Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning dynamics by computational integration of single cell genomic and lineage information

A goal of single cell genome-wide profiling is to reconstruct dynamic transitions during cell differentiation, disease onset, and drug response. Single cell assays have recently been integrated with lineage tracing, a set of methods that identify cells of common ancestry to establish bona fide dynamic relationships between cell states. These integrated methods have revealed unappreciated cell dynamics, but their analysis faces recurrent challenges arising from noisy, dispersed lineage data. Here, we develop coherent, sparse optimization (CoSpar) as a robust computational approach to infer cell dynamics from single-cell genomics integrated with lineage tracing. CoSpar is robust to severe down-sampling and dispersion of lineage data, which enables simpler, lower-cost experimental designs and requires less calibration. In datasets representing hematopoiesis, reprogramming, and directed differentiation, CoSpar identifies fate biases not previously detected, predicting transcription factors and receptors implicated in fate choice. Documentation and detailed examples for common experimental designs are available at https://cospar.readthedocs. io/.
Editorial: Cell Signaling Mediating Critical Radiation Responses

Radiotherapy is an important loco-regional component of modern multimodal cancer therapy. Classically, radiobiology’s 5 Rs: repair, repopulation, redistribution, reoxygenation, and radiosensitivity, as described by Steele et al. (1) have informed the use of radiotherapy. The past several decades have filled in molecular mechanism by which the radiation response of cells and tissues affect tumor control, expanding our knowledge of survival pathways beyond repair of radiation damage to DNA (2). In many cases, these pathways receive cues from extracellular signaling molecules via membrane-bound receptors (3). This emphasizes the importance of both intraand extracellular signaling, and the interaction between different cell types in radiationinduced cell death as well as normal-tissue reaction after radiotherapy (4–6). The articles in the present Research Topic discuss recent progress and present original research on the contribution of cell signaling to radiation responses and radiation effects on cell signaling. Residual double-strand breaks and complex DNA lesions are considered lethal and characteristic for ionizing radiation although typically some 98% are repaired by non-homologous end joining (NHEJ; all cell-cycle phases) or homologous recombination (HR, which is restricted to late Sand G2 phase). While the yield of single-strand breaks and base damage is much higher, these lesions contribute little to cell killing under normal circumstances as they are repaired with very high efficiency by the base excision repair (BER) system, although some single strand breaks in S-phase may be converted to double-strand break at replication forks. If HR is compromised (e.g. by BRCA1 mutation), or overloaded, an error-prone backup mechanism, alternative end joining (alt-EJ) will repair the lesions. Liu et al. reviews the significant regulation of repair pathway choices by an extracellular cytokine, transforming growth factor (TGFb), whose activity is a prominent signal in the irradiated tumor. TGFb promotes HR and NHEJ but suppresses alt-EJ (7), and thus blocking TGFb signaling increases radiosensitivity. An intracellular route to shifting repair competency is reviewed by Starcher et al. who describe the rationale for using quinone substrates to induce futile redox cycles leading to oxidative damage, BER hyperactivation, and depletion of NAD+ and ATP, which synergizes with ionizing radiation to radiosensitize human cancer cells at moderate doses. The study by Shukla et al. explores the synergy of combining the quinone derivative, b-lapachone with inhibition of a mitochondrial enzyme involved in folate metabolism. Tumor hypoxia is well-recognize factor associated with resistance to radiotherapy and other therapies. The review by Sørensen and Horsman focuses on the hypoxia-inducible factor (HIF)
Salvaging complete and high-quality genomes of novel microbial species from a meromictic lake using a workflow combining long- and short-read sequencing platforms

