bluuebunny/crossref_metadata_2025 huggingface dataset:
Managing Hi-Railer Set-on and Set-Off in a Train Control System Using Axle Counters
Authors: Diemunsch Kenneth , Walker Alyssa
Published: June 2024

This paper presents a new comprehensive method for managing hi-rail vehicle set-on and set-off in a Communications-Based Train Control (CBTC) system using axle counters as a secondary train detection system.

Due to its high performance in terms of headway combined with low required maintenance [1], CBTC is now the preferred technology for metropolitan rapid transit systems around the world. Metropolitan transit lines such as New York City Transit and Toronto Transit Commission are often underground or elevated on a structure and/or are relatively short so maintenance vehicles access work areas only via rail from the yard or a spur track used as storage.

In the past few years, CBTC has started to be deployed on what the industry refers to as commuter rail lines. Commuter rail lines have short distances between stations within the city centers and long distances between stations in suburban areas using at grade tracks running along highways. Therefore, to facilitate maintenance activities, operators of commuter rail lines use hi-rail vehicles that drive on the roads and enter the rail network at specific set-on areas. Examples of CBTC projects on commuter rail lines include Bay Area Rapid Transit, Paris Réseau Express Régional, and Montreal Réseau Express Métropolitain.

The majority of new CBTC systems for commuter rail lines are using axle counters as a secondary means of train detection. The CBTC and axle counter systems have a complex functional interface. Using hi-railers in a CBTC system that relies on axle counters generates challenges for both the CBTC system and axle counters. The method to handle those challenges is the result of collaborative design effort over several years by a transit agency, a CBTC contractor, an axle counter vendor, and numerous consultants.

This work starts by introducing relevant CBTC technology functions. Principles of axle counters, including the need for a reset of axle counter blocks and the different reset methods are described. The challenges resulting from hi-rail set-on and set-off are explained, showing the impact on both the axle counter system and the CBTC train movements. Then, the preferred method for managing the challenges introduced by hi-rail vehicles set-on and set-off are presented. There are two variations depending on whether events arise during revenue service or at night when revenue service is stopped. Other disregarded methods are briefly explained with the reasons why they are not suitable. Finally, the authors provide thoughts on this method and describe the possible improvements.
AI-Enabled Vibration Sensing System for Early Detection of Trains at Active Highway-Rail Grade Crossings
Authors: Amjadian Mohsen , Rahman Md Masnun , Tarawneh Constantine , Villarreal Valik , Rocha Dylan
Published: June 2024

Highway-rail grade crossings (HRGCs) play an essential role in ensuring the secure traversal of road users across railway tracks. However, despite their significance, they present safety challenges, particularly when trains go undetected, heightening the risk of potential collisions between the road user and train. This paper aims to explore the viability of employing vibration sensors for detection and characterization of an approaching train’s speed at HRGCs. The methodology involves analyzing rail vibrations and developing a time series predictive machine learning (ML) model. To accomplish this, a Finite Element (FE) model of a ballasted track railway is created in SAP2000, consisting of essential track components such as rails, sleepers, rail pads, ballast, and subgrade. The acceleration time history of the rails, induced by a moving single car, is recorded, and employed as input data for training and testing a Long Short-Term Memory (LSTM) network. The LSTM model predicts crucial parameters of the approaching train, including its location and speed. Successful prediction of these parameters is anticipated to enable the determination of the precise moment when the train reaches the HRGC, affording road users sufficient reaction time to safely traverse the railway track.
Research on Wheel Wear Coefficient Considering Wheel Profile and Operating Route Based on Multi-Rigid-Body Method
Authors: Song Ruiyang , Sun Lixia , Zhang Jimin
Published: June 2024

Wheel wear has always been a problem in the railway industry, and wear prediction simulation is an important approach to address this problem. However, the use of simulation requires the use of wear coefficients. The existing wear coefficients are based on laboratory rolling test rigs, which have different operating environments and materials compared to actual wheel-rail systems. Directly applying these coefficients to wear calculations can result in significant errors, so they need to be calibrated accordingly.

In this paper, a wheel wear prediction model that considers wheel profile and operating route is established. The model consists of a vehicle dynamics model and a wear rate calculation model, and the prediction method takes into account the track roughness, curve ratio, and different wheel profiles. In the dynamics model, the Hertz-Fastsim wheel-rail contact model is used to calculate the physical quantities such as normal force and tangential force in the contact patch, which are then inputted into the wear rate calculation model to obtain the wear amount. During the calculation process, the influence of various curve radii and the proportion of straight tracks is considered. Based on the proportion of different curve radii and straight tracks in the actual operating track, the wear amount is weighted to obtain wear prediction results that are consistent with the actual track conditions.

The wear model adopts the Archard local model, which has four wear regions (i.e., seizure mild I, severe and mild II). Simulation and experimental results show that when the two endpoint values in the Jendel wear coefficient diagram are selected, there is a significant prediction error. For the study in this paper, the initial values are set to the median values of each region in the Jendel wear coefficient graph, that is k1 = 350 × 10−4, k2 = k4 = 5 × 10−4, k3 = 35 × 10−4. The wear of the wheels is predicted based on the dynamic model and wear rate calculation model. This prediction is then compared with actual measured data at different operating distances. The differences in the comparison results are used to narrow down the range of values for each region in the Jendel wear coefficient graph. In the end, the wheel-rail wear coefficient was obtained.
Joint equalization and decoding with per-survivor processing based on super-trellis in time-varying underwater acoustic channels
Authors: Kou Xu , Wu Yanbo , Zhu Min
Published: June 2024

