Miracle-dz/UniFAR-FTUs huggingface dataset:
Dense Cores Mapped in Ammonia: A Database

We present a database of 264 cores mapped in the (J,K) = (1,1) and (2,2) lines of NH3. We list the core gas properties—peak positions, total ammonia column densities, intrinsic line widths, kinetic temperatures, volume densities, core sizes, aspect ratios, and velocity gradients, as well as the properties of associated young stellar objects (YSOs)—associated IRAS sources along with their luminosities and core-YSO distances, outflow velocities, and SIMBAD and cluster associations. We also present the results of our statistical analysis and enumerate important pairwise correlations among the various gas and YSO properties. The results indicate that the association of stellar clusters with star-forming cores has a greater impact on their properties than does the presence of associated YSOs within these cores, although the latter influence is also statistically significant. In other words, the difference in core properties (nonthermal line widths, kinetic temperatures, and core sizes) between cores with and without associated YSOs is less significant when compared with the difference in these properties between cores with and without cluster associations. Furthermore, core gas and YSO properties show a significant dependence on the star-forming region in which the core is located. For instance, cores in Orion have larger line widths, higher kinetic temperatures, and larger sizes compared with cores in Taurus. Similarly, YSOs in Orion are more luminous than those in Taurus. These cluster and regional dependencies seem important enough that they ought to be accounted for in any self-consistent theory of star formation. Finally, the ratio of starless to stellar cores is too small (8:12 in Taurus, 2:41 in Orion A) to be consistent with ambipolar diffusion timescales that predict ratios as high as 3-30. This result is true even for regions that are known to be well surveyed and not to suffer from significant sample biases.
Artificial Intelligence-Based Diagnosis of Oral Lichen Planus Using Deep Convolutional Neural Networks

Abstract Objective The aim of this study was to employ artificial intelligence (AI) via convolutional neural network (CNN) for the separation of oral lichen planus (OLP) and non-OLP in biopsy-proven clinical cases of OLP and non-OLP. Materials and Methods Data comprised of clinical photographs of 609 OLP and 480 non-OLP which diagnosis has been confirmed histopathologically. Fifty-five photographs from the OLP and non-OLP groups were randomly selected for use as the test dataset, while the remaining were used as training and validation datasets. Data augmentation was performed on the training dataset to increase the number and variation of photographs. Performance metrics for the CNN model performance included accuracy, positive predictive value, negative predictive value, sensitivity, specificity, and F1-score. Gradient-weighted class activation mapping was also used to visualize the important regions associated with discriminative clinical features on which the model relies. Results All the selected CNN models were able to diagnose OLP and non-OLP lesions using photographs. The performance of the Xception model was significantly higher than that of the other models in terms of overall accuracy and F1-score. Conclusions Our demonstration shows that CNN models can achieve an accuracy of 82 to 88%. Xception model performed the best in terms of both accuracy and F1-score.
Strength and Wear Behavior of Three-Dimensional Printed and Prefabricated Denture Teeth: An In Vitro Comparative Analysis

Abstract Objectives With advanced technology for complete denture fabrication, there is a lack of knowledge on the mechanical behavior of three-dimensional (3D) printed teeth despite the development of complete denture fabrication technologies. This study aimed to compare different types of 3D-printed teeth in terms of wear and fracture resistance in comparison to control prefabricated denture teeth. Materials and Methods One prefabricated tooth was selected and fixed in a resin holder and half of the tooth remained in anatomic form, while the other half was flattened for the wear test. One from each type was scanned and then printed with different resins; Asiga (DentaTOOTH, Asiga, Alexandria 2015,NSW, Australia), FormLabs (Denture Base LP, FormLabs, Berlin, Germany), and NextDent (NextDent C&B MFH, NextDent B.V., Soesterberg, the Netherlands) according to manufacturer recommendations. A total of 60 specimens (20/resin, n = 10) were thermo cycled (5,000 cycles) and wear test samples were further subjected to cyclic loading (1,70,000 cycles) in a chewing simulator machine CS-4.2 (SD Mechatronik GmbH, Germany). The fracture strength of anatomic teeth was measured using a universal testing machine (Instron model 5965, Massachusetts, United States), while Geomagic Control X software was used to assess the amount of wear of flattened teeth. Statistical analyses were performed with one-way analysis of variance with Tukey's post hoc test at significance level of α = 0.05. Results NextDent specimens showed the greatest volume loss, whereas FormLabs specimens showed the least volume loss. Comparing NextDent specimens to FromLabs specimens, FromLabs showed statistically significantly less volume loss ( p < 0.001). No other group pairs differed significantly from one another in terms of volume loss ( p > 0.06). Conclusion 3D-printed denture teeth showed comparable strength and wear resistance with the prefabricated denture teeth and were suitable for long-term clinical usage except for NextDent that significantly showed the lowest fracture resistance.
DOF transcription factors: Specific regulators of plant biological processes

