Miracle-dz/UniFAR-FTUs huggingface dataset:
Curved Buildings Reconstruction From Airborne LiDAR Data by Matching and Deforming Geometric Primitives

Airborne light detection and ranging (LiDAR) data are widely applied in building reconstruction, with studies reporting success in typical buildings. However, the reconstruction of curved buildings remains an open research problem. To this end, we propose a new framework for curved building reconstruction via assembling and deforming geometric primitives. The input LiDAR point clouds are first converted into contours where individual buildings are identified. After recognizing geometric units (primitives) from building contours, we get initial models by matching the basic geometric primitives to these primitives. To polish assembly models, we employ a warping field for model refinements. Specifically, an embedded deformation (ED) graph is constructed via downsampling the initial model. Then, the point to model displacements is minimized by adjusting node parameters in the ED graph based on our objective function. The presented framework is validated on several highly curved buildings collected by various LiDAR in different cities. The experimental results, as well as accuracy comparison, demonstrate the advantage and effectiveness of our method. The new insight attributes to an efficient reconstruction manner. Moreover, we prove that the primitive-based framework significantly reduces the data storage to 10%–20% of classical mesh models.
Unsupervised Word Polysemy Quantification with Multiresolution Grids of Contextual Embeddings

The number of senses of a given word, or polysemy, is a very subjective notion, which varies widely across annotators and resources. We propose a novel method to estimate polysemy based on simple geometry in the contextual embedding space. Our approach is fully unsupervised and purely data-driven. Through rigorous experiments, we show that our rankings are well correlated, with strong statistical significance, with 6 different rankings derived from famous human-constructed resources such as WordNet, OntoNotes, Oxford, Wikipedia, etc., for 6 different standard metrics. We also visualize and analyze the correlation between the human rankings and make interesting observations. A valuable by-product of our method is the ability to sample, at no extra cost, sentences containing different senses of a given word. Finally, the fully unsupervised nature of our approach makes it applicable to any language. Code and data are publicly available https://github.com/ksipos/polysemy-assessment .
Variation across Scales: Measurement Fidelity under Twitter Data Sampling

A comprehensive understanding of data quality is the cornerstone of measurement studies in social media research. This paper presents in-depth measurements on the effects of Twitter data sampling across different timescales and different subjects (entities, networks, and cascades). By constructing complete tweet streams, we show that Twitter rate limit message is an accurate indicator for the volume of missing tweets. Sampling also differs significantly across timescales. While the hourly sampling rate is influenced by the diurnal rhythm in different time zones, the millisecond level sampling is heavily affected by the implementation choices. For Twitter entities such as users, we find the Bernoulli process with a uniform rate approximates the empirical distributions well. It also allows us to estimate the true ranking with the observed sample data. For networks on Twitter, their structures are altered significantly and some components are more likely to be preserved. For retweet cascades, we observe changes in distributions of tweet inter-arrival time and user influence, which will affect models that rely on these features. This work calls attention to noises and potential biases in social data, and provides a few tools to measure Twitter sampling effects.
HierTrain: Fast Hierarchical Edge AI Learning With Hybrid Parallelism in Mobile-Edge-Cloud Computing

Nowadays, deep neural networks (DNNs) are the core enablers for many emerging edge AI applications. Conventional approaches for training DNNs are generally implemented at central servers or cloud centers for centralized learning, which is typically time-consuming and resource-demanding due to the transmission of a large number of data samples from the edge device to the remote cloud. To overcome these disadvantages, we consider accelerating the learning process of DNNs on the Mobile-Edge-Cloud Computing (MECC) paradigm. In this paper, we propose HierTrain, a hierarchical edge AI learning framework, which efficiently deploys the DNN training task over the hierarchical MECC architecture. We develop a novel hybrid parallelism method, which is the key to HierTrain, to adaptively assign the DNN model layers and the data samples across the three levels of the edge device, edge server and cloud center. We then formulate the problem of scheduling the DNN training tasks at both layer-granularity and sample-granularity. Solving this optimization problem enables us to achieve the minimum training time. We further implement a hardware prototype consisting of an edge device, an edge server and a cloud server, and conduct extensive experiments on it. Experimental results demonstrate that HierTrain can achieve up to $6.9\times $ speedups compared to the cloud-based hierarchical training approach.
Experimental and theoretical study of tracer diffusion in a series of (CoCrFeMn)$_{100-x}$Ni$_x$ alloys.

