Miracle-dz/UniFAR-FTUs huggingface dataset:
ImmCellTyper: an integrated computational pipeline for systematic mining of Mass Cytometry data to assist deep immune profiling

Mass cytometry, also known as Cytometry by time-of-flight (CyTOF), is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level. This technology significantly advances clinical research in immune monitoring and the interrogation of immune cell populations. Nevertheless, the vast amount of data generated by CyTOF poses a daunting challenge for analysis. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel and robust toolkit designed for CyTOF data analysis. The analytical framework incorporates an in-house developed semi-supervised clustering tool named BinaryClust, which first characterises main cell lineages, followed by in-depth interrogation for population of interest using unsupervised methods. BinaryClust was benchmarked with existing clustering tools and demonstrated superior accuracy and speed across two datasets comprising around 4 million cells, performing as good as manual gating by human experts. Furthermore, this computational pipeline provides a variety of visualization and analytical tools spanning from quality control to differential analysis, which can be tailored to user’s specific needs, aiming to provide a one-stop solution for CyTOF data analysis. The general workflow consists of five key steps: 1) Batch effect evaluation and correction, 2) Data quality control and pre-processing, 3) Main cell lineage characterisation and quantification, 4) Extraction and in-depth investigation of cell type of interest; 5) Differential analysis of cell abundance and functional marker expression (supporting multiple study groups). Overall, ImmCellTyper integrates expert’s biological knowledge in a semi-supervised fashion to accurately deconvolute well-defined main cell lineages, while also preserving the potential of unsupervised approaches to discover novel cell subsets and providing a user-friendly toolset to remove the analytical barrier for high-dimensional immune profiling.
MCLand: A Python program for drawing emerging shapes of Waddington’s epigenetic landscape by Monte Carlo simulations

Waddington’s epigenetic landscape is a powerful metaphor for illustrating the process of cell differentiation. Recently, it has been used to model cancer progression and stem cell reprogramming. User-friendly software for landscape quantification and visualization is needed to allow more modeling researchers to benefit from this theory. Results We present MCLand, a Python program for plotting Waddington’s epigenetic landscape with a user-friendly graphical user interface. It models gene regulatory network (GRN) in ordinary differential equations (ODEs), and uses a Monte Carlo method to estimate the probability distribution of cell states from simulated time-course trajectories to quantify the landscape. Monte Carlo method has been tested on a few GRN models with biologically meaningful results. MCLand shows better intermediate details of kinetic path in Waddington’s landscape compared to the state-of-the-art software Netland. Availability and implementation The source code and user manual of MCLand can be downloaded from https://mcland-ntu.github. io/MCLand/index.html.
An Alternative Scaling Method for Cross-Validation of Land Surface Temperature from Remote Sensing Data: A Case Study of Fars Province

Land surface temperature (LST) is one of the key parameters in a wide range of geosciences and environmental studies. Remote sensing technology, can monitor the space and time variations of this quantity in large areas. But evaluating the accuracy of this parameter is the most challenging issues. On the one hand, rapid changes in temperature occur in space and time and the mismatch between the spatial scale of satellite and ground-based sensors, validation of LST is difficult by ground based temperature data. In addition to the validation of the LST with ground data, three other methods are generally considered to validate LST values retrieved from space: the radiance-based method, the indirect validation method, and the cross-validation method. Among these methods, Due to development of thermal sensors, cross-validation procedure is the most common method to evaluate the accuracy of surface temperature. Due to the large spatial and temporal variations in the LST, geographic coordinate matching, time matching, and view zenith angle matching are basic requirements of the cross-validation. In this paper, an alternative scaling method was proposed for cross-validation between LST product of LDCM and MODIS sensors. Because of the wide coverage and taken LST product twice per day by each of the MODIS sensors (Terra and Aqua), this product was selected as the reference temperature. The LST products of MODIS sensors have been validated with in situ measurements and by various methods in more than 50 clear-sky cases taking into account the higher accuracies within 1 °K for both Terra and Aqua. The results of the proposed method showed that evaluation of LST accuracy in areas with high homogeneity and in the first examined LDCM scene, in terms of mean differences and mean absolute differences measures, is 0.6 °K and 1.63 °K, respectively. For the second examined LDCM scene, the accuracy measures were 0.94 °K and 1.27 °K in the LST, respectively. Generally, the experimental results on two LDCM data demonstrated that the proposed cross-validation method not only is a robust and accurate LST validation approach, but also it is applicable for each thermal sensor and every time and place.
Measurement of Lead in Seawater using Gold Nanoparticles Modified Screen Printed Carbon Electrode

