Miracle-dz/UniFAR-FTUs huggingface dataset:
Unleashing GPUs for Network Function Virtualization: an open architecture based on Vulkan and Kubernetes

General-purpose computing on graphics processing units (GPGPU) is a promising way to speed up computationally intensive network functions, such as performing real-time traffic classification based on machine learning. Recent studies have focused on integrated graphics units and various performance optimizations to address bottlenecks such as latency. However, these approaches tend to produce architecture-specific binaries and lack the orchestration of functions. A complementary effort would be a GPGPU architecture based on standard and open components, which allows the creation of interoperable and orchestrable network functions.This study describes and evaluates such open architecture based on the cross-platform Vulkan API, in which we execute hand-written SPIR-V code as a network function. We also demonstrate a multi-node orchestration approach for our proposed architecture using Kubernetes. We validate our architecture by executing SPIR-V code performing traffic classification with random forest inference. We test this application both on discrete and integrated graphics cards and on x86 and ARM. We find that in all cases the GPUs are faster than the baseline Cython code.
Towards Adaptive Quality Assurance in Industrial Applications

We propose the AQUILA framework (Adaptive Quality Assurance in Industrial Applications), a concept for digitalization in Industry 4.0 to support the entire industrial manufacturing chain, laying the groundwork for adaptive quality assurance in times of disrupted supply chains and, due to the COVID-19 pandemic, restricted travel possibilities. To that end, our proposed framework allows for the definition and description of industrial processes, quality assurance and testing protocols, and training scenarios in a comprehensive notation based on BPMN, and supports users in task execution, documentation, and evaluation by providing smart glass-based HCI with eye tracking technology, delivering a combination of process documentation, context-sensitive AR visualization, gaze-based interaction schemes, and remote maintenance and assistance functionality.
Characterizing DNS query response sizes through active and passive measurements

DNS has been one of the most important pieces in the current Internet. As an advanced feature, DNS provides chains of trusts for query responses from authoritative servers (i.e., DNSSEC). However, DNSSEC requires a larger payload size in a DNS query, which could yield packet fragmentation, truncation, and TCP fallback. In this paper, we characterize the DNS query response behavior from client (caching resolver) and server (authoritative server) views. For the client view, we analyze the offered maximum response sizes (EDNS0 size) from resolvers and actual response sizes at the servers of the ccTLD of jp (JP-DNS). For the server view, we characterize DNS response size distributions for different TLDs by actively querying the top 300K popular domain names in the Tranco list. The main findings of our work are as follows: (1) We confirm an increase of an EDNS0 size of 1232B from clients in Apr. 2021 despite not being so evident during the DNS flag day event in Oct. 2020. (2) Query truncation and TCP fallbacks almost occurred in an EDNS0 size of 512B, but its queries were legitimate A/AAAA records. (3) The response size distributions of popular domains are significantly different in TLDs, and median response size does not fit the minimum size (512B) in many TLDs. (4) We clarify that several issues affect the response size distribution: the ratio of signed zones and configurations (e.g., NSEC/NSEC3, signed algorithms).
Network-based Intrusion Detection: A One-class Classification Approach

The adoption of new technologies and the increasing amount of connected devices have drawn the attention of cyber-attackers, whose intentions are oriented to disturb computational services or even steal critical information. This poses new challenges in the design of Intrusion Detection Systems (IDS), which are in charge of detecting threats. When dealing with unknown cyber-attacks, anomaly-based IDS (AIDS) have drawn the attention of the research community, since they could detect, for instance, zero-day attacks. A recurrent critical aspect in the design of these systems is the training procedures. In the context of attack detection, training involves difficulties due to the imbalanced nature (one class much more represented than the other) of the associated data sets. Hence, approaches to address the class imbalance are always relevant. In this work, we present the evaluation of different machine learning (ML) algorithms, known as one-class classifiers, that hold the potential to be implemented over an AIDS. For this task, we used the UNSW-NB15, comparing their performance using pertinent metrics that are normally used to assess an attack detection algorithm.
The Bangkok Urbanscapes Dataset for Semantic Urban Scene Understanding Using Enhanced Encoder-Decoder With Atrous Depthwise Separable A1 Convolutional Neural Networks

