Miracle-dz/UniFAR-FTUs huggingface dataset:
Adult Rat Bones Maintain Distinct Regionalized Expression of Markers Associated with Their Development

The incidence of limb bone fracture and subsequent morbidity and mortality due to excessive bone loss is increasing in the progressively ageing populations of both men and women. In contrast to bone loss in the weight-bearing limb, bone mass in the protective skull vault is maintained. One explanation for this could be anatomically diverse bone matrix characteristics generated by heterogeneous osteoblast populations. We have tested the hypothesis that adult bones demonstrate site-specific characteristics, and report differences at the organ, cell and transcriptome levels. Limb bones contain greater amounts of polysulphated glycosaminoglycan stained with Alcian Blue and have significantly higher osteocyte densities than skull bone. Site-specific patterns persist in cultured adult bone-derived cells both phenotypically (proliferation rate, response to estrogen and cell volumes), and at the level of specific gene expression (collagen triple helix repeat containing 1, reelin and ras-like and estrogen-regulated growth inhibitor). Based on genome-wide mRNA expression and cluster analysis, we demonstrate that bones and cultured adult bone-derived cells segregate according to site of derivation. We also find the differential expression of genes associated with embryological development (Skull: Zic, Dlx, Irx, Twist1 and Cart1; Limb: Hox, Shox2, and Tbx genes) in both adult bones and isolated adult bone-derived cells. Together, these site-specific differences support the view that, analogous to different muscle types (cardiac, smooth and skeletal), skull and limb bones represent separate classes of bone. We assign these differences, not to mode of primary ossification, but to the embryological cell lineage; the basis and implications of this division are discussed.
Oral health in postmenopausal and premenopausal women after myocardial infarction in Poland: a preliminary study

Introduction Age and hormonal disorders are recognized factors impacting the periodontium and the prevalence of cardiovascular diseases, but as yet the relationship between these two conditions in postmenopausal (post-M) and premenopausal (pre-M) women in Poland has not been assessed. The aim of this study was to compare the periodontal status in women after myocardial infarction (MI) with women without MI history and to determine risk factors for periodontitis. Material and methods The study included 35 women hospitalized due to MI, average age 54.7 ± 9.4 years, and 96 women randomly drawn from the general population, average age 56.1 ± 10.0 years. All women were checked for periodontitis risk factors (education, socioeconomic status, tobacco smoking, stress), and underwent dental examination. Results The lowest number of teeth was found in post-M women after MI (median = 8), whereas pre-M women without MI history had 25 teeth. Edentulousness occurred more frequently in post-M women compared with pre-M women (12.2% vs. 0%), the same was observed for advanced periodontitis (28.4% vs. 21.1%). The severity of periodontitis was highest in the post-M subgroup (more than half demonstrated advanced periodontitis or edentulousness). The most important risk factor for periodontitis, regardless of age, was the level of education. In post-M women the second risk factor was smoking, while in pre-M women negative stress. Conclusions The status of oral health in post-M women is unsatisfactory, particularly in those affected by cardiovascular diseases. It is necessary to take preventive and educational measures targeted at these women.
High-Speed FPGA-Based Pseudorandom Generators with Extremely Long Periods

In this paper, we propose the use of a field programmable gate array (FPGA) to construct high-speed pseudorandom generators with extremely long periods of generated number sequences. The output streams pass all statistical tests from the NIST 800-22 statistical test suite. The numbers are encoded using only 31 bits. We show that by implementing many generators in a single FPGA, a new source of pseudorandom sequences with extremely long periods can be obtained. This source produces sequences that pass the NIST 800-22 statistical tests and the bit rate of the output stream is k times greater, where k is the number of 31-bit generators used. The upper limit of the bit rate depends on the number of 31-bit generators that produce streams passing all NIST 800-22 statistical tests. Although the new generator is not secure, it can be used in cryptography if an auxiliary source of pseudorandom numbers is implemented in the same FPGA.
Transferencia, relación y el analista como objeto: Hallazgos del Grupo de Trabajo Norteamericano sobre Métodos Clínicos Comparados