This Letter proposes a low-complexity joint equalization and decoding reception scheme based on super-trellis per-survivor processing, making it possible to apply maximum likelihood sequence estimation in high-order underwater acoustic communications under fast time-varying channels. The technique combines trellis-coded modulation states and intersymbol interference states and uses per-survivor processing to track channel parameters. Furthermore, a general trellis configuration for arbitrary order quadrature amplitude modulation signal is provided when truncate the channel is used to describe the intersymbol interference state to 1. Sea trials results show that the performance of proposed method can be more than 1.4 dB superiority than conventional schemes.
Antibody nanoparticle conjugate–based targeted immunotherapy for non–small cell lung cancer
Authors: Saha Tanmoy , Fojtů Michaela , Nagar Astha Vinay , Thurakkal Liya , Srinivasan Balaaji Baanupriya , Mukherjee Meghma , Sibiyon Astralina , Aggarwal Heena , Samuel Akash , Dash Chinmayee , Jang Hae Lin , Sengupta Shiladitya
Published: June 2024

The use of immune checkpoint inhibitors, which activate T cells, is a paradigm shift in the treatment of non–small cell lung cancer. However, the overall response remains low. To address this limitation, here we describe a novel platform, termed antibody-conjugated drug-loaded nanotherapeutics (ADN), which combines immunotherapy and molecularly targeted therapy. An ADN was designed with an anti-CD47 and anti–programmed death ligand 1 (PDL1) antibody pair on the surface of the nanoparticle and a molecularly targeted inhibitor of the PI3K (phosphatidylinositol 3-kinase)/AKT/mTOR (mammalian target of rapamycin) pathway, PI103, entrapped in the nanoparticle. The anti–CD47-PDL1-ADN exhibited greater antitumor efficacy than current treatment options with a PDL1 inhibitor in vivo in an aggressive lung cancer immunocompetent mouse model. Dual antibody-drug–loaded nanotherapeutics can emerge as an attractive platform to improve outcomes with cancer immunotherapy.
Modeling the transmission mitigation impact of testing for infectious diseases
Authors: Middleton Casey , Larremore Daniel B.
Published: June 2024

A fundamental question of any program focused on the testing and timely diagnosis of a communicable disease is its effectiveness in reducing transmission. Here, we introduce testing effectiveness (TE)—the fraction by which testing and post-diagnosis isolation reduce transmission at the population scale—and a model that incorporates test specifications and usage, within-host pathogen dynamics, and human behaviors to estimate TE. Using TE to guide recommendations, we show that today’s rapid diagnostics should be used immediately upon symptom onset to control influenza A and respiratory syncytial virus but delayed by up to two days to control omicron-era severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Furthermore, while rapid tests are superior to reverse transcription quantitative polymerase chain reaction (RT-qPCR) to control founder-strain SARS-CoV-2, omicron-era changes in viral kinetics and rapid test sensitivity cause a reversal, with higher TE for RT-qPCR despite longer turnaround times. Last, we illustrate the model’s flexibility by quantifying trade-offs in the use of post-diagnosis testing to shorten isolation times.
Congener-welded crystalline carbon nitride membrane for robust and highly selective Li/Mg separation
Authors: Zhang Yuanyuan , Zhou Ke , Su Shigang , Gao Jun , Liu Jian , Jiang Lei
Published: June 2024

Extracting lithium from salt-lake brines critically relies on the separation of Li
+
and Mg
2+
, which could combat the lithium shortage. However, designing robust sieving membrane with high Li
+
/Mg
2+
selectivity in the long-time operation has remained highly challenging. Here, we demonstrate a bioinspired congener-welded crystalline carbon nitride membrane that can accomplish efficient and stable monovalent ion sieving over divalent Mg ion. The crystalline carbon nitrides have uniform and narrow pore size to reject the large hydrated Mg
2+
and rich ligating sites to facilitate an almost barrierless Li
+
transport as suggested by ab initio simulations. These crystals were then welded by vapor-deposited congeners, i.e., amorphous polymer carbon nitride, which have similar composition and chemistry with the crystals, forming intimate and compatible crystal/polymer interface. As a result, our membrane can sieve out highly dilute Li
+
(0.002 M) from concentrated Mg
2+
(1.0 M) with a high selectivity of 1708, and can be continuously operated for 10 days.
H3N2 canine influenza virus-like particle vaccine with great protection in beagle dogs
Authors: Ge Fei-fei , Shen Li-pin , Yang De-quan , Yang Xian-cao , Li Xin , Shen Hai-xiao , Wang Jian , Huang Shixin
Published: June 2024

In 2016, a distinct branch of H3N2 canine influenza virus (CIV) emerged, which has mutations related to mammalian adaptation and has replaced previously prevalent strains. This branch poses a risk of zoonotic infection. To prevent and control H3N2 CIV, an H3N2 virus-like particle (VLP) vaccine based on the insect cell baculovirus expression system has been developed in the study. The H3N2 VLP vaccine induced high titers of hemagglutination inhibition (HI) antibodies in nasal and muscular immunized beagle dogs. Meanwhile, the VLP vaccine provided effective protection against homologous virus challenge comparable to inactivated H3N2 canine influenza virus. In addition, the intranasal H3N2 VLP vaccine induced significantly higher Th1, Th2, and Th17 immune responses, respectively (p,0.05). Importantly, intramuscular injection of VLP and inactivated H3N2 virus has complete protective effects against homologous H3N2 virus attacks. Nasal immunization with H3N2 VLP can partially protect beagles from H3N2 influenza.

