Miracle-dz/UniFAR-FTUs huggingface dataset:
Berry Flesh and Skin Ripening Features in Vitis vinifera as Assessed by Transcriptional Profiling

Background Ripening of fleshy fruit is a complex developmental process involving the differentiation of tissues with separate functions. During grapevine berry ripening important processes contributing to table and wine grape quality take place, some of them flesh- or skin-specific. In this study, transcriptional profiles throughout flesh and skin ripening were followed during two different seasons in a table grape cultivar ‘Muscat Hamburg’ to determine tissue-specific as well as common developmental programs. Methodology/Principal Findings Using an updated GrapeGen Affymetrix GeneChip® annotation based on grapevine 12×v1 gene predictions, 2188 differentially accumulated transcripts between flesh and skin and 2839 transcripts differentially accumulated throughout ripening in the same manner in both tissues were identified. Transcriptional profiles were dominated by changes at the beginning of veraison which affect both pericarp tissues, although frequently delayed or with lower intensity in the skin than in the flesh. Functional enrichment analysis identified the decay on biosynthetic processes, photosynthesis and transport as a major part of the program delayed in the skin. In addition, a higher number of functional categories, including several related to macromolecule transport and phenylpropanoid and lipid biosynthesis, were over-represented in transcripts accumulated to higher levels in the skin. Functional enrichment also indicated auxin, gibberellins and bHLH transcription factors to take part in the regulation of pre-veraison processes in the pericarp, whereas WRKY and C2H2 family transcription factors seems to more specifically participate in the regulation of skin and flesh ripening, respectively. Conclusions/Significance A transcriptomic analysis indicates that a large part of the ripening program is shared by both pericarp tissues despite some components are delayed in the skin. In addition, important tissue differences are present from early stages prior to the ripening onset including tissue-specific regulators. Altogether, these findings provide key elements to understand berry ripening and its differential regulation in flesh and skin.
Semantic Rule Labeling dan Sentence Information Density Dalam Pemilihan Kalimat Representatif Cluster Pada Peringkasan Multi-Dokumen

Coverage dan salient merupakan masalah utama yang menjadi perhatian para peneliti dalam peringkasan dokumen. Pendekatan clustering mampu memberikan coverage yang baik terhadap semua topik namun tidak memiliki informasi-informasi yang bisa mewakili kalimat-kalimat lain (salience sentence). Salience dapat digali dengan melihat hubungan dari satu kalimat dengan kalimat lain yang dibangun dengan pendekatan position text graph, namun position text graph hanya mampu menggali hubungan antar kalimat tanpa memperhatikan peran semantik kata (“who” did “what” to “whom”, “where”, “when”, and “how”) dalam kalimat yang dibandingkan.Pada paper ini kami mengusulkan sebuah metode baru strategi pemilihan kalimat representatif cluster dengan pendekatan sentence information density dan Semantic Rule labeling. Hasil uji coba menunjukkan metode yang metode yang diusulkan mampu memilih kalimat ringkasan lebih baik dari metode Sentence Information Density (SID) dengan rata-rata nilai Rouge-1 0.32511.
Spatial reproducibility of complex fractionated atrial electrogram depending on the direction and configuration of bipolar electrodes: an in-silico modeling study

