Miracle-dz/UniFAR-FTUs huggingface dataset:
Ultrasonic resonance spectroscopy of composite rings for flywheel rotors

Flywheel energy storage devices comprised of multilayered composite rotor systems are being studied extensively for utilization in the international space station. These composite material systems were investigated with a recently developed ultrasonic resonance spectroscopy technique. The system, UltraSpecTM, employs a swept frequency approach and performs a fast Fourier transform (FFT) on the frequency spectrum of the response signal. In addition, the system allows for equalization of the frequency spectrum, providing all frequencies with equal amounts of energy to excite higher order resonant harmonics. Interpretation of the second FFT, along with equalization of the frequency spectrum, offers greater assurance in acquiring and analyzing the fundamental frequency, or spectrum resonance spacing. The range of frequencies swept in a pitch-catch mode was varied up to 8 MHz depending on the material and geometry of the component. Single and multilayered material samples, with and without known defects, were evaluated to determine how the constituents of a composite material system affect the resonant frequency. Amplitude and frequency changes in the spectrum and spectrum resonance spacing domains were examined from ultrasonic response of a flat composite coupon, thin composite rings, and thick composite rings. Also, the ultrasonic spectroscopy responses from areas with an intentional delamination and a foreign material insert, similar to defects that may occur during manufacturing malfunctions, were compared to those from defect free areas in thin composite rings.A thick composite ring with varying thickness was tested to investigate the full thickness resonant frequency and any possible bulk interfacial bond issues. Finally, the effect on the frequency response of naturally occuring single and clustered voids in a composote ring was established.
Improving Phrase-Based SMT Using Cross-Granularity Embedding Similarity

The phrase–based statistical machine translation (PBSMT) model can be viewed as a log-linear combination of translation and language model features. Such a model typically relies on the phrase table as the main resource for bilingual knowledge, which in its most basic form consists of aligned phrases, along with four probability scores. These scores only indicate the co-occurrence of phrase pairs in the training corpus, and not necessarily their semantic relatedness. The basic phrase table is also unable to incorporate contextual information about the segments where a particular phrase tends to occur. In this paper, we deﬁne six new features which express the semantic relatedness of bilingual phrases. Our method utilizes both source and target side information to enrich the phrase table. The new features are inferred from a bilingual corpus by a neural network (NN). We evaluate our model on the English–Farsi (En–Fa) and English–Czech (En–Cz) pairs and observe considerable improvements in the all En ↔ Fa and En ↔ Cz directions.
miR-100 Induces Epithelial-Mesenchymal Transition but Suppresses Tumorigenesis, Migration and Invasion

Whether epithelial-mesenchymal transition (EMT) is always linked to increased tumorigenicity is controversial. Through microRNA (miRNA) expression profiling of mammary epithelial cells overexpressing Twist, Snail or ZEB1, we identified miR-100 as a novel EMT inducer. Surprisingly, miR-100 inhibits the tumorigenicity, motility and invasiveness of mammary tumor cells, and is commonly downregulated in human breast cancer due to hypermethylation of its host gene MIR100HG. The EMT-inducing and tumor-suppressing effects of miR-100 are mediated by distinct targets. While miR-100 downregulates E-cadherin by targeting SMARCA5, a regulator of CDH1 promoter methylation, this miRNA suppresses tumorigenesis, cell movement and invasion in vitro and in vivo through direct targeting of HOXA1, a gene that is both oncogenic and pro-invasive, leading to repression of multiple HOXA1 downstream targets involved in oncogenesis and invasiveness. These findings provide a proof-of-principle that EMT and tumorigenicity are not always associated and that certain EMT inducers can inhibit tumorigenesis, migration and invasion.
Assessing an Ensemble Docking-Based Virtual Screening Strategy for Kinase Targets by Considering Protein Flexibility

In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.
v-SNARE cellubrevin is required for basolateral sorting of AP-1B–dependent cargo in polarized epithelial cells

The epithelial cell–specific adaptor complex AP-1B is crucial for correct delivery of many transmembrane proteins from recycling endosomes to the basolateral plasma membrane. Subsequently, membrane fusion is dependent on the formation of complexes between SNARE proteins located at the target membrane and on transport vesicles. Although the t-SNARE syntaxin 4 has been localized to the basolateral membrane, the v-SNARE operative in the AP-1B pathway remained unknown. We show that the ubiquitously expressed v-SNARE cellubrevin localizes to the basolateral membrane and to recycling endosomes, where it colocalizes with AP-1B. Furthermore, we demonstrate that cellubrevin coimmunoprecipitates preferentially with syntaxin 4, implicating this v-SNARE in basolateral fusion events. Cleavage of cellubrevin with tetanus neurotoxin (TeNT) results in scattering of AP-1B localization and missorting of AP-1B–dependent cargos, such as transferrin receptor and a truncated low-density lipoprotein receptor, LDLR-CT27. These data suggest that cellubrevin and AP-1B cooperate in basolateral membrane trafficking.
Quality Programming Begets Software Quality

