Miracle-dz/UniFAR-FTUs huggingface dataset:
Natural Deadlock Resolution for Multi-agent Multi-Swarm Navigation

This paper presents a nonlinear and discontinuous control scheme for two-dimensional (2-D) multi-agent multi-swarm navigation that resolves deadlocks, without heuristics, by agents reacting purely to their constrained dynamics. The method is based on extensions of Gauss's Principle of Least Constraint that dynamically identify, incorporate, and stabilize time-varying sets of constraints and that integrate actuator saturation and delay. The deadlocks are naturally resolved by formulating the 2-D leader following and collision avoidance requirements as decomposed inequality constraints along the X and Y axes and by asymmetrically assigning zero collision avoidance constraint value to a specific branch. Numerical results are presented for two agents and two 15-agent swarms resolving nominal deadlocks at a computation time order of 10 microseconds, demonstrating the efficacy and efficiency of the proposed approach.
SUTRA: An Approach to Modelling Pandemics with Undetected (Asymptomatic) Patients, and Applications to COVID-19

The COVID-19 pandemic that has swept the world has shown a wide variety of behavior across countries, ranging from a gentle rise and gentle fall in India, to multiple waves with each peak higher than its predecessor in the USA, UK, and other countries. It is therefore a challenge to present a unified model that can manifest this wide range of behavior. In this paper, we present a new mathematical model called SUTRA for pandemics that have undetected (asymptomatic) patients, and demonstrate that it does indeed accurately predict the variety of behavior observed during the COVID-19 pandemic. The acronym SUTRA stands for Susceptible, Undetected, Tested (positive), and Removed Approach. There are several novel features of our proposed model. First, whereas previous papers have divided the patient population into Asymptomatic and Infected, we divide patients instead into Tested (T) and Undetected (U). This explicitly accounts for the fact that, due to contact tracing and other such protocols, some fraction of asymptomatic patients do get detected. Second, we introduce a parameter called "reach," to take into account the spatial spread of apandemic over time. Third, we present numerically stable methods for estimating the parameters in our model.We have applied our model to predict the progression of the COVID-19 pandemic in several countries, displaying a variety of behaviors. In all cases, the predictions closely match the actually observed outcomes. In the interests of brevity, we present only the predictions for India.
Extracellular Vesicles in Transplantation

Extracellular vesicles (EVs) have been extensively studied in the last two decades. It is now well documented that they can actively participate in the activation or regulation of immune system functions through different mechanisms, the most studied of which include protein–protein interactions and miRNA transfers. The functional diversity of EV-secreting cells makes EVs potential targets for immunotherapies through immune cell-derived EV functions. They are also a potential source of biomarkers of graft rejection through donor cells or graft environment-derived EV content modification. This review focuses on preclinical studies that describe the role of EVs from different cell types in immune suppression and graft tolerance and on the search for biomarkers of rejection.
Hi-C Metagenomics in the ICU: Exploring Clinically Relevant Features of Gut Microbiome in Chronically Critically Ill Patients

Gut microbiome in critically ill patients shows profound dysbiosis. The most vulnerable is the subgroup of chronically critically ill (CCI) patients – those suffering from long-term dependence on support systems in intensive care units. It is important to investigate their microbiome as a potential reservoir of opportunistic taxa causing co-infections and a morbidity factor. We explored dynamics of microbiome composition in the CCI patients by combining “shotgun” metagenomics with chromosome conformation capture (Hi-C). Stool samples were collected at 2 time points from 2 patients with severe brain injury with different outcomes within a 1–2-week interval. The metagenome-assembled genomes (MAGs) were reconstructed based on the Hi-C data using a novel hicSPAdes method (along with the bin3c method for comparison), as well as independently of the Hi-C using MetaBAT2. The resistomes of the samples were derived using a novel assembly graph-based approach. Links of bacteria to antibiotic resistance genes, plasmids and viruses were analyzed using Hi-C-based networks. The gut community structure was enriched in opportunistic microorganisms. The binning using hicSPAdes was superior to the conventional WGS-based binning as well as to the bin3c in terms of the number, completeness and contamination of the reconstructed MAGs. Using Klebsiella pneumoniae as an example, we showed how chromosome conformation capture can aid comparative genomic analysis of clinically important pathogens. Diverse associations of resistome with antimicrobial therapy from the level of assembly graphs to gene content were discovered. Analysis of Hi-C networks suggested multiple “host-plasmid” and “host-phage” links. Hi-C metagenomics is a promising technique for investigating clinical microbiome samples. It provides a community composition profile with increased details on bacterial gene content and mobile genetic elements compared to conventional metagenomics. The ability of Hi-C binning to encompass the MAG’s plasmid content facilitates metagenomic evaluation of virulence and drug resistance dynamics in clinically relevant opportunistic pathogens. These findings will help to identify the targets for developing cost-effective and rapid tests for assessing microbiome-related health risks.
Visual Haptic Feedback for Training of Robotic Suturing

