Miracle-dz/UniFAR-FTUs huggingface dataset:
Single-cell RNA-seq reveals a link of ovule abortion and sugar transport in Camellia oleifera

Camellia oleifera is the most important woody oil crop in China. Seed number per fruit is an important yield trait in C. oleifera. Ovule abortion is generally observed in C. oleifera and significantly decreases the seed number per fruit. However, the mechanisms of ovule abortion remain poorly understood at present. Single-cell RNA sequencing (scRNA-seq) was performed using mature ovaries of two C. oleifera varieties with different ovule abortion rates (OARs). In total, 20,526 high-quality cells were obtained, and 18 putative cell clusters were identified. Six cell types including female gametophyte, protoxylem, protophloem, procambium, epidermis, and parenchyma cells were identified from three main tissue types of ovule, placenta, and pericarp inner layer. A comparative analysis on scRNA-seq data between high- and low-OAR varieties demonstrated that the overall expression of CoSWEET and CoCWINV in procambium cells, and CoSTP in the integument was significantly upregulated in the low-OAR variety. Both the infertile ovule before pollination and the abortion ovule producing after compatible pollination might be attributed to selective abortion caused by low sugar levels in the apoplast around procambium cells and a low capability of hexose uptake in the integument. Here, the first single-cell transcriptional landscape is reported in woody crop ovaries. Our investigation demonstrates that ovule abortion may be related to sugar transport in placenta and ovules and sheds light on further deciphering the mechanism of regulating sugar transport and the improvement of seed yield in C. oleifera.
Functional dependence at discharge from the intensive care unit: relevance for rehabilitation nursing

Background: Stays in the intensive care unit can cause adverse effects that lead to situations of functional disability, which persist for a long time. Early rehabilitation can prevent or limit such situations. Objectives: To characterize the functional level and dependencies at discharge from intensive care. To assay the timing for initiating rehabilitation nursing interventions. Methodology: Descriptive/exploratory study, quantitative method, in a sample of 30 patients. Results: Average of Medical Research Council value was 27 (first evaluation) and 38 (at discharge). The mean value of the Functional Independence Measure, in the area of self-care, mobility / transfers was 2. The first intervention of rehabilitation nursing occurred, on average, on the 10th day and the patient got out of bed after 13 days. Conclusion: At discharge, there were high levels of functional dependence at the level of basic self-care and mobility/transfers, and their characterization should be improved for the continuity of rehabilitation care. Early mobilization of critical patients is necessary.
Pitfalls with the MAKO Robotic-Arm-Assisted Total Knee Arthroplasty

Robotic-arm-assisted total knee arthroplasty (RATKA) with the MAKO system minimizes deviations in implant alignment and yields superior precision in implant position compared to a manual total knee arthroplasty. In this comprehensive commentary, we present and categorize the limitations and pitfalls of the procedure and we also provide recommendations for avoiding each limitation. The main surgeon-related limitations include prolonged operation duration, loose insertion of the checkpoints and pins, wrong registration and mapping, and damage to soft tissues during bone cutting. The system-related issues include the interruptions of the saw-cutting due to vibrations, specifications for the operating room floor and power supply, the high cost of the system, as well as the cost of each operation due to the extra implants, inability to use the system with various prostheses, wireless connection interruptions between the system’s components, and hardware issues with the six joints of the robotic device. In order to circumvent the potential challenges in this surgical procedure, it is essential to possess sufficient experience and undergo comprehensive training. Maintaining continuous awareness of the additional implants throughout the entire operation and prioritizing the preservation of soft tissues are of paramount significance. A profound comprehension of the system and its inherent constraints can also prove to be pivotal in certain situations.
Diverse Methodologies to Improve Covariance based Object Tracking

Tracking is an important process of computer vision research. But still after so many researches accuracy is still become a bottleneck. Within different tracking techniques covariance based tracking is a new technique which gives more accuracy than other techniques. There are several methods and researches have been done on covariance tracking. The covariance tracking process also uses some distance measures to calculate the dissimilarity between two target regions. Here we have list down some of the most useful distance measurement techniques which provide accurate results. We have also implemented those distance measurement techniques and shown their results with accuracy comparison. Even the distance between the target and the candidate covariance matrix is itself enough track an object, but to get more accurate result some techniques are applied on covariance tracking. Here we have listed some of those techniques which happen to provide better results after applying on covariance tracking and also pointed out the advantages and drawbacks of those techniques.
Can unguided machine learning re-discover physiologic signatures of neonatal sepsis?

