bluuebunny/crossref_metadata_2025 huggingface dataset:
Variable Length and Temperature-Dependent Analysis of MLGNR at Nano-Scale Regime
Authors: Sharma Himanshu , Sandha Karmjit Singh
Published: March 2024

In this paper, a thermally aware equivalent single conductor is proposed, along with analytical modeling to evaluate the parasitic parameters of multilayer graphene nanoribbon (MLGNR) as interconnect, and its performance is analyzed in terms of delay and power delay product (PDP) for 32[Formula: see text]nm, 22[Formula: see text]nm and 16[Formula: see text]nm technology nodes at variable global interconnect lengths (500–2000[Formula: see text]m). It was examined that with rising temperature, there is a strident decrease in the mean free path (MFP) of GNR interconnect, which further influences its own resistance at global length (2000[Formula: see text][Formula: see text]m) for all three technology nodes. The simulation tool Simulation Program with Integrated Circuit Emphasis (SPICE) is used to estimate and compare MLGNR performance in terms of signal delay and PDP for three different technology nodes. It is revealed from the outcomes that the propagation delay and PDP increase at long interconnects (500–2000[Formula: see text][Formula: see text]m) over a temperature range of 200–500[Formula: see text]K for deep submicron technology nodes (16[Formula: see text]nm, 22[Formula: see text]nm and 32[Formula: see text]nm). A similar investigation was performed on the copper interconnect, and it was discovered that the MLGNR performs better in terms of delay and PDP at global levels with a temperature range of 200–500[Formula: see text]K for nano-scaled technology nodes (32[Formula: see text]nm, 22[Formula: see text]nm and 16[Formula: see text]nm).
Infrared Emissivity–Resistivity Correlation of RU Thin Films for EUV Pellicle Applications
Authors: Hwang Jeongwoon , Kim Dongwook , Lee Yeonghun , Hwang Taesoon , Ahn Jinho , Cho Kyeongjae
Published: March 2024

A high-infrared (IR) emissivity is required to dissipate heat effectively from high-temperature surfaces even in a near-vacuum environment. This radiative cooling capability is essential for the emissive layer of EUV pellicles operating under high vacuum conditions with increasing EUV source powers to ensure thermomechanical stability. We compute the IR emissivity of metal films by combining the classical oscillator model and DFT calculations. Based on the calculations, we predict a positive correlation between the electrical resistivity and IR emissivity of metal films, which is consistent with a recent experiment on Ru thin films. Our findings can provide a practical indicator for achieving high IR emissivity of metallic thin films based on electrical measurements. This emissivity–resistivity correlation can provide an effective way to search a large material space, and choose and synthesize a highly emissive layer of EUV pellicles.
Efficient Dynamic IC Design Analysis Using Graph-Based Semi-Supervised Learning
Authors: Obert James , Hamlet Jason , Turner Sean
Published: March 2024

Graph analysis in large integrated circuit (IC) designs is an essential tool for verifying design logic and timing via dynamic analysis (DA). IC designs resemble graphs with each logic gate as a vertex and the conductive connections between gates as edges. Using DA digital statistical correlations, graph condensation, and graph partitioning, it is possible to identify anomalies in high-entropy component centers (HECCs) and paths within an IC design. Identification of HECC aids in DA signal integrity analysis when comparing design iterations which effectively lowers the computational complexity of DA within large IC graphs. In this paper, a devised methodology termed IC layout subgraph component center identification (CCI) is described. For design deviation analysis in DA, CCI lowers design computational complexity by identifying design deviations within an IC’s subgraphs. The CCI logic function signal integrity is verified using semi-supervised learning consisting of an unsupervised autoencoder anomaly detector to first identify anomalous subgraphs followed by efficient subgraph iterative refinement to locate specific deviated logic signals within the subgraphs.
The role of singlet oxygen and hydroxyl radical in the photobleaching of meso-substituted cationic pyridyl porphyrins in the presence of folic acid
Authors: Mkrtchyan Lusine , Seferyan Torgom , Parkhats Marina , Lepeshkevich Sergei , Dzhagarov Boris , Shmavonyan Gagik , Tuchina Elena , Tuchin Valery , Gyulkhandanyan Grigor
Published: March 2024

