Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Phenotypic Repeatability of Canopy Temperature in Wheat Using Continuous-Terrestrial and Airborne Measurements

Infrared canopy temperature (CT) is a well-established surrogate measure of stomatal conductance. There is ample evidence showing that genotypic variation in stomatal conductance is associated with grain yield in wheat. Our goal was to determine when CT repeatability is greatest (throughout the season and within the day) to guide CT deployment for research and wheat breeding. CT was measured continuously with ArduCrop wireless infrared thermometers from post-tillering to physiological maturity, and with airborne thermography on cloudless days from manned helicopter at multiple times before and after flowering. Our experiments in wheat, across two years contrasting for water availability, showed that repeatability for CT was greatest later in the season, during grain-filling, and usually in the afternoon. This was supported by the observation that repeatability for ArduCrop, and more so for airborne CT, was significantly associated (P < 0.0001) with calculated clear-sky solar radiation and to a lesser degree, vapor pressure deficit. Adding vapor pressure deficit to a model comprising either clear-sky solar radiation or its determinants, day-of-year and hour-of-day, made little to no improvement to the coefficient of determination. Phenotypic correlations for airborne CT afternoon sampling events were consistently high between events in the same year, more so for the year when soil water was plentiful (r = 0.7 to 0.9) than the year where soil water was limiting (r = 0.4 to 0.9). Phenotypic correlations for afternoon airborne CT were moderate between years contrasting in soil water availability (r = 0.1 to 0.5) and notably greater on two separate days following irrigation or rain in the drier year, ranging from r = 0.39 to 0.53 (P < 0.0001) for the midday events. For ArduCrop CT the pattern of phenotypic correlations, within a given year, was similar for both years: phenotypic correlations were higher during the grain-filling months of October and November and for hours-of-day from 11 onwards. The lowest correlations comprised events from hours-of-day 8 and 9 across all months. The capacity for the airborne method to instantaneously sample CT on hundreds of plots is more suited to large field experiments than the static ArduCrop sensors which measure CT continuously on a single experimental plot at any given time. Our findings provide promising support for the reliable deployment of CT phenotyping for research and wheat breeding, whereby the high repeatability and high phenotypic correlations between afternoon sampling events during grain-filling could enable reliable screening of germplasm from only one or two sampling events.
Engaging Fishers' Ecological Knowledge for Endangered Species Conservation: Four Advantages to Emphasizing Voice in Participatory Action Research

Using social science to integrate local knowledge into conservation science can provide unique insights to conservation challenges. Especially when baseline data of a vulnerable wildlife population is deficient, these methods can help fill critical data gaps. In this study, we integrate the principals from the trinity of voice (TOV) and participatory action research (PAR) to generate baseline data on in-water habitat use of critically endangered hawksbill sea turtles (Eretmochelys imbricata) and to build mutually beneficial relationships with local stakeholders near the hawksbill’s two primary nesting grounds: mangrove estuaries in El Salvador and Nicaragua. Local stakeholders, in this study referred to as fishers, hold expert knowledge they have acquired both experientially and culturally. Using TOV to shape PAR, we invited stakeholders to use their fishers’ ecological knowledge (FEK) to enhance conservation of this at-risk species. Our results demonstrate that in addition to using FEK to produce quantifiable data (e.g., turtle habitat use), there are four advantages to emphasizing voice throughout a PAR project: 1) provides locality-specific information, 2) enhances mutual learning and leadership, 3) incorporates local experience, knowledge, and creativity, and 4) encourages local participation and commitment to the conservation challenge.
A Novel Role of Connexin 40-Formed Channels in the Enhanced Efficacy of Photodynamic Therapy

Despite responses to initial treatment of photodynamic therapy (PDT) being promising, a recurrence rate exists. Thus, finding novel therapeutic targets to enhance PDT efficacy is an urgent need. Reports indicate that connexin (Cx) 40 plays an important role in tumor angiogenesis and growth. However, it is unknown whether Cx40-composed channels have effects on PDT efficacy. The study uniquely demonstrated that Cx40-formed channels could enhance the phototoxicity of PDT to malignant cells in vitro and in vivo. Specifically, Cx40-formed channels at high cell density could increase PDT photocytotoxicity. This action was substantially restricted when Cx40 expression was not induced or Cx40 channels were restrained. Additionally, the presence of Cx40-composed channels enhanced the phototoxicity of PDT in the tumor xenografts. The above results indicate that enhancing the function of Cx40-formed channels increases PDT efficacy. The enhancement of PDT efficacy mediated by Cx40 channels was related with intracellular pathways mediated by ROS and calcium pathways, but not the lipid peroxide-mediated pathway. This work demonstrates the capacity of Cx40-mediated channels to increase PDT efficacy and suggests that therapeutic strategies designed to maintain or enhance Cx40 expression and/or channels composed by Cx40 may increase the therapeutic efficacy of PDT.
Waves and Swells in High Wind and Extreme Fetches, Measurements in the Southern Ocean