Although 3D-complex fractionated atrial electrogram (CFAE) mapping is useful in radiofrequency catheter ablation for persistent atrial fibrillation (AF), the directions and configuration of the bipolar electrodes may affect the electrogram. This study aimed to compare the spatial reproducibility of CFAE by changing the catheter orientations and electrode distance in an in-silico left atrium (LA). We conducted this study by importing the heart CT image of a patient with AF into a 3D-homogeneous human LA model. Electrogram morphology, CFAE-cycle lengths (CLs) were compared for 16 different orientations of a virtual bipolar conventional catheter (conv-cath: size 3.5 mm, inter-electrode distance 4.75 mm). Additionally, the spatial correlations of CFAE-CLs and the percentage of consistent sites with CFAE-CL<120 ms were analyzed. The results from the conv-cath were compared with that obtained using a mini catheter (mini-cath: size 1 mm, inter-electrode distance 2.5 mm). Depending on the catheter orientation, the electrogram morphology and CFAE-CLs varied (conv-cath: 11.5±0.7% variation, mini-cath: 7.1±1.2% variation), however the mini-cath produced less variation of CFAE-CL than conv-cath (p<0.001). There were moderate spatial correlations among CFAE-CL measured at 16 orientations (conv-cath: r=0.3055±0.2194 vs. mini-cath: 0.6074±0.0733, p<0.001). Additionally, the ratio of consistent CFAE sites was higher for mini catheter than conventional one (38.3±4.6% vs. 22.3±1.4%, p<0.05). Electrograms and CFAE distribution are affected by catheter orientation and electrode configuration in the in-silico LA model. However, there was moderate spatial consistency of CFAE areas, and narrowly spaced bipolar catheters were less influenced by catheter direction than conventional catheters.
Secret Telephone Technology Based on Information Hiding and Encryption

This paper discussed the model and realization strategy of information hiding and encryption in secret telephone communication, and presented a novel information hiding and pickup method based on DCT. A mode switcher was used to let the system have the same process procedure for secret and non-secret communication. The system proposed in the paper had advantages such as high safety, real time, extensible and so on. It is a new effective approach of secret speech communication
Image Denoising Using Mean Curvature of Image Surface

We propose a new variational model for image denoising, which employs the $L^{1}$-norm of the mean curvature of the image surface $(x,f(x))$ of a given image $f:\Omega\rightarrow\mathbb{R}$. Besides eliminating noise and preserving edges of objects efficiently, our model can keep corners of objects and greyscale intensity contrasts of images and also remove the staircase effect. In this paper, we analytically study the proposed model and justify why our model can preserve object corners and image contrasts. We apply the proposed model to the denoising of curves and plane images, and also compare the results with those obtained by using the classical Rudin-Osher-Fatemi model [Phys. D, 60 (1992), pp. 259-268].
Content Sharing for Mobile Devices

The miniaturisation of computing devices has seen computing devices become increasingly pervasive in society. With this increased pervasiveness, the technologies of small computing devices have also improved. Mobile devices are now capable of capturing various forms of multimedia and able to communicate wirelessly using increasing numbers of communication techniques. The owners and creators of local content are motivated to share this content in ever increasing volume; the conclusion has been that social networks sites are seeing a revolution in the sharing of information between communities of people. As load on centralised systems increases, we present a novel decentralised peer-to-peer approach dubbed the Market Contact Protocol (MCP) to achieve cost effective, scalable and efficient content sharing using opportunistic networking (pocket switched networking), incentive, context-awareness, social contact and mobile devices. Within the report we describe how the MCP is simulated with a superimposed geographic framework on top of the JiST (Java in Simulation Time) framework to evaluate and measure its capability to share content between massively mobile peers. The MCP is shown in conclusion to be a powerful means by which to share content in a massively mobile ad-hoc environment.
PushMenu: Extending Marking Menus for Pressure-Enabled Input Devices

Several approaches have been proposed to increase the breadth of standard Marking Menus over the 8 item limit, most of which have focused on the use of the standard 2D input space (x-y). We present Push Menu, an extension of Marking Menu that takes advantage of pressure input as a third input dimension to increase menu breadth. We present the results of a preliminary experiment that validates our design and shows that Push Menu users who are neither familiar with pen-based interfaces nor continuous pressure control can handle up to 20 items reliably. We also discuss the implications of these results for using Push Menu in user in- terfaces and for improving its design.
PRICE STABILITY IN THE UK

‘To fortune I am perfectly indifferent, and I shall make no demand of that nature on your father, since I am well aware that it could not be complied with; and that one thousand pounds in the 4 per cents, which will not be yours till after your mother’s decease, is all that you may ever be entitled to. On that head, therefore, I shall be uniformly silent; and you may assure yourself that no ungenerous reproach shall ever pass my lips when we are married. ’
Unconditional Variance , Mean Reversion and Short Rate Volatility in the Calibration of the Black-Derman and Toy Model and of Two-Dimensional Log-Normal Short Rate Models

