Hot Spots Research Articles

Improving community resilience to disrupted food access: Empirical spatio-temporal analysis of volunteer-based crowdsourced food delivery

Unplanned disaster events can greatly disrupt access to essential resources, with calamitous outcomes for already vulnerable households. This is particularly challenging when concurrent extreme events affect both the ability of households to travel and the functioning of traditional transportation networks that supply resources. This paper examines the use of volunteer-based crowdsourced food delivery as a community resilience tactic to improve food accessibility during overlapping disruptions with lasting effects, such as the COVID-19 pandemic and climate disasters. The study uses large-scale spatio-temporal data (n = 28,512) on crowdsourced food deliveries in Houston, TX, spanning from 2020 through 2022, merged with data on community demographics and significant disruptive events occurring in the two-year timespan. Three research lenses are applied to understand the effectiveness of crowdsourced food delivery programs for food access recovery: 1) geographic analysis illustrates hot spots of demand and impacts of disasters on requests for food assistance within the study area; 2) linear spatio-temporal modeling identifies a distinction between shelter-in-place emergencies and evacuation emergencies regarding demand for food assistance; 3) structural equation modeling identifies socially vulnerable identity clusters that impact requests for food assistance. The findings from the study suggest that volunteer-based crowdsourced food delivery adds to the resilience of food insecure communities, supporting its effectiveness in serving its intended populations. The paper contributes to the literature by illustrating how resilience is a function of time and space, and that similarly, there is value in a dynamic representation of community vulnerability. The results point to a new approach to resource recovery following disaster events by shifting the burden of transportation from resource-seekers and traditional transportation systems to home delivery by a crowdsourced volunteer network.

Machine learning-aided quantitative detection of two mixed antibiotics in a narrow concentration range based on oxygen incorporation-induced 3D SERS substrates

Amoxicillin (AMO) and ciprofloxacin (CIP) as frequently-used antibiotics are often simultaneously taken for anti-infection to protect pig and poultry production, while their effective therapeutic window is narrow. How to quantitatively detect the two antibiotics mixed in a narrow concentration range is essential to ensure their treatment efficacy and food safety. In this study, quantitative detection of AMO and CIP mixed in animal flesh in one order of magnitude concentration range was performed using a triple SERS signal amplification sensor combined with machine learning. The SERS sensor based on oxygen incorporation (Oi)-induced 3D NiO nanoflowers (NFs) coated with Ag nanoparticles included 3D hot spot effect from strong internal electromagnetic couple in NiO NFs, the Oi effect of NiO and synergistic charge transfer effect of between NiO and Ag. Based on triple enhancement effects, sensitive SERS detection of AMO and CIP was made with the limits of detection of 1 nM and 100 nM. Through the use of machine learning techniques like principal component analysis and partial least square regression, qualitative and quantitative detection of AMO and CIP in their mixture from 1.33 μM to 8.69 μM was successfully achieved, where the average proportion of absolute prediction error (p ≤ 0.15) for concentration was 98.06 %.

Thermal management for microelectronic chips under non-uniform heat flux with supercritical CO2

With the rapid growth of information technology and the evolution in the use of microelectronic chips, these components are facing major challenges of high heat dissipation and inhomogeneous heat flux. To address the hotspot issues, a combination of microchannel heat sinks (MCHS) with cavity-rib designs and supercritical fluids is a potential solution. This study compares the thermo-hydraulic properties of water and supercritical carbon dioxide (sCO2) under various boundary conditions and hotspot locations during non-uniform heating. The results showed that sCO2 can effectively improve temperature uniformity along the heat sink in the presence of hotspots as compared to water. Considering a mass flow rate of 600 kg/(m2·s), the inhomogeneity index of the basal temperature of sCO2 is found to be 0.24, significantly lower than 4.22 for water. This indicates that sCO2 eliminates hot spots by rapidly increasing specific heat capacity near the pseudo-critical temperature. Furthermore, it is noted that maintaining the operating temperature of sCO2 near the pseudo-critical temperature can increase the specific heat capacity of the fluid in a short time, in addition to reducing the corresponding density and viscosity. Consequently, the entropy generation rate of sCO2 under ideal conditions is 46.6 % of that of water. Therefore, the proposed combination of a microchannel of complex structure and sCO2 in this study is demonstrated to effectively reduce the influence of hot spots and improve the overall thermal performance of heat sinks.

