Miracle-dz/UniFAR-FTUs huggingface dataset:
Consumption of Stilbenes and Flavonoids is Linked to Reduced Risk of Obesity Independently of Fiber Intake

Background: Polyphenol consumption is implicated in gut microbiome composition and improved metabolic outcomes, but it is unclear whether the effect is independent of dietary fiber. Methods: We investigated the links between (poly)phenol intake, gut microbiome composition (16s RNA) and obesity independently of fiber intake in UK women (n = 1810) and in a small group of UK men (n = 64). Results: (Poly)phenol intakes correlated with microbiome alpha diversity (Shannon Index) after adjusting for confounders and fiber intake. Moreover, flavonoid intake was significantly correlated with the abundance of Veillonella, (a genus known to improve physical performance), and stilbene intake with that of butyrate-producing bacteria (Lachnospira and Faecalibacterium). Stilbene and flavonoid intake also correlated with lower odds of prevalent obesity (Stilbenes: Odds Ratio (95% Confidence Interval) (OR(95%CI)) = 0.80 (0.73, 0.87), p = 4.90 × 10−7; Flavonoids: OR(95%CI) = 0.77 (0.65, 0.91), p = 0.002). Formal mediation analyses revealed that gut microbiome mediates ~11% of the total effect of flavonoid and stilbene intake on prevalent obesity. Conclusions: Our findings highlight the importance of (poly)phenol consumption for optimal human health.
Analysis of Photosynthesis with Mutants of Higher Plants and Algae

INTRODUCfION . 468 MUTATIONS AFFECfING CO2 FIXATION AND PHOTORESPIRATION . 469 Mutants of Higher Plants . 469 Algal Mutants . 470 Mutations in Photorespiratory Metabolism. 472 Mutations A ffecting Rubisco . 476 MUTATIONS AFFECTING PHOTOS YNTHETIC ELECTRON TRANSPORT. 478 Methods of Mutant Isolation . 478 PSI-Deficient Mutants . 480 PSIl-Deficient Mutants . 481 Coupling Factor. 484 Mutants Lacking Chlorophyll b . 485 Thylakoid Ultrastructure. 487 Analysis of Fluorescence Phenomena . 488 Chlorophyll-Deficient Mutants . 489 Carotenoid-Deficient Mutants. 491 Stoichiometry of the Photosynthetic Apparatus . 493 Mutations Affecting Chloroplast Development . 495 Mutations Conferring Herbicide Resistance . 496 CONCLUDING REMARKS . 498
Reactive machine control : a simulation approach using chi

ion level function, 8 goal, 8 layout, 8 lowering, 8, 72, 76, 79 structure, 8 accuracy virtual machine, 80 application data structure machine control, 33 framework machine control, 31 machine control, 27, 31, 34 realtime, 31 structure machine control, 32 aspects time-related, 20 assignment statement, 18 behaviour real-time, 44 case study, 67 virtual machine, 71 channel object, 33, 36, 51–53 chi, see χ communication object, 39, 52 protocol, 33 service synchronous, 32 statement, 19, 39 synchronous, 15, 17, 45 compiler χ, see compiler, tool tool, 9, 16, 31, 34, 39, 41, 45, 81, 85, 87 conceptual design, 7 constant χ, 17 continuous polling, 82 control feedback, 25 real-time, 3, 6 supervisory, 25 data structure machine control application, 33
Growing Tomorrow's Teachers Together: The CaBan Initial Teacher Education Partnership

