Miracle-dz/UniFAR-FTUs huggingface dataset:
The Relationship between theDimensions of the “Measurements inthe Addictions for Triage andEvaluation” (MATE) Questionnaireand Personality Disorders - Possible risk profiles

Objective: The purpose of this study was to develop a model to predict the presence of personality disorder traits in general, as well as per cluster, using the total scores of the MATE. Methods: The sample consisted of 102 patients registering for treatment at Tactus Addiction Treatment. During the 90-minute intake session, the MATE was administered. The SIDP-IV was administered in the second session. Because of the low prevalence of personality disorders in the sample (23%), a dimensional score was conducted for personality disorder traits in general, cluster A traits, cluster B traits, and cluster C traits. Variables that showed a relationship (p<.05) with the percentage of present personality disorder traits and variables that were in accordance with the hypotheses were included in a multivariate linear regression model. This was done for all four dependent variables separately. Subsequently, variables that did not remain independent predictors of present personality disorder traits were one by one removed. Results: The optimal predictive model (comprising the MATE total scores), after excluding non-significant predictors, consisted of depression (β=.394, p<.001) and personality (β=.340, p<.001). Overall, 34.8% of the variance of present personality disorder traits was explained by these variables (p<.001). After excluding non-predictive variables in the stepwise multiple linear regression method, the optimal model consisted of psychiatric comorbidity (β=.254, p=.008) and personality (β=.288, p=.003). In total, this model explained 17.2% of the variance in the percentage of present cluster A traits (p<.001) which indicated that the model explains present cluster A traits inadequately. The optimal model of cluster B traits consisted of depression (β=.223, p=.022), anxiety (β=.304, p=.002), and personality (β=.209, p=.023) after the exclusion of all non-predictive variables. The model explained 30.5% of the variance in the percentage of cluster B personality traits. For cluster C traits, the optimal model was composed of depression (β=.358, p<.001) and personality (β=.252, p=.008). Overall, 24.4% of the variance in the present cluster C personality traits was explained by these variables. Conclusion: This study has shown that the MATE possibly provides more information than was thought. It has been proven that the MATE can disclose risk-profiles which might point to a personality disorder. High scores in depression in combination with high personality scores should thus alarm the professionals to perform additional diagnosis for personality disorders.
Thermal Properties of Copper Nickel-Titanium Orthodontic Archwires

THERMAL PROPERTIES OF COPPER NICKEL-TITANIUM ORTHODONITC ARCHWIRES Joshua Gilbert, DMD Marquette University, 2016 Introduction: Copper Nickel-Titanium (CuNiTi) is a relatively new composition of Nickel-Titanium (NiTi) archwires that was originally patented in 1991 as part of the Ormco line of wires. The patent has now recently expired and many other orthodontic companies are making their own CuNiTi wires. Advertisement claims have focused on the laboratory benefits of adding Copper (Cu) to the NiTi, however few independent laboratory testings have been conducted on these new wires to verify claims. The purpose of this study was to conduct thermal analysis of CuNiTi for all currently available wires in two Austenite Finish (Af) variants and two commonly used archwire dimensions. Materials and Methods: Ten as-received wires of 27C and 35C CuNiTi were tested in 0.018” and 0.016” x 0.022” archwire dimensions. The wires examined were Ormco Copper Nickel Titanium (Ormco, Orange, CA, USA), FLI Copper Nickel Titanium (Rocky Mountain Orthodontics, Denver, CO, USA), Copperloy Nickel Titanium (GAC, York, PA, USA), Copper Nitanium (Henry Schein/Ortho Organizers, Carlsbad, CA, USA), Truflex Copper Nickel Titanium (Ortho Technology, Tampa, FL, USA), and Tanzo Copper Nickel Titanium (American Orthodontics, Sheboygan, WI, USA). Segments of archwire were investigated by differential scanning calorimetry over the temperature range from -100C to 100C at 10C per minute. Results: There were significant differences for all values when comparing across different brands in regards to Heating endset, onset, and enthalpy as well as cooling endset, onset, and enthalpy. Some brands were very close to advertised values, however others were as far away as 4C from advertised. In addition the difference between higher and lower Af values were as close as 1.5C for certain brands when expecting 8C. Conclusions: One cannot expect to have CuNiTi wires perform similarly across different brands even when they are of the same Af and archwire dimension. For certain brands there may be very little difference between higher and lower Af variants.
Strategic or Nonstrategic: The Role of Financial Benefit in Bankruptcy