Se utilizan los datos del Grupo de Trabajo Norteamericano sobre Métodos Clínicos Comparados (MCC) con el fin de 1) explorar cómo los psicoanalistas norteamericanos conciben y abordan la transferencia y la relación entre el analista y el analizado y 2) estudiar en qué tipo de ‘objetos’ se convierten los analistas, de manera explícita e implícita, dentro de los tratamientos psicoanalíticos. El Grupo de Trabajo Norteamericano sobre Métodos Clínicos Comparados estudió detenidamente 17 casos clínicos presentados por psicoanalistas norteamericanos en varios encuentros de un amplio espectro de escuelas analíticas. Hallamos que los 17 analistas podían dividirse en tres grupos, según la coherencia interna de sus métodos y su abordaje de la transferencia, la relación analista-analizado y la situación del analista como objeto. También descubrimos que el trabajo individual de los analistas, aunque muy influenciado por sus escuelas de pensamiento, también incluía singulares interpretaciones de sus paradigmas particulares.
Performance Analysis of Maximum Power Point Tracking based Photovoltaic Module with Cuk Converter for Electrical Applications

In recent days, Photovoltaic power generation systems are becoming increasingly prevalent in distribution and generation systems. Many industrialized nations are installing significant solar power capacity in their grids as a supplement or alternative to other power sources. This project presents an MPPT based PV module with CUK converter for electrical applications. In conventional system, high ratio DC-DC converter is having high switching loss due to extreme duty ratios and numerous turns’ ratios in the coupled inductor. Also the converter used is single stage, having low power. Also the DC-DC converter used is the boost converter, whose voltage gain is comparatively lower. It also possess severe diode reverse recovery problem. If high duty cycle is used for getting high output voltage, will lead to poor dynamic responses. To overcome these difficulties and to use in application level CUK converter with a PWM inverter is used. In the proposed method, instead of using the boost converter, the CUK converter with a PWM inverter is used. The PWM inverter uses a filter to reduce the harmonics . The PV model also uses MPPT to track maximum power from the panel.
An online incremental language model adaptation method

In this paper, an online incremental language model adaptation method is proposed, which is different from the traditional offline language model adaptation method. There are some problems in the online incremental adaptation. The first one is how to adjust the model parameters online and modify the model incrementally. The second one is how to induce new words and assign initial probabilities to the ngrams related to them. In our application for Chinese character input method editor, the language model is divided into two parts, corresponding to the background (generalpurpose) model and the user model, respectively. A modified maximum a posterior method is proposed for adapting the user model dynamically. Experiments are done to test the proposed method on an Chinese sentence input system and the results show that a satisfying word error rate reduction is obtained when the input articles are of similar topics.
Social Intelligence Design for Cultivating Shared Situated Intelligence

One of the technical challenges in the knowledge society is to build a situated intelligent agent that can join our knowledge process to learn and exploit tacit knowledge in a situated fashion. Social intelligence design sheds light on the social context in which agents might take part in our knowledge process where tacit knowledge comes into play. We aim at building a computational framework for understanding and augmenting social intelligence that is defined as the ability of an agent to build a social relationship with others and to use it when solving a variety of problems, and the ability of a group to learn from experience when solving problems. In this paper, I outline a conceptual framework of social intelligence design at three scales ranging from the micro to the macro.
A Novel Approach to Big Data Veracity Using Crowdsourcing Techniques and Bayesian Predictors

In today's world data is being generated at a tremendous pace and there have to be enough measures in place to verify the nature of big data. Analysis performed on 'dirty' data may lead to erroneous insights and thereby shaping decisions poorly. The aspect of big data that deals with its correctness is known as big data veracity. Trusting the data acquired goes a long way in implementing decisions from an automated decision-making system and veracity helps to validate the data acquired. In this paper, we present our solution to the big data veracity problem using crowdsourcing techniques. Our solution involves the use of sentiment analysis, which deals with identifying the sentiment expressed in a piece of text. As a proof of concept, we have developed an app that requires users to tag tweets as per the sentiment it evokes in them. Each tweet would therefore get ratified by hundreds of our participants and the sentiment associated to the tweet gets tagged. The tagged emotion was then evaluated against the verified emotion as compared to a verified data set. This analysis was then plotted on a ROC curve and also evaluated against verified data using a Bayesian predictor trained with a trinomial function. As can be seen, an accuracy of 81% was obtained as displayed by the ROC curve and 89% through the Bayesian predictor. Also, a MAP analysis of the Bayesian predictor yields neutral sentiment as the most probable hypothesis. By doing this, we have proven that crowdsourcing of sentiment analysis is a viable solution to the problem of big data veracity and therefore an aid in making better decisions.
Explicating Divided Approaches to Gentrification and Growing Income Inequality