Tracer diffusion of all constituting elements is studied at various temperatures in a series of (CoCrFeMn)$_{100-x}$Ni$_x$ alloys with compositions ranging from pure Ni to the equiatomic CoCrFeMnNi high-entropy alloy. At a given homologous temperature, the measured tracer diffusion coefficients change non-monotonically along the transition from pure Ni to the concentrated alloys and finally to the equiatomic CoCrFeMnNi alloy. This is explained by atomistic Monte-Carlo simulations based on a modified embedded-atom potentials, which reveal that local heterogeneities of the atomic configurations around a vacancy cause correlation effects and induce significant deviations from predictions of the random alloy model.
Assessing the stigma content of urinary incontinence intervention outcome measures

The goal of this narrative review is to evaluate the efficacy of available questionnaires for assessing the outcomes of “continence difficulty” interventions and to assess the selected questionnaires concerning aspects of stigmatization. The literature was searched for research related to urinary incontinence, as well as questionnaires and rating scale outcome measurement tools. The following sources were searched: Cochrane Library, EMBASE, Medline, and PubMed. The following keywords were used separately or in combination: “Urinary incontinence,” “therapy,” ”treatment outcome,” “patient satisfaction,” “quality of life,” “systematic reviews,” “aged 65+ years,” and “questionnaire. ” The search yielded 194 references, of which 11 questionnaires fit the inclusion criteria; 6 of the 11 questionnaires did not have any stigma content and the content regarding stigma that was identified in the other five was very limited. A representative model of how stigma impacts continence difficulty interventions was proposed. While the 11 incontinence specific measurement tools that were assessed were well researched and designed specifically to measure the outcomes of incontinence interventions, they have not been used consistently or extensively and none of the measures thoroughly assess stigma. Further studies are required to examine how the stigma associated with continence difficulty impacts upon health care interventions.
The Effects of Host Plant Species and Plant Quality on Growth and Development in the Meadow Spittlebug (Philaenus spumarius) on Kent Island in the Bay of Fundy

Abstract Philaenus spumarius (Meadow Spittlebug, Homoptera: Cercopoidea) is a cosmopolitan generalist insect that feeds on a wide repertoire of host plants in the field. We studied density and growth of Meadow Spittlebugs on a range of host plants on Kent Island, a boreal island in the Bay of Fundy, NB, Canada. The highest spittlebug densities were on Cirsium arvense (Canadian Thistle), although spittlebugs had larger body sizes on Solidago rugosa (Rough-stemmed Goldenrod) and Anaphalis margaritacea (Pearly Everlasting). We fertilized plots of Rough-stemmed Goldenrod in the field over 3 weeks to examine the effects of plant quality on development of Meadow Spittlebugs. Following fertilization, there were fewer nymphs present in fertilized plots than in unfertilized plots, indicating faster nymph maturation to adulthood on fertilized plants. This study offers an initial report of the host plants used by Meadow Spittlebugs in northeastern boreal habitat, variation in density and performance of the species on a range of host plants, and the effects of plant fertilization on spittlebug life history.
Low Serum ZAG Levels Correlate With Determinants of the Metabolic Syndrome in Chinese Subjects