Using a photosensitizer (PS), light, and oxygen, photodynamic therapy creates cytotoxic reactive oxygen species, such as singlet oxygen (1O2), that kill cancer cells. Many cancer cell lines have up to 300 times more folic acid receptors than healthy cells. Therefore, folic acid is often used to improve selectivity of PSs. Photobleaching poses a disadvantage for PSs. In this paper, we have studied the photoinduced changes of meso-substituted cationic pyridyl porphyrins in the presence of folic acid using fluorescence and absorption spectroscopy. In this work, it was demonstrated that L-histidine, which is a 1O2 quencher, and D-mannitol, which is a hydroxyl radical quencher, can reduce photobleaching of cationic porphyrins and their interaction products with FA. This implies both singlet oxygen and hydroxyl radicals are involved in photobleaching. Additionally, our study revealed certain important features of the photobleaching of cationic porphyrins in the presence of folic acid.
In vivo 3-photon fluorescence microscopy of white matter in mouse brain excited at the 1700 nm window
Authors: Huang Jie , Zhong Jincheng , Tong Shen , Zhang Yingxian , Qiu Ping , Wang Ke
Published: March 2024

White matter, a densely packed collection of myelinated axons, plays an essential part in neural networks. With high spatial resolution and deep penetration, multi-photon microscopy (MPM) is promising for white matter imaging in animal models in vivo. The third harmonic generation (THG) signal can be generated from white matter, but the bottom part of the white matter layer generates weak THG due to its high scattering. Here, we demonstrate an in vivo labeling and imaging technology, capable of visualizing the white matter layer in the mouse brain, combining fluorescence labeling with MitoTracker Red and three-photon fluorescence (3PF) microscopy excited at the 1700 nm window. 3PF signals are several times higher than THG signals, resulting in deeper imaging of the white matter layer with the former. Our results indicate that 3PF microscopy is a promising technology for white matter imaging in the deep brain in vivo.
A modified fixed point iterative scheme based on Green’s function with application to BVPs
Authors: Ahmad Junaid , Arshad Muhammad
Published: March 2024

This paper presents a new faster iteration approach that is based upon the well-known three-step fixed point iteration scheme called SP-iterative scheme for a broad and larger class of non-linear BVPs. The scheme is constructed using Green’s function based integral operator and the new modified scheme in the paper will be called SP–Green’s iterative scheme. We present a fixed point convergence theorem using some assumption on the sequences of scalars in our scheme. We also prove the weak [Formula: see text]-stability for our scheme and present a numerical example to support our scheme. We provide eventually applications of our scheme to a second-order BVP and a singular BVP of isothermal gas sphere.
A Comprehensive Review on Low-Cost MEMS Accelerometers for Vibration Measurement: Types, Novel Designs, Performance Evaluation, and Applications
Authors: Binali Rüstem , Demirpolat Havva , Kuntoğlu Mustafa , Makhesana Mayur , Yaghoubi Saeed , Sayın Kul Bahar
Published: March 2024

Maintenance of mechanical elements is considered to be the most crucial task in industry and affects the economics, predominantly. There are many techniques available for fault diagnosis and condition monitoring of rotatory machine elements and one of the popular tools is vibration monitoring. Analyzing vibrations would be useful in supervising equipment/machine components in an attempt to detect the significant change which is the cause of growing failures or faults. Broadly speaking, it comes under prognostics and health monitoring (PHM) and prevents unexpected failure and costly repair. Proficient predictive monitoring and on-board recognition of failures is a need of the Fourth Industrial Revolution. Several types of vibration analyzers and sensors are commercially available, however, their total budget is not affordable. This motivates reviewing the suitability of low-cost sensors for vibration monitoring. An inclusive review of a variety of applications wherein microelectromechanical system (MEMS)-based accelerometer is used is presented in this paper. This would support an open-design movement for creating open.
X-Ray Crystallographic Analysis of Pr Modified BaTiO3 Ceramics with a Theoretical Perspective for Potential Applications in Microelectronics
Authors: Panigrahi Manas Ranjan
Published: March 2024

