Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of sunflower pollen age and origin on pathogen infection in the common eastern bumble bee (Apidae: Hymenoptera)

Bumble bees are globally important pollinators, contributing hundreds of millions of dollars annually in crop pollination services. Several species are in decline, making it paramount to understand how pathogens and nutrition shape bee health. Previous work has shown that consuming sunflower pollen (Helianthus annuus) dramatically reduces infection by the trypanosomatid gut pathogen, Crithidia bombi, in the common eastern bumble bee (Bombus impatiens). Sunflower pollen may therefore be useful as a dietary supplement for reducing this pathogen in managed bumble bee colonies. Here, we assessed the efficacy of freezer-stored sunflower pollen that was collected in different years and locations for reducing pathogen infection. We tested sunflower pollen that was 1, 3, 4, or 5 yr old and from sunflowers grown in the United States or China against a control of 1-yr-old buckwheat pollen from China, since buckwheat pollen results in high infection. We hypothesized that older pollen would have weaker medicinal effects due to degradation of pollen quality. We found that all sunflower pollen treatments significantly decreased Crithidia infection compared to controls. These results suggest that sunflower pollen can be freezer-stored for up to 5 yr and sourced from a wide range of geographic areas and still maintain its medicinal effects against Crithidia in the common eastern bumble bee. This is helpful information for stakeholders who might administer sunflower pollen as a dietary supplement to manage Crithidia in commercial bumble bee colonies.
Leptospiral uveitis- “Transition ‘from epidemic to endemic form” difficulties in laboratory confirmation

Purpose: Leptospirosis is a waterborne zoonotic disease that primarily causes systemic illness, followed by uveitis. After heavy flooding in Madurai district, an epidemic outbreak of systemic and ocular leptospirosis occurred in 1994. Our data shows a transition to endemicity after each epidemic. Aim: The aim of this study is to report the clinical signs, epidemic outbreaks, and persistent endemicity of leptospiral uveitis, as well as the diagnostic dilemmas associated with it. Methods: A retrospective analysis of clinical signs was conducted using medical records of leptospiral uveitis patients over a period of 27 years (1994–2020) in a tertiary care eye hospital. The clinical workup of uveitis included a detailed clinical history, systemic, and ophthalmic examination. Microagglutination tests (MATs) was done at the Centers for Disease Control and Prevention (CDC) in Atlanta and later in our regional laboratory. Serum samples were collected from human systemic leptospirosis cases and a small group of animals in and around Madurai. Results: The first epidemic outbreak resulted in 200 seropositive patients. Subsequent epidemic outbreaks occurred in 1997, 1998, 2001, 2005, and 2012, with Madurai experiencing multiple outbreaks. However, the disease remained endemic, with 25–50 patients being observed per year in between the peaks. Ocular examination revealed acute non-granulomatous uveitis (94.9%), pan uveitis (59.8%), vitreous inflammatory reaction (55.4%), retinal vasculitis (29.5%), disc hyperemia (20.9%), and hypopyon. (16.2%). New serovars emerged every year, resulting in decreased sensitivity of the MAT. Over time, the MAT started to miss diagnoses. Conclusion: The persistent endemicity of leptospiral uveitis emphasizes the need for accessible diagnostic tests. The low performance of the MAT can be attributable to the use of an older panel. The incorporation of new isolates in the MAT by a national laboratory will improve the accuracy of diagnosis.
The Trifold Universe

This paper studies a new concept called universal folding. The visible universe is the result of a complex invisible folding series. There are three major folds (Trifold): from the Plank length, to the radius of an electron, and finally, to the radius of universe. Each of the three-major folds follows the same folding formula. Our findings help us understand the grand architecture of the universe. The ideal average human height, city block size, city size, diameter of the continents, the diameter of the Sun, the distance between the Earth and the Sun, the radius of the solar system, the radius of the Milky Way galaxy, the average diameter of the filament of the universe, and the radius of the universe are important resonance lengths in the formula. This paper helps scientists study everything from a new angle and become aware of the architectural design of the universe.
Digital health interventions in dermatology—Mapping technology and study parameters of systematically identified publications