A partial test for strategic behavior in bankruptcy filing may be formulated by testing whether consumers manipulate their debt and filing decision jointly, or not: that is, testing for endogeneity of financial benefit and the bankruptcy filing decision. Using joint maximum likelihood estimation of an extended discrete choice model, test results are consistent with non-strategic filing: financial benefit is exogenous to the filing decision. This result is confirmed in two different datasets (PSID and SCF). This result is consistent with an ex ante low net gain from a bankruptcy filing; a type of “rational inattention” to rare events such as bankruptcy.
Modified SIFT Algorithm for Image Feature Detection

: Image feature detection is the fundamental task in most of the video analytic and computer vision systems. The feature keypoints from the images taken at different instant is detected in these systems. To most of the embedded systems, the challenge is its large complexity in computation. This computational complexities and time consuming properties are eliminated by proposing a new feature detector based on SIFT algorithm. Efficient image feature detection and matching is a fundamental problem in object recognition, image indexing, visual localization etc. The thesis work proposes a new FPGA-based embedded architecture for image feature detection. In this the modified Scale Invariant Feature Transform (SIFT) feature detector is used to reduce the utilization of FPGA resources. An optimized Gaussian filtering is undergone in this design for reducing the memory utilization. The corresponding key-points obtained can be either used in an embedded application or accessed via Ethernet for remotely computer vision applications.
The Allocation of Effort under Uncertainty: The Case of Risk-Averse Behavior

This paper analyzes the labor supply decision of a single economic agent within the expected utility framework. Two formulations of the problem are considered: pure income uncertainty and wage rate uncertainty. In each case, the effects on the labor supply decision of changes in both expected returns and the dispersion of returns (about a constant mean) are investigated. Arguments concerning the "disincentive effects" of uncertainty are shown not to be unambiguously supported by theory.
Object Recognition Using Log-Euclidean Multivariate Gaussian Descriptors

Visual features such as color, texture and shape are used extensively to represent image signatures in content based image retrieval systems (CBIR). The retrieval quality is adequate for some retrieval tasks but there is still a semantic gap between the low-level visual features (textures, shapes, colors) and automatically extracted high-level concepts that users normally search for. We proposed novel approach based on Log-Euclidean Multivariate Gaussian to represent the image visual features efficiently which enjoy the important applications of computer vision. This approach extracts image features using SIFT algorithm and these features again represented using multivariate Gaussian. The resulting descriptors called Log-Euclidean Multivariate Gaussian Descriptors, works well with low and high dimensional raw features. Extensive experiments were conducted to evaluate thoroughly this approach and the result showed that this approach is very competitive in object recognition and classification.
Awakening p53 in vivo by D-peptides-functionalized ultra-small nanoparticles: Overcoming biological barriers to D-peptide drug delivery

