Miracle-dz/UniFAR-FTUs huggingface dataset:
Integrated transcriptome and epigenome analyses identify alternative splicing as a novel candidate linking histone modifications to embryonic stem cell fate decision

Understanding embryonic stem cell (ESC) fate decision between self-renewal and proper differentiation is important for developmental biology and regenerative medicine. Attentions have focused on underlying mechanisms involving histone modifications (HMs), alternative pre-mRNA splicing (AS), and cell-cycle progression. However, their intricate interrelations and joint contributions to ESC fate decision remain unclear. We performed integrative analyses on transcriptomic and epigenomic data derived from human ESC (hESC) and five types of differentiated cells. We identified thousands of AS exons and revealed their development- and lineage-dependent characterizations. Following the observation that dynamic HM changes predominantly occur in AS exons upon hESCs differentiation, we identified 3 of 16 investigated HMs (H3K36me3, H3K27ac, and H4K8ac) that are strongly associated with 52.8% of hESC differentiation-related AS events. Further analyses showed that the HM-associated AS genes predominantly function in G2/M phases and ATM/ATR-mediated DNA damage response pathway for cell differentiation, whereas HM-unassociated AS genes enrich in G1 phase and pathways for self-renewal. These results imply a potential epigenetic mechanism by which some HMs contribute to ESC fate decision through the AS regulation of specific pathways and cell-cycle genes. We exemplified the potential mechanism by a cell cycle-related transcription factor, PBX1, which regulates the pluripotency regulatory network by binding to NANOG. We found that the isoform switch between PBX1a and PBX1b is strongly associated with H3K36me3 alteration and implicated in hESC fate determination. Supported by extended dataset from Roadmap/ENCODE projects, we identified the alternative splicing of PBX1 as a novel candidate linking H3K36me3 to embryonic stem cell fate decision.
A New Method for Mapping Aquatic Vegetation Especially Underwater Vegetation in Lake Ulansuhai Using GF-1 Satellite Data

It is difficult to accurately identify and extract bodies of water and underwater vegetation from satellite images using conventional vegetation indices, as the strong absorption of water weakens the spectral feature of high near-infrared (NIR) reflected by underwater vegetation in shallow lakes. This study used the shallow Lake Ulansuhai in the semi-arid region of China as a research site, and proposes a new concave–convex decision function to detect submerged aquatic vegetation (SAV) and identify bodies of water using Gao Fen 1 (GF-1) multi-spectral satellite images with a resolution of 16 meters acquired in July and August 2015. At the same time, emergent vegetation, “Huangtai algae bloom”, and SAV were classified simultaneously by a decision tree method. Through investigation and verification by field samples, classification accuracy in July and August was 92.17% and 91.79%, respectively, demonstrating that GF-1 data with four-day short revisit period and high spatial resolution can meet the standards of accuracy required by aquatic vegetation extraction. The results indicated that the concave–convex decision function is superior to traditional classification methods in distinguishing water and SAV, thus significantly improving SAV classification accuracy. The concave–convex decision function can be applied to waters with SAV coverage greater than 40% above 0.3 m and SAV coverage 40% above 0.1 m under 1.5 m transparency, which can provide new methods for the accurate extraction of SAV in other regions.
Land Cover Change in the Lower Yenisei River Using Dense Stacking of Landsat Imagery in Google Earth Engine