The Clustering of the Population at Building Scale in Bursa City (Türkiye)

Research on spatial statistical methods related to population estimation at the building scale and its implications for urban land use has attained little attention. The main target of this study is to propose a new method for population estimation at the building level with minimal data and methodology and a high accuracy rate. In addition to this, it discusses urban population from various perspectives by using spatial statistical methods (Local Moran’s I and Hot–Cold Spot) to examine the population calculated based on the number of residential units in buildings and the household size of the neighborhood along with urban land use types in the case of Bursa. The results showed the following: (1) The suggested method achieves a 76% accuracy rate in population estimation at the building level; (2) 64.6% of the city’s population (2,101,581 individuals) is located in areas classified as Discontinuous High-Density Urban Fabric (50–80%) and Continuous Urban Fabric (>80); (3) 13.2% of the population is located in hot spot areas of these two types, while 14.5% is in cold spot areas. This research provides decision-makers with a framework for addressing urban problems related to housing, transportation, health, and energy in addition to the methods it proposes.

Clinical application of photoacoustic imaging for cervical precursor lesion detection.

Early diagnosis of a precursor lesion in the uterine cervix is an essential factor in uterine cervical cancer prevention. Although colposcopy is an established procedure for detecting high-risk patients, its accuracy and reproducibility are relatively low. Some supportive or alternative techniques to improve the early diagnosis of a precursor lesion have been studied, and correct diagnosis with high reliability using a minimally invasive, cost-effective technique has been pursued. This study aimed to examine the possibility of using photoacoustic (PA) imaging as a supportive technique to improve the accuracy of early diagnosis of cervical precursor lesions. A PA imaging system for microvessels was used to detect angiogenesis in severe lesions. A total of 21 patients who underwent surgical treatment and 114 outpatients who visited our colposcopy clinic were examined. A retrospective evaluation of PA images was performed as follows: (i) pathological assessment of the specific PA findings and (ii) retrospective evaluation of the severe lesion detection rate through PA. PA image evaluation and pathological findings showed dense angiogenesis in a severe precursor lesion appearing as a "hot spot" in the PA image. A comparison with colposcopy findings was performed for accuracy evaluation, and the detection rate of severe lesions using PA was relatively high (positive predictive value, 84.5%; negative predictive value, 82.1%). Our results indicate the possibility of using PA imaging for early diagnosis of severe cervical precursor lesions. With its ability to yield quantitative information, PA imaging can improve ultrasound diagnosis.

Differential effect of plakoglobin in restoring the tumor suppressor activities of p53-R273H vs. p53-R175H mutants.

The six most common missense mutations in the DNA binding domain of p53 are known as "hot spots" and include two of the most frequently occurring p53 mutations (p53-R175H and p53-R273H). p53 stability and function are regulated by various post-translational modifications such as phosphorylation, acetylation, sumoylation, methylation, and interactions with other proteins including plakoglobin. Previously, using various carcinoma cell lines we showed that plakoglobin interacted with wild-type and several endogenous p53 mutants (e.g., R280K, R273H, S241F, S215R, R175H) and restored their tumor suppressor activities in vitro. Since mutant p53 function is both mutant-specific and cell context-dependent, we sought herein, to determine if plakoglobin tumor suppressive effects on exogenously expressed p53-R273H and p53-R175H mutants are similarly maintained under the same genetic background using the p53-null and plakoglobin-deficient H1299 cell line. Functional assays were performed to assess colony formation, migration, and invasion while immunoblotting and qPCR were used to examine the subcellular distribution and expression of specific proteins and genes that are typically regulated by or regulate p53 function and are altered in mutant p53-expressing cell lines and tumors. We show that though, plakoglobin interacted with both p53-R273H and p53-R175H mutants, it had a differential effect on the transcription and subcellular distribution of their gene targets and their overall oncogenic properties in vitro. Notably, we found that plakoglobin's tumor suppressive effects were significantly stronger in p53-R175H expressing cells compared to p53-R273H cells. Together, our results indicate that exploring plakoglobin interactions with p53-R175H may be useful for the development of cancer therapeutics focused on the restoration of p53 function.