Introduction: Zinc-α2-glycoprotein (ZAG) is a novel adipokine, which is involved in metabolic syndrome (MetS). This study aimed to investigate the relationship between serum ZAG and MetS in Chinese adults, who diagnosed according to the 2005 International Diabetes Federation (IDF) criteria. Methods: A group of 151 MetS patients, 84 patients with central obesity and 70 healthy controls were enrolled. General clinical information, serum samples were obtained from all subjects and serum ZAG levels were determined via the commercial ELISA kits. Results: Serum ZAG levels were the highest in the control group, then gradually decreased with the severity of the metabolic abnormalities increased (8.78 ± 1.66 μg/mL for control vs. 8.37 ± 1.52 μg/mL for central obesity vs. 7.98 ± 0.94 μg/mL for MetS, P < 0.05). It was also decreased progressively with an increasing number of the MetS components (P for trend = 0.002). Additionally, serum ZAG/fat mass ratio was calculated and the similar changes were observed in the three groups (0.85 ± 0.53 μg/mL/kg for control vs. 0.39 ± 0.10 μg/mL/kg for central obesity vs. 0.36 ± 0.08 μg/mL/kg for MetS, P < 0.05). In the multiple regression analysis, group was a strong independent factor contributing to serum ZAG levels (P < 0.001). Furthermore, compared with subjects with the highest tertile of ZAG, subjects in the lowest tertile of ZAG had 1.946-fold higher risk of MetS (95% CI 1.419–6.117, P = 0.004). This phenomenon still existed after controlling for age, gender (Model 1), ALP, AST, Cr, UA, Urea based on Model 1 (Model 2), grip strength, smoking, drinking, birth place, current address, education level, manual labor, and exercise frequency based on Model 2 (Model 3). Receiver operation characteristic (ROC) curve analysis revealed that serum ZAG might serve as a candidate biomarker for MetS (sensitivity 57.6%, specificity 70.0% and area under the curve 0.655), and serum ZAG/fat mass ratio showed improved diagnosis value accuracy, with ROC curve area of 0.951 (95% CI, 0.920–0.983, P < 0.001), and 90.7% sensitivity and 88.6% specificity. Conclusions: Serum ZAG levels were lowered in patients with MetS and central obesity. The decreased serum ZAG levels were associated with the increased risks of MetS. Serum ZAG, especially serum ZAG/fat mass ratio might be the candidate diagnostic biomarkers for MetS.
Investigating the Role of FlhF Identifies Novel Interactions With Genes Involved in Flagellar Synthesis in Campylobacter jejuni

FlhF is a key protein required for complete flagellar synthesis, and its deletion results in the complete absence of a flagella and thus motility in Campylobacter jejuni. However, the specific mechanism still remains unknown. In this study, RNA-Seq, EMSAs, ChIP-qPCR and β-Galactosidase assays were performed to elucidate the novel interactions between FlhF and genes involved in flagellar synthesis. Results showed that FlhF has an overall influence on the transcription of flagellar genes with an flhF mutant displaying down-regulation of most flagellar related genes. FlhF can directly bind to the flgI promoter to regulate its expression, which has significant expression change in an flhF mutant. The possible binding site of FlhF to the flgI promoter was explored by continuously narrowing the flgI promoter region and performing further point mutations. Meanwhile, FlhF can directly bind to the promoters of rpoD, flgS, and fliA encoding early flagellin regulators, thereby directly or indirectly regulating the synthesis of class I, II, and III flagellar genes, respectively. Collectively, this study demonstrates that FlhF may directly regulate the transcription of flagellar genes by binding to their promoters as a transcriptional regulator, which will be helpful in understanding the mechanism of FlhF in flagellar biosynthetic and bacterial flagellation in general.
Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke

Atrial fibrillation (AF) increases the risk of ischemic stroke and systemic arterial embolism. However, the risk factors or predictors of stroke in AF patients have not been clarified. Therefore, it is necessary to find effective diagnostic and therapeutic targets. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network and significant module, and the receiver operator characteristic (ROC) curve analysis were performed. A total of 524 DEGs were common to both datasets. Analysis of KEGG pathways indicated that the top canonical pathways associated with DEGs were ubiquitin-mediated proteolysis, endocytosis, spliceosome, and so on. Ten hub genes (SMURF2, CDC42, UBE3A, RBBP6, CDC5L, NEDD4L, UBE2D2, UBE2B, UBE2I, and MAPK1) were identified from the PPI network and were significantly associated with a diagnosis of atrial fibrillation and stroke (AFST). In summary, a total of 524 DEGs and 10 hub genes were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. These genes may serve as the target of early diagnosis or treatment of AF complicated by stroke.
Dissolved Gas and Metal Composition of Hydrothermal Plumes From a 2008 Submarine Eruption on the Northeast Lau Spreading Center

