Miracle-dz/UniFAR-FTUs huggingface dataset:
SELL DEEP? SELL WIDE? OR BOTH? PERCEIVED QUALITY AND PRODUCT SCOPE OF CHINESE EXPORTERS OF ELECTRICAL PRODUCTS

There is a surging trade literature on multi-product exporters who account for a disproportionally large share of total exports. On the other side, it is also well known that new exporters usually start small and many with a single product. In this paper, I bring the two bodies of literature, one on multi-product exporters and one on the post-entry dynamics, together to study how single-product exporters evolve into multi-product exporters, with special attention to the role of perceived quality in this process. I use the detailed price and quantity information on firms’ exports between 2000 and 2006 from China’s customs data to recover the latent quality as residuals from marketand product-specific demand functions for China’s exports. A cross-sectional comparison reveals that relative to a single-product exporter, a multi-product exporter has quality premium in its core products, but quality discount in its peripheral products. But overtime within a firm-destination-product cell, the perceived quality is positively correlated with an exporter’s product scope, which I argue is mainly driven by the addition of new product lines at the exact time when the existing products get well accepted by the market. A trade model of heterogeneous firms self-selecting into exporting markets with an once-andfor-all draw of firmor firmand product-specific productivity that abstracts away from the process of learning and gradual resolution of uncertainty on the demand side cannot generate these patterns. JEL Classifications: F12, F14, O12, O14.
Validation of the GOAL questionnaire: an outcome measure for ambulatory children with cerebral palsy

Validation of the GOAL questionnaire: an outcome measure for ambulatory children with cerebral palsy U NARAYANAN, R MOLINE, C ENCISA, C YEUNG, S WEIR The Hospital for Sick Children, Holland Bloorview Kids Rehabilitation Hospital, University of Toronto, Toronto, ON, Canada; University of Waterloo, Toronto, ON, Canada; Child Health Evaluative Sciences, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada; McMaster University, Toronto, ON, Canada; Child Health Evaluative Sciences, The Hospital for Sick Children, Toronto, ON, Canada
Neurocognitive stability in Asperger syndrome, ADHD, and reading and writing disorder: a pilot study

Boys with Asperger syndrome (n=20), attention‐deficit‐hyperactivity disorder (n=20), and reading and writing disorder (n=20) were followed up and retested on several neuropsychological measures 1 to 2 years after initial assessments. Wechsler Intelligence Scale for Children (WISC‐III) Full Scale, Verbal, and Performance IQ scores remained stable for all diagnostic groups. Kaufman factors and ‘fluid’ and ‘crystallized’ abilities were also stable measures. Subtest stability over time, was slightly more variable. There was a tendency for the group with Asperger syndrome to deteriorate over time with respect to logical reasoning abilities. Measures of executive function/attention (‘go‐no‐go’ and ‘conflict’ tests) showed good test‐retest stability in all diagnostic groups. This is the first study of its kind.
Jovian Magnetospheric Plasma and Energetic Particle Interaction with Ganymede’s Magnetic Field and Surface

The Galileo Orbiter flybys of Ganymede revealed a rich variety of features associated with the newly discovered intrinsic dipolar magnetic field of Ganymede. Dropouts in plasma flows clearly indicated transitions from Jovian to Ganymedian magnetospheric domains. Transitions from open polar to closed field lines were probed by directional distributions of energetic particles. Numerical modeling predicted strong magnetic shielding of the equatorial region against penetration by energetic electrons and protons below 10 MeV. We review comparisons of time histories, moments, and directional distributions for data from the Galileo Plasma Spectrometer (PLS) and Energetic Particle Detector (EPD) instruments to survey these magnetic and surface interaction features. The earlier numerical models for particle penetration to the surface in the open and closed field regions are updated from parameters provided by the combined analysis. Orbit phase variations and time-averages of penetrating particle energy fluxes are modeled for orbiting spacecraft such as the planned Juice Icy Moons Explorer (JUICE).
A CMOS Electrochemical Biochip With 32×32 Three-Electrode Voltammetry Pixels