Background: Cardiorespiratory deterioration due to sepsis is a leading cause of morbidity and mortality for extremely premature infants with very low birth weight (VLBW, birthweight <1500g). Abnormal heart rate (HR) patterns precede the clinical diagnosis of late-onset sepsis in this population. Decades ago, clinicians recognized a pattern of reduced HR variability and increased HR decelerations in electrocardiogram tracings of septic preterm infants. A predictive logistic regression model was developed from this finding using mathematical algorithms developed to detect this signature of illness. Display of this model as the fold increase in risk of imminent sepsis reduced mortality in a large randomized trial. Here, we sought to determine if machine learning or deep learning approaches would identify this rare but distinctive signature of sepsis in VLBW infants. Methods: We studied VLBW infants admitted from 2012 to 2021 to a regional Level IV NICU. We collected one-hour HR time series data from bedside monitoring sampled at 0.5 Hz (n=300 HR values per series) throughout the NICU admission. First, we applied the principles of highly comparative time series analysis (HCTSA) to generate many mathematical time series features and combined them in a machine learning model. Next, we used deep learning in the form of a convolutional neural network on the raw data to learn the HR features. The output was a set of HR records determined by HCTSA or deep learning to be at high risk for imminent sepsis. Results: We analyzed data from 566 infants with 61 episodes of sepsis. HCTSA and deep learning models predicted sepsis with high out-of-sample validation metrics. The riskiest records determined by both approaches demonstrated the previously identified HR signatures- reduced variability and increased decelerations. Conclusions: We tested the ability of unguided machine learning approaches to detect the novel HR signature of sepsis in VLBW infants previously identified by human experts. Our main finding is that the computerized approach returned the same result - it identified heart rate characteristics of reduced variability and transient decelerations. We conclude that unguided machine learning can be as effective as human experts in identifying even a very rare phenotype in clinical data.
Selection of artemisinin partial resistance Kelch13 mutations in Uganda in 2016–22 was at a rate comparable to that seen previously in South-East Asia

Background Artemisinin partial resistance, mediated by mutations in the Plasmodium falciparum Kelch13 protein (K13), rapidly spread in South-East Asia (SEA), undermining antimalarial efficacies of artemisinin-based combination therapies (ACT). Validated K13 mutations have recently arisen in Africa, but rates of increase are not well characterized. Methods We investigated K13 mutation prevalence at 16 sites in Uganda (2016-2022, 6586 samples), and five sites in SEA (2003-2018, 5465 samples) by calculating selection coefficients using Bayesian mixed-effect linear models. We then tested whether SEA K13 mutation prevalence could have been forecast accurately using up to the first five years of available data and forecast future K13 mutation prevalence in Uganda. Findings The selection coefficient for the prevalence of relevant K13 mutations (441L, 469F/Y, 561H, 675V) was estimated at s=0.383 (95% CrI: 0.247 - 0.528) per year, a 38% relative prevalence increase. Selection coefficients across Uganda were s=0.968 (0.463 - 1.569) for 441L, s=0.153 (-0.445 - 0.727) for 469F, s=0.222 (-0.011 - 0.398) for 469Y, and s=0.152 (-0.023 - 0.312) for 675V. In SEA, the selection coefficient was s=-0.005 (-0.852 - 0.814) for 539T, s=0.574 (-0.092 - 1.201) for 580Y, and s=0.308 (0.089 - 0.536) for all validated K13 mutations. Forecast prevalences for Uganda assuming constant selection neared fixation (>95% prevalence) within a decade (2028-2033) for combined K13 mutations. Interpretation The selection of K13 mutations in Uganda was at a comparable rate to that observed in SEA, suggesting K13 mutations may continue to increase quickly in Uganda.
Changes to an intensive care unit Acinetobacter baumannii population following COVID-19 disruptions and targeted infection prevention interventions.

