Miracle-dz/UniFAR-FTUs huggingface dataset:
The development of biology instructional media based on macromedia flash from the invertebrate’s inventory output at “Pulau Tikus”

The Purpose of this research is: 1) to know and inventories the types of invertebrates which live is in Tikus Island; 2) to develop the biology instructional media of animal course based on the macromedia flash for the 10th grade of high school students, 3) to study the quality of learning based media through the invertebrate’s macromedia, and its assessment on biology teachers. The object of this study utilizes the invertebrate inventory at Tikus island, in which practical survey, interview and explorative descriptive on another types of biota was conducted at Tikus island. The development of product learning was based on macromedia flash research (Research and Development), by implementing the ADDIE Model (Analysis, Design, Development and Production, Implementation, Evaluation). According to the obtained results, there were 18 Species taken from 6 phylum invertebrates. These are Porifera, Coelenterate, Mollusca, Vermes, Echinoderms and Arthropods. The survey showed that based on the validation of linguistic expert (86,4%), validation subject matter experts (83,9 %), validation of media expert (87,8%) the validator eligibility by teachers (84,5%) and the test of the students (86,04%) are all in very good criteria. As seen at the percentage range, it can be inferred that biology media based on macromedia flash of the invertebrate inventory at Tikus island is deemed as very appropriately used by the teachers and students.
A likelihood approach to nonparametric estimation of a singular distribution using deep generative models

We investigate statistical properties of a likelihood approach to nonparametric estimation of a singular distribution using deep generative models. More specifically, a deep generative model is used to model high-dimensional data that are assumed to concentrate around some low-dimensional structure. Estimating the distribution supported on this low-dimensional structure, such as a low-dimensional manifold, is challenging due to its singularity with respect to the Lebesgue measure in the ambient space. In the considered model, a usual likelihood approach can fail to estimate the target distribution consistently due to the singularity. We prove that a novel and effective solution exists by perturbing the data with an instance noise, which leads to consistent estimation of the underlying distribution with desirable convergence rates. We also characterize the class of distributions that can be efficiently estimated via deep generative models. This class is sufficiently general to contain various structured distributions such as product distributions, classically smooth distributions and distributions supported on a low-dimensional manifold. Our analysis provides some insights on how deep generative models can avoid the curse of dimensionality for nonparametric distribution estimation. We conduct a thorough simulation study and real data analysis to empirically demonstrate that the proposed data perturbation technique improves the estimation performance significantly.
Optimization of Leachate Treatment with Granular Biomedia: Feldspar and Zeolite

Background/Objectives: Landfills generate leachate having an elevated concentration of contaminants and hazardous to health and the ecosystem. Feldspar and zeolite mixture was investigated for minimizing COD and ammonia from the leachate. Methods/Statistical Analysis: All adsorbent media were sieved to a particle size between 2.00 and 3.35 mm. The optimum shaking speed, mixing ratio, and pH were determined. Raw leachate Sample used in the study was collected from the influent of the detention pond at the SimpangRenggam Municipal landfill in Johor (Malaysia). Findings: Results of the leachate characteristics indicated a non-biodegradable leachate with a high concentration of COD (1763 mg/L), ammonia nitrogen (573 mg/L) and BOD5/COD ratio (0.09). The optimum condition for shaking speed was 150 rpm, the optimum mix ratio of zeolite and feldspar was 20:20, and the optimum pH was 6–6.5. Applications/Improvements: The mixed media produced encouraging results for leachate treatment. It will significantly be applicable in reducing zeolite usage conventionally and consequently decreasing the operational cost in leachate treatments.
Pseudogap and superconductivity emerging from quantum magnetic fluctuations: a Monte Carlo study

Weilun Jiang,1, 2 Yuzhi Liu,1, 2 Avraham Klein,3 Yuxuan Wang,4 Kai Sun,5 Andrey V. Chubukov,6 and Zi Yang Meng7, 1, ∗ Beijing National Laboratory for Condensed Matter Physics and Institute of Physics, Chinese Academy of Sciences, Beijing 100190, China School of Physical Sciences, University of Chinese Academy of Sciences, Beijing 100190, China Department of Physics, Faculty of Natural Sciences, Ariel University, Ariel, Israel Department of Physics, University of Florida, Gainesville, FL 32601 Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA School of Physics and Astronomy, University of Minnesota, Minneapolis, MN 55455, USA Department of Physics and HKU-UCAS Joint Institute of Theoretical and Computational Physics, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China (Dated: May 11, 2021)
TQM and Six Sigma: A Literature Review of Similarities, Dissimilarities and Criticisms