Extrusion of lava onto the seafloor transports heat and mass from the lithosphere to the hydrosphere and the biosphere. During this process, large amounts of dissolved gases can be released into the ocean as hydrothermal plumes and serve as nutrients for microbial activity. Here, we report the dissolved gas and metal composition of hydrothermal plumes associated with a submarine eruption at the Northeast Lau Spreading Center (NELSC) in the SW Pacific Ocean in November 2008. During this eruption, two different types of plumes were observed in the water column: a shallow event plume rich in H2 and poor in 3He and CH4, and a deep near-seafloor plume with high CH4, metals and 3He and intermediate H2 concentrations. Both were generated at the same time and at the same location. While the high abundance of H2 in the event plume points to ongoing reactions between hot rock and seawater, the distinct chemical characteristics of the near-seafloor plume likely result from the release of a mature fluid stored in the crust. The plume chemistry of the event plume favors a seawater-lava interaction event plume generation model. However, the heat budget asks for an additional process releasing enough heat to lift the plume within the time frame of this short event. The extremely high H2 concentrations suggest that the eruption was locally more explosive than assumed. A more explosive eruption style might enhance the heat flux from lava cooling.
Volume Guarantee High-Frequency Oscillatory Ventilation in Preterm Infants With RDS: Tidal Volume and DCO2 Levels for Optimal Ventilation Using Open-Lung Strategies

High frequency oscillatory ventilation with volume-guarantee (HFOV-VG) is a promising lung protective ventilator mode for the treatment of respiratory failure in newborns. However, indicators of optimal ventilation during HFOV-VG mode are not identified yet. In this study, we aimed to evaluate optimal high-frequency tidal volume (VThf) and the dissociation coefficient of CO2 (DCO2) levels to achieve normocapnia during HFOV-VG after lung recruitment in very low birthweight infants with respiratory distress syndrome (RDS). Preterm babies under the 32nd postmenstrual week with severe RDS that received HFOV-VG using open-lung strategy between January 2014 and January 2019 were retrospectively evaluated. All included patients were treated with the Dräger Babylog VN500 ventilator in the HFOV-VG mode. In total, 53 infants with a mean gestational age of 26.8 ± 2.3 weeks were evaluated. HFOV mean optimal airway pressure (MAPhf) level after lung recruitment was found to be 10.2 ± 1.7 mbar. Overall, the mean applied VThf per kg was 1.64 ± 0.25 mL/kg in the study sample. To provide normocapnia, the mean VThf was 1.61 ± 0.25 mL/kg and the mean DCO2corr was 29.84 ± 7.88 [mL/kg]2/s. No significant correlation was found between pCO2 levels with VThf (per kg) or DCO2corr levels. VThf levels to maintain normocarbia were significantly lower with 12 Hz frequency compared to 10 Hz frequency (1.50 ± 0.24 vs. 1.65 ± 0.25 mL/ kg, p < 0.001, respectively). A weak but significant positive correlation was found between mean airway pressure (MAPhf) and VThf levels. To our knowledge, this is the largest study to evaluate the optimal HFOV-VG settings in premature infants with RDS, using the open-lung strategy. According to the results, a specific set of numbers could not be recommended to achieve normocarbia. Following the trend of each patient and small adjustments according to the closely monitored pCO2 levels seems logical.
Comparative Genomic and Transcriptomic Analyses of Mycobacterium kansasii Subtypes Provide New Insights Into Their Pathogenicity and Taxonomy

Mycobacterium kansasii is an important opportunistic pathogen of humans and has a close phylogenetic relationship with Mycobacterium tuberculosis. Seven subtypes (I–VII) have been identified using molecular biology approaches, of which subtype I is the most frequent causative agent of human disease. To investigate the genotypes and pathogenic components of M. kansasii, we sequenced and compared the complete base-perfect genomes of different M. kansasii subtypes. Our findings support the proposition that M. kansasii “subtypes” I-VI, whose assemblies are currently available, should be considered as different species. Furthermore, we identified the exclusive presence of the espACD operon in M. kansasii subtype I, and we confirmed its role in the pathogenicity of M. kansasii in a cell infection model. The espACD operon is exclusively present in mycobacterial species that induce phagosomal rupture in host phagocytes and is known to be a major determinant of ESX1-mediated virulence in pathogenic mycobacteria. Comparative transcriptome analysis of the M. kansasii I-V strains identified genes potentially associated with virulence. Using a comparative genomics approach, we designed primers for PCR genotyping of M. kansasii subtypes I-V and tested their efficacy using clinically relevant strains of M. kansasii.
Transforming Growth Factor-Beta1 in Diabetic Kidney Disease