Plant biological processes, such as growth and metabolism, hormone signal transduction, and stress responses, are affected by gene transcriptional regulation. As gene expression regulators, transcription factors activate or inhibit target gene transcription by directly binding to downstream promoter elements. DOF (DNA binding with One Finger) is a classic transcription factor family exclusive to plants that is characterized by its single zinc finger structure. With breakthroughs in taxonomic studies of different species in recent years, many DOF members have been reported to play vital roles throughout the plant life cycle. They are not only involved in regulating hormone signals and various biotic or abiotic stress responses but are also reported to regulate many plant biological processes, such as dormancy, tissue differentiation, carbon and nitrogen assimilation, and carbohydrate metabolism. Nevertheless, some outstanding issues remain. This article mainly reviews the origin and evolution, protein structure, and functions of DOF members reported in studies published in many fields to clarify the direction for future research on DOF transcription factors.
LAG3 genotype of the donor and clinical outcome after allogeneic transplantation from HLA-identical sibling donors

Introduction The association of polymorphisms in molecules involved in the immune response (checkpoint inhibitors) with the clinical outcome after allogeneic transplantation (alloHSCT) has been described. Lymphocyte Activation 3 (LAG3) is a surface protein that plays a regulatory role in immunity as an inhibitory immune checkpoint molecule. Methods To determine its role in the alloHSCT setting, we analyzed 797 patients transplanted from HLA-identical sibling donors. The LAG3 rs870849 C>T polymorphism was genotyped in donors. Results We detected a higher incidence of severe acute GVHD in patients transplanted from donors with TT genotype (p: 0.047, HR 1.64; 95% CI 1.01 – 2.67). Overall survival (OS) was worse for patients transplanted from donors with the rs870849 CT/TT genotype (0.020; HR, 1.44; 95% CI 1.06 – 1.96), as well as disease-free survival (DFS) (p: 0.002; HR 1.58, 95%CI: 1.18 – 2.14) and transplant-related mortality (TRM) (p< 0.001; HR: 1.88, 95% CI 1.29 – 2.74). When combining the LAG3 rs870849 and the PDCD1 rs36084323 genotypes of the donor, three genetic groups were well defined, allowing a good stratification of the risk of acute GVHD, TRM, OS and DFS. Discussion We conclude that the LAG3 genotype of the donor may be considered in donors’ selection. As this selection may be limited in the HLA-identical sibling donor scenario, further studies exploring the impact of LAG3 genotype of the donor in unrelated transplantation are warranted.
On the inexactness level of robust Levenberg–Marquardt methods

Recently, the Levenberg–Marquardt (LM) method has been used for solving systems of nonlinear equations with nonisolated solutions. Under certain conditions it converges Q-quadratically to a solution. The same rate has been obtained for inexact versions of the LM method. In this article the LM method will be called robust, if the magnitude of the regularization parameter occurring in its sub-problems is as large as possible without decreasing the convergence rate. For robust LM methods the article shows that the level of inexactness in the sub-problems can be increased significantly. As an application, the local convergence of a projected robust LM method is analysed.
Interstitial lung disease in rheumatoid arthritis: incidence, prevalence and related drug prescriptions between 2007 and 2020

