Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression of Neuregulins and their Putative Receptors, ErbB2 and ErbB3, Is Induced during Wallerian Degeneration

Schwann cell dedifferentiation and proliferation is a prerequisite to axonal regeneration in the injured peripheral nervous system. The neuregulin (NRG) family of growth and differentiation factors may play a particularly important role in this process, because these axon-associated molecules are potent Schwann cell mitogens and differentiation factors in vitro. We have examined Schwann cell DNA synthesis and the expression of NRGs and their receptors, the erbB membrane tyrosine kinases, in rat sciatic nerve, sensory ganglia, and spinal cord 0–30 d postaxotomy. Analysis of NRG cDNAs from these tissues revealed several novel splice variants and showed that cells endogenous to injured nerve express NRG mRNAs. A selective induction of mRNAs encoding the glial growth factor (GGF) subfamily of NRGs occurs in nerve beginning 3 d postaxotomy and thus coincides with the onset of Schwann cell DNA synthesis. In later stages of Wallerian degeneration, however, Schwann cell mitogenesis markedly decreases, whereas elevated GGF expression persists. Of the four known erbB kinases, Schwann cells express both erbB2 and erbB3 receptors over the entire interval studied. Expression of erbB2 and erbB3 is coordinately induced in response to axotomy, indicating that Schwann cell responses to NRGs may be modulated by changes in receptor density. Neuregulin (including transmembrane precursors) and erbB protein are associated with Schwann cells postaxotomy. Thus, in contrast to the concept of NRGs as axon-associated mitogens, our findings suggest that NRGs produced by Schwann cells themselves may be partially responsible for Schwann cell proliferation during Wallerian degeneration, probably acting via autocrine or paracrine mechanisms.
Enhanced photon absorption in spiral nanostructured solar cells using layered 2D materials

Recent investigations of semiconducting two-dimensional (2D) transition metal dichalcogenides have provided evidence for strong light absorption relative to its thickness attributed to high density of states. Stacking a combination of metallic, insulating, and semiconducting 2D materials enables functional devices with atomic thicknesses. While photovoltaic cells based on 2D materials have been demonstrated, the reported absorption is still just a few percent of the incident light due to their sub-wavelength thickness leading to low cell efficiencies. Here we show that taking advantage of the mechanical flexibility of 2D materials by rolling a molybdenum disulfide (MoS2)/graphene (Gr)/hexagonal boron nitride stack to a spiral solar cell allows for optical absorption up to 90%. The optical absorption of a 1 μm long hetero-material spiral cell consisting of the aforementioned hetero stack is about 50% stronger compared to a planar MoS2 cell of the same thickness; although the volumetric absorbing material ratio is only 6%. A core–shell structure exhibits enhanced absorption and pronounced absorption peaks with respect to a spiral structure without metallic contacts. We anticipate these results to provide guidance for photonic structures that take advantage of the unique properties of 2D materials in solar energy conversion applications.
Leadership with a Purpose: Nine Case Studies of Schools in Tasmania and Victoria Where the Principal Had Undertaken the Principals as Literacy Leaders (PALL) Program

ABSTRACT This paper reports on Australian case study research in schools where principals completed the Principals as Literacy Leaders (PALL) program. The purpose was to gather data about the effects of PALL on principalsd’ leadership and the impact of interventions in Reading on teaching, student learning, and achievement. Data gathering included interviews with principals, leadership teams and teachers (parents in some schools), a student survey and examples, and reading progress data. Findings indicated that PALL had impacted positively on principals’ leadership and provided a framework to lead their teachers in ways that improved teaching practice, student engagement and learning.
Calcium Carbonate Dissolution Rate in Limestone Contactors

The project summarized here investigated some of the parameters and relationships used to predict the performance of limestone contactors. The purpose of the project was to study the effect of limestone composition, especially the dolomite [CaMg(CO 3) 2 ] and impurity content of the stone, on the kinetics of carbonate mineral dissolution and to determine the effect of temperature on the rate of dissolution. The rate of dissolution was determined by using a rotating disk apparatus and samples of limestone of varied composition. The limestone samples included a white marble and a selection of sedi-mentary stones. The white marble contained a significant amount of silica (approximately 35%). The major mineral constituents of the sedimentary limestones ranged from approximately 100% calcite (CaCO 3) to essentially pure dolomite. The approximate iron (Fe) content of the stones ranged from 15 to 377 mg Fe/100g and the approximate aluminum content (Al) from 1 to 134 mg Al/100g. A heterogeneous reaction model for mineral dissolution effectively explained the results of the rotating disk experiments for all samples except the two with the highest dolomite content. The magnitude of the dissolution rate constant for fresh stone decreased by approximately 60% as the calcite content of the stone decreased from 0.92 to 0.09 g CaCO 3 /g stone. The rate of dissolution of stones with a high dolomite content may have been enhanced by the presence of small amounts of cal-cite. The rate of solubilization of magnesium (Mg) was negligible in all samples except the two with the highest dolomite content (93 and 100 mass percent dolomite). The overall dissolution rate constant decreased as the amount of calcium dissolved from the surface of the stone increased. For a given amount of calcium dissolved per unit area of stone surface, the magnitude of the percentage decrease in the dissolution rate constant increased as the iron and aluminum content of the stone increased. The effect of sample aging on the rate of dissolution was lowest when the weighted sum of the iron and aluminum content of the stone was less than about 10 mg/g. The weighted sum is equal to the aluminum content in mg Al/g plus 0.30 times the iron content in mg Fe/g. The presence of silica as the principal impurity in the white marble seemed to reduce the effective (cal-cite) surface area of the stone in proportion to the mass of silica in the sample, but …
An Empirical Study of the Applications of Data Mining Techniques in Higher Education

