Miracle-dz/UniFAR-FTUs huggingface dataset:
An Improved Trans-Z-Source Inverter with Continuous Input Current and Boost Inversion Capability

The paper deals with a new family of high boost voltage inverters which improve upon the conventional trans-Z-source inverter and trans-quasi-Z-source inverters. The improved trans-Z-source inverter (ITZI) that provides continuous input current and a higher boost voltage inversion capability. In addition the improved inverter can suppress resonant current at start up, which might destroy the device. In comparison to the conventional trans-Z-source and trans-quasi-Z-source inverters, for same transformer turn ratio, input and output voltages, the improved inverter has a higher modulation index with reduced voltage stress on the DC link, lower current stress flow on the transformer windings and diode, are validated by simulating (ITZI) in MATLAB/SIMULINK.
PROXIMATE CONTENT AND ANTIOXIDANT PROFILE OF PUMPKIN (Cucurbita pepo L.) LEAFY VEGETABLE AS INFLUENCED BY NPK FERTILIZER OLOYEDE F.M.1*, OBUOTOR E. M.2 and OBISESAN I.O.3

This study evaluated the influence of NPK fertilizer on the proximate content and antioxidant profile of pumpkin leafy vegetable. The vegetable was raised at the Teaching and Research Farm, Obafemi Awolowo University, Nigeria in 2010 for two seasons and the following NPK fertilizer rates were applied: 0, 50, 100, 150, 200 and 250 kg/ha and replicated six times. Six composite samples from the six replications were analyzed in duplicates for proximate content and antioxidant profile. For the antioxidant assays, crude extract was obtained from cold extraction of each of the samples with 80% methanol and evaporated to dryness. The hydrogen donating or radical scavenging of the extract was determined using the stable radical DPPH (2, 2-diphenyl-2-picrylhydrazyl hydrate). Total phenol content was determined by the method of Singleton and Rossi using the Folin – Ciocalteau reagent in alkaline medium while total flavonoid content was determined using AlCl3 method as described by Lamaison and Carnet. The proanthocyanidin content was determined using a modified method of Porter et al, using the AlCl / Butan – 1-0l assay method while the total anthocyanin content of the test samples was determined using the pH differential method of Fuleki and Francis as described by Guisti and Wrolstad. Crude protein, Carbohydrate, Ash, Crude fibre, Ether extract (fat) and Moisture contents were determined using the routine chemical analytical methods of Association of Official Agricultural Chemists (AOAC). The chemical compositions analyzed were reduced significantly when fertilizer rate exceeded 100 kg NPK/ha. The proximate values in pumpkin leaves are 23.8, 0.18, 1.65, and 2.16 g/100g for protein, fat, ash and crude fibre respectively. Fertilizer rates from 150 – 250 kg/ha reduced these values by 10 – 40%. With the increase in fertilizer rates from 100 kg – 250 kg/ha, antioxidant activities was reduced by 19%, phenol by 57% and flavonoid by 65%. For the food value and bioactive compounds of pumpkin to be retained, NPK fertilizer application should not exceed 100 kg/ha if it must be applied.
Enhancement of additives polymeric drag resistance to degradation

Liquid transportation in strategic pipelines consumes high percentage of energy often attributed to the amount of energy required to pump these liquids to their desired destination. As the liquid experience turbulent associated with their mode of transportation, there is a reduced flow rate. Most materials which could enhance such movement degrade over time as a result of shear stress and at high temperatures, this could be greatly improved upon by the physiochemical interactions between polymers molecules and surfactants micellar aggregates since individual materials are less effective. This paper in introduce a novel complex system to enhance Degradation of Polymeric Drag by using, polymer and surfactant. These materials were tested individually and the complexes were as well examined in a Brookfield viscometer and a Rotating Disk apparatus (RDA) at varied concentrations and speed (r.p.m). From the experimental results, it could be observed that, the drag reduction of this complex mixture of polymer anionic with surfactant anionic has better performance than their individual drag reduction. This could be as a result of the critical role played by the complex mixtures which is greatly dependent upon the alky chain in the surfactant.
Bootstrapping Hypothesis Tests and Confidence Regions

