Miracle-dz/UniFAR-FTUs huggingface dataset:
Separation of photonic crystal waveguides modes using femtosecond time-of-flight

We demonstrate that ultrabroadband ultrashort-pulse white light supercontinua can be used to track the group velocity of photons in optical waveguides using a Kerr gate technique. Results on silicon nitride slab waveguides show both polarization birefringence and multimode dispersion, which vanish at critical wavelengths. When photonic crystals are embedded in the waveguides, the higher order modes are excited within the band-gap region, demonstrating the need to control their dispersion to make effective use of photonic crystal waveguide devices.
A Diagnostic Study of the Intensity of Three Tropical Cyclones in the Australian Region. Part I: A Synopsis of Observed Features of Tropical Cyclone Kathy (1984)

Abstract Objective streamline analyses and digitized high-resolution IR satellite cloud data have been used to examine in detail the changes in the environmental circulation and in the cloud structure that took place in and around Tropical Cyclone Kathy (1984) when it started to intensify, and during its intensification and dissipation stages. The change of low-level circulation around Tropical Cyclone Kathy was measured by the change in the angle of inflow (α4) at a radius of 4° latitude from the cyclone center. When Kathy started to intensify, α4 increased suddenly from 20° to 42.5° in the northerly airstream to the north and northeast of the depression, and decreased to 0° to the south of the depression. At that stage the low-level circulation around the depression appeared as a giant swirl that started some 600 km to the north and northeast of the depression and spiraled inward toward its center, while trade air, which is usually cool, dry, and stable, did not enter the cyclonic circulation. The angle.
Diversity of Bacterial Secondary Metabolite Biosynthetic Gene Clusters in Three Vietnamese Sponges

Recent reviews have reinforced sponge-associated bacteria as a valuable source of structurally diverse secondary metabolites with potent biological properties, which makes these microbial communities promising sources of new drug candidates. However, the overall diversity of secondary metabolite biosynthetic potential present in bacteria is difficult to access due to the fact that the majority of bacteria are not readily cultured in the laboratory. Thus, use of cultivation-independent approaches may allow accessing “silent” and “cryptic” secondary metabolite biosynthetic gene clusters present in bacteria that cannot yet be cultured. In the present study, we investigated the diversity of secondary metabolite biosynthetic gene clusters (BGCs) in metagenomes of bacterial communities associated with three sponge species: Clathria reinwardti, Rhabdastrella globostellata, and Spheciospongia sp. The results reveal that the three metagenomes contain a high number of predicted BGCs, ranging from 282 to 463 BGCs per metagenome. The types of BGCs were diverse and represented 12 different cluster types. Clusters predicted to encode fatty acid synthases and polyketide synthases (PKS) were the most dominant BGC types, followed by clusters encoding synthesis of terpenes and bacteriocins. Based on BGC sequence similarity analysis, 363 gene cluster families (GCFs) were identified. Interestingly, no GCFs were assigned to pathways responsible for the production of known compounds, implying that the clusters detected might be responsible for production of several novel compounds. The KS gene sequences from PKS clusters were used to predict the taxonomic origin of the clusters involved. The KS sequences were related to 12 bacterial phyla with Actinobacteria, Proteobacteria, and Firmicutes as the most predominant. At the genus level, the KSs were most related to those found in the genera Mycolicibacterium, Mycobacterium, Burkholderia, and Streptomyces. Phylogenetic analysis of KS sequences resulted in detection of two known ‘sponge-specific’ BGCs, i.e., SupA and SwfA, as well as a new ‘sponge-specific’ cluster related to fatty acid synthesis in the phylum Candidatus Poribacteria and composed only by KS sequences of the three sponge-associated bacterial communities assessed here.
Use of Log-Normal Distributions for Numerical Calculations of Condensation and Collection