This paper discusses the similarity and dissimilarity between TQM and Six Sigma methodologies. Specifically, it contributes by revealing the resemblances and divergences between CSF’s of TQM and Six Sigma. The discussion arises firstly based on the considerable criticismsappears in the literature concerning this controversy: Six Sigmais a repackage of TQM or Six Sigmais an extension of TQM? As of interest to resolve this controversy, a research framework is developed preceded by a theoretical background of the basics, strategies, objectives and CSF’s of each methodology. The primary proposition of this work is that the implementation of Six SigmaCSF’s are based on the major part on the TQM CSF’s. Firstly, this paper reveals that Six Sigmais an extension of TQM and stresses its distinguished characteristics compared to TQM.
Effect of oil-seed pressing residue on bread colour and texture

Abstract Cold-pressing residue of walnut kernel (WKR) and brown linseed (BLR) was applied in wheat flour blends at 100:0, 95:5 and 90:10 ratios, of which enriched breads were baked, then stored for 3 days at ambient temperature. Colour parameters and firmness of bread crumb were measured daily. Bavarian rye-bread (BR) and wholemeal multigrain bread (WMMG) were used as competitive, marketable breads for comparing tests. The studied oil-seed pressing residues (OSRs) resulted brown colour with different characteristics, depending both on the type of OSR and in comparison with marketed breads, too. The type and the ratio of OSR applied had no influence on the varying of crumb texture (P = 0.107). WKR and BLR enrichment provided stable texture for breads with a 3-day shelf-life, independently from their addition ratio. BLR resulted in softer crumb than WKR; however, this difference was considered to be negligible (P = 0.128). The WKR- and BLR-enriched breads stayed significantly softer at the end of storage time than the marketed breads (P = 0.000). Our results indicate that competitive bakery goods can be produced using oil-seed pressing residue/wheat flour blends.
The ergodic decomposition defined by actions of amenable groups

Let G be a locally compact separable metric group, and assume that G is amenable. Let m L be a left Haar measure on G , and let α = ( F n ) n ∈ N be a tempered Følner sequence. Let ( X, d ) be a locally compact separable metric space, and let w : G × X → X be a left action which is jointly measurable and continuous in the ﬁrst variable. Our goal in this work is to obtain an ergodic decomposition of X deﬁned by w . An essential tool in obtaining the decomposition is an ergodic theorem of Elon Lindenstrauss [Invent. Math. 146 (2001)]. The decomposition is obtained by studying the convergence properties of the sequences (cid:0) 1 m L ( F n ) F n h ( gx ) d m L ( g ) (cid:1) n ∈ N , x ∈ X , h ∈ C 0 ( X ) = the Banach space of all real-valued continuous functions that vanish at inﬁnity (along compact sets), where gx stands for w ( g, x ) , g ∈ G , x ∈ X .
Influence of Mineral Fertilizer, Farmyard Manure, Natural Zeolite, and their Mixture on Fruit Quality and Leaf Micronutrient Levels of Apple Trees