Current surgical robotic systems are teleoperated and do not have force feedback. Considerable practice is required to learn how to use visual input such as tissue deformation upon contact as a substitute for tactile sense. Thus, unnecessarily high forces are observed in novices, prior to specific robotic training, and visual force feedback studies demonstrated reduction of applied forces. Simulation exercises with realistic suturing tasks can provide training outside the operating room. This paper presents contributions to realistic interactive suture simulation for training of suturing and knot-tying tasks commonly used in robotically-assisted surgery. To improve the realism of the simulation, we developed a global coordinate wire model with a new constraint development for the elongation. We demonstrated that a continuous modeling of the contacts avoids instabilities during knot tightening. Visual cues are additionally provided, based on the computation of mechanical forces or constraints, to support learning how to dose the forces. The results are integrated into a powerful system-agnostic simulator, and the comparison with equivalent tasks performed with the da Vinci Xi system confirms its realism.
Differentiation of Cold Tolerance in an Artificial Population of a Mangrove Species, Kandelia obovata, Is Associated With Geographic Origins

Temperature is one of the climatic factors that shape the geographic distribution of plant populations. Mangroves are temperature-sensitive plants, and their distributions are severely limited by low temperatures. It is unknown, however, to what extent temperature contributes to their population differentiation and evolution. Kandelia obovata (Rhizophoraceae) is a mangrove species with high cold tolerance in the Northern Hemisphere. We investigated the phenotypic responses of an artificial population of K. obovata, with plants transplanted from different source populations, to extremely low temperatures during winter of 2015–2016 in Yueqing County (28°20′N), Zhejiang Province of China. Using two binary traits, “with/without leaves alive on the branches” and “with/without alive buds on the tips of branches,” we classified plants in this artificial population into strong, moderate and poor cold resistance groups. We further assessed the genetic diversity, structure and differentiation of these three groups, as well as five natural populations along a latitudinal gradient using ten nuclear and six plastid microsatellite markers. Microsatellite data revealed genetic differentiation among the natural populations along the latitudinal gradient. Molecular data indicated that the cold tolerance of three groups in the artificial population was associated with their geographic origins, and that the most cold-tolerant group came from the northernmost natural population. Our study thus indicates that natural populations of K. obovata may have evolved divergent capacity of cold tolerance.
Abundance of Major Cell Wall Components in Natural Variants and Pedigrees of Populus trichocarpa

