bluuebunny/crossref_metadata_2025 huggingface dataset:
Kernel vs. User-Level Networking: Don't Throw Out the Stack with the Interrupts
Authors: Cai Peter , Karsten Martin
Published: June 2024

This paper reviews the performance characteristics of network stack processing for communication-heavy server applications. Recent literature often describes kernel-bypass and user-level networking as a silver bullet to attain substantial performance improvements, but without providing a comprehensive understanding of how exactly these improvements come about. We identify and quantify the direct and indirect costs of asynchronous hardware interrupt requests (IRQ) as a major source of overhead. While IRQs and their handling have a substantial impact on the effectiveness of the processor pipeline and thereby the overall processing efficiency, their overhead is difficult to measure directly when serving demanding workloads. This paper presents an indirect methodology to assess IRQ overhead by constructing preliminary approaches to reduce the impact of IRQs. While these approaches are not suitable for general deployment, their corresponding performance observations indirectly confirm the conjecture. Based on these findings, a small modification of a vanilla Linux system is devised that improves the efficiency and performance of traditional kernel-based networking significantly, resulting in up to 45% increased throughput without compromising tail latency. In case of server applications, such as web servers or Memcached, the resulting performance is comparable to using kernel-bypass and user-level networking when using stacks with similar functionality and flexibility.
Machine Learning Systems are Bloated and Vulnerable
Authors: Zhang Huaifeng , Alhanahnah Mohannad , Ahmed Fahmi Abdulqadir , Fatih Dyako , Leitner Philipp , Ali-Eldin Ahmed
Published: June 2024

Today's software is bloated with both code and features that are not used by most users. This bloat is prevalent across the entire software stack, from operating systems and applications to containers. Containers are lightweight virtualization technologies used to package code and dependencies, providing portable, reproducible and isolated environments. For their ease of use, data scientists often utilize machine learning containers to simplify their workflow. However, this convenience comes at a cost: containers are often bloated with unnecessary code and dependencies, resulting in very large sizes. In this paper, we analyze and quantify bloat in machine learning containers. We develop MMLB, a framework for analyzing bloat in software systems, focusing on machine learning containers. MMLB measures the amount of bloat at both the container and package levels, quantifying the sources of bloat. In addition, MMLB integrates with vulnerability analysis tools and performs package dependency analysis to evaluate the impact of bloat on container vulnerabilities. Through experimentation with 15 machine learning containers from TensorFlow, PyTorch, and Nvidia, we show that bloat accounts for up to 80% of machine learning container sizes, increasing container provisioning times by up to 370% and exacerbating vulnerabilities by up to 99%. For more detail, see the full paper, ~\citezhang2024machine.
Nautilus: A Framework for Cross-Layer Cartography of Submarine Cables and IP Links
Authors: Ramanathan Alagappan , Abdu Jyothi Sangeetha
Published: June 2024

Submarine cables constitute the backbone of the Internet. However, these critical infrastructure components are vulnerable to several natural and man-made threats, and during failures, are difficult to repair in remote oceans. In spite of their crucial role, we have a limited understanding of the impact of submarine cable failures on global connectivity, particularly on the higher layers of the Internet.

In this paper, we present Nautilus, a framework for cross-layer cartography of submarine cables and IP links. Using a corpus of public datasets and Internet cartographic techniques, Nautilus identifies IP links that are likely traversing submarine cables and maps them to one or more potential cables. Nautilus also gives each IP to cable assignment a prediction score that reflects the confidence in the mapping. Nautilus generates a mapping for 3.05 million and 1.43 million IPv4 and IPv6 links, respectively, spanning 91% of all active cables. In the absence of ground truth data, we validate Nautilus mapping using three techniques: analyzing past cable failures, using targeted traceroute measurements, and comparing with public network maps of two operators.
NetDiffusion: Network Data Augmentation Through Protocol-Constrained Traffic Generation
Authors: Jiang Xi , Liu Shinan , Gember-Jacobson Aaron , Bhagoji Arjun Nitin , Schmitt Paul , Bronzino Francesco , Feamster Nick
Published: June 2024

Datasets of labeled network traces are essential for a multitude of machine learning (ML) tasks in networking, yet their availability is hindered by privacy and maintenance concerns, such as data staleness. To overcome this limitation, synthetic network traces can often augment existing datasets. Unfortunately, current synthetic trace generation methods, which typically produce only aggregated flow statistics or a few selected packet attributes, do not always suffice, especially when model training relies on having features that are only available from packet traces. This shortfall manifests in both insufficient statistical resemblance to real traces and suboptimal performance on ML tasks when employed for data augmentation. In this paper, we apply diffusion models to generate high-resolution synthetic network traffic traces. We present NetDiffusion, a tool that uses a finely-tuned, controlled variant of a Stable Diffusion model to generate synthetic network traffic that is high fidelity and conforms to protocol specifications. Our evaluation demonstrates that packet captures generated from NetDiffusion can achieve higher statistical similarity to real data and improved ML model performance than current state-of-the-art approaches (e.g., GAN-based approaches). Furthermore, our synthetic traces are compatible with common network analysis tools and support a myriad of network tasks, suggesting that NetDiffusion can serve a broader spectrum of network analysis and testing tasks, extending beyond ML-centric applications.
Scalability Limitations of Processing-in-Memory using Real System Evaluations
Authors: Jonatan Gilbert , Cho Haeyoon , Son Hyojun , Wu Xiangyu , Livesay Neal , Mora Evelio , Shivdikar Kaustubh , Abellán José L. , Joshi Ajay , Kaeli David , Kim John
Published: June 2024