ABSTRACT Adequate soil conditions and fertilization as a cultural practice are the basis of fruit crops production. This study was conducted in 2011 and 2012 to determine impact of soil application of complex nitrogen, phosphorus, and potassium (NPK) mineral fertilizer alone and its mixture with cattle manure (M) and natural zeolite (A) on yield, fruit physico-chemical traits and leaf micronutrient amounts at 120 days after full bloom (DAFB) in “Idared” and “Melrose apples grown on heavy and acidic soil under Serbian conditions. Results showed that NPK increased yield in “Idared” and both NPK+A and NPK+M in “Melrose. ” Fertilizer applications were not influenced by fruit physico-chemical attributes, but differences between cultivars were significant. Fertilizers induced changes of leaf micronutrients amount, but effect was not consistent. In “Idared,” NPK+A and NPK+M mixtures improved amounts of the most micronutrients, whereas in “Melrose,” NPK and mixture NPK+A+M increased leaf micronutrients in more cases. According to deviation from optimum percentage (DOP and ΣDOP indexes), excessive leaf iron (Fe) and zinc (Zn) was found and deficiency of manganese (Mn), copper (Cu), and boron (B). “Melrose” exhibited much better balanced nutritional values for nutrients as compared to “Idared,” whereas NPK+M in “Idared” and NPK alone in “Melrose” promoted better balanced nutritional values. Since the impact of nutrients on the studied features is not consistent, more research will need to be conducted to investigate the long-term effect of NPK alone or in mixture with natural zeolite and manure fertilization on apples.
Prenatal and Early Childhood Determinants of Enamel Hypoplasia in Infants

Objective: Enamel hypoplasia (EH) is a recognized risk factor for dental caries. The purpose was to investigate the relationship between prenatal and early life risk factors, including prenatal nutritional status, and EH among infants. Methods: Pregnant mothers from an at-risk urban population in Manitoba, Canada were recruited during the second or early third trimester into a prospective cohort study. At baseline participants completed a questionnaire and provided a serum sample to analysze calcium and 25-hydroxyvitamin D [25(OH)D]. Dental examinations were completed at one year of age by an examiner blinded to mothers’ serum nutrient levels and parents completed a questionnaire by interview. Enamel defects were determined using the DDE index. Data were analyzed using descriptive techniques and regression analysis. A p value < 0.05 was significant. Results: Overall, 22% of infants had EH. Although mothers of infants with EH had lower mean concentrations of 25(OH)D, they did not statistically differ from values associated with children without EH (p=0.072). Infants with EH were significantly more likely to have early childhood caries (73% vs. 27%, p<.001). Four factors were significantly and independently associated with EH: prenatal maternal calcium levels (p=.030), not having heard of vitamin D (p=.033), not drinking milk frequently during pregnancy (p=.034), and not consuming margarine daily (p=.023). Conclusions: Several prenatal and early childhood determinants were identified to be associated with EH in infants and, due to the strong association with early childhood caries, the management of EH risk factors is critical to reducing oral health disparities in at-risk children.
Adaptive estimation in symmetric location model under log-concavity constraint

We revisit the problem of estimating the center of symmetry $\theta$ of an unknown symmetric density $f$. Although stone (1975), Eden (1970), and Sacks (1975) constructed adaptive estimators of $\theta$ in this model, their estimators depend on external tuning parameters. In an effort to reduce the burden of tuning parameters, we impose an additional restriction of log-concavity on $f$. We construct truncated one-step estimators which are adaptive under the log-concavity assumption. Our simulations suggest that the untruncated version of the one step estimator, which is tuning parameter free, is also asymptotically efficient. We also study the maximum likelihood estimator (MLE) of $\theta$ in the shape-restricted model.
FNet: Mixing Tokens with Fourier Transforms

We show that Transformer encoder architectures can be sped up, with limited accuracy costs, by replacing the self-attention sublayers with simple linear transformations that “mix” input tokens. Most surprisingly, we find that replacing the self-attention sublayer in a Transformer encoder with a standard, unparameterized Fourier Transform achieves 92-97% of the accuracy of BERT counterparts on the GLUE benchmark, but trains 80% faster on GPUs and 70% faster on TPUs at standard 512 input lengths. At longer input lengths, our FNet model is significantly faster: when compared to the “efficient Transformers” on the Long Range Arena benchmark, FNet matches the accuracy of the most accurate models, while outpacing the fastest models across all sequence lengths on GPUs (and across relatively shorter lengths on TPUs). Finally, FNet has a light memory footprint and is particularly efficient at smaller model sizes; for a fixed speed and accuracy budget, small FNet models outperform Transformer counterparts.
Prognostic value of glasgow prognostic score in patients with non-small cell lung cancers undergoing pn2 pneumonectomy