The rapid analysis of biopolymers including lignin and sugars in lignocellulosic biomass cell walls is essential for the analysis of the large sample populations needed for identifying heritable genetic variation in biomass feedstocks for biofuels and bioproducts. In this study, we reported the analysis of cell wall lignin content, syringyl/guaiacyl (S/G) ratio, as well as glucose and xylose content by high-throughput pyrolysis-molecular beam mass spectrometry (py-MBMS) for >3,600 samples derived from hundreds of accessions of Populus trichocarpa from natural populations, as well as pedigrees constructed from 14 parents (7 × 7). Partial Least Squares (PLS) regression models were built from the samples of known sugar composition previously determined by hydrolysis followed by nuclear magnetic resonance (NMR) analysis. Key spectral features positively correlated with glucose content consisted of m/z 126, 98, and 69, among others, deriving from pyrolyzates such as hydroxymethylfurfural, maltol, and other sugar-derived species. Xylose content positively correlated primarily with many lignin-derived ions and to a lesser degree with m/z 114, deriving from a lactone produced from xylose pyrolysis. Models were capable of predicting glucose and xylose contents with an average error of less than 4%, and accuracy was significantly improved over previously used methods. The differences in the models constructed from the two sample sets varied in training sample number, but the genetic and compositional uniformity of the pedigree set could be a potential driver in the slightly better performance of that model in comparison with the natural variants. Broad-sense heritability of glucose and xylose composition using these data was 0.32 and 0.34, respectively. In summary, we have demonstrated the use of a single high-throughput method to predict sugar and lignin composition in thousands of poplar samples to estimate the heritability and phenotypic plasticity of traits necessary to develop optimized feedstocks for bioenergy applications.
Variation in Coarse Particulate Matter (PM10) and Its Characterization at Multiple Locations in the Semiarid Region

Introduction: The elemental composition and morphological study of particulate matter are very important to understand the nature of particles influencing the environment, climate, soil, and health. Methods: The PM10 samples were collected during the winter season (2018) in Nowshera city, KPK, Pakistan, in three locations, namely, urban, industrial, and suburban. Scanning electron microscopy (SEM) and electron-dispersive X-ray (EDX) spectroscopy were used to examine the PM samples for morphological examination and elemental composition. Results: The average mass concentrations of particulate matter (PM10) at the urban, industrial, and suburban locations were 238.5, 505.1, and 255.0 μg m−3, respectively. The average PM10 mass concentration was higher than the WHO and National Ambient Air Quality Standards (NAAQS). The results of EDX showed that samples contained variable amounts of thirteen elements, such as oxygen, carbon, silicon, magnesium, sodium, calcium, iron, aluminum, potassium, sulfur, titanium, gold, and chlorine. The probable sources of PM were biogenic like plant debris, pollen, and diatoms; geogenic like road dust and resuspended soil dust; and anthropogenic like carbonaceous particles and fly ash, as confirmed by SEM–EDX. The carbonaceous species, that is, OC and EC, had average values of 55.8 ± 13.1 and 4.6 ± 0.6, 5.2 ± 3.2, and 36.4 ± 10.4, 40.0 ± 2.6 and, 6.3 ± 0.2 in industrial, urban, and suburban locations, respectively. Similarly, OC/EC had average values of 12.0 ± 1.2, 8.0 ± 3.0, and 6.3 ± 0.2 in industrial, urban, and suburban locations, respectively. Highly significant correlations among water-soluble ions (K+), OC, and EC were found in each location. Conclusions: The examined PM10 mass concentration in Nowshera city was above the thresholds of National Ambient Air Quality Standards (NAAQS) set by the U.S. Environmental Protection Agency (EPA). In addition, the concentration of pollutants was the highest at the industrial site compared to the other sites. The HYSPLIT model showed that the air mass originated from local sources like cement industries, brick kiln industries, and others.
Genome-Wide SNP Analysis of Hybrid Clariid Fish Reflects the Existence of Polygenic Sex-Determination in the Lineage

The African catfish (Clarias gariepinus) may exhibit the co-existence of XX/XY and ZZ/ZW sex-determination systems (SDSs). However, the SDS of African catfish might be influenced by a polygenic sex-determination (PSD) system, comprising multiple independently segregating sex “switch” loci to determine sex within a species. Here, we aimed to detect the existence of PSD using hybrid. The hybrid produced by crossing male African catfish with female bighead catfish (C. macrocephalus, XX/XY) is a good animal model to study SDSs. Determining the SDS of hybrid catfish can help in understanding the interactions between these two complex SDS systems. Using the genotyping-by-sequencing “DART-seq” approach, we detected seven moderately male-linked loci and seventeen female-linked loci across all the examined hybrid specimens. Most of these loci were not sex-linked in the parental species, suggesting that the hybrid exhibits a combination of different alleles. Annotation of the identified sex-linked loci revealed the presence of one female-linked locus homologous with the B4GALNT1 gene, which is involved in the spermatogenesis pathway and hatchability. However, this locus was not sex-linked in the parental species, and the African catfish might also exhibit PSD.
New Insight Into the Interspecies Shift of Anammox Bacteria Ca. “Brocadia” and Ca. “Jettenia” in Reactors Fed With Formate and Folate