Climate warming is occurring at an unprecedented rate in the Arctic due to regional amplification, potentially accelerating land cover change. Measuring and monitoring land cover change utilizing optical remote sensing in the Arctic has been challenging due to persistent cloud and snow cover issues and the spectrally similar land cover types. Google Earth Engine (GEE) represents a powerful tool to efficiently investigate these changes using a large repository of available optical imagery. This work examines land cover change in the Lower Yenisei River region of arctic central Siberia and exemplifies the application of GEE using the random forest classification algorithm for Landsat dense stacks spanning the 32-year period from 1985 to 2017, referencing 1641 images in total. The semiautomated methodology presented here classifies the study area on a per-pixel basis utilizing the complete Landsat record available for the region by only drawing from minimally cloudand snow-affected pixels. Climatic changes observed within the study area’s natural environments show a statistically significant steady greening (~21,000 km2 transition from tundra to taiga) and a slight decrease (~700 km2) in the abundance of large lakes, indicative of substantial permafrost degradation. The results of this work provide an effective semiautomated classification strategy for remote sensing in permafrost regions and map products that can be applied to future regional environmental modeling of the Lower Yenisei River region.
Surface-Limited Electrodeposition of Continuous Platinum Networks on Highly Ordered Pyrolytic Graphite

Continuous thin platinum nanoplatelet networks and thin films were obtained on the flat surface of highly ordered pyrolytic graphite (HOPG) by high overpotential electrodeposition. By increasing the deposition time, the morphology of the Pt deposits can be progressively tuned from isolated nanoplatelets, interconnected nanostructures, and thin large flat islands. The deposition is surface-limited and the thickness of the deposits, equivalent to 5 to 12 Pt monolayers, is not time dependent. The presence of Pt (111) facets is confirmed by High Resolution Transmission Electron Microscopy (HRTEM) and evidence for the early formation of a platinum monolayer is provided by Scanning Transmission Electron Microscopy and Energy Dispersive X-rays Spectroscopy (STEM-EDX) and X-ray Photoelectron Spectroscopy (XPS) analysis. The electroactivity towards the oxygen reduction reaction of the 2D deposits is also assessed, demonstrating their great potential in energy conversion devices where ultra-low loading of Pt via extended surfaces is a reliable strategy.
De invloed van cultuur : verzuim en WAO-intrede

Het is al langer bekend dat een organisatiecultuur van grote invloed kan zijn op het verzuim. Dit blijkt ook uit een recent onderzoek naar de aanpak van preventie, verzuim en reintegratie in de sector zorg en welzijn. Het probleem van het verzuim en de hoge WAO-instroom van medewerkers in de zorg, met name vrouwen, is dan ook complex. Ruim de helft van de grotere kans op arbeidsongeschiktheid van vrouwen is te wijten aan de arbeidsomstandigheden. Minder grijpbare factoren spelen echter ook een rol. Dan gaat het om opvattingen van de vrouwen zelf, hun sociale omgeving, artsen, arbeidsdeskundigen en werkgevers.
Online scheduling of deadline‐constrained bag‐of‐task workloads on hybrid clouds

The advent of hybrid cloud technologies and public Infrastructures as a Service (IaaS) allows service developers to offer services to their customers with little upfront investment and to adapt services to different workload sizes. The problem of minimizing the costs of the hired public infrastructure while providing the quality of service needed by the final customer arises when using hybrid clouds. Several scheduling strategies have been proposed to solve this problem for services dealing with deadline‐constrained bag‐of‐tasks workloads. Most of these solutions do not consider the variable performance of the clouds, the provisioning delay of virtual machine instances that affects the elasticity, and the impracticality of having good processing time estimations in real systems. We propose a scheduler algorithm that overcomes previous limitations and can minimize the cost of the infrastructure while maximizing the number of deadlines met by the service. Our solution can work autonomously by using sampled observations of the processing times and considers the heterogeneity and the provisioning time of the virtual machine instances. An evaluation was conducted by simulating different scenarios and workload types. Simulation results show that our solution obtains better or similar results than previous techniques in most scenarios in terms of deadlines met.
Reward-Based Exploration: Adaptive Control for Deep Reinforcement Learning