Background: The aim of this study was to assess the relationship between Glasgow Prognosis Score (GPS) and survival in patients who underwent pneumonectomy due to pN2 non-small cell lung cancer (NSCLC). Materials and Methods: A total of 45 patients who were determined to have pN2 disease after pneumonectomy between 2007 and 2016 were retrospectively analyzed. The patients were assigned a GPS between 0 and 2 as follows: elevated CRP level (>1.0 mg/dL) and hypoalbuminemia (<35 mg/dL) was classified as GPS 2, elevated CRP but albumin >35 mg/dL was classified as GPS 1, and CRP <1.0 mg/dl and albumin >35 mg/dL were classified as GPS 0. Results: Of the 45 patients included in the study, 42 (93.3%) were male and 3 (6.7%) were female. Eighteen (40%) of the patients had adenocarcinoma and 27 (60%) had squamous cell carcinoma. Skip pN2 (pN0N2) was detected in 10 patients. Mean follow-up time was 28 months. The 5-year survival rate was 40.2%. The main prognostic factors associated with survival were GPS and adjuvant therapy (p = 0.023, p = 0.001). Conclusions: In this study, there was no relationship between N1 status and survival in pneumonectomy patients with pN2 NSCLC, whereas GPS score and adjuvant therapy were found to be prognostically significant in terms of survival.
Covariant theory of light in a dispersive medium

The relativistic theory of the time- and position-dependent energy and momentum densities of light in glasses and other low-loss dispersive media, where different wavelengths of light propagate at different phase velocities, has remained a largely unsolved challenge until now. This is astonishing in view of the excellent theoretical understanding of Maxwell's equations and the abundant experimental measurements of optical phenomena in dispersive media. The challenge is related to the complexity of the interference patterns of partial waves and to the coupling of the field and medium dynamics by the optical force. In this work, we use the mass-polariton theory of light [Phys. Rev. A 96, 063834 (2017)] to derive the stress-energy-momentum (SEM) tensors of the field and the dispersive medium. Our starting point, the fundamental local conservation laws of energy and momentum, is close to that of a recent theoretical work on light in dispersive media by Philbin [Phys. Rev. A 83, 013823 (2011)], which however, excludes the power-conversion and force density source terms describing the coupling between the field and the medium. In the general inertial frame, we present the SEM tensors in terms of Lorentz scalars, four-vectors, and field tensors that reflect in a transparent way the Lorentz covariance of the theory. The SEM tensors of the field and the medium are symmetric, form-invariant, and in full accordance with the covariance principle of the special theory of relativity. The SEM tensor of the coupled field-medium state of light also has zero four-divergence. Therefore, light in a dispersive medium has well-defined four-momentum and rest frame. The volume integrals of the total energy and momentum densities of light agree with the model of mass-polariton quasiparticles having a nonzero rest mass. The predictions of our work are directly accessible to experiments.
Fuzzy Based Adaptive Deblocking Filters at Low-Bitrate HEVC Videos for Communication Networks

: In-loop filtering significantly helps detect and remove blocking artifacts across block boundaries in low bitrate coded High Efficiency Video Coding (HEVC) frames and improves its subjective visual quality in multimedia services over communication networks. However, on faster processing of the complex videos at a low bitrate, some visible artifacts considerably degrade the picture quality. In this paper, we proposed a four-step fuzzy based adaptive deblocking filter selection technique. The proposed method removes the quantization noise, blocking artifacts and corner outliers efficiently for HEVC coded videos even at low bit-rate. We have considered Y (luma), U (chroma-blue), and V (chroma-red) components parallelly. Finally, we have developed a fuzzy system to detect blocking artifacts and use adaptive filters as per requirement in all four quadrants, namely up 45 ◦ , down 45 ◦ , up 135 ◦ , and down 135 ◦ across horizontal and vertical block boundaries. In this context, experimentation is done on a wide variety of videos. An objective and subjective analysis is carried out with MATLAB software and Human Visual System (HVS). The proposed method substantially outperforms existing post-processing deblocking techniques in terms of YPSNR and BD_rate. In the proposed method, we achieved 0.32–0.97 dB values of YPSNR. Our method achieved a BD_rate of + 1.69% for the luma component, − 0.18% (U) and − 1.99% (V) for chroma components, respectively, with respect to the state-of-the-art methods. The proposed method proves to have low computational complexity and has better parallel processing, hence suitable for a real-time system in the near future.
Detection of acoustic events in Lavender for measuring the xylem vulnerability to embolism and cellular damages.