The generation and evolution of ocean waves by wind is one of the most complex phenomena in geophysics, and is of great practical significance. Predictive capabilities of respective wave models, however, are impaired by lack of field in situ observations, particularly in extreme Metocean conditions. The paper outlines and highlights important gaps in understanding the Metocean processes and suggests a major observational program in the Southern Ocean. This large, but poorly investigated part of the World Ocean is home to extreme weather around the year. The observational network would include distributed system of buoys (drifting and stationary) and autonomous surface vehicles (ASV), intended for measurements of waves and air-sea fluxes in the Southern Ocean. It would help to resolve the issues of limiting fetches, extreme Extra-Tropical cyclones, swell propagation and attenuation, wave-current interactions, and address the topics of wave-induced dispersal of floating objects, wave-ice interactions in the Marginal Ice Zone, Metocean climatology and its connection with the global climate.
Interactome of Glyceraldehyde-3-Phosphate Dehydrogenase Points to the Existence of Metabolons in Paracoccidioides lutzii

Paracoccidioides is a dimorphic fungus, the causative agent of paracoccidioidomycosis. The disease is endemic within Latin America and prevalent in Brazil. The treatment is based on azoles, sulfonamides and amphotericin B. The seeking for new treatment approaches is a real necessity for neglected infections. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) is an essential glycolytic enzyme, well known for its multitude of functions within cells, therefore categorized as a moonlight protein. To our knowledge, this is the first approach performed on the Paracoccidioides genus regarding the description of PPIs having GAPDH as a target. Here, we show an overview of experimental GAPDH interactome in different phases of Paracoccidioides lutzii and an in silico analysis of 18 proteins partners. GAPDH interacted with 207 proteins in P. lutzii. Several proteins bound to GAPDH in mycelium, transition and yeast phases are common to important pathways such as glycolysis and TCA. We performed a co-immunoprecipitation assay to validate the complex formed by GAPDH with triose phosphate isomerase, enolase, isocitrate lyase and 2-methylcitrate synthase. We found GAPDH participating in complexes with proteins of specific pathways, indicating the existence of a glycolytic and a TCA metabolon in P. lutzii. GAPDH interacted with several proteins that undergoes regulation by nitrosylation. In addition, we modeled the GAPDH 3-D structure, performed molecular dynamics and molecular docking in order to identify the interacting interface between GAPDH and the interacting proteins. Despite the large number of interacting proteins, GAPDH has only four main regions of contact with interacting proteins, reflecting its ancestrality and conservation over evolution.
Neuronal Activity in the Hibernating Brain

Hibernation is a natural phenomenon in many species which helps them to survive under extreme ambient conditions, such as cold temperatures and reduced availability of food in the winter months. It is characterized by a dramatic and regulated drop of body temperature, which in some cases can be near 0°C. Additionally, neural control of hibernation is maintained over all phases of a hibernation bout, including entrance into, during and arousal from torpor, despite a marked decrease in overall neural activity in torpor. In the present review, we provide an overview on what we know about neuronal activity in the hibernating brain focusing on cold-induced adaptations. We discuss pioneer and more recent in vitro and in vivo electrophysiological data and molecular analyses of activity markers which strikingly contributed to our understanding of the brain’s sensitivity to dramatic changes in temperature across the hibernation cycle. Neuronal activity is markedly reduced with decreasing body temperature, and many neurons may fire infrequently in torpor at low brain temperatures. Still, there is convincing evidence that specific regions maintain their ability to generate action potentials in deep torpor, at least in response to adequate stimuli. Those regions include the peripheral system and primary central regions. However, further experiments on neuronal activity are needed to more precisely determine temperature effects on neuronal activity in specific cell types and specific brain nuclei.
Efficacy of CT Guided Pulsed Radiofrequency Treatment for Trigeminal Postherpetic Neuralgia

