Miracle-dz/UniFAR-FTUs huggingface dataset:
Chop and tumble nucleotomy – A technique for safe nuclear emulsification in posterior polar cataract

A modified phaco chop technique for nuclear emulsification in posterior polar cataracts with nuclear sclerosis that avoids hydrodissection or nuclear rotation has been described. After performing a vertical chop maneuver to divide the nucleus, two pie-shaped nuclear fragments are removed from either side of the initial chop. The remaining nuclear fragments are then sequentially tumbled toward the center using the second instrument and emulsified while maintaining an intact epinuclear shell, which safeguards the fragile posterior capsule. The technique was successfully performed in 62 eyes of 54 patients with posterior polar cataract and grade II–IV nuclear sclerosis. The Chop and Tumble nucleotomy is a safe and effective technique for phacoemulsification in posterior polar cataracts with nuclear sclerosis, where hydrodissection and nuclear rotation are typically avoided.
Activation of regulatory dendritic cells by Mertk coincides with a temporal wave of apoptosis in neonatal lungs

Multiple mechanisms restrain inflammation in neonates, most likely to prevent tissue damage caused by overly robust immune responses against newly encountered pathogens. Here, we identify a population of pulmonary dendritic cells (DCs) that express intermediate levels of CD103 (CD103int) and appear in the lungs and lung-draining lymph nodes of mice between birth and 2 weeks of age. CD103int DCs express XCR1 and CD205 and require expression of the transcription factor BATF3 for development, suggesting that they belong to the cDC1 lineage. In addition, CD103int DCs express CCR7 constitutively and spontaneously migrate to the lung-draining lymph node, where they promote stromal cell maturation and lymph node expansion. CD103int DCs mature independently of microbial exposure and TRIF- or MyD88-dependent signaling and are transcriptionally related to efferocytic and tolerogenic DCs as well as mature, regulatory DCs. Correlating with this, CD103int DCs show limited ability to stimulate proliferation and IFN-γ production by CD8+ T cells. Moreover, CD103int DCs acquire apoptotic cells efficiently, in a process that is dependent on the expression of the TAM receptor, Mertk, which drives their homeostatic maturation. The appearance of CD103int DCs coincides with a temporal wave of apoptosis in developing lungs and explains, in part, dampened pulmonary immunity in neonatal mice. Together, these data suggest a mechanism by which DCs sense apoptotic cells at sites of noninflammatory tissue remodeling, such as tumors or the developing lungs, and limit local T cell responses. Description Mertk promotes maturation of regulatory dendritic cells in neonatal lungs. Editor’s summary Dendritic cells (DCs) can participate in processes underpinning immune tolerance. Silva-Sanchez et al. found that a discrete population of mature DCs accumulated transiently in the lungs and lung-draining lymph nodes of neonatal mice during a period of elevated apoptosis associated with the postnatal development of alveoli. These DCs, distinguished by intermediate expression levels of the integrin CD103, could restrain CD8 T cell responses, had a transcriptome that was similar to that of regulatory and tolerogenic DCs, and underwent a distinct maturation process that was dependent on the TAM receptor, Mertk, and the engulfment of apoptotic cells. This study indicates that tissue remodeling may stimulate the maturation of tolerogenic DCs to restrain immune responses and contribute to suppressed pulmonary immunity in neonates. —Sarah H. Ross
Multiple sequence analysis in the presence of alignment uncertainty

Sequence alignment is one of the most intensely studied problems in bioinformatics, and is an important step in a wide range of analyses. An issue that has gained much attention in recent years is the fact that downstream analyses are often highly sensitive to the specific choice of alignment. One way to address this is to jointly sample alignments along with other parameters of interest. In order to extend the range of applicability of this approach, the first chapter of this thesis introduces a probabilistic evolutionary model for protein structures on a phylogenetic tree; since protein structures typically diverge much more slowly than sequences, this allows for more reliable detection of remote homologies, improving the accuracy of the resulting alignments and trees, and reducing sensitivity of the results to the choice of dataset. In order to carry out inference under such a model, a number of new Markov chain Monte Carlo approaches are developed, allowing for more efficient convergence and mixing on the high-dimensional parameter space. The second part of the thesis presents a directed acyclic graph (DAG)-based approach for representing a collection of sampled alignments. This DAG representation allows the initial collection of samples to be used to generate a larger set of alignments under the same approximate distribution, enabling posterior alignment probabilities to be estimated reliably from a reasonable number of samples. If desired, summary alignments can then be generated as maximum-weight paths through the DAG, under various types of loss or scoring functions. The acyclic nature of the graph also permits various other types of algorithms to be easily adapted to operate on the entire set of alignments in the DAG. In the final part of this work, methodology is introduced for alignment-DAG-based sequence annotation using hidden Markov models, and RNA secondary structure prediction using stochastic context-free grammars. Results on test datasets indicate that the additional information contained within the DAG allows for improved predictions, resulting in substantial gains over simply analysing a set of alignments one by one.
Short-term vehicle trajectory prediction using attention mechanism integrated GRU network