Carbapenem-resistant Acinetobacter baumannii (CRAB) is a persistent nosocomial pathogen that poses a significant threat to global public health. A three-month cross-sectional observational study was conducted in a 28-bed ICU in Hangzhou, China. The same ICU was sampled for the same duration and with a similar methodology in 2019, 20 months prior to the outset of this study. Following COVID-19-associated delays, a series of IPC measures targeting patients, staff and the ICU environment were implemented for 8 months prior to and throughout this study. A total of 5,341 samples were collected from the ICU environment (n = 4450) and patients (n = 891). A. baumannii isolates were obtained from 9.5% of these samples (n = 505). Most A. baumannii isolated in this ICU were CRAB (419/518; 80.9%). Fewer CRAB were isolated here (407 from 363 sampling occasions) than in 2019 (502 from 336 sampling occasions). However, MIC50/MIC90 values for imipenem increased from 32/64 mg/L in the 2019 study to 64/128 mg/L here. This was accompanied by the proportion of global clone 2 (GC2) isolates falling from 99.5% in 2019 to 50.8% (213/419) in 2021. The phylogenetic diversity of GC2 increased, apparently driven by regular introductions of distinct clusters in association with patients. The remaining CRAB (40.2%; 206/419) were a highly clonal population of ST164, which appears to have persisted in the ICU since an introduction in mid-2020. We found clusters of GC2 and ST164 isolates with identical core genomes in different room or bed unit environments, and in multiple patients, indicative of transmission in the ICU. Changes to IPC procedures in this ICU were associated with a reduction in the total prevalence of CRAB, and in the number of CRAB isolated from clinical specimens. At the phenotypic level, the CRAB population exhibited increased resistance to carbapenems, and this may be the result of increased antibiotic prescribing over the COVID-19 period. The increased diversity of this CRAB population appears to have been the result of repeated introductions to the ICU with patients, which have continued despite interventions.
Neck circumference is a highly reliable anthropometric measure in older adults requiring long-term care

The reliability of neck circumference measurement as an assessment tool for older adults requiring long-term care remains unknown. This study aimed to evaluate the reliability of neck circumference measurement in older adults requiring long-term care, and the effect of edema on measurement error. Two physical therapists measured the neck circumference. Intraclass correlation coefficient (ICC) and Bland–Altman analyses were performed to examine the reliability of neck circumference measurement. Correlation analysis was used to evaluate the relationship between edema values (extracellular water/total body water) and neck circumference measurement difference. For inter-rater reliability of neck circumference measurement, the overall ICC (2,1) was 0.98. The upper and lower limits of the difference between examiners ranged from −0.9 to 1.2 cm. There was no association between edema values and neck circumference measurement error. Thus, measurement of the neck circumference in older adults requiring long-term care is a reliable assessment tool, with a low error rate, even in older adults with edema.
Bibliometric analysis and visualization of top papers in dentistry from 2012 to 2022 based on essential science indicators