Communication Breakdown - Of Disease Clusters, a Trillium and One Health.

One health is based on an interdisciplinary collaboration across professions using a common language. Geographic epidemiology is the study of spatial patterns of population health in a study area. Such spatial patterns (trend, cluster and clustering) require clear definition to be meaningful in science communication. However, the term "disease cluster" has been defined in the literature in various and rather different ways. When geographic epidemiology is unable to make sense of its own concepts it is questionable how respective research results can benefit one health. The goal of this study was to clarify the disease cluster concept. Examples of disease cluster definitions from the literature were used for illustration. The epidemiological triangle of causation (agent, host and environment) was used to conceptualize geographic epidemiological data analysis. The term disease cluster was distinguished from related concepts (clustering, high-risk area, hot spot and outbreak) additionally the semantics and statistical meaning of expectation and prediction were reviewed to further identify the cluster concept as a statistical outlier. The new paradigm of the geographic epidemiological trillium is proposed here and embedded within the spatial generalized linear mixed model to clarify concepts of spatial patterns and guide epidemiological research and teaching.

Thermal performance assessment of traditional Japanese wooden houses with short-term measurements: Machine learning approaches

Traditional Japanese wooden houses are sustainable and vernacular in nature; however, energy consumption owing to poor insulation is inevitable in the winter. These wooden houses in Japan are an integral part of historical landscapes and are protected from the potential risks of retrofitting. To continue using these houses without bearing additional energy burdens, it is necessary to better understand their actual thermal performance. Therefore, this study proposes a combined approach to assess the thermal performance of traditional Japanese-style rooms using in-situ thermal measurements and machine learning predictive methods. The in-situ thermal measurements evaluated the actual thermal environment of traditional Japanese-style rooms with and without air conditioners (AC) during winter. Similarly, two machine learning models, support vector regression (SVR) and random forest regression (RFR) were developed to predict the indoor temperature based on the external factors and their adjacent rooms temperature. The result revealed strong thermal interaction between adjacent rooms, likely driven by heat transfer dynamic. To further investigate these interactions, thermal images of each room were analyzed after the AC was in use. The result revealed the presence of hot and cold spot within the gap of sliding fusuma (thick paper made door) and ranma (transom or indoor ventilation), indicating significant heat transfer between the AC and non-AC rooms. Consequently, the prediction model for the AC room temperature was notably influenced by the thermal conditions of adjacent non-AC room. Thus, this study proposes a simple yet reliable approach that enables resident to prioritize thermal improvements for efficient and cost-effective renovations.

Comparison of translation algorithms in determining maximum allowable CTV shifts for Real-Time Gated Proton Therapy (RGPT) robustness evaluation in prostate cancers.

Real-Time Gated Proton Therapy (RGPT) is an active motion management technique that utilizes treatment gating and tumor tracking via fiducial markers. When performing RGPT treatment for prostate cancer, it is essential to account for the CTV displacement relative to the body in the clinical workflow. The workflow at the National Cancer Centre Singapore (NCCS) includes bone matching via CT-CBCT images, followed by fiducial matching via pulsed fluoroscopy (soft tissue matching), and finally, a robustness evaluation procedure to determine if the difference is within an allowable tolerance. In this study, we compare two CTV translation methods for robustness evaluation: (1) an in-house translation algorithm and (2) the RayStation "simulate organ motion" Deformable image registration (DIR) algorithm. Nine RGPT prostate patient plans with CTV volumes ranging from 17.1 to 96.72 cm2 were included in this study. An in-house translation algorithm and "simulate organ motion" DIR RayStation algorithm were used to generate CTV shifts along R-L, I-S, and P-A axes between 10mm at 2mm steps. At each step, dose metrics, which include CTV Dmax, CTV D95%, and CTV D98%, were extracted and used as comparative metrics for CTV target coverage and hot spot evaluation. Across all axes, there were no statistically significant differences between the two algorithms for all three dose metrics: CTV Dmax (P=0.92, P=0.91, and P=0.47), CTV D95% (P=0.97, P=0.22, and P=0.33), and CTV D98% (P=0.85, P=0.33, and P=0.36). Further, the in-house translation algorithm evaluation time was less than 10s, two orders of magnitude faster than the DIR algorithm. Our results demonstrate that the simpler in-house algorithm performs equivalently to the realistic DIR algorithm when simulating CTV motion in prostate cancers. Furthermore, the in-house algorithm completes the robustness evaluation two orders of magnitude faster than the DIR algorithm. This significant reduction in evaluation time is crucial especially when preparatory time efficiency is of paramount importance in a busy clinic.

