Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Requirements of Future Intelligent Networks: Solutions and Future Research Directions

The context of this study examines the requirements of Future Intelligent Networks (FIN), solutions, and current research directions through a survey technique. The background of this study is hinged on the applications of Machine Learning (ML) in the networking field. Through careful analysis of literature and real-world reports, we noted that ML has significantly expedited decision-making processes, enhanced intelligent automation, and helped resolve complex problems economically in different fields of life. Various researchers have also envisioned future networks incorporating intelligent functions and operations with ML. Several efforts have been made to automate individual functions and operations in the networking domain; however, most of the existing ML models proposed in the literature lack several vital requirements. Hence, this study aims to present a comprehensive summary of the requirements of FIN and propose a taxonomy of different network functionalities that needs to be equipped with ML techniques. The core objectives of this study are to provide a taxonomy of requirements envisioned for end-to-end FIN, relevant ML techniques, and their analysis to find research gaps, open issues, and future research directions. The real benefit of ML applications in any domain can only be ensured if intelligent capabilities cover all of its components. We observed that future generations of networks are heterogeneous, multi-vendor, and multidimensional, and ML can provide optimal results only if intelligent capabilities are used on a holistic scale. Realizing intelligence on a holistic scale is only possible if the ML algorithms can solve heterogeneous problems in a multi-vendor and multidimensional environment. ML models must be reliable and efficient, support, and possess the capability to learn and share the knowledge across the network layers and administrative domains to solve issues. First, this study ascertains the requirements of the FIN and proposes their taxonomy through reviews on envisioned ideas by various researchers and articles gathered from reputed conferences and standard developing organizations using keyword queries. Second, we have reviewed existing studies on ML applications focusing on coverage, heterogeneity, distributed architecture, and cross-domain knowledge learning and sharing. Our study observed that in the past, ML applications were focused mainly on an individual/isolated level only, and aspects of global and deep holistic learning with cross-layer/cross-domain knowledge sharing with agile ML operations are not explored at large. We recommend that the issues mentioned previously be addressed with improved ML architecture and agile operations and propose an ML pipeline based architecture for FIN. The significant contribution of this study is the impetus for researchers to seek ML models suitable for a modular, distributed, multi-domain, and multi-layer environment and provide decision making on a global or holistic rather than an individual function level.
A Novel Bci Paradigm Combining Visual Imagery and Emotion: A Pilot Study

Visual imagery (VI) has become a research hotspot with the development of brain-computer Interface (BCI). But it's very difficult to decode the electroencephalogram (EEG) during the VI task because of the lack of effective classification features. However, the classification of emotion-based EEG now can achieve a very high accuracy. We proposed a new BCI paradigm in which emotions would be integrated into VI to improve the performance. To verify the feasibility of our paradigm, we designed a two-session EEG acquisition experiment. We designed three kinds of emotions and three kinds of semantic correspondence i.e., negative animal, positive human and neutral thing. Sixteen subjects were asked to observe and imagine three pictures selected by subjects in visual observation (VO) and VI session, respectively. Then, we used power spectral density (PSD), common spatial pattern (CSP) and Riemann tangent space three features with SVM to analysis the EEG during three statements. The classification results show that the Riemann features obtain the highest average accuracies which are 84.36% and 67.36% for VO and VI, respectively. All the three types of features can exceed chance level on all the subjects. The results prove that our VI integrating emotion is a promising paradigm.
Design of Intelligent Monitoring System for the Life Safety of the Eldly

In order to solve the problems in elderly care service such as elderly health and safety monitoring difficulties caused by the aging of the population, based on the Internet of Things architecture, with the help of Internet of Things technologies such as sensor networks, embedded development, cloud computing and big data technology, a set of intelligent vital signs and safety monitoring system is designed for the elderly. The system uses a parallel ARM processor as the core, uses GPS, MEMS, cameras, and heart rate and blood oxygen sensors to combine functions such as vital signs collection, safety information monitoring, network data communication, intelligent gesture recognition, cloud visualization. At the same time, the system introduces intelligent algorithms to autonomously identify and judge the vital characteristics and safety information of the elderly based on reasonable preset thresholds. Experimental results show that the intelligent monitoring system for the life safety of the elderly designed in this paper can monitor vital signs and safety information around the clock, and can accurately monitor safety abnormal events and provide real-time alarms on the cloud and locality.
Numerical Investigation on the Influence of Tail Structure upon the Projectile