Abstract Objectives This study aims to analyze and visualize the top dental papers from 2012 to 2022 using data from essential science indicators (ESIs). Materials and Methods The present study was conducted using library and retrospective bibliometric analysis methods. Additionally, a science map has been created. Web of Science was searched on January 18, 2023. The results were limited to the top papers in ESIs. The bibliometric information of the top papers was evaluated. Next, the VOSviewer was used to perform a co‐occurrence analysis and visualize data. Results The findings showed that Mariano Belén Sanz and Maurizio S. Tonetti were the top two authors. The University of London and the University of Bern had the highest number of articles. These articles were published in 55 journals. According to the analysis of keyword co‐occurrence, the most frequently used keywords in the field of dentistry include “periodontitis,” “dental implants,” “periodontal disease,” “mechanical properties,” “peri‐implantitis,” “oral health,” “dental caries,” “dental materials,” “3D printing. ” Conclusion The findings of this study enable readers to pinpoint the authors, organizations, countries, and journals that have made the biggest contributions to the list of the most often cited dentistry papers. In medicine, bibliometric citation analysis is frequently used to assist researchers in learning the fundamentals of a subject and pinpoint subtopics of broad interest for additional study.
An exploratory network analysis of mobile broadband provider's infrastructure relationships in Tamil Nadu, India

This study analyses the emergent network features of the upstream connectivity structure of three mobile broadband providers in the area included between the cities of Kancheepuram and Chennai in Tamil Nadu, India, from an original end-users perspective. This perspective is based on using a large dataset, collected by the authors, in February 2015, generated by the crowdsourcing-based Portolan Network Sensing Application on Android devices. The key feature of these data is that they are user generated and reflect mobility, as they were sourced from smartphones along the route between Chennai and Kancheepuram, rather than being based on stationary operators masts. Internet Service Providers traditionally rely on Border Gateway Protocols (BGP) for interconnecting purposes. Adding an end-user perspective to the existing BGP routing tables reveals a more complete picture of the underlying topology for the studied mobile broadband providers. The data were then used to conduct an Internet Periphery Analysis, pointing towards the roles of existing traffic peering agreements among the Internet Service Providers, and focussing on the role played by International Exchange Points (IXPs) key electronic infrastructures in the region. The analysis identifies the emergence of possible bottlenecks affecting upstream competition and the key role played by IXPs in providing a more widely distributed network access structure. This paper proposes to further study the usage of settlement free peering in fair competition and the preconditions of Quality of Service and service pricing in the Indian Mobile Broadband Market.
Unmanned Aerial Vehicles (UAVs) in environmental biology: a review

Abstract Acquiring information about the environment is a key step during each study in the field of environmental biology at different levels, from an individual species to community and biome. However, obtaining information about the environment is frequently difficult because of, for example, the phenological timing, spatial distribution of a species or limited accessibility of a particular area for the field survey. Moreover, remote sensing technology, which enables the observation of the Earth’s surface and is currently very common in environmental research, has many limitations such as insufficient spatial, spectral and temporal resolution and a high cost of data acquisition. Since the 1990s, researchers have been exploring the potential of different types of unmanned aerial vehicles (UAVs) for monitoring Earth’s surface. The present study reviews recent scientific literature dealing with the use of UAV in environmental biology. Amongst numerous papers, short communications and conference abstracts, we selected 110 original studies of how UAVs can be used in environmental biology and which organisms can be studied in this manner. Most of these studies concerned the use of UAV to measure the vegetation parameters such as crown height, volume, number of individuals (14 studies) and quantification of the spatio-temporal dynamics of vegetation changes (12 studies). UAVs were also frequently applied to count birds and mammals, especially those living in the water. Generally, the analytical part of the present study was divided into following sections: (1) detecting, assessing and predicting threats on vegetation, (2) measuring the biophysical parameters of vegetation, (3) quantifying the dynamics of changes in plants and habitats and (4) population and behaviour studies of animals. At the end, we also synthesised all the information showing, amongst others, the advances in environmental biology because of UAV application. Considering that 33% of studies found and included in this review were published in 2017 and 2018, it is expected that the number and variety of applications of UAVs in environmental biology will increase in the future.
Which trees die during drought? The key role of insect host‐tree selection