Few years ago, the information flow in education field was relatively simple and the application of technology was limited. However, as we progress into a more integrated world where technology has become an integral part of the business processes, the process of transfer of information has become more complicated. Today, one of the biggest challenges that educational institutions face is the explosive growth of educational data and to use this data to improve the quality of managerial decisions. Data mining techniques are analytical tools that can be used to extract meaningful knowledge from large data sets. This paper addresses the applications of data mining in educational institution to extract useful information from the huge data sets and providing analytical tool to view and use this information for decision making processes by taking real life examples. In modern world a huge amount of data is available which can be used effectively to produce vital information. The information achieved can be used in the field of Medical science, Education, Business, Agriculture and so on. As huge amount of data is being collected and stored in the databases, traditional statistical techniques and database management tools are no longer adequate for analyzing this huge amount of data. Data Mining (sometimes called data or knowledge discovery) has become the area of growing significance because it helps in analyzing data from different perspectives and summarizing it into useful information. (1) There are increasing research interests in using data mining in education. This new emerging field, called Educational Data Mining, concerns with developing methods that discover knowledge from data originating from educational environments (1). The data can be collected from various educational institutes that reside in their databases. The data can be personal or academic which can be used to understand students' behavior, to assist instructors, to improve teaching, to evaluate and improve e-learning systems , to improve curriculums and many other benefits. (1)(2) Educational data mining uses many techniques such as decision trees, neural networks, k-nearest neighbor, naive bayes, support vector machines and many others. (3) Using these techniques many kinds of knowledge can be discovered such as association rules, classifications and clustering. The discovered knowledge can be used for organization of syllabus, prediction regarding enrolment of students in a particular programme, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students and so on. This paper is organized as follows: Section II describes the related work. Section III describes the research question. Section IV describes data mining techniques adopted. Section V discusses the application areas of these techniques in an educational institute. Section VI concludes the paper.
Empirical Cross-Sectional Asset Pricing

I review recent research efforts in the area of empirical cross-sectional asset pricing. I start by summarizing the evidence on cross-sectional return predictability and the failure of standard (consumption) CAPM models and their conditional versions to explain these predictability patterns. One response in part of the recent literature is to focus on ad-hoc factor models, which summarize the cross-section of expected returns in parsimonious form, or on production-based approaches, which suggest links between firm characteristics and expected returns. Without imposing restrictions on investor preferences and beliefs, neither one of these two approaches can answer the question why investors price assets the way they do. Within the rational expectations paradigm, recent research that imposes such restrictions has focused on the ICAPM, long-run risks models, as well as frictions and liquidity risk. Approaches based on investor sentiment have focused on the development of empirical proxies for sentiment and for the limits to arbitrage that allow sentiment to affect prices. Empirical work that considers learning and adaptation of investors has worked with out-of-sample tests of cross-sectional predictability.
Capturing Business Strategy and Value in Enterprise Architecture to Support Portfolio Valuation

This paper investigates and enhances the suitability of the Archi Mate enterprise architecture modeling language to support the modeling of business strategy concepts and architecture-based approaches to IT portfolio valuation. It gives an overview of existing strategy and valuation concepts and methods in the literature and motivates the need for enterprise architecture and business requirements modeling to capture these aspects as well. This overview results in the identification of strategy and value related concepts, such as value, risks, resources, capabilities, competencies and constraints. The paper provides an analysis of the extent to which Archi Mate may support some of the above-mentioned concepts and extends it with the missing concepts. The proposed language extension is formalized in terms of a met model fragment, which is aligned with the Archi Mate metamodel. The approach is also illustrated by means of an application portfolio consolidation case study in which we demonstrate how a constrained optimization valuation method can be applied to architecture models enhanced with the new concepts.
Learning Disability Identification Criteria and Reporting in Empirical Research: A Review of 2001–2013