IMPORTANCE

A new antigenically and genetically distinct canine influenza virus (CIV) H3N2 clade possessing mutations associated with mammalian adaptation emerged in 2016 and substituted previously circulating strains. This clade poses a risk for zoonotic infection. In our study, intramuscular injection of the H3N2 virus-like particle (VLP) vaccine and inactivated H3N2 CIV confer completely sterilizing protection against homologous H3N2 canine influenza virus challenge. Our results provide further support for the possibility of developing VLP vaccines that can reliably induce immunity in animal species.
Supplemental Material: High-pressure, low-temperature metamorphism preserved in the Indus-Yarlung suture zone of the eastern Himalaya: Overprinting at amphibolite facies and comparison with occurrences in the western Himalaya
Authors: Li Wangchao , Yin Changqing , et al.
Published: June 2024

Description of supplemental figure, analytical and phase equilibria modeling methods.
Progressive spasticity and developmental delay in an infant with aCTNNB1mutation
Authors: Freeman Meagan , Fakhori Nina , Monteil Danielle
Published: June 2024

We present an infant referred to Developmental Paediatrics for delays, slow growth, hypotonia, esotropia and spasticity. Over the course of 2 months, the infant’s exam progressed, demonstrating worsening spasticity and tonal changes in the setting of a normal brain MRI with acquired microcephaly. Genetic testing demonstrated a pathogenicCTNNB1nonsense mutation. Following the discovery of the underlying cause for the child’s clinical picture, the child was evaluated by therapeutic services and neurology, which was initially only available via asynchronous telehealth, due to a resource limited area. Cerebral palsy is a nonprogressive neurodevelopmental disorder and, when associated with developmental delay, qualifies for further genetic investigation into the underlying aetiology. Genetic testing recommendations exist for developmental delay, but there is no current algorithm regarding testing for cerebral palsy. Education and clear guidelines on genetic testing allow for better prognostication and potential treatment in cases of cerebral palsy, especially when associated with other disorders.
Changes in the prevalence of mental health problems during the first year of the pandemic: a systematic review and dose-response meta-analysis
Authors: Salanti Georgia , Peter Natalie Luise , Tonia Thomy , Holloway Alexander , Darwish Leila , Kessler Ronald C , White Ian , Vigod Simone N. , Egger Matthias , Haas Andreas D , Fazel Seena , Herrman Helen , Kieling Christian , Patel Vikram , Li Tianjing , Cuijpers Pim , Cipriani Andrea , Furukawa Toshi A , Leucht Stefan
Published: June 2024

Aim

To describe the pattern of the prevalence of mental health problems during the first year of the COVID-19 pandemic and examine the impact of containment measures on these trends.

Methods

We identified articles published until 30 August 2021 that reported the prevalence of mental health problems in the general population at two or more time points. A crowd of 114 reviewers extracted data on prevalence, study and participant characteristics. We collected information on the number of days since the first SARS-CoV-2 infection in the study country, the stringency of containment measures and the number of cases and deaths. We synthesised changes in prevalence during the pandemic using a random-effects model. We used dose-response meta-analysis to evaluate the trajectory of the changes in mental health problems.

Results

We included 41 studies for 7 mental health conditions. The average odds of symptoms increased during the pandemic (mean OR ranging from 1.23 to 2.08). Heterogeneity was very large and could not be explained by differences in participants or study characteristics. Average odds of psychological distress, depression and anxiety increased during the first 2 months of the pandemic, with increased stringency of the measures, reported infections and deaths. The confidence in the evidence was low to very low.

Conclusions

We observed an initial increase in the average risk of psychological distress, depression-related and anxiety-related problems during the first 2 months of the pandemic. However, large heterogeneity suggests that different populations had different responses to the challenges imposed by the pandemic.
Neurological disorders provoked by head and neck movement
Authors: Watson Neil
Published: June 2024

Neurologists encounter a range of neurological disorders triggered by head and neck movement, reflecting an array of underlying pathologies and producing diverse symptoms. This article provides a practically orientated review of 14 disorders and how to diagnose and manage them, including common disorders such as benign paroxysmal positional vertigo and uncommon entities such as arterial compression syndromes leading to stroke or syncope, mobile intraventricular masses and medication withdrawal states. The article considers atypical scenarios including unusual manifestations and important mimics and discusses controversial entities, as well as the risk of misattributing symptoms based on incidental imaging abnormalities. Guidelines are referenced where they exist, while in rarer situations, approaches taken in published cases are described, with the acknowledgement that management decisions are at the clinician’s discretion.
Artificial intelligence and regional anesthesiology education curriculum development: navigating the digital noise
Authors: Schroeder Kristopher M , Elkassabany Nabil
Published: June 2024

Artificial intelligence (AI) has demonstrated a disruptive ability to enhance and transform clinical medicine. While the dexterous nature of anesthesiology work offers some protections from AI clinical assimilation, this technology will ultimately impact the practice and augment the ability to provide an enhanced level of safe and data-driven care. Whether predicting difficulties with airway management, providing perioperative or critical care risk assessments, clinical-decision enhancement, or image interpretation, the indications for AI technologies will continue to grow and are limited only by our collective imagination on how best to deploy this technology.