Digital health interventions (DHI) potentially improve the efficiency and effectiveness of dermatological care. Currently, an overview clustering and characterizing the evidence on DHIs is missing. This systematic mapping of the literature aims to analyse published research on DHIs in dermatology to identify trends and gaps in research. For this purpose, a systematic search of the MEDLINE database was conducted in August 2022 to identify original publications on DHIs in dermatology. Data on country, targeted audience, DHI category, indication, outcome parameter and study design were extracted. Out of 12,009 records identified in MEDLINE, 403 studies were included in the final analysis. Studies on DHIs mainly performed in western countries, headed by the United States (n = 133), Germany (n = 32) and Spain (n = 23). Of all identified DHIs, 261 targeted healthcare providers (HCP), 66 clients (e.g. patients, caregivers, healthy individuals) and 67 both clients and HCPs. A majority of DHIs focussed on establishing a diagnosis (n = 254). Every other study analysed store‐and‐forward teledermatology (n = 187), followed by artificial intelligence applications for image analysis (n = 65). The most often analysed DHI category for clients was a support of health behaviour change (n = 31). Monitoring of clients was targeted by 77 studies. Skin cancer (n = 148), wounds (n = 29) and psoriasis (n = 29) were the most targeted indications by DHIs. Most studies analysed diagnostic performance (n = 166), fewer studies analysed acceptance (n = 92) and effectiveness (n = 98). Usability (n = 32) and efficiency (n = 36) were investigated only to a small extent. Studies on DHIs in dermatology have focused on teledermatology and AI applications, with an emphasis on skin cancer diagnosis. Apart from that, a range of DHIs for different user groups, purposes and indications were identified, demonstrating the broad potential for DHIs in dermatology. Further research with a wider set of outcome parameters is needed to fully understand the potential of DHIs and ensure their sustainable implementation into dermatological care.
Reconstruction of the Dark Energy Equation of State from the Latest Observations

Since the discovery of the accelerating expansion of our universe in 1998, studying the features of dark energy has remained a hot topic in modern cosmology. In the literature, dark energy is usually described by w ≡ P/ρ, where P and ρ denote its pressure and energy density. Therefore, exploring the evolution of w is the key approach to understanding dark energy. In this work, we adopt three different methods, polynomial expansion, principal component analysis, and the correlated prior method, to reconstruct w with a collection of the latest observations, including the type-Ia supernova, cosmic microwave background, large-scale structure, Hubble measurements, and baryon acoustic oscillations (BAOs), and find that the concordance cosmological constant model (w = −1) is still safely consistent with these observational data at the 68% confidence level. However, when we add the high-redshift BAO measurement from the Lyα forest (Lyα FB) of BOSS DR11 quasars into the calculation, there is a significant impact on the reconstruction result. In the standard ΛCDM model, since the Lyα FB data slightly prefer a negative dark energy density, in order to avoid this problem, a dark energy model with a w significantly smaller than −1 is needed to explain this Lyα FB data. In this work, we find the consistent conclusion that there is a strong preference for the time-evolving behavior of dark energy w at high redshifts, when including the Lyα FB data. Therefore, we think that this Lyα FB data needs to be watched carefully attention when studying the evolution of the dark energy equation of state.
Retrospective Study of Treatment Patterns and Natural History of Patients with T1a/b N0 Triple-Negative Breast Cancers: A Single-Institution Experience