Processing-in-memory (PIM) has been widely explored in academia and industry to accelerate numerous workloads. By reducing the data movement and increasing parallelism, PIM offers great performance and energy efficiency. A large amount of cores or nodes present in PIM provide massive parallelism and compute throughput; however, this also proposes challenges and limitations for some workloads. In this work, we provide an extensive evaluation and analysis of a real PIM system from UPMEM. We specifically target emerging workloads featuring collective communication, demonstrating its role as the primary limitation within current PIM architecture.
StarShip: Mitigating I/O Bottlenecks in Serverless Computing for Scientific Workflows
Authors: Basu Roy Rohan , Tiwari Devesh
Published: June 2024

This work highlights the significance of I/O bottlenecks that data-intensive HPC workflows face in serverless environments - an issue that has been largely overlooked by prior works. We propose StarShip, a framework that leverages different storage options and multi-tier functions to reduce I/O overhead by co-optimizing for service time and service cost. StarShip leverages the Levenberg-Marquardt optimization to find an effective solution in a large, complex search space. It outperforms existing methods with a 45% improvement in service time and a 37.6% reduction in service cost.
Strategyproof Decision-Making in Panel Data Settings and Beyond
Authors: Harris Keegan , Agarwal Anish , Podimata Chara , Wu Zhiwei Steven
Published: June 2024

We consider the problem of decision-making using panel data, in which a decision-maker gets noisy, repeated measurements of multiple units (or agents). We consider the setup used in synthetic control methods, where there is a pre-intervention period when the principal observes the outcomes of each unit, after which the principal uses these observations to assign a treatment to each unit. Unlike this classical setting, we permit the units generating the panel data to be strategic, i.e. units may modify their pre-intervention outcomes in order to receive a more desirable intervention. The principal's goal is to design a strategyproof intervention policy, i.e. a policy that assigns units their utility-maximizing interventions despite their potential strategizing. We first identify a necessary and sufficient condition under which a strategyproof intervention policy exists, and provide a strategyproof mechanism with a simple closed form when one does exist. Along the way, we prove impossibility results for strategic multiclass classification, a natural extension of the well-studied (binary) strategic classification problem to the multiclass setting, which may be of independent interest. When there are two interventions, we establish that there always exists a strategyproof mechanism, and provide an algorithm for learning such a mechanism. For three or more interventions, we provide an algorithm for learning a strategyproof mechanism if there exists a sufficiently large gap in the principal's rewards between different interventions. Finally, we empirically evaluate our model using real-world panel data collected from product sales over 18 months. We find that our methods compare favorably to baselines which do not take strategic interactions into consideration, even in the presence of model misspecification.
TAO: Re-Thinking DL-based Microarchitecture Simulation
Authors: Pandey Santosh , Yazdanbakhsh Amir , Liu Hang
Published: June 2024

Microarchitecture simulators are indispensable tools for microarchitecture designers to validate, estimate, and optimize new hardware that meets specific design requirements. While the quest for a fast, accurate and detailed microarchitecture simulation has been ongoing for decades, existing simulators excel and fall short at different aspects: (i) Although execution-driven simulation is accurate and detailed, it is extremely slow and requires expert-level experience to design. (ii) Trace-driven simulation reuses the execution traces in pursuit of fast simulation but faces accuracy concerns and fails to achieve significant speedup. (iii) Emerging deep learning (DL)-based simulations are remarkably fast and have acceptable accuracy, but introduce substantial overheads from trace regeneration and model re-training when simulating a new microarchitecture.

Re-thinking the advantages and limitations of the aforementioned three mainstream simulation paradigms, this paper introduces TAO that redesigns the DL-based simulation with three primary contributions: First, we propose a new training dataset design such that the subsequent simulation (i.e., inference) only needs functional trace as inputs, which can be rapidly generated and reused across microarchitectures. Second, to increase the detail of the simulation, we redesign the input features and the DL model using self-attention to support predicting various performance metrics of interest. Third, we propose techniques to train a microarchitecture agnostic embedding layer that enables fast transfer learning between different microarchitectural configurations and effectively reduces the re-training overhead of conventional DL-based simulators. TAO can predict various performance metrics of interest, significantly reduce the simulation time, and maintain similar simulation accuracy as state-of-the-art DL-based endeavors.
Thorough Characterization and Analysis of Large Transformer Model Training At-Scale
Authors: Cheng Scott , Lin Jun-Liang , Emani Murali , Raskar Siddhisanket , Foreman Sam , Xie Zhen , Vishwanath Venkatram , Kandemir Mahmut T.
Published: June 2024

Large transformer models have recently achieved great success across various domains. With a growing number of model parameters, a large transformer model training today typically involves model sharding, data parallelism, and model parallelism. Thus, the throughput of large-scale model training depends heavily on the network bandwidth since a combination of model sharding and multiple parallelism strategies incurs various costs. However, prior characterizations of transformer models on high-bandwidth DGX machines that use TFLOPS as a metric may not reflect the performance of a system with lower bandwidth. Furthermore, data and model parallelism reveal significantly distinct training profiles on different system bandwidths at scale and, thus, need a thorough study.