A CMOS-integrated electrochemical biochip for high-performance molecular testing is presented. The system includes an array of 32×32 three-electrode voltammetry pixels and on-chip temperature control between 25 and 95 ◦C. Each 100 μm ×100 μm pixel includes a CMOS-compatible and chemo-stable amorphous carbon electrode transducer connected to in-pixel current detection circuitry with 280 fA rms input-referred noise (0.1–20 Hz bandwidth) and 93 dB dynamic range (DR). Array-based DNA detection assays are implemented, and successful DNA melt-analysis and real-time label-free DNA hybridization detection are reported.
Point cloud surface reconstruction and image segmentation by level set method

In this work, we deal with the problem of surface reconstruction from 3D point cloud data and the segmentation of 3D images. For these tasks, we apply a mathematical model and numerical method based on the level set algorithm. This method solves the advection equation with a curvature term, which gives the evolution of an initial condition to the ﬁnal state. For surface reconstruction, the advective velocity can be deﬁned as the gradient of the distance function calculated to the point cloud data. The 3D images contain complicated structures without clear boundaries for which automatic segmentation may not give useful results. We use manually identiﬁed point cloud data to distinguish the subvolumes of the image we want to segment. Combining the information of the point cloud data with the 3D image intensity we can deﬁne the advective velocity of the level set equation for image segmentation as the weighted sum of distance function and edge detector function gradients. The edge detector function is applied to the presmoothed 3D image. For the calculation of the distance function, we compare the fast sweeping method, the vector distance transform algorithm, the fast marching method, and the Dijkstra-Pythagoras algorithm, and propose how to modify the fast sweeping method and the vector distance transform algorithm for ﬁnding the middle surface between different shapes. For the numerical discretization, we use a semi-implicit co-volume scheme in the curvature part and an implicit upwind scheme in the advective part. The method was tested on representative examples and applied to real data. For surface reconstruction, we used data representing archaeological ﬁnds and for tissue segmentation microscopic 3D images.
Can artificial intelligence help predict a learner’s needs? Lessons from predicting student satisfaction

The successes of using artificial intelligence (AI) in analysing large-scale data at a low cost make it an attractive tool for analysing student data to discover models that can inform decision makers in education. This article looks at the case of decision making from models of student satisfaction, using research on ten years (2008–17) of National Student Survey (NSS) results in UK higher education institutions. It reviews the issues involved in measuring student satisfaction, shows that useful patterns exist in the data and presents issues involved in the value within the data when they are examined without deeper understanding, contrasting the outputs of analysing the data manually, and with AI. The article discusses risks of using AI and shows why, when applied in areas of education that are not clear, understood and widely agreed, AI not only carries risks to a point that can eliminate cost savings but, irrespective of legal requirement, it cannot provide algorithmic accountability.
A Systematic Review of Ten Years of Research on Human Interaction with Social Robots

ABSTRACT While research and development related to robotics has been going on for decades, the past decade in particular has seen a marked increase in related efforts, in part due to technological advances, increased technological accessibility and reliability, and increased commercial availability. What have come to be known as social robots are now being used to explore novel forms of human-robot interaction, to understand social norms, and to test expectations and human responses. To capture the contributions of these research efforts, identify the current trends, and future directions, we systematically review 10 years of research in the field of social robotics between 2008 and 2018, which includes 86 publications with 70 user studies. We classify the past work based on the research topics and application areas, and provide information about the publications, their user studies, and the capabilities of the social robots utilized. We also discuss selected papers in detail and outline overall trends. Based on these findings, we identify some areas of potential future research.
Probing a Semantic Dependency Parser for Translational Relation Embeddings

Translational relation models are primarily applied to the task of Knowledge Graph embedding. We present a structural probe for testing whether a state-of-the-art semantic dependency parser learns contextualized word representations which ﬁt a translational relation model. We ﬁnd that the parser does not explicitly learn a translational relation model. We do, however, ﬁnd that a simple transformation of the word representations is enough to induce a TransE model with 73.45% label recall, indicating that translational relation models are at least implicitly learned by the parser. We believe that our ﬁndings can in the future be used to develop new Natural Language Understanding systems that are more useful for Knowledge Graph generation and completion.
Story Fragment Stitching: The Case of the Story of Moses