Introduction: T1a/b, node-negative (node−), triple-negative breast cancers (TNBCs) are underrepresented in randomized drug-approving clinical trials. Given their low incidence, the clinicopathological features, natural history, and treatment patterns of these tumors remain insufficiently understood. Methods: We conducted a single-institution retrospective cohort study of patients with T1a/b, N0, M0 TNBCs. Deidentified patient- and tumor-related data were collected and summarized. Kruskal-Wallis, χ2, or Fisher exact tests were used to evaluate associations of interest. Kaplan-Meier methods, log-rank tests, and Cox’s proportional hazards models were applied for survival analyses. Results: Of 108 cases of node– TNBCs measuring ≤2 cm, 34 node– T1a/b tumors were included in our analysis. All cases had an intermediate to high histological grade, and most had a Ki-67 score of ≥20%. All patients received adjuvant chemotherapy, and many underwent mastectomy (47%). Docetaxel combined with cyclophosphamide was the most common adjuvant chemotherapy regimen (75%). We did not observe significant associations between improved outcomes and treatment with anthracycline-containing regimens. Among patients with node– pT1a/b tumors, the estimated 3-year recurrence-free survival (RFS) and distant RFS rates were both 96.3% (95% CI: 76.5–99.5), and the overall survival rate was estimated to be 100% (95% CI: 100–100). There were no cases of local recurrences observed. Conclusions: In our cohort, all patients with T1a/b node– TNBCs were treated with adjuvant chemotherapy and had favorable outcomes even when treated with anthracycline-sparing regimens.
Diversity and genetic architecture of agro-morphological traits in a core collection of European traditional tomato

Abstract European traditional tomato varieties have been selected by farmers given their consistent performance and adaptation to local growing conditions. Here we developed a multipurpose core collection, comprising 226 accessions representative of the genotypic, phenotypic, and geographical diversity present in European traditional tomatoes, to investigate the basis of their phenotypic variation, gene×environment interactions, and stability for 33 agro-morphological traits. Comparison of the traditional varieties with a modern reference panel revealed that some traditional varieties displayed excellent agronomic performance and high trait stability, as good as or better than that of their modern counterparts. We conducted genome-wide association and genome-wide environment interaction studies and detected 141 quantitative trait loci (QTLs). Out of those, 47 QTLs were associated with the phenotype mean (meanQTLs), 41 with stability (stbQTLs), and 53 QTL-by-environment interactions (QTIs). Most QTLs displayed additive gene actions, with the exception of stbQTLs, which were mostly recessive and overdominant QTLs. Both common and specific loci controlled the phenotype mean and stability variation in traditional tomato; however, a larger proportion of specific QTLs was observed, indicating that the stability gene regulatory model is the predominant one. Developmental genes tended to map close to meanQTLs, while genes involved in stress response, hormone metabolism, and signalling were found within regions affecting stability. A total of 137 marker–trait associations for phenotypic means and stability were novel, and therefore our study enhances the understanding of the genetic basis of valuable agronomic traits and opens up a new avenue for an exploitation of the allelic diversity available within European traditional tomato germplasm.
Sufficient Time-Frequency Resolution for Reproducing Vibrotactile Sensation

In vibrotactile stimuli, it is essential to reproduce realistic tactile sensations to enhance the immersiveness of applications. To reproduce more realistic tactile experiences, various tools have been proposed to fine-tune and design vibrotactile sensations. Considering the situation where users adjust parameters manually, providing tactile sensations with fewer parameters is desirable. This study examines the coarsest resolution in the time and frequency dimensions necessary to present tactile sensations as realistic as vibrations recorded by the sensor. Time and frequency are fundamental parameters to express vibrations as a spectrogram, and we considered it important to investigate how much coarser the resolution could be without changing perception. We focus on the textural vibrations and the preliminary experiment compared actual texture vibrations with the reconstructed vibration as coarse as possible in the frequency dimension. The result showed that the frequency resolution above 172 Hz makes it difficult to distinguish between the vibrations. The main experiment, a similar discrimination experiment, verified the time resolution using the averaging filter of vibration intensity over time. The results indicate that with the update interval set to 30 ms, the discrimination rate compared to the original vibration is approximately 60%. This percentage is below the chance level of 75%, indicating that distinguishing between the two is difficult. Based on our experiments, it is necessary to have a frequency resolution of at least 172 Hz and a time resolution that updates intensity at a rate of 30 fps or higher to recreate tactile sensations comparable to actual vibrations.
Refractive outcomes of toric intra-ocular lens implantation in cases of high posterior corneal astigmatism