Abstract Lagragian parcel calculations of condensation and coalescence theory are presented where both a distribution function approach as well as a conventional finite-difference approach are compared. The comparisons suggest that the use of series of log-normal distributions to represent the water droplet spectra may be a practical approach to treating cloud physical process in multi-dimensioned cloud models.
Ultraviolet and X-Ray Spectroscopy of the Solar Atmosphere: Preface

1. The solar atmosphere 2. Fundamentals of solar radiation 3. Fundamentals of atomic physics 4. Mechanisms of formation of the solar spectrum 5. Plasma diagnostic techniques 6. Ultraviolet and X-ray emission lines 7. Spectrometers and imagers for observing the solar ultraviolet and X-ray spectrum 8. Quiet Sun and coronal holes 9. Active regions 10. Solar flares 11. Element abundances Appendices References Index.
Piloting Historical Thinking Lessons to Address Climate Change

To demonstrate how the history classroom could become an important site for addressing climate change, this article describes the piloting of three lessons. Our qualitative case study occurred in an elective environmental education course with teacher candidates who participated in the lessons and were invited to provide feedback. We describe the lessons and their development, and share results from surveys and an interview. Participants identified several educational benefits and expressed feeling better prepared to teach both history and critical thinking in general. Our findings suggest that these lessons may serve as useful examples for developing new resources to support educators in teaching climate change alongside critical and historical thinking.
Synthesis of Bistable Periodic Structures Using Topology Optimization and a Genetic

A formulation for the automatic synthesis of two-dimensional bistable, compliant periodic structures is presented, based on standard methods for topology optimization. The design space is parametrized using nonlinear beam elements and a ground structure approach. A performance criterion is suggested, based on characteristics of the load-deformation curve of the compliant structure. A genetic algorithm is used to find candidate solutions. A numerical implementation of this methodology is discussed and illustrated using simple examples.
Causal Relationship between Energy Consumption, Economic Growth, and Financial Development: Evidence from South Asian Countries

Energy is a challenging and emerging problem in the world. Most South Asian countries have limited means but they cannot utilize a major part of their resources due to the high cost of exploration. However, few countries in this region have sufficient capacity and abundant energy resources to overcome the issues related to energy, but due to several reasons, they are not going to play an effective role in this field. As we know South Asian economies have limited resources and facing energy crises due to these reasons, we conduct research on this region as well. The aim of this study is to examine the relationship between economic growth (GDP), financial development (FD), and energy consumption (ENC) for South Asian countries for the period 1991-2020. For the empirical purpose, panel co-integration approaches are applied. However, the Pooled Mean Group (PMG) long-run result shows that the impact of financial development (FD) and economic growth (GDP) on energy consumption (ENC) is positive and significant. Based on the Vector Error Correction Methodology (VECM) Granger causality results, Conservation Hypothesis holds between the economic growth (GDP) and energy consumption (ENC) in the South Asian Region both in the short-run as well as in the long run. Moreover, the results also indicate that two-way causality exists between financial development (FD) and energy consumption.
Modeling of Single-Process 3D-Printed Piezoelectric Sensors with Resistive Electrodes: The Low-Pass Filtering Effect

Three-dimensional printing by material extrusion enables the production of fully functional dynamic piezoelectric sensors in a single process. Because the complete product is finished without additional processes or assembly steps, single-process manufacturing opens up new possibilities in the field of smart dynamic structures. However, due to material limitations, the 3D-printed piezoelectric sensors contain electrodes with significantly higher electrical resistance than classical piezoelectric sensors. The continuous distribution of the capacitance of the piezoelectric layer and the resistance of the electrodes results in low-pass filtering of the collected charge. Consequently, the usable frequency range of 3D-printed piezoelectric sensors is limited not only by the structural properties but also by the electrical properties. This research introduces an analytical model for determining the usable frequency range of a 3D-printed piezoelectric sensor with resistive electrodes. The model was used to determine the low-pass cutoff frequency and thus the usable frequency range of the 3D-printed piezoelectric sensor. The low-pass electrical cutoff frequency of the 3D-printed piezoelectric sensor was also experimentally investigated and good agreement was found with the analytical model. Based on this research, it is possible to design the electrical and dynamic characteristics of 3D-printed piezoelectric sensors. This research opens new possibilities for the design of future intelligent dynamic systems 3D printed in a single process.
Neurobehavioral Alterations from Noise Exposure in Animals: A Systematic Review

