Miracle-dz/UniFAR-FTUs huggingface dataset:
The Smart Predicting of Algal Concentration for Safer Drinking Water Production with Sensor Data

To better predict the timely variation of algal blooms and other vital factors for safer drinking water production, a new AI scanning–focusing process was investigated for improving the simulation and prediction of algae counts. With a feedforward neural network (FNN) as a base, nerve cell numbers in the hidden layer and the permutation and combination of factors, etc., were fully scanned to select the best models and highly correlated factors. All the factors involved in the modeling and selection included the date (year/month/day), sensor data (temperature, pH, conductivity, turbidity, UV254-dissolved organic matter, etc.), lab measurements (algae concentration) and calculated CO2 concentration. The new AI scanning–focusing process resulted in the best models with the most suitable key factors, which are named closed systems. In this case study, models with highest prediction performance are the (1) date–algae–temperature–pH (DATH) and (2) date–algae–temperature–CO2 (DATC) systems. After the model selection process, the best models from both DATH and DATC were used to compare the other two methods in the modeling simulation process: the simple traditional neural network method (SP), where only date and target factor as inputs, and a blind AI training process (BP), which considers all available factors as inputs. Validation results show that all methods except BP had comparable results for algae prediction and other water quality factors, such as temperature, pH and CO2, among which DATC displayed an obviously poorer performance through curve fitting with original CO2 data compared to that of SP. Therefore, DATH and SP were selected for the application test, where DATH outperformed SP due to the uncompromised performance after a long training period. Our AI scanning–focusing process and model selection showed the potential for improving water quality prediction by identifying the most suitable factors. This provides a new method to be considered in the enhancing of numerical prediction for the factors in water quality prediction and broader environment-related areas.
A comparison of conservation law construction approaches for the two-dimensional incompressible Mooney-Rivlin hyperelasticity model

An extended Kovalevskaya form is derived for the two-dimensional incompressible Mooney-Rivlin nonlinear hyperelasticity equations and is used to compute a complete set of local conservation laws of the model through the direct method. Conserved densities and fluxes of the conservation laws are derived, and their physical interpretation is discussed. Since the model admits a variational formulation, the equations are rewritten in the self-adjoint form. Computation of local conservation laws through the direct method applied to the self-adjoint form, as well as a conservation law computation through the local symmetry analysis and the Noether’s first theorem, is performed. A correspondence between local variational symmetries and conservation law multipliers is illustrated. It is argued that even though it leads to more complicated forms of multipliers, the direct conservation law construction method applied to the Kovalevskaya form of the equations is a preferred systematic way of conservation law computat.
CAMK2D De Novo Missense Variant in Patient with Syndromic Neurodevelopmental Disorder: A Case Report

Background: Intellectual disability with developmental delay is the most common developmental disorder. However, this diagnosis is rarely associated with congenital cardiomyopathy. In the current report, we present the case of a patient suffering from dilated cardiomyopathy and developmental delay. Methods: Neurological pathology in a newborn was diagnosed immediately after birth, and the acquisition of psychomotor skills lagged behind by 3–4 months during the first year of life. WES analysis of the proband did not reveal a causal variant, so the search was extended to trio. Results: Trio sequencing revealed a de novo missense variant in the CAMK2D gene (p.Arg275His), that is, according to the OMIM database and available literature, not currently associated with any specific inborn disease. The expression of Ca2+/calmodulin-dependent protein kinase II delta (CaMKIIδ) protein is known to be increased in the heart tissues from patients with dilated cardiomyopathy. The functional effect of the CaMKIIδ Arg275His mutant was recently reported; however, no specific mechanism of its pathogenicity was proposed. A structural analysis and comparison of available three-dimensional structures of CaMKIIδ confirmed the probable pathogenicity of the observed missense variant. Conclusions: We suggest that the CaMKIIδ Arg275His variant is highly likely the cause of dilated cardiomyopathy and neurodevelopmental disorders.
MEETING HAUSDORFF IN MONTE CARLO: A SURPRISING TOUR WITH ANTIHYPE FRACTALS