We introduce the task of story fragment stitching , which is the process of automatically aligning and merging event sequences of partial tellings of a story (i.e., story fragments ). We assume that each fragment contains at least one event from the story of interest, and that every fragment shares at least one event with another fragment. We propose a graph-based unsupervised approach to solving this problem in which events mentions are represented as nodes in the graph, and the graph is compressed using a variant of model merging to combine nodes. The goal is for each node in the ﬁnal graph to contain only coreferent event mentions. To ﬁnd coref-erent events, we use BERT contextualized embedding in conjunction with a tf-idf vector representation. Constraints on the merge compression preserve the overall timeline of the story, and the ﬁnal graph represents the full story timeline. We evaluate our approach using a new annotated corpus of the partial tellings of the story of Moses found in the Quran, which we release for public use. Our approach achieves a performance of 0.63 F 1 score.
Analysis of Proteinuria in Health and Disease Using Sodium Dodecyl Sulphate—Acrylamide Gel Electrophoresis

Abstract. Sodium dodecyl sulphate—acrylamide gel electrophoresis (SDS‐AGE) separates proteins according to their molecular weight (MW) without being influenced by their electrostatic charge. It was carried out on the urine of 17 healthy control subjects and 92 ambulatory patients with suspected or known renal impairment. The SDS‐AGE patterns were classified as physiological, low MW predominance, middle MW predominance, high MW predominance, or mixed low and high MW. Patients were separately classified as having either normal kidneys or glomerular, tubular or mixed renal lesions according to the results of clinical investigation. Comparison of both classifications revealed that SDS‐AGE allowed a correct diagnosis of the site of renal involvement in 83 per cent of cases. Predominantly low MW protein excretion correlated with tubular damage. Middle and high MW patterns correlated with glomerular disease, and a relationship between nephrotic syndrome with minimal glomerular changes and middle MW pattern was found in two cases, suggesting that SDS‐AGE could be used to evaluate the selectivity of proteinuria. However, the estimation of selectivity by SDS‐AGE should be studied in a sufficient number of cases and compared with measurements of selectivity by the protein clearance method.
A tutorial on ﬁtting discrete response models in high-dimensional datasets with the countgmifs package

In this tutorial we describe our countgmifs R package, available from the Comprehensive R Archive Network, that can ﬁt Poisson and negative binomial models when the number of predictors ( P ) exceeds the sample size ( N ). We then illustrate the functions in the countgmifs R package using simulated data.
Smoothed Analysis of Local Search

Local search is a powerful paradigm for ﬁnding good solutions to intractable combinatorial optimization problems. However, for many local search heuristics there exist worst-case instances on which they are extremely slow or provide solutions that are far from optimal. Smoothed analysis is a semi-random input model that has been invented to bridge the gap between poor worst-case and good empirical performance of algorithms. In smoothed analysis, an adversary picks an arbitrary input, which is then slightly randomly perturbed. In particular, smoothed analysis has been applied successfully to local search algorithms in a variety of cases. We use the 2-opt heuristic for the traveling salesman problem and the k -means method for clustering as examples to explain how local search heuristics can be analyzed in the framework of smoothed analysis. For both algorithm, as for many other local search algorithms, the worst-case running time is exponential in the input size, but polynomial in the framework of smoothed analysis.
Combinatorial Applications of Grassmann Algebra on Laplacian Matrices and Subgraph Enumerations

In the field of graph theory, Laplacian matrices corresponding to graphs prove useful in deriving graph properties. Grassmann algebra and the Berezin integral, devised for integrating fermionic fields, possess combinatorial properties via exponential generating functions. In this paper, we integrate Grassmann polynomials to formulate expressions for the determinant and permanent of Laplacian matrices. After deriving an alternate proof of Kirchhoff’s Theorem, we introduce modifications to the Grassmann algebra; this allows us to evaluate the Laplacian permanent and construct an alternative proof for its enumeration of bipartite subgraphs. We then generalize this enumeration to submatrices and modify the Laplacian to generalize enumerated subgraphs to an even greater extent. These computations possess applications in graphical situations involving high levels of connectivity; specifically, the bijection between even-cycled graphs and bipartite graphs is key for specific data structures. Our results prove especially ideal in formulating an efficient method in computing paths and cycles within complex biological interaction graphs. Our paper presents a rigorous set of applications for Grassmann algebra in order to derive properties of Laplacian permanents, which are widely believed to be too difficult to calculate and impractical to use, and to count specific and applicable subgraphs.
Temperature dependent 2,3-dihydroxybenzoic acid production in Acinetobacter sp. B-W