Ecosystems are increasingly involved and influenced by human activities, which are ever-increasing. These activities are mainly due to vehicular, air and sea transportation, thus causing possible repercussions on the fauna that exists there. The aim of this systematic review is to investigate the possible consequences that these activities may have in the field of animal neurobehavior, with special emphasis on the species involved, the most common environment concerned, the noise source and the disturbance that is caused. This research includes articles published in the major databases (PubMed, Cochrane Library, Scopus, Embase, Web of Sciences); the online search yielded 1901 references. After selection, 49 articles (14 reviews and 35 original articles) were finally scrutinized. The main problems that were reported were in relation to movement, reproduction, offspring care and foraging. In live experiments carried out, the repercussions on the marine environment mainly concerned altered swimming, shallower descents, less foraging and an escape reaction for fear of cetaceans and fish. In birds, alterations in foraging, vocalizations and nests were noted; laboratory studies, on the other hand, carried out on small mammals, highlighted spatio-temporal cognitive alterations and memory loss. In conclusion, it appears that greater attention to all ecosystems should be given as soon as possible so as to try to achieve a balance between human activity and the well-being of terrestrial fauna.
Analysis and Modeling of Axial Leakage for Spoke-Type Hybrid Permanent Magnet Machines

In this study, we propose a novel analysis method for a spoke-type permanent magnet (PM) synchronous motor (PMSM) using two types of PMs that consider axial leakage flux using a magnetic equivalent circuit (MEC). Spoke-type ferrite PMSM have the advantage of concentrating magnetic flux; however owing to the shape in which the PMs are arranged along the radial direction, some magnetic flux leaks in the axial direction, which causes inconsistency between the 2D and 3D finite element analysis (FEA) results. Because 3D FEA requires considerable analysis time, using it in the initial design stage of the motor is inefficient. Therefore, we present a new analytical method combined with MEC to overcome the existing inefficient approach. To obtain analysis results equivalent to 3D FEA, the new residual magnetic flux density considering axial flux leakage was applied to 2D FEA PMs using MEC and 2D FEA. The validity of the proposed method was verified through 3D FEA and experiments conducted on the test models using two magnet types.
Indole Derivatives as New Structural Class of Potent and Antiproliferative Inhibitors of Monocarboxylate Transporter 1 (MCT1; SLC16A1)

The solute carrier (SLC) monocarboxylate transporter 1 (MCT1; SLC16A1) represents a promising target for the treatment of cancer; however, the MCT1 modulator landscape is underexplored with only roughly 100 reported compounds. To expand the knowledge about MCT1 modulation, we synthesized a library of 16 indole-based molecules and subjected these to a comprehensive biological assessment platform. All compounds showed functional inhibitory activities against MCT1 at low nanomolar concentrations and great antiproliferative activities against the MCT1-expressing cancer cell lines A-549 and MCF-7, while the compounds were selective over MCT4 (SLC16A4). Lead compound 24 demonstrated a greater potency than the reference compound, and molecular docking revealed strong binding affinities to MCT1. Compound 24 led to cancer cell cycle arrest as well as apoptosis, and it showed to sensitize these cancer cells toward an antineoplastic agent. Strikingly, compound 24 had also significant inhibitory power against the multidrug transporter ABCB1 and showed to reverse ABCB1-mediated multidrug resistance (MDR).
Resource-Allocation Behavior in Complex but Commonplace Tasks☆