Generation of Plasmonic and Chemical Hot Spots near the Reaction Sites in Solar-Driven Photoelectrochemical Ammonia Splitting

Generation of Plasmonic and Chemical Hot Spots near the Reaction Sites in Solar-Driven Photoelectrochemical Ammonia Splitting

Evaluation of Tidal Asymmetry and Its Effect on Tidal Energy Resources in the Great Island Region of the Gulf of California

Hydrokinetic tidal energy is one of the few marine renewable energy resources with sufficiently mature technology for commercial exploitation. However, several parameters affect its exploitability, such as the minimum speed threshold, ambient turbulence levels, or tidal asymmetry, to name but a few. These parameters are particularly important in regions with lower mean speeds than those in first-generation sites, such as the North Sea. The Gulf of California is one of those regions. In this paper, a Delft3D Flexible Mesh Suite (Delft3D FM) model in barotropic configuration is set up over the Gulf of California using a flexible mesh with resolution varying from O (500 m) in the deep regions to O (10 m) in the coastal regions. A simulation is run over the year of 2020, with a tidal forcing of 75 components. The model is validated at four tidal gauge locations and four Acoustic Doppler Current profiler (ADCP) locations. The speed, U, and tidal power density (TPD) indicators used for the validation were the annual means, the annual means for speeds above the 0.5 m s−1 threshold, the annual means of the spring tide maxima, and the annual maxima. The contour maps of the annual means, that is, the annual means for speeds above the 0.5 m s−1 threshold, allow us to identify tidal energy hot spots throughout the Gulf of California, particularly in the Great Island region (GIR). In this region, these hot spots have higher U and TPD values, in agreement with previous studies. The patterns of circulation around Tiburón Island and San Esteban Island on the East, and Ángel de la Guarda Island and San Lorenzo Island on the West, the four islands in the region with the highest tidal energy potential, are also discussed while recognizing that Tiburón Channel, between Tiburón Island and San Esteban Island, has proved to be the best siting location, based on the technical results obtained so far. The hot spots sites are further characterized by computing the tidal asymmetry in these small regions, showing the locations of the sites with smallest asymmetry, which would be the best for tidal energy exploitation. The hot spots around San Esteban Island are particularly important because they have the largest TPD in the GIR, with the model predicting a TPD on the order of 500–1000 W m−2. Here, complementary field measurements obtained with two ADCPs, close to San Esteban Island, one at 15 m depth, SEs (shallow region), and the other at 60 m depth, SEd (deep region), produced TPDs of 1200 W m−2 and 400 W m−2, respectively. The analysis of the vertical profiles and the tidal asymmetry over the vertical shows the importance of developing 3D models in future investigations.

Pore collapse, shear bands, and hotspots using atomistics-consistent continuum models for RDX (1,3,5-trinitro-1,3,5-triazinane): Comparison with molecular dynamics calculations

Shock-induced energy localization is a crucial mechanism for determining shock sensitivity of energetic materials (EMs). Hotspots, i.e., localized areas of elevated temperature, arise when shocks interact with defects (cracks, pores, and interfaces) in the EM microstructure. The ignition and growth of hotspots in a shocked energetic material contribute to rapid chemical reactions that can couple with the passing shock wave, potentially leading to a self-sustained detonation wave. Predictive models for shock-to-detonation transition must correctly capture hotspot dynamics, which demands high-fidelity material models for meso-scale calculations. In this work, we deploy atomistics-guided material models for the energetic crystal RDX (1,3,5-trinitro-1,3,5-triazinane) and perform tandem continuum and all-atom molecular dynamics (MD) simulations. The computational setup for the continuum and MD simulations are nearly identical. The material models used for the calculations are derived from MD data, particularly the equations of state, rate-dependent Johnson–Cook strength model, and pressure-dependent shear modulus and melting temperature. We show that a modified Johnson–Cook model that accounts for shear-induced localization at the pore surface is necessary to represent well—relative to MD as the ground truth—the inelastic response of the crystal under a range of shock conditions. A head-to-head comparison of continuum and atomistic calculations across several metrics of pore collapse and energy deposition demonstrates that the continuum calculations are in good overall agreement with MD. Therefore, this work provides improved RDX material models to perform physically accurate meso-scale simulations, to enhance understanding of hot spot formation, and to use meso-scale hot spot data to inform macro-scale shock simulations.