Semantic segmentation is one of the computer vision tasks which is widely researched at present. It plays an essential role to adapt and apply for real-world use-cases, including the application with autonomous driving systems. To further study self-driving cars in Thailand, we provide both the proposed methods and the proposed dataset in this paper. In the proposed method, we contribute Deeplab-V3-A1 with Xception, which is an extension of DeepLab-V3+ architecture. Our proposed method as DeepLab-V3-A1 with Xception is enhanced by the different number of $1\times1$ convolution layers on the decoder side and refining the image classification backbone with modification of the Xception model. The experiment was conducted on four datasets: the proposed dataset and three public datasets i.e., the CamVid, the cityscapes, and IDD datasets, respectively. The results show that our proposed strategy as DeepLab-V3-A1 with Xception performs comparably to the baseline methods for all corpora including measurement units such as mean IoU, F1 score, Precision, and Recall. In addition, we benchmark DeepLab-V3-A1 with Xception on the validation set of the cityscapes dataset with a mean IoU of 78.86%. For our proposed dataset, we first contribute the Bangkok Urbanscapes dataset, the urban scenes in Southeast Asia. This dataset contains the pair of input images and annotated labels for 701 images. Our dataset consists of various driving environments in Bangkok, as shown for eleven semantic classes (Road, Building, Tree, Car, Footpath, Motorcycle, Pole, Person, Trash, Crosswalk, and Misc). We hope that our architecture and our dataset would help self-driving autonomous developers improve systems for driving in many cities with unique traffic and driving conditions similar to Bangkok and elsewhere in Thailand. Our implementation codes and dataset are available at https://kaopanboonyuen.github. io/bkkurbanscapes.
Enabling Malware Detection with Machine Learning on Programmable Switch

Malware detection is an important issue for network security, especially for the Internet of Things (IoT) network. Traditional network intrusion detection system (NIDS), running on external host servers, are not scalable for ever-increasing IoT traffic and waste time on transmitting data back and forth. Here, we propose a novel architecture called on-switch malware detector that utilizes the programmable switch and the machine-learning technique to achieve better performance on detecting malicious flows in the network. The on-switch malware detector mainly consists of four components: (1) packet forwarder, (2) feature extractor, (3) flow director, and (4) neural-network detector. According to the experimental results, the on-switch malware detection has a 99.57% shorter response time than a conventional signature-based NIDS; meanwhile its processing capacity increases by 800 times. As a result, the on-switch malware detector efficiently overcomes the shortcomings of conventional NIDSs, making it a better fit for the IoT network.
Modelling of Electromagnetic Fields Generated by 25 kV Traction Networks on Multi-Track Sections

When forming modern railroad power supply systems (RPSS) special attention is paid to the issues of power engineering facilities safe functioning and reduction in their negative impact on personnel and environment. An important factor of such exposure is that significant levels of electromagnetic field strengths (EMF) can be observed at these facilities. To improve electromagnetic safety in contemporary conditions, characterized by large-scale implementation of digitalization, algorithms of EMF digital modeling shall be developed. In order to adequately determine the EMF generated by traction networks (TN), computer models based on the methods of determining the modes of RPSS in phase coordinates can be used, developed at Irkutsk State University of Railway Transport. The methodology of electromagnetic safety analysis is implemented on the basis of these models; this methodology differs from the known approaches in the following features: systematicity, universality, conformity with the external environment and integrated approach. Systematicity is the possibility of computing EMF based on determining the modes of complex RPSS in phase coordinates. Universality is achieved by the possibility of simulating traction networks of various designs. Conformity with the external environment is ensured by the correct consideration of the underlying surface profile, underground communications, as well as extended metal structures located near the simulated TN. The integrated approach is the possibility of combining the computations of complex network modes and computing EMF strengths. The article describes computer models that allow to determine the strengths of electromagnetic fields generated by complex traction networks of multi-track sections.
Interacting with digital resonators by acoustic excitation

