Miracle-dz/UniFAR-FTUs huggingface dataset:
Pluripotency inducing Yamanaka factors: role in stemness and chemoresistance of liver cancer

ABSTRACT Introduction: Liver cancer is a major cause of mortality and is characterized by the transformation of cells into an uncontrolled mass of tumor cells with many genetic and epigenetic changes, which lead to the development of tumors. A small subpopulation of cell population known as Cancer Stem Cells (CSCs) is responsible for cancer stemness and chemoresistance. Yamanaka factors [octamer-binding transcription factor 4 (OCT4), SRY (sex-determining region Y)-box 2 (SOX2), kruppel-like factor 4 (KLF4), and Myelocytomatosis (MYC); OSKM] are responsible for cancer cell stemness, chemoresistance, and recurrence. Area covered: We cover recent discoveries and investigate the role of OSKM in inducing pluripotency and stem cell-like properties in various cancers with special emphasis on liver cancer. We review Yamanaka factors’ role in stemness and chemoresistance of liver cancer. Expert opinion: In CSCs, including liver CSCs, the deregulation of various signaling pathways is one of the major reasons for stemness and drug resistance and is primarily due to OSKM. OSKM are responsible for tumor heterogeneity which renders targeting drug useless after a certain period. These factors can be exploited to understand the underlying mechanism of cancer stemness and resistance to chemotherapeutic drugs. Graphical Abstract
Severe hypercalcemia in a patient with chronic lymphocytic leukemia and non-small cell lung carcinoma

Abstract Rationale: Hypercalcemia is a common finding in patients with advanced-stage cancers. Paraneoplastic hypercalcemia is commonly associated with dismal prognoses, with survival rates of about 3 months. In this paper, we report on a patient with advanced chronic lymphocytic leukemia and non-small cell lung carcinoma who developed severe hypercalcemia and discuss the diagnosis and treatment of this metabolic complication. Patient concerns: A 56-year old male with a 2-year history of Rai stage IV chronic lymphocytic leukemia presented with life-threatening hypercalcemia. Positron emission tomography/computed tomography revealed a suspicious lung lesion. A transbronchial biopsy was performed from the upper left lobe. Due to the small size of the specimen, immunohistochemical markers were performed and revealed positive staining for cytokeratin 7 and negative for TTF-1, napsin A and p 40, which were consistent with non-small cell lung carcinoma. Diagnosis: Humoral hypercalcemia of malignancy was diagnosed. Intervention: The patient was treated with saline infusion, calcitonin, intravenous pamidronate, followed with denosumab. Outcomes: The hypercalcemia was successfully treated and the patient's calcium levels returned to normal. Further evaluation revealed a non-small cell lung carcinoma as a second primary malignancy. The patient was treated with venetoclax for his refractory CLL and received chemotherapy and immunotherapy for lung adenocarcinoma. Several days after starting venetoclax, he developed Legionella pneumonia and short time after the second course of chemotherapy, a severe sepsis occurred and he passed away. Lessons: Coexistence of 2 unrelated malignancies, whichever could be a reason for hypercalcemia of malignancy is a rare event. Severe hypercalcemia, which is possible but rare feature of CLL should be a reason for further prompt evaluation.
Effect of desmopressin lyophilisate (MELT) plus anticholinergics combination on functional bladder capacity and therapeutic outcome as the first-line treatment for primary monosymptomatic nocturnal enuresis: A randomized clinical trial