Contemporary sociology offers competing images of the breadth and consequences of gentrification. One subset presents gentrification as a nearly unstoppable force that plays a prominent role in the spatial reorganization of urban life; another presents it as less monolithic and less momentous for marginalized residents, particularly racial minorities. Although neither camp is methodologically homogenous, more qualitative scholars, typically relying on micro-level analyses of individual neighborhoods, tend to present gentrification as increasingly endemic, advanced, and consequential, whereas more quantitative scholars, typically relying on macro analyses, tend to present it in less dire terms. These competing images of gentrification originate in the fact that each subset of research asks different questions, employs distinct methods, and produces particular answers. Exacerbating and partially driving these divergences are different responses to an anxiety within and beyond the academy about broader spati.
Sentiment Analysis Using Collaborated Opinion Mining

Opinion mining and Sentiment analysis have emerged as a field of study since the widespread of World Wide Web and internet. Opinion refers to extraction of those lines or phrase in the raw and huge data which express an opinion. Sentiment analysis on the other hand identifies the polarity of the opinion being extracted. In this paper we propose the sentiment analysis in collaboration with opinion extraction, summarization, and tracking the records of the students. The paper modifies the existing algorithm in order to obtain the collaborated opinion about the students. The resultant opinion is represented as very high, high, moderate, low and very low. The paper is based on a case study where teachers give their remarks about the students and by applying the proposed sentiment analysis algorithm the opinion is extracted and represented.
Is Cytomegalovirus a Therapeutic Target in Glioblastoma?

Several investigators have now demonstrated the expression of genes unique to cytomegalovirus (CMV) in malignant gliomas. Many of these genes promote oncogenesis, alter tumor microenvironment, and serve as immunologic targets. Is the level of CMV infection within tumor cells sufficient to drive important oncogenic or immunosuppressive processes? Can CMV serve as a target for therapeutic intervention? Clin Cancer Res; 17(14); 4619–21. ©2011 AACR.
Prediction and Scheduling in Navigation Systems

This position paper makes a case for the need to predict pedestrian position and schedule communication acts in mobile navigation systems. In our work, carried out in the context of a voice guided city navigation system, we have found that improperly timed route instructions are a major cause of failure in guiding pedestrians in unknown environments. Furthermore, the need to communicate other information while guiding users on routes, as well as complications caused by network latencies, occurs often enough to require that we be able synchronize communication acts with user position as they follow a route. This has led us to focus our efforts on scheduling utterances to maximize route following success. In this position paper we motivate this problem and present our initial approach and findings which should be of interest to others engaged in similar efforts in both the Geography and HCI communities. Author Keywords location-based systems; natural user interfaces; navigat ion systems; pedestrian interfaces; open street maps
Managing Change in Pacific Island Economies

World Bank Country Study Reports are among the many reports originally prepared for internal use as part of the continuing analysis by the Bank of the economic and related conditions of its developing member countries and of its dialogues with the governments. Some of the reports are published in this series with the least possible delay of the use of the governments and the academic, business and financial, and development communities. The typescript of this paper therefore has not been prepared in accordance with the procedures appropriate to formal printed texts, and the World Bank accepts no responsibility for errors. Some sources cited in this paper may be informal documents that are not readily available. The World Bank does not guarantee the accuracy of the data included in this publication and accepts no responsibility whatsoever for any consequence of their use. The boundaries, colors, denominations, and other information shown on any map in this volume do not imply on the part of the World Bank Group any judgment on the legal status of any territory or the endorsement or acceptance of such boundaries. A partner in strengthening economies and expanding markets to improve the quality of life for people everywhere, especially the poorest.
One-to-Many and Many-to-One Voice Conversion Based on Eigenvoices

This paper describes two flexible frameworks of voice conversion (VC), i.e., one-to-many VC and many-to-one VC. One-to-many VC realizes the conversion from a user's voice as a source to arbitrary target speakers' ones and many-to-one VC realizes the conversion vice versa. We apply eigenvoice conversion (EVC) to both VC frameworks. Using multiple parallel data sets consisting of utterance-pairs of the user and multiple pre-stored speakers, an eigenvoice Gaussian mixture model (EV-GMM) is trained in advance. Unsupervised adaptation of the EV-GMM is available to construct the conversion model for arbitrary target speakers in one-to-many VC or arbitrary source speakers in many-to-one VC using only a small amount of their speech data. Results of various experimental evaluations demonstrate the effectiveness of the proposed VC frameworks.
Techniques for efficient inline tracing on a shared-memory multiprocessor