ABSTRACT Lee, Y. -G. and Jang, A. , 2017. Measurement of lead in seawater using gold nanoparticles modified screen-printed carbon electrode. In: Lee, J.L. ; Griffiths, T. ; Lotan, A. ; Suh, K. -S. , and Lee, J. (eds.), The 2nd International Water Safety Symposium. Journal of Coastal Research, Special Issue No. 79, pp. 45–49. Coconut Creek (Florida), ISSN 0749-0208. Due to their low detection limits, various types of spectrometry techniques have been used for determining lead [Pb(II)] in water. However, these methods are not applicable for the on-site measurements of Pb(II) since the equipment is too bulky and skilled laboratory staff are needed. In this study, coastal water samples were collected from different sites close to two coastal industrial complexes in Korea. Their Pb(II) concentrations were determined using electrodeposited gold nanoparticles (AuNPs) on a disposable screen-printed carbon electrode. Square wave anodic stripping voltammetry was used to enhance the sensitivity of the Pb(II) detection level with less than 5 μg/L. The square wave anodic stripping voltammetric response for high sensitivity was 0.018 μA/μg/L, the Pb(II) concentration range was 2 to 500 μg/L at the deposition time of 180 s, and the detection limit was 4.4 μg/L with good selectivity. These results indicate that there was no significant difference between our sensor and the conventional spectrometry method in precision and accuracy. The AuNPs based sensor demonstrated long-term stability for up to 7 days while being used in the continuous monitoring of 100 μg/L Pb(II) in seawater. An RSD value of 2.7% was obtained, and the sensor retained 93% of its initial activity after 7 days.
Charcoal Briquette Production from Peanut ( Arachis hypogaea L. ) Shells using Cornick Industry Wastewater as Binder through a Torrefaction Process

The torrefaction process was applied to the peanut shells to produce charcoal briquette using Cornick industry wastewater as a binder and a charcoal briquetting press. The results showed that the conversion of peanut shell to biochar was 30.1 wt. %. The density and heating values of the three treatments with charcoal to binder ratio of 80:20 (T1), 75:25 (T2), and 70:30 (T3) were from 0.4623 g/cm 3 to 0.4990 g/cm 3 , from 26.6 MJ/kg to 27.3 MJ/kg. The samples of the peanut charcoal briquette were subjected to proximate analysis and ultimate analysis. For the proximate analysis, the moisture content was from 1.88 wt. % to 2.13 wt. %, the volatile matter was from 8.37 wt. % to 8.82 wt. %, ash content was from 6.61 wt. % to 7.34 wt. % and the fixed carbon was from 81.9 wt. % to 83.1 wt. %. Results of the ultimate analysis showed that the content of C, H, O, and S was as follows; 71.6 wt. % to 72.6 wt. %, 2.28 wt. % to 2.40 wt. %, 24.6 wt. % to 25.7 wt. %, and 0.3078 wt. % to 0.4144 wt. %. The characteristics of the charcoal briquettes derived from peanut shells and Cornick wastewater as a binder were compared to the standards for charcoal briquettes used in grilling, cooking, and for electricity generation. The abundance of locally available raw material in the production of charcoal briquette could provide employment to the unemployed individual in the locality. The characteristics of the charcoal briquettes produced demonstrated that it can be used for grilling, cooking, and electricity generation.
Trust and Online Privacy Concerns in a General Population of Internet Users