This demo presents an acoustic interface 1 which allows to directly excite digital resonators (digital waveguides, lumped models, modal synthesis and sample convolution). Parameters are simultaneously controlled by the touch position on the same surface. The experience is an intimate and intuitive interaction with sound for percussive and melodic play.
Decreasing the likelihood of cycling accidents by signalling intentions to other road users through a lighting system: A feasibility study

A new intelligent lighting system for on a bicycle was designed so that road-users can easily interpret cyclist’s intentions and behaviour. The system conveys speed, breaking- and turning intentions to other road users through lighting signals. The effect the system has on other cyclists’ behaviour needs to be explored, but no general guidelines for setting up a test like this exist. For this reason, an exploratory feasibility study is carried out. This study aims to answer whether the distance between cyclists can be reliably measured, whether time-to-collision(TTC) is a useful indicator for cycling safety, and whether the System usability Scale (SUS) can be used for systems with less (complex) functions. Results show that participants were generally positive about the lighting system, mostly about the turning- and breaking signal. The distance between two cyclists can be measured reliably, but speed cannot. Therefore TTC is a less useful indicator than following distance. The SUS can be used for systems with less (complex) functions. Other recommendations to improve the validity of a follow-up study were made. Finally, it is recommended that feasibility studies in general are conducted and reported on more often, so that the exploratory nature of research is stressed more clearly.
Successful treatment with osimertinib and its subsequent resistance mechanism in a patient with non-small-cell lung cancer harboring acquired EGFR T790M mutation after recovery from AC0010-induced interstitial lung disease

Objective: Treatment with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs)can occasionally lead to interstitial lung disease (ILD), and the appropriate treatment after recovery from ILD remains controversial. AC0010 is an investigational third-generation TKI used in China to selectively target the T790M mutation. Here, we describe a patient who developed ILD after AC0010 treatment and was then successfully re-challenged with osimertinib. Methods: The patient was a 67-year-old male with a diagnosis of metastatic pulmonary adenocarcinoma with an L858R mutation on exon 21. Acquired T790M mutation was con ﬁ rmed by re-biopsy after progression on erlotinib treatment. The patient was treated with AC0010, and developed ILD 54 days after treatment initiation. Following his recovery from ILD, osimertinib (80 mg/day) was administered with no adverse effects. After progression on osimertini\b 11 months later, a histological transformation from adenocarcinoma to large-cell neuroendocrine carcinoma was con ﬁ rmed by re-biopsy, with a marked increase in serum neuron-speci ﬁ c enolase. Conclusions: This is the ﬁ rst report of interstitial pneumonitis caused by AC0010. Osimertinib re-challenge after recovery from ILD was a safe and effective treatment option. Our report further highlights that pathological transformation of large-cell neuroendocrine carcinoma represents one of the resistance mechanisms of osimertinib, and may be accompanied by an increase in serum neuron-speci ﬁ c enolase.
CMAR_A_268378 9417..9428

