Miracle-dz/UniFAR-FTUs huggingface dataset:
Metallic Scaffolds for Bone Regeneration

Bone tissue engineering is an emerging interdisciplinary field in Science, combining expertise in medicine, material science and biomechanics. Hard tissue engineering research is focused mainly in two areas, osteo and dental clinical applications. There is a lot of exciting research being performed worldwide in developing novel scaffolds for tissue engineering. Although, nowadays the majority of the research effort is in the development of scaffolds for non-load bearing applications, primarily using soft natural or synthetic polymers or natural scaffolds for soft tissue engineering; metallic scaffolds aimed for hard tissue engineering have been also the subject of in vitro and in vivo research and industrial development. In this article, descriptions of the different manufacturing technologies available to fabricate metallic scaffolds and a compilation of the reported biocompatibility of the currently developed metallic scaffolds have been performed. Finally, we highlight the positive aspects and the remaining problems that will drive future research in metallic constructs aimed for the reconstruction and repair of bone.
An efficient self-recovering adaptive algorithm for BPSK signals transmitted through underwater acoustic channels

Proposes a receiver which performs fast self-recovering adaptive identification and equalization based on decision feedback equalization and reduced maximum likelihood sequence estimation. It runs on binary-phase-shift keying signals through underwater acoustic channels. Considerations for its implementation are discussed. Its performance is demonstrated both on experimental data from a long-range deep water channel and on simulated data from two discrete-time channels with severe amplitude distortion and additive white Gaussian noise.
QCMA with One-sided Error Equals QCMA with Two-sided Error | NIST

QCMA is the set of decision problems such that if the answer is yes, there exists a classical bit string, or proof, that can be efficiently verified by a quantum computer. The verifier is allowed a small probability of rejecting a valid proof or accepting invalid proofs. We show that for all problems in QCMA, the acceptance probability for valid proofs can be amplified to one, thus QCMA with one-sided error is equal to QCMA. This is a quantum analog to the result of Zachos and Furer, that the classical complexity class MA with one sided error is the same as MA with two-sided error. Because a quantum oracle separating QCMA and QCMA with one sided error is known [1], our result provides an example of a quantumly non-relativizing proof.
Inhibition of Germinal Centre Apoptotic Programmes by Epstein-Barr Virus

To establish a persistent latent infection, Epstein-Barr virus (EBV) faces a challenge in that the virus-infected host cell must transit through the germinal centre reaction. This is a site of B cell differentiation where antibody responses are optimised, and the selection criteria for B cells are stringent. The germinal centre environment is harsh, and the vast majority of B cells here die by apoptosis. Only cells receiving adequate survival signals will differentiate fully to be released into the periphery as long-term memory B cells (the site of persistence). In this review, we detail the apoptotic pathways potentially encountered by EBV-infected B cells during the process of infection, and we describe the functions of those EBV-regulated cellular and viral genes that help promote survival of the host B cell.
Information is Power : Toward Intelligent Tools for Information Access and Evaluation

Despite the vast array of alternative sources of information brought by the advent of the Internet, comprehensible information on all but the most basic topics remains unavailable to most people, including those with access to ICT, because it is not in a language that the user can understand. At the same time, those who do have access to information because they can read English or one of the other major languages of the Internet face the problem of locating reliable information on a given topic. Much of the information is provided by unqualified agents or is designed to manipulate users through the use of deceptive arguments, exaggerations, and false claims. We believe that research within artificial intelligence and cognitive science can be brought to bear on these problems in the development of tools that provide access to and evaluation of information, an intelligent Interface to the Information World. In this paper we discuss three specific projects that we
Assembling a Balanced Corpus from the Internet

For empirically oriented textual research it is crucial to have materials available for extraction of statistics, training probabilistic algorithms, and testing hypotheses about language and language processing in general. In recent years, the awareness that text is not just text, but that texts comes in several forms, has spread from more theoretical and literary subfields of linguistics to the more practically oriented information retrieval and natural language processing fields. As a consequence, several test collections available for research explicitly attempt to cover many or most well-established textual genres , or functional styles in well-balanced proportions (Francis and Kucera, 1982; Kallgren, 1990). The creation of such a collection is a complex matter in several respects. Our reseach area is to build retrieval tools for the Internet, and thus, for our purposes, the choice of genres to include is one of the more central problems: there is no well-established genre palette for Internet materials. To find materials to experiment with, we need to create them in a form suitable for our purposes. This is a double edged problem, involving both vaguely expressed user expectations and establishing categories using large numbers of features which taken singly have low predictive and explanatory power. This paper gives an outline of the methodology we use for determining which genres to include.
AE-BP: Adaptive Erasure Belief Propagation Decoding Algorithm of LDPC Codes

