Miracle-dz/UniFAR-FTUs huggingface dataset:
Biomechanical considerations: evaluating scleral reinforcement materials for pathological myopia.

OBJECTIVE Scleral biomechanical weakness and thinness are known to be one of the main factors in the pathogenesis of progressive myopia. Posterior scleral reinforcement surgery remains the rational treatment for pathological myopia. We tested the biomechanical properties of 3 types of scleral reinforcement materials (artificial pericardium, human sclera, and all-dermal matrix) in an attempt to select the ideal material for the reinforcement of pathologic sclera. DESIGN Experimental study. PARTICIPANTS Forty-five adult Japanese white rabbits. METHODS Animals were equally divided into 3 groups. For each group, 1 type of material was surgically implanted at the back of the globe. We harvested samples after 10 months of implantation, tested the elasticity modulus for both reinforced sclera and unreinforced control sclera, and assessed data by t test methods. Statistically significant differences were considered when p < 0.05. RESULTS Rabbit sclera reinforced by artificial pericardium or human sclera showed significant increases in the elasticity modulus compared with control eyes. However, the rabbit sclera reinforced by all-dermal matrix showed no significant difference in the elasticity modulus compared with normal controls. CONCLUSIONS The analysis of biomechanical considerations in scleral reinforcement materials presented here is a very helpful method to choose the best materials for treatment of myopia. Of all materials tested, the artificial pericardium and human foreign-body sclera provided the best biomechanical characteristics.
Early and late responses in patients with rheumatoid arthritis who were conventional synthetic disease-modifying anti-rheumatic drug inadequate responders and were treated with tocilizumab or switched to rituximab: an open-label phase 3 trial (MIRAI).

OBJECTIVES To evaluate early and late responses in biological-naïve patients with rheumatoid arthritis (RA) initiating tocilizumab and early tocilizumab non-responders who switched to rituximab. METHODS In this open-label, non-randomised phase 3 study, RA patients with inadequate response to conventional synthetic DMARDs received tocilizumab 8 mg/kg intravenously at study begin and weeks 4, 8 and 12. After evaluation at week 16, early responders (Disease Activity Score based on 28 joints-erythrocyte sedimentation rate [DAS28-ESR] <2.6) completed the study; partial responders (DAS28-ESR decrease >1.2 or DAS28-ESR ≥2.6-≤3.2) were to continue tocilizumab through week 28; non-responders (DAS28-ESR decrease ≤1.2) switched to rituximab (1000 mg, weeks 16 and 18) with safety follow-up through week 66. RESULTS Of 519 patients, 222 (42.8%) achieved early DAS28-ESR remission at week 16; 240 patients continued treatment, 213 (41.0%) received tocilizumab, and 27 (5.2%) switched to rituximab. At week 32 DAS28-ESR remission was achieved by 117/213 patients (54.9%) who continued tocilizumab and 4/27 patients (14.8%) who switched to rituximab; good EULAR response was achieved by 66.7% and 25.9% and CDAI remission by 19.2% and 14.8% of patients, respectively. Serious adverse events occurred through week 32 in 45/490 patients (9.2%) who received tocilizumab (serious infections, 2.7%) and through week 66 in 8/27 patients (29.6%) who switched to rituximab. CONCLUSIONS Early response to tocilizumab was observed in 42.8% of patients. Half of early partial responders benefitted from continuing tocilizumab. Switching non-responders to rituximab seems feasible. No new safety signals were observed in patients treated with tocilizumab or switched to rituximab.
Sample Set Reduction Method Based on Neighborhood Non-Dominated Crowding-Distance Sorting

