Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Multimodal Species Distribution Model Fusing Remote Sensing Images and Environmental Features

Species distribution models (SDMs) are critical in conservation decision-making and ecological or biogeographical inference. Accurately predicting species distribution can facilitate resource monitoring and management for sustainable regional development. Currently, species distribution models usually use a single source of information as input for the model. To determine a solution to the lack of accuracy of the species distribution model with a single information source, we propose a multimodal species distribution model that can input multiple information sources simultaneously. We used ResNet50 and Transformer network structures as the backbone for multimodal data modeling. The model’s accuracy was tested using the GEOLIFE2020 dataset, and our model’s accuracy is state-of-the-art (SOTA). We found that the prediction accuracy of the multimodal species distribution model with multiple data sources of remote sensing images, environmental variables, and latitude and longitude information as inputs (29.56%) was higher than that of the model with only remote sensing images or environmental variables as inputs (25.72% and 21.68%, respectively). We also found that using a Transformer network structure to fuse data from multiple sources can significantly improve the accuracy of multimodal models. We present a novel multimodal model that fuses multiple sources of information as input for species distribution prediction to advance the research progress of multimodal models in the field of ecology.
On-chip single photon sources based on quantum dots in photonic crystal structures

In order to harness the enormous potential of schemes in optical quantum information processing, readily scalable photonic circuits will be required. A major obstacle for this scalability is the monolithic integration of quantum light sources with the photonic circuit on a single chip. This dissertation presents the experimental demonstration of different inplane single photon sources that allow for this integration with planar light circuits. To this end, the spontaneous recombination of excitons in single indium arsenide quantum dots was exploited to generate single photons. The emission into on-chip waveguides was achieved by the use of advanced two-dimensional photonic crystal structures. First, slow-light effects in a unidirectional photonic crystal waveguide were exploited to achieve ondemand single photon emission with a rate of up to 18.7 MHz, corresponding to a remarkable estimated internal device efficiency of up to 47%. Waveguide-coupled L3 defect cavities with record Q-factors of up to 5 150 were then studied for improved Purcell enhancement of the emission, and in-plane single photon generation from such a device was demonstrated. Finally, an electrically tunable, integrable quantum light source with a total tuning range of 1.9 nm was demonstrated by exploiting the quantumconfined Stark effect in an electrical PIN diode. These results are the first demonstrations of in-plane single photon emission at optical wavelengths and mark an important cornerstone for the realisation of fully integrated quantum photonic circuits in optical quantum information science.
Block-Adaptive Rényi Entropy-Based Denoising for Non-Stationary Signals

This paper approaches the problem of signal denoising in time-variable noise conditions. Non-stationary noise results in variable degradation of the signal’s useful information content over time. In order to maximize the correct recovery of the useful part of the signal, this paper proposes a denoising method that uses a criterion based on amplitude segmentation and local Rényi entropy estimation which are limited over short time blocks of the signal spectrogram. Local estimation of the signal features reduces the denoising problem to the stationary noise case. Results, presented for synthetic and real data, show consistently better performance gained by the proposed adaptive method compared to denoising driven by global criteria.
DeepNup: Prediction of Nucleosome Positioning from DNA Sequences Using Deep Neural Network

Nucleosome positioning is involved in diverse cellular biological processes by regulating the accessibility of DNA sequences to DNA-binding proteins and plays a vital role. Previous studies have manifested that the intrinsic preference of nucleosomes for DNA sequences may play a dominant role in nucleosome positioning. As a consequence, it is nontrivial to develop computational methods only based on DNA sequence information to accurately identify nucleosome positioning, and thus intend to verify the contribution of DNA sequences responsible for nucleosome positioning. In this work, we propose a new deep learning-based method, named DeepNup, which enables us to improve the prediction of nucleosome positioning only from DNA sequences. Specifically, we first use a hybrid feature encoding scheme that combines One-hot encoding and Trinucleotide composition encoding to encode raw DNA sequences; afterwards, we employ multiscale convolutional neural network modules that consist of two parallel convolution kernels with different sizes and gated recurrent units to effectively learn the local and global correlation feature representations; lastly, we use a fully connected layer and a sigmoid unit serving as a classifier to integrate these learned high-order feature representations and generate the final prediction outcomes. By comparing the experimental evaluation metrics on two benchmark nucleosome positioning datasets, DeepNup achieves a better performance for nucleosome positioning prediction than that of several state-of-the-art methods. These results demonstrate that DeepNup is a powerful deep learning-based tool that enables one to accurately identify potential nucleosome sequences.
Synthesizing Quantum Circuits for Simple Periodic Functions