Calibration of the BDT model to cap prices is notoriously simple, since an almost exact`guess’ of the correct time-dependent volatility can be obtained from the market implied volatility of caplets. This is a priori surprising, since the unconditional variance of the BDTshort rate process should be expected to depend on the (deterministic) history of the short rate volatility, and on the mean reversion of logarithm of the short rate. This apparent paradox is resolved in the first part of the paper, where general expressions (usable, for instance, to calibrate the BlackKarasinsky model) for the unconditional variance are obtained for a variety of onefactor models. The class of one-factor models for which the same type of relationship holds true is also introduced. The results are then extended to more-than-one-factor models, with the introduction of a class of stable and arbitrage-free Generalized Brennan and Schwartz models. It is shown that, if no arbitrage is to be enforced, this very large class of log-normal-short rate models cannot be calibrated to cap prices using higher-dimensional extensions of the BDT procedure.
Age-Related Decrease in Striatal DA Produces Cognitive Deficits in Male Rats

Aging is a process that presents various alterations in physiological, behavioral and neurochemical processes. It causes impairment of CNS functions which lead to changes in memory, cognition and other behavioral performances. Reports have shown that aging causes neurochemical alterations in various physiological functions. The aim of the present study was to evaluate the cognitive changes in relation to process of aging. For this 20 male rats were taken, 10 young (4-6 months) and 10 old (18-22 months). Morris Water Maze (MWM) test was performed to monitor changes in learning and memory while Object-Recognition Task (ORT) was performed to evaluate changes in cognitive function. After behavioral assessment decapitation was done and rat brain was dissected to isolate striatum. Then neurochemical analysis was performed by HPLC-EC to monitor changes in striatal DA and DOPAC levels. Results of behavioral tests showed that aged rats exhibited a significant impairment of long-term memory. While cognitive ability assessed by ORT was also impaired in aged rats. Neurochemical results showed that there was a significant decline in striatal dopamine (DA) concentration while its metabolite DOPAC was significantly increased in aged rats. Hence aging has a significant negative influence on cognitive functions. Age-related behavioral deficits may occur as a result of decline in DA levels in striatum leading to changes in memory and cognitive performance. DOI: http://dx.doi. org/10.6000/1927-5951.2011. 01.01. 05
Effect of Polydextrose on Subjective Feelings of Appetite during the Satiation and Satiety Periods: A Systematic Review and Meta-Analysis

Introduction: Subjective feelings of appetite are measured using visual analogue scales (VAS) in controlled trials. However, the methods used to analyze VAS during the Satiation (pre- to post-meal) and Satiety (post-meal to subsequent meal) periods vary broadly, making it difficult to compare results amongst independent studies testing the same product. This review proposes a methodology to analyze VAS during both the Satiation and Satiety periods, allowing us to compare results in a meta-analysis. Methods: A methodology to express VAS results as incremental areas under the curve (iAUC) for both the Satiation and Satiety periods is proposed using polydextrose as a case study. Further, a systematic review and meta-analysis on subjective feelings of appetite was conducted following the PRISMA methodology. Meta-analyses were expressed as Standardized Mean Difference (SMD). Results: Seven studies were included in the meta-analysis. There were important differences in the methods used to analyze appetite ratings amongst these studies. The separate subjective feelings of appetite reported were Hunger, Satisfaction, Fullness, Prospective Food Consumption, and the Desire to Eat. The method proposed here allowed the results of the different studies to be homogenized. The meta-analysis showed that Desire to Eat during the Satiation period favors polydextrose for the reduction of this subjective feeling of appetite (SMD = 0.24, I2 < 0.01, p = 0.018); this effect was also significant in the sub-analysis by sex for the male population (SMD = 0.35, I2 < 0.01, p = 0.015). There were no other significant results. Conclusion: It is possible to compare VAS results from separate studies. The assessment of iAUC for both the Satiation and Satiety periods generates results of homogeneous magnitudes. This case study demonstrates, for the first time, that polydextrose reduces the Desire to Eat during the Satiation period. This may explain, at least in part, the observed effects of polydextrose on the reduction of levels of energy intake at subsequent meals.
Predicting the Development of Diabetes Using the Product of Triglycerides and Glucose: The Chungju Metabolic Disease Cohort (CMC) Study