An essential mission of academia is education, and challenges are frequently encountered when working to develop and implement comprehensive and effectively targeted curriculum appropriate for the diverse set of learners assigned to teaching faculty. Curriculum development in this context frequently requires substantial efforts to identify baseline knowledge, learning needs, content requirement, and education strategies. Large language models offer the promise of targeted and nimble curriculum and content development that can be individualized to a variety of learners at various stages of training. This technology has not yet been widely evaluated in the context of education deployment, but it is imperative that consideration be given to the role of AI in curriculum development and how best to deploy and monitor this technology to ensure optimal implementation.
NIR-sighted: A Programmable Streaming Architecture for Low-Energy Human-Centric Vision Applications
Authors: Mamish John , Alharbi Rawan , Sen Sougata , Holla Shashank , Kamath Panchami , Sangar Yaman , Alshurafa Nabil , Hester Josiah
Published: June 2024

Human studies often rely on wearable lifelogging cameras that capture videos of individuals and their surroundings to aid in visual confirmation or recollection of daily activities like eating, drinking, and smoking. However, this may include private or sensitive information that may cause some users to refrain from using such monitoring devices. Also, short battery lifetime and large form factors reduce applicability for long-term capture of human activity. Solving this triad of interconnected problems is challenging due to wearable embedded systems’ energy, memory, and computing constraints. Inspired by this critical use case and the unique design problem, we developed NIR-sighted, an architecture for wearable video cameras that navigates this design space via three key ideas: (i) reduce storage and enhance privacy by discarding masked pixels and frames, (ii) enable programmers to generate effective masks with low computational overhead, and (iii) enable the use of small MCUs by moving masking and compression off-chip. Combined together in an end-to-end system, NIR-sighted’s masking capabilities and off-chip compression hardware shrinks systems, stores less data, and enables programmer-defined obfuscation to yield privacy enhancement. The user’s privacy is enhanced significantly as nowhere in the pipeline is any part of the image stored before it is obfuscated. We design a wearable camera called NIR-sightedCam based on this architecture; it is compact and can record IR and grayscale video at 16 and 20+ fps, respectively, for 26 hours nonstop (59 hours with IR disabled) at a fraction of comparable platforms power draw. NIR-sightedCam includes a low-power Field Programmable Gate Array that implements our mJPEG compress/obfuscate hardware, Blindspot. We additionally show the potential for privacy-enhancing function and clinical utility via an in-lab eating study, validated by a nutritionist.
A Role and Reward Analysis in Off-chain Mechanisms for Executing MEV Strategies in Ethereum Proof-of-Stake
Authors: Mancino Davide , Leporati Alberto , Viviani Marco , Denaro Giovanni
Published: June 2024

Recently, the Ethereum blockchain changed its consensus algorithm from Proof-of-Work (PoW) to Proof-of-Stake (PoS). This change has greatly reduced overall energy consumption but has paved the way for the profiling of numerous mechanisms and actors that can operate off-chain to achieve Maximal Extractable Value (MEV). This raises questions about how transparent such a scenario is, both from the point of view of block validation power and from the point of view of the rewards achieved by distinct actors within the platform. To address this concern and to mitigate potential negative externalities, a permissionless ecosystem has recently been proposed that should be transparent and fair for the extraction of MEV. In this article, after briefly describing the new ecosystem, we conduct an in-depth analysis of Ethereum blocks and other information about the actors operating in the ecosystem, to highlight potential critical situations.
Sectored DRAM: A Practical Energy-Efficient and High-Performance Fine-Grained DRAM Architecture
Authors: Olgun Ataberk , Bostanci F. Nisa , Francisco de Oliveira Junior Geraldo , Tugrul Yahya Can , Bera Rahul , Yaglikci Abdullah Giray , Hassan Hasan , Ergin Oguz , Mutlu Onur
Published: June 2024

Modern computing systems access data in main memory at coarse granularity (e.g., at 512-bit cache block granularity). Coarse-grained access leads to wasted energy because the system does not use all individually accessed small portions (e.g.,
words
, each of which typically is 64 bits) of a cache block. In modern DRAM-based computing systems, two key coarse-grained access mechanisms lead to wasted energy: large and fixed-size (i) data transfers between DRAM and the memory controller and (ii) DRAM row activations.

We propose Sectored DRAM, a new, low-overhead DRAM substrate that reduces wasted energy by enabling fine-grained DRAM data transfer and DRAM row activation. To retrieve only useful data from DRAM, Sectored DRAM exploits the observation that many cache blocks are not fully utilized in many workloads due to poor spatial locality. Sectored DRAM predicts the words in a cache block that will likely be accessed during the cache block’s residency in cache and (i) transfers only the predicted words on the memory channel by dynamically tailoring the DRAM data transfer size for the workload and (ii) activates a smaller set of cells that contain the predicted words by carefully operating physically isolated portions of DRAM rows (i.e., mats). Activating a smaller set of cells on each access relaxes DRAM power delivery constraints and allows the memory controller to schedule DRAM accesses faster.