In this paper we outline the philosophy and research foundations underpinning the development of CaBan – an Initial Teacher Education (ITE) Partnership developed for the purpose of educating the teachers of tomorrow for North Wales. CaBan represents an ambitious ‘learning partnership’ of five partners consisting of regional schools, Bangor University, University of Chester, the regional school improvement service (GwE), and the Collaborative Institute for Education Research, Evidence and Impact (CIEREI). Each partner plays a key role in fulfilling our ambitions to contribute to Our National Mission and achieve our vision of ‘Growing Tomorrow’s Teachers Together. ’ At its core, the goal of CaBan is to support our new Associate Teachers (ATs) to become creative, inspiring and highly skilled teachers who will contribute to the delivery of A curriculum for Wales – a curriculum for life (Welsh Government, 2015). In this paper we outline: (i) our basic vision and mission as a learning partnership; (ii) the evidence to support our strategic pedagogical position with respect to growing tomorrow’s teachers; (iii) the crucial role of mentoring in the development of our ATs as critically reflective practitioners; (iv) how we integrate research as a fundamental element of all we do; (v) how our programme design is underpinned by the notion of professional enquiry 10 Griffiths WJE 22/1.indd 201 14/05/2020 13:21 Wales Journal of Education 202 Jeremy Griffiths et al. and career long professional learning (vi) the specific modes of learning that help nurture ATs’ sense of their ‘teaching self ’; and crucially (vii) the importance of Welsh culture and the Welsh language in education and the role the CaBan partnership has in building capacity to help realise Welsh Government’s vision for a million Welsh speakers by 2050.
Professional Mechanical Tooth Cleaning Method for Dental Implant Surface by Agar Particle Blasting

Oral dysfunction due to peri-implantitis and shortened life of implants has become a major concern. Self-care and removal of oral biofilms by professional mechanical tooth cleaning (PMTC) are indispensable for its prevention. However, if the surface roughness of the implant is increased, it may result in the adhesion of biofilm in the oral cavity. Therefore, the PMTC method can serve for long-term implant management. Calcium carbonate (CaCO3) has been used as a cleaning method for implant surfaces; however, there is concern that the implant surface roughness could increase due to particle collision. Therefore, in this study, to establish a blasting cleaning method that does not adversely affect the implant surface, a new blasting cleaning method using agar particles was devised and its practical application examined. When the simulated stains were blasted with white alumina (WA) abrasive grains and CaCO3 particles, the simulated stains were almost removed, the surface roughness changed to a satin-finished surface—which was thought to be due to fine scratches—and the surface roughness increased. Most of the simulated stains were removed on the surface of the sample blasted with glycine particles and agar particles. Conversely, the gloss of the sample surface was maintained after cleaning, and the increase in surface roughness was slight.
Unsymmetrical plate girders under shear and moment, October 1970

• • • . Page No. 1 1 c INTRODUCTION. ~ • • • • • • • • • • • • • • •• 2 ANALYTICAL MODEL ANO INTERNAL FORCES . 6 3. ULTIMATE STRENGTH. • (I • • • • • • • • • • • • • • • • • • • • 14 40 COMPARISON WITH TEST RESULTS . • • • • . • • • • • . • • . 23 CONCLUSIONS . 26 6 '" ACKNOWLEDGEMENTS. • • • • • • • • • • • • • • • • • • • • • • • 2 7 7. APPENDIX I. REFERENCES · · . • • . • • . • • • • . • •• 28 8", APPENDIX II. NOTATION . 31 9 Q T.i\BLES AND FIGURES • • • • • " • • • • • • • • • • • • • • • •• 35 UNSYMMETRICAL PLATE GIRDERS UNDER SHEAR AND MOMENT by Chingmiin Chern l and Alexis Ostapenko 2
Exploring Structural Sparsity of Deep Networks Via Inverse Scale Spaces

The great success of deep neural networks is built upon their over-parameterization, which smooths the optimization landscape without degrading the generalization ability. Despite the benefits of over-parameterization, a huge amount of parameters makes deep networks cumbersome in daily life applications. On the other hand, training neural networks without over-parameterization faces many practical problems, e.g., being trapped in the local optimal. Though techniques such as pruning and distillation are developed, they are expensive in fully training a dense network as backward selection methods; and there is still a void on systematically exploring forward selection methods for learning structural sparsity in deep networks. To fill in this gap, this paper proposes a new approach based on differential inclusions of inverse scale spaces. Specifically, our method can generate a family of models from simple to complex ones along the dynamics via coupling a pair of parameters, such that over-parameterized deep models and their structural sparsity can be explored simultaneously. This kind of differential inclusion scheme has a simple discretization, dubbed Deep structure splitting Linearized Bregman Iteration (DessiLBI), whose global convergence in learning deep networks could be established under the Kurdyka-Łojasiewicz framework. Particularly, we explore several applications of DessiLBI, including finding sparse structures of networks directly via the coupled structure parameter and growing networks from simple to complex ones progressively. Experimental evidence shows that our method achieves comparable and even better performance than the competitive optimizers in exploring the sparse structure of several widely used backbones on the benchmark datasets. Remarkably, with early stopping, our method unveils “winning tickets” in early epochs: the effective sparse network structures with comparable test accuracy to fully trained over-parameterized models, that are further transferable to similar alternative tasks. Furthermore, our method is able to grow networks efficiently with adaptive filter configurations, demonstrating the good performance with much less computational cost. Codes and models can be downloaded at https://github.com/DessiLBI2020/DessiLBI.
Efﬁciency Beneﬁts Through Load-Balancing with Link Reliability Based Routing in WSNs