Predicting the motion and behavior of surrounding vehicles is an essential task for motion planning and decision-making of autonomous vehicles in complex traffic conditions. In this paper, we propose a short-term vehicle trajectory prediction framework using attention mechanism integrated GRU network. We use an encoder-decoder model as the main architecture. A gate recurrent unit (GRU) coupled with temporal attention and graph attention is used to extract and fuse more important information which could be used for trajectory prediction. The temporal attention could extract temporal information and graph attention could consider interactions between surrounding vehicles within sensing range. The extracted information is fed into fully connected layers to obtain predicted trajectory. The publicly next generation simulation (NGSIM) I-80 and US-101 datasets are used to evaluate proposed model. Compared to other prediction models, our model shows improvement on final displacement error (FDE) and average displacement error (ADE). The results show that model with attention mechanism improves prediction accuracy by 1% ~5% in 5 second prediction horizon.
Exacerbated climate risks induced by precipitation extremes in the Yangtze River basin under warming scenarios

The Yangtze River basin is a typical region of the world that has a well-developed economy but is also greatly affected by multiple climate extremes. An improved understanding of future climate trends and associated exposures in this region is urgent needed to address socioeconomic risks. This research aims to quantify historical and future projected population exposure to precipitation extremes in the Yangtze basin using meteorological records and downscaled climate models. The study found that the hazard zone for precipitation extremes during baseline period was primarily located in the mid-lower Yangtze basin, particularly around the Poyang Lake watershed. Climate projections for 2050 indicate a further increase in the occurrence of precipitation extremes in this hazard zone, while a decrease in extreme events is detectable in the upper Yangtze basin under higher radiative forcing. Future socioeconomic scenarios suggest a tendency for population growth and migration towards the lower Yangtze basin, resulting in aggravated climate risks in megacities. Multi-model simulations indicate that population exposure to precipitation extremes in the lower Yangtze basin will increase by 9–22% around 2050, with both climate and population factors contributing positively. Shanghai, Changsha, Hangzhou, Ganzhou, and Huanggang are identified as hotspot cities facing the highest foreseeable risks of precipitation extremes in the Yangtze basin. GRAPHICAL ABSTRACT
Visual localization and mapping based on road constraints

Conventional SLAM only requires the construction of sparse maps for localization, while in order to meet the safe driving needs of unmanned vehicles, they need to understand the edges of the road, i.e., with a semantic level of understanding. In addition, unmanned vehicles are more sensitive to lateral errors than longitudinal errors, which requires SLAM algorithms with higher accuracy for lateral errors. We investigate the ORB-SLAM3 algorithm by introducing satellite maps as a priori knowledge, using the corners in satellite maps to initialize the odometer, remove the accumulated errors, and correct the previous positions; using the results of particle filtering and lane line identification to further optimize the localization results of ORB-SLAM3 and to draw maps with lane semantic information. Our experiments show that our algorithm significantly reduces the cumulative error without loopback, improves the localization accuracy, and yields lane line maps with large engineering applications.
Application of LSTM intelligent algorithm in shale gas development

Shale gas is regard as a clean, low-carbon and green energy, and the utilization and efficient development of shale gas is of great significance for achieving the dual carbon goals. Horizontal well hydraulic fracturing is an important way to develop shale gas resources. Predicting the production of shale gas under different engineering or geological conditions of shale reservoirs is crucial to the optimal fracturing design of shale gas development. This study proposes a LSTMbased intelligent model to predict the gas production of shale, and this novel smart model predicts gas production quickly and accurately. We comprehensively evaluate and compare the performance of the AI network, and the results of test show that the LSTM-based AI model can output gas production data by inputting reservoir and engineering parameters. The mean value of relative error of the LSTM-based AI model is 5.32%, which is reliably for the prediction of gas production. The peak of relative errors of this AI model in this study on day 100, 300, and 500 are 4.67%, 6.53%, and 8.23%, respectively. This study can provide an effective and quick method for shale gas prediction and improve the intelligence level of energy development.
Interaction strength prediction based on neural networks of graph scrolls considering geographical features