This review documents the learning disabilities (LD) identification criteria and procedures utilized in empirical research including students with LD published from 2001 to 2013 in three journals dedicated to the study of LD. Results reveal several troublesome findings related to transparency in reporting and the coherence of the LD construct. Nearly one–third of all empirical studies investigating LD did not describe who identified the participants as having LD or how they were identified. Information on the specific area of LD was similarly lacking. Across studies, identification criteria varied widely. Moving forward, we contend that greater transparency and consistency with regard to the definition and operationalization of the construct of LD in empirical research is necessary if solidification of the scientific construct of LD is to be achieved.
Beyond high school : An examination of Hispanic educational attainment

Low educational attainment has been a barrier to the advancement of Hispanic Americans in the United States, and a number of explanations for this have been suggested. One group of explanations centers around Hispanic Americans' use and exposure to English. A second group of explanations focuses more on socioeconomic disadvantages facing this population. Much of the research that looks at educational attainment among Hispanic Americans, however, does not consider Hispanic group differences. This research used the National Education Longitudinal Study, a stratified probability sample of approximately 24,000 students, to examine educational attainment among the 6,294 White non-Hispanic, and 492 Mexican, Cuban, and Puerto Rican youth included in all four waves of the survey. The results suggest the importance of both the diversity of the Hispanic population and socioeconomic factors in explaining participation in postsecondary education. Effective policies targeted toward Hispanic educational attainment need to address economic circumstances of these students rather than focus primarily on language deficiencies or immigration status
Two case studies illustrating how relatively selective hippocampal lesions in humans can have quite different effects on memory

Two patients, with magnetic resonance imaging (MRI)‐confirmed relatively selective hippocampal damage, showed distinct patterns of performance on tests of recall, item recognition, and associative recognition. Patient AC showed a mean bilateral volume reduction of the hippocampus of 28%, but displayed no memory deficit. Both recall and recognition memory were unimpaired. In contrast, patient PR, who showed a mean bilateral hippocampal volume reduction of 59%, was more consistently impaired on recall than recognition tests, although his recognition scores were highly variable. Patients AC and PR illustrate how variable the memory deficit following seemingly selective hippocampal damage can be in humans. They highlight the need for more sophisticated imaging in future studies if the human hippocampus' role in memory is to be fully identified. © 2008 Wiley‐Liss, Inc.
“If We Become Friends, Maybe I Can Change My Perspective: ” Intergroup Contact, Endorsement of Conflict Narratives, and Peace-Related Attitudes in Turkey

Positive intergroup contact is effective in reducing prejudice in both high- and low-status groups. However, it is important to study the impact of contact between groups in conflict-ridden societies on additional outcomes, such as attitudes toward reconciliation and peace-related policies. The current conditions in Turkey offer the opportunity to study the relations between intergroup contact, endorsement of conflict narratives, and peace-related attitudes in 3 different groups: (a) the ethnic majority (Turks); (b) a subgroup within the ethnic majority who feel excluded due to their political preferences (i.e., participants in the recent Gezi Park protests who developed a common identity as “çapulcu” [looter]); and (c) the ethnic minority (Kurds). Bivariate correlations and multigroup path analysis suggested that intergroup contact may not lead majority-status groups to support prominority conflict narratives, but may lead them to support prominority policies, whereas it may lead majority-status groups who feel excluded to support both prominority narratives and policies. Results also indicated that contact may be counterproductive for minority groups by altering their endorsement of specific conflict narratives, which then reduces their support for changes that would benefit their group.
Risk Perceptions and Risk Management Strategies in French Oyster Farming

The article analyses risk perception in shellfish farming as well as farmers' willingness to rely on coverage mechanisms. Factor and econometric analyses (logit and ordered multinomial logit models) have shown that a number of socio-economic factors specific to farmers and their businesses contribute to defining their degree of risk perception and reliance on management tools. Beyond the conventional self-protective mechanisms, the study will focus on farmers' willingness to rely on risk-transfer mechanisms that the market has so far failed to provide.
ovement patterns in leiopelmatid frogs : Insights into the locomotor epertoire of basal anurans

Movements and locomotor behaviour were studied in the most basal living frog family (Leiopelmatidae: Ascaphus + Leiopelmatidae), which includes two stream-dwelling species and several that have transitioned into terrestrial niches. These cryptic frogs remain immobile over 99.6% of the time above ground as they sit in wait of prey and only rarely use jumping to escape. Walking is their primary mode of locomotion. The two stream species, which are separated by deep time and extreme geographic distance, have nearly identical behavioural repertoires and locomotor performance, which included occasional jumping as a means to change foraging positions. The terrestrial species, one of which has become semi-arboreal, rarely jump in nature and rely on chemical and postural antipredator behaviours to avoid predation. If
Constraints of Tones, Vowels and Consonants on Lexical Selection in Mandarin Chinese