—In wireless sensor networks (WSN) energy efﬁciency of routing protocols is of primary importance. Embedded with local load balancing mechanisms, the proposed L2RP protocol is a link reliability based routing protocol which aims to help source nodes to exploit the potential capabilities of their respective neighbors. As it is a reliability-oriented protocol, L2RP discards unreliable links to avoid the substantial energy cost of packet losses. Simulation results show major efﬁciency beneﬁts that stem from load balancing which helps in lengthening the network lifetime while minimizing packet losses. In WSN, the choice of a routing protocol and its key parameters depends on the nature of the application and on its primary mission. Lot of works addressed routing issues with more or less effectiveness, some of which pointed out the use of the link quality indicator (LQI) as a route selection criterion (metric). In a previous work, following an experimental study, we have shown, under some conditions, the inefﬁciency of the LQI based routing. In this paper, we propose through L2RP a simple way to improve reliability and efﬁciency of the LQI based routing in WSN. We also give a comparative study of several metrics including new deﬁnitions of LQI based metrics. Simulation results show that our adaptation of the LQI metric is among the best route selection criteria regardless of the performance criterion under consideration.
Reconstruction of Connected Digital Lines Based on Constrained Regularization

This paper presents a new approach for reconstruction of disconnected digital lines (DDLs) based on a constrained regularization model which ensures connectivity of the digital lines (DLs) in the discrete image plane. The first step in this approach is to determine the order of given pixels of the DDL. To determine connectivity of pixels, we use the usual 8-neighbor connectivity in discrete images. For any neighboring pixels of the DDL that are not connected, we determine a number of new pixel values that need to be reconstructed between these pixels. Next, the integer-valued <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula>- and <inline-formula> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula>-coordinates of the location of the pixels of the DDLs are segregated into two 1D signal vectors. Then the <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula>- and <inline-formula> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula>-coordinates of the missing pixels of the DDLs are estimated using a new constrained regularization. While the solution of this constrained minimization problem provides real values for the <inline-formula> <tex-math notation="LaTeX">$x$ </tex-math></inline-formula>- and <inline-formula> <tex-math notation="LaTeX">$y$ </tex-math></inline-formula>-coordinates of pixels positions, the imposed constraint ensures connectivity of the resulting DLs in the image plane after transforming the computed values from <inline-formula> <tex-math notation="LaTeX">$\mathbb {R}$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$\mathbb {N}$ </tex-math></inline-formula>. The proposed regularization approach forces connected lines with small curvature. The experimental results demonstrate that the proposed technique improves DL intersection detection, as well. Moreover, this technique has a high potential to be used as a fast approach in binary image inpainting particularly overcoming the shortcomings of conventional methods which cause destruction of thin objects and blurring in the recovered regions.
The Relationship between Neuropsychiatric Symptoms and Cognitive Performance in Older Adults with Normal Cognition