Domain As previously mentioned, these tools work by exploring paths and looking for anomalies in the abstract state of the program. The appeal of the symbolic execution is that each abstract state represents potentially many possible concrete states. For example, given an 8-bit variable x, there are 2 possible concrete values: 0, 1, . , 255. The symbolic execution, however, might represent the value as two abstract states: x=0, and x>0. So where a concrete execution has 256 states to explore, the symbolic execution has only two. As such, the expressivity of this abstract domain is an important factor that determines the effectiveness of the analysis. Again, there is a trade-off here: better precision and recall can be achieved by more sophisticated abstract domains, but more resources will then be required to complete an analysis. Values in the abstract domain are equations that represent constraints on values, i.e., x=0, or y>10. As the analysis progresses, a constraint solver is used to combine and simplify these equations. A key characteristic of these abstract domains is that there is a special value, usually named bottom, which indicates that the analysis knows no useful information about the actual value. Bottom is the abstract value that corresponds to all possible concrete values. Reaching bottom is impossible to avoid for any non-trivial abstraction in general as this would require solving the halting problem. Once bottom is reached, the analysis has a choice of treating it as a potentially dangerous value, which would increase recall, or as a probably safe value, which would increase precision. Most tools opt for the latter as the former also has the effect of decreasing precision enormously. If there are program constructs that step outside the bounds of what can be expressed in the abstract domain, this causes the analysis to lose track of variables and their relationships. For example, an abstract domain that allows the expression of affine relationships between no more than two variables admits expressions such as x=2y. However, something such as x=y+z is out of bounds because it involves three variables and the analysis would be forced to conclude x=bottom instead. The consequence of this is the abstract domain that a tool uses determines a great deal about the kind of flaws that it is capable of detecting. For example, if the tool uses an abstract domain of affine relations between two variables, then it may fail to find flaws that depend on three variables. “If asynchronous paths can occur (such as those caused by interrupts or exceptions) or if the program uses concurrency,
GLOBALIZATION, ECONOMIC EFFICIENCY, RELIGION AND THE EURO: SOME MYTHS AND A METHODOLOGY

Many myths currently circulate in the U.S. about globalization and its impact on the U.S. and world economy. The collection of statistical data can often destroy the myth and shed light on what is truly going on but require statistical methods beyond descriptive graphs and tables to deepen the analysis and truly explore economic performance. The article discusses some current myths about globalization and proposes a methodology that has been used to analyze microeconomic and macroeconomic issues in many countries. It is hoped that such a methodology might be used in this journal to further the journal's mission of fact-cantered research that goes beyond purely descriptive analysis. A discussion of linkages between applying the method and other topics follows to stimulate research using the method.
PCA-aided fully convolutional networks for semantic segmentation of multi-channel fMRI

Semantic segmentation of functional magnetic resonance imaging (fMRI) makes great sense for pathology diagnosis and decision system of medical robots. The multi-channel fMRI provides more information of the pathological features. But the increased amount of data causes complexity in feature detections. This paper proposes a principal component analysis (PCA)-aided fully convolutional network to particularly deal with multi-channel fMRI. We transfer the learned weights of contemporary classification networks to the segmentation task by fine-tuning. The results of the convolutional network are compared with various methods e.g. k-NN. A new labeling strategy is proposed to solve the semantic segmentation problem with unclear boundaries. Even with a small-sized training dataset, the test results demonstrate that our model outperforms other pathological feature detection methods. Besides, its forward inference only takes 90 milliseconds for a single set of fMRI data. To our knowledge, this is the first time to realize pixel-wise labeling of multi-channel magnetic resonance image using FCN.
Context-Aware Platform for Integrated Mobile Services

Today smart phones integrate many sensors and provide large computing capacities. They enable the shift towards massive quantities of real-time information becoming access push rather than demand pull on a global case. In this we describe CAPIM, a platform to support such a paradigm. It integrates services to monitor and a context for adapt with the user's context using sensors and capabilities of smart phones, together with online social data. It integrates context-aware services that are dynamically configurable and use the user's location, identity, preferences, profile, and relations with individuals, as well as capabilities of the mobile devices to manifest themselves in many different ways and re-invent themselves over and over again. Such services aggregate and semantically organize the context data. They react based on dynamically defined context-oriented workflows, and the platform includes an execution engine that supports context-aware actions for orientation, information, and recommendation. We describe the design of our system, the challenges that need to be solved, and the evaluation methodology we are planning to adopt.
Video Streaming over the UWB network