A soil microorganism producing iron chelator (siderophore) under low iron stress (up to 2 μM of iron) was identified as Acinetobacter sp. B-W by 16S rDNA sequence analysis, biochemical-, physiological tests and morphological analysis using electron microscope. Catechol nature of siderophore was detected by Arnow test. Although optimal cell growth was identified at 36°C in iron-limited media, significant quantities of siderophore were produced only at 28°C. Biosynthesis of siderophore was strongly inhibited by growth at 36°C. Production of siderophore was completely inhibited by 10 μM FeCl3. Iron chelator produced from Acinetobacter sp. B-W was purified from supernatant using butanol extraction, Sephadex LH-20 column chromatography and HPLC. Purified sideropore was identified as 2,3-dihydroxybenzoic acid by HPLC, TLC and IR analysis.
Supervised Machine Learning Model-Based Approach for Performance Prediction of Students

Predicting students’ performance is one of the crucial issue for learning contexts, since it helps to develop alternative recommendation systems for academically weak students. Thus, several methods and practices have been applied for educational improvement. However, most of the existing methods do not determine the performance of the students. In this study, we have studied the execution of six machine learning models (Decision tree, Random Forest, Support Vector Machine, Logistic Regression, Ada Boost, Stochastic Gradient Descent) to analyze and evaluate the students’ achievements. The performance is evaluated in term of accuracy, precision, sensitivity and f-measure. Among the selected models, the results validate that the efficiency of Stochastic Gradient Descent is better in training small dataset. In addition, it also produces the higher accuracy as compared with other models. This contribution aims to develop the best model which may derive the conclusion on students' academic achievement.
Evaluation of the Sealing Ability of Mineral Trioxide Aggregate, Biodentine, Bone Cement used in the Retro Cavities Prepared with two types of Ultrasonic Retro Tips-A Comparative In Vitro Study

Original Research Article The aim of this study is to compare the sealing ability of three retro filling materials; Mineral Trioxide Aggregate, Biodentine and Bone Cement and to compare the effect of two different ultrasonic retro tips; stainless steel and diamond coated on the sealing ability of these materials. Sixty human mandibular premolars were decoronated and root canal treatment was performed. 3 mm of root apex was resected at 90 0 to the long axis of root were randomly divided into two groups of 30 specimens each. Retro cavity was prepared with stainless steel retro tips in group I and in group II using diamond coated tip. Subgroups IA and IIA were filled with Mineral trioxide aggregate (n = 10), Subgroups IIA and IIB were filled with Biodentine (n=10) and subgroups IC and IIC were filled with Bone Cement (n=10). The teeth were sectioned longitudinally through the centre after immersion in Rhodamine B solution. The sections were visualised under confocal laser scanning microscope for depth of dye penetration. Results: Biodentine showed least dye penetration followed by MTA and Bone Cement. Diamond coated retro tips performed better than stainless steel retro tips. Conclusion: Biodentine group showed excellent sealing ability than MTA and Bone Cement. Diamond coated retro tip groups showed least leakage than stainless steel retro tip groups.
High refractive polymer materials based on the silicon

For developing THz technologies transparent materials with controllable refractive index are requested. We create such materials by incorporation of micro-and nano particles of high refractive semiconductors into a transparent polymer. With THz time-domain spectroscopy composite materials based on nano-and micro-particles of silicon are investigated. The ultimate achievable value of absorption, refraction and scattering, as well spectral tuning due to laser illumination are discussed. Keywords—nanoparticles; silicon; terahertz; refraction; scattering; plasma frequency
Dated phylogenies and historical biogeography of Dontostemon and Clausia (Brassicaceae) mirror the palaeogeographical history of the Eurasian steppe

We hypothesize that molecular signals in Eurasian steppe plants reflect their biogeographical history as well as the climate/landscape history of the Eurasian steppe. To test this hypothesis we focus here on the characteristic Eurasian steppe genera Dontostemon and Clausia (Brassicaceae), and have included all presently accepted species in our study.
Protective effect of Cupressus macrocarpa and Dioon edule against gentamicin-induced nephrotoxicity in rats