1Department of Medical Oncology, Yantai Yuhuangding Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong 250012, People’s Republic of China; 2Department of Oncology, Yantai Shan Hospital, Yantai 264000, People’s Republic of China; 3Department of Oncology, The Affiliated Yantai Yuhuangding Hospital of Qingdao University, Yantai 264000, People’s Republic of China Purpose: The effects of miR-139 on the tumorigenicity of triple negative breast cancer (TNBC) and the underlying mechanisms were investigated. Methods: Normal human breast epithelial (MCF-10A) and TNBC cell lines (HCC1806 and BT549) were used for microRNA (miR)-139 overexpression, SOX8 overexpression, and knockdown studies as in vitro models of TNBC. The expression of SOX8 and miR-139 was detected by reverse transcription-polymerase chain reaction. CCK8 and clone formation assays were used to evaluate cell proliferation ability. Transwell assays and flow cytometry were used to test cell migration and apoptosis, respectively. Cell tumorigenicity was examined by tumor sphere formation assays. The interaction between miR-139 and SOX8 was examined by dual-luciferase reporter assays. The expression of SOX8, cleaved caspase-3, and cleaved caspase-9 was analyzed by Western blotting. The findings were validated in vivo using a nude mouse transplanted tumor model. Results: SOX8 expression was higher (P < 0.05) and miR-139 expression was lower (P < 0.05) in HCC1806 and BT549 cells than in MCF-10A cells. SOX8 overexpression significantly enhanced cell proliferation and migration, reduced the rate of cell apoptosis, and increased tumor sphere formation (P < 0.05) compared with the control group, whereas SOX8 knockdown had the opposite effect (P < 0.05). Overexpression of miR-139 markedly decreased cell proliferation and migration, increased cell apoptosis in vitro, and decreased tumor angiogenesis and volume in vivo (P < 0.05). Conclusion: miR-139 suppressed the tumorigenicity of TNBC cells by targeting SOX8.
Molecular and Cell Biology of a Family of Voltage- Dependent Anion Channel Porins in Lotus japonicus

Voltage-dependent anion channels (VDACs) are generally considered as the main pathway for metabolite transport across the mitochondrial outer membrane. Recent proteomic studies on isolated symbiosome membranes from legume nodules indicated that VDACs might also be involved in transport of nutrients between plants and rhizobia. In an attempt to substantiate this, we carried out a detailed molecular and cellular characterization of VDACs in Lotus japonicus and soybean (Glycine max). Database searches revealed at least five genes encoding putative VDACs in each of the legumes L. japonicus, Medicago truncatula, and soybean. We obtained and sequenced cDNA clones from L. japonicus encoding five full-length VDAC proteins (LjVDAC1.1–1.3, LjVDAC2.1, and LjVDAC3.1). Complementation of a yeast (Saccharomyces cerevisiae) mutant impaired in VDAC1, a porin of the mitochondrial outer membrane, showed that LjVDAC1.1, LjVDAC1.2, LjVDAC2.1, and LjVDAC3.1, but not LjVDAC1.3, are functional and targeted to the mitochondrial outer membrane in yeast. Studies of the expression pattern of the five L. japonicus VDAC genes revealed largely constitutive expression of each throughout the plant, including nodules. Antibodies to LjVDAC1.1 of L. japonicus and the related POM36 protein of potato (Solanum tuberosum) recognized several proteins between 30 and 36 kD on western blots, including LjVDAC1.1, LjVDAC1.2, LjVDAC1.3, and LjVDAC2.1. Immunolocalization of VDACs in L. japonicus and soybean root nodules demonstrated their presence on not only mitochondria but also on numerous, small vesicles at the cell periphery. No evidence was found for the presence of VDACs on the symbiosome membrane. Nonetheless, the data indicate that VDACs may play more diverse roles in plants than suspected previously.
OTT_A_246412 4075..4088

Shanshan Nie Guoping Yang 1 Hongwei Lu 1Center for Clinical Pharmacology, The Third Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China; 2Department of Cardiology, The Third Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China; 3Center for Experimental Medical Research, The Third Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China Abstract: Gastric cancer is the third leading cause of malignant tumor-related mortality worldwide. Traditional cytotoxic agents prolong the overall survival and progression-free survival of patients with advanced gastric cancer (AGC) compared to that with best supportive care. Due to the occurrence of serious adverse drug reactions that result in discontinued treatment, the survival benefit in AGC remains unsatisfactory. Systemic chemotherapy regimens have changed greatly, especially since the introduction of trastuzumab. Nevertheless, HER2 positivity is present in only approximately 20% of tumors. Due to the genetic heterogeneity and complexity of patients, there are many studies in progress that are exploring novel targeted drugs as an alternative to chemotherapy or adjuvant treatment in early-stage, progressive, and advanced gastric cancer. On the basis of the differences in gene expression profiles among patients, searching for specific and sensitive predictive biomarkers is important for identifying patients who will benefit from a specific targeted drug.With the development of targeted therapies and available chemotherapeutic drugs, there is no doubt that, over time, more patients will achieve better survival outcomes. Recently, immune checkpoint blockade has been well developed as a promising anticancer strategy. This review outlines the currently available information on clinically tested molecular targeted drugs and immune checkpoint inhibitors for AGC to provide support for decision-making in clinical practice.
Efﬁcient Alignment of Aerial Images Based on Virtual Forces