Accurate interaction strength prediction plays an important role in urban planning and development. Based on the existing national interaction intensity data between cities, the research uses GCN model, ChebNet model and GAT model based on graph convolutional neural network to realize the prediction of urban interaction intensity, and determines the optimal model through accuracy evaluation. Further we introduce geographical features, optimize the optimal GAT model, and finally the graph neural network model considering geographical characteristics is constructed to realize real-time, efficient, and long-term prediction of urban interaction intensity. It is found that there is a strong interaction betweend cities.
Analysis of urban contraction based on grey correlation and entropy weight models

Liaoning Province, as a national traditional heavy industry area, contains 30 cities facing varying degrees of urban contraction. We classify these 30 cities by K-means clustering analysis. Then, the grey correlation model is established. By solving the grey correlation coefficient between the economic and social indicators and the total population of shrinking cities, the factors affecting the shrinking urban population are obtained. Finally, we establish a comprehensive evaluation system of shrinking cities with population, indicators and GDP as evaluation indicators. The entropy weight method model is established to determine the weight of each evaluation index in order to obtain the contraction comprehensive index of each city. The change rate of the comprehensive index of each city is calculated respectively, and then the development and evolution trend of each shrinking city is analyzed.
2-arc transitive polygonal graphs of large girth and valency

A near-polygonal graph is a graph Γ which has a set C of m-cycles for some positive integer m such that each 2-path of Γ is contained in exactly one cycle in C. If m is the girth of Γ then the graph is called polygonal. Up until now, the only examples of 2-arc transitive polygonal graphs with arbitrarily large valency had girth no larger than seven, and the 2-arc transitive polygonal graph with largest girth had valency five and girth twenty-three (in fact, even with no restrictions on the automorphism group, there were no examples of polygonal graphs with odd girth greater than twenty-three). This thesis provides a construction of an infinite family of polygonal graphs of arbitrary girth m with 2-arc transitive automorphism groups, showing that there are 2-arc transitive polygonal graphs of arbitrarily large valency for each girth m. Furthermore, this thesis also provides a construction that, given a polygonal graph of valency r and girth m, produces a polygonal graph of valency r and girth 3m, and that the graphs constructed via this method will be 2-arc transitive if the original graph was 2-arc transitive. Finally, this thesis provides a construction of a new infinite family of near-polygonal graphs of valency 10 and a method for determining which graphs can have a given girth, which yields a few new examples of polygonal graphs.
Relations between PTSD symptom clusters and pain in three trauma-exposed samples with pain

Abstract Objectives Little is known about how the individual PTSD symptom clusters relate to intensity and interference of pain and whether these relationships differ across clinical groups. The present study examines relations between PTSD symptom clusters and pain in three trauma-exposed, unique clinical groups: 1) adults seeking treatment for chronic pain with current symptoms of PTSD, 2) trauma affected refugees seeking treatment for PTSD and chronic pain; and 3) individuals identified at admission to the emergency ward after whiplash injury. Methods Network analysis was used to assess unique relations between pain intensity, pain interference, re-experiencing, avoidance, numbing, hyperarousal, depression, and anxiety separately in each sample. Links between PTSD clusters and pain were then compared within and between samples. Results No within-group differences were identified for the links between pain and any of PTSD clusters in the chronic pain and refugee groups. In the whiplash group, hyperarousal was more strongly related to pain than re-experiencing, avoidance, and numbing. Between group comparisons revealed a more pronounced relationship between hyperarousal and pain in the whiplash group, with no between-group differences between the chronic pain and refugee groups. Conclusions The findings suggest that when depression and anxiety are accounted for, few unique associations are found between pain and the PTSD symptom clusters in trauma-exposed samples with pain, with the exception of a link between pain and hyperarousal in individuals with whiplash-related PTSD symptoms.
An experimental study for chemical characterization of artificial anterior cruciate ligament with coated chitosan as biomaterial

Abstract The importance and aim of this experimental study is that raw artificial anterior cruciate ligament samples were produced with various 3-D braiding constructions with various technical yarns using the 3-D braiding method. Later, it is aimed to determine the chemical bond changes between raw samples with ethylene oxide (EtO) sterilization and bio-chemical finishing samples by applying padding process and EtO sterilization processes for all samples with 3-D braiding structures, due to the cross-linking of biocompatible chitosan (CHI) with biological cross-linker glutaraldehyde (GA). The importance of this experimental study is that it is the first experimental chemical analysis in this field in the world scientific study. Padding and EtO sterilization processes were applied on all samples and compared to various technical yarns with 3-D braiding structures thanks to biocompatible CHI. Chemical analysis was interpreted for all samples. It was determined that the applied temperature, concentration, pH, yarn types, characteristic bonds in the chemical structure of the technical yarns, applied bio-chemical finishing process and EtO sterilization had effect on the formation, shifting and breaking of chemical bonds. It was determined that the yarn number, braiding geometry, braiding angle (°) and braid construction had no effect on the formation or shifting of chemical bonds. New bonds were formed thanks to CHI and GA due to their extremely reactive between 5 and 5.5 pH. They reacted quickly with Schiff base bond in all samples. CHI was ionized in all samples. It was determined that new bonds were formed in UHMWPE, PPD-T and HT PET structures. The most common bond formations were HT PET > PPD-T > UHMWPE. The reasons for these chemical structure changes in all samples depended on their chemical structures, bond types, molecular weights, reactivities, ease and speed of diffusions, crystallinities of technical yarns and all chemicals used. In order to increase the formation of new chemical bonds the pH should be between 5 and 5.5. GA concentration should be a minimum of 25% or higher. The dissolution time of CHI should be minimum 3 h or more. The dissolution process temperature of CHI should be minimum of 70°C or higher. The absorption, adsorption and chelation properties of CHI on all samples will also be evident successfully as in this experimental chemical study.
Protein sequence features of H1N1 swine influenza A viruses detected on commercial swine farms in Serbia