We evaluate Sectored DRAM using 41 workloads from widely used benchmark suites. Compared to a system with coarse-grained DRAM, Sectored DRAM reduces the DRAM energy consumption of highly memory intensive workloads by up to (on average) 33% (20%) while improving their performance by up to (on average) 36% (17%). Sectored DRAM’s DRAM energy savings, combined with its system performance improvement, allows system-wide energy savings of up to 23%. Sectored DRAM’s DRAM chip area overhead is 1.7% of the area of a modern DDR4 chip. Compared to state-of-the-art fine-grained DRAM architectures, Sectored DRAM greatly reduces DRAM energy consumption, does not reduce DRAM bandwidth, and can be implemented with low hardware cost. Sectored DRAM provides 89% of the performance benefits of, consumes 12% less DRAM energy than, and takes up 34% less DRAM chip area than a high-performance state-of-the-art fine-grained DRAM architecture (Half-DRAM). It is our hope and belief that Sectored DRAM’s ideas and results will help to enable more efficient and high-performance memory systems. To this end, we open source Sectored DRAM at https://github.com/CMU-SAFARI/Sectored-DRAM.
SAL: Optimizing the Dataflow of Spin-based Architectures for Lightweight Neural Networks
Authors: Zhao Yunping , Ma Sheng , Liu Hengzhu , Li Dongsheng
Published: June 2024

As the Convolutional Neural Network (CNN) goes deeper and more complex, the network becomes memory-intensive and computation-intensive. To address this issue, the lightweight neural network reduces parameters and Multiplication-and-Accumulation (MAC) operations by using the Depthwise Separable Convolution (DSC) to improve speed and efficiency. Nonetheless, the energy efficiency of classical Von Neumann architectures for CNNs is limited due to the memory wall challenge. Spin-based architectures have the potential to address this challenge thanks to the integration of memory and computing with ultra-high energy efficiency. However, deploying the DSC on spin-based architectures with the traditional dataflow leads to huge activation movements and low hardware utilization. Moreover, the inter-layer data dependency of neural networks increases latency. These factors become the bottleneck of improving energy efficiency and performance.

Inspired by these challenges, we propose a novel dataflow on Spin-based Architectures for Lightweight neural networks (SAL). The novel dataflow replaces convolution unrolling by selecting activations in the crossbar according to the convolution window and also realizes the inter-layer data reuse. Moreover, the novel dataflow also reduces the latency due to the data dependency between layers, realizing higher performance. To the best of our knowledge, this is the first design to use hybrid dataflow for the PIM architecture. We also optimize the structure of the spin-based crossbar and the pipeline based on the dataflow to achieve better data reuse and computational parallelism. For deploying the MobileNet V1, the novel dataflow improves the hardware utilization by 23×∼ 105× and reduces the data traffic by 1.09×∼ 18.6×. Compared with the NEBULA, a spin-based non-Von Neumann architecture, the SAL reduces the energy consumption by 4× and improves the performance by 7.3×, which are 0.32mJand 10.43GOPs-1, respectively. Moreover, the SAL improves power efficiency over 29 times more than the NEBULA. Compared with the Eyeriss, the SAL improves the energy efficiency by four orders of magnitude.
A Hop Away from Everywhere: A View of the Intercontinental Long-haul Infrastructure
Authors: Carisimo Esteban , Wang Caleb J. , Weaver Mia , Bustamante Fabián , Barford Paul
Published: June 2024

We present a longitudinal study of intercontinental long-haul links (LHL) - links with latencies significantly higher than that of all other links in a traceroute path. Our study is motivated by the recognition of these LHLs as a network-layer manifestation of transoceanic undersea cables. We present a methodology and associated processing system for identifying long-haul links in traceroute measurements, and report on our findings from. We apply this system to a large corpus of traceroute data and report on multiple aspects of long haul connectivity including country-level prevalence, routers as international gateways, preferred long-haul destinations, and the evolution of these characteristics over a 7 year period.
A Large Scale Study and Classification of VirusTotal Reports on Phishing and Malware URLs
Authors: Choo Euijin , Nabeel Mohamed , Kim Doowon , De Silva Ravindu , Yu Ting , Khalil Issa
Published: June 2024

VirusTotal (VT) is a widely used scanning service for researchers and practitioners to label malicious entities and predict new security threats. Unfortunately, it is little known to the end-users how VT URL scanners decide on the maliciousness of entities and the attack types they are involved in (e.g., phishing or malware-hosting websites). In this paper, we conduct a systematic comparative study on VT URL scanners' behavior for different attack types of malicious URLs, in terms of 1) detection specialties, 2) stability, 3) correlations between scanners, and 4) lead/lag behaviors. Our findings highlight that the VT scanners commonly disagree with each other on their detection and attack type classification, leading to challenges in ascertaining the maliciousness of a URL and taking prompt mitigation actions according to different attack types. This motivates us to present a new highly accurate classifier that helps correctly identify the attack types of malicious URLs at the early stage. This in turn assists practitioners in performing better threat aggregation and choosing proper mitigation actions for different attack types.
GuaNary: Efficient Buffer Overflow Detection In Virtualized Clouds Using Intel EPT-based Sub-Page Write Protection Support
Authors: Bitchebe Stella , Kone Yves , Olivier Pierre , Boukhobza Jalil , Bromberg Yérom-David , Hagimont Daniel , Tchana Alain
Published: June 2024

Buffer overflow is a widespread memory safety violation in C/C++, reported as the top vulnerability in 2022. Secure memory allocators are generally used to protect systems against attacks that may exploit buffer overflows. Existing allocators mainly rely on two types of countermeasures to prevent or detect overflows: canaries and guard pages, each with pros and cons in terms of detection latency and memory footprint.