Objective To investigate prevalence, incidence and medication of interstitial lung disease (ILD) among German individuals with rheumatoid arthritis (RA). Methods Nationwide BARMER claims data from 2007 to 2020 were used. RA-ILD was identified by diagnosis codes, prescription of disease-modifying antirheumatic drugs (DMARDs) and lung diagnostics. ILD was assigned as incident or prevalent relative to the year of the first diagnosis. We identified prescriptions of glucocorticoids, conventional synthetic (cs), biological (b) and targeted synthetic (ts)DMARDs, antifibrotics and rheumatology and/or pulmonology care. Results Among all persons with RA (40 686 in 2007 to 85 175 in 2020), 1.7%–2.2%/year had ILD with a slight decline since 2013. Incident ILD was 0.13%–0.21% per year and remained stable over time. ILD was more common in seropositive RA, in men and in the elderly (mean age 72 years in 2020). Glucocorticoids (84% to 68%), csDMARD (83% to 55%) and non-steroidal anti-inflammatory drug use (62% to 38%) declined, while bDMARDs (16% to 24%) rose. In 2020, 7% received tsDMARDs, 3% antifibrotics, 44% analgesics and 30% opioids. DMARD therapy was more common if a rheumatologist was involved and antifibrotics if a pulmonologist was involved. Opioid use was highest if no specialist was involved (39%) but also common in rheumatology care (32%) and less frequent in pulmonology care (21%). Conclusions RA-ILD is rare and mainly affects elderly persons. No trend in incidence was observed but treatment strategies have enlarged. Specialist care is necessary to provide disease-specific therapies. The continuing high analgesic and opioid demand shows unmet needs in these patients.
DT-DS: CAN Intrusion Detection with Decision Tree Ensembles

The controller area network (CAN) protocol, used in many modern vehicles for real-time inter-device communications, is known to have cybersecurity vulnerabilities, putting passengers at risk for data exfiltration and control system sabotage. To address this issue, researchers have proposed to utilize security measures based on cryptography and message authentication; unfortunately, such approaches are often too computationally expensive to be deployed in real time on CAN devices. Additionally, they have developed machine learning (ML) techniques to detect anomalies in CAN traffic and thereby prevent attacks. The main disadvantage of existing ML-based techniques is that they either depend on additional computational hardware or they heuristically assume that all communication anomalies are malicious. In this article, we show that tree-based learning ensembles outperform anomaly-based techniques like AutoRegressive Integrated Moving Average (ARIMA) and Z-Score when used to detect attacks that result in increased bus utilization. We evaluated the detection capacity of three tree-based ensembles, Adaboost, gradient boosting, and random forests, and collectively refer to these as DT-DS. We conclude that the decision tree ensemble with Adaboost performs best with an area under curve (AUC) score of 0.999, closely followed by gradient boosting and random forests with 0.997 and 0.991 AUC scores, respectively, when trained using message profiles. We observe that with an increase in the observation window, the DT-DS models present an average AUC score of 0.999, and offer a nearly perfect detection of attacks, at the cost of increased latency in detection of attacked messages. We evaluate the performance of the IDS for Aeronautical Radio, Incorporated– (ARINC) encoded CAN communication traffic in avionic systems, generated using an aerospace testbench, ARINC-825TBv2. The IDS has been evaluated against the active attacks of a state-of-the-art predictive attacker model. Additionally, we observed that the performance of IDS approaches such as ARIMA and Z-Score degrade considerably with a decrease in the size of the observation time window. In contrast, the performance of DT-DS models is consistent, with only an average drop of 0.005 in the AUC score.
Proving Data-Poisoning Robustness in Decision Trees

Machine learning models are brittle, and small changes in the training data can result in different predictions. We study the problem of proving that a prediction is robust to data poisoning, where an attacker can inject a number of malicious elements into the training set to influence the learned model. We target decision tree models, a popular and simple class of machine learning models that underlies many complex learning techniques. We present a sound verification technique based on abstract interpretation and implement it in a tool called Antidote. Antidote abstractly trains decision trees for an intractably large space of possible poisoned datasets. Due to the soundness of our abstraction, Antidote can produce proofs that, for a given input, the corresponding prediction would not have changed had the training set been tampered with or not. We demonstrate the effectiveness of Antidote on a number of popular datasets.
Some Convexity Results for the Cartan Decomposition