In this paper, we provide a bottom-up breakdown of training throughput into compute and communication time, and quantitatively analyze their respective influences on overall end-to-end training scaling. Our evaluation involves an in-depth exploration of data parallelism, scaling up to 512 GPUs with limited bandwidth, and examines three model sharding strategies among six model sizes. We also evaluate three combinations of model parallelism on both high and low bandwidth supercomputing systems. Overall, our work provides a broader perspective on large-scale transformer model training, and our analysis and evaluation yield practical insights for predicting training scaling, shaping the future development of supercomputing system design.
Xaminer: An Internet Cross-Layer Resilience Analysis Tool
Authors: Ramanathan Alagappan , Sankaran Rishika , Abdu Jyothi Sangeetha
Published: June 2024

A resilient Internet infrastructure is critical in our highly interconnected society. However, the Internet faces several vulnerabilities, ranging from natural disasters to human activities, that can impact the physical layer and, in turn, the higher network layers, such as IP links. In this paper, we introduce Xaminer, the first Internet cross-layer resilience analysis tool, to evaluate the interplay between physical-and network-layer failures. Using a cross-layer Internet map and a failure event model, Xaminer generates a risk profile encompassing a cross-layer impact report, critical infrastructure identification at each layer, and the discovery of trends and patterns under different failure event settings. Xaminer's key strengths lie in its adaptability to diverse disaster scenarios, the ability to assess risks at various granularities, and the capability to generate joint risk profiles for multiple events. We demonstrate Xaminer's capabilities in cross-layer analysis across a spectrum of disaster event models and regions, showcasing its potential role in facilitating well-informed decision-making for resilience planning and deployments. The Xaminer tool is available as open-source software.
Eleanor Jack Gibson: A Life in Science
Authors: Spelke Elizabeth S.
Published: June 2024

Eleanor Gibson's groundbreaking research on perception, learning, and development challenged the tenets of behaviorist and introspectionist psychology and extended the scope of Helmholtzian psychophysics to forge a unified experimental, comparative, and developmental science of perception and learning. Gibson faced obstacles throughout her career: She held a full-time faculty position, with her own lab and students, for only 3 years. Nevertheless, she was remarkably productive and happy. Her rigorous, innovative experiments on adults, children, and animals brought new life to the study of perception and learning. Consistently and wisely, she viewed humans and animals as lifelong learners with intrinsic talents and penchants for perceiving, exploring, and discovering environmental structures and affordances. Her experiments placed the study of development at the center of interdisciplinary research on the origins and nature of knowledge and intelligence, inspiring current studies of the processes that give rise to knowledge in human minds, brains, and machines.
Shedding the Light on Powdery Mildew: The Use of Optical Irradiation in Management of the Disease
Authors: Suthaparan Aruppillai , Stensvand Arne
Published: June 2024

Ultraviolet (UV) irradiation below 300 nm may control powdery mildew in numerous crops. Depending on disease pressure, wavelength, and crop growth stage, one to three applications of 100–200 J/m2 per week at night are as effective or better than the best fungicides. Higher doses may harm the plants and reduce yields. Although red light alone or in combination with UV has a suppressive effect on powdery mildew, concomitant or subsequent exposure to blue light or UV-A strongly reduces the efficacy of UV treatments. To be effective, direct exposure of the pathogen/infection sites to UV/red light is important, but there are clear indications for the involvement of induced resistance in the host. Other pathogens and pests are susceptible to UV, but the effective dose may be phytotoxic. Although there are certain limitations, this technology is gradually becoming more used in both protected and open-field commercial production systems.
Leveraging the Surface Effect of Dual-Phase Lanthanum Dioxycarbonate to Sense Carbon Dioxide
Authors: Hsiao Yu-Jen , Fang Te-Hua , Ji Liang-Wen , Yang Shi-Hong
Published: June 2024

In this study, fabrication of dual phased La2O2CO3 films using an electrostatic spray technique was investigated and the developed films were used as CO2 gas sensors. Results demonstrated that La2O2CO3 films contained relatively high amounts of hexagonal phase formation when high concentrations of polyvinyl pyrrolidone (PVP) are used. Furthurmore, low concentrations of PVP yielded discontinuous films. The gas sensing results demonstrated that sensing efficiency can be improved by optimizing the concentration of PVP content. The results indicated that the highest response of 18% in the presence of 2000 ppm CO2 was attained by the film having a PVA concentration of 6 wt%. Structural and elemental analysis of La2O2CO3 films were verified using X-ray diffractometry, scanning electron microscopy, and energy-dispersive X-ray spectroscopy analyses. This study validates the sensing functionality of dual-phase La2O2CO3 films, which can function at gas concentrations that are as low as 800 ppm and are environmentally friendly.
Hydrothermal Preparation of Manganese Dioxide/Sulfur Doped Reduced Graphene Oxide and Construction of 4-Nitrotoluene Sensor
Authors: Khan Mohd Quasim , Ahmad Khursheed , Khan Rais Ahmad , Almadhhi Sultan Saad , Alsulmi Ali
Published: June 2024