Objectives Trigeminal postherpetic neuralgia (TPHN) often presents with moderate to severe pain, hyperalgesia, and allodynia. Conventional analgesic treatments are poorly effective, which seriously affects the quality of life. This retrospective study aimed to evaluate the efficacy of pulsed radiofrequency (PRF) for the treatment of TPHN. Methods A total of 90 TPHN patients were selected between January 2014 and December 2016 in the Department of Pain Management, Shengjing Hospital, China Medical University. Patients were randomly divided into two groups according to the order of enrollment (n = 45 per group): group A, peripheral nerve (supraorbital nerve, infraorbital nerve and mental nerve) PRF; group B, gasserian ganglion PRF. Follow-up assessments of visual analogue scale (VAS) pain assessment, SF-36 health status questionnaire, total efficiency rate, and drug dosage of anticonvulsants and opioid analgesics were performed at time points of 1 week, 1 month, 3 months, 6 months, and 1 year after surgery. Results At each postsurgery time point, the VAS decreased, SF-36 (physical and mental components) increased, and drug dosage of anticonvulsants and opioids analgesics decreased in both treatment groups; values at each time point were significantly different from presurgery values (P < 0.05). Compared with group A, VAS decreased, SF-36 increased, and dosage of anticonvulsants and opioids analgesics decreased significantly in group B (P < 0.05). The total efficiency rates one year after surgery in group A and group B were 68.9 and 86.7%, respectively. The total efficiency rate of group B was statistically higher than that of group A (P < 0.05). Conclusion PRF relieved TPHN, and gasserian ganglion PRF was more effective than peripheral nerve PRF. The method was effective and improved the quality of life of the patients. PRF is recommended as a treatment for TPHN.
BE VOCAL: Characteristics of Successful Online Instructors

While classroom teaching and management strategies are well documented, the online learning environment presents different challenges and benefits. Teaching in an online environment requires a special set of teaching skills since many of the strategies and tactics associated with best teaching practices are somewhat constrained by the primarily text-based environment. The VOCAL approach summarizes the key characteristics that a master instructor utilizes to be effective in an online environment. VOCAL is an acronym for Visible, Organized, Compassionate, Analytical and Leader-byexample. The ability of the teacher to effectively infuse these characteristics into their instructional practice – to BE VOCAL - will promote a supportive, challenging, constructive, rigorous and effective instructional environment. Instructors who practice a VOCAL approach will have more productive learning environments, fewer management problems and more positive learning experiences with their students.
On the Fixed-Parameter Tractability of Capacitated Clustering

We study the complexity of the classic capacitated k -median and k -means problems parameterized by the number of centers, k . These problems are notoriously diﬃcult since the best known approximation bound for high dimensional Euclidean space and general metric space is Θ(log k ) and it remains a major open problem whether a constant factor exists. We show that there exists a (3 + (cid:15) )-approximation algorithm for the capacitated k -median and a (9 + (cid:15) )-approximation algorithm for the capacitated k -means problem in general metric spaces whose running times are f ( (cid:15), k ) n O (1) . For Euclidean inputs of arbitrary dimension, we give a (1 + (cid:15) )-approximation algorithm for both problems with a similar running time. This is a signiﬁcant improvement over the (7 + (cid:15) )-approximation of Adamczyk et al. for k -median in general metric spaces and the (69 + (cid:15) )-approximation of Xu et al. for Euclidean k -means.
Machine Learning Techniques to Identify Antimicrobial Resistance in the Intensive Care Unit

The presence of bacteria with resistance to specific antibiotics is one of the greatest threats to the global health system. According to the World Health Organization, antimicrobial resistance has already reached alarming levels in many parts of the world, involving a social and economic burden for the patient, for the system, and for society in general. Because of the critical health status of patients in the intensive care unit (ICU), time is critical to identify bacteria and their resistance to antibiotics. Since common antibiotics resistance tests require between 24 and 48 h after the culture is collected, we propose to apply machine learning (ML) techniques to determine whether a bacterium will be resistant to different families of antimicrobials. For this purpose, clinical and demographic features from the patient, as well as data from cultures and antibiograms are considered. From a population point of view, we also show graphically the relationship between different bacteria and families of antimicrobials by performing correspondence analysis. Results of the ML techniques evidence non-linear relationships helping to identify antimicrobial resistance at the ICU, with performance dependent on the family of antimicrobials. A change in the trend of antimicrobial resistance is also evidenced.
When Algorithms for Maximal Independent Set and Maximal Matching Run in Sublinear Time