The sensitivity of anaerobic ammonium-oxidizing (anammox) bacteria to environmental fluctuations is a frequent cause of reactor malfunctions. It was hypothesized that the addition of formate and folate would have a stimulating effect on anammox bacteria, which in turn would lead to the stability of the anammox process under conditions of a sharp increase in ammonium load, i.e., it helps overcome a stress factor. The effect of formate and folate was investigated using a setup consisting of three parallel sequencing batch reactors equipped with a carrier. Two runs of the reactors were performed. The composition of the microbial community was studied by the 16S rRNA gene profiling and metagenomic analysis. Among anammox bacteria, Ca. “Brocadia” spp. dominated during the first run. A stimulatory effect of folate on the daily nitrogen removal rate (dN) was identified. The addition of formate led to progress in dissimilatory nitrate reduction and stimulated the growth of Ca. “Jettenia” spp. The spatial separation of two anammox species was observed in the formate reactor: Ca. “Brocadia” occupied the carrier and Ca. “Jettenia”—the walls of the reactors. Biomass storage at low temperature without feeding led to an interspecies shift in anammox bacteria in favor of Ca. “Jettenia. ” During the second run, a domination of Ca. “Jettenia” spp. was recorded along with a stimulating effect of formate, and there was no effect of folate on dN. A comparative genome analysis revealed the patterns suggesting different strategies used by Ca. “Brocadia” and Ca. “Jettenia” spp. to cope with environmental changes.
Muscle Adaptations to Heavy-Load and Blood Flow Restriction Resistance Training Methods

Resistance-based blood flow restriction training (BFRT) improves skeletal muscle strength and size. Unlike heavy-load resistance training (HLRT), there is debate as to whether strength adaptations following BFRT interventions can be primarily attributed to concurrent muscle hypertrophy, as the magnitude of hypertrophy is often minor. The present study aimed to investigate the effect of 7 weeks of BFRT and HLRT on muscle strength and hypertrophy. The expression of protein growth markers from muscle biopsy samples was also measured. Male participants were allocated to moderately heavy-load training (HL; n = 9), low-load BFRT (LL + BFR; n = 8), or a control (CON; n = 9) group to control for the effect of time. HL and LL + BFR completed 21 training sessions (3 d.week−1) comprising bilateral knee extension and knee flexion exercises (HL = 70% one-repetition maximum (1-RM), LL + BFR = 20% 1-RM + blood flow restriction). Bilateral knee extension and flexion 1-RM strength were assessed, and leg muscle CSA was measured via peripheral quantitative computed tomography. Protein growth markers were measured in vastus lateralis biopsy samples taken pre- and post the first and last training sessions. Biopsy samples were also taken from CON at the same time intervals as HL and LL + BFR. Knee extension 1-RM strength increased in HL (19%) and LL + BFR (19%) but not CON (2%; p < 0.05). Knee flexion 1-RM strength increased similarly between all groups, as did muscle CSA (50% femur length; HL = 2.2%, LL + BFR = 3.0%, CON = 2.1%; TIME main effects). 4E-BP1 (Thr37/46) phosphorylation was lower in HL and LL + BFR immediately post-exercise compared with CON in both sessions (p < 0.05). Expression of other growth markers was similar between groups (p > 0.05). Overall, BFRT and HLRT improved muscle strength and size similarly, with comparable changes in intramuscular protein growth marker expression, both acutely and chronically, suggesting the activation of similar anabolic pathways. However, the low magnitude of muscle hypertrophy was not significantly different to the non-training control suggesting that strength adaptation following 7 weeks of BFRT is not driven by hypertrophy, but rather neurological adaptation.
Identifying Potential Biomarkers of Prognostic Value in Colorectal Cancer via Tumor Microenvironment Data Mining