Aknowledgments: The authors thank Johanna Roustant (EARL Les roustanets, Les GrangesGontardes) for providing plant materials; Patrice Chaleil and Aline Faure (Université Clermont Auvergne, Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, Unité Mixte de Recherche PIAF) for plant care during the growing period; Pierre Conchon for his help in micro-CT measurements.
Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions

Uncertainty awareness is crucial to develop reliable machine learning models. In this work, we propose the Natural Posterior Network (NatPN) for fast and highquality uncertainty estimation for any task where the target distribution belongs to the exponential family. Thus, NatPN finds application for both classification and general regression settings. Unlike many previous approaches, NatPN does not require out-of-distribution (OOD) data at training time. Instead, it leverages Normalizing Flows to fit a single density on a learned low-dimensional and taskdependent latent space. For any input sample, NatPN uses the predicted likelihood to perform a Bayesian update over the target distribution. Theoretically, NatPN assigns high uncertainty far away from training data. Empirically, our extensive experiments on calibration and OOD detection show that NatPN delivers highly competitive performance for classification, regression and count prediction tasks.
Dual-Band Dual-Circularly Polarized Antenna Array With Printed Ridge Gap Waveguide

A dual-band dual-circularly polarized magneto-electric dipole antenna array for full-duplex communication systems is presented in this communication. The proposed array can simultaneously achieve left-hand circular polarization (LHCP) around 20 GHz and right-hand circular polarization (RHCP) around 30 GHz with a low-loss feed network using the printed ridge gap waveguide (PRGW). The antenna is composed of two sets of stacked interconnected short-circuit patches operating at different frequencies and fed by the same gap. The LHCP at the 20 GHz band and RHCP at the 30 GHz band are realized by exciting the corresponding orthogonal electric-dipole mode and magnetic-dipole mode with −90°/90° phase difference. A cylindrical cavity consists of a series of metalized vias with a top metal strip used for surface wave inhibition. Using the PRGW, a four-way power divider with a low transmission loss is designed. Finally, the simulated $2 \times 2$ array was fabricated and measured. The measurement results show that the impedance bandwidths are 18.85–20.8 and 29.5–30.9 GHz. The 3 dB axial ratio bandwidths are 19.4–20.4 and 28.5–31.4 GHz, with the peak gains of 13.2 and 11.5 dBic, respectively.
Milky Stage Versus Dough Stage of Immature Wheat Grain: Effects on Phytic Acid and Fructan Contents, Antioxidant Activity, Textural Parameters, and Sensory Characteristics of Set-Type Yoghurts

HIGHLIGHTS Yoghurts were supplemented with milky and dough stage wheat grain flours. Total antioxidant capacity was improved by wheat grain flour supplementation. Milky stage wheat provided higher fructan content than that of dough stage wheat. Fermentation reduced phytic acid levels in yoghurts containing wheat grain flours.
How Does Environmental Dynamism Impact Green Process Innovation? A Supply Chain Cooperation Perspective

Environmental dynamism, as exemplified by the rate of change and the degree of instability of the environment, plays a considerable role in determining whether firms will adopt green process innovation (GPI). Although environmental dynamism may offer new development opportunities, it also increases the risks and uncertainties associated with market potential and technology prospects. Integrating works on organizational adaptation theory and the framework of technology push, market pull, and regulatory push/pull, we examine the effects of environmental dynamism on GPI, with a focus on the moderating effects of supply chain cooperation. Examining a sample of 210 manufacturing firms in China, we find that GPI is positively related to technological dynamism but negatively associated with regulatory dynamism. In addition, supply chain cooperation weakens the association between environmental dynamism and GPI: specifically, supply chain cooperation reduces both the positive effect of technological dynamism and the negative effect of regulatory dynamism on GPI. These findings offer a new explanation for the ambiguous viewpoints and results by providing finer-grained insights on how and under which situation environmental dynamism impacts GPI.