Nitro-groups containing compounds are widely used in various applications but are considered highly toxic compounds. 4-nitrotoluene (4NT) belongs to the nitro-aromatic compounds and is a highly hazardous water contaminant. Thus, exploring new materials with excellent physiochemical and electrochemical properties is desirable for the construction of efficient 4NT sensors. The present study reports the fabrication of manganese dioxide/sulfur-doped reduced graphene oxide (α-MnO2/S@rGO) via hydrothermal synthesis procedure. The well-characterized α-MnO2/S@rGO was employed as a catalyst for the construction of α-MnO2/S@rGO modified screen printed carbon electrode (SPCE) for the detection of 4NT using cyclic voltammetry (CV). The α-MnO2/S@rGO modified electrode exhibits good electro-catalytic properties for the detection of 4NT compared to the bare SPCE, α-MnO2-, or S@rGO-modified electrodes. A reasonable detection limit of 0.5 μM with sensitivity of 1.97 μA.μM−1.cm−2 was obtained using α-MnO2/S@rGO modified electrode. The α-MnO2/S@rGO modified electrode demonstrated considerable selectivity for the sensing of 4NT in presence of various electro-active species. Note that the combination of catalytic α-MnO2 and conductive S@rGO present excellent synergistic interactions which improved the performance of the α-MnO2/S@rGO-modified electrode.
GLP-1RA therapy increases circulating vascular regenerative cell content in people living with type 2 diabetes
Authors: Park Brady , Krishnaraj Aishwarya , Teoh Hwee , Bakbak Ehab , Dennis Fallon , Quan Adrian , Hess David A. , Verma Subodh
Published: June 2024

In this post hoc subanalysis of 92 individuals living with T2D and at high cardiovascular risk, the authors summarize the differences in circulating vascular regenerative (VR) progenitor cell content between those on GLP-1RA therapy, on SGLT2 inhibitor without GLP-1RA therapy, and on neither therapy. Those on GLP-1RA therapy demonstrated greater circulating VR progenitor cell content and reduced proinflammatory granulocyte precursor content. These results offer novel mechanistic insights into the cardiometabolic benefits associated with GLP-1RA therapy.
Resilient Event Triggered Interval Type‐2 Fuzzy Sliding Mode Control for Connected and Autonomous Vehicles Subjected to Multiple Cyber Attacks
Authors: Mohammed Amir , Ramlal Craig , Marine Lincoln , Muddeen Fasil
Published: June 2024

Connected and autonomous vehicles (CAVs) are considered a hot area of research in the field of intelligent transportation systems. However, over the past few years, cybersecurity threats have posed significant challenges to such systems, given the ever‐evolving automotive industry. Thus, there is a growing need to design resilient control strategies to address the issue of cyberattacks. This article proposes the design of a distributed multiagent expert control scheme for cyberattack‐resilient control of CAVs. The study implemented an event‐triggered consensus‐based attack detection scheme capable of distinguishing between replay (RA), denial‐of‐service (DoS), and false data injection (FDI) attacks. The attacks in this study occur randomly, are bounded and time‐varying, and can overlap with each other. It was demonstrated that by considering an estimator error bound ε for the attacked signal reconstruction, the SMC controller in feedback with a vehicle remains stable in the sense of Lyapunov. Conditions were then provided that guarantee global asymptotic stability for a minimum dwell‐time constraint , and the platoon was shown to be string stable for the minimum distance between vehicles, denoted as . Finally, the performance of the control strategy was evaluated using multiple performance indices, considering platoons of varying sizes.
Microencapsulation, Physicochemical Characterization, and Antioxidant, Antibacterial, and Antiplasmodial Activities of Holothuria atra Microcapsule
Authors: Utami Prawesty Diah , Setianingsih Herin , Tirto Sari Dewi Ratih
Published: June 2024

This study provides the design of a microencapsulation formula, physicochemical characterization, and antioxidant, antibacterial, and antiplasmodial activities of Holothuria atra microcapsules. The ethanolic extract of H. atra was microencapsulated with chitosan (CHI) and sodium tripolyphosphate (Na‐TPP) with various stirring times: 60 minutes (CHI60), 90 minutes (CHI90), and 120 minutes (CHI120). The microcapsules were then observed for physicochemical properties using scanning electron microscopy (SEM) and Fourier‐transform infrared spectroscopy (FTIR). The microcapsules were tested for antioxidant activity and antibacterial activity against Staphylococcus aureus and Escherichia coli using the DPPH (2,2‐diphenyl‐1‐picrylhydrazyl) method. Antiplasmodial bioactivity was assessed through in silico molecular docking. The CHI60 and CHI120 microcapsules exhibited a smaller size and an irregular spherical shape, while the same FTIR profile was observed in CHI90 and CHI120. The bioactivity tests demonstrated that CHI90 exhibited high antibacterial activity against E. coli and S. aureus, while CHI120 exhibited high antioxidant performance. Calcigeroside B and Echinoside B exhibited antiplasmodial activity against the Plasmodium falciparum dihydroorotate dehydrogenase (PfDHODH) protein, along with an artemisinin inhibition mechanism. In conclusion, the microcapsules with the CHI90 formula demonstrated the best antibacterial activity, while the CHI120 formula exhibited high antioxidant activity. Two terpenoids, Calcigeroside B and Echinoside B, exhibited the best antiplasmodial activity.
Effects of Microwave Pretreatment on Licorice Cell Structure, Components Content, and Physical Properties
Authors: Luo Xiya , Xu Jian , Miao Yanyan , Guo Ling , Liu Yao , Fu Jian , Zhang Yongping
Published: June 2024

