Miracle-dz/UniFAR-FTUs huggingface dataset:
Interactions between dietary fat type and exogenous enzyme supplementation of broiler diets based on maize, wheat, triticale or barley

Four growth experiments and a balance study were carried out to examine the effects of different fat types (beef tallow or soyabean oil) in broiler diets based on wheat, triticale, maize or barley in response to feed enzyme supplementation. Performance parameters were recorded over 35 days. Viscosity in the ileal digesta, apparent digestibility of fat and protein at the terminal ileum were measured at day 21 of age. In addition, fat digestibility was measured at the faecal level along with apparent metabolizable energy value (AME N ) and apparent net protein utilization (NPU a). It was found that enzyme addition to all diets improved feed to gain ratio significantly. This was most visible in triticaleand barley-based diets supplemented with tallow than in the soyabean oilcontaining counterparts until 21 days of age. Effects became smaller or disappeared when the whole fattening period was considered. Significantly better performance of broilers fed soyabean oil compared with tallow-containing diets was observed over the whole fattening period. Intestinal viscosity was significantly reduced by enzyme addition to all diets. Furthermore, significantly higher intestinal viscosity was found in tallow-fed birds (triticale-, barleyor maize-based diets). Apparent protein digestibility at the terminal ileum was not affected by fat type but was Corresponding author: Sven Danicke, Institute of Animal Nutrition, Federal Agricultural Research Centre, Braunschweig (FAL), Bundesallee 50, D-38 116 Braunschweig, Germany 468 FAT AND EXOGENOUS ENZYME FOR BROILER improved by enzyme supplementation in wheatand barley-based diets. Fat digestibility at both the ileal and faecal levels was significantly higher in birds fed the soyabean oil-containing diets and was significantly improved after enzyme supplementation. The enzyme effect on fat digestibility was more pronounced at the faecal level and was positively correlated to A M E N and NPU a.
Production of Maize Silage is Possible in Integrated Systems with Arboreal Component

Distribution of the intercropped plants determines the production but it is highly dependent on the machinery of the property. Producers, who harvest silage row by row, depend on plantings with greater spacing. This study was aimed to evaluate the maize intercropped for cultivated silage in 0.90 m between rows, with grass under the shade and full sunlight conditions. Maize with brachiaria grass was tested in four sowing densities (0, 2, 4 and 6 kg of pure and viable seeds per hectare). The factorial treatments (2x2x4) were distributed in a split-plot design with four repetitions. The maize agronomic characteristics and the silage quality were evaluated. There was a high level of competition when associated with maize, piatã and eucalyptus. Aggressive piatã grass growth, with light restriction by trees, have affected strongly the maize forage mass-produced, and consequently, reduced silage production. Regarding grain yield, the intercrop with ruziziensis grass was superior (210%) to the intercrop with piatã grass. It was mainly influenced by the low yield in the piatã grass intercropped under shade conditions. This pattern was different for ruziziensis because it was a less aggressive grass in terms of growth. For plantations with 0.90 m of spacing, there was a light restriction. The maize intercropped under the shade of trees must be done with lower growth rate grass to reduce competition and maintain the yield.
The Establishment of Physical Aspects of Science Laboratory Environment Inventory (PSLEI)

The purpose of this study is to develop and validate the learning environment instrument designed to identify teachers’ perceptions towards the physical aspect of science learning environment in secondary schools in Malaysia. Through extensive review of the literature and interviews with experienced teachers, items contribute to the physical learning environment in the science laboratory are identified. In order to enhance the validity of this instrument, two experts are invited to review the instrument. In addition, 800 teachers are involved in this study and validated the instrument, revealing six scales regarding physical aspects of the learning environment. The six scales are (1) furniture and equipment; (2) space; (3) lighting; (4) technology; (5) indoor air quality; and (6) safety aspects. Each item in the instrument has a factor loading range between 0.85 and 0.45, while the alpha reliability coefficient for each scale ranges between 0.86 and 0.76. The findings of this study confirm the validity and reliability of the physical science laboratory environment inventory.
Ciliary IFT80 regulates dental pulp stem cells differentiation by FGF/FGFR1 and Hh/BMP2 signaling