To many statistical researchers, fractals are aesthetically pleasing math- ematical objects or ingredients of complex theoretical studies. This article docu- ments an exception: during recent research on improving eectiv eness of Markov chain Monte Carlo (MCMC), we unexpectedly encountered a class of intriguing fractals in the simple context of generating negatively correlated random variates that achieve extreme antithesis. This class of antihype fractals enticed us to tour the world of fractals, because it has intrinsic connections with classical fractals such as Koch's snowak e and it illustrates theoretical concepts such as Hausdor dimension in a very intuitive way. It also provides a practical example where a sequence of uniform variables converges exponentially in the Kolmogorov-Smirnov distance, yet fails to converge in other common distances, including total variation distance and Hellinger distance. We also show that this non-convergence result ac- tually holds for any sequence of (proper) uniform distributions on supports formed by the generating process of a self-similar fractal. These negative results remind us that the choice of metrics, e.g., for diagnosing convergence of MCMC algorithms, do matter sometimes in practice.
Flavocytochrome b2-Mediated Electroactive Nanoparticles for Developing Amperometric L-Lactate Biosensors

L-Lactate is an indicator of food quality, so its monitoring is essential. Enzymes of L-Lactate metabolism are promising tools for this aim. We describe here some highly sensitive biosensors for L-Lactate determination which were developed using flavocytochrome b2 (Fcb2) as a bio-recognition element, and electroactive nanoparticles (NPs) for enzyme immobilization. The enzyme was isolated from cells of the thermotolerant yeast Ogataea polymorpha. The possibility of direct electron transfer from the reduced form of Fcb2 to graphite electrodes has been confirmed, and the amplification of the electrochemical communication between the immobilized Fcb2 and the electrode surface was demonstrated to be achieved using redox nanomediators, both bound and freely diffusing. The fabricated biosensors exhibited high sensitivity (up to 1436 A·M−1·m−2), fast responses, and low limits of detection. One of the most effective biosensors, which contained co-immobilized Fcb2 and the hexacyanoferrate of gold, having a sensitivity of 253 A·M−1·m−2 without freely diffusing redox mediators, was used for L-Lactate analysis in samples of yogurts. A high correlation was observed between the values of analyte content determined using the biosensor and referenced enzymatic-chemical photometric methods. The developed biosensors based on Fcb2-mediated electroactive nanoparticles can be promising for applications in laboratories of food control.
Genomic Characterization of Arcobacter butzleri Strains Isolated from Various Sources in Lithuania

Arcobacter (A.) butzleri, the most widespread species within the genus Arcobacter, is considered as an emerging pathogen causing gastroenteritis in humans. Here, we performed a comparative genome-wide analysis of 40 A. butzleri strains from Lithuania to determine the genetic relationship, pangenome structure, putative virulence, and potential antimicrobial- and heavy-metal-resistance genes. Core genome single nucleotide polymorphism (cgSNP) analysis revealed low within-group variability (≤4 SNPs) between three milk strains (RCM42, RCM65, RCM80) and one human strain (H19). Regardless of the type of input (i.e., cgSNPs, accessory genome, virulome, resistome), these strains showed a recurrent phylogenetic and hierarchical grouping pattern. A. butzleri demonstrated a relatively large and highly variable accessory genome (comprising of 6284 genes with around 50% of them identified as singletons) that only partially correlated to the isolation source. Downstream analysis of the genomes resulted in the detection of 115 putative antimicrobial- and heavy-metal-resistance genes and 136 potential virulence factors that are associated with the induction of infection in host (e.g., cadF, degP, iamA), survival and environmental adaptation (e.g., flagellar genes, CheA-CheY chemotaxis system, urease cluster). This study provides additional knowledge for a better A. butzleri-related risk assessment and highlights the need for further genomic epidemiology studies in Lithuania and other countries.
Establishing Opportunities for Children to Initiate Participatory Activities: The Kinshai Campus Project

Abstract:This paper describes Kinshai Campus, a stopping place on a neighborhood shopping street where children can come daily to play freely with each other and with supportive adults. It analyzes how children themselves were enabled to initiate significant participatory activities with each other and with adults. It describes several participatory episodes in which children felt comfortable in being the initiators of activities rather than waiting for adult initiatives. The paper concludes that small but significant changes in the informal ways that children relate to adults in their daily lives may be more important for establishing a more participatory community culture than short-term participation events designed by adults.
Approximation of skewed and leptokurtic return distributions

There is considerable empirical evidence that financial returns exhibit leptokurtosis and nonzero skewness. As a result, alternative distributions for modelling a time series of the financial returns have been proposed. A family of distributions that has shown considerable promise for modelling financial returns is the tempered stable and tempered infinitely divisible distributions. Two representative distributions are the classical tempered stable and the Rapidly Decreasing Tempered Stable (RDTS). In this article, we explain the practical implementation of these two distributions by (1) presenting how the density functions can be computed efficiently by applying the Fast Fourier Transform (FFT) and (2) how standardization helps to drive efficiency and effectiveness of maximum likelihood inference.
Instructional quality in science teacher education: comparing evaluations by chemistry pre-service teachers and their advisors