During drought, the tree subpopulations (such as size or vigour classes) that suffer disproportionate mortality can be conceptually arrayed along a continuum defined by the actions of biotic agents, particularly insects. At one extreme, stress dominates: insects are absent or simply kill the most physiologically stressed trees. At the opposite extreme, host selection dominates: outbreaking insects kill trees independently of their stress, instead selecting trees based on size or other traits. Intermediate responses are also possible. Yet for mixed‐species forests, we lack a broad understanding of the relative importance of insects in determining exactly which subpopulations of trees suffer disproportionate mortality during drought, and whether these subpopulations differ among co‐occurring tree species. During an extreme drought, we documented the roles of native bark beetles in the mortality of five tree species in California’s Sierra Nevada. We analysed the patterns and agents of tree mortality in 12 permanent plots and the patterns of mortality in 89 temporary plots. Most tree mortality was associated with bark beetles. However, the growth rates (an indicator of chronic stress) and sizes of trees that suffered greatest bark beetle‐related mortality differed sharply among tree taxa, variously conforming with domination by stress (Abies concolor), domination by host selection (Pinus lambertiana and P. ponderosa) or a mix of the two (Calocedrus decurrens). Quercus kelloggii mortality remained relatively low. Thus, even during extreme drought substantial proportions of stressed trees survived because they were of sizes that mostly avoided fatal insect attack. Conversely, substantial proportions of comparatively unstressed trees died because they were of sizes that were selectively killed by outbreaking insects. Synthesis. Native bark beetles were primarily responsible for determining which subpopulations of trees suffered greatest mortality during drought. However, idiosyncratic host‐tree selection by the different bark beetle taxa meant that the tree subpopulations suffering greatest mortality differed strikingly among tree taxa—for example, high mortality of small trees of one species, but of large trees of another. If idiosyncratic host‐tree selection by biotic mortality agents proves to be a generally common phenomenon, it could help explain weak broadscale correlations between tree traits and tree mortality during drought.
The Moran model with random resampling rates

In this paper we consider the two-type Moran model with $N$ individuals. Each individual is assigned a resampling rate, drawn independently from a probability distribution ${\mathbb P}$ on ${\mathbb R}_+$, and a type, either $1$ or $0$. Each individual resamples its type at its assigned rate, by adopting the type of an individual drawn uniformly at random. Let $Y^N(t)$ denote the empirical distribution of the resampling rates of the individuals with type $1$ at time $Nt$. We show that if ${\mathbb P}$ has countable support and satisfies certain tail and moment conditions, then in the limit as $N\to\infty$ the process $(Y^N(t))_{t \geq 0}$ converges in law to the process $(S(t)\,\P)_{t \geq 0}$, in the so-called Meyer-Zheng topology, where $(S(t))_{t \geq 0}$ is the Fisher-Wright diffusion with diffusion constant $D$ given by $1/D = \int_{{\mathbb R}_+} (1/r)\,{\mathbb P}(\mathrm{d} r)$.
Decoupled few-femtosecond phase transitions in vanadium dioxide

The nature of the insulator-to-metal phase transition in vanadium dioxide (VO2) is one of the longest-standing problems in condensed-matter physics. Ultrafast spectroscopy has long promised to determine whether the transition is primarily driven by the electronic or structural degree of freedom, but measurements to date have been stymied by their sensitivity to only one of these components and/or their limited temporal resolution. Here we use ultra-broadband few-femtosecond pump-probe spectroscopy to resolve the electronic and structural phase transitions in VO2 at their fundamental time scales. We find that the system transforms into a bad-metallic phase within 10 fs after photoexcitation, but requires another 100 fs to complete the transition, during which we observe electronic oscillations and a partial re-opening of the bandgap, signalling a transient semi-metallic state. Comparisons with tensor-network simulations and density-functional theory calculations show these features originate from oscillations around the equilibrium high-symmetry atomic positions during an unprecedentedly fast structural transition, in which the vanadium dimers separate and untwist with two different timescales. Our results resolve the complete structural and electronic nature of the light-induced phase transition in VO2 and establish ultra-broadband few-femtosecond spectroscopy as a powerful new tool for studying quantum materials out of equilibrium.