Primary cilia and intraflagellar transport (IFT) proteins control a wide variety of processes during development and tissue homeostasis. However, their potential roles in the regulation of stem cell differentiation and tooth development remain elusive. Here, we uncovered the critical roles of ciliary IFT80 in cilia formation and differentiation of dental pulp stem cells (DPSCs). IFT80-deficient DPSCs showed reduced fibroblast growth factor receptor 1 (FGFR1) expression, leading to the disruption of FGF2-FGFR1 signaling. We found, during DPSC differentiation, FGF2-FGFR1 signaling induces stress fiber rearrangement to promote cilia elongation, meanwhile stimulates PI3K-AKT signaling to aid Hh/bone morphogenetic protein 2 (BMP2) signaling activation. These signaling pathways and their coupling were disrupted in IFT80-deficient DPSCs, causing impaired differentiation. Our findings revealed a novel mechanism that ciliary protein regulates the odontogenic differentiation of DPSCs through FGF/FGFR1 and Hh/BMP2 signaling.
Product-market competition, corporate governance and innovation: evidence on US-listed firms

The debate on competition and innovation has produced a wide range of theoretical and empirical findings. Recently, corporate governance quality has emerged as an additional factor that may complement or substitute for competition’s effect on innovation. We aim to contribute to the debate by investigating whether product-market competition and corporate governance quality affect firm-level innovation, utilising a dataset for 1,400 non-financial US-listed companies. Using two-way cluster-robust estimation, we report several findings. First, the relationship between industry-level competition and input as well as output measures of innovation is non-linear. Secondly, the non-linear relationship is of an inverted-U shape with respect to input measures of innovation, but the relationship has a U-shape when output measure of innovation is estimated. Third, corporate governance indicators such as anti-takeover defences and insider control tend to have a negative effect on input measures of innovation but their effect is positive with respect to the output measure. Finally, when interacted with market concentration, anti-takeover defences and insider control emerge as substitutes, leading to sign reversals in the relationship between competition and innovation. The results are obtained by using two-way cluster-robust estimation that controls for dependence within company/year and industry/year clusters, but they are robust to different estimation methods including fixed-effect and Fama-Macbeth procedure.
Progress in organ 3D bioprinting

Three dimensional (3D) printing is a hot topic in today’s scientific, technological and commercial areas. It is recognized as the main field which promotes “the Third Industrial Revolution”. Recently, human organ 3D bioprinting has been put forward into equity market as a concept stock and attracted a lot of attention. A large number of outstanding scientists have flung themselves into this field and made some remarkable headways. Nevertheless, organ 3D bioprinting is a sophisticated manufacture procedure which needs profound scientific/technological backgrounds/knowledges to accomplish. Especially, large organ 3D bioprinting encounters enormous difficulties and challenges. One of them is to build implantable branched vascular networks in a predefined 3D construct. At present, organ 3D bioprinting still in its infancy and a great deal of work needs to be done. Here we briefly overview some of the achievements of 3D bioprinting technologies in large organ, such as the bone, liver, heart, cartilage and skin, manufacturing.
Exploration through Interactive Visualization

Blogs are widely used today to publish information on a regular basis. However, users have difficulty in exploring their content and in discovering relevant information. This is due, among other things, to blogs rigid structure, with very long pages, and to the lack of mechanisms for effective navigation and exploration. To overcome these problems, we developed an exploration tool, to help users navigate, browse and visualize blogs. It was developed based on the following four design principles: i) a blog should provide an overview of its activity and content to help users identify publication patterns and relevant entries; ii) blogs should present rich compact representations of entries to help readers anticipate the content of posts; iii) comments should have a relevant role, since they convey the social component of the blog; iv) blogs should offer an interactive filtering mechanism to help users explore and find relevant posts. A comparative evaluation with users confirmed the validity of the design principles, since our solution was more efficient, effective and usable than the usual blog interface and the Google Reader.
Multivariate adaptive regression splines

Abstract : A new method is presented for flexible regression modeling of high dimensional data. The model takes the form of an expansion in product spline basis functions, where the number of basis functions as well as the parameters associated with each one (product degree and knot locations) are automatically determined by the data. This procedure is motivated by the recursive partitioning approach to regression and shares its attractive properties. Unlike recursive partitioning, however this method produces continuous models with continuous derivatives. It has more power and flexibility to model relationships that are nearly additive or involve interactions in at most a few variables. In addition, the model can be represented in a form that separately identifies the additive contributions and those associated with the different multivariable interactions.
New microsatellite markers developed from an enriched microsatellite common bean library

The objective of this work was to develop new microsatellite markers in common bean. Ninety nine new microsatelitte loci were developed from a microsatellite enriched library for (CT)8 and (GT)8 motifs, from CAL-143 line. The majority of microsatellite sequences (51%) was related to cellular metabolism. The remaining sequences were associated to transcription functions. Only 17.2% of the sequences presented some level of similarity with other plant species genes.
Optimum and Practical Noncausal Smoothing Filters for Estimating Carrier Phase With Phase Process Noise