Abstract In this paper, we consider the set $\text{S}=a\left( {{e}^{X}}K{{e}^{Y}} \right)$ where $a\left( g \right)$ is the abelian part in the Cartan decomposition of $g$ . This is exactly the support of the measure intervening in the product formula for the spherical functions on symmetric spaces of noncompact type. We give a simple description of that support in the case of $\text{SL}\left( 3,\,\mathbf{F} \right)\,\text{where}\,\mathbf{F}\,=\,\mathbf{R},\,\mathbf{C}\,\text{or}\,\mathbf{H}$ . In particular, we show that $\text{S}$ is convex. We also give an application of our result to the description of singular values of a product of two arbitrary matrices with prescribed singular values.
A Degenerate Neumann Problem for Quasilinear Elliptic Equations

The degenerate Neumann problem is studied in the case where $a(x)$ and $b(x)$ are non-negative functions on $\Gamma$ such that $a(x)+b(x)>0$ on $\Gamma$ . A classical existence and uniqueness theorem in the Holder space $C^{2+\alpha}(\overline{\Omega})$ is proved under suitable regularity and structure conditions on the data.
Probing the sub-cellular mechanisms of LCA5-Leber Congenital Amaurosis and associated gene therapy with expansion microscopy

Leber Congenital Amaurosis (LCA) is a group of Inherited Retinal Diseases (IRDs) characterized by the early onset and rapid loss of photoreceptor cells. Despite the discovery of a growing number of genes associated with this disease, the molecular mechanisms of photoreceptor cell degeneration of most LCA subtypes remain poorly understood. Here, using retina-specific affinity proteomics combined with Ultrastructure Expansion Microscopy (U-ExM), we revealed the structural and molecular defects underlying LCA type 5 (LCA5) with unprecedented resolution. We showed that LCA5-encoded lebercilin, together with Retinitis Pigmentosa 1 protein (RP1) and the intraflagellar transport (IFT) proteins IFT81 and IFT88, localize at the bulge region of the photoreceptor outer segment (OS), a region crucial for OS membrane disc formation. Next, we demonstrated that mutant mice deficient for lebercilin exhibit early axonemal defects at the bulge region and the distal OS, accompanied by reduced level of RP1 and IFT proteins, affecting membrane disc formation and presumably leading to photoreceptor death. Finally, we probed the LCA5 gene augmentation therapy strategy using U-ExM by monitoring its subcellular outcome. We found that, expression of LCA5 partially restores the bulge region, preserves OS axoneme structure and membrane disc formation, as well as photoreceptor survival.
FROM FOREST TO SAVANNA AND BACK TO FOREST: EVOLUTIONARY HISTORY OF THE GENUS Dimorphandra (LEGUMINOSAE)

The tree genus Dimorphandra comprises 26 species, which are circumscribed into three subgenera. The subgenus Dimorphandra is associated with both rainforests (Amazon and Atlantic Forest) and savanna-like vegetation (Cerrado); whereas the subgenera Pocillum and Phaneropsia are restricted to the Amazon. We obtained DNA sequence data from six gene regions of the chloroplast genome (cpDNA) and the nuclear internal transcribed spacer (ITS) from 17 species of Dimorphandra and 12 closely related species. Bayesian phylogeny and haplotype network analyses together with both ancestral area reconstructions and ecological niche modeling allowed for exploring the late evolutionary history of the genus Dimorphandra. Species within the subgenus Phaneropsia were more closely related to species of the genus Mora than to the remaining congeners in the plastid tree (but not in the ITS tree), casting doubts on the monophyly of Dimorphandra. Such incongruence may be the result of incomplete lineage sorting of ancient polymorphisms. Amazonian lineages (subgenera Pocillum and Phaneropsia) were highly polymorphic and divergent; whereas lineages from either the Cerrado or the Atlantic Forest were genetically depauperate. The Amazon seems to be the likely source of the lineage that gave rise to the extant species of Dimorphandra of the Cerrado. In turn, a lineage that occupied the Cerrado likely gave rise to the extant species that occur in the Atlantic Forest. Habitat shifts may have been a key driving force that shaped the late evolutionary history of Dimorphandra.
VAP spatially stabilizes dendritic mitochondria to locally fuel synaptic plasticity