ABSTRACT Evaluating and improving instructional quality is important in pre-service teacher education, given it is a crucial factor for students’ learning gains. This process is complex and involves multiple classroom events with various interpretations. Criteria for instructional quality are rarely applied systematically in teacher education, leading to divergent evaluations and hindering comparable development. Comparability has rarely been researched in science pre-service teacher education. Therefore, we compared evaluations from 17 chemistry-specific advisors and 17 science pre-service teachers with regard to their choice of criteria, their respective rating and grading of a videotaped chemistry lesson, in Germany. Their evaluations were compared using the Science Education Perspectives (SEP) framework for instructional quality. Although advisors can be considered evaluation experts, our findings show differences in the choice of criteria, ratings, and how the lesson was graded within and between both groups. Pre-service teachers focused more on aspects of classroom and time management, and gave higher average ratings, whereas their advisors focused more on cognitive activation. Overall, 16 different criteria were used by the majority of participants. These criteria show a strong science-specific focus. Our findings have implications for science pre-service teacher education, showing a need for a common approach in evaluations, with extended observation periods.
Uterine Artery Embolization for the Treatment of Symptomatic Uterine Fibroids of Different Sizes: A Single Center Experience

The present study aimed to evaluate the clinical and radiological 1-year outcomes of uterine artery embolization (UAE) performed in a selected population of women with symptomatic myomas and who do not wish to conceive. Between January 2004 and January 2018, a total of 62 patients with pre-menopausal status and with no wish to conceive in the future underwent UAE for the treatment of symptomatic fibroids. All the patients underwent magnetic resonance imaging (MRI) and/or transvaginal ultrasonography (TV-US) before and after the procedure at 1-year follow-up. Clinical and radiological parameters were recorded, stratifying the population into 3 groups according to the size of the dominant myoma (group 1: <50 mm; group 2: ≥50 and ≤80 mm; group 3: >80 mm). Mean fibroid diameter was significantly reduced (42.6% ± 21.6%) at 1-year follow-up, with excellent improvements in terms of both symptoms and quality of life. No significant difference was observed regarding baseline dimension and the number of myomas. No major complications were reported (2.5%). The present study confirms the safety and efficacy of UAE in the treatment of symptomatic fibroids in pre-menopausal women with no desire to conceive.
Green Management of Postharvest Anthracnose Caused by Colletotrichum gloeosporioides

Fruits and vegetables are constantly affected by postharvest diseases, of which anthracnose is one of the most severe and is caused by diverse Colletotrichum species, mainly C. gloeosporioides. In the last few decades, chemical fungicides have been the primary approach to anthracnose control. However, recent trends and regulations have sought to limit the use of these substances. Greener management includes a group of sustainable alternatives that use natural substances and microorganisms to control postharvest fungi. This comprehensive review of contemporary research presents various sustainable alternatives to C. gloeosporioides postharvest control in vitro and in situ, ranging from the use of biopolymers, essential oils, and antagonistic microorganisms to cultivar resistance. Strategies such as encapsulation, biofilms, coatings, compounds secreted, antibiotics, and lytic enzyme production by microorganisms are revised. Finally, the potential effects of climate change on C. gloeosporioides and anthracnose disease are explored. Greener management can provide a possible replacement for the conventional approach of using chemical fungicides for anthracnose postharvest control. It presents diverse methodologies that are not mutually exclusive and can be in tune with the needs and interests of new consumers and the environment. Overall, developing or using these alternatives has strong potential for improving sustainability and addressing the challenges generated by climate change.
Ab initio Molecular Dynamics of H 2 Dissociative Adsorption on Graphene Surfaces

Hydrogen technologies are currently one of the most actively researched topics. A lot of researches have tied to enhance their energy conversion efficiencies. In the present study, numerical analyses have been carried out focusing on hydrogen-storage carbon materials which are expected to realize high gravimetric and volumetric capacities. In particular, dissociative adsorption processes of H2 molecules above graphene surfaces have been investigated by ab initio molecular dynamics. The present results indicate that a steric graphene surface plays an important role in enhancing the charge transfer which induces dissociation of H2 and adsorption of H atoms on the surface. The dissociation energy required for the reaction H2 → 2H above the steric sites is expected to be reduced to 56.2 % of that in vacuum without graphene. Thus, distorted graphenes are an effective hydrogen-storage material, which functions as a catalytic agent.
A Scheme for Teleportation of an Unknown Multi-atom Entangled State via Raman Interaction