In this paper, projectile cases with different tail structure, slope angle of base cavity “α” (2°, 5°, 8°, 10°, 15°), which is equal to the boattail angle, are simulated. The rotatory Navier-Stokes equations with the k-ɛ turbulence model are used as a governing equation. Under the same flow conditions, flow field parameters of the projectile and the aerodynamic force were accquired. Analysis these numerical results, the slope angle of the base cavity and the boattail angle play a pivotal role for the aerodynamic force of each pellet. To aerodynamic drag, there is an optimal angle. For all cases in this paper, the case with the boattail angle α=8° gets the minimal drag coefficient.
The Effect of Digital Communication and Agile Leadership on Employee Work Motivation in a Pharmaceutical Distribution Company in a Pandemic

This study determines and analyzes the effect of digital communication and agile leadership from different generations on employee motivation in a pharmaceutical distribution company during the Covid-19 pandemic. This study has a sample of 164 employees of PT Enseval Putera Megatrading Tbk. Sampling was done through Stratified Random Sampling. Data were collected through observation, interviews, and questionnaires. The data were analyzed by PLS Algorithm analysis through the PLS-SEM program for windows. The results showed that digital communication technology and agile leadership style simultaneously significantly affected employee work motivation with a determination of 0.378 or 37.8%. Digital communication technology and intergenerational agile leadership style partially significantly affect employee work motivation. The dominant variable that influences employee work motivation is the Digital Communication variable. It is hoped that further research will need to consider other factors that affect employee work motivation, namely Digital Innovation, Flexible Working Hours, and the 80/20 Rule.
Detection of Abnormal Opacity on Chest CT Images Using A 3D-CNN

In recent years, the rate of deaths from cancer tends to increase in Japan. Especially the number of deaths from lung cancer is increasing. Computed tomography (CT) device is effective screening tool for early detection of lung cancer. Simultaneously, there is concern that an increase in burden on doctors will be caused by high performance of CT improving. Therefore, by presenting the “second opinion” by the computer aided diagnosis (CAD) system, it reduces the burden on the doctor. In this paper, we developed a CAD system for automatic detection of abnormal opacities such as lung nodules or ground glass opacity (GGO) on CT images from temporal subtraction image by incorporating a sparse coding technique to convolutional neural network (CNN). We extend the sparse coding and CNN to 3D and applied them to 32 cases which is obtained different time series on same subject. As a result, we obtained true positive rate (TPR) of 80.556%, false positive rate (FPR) of 22.892% and AUC of 0.768.
Defect Detection Method for Die-casting Aluminum Parts Based on RESNET

Surface defect detection of die-cast aluminum parts is always the focus of auto-mobile quality control. Most of the existing algorithms are designed to detect defects in a particular working condition. Although the effect is good, the application scope is relatively narrow. In the field of surface defect detection of die-cast aluminum parts, one of the current challenges is to segment target detection positions from complex field camera images and effectively detect defects in products in real time. In this paper, a defect detection algorithm combining traditional digital image processing algorithm and deep learning algorithm is proposed. The tar-get detection area is cut out timely and effectively through traditional image processing, and then the target area is classified by using residual network. The experimental results on the surface defect data set of die-casting aluminum parts show that the detection speed of this algorithm is very fast, and the accuracy rate reaches 98%.
Development of a tractable model system to mimic wood-ageing of beer on a lab scale