Synapses are pivotal sites of memory formation and undergo plasticity in response to external inputs. Consequently, synapses are hotspots of energy consumption and are susceptible to dysfunction when their energy supplies are perturbed. Mitochondria are stabilized near synapses via cytoskeletal tethering and serve as local energy supplies to fuel synaptic plasticity. However, the mechanisms that tether and stabilize neuronal mitochondria for long durations and determine the spatial dendritic segment supported during synaptic plasticity are unknown. We identified a list of novel mitochondrial-cytoskeletal interactors in neurons using APEX-based proximity labeling. We narrowed down the protein candidates that exclusively tether mitochondria to actin near postsynaptic spines using high-resolution Airyscan confocal imaging. We find that VAP, the vesicle-associated membrane protein-associated protein implicated in Amyotrophic Lateral Sclerosis and interacts with the endoplasmic reticulum, stabilizes mitochondria via actin near the spines. To test if the VAP-dependent stable mitochondrial compartments can locally support synaptic plasticity, we investigated individual spines stimulated by two-photon glutamate uncaging for spine plasticity induction and their adjacent spines. We find that, along with actin, VAP functions as a spatial stabilizer of mitochondrial compartments to sustain synaptic plasticity for up to ~60 min and as a spatial ruler that determines the ~30 μm length of the dendritic segment supporting synaptic plasticity.
A century of sampling at an ecological preserve reveals declining diversity of wild bees

We analyzed the wild bee community from 1921 to 2018 at a nature preserve in southern Michigan, USA using museum records and found significant shifts in the bee community. Across the near century of records, species richness peaked in the 1970s and 1980s. There was an intensive bee survey completed by F.C. Evans in 1972 and 1973. We attempted to replicate his effort in 2017 and 2018, and again found a significant decline in species richness and evenness. There was also evidence of declining abundance in many of the more common species. We also conducted traits analyses using neural networks, revealing that oligolectic ground-nesting bees and cleptoparasitic bees were more likely to be extirpated whereas polylectic cavity-nesting bees were more likely to have persisted. Additionally, larger body size was associated with increased probability of local extirpation for polylectic cavity-nesting species. Larger phenological range was associated with increased chances of persistence for polylectic species, while it was associated with extirpation for oligolectic ground-nesting species. Species in the contemporary samples also had a more southerly overall distribution compared to the historic one. Open Research Statement Data used for analyses in this manuscript, including Evans’ original dataset from 1972/1973 with updated species nomenclature, will be permanently archived at the USDA Ag Data Commons after the acceptance of this manuscript and will be citable and accessible here: https://data.nal. usda.gov/dataset/century-sampling-ecological-preserve-reveals-declining-diversity-wild-bees. Complete instructions on how to access all data referenced in this manuscript can be found in Appendix S1.
Colonization of a novel host plant reduces phenotypic variation

Understanding the evolutionary potential of populations –evolvability– is key to predicting their ability to cope with novel environments. Despite growing evidence that evolvability determines the tempo and mode of adaptation, it remains unclear how adaptations to novel environments influence evolvability in turn. Here we address the interplay between adaptation and evolvability in the peacock fly Tephritis conura, which recently underwent an adaptive change in the length of female ovipositor following a host shift. By comparing evolvability in various morphological traits including female ovipositor length between ancestral and derived host races, we found that evolvability is decreased in females of the derived host race compared to the ancestral host race. We found a correlation between evolvability and divergence between populations in both sexes, indicating that the overall pattern of evolvability has not been disrupted by the host shift despite the reduction in females of the derived host race. Exploration of the pattern of phenotypic integration further revealed that the ovipositor length constitutes a module that is separated from other measured traits. These results suggest that adaptation to novel environments can affect evolvability, and that modularity helps minimizing detrimental effects that adaptations may cause to other correlated traits.