Microwave pretreatment, utilizing microwave thermal radiation to disrupt plant cell walls before the traditional extraction process, shows great promise in overcoming key challenges such as low extraction efficiency, high energy consumption, and excessive solvent usage in industrial licorice extraction. This study explored the effects of microwave pretreatment on cell structure, components content, and physical properties of licorice. Results revealed that microwave pretreatment disrupted the structural integrity of licorice cells, leading to a notable increase in the content of active ingredients. Specifically, the total of the five components peaked when treated at 500 W for 4 min. A comparison with the untreated group showed that glycyrrhizin, isoglycyrrhizin, liquiritigenin, isoliquiritigenin and glycyrrhizic acid increased by 29.09%, 25.09%, 21.82%, 16.04%, and 22.62%, respectively. Furthermore, differences in physical parameters such as electrical conductivity, solid content, pH, and relative density were observed between the microwave pretreated and untreated extracts, indicating variations in conductive substances, acidic components, substance quality, or types between the two extract groups. Infrared spectrum analysis demonstrated that microwave pretreatment did not alter the overall chemical composition of licorice extract, but increased the content of active substances such as flavonoids, saponins, amides, lipids, sugars, and proteins. In addition, the ratio of material to liquid postmicrowave pretreatment was 1 : 4, with each component’s content being equivalent to 1 : 12 in the untreated group. These findings provide strong evidence for the effectiveness of microwave pretreatment in enhancing the content of active ingredients in licorice, while simultaneously reducing solvent usage and energy consumption.
Simulation and Test Study of Blast Crater in Deep Ore Body of Metal Mine Based on Lsdyna
Authors: Dong Erhu , An Long , Li Yuanhui , Zhang Jiahua
Published: June 2024

The blast technology in metal mining is still the most important method of ore body mining. With the increase of mining depth, the blast process is more and more affected by the rock mechanical properties of the ore body, explosive properties, and crustal stress. In order to study the effects of rock physical and mechanical properties of the ore body, explosive detonation pressure and deep crustal stress on powder factor, blast action index and blast vibration. In this paper, a numerical simulation method under the fluid‐solid coupling algorithm of rock body and explosive is constructed by combining the on‐site blast crater test, Lsdyna JHC (Johnson Holmquist Concrete) damage model, and MATLAB parameter fitting algorithm. First, an exponential fitting function of the type “y = A × e(x/B) + C” is proposed to measure the rock body structure. Second, by modulating the strength and damage parameters and defining the unit failure criterion, the damage volume and blast action index obtained from the dynamic calculation are consistent with the 3D scanning results of the on‐site blast crater test. Finally, the difference in HHT (Hilbert–Huang Transform) analysis results between the vibration signals of the surrounding rock body in simulation and test is clarified. By combining the blast crater test of the ore body and the numerical simulation of Lsdyna, the prediction of powder factor, blast action index, and blast vibration intensity is realized, which provides a reference for the controlled blasting of the deep ore body.
Data 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

Abstract
Metabolic subtypes of glioblastoma (GBM) have different prognoses and responses to treatment. Deuterium metabolic imaging with 2H-labeled substrates is a potential approach to stratify patients into metabolic subtypes for targeted treatment. In this study, we used 2H magnetic resonance spectroscopy and magnetic resonance spectroscopic imaging (MRSI) measurements of [6,6′-2H2]glucose metabolism to identify metabolic subtypes and their responses to chemoradiotherapy in patient-derived GBM xenografts in vivo. The metabolism of patient-derived cells was first characterized in vitro by measuring the oxygen consumption rate, a marker of mitochondrial tricarboxylic acid cycle activity, as well as the extracellular acidification rate and 2H-labeled lactate production from [6,6′-2H2]glucose, which are markers of glycolytic activity. Two cell lines representative of a glycolytic subtype and two representative of a mitochondrial subtype were identified. 2H magnetic resonance spectroscopy and MRSI measurements showed similar concentrations of 2H-labeled glucose from [6,6′-2H2]glucose in all four tumor models when implanted orthotopically in mice. The glycolytic subtypes showed higher concentrations of 2H-labeled lactate than the mitochondrial subtypes and normal-appearing brain tissue, whereas the mitochondrial subtypes showed more glutamate/glutamine labeling, a surrogate for tricarboxylic acid cycle activity, than the glycolytic subtypes and normal-appearing brain tissue. The response of the tumors to chemoradiation could be detected within 24 hours of treatment completion, with the mitochondrial subtypes showing a decrease in both 2H-labeled glutamate/glutamine and lactate concentrations and glycolytic tumors showing a decrease in 2H-labeled lactate concentration. This technique has the potential to be used clinically for treatment selection and early detection of treatment response.
Significance:
Deuterium magnetic resonance spectroscopic imaging of glucose metabolism has the potential to differentiate between glycolytic and mitochondrial metabolic subtypes in glioblastoma and to evaluate early treatment responses, which could guide patient treatment.
Supplementary Data 8 from Comprehensive Genomic Profiling Alters Clinical Diagnoses in a Significant Fraction of Tumors Suspicious of Sarcoma
Authors: Öfverholm Ingegerd , Wallander Karin , Haglund Cecilia , Chellappa Venkatesh , Wejde Johan , Gellerbring Anna , Wirta Valtteri , Renevey Annick , Caceres Eva , Tsagkozis Panagiotis , Mayrhofer Markus , Papakonstantinou Andri , Linder-Stragliotto Christina , Bränström Robert , Larsson Olle , Lindberg Johan , Lin Yingbo , Haglund de Flon Felix
Published: June 2024