Context: It has been reported that Cupressus macrocarpa Hartw. ex Gordon (Cupressaceae) and Dioon edule Lindl. (Zamiaceae) contain compounds with antioxidant and anti-inflammatory effects; therefore, they may exert a nephroprotective effect. Aims: To explore the renoprotective effect of C. macrocarpa and D. edule and the underlying molecular mechanisms. Methods: Ten male Wister rats were used for each group of control (1% CMC in saline), gentamicin (GM, 40 mg/kg), D. edule leaves methanol extract (DLM), C. macrocarpa leaves combined petroleum ether and methanol extract (CLEM) and C. macrocarpa roots methanol extract (CRM). Rats were orally administered the extracts (250 mg/kg) daily concomitantly for 9 days with GM. Evaluation of kidney function, histopathology and measuring renal AMPK-α1, NF-κB and iNOS genes expression were carried out. There were no symptoms of systemic adverse effects in any treated group. Results: Blood urea nitrogen (mg/dL) was significantly reduced by CLEM (24.0 ± 1.205) and CRM (22.889 ± 1.250). Creatinine (mg/dL) was significantly decreased by CLEM (0.59 ± 0.022) and CRM (0.580 ± 0.029). Gene expression of AMPK-α1 enhanced by CLEM (16.717 ± 0.430), CRM (19.18 ± 0.871), DLM (0.417 ± 0.020). iNOS was downregulated by CLEM (0.9 ± 0.056), CRM (1.53 ± 0.044), and DLM (1.642 ± 0.050). NF-κB was decreased by CLEM (1.148 ± 0.076), CRM (0.918 ± 0.065), and DLM (1.783 ± 0.071). CRM and CLEM exhibited normal to mild renal degeneration and mild to moderate expression of iNOS. Conclusions: C. macrocarpa extracts exhibited significant renoprotective effect and could be considered as a new promising strategy against renal complications.
Design, Simulation and Comparison of Controllers for Temperature Profile Tracking Control of a Heat Flow System

Bu makalede, isi-akis sistemine uygulanan uc farkli kontrolcunun tasarimi, simulasyonu ve performans karsilastirmasi sunulmustur. Ilk olarak, isi-akis sisteminin dinamik modeli elde edilmis ve devaminda isi kontrolunu gerceklestirmek icin kayan kipli kontrol (KKK), adaptif kayan kipli kontrol (AKKK) ve adaptif kesir dereceli kayan kipli kontrol (AKDKKK) yontemleri tasarlanmis ve uygulanmistir. Tasarlanan kontrolculerin performansini analiz etmek icin Matlab/Simulink programi araciligiyla isi–akis sisteminin simulasyonu olusturulmus ve tasarlanan kontrolculerin performansi analiz edilmistir. Simulasyon ortamindan elde edilen referans sicaklik takip hatasi, adaptasyon kazanci, ani degisimlere karsi kontrolcunun tepkisi, maksimum asim, yukselme ve yerlesme zamani gibi sonuclar sunulmus ve elde edilen sonuclardan AKDKKK’nun diger kontrolculere gore referans sicakligi daha az hata ile takip ettigi, daha dusuk asim, yukselme ve yerlesme zamanina sahip oldugu gozlemlenmistir. Ayrica, KKK uygulandiginda en yuksek referans sicaklik takip hatasi, yukselme ve yerlesme zamanina sahip oldugu gozlemlenmistir.
Color responses of the human lateral geniculate nucleus: selective amplification of S‐cone signals between the lateral geniculate nucleus and primary visual cortex measured with high‐field fMRI

In the published paper of Mullen et al. (2008) there was an error in the title (‘nucleus’ was spelt incorrectly). The correct title is given here. Also in the last sentence of the second paragraph of the results, the abbreviation ‘RG’ was incorrectly printed as ‘Rt’. The corrected sentence reads: ‘Thus, a key feature of the comparison of the responses between the LGN and V1 is a marked increase in the BY response relative to the RG and Ach, which occurs for both ring and check stimuli’. We apologise for any inconvenience caused.