Background Most of Earth’s bacteria have yet to be cultivated. The metabolic and functional potentials of these uncultivated microorganisms thus remain mysterious, and the metagenome-assembled genome (MAG) approach is the most robust method for uncovering these potentials. However, MAGs discovered by conventional metagenomic assembly and binning methods are usually highly fragmented genomes with heterogeneous sequence contamination, and this affects the accuracy and sensitivity of genomic analyses. Though the maturation of long-read sequencing technologies provides a good opportunity to fix the problem of highly fragmented MAGs as mentioned above, the method’s error-prone nature causes severe problems of long-read-alone metagenomics. Hence, methods are urgently needed to retrieve MAGs by a combination of both long- and short-read technologies to advance genome-centric metagenomics. Results In this study, we combined Illumina and Nanopore data to develop a new workflow to reconstruct 233 MAGs—six novel bacterial orders, 20 families, 66 genera, and 154 species—from Lake Shunet, a secluded meromictic lake in Siberia. Those new MAGs were underrepresented or undetectable in other MAGs studies using metagenomes from human or other common organisms or habitats. Using this newly developed workflow and strategy, the average N50 of reconstructed MAGs greatly increased 10–40-fold compared to when the conventional Illumina assembly and binning method were used. More importantly, six complete MAGs were recovered from our datasets, five of which belong to novel species. We used these as examples to demonstrate many novel and intriguing genomic characteristics discovered in these newly complete genomes and proved the importance of high-quality complete MAGs in microbial genomics and metagenomics studies. Conclusions The results show that it is feasible to apply our workflow with a few additional long reads to recover numerous complete and high-quality MAGs from short-read metagenomes of high microbial diversity environment samples. The unique features we identified from five complete genomes highlight the robustness of this method in genome-centric metagenomic research. The recovery of 154 novel species MAGs from a rarely explored lake greatly expands the current bacterial genome encyclopedia and broadens our knowledge by adding new genomic characteristics of bacteria. It demonstrates a strong need to recover MAGs from diverse unexplored habitats in the search for microbial dark matter.
Carbon dots decorated vertical SnS2 nanosheets for efficient photocatalytic oxygen evolution

Metal sulfides are highly desirable materials for photocatalytic water splitting because of their appropriate energy bands. However, the poor stability under light illumination in water hinders their wide applications. Here, two-dimensional SnS2 nanosheets, along with carbon dots of the size around 10 nm, are uniformly grown on fluorine doped tin oxide glasses with a layer of nickel nanoparticles. Significantly, strong light absorption and enhanced photocurrent density are achieved after integration of SnS2 nanosheets with carbon dots. Notably, the rate of oxygen evolution reached up to 1.1 mmol g−1 h−1 under simulated sunlight irradiation featuring a good stability.
Cell-type-specific silence in thalamocortical circuits precedes hippocampal sharp-wave ripples

Memory consolidation requires the encoding of neocortical memory traces, which is thought to occur during hippocampal oscillations called sharp-wave ripples (SWR). Evidence suggests that the hippocampus communicates memory-related neural patterns across distributed cortical circuits via its major output pathways. Here, we sought to understand how this information is processed in the retrosplenial cortex (RSC), a primary target circuit. Using patch-clamp recordings from mice during quiet wakefulness, we found that SWR-aligned synaptic modulation is widespread but weak, and that spiking responses are sparse. However, using cell type and projection-specific two-photon calcium imaging and optogenetics, we show that, starting 1-2 seconds before SWR, superficial inhibition in RSC is reduced, along with thalamocortical input. We propose that pyramidal dendrites experience a period of decreased local inhibition and subcortical interference in a seconds-long time window preceding hippocampal SWR. This may aid communication of weak and sparse SWR-aligned excitation between the hippocampus and neocortex, and promote the selective strengthening of memory-related connections.
Identification of the Resveratrol Potential Targets in the Treatment of Osteoarthritis

Objectives Osteoarthritis (OA) is a chronic joint degenerative disease and has become an important health problem for the elderly. However, there is still a lack of effective drugs for the treatment of OA. Our research combines bioinformatics and experimental strategies to determine the target of resveratrol for OA treatment. Methods First, the differentially expressed genes (DEGs) of OA joint tissues were obtained from the related microarray gene expression data. Second, resveratrol, a natural polyphenol compound, was used to screen the drug treatment target genes. Third, the drug-disease network was established, and the resveratrol target genes for OA treatment were obtained and verified through experimental verification. Results A total of 300 differentially expressed genes with 246 upregulated and 54 downregulated were found in OA joint tissues, and 310 resveratrol potential target genes were obtained. Finally, six genes, namely, CXCL1, HIF1A, IL-6, MMP3, NOX4, and PTGS2, were selected to validate the treatment effects of the resveratrol. The results showed that all six genes in human OA chondrocytes were significantly increased. In addition, in these chondrocytes, CXCL1, HIF1A, IL-6, MMP3, NOX4, and PTGS2 were reduced considerably, but HIF1A was significantly increased after resveratrol treatment. Conclusions Our data indicates that CXCL1, HIF1A, IL-6, MMP3, NOX4, and PTGS2 are all targets of resveratrol therapy. Our findings may provide valuable information for the mechanism and therapeutic of OA.
Corrigendum

In Weber and Talkner (1993) it is reported that the Gaussian correlation model exp(2au2) (u is the great circle distance) is not positive definite on the sphere for small values of a, but is positive definite for large values of a. This latter claim was based on the results of approximations of the spectral expansion of the correlation function. However, beyond the validity range of these approximations the spectral expansion coefficients may become negative for all values of a, thus demonstrating
History and Development of Permanent Magnets