Diffuse reflectance spectroscopy and RGB-imaging: a comparative study of non-invasive haemoglobin assessment

Non-invasive assessment of haemoglobin (Hb) level in blood is a hot spot in the point-of-care biomedical diagnostics. Several optical methods are suggested as a solution, some of them being approved for clinical use. Still, there is no consensus on the accuracy of optical techniques, the quality of Hb assessment on different tissue sites, and on the ability of combined use of several optical techniques to improve the quality of Hb level prediction. In this work we examined the capabilities of two optical techniques—diffuse reflectance spectroscopy and RGB-imaging of the skin and fingernails areas—in detecting low blood Hb level. The test sample consisted of 240 adult volunteers with 70 volunteers exhibiting Hb level lower than 120 g/L. We show that using simple descriptors of the diffuse reflectance spectrum of the forearm skin and fingernails is applicable for predicting low blood Hb concentration (ROC-AUC = 0.84 ± 0.08), while RGB-imaging shows similar performance when applied to the fingernail areas (ROC-AUC = 0.83 ± 0.07), which can be considered perspective for clinical use and screening properties. We also report that while the joint use of predictions from two optical methods slightly improves the accuracy of non-invasive Hb level assessment (ROC-AUC = 0.86 ± 0.07), the effect is not as high as one might expect from combining predictions of truly independent modalities, indicating the limit of the accuracy one can expect with multimodal optical approach. We review this case and propose possible solutions towards more sensitive non-invasive optical determination of hemoglobin.

Selective, Intrinsically Fluorescent Trk Modulating Probes.

Neurotrophins (NTs) elicit the growth, survival, and differentiation of neurons and other neuroectoderm tissues via activation of Trk receptors. Hot spots for NT·Trk interactions involve three neurotrophin loops. Mimicry of these using "cyclo-organopeptides" comprising loop sequences cyclized onto endocyclic organic fragments accounts for a few of the low molecular mass Trk agonists or modulators reported so far; the majority are nonpeptidic small molecules accessed without molecular design and identified in random screens. It has proven difficult to verify activities induced by low molecular mass substances are due to Trk activation (rather than via other receptors), enhanced Trk expression, enhanced NT expression, or other pathways. Consequently, identification of selective probes for the various Trk receptors (e.g., A, B, and C) has been very challenging. Further, a key feature of probes for early stage assays is that they should be easily detectable, and none of the compounds reported to date are. In this work, we designed novel cyclo-organopeptide derivatives where the organic fragment is a BODIPY fluor and found ones that selectively, though not specifically, activate TrkA, B, or C. One of the assays used to reach this conclusion (binding to live Trk-expressing cells) relied on intrinsic fluorescence in the tested materials. Consequently, this work established low molecular mass Trk-selective probes exhibiting neuroprotective effects.

Tumor NOS2 and COX2 Spatial Juxtaposition with CD8+ T Cells Promote Metastatic and Cancer Stem Cell Niches that Lead to Poor Outcome in ER- Breast Cancer.