Even though research on online privacy has been accumulating for the last two decades, the etiology of online privacy concerns is still open to more inquiry. The present study investigates whether and to what extent online privacy concerns are affected by trust, a variable that has received limited dedicated attention in this respect. Using data from a telephone survey of a representative sample of the general population of Internet users in a Mediterranean society, the study models trust in people and trust in institutions as the focal predictors of Internet users’ concerns about online privacy violations by other people, corporations, and governments. Five hypotheses are tested using multiple regression equations with several controls, including measures of offline and online social capital, digital literacy, length of Internet use, and privacy violation experience. The study concludes that trust, independently and consistently, albeit mildly, reduces online privacy concerns.
TECHNOLOGICAL FRAUDS AND MILK ADULTERATIONS: A REVIEW

The milk consumption has increased constantly, with milk being part of the diet of a large proportion of the global population. As a result of this growing demand, the increased competition in the dairy market and the increasing complexity of the supply chain, the producers in the sector of milk and dairy products resort to technological fraud, which is considered to be a predominant problem in countries without a specific legislation. Therefore, this paper aims to review the main adulterants, the counterfeiting techniques and various methods of detecting counterfeiting.
Two-Face: Combining Collective and One-Sided Communication for Efficient Distributed SpMM

Sparse matrix dense matrix multiplication (SpMM) is commonly used in applications ranging from scientific computing to graph neural networks. Typically, when SpMM is executed in a distributed platform, communication costs dominate. Such costs depend on how communication is scheduled. If it is scheduled in a sparsity-unaware manner, such as with collectives, execution is often inefficient due to unnecessary data transfers. On the other hand, if communication is scheduled in a fine-grained sparsity-aware manner, communicating only the necessary data, execution can also be inefficient due to high software overhead. We observe that individual sparse matrices often contain regions that are denser and regions that are sparser. Based on this observation, we develop a model that partitions communication into sparsity-unaware and sparsity-aware components. Leveraging the partition, we develop a new algorithm that performs collective communication for the denser regions, and fine-grained, one-sided communication for the sparser regions. We call the algorithm Two-Face . We show that Two-Face attains an average speedup of 2.11x over prior work when evaluated on a 4096-core supercomputer. Additionally, Two-Face scales well with the machine size. CCS Concepts: • Computing methodologies → Distributed algorithms .
Research on the Modeling of Automatic Pricing and Replenishment Strategies for Perishable Goods with Time-Varying Deterioration Rates

This paper focuses on the modeling of automatic pricing and replenishment strategies for perishable products with time-varying deterioration rates based on an improved SVR-LSTM-ARIMA hybrid model. This research aims to support supermarkets in planning future strategies, optimizing category structure, reducing loss rates, and improving profit margins and service quality. Specifically, the paper selects perishable vegetables as the research category and calculates the cost-plus ratio for each vegetable category. Correlation analysis is conducted with total sales, and a non-parametric relationship curve is obtained using support vector regression for nonlinear fitting. The long and short memory recurrent neural network is then used to predict sales volume, and a pricing strategy is calculated based on the fitting curve. Additionally, the paper establishes a correlation between loss rate and shelf life, corrects the daily average sales volume index, and solves the problem of quantity and category of replenishment using a backpack problem approach. By considering multiple constraints, a quantitative category replenishment volume and pricing strategy is obtained. The mathematical model proposed in this paper addresses the replenishment and pricing challenges faced by supermarkets, aiming to improve revenue and reduce loss while meeting market requirements.
Climatic requirements for mangroves: what does ecological niche modelling reveal? – Preliminary results