Purpose To assess the efficacy of desmopressin plus anticholinergic combination therapy as first-line treatment for children with primary monosymptomatic nocturnal enuresis (PMNE) and to analyze this combination's effect on functional bladder capacity (FBC). Materials and Methods A total of 99 children with PMNE were prospectively enrolled from 2015 to 2019 and randomly allocated to a monotherapy group (n=49), with oral desmopressin lyophilisate (MELT) only; and a combination group (n=50), with desmopressin plus an anticholinergic (propiverine 5 mg). Efficacy and FBC were evaluated at 1 and 3 months after treatment initiation; the relapse rate was assessed at 6 months after treatment cessation. Results The combination therapy group showed a higher rate of complete response than the monotherapy group after 3 months of treatment (44.0% vs. 22.4%, p=0.002). A significant increase in mean FBC was observed only in the combination group, from 88.72±26.34 mL at baseline to 115.52±42.23 mL at 3 months of treatment (p=0.024). Combination therapy was significantly associated with treatment success at 3 months after treatment initiation (odds ratio [OR], 3.527; 95% confidence interval [CI], 1.203–6.983; p=0.011) and decreased risk of relapse at 6 months after treatment cessation (OR, 0.306; 95% CI, 0.213–0.894; p=0.021), by multivariable analysis. Conclusions This study represents the first prospective, randomized controlled trial showing higher response rates and lower relapse rates with desmopressin plus anticholinergic combination therapy compared with desmopressin monotherapy as first-line treatment for children with PMNE.
Seed rain-successional feedbacks in wet tropical forests.

Tropical forest regeneration after abandonment of former agricultural land depends critically on the input of tree seeds, yet seed dispersal is increasingly disrupted in contemporary human-modified landscapes. Here, we introduce the concept of seed rain-successional feedbacks as a deterministic process in which seed rain is shaped by successional dynamics internal to a forest site and that acts to reinforce priority effects. We used a combination of time series and chronosequence approaches to investigate how the quantity and taxonomic and functional composition of seed rain change during succession and to evaluate the strength of seed rain-successional feedbacks, relative to other deterministic and stochastic mechanisms, in secondary wet forests of Costa Rica. We found that both successional niches and seed rain-successional feedbacks shaped successional trajectories in the seed rain. Determinism due to successional niche assembly was supported by the increasing convergence of community structure to that of a mature forest, in terms of both functional and taxonomic composition. With successional age, the proportions of large-seeded, shade-tolerant species in the seed rain increased, whereas the proportion of animal-dispersed species did not change significantly. Seed rain-successional feedbacks increased in strength with successional age, as the proportion of immigrant seeds (species not locally represented in the site) decreased with successional age, and the composition of the seed rain became more similar to that of the adult trees at the forest site. The deterministic assembly generated by seed rain-successional feedback likely contributed to the increasing divergence of secondary forest sites from each other during succession. To the extent that human modification of tropical forest landscapes reduces connectivity via factors such as forest cover loss, our results suggest that seed rain-successional feedbacks are likely to increasingly shape regeneration trajectories in and amplify floristic heterogeneity among tropical secondary forests.
Milestone Development in Genetic Conditions from SFARI Registries

Abstract Background: Several recent initiatives have sought to better understand characteristic behaviors of rare genetic conditions associated with autism spectrum disorder (ASD). The onset of developmentally expected skills, such as walking and talking, serve as readily quantifiable aspects of the behavioral phenotype. The goals of this study were to describe attainment of major motor and language milestones in genetic conditions implicated in the etiology of ASD and other neurodevelopmental disorders and to compare those phenotypes to idiopathic ASD. Methods: Participants ages 3 years and older were drawn from two Simons Foundation Autism Research Initiative-funded registries with consistent phenotyping protocols. Inclusion criteria consisted of a confirmed genetic diagnosis for one of 16 specific genetic conditions (Simons Searchlight), and absence of pathogenic genetic findings in idiopathic ASD controls (SPARK). Parent-reported age of acquisition of three motor and two language milestones was described and quantified as on-time or delayed relative to normative expectations. Results: Delay was more common among participants with rare genetic conditions than idiopathic ASD for all milestones. Compared to the idiopathic ASD group, the median odds of delay among the genetic groups were 8.3 times (IQR 5.8-16.3) higher for sitting, 12.4 times (IQR 5.3-19.5) higher for crawling, 26.8 times (IQR 7.7-41.1) higher for walking, 2.7 times (IQR 1.7-5.5) higher for single words, and 5.7 times (IQR 2.8-18.3) higher for combined words. Conclusion: Delays in major developmental milestones, particularly in motor skills, may be among the earliest clues that developmental processes may be differentially affected in specific genetically defined conditions versus a behaviorally defined disorder such as idiopathic ASD.
The fossil record and phylogeny of South American horned frogs (Anura, Ceratophryidae)