In the decoding process of LDPC codes, variable node messages often fluctuate continuously and thereby become the hindrance to the successful decoding. This paper proposes an Adaptive Erasure Belief Propagation (AE-BP) decoding algorithm to reduce the influence of these unreliable messages. The idea behind AE-BP is recording the continuous fluctuant times of variable nodes by introducing a sequence of counters, and then adaptively erasing the messages according to their fluctuant times so that other messages would recover to more precise states. Semi-Gaussian approximation demonstrates adaptive erasure is a good candidate towards offsetting the defect of unreliable messages. Experimental simulations show that, for LDPC codes AE-BP outperforms most decoding algorithms in the literature.
ILR: a Self-Tuning Distributed Attacks Detection System 1

In order to protect Internet users from various attacks such as worms, viruses and other intrusions, signature-based intrusion detection system (IDS) should be deployed at the critical part of the network with rapid response for updating newly emerged attack signatures and containing the spread of worms or viruses at their early stage. The processing speed of one IDS cannot achieve the throughput requirement in the core networks because of the pattern matching, the key operation for signature-based IDS, is complex and time consuming. In this paper, it argues that if the signature set is shared by multiple IDSs, a packet needs to be checked once and once only by one of the IDSs, so traffic load can be redistributed among the IDSs to avoid local congestion. Packet marking is used to indicate the status of this packet utilized by collaborative IDSs, and a redistribution strategy named inner logical ring (ILR) is built among IDSs to redistribute the traffic load. Meanwhile, caching scheme is used to keep sequence for packets belonging to the same flow. This collaborative distributed IDS is robust with rapid response to various attacks, and the detection throughput is significantly increased from the throughput of the weakest IDS to the summation of all the collaborative IDSs.
ComeWithMe: An Activity-Oriented Carpooling Approach

The interest in carpooling is increasing due to the need to reduce traffic and noise pollution. Most of the available approaches and systems are route oriented, where driver and passengers are matched when the destination location is the same. ComeWithMe offers a new perspective: the destination is the intended activity instead of a location. This novel matching method is aimed to boost the possibilities of rides if passenger reaches a different location maintaining the activity. We conducted experiments using a real data set of trajectories and our results showed that the proposed matching algorithm improved the traditional carpooling approach in more than 80%.
Learning Bilingual Collocations by Word-Level Sorting

This paper proposes a new method for learning bilingual collocations from sentence-aligned parallel corpora. Our method comprises two steps: (1) extracting useful word chunks (n-grams) by word-level sorting and (2) constructing bilingual collocations by combining the word-chunks acquired in stage (1). We apply the method to a very challenging text pair: a stock market bulletin in Japanese and its abstract in English. Domain specific collocations are well captured even if they were not contained in the dictionaries of economic terms.
G Protein–Coupled Receptor Kinase 2: A Link Between Myocardial Contractile Function and Cardiac Metabolism

Heart failure (HF) causes a tremendous burden on the worldwide healthcare system, affecting >23 million people. There are many cardiovascular disorders that contribute to the development of HF and multiple risk factors that accelerate its occurrence, but regardless of its underlying cause, HF is characterized by a marked decrease in myocardial contractility and loss of pump function. One biomarker molecule consistently shown to be upregulated in human HF and several animal models is G protein–coupled receptor kinase-2 (GRK2), a kinase originally discovered to be involved in G protein–coupled receptor desensitization, especially &bgr;-adrenergic receptors. Higher levels of GRK2 can impair &bgr;-adrenergic receptor–mediated inotropic reserve and its inhibition, or molecular reduction has shown to improve pump function in several animal models including a preclinical pig model of HF. Recently, nonclassical roles for GRK2 in cardiovascular disease have been described, including negative regulation of insulin signaling, a role in myocyte cell survival and apoptotic signaling, and it has been shown to be localized in/on mitochondria. These new roles of GRK2 suggest that GRK2 may be a nodal link in the myocyte, influencing both cardiac contractile function and cell metabolism and survival and contributing to HF independent of its canonical role in G protein–coupled receptor desensitization. In this review, classical and nonclassical roles for GRK2 will be discussed, focusing on recently discovered roles for GRK2 in cardiomyocyte metabolism and the effects that these roles may have on myocardial contractile function and HF development.
Postponed Updates for Temporal-Difference Reinforcement Learning