Estrogen receptor-negative breast cancer is an aggressive subtype with limited therapeutic options. Elevated nitric oxide synthase (NOS2) and cyclo-oxygenase (COX2) mediates immunosuppression and poor survival in these tumors. Therefore, the influence of tumor NOS2/COX2 on immune architecture was examined in 16 African American and 5 Caucasian ER- tumors. Elevated tumor NOS2/COX2 limited CD8+ T cell infiltration at 5-yr survival. Distinct CD8+/-NOS2+/-COX2+/- phenotypes defining metastatic and cancer stem cell niches, and immune desert regions were identified. These results were supported by an unbiased, unsupervised nonlinear dimensionality-reduction UMAP technique incorporating spatial relations between cells and validated in a separate gene expression cohort using NOS2/CD8 and COX2/CD8 ratios. Additionally, elongated tumor cells were specifically in CD8-NOS2+COX2+ regions, suggesting metastatic hot spots. This work demonstrates predictive power of spatial analyses of CD8/NOS2/COX2 architecture and supports the use of clinically available NOS2/COX2 inhibitors for improved survival in patients with these aggressive tumors.

Capturing Urban Heterogeneity Enhances Tropical Cyclones Simulation in Houston

AbstractUrbanization in the coastal region has increased socioeconomic losses from landfalling tropical cyclones (TCs). Although previous studies have explored the broad impacts of urbanization on TCs, the effect of heterogeneity caused by local intra‐urban variability has not been examined. To address this gap, this study utilized the urban Local Climate Zone (LCZ) to capture the urban landscape heterogeneity and the impacts of this representation on the simulation of the post‐landfall TCs characteristics in Houston. Taking the case of two recent TCs: Hurricane Harvey (occurred in 2017) and Tropical Storm Imelda (occurred in 2019), the study evaluated the impact of urban heterogeneity on 10‐m winds, 2‐m temperature, land surface temperature, and precipitation across Houston. The consideration of intra‐urban heterogeneity using LCZ can improve the 10‐m winds, 2‐m temperature, and spatial pattern of land surface temperature. Although the cumulative rainfall remained largely similar within the experiments (with and without LCZ), incorporating intra‐urban heterogeneity notably modified the spatial structure of urban rainfall, particularly in simulating heavy rainfall hot spots. These findings are consistent for both TCs and demonstrate the positive impact of incorporating intra‐urban heterogeneity on the landfalling TC simulations over the Houston area.

Spatial analysis of disaster resilience research: A bibliometric study

We analyzed the global disaster resilience research literature to advance understanding of its geographical context. A key objective was to map the variation in disaster research resilience activity to identify hotspots and areas of less activity. The motivation is to reveal regional imbalances in resilience research and collaboration to contribute to the global narrative regarding marginalized regions. The methodology involves an in-depth examination of Web of Science (WoS) bibliographic data from 2010 to 2020, using keywords to develop a comprehensive perspective of disaster resilience research. Additionally, the study incorporates empirical data from the Emergency Events Data (EM-DAT) maintained by the Centre for Research on the Epidemiology of Hazards at the Université Catholique de Louvain (CRED/UCLouvain) to provide context on the impact of disasters. A key innovation of this study is the Disaster Resilience Research Score (DRRS), a quantifiable metric to evaluate the state of disaster resilience research globally by country. The DRRS considers publications, citations, and institutional involvement to provide a well-rounded view of each country's contributions to the field. The results highlight the leading role in disaster resilience research of countries including the United States, Australia, the United Kingdom, Germany, and Italy. However, there is a notable lack of research activity in countries such as Ecuador, Algeria, Kenya, Cambodia, and Myanmar, which also exhibit relatively high vulnerability to environmental hazards. Our findings indicate that countries identified as resilience hotspots predominantly collaborate within their country. This study highlights opportunities for strengthening collaborations between resilience research hotspots and locations less represented in the resilience research literature. It underscores the importance of identifying hot and cold spots to direct future research and foster a more equitable and sustainable response to climate change and hazards.

Characterization of Hibiscus Chlorotic Ringspot Virus-Derived vsiRNAs from Infected Hibiscus rosa-sinensis in China.