Ultra wideband (UWB), a radio technology, can be used at very low energy consumption levels for short-range high data rate communications by using a large portion of the radio spectrum. The high data rate (up to 480 Mbps) offered by UWB systems tends to favour multimedia applications with Quality-of-Service (QoS) requirements. Our course project investigated how the high data rate, different acknowledgement policies and different slots reservation sch emes affect the performance of video streaming over UWB networks. Experimental results demonstrate the feasibility of using UWB to provide QoS support in multimedia applications over wireless personal area networks.
A New soft switching multi-output forward converter with independent and precise regulation

In this study, a soft switching, independently and precisely regulated multi-output forward converter is proposed. Proposed multi-output forward converter has synchronous rectifiers at each output and an active clamp at the primary. All of the semiconductor switches in the converter are soft switched. Each output is controlled by a separate controller. Duty cycles of the active clamp switch and primary switch are determined from outputs' duty cycle information. The topology and control method ensures high efficiency and precise voltage regulation of multi-output forward converters with wide load variations. Simulation results have verified the proposed concept.
Recognizing textual entailment: Rational, evaluation and approaches

Abstract The goal of identifying textual entailment – whether one piece of text can be plausibly inferred from another – has emerged in recent years as a generic core problem in natural language understanding. Work in this area has been largely driven by the PASCAL Recognizing Textual Entailment (RTE) challenges, which are a series of annual competitive meetings. The current work exhibits strong ties to some earlier lines of research, particularly automatic acquisition of paraphrases and lexical semantic relationships and unsupervised inference in applications such as question answering, information extraction and summarization. It has also opened the way to newer lines of research on more involved inference methods, on knowledge representations needed to support this natural language understanding challenge and on the use of learning methods in this context. RTE has fostered an active and growing community of researchers focused on the problem of applied entailment. This special issue of the JNLE provides an opportunity to showcase some of the most important work in this emerging area.
The Chiari Severity Index: a preoperative grading system for Chiari malformation type 1.

BACKGROUND To develop evidence-based treatment guidelines for Chiari malformation type 1 (CM-1), preoperative prognostic indices capable of stratifying patients for comparative trials are needed. OBJECTIVE To develop a preoperative Chiari Severity Index (CSI) integrating the clinical and neuroimaging features most predictive of long-term patient-defined improvement in quality of life (QOL) after CM-1 surgery. METHODS We recorded preoperative clinical (eg, headaches, myelopathic symptoms) and neuroimaging (eg, syrinx size, tonsillar descent) characteristics. Brief follow-up surveys were administered to assess overall patient-defined improvement in QOL. We used sequential sequestration to develop clinical and neuroimaging grading systems and conjunctive consolidation to integrate these indices to form the CSI. We evaluated statistical significance using the Cochran-Armitage test and discrimination using the C statistic. RESULTS Our sample included 158 patients. Sequential sequestration identified headache characteristics and myelopathic symptoms as the most impactful clinical parameters, producing a clinical grading system with improvement rates ranging from 81% (grade 1) to 58% (grade 3) (P = .01). Based on sequential sequestration, the neuroimaging grading system included only the presence (55% improvement) or absence (74% improvement) of a syrinx ≥6 mm (P = .049). Integrating the clinical and neuroimaging indices, improvement rates for the CSI ranged from 83% (grade 1) to 45% (grade 3) (P = .002). The combined CSI had moderately better discrimination (c = 0.66) than the clinical (c = 0.62) or neuroimaging (c = 0.58) systems alone. CONCLUSION Integrating clinical and neuroimaging characteristics, the CSI is a novel tool that predicts patient-defined improvement after CM-1 surgery. The CSI may aid preoperative counseling and stratify patients in comparative effectiveness trials.
What I Learned In School: Reflections on Race, Child Development, and School Reform

Introduction. Introductory remarks (Dr. David Reynolds and Address from Dr. James Comer given at The Grawemeyer Award Ceremony). Chapter 1. Washington Elementary School. Maggie's American Dream. Chapter 2. Me, Walter, and America Beyond Black and White. Chapter 3. Three Networks and a Baby Waiting for a Miracle. Chapter 4. So You Want to Work in Schools. Maggie's American Dream. Chapter 5. My Work. Waiting for a Miracle. Chapter 6. To Leave No Child Behind. Leave No Child Behind. Chapter 7. All Our Children. Maggie's American Dream. Questions for Reflection. Index. Credit Lines. The Author.
City Research Online Parents' Mental Health and Parent-baby Interactions 3