Communications Ground Systems Section Noncausal smoothing fllters have signiflcant performance advantages over causal fllters for estimation of the phase of radio frequency signals. This article presents the optimum smoothing fllters for the cases where the spectral density of the carrier phase is of the form f ifi , where fi =3 is typical of oscillator noise and fi =8 = 3is typical of phase perturbations due to propagation through charged particles, such as solar wind. It is shown that the optimum smoothers perform approximately 5-dB better than causal fllters of optimum bandwidth, and that the performance of practical-to-implement smoothing fllters is within 0.03 to 0.24 dB of the optimum smoothers. Some important examples where smoothing can be used are in the Deep Space Network Galileo Telemetry System, where the data are recorded and processed in nonreal time; in the DSN Block V Receiver, which provides data bufiering of su‐cient size to enable near-real-time smoothing; and in processing recorded radio science data, where carrier amplitude and phase are the primary data.
A Consistent Track-to-Track Fusion Method Based on Copula Theory

This paper addresses the problem of distributed fusion when the conditional independence assumptions on sensor measurements or local estimates are not met. A new data fusion algorithm called Copula fusion is presented. The proposed method is grounded on Copula statistical modeling and Bayesian analysis. The primary advantage of the Copula-based methodology is that it could reveal the unknown correlation that allows one to build joint probability distributions with potentially arbitrary underlying marginals and a desired intermodal dependence. The proposed fusion algorithm requires no a priori knowledge of communications patterns or network connectivity. The simulation results show that the Copula fusion brings a consistent estimate for a wide range of process noises.
Chapter 2 Epidemiology of Environmental Health

There has been a growing awareness of environmental effects among human. More epidemiologic studies have been triggered toward investigating exposure effects of chemical, social or physical factors in relation to the common or complex diseases, such as heart disease, cancer, and diabetes afterward. Following recent advances in genomics and risk assessment, environmental epidemiologic studies are incorporating gene-environment interactions and epigenetic changes to explore the multidisciplinary nature of individual. The challenges for human population work in this fi eld include the complexity of exposure biology and the small effects that are easily disturbed. Several strategies have been developed with an attempt to resolve these challenges, such as the development of exposome, the two-stage designs and Mendelian randomization. In this chapter, the conventional study design features, including particular strengths and limitations, have been summarized.
Model Predictive Torque Ripple Reduction with Weighting Factor Optimization Fed by an Indirect Matrix Converter

Abstract—Model predictive control has emerged as a powerful control tool in the field of power converter and drive's system. In this article, a weighting factor optimization for reducing the torque ripple of induction machine fed by an indirect matrix converter is introduced and presented. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponding to minimum torque ripple. However, model predictive torque and flux control of the induction machine with conventionally selected weighting factor is being investigated in this article and is compared with the proposed optimum weighting factor based model predictive control algorithm to reduce the torque ripples. The proposed model predictive control scheme utilizes the discrete phenomena of power converter and predicts the future nature of the system variables. For the next sampling period, model predictive method selects the optimized switching state that minimizes a cost function based on optimized weighting factor to actuate the power converter. The introduced weighting factor optimization method in model predictive control algorithm is validated through simulations and shows potential control, tracking of variables with their respective references and consequently reduces the torque ripples corresponding to conventional weighting factor based predictive control method.
SP ] 2 N ov 2 01 4 SOS-Hankel Tensors : Theory and Application

Hankel tensors arise from signal processing and some other applications. SOS (sum-ofsquares) tensors are positive semi-definite symmetric tensors, but not vice versa. The problem for determining an even order symmetric tensor is an SOS tensor or not is equivalent to solving a semi-infinite linear programming problem, which can be done in polynomial time. On the other hand, the problem for determining an even order symmetric tensor is positive semi-definite or not is NP-hard. In this paper, we study SOS-Hankel tensors. Currently, there are two known positive semi-definite Hankel tensor classes: even order complete Hankel tensors and even order strong Hankel tensors. We show complete Hankel tensors are strong Hankel tensors, and even order strong Hankel tensors are SOS-Hankel tensors. We give several examples of positive semi-definite Hankel tensors, which are not strong Hankel tensors. However, all of them are still SOS-Hankel tensors. Does there exist a positive semi-definite non-SOS-Hankel tensor? The answer to this question remains open. If the answer to this question is no, then the problem for determining an even order Hankel tensor is positive semidefinite or not is solvable in polynomial-time. An application of SOS-Hankel tensors to the positive semi-definite tensor completion problem is discussed. We present an ADMM algorithm for solving this problem. Some preliminary numerical results on this algorithm are reported.
In Silico Prediction of Cell Wall Remodeling Genes in Tomato, Banana, Melon and Grape