Peptides are a rapidly growing class of therapeutics with many advantages over conventional small molecule drugs. Dextrorotary (D)-peptides, with increased enzymatic stability and prolonged plasma half-life in comparison with natural L-peptides, are considered to have great potential as recognition molecules and therapeutic agents. However, the in vivo efficacy of current therapeutic D-peptides is hindered by their inefficient cellular uptake in diseased tissues. Methods: To overcome physiological and cellular barriers to D-peptides, we designed a gold-based ultra-small nanocarrier coupled with polylysine (PLL) and a receptor-targeted peptide to deliver therapeutic D-peptides. Using a D-peptide p53 activator (DPA) as a proof of concept, we synthesized, functionalized and characterized gold- and DPA-based nanoparticles termed AuNP-DPA. Results: AuNP-DPA were effectively enriched in tumor sites and subsequently internalized by cancer cells, thereby suppressing tumor growth via reactivating p53 signaling. More importantly, through a series of in vivo experiments, AuNP-DPA showed excellent biosafety without the common side effects that hinder p53 therapies in clinic trials. Conclusion: The present study not only sheds light on the development of AuNP-DPA as a novel class of antitumor agents for drugging the p53 pathway in vivo, but also supplies a new strategy to use D-peptides as intracellular PPI inhibitors for cancer-targeted therapy.
Meng Wang POLYMER INTEGRATED YOUNG INTERFEROMETERS FOR LABEL-FREE BIOSENSING

Integrated optical (IO) sensor allowing sensitive, label-free, real-time and multi-parameter monitoring of bio-molecular interactions are conventionally fabricated with inorganic dielectrics inherited from CMOS manufacturing technology. Polymers as complement materials to inorganic dielectrics are becoming to have an increasing market share for IO circuits in optical communications networks owing to its good optical properties, versatile processibility and low cost. This work aims at developing disposable low-cost biosensors based mainly on polymeric materials, with a performance comparable to inorganic-dielectric based IO biosensors. This thesis describes the development of polymer IO biosensors based on the Young interferometer (YI) transducer platform for ambient noise compensation and a complete periodic intensity fringe pattern. Three different waveguide configurations were utilized, taking into consideration operational simplicity, fabrication simplicity and enhanced sensitivity. Among the developed polymer biosensors, an unconventional interferometer structure: a vertically placed dual-slab waveguide interferometer and an inverted rib waveguide configuration were employed. To enhance the sensitivity of the waveguides, deposition of Ta2O5 high index coating was performed on the rib waveguide configuration. Along with the development of polymer biosensors based on the inverted-rib waveguide configuration, a fabrication process was also developed featuring UV-imprinting and spin coating. The simple two-step fabrication process demonstrated using a polymer mold is potentially transferable to the roll-to-roll manufacture process. Calibration of the developed sensors was performed by homogeneous refractive index (RI) sensing with glucose de-ionized water solutions. By investigating an antibody – antigen binding interaction involving C-reactive protein and its conjugates, this thesis confirmed the applicability of the developed sensors to specific molecule detection. Moreover, to establish the influence of water molecular absorption on measurement stability, an evaluation was carried out on the polymeric waveguide. Finally, the thesis presented a comparison between the developed sensors, exploring their sensitivities, stabilities, limits of detection (LODs) and other aspects related to operation and fabrication. The results indicated that the Ta2O5-coated polymer waveguide sensor had a high sensing capability. In homogeneous RI sensing, the achieved detection limits were 9×10-7 RIU (refractive index unit), i.e., three times the noise level, and 270 fg/mm2 for surface mass density.
Release of acid phosphatase from extraradical hyphae of arbuscular mycorrhizal fungus Rhizophagus clarus