It will be shown that under regularityconditions, applying the Olive (2013) large sample 100(1 �)%prediction region to the bootstrap sample T � 1,. ,T � B gives a large sample 100(1 �)% confidence region for an r×1 parameter vector µ, generalizing the percentile method for r = 1 to r � 1. This prediction region method will be compared to the Efron (2014) confidence interval for variable selection, and used to bootstrap a correlation matrix. Consider testing H0 : µ = c versus H1 : µ 6 c where c is a known r×1 vector. Let ˆ µ be a consistent estimator of µ and make a bootstrap sample wi = ˆ µ � c for i = 1,. ,B. Make the prediction region for the wi and determine whether 0 is in the prediction region. Bootstrapping test statistics is well known, and the prediction region method can be regarded as a special case where the bootstrapped test statisticis the squared Mahalanobis distance D 2 0 = (T � µ0) T [S �] 1 (T � µ0) where the bagging esti
xpression levels or invasive capacity in saphenous vein smooth muscle cells ultured from different patients

Matrix metalloproteinase-9 (MMP-9) is an important regulator of vascular smooth muscle cell (SMC) invasion and proliferation. The T allele of the −1562C/T MMP-9 promoter polymorphism reportedly confers increased MMP-9 promoter activity, plasma MMP-9 levels and susceptibility to vascular pathologies. The aim of this study was to determine whether the MMP-9 −1562C/T polymorphism directly influences endogenous MMP-9 expression levels in saphenous vein (SV) SMC cultured from patients with different genotypes. Genotyping of 408 patients revealed −1562C/T genotype frequencies of 73.3% CC, 25.0% CT and 1.7% TT. Using a standardized, controlled protocol we investigated the effects of phorbol ester (TPA) and a physiological stimulus (PDGF + IL-1) on MMP-9 expression in cultured SV-SMC from 15 CC, enotype uman mooth muscle cells aphenous vein nvasion 15 CT and 3 TT patients, and on PDGF + IL-1-induced SV-SMC invasion (Boyden chamber with Matrigel barrier). A strong correlation between MMP-9 mRNA levels (real-time RT-PCR) and MMP-9 protein secretion (gelatin zymography) was observed. However, no significant differences were observed in MMP-9 expression levels, or in SV-SMC invasion, between cells with different −1562C/T genotypes. Moreover, MMP-9 promoter activity of the C and T variants was similar. Our data challenge the functional nature of the −1562C/T polymorphism and its capacity to modulate MMP-9 expression levels and SV-SMC invasion, to vas and hence susceptibility
Mediating role of supervisor on the association between work stress with physical and psychological symptoms among employees of Isfahan Steel Company in 2012

Received: December 2013, Accepted: November 2013 Background: Nowadays job stress is one of the most important health problems that health and safety professionals are facing with. Much of previous studies have focused on interventions such as stress management and, they have ignored the role of psychosocial factors in occurrence of job stress. This study investigated the mediator role of supervisor support on the association between work stress and both physical and psychological symptoms, among Isfahan steel company employees in 2012. Materials and Methods: The study questionnaire was completed by 189 employees of Isfahan Steel Company in 2012 who accepted to help with this descriptive study. The questionnaire consisted of items asking about work stress, physical and psychological symptoms as well as supervisor support. Results: There were significant intercorrelations between the dependent and independent variables under research. Hierarchy regression analysis showed that supervisor support partially mediated the relationship between work stress and physical and psychological symptoms (p<0.05). Conclusion: It was concluded that supervisor support is a protective shield against the effects of stress on psychological and physical health, among employees working in the steel company.
The structural-informational power of business: credibility, signalling and the UK banking reform process

ABSTRACT This article seeks to provide a better understanding of why business power varies over time and between firms. It assumes that business influence derives from firms’ ability to send credible information signals about policy costs, causing policy-makers to amend proposals. This ‘structural-informational’ power is mediated by two factors. First, the structure of the policy process enables policy-makers to assess the credibility of industry claims through institutional screening mechanisms, which vary over time. Second, the influence of individual firms is dependent on anticipated policy costs and past reputational damage, leading them to pursue different signalling strategies to maximize credibility. These claims are illustrated using the case study of United Kingdom banking reform between 2010 and 2013. Structural-informational power helps to explain why bank ‘ring-fencing’ reforms were agreed in the face of powerful industry opposition, but also why specific banks were subsequently able to extract important policy concessions.
Responsiveness optimisation in the fractal supply network

