Miracle-dz/UniFAR-FTUs huggingface dataset:
Discretization Approach for the Homogenization of Three-Dimensional Solid-Solid Phononic Crystals in the Quasi-Static Limit: Density and Elastic Moduli

With the application of a homogenization theory, based on the Fourier formalism (which provides efficient and exact formulas by which to determine all the components of the effective stiffness and mass density tensors, valid in the regime of large wavelengths), a new approach to calculate the effective quasi-static response in three-dimensional solid-solid phononic crystals is reported. The formulas derived in this work for calculating the effective elastic parameters show a dependence, in terms of summations over the vectors, of the reciprocal lattice by the discretization of the volume of the inclusion in small parts (e.g., small cubes), to obtain a system of equations from which we define the effective response. In particular, we present the numerical results calculated for several cubic lattices with solid constituents and different shapes of inclusions in the unit cell versus the filling fraction, as well as for fixed values of it. By this means, we analyzed the effect of the type of Bravais lattice of the materials, and the geometry of the inclusions that constitute the three-dimensional phononic array, on the resulting effective anisotropy. Finally, our theory confirms other well-known results with previous homogenization theories as a particular case study. In this regard, the examples and results shown here can be useful for the design of metamaterials with predetermined elastic properties.
Content, Construct, and Criterion Validity, Reliability, and Objectivity for Aquatic Readiness Assessment for Brazilian Children

The Aquatic Readiness Assessment (ARA) is an assessment instrument for measuring children's aquatic readiness. The objective of the study was to translate the English version into Portuguese and to investigate the content, construct, and criterion validity as well as the reliability and rater objectivity of the ARA for Brazilian children. Twenty-three professionals and 464 children, newborn to 13 years-old participated in the study. We found strong content (94% to 100% of judges’ agreement) and criterion validity, internal consistency (α from .96 to .97), and inter-rater objectivity (ICC from .81 to .98), and test-retest reliability (ICC from .94 to .98). Appropriate fit indices were observed for the model (CFI = .99; TLI = .99; RMSEA .08, CI 90% = .67 to .10); the model was invariant for boys and girls (CFI = .99; RMSEA = .080; ΔCFI = .009; Δ RMSEA = .015) but not for age groups (CFI = .87, RMSEA = .160). The ARA presented adequate validity and reliability for evaluating the swimming performance of Brazilian children.
High-resolution voice transformation

Speaker identity, the sound of a person's voice, plays an important role in human communication. With speech systems becoming more and more ubiquitous, Voice Transformation (VT), a technology that modifies a source speaker's speech utterance to sound as if a target speaker had spoken it, offers a number of useful applications. For example, a novice user can adapt a text-to-speech system to speak with a new voice quickly and inexpensively. In this dissertation, we consider new approaches in both the design and the evaluation of VT techniques. We propose a new type of speech corpus that is especially suited to VT research and development by consisting of naturally time-aligned sentences. Consequently, removal of individual prosodic characteristics, such as fundamental pitch and durations, requires only very little processing and results in high-quality speech samples that only differ in their segmental properties, our focus of transformation. These “prosody-normalized” speech samples are used for training VT systems, as well as for evaluating their transformation performance objectively and subjectively. Our baseline transformation system (SET) is based on transforming the spectral envelope as represented by the LPC spectrum, using a harmonic sinusoidal model for analysis and synthesis. The transformation function is implemented as a regressive, joint-density Gaussian mixture model, trained on aligned LSF vectors by an expectation maximization algorithm. We improve upon the baseline by adding a residual prediction module, which predicts target LPC residuals from transformed LPC spectral envelopes, using a classifier and residual codebooks. The resulting high resolution transformation system (HRT) is capable of rendering transformed speech with a high degree of spectral detail. Because of the severe shortcomings of evaluating VT performance objectively, we propose a subjective evaluation strategy, consisting of several listening tests. In a speaker discrimination test, the HRT system performed significantly better than the SET system. However, discrimination is below that of natural utterances. Similarly, listeners selected the HRT system over other systems in a system comparison test. Finally, listeners rated the speech quality of the HRT system as better than the SET system. However, the quality of natural utterances was considered better than that of transformed speech.
A deep data‐driven approach for enhanced segmentation of blood vessel for diabetic retinopathy