To remove the redundant samples and reduce sample set size of big data analysis while ensuring classification accuracy, a sample set reduction method based on Neighborhood Non-dominated Crowding-distance Sorting (NNCS) is proposed. The proposed method is based on the idea of neighborhood, in which the distance between the samples of one class and the other classes is taken as the evaluation criterion. Furthermore, optimization algorithm NSGA-II is adapted to select the key samples by non-dominated crowding-distance sorting and the purpose of reducing the sample set is achieved finally. The experimental results on nine UCI standard data sets show that the method has good generalization performance and reduces the sample set size effectively under the premise of fully guaranteed classification accuracy.
Face model adaptation using robust matching and active appearance models

This paper addresses the 3D tracking of pose and animation of the human face in monocular image sequences using deformable 3D models. For each frame, the proposed adaptation is split into two consecutive stages: global and local. In the first stage, the 3D pose of the face is recovered using a RANSAC-based technique involving both the consensus measure and the consistency with a statistical model of a face texture. In the second stage, the local motion associated with some facial features is recovered using the concept of the active appearance model search. Adaptation examples demonstrate the feasibility and robustness of the developed framework.
A New K-Shell Decomposition Method for Identifying Influential Spreaders of Epidemics on Community Networks

Abstract An efficient method for the identification of influential spreaders that could be used to control epidemics within populations would be of considerable importance. Generally, populations are characterized by its community structures and by the heterogeneous distributions of out-leaving links among nodes bridging over communities. A new method for community networks capable of identifying influential spreaders that accelerate the spread of disease is here proposed. In this method, influential spreaders serve as target nodes. This is based on the idea that, in k-shell decomposition method, out-leaving links and inner links are processed separately. The method was used on empirical networks constructed from online social networks, and results indicated that this method is more accurate. Its effectiveness stems from the patterns of connectivity among neighbors, and it successfully identified the important nodes. In addition, the performance of the method remained robust even when there were errors in the structure of the network.
An identity-authentication system using fingerprints : Automated biometrics

Fingerprint verification is an important biometric technique for personal identification. In this paper, we describe the design and implementation of a prototype automatic identity-authentication system that uses fingerprints to authenticate the identity of an individual. We have developed an improved minutiae-extraction algorithm that is faster and more accurate than our earlier algorithm [58]. An alignment-based minutiae-matching algorithm has been proposed. This algorithm is capable of finding the correspondences between input minutiae and the stored template without resorting to exhaustive search and has the ability to compensate adaptively for the nonlinear deformations and inexact transformations between an input and a template. To establish an objective assessment of our system, both the Michigan State University and the National Institute of Standards and Technology NIST 9 fingerprint data bases have been used to estimate the performance numbers. The experimental results reveal that our system can achieve a good performance on these data bases. We also have demonstrated that our system satisfies the response-time requirement. A complete authentication procedure, on average, takes about 1.4 seconds on a Sun ULTRA I workstation (it is expected to run as fast or faster on a 200 HMz Pentium [7]).
Answers for Sentence Retrieval in Question Answering

Question answering systems which automatically search for user’s information need are considered as a separate issue from the community-generated question answering which answers users’ questions by human respondents. Although the two answering systems have different applications, both of them aim to present a correct answer to the users’ question and consequently they can feed each other to improve their performance and efficiency. In this paper, we propose a new idea to use the information derived from a community question answering forum in an automatic question answering system. To this end, two different frameworks, namely the class-based model and the trained trigger model, have been used in a language model-based sentence retrieval system. Both models try to capture word relationships from the question-answer sentence pair of a community forum. Using a standard TREC question answering dataset, we evaluate our proposed models on the subtask of sentence retrieval, while training the models on the Yahoo! Answer corpus. Results show both methods that trained on Yahoo! Answers logs significantly outperform the unigram model, in which the class-based model achieved 4.72% relative improvement in mean average precision and the trained triggering model achieved 18.10% relative improvement in the same evaluation metric. Combination of both proposed models also improved the system mean average precision 19.29%.
Multipath Issues in Unicast and Multicast Next-Hop Selection