Periodic functions are of special importance in quantum computing, particularly in applications of Shor's algorithm. We explore methods of creating circuits for periodic functions to better understand their properties. We introduce a method for constructing the circuit for a simple monoperiodic function, that is one-to-one within a single period, of a given period p. We conjecture that to create a simples periodic function of period p, where p is an n-bit number, one needs at most n Toffoli gates.
A Survey of Hybrid Free Space Optics (FSO) Communication Networks to Achieve 5G Connectivity for Backhauling

Increased capacity, higher data rate, decreased latency, and better service quality are examples of the primary objectives or needs that must be catered to in the near future, i.e., fifth-generation (5G) and beyond. To fulfil these needs, cellular network design must be drastically improved. The 5G cellular network design, huge multiple-input multiple-output (MIMO) technology, and device-to-device communication are all highlighted in this comprehensive study. Hence, free-space optics (FSO) is a promising solution to address this field. However, FSO standalone is insufficient during turbulent weather conditions. FSO systems possess some limitations, such as being able to be disturbed by any interference between sender and receiver such as a flying bird and a tree, as it requires line-of-sight (LOS) connectivity. Moreover, it is sensitive to weather conditions; the FSO performance significantly decreases in bad weather conditions such as fog and snow; those factors deteriorate the performance of FSO. This paper conducts a systematic survey on the existing projects in the same area of research such as the hybrid FSO/Radio frequency (RF) communication system by listing each technique used for each model to achieve optimum performance in terms of data rate and Bit Error Rate (BER) to be implemented in 5G networks.
Graphene Quantum Dots: Novel Properties and Their Applications for Energy Storage Devices

Batteries and supercapacitors are the next-generation alternative energy resources that can fulfil the requirement of energy demand worldwide. In regard to the development of efficient energy storage devices, various materials have been tested as electrode materials. Graphene quantum dots (GQDs), a new class of carbon-based nanomaterial, have driven a great research interest due to their unique fundamental properties. High conductivity, abundant specific surface area, and sufficient solubility, in combination with quantum confinement and edge effect, have made them appropriate for a broad range of applications such as optical, catalysis, energy storage and conversion. This review article will present the latest research on the utilization of GQDs and their composites to modify the electrodes used in energy storage devices. Several major challenges have been discussed and, finally, future perspectives have been provided for the better implementation of GQDs in the energy storage research.
External Validation of Finnish Diabetes Risk Score and Australian Diabetes Risk Assessment Tool Prediction Models to Identify People with Undiagnosed Type 2 Diabetes: A Cross-sectional Study in Iran