The segmentation step of retinal blood vessel helps to diagnosis the diseases including diabetic retinopathy, glaucoma, etc. The automatic image segmentation process helps experts to speed up the diagnosis of DR, since analytic methods are time consuming and error prone. The neural network (NN) based methods like U‐Net uses leap bonding that extract fine information from the training dataset. However automatic segmentation of image using neural network is a challenging process because of uneven and irregular geometry of organ. In this article, we proposed a U‐Net based approach for segmentation of retinal vessels. Before applying segmentation step, the affected area of image is enhanced with some preprocessing techniques. Then a dual tree discrete Ridgelet transform (DT‐DRT) is apply on the dataset to extract the features from the region of interest. The features accumulation with DT‐DRT ensures better feature representation of vessel for segmentation task. The proposed segmentation is implemented on different publicly available dataset and achieve accuracy of 96.01% in CHASE DB1, 97.65% in DRIVE and 98.61% in STARE dataset. The performance of this algorithm is also compared with some other deep learning models, and results demonstrate that this proposed algorithm performed better than them.
The Social Life of High School Seniors: COVID Experiences

COVID-19 marks a time of social isolation and social change in the lives of many people. While previous literature has focused on the mental health consequences of isolation on young people, our qualitative research aims to explore the lived experiences of adolescents during the pandemic. Based on 10 in-depth, semi-structured interviews with senior year students at the John F. Kennedy School in Berlin, this study seeks to determine whether both the government and school-imposed COVID-measures have impacted the social lives of our participants and to understand how they experience these potential changes. Our research found that students report a significant change in social life, but, in contrast with the existing literature, their experience of this social change is perceived as positive. These positive changes included a reported improvement in social connections, a more conscious use of social media, and the potential for more alone time. By exploring these three themes, our participants’ unexpected positivity can be placed into a larger context in which the pandemic is an opportunity to forge more meaningful connections while learning to be more conscious in spending time alone in an “always-on” culture.
A Quantitative Study of Non-Linear Convective Heat Transfer Model by Novel Hybrid Heuristic Driven Neural Soft Computing

Heat transfer has a vital role in material selection, machinery efficacy, and energy consumption. The notion of heat transfer is essential in understanding many phenomena related to several engineering fields. Particularly, Mechanical, civil and chemical engineering. The presentation of the heat transfer model in this manuscript is a dedication to the heat transfer characteristics such as conduction, convection, and radiation. The heat energy consumption mainly depends on these characteristics. A better conductive and convective paradigm is required for miniaturization of heat loss or transfer. The phenomenon is mathematically assumed with the required parameters. A new mathematical strategy is also designed and implemented in the manuscript to evaluate the dynamics of heat transfer model. The mathematical approach is the hybrid structure of the Sine-Cosine algorithm and Interior point algorithm. The validation of new technique is evaluated by mean absolute deviation, root mean square errors, and error in Nash–Sutcliffe efficiency. For better illustration, an extensive data set executed by the proposed mathematical strategy is also drawn graphically with convergence plots.
radioactivedecay: A Python package for radioactive decay calculations

radioactivedecay is a Python package for radioactive decay modelling. It contains functions to fetch decay data, define inventories of nuclides and perform decay calculations. The default nuclear decay dataset supplied with radioactivedecay is based on ICRP Publication 107, which covers 1252 radioisotopes of 97 elements. The code calculates an analytical solution to a matrix form of the decay chain differential equations using double or higher precision numerical operations. There are visualization functions for drawing decay chain diagrams and plotting activity decay curves.
MANIPULATING MEMBRANE HYDROPHOBICITY BY INTEGRATING POLYTHYLENE-COATED FUME SILICA IN PVDF MEMBRANE