Abstract We all face resource-allocation tasks, yet little is known about how people make resource-allocation decisions. Three earlier papers (Langholtz, Gettys, & Foote, 1993, 1994, 1995) established that people can intuitively solve technical two-dimensional resource-allocation problems, where allocations are made on a continuous scale, reaching solutions that approach the optimum solution determined with Linear Programming (LP). In this research we expand our understanding of how people make resource-allocation decisions by examining how people perform complex but commonplace problems using a discrete scale where optimal solutions are determined with Integer Programming. We also contrast performance under conditions where progressively unequal scheduling is required to reach the optimum solution. The data show people can achieve solutions that provide most of the payoffs found with LP, even when they are faced with a complicated three-dimensional problem, but there is a tendency toward equal scheduling under all conditions.
Comprehensive Review of Power Electronic Converters in Electric Vehicle Applications

Emerging electric vehicle (EV) technology requires high-voltage energy storage systems, efficient electric motors, electrified power trains, and power converters. If we consider forecasts for EV demand and driving applications, this article comprehensively reviewed power converter topologies, control schemes, output power, reliability, losses, switching frequency, operations, charging systems, advantages, and disadvantages. This article wasis article intended to help engineers and researchers forecast typical recharging/discharging durations, the lifetime of energy storage with the help of control systems and machine learning, and the performance probability of using AlGaN/GaN heterojunction-based high-electron-mobility transistors (HEMTs) in EV systems. The analysis of this extensive review paper suggests that the Vienna rectifier provides significant performance among all AC–DC rectifier converters. Moreover, the multi-device interleaved DC–DC boost converter is best suited for the DC–DC conversion stage. Among DC–AC converters, the third harmonic injected seven-level inverter is found to be one of the best in EV driving. Furthermore, the utilization of multi-level inverters can terminate the requirement of the intermediate DC–DC converter. In addition, the current status, opportunities, challenges, and applications of wireless power transfer in hybrid and all-electric vehicles were also discussed in this paper. Moreover, the adoption of wide bandgap semiconductors was considered. Because of their higher power density, breakdown voltage, and switching frequency characteristics, a light yet efficient power converter design can be achieved for EVs. Finally, the article’s intent was to provide a reference for engineers and researchers in the automobile industry for forecasting calculations.
Nesfatin-1 in Human Milk and Its Association with Infant Anthropometry

Breastfed infants have different growth patterns to formula-fed infants and are less likely to develop obesity later in life. Nesfatin-1 is an anorexigenic adipokine that was discovered in human milk more than a decade ago, and its role in infant appetite regulation is not clear. Our aim was to describe nesfatin-1 levels in human milk collected 3–4 months postpartum, associations with infant anthropometry, and factors (maternal pre-pregnancy body mass index (mBMI), high weight gain during pregnancy, milk fat, and energy content) possibly influencing nesfatin-1 levels. We hypothesized that nesfatin-1 levels in mother’s milk would differ for infants that were large (high weight-for-age Z-score (WAZ)) or small (low WAZ) at the time of milk sample collection. We used enzyme-linked immunosorbent assay to detect the nesfatin-1 concentration in milk samples from mothers to high WAZ (n = 50) and low WAZ (n = 50) infants. We investigated associations between nesfatin-1 levels and infant anthropometry at 3–4 months of age and growth since birth, using linear regression adjusted for mBMI, birth weight, infant sex, and exclusivity of breastfeeding. We found no difference in nesfatin-1 levels between the two groups and no association with infant anthropometry, even after adjusting for potential confounders. However, high nesfatin-1 levels were correlated with low mBMI. Future research should investigate serum nesfatin-1 level in both mothers, infants and associations with growth in breastfed children.
Loss of Function TGFBR2 Variant as a Contributing Factor in Generalized Pustular Psoriasis and Adult-Onset Immunodeficiency