Wood-ageing of conventionally fermented beers is gaining increased attention in the production of sour beers with a noteworthy balance between sourness, wood aroma and flavour complexity. Besides the extraction of wood-derived compounds into the beer, wood-aged sours owe their layered flavour profile to the activity of a variety of ‘wild’ microorganisms that reside in the barrels or that emerge from the brewing or maturation environment. However, until now wood-ageing of craft beers largely remains a process of trial and error that often generates unexpected or undesirable results. Therefore, to better understand the process and develop control strategies to improve the consistency, predictability and overall quality of the resulting beer, more insight is needed into the interactions between the wood, the microorganisms and the maturing beer. Nevertheless, as studying these interactions on an industrial scale is highly challenging, the objective of this study was to develop a reproducible and easy-to-manipulate experimentally tractable system that can be used to study wood-ageing of beer on a lab scale. Barrel-ageing was mimicked in a 0.5 liter glass jar filled with beer and closed off by a wooden disk. Furthermore, the system was equipped with a synthetic community composed of four bacterial species (Acetobacter malorum, Gluconobacter oxydans, Lactobacillus brevis and Pediococcus damnosus) and four fungal species (Brettanomyces bruxellensis, Candida friedrichii, Pichia membranifaciens and Saccharomyces cerevisiae) that represented key microbes previously identified in wood-ageing experiments with 225-liter barrels. In order to test the hypothesis that the barrel-ageing process of beer can be replicated in the simplified in-vitro system, the system was subjected to 60 days of ageing and microbial community dynamics and beer chemistry were compared with a 38-week industrial barrel-ageing experiment using the same beer. Beer samples were collected at regular time points and subjected to both qPCR assays targeting the eight selected species and chemical analysis. Results revealed that in vitro ageing showed similar trends in the temporal dynamics of the microbial populations and beer chemistry as those observed during 38-weeks of barrel-ageing in 225-liter barrels. Furthermore, results were found to be highly reproducible. Altogether, the in-vitro system was found to be a robust and reproducible system that has great potential to perform more in-depth research about the intricate interactions between microbes, wood and maturing beer and to develop control strategies to improve the consistency, predictability and overall quality of the resulting beer.
The Musashi proteins are post-transcriptional activators of protein expression and alternative exon splicing in vertebrate photoreceptors

The Musashi proteins, MSI1 and MSI2, are conserved RNA binding proteins with a role in the maintenance and renewal of stem cells. Contrasting with this role, retina and terminally differentiated photoreceptor cells express high levels of MSI1 and MSI2, indicating that the two proteins have a role unrelated to maintaining undifferentiated cell state. Here we show that the Musashi proteins are essential in mature photoreceptors. Combined knockout of Msi1 and Msi2 lead to loss of the retina response to light and progressive photoreceptor cell death. The two proteins are fully redundant as individual deletion of Msi1 or Msi2 did not produce a phenotype. To define the molecular functions underlying the requirement for Musashi in photoreceptors, we delineated their RNA targets and analyzed the effect of the combined Msi1/Msi2 knockout on transcript levels, pre-mRNA splicing, and protein expressions. We show distinct nuclear and cytoplasmic functions for the Musashi proteins in photoreceptor cells. In the nucleus, Musashi binding to the downstream proximal intron promotes splicing of alternative exons. Surprisingly, four conserved photoreceptor-specific alternative exons in genes critical for vision proved to be dispensable, leaving open questions about the selective pressures that lead to the conservation of these exons and the contribution of alternative splicing to the phenotype of the Musashi knockout. In the photoreceptor cell cytoplasm MSI1 and MSI2 act as activators of protein expression. The combined knockout of Msi1 and Msi2 reduced the levels of multiple proteins including proteins required for vision and photoreceptor survival.
Dissecting β-Cardiac Myosin and Cardiac Myosin-Binding Protein C Interactions using a Nanosurf Assay