Aiming at the contradiction between exploration and exploitation in deep reinforcement learning, this paper proposes “rewardbased exploration strategy combined with Softmax action selection” (RBESoftmax) as a dynamic exploration strategy to guide the agent to learn. The superiority of the proposed method is that the characteristic of agent’s learning process is utilized to adapt exploration parameters online, and the agent is able to select potential optimal action more effectively. The proposed method is evaluated in discrete and continuous control tasks on OpenAI Gym, and the empirical evaluation results show that RBE-Softmax method leads to statistically-significant improvement in the performance of deep reinforcement learning algorithms. key words: deep reinforcement learning, reward, exploration, exploitation
Oral health‐related quality of life and standard of treatment in aggressive periodontitis patients more than 5 years after therapy

OBJECTIVES To assess OHRQoL in patients with aggressive periodontitis (AgP) after periodontal treatment using the Oral Health Impact Profile-49 (OHIP-49) and compare to patients' dental status. MATERIAL AND METHODS More than 5 years after therapy, 71 patients were examined and answered the OHIP-questionnaire. The dental and periodontal status were assessed according to the SSO (Swiss Dental Society) criteria. Descriptive statistics were performed with SPSS, correlation analysis and tests for differences using R 3.2. 2. RESULTS More than 90% of all patients showed no probing depths (PD) >5 mm, a bleeding on probing (BOP) index below 35%, and a sufficient function. Four patients showed no visible plaque, PDs ≤ 3 mm, a BOP below 10%, and an optimum function. Non-smoking and compliant patients exhibited a more favourable status. The OHIP-49 added up to 24.9 points, representing a comparatively high satisfaction of AgP-patients with their oral status. The subscale which most patients reported impairment in was "functional limitation. " A correlation between quality standard and the OHIP-49G could only be shown in the psychological disability subscale. CONCLUSION After treatment, a moderate to high quality level can be retained over more than 5 years. Most patients are satisfied with their oral health. Correlations between the objective and subjective view could not be found, apart from the subscale "psychological disability. "
Targeted Gene Panel Sequencing for Molecular Diagnosis of Kallmann Syndrome and Normosmic Idiopathic Hypogonadotropic Hypogonadism.

BACKGROUND Isolated gonadotropin-releasing hormone (GnRH) deficiency (IGD) is classified either as Kallmann syndrome (KS) with anosmia or normosmic idiopathic hypogonadotropic hypogonadism (nIHH) and caused by mutations in more than 30 different genes. Recent advances in next-generation sequencing technologies have revolutionized the identification of causative genes by using massively parallel sequencing of multiple samples. This study was performed to establish the genetic etiology of IGD using a targeted gene panel sequencing of 69 known human IGD genes. METHODS This study included 28 patients with IGD from 27 independent families. Exomes were captured using customized SureSelect kit (Agilent Technologies) and sequenced on the Miseq platform (Illumina, Inc.), which includes a 163,269 bp region spanning 69 genes. RESULTS Four pathogenic and six likely pathogenic sequence variants were identified in 11 patients from 10 of the 27 families (37%) included in the study. We identified two known pathogenic mutations in CHD7 and PROKR2 from two male patients (7.4%). Novel sequence variants were also identified in 10 probands (37%) in CHD7, SOX3, ANOS1, FGFR1, and TACR3. Of these, while eight variants (29.6%) were presumed to be pathogenic or likely pathogenic, the remaining two were classified as variants of uncertain significance. Of the two pre-pubertal males with anosmia, one harbored a novel heterozygous splice site variant in FGFR1. CONCLUSIONS The overall diagnostic yield was 37% of the patients who had undergone targeted gene panel sequencing. This approach enables rapid, cost-effective, and comprehensive genetic screening in patients with KS and nIHH.
Composition, Structure and Morphology Evolution of Octadecylamine (ODA)–Reduced Graphene Oxide and Its Dispersion Stability under Different Reaction Conditions