Lots of progress have been made about pathogen system of Hibiscus rosa-sinensis and hibiscus chlorotic ringspot virus (HCRSV), however, interactions between H. rosa-sinensis and HCRSV remain largely unknown. Hereon, firstly, HCRSV infection in H. rosa-sinensis from Zhangzhou city of China was confirmed by traditional electron microscopy, modern reverse transcription polymerase chain reaction and RNA-seq methods. Secondly, sequence feature analysis showed the full-length sequence of HCRSV-ZZ was 3,909 nucleotides (nt) in length and had a similar genomic structure with other carmovirus. It contains a 5' untranslated region (UTR), followed by seven open reading frames encoding for P28, P23, P81, P8, P9, P38, and P25, and the last a 3-terminal UTR. Thirdly, HCRSV- ZZ-derived vsiRNAs were identified and characterized for the first time from disease H. rosa-sinensis through sRNA-seq to reveal interactions between pathogen ant plant host. It was shown that the majority of HCRSV-ZZ-derived vsiRNAs were 21 nt, 22 nt, and 20 nt, with 21 nt being most abundant. The 5'-terminal nucleotide of HCRSV-ZZ vsiRNAs preferred U and C. HCRSV-ZZ vsiRNAs derived predominantly (72%) from the viral genome positive-strand RNA. The distribution of HCRSV-ZZ vsiRNAs along the viral genome is generally even, with some hot spots and cold spots forming in local regions. These hot spots and cold spots could be corresponded to the regions of stem loop secondary structures forming in HCRSV-ZZ genome by nucleotide paring. Taken together, our findings certify HCRSV infection in H. rosa-sinensis and provide an insight into interaction between HCRSV and H. rosa-sinensis and contribute to the prevention and treatment of this virus.

Parameter study for hot spot trajectories around SgrA*

Context. Intense flaring events in the near-infrared and X-ray wavebands of our Galactic center have been the subject of research for decades. In recent years, the GRAVITY instrument of the Very Large Telescope captured the motion and polarimetric signature of such a flare in close proximity to the supermassive black hole. Aims. This study aims to investigate a broad parameter space for hot spot motion in the vicinity of SgrA* and reproduce the observed flaring behavior. Methods. To this end, we have developed a general relativistic radiative transfer code and conducted a parameter study including both planar and ejected hot spot configurations around supermassive black holes. Results. Super-Keplerian orbital frequencies are favored by circular equatorial, cylindrical and parabolic models, whereas conical hot spot trajectories provide a better fit for orbital frequencies below the Keplerian value. Additionally, a distant observer cannot effectively differentiate between Schwarzschild and Kerr black holes, as well as face-on orbits at different observation angles.

Evidence for magnetic boundary layer accretion in RU Lup

Context. It is well established that classical T Tauri stars accrete material from a circumstellar disk through magnetic fields. However, the physics regulating the processes in the inner (0.1 AU) disk is still not well understood. Aims. Our aim is to characterize the accretion process of the classical T Tauri Star RU Lup. Methods. Optical high-resolution spectroscopic observations with CHIRON and ESPRESSO were obtained simultaneously with photometric data from AAVSO and TESS. Results. We detected a periodic modulation in the narrow component of the He I 5876 line with a period that is compatible with the stellar rotation period, indicating the presence of a compact region on the stellar surface that we identified as the footprint of the accretion shock. We show that this region is responsible for the veiling spectrum, which is made up of a continuum component plus narrow line emission that fills in the photospheric lines. An analysis of the high-cadence TESS light curve reveals quasi-periodic oscillations on timescales shorter than the stellar rotation period, suggesting that the accretion disk in RU Lup extends inward of the corotation radius, with a truncation radius at ~2 R*. This is compatible with predictions from three-dimensional magnetohydrodynamic models of accretion through a magnetic boundary layer (MBL). In this scenario, the photometric variability of RU Lup is produced by a nonsta-tionary hot spot on the stellar surface that rotates with the Keplerian period at the truncation radius. We also qualitatively discuss how more complex hot spot shapes may generate the same variability pattern. The analysis of the broad components of selected emission lines reveals the existence of a non-axisymmetric, temperature-stratified flow around the star, in which the gas leaves the accretion disk at the truncation radius and accretes onto the star channeled by the magnetic field lines. The unusually rich metallic emission line spectrum of RU Lup might be characteristic of the MBL regime of accretion. Conclusions. Our extensive multiwavelength database of RU Lup reveals many similarities to predictions from the scenario of accretion through a magnetic boundary layer. Alternative explanations would require the existence of a hot spot with a complex shape, perhaps made of two brighter knots, or a warped structure in the inner disk.