Abstract Arbuscular mycorrhizal (AM) fungi enhance plant uptake of available phosphorus (P) from soil through their extraradical hyphae. The mechanism underlying this P uptake enhanced by AM fungi is the increase in the surface area for absorption of available P. Little is known about utilization of unavailable P by AM fungi. We investigated whether extraradical hyphae of AM fungi release acid phosphatase (ACP). Sterilized Andosol was packed in pots that were separated into the mycorrhizal and hyphal compartments with a nylon net of 30-μm pore size. Seeds of Allium fistulosum L. were inoculated or uninoculated with the AM fungus Rhizophagus clarus (Nicolson & Schenck) Walker & Schüßler. Mullite ceramic tubes were buried in the soil of each compartment, and soil solution was collected. A. fistulosum L. and Linum usitatissimum L. inoculated with R. clarus were grown in sand culture and in vitro monoxenic culture, respectively. Uninoculated A. fistulosum L was grown in hydroponic culture to collect root exudate. The soil solution, hyphal extracts, root extract and root exudates were subjected to sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis. Shoot P concentration, shoot P content and shoot dry weight were higher in the inoculated treatment than in the uninoculated treatment. Activity staining of the gel revealed that ACP activity at 187 kDa was observed in the soil solution in the inoculation treatment, and in the hyphal extract collected from sand culture and in vitro monoxenic culture, but neither in the root exudate of non-mycorrhizal plant grown in the hydroponic culture nor in the root extracts irrespective of mycorrhizal status. Those results provide strong evidence that the corresponding activity in the soil solutions in soil culture is of R. clarus CK001 origin. These findings suggest that the fungus releases ACP from extraradical hyphae into the hyphosphere.
Insomnia in College Students: Specificities Regarding Psychological Treatment

Cognitive and behavioral techniques for insomnia ́s treatment have solid empirical evidence. Generally, when psychologists treat insomniac college students they face important challenges in the implementation of standard techniques. This paper aims to present a script of cognitive-behavioral therapy for insomnia (CBT-I) adapted to college students based on our clinical experience. We discuss the most frequently strategies recommended for the treatment of insomnia in adults taking into account the adjustments that might be necessary to do in order to maximize its effectiveness and efficiency for a college student population. In the end, we highlight the main points that should be explored in future empirical studies. CBT-I seems to be relevant for treating insomnia in college settings, however, the study of adaptation of the well-known techniques seems necessary to maximize its therapeutic effect.
Technology Platforms in Europe: an empirical investigation

In the last decades, innovation activity has been defined by an increasing complexity and a faster pace of the underlying technological change. Accordingly, several studies have shown that competitive systems of innovation benefit from being able to build upon a wide but integrated spectrum of technological capabilities characterised by a sustained dynamism in the level of inter-sectoral technology flows. In this context, technological platforms – defined as knowledge and scientific launching pads that spin out of key enabling technologies - may create the opportunity for technological externalities to take place across a set of related sectors through a swarm of increasingly applied and incremental innovations. In this report, we look at the presence and determinants of these technological platforms across EU Countries and explore the mechanisms through which these influence inter sectoral technology spillovers, thus fostering technological shifts and technological synthesis within the broader economy. Using data on patents and patent citations obtained from the PATSTAT-CRIOS database, covering all patent applications made to the European Patent Office (EPO), we try to model the systemic nature of technology platforms. In particular, our aim is to provide empirical evidence that the presence of key enabling technologies at the base of the platform may lead to a more sustained interaction across second tier innovations characterised by a “distant” knowledge base. Then, we endeavour to investigate the relationship that may take place between this process and the role played by the national dimension.
Explicit representation of subgrid heterogeneity in a GCM land surface scheme

Abstract A land surface scheme that may be run with or without a tiled representation of subgrid heterogeneity and includes an implicit atmospheric coupling scheme is described. Simulated average surface air temperatures and diurnal temperature ranges in a GCM using this surface model are compared with climatology. Surface tiling is not found to give a clear improvement in the simulated climate but offers more flexibility in the representation of heterogeneous land surface processes. Using the same meteorological forcing in offline simulations using versions of the surface model with and without tiling, the tiled model gives slightly lower winter temperatures at high latitudes and higher summer temperatures at midlatitudes. When the surface model is coupled to a GCM, reduced evaporation in the tiled version leads to changes in cloud cover and radiation at the surface that enhance these differences.
Lexical embedding adaptation for open-domain spoken language understanding