Octadecylamine (ODA) can solve the aggregation problem of graphene sheets in the chemical exfoliation method. However, no attempts have been made to investigate the evolution of ODA–reduced graphene oxide (ORGO) with reaction conditions and the modification mechanism, which is the core problem to realize the controllable production and practical application of graphene. In this study, we treated graphene oxide (GO) with ODA under different reaction conditions to prepare ORGO. Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy, atomic force microscopy, Raman spectroscopy, thermogravimetric analysis (TGA), and UV–vis spectrophotometry were employed to analyze the composition, structure, morphology and characteristics of the as–prepared graphene sheets. The results showed that the reduction reaction could occur under mild conditions, but the edge grafting reaction could only be activated by a higher temperature. Moreover, the ORGO created at 80 °C for 5 h and 120 °C for 0.5 h exhibited the optimized properties, both excellent dispersing stability and high heat resisting property, since they had more edge grafting chains and a suitable reduction degree.
The Broker Queue: A Fast, Linearizable FIFO Queue for Fine-Granular Work Distribution on the GPU

Harnessing the power of massively parallel devices like the graphics processing unit (GPU) is difficult for algorithms that show dynamic or inhomogeneous workloads. To achieve high performance, such advanced algorithms require scalable, concurrent queues to collect and distribute work. We show that previous queuing approaches are unfit for this task, as they either (1) do not work well in a massively parallel environment, or (2) obstruct the use of individual threads on top of single-instruction-multiple-data (SIMD) cores, or (3) block during access, thus prohibiting multi-queue setups. With these issues in mind, we present the Broker Queue, a highly efficient, fully linearizable FIFO queue for fine-granular parallel work distribution on the GPU. We evaluate its performance and usability on modern GPU models against a wide range of existing algorithms. The Broker Queue is up to three orders of magnitude faster than nonblocking queues and can even outperform significantly simpler techniques that lack desired properties for fine-granular work distribution.
Electronic structures and unusually robust bandgap in an ultrahigh-mobility layered oxide semiconductor, Bi2O2Se

A new layered oxide semiconductor (Bi2O2Se) is found with excellent electronic properties for promising applications. Semiconductors are essential materials that affect our everyday life in the modern world. Two-dimensional semiconductors with high mobility and moderate bandgap are particularly attractive today because of their potential application in fast, low-power, and ultrasmall/thin electronic devices. We investigate the electronic structures of a new layered air-stable oxide semiconductor, Bi2O2Se, with ultrahigh mobility (~2.8 × 105 cm2/V⋅s at 2.0 K) and moderate bandgap (~0.8 eV). Combining angle-resolved photoemission spectroscopy and scanning tunneling microscopy, we mapped out the complete band structures of Bi2O2Se with key parameters (for example, effective mass, Fermi velocity, and bandgap). The unusual spatial uniformity of the bandgap without undesired in-gap states on the sample surface with up to ~50% defects makes Bi2O2Se an ideal semiconductor for future electronic applications. In addition, the structural compatibility between Bi2O2Se and interesting perovskite oxides (for example, cuprate high–transition temperature superconductors and commonly used substrate material SrTiO3) further makes heterostructures between Bi2O2Se and these oxides possible platforms for realizing novel physical phenomena, such as topological superconductivity, Josephson junction field-effect transistor, new superconducting optoelectronics, and novel lasers.
Enhancing security of NVM-based main memory with dynamic Feistel network mapping

As promising alternatives in building future main memory systems, emerging non-volatile memory (NVM) technologies can increase memory capacity in a cost-effective and power-efficient way. However, NVM is facing security threats due to its limited write endurance: a malicious adversary can wear out the cells and cause the NVM system to fail quickly. To address this issue, several wear-leveling schemes have been proposed to evenly distribute write traffic in a security-aware manner. In this study, we present a new type of timing attack, remapping timing attack (RTA), based on information leakage from the remapping latency difference in NVM. Our analysis and experimental results show that RTA can cause three of the latest wear-leveling schemes (i.e., region-based start-gap, security refresh, and multi-way wear leveling) to lose their effectiveness in several days (even minutes), causing failure of NVM. To defend against such an attack, we further propose a novel wear-leveling scheme called the ‘security region-based start-gap (security RBSG)’, which is a two-stage strategy using a dynamic Feistel network to enhance the simple start-gap wear leveling with level-adjustable security assurance. The theoretical analysis and evaluation results show that the proposed security RBSG not only performs well when facing traditional malicious attacks, but also better defends against RTA.
Nicotine modulates human brain plasticity via calcium‐dependent mechanisms