Ripening is a complex developmental process and involves many events such as textural and constitutional changes. The texture of fleshy fruits is one of the major criteria for consumer choice. However, the molecular determinants of ripening- associated changes in texture or “softening” are relatively poorly understood and seem to involve a large number of cell wall remodelling factors. The recent completion of the tomato genome sequence has revealed more than 50 cell wall structure-related genes that are expressed during fruit development and ripening and may impact texture changes in this fruit. The aim of the project is to compare, on a genome-wide scale, ripening-related gene expression in a range of fleshy fruits and especially those linked with cell wall remodelling. Then by identifying orthologous genes in different fruit species to make predictions about those genes likely to important for the softening process in all fleshy fruits. Comparative genomics analysis of tomato ( Solanum lycopersicum ), banana ( Musa acuminate ), melon ( Cucumis melo ) and grape ( Vitis vinifera ), has been undertaken using Inparanoid, Multiparanoid and BLAST2GO software. This analysis showed that a total of 8,982 (25.86%) gene models could be identified in common between all four genomes based on comparison of amino acid sequences. Of these genes, 262 in tomato, 252 in grape, 261 in melon, and 198 in banana were identified as encoding cell wall structure-related proteins. However, comparison of the expression patterns of these genes revealed that most were expressed in tissues other than ripening fruits, and of the fruit expressed genes only a small number were common between different fruit species. This in silico analysis should provide additional clues as a target for manipulation of fruit softening in a range of fleshy fruit species. These also provide new opportunities to develop varieties of tomatoes that can survive the trip from the farm to the grocery store whilst maintaining excellent flavour and shelf-life.
Cliques of single-cell RNA-seq profiles reveal insights into cell ecology during development and differentiation

The lack of a formal link between cell-cell cohabitation and its emergent dynamics into cliques during development has hampered our understanding of how cell populations proliferate, differentiate, and compete, i.e. the cell ecology. With the advancement of single-cell RNAsequencing (RNA-seq), we have now come closer to describing such a link by taking cell-specific transcriptional programs into account, constructing graphs of a network that reflect the similarity of gene expression, and analyzing these graphs using algebraic topology. We proposed single-cell topological simplicial analysis (scTSA). Applying this approach to single-cell gene expression profiles from local networks of cells in different developmental stages with different outcomes revealed a previously unseen topology of cellular ecology. These networks contain an abundance of cliques of single-cell profiles bound into cavities that guide the emergence of more complicated habitation forms. We visualize these ecological patterns with topological simplicial architectures of these networks, compared with the null models. Benchmarked on single-cell RNA-seq of zebrafish embryogenesis over 25 cell types and 12 time steps, our approach highlights the gastrulation as the most critical stage, consistent with consensus in developmental biology. As a nonlinear, model-independent, and unsupervised framework, our approach can also be applied to tracing multi-scale cell lineage, identifying critical stages, or creating pseudo-time series. Simplicial Filtration Unlike traditional TDA, we computed simplices into high dimension (towards 7) during the entire filtration process (as above). Lazy Witness Complex As the number of cells collected in each time points vary differently, direct simplicial computation can be incomparable. For these larger datasets, if we include every data point as a vertex, the filtrated simplicial complexes can quickly contain too many simplices for efficient computation. Instead, we extracted lazy witness complexes by sampling n data points [1] with sequential maxmin procedure [2] setting nearest neighbor inclusion of 2 (as in “lazy”). Control Models for scTSA Usually for binary connectivity data (like brain connectome), Erdős-Rényi random graph [3] can be used as control. However, in similarity-based data, the connectivity is entirely dependent on the filtration factor. To avoid this caveat, we take a different approach by shuffling the pairwise distances of the data points, such that the MDS embedding can form different connectivity profiles but maintain the same distance distribution.
Aalborg Universitet Autonomous Active and Reactive Power Distribution Strategy in Islanded

This paper proposes an autonomous active and reactive power distribution strategy that can be applied directly on current control mode (CCM) inverters, being compatible as well with conventional droop-controlled voltage control mode (VCM) converters. In a microgrid, since renewable energy sources (RES) units regulate different active power, the proposed reactive power distribution is adaptively controlled according to the active power distribution among energy storage systems (ESS) and RES units. The virtual impedance is implemented in order to improve the reactive power sharing in a distributed way. Real-time hardware-in-the-loop results are presented to verify the proposed control strategy.