This paper presents postponed updates, a new strategy for TD methods that can improve sample efficiency without incurring the computational and space requirements of model-based RL. By recording the agent's last-visit experience, the agent can delay its update until the given state is revisited, thereby improving the quality of the update. Experimental results demonstrate that postponed updates outperforms several competitors, most notably eligibility traces, a traditional way to improve the sample efficiency of TD methods. It achieves this without the need to tune an extra parameter as is needed for eligibility traces.
MODELING CONTROL OF AUTOMATIC VOLTAGE REGULATOR WITH PROPORTIONAL INTEGRAL DERIVATIVE

The Automatic Voltage Regulator (AVR) cannot respond generator output voltage quickly resulting in drop voltage and can be affected to the electrical system. AVR controller simulation model created in power system based on real data from National Electricity Company (PLN) ( Tello Power Plant Makassar case). AVR controller response time under normal conditions has the oscillation time of about 9 seconds and response time when loaded is about 15 seconds. Resulting unstable voltage in the system follows load changes. With the addition of Proportional Integral Derivative (PID) controllers acquired a controlling response time to changing loads faster and system voltage will change the voltage stability limit of ± 5% of nominal voltage. AVR controller with PID is very suitable for controlling the voltage of power generation system due to changes in load.
Clinical Applications of Circulating Tumor Cells and Circulating Tumor DNA as Liquid Biopsy.

UNLABELLED "Liquid biopsy" focusing on the analysis of circulating tumor cells (CTC) and circulating cell-free tumor DNA (ctDNA) in the blood of patients with cancer has received enormous attention because of its obvious clinical implications for personalized medicine. Analyses of CTCs and ctDNA have paved new diagnostic avenues and are, to date, the cornerstones of liquid biopsy diagnostics. The present review focuses on key areas of clinical applications of CTCs and ctDNA, including detection of cancer, prediction of prognosis in patients with curable disease, monitoring systemic therapies, and stratification of patients based on the detection of therapeutic targets or resistance mechanisms. SIGNIFICANCE The application of CTCs and ctDNA for the early detection of cancer is of high public interest, but it faces serious challenges regarding specificity and sensitivity of the current assays. Prediction of prognosis in patients with curable disease can already be achieved in several tumor entities, particularly in breast cancer. Monitoring the success or failure of systemic therapies (i.e., chemotherapy, hormonal therapy, or other targeted therapies) by sequential measurements of CTCs or ctDNA is also feasible. Interventional studies on treatment stratification based on the analysis of CTCs and ctDNA are needed to implement liquid biopsy into personalized medicine. Cancer Discov; 6(5); 479-91. ©2016 AACR.
Self-tuning of Data Allocation and Storage Management: Advantages and Implications

Many important business applications use complex database management systems (DBMS). These DBMS have to be administrated and optimized for an optimal performance, especially in time-critical applications. Administration and optimization are very complex and costly tasks. Therefore, researchers and DBMS vendors focus on development of self-tuning techniques for a continuous adaption, e.g., the COMFORT automatic tuning project [6] or the MAPE approach by IBM [2]. However, the optimization and usage of self-tuning techniques for allocation and storage management of data are less investigated. DBMS vendors inform their customers about advantages and disadvantages of optimizing data storage in their user manuals and tuning guidelines. They recommend usage of functionality to optimize data storage with respect to the higher administration costs. But, DBMS vendors do not publish guidelines for this. Optimization of data storage is a complex (high administrative needs) task with many of options and parameters. For instance, the number of parameters for table space creation is huge, e.g., page size or database partition group. These two parameters affect essentially the performance of data allocation and storage management. In the scope of data allocation and storage management, many parameters dependencies and implications are unobserved. Our approach will observe the affect of the parameters. This paper presents first steps for better solutions and estimations for data allocation and storage management based on the parameter page size and its configuration.
Storing and Querying XML Data using an RDMBS