Maximal independent set (MIS), maximal matching (MM), and (Delta+1)-(vertex) coloring in graphs of maximum degree Delta are among the most prominent algorithmic graph theory problems. They are all solvable by a simple linear-time greedy algorithm and up until very recently this constituted the state-of-the-art. In SODA 2019, Assadi, Chen, and Khanna gave a randomized algorithm for (Delta+1)-coloring that runs in O~(n sqrt{n}) time, which even for moderately dense graphs is sublinear in the input size. The work of Assadi et al. however contained a spoiler for MIS and MM: neither problems provably admits a sublinear-time algorithm in general graphs. In this work, we dig deeper into the possibility of achieving sublinear-time algorithms for MIS and MM. The neighborhood independence number of a graph G, denoted by beta(G), is the size of the largest independent set in the neighborhood of any vertex. We identify beta(G) as the "right" parameter to measure the runtime of MIS and MM algorithms: Although graphs of bounded neighborhood independence may be very dense (clique is one example), we prove that carefully chosen variants of greedy algorithms for MIS and MM run in O(n beta(G)) and O(n log{n} * beta(G)) time respectively on any n-vertex graph G. We complement this positive result by observing that a simple extension of the lower bound of Assadi et al. implies that Omega(n beta(G)) time is also necessary for any algorithm to either problem for all values of beta(G) from 1 to Theta(n). We note that our algorithm for MIS is deterministic while for MM we use randomization which we prove is unavoidable: any deterministic algorithm for MM requires Omega(n^2) time even for beta(G) = 2. Graphs with bounded neighborhood independence, already for constant beta = beta(G), constitute a rich family of possibly dense graphs, including line graphs, proper interval graphs, unit-disk graphs, claw-free graphs, and graphs of bounded growth. Our results suggest that even though MIS and MM do not admit sublinear-time algorithms in general graphs, one can still solve both problems in sublinear time for a wide range of beta(G) << n. Finally, by observing that the lower bound of Omega(n sqrt{n}) time for (Delta+1)-coloring due to Assadi et al. applies to graphs of (small) constant neighborhood independence, we unveil an intriguing separation between the time complexity of MIS and MM, and that of (Delta+1)-coloring: while the time complexity of MIS and MM is strictly higher than that of (Delta+1) coloring in general graphs, the exact opposite relation holds for graphs with small neighborhood independence.
Multifractal Spectrum Curvature of RR Tachograms of Healthy People and Patients with Congestive Heart Failure, a New Tool to Assess Health Conditions

We calculate the multifractal spectra of heartbeat RR-interval time series (tachograms) of healthy subjects and patients with congestive heart failure (CHF). From these time series, we obtained new subseries of 6 h durations when healthy persons and patients were asleep and awake respectively. For each time series and subseries, we worked out the multifractal spectra with the Chhabra and Jensen method and found that their graphs have different shapes for CHF patients and healthy persons. We suggest to measure two parameters: the curvature around the maximum and the symmetry for all these multifractal spectra graphs, because these parameters were different for healthy and CHF subjects. Multifractal spectra of healthy subjects tend to be right skewed especially when the subjects are asleep and the curvature around the maximum is small compared with the curvature around the maximum of the CHF multifractal spectra; that is, the spectra of patients tend to be more pointed around the maximum. In CHF patients, we also have encountered differences in the curvature of the multifractal spectra depending on their respective New York Heart Association (NYHA) index.
Polynomial Anonymous Dynamic Distributed Computing Without a Unique Leader

© Dariusz R. Kowalski and Miguel A. Mosteiro; licensed under Creative Commons License CC-BY Counting the number of nodes in Anonymous Dynamic Networks is enticing from an algorithmic perspective: an important computation in a restricted platform with promising applications. Starting with Michail, Chatzigiannakis, and Spirakis [18], a flurry of papers sped up the running time guarantees from doubly-exponential to polynomial [16]. There is a common theme across all those works: a distinguished node is assumed to be present, because Counting cannot be solved deterministically without at least one. In the present work we study challenging questions that naturally follow: how to efficiently count with more than one distinguished node, or how to count without any distinguished node. More importantly, what is the minimal information needed about these distinguished nodes and what is the best we can aim for (count precision, stochastic guarantees, etc.) without any. We present negative and positive results to answer these questions. To the best of our knowledge, this is the first work that addresses them.
Task-based Augmented Reeb Graphs with Dynamic ST-Trees

This paper presents, to the best of our knowledge, the ﬁrst parallel algorithm for the computation of the augmented Reeb graph of piecewise linear scalar data. Such augmented Reeb graphs have a wide range of applications, including contour seeding and feature based segmentation. Our approach targets shared-memory multi-core workstations. For this, it completely revisits the optimal, but sequential, Reeb graph algorithm, which is capable of handing data in arbitrary dimension and with optimal time complexity. We take advantage of Fibonacci heaps to exploit the ST-Tree data structure through independent local propagations, while maintaining the optimal, linearithmic time complexity of the sequential reference algorithm. These independent propagations can be expressed using OpenMP tasks, hence beneﬁting in parallel from the dynamic load balancing of the task runtime while enabling us to increase the parallelism degree thanks to a dual sweep. We present performance results on triangulated surfaces and tetrahedral meshes. We provide comparisons to related work and show that our new algorithm results in superior time performance in practice, both in sequential and in parallel. An open-source C++ implementation is provided for reproducibility.
Polar codes for distributed source coding

A polar coding method to construct a distributed source coding scheme which can achieve any point on the dominant face of the Slepian-Wolf rate region for sources with uniform marginals is proposed. Source encoding and decoding operations are performed using efficient algorithms which makes practical implementation feasible. Simulation results are given to exhibit the performance of the presented method.