Various routing protocols, including Open Shortest Path First (OSPF) and Intermediate System to Intermediate System (ISIS), explicitly allow "Equal-Cost Multipath" (ECMP) routing. Some router implementations also allow equal-cost multipath usage with RIP and other routing protocols. The effect of multipath routing on a forwarder is that the forwarder potentially has several next-hops for any given destination and must use some method to choose which next- hop should be used for a given data packet.
Investigating cognitive deficits and symptomatology across pre-morbid adjustment patterns in first-episode psychosis

Background Cognitive deficits in schizophrenia are well established and are known to be present during the first episode of a psychotic disorder. In addition, consistent heterogeneity within these impairments remains unexplained. One potential source of variability may be the level of pre-morbid adjustment prior to the onset of first-episode psychosis (FEP). Method Ninety-four FEP patients and 32 healthy controls were assessed at baseline on several neuropsychological tests comprising six cognitive domains (verbal memory, visual memory, working memory, processing speed, reasoning/problem-solving and attention) and an abbreviated version of the full IQ. A global neurocognitive domain was also computed. Pre-morbid adjustment patterns were divided into three distinct groups: stable-poor, stable-good and deteriorating course. Results Based on a cut-off of 0.8 for effect size, the stable-poor pre-morbid adjustment group was significantly more impaired on most cognitive domains and full IQ compared to the deteriorating group, who were more severely impaired on all measures compared to the stable-good group. The type of cognitive deficit within each subgroup did not differ and the results indicate that a global neurocognition measure may reliably reflect the severity of cognitive impairment within each subgroup. Conclusions Pre-morbid adjustment patterns prior to onset of psychosis are associated with severity but not type of cognitive impairment. Patients in the stable-poor group are generally more impaired compared to the deteriorating group, who are, in turn, more impaired than the stable-good group.
Classifying patents based on their semantic content

In this paper, we extend some usual techniques of classification resulting from a large-scale data-mining and network approach. This new technology, which in particular is designed to be suitable to big data, is used to construct an open consolidated database from raw data on 4 million patents taken from the US patent office from 1976 onward. To build the pattern network, not only do we look at each patent title, but we also examine their full abstract and extract the relevant keywords accordingly. We refer to this classification as semantic approach in contrast with the more common technological approach which consists in taking the topology when considering US Patent office technological classes. Moreover, we document that both approaches have highly different topological measures and strong statistical evidence that they feature a different model. This suggests that our method is a useful tool to extract endogenous information.
Dialect in digitally mediated written interaction: a survey of the geohistorical distribution of the ditransitive in British English using Twitter

Recent research (Gerwin, 2013; Siewierska & Hollmann, 2007; Yanez Bouza & Denison, 2015) uses historical and contemporary corpora to quantify diachronic and spatial distributions of variants of the ditransitive in British English. Each study pays particular attention to ditransitives with two pronominal objects, where internal factors influencing variation are reduced primarily to the choice of pronoun and verb type. Three variants are attested, a ‘prepositional dative’ (PDAT - ‘send it to me’), a double-object (GTD - ‘send me it’) and an alternative regionally marked double object construction (TGD - ‘send it me’). Corpus evidence reveals the pronominal TGD as the most frequent variant until the beginning of the 19th century, when the PDAT gained preference. The pronominal GTD, now considered canonical, emerges at the beginning of the 20th century. Broad agreement over the geographical distribution of the ditransitive is based primarily on maps drawn from the Survey of English Dialects (SED), but “comprehensive frequency data” (Yanez Bouza & Denison, 2015, p.248) is lacking. The current project provides detailed frequency data drawn from language use on Twitter which is accurately mapped according to GPS coding. This map shows remarkable crossover with the SED maps, demonstrating both the stability of the geographical distribution over time and the amenability of “interactive written discourse” (Ferrara, Brunner, & Whittemore, 1991) to the expression of dialect. The results detail a large degree of variation in the relative frequency of each variable over physical space. Such variation brings into focus some important questions regarding the nature of a language as conceived in formal linguistic theory and a problematic tendency to ‘lump together’ large, linguistically diverse regions and treat them as one entity (Siewierska & Hollmann, 2007, p.97). Instead, using statistical tests for difference, the present study groups contiguous regions by the relative probabilistic frequencies of each variant. The results have implications for dialect geography, dialect syntax and recent approaches concerning regionally sensitive probabilistic approaches to grammar (Bresnan & Ford, 2010).
Secure In-Network Processing in Sensor Networks