South American horned frogs (Ceratophryidae), with their large heads, wide gapes and fang-like teeth, are among the most charismatic, best-known and well-studied neobatrachian anurans. The family comprises 12 extant species with hyperossified skulls and has a relatively rich fossil record, particularly in the Pampas, which dates back to the late Miocene. However, several records have been overlooked in recent summaries, and many taxonomic assignments remain indeterminate or are questionable and have yet to be tested within a quantitative phylogenetic framework. Here we provide a complete up-to-date survey of the palaeontological record of Ceratophryidae, including some remarkable new records. We also tested their systematic position through comprehensive phylogenetic analyses based on osteological data, providing several synapomorphies for all relevant nodes. Finally, we discuss these integrated data in relation to divergence time estimates, and propose a set of fossil calibrations that provide hard minimum bounds for crown-group Ceratophryidae and the subclades within it, and illuminate the acquisition of polyploidy within the group.
Le capital social comme socle des échanges inter-organisationnels : une lecture à travers le prestataire de services logistiques

RÉSUMÉ La chaîne logistique est un cadre relationnel traversé par des agencements et des interdépendances de schémas organisationnels indissolublement imbriqués. Cette réalité interactionnelle est marquée par la présence quasi systématique de prestataires de services logistiques (PSL) et plus particulièrement un prestataire dématérialisé dénommé fourth-party logistics (4PL). Cet acteur opère des architectures connexionnistes en se plaçant à l’intersection de plusieurs chaînes logistiques. Cela requiert une intégration logistique mais aussi une logique relationnelle bâtie sur la confiance et la prise en compte de la dimension informelle des relations inter-organisationnelles. Les axes traversant notre article valorisent le capital social, l’encastrement ainsi que la dynamique d’intégration et d’intermédiation opérées par le 4PL. Les principaux résultats valorisent le capital social comme étant facilitateur, pourvoyeur d’opportunités d’affaires, vecteur d’acquisition d’informations et par conséquent une compétence distinctive à valoriser et à mobiliser dans les échanges inter-organisationnels.
A new species of Cricosaurus (Thalattosuchia: Crocodylomorpha) from southern Germany: the first three-dimensionally preserved Cricosaurus skull from the Solnhofen Archipelago

Cricosaurus represents one of the most important radiations within Metriorhynchidae, a specialized marine clade of Crocodylomorpha that flourished in marine environments from the Middle Jurassic until the Early Cretaceous. Here, we describe a new species of Cricosaurus, Cricosaurus rauhuti sp. nov., from the Mörnsheim Formation (lower Tithonian) of southern Germany. The specimen is the first three-dimensionally preserved Cricosaurus from this realm, and it is represented by a partially preserved cranium and lower jaw that has autapomorphic characters that distinguish it from any other species of Cricosaurus. The phylogenetic analysis shows that the new species is more closely related to some non-European forms from the Late Jurassic and one taxon from the Valanginian of Germany (all 3D-preserved) than to other Late Jurassic Cricosaurus from southern Germany (all 2D-preserved). Our exploratory analyses confirm that this is not a preservation bias. For the first time, this shows that there are two clades of Cricosaurus present during the Late Jurassic in Germany. Furthermore, it provides additional evidence of a close faunal relationship between Europe and South America in the Late Jurassic, as also evidenced by the fossil record of other marine reptiles. Finally, the distribution of metriorhynchids in localities of the Solnhofen Archipelago suggests a change in the taxic diversity of the region during the early Tithonian, which might be the result of environmental changes in the Solnhofen Archipelago. http://zoobank.org/urn:lsid:zoobank.org:pub:488705BF-AEAD-4F02-BB4E-429E3117BCD1
Self-care management 101: Strategies for social workers and other frontline responders during the COVID-19 pandemic in rural communities