Background Noninvasive risk prediction models have been widely used in various settings to identify individuals with undiagnosed diabetes. Objectives We aimed to evaluate the discrimination, calibration, and clinical usefulness of the Finnish Diabetes Risk Score (FINDRISC) and Australian Diabetes Risk Assessment (AUSDRISK) to screen undiagnosed diabetes in Kerman, Iran. Methods We analyzed data from 2014 to 2018 in the second round of the Kerman Coronary Artery Disease Risk Factors Study (KERCADRS), Iran. Participants aged 35 - 65 with no history of confirmed diabetes were eligible. The area under the receiver operating characteristic curve (AUROC) and decision curve analysis were applied to evaluate the discrimination power and clinical usefulness of the models, respectively. The calibration was assessed by the Hosmer-Lemeshow test and the calibration plots. Results Out of 3262 participants, 145 (4.44%) had undiagnosed diabetes. The estimated AUROCs were 0.67 and 0.62 for the AUSDRISK and FINDRISC models, respectively (P < 0.001). The chi-square test results for FINDRISC and AUSDRISC were 7.90 and 16.47 for the original model and 3.69 and 14.61 for the recalibrated model, respectively. Based on the decision curves, useful threshold ranges for the original models of FINDRIS and AUSDRISK were 4% to 10% and 3% to 13%, respectively. Useful thresholds for the recalibrated models of FINDRISC and AUSDRISK were 4% to 8% and 4% to 9%, respectively. Conclusions The original AUSDRISK model performs better than FINDRISC in identifying patients with undiagnosed diabetes and could be used as a simple and noninvasive tool where access to laboratory facilities is costly or limited.
First Evidence of Anti-Steatotic Action of Macrotympanain A1, an Amphibian Skin Peptide from Odorrana macrotympana

Many different amphibian skin peptides have been characterized and proven to exert various biological actions, such as wound-healing, immunomodulatory, anti-oxidant, anti-inflammatory and anti-diabetic effects. In this work, the possible anti-steatotic effect of macrotympanain A1 (MA1) (FLPGLECVW), a skin peptide isolated from the Chinese odorous frog Odorrana macrotympana, was investigated. We used a well-established in vitro model of hepatic steatosis, consisting of lipid-loaded rat hepatoma FaO cells. In this model, a 24 h treatment with 10 µg/mL MA1 exerted a significant anti-steatotic action, being able to reduce intracellular triglyceride content. Accordingly, the number and diameter of cytosolic lipid droplets (LDs) were reduced by peptide treatment. The expression of key genes of hepatic lipid metabolism, such as PPARs and PLINs, was measured by real-time qPCR. MA1 counteracted the fatty acid-induced upregulation of PPARγ expression and increased PLIN3 expression, suggesting a role in promoting lipophagy. The present data demonstrate for the first time a direct anti-steatotic effect of a peptide from amphibian skin secretion and pave the way to further studies on the use of amphibian peptides for beneficial actions against metabolic diseases.
Effect of Diet on the Midgut Microbial Composition and Host Immunity of the Fall Armyworm, Spodoptera frugiperda

Simple Summary Gut microbiota plays an important role in the colonization of insects in a new environment. The present study explored the effect of different diets on the midgut microbial composition and host immunity in Spodoptera frugiperda. A significant difference was observed in the gut microbiota of S. frugiperda feeding on corn leaf (field diet) compared to those on a starch-rich artificial diet (lab diet). Furthermore, an antibiotic-mediated perturbation of the midgut microbiota significantly impacts the expression profile of the important immune genes. Overall, this study reveals that diet composition affects the insect gut microbiome and immune gene expression, ultimately playing an important role in the pest defense system. Abstract The fall armyworm (Spodoptera frugiperda, J.E. Smith) is one of the most important agricultural pests in the world and causes serious damage to many significant crops. Insect gut microbiota plays a vital role in host immunity, digestion, and development, helping the higher organism colonize in a new environment. However, the effects of different diets on midgut microbial composition and host immunity in S. frugiperda remain unclear. So far, no reports have compared the gut microbiota of fall armyworm reared using an artificial diet compared to corn leaf in Guangzhou, China. High-throughput 16S rRNA sequencing technology was applied to gain insight into the composition of the gut microbiota of S. frugiperda feeding on corn leaf (field diet) and on a starch-rich artificial diet (lab diet). The fall armyworm gut microbiota was dominated by the bacterial phyla Firmicutes and Proteobacteria. Despite the difference in diet, the core bacterial community was represented by the genus Enterococcus. However, the bacterial community is dominated by a few phylotypes, namely operational taxonomical units 1 (OTU1) (Enterococcus casseliflavus), OTU3 (Enterobacteriaceae), OTU2 (Weissella), and OTU4 (Clostridium), accounting for 97.43% of the total OTUs in the complete dataset. A significant difference was identified in the bacterial communities between the “lab diet” and the “field diet” groups. OTU1 and OTU2 were significantly higher in the “field diet” group, whereas OTU3 and OTU4 were higher in the “lab diet” group. A phylogenetic investigation of the communities by reconstruction of unobserved states (PICRUSt) predicted functional analysis indicates the presence of several genes associated with plant biomass degradation. Importantly, antibiotic-mediated perturbation of the midgut microbial community significantly impacts the expression profile of the important immune genes of the host. Furthermore, the oral reintroduction of gut bacterial isolates (E. mundtii and E. gallinarum) significantly enhances host resistance to AcMNPV infection. Taken together, our results indicate that diet composition is an important driver in shaping insect gut microbiome and immune gene expression, ultimately playing an important role in the pest defense system.
Blocking Metal Accretion onto Population III Stars by Stellar Wind