By examining the diffraction data, the microstructure of the ball-milled synthesized powder sample ([Formula: see text][Formula: see text]TiO3) was characterized. Through the application of Rietveld’s powder structure refinement approach to analyze X-ray powder diffraction data of ball-milled powder mixes, structural and microstructural alterations in terms of lattice defects have been assessed in the formation of single-phase praseodymium-modified BaTiO3. Bond lengths, bond angles, and generated locations of the [Formula: see text]Pr0[Formula: see text]TiO3 ceramic have been discussed about its generated structure. X-ray diffraction with respect to the first sharp diffraction peak (FSDP) is used to study the nanostructure of void species. General equations were utilized to determine various FSDP characteristics such as interlayer separation, correlation length, nanovoid diameter and scattering vector magnitude. Although the literature reports on many properties of Pr-modified barium titanate ceramic, this sample’s quantitative analysis and nanovoid determination are presented for the first time.
LENet: Lightweight and Effective Detector for Aerial Object
Authors: Zhou Xunkuai , Li Li , Chen Ben M.
Published: March 2024

Aerial object detection is crucial in various computer vision tasks, including video monitoring, early warning systems, and visual tracking. While current methods can accurately detect normal-sized objects, they face challenges distinguishing small objects from cluttered backgrounds. Developing methods that can be deployed on edge devices to achieve fast, accurate, and energy-efficient performance is also an urgent challenge. This paper proposes a network for aerial object detection by incorporating an attention mechanism to enhance feature extraction and elevate the accuracy of aerial moving object detection. Additionally, we optimize the channel dimensions of the feature extraction framework, resulting in a reduction in model parameters, acceleration of inference speed, and alleviation of the computational burden. Ulteriorly, we optimize the Spatial Pyramid Pooling (SPP) module to enhance detection accuracy and processing speed. Inspired by the ResNet and RepVGG structures, we design a feature fusion module to combine early-extracted features, improving speed and accuracy. Based on the design mentioned above principles, we develop a neural network method with an impressively small model size of only [Formula: see text][Formula: see text]M. The proposed approach achieves state-of-the-art performance on five benchmark datasets. Besides its superior performance, our method demonstrates excellent throughput on edge computing devices. Experimental results show that even when running on low-performance computing devices, the CPU and GPU temperatures remain below 50∘C and achieve a detection speed of 14.8 frames per second (fps) and power consumption of only 2.9[Formula: see text]W. These findings suggest that a high-accuracy, low-power, low-latency, and low-memory footprint aerial object detection solution is achievable.
Predicting root numbers with neural networks
Authors: Pozdnyakov Alexey
Published: March 2024

In this paper, we report on two machine learning experiments in search of statistical relationships between Dirichlet coefficients and root numbers or analytic ranks of certain low-degree [Formula: see text]-functions. The first experiment is to construct interpretable models based on murmurations, a recently discovered correlation between Dirichlet coefficients and root numbers. We show experimentally that these models achieve high accuracy by learning a combination of Mestre–Nagao-type heuristics and murmurations, noting that the relative importance of these features varies with degree. The second experiment is to search for a low-complexity statistic of Dirichlet coefficients that can be used to predict root numbers in polynomial time. We give experimental evidence and provide heuristics that suggest this cannot be done with standard machine learning techniques.
PACMNET, V2, CoNEXT1, March 2024 Editorial
Authors: Mellia Marco , Steenkiste Peter , Qiu Lili , Bonaventure Olivier
Published: March 2024

The Proceedings of the ACM on Networking (PACMNET) series present the highest-quality research conducted in the areas of emerging computer networks and their applications. We encourage submissions that present new technologies, novel experimentation, creative use of networking technologies, and new insights made possible using analysis. The journal is strongly supported by the ACM Special Interest Group on Communications and Computer Networks (SIGCOMM) and involves top-level researchers in its Editorial Board.

This issue contains four papers submitted for the June '23 deadline that were revised by their authors based on the extensive feedback provided by the reviewers.