This paper follows the Out of Hypervisor (OoH) trend for virtualized cloud applications. It introduces GuaNary, a novel safety guard against overflows allowing synchronous detection at a low memory footprint cost. OoH is a new virtualization research axis introduced in 2022 advocating the exposure of hardware features for virtualization to the guest OS so that its processes can take advantage of them. Based on the OoH principle, GuaNary leverages Intel Sub-Page write Permission (SPP), a recent hardware virtualization feature that allows to write-protect guest memory at the granularity of 128B (namely, sub-page) instead of 4KB. We implement a software stack, LeanGuard, which promotes the utilization of SPP from inside virtual machines by new secure allocators that use GuaNary. Our evaluation shows that for the same number of protected buffers, LeanGuard consumes 8.3x less memory than SlimGuard, a state-of-the-art secure allocator. Furthermore, for the same memory consumption, LeanGuard protecting 25x more buffers than SlimGuard.
Lightweight Acquisition and Ranging of Flows in the Data Plane
Authors: Monterubbiano Andrea , Langlet Jonatan , Walzer Stefan , Antichi Gianni , Reviriego Pedro , Pontarelli Salvatore
Published: June 2024

As networks get more complex, the ability to track almost all the flows is becoming of paramount importance. This is because we can then detect transient events impacting only a subset of the traffic. Solutions for flow monitoring exist, but it is getting very difficult to produce accurate estimations for every  tuple given the memory constraints of commodity programmable switches. Indeed, as networks grow in size, more flows have to be tracked, increasing the number of tuples to be recorded. At the same time, end-host virtualization requires more specific flowIDs, enlarging the memory cost for every single entry. Finally, the available memory resources have to be shared with other important functions as well (e.g., load balancing, forwarding, ACL).

To address those issues, we present FlowLiDAR (Flow Lightweight Detection and Ranging), a new solution that is capable of tracking almost all the flows in the network while requiring only a modest amount of data plane memory, which is not dependent on the size of flowIDs. We implemented the scheme in P4, tested it using real traffic from ISPs, and compared it against four state-of-the-art solutions: FlowRadar, NZE, PR-sketch, and Elastic Sketch.
Miracle or Mirage? A Measurement Study of NFT Rug Pulls
Authors: Huang Jintao , He Ningyu , Ma Kai , Xiao Jiang , Wang Haoyu
Published: June 2024

NFT rug pull is one of the most prominent type of NFT scam, whose definition is that the developers of an NFT project abandon it and run away with investors' funds. Although they have drawn attention from our community, to the best of our knowledge, the NFT rug pulls have not been systematically measured. To fill the void, this paper presents the first in-depth measurement study of NFT rug pulls. Specifically, we first compile a list of 253 known NFT rug pulls as our initial confirmed rug pulls (i.e., ground truth), based on which we perform a pilot study, highlighting the key symptoms of NFT rug pulls. Then, we design an effective rule-based detector to measure the prevalence of NFT rug pulls in the ecosystem. We have labelled 7,487 happened NFT rug pull projects which were not revealed by our community. To eliminate the potential damage brought by rug pull scams, we take a step further towards designing a real-time prediction model to proactively identify the potential rug pull projects in an early stage ahead of the scam happens. We have implemented a prototype system, and deployed it in the real-world setting for over 6 months. Our system has raised alarms for 5,557 new NFT projects, which works as a whistle blower that pinpoints rug pull scams timely, thus mitigating the impacts.
Prelimit Coupling and Steady-State Convergence of Constant-stepsize Nonsmooth Contractive SA
Authors: Zhang Yixuan , Huo Dongyan (Lucy) , Chen Yudong , Xie Qiaomin
Published: June 2024

Motivated by Q-learning, we study nonsmooth contractive stochastic approximation (SA) with constant stepsize. We focus on two important classes of dynamics: 1) nonsmooth contractive SA with additive noise, and 2) synchronous and asynchronous Q-learning, which features both additive and multiplicative noise. For both dynamics, we establish weak convergence of the iterates to a stationary limit distribution in Wasserstein distance. Furthermore, we propose a prelimit coupling technique for establishing steady-state convergence and characterize the limit of the stationary distribution as the stepsize goes to zero. Using this result, we derive that the asymptotic bias of nonsmooth SA is proportional to the square root of the stepsize, which stands in sharp contrast to smooth SA. This bias characterization allows for the use of Richardson-Romberg extrapolation for bias reduction in nonsmooth SA.
SCADA World: An Exploration of the Diversity in Power Grid Networks
Authors: Ortiz Neil , Cardenas Alvaro A. , Wool Avishai
Published: June 2024

Despite a growing interest in understanding the industrial control networks that monitor and control our critical infrastructures (such as the power grid), to date, SCADA networks have been analyzed in isolation from each other. They have been treated as monolithic networks without taking into consideration their differences. In this paper, we analyze real-world data from different parts of a power grid (generation, transmission, distribution, and end-consumer) and show that these industrial networks exhibit a variety of unique behaviors and configurations that have not been documented before. To the best of our knowledge, our study is the first to tackle the analysis of power grid networks at this level. Our results help us dispel several misconceptions proposed by previous work, and we also provide new insights into the differences and types of SCADA networks.
Parameters Optimization for Electrophoretic Deposition of Mn1.5Co1.5O4 on Ferritic Stainless Steel Based on Multi-Physical Simulation
Authors: Zhou Yaqin , Mao Jingwen , Wang Enhua , Zhang Hongguang
Published: June 2024