Background To determine whether the TyG index, a product of the levels of triglycerides and fasting plasma glucose (FPG) might be a valuable marker for predicting future diabetes. Methods A total of 5,354 nondiabetic subjects who had completed their follow-up visit for evaluating diabetes status were selected from a large cohort of middle-aged Koreans in the Chungju Metabolic Disease Cohort study. The risk of diabetes was assessed according to the baseline TyG index, calculated as ln[fasting triglycerides (mg/dL) × FPG (mg/dL)/2]. The median follow-up period was 4.6 years. Results During the follow-up period, 420 subjects (7.8%) developed diabetes. The baseline values of the TyG index were significantly higher in these subjects compared with nondiabetic subjects (8.9±0.6 vs. 8.6±0.6; P<0.0001) and the incidence of diabetes increased in proportion to TyG index quartiles. After adjusting for age, gender, body mass index, waist circumference, systolic blood pressure, high-density lipoprotein (HDL)-cholesterol level, a family history of diabetes, smoking, alcohol drinking, education level and serum insulin level, the risk of diabetes onset was more than fourfold higher in the highest vs. the lowest quartile of the TyG index (relative risk, 4.095; 95% CI, 2.701–6.207). The predictive power of the TyG index was better than the triglyceride/HDL-cholesterol ratio or the homeostasis model assessment of insulin resistance. Conclusions The TyG index, a simple measure reflecting insulin resistance, might be useful in identifying individuals at high risk of developing diabetes.
What primary grade teachers need to know about speech and language

The primary purpose of my action research and thesis is to write a guide for the teachers of very young children (Grades preK-2) to help them identify the children in their classrooms who may have speech and language disorders, and therefore refer them for assistance in a timely manner. There are several studies supporting the idea that difficulty in speech and language affects the development of literacy skills, and I believe all teachers need to be informed of the problem. I therefore decided to write a guide for the teachers of preschool, kindergarten, and 1st and 2nd grade children including researchbased information to help them identify children with these special needs. In addition, I conducted six interviews with teachers: four general educators—one from each of grades preschool, kindergarten, 1, and 2 grade—and two special educators about what they would like me to include in the guide about this topic. Their answers along with data from research are included in the guide.
Gate-Recessed Enhancement-Mode InAlN/AlN/GaN HEMTs With 1.9-A/mm Drain Current Density and 800-mS/mm Transconductance

Having a drain current density of 1.9 A/mm, a peak extrinsic transconductance of 800 mS/mm (the highest reported in III-nitride transistors), ft/fmax of 70/105 GHz, and Vbr of 29 V, 150-nm-gate enhancement-mode InAlN/AlN/GaN high-electron-mobility transistors are demonstrated on SiC substrates using plasma-based gate-recess etch. The possible plasma-induced damage in the gate region was investigated using interface-trap states extracted from temperature-dependent subthreshold slopes.
A New Concept of Network Intrusion Detection using Fuzzy Clustering

Internet has become a vital part of any organization. Sensitive and confidential information is being sent over the network. But with the growth of internet, intrusion and attacks have also increased. Thus, there arises a need of robust and powerful intrusion detection systems which can detect the attacks. Recently, many novel methods are experimented to build strong IDSs. The aim of this paper is to present a methodology that can recognise and detect attacks efficiently. In this paper, we implement the FCM algorithm and successfully integrate it in WEKA to expand the system functions of the open-source platform, so that users can directly call the FCM algorithm to do fuzzy clustering analysis. Besides, considering the shortcoming of the classical FCM algorithm in selecting the initial cluster centers, we represent an improved FCM algorithm which adopts a new strategy to optimize the selection of original cluster centers. A novel classification via dynamic fuzzy c means clustering algorithm has been proposed to build an efficient anomaly based network intrusion detection model. A subset of KDDCup 1999 intrusion detection benchmark dataset has been used for the experiment. The proposed novel concept will be efficient in terms of detection accuracy, low false positive rate in comparison to the other existing methods.
A novel sparsity-inspired blind image quality assessment algorithm