Responsiveness is one of the significant performance measures in today's market based on which organisations can measure their success in seizing markets opportunities within Fractal Supply Chain. This paper aims to present this fractal supply network and also proposes a new mathematical model through which replenishment; transportation, production and handling time can be optimised at different stages of the fractal supply network. Both the proposed Fractal Supply Network and the mathematical model are implemented and validated using Supply Chain GURU Software. Application of the proposed mathematical model has led to a reduction in the total replenishment time and enables practitioners to systematically decide upon the optimum replenishment time at different stage of the network.
Effects of attachment sites and joint angle at the time of lateral suture fixation on tension in the suture for stabilization of the cranial cruciate ligament deficient stifle in dogs.

OBJECTIVE To investigate the influence of different sites of lateral suture fixation for stabilization of the cranial cruciate ligament (CCL) deficient stifle and different joint angles at time of tightening on suture tension. STUDY DESIGN Controlled laboratory study. SAMPLE POPULATION Stifle joints (n=9) of dogs >or=20 kg. METHODS After CCL transection, each stifle was stabilized using 12 combinations of 4 different methods of lateral suture stabilization (LSS) and 3 different joint angles at time of suture tightening. Load within the suture throughout a full range of passive motion (ROM) was measured for each combination using a custom made load cell. RESULTS All 4 LSS methods had an increase in suture tension on stifle flexion. LSS with the suture looped around the lateral fabella and secured to the proximal aspect of the tibia through 2 parallel drill holes at the tibial crest had the least change in suture tension during ROM. Tightening the suture at 70 degrees joint angle resulted in a significant loss of suture tension on extension. CONCLUSIONS None of the LSS resulted in constant suture tension, questioning current recommendations regarding "isometric" points for lateral suture fixation. Tightening the suture with the stifle held in flexion may result in joint instability on extension. CLINICAL RELEVANCE LSS as commonly performed is associated with a significant increase in suture tension on flexion of the stifle, potentially over-constraining the joint. Tightening should be performed with the stifle in slight extension rather than in flexion.
A Method of Traffic Lights Detection Based on Visual Selective Attention

In this paper, the candidate target traffic lights under different backgrounds were automatically detected with the visual selective attention mechanism. The region of interest in color image was projected into the gray, and the gray image enhancement was done through top-hat algorithm. The binary image was obtained by using Otsu's method. And finally the logical 'and' operation was carried out for the binary image and the binary image which was obtained according to threshold segmentation in HSI space. The detection on depth information feature of the lights surrounded by the dark boundary was applied to the interested target candidate region. Experimental results show that this method was robust.
Title Steering time-dependent estimation of posteriors with hyperparameterindexing in Bayesian topic models

This paper provides a new approach to topical trend analysis. Our aim is to improve the generalization power of latent Dirichlet allocation (LDA) by using document timestamps. Many previous works model topical trends by making latent topic distributions timedependent. We propose a straightforward approach by preparing a different word multinomial distribution for each time point. Since this approach increases the number of parameters, overfitting becomes a critical issue. Our contribution to this issue is two-fold. First, we propose an effective way of defining Dirichlet priors over the word multinomials. Second, we propose a special scheduling of variational Bayesian (VB) inference. Comprehensive experiments with six datasets prove that our approach can improve LDA and also Topics over Time, a well-known variant of LDA, in terms of test data perplexity in the framework of VB inference.
Efficient Ridge Solution for the Incremental Broad Learning System on Added Nodes by Inverse Cholesky Factorization of a Partitioned Matrix