Online is checked for eligibility for copyright before being made available in the live archive. URLs from City Research Online may be freely distributed and linked to from other web pages. Enquiries If you have any enquiries about any aspect of City Research Online, or if you wish to make contact with the author(s) of this paper, please email the team at publications@city.ac. uk. Abstract The aims of the current study were to examine the effect of fathers' and mothers' pre and postnatal mental health on mother-infant and father-infant interactions. Mental health was broadly defined to include anxiety, depression and PTSD. A community sample of 44 mothers and 40 fathers from 45 families completed questionnaire measures of mental health in late pregnancy and three months postpartum. Mother-infant and father-infant interactions were observed and videoed three months postpartum and analysed using the CARE-index. Results showed that prenatal mental health, in particular anxiety, was associated with parent-infant interactions to a greater extent than postnatal mental health. Fathers' prenatal symptoms were associated with higher paternal unresponsiveness and infant passivity whilst fathers' postnatal symptoms were associated with higher levels of infant difficulty in the father-baby interaction. The results also indicated that mothers and fathers interaction with their babies were similar, both on average and within the couples, with 34% being inept or at risk. These findings highlight the need for early detection and prevention of both mental health and parent-infant relationship problems in fathers as well as mothers. However, further prospective and longitudinal studies are needed to understand the influences of parental mental health on the parent-infant interactions further. Also it should be noted that the mental health scores were low in this well-educated, middle-class relatively low risk community sample of two-parent families, and that future studies therefore would benefit from focusing on more vulnerable groups of parents.
Another Compression Method for Homomorphic Ciphertexts

In this work we describe a message packing and unpacking method for homomorphic ciphertexts. Messages are packed into the coefficients of plaintext polynomials. We propose an unpacking procedure which allows to obtain a ciphertext for each packed message. The packing and unpacking of ciphertexts represents a solution for reducing the transmission bottleneck in cloud based applications, in particular when sending homomorphic calculations results. The results we obtain (packing ratio, unpacking time) are compared to existing packing methods based on trans-ciphering.
Beneish Model as Effective Complement to the Application of SAS No. 99 in the Conduct of Audit in Nigeria

This paper gives due consideration to determining the contribution made by SAS 99 towards improving the skills of Nigerian Auditors in the detection of fraud in Financial Statements of corporate organisations, while laying emphasis on the extent to which the Beneish Model could further strengthen Auditors likelihood to detecting such manipulations in the Financial Statements. The research was descriptively and historically designed. 100 respondents comprising Auditors, Accountants in the Industries and the Accounting Academics in Anambra and Enugu State were infinitely determined using the Topman’s formula. Data from secondary sources comprising Audited Annual Reports of the first five most capitalised manufacturing companies in Nigeria for the years 2002-2006 (in Cadbury, for model confirmatory test purpose) and 2006-2010 were used to complement this work. Inputs from the questionnaire distributed and the Annual Reports and Accounts, were analysed with the aid of SPSS software package using the Two way ANOVA statistical technique, and the Beneish Model. The analyses result showed that SAS 99 will significantly contributed to the deterrence and detection of fraud by Auditors in Nigeria, especially where complemented with the Beneish model. Thus, the Model should be introduced into the Nigeria Audit System as one of the prescribed analytical Audit techniques to aid External Auditors perform the relevant substantive tests where necessary so as to effectively curtail the rising incidence of fraud among corporate organisations in Nigeria.
Practical Use of Macroeconomic Models at Central Banks

Macroeconomic models are effective tools for central banks in economic projection, including risk assessment. In recent years, a multiple-model approach called the "Suite of Models" has become popular with central banks. This approach advocates the use of multiple models for several purposes, including checks of the robustness of projections. This idea has encouraged major central banks to use different types of models. These include hybrid-type models, which pursue short-run empirical coherence and long-run theoretical consistency, and Dynamic Stochastic General Equilibrium (DSGE) models, which place greater emphasis on theory. At the Bank of Japan, a new hybrid-type model named Q-JEM (Quarterly-Japanese Economic Model) has been recently added to the Bank's suite of models. A suite of models is useful for forecasting and for policy analysis. The use of models, however, requires sufficient understanding on the properties and limitations of each model.