The history of development of permanent magnets has been reviewed. The magnet began with the mineral magnetite (Fe3O4) or lodestone, was the first hard magnet known to man with Energy Product of about 1kJ/m 3 . The steps of development have been classified due to the type of materials used in the manufacturing of permanent magnets. The first type of steel magnets are those which were developed to reach (BH)max of about 8kJ/m 3 . A big jump in the energy product and coercivity occurred after the discovery of Rare Earth magnets. A (BH)max of around 474 kJ/m 3 has been achieved. A theoretical value of (BH)max of about 512kJ/m 3 for Nd2Fe14B hard Phase has been reported. A 93% of this theoretical value has been achieved so far. In addition, an idea about large scale applications of Nd-Fe-B magnets has been mentioned in this work. Furthermore, some recent developments in the field of permanent magnets have been summarized in this article.
An Exploration of Airline Sentimental Tweets with Different Classification Model

-In Twitter, the customer of airline services can tweet their opinions about their travelled experiences in flight. So Twitter contains massive amount of data and information regarding airline services. These tweets are collected and explored the sentiments about the airline services to track customer satisfaction reports and to discover location of the customer. The main aim of this paper is to analyze the twitter airline dataset for finding the best and the worst airlines and also to predict the most common issues occurred during the airline services. Then the word clouds of negative tweets are created and also the location of the negatively tweeted customer is predicted and visualized using geographical analysis. Finally training and testing was done on the dataset and also compared with seven different classifiers such as Logistic Regression classifier, KNeighbors classifier, SVC, Decision Tree classifier, Random Forest classifier, AdaBoost classifier and GaussianNB. The results of our experiments demonstrate that the Random forest approach works best in real-world practice on sentiment classification of tweet data.
Anatomy of contemporary GSM cellphone hardware

Billions of cell phones are being used every day by an almost equally large number of users. The majority of those phones are built according to the GSM protocol and interoperate with GSM networks of hundreds of carriers. Despite being an openly published international standard, the architecture of the GSM network and its associated protocols are only known to a relatively small group of R&D engineers. Even less public information exists about the hardware architecture of the actual mobile phones themselves, at least as far as it relates to that part of the phone implementing the GSM protocols and facilitating access to the public GSM networks. This paper is an attempt to serve as an introductory text into the hardware architecture of contemporary GSM mobile phone hardware anatomy. It is intended to widen the technical background on mobile phones within the IT community.
Classification Techniques to Enhance the Performance in Diagnosis of Alzheimer's Disease

A novel method is proposed for the Alzheimer's Disease (AD) conversion. Various relevant parameters are analyzed based on the feature selection, age factor, accurate prediction and the amount of training data. In accordance with the analysis of the above parameters, method. The proposed ADNI dataset achieves an area in global grading. The classification improves when age and cognitive methods are combined with proposed grading. Finally, the architectures classifying Pap Smear Images into broader classes that will define the exact precancerous stages could be developed for better clarity in medical diagnosis. The K-SVM classifier gives better accuracy of 96% than the other existing classifiers when compared to other models.
Risk Factors for the Development of High-risk Stigmata in Branch-duct Intraductal Papillary Mucinous Neoplasms

Objective Strict follow-up is recommended for branch-duct intraductal papillary mucinous neoplasms (BD-IPMNs) to avoid missing the development of high-risk stigmata (HRS) at a premalignant stage. This study explored the risk factors associated with the development of HRS during follow-up. Methods We performed a retrospective analysis of 283 patients with BD-IPMN, treated at Okayama University Hospital in Japan between January 2009 and December 2016. Only patients with imaging studies indicative of classical features of BD-IPMN without HRS and followed for over one year were included in the study. We performed radiological follow-up every six months and collected patients' demographic data, cyst characteristics, and clinical outcomes and used univariate logistic regression models to determine the odds of developing HRS. Results Ten patients (3.5%) developed HRS after a median surveillance period of 55.8 months. The main pancreatic duct (MPD) size (5-9 mm) and cyst growth rate (>2.5 mm/year) were both suggested to be possible risk factors for the development of HRS [odds ratio, 14.2; 95% confidence interval (CI), 3.1-65.2, p=0.0006, and odds ratio, 6.1; 95% CI 1.5-25.5, p=0.014]. Regarding the number of worrisome features (WFs), the rate of HRS development was 2.0% (4/199) in cases with no WF, 1.6% (1/62) in cases with single WF and 22.7% (5/22) in cases with multiple WFs, respectively. The rate of HRS development was significantly higher in cases with multiple WFs than in the other cases (p<0.0001). Conclusion MPD dilation, rapid cyst growth, and multiple WFs were significant risk factors for the development of HRS. In the presence of such features, it is necessary to closely follow the development of HRS and avoid missing the best opportunity to perform surgical intervention.
A Conceptual Model of Healthy Food Consumption Pattern among Malaysian Consumers