We present a novel blind image quality assessment (BIQA) algorithm inspired by the sparse representation of natural images in the human visual system (HVS). The hypothesis behind the proposed method is that the properties of natural images that afford their sparse representation are altered in the presence of distortion. We attempt to quantify this change in sparsity and show that it is indeed a measure of the unnatu-ralness or distortion in an image. We first construct an over-complete dictionary from a set of pristine images using the K-SVD algorithm. This dictionary is then used to sparsely represent a different and significantly smaller set of pristine images to extract "reference" features. To evaluate the quality of a given image, features are extracted from its sparse representation and quantified with respect to the "reference" features. We call our algorithm Sparsity-based Blind Image Quality Evaluation (SBIQE). We show that the proposed algorithm consistently correlates well with subjective scores over several popular image databases. Further, it compares reasonably with state-of-the-art BIQA algorithms. Additionally, our algorithm is both opinion-unaware and distortion-unaware.
Analysis of reflectometry and ellipsometry data from patterned structures

Specular reflected light techniques, including both single wavelength and spectroscopic versions of ellipsometry and reflectometry, have been used for both etch and growth rate control. However, use of these techniques for process control on products has been limited due to the problems inherent in the analysis of reflected light from patterned structures. In this paper, we examine techniques for the quantitative analysis of data from both highly regular grating structures and from patterns with low local order. We find good quantitative agreement of vector diffraction theory to specular reflection data. We conclude that there is significant promise for the use of specular techniques for in situ monitoring of topography provided that computational speed issues can be improved.
Some Self-Orthogonal Codes Related to Higman's Geometry

We examine some self-orthogonal codes constructed from a rank-5 primitive permutation representation of degree 1100 of the sporadic simple group ${\rm HS}$ of Higman-Sims. We show that ${\rm Aut}(C) = {\rm HS}{:}2$, where $C$ is a code of dimension 21 associated with Higman's geometry.
The Jurisdiction of the Man within – Introspection, Identity, and Cooperation in a Public Good Experiment

According to Adam Smith (1790), human selfishness can be restrained by introspection. We test the effect of introspection on people’s willingness to cooperate in a public good game. Drawing on the concept of identity utility (George A. Akerlof and Rachel E. Kranton, 2000), we show theoretically that introspection may enhance cooperation by increasing the relative cost of deviating from one’s self-image. Experimentally, we induce introspection through the elicitation of (normative) expectations. Our results show that introspection causally increases cooperation. Both home-grown idealism and the experiences with the cooperativeness of the environment predict individual cooperativeness throughout the game.
PCA, LDA and neural network for face identification

Algorithms based on Principal Component Analysis (PCA) and subspace Linear Discriminant Analysis (LDA) are popular in face recognition. PCA is used to perform dimension reduction on human face data and LDA creates another subspace to improve discriminant of PCA features. In this paper, we propose Artificial Neural Networks (ANN) as an alternative to replace Euclidean distances in classification of human face features extracted by PCA and LDA. ANN is well recognized by its robustness and good learning ability. The algorithms were evaluated using the Database of Faces which comprises 40 subjects and with a total size of 400 images. Experimental results show that ANN reasonably improves the performance of PCA and LDA method. LDA-NN achieves an average recognition accuracy of 95.8%.
Multi-organizational Access Control Model Based on Mobile Agents for Cloud Computing

The development of new digital technologies is swiftly rising. Thus, the cloud computing is grabbing-attention of information technology communities. In this context, diverse security issues are amplified. Particularly, access control seems of main importance because it ensures diverse security services, such as, authentication, identification, confidentiality and integrity. Several works are devoted for designing access control models. In this paper, we are particularly interested on distributed access control approaches. According to identified drawbacks of Multi-OrBAC model, we introduce a new distributed access control model for cloud computing based on Mobile Agent.