—Getting a contemporary aerial overview of a disaster area is a foremost task in search and rescue operations. We previously have introduced a novel method for registering a large amount of aerial images when camera parameters are almost unknown and no reference images are available. This paper provides two new methods, which improve our method for image registration based on virtual forces. The goal is to improve the performance of creating a contemporary overview map of a disaster area assembling several images taken by unmanned aerial vehicles (UAVs) equipped with cameras. In this paper, two new methods are introduced: a method for rotation estimation and a method for scale estimation. Both methods use fast heuristic approximation approaches and statistical methods to provide high robustness. We discuss the methods in detail and compare them to our previous approach regarding robustness and calculation speed. We can show that the new methods signiﬁcantly increase the performance of the image registration process.
Enhancing Quality of Service for Adhoc on Demand Distance Vector Protocol based on time for Mobile Ad-hoc Networks

In MANET (Mobile Adhoc Network) the physical connectivity of the network keeps on changing dynamically. Because of the several MANET constraints such as limited bandwidth, mobility,battery power etc; it becomes very important to design a protocol that suits the requirements for MANETS. The QoS mechanism is done by improving quality in between wireless nodes. This Paper will reflect the link failure and the will provides solutions for it. This work will be focus on the Time based on demand distance vector protocol so that the faulty networks can be prevented. It particularly works on the detection of faulty nodes at the early state of the node connectivity. It will find out the nodes which have low resources to sustain in whole process of routing and by removing these node we can shred out the week links from whole topology which in turns can enhance the quality and fault tolerance. Initially work will start with battery resources as the prime factor in deciding the propose work and latter we can find out other dependent factors. The research work is carried out on Network simulator and parameters are analysed with it.
PPAR Activation Induces Rapid Changes of Both AMPK Subunit Expression and AMPK Activation in Mouse Skeletal Muscle

AMP-activated protein kinases (AMPK) are heterotrimeric, , serine/threonine kinases. The 3AMPK subunit is particularly interesting in muscle physiology because 1) it is specifically expressed in skeletal muscle, 2) 2 2 3 is the AMPK heterotrimer activated during exercise in humans, and 3) it is down-regulated in humans after a training period. However, mechanisms underlying this decrease of 3-AMPK expression remained unknown. We investigated whether the expression of AMPK subunits and particularly that of 3-AMPK are regulated by the PPAR pathway. We report that PPAR activation with GW0742 induces a rapid (2 h) and sustained down-regulation of 3-AMPK expression both in mouse skeletal muscles and in culture myotubes. Concomitantly, phosphorylation levels of both AMPK and acetyl-coenzyme A carboxylase are rapidly modified. The 3-AMPK down-regulation is also observed in muscles from young and adult transgenic mice with musclespecific overexpression of peroxisome proliferator-activated receptor (PPAR ). We showed that 3-AMPK down-regulation is a rapid physiological muscle response observed in mouse after running exercise or fasting, two situations leading to PPAR activation. Finally, using C2C12, we demonstrated that dose and time-dependent down-regulation of 3-AMPK expression upon GW0742 treatment, is due to decrease 3-AMPK promoter activity. (Molecular Endocrinology 25: 1487–1498, 2011)