Solid oxide fuel cells (SOFCs) are an effective and sustainable energy conversion technology. As operating temperatures decrease, metal interconnects and supports are widely employed in SOFCs. It is critical to apply a protective coat on ferritic stainless steel (FSS) to suppress Cr evaporation and element interdiffusion under high temperatures. Electrophoretic deposition (EPD) is a promising approach for depositing metal oxides on FSS substrate. Here, a method based on 3D multi-physical simulation and orthogonal experimental design was proposed to optimize deposition parameters, including applied voltage, deposition time, and electrode distance. The EPD process to deposit Mn1.5Co1.5O4 particles in a suspension of ethanol and isopropanol was simulated and the effects of these three factors on the film thickness and uniformity were analyzed. The results indicate that applied voltage has the greatest impact on deposition thickness, followed by deposition time and electrode distance. Meanwhile, deposition time exhibits a more significant effect on film unevenness than applied voltage. Additionally, the particle-fluid coupling phenomenon was analyzed during the EPD process. In practice, these deposition parameters must be selected appropriately and the deposition time must be controlled to obtain a uniform coating. The proposed method can reduce cost and shorten the design period.
On Mixed Nonlinear Skew Lie (Jordan) Products on Von Neumann Algebras
Authors: Alhazmi Husain , Raza Mohd Arif , Khan Abdul Nadim , AL-Sobhi Tahani
Published: June 2024

Let and be von Neumann algebras. For , define by the skew Lie (Jordan) product of and . In this manuscript, we study a bijective mapping satisfying for all . Especially, we elaborate on the characteristics of the map Λ. The study revealed several constructive facts, leading to the conclusion that the map Λ is additive.
Fusobacterium nucleatum Bacteremia Presenting as Isolated Superior Mesenteric Vein Thrombophlebitis
Authors: Agarwal Alaukika , Yetiskul Ekrem , Patel Ronak , Qaqish Faris , Qandil Hamzah , Mobarakai Neville
Published: June 2024

Fusobacterium nucleatum (F. nucleatum) is a commensal Gram‐negative anaerobic bacterium that lives in the oral cavity and gastrointestinal tract of humans. While it is a regular resident of the human oral cavity, F. nucleatum has been implicated in various infections and inflammatory conditions. This case report highlights an unusual association between F. nucleatum and isolated superior mesenteric vein (SMV) thrombosis.
Supplementary Table S3 from m6A Modification Promotes EMT and Metastasis of Castration-Resistant Prostate Cancer by Upregulating NFIB
Authors: Shu Feng , Liu Hao , Chen Xiaohui , Liu Ye , Zhou Jiangli , Tang Lei , Cao Wanwei , Yang Shanshan , Long Yili , Li Rongna , Wang Hao , Wang Hongsheng , Jiang Guanmin
Published: June 2024

The differentially expressed genes in the DU145-shNFIB cells vs DU145-shNC cells was listed in Supplementary Table S3.
Supplementary Figures 1-4 from m6A Modification Promotes EMT and Metastasis of Castration-Resistant Prostate Cancer by Upregulating NFIB
Authors: Shu Feng , Liu Hao , Chen Xiaohui , Liu Ye , Zhou Jiangli , Tang Lei , Cao Wanwei , Yang Shanshan , Long Yili , Li Rongna , Wang Hao , Wang Hongsheng , Jiang Guanmin
Published: June 2024

This PDF contais Supplementary Figures 1-4.
Figure 6 from Deuterium Metabolic Imaging Differentiates Glioblastoma Metabolic Subtypes and Detects Early Response to Chemoradiotherapy
Authors: Low Jacob C.M. , Cao Jianbo , Hesse Friederike , Wright Alan J. , Tsyben Anastasia , Alshamleh Islam , Mair Richard , Brindle Kevin M.
Published: June 2024

Histologic assessment of tumor cell proliferation and cell death before and 24 hours after treatment. A-D, Representative sections of A11 and S2 tumors stained for Ki67 (A and B) and CC3 (C and D) pre- and posttreatment with chemoradiation. E-H, The percentage of Ki67-positive cells for A11 (E) and S2 (F) tumors and the percentage of CC3-positive cells for A11 (G) and S2 (H) tumors before and at 24 hours after completion of treatment. **, P < 0.01; ***, P < 0.001.
Figure 5 from Deuterium Metabolic Imaging Differentiates Glioblastoma Metabolic Subtypes and Detects Early Response to Chemoradiotherapy
Authors: Low Jacob C.M. , Cao Jianbo , Hesse Friederike , Wright Alan J. , Tsyben Anastasia , Alshamleh Islam , Mair Richard , Brindle Kevin M.
Published: June 2024

Imaging the effects of chemoradiation on glucose metabolism in tumor models representative of the glycolytic and mitochondrial subtypes. A-D, Representative spectra from voxels within the tumor and normal-appearing brain in 3D 2H chemical shift images of A11 (A and B) and S2 (C and D) tumor–bearing animals infused with 2 g/kg [6,6-2H2]glucose before (A and C) and after (B and D) treatment. Fits to the spectra are shown in color: red, water; green, glucose; blue, Glx; and purple, lactate. The tumor is outlined in yellow on the T2-weighted 1H image. The locations of the CSI voxels are indicated by the boxes. The spectra are the sum of six 10-minute spectra acquired from 3 × 3 × 9 mm voxels. Labeled glucose, Glx, and lactate concentrations were determined from summed spectra. E-J, Labeled glucose (E), Glx (F), and lactate (G) concentrations in A11 tumors before and after treatment, and labeled glucose (H), Glx (I), and lactate (J) concentrations in S2 tumors before and after treatment. ns, not significant; *, P < 0.05.
Supplemental Tables 1–3 from Fc-Silent Anti-TIGIT Antibodies Potentiate Antitumor Immunity without Depleting Regulatory T Cells
Authors: Piovesan Dana , de Groot Amber E. , Cho Soonweng , Anderson Amy E. , Ray Rebecca D. , Patnaik Amita , Foster Paul G. , Mitchell Casey G. , Lopez Espinoza Alejandra Y. , Zhu Wandi S. , Stagnaro Carlo E. , Singh Hema , Zhao Xiaoning , Seitz Lisa , Walker Nigel P. , Walters Matthew J. , Sivick Kelsey E.
Published: June 2024