Table S8
A statistical testing strategy accounting for random and non-random (skewed) X-chromosome inactivation identifies lung cancer susceptibility loci among smokers
Authors: Jantzen Rodolphe , Camilleri-Broët Sophie , Ezer Nicole , Broët Philippe
Published: June 2024

Introduction: Lung cancer is the most common cancer worldwide in mortality and the second in incidence. Epidemiological studies found a higher lung cancer risk for smoking women in comparison to men, but these sex differences, irrespective of smoking habits, remains controversial. One of the hypotheses concerns the genetic contribution of the sex chromosomes. However, while genomewide association studies identified many lung cancer susceptibility loci, these analyses have excluded X-linked loci.
Methods: To account for non-genetic factors, we first presented an association test based on an additive-multiplicative hazard model accounting for random/non-random X-inactivation process. A simulation study was performed to investigate the properties of the proposed test as compared with the Wald test from a Cox model with random X-inactivation process and the partial likelihood ratio test proposed by Xu et al. accounting for non-random X-inactivation process. Then, we performed an X chromosome-wide association study on 9,261 individuals from the population based cohort CARTaGENE to identify susceptibility loci for lung cancer among current and past smokers. We adjusted for the PLCOm2012 lung cancer risk score used in screening programs.
Results: Simulation results show the good behavior of the proposed test in terms of power and Type I error probability as compared to the Xu et al. and the Wald test. Using the proposed test statistic and adjusting for the PLCOm2012 score, the X chromosome-wide statistical analysis identified two SNPs in low-linkage disequilibrium located in the IL1RAPL1 (IL-1 R accessory protein-like) gene: rs12558491 (p=2.75*10-9) and rs12835699 (p=1.26*10-6). For both SNPs, the minor allele was associated with lower lung cancer risk. Adjusting for multiple testing, no signal was detected using the Wald or the Xu et al. likelihood ratio tests.
Conclusion: By taking into account smoking behavior and the X-inactivation process, the investigation of the X chromosome has shed a new light on the association between X-linked loci and lung cancer. We identified two loci associated with lung cancer located in the IL1RAPL1 gene. This finding would have been overlooked by examining only results from other test statistics.
Exploring CHAPS as a Potential Measurement for Auditory Processing and Cognitive Ability in Children with Hearing Loss
Authors: Tuz Deniz , Bodur Ceren , Akti Beyza , Kılıç Samet , Kirazlı Gülce , Piştav Akmeşe Pelin
Published: June 2024

Objectives: The primary goal was to investigate the suitability of CHAPS for assessing cognitive abilities and auditory processing in people with hearing loss (HL), specifically in the domains of auditory processing, verbal working memory, and auditory attention. Method: The study comprised 44 individuals between the ages of seven and 14, 22 with HL (N = 11 males) and 22 with normal hearing (N = 10 males). Individuals’ auditory attention, working memory, and auditory processing skills were assessed in the study, and self-report questionnaires were used. The evaluation utilized the Sustained Auditory Attention Capacity Test (SAACT), Working Memory Scale (WMS), Filtered Words Test, Auditory Figured Ground Test (AFGT), and the Children’s Auditory Performance Scale (CHAPS). Analyses were conducted, including group comparisons, correlation examinations, and receiver operating characteristic evaluations. Results: There were significant differences in CHAPS total, attention, noise, quiet, and multiple inputs between groups. No significant differences were seen in CHAPS_ideal and CHAPS_auditory memory across groups. The study of SAACT and its subscores, WMS and its subscores, FWT, and AFGT revealed a significant difference between groups, caused by the poor performance of persons in the HL group compared to those in the NH group. The SAACT and its subscores correlated significantly with CHAPS_attention. The AUC calculation showed that The SAACT and CHAPS_attention distinguished persons with or without HL (p < 0.05). WMS_STM and WMS_total correlated with CHAPS auditory memory subscale; however, WMS_VWM did not. AUC values for WMS and its subscores showed significant discrimination in identifying children with or without HL (p < 0.05), whereas CHAPS_auditory memory did not (AUC = 0.665; p = 0.060). FWT and AFGT had a significant relationship with CHAPS_noise and CHAPS_multiple inputs subscales. The CHAPS_quiet and CHAPS_ideal subtests only correlated with AFGT. CHAPS_quite and CHAPS_ideal did not exhibit significant discriminative values (p < 0.05) for identifying children with or without HL, while CHAPS_noise, CHAPS_multiple inputs, FWT, and AFGT did. Conclusion: The CHAPS_attention subscale could be a trustworthy instrument for assessing auditory attention in children with HL. However, the CHAPS_auditory memory subscale may not be suitable for testing working memory. While performance-based auditory processing tests showed improved discrimination, the CHAPS_noise and CHAPS_multiple inputs subtests can still assess hearing-impaired auditory processing. The CHAPS_quiet and CHAPS_ideal subtests may not evaluate auditory processing.
Impact of distance learning on the university students’ academic performance and experiences
Authors: Olvido Michelle Mae Jugasan , Sanchez Joje Mar Perino , Alejandro Isidro Max Veloso
Published: June 2024