In economic studies the term ―consumption‖ are defined as purchased food, or some a form of sales data of analysis, relatively to actual dietary intake. Additionally, [4] Piana (2001) definition of consumption as ―the use by human individuals of goods and services to satisfy some of their needs and wants. ̳Goods and services‘ are often referred to as ̳commodities‘‖ and [5] Castellari (2016) defined consumption as ―any activity involving the selection, purchase, use, maintenance, repair and disposition of any product or service‖ as well as [6] (Boulanger, 2007).
What Causes Wrong Sentiment Classifications of Game Reviews?

Sentiment analysis is a popular technique to identify the sentiment of a piece of text. Several different domains have been targeted by sentiment analysis research, such as Twitter, movie reviews, and mobile app reviews. Although several techniques have been proposed, the performance of current sentiment analysis techniques is still far from acceptable, mainly when applied in domains on which they were not trained. In addition, the causes of wrong classifications are not clear. In this article, we study how sentiment analysis performs on game reviews. We first report the results of a large-scale empirical study on the performance of widely used sentiment classifiers on game reviews. Then, we investigate the root causes for the wrong classifications and quantify the impact of each cause on the overall performance. We study three existing classifiers: Stanford CoreNLP, NLTK, and SentiStrength. Our results show that most classifiers do not perform well on game reviews, with the best one being NLTK (with an AUC of 0.70). We also identified four main causes for wrong classifications, such as reviews that point out advantages and disadvantages of the game, which might confuse the classifier. The identified causes are not trivial to be resolved and we call upon sentiment analysis and game researchers and developers to prioritize a research agenda that investigates how the performance of sentiment analysis of game reviews can be improved, for instance by developing techniques that can automatically deal with specific game-related issues of reviews (e.g., reviews with advantages and disadvantages). Finally, we show that training sentiment classifiers on reviews that are stratified by the game genre is effective.
AI-Based Camera: Integrated Speech Recognition and Emotion Detection

— In the current scenario, Artificial Intelligence is emphasizing the development of intelligent machines. Considering the frequent use of web camera applications, there is a need for an enhanced and automated version of the application. Emotion Recognition also plays a crucial role in daily lives. An integrated solution of speech detection with the camera application is a great duo and handy to the user as well. In this paper, we present a method for accessing the camera to take an image and perform image processing using pre-trained voice commands. Additionally, the model also predicts the emotion of the user and produces speech output of the emotion recognized.
Follicular Ultrasound Image Segmentation based on Improved Deeplabv3

: The ultrasound image segmentation technique of yellow cattle follicles plays an important role in the monitoring of the dynamic changes of follicles in yellow cattle. With the development of deep learning, the image segmentation technology based on deep learning neural network model has made great breakthroughs, such as DeepLabv3, an end-to-end semantic segmentation network model. However, the above algorithm can’t meet the requirements of follicle segmentation in cattle follicle monitoring. Because of its deep network depth, multiple operational parameters, many iterations, and huge amount of computation, it has high requirements for the operating environment of the system (memory, CPU, GPU, etc.), and cannot be easily applied to the actual production practices. Therefore, an improved DeepLabv3 model was proposed in this paper. By removing the ASPP layer and moving the atrous convolution layer forward, the improved model is more suitable for the actual production of follicle segmentation, which is more in line with the economic cost of follicle monitoring. Finally, the experimental results show that the computational resources and the running time of the improved model decrease obviously when the average segmentation precision of follicular ultrasound image does not decrease significantly.
SAR to Optical Image Synthesis using Atrous Convolution in cGANs

—Optical images of satellites have to deal with un-controllable phenomena like cloud coverage, that affects the integrity of the data. An alternative to solve this problem in the remote sensing community is using data from active sensors like Synthetic Aperture Radar. Recently, the Conditional Generative Adversarial Networks (cGANs) have become a useful tool to generate images of one domain from another one, generally adopting as generator an encoder-decoder module with the underlying loss of feature spatial resolution. In this report, it is proposed the use of DeepLabv3 architecture to avoid this effect through atrous convolutions, and then generate more realistic cloud-free images from SAR ones. The results are still qualitative, but with an acceptable performance.