Low-mass population III (PopIII) stars of could survive up until the present. The nondetection of low-mass PopIII stars in our Galaxy has already put a stringent constraint on the initial mass function (IMF) of PopIII stars, suggesting that PopIII stars have a top-heavy IMF. On the other hand, some claim that the lack of such stars stems from metal enrichment of their surfaces by the accretion of heavy elements from the interstellar medium (ISM). We investigate the effects of the stellar wind on metal accretion onto low-mass PopIII stars because accretion of the local ISM onto the Sun is prevented by the solar wind, even for neutrals. The stellar wind and radiation of low-mass PopIII stars are modeled based on knowledge of nearby low-mass stellar systems, including our Sun. We find that low-mass PopIII stars traveling across the Galaxy form a stellar magnetosphere in most of their life. Once the magnetosphere is formed, most of the neutral interstellar particles are photoionized before reaching the stellar surface and are blown away by the wind. Especially, the accretion abundance of iron will be reduced by a factor of compared with Bondi–Hoyle–Lyttleton accretion. The metal accretion can enhance iron abundance [Fe/H] only up to ∼−14. This demonstrates that low-mass PopIII stars remain pristine and will be found as metal-free stars and that further searches for them are valuable in constraining the IMF of PopIII stars.
Effect of Home-Based Training with a Daily Calendar on Preventing Frailty in Community-Dwelling Older People during the COVID-19 Pandemic

It has been reported that marked decreases in physical activity including social activities, deterioration in eating habits and mental health, and an increase in frailty have occurred during the COVID-19 pandemic. This study aimed to devise a method to prevent the onset and progression of frailty during the COVID-19 pandemic and to verify its effect. The subjects were 111 community-dwelling older people who answered questionnaires before and after the intervention. A calendar incorporating 31 different tasks, one for each day, was created as an intervention tool with the aim of improving motor, oral, and cognitive functions. The intervention group (n = 49) participants performed these tasks every day for 3 months. The primary outcome was the Kihon checklist (KCL) score. When the amount of change in the KCL score before and after 3 months was compared between the two groups, no difference in the total score was observed between the two groups; however, the intervention group showed significantly improved cognitive function in the KCL sub-domain. In the intervention group, the number of pre-frailty and frailty patients decreased significantly after the intervention compared to before the intervention. These results suggest that the use of the calendar created in this study during the COVID-19 pandemic could prevent decreased cognitive function in the KCL sub-domain and could help prevent the onset and progression of pre-frailty and frailty.
Polarimetric and Photometric Investigation of the Dark Globule LDN 1225: Distance, Extinction Law, and Magnetic Fields