To accelerate the existing Broad Learning System (BLS) for new added nodes in [7], we extend the inverse Cholesky factorization in [10] to deduce an efficient inverse Cholesky factorization for a Hermitian matrix partitioned into 2 * 2 blocks, which is utilized to develop the proposed BLS algorithm 1. The proposed BLS algorithm 1 compute the ridge solution (i.e, the output weights) from the inverse Cholesky factor of the Hermitian matrix in the ridge inverse, and update the inverse Cholesky factor efficiently. From the proposed BLS algorithm 1, we deduce the proposed ridge inverse, which can be obtained from the generalized inverse in [7] by just change one matrix in the equation to compute the newly added sub-matrix. We also modify the proposed algorithm 1 into the proposed algorithm 2, which is equivalent to the existing BLS algorithm [7] in terms of numerical computations. The proposed algorithms 1 and 2 can reduce the computational complexity, since usually the Hermitian matrix in the ridge inverse is smaller than the ridge inverse. With respect to the existing BLS algorithm, the proposed algorithms 1 and 2 usually require about 13 and 2 3 of complexities, respectively, while in numerical experiments they achieve the speedups (in each additional training time) of 2.40 - 2.91 and 1.36 - 1.60, respectively. Numerical experiments also show that the proposed algorithm 1 and the standard ridge solution always bear the same testing accuracy, and usually so do the proposed algorithm 2 and the existing BLS algorithm. The existing BLS assumes the ridge parameter lamda->0, since it is based on the generalized inverse with the ridge regression approximation. When the assumption of lamda->0 is not satisfied, the standard ridge solution obviously achieves a better testing accuracy than the existing BLS algorithm in numerical experiments.
Systematic Analysis of Cluster Similarity Indices: Towards Bias-free Cluster Validation

There are many cluster similarity indices used to evaluate clustering algorithms and choosing the best one for a particular task is usually an open problem. In this paper, we perform a thorough analysis of this problem: we develop a list of desirable properties (requirements) and theoretically verify which indices satisfy them. In particular, we investigate dozens of pair-counting indices and prove that none of them satisfies all the requirements. Based on our analysis, we propose using the arccosine of the correlation coefficient as a similarity measure and prove that it satisfies almost all requirements (except for one, which is still satisfied assymptotically). This new measure can be thought of as an angle between partitions.
The Schrödinger-Poisson method for Large-Scale Structure

We study the Schrödinger-Poisson (SP) method in the context of cosmological large-scale structure formation in an expanding background. In the limit 0ℏ → , the SP technique can be viewed as an effective method to sample the phase space distribution of cold dark matter that remains valid on non-linear scales. We present results for the 2D and 3D matter correlation function and power spectrum at length scales corresponding to the baryon acoustic oscillation (BAO) peak. We discuss systematic effects of the SP method applied to cold dark matter and explore how they depend on the simulation parameters. In particular, we identify a combination of simulation parameters that controls the scale-independent loss of power observed at low redshifts, and discuss the scale relevant to this effect.
Scaling limits of permutations avoiding long decreasing sequences

We determine the scaling limit for permutations conditioned to have longest decreasing subsequence of length at most $d$. These permutations are also said to avoid the pattern $(d+1)d \cdots 2 1$ and they can be written as a union of $d$ increasing subsequences. We show that these increasing subsequences can be chosen so that, after proper scaling, and centering, they converge in distribution. As the size of the permutations tends to infinity, the distribution of functions generated by the permutations converges to the eigenvalue process of a traceless $d\times d$ Hermitian Brownian bridge.
Aplib: Tactical Programming of Intelligent Agents

This paper presents aplib, a Java library for programming intelligent agents, featuring BDI and multi agency, but adding on top of it a novel layer of tactical programming inspired by the domain of theorem proving. Aplib is also implemented in such a way to provide the fluency of a Domain Specific Language (DSL). Compared to dedicated BDI agent programming languages such as JASON, 2APL, or GOAL,aplib's embedded DSL approach does mean that \aplib\ programmers will still be limited by Java syntax, but on other hand they get all the advantages that Java programmers get: rich language features (object orientation, static type checking, $\lambda$-expression, libraries, etc), a whole array of development tools, integration with other technologies, large community, etc.
Inducing strong convergence of trajectories in dynamical systems associated to monotone inclusions with composite structure