Purpose: To evaluate whether the toric intra-ocular lens (IOL) power calculation based on total corneal astigmatism (TCA) in eyes with high posterior corneal astigmatism (PCA) could result in a systematic over-correction or under-correction after operation. Methods: The present study included a mono-centric retrospective study design. The data were collected from 62 consecutive eyes during uncomplicated cataract surgery by a single surgeon with a measured PCA of 0.50 diopters (D) or higher. Toric IOL calculations were made using TCA measurements. The eyes were grouped as either “with-the-rule” (WTR) or “against-the-rule” (ATR) on the basis of the steep anterior corneal meridian. The post-operative refractive astigmatic prediction error was analyzed 1 month post-operatively using the vector analysis by the Alpins method and double-angle plots method. Results: The correction indexes were 1.14 ± 0.29 in the ATR eyes and 1.25 ± 0.18 for the WTR eyes, indicating a tendency toward over-correction. The mean over-correction was 0.22 ± 0.52D in the ATR group and 0.65 ± 0.60D in the WTR group. The magnitude of error (ME) values were significantly different from the ideal value of zero in both groups (ATR: P = 0.03; WTR: P = 0.00). No significant difference in mean absolute error (MAE) in predicted residual astigmatism was found between ATR and WTR groups (0.61 ± 0.42 D versus 0.64 ± 0.39 D; P = 0.54). The ATR group yielded better results, with 48% <0.50D prediction error in the main analysis. Conclusions: The results suggested that in cases of high PCA, the toric IOL calculation, which was performed using TCA, may cause a potential over-correction in the ATR and WTR eyes. For ATR eyes, over-correction led to slight disruption of post-operative visual quality because of the “with-the-rule” residual astigmatism after operation. Therefore, we suggested using TCA for toric IOL calculation in ATR eyes.
Arithmetic research about boolean operation of surfel model based on hierarchical bounding volumes

As CSG primitive, the point is not studied deeply in application of digital geometry. With no topology and adjacency of point models, it is unnecessary to keep consistent with the topology at the time of modeling, but it brings more difficulties to drawing and keeping the surface flow. Review the point model-based geometrical expressions, this paper puts forward a improved data structure of surfel, achieves the complicated surfel modeling with constructive solid geometry technique and brings forward the Boolean operators for the complicated surfel modeling. Based on the point modeling process, solves the quick intersection and lowers the time complexity of algorithm with the theory of hierarchical bounding volumes. This paper describes the intersection test with the grid-topological relations to further quicken the intersection test and puts forward that the time complexity of n primitives is reduced from O(n2) to O(logd-1 n + Kb) in the bounding box way of the Boolean operators based on the improved basic surfel data structures. (5 pages)
A multiphase active contour model based on the Hermite transform for texture segmentation

Texture is one of the most important elements used by the human visual system (HVS) to distinguish different objects in a scene. Early bio-inspired methods for texture segmentation involve partitioning an image into distinct regions by setting a criterion based on their frequency response and local properties in order to further perform a grouping task. Nevertheless, the correct texture delimitation still remains as an important challenge in image segmentation. The aim of this study is to generate a novel approach to discriminate different textures by comparing internal and external image content in a set of evolving curves. We propose a multiphase formulation with an active contour model applied on the highest energy coefficients generated by the Hermite transform (HT). Local texture features such as scale and orientation are reflected in the HT coefficients which guide the evolution of each curve. This process leads to the enclosure of similar characteristics in a region associated with a level set function. The efficiency of our proposal is evaluated using a variety of synthetic images and real textured scenes.
A Hybrid Approach To Real-Time Multi-Object Tracking