XML is rapidly becoming a popular data format. It can be expected that soon large volumes of XML data will exist. XML data is either produced manually (like html documents today), or it is generated by a new generation of software tools for the WWW and/or electronic data interchange (EDI). The purpose of this paper is to present the results of an initial study about storing and querying XML data. As a first step, this study was focussed on the use of relational database systems and on very simplistic schemes to store and query XML data. In other words, we would like to study how the simplest and most obvious approaches perform, before thinking about more sophisticated approaches. In general, numerous different options to store and query XML data exist. In addition to a relational database, XML data can be stored in a file system, an object-oriented database (e.g., Excelon), or a special-purpose (or semi-structured) system such as Lore (Stanford), Lotus Notes, or Tamino (Software AG). It is still unclear which of these options will ultimately find wide-spread acceptance. A file system could be used with very little effort to store XML data, but a file system would not provide any support for querying the XML data. Object-oriented database systems would allow to clusterXML elements and sub-elements; this feature might be useful for certain applications, but the current generation of object-oriented database systems is not mature enough to process complex queries on large databases. It is going to take even longer before special-purpose systems are mature. Even when using an RDBMS, there are many different ways to store XML data. One strategy is to ask the user or a system administrator in order to decide how XML elements are stored in relational tables. Such an approach is supported, e.g., by Oracle 8i. Another option is to infer from the DTDs of the XML documents how the XML elements should be mapped into tables; such an approach has been studied in [4]. Yet another option is to analyze the XML data and the expected query workload; such an approach has been devised, e.g., in [2]. In this work, we will only study very simplead-hocschemes; we think that such a study is necessary before adopting a more complex approach. The schemes that we analyze require no input by the user, they work in the absence of DTDs or if DTDs are meaningless, and they do not involve any analysis of the XML data. Due to their simplicity, the approaches we study will not show the best possible performance, but as we will see, some of them will show very good query performance in most situations. Also, there is no guarantee that any of the more sophisticated approaches known so far will perform better than our simple schemes; see [3] for some experimental results in this respect. Furthermore, the results of our study can be used as input for more sophisticated approaches.
Spatial Distribution of Soil Organic Carbon and Total Nitrogen Based on GIS and Geostatistics in a Small Watershed in a Hilly Area of Northern China

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km2) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.
Neuropeptide Y2 Receptor (NPY2R) Expression in Saliva Predicts Feeding Immaturity in the Premature Neonate

Background The current practice in newborn medicine is to subjectively assess when a premature infant is ready to feed by mouth. When the assessment is inaccurate, the resulting feeding morbidities may be significant, resulting in long-term health consequences and millions of health care dollars annually. We hypothesized that the developmental maturation of hypothalamic regulation of feeding behavior is a predictor of successful oral feeding in the premature infant. To test this hypothesis, we analyzed the gene expression of neuropeptide Y2 receptor (NPY2R), a known hypothalamic regulator of feeding behavior, in neonatal saliva to determine its role as a biomarker in predicting oral feeding success in the neonate. Methodology/Principal Findings Salivary samples (n = 116), were prospectively collected from 63 preterm and 13 term neonates (post-conceptual age (PCA) 26 4/7 to 41 4/7 weeks) from five predefined feeding stages. Expression of NPY2R in neonatal saliva was determined by multiplex RT-qPCR amplification. Expression results were retrospectively correlated with feeding status at time of sample collection. Statistical analysis revealed that expression of NPY2R had a 95% positive predictive value for feeding immaturity. NPY2R expression statistically significantly decreased with advancing PCA (Wilcoxon test p value<0.01), and was associated with feeding status (chi square p value = 0.013). Conclusions/Significance Developmental maturation of hypothalamic regulation of feeding behavior is an essential component of oral feeding success in the newborn. NPY2R expression in neonatal saliva is predictive of an immature feeding pattern. It is a clinically relevant biomarker that may be monitored in saliva to improve clinical care and reduce significant feeding-associated morbidities that affect the premature neonate.
Lipids of the fin whale (Balaenoptera physalus) from North Atlantic waters. I. Fatty acid composition of whole blubber and blubber sections.

Oils from sectioned blubber, whole blubber oils, and commercial oils from the fin whale (Balaenoptera physalus) taken in Nova Scotia waters have been examined. The general properties include much lower iodine values (105–117) than those commonly reported for North Atlantic (Arctic) baleen whales. The fatty acid composition pattern has been determined by gas–liquid chromatography and varies systematically with the type of acid across the blubber section, the inner section having the highest iodine value. The roles of the blubber in physiological functions other than as an insulating layer are discussed in terms of fatty acid composition.