Abstract In this work we investigate dynamical systems designed to approach the solution sets of inclusion problems involving the sum of two maximally monotone operators. Our aim is to design methods which guarantee strong convergence of trajectories towards the minimum norm solution of the underlying monotone inclusion problem. To that end, we investigate in detail the asymptotic behavior of dynamical systems perturbed by a Tikhonov regularization where either the maximally monotone operators themselves, or the vector field of the dynamical system is regularized. In both cases we prove strong convergence of the trajectories towards minimum norm solutions to an underlying monotone inclusion problem, and we illustrate numerically qualitative differences between these two complementary regularization strategies. The so-constructed dynamical systems are either of Krasnoselskiĭ-Mann, of forward-backward type or of forward-backward-forward type, and with the help of injected regularization we demonstrate seminal results on the strong convergence of Hilbert space valued evolutions designed to solve monotone inclusion and equilibrium problems.
Unveiling the most luminous Lyman-α emitters in the epoch of reionisation

Abstract Distant luminous Lyman-α emitters are excellent targets for detailed observations of galaxies in the epoch of reionisation. Spatially resolved observations of these galaxies allow us to simultaneously probe the emission from young stars, partially ionised gas in the interstellar medium and to constrain the properties of the surrounding hydrogen in the circumgalactic medium. We review recent results from (spectroscopic) follow-up studies of the rest-frame UV, Lyman-α and [CII] emission in luminous galaxies observed ∼500 Myr after the Big Bang with ALMA, HST/WFC3 and VLT/X-SHOOTER. These galaxies likely reside in early ionised bubbles and are complex systems, consisting of multiple well separated and resolved components where traces of metals are already present.
Index Tracking with Cardinality Constraints: A Stochastic Neural Networks Approach

Partial (replication) index tracking is a popular passive investment strategy. It aims to replicate the performance of a given index by constructing a tracking portfolio which contains some constituents of the index. The tracking error optimisation is quadratic and NP-hard when taking the ℓ0 constraint into account so it is usually solved by heuristic methods such as evolutionary algorithms. This paper introduces a simple, efficient and scalable connectionist model as an alternative. We propose a novel reparametrisation method and then solve the optimisation problem with stochastic neural networks. The proposed approach is examined with S&P 500 index data for more than 10 years and compared with widely used index tracking approaches such as forward and backward selection and the largest market capitalisation methods. The empirical results show our model achieves excellent performance. Compared with the benchmarked models, our model has the lowest tracking error, across a range of portfolio sizes. Meanwhile it offers comparable performance to the others on secondary criteria such as volatility, Sharpe ratio and maximum drawdown.
ContamiNet: Detecting Contamination in Municipal Solid Waste

Leveraging over 30,000 images each with up to 89 labels collected by Recology---an integrated resource recovery company with both residential and commercial trash, recycling and composting services---the authors develop ContamiNet, a convolutional neural network, to identify contaminating material in residential recycling and compost bins. When training the model on a subset of labels that meet a minimum frequency threshold, ContamiNet preforms almost as well human experts in detecting contamination (0.86 versus 0.88 AUC). Recology is actively piloting ContamiNet in their daily municipal solid waste (MSW) collection to identify contaminants in recycling and compost bins to subsequently inform and educate customers about best sorting practices.
Fairness-Aware Neural Rényi Minimization for Continuous Features

The past few years have seen a dramatic rise of academic and societal interest in fair machine learning. While plenty of fair algorithms have been proposed recently to tackle this challenge for discrete variables, only a few ideas exist for continuous ones. The objective in this paper is to ensure some independence level between the outputs of regression models and any given continuous sensitive variables. For this purpose, we use the Hirschfeld-Gebelein-Rényi (HGR) maximal correlation coefficient as a fairness metric. We propose to minimize the HGR coefficient directly with an adversarial neural network architecture. The idea is to predict the output Y while minimizing the ability of an adversarial neural network to find the estimated transformations which are required to predict the HGR coefficient. We empirically assess and compare our approach and demonstrate significant improvements on previously presented work in the field.