Abstract Introduction Swine influenza A viruses (swIAVs) are characterised by high mutation rates and zoonotic and pandemic potential. In order to draw conclusions about virulence in swine and pathogenicity to humans, we examined the existence of molecular markers and accessory proteins, cross-reactivity with vaccine strains, and resistance to antiviral drugs in five strains of H1N1 swIAVs. Material and Methods Amino acid (AA) sequences of five previously genetically characterised swIAVs were analysed in MEGA 7.0 software and the Influenza Research Database. Results Amino acid analysis revealed three virus strains with 590S/591R polymorphism and T271A substitution within basic polymerase 2 (PB2) AA chains, which cause enhanced virus replication in mammalian cells. The other two strains possessed D701N and R251K substitutions within PB2 and synthesised PB1-F2 protein, which are the factors of increased polymerase activity and virulence in swine. All strains synthesised PB1-N40, PA-N155, PA-N182, and PA-X proteins responsible for enhanced replication in mammalian cells and downregulation of the immune response of the host. Mutations detected within haemagglutinin antigenic sites imply the antigenic drift of the five analysed viruses in relation to the vaccine strains. All viruses show susceptibility to neuraminidase inhibitors and baloxavir marboxil, which is important in situations of incidental human infections. Conclusion The detection of virulence markers and accessory proteins in the analysed viruses suggests their higher propensity for replication in mammalian cells, increased virulence, and potential for transmission to humans, and implies compromised efficacy of influenza vaccines.
Parenting the Successor: It Starts at Home and Leaves an Enduring Impact on the Family Business

Transferring leadership across generations is a defining characteristic of family businesses. Yet many successors underperform, and little is known about why. We extend parental control theory to develop a model of parenting effects in family businesses. Primary dyadic data from successors and subordinates in 119 family businesses, supplemented with 24 interviews with family business leaders, shows that predecessors’ parenting style affects successors’ psychological functioning, which impacts employees’ citizenship and counterproductive behaviors. Among firms that make it to the second generation, the seeds of success are partially sown long before succession takes place, drawing attention to the important role of parenting.
Towards Precise, Ubiquitous and Real-Time Positioning

Positioning is an enabler for many location-based services in the vertical industrial domain such as autonomous driving and robot-to-cobot interaction, to name a few. Industry and academia are actively enabling localization through 5G and WiFi as they are universally deployed. However, the current WiFi and 5G protocols cannot deal with the hard requirements of accuracy, latency, and robustness. To deal with that, we have proposed a series of works to enable precise, pervasive, and real-time positioning.
EMISSARY: Enhanced Miss Awareness Replacement Policy for L2 Instruction Caching

For decades, architects have designed cache replacement policies to reduce cache misses. Since not all cache misses affect processor performance equally, researchers have also proposed cache replacement policies focused on reducing the total miss cost rather than the total miss count. However, all prior cost-aware replacement policies have been proposed specifically for data caching and are either inappropriate or unnecessarily complex for instruction caching. This paper presents EMISSARY, the first cost-aware cache replacement family of policies specifically designed for instruction caching. Observing that modern architectures entirely tolerate many instruction cache misses, EMISSARY resists evicting those cache lines whose misses cause costly decode starvations. In the context of a modern processor with fetch-directed instruction prefetching and other aggressive front-end features, EMISSARY applied to L2 cache instructions delivers an impressive 3.24% geomean speedup (up to 23.7%) and a geomean energy savings of 2.1% (up to 17.7%) when evaluated on widely used server applications with large code footprints. This speedup is 21.6% of the total speedup obtained by an unrealizable L2 cache with a zero-cycle miss latency for all capacity and conflict instruction misses.