Multi-Object Tracking, also known as Multi-Target Tracking, is a significant area of computer vision that has many uses in a variety of settings. The development of deep learning, which has encouraged researchers to propose more and more work in this direction, has significantly impacted the scientific advancement around the study of tracking as well as many other domains related to computer vision. In fact, all of the solutions that are currently state-of-the-art in the literature and in the tracking industry, are built on top of deep learning methodologies that produce exceptionally good results. Deep learning is enabled thanks to the ever more powerful technology researchers can use to handle the significant computational resources demanded by these models. However, when real-time is a main requirement, developing a tracking system without being constrained by expensive hardware support with enormous computational resources is necessary to widen tracking applications in real-world contexts. To this end, a compromise is to combine powerful deep strategies with more traditional approaches to favor considerably lower processing solutions at the cost of less accurate tracking results even though suitable for real-time domains. Indeed, the present work goes in that direction, proposing a hybrid strategy for real-time multi-target tracking that combines effectively a classical optical flow algorithm with a deep learning architecture, targeted to a human-crowd tracking system exhibiting a desirable trade-off between performance in tracking precision and computational costs. The developed architecture was experimented with different settings, and yielded a MOTA of 0.608 out of the compared state-of-the-art 0.549 results, and about half the running time when introducing the optical flow phase, achieving almost the same performance in terms of accuracy.
DeepTSF: Codeless machine learning operations for time series forecasting

This paper presents DeepTSF, a comprehensive machine learning operations (MLOps) framework aiming to innovate time series forecasting through workflow automation and codeless modeling. DeepTSF automates key aspects of the ML lifecycle, making it an ideal tool for data scientists and MLops engineers engaged in machine learning (ML) and deep learning (DL)-based forecasting. DeepTSF empowers users with a robust and user-friendly solution, while it is designed to seamlessly integrate with existing data analysis workflows, providing enhanced productivity and compatibility. The framework offers a front-end user interface (UI) suitable for data scientists, as well as other higher-level stakeholders, enabling comprehensive understanding through insightful visualizations and evaluation metrics. DeepTSF also prioritizes security through identity management and access authorization mechanisms. The application of DeepTSF in real-life use cases of the I-NERGY project has already proven DeepTSF's efficacy in DL-based load forecasting, showcasing its significant added value in the electrical power and energy systems domain.
Hand tracking for clinical applications: validation of the Google MediaPipe Hand (GMH) and the depth-enhanced GMH-D frameworks

Accurate 3D tracking of hand and fingers movements poses significant challenges in computer vision. The potential applications span across multiple domains, including human-computer interaction, virtual reality, industry, and medicine. While gesture recognition has achieved remarkable accuracy, quantifying fine movements remains a hurdle, particularly in clinical applications where the assessment of hand dysfunctions and rehabilitation training outcomes necessitate precise measurements. Several novel and lightweight frameworks based on Deep Learning have emerged to address this issue; however, their performance in accurately and reliably measuring fingers movements requires validation against well-established gold standard systems. In this paper, the aim is to validate the handtracking framework implemented by Google MediaPipe Hand (GMH) and an innovative enhanced version, GMH-D, that exploits the depth estimation of an RGB-Depth camera to achieve more accurate tracking of 3D movements. Three dynamic exercises commonly administered by clinicians to assess hand dysfunctions, namely Hand Opening-Closing, Single Finger Tapping and Multiple Finger Tapping are considered. Results demonstrate high temporal and spectral consistency of both frameworks with the gold standard. However, the enhanced GMH-D framework exhibits superior accuracy in spatial measurements compared to the baseline GMH, for both slow and fast movements. Overall, our study contributes to the advancement of hand tracking technology, the establishment of a validation procedure as a good-practice to prove efficacy of deep-learning-based hand-tracking, and proves the effectiveness of GMH-D as a reliable framework for assessing 3D hand movements in clinical applications.