Mangroves are forests in the intertidal zone along (sub)tropical coastlines. This vulnerable ecosystem is under threat of increasing coastal human population and land-use changes. Global warming has a major impact on the mangrove distribution as sea level is rising and the position of the intertidal zones is moving landwards. Next to this, an increase of temperature creates the possibility for mangroves to move polewards beyond their current distribution. By investigating the temperature at the mangrove latitudinal range limits, we found that (1) there is not one isotherm that coincides with mangrove latitudinal limits: monthly air and sea surface temperature are highly variable among congeneric mangrove limits, (2) the larger distribution of the genus Avicennia compared to the genus Rhizophora is reflected in the temperature requirements: Avicennia limits are colder than Rhizophora limits (Quisthoudt et al., submitted).
ON INFORMATICS VISUALIZATION

— Event-predicate-based storyline extraction results in a chronologically ordered activity journal. The extraction results contain complex human activities, so the activity journal requires a visualization model to describe actor interactions. This paper proposes a chart to visualize the activities' flow to describe the characters' interactions in an activity journal. This chart is called a storychart. Storycharts have an actor channel that can accept single entities or teams. The actor channel allows changing the type from single to a team or vice versa and moving members to other teams. The activity channel serves as a connector to accommodate interactions between actors. The activity channel provides a visual space for the elements of what, where, and when. Event predicates are the core of what. Therefore, the storychart visualizes the event predicate using glyphs to attract the reader’s attention. The main contribution of this paper is to introduce a team channel that can visualize the identity of team members and an activity channel that can visualize the details of events. We invited participants to discover the reader’s perception of the ease of team recognition and the integrity of the meaning of the narrative visualized by the storychart. Participants involved in the evaluation were filtered by literacy score. Evaluation of storychart reading showed that readers could easily distinguish teams from single actors, and storycharts could convey the story in the activity journal with little reduction in meaning.
Selection of Surgical Treatment Pathways for Carcinoma of the Root of the Tongue and Discussion of Their Advantages and Disadvantages

: Tongue root cancer is a great challenge for surgeons, and its treatment is still controversial, and surgical treatment is still one of the main therapeutic options. Tongue root cancer belongs to the category of oropharyngeal cancer and accounts for 40% of oropharyngeal cancers. In recent years, an increase in the global prevalence of tongue root cancer due to HPV infection has brought tongue root cancer back into the limelight. The tongue plays an important role in swallowing and speech, etc. The location of the root of the tongue is hidden, and surgical access to this area is difficult. The commonly used surgical pathways for tongue root cancer include transoral approach, transmandibular approach and prepharyngeal incision approach. Different surgical pathways have their own characteristics, this article reviews the surgical methods of different approaches for tongue root cancer and their respective advantages and disadvantages as well as the scope of application, with the aim of providing a reference for the selection of surgical treatment pathways for tongue root cancer
Electric Cable Insulator Damage Monitoring by Lasso Regression

Since the discovery of electricity, electric cables have become ubiquitous in human constructions, from machines to buildings. Insulators play a crucial role in ensuring the proper functioning of these cables, so it is important to monitor their possible damage, which can be caused by environmental contamination, severe temperature variations, and electrical and mechanical stress. While shunt conductance is a direct health indicator of cable insulation, measuring the cable average shunt conductance is not sufficient for the detection of localized insulator damage, since localized conductance variations are diluted over a long cable length in such measurements. The objective of this paper is to assess the feasibility of reflectometry techniques for the monitoring of insulator damage in electric cables. To this end, the estimation of localized conductance variations is investigated based on electrical measurements made at one end of a cable. To avoid estimating a large number of discretized conductance values along a long cable, the proposed method relies on sparse regression, which automatically focuses on localized conductance variations at unknown positions caused by accidental insulator damage. In order to efficiently apply sparse regression techniques, the telegrapher’s equations describing electric wave propagation in cables are transformed through several steps into a simple linear regression form. Then, Lasso (Least Absolute Shrinkage and Selection Operator) regression is applied to process the voltage and current data collected at a single end of the monitored cable. Numerical simulations show the potential of this method for fast estimation of localized shunt conductance variations.
biomarker of lipogenesis and has links to inflammation and immunity. In macrophages, FABP4 regulates inflammatory responses through the IKK Regulation of Chicken FABP4 Transcription by Toll-Like Receptor 3 Activation in DF-1 Cells