Membrane gas absorption (MGA) as an emerging technology exhibits superior advantages in comparison to conventional carbon dioxide (CO2) absorption processes. However, the decrease in membrane flux, induced by membrane wetting is a significant issue to be pondered upon. Thus, fabrication of an anti-wetting composite membrane is essential to retain and sustain the MGA performance. In this work, silica nanoparticles (SiNPs) is first coated with hydrophobic low-density polyethylene (LDPE). Then, integrating LDPE-HMDS/SiNPs fillers into the polyvinylidene fluoride (PVDF) matrix to increase its hydrophobicity. The incorporation of LDPE-coated silica into PVDF polymer enhanced the contact angle values from 71.8° to 111.8°, indicates the improvement of membrane anti-wetting ability. Despite the similar finger-like layer laid on top of the sponge-like structure for pristine and composite membranes, the incorporation of LDPE-HMDS/SiNPs has reduced in the length ratio of finger-like to sponge-like layer. The changed in the membrane morphology induced higher membrane hydrophobicity which prevent membrane from getting wet easily especially in long term of operation. In addition, EDX surface mapping and lining profiles clearly proved that the LDPE-HMDS/SiNPs were distributed evenly in the composite membranes indicates the good interfacial compatibility between PVDF polymer and LDPE-coated silica. In term of CO2 absorption flux, the embedment of LDPE-HMDS/SiNPs in PVDF polymer matrix demonstrated 2.4x10-3 mol/m2.s which was 2 times higher than that of the pristine membrane. This means the incorporation of LDPE-HMDS/SiNPs into the PVDF membrane has still played a pivotal role in overcoming membrane wetting drawbacks when in contact with the liquid absorbents.
The SCML-05 Developed for Studying the 3D Force and PMG Irregularities Characteristics of HTS Maglev

In order to promote the application of high temperature superconducting (HTS) maglev vehicle, the series of superconducting maglev (SCML) measurement devices — 01, 02 & 03 have been developed in Southwest Jiaotong University. During the course of research, the importance of three-dimensional (3D) study of the interaction between HTS bulks and permanent magnet guideways (PMGs) has become evident. More specifically, when the HTS vehicle is moving at a high speed, small irregularities of the PMG's magnetic field become the source of vibration. Therefore, in order to study the 3D force and the characteristics of HTS maglev under PMG irregularities, a new measurement device called SCML-05 was designed, constructed, and validated. This newly developed measurement device consists of two major parts. The first one is a closed-loop sliding platform providing 3D motion. The second part is measurement and data acquisition system with the software developed for this purpose. In addition, a laser displacement sensor is used to measure the geometry irregularities of the PMG. Overall, the SCML-05 is flexible and light. The force characteristics of the HTS bulks placed above the PMG can be precisely investigated by means of this system. Additionally, the PMG irregularities including geometry and magnetic field irregularities can be measured. These parameters are required to analyze the relationship between the PMG irregularities and the force of HTS maglev vehicle. The test process and typical results obtained by this system are presented in this paper.
The Macronutrient Composition of Infant Formula Produces Differences in Gut Microbiota Maturation That Associate with Weight Gain Velocity and Weight Status