Cardiac myosin-binding protein C (cMyBP-C) regulates cardiac contractility by slowing shortening velocity and sensitizing the thin filament to calcium. cMyBP-C has been shown to interact with the proximal myosin S2 tail and the thin filament. However, the relative contribution of these interactions to the collective modulation of actomyosin ensemble function remains unclear. Hence, we developed a “nanosurf” assay as a model system to interrogate cMyBP-C interactions with actin and/or myosin. Synthetic thick filaments were generated using recombinant human β-cardiac myosin subfragments (HMM or S1) attached to DNA nanotubes, with 14 or 28 nm spacing, corresponding to the 14.3 nm myosin spacing found in native thick filaments. In vitro motility assays with myosin bound to the surrounding surface, exhibit enhanced thin filament interactions with synthetic thick filaments. No significant differences were observed in mean thin filament velocities between 14 and 28 nm spacing, consistent with our previous results for myosin V, VI, and β-cardiac myosin S1. Our nanosurf assay demonstrates the slowing of actomyosin motility by cMyBP-C. Alternating β-cardiac myosin HMM and cMyBP-C N-terminal fragments, C0-C2 or C1-C2, every 14 nm on the nanotube, reduced the mean thin filament velocity 4-6 fold relative to myosin alone. Interestingly, similar inhibition was observed using a β-cardiac myosin S1 construct, which lacks the S2 region proposed to interact with cMyBP-C, suggesting the actin-cMyBP-C interactions may dominate the inhibitory mechanism. No significant inhibition of thin filament velocity was observed with a C0-C1f fragment, lacking the majority of the M-domain, supporting the importance of this domain for inhibitory interaction(s). A phosphomimetic C0-C2 fragment showed a 3-fold higher velocity compared to its phosphonull counterpart, further highlighting phosphorylation-dependent regulation via the M-domain. Together, we have established the nanosurf assay as a tool to precisely manipulate spatially dependent cMyBP-C binding partner interactions, shedding light on the molecular regulation of β-cardiac myosin contractility. STATEMENT OF SIGNIFICANCE Cardiac myosin-binding protein C (cMyBP-C) is the most frequently mutated protein associated with hypertrophic cardiomyopathy (HCM), a common cause of sudden cardiac death. Despite the importance of cMyBP-C in cardiac contractility, the mechanisms underlying this regulation are unclear due to experimental challenges in studying the complex, transient, weak interactions of cMyBP-C with the contractile proteins of the sarcomere. In this study, we created a nanosurf synthetic DNA thick filament assay to dissect the cMyBP-C interactions with actin and human β-cardiac myosin. We demonstrate actomyosin inhibition by cMyBP-C fragments regardless of recombinant human β-cardiac myosin subfragment (HMM or S1) and highlight the importance of the cMyBP-C M-domain using cMyBP-C fragments and phosphomimetics.
CRISPRcleanRWebApp: an interactive web application for processing genome-wide pooled CRISPR-Cas9 viability screen

A major limitation of pooled CRISPR-Cas9 viability screens is the high false-positive rate in detecting essential genes arising from copy number-amplified (CNA) regions of the genome. To solve this issue, we developed CRISPRcleanR: a widely-used computational method implemented as R/python package and in a dockerized version. CRISPRcleanR detects and corrects biased gene-independent responses to CRISPR-Cas9 targeting in an unsupervised fashion, and it accurately reduces false-positive signals, while maintaining sensitivity in identifying relevant genetic dependencies. Here we present CRISPRcleanRWebApp, a web-based application that enables access to CRISPRcleanR through an intuitive graphical web interface. CRISPRcleanRWebApp removes the complexity of low-level R/python-language user interactions, including a range of interactively explorable plots. In addition, it supports a wider range of CRISPR guide RNAs’ libraries with respect to the original package. CRISPRcleanRWebApp is freely available and open to all users at: https://iorio-apps.fht. org/ccr. Highlights CRISPR-Cas9 screens are widely used for the identification of cancer dependencies False-positives in CRISPR-Cas9 screens arise from targeting copy-number (CN) amplified genomic regions CRISPRcleanR corrects this bias in an unsupervised fashion CRISPRcleanRWebApp is a web user-friendly front-end for CRISPRcleanR CRISPRcleanRWebApp supports a wider range of CRISPR libraries and supports interactive results’ explorations
Blockade of redox second messengers inhibits JAK/STAT and MEK/ERK signaling sensitizing FLT3-mutant acute myeloid leukemia to targeted therapies