While much current research concerns multiprocessor design, few traces of parallel programs are available for analyzing the effect of design trade-offs. Existing trace collection methods have serious drawbacks: trap-driven methods often slow down program execution by more than 1000 times, significantly perturbing program behavior; microcode modification is faster, but the technique is neither general nor portable. This paper describes a new tool, called MPTRACE, for collecting traces of multithreaded parallel programs executing on shared-memory multiprocessors. MPTRACE requires no hardware or microcode modification; it collects complete program traces; it is portable; and it reduces execution-time dilation to less than a factor 3. MPTRACE is based on inline tracing, in which a program is automatically modified to produce trace information as it executes. We show how the use of compiler flow analysis techniques can reduce the amount of data collected and therefore the runtime dilation of the traced program. We also discuss problematic issues concerning buffering and writing of trace data on a multiprocessor.
Recognising Classical Works in Historical Recordings

In collections of recordings of classical music, it is normal to find multiple performances, usually by different artists, of the same pieces of music. While there may be differences in many dimensions of musical similarity, such as timbre, pitch or structural detail, the underlying musical content is essentially and recognizably the same. The degree of divergence is generally less than that found between ‘cover songs’ in the domain of popular music, and much less than in typical performances of jazz standards. MIR methods, based around variants of the chroma representation, can be useful in tasks such as work identification especially where disco/bibliographical metadata is absent or incomplete as well as for access, curation and management of collections. We describe some initial experiments in work-recognition on a test-collection comprising c. 2000 digital transfers of historical recordings, and show that the use of NNLS chroma, a new, musically-informed chroma feature, dramatically improves recognition.
EVIDENCE FACTOR BIASED TECHNOLOGICAL CHANGE IN DEVELOPING COUNTRIES

This paper investigates the skill-bias of technological change in developing countries using a global sample of manufacturing industries. We report a striking increase in demand for skilled workers in the 1980s in middle income countries (GDP/capita between $2000 and $10,000). This increase is mostly due to skill-upgrading within industries rather than a reallocation of employment from low to high-skill industries and cannot be explained by capital-skill complementarity, thus indicating skill-biased technological change. Furthermore, the same industries that substituted toward skilled labor in middleincome countries in the 1980s had been doing so in the U.S. through the 1960s, 1970s and 1980s. We conclude that recent skill-biased innovations migrated rapidly from developed to middle income countries, but find no evidence of transfer to low income countries. Eli Berman Stephen Machin Boston University University College, London eli@bu.edu s.machin@ucl.ac. uk http://econ.bu.edu/eli
Adaptive Connection Strength Models for Relationship-Based Entity Resolution

Entity Resolution (ER) is a data quality challenge that deals with ambiguous references in data and whose task is to identify all references that co-refer. Due to practical significance of the ER problem, many creative ER techniques have been proposed in the past, including those that analyze relationships that exist among entities in data. Such approaches view the database as an entity-relationship graph, where direct and indirect relationships correspond to paths in the graph. These techniques rely on measuring the connection strength among various nodes in the graph by using a connection strength (CS) model. While such approaches have demonstrated significant advantage over traditional ER techniques, currently they also have a significant limitation: the CS models that they use are intuition-based fixed models that tend to behave well in general, but are very generic and not tuned to a specific domain, leading to suboptimal result quality. Hence, in this article we propose an approach that employs supervised learning to adapt the connection strength measure to the given domain using the available past/training data. The adaptive approach has several advantages: it increases both the quality and efficiency of ER and it also minimizes the domain analyst participation needed to tune the CS model to the given domain. The extensive empirical evaluation demonstrates that the proposed approach reaches up to 8% higher accuracy than the graph-based ER methods that use fixed and intuition-based CS models.
of Recent Trends in Engineering , Vol 2 , No . 8 , November 2009 42 An Insight into Swarm Intelligence

Swarm intelligence (SI) is a type of artificial intelligence based on the collective behavior of decentralized, self-organized systems. The expression was introduced by Gerardo Beni and Jing Wang in 1989, in the context of cellular robotic systems. Swarm Intelligence systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of "intelligent" global behavior, unknown to the individual agents. Natural examples of SI include ant colonies, bird flocking, animal herding, bacterial growth, and fish schooling. Robots are a perfect platform to study the principles of selforganisation in a precisely controlled environment.