Background: Generalized pustular psoriasis (GPP; MIM 614204) is a rare multisystemic autoinflammatory disease, characterized by episodes of acute generalized erythema and scaling developed with the spread of numerous sterile pustules. Adult-onset immunodeficiency syndrome (AOID) with anti-interferon-γ autoantibodies is an immunodeficiency disorder associated with disruptive IFN-γ signaling. Methods: Clinical examination and whole exome sequencing (WES) were performed on 32 patients with pustular psoriasis phenotypes and 21 patients with AOID with pustular skin reaction. Histopathological and immunohistochemical studies were performed. Results: WES identified four Thai patients presenting with similar pustular phenotypes—two with a diagnosis of GPP and the other two with AOID—who were found to carry the same rare TGFBR2 frameshift mutation c.458del; p.Lys153SerfsTer35, which is predicted to result in a marked loss of functional TGFBR2 protein. The immunohistochemical studied showed overexpression of IL1B, IL6, IL17, IL23, IFNG, and KRT17, a hallmark of psoriatic skin lesions. Abnormal TGFB1 expression was observed in the pustular skin lesion of an AOID patient, suggesting disruption to TGFβ signaling is associated with the hyperproliferation of the psoriatic epidermis. Conclusions: This study implicates disruptive TGFBR2-mediated signaling, via a shared truncating variant, c.458del; p.Lys153SerfsTer35, as a “predisposing risk factor” for GPP and AOID.
Intraoperative Assessment of Tumor Margins in Tissue Sections with Hyperspectral Imaging and Machine Learning

Simple Summary The complete resection of the malignant tumor during surgery is crucial for the patient’s survival. To date, surgeons have been intraoperatively supported by information from a pathologist, who performs a frozen section analysis of resected tissue. This tumor margin evaluation is subjective, methodologically limited and underlies a selection bias. Hyperspectral imaging (HSI) is an established and rapid supporting technique. New artificial-intelligence-based techniques such as machine learning (ML) can harness this complex spectral information for the verification of cancer tissue. We performed HSI on 23 unstained tissue sections from seven patients with oral squamous cell carcinoma and trained the ML model for tumor recognition resulting in an accuracy of 0.76, a specificity of 0.89 and a sensitivity of 0.48. The results were in accordance with the histopathological annotations and do, therefore, enable the delineation of tumor margins with high speed and accuracy during surgery. Abstract The intraoperative assessment of tumor margins of head and neck cancer is crucial for complete tumor resection and patient outcome. The current standard is to take tumor biopsies during surgery for frozen section analysis by a pathologist after H&E staining. This evaluation is time-consuming, subjective, methodologically limited and underlies a selection bias. Optical methods such as hyperspectral imaging (HSI) are therefore of high interest to overcome these limitations. We aimed to analyze the feasibility and accuracy of an intraoperative HSI assessment on unstained tissue sections taken from seven patients with oral squamous cell carcinoma. Afterwards, the tissue sections were subjected to standard histopathological processing and evaluation. We trained different machine learning models on the HSI data, including a supervised 3D convolutional neural network to perform tumor detection. The results were congruent with the histopathological annotations. Therefore, this approach enables the delineation of tumor margins with artificial HSI-based histopathological information during surgery with high speed and accuracy on par with traditional intraoperative tumor margin assessment (Accuracy: 0.76, Specificity: 0.89, Sensitivity: 0.48). With this, we introduce HSI in combination with ML hyperspectral imaging as a potential new tool for intraoperative tumor margin assessment.
Symmetrically coupled partial differential equations in scattering. I. Model electron-hydrogen collisions

A new method is presented for obtaining scattering information for electron-atom/ion collisions. Results are obtained for model electron-hydrogen collisions (when angular momentum is neglected), for which a very accurate solution is already known. Schrodinger's equation is then separable in the outer region, so that the wavefunction is a linear sum of Coulomb functions multiplied by exponentials. An explicit interpolation scheme is used for the generalised S matrix, thus eliminating any ill conditioning. This scheme is rapidly convergent, so that the use of five adjustable parameters gives errors of around 1-2% for incident energies of 0.8 to 3 Ryd. Finally, results are obtained by using a pseudo-state expansion (which is also separable) in the outer region.