In-network processing in large-scale sensor networks has been shown to improve scalability, eliminate information redundancy and increase the lifetime of the network. In this chapter we address the challenge of securing innetwork processing, both for aggregating sensor node’s measurements and disseminating commands from the aggregators to individual sensor nodes. We present the key mechanisms for establishing a secure communication channel between sensor nodes and aggregators and show how scalability and resiliency against different type of attacks can be achieved. We also present how requirements such as dynamically adding new nodes in the network and harmonious existence with other security protocols of the network can be met. Finally we elaborate on resilient aggregation under corrupted measurements and the proposed solutions.
The abbreviated form of the Brief Cognitive Battery in the diagnosis of dementia in Alzheimer’s disease

The Brief Cognitive Battery (BCB) developed by our group for cognitive assessment of low educated individuals has also shown to be highly accurate in diagnosing dementia of individuals with medium or high levels of education, making it a useful tool for populations with heterogeneous educational background. The application of BCB takes around eight minutes, a rather long period for a screening test. Objectives Our aim was to evaluate whether the exclusion of items of the BCB could reduce its application time without losing accuracy. Methods Patients with Alzheimer’s disease with mild or moderate dementia (N=20), and 30 control subjects were submitted to an abbreviated version of the BCB in which the clock drawing test was not included as an interference test for the delayed recall test. Data from another 22 control individuals who were submitted to the original BCB in another study were also included for comparison. A mathematical formula was employed to compare the two versions of the BCB. Descriptive statistics and ROC (receiver operator characteristic) curves were used (alpha=0.05). Results Using the abbreviated version, the delayed recall test also had high accuracy in diagnosing dementia and the mathematical formula results did not differ to those obtained using the original version, while mean time was reduced by 2 minutes and 37 seconds. Conclusions This abbreviated form of the BCB is a potentially valuable tool for screening dementia in population studies as well as in busy clinical practices in countries with heterogeneous educational backgrounds.
INTERMEDIATION EFFICIENCY AND PRODUCTIVITY OF THE BANKING SECTOR IN KENYA

The main objective of the study is to investigate intermediation efficiency and productivity in the banking sector in the post liberalization period in Kenya. The study is motivated by the fact that though the banking sector constitutes a large part of the financial system in Kenya, little is known about its intermediation efficiency and productivity status. Further banks are awash with liquidity despite private sector credit demand indicating some inefficiency in the intermediation process in Kenya. This study adopts a non-parametric Data Envelopment Analysis (DEA) to analyze intermediation efficiency in the banking sector and Malmquist Productivity Index (MPI) to measure productivity gains of banks in Kenya. The results show that though the banks were not fully efficient in all respects, they performed fairly well during the period under study. Banks still have reason and scope to improve performance by improving their technology, skills and enlarging their scale of operations so as to be fully efficient. Based on the main conclusions, policies encouraging competition, products diversification to advance loans, risks minimization through increased capital regulation and privatization of some banks are generally recommended.
The Apoplastic Copper AMINE OXIDASE1 Mediates Jasmonic Acid-Induced Protoxylem Differentiation in Arabidopsis Roots1