Supplemental Tables 1–3
Figure S6 from Fc-Silent Anti-TIGIT Antibodies Potentiate Antitumor Immunity without Depleting Regulatory T Cells
Authors: Piovesan Dana , de Groot Amber E. , Cho Soonweng , Anderson Amy E. , Ray Rebecca D. , Patnaik Amita , Foster Paul G. , Mitchell Casey G. , Lopez Espinoza Alejandra Y. , Zhu Wandi S. , Stagnaro Carlo E. , Singh Hema , Zhao Xiaoning , Seitz Lisa , Walker Nigel P. , Walters Matthew J. , Sivick Kelsey E.
Published: June 2024

Figure S6
Table S1 from Oncogenic KRAS Induces Arginine Auxotrophy and Confers a Therapeutic Vulnerability to SLC7A1 Inhibition in Non–Small Cell Lung Cancer
Authors: Gai Xiameng , Liu Yingluo , Lan Xiaojing , Chen Luoyi , Yuan Tao , Xu Jun , Li Yize , Zheng Ying , Yan Yiyang , Yang Liya , Fu Yixian , Tang Shuai , Cao Siyuwei , Dai Xiaoyang , Zhu Hong , Geng Meiyu , Ding Jian , Pu Congying , Huang Min
Published: June 2024

Differential gene expression of BEAS-2B cells expressing KRAS-G12D or empty vector control
Figure S1 from Fc-Silent Anti-TIGIT Antibodies Potentiate Antitumor Immunity without Depleting Regulatory T Cells
Authors: Piovesan Dana , de Groot Amber E. , Cho Soonweng , Anderson Amy E. , Ray Rebecca D. , Patnaik Amita , Foster Paul G. , Mitchell Casey G. , Lopez Espinoza Alejandra Y. , Zhu Wandi S. , Stagnaro Carlo E. , Singh Hema , Zhao Xiaoning , Seitz Lisa , Walker Nigel P. , Walters Matthew J. , Sivick Kelsey E.
Published: June 2024

Figure S1
Supplementary Figure S6 from Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors
Authors: Zhang Weijie , Maeser Danielle , Lee Adam , Huang Yingbo , Gruener Robert F. , Abdelbar Israa G. , Jena Sampreeti , Patel Anand G. , Huang R. Stephanie
Published: June 2024

Supplementary Figure S6
Supplementary Figure S5 from Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors
Authors: Zhang Weijie , Maeser Danielle , Lee Adam , Huang Yingbo , Gruener Robert F. , Abdelbar Israa G. , Jena Sampreeti , Patel Anand G. , Huang R. Stephanie
Published: June 2024

Supplementary Figure S5
Supplementary Figure S2 from Integration of Pan-Cancer Cell Line and Single-Cell Transcriptomic Profiles Enables Inference of Therapeutic Vulnerabilities in Heterogeneous Tumors
Authors: Zhang Weijie , Maeser Danielle , Lee Adam , Huang Yingbo , Gruener Robert F. , Abdelbar Israa G. , Jena Sampreeti , Patel Anand G. , Huang R. Stephanie
Published: June 2024

Supplementary Figure S2
Data from m6A Modification Promotes EMT and Metastasis of Castration-Resistant Prostate Cancer by Upregulating NFIB
Authors: Shu Feng , Liu Hao , Chen Xiaohui , Liu Ye , Zhou Jiangli , Tang Lei , Cao Wanwei , Yang Shanshan , Long Yili , Li Rongna , Wang Hao , Wang Hongsheng , Jiang Guanmin
Published: June 2024

Abstract
The widespread use of androgen receptor (AR) signaling inhibitors has led to an increased incidence of AR-negative castration-resistant prostate cancer (CRPC), limiting effective treatment and patient survival. A more comprehensive understanding of the molecular mechanisms supporting AR-negative CRPC could reveal therapeutic vulnerabilities to improve treatment. This study showed that the transcription factor nuclear factor I/B (NFIB) was upregulated in patient with AR-negative CRPC tumors and cell lines and was positively associated with an epithelial-to-mesenchymal transition (EMT) phenotype. Loss of NFIB inhibited EMT and reduced migration of CRPC cells. NFIB directly bound to gene promoters and regulated the transcription of EMT-related factors E-cadherin (CDH1) and vimentin (VIM), independent of other typical EMT-related transcriptional factors. In vivo data further supported the positive role of NFIB in the metastasis of AR-negative CRPC cells. Moreover, N6-methyladenosine (m6A) modification induced NFIB upregulation in AR-negative CRPC. Mechanistically, the m6A levels of mRNA, including NFIB and its E3 ubiquitin ligase TRIM8, were increased in AR-negative CRPC cells. Elevated m6A methylation of NFIB mRNA recruited YTHDF2 to increase mRNA stability and protein expression. Inversely, the m6A modification of TRIM8 mRNA, induced by ALKBH5 downregulation, decreased its translation and expression, which further promoted NFIB protein stability. Overall, this study reveals that upregulation of NFIB, mediated by m6A modification, triggers EMT and metastasis in AR-negative CRPC. Targeting the m6A/NFIB axis is a potential prevention and treatment strategy for AR-negative CRPC metastasis.
Significance:
NFIB upregulation mediated by increased m6A levels in AR-negative castration-resistant prostate cancer regulates transcription of EMT-related factors to promote metastasis, providing a potential therapeutic target to improve prostate cancer treatment.