This proof-of-principle study analyzed fecal samples from 30 infants who participated in a randomized controlled trial on the effects of the macronutrient composition of infant formula on growth and energy balance. In that study, infants randomized to be fed cow milk formula (CMF) had faster weight-gain velocity during the first 4 months and higher weight-for-length Z scores up to 11.5 months than those randomized to an isocaloric extensive protein hydrolysate formula (EHF). Here we examined associations among infant formula composition, gut microbial composition and maturation, and children’s weight status. Fecal samples collected before and monthly up to 4.5 months after randomization were analyzed by shotgun metagenomic sequencing and targeted metabolomics. The EHF group had faster maturation of gut microbiota than the CMF group, and increased alpha diversity driven by Clostridia taxa. Abundance of Ruminococcus gnavus distinguished the two groups after exclusive feeding of the assigned formula for 3 months. Abundance of Clostridia at 3–4 months negatively correlated with prior weight-gain velocity and body weight phenotypes when they became toddlers. Macronutrient differences between the formulas likely led to the observed divergence in gut microbiota composition that was associated with differences in transient rapid weight gain, a well-established predictor of childhood obesity and other comorbidities.
Influence of Relative Humidity on the Temperature Increase of a Power Converter

As a vital part of renewable energy and electrical traction, power converters are supposed to have high reliability and good performance. However, power semiconductors produce considerable heat when the power converter works, which results in high junction temperatures that lower the reliability and performance of the power semiconductors. Many studies show that ambient humidity has a significant effect on power devices, but the influence of high humidity on junction temperatures has yet to be studied. Therefore, this paper presents a thermal model for power converters in moist air to obtain the junction temperature increase, which is utilized for the power converter used in a Switched Reluctance Motor System. Simulation results show that the law of converter temperature distribution is independent of the relative humidity in the case of fixed ambient temperature, whereas the temperature in the power converter decreases as the ambient relative humidity increases. These simulation results are validated with the experimental results.
An empirical study on the effect of a driving companion bot on anger coping behaviors

ABSTRACT When anger is abruptly triggered during driving, it becomes difficult to control one’s feelings. In this situation, other people can help mediate the angry emotional state through social interaction. However, it is not feasible to expect a passenger’s help for controlling the driver’s anger during every single drive. Failure to control the driver’s anger can lead to road rage, which can cause a critical danger. In this study, we addressed these concerns by designing and evaluating a driving companion bot that helps drivers control their anger. The bot was designed to deliver verbal comments which was developed based on five different cognitive coping strategies to the driver when the driver faced anger-inducing situations while driving. A within-subjects lab experiment was conducted with 38 participants who had driver’s licences. The results indicated that the use of a blaming others coping strategy was the most effective for anger reduction, perceived empathy, and companionship with no additional cognitive load compared to other strategies. Feedback from a post-experiment interview was also presented to discuss the long-term application of the study results. This includes theoretical findings and practical implications for designers and stakeholders focused on safe driving.
Al–Mn–Cr–Zr-based alloys tailored for powder bed fusion-laser beam process: Alloy design, printability, resulting microstructure and alloy properties

This study introduces a family of unique Al–Mn–Cr–Zr-based aluminium alloys illustrated by two ternary and one quaternary variants. The choice of alloy compositions has created a system resistant to solidification cracking while retaining high amount of solutes in solid solution in as-printed condition. Good relative density (~ 99.5%) has been demonstrated along with microstructural study supported by X-ray diffraction to display solidification structure with nanometric precipitate formation in small amounts in as-printed condition. High levels of Mn and Cr produce significant solid solution strengthening reaching hardness of up to 102 HV in as-printed condition. Additionally, the combination of Mn, Cr and Zr is shown to be important to control precipitation strengthening upon direct ageing and coarsening resistance due to slow diffusivity. To elucidate the concept of precipitation strengthening, one set of alloys was aged at 678 K between 0 and 10 h and microhardness results showed that average hardness response reached 130 HV for the quarternary alloy.
Zinc sulfate application to grass forages (oat, barley, annual ryegrass and triticale) for increasing their yield, quality and profitability