ABSTRACT The Coronavirus Disease (COVID-19) has taken the world by storm, causing massive death and infection rates, along with a myriad of challenges for individuals, families, groups, organizations, and communities everywhere. Rural communities are disproportionally impacted by COVID-19 as they were already challenged by social, economic, and health disparities. Social workers and frontline responders in these communities also face unique challenges as the people they serve are poorer, older, and have more chronic health conditions as compared to people in urban communities (Center for Disease Control and Prevention [CDC], 2019). As social workers and other frontline responders become more overwhelmed and burdened with the responsibility to care for others during this pandemic, their own needs are often overlooked and unmet. To that end, there is increasing recognition of the relevance of self-care among social workers and other frontline responders, particularly those in rural communities where there is a shortage of professional service providers and resources. This article explores stressors associated with COVID-19 and the impact of COVID-19 on rural communities, social workers, and other frontline responders. It also presents self-care strategies for reducing the burden of COVID-19. It concludes with implications for social work practice. Lastly, practical strategies for self-care and implications for social work will be provided.
A systematic parallel strategy for generating contours from large-scale DEM data using collaborative CPUs and GPUs

ABSTRACT This study aims to employ both central processing units (CPUs) and graphics processing units (GPUs) to collaboratively generate contour lines from a large-scale digital elevation model (DEM). The performance was improved with regard to three aspects. First, the original DEM data were decomposed and assigned according to the GPU’s limited memory so that large-scale data could be correctly addressed. Second, different types of computational tasks between the CPUs and GPUs were dynamically scheduled to ensure that both accelerators cooperate for performance improvement. Third, parallel processing on GPUs and CPUs was separately optimized for more efficient acceleration. Experimental results indicated that applying the parallel algorithm to data with a volume of 37.81 GB and area of 5,975,625.16 km2 reduced the total execution time from 332.84 min to 8.29 min for an optimal speedup of 40.15. In addition, we investigated the effects of the computational intensity, decomposition granularity, and task scheduling on parallel efficiency and performance improvement. We also discussed its degree of effectiveness, broader application, and the future direction of research in the field of geographic information systems.
New Directions in Employment Relations Theory: Understanding Fragmentation, Identity, and Legitimacy

This article introduces the special issue on New Theories in Employment Relations. The authors summarize the history of employment relations theory and reflect on the implications of recent disruptive changes in the economy and society for new theory development. Three sets of changes are identified: the growing complexity of actors in the employment relationship, an increased emphasis on identity as a basis for organizing and extending labor protections, and the growing importance of norms and legitimacy as both a constraint on employer action and a mobilizing tool. The articles in this special issue advance new frameworks to analyze these changes and their implications for the future of employment relations.
Human Protein Classification in Microscope Images Using Deep Learning and Focal-Lovász Loss

Subcellular proteins in human cells play a crucial role in maintaining physiological activities of cells. Understanding the complexity of human proteins will open doors to the next breakthrough in medical science. However, despite the rapid development of classification techniques for microscope images based on deep learning, the diversity and class imbalance of subcellular human proteins still challenge the models to achieving a promising classification performance. In this paper, to address this challenging task, we build a composite loss function, which combines focal loss and Lovász-Softmax loss together (Focal-Lovász loss) for training. We show that a series of deep convolutional neural networks (ResNet-50, DenseNet-121 and SE-ResNeXt-50) can all get a higher macro F1-score on Human Protein Atlas dataset when utilizing Focal-Lovász loss than traditional loss functions. The results manifest that Focal-Lovász loss can effectively address the minority classes and balance the recall and precision. By applying K-Fold cross validation and model ensemble, we obtain a macro F1 score 0.5292 on the private test set, which locates at the top 3% among all teams and can get a silver medal in the Kaggle competition.
SuanMing: Explainable Prediction of Performance Degradations in Microservice Applications