Background and Objectives: To explore whether specific Neuropsychiatric Symptoms (NPS) are related to worse performance in particular cognitive domains. Materials and Methods: A cross-sectional analysis of the baseline evaluations of older (≥60 years), cognitively unimpaired (CU) participants from the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set was performed. Data were derived from 43 Alzheimer’s Disease Research Centers. Cognitively impaired individuals, participants with psychiatric disorders and/or under treatment with antipsychotic, anxiolytic, sedative, or hypnotic agents were excluded. NPS were assessed using the Neuropsychiatric Inventory Questionnaire. The association of NPS with participants’ performance on episodic memory, semantic memory, language, attention, processing speed and executive function was analysed using an adjusted (considering important demographic and medical factors) multivariate general linear model. Results: A total of 7179 CU, older, predominantly female, Caucasian, and well-educated participants were included in the present analysis. Among them, 1856 individuals had one or more NPS. Our analysis revealed that moderate/severe anxiety was related to worse performance on semantic memory, attention and executive function, the presence of hallucinations was linked to worse processing speed and executive function scores, while the presence of elation/euphoria and aberrant motor behaviour were associated with poorer attention and language performance, respectively. In the context of a secondary, exploratory analysis, the presence of moderate/severe delusions was related to worse processing speed and executive function performance. Conclusions: The relationship between specific NPS and worse performance in particular cognitive domains could inform the formulation of individualized preventive strategies directed to the ‘‘fortification’’ of specific cognitive functions in CU individuals with NPS.
IPLS-LDA: An Improved Partial Least Square Discriminant Analysis for Heterogeneous Transcriptomics and Metabolomics Data Analysis

Supervised machine learning (SML) is an approach that learns from training data with known category membership to predict the unlabeled test data. There are many SML approaches in the literature and most of them use a linear score to learn its classifier. However, these approaches fail to elucidate biodiversity from heterogeneous biomedical data. Therefore, their prediction accuracies become low. Partial Least Square Linear Discriminant Analysis (PLS-LDA) is widely used in gene expression (GE) and metabolomics datasets for predicting unlabelled test data. Nevertheless, it also does not consider the non-linearity and heterogeneity pattern of the datasets. Hence, in this study, an improved PLS-LDA (IPLS-LDA) was developed by capturing the heterogeneity of datasets through an unsupervised hierarchical clustering approach. In our approach a non-linear score was calculated by combining all the linear scores obtained from the clustering method. The performance of IPLS-LDA was investigated in a comparison with six frequently used SML methods (SVM, LDA, KNN, Naïve Bayes, RF, PLS-LDA) using one simulation data, one colon cancer gene expression data (GED) and one lung cancer metabolomics datasets. The resultant IPLS-LDA predictor achieved accuracy 0.841 using 10-fold cross validation in colon cancer data and accuracy 0.727 from two independent metabolomics data analysis. In both the cases IPLS-LDA outperformed other SML predictors. The proposed algorithm has been implemented in an R package, Uplsda was given in the https://github.com/snotjanu/UplsLda.
Topological insulators on the decorated honeycomb lattice

We show that the decorated honeycomb (\star") lattice supports a number of topological insulating phases with a non-trivial Z2 invariant and time-reversal symmetry protected gapless edge modes. We investigate the stability of these phases with respect to various symmetry breaking perturbations and demonstrate the connection to the recent discovery of an exactly solvable S = 1=2 chiral spin liquid model [Phys. Rev. Lett. 99, 247203 (2007)] with non-Abelian and Abelian excitations on the same lattice at strong interaction strength. Our work highlights the relationship between non-interacting topological band insulators and strongly interacting topologically ordered spin systems, and points to promising avenues for enlarging the number of known examples of both.
On special subgroups of fundamental group

Suppose ? is a nonzero cardinal number, I is an ideal on arc connected Topological space X, and B? I(X) is the subgroup of ? 1(X) (the first fundamental group of X) generated by homotopy classes of ? _I loops. The main aim of this text is to study B? I(X)s and compare them. Most interest is in ? {? ,c} and I ? {Pfin(X), {? }}, where Pfin(X) denotes the collection of all finite subsets of X. We denote B? {? }(X) with B? (X). We prove the following statements: for arc connected topological spaces X and Y if B? (X) is isomorphic to B? (Y) for all infinite cardinal number ? , then ? 1(X) is isomorphic to ? 1(Y); there are arc connected topological spaces X and Y such that ? 1(X) is isomorphic to ? 1(Y) but B? (X) is not isomorphic to B? (Y); for arc connected topological space X we have B? (X) ? Bc(X) ? 1(X); for Hawaiian earring X, the sets B? (X), Bc(X), and ? 1(X) are pairwise distinct. So B? (X)s and B? I(X)s will help us to classify the class of all arc connected topological spaces with isomorphic fundamental groups.
A Simple and Exact Simulation Approach to Heston Model