ABSTRACT Livestock is a major component of agriculture, and a continuous supply of nutritious forage/fodder is necessary for sustainable livestock production. Zinc (Zn) deficiency is a global concern for human as well as animal health, but Zn fertilisation for productivity and biofortification of forages is not well understood. Therefore, a 2-year field study was conducted to investigate the influence of soil-applied ZnSO4 on morphological traits, yield, nutritional quality and Zn biofortification in four forages. The grass forages (oat, barley, annual ryegrass and triticale) were factorially combined with four levels of soil-applied ZnSO4 (0, 5, 10 and 15 kg ha-1) and two harvesting stages (booting and 50% heading). The treatments were arranged in a triplicate randomised complete block design with a split–split plot arrangement where grass forage species were kept in main plots, ZnSO4 application in subplots and harvest stage in subsub plots. ZnSO4 fertilisation significantly improved morphological traits, dry-matter yield, crude protein, acid detergent fibre (ADF) and shoot Zn concentration in all grass forages at both harvesting stages. Best performance for yield, quality traits, and Zn contents across all crops was observed where ZnSO4 was applied at 15 kg ha-1 and harvested at 50% heading stage. The highest economic returns were provided by triticale and annual ryegrass with 15 kg ZnSO4 ha-1 harvested at 50% heading. In conclusion, for a profitable forage production with good nutritional quality and Zn biofortification, triticale and annual ryegrass may be recommended with a 15 kg ZnSO4 ha-1 fertilisation.
Incidental Finding in Pre-Orthodontic Treatment Radiographs of an Aural Foreign Body: A Case Report

The presence of foreign bodies in the external auditory canal of young patients may cause, if left untreated, severe permanent damage to the adjacent anatomical structures, and infections. A 10-year-old patient with an intellectual disability underwent orthodontic evaluation. An aural radiopaque finding was visible in the lateral cephalogram and in the orthopantomography. The patient’s mother reported that her son never showed any ear discomfort, except for a mild hearing impairment that was never investigated. The patient was referred to an ear, nose and throat (ENT) specialist that removed the foreign body located in the left external auditory meatus. The careful evaluation of dental radiographs, including pre-orthodontic and interim orthodontic radiographs, may help to identify silent incidental findings that may otherwise lead to severe complications if left untreated.
Differentiating Degenerative from Vascular Dementia with the Help of Optical Coherence Tomography Angiography Biomarkers

Alzheimer’s disease and vascular dementia account for the majority of cases of cognitive decline in elderly people. These two main forms of dementia, under which various subtypes fall, are often overlapping and, in some cases, definitive diagnosis may only be possible post-mortem. This has implications for the quality of care and the design of individualized interventions for these patients. Optical coherence tomography angiography (OCTA) is a non-invasive imaging modality used to visualize the retinal layers and vessels which shows encouraging results in the study of various neurological conditions, including dementia. This review aims to succinctly sum up the present state of knowledge and provide critical insight into emerging patterns of OCTA biomarker values in Alzheimer’s disease and vascular dementia. According to the current literature, vessel density seems to be a common biomarker for both forms; inner retinal layer thickness might represent a biomarker preferentially affected in degenerative dementia including Alzheimer’s, while, in contrast, the outer-layer thickness as a whole justifies attention as a potential vascular dementia biomarker. Radial peripapillary capillary density should also be further studied as a biomarker specifically linked to vascular dementia.
How to Improve the Drafting of Health Profiles

Delineating patients’ health profiles is essential to allow for a proper comparison between medical care and its results in patients with comorbidities. The aim of this work was to evaluate the concordance of health profiles outlined by ward doctors and by epidemiologists and the effectiveness of training interventions in improving the concordance. Between 2018 and 2021, we analyzed the concordance between the health profiles outlined by ward doctors in a private hospital and those outlined by epidemiologists on the same patients’ medical records. The checks were repeated after training interventions. The agreement test (Cohen’s kappa) was used for comparisons through STATA. The initial concordance was poor for most categories. After our project, the concordance improved for all categories of CIRS. Subsequently, we noted a decline in concordance between ward doctors and epidemiologists for CIRS, so a new training intervention was needed to improve the CIRS profile again. Initially, we found a low concordance, which increased significantly after the training interventions, proving its effectiveness.