Application performance management (APM) tools are useful to observe the performance properties of an application during production. However, APM is normally purely reactive, that is, it can only report about current or past performance degradation. Although some approaches capable of predictive application monitoring have been proposed, they can only report a predicted degradation but cannot explain its root-cause, making it hard to prevent the expected degradation. In this paper, we present SuanMing---a framework for predicting performance degradation of microservice applications running in cloud environments. SuanMing is able to predict future root causes for anticipated performance degradations and therefore aims at preventing performance degradations before they actually occur. We evaluate SuanMing on two realistic microservice applications, TeaStore and TrainTicket, and we show that our approach is able to predict and pinpoint performance degradations with an accuracy of over 90%.
Using Temporal Convolutional Networks to Enable Action Recognition for Construction Equipment

In order to improve the efficiency of construction and reduce or avoid accidents, it is necessary to accurately identify the activities of construction equpment. However, research on construction equipment action recognition (CEAR) is still very limited, mainly due to the lack of video datasets for algorithm development. This research developed a video dataset of 2064 clips with five action categories of excavators and dump trucks. Using this dataset, a simplified temporal convolutional network (STCN) was developed by combining convolutional neural networks (CNN) with long-short-term memory networks (LSTM), where CNN is used to extract image features from video clips and LSTM is used to extract time-series features from the frame sequences of videos. By comparing with a similar CEAR method (CNN-DLSTM) and two advanced human action recognition methods (C3D and two-stream ConvNets), the STCN method has comparable performance and requires less training time. This study also preliminarily proved that the human action recognition (HAR) methods have the potential for action recongnition of construction equipment.
Deep Neural Networks for Automatic Classification of Knee Osteoarthritis Severity Based on X-ray Images

Knee Osteoarthritis (KOA) is a type of chronic disease that commonly occurs in older, obese citizens and those with a sedentary lifestyle. This disease causes damage to knee cartilage and causes pain so that the patient's activity is reduced. Radiologists classify the KOA severity based on Joint Space Narrowing (JSN) and the presence or absence of osteophytes into five stages from healthy knee (stage 0) to the worst damage (stage 4). We developed a methodology that aims to accelerate the classification of KOA severity based on information obtained from X-ray images and to reduce the subjectivity of radiologists. This paper describes an automated KOA diagnostic model using hyper-parameter Deep Convolutional Neural Networks (DCNN). Based on our experimental result, it shows the accuracy of the proposed method outperforms other KOA severity classification algorithms, which also discussed deep learning, namely 77.24%. This value is the average result of the accuracy of each fold from each stage of the KOA severity level where we use three-folds cross validation as a method of evaluating system performance. Thus computationally, this method is efficient in automatic diagnosis and has the potential to be a clinician application aid to specify the KOA severity.
High-resolution Ultrasonic Echo Detection with Two-stage Recurrent Neural Network

Ultrasonic echo methods have been widely researched for the application of flaw detection, where the flaw locations are identified by the arrival time of each echo. The main difficulty is that the receiving echoes from consecutive flaws overlap in time when the flaws are close. Over the last decades, sparse approximation and neural-network-based methods have been used to address this issue. However, these methods cannot achieve satisfactory performance in high-noise and severe overlapping scenarios. In this paper, we propose a high-resolution ultrasonic echo detection method with two-stage recurrent neural network, which includes the localization of echo and the regression of echo amplitude. The proposed method adopts two-stage ideology which filters interfering sequences through localization and predicts the amplitude of echo. The proposed method realizes high-resolution ultrasonic echo detection and performs well under severe overlapping, while it improves greatly the detection speed.
A Multi Perspective Access Control in a Smart Home

Existing methods to manage privileges in smart home systems have not considered allocating privileges to users based on (i) the relationship of the user with the device, (ii) the location and risk of the device and (iii) the current environment. In this work, we take a multi perspective view on the problem of sharing fine-grained privileges of IoT devices among multiple users in a smart home. We propose the concepts of user role (subset of privileges specific to each device), tasks and security levels (labels for each privilege) to allot right privileges to users. Thereby, limiting the exploitation of privileges assigned to legitimate insiders of the house. Thus, our work matches the aspirations of previous surveys on building a comprehensive access control system to manage privileges in a shared smart home.