The COVID-19 pandemic has impacted the Asian educational sector, prompting countries to shift educational delivery to distance learning. With this, the researchers determined the impact of distance learning during the pandemic on students’ academic performance. Utilizing a mixed-methods design employing data mining and focus group discussions, pertinent student data (n=1,305) and qualitative responses (students, n=10; teachers, n=5) from a teacher education college in a state university in Central Visayas, Philippines, were obtained and analyzed through descriptive, correlational, and thematic analyses. The students had very good academic performances in general education, professional education, and specialization courses, and most of them had online capabilities, including gadgets and internet access. No significant relationships were observed between the student’s academic performance and their profiles and distance learning capacity. The distance learning experiences of students and teachers were themed as challenges in adoption, the reality of the digital divide, the journey of the self, the role of the community, and the learning process. In conclusion, students’ profiles and distance learning capacity are not determinants of academic performance, and their experiences reflect the sad reality of distance learning in the first stage of the pandemic.
Systematic literature review: effects of digital teaching materials on learning achievement
Authors: Djono Djono , Sudiyanto Sudiyanto , Sukmawati Fatma , Salimi Moh
Published: June 2024

This research aims to examine the effect of digital teaching materials based on their classification on learning achievement at various levels of education. The research design is a systematic literature review (SLR). The stages of conducting a review consist of three major parts: planning, conducting, and reporting. The articles reviewed in this study were drawn from reputable academic databases. The inclusion criteria for this research are as: i) indexed by Scopus; ii) the specified time is 15 years; iii) the research subjects must be students; iv) the minimum number of research participants is 15 people; and v) the article must be a scientific research article. The exclusion criteria in this study are article topics that are outside the field of education. The procedure used to analyze the results of the research obtained using a literature survey. The results showed that the advantages of digital teaching materials, in general, are: i) easy to apply; ii) low-cost; iii) highly flexible; and iv) broad. Each type of digital teaching material has several impacts on learning achievement, including: increasing scientific activities; improving students’ independent learning, self-reflection and metacognitive; reducing learning difficulties; and creating the impression that learning is fun.
Assessing graduates’ attributes and job performance for program curriculum enhancement
Authors: Albay Eduard M. , Aquino Ronald L. , Alambra Ralph Vincent E. , Eisma Delia V. , Quiambao Raquel D.
Published: June 2024

Graduate tracer studies are essential for higher education institutions (HEIs) as valuable information can be uncovered and derived that is useful for curriculum development, revision, or enhancement. This descriptive research study, using a questionnaire as the main data-gathering tool, determined the job attributes and job performance of the Bachelor of Science (BS) Mathematics graduates from 2013 to 2017 from a state university in the Philippines. Results revealed that the graduates were currently employed in various positions in both private and government institutions, with either permanent or contractual status. The graduates identified skills in mathematics, communication, computer, human relations, entrepreneurship, problem- solving, and critical thinking as vital in performing their duties and obligations in the workplace. Overall, the graduates’ job performance is outstanding. Based on the findings, suggestions to improve the BS Mathematics curriculum of the concerned HEIs were discussed to make it more relevant, responsive, adaptive, and inclusive.
Teachers’ autonomy and innovative work behavior: the mediating role of schools’ innovation climate
Authors: Mokhlis Safiek , Abdullah Abdul Hakim
Published: June 2024