The differentiation of wood cells in Arabidopsis can be triggered by the plant hormone methyl jasmonate acting via hydrogen peroxide. Polyamines are involved in key developmental processes and stress responses. Copper amine oxidases oxidize the polyamine putrescine (Put), producing an aldehyde, ammonia, and hydrogen peroxide (H2O2). The Arabidopsis (Arabidopsis thaliana) amine oxidase gene At4g14940 (AtAO1) encodes an apoplastic copper amine oxidase expressed at the early stages of vascular tissue differentiation in roots. Here, its role in root development and xylem differentiation was explored by pharmacological and forward/reverse genetic approaches. Analysis of the AtAO1 expression pattern in roots by a promoter::green fluorescent protein-β-glucuronidase fusion revealed strong gene expression in the protoxylem at the transition, elongation, and maturation zones. Methyl jasmonate (MeJA) induced AtAO1 gene expression in vascular tissues, especially at the transition and elongation zones. Early protoxylem differentiation was observed upon MeJA treatment along with Put level decrease and H2O2 accumulation in wild-type roots, whereas Atao1 loss-of-function mutants were unresponsive to the hormone. The H2O2 scavenger N,N1-dimethylthiourea reversed the MeJA-induced early protoxylem differentiation in wild-type seedlings. Likewise, Put, which had no effect on Atao1 mutants, induced early protoxylem differentiation in the wild type, this event being counteracted by N,N1-dimethylthiourea treatment. Consistently, AtAO1-overexpressing plants showed lower Put levels and early protoxylem differentiation concurrent with H2O2 accumulation in the root zone where the first protoxylem cells with fully developed secondary wall thickenings are found. These results show that the H2O2 produced via AtAO1-driven Put oxidation plays a role in MeJA signaling leading to early protoxylem differentiation in root.
Exploration of the potential for using Spark-I observations to derive atmospheric parameters

ABSTRACT As part of a low-cost nanosatellite constellation, Spark-I, a hyperspectral resolution instrument with 149 channels covering blue to near-infrared, has been successfully launched on 22 December 2016. In this study, we try to explore its potential to derive atmospheric parameters according to optimal estimation theory. From simulated measurements, we estimated the information content described as degrees of freedom for signal (DFS) and error reduction of typical aerosols, including dust, soot, sea salt, and sulphate, as well as water vapour (H2O), nitrogen dioxide (NO2), surface pressure, and Sun-induced fluorescence (SIF). Based on the results, only the H2O column, aerosol optical depth (AOD), and surface albedo could be derived with error reduction of 20%, 40%, and near 100%, respectively. The retrieval of aerosol was strongly correlated with surface albedo, especially dust, with a DFS of 0.3–0.9 due to surface variations. After investigating the impact of the oxygen and H2O absorption bands on the aerosol information content, we recommend retrieving aerosol characteristics using full channels, rather than sub-band channels. The more fraction one type of aerosol is, the larger information about it we can get. Different AOD results in 0.3–0.8 aerosol DFS change and solar zenith angle influences less. The information of atmospheric gases was sensitive to both signal-to-noise ratio (SNR) and spectral resolution due to their particular absorption patterns. However, improving only the SNR by double or more could allow for the derivation of SIF emissions, assuming the a priori estimation is accurate.
Poor responder protocols for in-vitro fertilization: options and results

Purpose of review To present the options and the results in the management of poor responders in in-vitro fertilization. Recent findings There is no controlled ovarian hyperstimulation protocol which is best suited for all poor responders. Low dose gonadotropin-releasing hormone agonist regimes appear to be most advantageous. Prediction of compromised response prior to cycle initiation by a thorough assessment of ovarian reserve as well as a careful review of past responses could allow for a more appropriate selection of a controlled ovarian hyperstimulation protocol for each individual patient. Optimistic data have been presented by the use of high doses of gonadotropins, flare up gonadotropin-releasing hormone agonist protocols (standard or microdose), stop protocols, luteal onset of gonadotropin-releasing hormone agonist, and short protocols. Natural cycle also seems to be an appropriate strategy to be considered. Summary There is no universal definition for the ‘poor responder’. Numerous strategies have been proposed to improve ovarian stimulation in poor responders, but none of them is the ideal for all such patients. More data from good quality controlled trials are needed.