Colorectal cancer (CRC) is a common cancer that has increased rapidly worldwide in the past decades with a relatively high mortality rate. An increasing body of evidence has highlighted the importance of infiltrating immune and stromal cells in CRC. In this study, based on gene expression data of CRC patients in TCGA database we evaluated immune and stromal scores in tumor microenvironment using ESTIMATE method. Results showed there was potential correlation between these scores and the prognosis, and that patients with higher immune score and lower stromal score had longer survival time. We found that immune score was correlated with clinical characteristics including tumor location, tumor stage, and survival time. Specifically, the right-sided colon cancer had markedly elevated immune score, compared to left-sided colon cancer and rectal cancer. These results might be useful for understanding tumor microenvironment in colorectal cancer. Through the differential analysis we got a list of genes significantly associated with immune and stromal scores. Gene Set Enrichment and protein-protein interaction network analysis were used to further illustrate these differentially expressed genes. Finally, 15 hub genes were identified, and three (CXCL9, CXCL10 and SELL) of them were validated with favorable outcomes in CRC patients. Our result suggested that these tumor microenvironment related genes might be potential biomarkers for the prognosis of CRC.
Human Factors Considerations and Metrics in Shared Space Human-Robot Collaboration: A Systematic Review

The degree of successful human-robot collaboration is dependent on the joint consideration of robot factors (RF) and human factors (HF). Depending on the state of the operator, a change in a robot factor, such as the behavior or level of autonomy, can be perceived differently and affect how the operator chooses to interact with and utilize the robot. This interaction can affect system performance and safety in dynamic ways. The theory of human factors in human-automation interaction has long been studied; however, the formal investigation of these HFs in shared space human-robot collaboration (HRC) and the potential interactive effects between covariate HFs (HF-HF) and HF-RF in shared space collaborative robotics requires additional investigation. Furthermore, methodological applications to measure or manipulate these factors can provide insights into contextual effects and potential for improved measurement techniques. As such, a systematic literature review was performed to evaluate the most frequently addressed operator HF states in shared space HRC, the methods used to quantify these states, and the implications of the states on HRC. The three most frequently measured states are: trust, cognitive workload, and anxiety, with subjective questionnaires universally the most common method to quantify operator states, excluding fatigue where electromyography is more common. Furthermore, the majority of included studies evaluate the effect of manipulating RFs on HFs, but few explain the effect of the HFs on system attributes or performance. For those that provided this information, HFs have been shown to impact system efficiency and response time, collaborative performance and quality of work, and operator utilization strategy.
Performance of a Finned Turbine Rim Seal

In gas turbines, rim seals are fitted at the periphery of the wheel-space between the turbine disc and its adjacent casing; their purpose is to reduce the ingress of hot mainstream gases. A superposed sealant flow, bled from the compressor, is used to purge the wheel-space or at least dilute the ingress to an acceptable level. The ingress is caused by the circumferential variation of pressure in the turbine annulus radially outward of the seal. Engine designers often use double rim seals where the variation in pressure is attenuated in the outer wheel-space between the two seals.This paper describes experimental results from a research facility which models an axial turbine stage with engine-representative rim seals. The radial variation of CO2 gas concentration, swirl and pressure, in both the inner and outer wheel-space, are presented over a range of purge flow rates. The data are used to assess the performance of two seals: a datum double-rim seal and a derivative with a series of radial fins.The concept behind the finned seal is that the radial fins increase the swirl in the outer wheel-space; measurements of swirl show the captive fluid between the fins rotate with near solid body rotation. The improved attenuation of the pressure asymmetry, which governs the ingress, results in an improved performance of the inner geometry of the seal. The fins also increased the pressure in the outer wheel-space and reduced the ingress though the outer geometry of the seal.Copyright © 2014 by Siemens Energy, Inc.