In this paper we will propose a simple approach to simulating Heston model efficiently and accurately. All existing simulation schemes so far directly work with the mean-reverting square root process of the variance in Heston model, instead we transform the variance to an equivalent volatility which follows a mean-reverting Ornstein-Uhlenbeck process. We will show it is more convenient to simulate the transformed volatility process than the original variance process since the new Ornstein-Uhlenbeck process does not have any term of square root, and is not restricted to any parameter restriction. Based on the transformed volatility process, we suggest a simple and exact scheme for the simulation of Heston model. Numerical examples show that the new scheme and Andersen's QE scheme perform very closely, and outperform other schemes such as log-normal scheme. While QE scheme suffers from the problem of "leaking correlation", transformed volatility scheme does not, and therefore, provides a high-quality alternative to the existing simulation schemes for Heston model.
A Survey of Personalized Interior Design

Interior design is the core step of interior decoration, and it determines the overall layout and style of furniture. Traditional interior design is usually laborious and time‐consuming work carried out by professional designers and cannot always meet clients' personalized requirements. With the development of computer graphics, computer vision and machine learning, computer scientists have carried out much fruitful research work in computer‐aided personalized interior design (PID). In general, personalization research in interior design mainly focuses on furniture selection and floor plan preparation. In terms of the former, personalized furniture selection is achieved by selecting furniture that matches the resident's preference and style, while the latter allows the resident to personalize their floor plan design and planning. Finally, the automatic furniture layout task generates a stylistically matched and functionally complete furniture layout result based on the selected furniture and prepared floor plan. Therefore, the main challenge for PID is meeting residents' personalized requirements in terms of both furniture and floor plans. This paper answers the above question by reviewing recent progress in five separate but correlated areas, including furniture style analysis, furniture compatibility prediction, floor plan design, floor plan analysis and automatic furniture layout. For each topic, we review representative methods and compare and discuss their strengths and shortcomings. In addition, we collect and summarize public datasets related to PID and finally discuss its future research directions.
An Ontology-Based Knowledge Model for Software Experience Management

The efficient management of experience knowledge is vital in today’s knowledgebased economy. This paper is concerned with proposing a model for software experience knowledge. The model is aimed to represent the backend of knowledge management tools that support organisational learning activities in a typical software organisation. Generic knowledge models have failed to produce good quality software experience management tools. The diversity in the types and forms of software experience knowledge makes it necessary to establish customised knowledge models to effectively accommodate such domainspecific knowledge. Our model extends the simple generic knowledge models that usually rely on non parameterised knowledge (i.e. free text) or that just reflect certain types of software experience knowledge (tacit or explicit). In contrast, our model aims to strike a delicate balance between explicit and tacit knowledge that in a way act as correlated information sources. This model can be easily adapted to software-oriented knowledge management tools eliminating many limitations of existing knowledge models used for the same purpose.
DNA recognition by proteins with the helix-turn-helix motif.

INTRODUCTION. 933 NOTIONS ABOUT RECOGNITION. 934 THE HTH MOTIF. 936 STRUCTURES. 937 Phage 434 Repressor and Cro 937 Lambda Repressor and Cro . , " . ,',. ,', . ,',. ,"'" . "',. ,',. 949 trp Repressor . , . , , 954 lac Repressor DNA-Binding Domain 958 CAP . " . , . , . " . , . 959 The Antp Homeodomain . ,', . ,"',. ,", . , . ,', . ,"" . ", . ,", . ,"' . "'. 961 COMMON FEATURES , ' , 962 Families of HTH Domains . 962 Characteristics of ProteinlDNA Contacts 963 Anchoring the HTH to DNA 963 RECOGNITION . 965