Long-chain fatty acids (LCFAs) are vital in cellular compartments, primarily regulating lipid metabolism. Fatty Acid-Binding Proteins (FABPs) facilitate LCFA transport, lipid synthesis, storage, and act as signaling molecules influencing various pathways, including inflammation. FABP4, in particular, is linked to vascular and cardio-related diseases, and it plays a role in macrophage-mediated inflammatory responses. Previous studies have identified FABP4 as not only a representative biomarker for lipogenesis but also as having correlations with immune responses. This study aims to investigate the regulation of the chicken FABP4 ( chFABP4 ) gene by toll-like receptor 3 (TLR3) activation and determine the signaling pathways that are involved in chFABP4 transcriptional regulation. We analyzed the transcriptional regulation of chFABP4 in TLR3-stimulated DF-1 cells. The results showed that chFABP4 was up-regulated upon stimulation with polyinosinic-polycytidylic acid (PIC), a TLR3 ligand. Notably, chFABP4 transcription was independently regulated in the NF-κ B signaling pathway. It was up-regulated in p38 inhibition, demonstrating that the p38 signaling pathway might suppress the transcription of chFABP4 within TLR3-activated DF-1 cells. In contrast, chFABP 4 expression was down-regulated in JNK signaling pathway inhibition, suggesting the positive regulation of JNK signaling pathway for chFABP4 transcription in DF-1 cells in response to TLR3 activation, consistent with findings in macrophages. MEK pathway inhibition resulted in a similar regulation to NF-κ B signaling. These results suggest that each MAPK contributes differentially to the transcriptional regulation of chFABP4 by in DF-1 cells in response to TLR3 activation.
The Exxon Factor: The Roles of Corporate and Academic Science in the Emergence and Legitimation of a New Global Model of Sequence Stratigraphy

In the 1970s, a paradigm shift took place in petroleum exploration with the development, within Exxon's research laboratories, of a new model for oil exploration based on seismic stratigraphy and global sea level change. We demonstrate that this approach was widely accepted by the academic and petroleum geology communities outside Exxon in the absence of data, replication, or independent peer review. We attribute this acceptance to the “Exxon Factor”, that is, others” perceptions of Exxon's reputational capital and control over the material means of scientific production. We further demonstrate that the model's legitimacy was not accepted within Exxon, where it was developed, until after external legitimation took place. Using Strauss's social worlds/arena analysis, concepts of technoscience, disciplines, and the new knowledge studies, and situational analysis, we consider elements and interactions in the situations in which this scientific knowledge was produced and assessed. We conclude that university and industry geologists validated the scientific knowledge of the other using nonscientific perceptions that they equated with scientific authority.
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"MIT CogNet is an important new venture that brings together many different resources for the cognitive and brain sciences. By bringing information directly to researchers and students and allowing rapid dissemination of important new research directions, CogNet bypasses the slow and expensive efforts in the commercial publishing world. A new model for how scientific publishing will look in the twenty-first century is already being tested today in CogNet~' Terrence J. Sejnowski, Professor, Salk Institute; Professor of Biology, University of California, San Diego; and Investigator, Howard Hughes Medical Institute
Aid Fragmentation and Development Outcomes in Sub-Saharan African Countries

This study examined the fragmentation of official development assistance (ODA) in Sub-Saharan African countries and the role played by development outcomes. Initially, it analyzed the fragmentation of aid over the period 2000 to 2019 using the Theil index. On the donor side, it appears that fragmentation of aid from bilateral Development Assistance Committee (DAC) donors and bilateral non-DAC donors has decreased significantly in recent years. In addition, the aid provided by bilateral DAC donors has been less fragmented than that given by non-DAC bilateral donors. Several traditional donors and so-called