For schools to maintain their competitiveness and enhance the standards of their education, they need to implement innovative approaches that allow them to stay abreast of the constantly changing technological, economic, and social environment. The success of these innovative approaches in schools relies heavily on teachers’ innovative work behavior (IWB), and so the role of teachers in this regard is pivotal. It is therefore crucial to determine the factors that affect teachers’ IWB. Thus, the purpose of the current study was to investigate the relationship between teachers’ autonomy, schools’ innovation climate, and IWB. A sample of teachers (n=376) from 12 primary and secondary schools in Kuala Terengganu, Malaysia, were surveyed through a questionnaire that was self-administered. Utilizing structural equation modelling with IBM AMOS version 24, schools’ innovation climate was found to have a full mediating role in the relationship between teachers’ autonomy and IWB. The findings suggest the important role of innovation climate in linking teachers’ autonomy to IWB and therefore have significant implications for school leaders.
Teachers’ self-perception of scientific competences: a gender approach
Authors: Garcés-Gómez Yeison Alberto , Alzate Valentina Cadavid , Rodríguez Ortiz Angélica María , Lara Escobar Rubén Darío
Published: June 2024

This study analyses the self-perception of 274 teachers from public, urban, and rural schools in Manizales, Colombia, using a Likert scale instrument developed considering the scientific competencies determined by UNESCO. In the analysis of the results, it was found that, even though in the sample analyzed, women have greater training in research and scientific competencies, their perception of their abilities in this aspect is lower than that of men. With the Mann-Whitney U test and rank-biserial correlation, it was possible to test the alternative hypothesis that the female self-perception of capabilities is lower than the male for each question. The instrument was validated with the internal consistency index with an α=0.98. Additionally, the instrument has been validated with a confirmatory factor analysis, obtaining values of comparative fit index (CFI) of 0.869 and Tucker-Lewis’s index (TLI) of 0.858 with RMSEA and SRMR of 0.103 and 0.063, respectively. The paper provides insights into the self-perception of scientific competencies among teachers, which can inform teacher training and professional development programs. The study highlighted the gender gap in self-perception of scientific competencies, which can inform policies and interventions to promote gender equity in science education.
Ensuring continuity in science education (on example of physics curriculum)
Authors: Nurmukhamedova Zhanara , Nurbayeva Dilara , Yerzhenbek Bulbul
Published: June 2024

The relevance of the research stems from the need to study the issues of continuity of the school and university curricula content in science disciplines on the example of the “physics” course. This study aims at identifying the principles of continuity of the content of school curricula and higher education programs in natural sciences in the example of the “physics” course, as well as disclosing methods to ensure the continuity of secondary and higher education in the Republic of Kazakhstan. The primary method in this study is system analysis, which is applied to examine the continuity of the school and university science curricula content, using the “physics” course as an example. Moreover, a theoretical analysis of recent scientific publications was carried out in the research process. The study deals with the problem of maintaining continuity in the general secondary education curricula in the field of natural sciences based on a renewed education program. The study presents the results of the analysis in the form of methodological suggestions and reveals possible barriers to the implementation of lifelong learning.
English for specific purposes curriculum evaluation from the social semiotic perspective
Authors: Sari Latifa Ika , Rukmini Dwi , Faridi Abdurrachman , Mujiyanto Januarius
Published: June 2024

This paper presents an evaluation of an English for specific purposes (ESP) curriculum using the social semiotic perspective. This perspective highlights the importance of authenticity, multimodality, and communicative competence in ESP teaching and learning. Five main components of the ESP curriculum at the Port and Shipping Management Department of a Maritime Polytechnic in Indonesia were evaluated, including the syllabus, lesson plans, resources, teaching activities, and assessment. In conducting the evaluation, the authors developed an evaluation framework based on three existing frameworks, namely Stufflebeam’s context input process product (CIPP) model for evaluation, Kaewpet’s ESP program evaluation, and Tsou and Chen’s ESP program evaluation. Multiple data collection methods were used and multiple perspectives of research participants were invited. The findings of the study revealed that there were several problems in the ESP curriculum of the Port and Shipping Management Department. The main problem was the poorly designed syllabus that has caused drawbacks on the other components, such as irrelevant and unauthentic teaching materials and activities, low variety of teaching media, lack of multimodal resources used in the classroom, and low validity and reliability of assessments. Pedagogical implications regarding the results of the evaluation are also discussed.
 
Psychology capital and organizational commitment of novice police: the mediation effect of career adaptability
Authors: Sutrisno Aristianto Budi , Suhariadi Fendy , Wijoyo Suparto , Aldhi Ian Firstian , Teofilus Teofilus , Hardaningtyas Dwi
Published: June 2024

This research aims to provide an understanding of the mechanisms underlying organizational commitment (OC) by utilizing psychological capital (PsyCap) as an antecedent and career adaptability (CA) as a mediator in this relationship. This study employs the conservation of resources (COR) theory to elucidate how PsyCap and CA can assist organizational members in enhancing OC when assessing the workforce quality in police settings. The study was conducted at police academy and state police school in Indonesia. The sampling technique adopted purposive sampling, targeting novice police totaling 417 individuals. Concerning the relationship between PsyCap and CA denoting a statistically significant positive relationship. This indicates that as PsyCap increases, CA tends to rise as well. The results demonstrate that the relationship between PsyCap and OC is not statistically significant. The relationship between CA and OC indicates an extremely significant positive relationship, meaning that a higher CA leads to an elevated OC. The indirect relationship between PsyCap and OC, when considering the mediating effect of CA on the relationship between PsyCap and OC, implies that PsyCap has a significant positive influence on OC through CA. It can be concluded that CA fully mediates the relationship between PsyCap and OC.