We present results based on the optical R-band observations of the polarization of 280 stars distributed toward the dark globule LDN 1225. Parallaxes from Gaia data release 2 along with the polarization data of ∼200 stars have been used to (a) constrain the distance of LDN 1225 as 830 ± 83 pc, (b) determine the contribution of interstellar polarization, and (c) characterize the dust properties and delineate the magnetic field (B-field) morphology of LDN 1225. We find that B-fields are more organized and exhibit a small dispersion of 12°. Using the 12CO molecular line data from the Purple Mountain Observatory, along with the column density and dispersion in B-fields, we estimate the B-field strength to be ∼56 ± 10 μG, the ratio of magnetic to turbulent pressure to be ∼3 ± 2, and the ratio of mass to magnetic flux (in units of the critical value) to be <1. These results indicate the dominant role of B-fields in comparison to turbulence and gravity in rendering the cloud support. B-fields are aligned parallel to the low-density parts (traced by a 12CO map) of the cloud; in contrast, they are neither parallel nor perpendicular to the high-density core structures (traced by 13CO and C18O maps). LDN 1225 hosts two 70 μm sources, which seem to be low-mass Class 0 sources. The ratio of total to selective extinction derived using optical and near-infrared photometric data is found to be anomalous (RV = 3.4), suggesting the growth of dust grains in LDN 1225. The polarization efficiency of dust grains follows a power law with an index of −0.7, implying that optical polarimetry traces B-fields in the outer parts of the cloud.
Problems of condensed matter physics : quantum coherence phenomena in electron-hole and coupled matter-light systems

0. Preface 1. Recollections 2. Once again on the "Physical Minimum" 3. Hybrid Organic-Inorganic Nanostructures and Light-Matter Interaction 4. The acoustic-wave driven quantum processor 5. On the problem of many-body localization 6. Raman scattering by LO phonons in semiconductors: the role of the Franz-Keldysh effect 7. Phenomena in cold exciton gases: from theory to experiments 8. Composite Fermions and Fractional Quantum Hall effect in two-dimensional electron system 9. Microcavities with quantum dots: weak and strong coupling regimes 10. Dynamics of cold excitons and electron-hole ensembles in direct-gap semiconductors studied by mid-infrared pump and probe spectroscopy 11. Exciton Coherence 12. Inelastic Light Scattering by Low-lying Excitations of Quantum Hall Fluids 13. Remarks on Surface-atoms Forces in London and Lifshitz Limits 14. Modern trends in semiconductor spintronics 15. Excitonic insulators, electron-hole liquids and metal-insulator transitions 16. Electron-hole liquid in semiconductors 17. Collective state of interwell excitons in double quantum wells heterostructures 18. Bose-Einstein condensation of excitons: Promise and disappointment 19. Acoustically induced superlattices: from photons and electrons to excitons and polaritons 20. Inelastic tunneling spectroscopy of single surface adsorbed molecules
A Theoretical Analysis on the Energy Production of III-V Multi-Junction Solar Cells under Realistic Spectral Conditions

In this paper we present a methodology which uses the detailed balance method to determine the optimum bandgap combination of III-V triple-junction solar cells for the highest yearly energy production. As an example for the methodology we analyse two geographical locations on Earth with distinct spectral conditions. For these places the monthly average of the measured aerosol optical depth and the precipitable water are used to calculate direct solar spectra with a discretisation of one spectrum per hour. The model is used to analyse the spectral sensitivity of the bandgap design of four practical III-V triple-junction solar cell structures. In addition, the impact of the designated operating temperature is investigated. Furthermore, the ideal bandgap combination for a maximal energy harvest is calculated for each location. It is shown that structures optimized for the standard AM1.5d reference spectrum yield nearly optimal energy harvesting efficiencies at geographical locations with "red-rich" spectral conditions. However, the choice of the right bandgap combination is essential. By contrast, structures should be re-optimized for locations with a high share of blue light.
Switchable strong coupling between dual hyperbolic phonon polaritons and photons in hybrid structure of metasurfaces and h-BN slab

We propose an all-dielectric hybrid structure combined with hexagonal boron nitride slab and strontium titanate (STO) metasurfaces to excite dual hyperbolic phonon polaritons (HPhPs) and an additional optical (TO) phonon, and achieve their strong coupling with photons. The metasurfaces, supporting tunable guided-mode resonance via adjusting the external temperature, consists of STO two-dimensional grating and STO layer. Thus, the strong coupling can be switched and tuned actively between the dual HPhPs and TO phonon via adjusting the external temperature of metasurfaces. This work has numerous potential applications on multi-channel biosensors, filters and tunable source and detectors.