FLT3-mutations are diagnosed in 25-30% of patients with acute myeloid leukemia (AML) and are associated with a poor prognosis. AML is associated with the overproduction of reactive oxygen species (ROS), which drives genomic instability through the oxidation of DNA bases, promoting clonal evolution, treatment resistance and poor outcomes. ROS are also important second messengers, triggering cysteine oxidation in redox sensitive signaling proteins, however, the specific pathways influenced by ROS in AML remain enigmatic. Here we have surveyed the posttranslational architecture of primary AML patient samples and assessed oncogenic second messenger signaling. Signaling proteins responsible for growth and proliferation were differentially oxidized and phosphorylated between patient subtypes either harboring recuring mutation in FLT3 compared to patients expressing the wildtype-FLT3 receptor, particularly those mapping to the Src family kinases (SFKs). Patients harboring FLT3-mutations also showed increased oxidative posttranslational modifications in the GTPase Rac activated-NADPH oxidase-2 (NOX2) complex to drive autocratic ROS production. Pharmacological and molecular inhibition of NOX2 was cytotoxic specifically to FLT3-mutant AMLs, and reduced phosphorylation of the critical hematopoietic transcription factor STAT5 and MAPK/ERK to synergistically increase sensitivity to FLT3-inhibitors. NOX2 inhibition also reduced phosphorylation and cysteine oxidation of FLT3 in patient derived xenograft mouse models in vivo, highlighting an important link between oxidative stress and oncogenic signaling. Together, these data raise the promising possibility of targeting NOX2 in combination with FLT3-inhibitors to improve treatment of FLT3-mutant AML. One Sentence Summary FLT3-precision therapies have entered the clinic for AML however, their durability is limited. Here we identify the Rac-NOX2 complex as the major driver of redox second messenger signaling in FLT3-mutant AML. Molecular and pharmacological inhibition of NOX2 decreased FLT3, STAT5 and MEK/ERK signaling to delay leukemia progression, and synergistically combined with FLT3 inhibitors.
Prokaryotic phospholipid translocation by ubiquitous PplT domain proteins

1. Interfaculty Institute of Microbiology and Infection Medicine Tübingen, Infection Biology Section, University of Tübingen, Germany. 2. German Center for Infection Research (DZIF), partner site Tübingen, Germany. 3. Cluster of Excellence EXC2124 Controlling Microbes to Fight Infection, University of Tübingen, Germany 4. Institute for Bioinformatics and Medical Informatics, University of Tübingen, Germany 5. Current address: Department of Molecular Biology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA 6. Pediatric Surgery and Urology, University Children's Hospital Tübingen, University of Tübingen, Germany.
Improving the Prediction Accuracy of Groundwater Salinity Mapping Using Indicator Kriging Method

AbstractThe saline groundwater irrigation is an important problem in the arid and semiarid region because it can cause soil salinization and reduce crop productivity. The accurate spatial distribution of groundwater salinity can be helpful to managers and decision makers. In this study, the mapping of salinity risk through groundwater electrical conductivity (EC) irrigation was performed based on data collected from 88 wells in the Lower-Cheliff plain (Algeria). The EC data showed a normal distribution based on elementary statistics. The EC classified using Riverside method point out a high risk of groundwater salinity (Class C3) or very high risk (Class C4) for soil salinization. The EC estimated by ordinary kriging method (OK) revealed on one hand, an underprediction of a high value, on the other hand, an overprediction of low value. The methodology of nonparametric and nonlinear of indicator kriging (IK) was performed by three thresholds: EC>2.25, EC>3, and EC>5 dS/m. The map has been obtained from th.