Planning with Trajectory Wide Constraints

Many of our everyday jobs are defined via a variety of task-specific constraints. In order for robots to perform these tasks, the robot’s motion planners must respect these constraints. To allow robots to collaboratively work along side human partners, we also want these constraints to be easily specified by non-experts. While a robotic manipulator moves and plans in its joint or configuration space, many human tasks are naturally defined in task space. For example, when carrying a glass full of water, we typically keep the glass upright to not spill the contents. For more complex tasks, we might require the robot’s end effector follow a particular trajectory, tracing out a specific shape. Therefore, in addition to joint limits and collision constraints, we further constrain our motion planner to follow a specified task space path. Our hope is that by defining constraints in task space, our constraints are easy to specify and generalize across scenes. For example, in Fig.1 a user demonstrates a path by tracing the robot’s arm, which is visualized to the right. Several prior approaches involve biasing the robot’s planner towards the desired motion [1–3] or by formulating this as a controls problem [4]. We began by examining this problem via trajectory optimization. We explored recreating task space demonstrations by optimizing a joint space path with respect to a cost function defining the distance between the demonstration and the task space motion achieved by the path [5]. While our method produced promising and exciting results, the optimization process was often slow and susceptible, as trajectory optimizers are, to finding a local, not global, minimum. To overcome this, we formulated our problem as an instance of graph search, interweaving task and configuration space. We propose a method that samples task space for poses and connects them via configuration space paths that maintain our constraint. By creating a graph of feasible sub-paths we can search over the graph to find our full path. This graph search method is still an active area of research for us, although we look forward to the coming results.
A MODEL OF THE AVIAN SUPERIOR OLIVARY NUCLEUS

Title of Thesis: A MODEL OF THE AVIAN SUPERIOR OLIVARY NUCLEUS Degree candidate: Raul Rodriguez Esteban Degree and year: Master of Science, 2002 Thesis directed by: Professor Jonathan Z. Simon Department of Electrical Engineering A computational model of the superior olivary nucleus (SON) was added to a model of the nucleus laminaris (NL) using the NEURON simulation language. The SON is an auditory nucleus situated in the ventrolateral region of the avian brainstem. It receives inputs from the ipsilateral nucleus laminaris (NL) and nucleus angularis (NA), and it projects back to the ipsilateral NL, NA and nucleus magnocellularis (NM). Its function is suggested to be inhibitory, controlling the size and precision of the spikes in the NL and the NM. However, the role it plays as a center of convergent input and divergent output is unknown. Our simulation shows how the SON improves the coincidence detection in the NL in different ways. First, the discrimination is increased because both coincidence detection spikes and erroneous spikes are reduced evenly, improving thus the ratio when the former outnumber the latter. Second, unilateral summation errors decrease because the inhibition helps differentiating these errors from binaural coincidence. The degree of heterogeneity of the SON cells leads us to hypothesize that it implies a specialization for the different kinds of inputs they receive. A MODEL OF THE AVIAN SUPERIOR OLIVARY NUCLEUS by Raul Rodriguez Esteban Thesis submitted to the Faculty of the Graduate School of the University of Maryland, College Park in partial fulfillment of the requirements for the degree of Master of Science 2002 Advisory Committee: Professor Jonathan Z. Simon Professor Timothy Horiuchi Professor Shihab A. Shamma
Query-Based Sampling using Only Snippets

Query-based sampling is a popular approach to model the content of an uncooperative server. It works by sending queries to the server and downloading the returned documents in the search results in full. This sample of documents then represents the server’s content. We present an approach that uses the document snippets as samples instead of downloading entire documents. This yields more stable results at the same amount of bandwidth usage as the full document approach. Additionally, we show that using snippets does not necessarily incur more latency, but can actually save time.
PPARs and Mitochondrial Metabolism: From NAFLD to HCC

Metabolic related diseases, such as type 2 diabetes, metabolic syndrome, and nonalcoholic fatty liver disease (NAFLD), are widespread threats which bring about a significant burden of deaths worldwide, mainly due to cardiovascular events and cancer. The pathogenesis of these diseases is extremely complex, multifactorial, and only partially understood. As the main metabolic organ, the liver is central to maintain whole body energetic homeostasis. At the cellular level, mitochondria are the metabolic hub connecting and integrating all the main biochemical, hormonal, and inflammatory signaling pathways to fulfill the energetic and biosynthetic demand of the cell. In the liver, mitochondria metabolism needs to cope with the energetic regulation of the whole body. The nuclear receptors PPARs orchestrate lipid and glucose metabolism and are involved in a variety of diseases, from metabolic disorders to cancer. In this review, focus is placed on the roles of PPARs in the regulation of liver mitochondrial metabolism in physiology and pathology, from NAFLD to HCC.