Recently approaches based on word embeddings, i.e. a continuous vector space representation for words, have been used in SLU to overcome the need of annotated corpus by taking advantage of very large collection of unlabeled data to model both semantic and syntactic information. One drawback of embeddings for SLU is the fact that they are usually obtained on very large written text corpora covering generic domains, such as news articles or Wikipedia pages, although SLU systems are dealing with spontaneous speech queries on specific domains. In the standard setting of embedding space usage, two kinds of training corpora are used: a very large unlabeled corpus on which word embeddings are learned, and a smaller in-domain training corpus with gold labels for supervised learning of task specific model. When the in-domain corpus is very specific and represents a different register of language than the unlabeled corpus, a large number of application-specific terms might have no representation in the embedding space. This paper deals with this particular problem of adapting a lexical embedding space to a specific SLU domain. We show that our method outperforms both a baseline using random initialization for unseen vectors and a CRF approach using Part-Of-Speech (POS) and Named Entity (NE) labels for a semantic frame recognition task.
Regeneration of plants from Fraxinus nigra Marsh. hypocotyls

Fraxinus nigra Marsh. (black ash) is a native North American hardwood tree species that is ecologically important and has ethnobotanical significance to American Indian communities of the eastern United States. Black ash has immature embryos at seed set, combined with complex stratification requirements, making natural regeneration difficult. This, combined with the threat and devastation being caused by the emerald ash borer, makes an in vitro adventitious shoot regeneration and rooting protocol imperative for mass propagation, conservation, and genetic improvement of this species.
ScienceDirect International Conference on Computational Modeling and Security ( CMS 2016 ) Integrated Multiple Features for Tumor Image Retrieval Using Classifier and Feedback Methods

The content based image retrieval method greatly assists in retrieving medical images close to the query image from a large database basing on their visual features. This paper presents an effective approach in which the region of the object is extracted with the help of multiple features ignoring the background of the object by employing edge following segmentation method followed by extracting texture and shape characteristics of the images. The former is extracted with the help of Steerable filter at different orientations and radial Chebyshev moments are used for extracting the later. Initially the images similar to the query image are extracted from a large group of medical images. Then the search is by accelerating the retrieval process with the help of Support Vector Machine (SVM) classifier. The performance of the retrieval system is enhanced by adapting the subjective feedback method. The experimental results show that the proposed region based multiple features and integrated with classifier and subjective feedback method yields better results than classical retrieval systems. © 2015 The Authors. Published by Elsevier B.V. Peer-review under responsibility of organizing committee of the 2016 International Conference on Computational Modeling and Security (CMS 2016).
Impacts of climate and farming management on maize yield in southernTanzania

Climate is one of the major factors controlling agricultural productivity in Africa. Changes in meteorological variables such as rising temperatures, changes in precipitation and increase in atmospheric carbon dioxide levels affect crop production. The objective of this study was to evaluate the impacts of climate change and variability, and crop management on yield of maize ( Zea mays L.) grown in the southern part of Tanzania. Using the Decision Support System for Agrotechnology Transfer Cropping System Model (DSSAT-CSM), a series of sensitivity experiments were conducted to evaluate the response of maize yields to a range of principal changes in rainfall and temperatures. The sensitivities were estimated under two management practices, one with traditional farming practices, and the other with application of external farm inputs. Dry-spells during the growing season caused yield losses of all cultivars of up to 43% for the prolonged dry-spells of 20 days. Increased rainfall intensity, during vegetative and reproductive stages, caused the decrease in yield of 5 and 2%, respectively. A 50-100% decrease in rainfall intensity during the growing season caused a loss of yields between 40-100%. Increased or decreased temperatures from the baseline values reduced or increased days to flowering and to physiological maturity, respectively. In addition, a decrease in temperature from the baseline values to 2 o C had an overall impact of yields loss for all cultivars. However, yields increased with an increase of temperature by up to 2.5 °C (UH6303 and H628) and 4.5 °C (PAN691). Growing seasons with lower total rainfall (<50 mm) and temperature (<1°C) from their climatological values, caused yield loss as much as 71 and 15%, respectively for PAN691 cultivar. Generally, the impacts depended on the management, cultivar, soil characteristics, magnitude, timing and duration of the stress. Keywords: DSSAT, rainfall, temperature, Zea mays