Previous studies have shown that when speakers of European languages are asked to turn nonwords into words by altering either a vowel or consonant, they tend to treat vowels as more mutable than consonants. These results inspired the universal vowel mutability hypothesis: listeners learn to cope with vowel variability because vowel information constrains lexical selection less tightly and allows for more potential candidates than does consonant information. The present study extends the word reconstruction paradigm to Mandarin Chinese–a Sino-Tibetan language, which makes use of lexically contrastive tone. Native speakers listened to word-like nonwords (e.g., su3) and were asked to change them into words by manipulating a single consonant (e.g., tu3), vowel (e.g., si3), or tone (e.g., su4). Additionally, items were presented in a fourth condition in which participants could change any part. The participants’ reaction times and responses were recorded. Results revealed that participants responded faster and more accurately in both the free response and the tonal change conditions. Unlike previous reconstruction studies on European languages, where vowels were changed faster and more often than consonants, these results demonstrate that, in Mandarin, changes to vowels and consonants were both overshadowed by changes to tone, which was the preferred modification to the stimulus nonwords, while changes to vowels were the slowest and least accurate. Our findings show that the universal vowel mutability hypothesis is not consistent with a tonal language, that Mandarin tonal information is lower-priority than consonants and vowels and that vowel information most tightly constrains Mandarin lexical access.
Novel Quantization Schemes for Very Low Bit Rate Video Coding Based on Sample Adaptation

In this report, we introduce a novel feed-forward adaptive quantization scheme called SAPQ (sampleadaptive product quantizer) as a structurally constrained vector quantizer. SAPQ is based on a concept of adaptive quantization t o the varying samples of the source and is very different, from traditional adaptation techniques for non-stationary sources. SAPQ quantizes each source sample using a sequence of quantizers. Even when using scalar quantization in SAPQ, we can achieve perforrnance comparable to vector quantization (with the complexity still of the order of scalar quantization). We also show that important lattice based vector quantizers can be constructed using scalar quantization in SAPQ with several examples. We asymptotically analyze SAPQ and propose a simple algorithm to implement it. We numerically study SAPQ for independent, and identically distributed Gaussian and I;aplacian sources. Through our numerical study, we find that SAPQ using scalar quantizers achieves typical gains of 1 3 dB in distortions over the Lloyd-Max quantizer. By employing SAPQ, we have extensively conducted image compressions. We considered a uniform quantizer for the current H.263 standard and a nonuniform quantizer for the differential pulse code modulation for images. We also show that a generalized SAPQ can be used in conjunction with vector quantizers to further improve the gains, especially for high correlated image signals a t large vector dimensions. Finally, the error-resilient aspect of SAPQ is also investigated. We find that SAPQ is robust to the channel noise, while achieving gains.
Attenuated Listeria monocytogenes: a powerful and versatile vector for the future of tumor immunotherapy

For over a century, inactivated or attenuated bacteria have been employed in the clinic as immunotherapies to treat cancer, starting with the Coley's vaccines in the 19th century and leading to the currently approved bacillus Calmette-Guérin vaccine for bladder cancer. While effective, the inflammation induced by these therapies is transient and not designed to induce long-lasting tumor-specific cytolytic T lymphocyte (CTL) responses that have proven so adept at eradicating tumors. Therefore, in order to maintain the benefits of bacteria-induced acute inflammation but gain long-lasting anti-tumor immunity, many groups have constructed recombinant bacteria expressing tumor-associated antigens (TAAs) for the purpose of activating tumor-specific CTLs. One bacterium has proven particularly adept at inducing powerful anti-tumor immunity, Listeria monocytogenes (Lm). Lm is a gram-positive bacterium that selectively infects antigen-presenting cells wherein it is able to efficiently deliver tumor antigens to both the MHC Class I and II antigen presentation pathways for activation of tumor-targeting CTL-mediated immunity. Lm is a versatile bacterial vector as evidenced by its ability to induce therapeutic immunity against a wide-array of TAAs and specifically infect and kill tumor cells directly. It is for these reasons, among others, that Lm-based immunotherapies have delivered impressive therapeutic efficacy in preclinical models of cancer for two decades and are now showing promise clinically. In this review, we will provide an overview of the history leading up to the development of current Lm-based immunotherapies, the advantages and mechanisms of Lm as a therapeutic vaccine vector, the preclinical experience with Lm-based immunotherapies targeting a number of malignancies, and the recent findings from clinical trials along with concluding remarks on the future of Lm-based tumor immunotherapies.