A scheme is proposed to teleportation of an unknown multi-atom entangled state, considering the entangled states of two or more particles play an important role in both demonstrating quantum nonlocality and quantum information processing. The scheme is based on the degenerate Raman interaction of a Λ-type three-level atom with a single-mode field. First let n atoms cross a coherent cavity field in succession to prepare a quantum channel. Then the sender lets the other n atoms which carry the unknown state cross the cavity in succession and makes a joint measurement by detecting the cavity field and the atoms separately. When ｜α｜1, the cavity field can be detected with the measurement method of detecting orthogonal states. Finally the receiver reconstructs the initial state according to the outcome of the joint measurement transmitted through a classical channel. The advantage of the scheme is that it uses an entangled state of a coherent state with n atoms as a quantum channel, which makes the scheme simple and easy. The scheme is expected to be useful in demonstrating quantum nonlocality and information processing.
Development of rapid methods for relaxation time mapping and motion estimation using magnetic resonance imaging

Recent technological developments in the field of magnetic resonance imaging have resulted in advanced techniques that can reduce the total time to acquire images. For applications such as relaxation time mapping, which enables improved visualisation of in vivo structures, rapid imaging techniques are highly desirable. TAPIR is a LookLocker-based sequence for high-resolution, multislice T1 relaxation time mapping. Despite the high accuracy and precision of TAPIR, an improvement in the k-space sampling trajectory is desired to acquire data in clinically acceptable times. In this thesis, a new trajectory, termed line-sharing, is introduced for TAPIR that can potentially reduce the acquisition time by 40 %. Additionally, the line-sharing method was compared with the GRAPPA parallel imaging method. These methods were employed to reconstruct time-point images from the data acquired on a 4T high-field MR research scanner. Multislice, multipoint in vivo results obtained using these methods are presented. Despite improvement in acquisition speed, through line-sharing, for example, motion remains a problem and artefact-free data cannot always be obtained. Therefore, in this thesis, a rapid technique is introduced to estimate in-plane motion. The presented technique is based on calculating the in-plane motion parameters, i.e., translation and rotation, by registering the low-resolution MR images. The rotation estimation method is based on the pseudo-polar FFT, where the Fourier domain is composed of frequencies that reside in an oversampled set of non-angularly, equispaced points. The essence of the method is that unlike other Fourier-based registration schemes, the employed approach does not require any interpolation to calculate the pseudo-polar FFT grid coordinates. Translation parameters are estimated by the phase correlation method. However, instead of two-dimensional analysis of the phase correlation matrix, a low complexity subspace identification of the phase correlation matrix is employed. This method is beneficial because it offers sub-pixel displacement estimation without interpolation, increased robustness to noise and limited computational complexity. Owing to all these advantages, the proposed technique is very suitable for the real-time implementation to solve the motion correction problem.
QuPath Algorithm Accurately Identifies MLH1-Deficient Inflammatory Bowel Disease-Associated Colorectal Cancers in a Tissue Microarray

Current methods for analysing immunohistochemistry are labour-intensive and often confounded by inter-observer variability. Analysis is time consuming when identifying small clinically important cohorts within larger samples. This study trained QuPath, an open-source image analysis program, to accurately identify MLH1-deficient inflammatory bowel disease-associated colorectal cancers (IBD-CRC) from a tissue microarray containing normal colon and IBD-CRC. The tissue microarray (n = 162 cores) was immunostained for MLH1, digitalised, and imported into QuPath. A small sample (n = 14) was used to train QuPath to detect positive versus no MLH1 and tissue histology (normal epithelium, tumour, immune infiltrates, stroma). This algorithm was applied to the tissue microarray and correctly identified tissue histology and MLH1 expression in the majority of valid cases (73/99, 73.74%), incorrectly identified MLH1 status in one case (1.01%), and flagged 25/99 (25.25%) cases for manual review. Qualitative review found five reasons for flagged cores: small quantity of tissue, diverse/atypical morphology, excessive inflammatory/immune infiltrations, normal mucosa, or weak/patchy immunostaining. Of classified cores (n = 74), QuPath was 100% (95% CI 80.49, 100) sensitive and 98.25% (95% CI 90.61, 99.96) specific for identifying MLH1-deficient IBD-CRC; κ = 0.963 (95% CI 0.890, 1.036) (p < 0.001). This process could be efficiently automated in diagnostic laboratories to examine all colonic tissue and tumours for MLH1 expression.