Diabetic kidney disease (DKD) is the leading cause of end-stage renal disease (ESRD) worldwide. Renin-angiotensin-aldosterone system (RAAS) inhibitors and sodium-glucose co-transporter 2 (SGLT2) inhibitors have shown efficacy in reducing the risk of ESRD. However, patients vary in their response to RAAS blockades, and the pharmacodynamic responses to SGLT2 inhibitors decline with increasing severity of renal impairment. Thus, effective therapy for DKD is yet unmet. Transforming growth factor-β1 (TGF-β1), expressed by nearly all kidney cell types and infiltrating leukocytes and macrophages, is a pleiotropic cytokine involved in angiogenesis, immunomodulation, and extracellular matrix (ECM) formation. An overactive TGF-β1 signaling pathway has been implicated as a critical profibrotic factor in the progression of chronic kidney disease in human DKD. In animal studies, TGF-β1 neutralizing antibodies and TGF-β1 signaling inhibitors were effective in ameliorating renal fibrosis in DKD. Conversely, a clinical study of TGF-β1 neutralizing antibodies failed to demonstrate renal efficacy in DKD. However, overexpression of latent TGF-β1 led to anti-inflammatory and anti-fibrosis effects in non-DKD. This evidence implied that complete blocking of TGF-β1 signaling abolished its multiple physiological functions, which are highly associated with undesirable adverse events. Ideal strategies for DKD therapy would be either specific and selective inhibition of the profibrotic-related TGF-β1 pathway or blocking conversion of latent TGF-β1 to active TGF-β1.
HIV-1 Tat Length: Comparative and Functional Considerations

Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, United States, Center for Molecular Virology and Translational Neuroscience, Institute for Molecular Medicine and Infectious Disease, Drexel University College of Medicine, Philadelphia, PA, United States, 3 School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA, United States, 4 Sidney Kimmel Cancer Center, Thomas Jefferson
Response of Midgut Trypsin- and Chymotrypsin-Like Proteases of Helicoverpa armigera Larvae Upon Feeding With Peanut BBI: Biochemical and Biophysical Characterization of PnBBI

Proteinase/Protease inhibitors (PIs) from higher plants play an important role in defense and confer resistance against various insect pests and pathogens. In the present study, Bowman-Birk Inhibitor (BBI) was purified from mature seeds of an interspecific advanced hybrid peanut variety (4368-1) using chromatographic techniques. The biochemical and biophysical characteristics such as low molecular mass, presence of several isoinhibitors and higher-ordered dimer/tetramer, predominance of antiparallel β-sheets and random coils in secondary structure, reactive sites against trypsin and chymotrypsin, broad spectrum of stability toward extreme pH and temperature along with MALDI TOF-TOF analysis (ProteomeXchange identifier PXD016933) ascertained the purified biomolecule from peanut as BBI (PnBBI). Surface plasmon resonance competitive binding analysis revealed the bifunctional PnBBI is a trypsin specific inhibitor with 1:2 stoichiometry as compared to chymotrypsin. A concentration-dependent self-association tendency of PnBBI was further confirmed by ‘red shift’ in the far-UV CD spectra. Furthermore, the insecticidal potential of PnBBI against Helicoverpa armigera was assessed by in vitro assays and in vivo feeding experiments. A significant reduction in larval body weight was observed with concomitant attenuation in the activity of midgut trypsin-like proteases of H. armigera (HaTPs) fed on PnBBI supplemented diet. The one and two-dimensional zymography studies revealed the disappearance of several isoforms of HaTP upon feeding with PnBBI. qRT-PCR analysis further suggests the role of PnBBI in not only inhibiting the activity of midgut trypsin and chymotrypsin-like proteases but also in modulating their expression. Taken together, the results provide a biochemical and molecular basis for introgressed resistance in peanut interspecific advanced hybrid variety against H. armigera.