Nicotine (NIC) modulates cognition and memory function by targeting the nicotinic ACh receptor and releasing different transmitter systems postsynaptically. With both NIC‐generated mechanisms, calcium influx and calcium permeability can be regulated, which is a key requirement for the induction of long‐term potentiation, comprising the physiological basis of learning and memory function. We attempt to unmask the underlying mechanism of nicotinic effects on anodal transcranial direct current stimulation (tDCS)‐induced long‐term potentiation‐like plasticity based on the hypothesis of calcium‐dependency. Abolished tDCS‐induced neuroplasticity as a result of NIC administration is reversed by calcium channel blockade with flunarizine in a dose‐dependent manner. The results of the present study suggest that there is a dose determination of NIC/NIC agonists in therapeutical settings when treating cognitive dysfunction, which partially explains the heterogeneous results on cognition observed in subjects in different experimental settings.
Classification-Driven Search for Effective SM Partitioning in Multitasking GPUs

Graphics processing units (GPUs) feature an increasing number of streaming multiprocessors (SMs) with each successive generation. At the same time, GPUs are increasingly widely adopted in cloud services and data centers to accelerate general-purpose workloads. Running multiple applications on a GPU in such environments requires effective multitasking support. Spatial multitasking in which independent applications co-execute on different sets of SMs is a promising solution to share GPU resources. Unfortunately, how to effectively partition SMs is an open problem. In this paper, we observe that compared to widely-used even partitioning, dynamic SM partitioning based on the characteristics of the co-executing applications can significantly improve performance and power efficiency. Unfortunately finding an effective SM partition is challenging because the number of possible combinations increases exponentially with the number of SMs and co-executing applications. Through offline analysis, we find that first classifying workloads, and then searching an effective SM partition based on the workload characteristics can significantly reduce the search space, making dynamic SM partitioning tractable. Based on these insights, we propose Classification-Driven search (CD-search) for low-overhead dynamic SM partitioning in multitasking GPUs. CD-search first classifies workloads using a novel off-SM bandwidth model, after which it enters the performance mode or power mode depending on the workload's characteristics. Both modes follow a specific search strategy to quickly determine the optimum SM partition. Our evaluation shows that CD-search improves system throughput by 10.4% on average (and up to 62.9%) over even partitioning for workloads that are classified for the performance mode. For workloads classified for the power mode, CD-search reduces power consumption by 25% on average (and up to 41.2%). CD-search incurs limited runtime overhead.
Smartphone passcode prediction

Many people now own smartphones and store all their documents such as pictures and financial statements on their phone. To protect this sensitive information, people generally use a passcode to prevent unauthorised access to their phone. Shoulder-surfing attacks are well known. However, contrary to common belief, they are not easy to carry out. Shoulder-surfing attacks to predict the passcode by humans are shown to not be accurate. The authors thus propose an automated algorithm to accurately predict the passcode entered by a victim on her smartphone by recording the video. Their proposed algorithm is able to predict over 92% of numbers entered in fewer than 75 s with training performed once.
Microfluidic-Based Single-Cell Study: Current Status and Future Perspective

Investigation of cell behavior under different environments and manual operations can give information in specific cellular processes. Among all cell-based analysis, single-cell study occupies a peculiar position, while it can avoid the interaction effect within cell groups and provide more precise information. Microfluidic devices have played an increasingly important role in the field of single-cell study owing to their advantages: high efficiency, easy operation, and low cost. In this review, the applications of polymer-based microfluidics on cell manipulation, cell treatment, and cell analysis at single-cell level are detailed summarized. Moreover, three mainly types of manufacturing methods, i.e., replication, photodefining, and soft lithography methods for polymer-based microfluidics are also discussed.