We would like to thank the many individuals who contributed to this issue of PACMNET, in particular the authors, who submitted their best work to PACMNET, and the Associate Editors, who provided constructive feedback to the authors in their reviews, participated in the online discussions and the Editors' meeting. We would like also to thank the SIGCOMM Executive Committee Chair and the CoNEXT Steering Committee members who supported and guided us as usual.
Navigating the Complexity of Generative AI Adoption in Software Engineering
Authors: Russo Daniel
Published: March 2024

This article explores the adoption of Generative Artificial Intelligence (AI) tools within the domain of software engineering, focusing on the influencing factors at the individual, technological, and social levels. We applied a convergent mixed-methods approach to offer a comprehensive understanding of AI adoption dynamics. We initially conducted a questionnaire survey with 100 software engineers, drawing upon the Technology Acceptance Model, the Diffusion of Innovation Theory, and the Social Cognitive Theory as guiding theoretical frameworks. Employing the Gioia methodology, we derived a theoretical model of AI adoption in software engineering: the Human-AI Collaboration and Adaptation Framework. This model was then validated using Partial Least Squares–Structural Equation Modeling based on data from 183 software engineers. Findings indicate that at this early stage of AI integration, the compatibility of AI tools within existing development workflows predominantly drives their adoption, challenging conventional technology acceptance theories. The impact of perceived usefulness, social factors, and personal innovativeness seems less pronounced than expected. The study provides crucial insights for future AI tool design and offers a framework for developing effective organizational implementation strategies.
The IDEA of Us: An Identity-Aware Architecture for Autonomous Systems
Authors: Gavidia-Calderon Carlos , Kordoni Anastasia , Bennaceur Amel , Levine Mark , Nuseibeh Bashar
Published: March 2024

Autonomous systems, such as drones and rescue robots, are increasingly used during emergencies. They deliver services and provide situational awareness that facilitate emergency management and response. To do so, they need to interact and cooperate with humans in their environment. Human behaviour is uncertain and complex, so it can be difficult to reason about it formally. In this article, we propose IDEA: an adaptive software architecture that enables cooperation between humans and autonomous systems, by leveraging the social identity approach. This approach establishes that group membership drives human behaviour. Identity and group membership are crucial during emergencies, as they influence cooperation among survivors. IDEA systems infer the social identity of surrounding humans, thereby establishing their group membership. By reasoning about groups, we limit the number of cooperation strategies the system needs to explore. IDEA systems select a strategy from the equilibrium analysis of game-theoretic models that represent interactions between group members and the IDEA system. We demonstrate our approach using a search-and-rescue scenario, in which an IDEA rescue robot optimises evacuation by collaborating with survivors. Using an empirically validated agent-based model, we show that the deployment of the IDEA system can reduce median evacuation time by 13.6%.
Properties of Fairness Measures in the Context of Varying Class Imbalance and Protected Group Ratios
Authors: Brzezinski Dariusz , Stachowiak Julia , Stefanowski Jerzy , Szczech Izabela , Susmaga Robert , Aksenyuk Sofya , Ivashka Uladzimir , Yasinskyi Oleksandr
Published: March 2024

Society is increasingly relying on predictive models in fields like criminal justice, credit risk management, and hiring. To prevent such automated systems from discriminating against people belonging to certain groups, fairness measures have become a crucial component in socially relevant applications of machine learning. However, existing fairness measures have been designed to assess the bias between predictions for protected groups without considering the imbalance in the classes of the target variable. Current research on the potential effect of class imbalance on fairness focuses on practical applications rather than dataset-independent measure properties. In this article, we study the general properties of fairness measures for changing class and protected group proportions. For this purpose, we analyze the probability mass functions of six of the most popular group fairness measures. We also measure how the probability of achieving perfect fairness changes for varying class imbalance ratios. Moreover, we relate the dataset-independent properties of fairness measures described in this work to classifier fairness in real-life tasks. Our results show that measures such as Equal Opportunity and Positive Predictive Parity are more sensitive to changes in class imbalance than Accuracy Equality. These findings can help guide researchers and practitioners in choosing the most appropriate fairness measures for their classification problems.
Machine Learning in Metaverse Security: Current Solutions and Future Challenges
Authors: Otoum Yazan , Gottimukkala Navya , Kumar Neeraj , Nayak Amiya
Published: March 2024

The Metaverse, positioned as the next frontier of the Internet, has the ambition to forge a virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self-sustainability. Recent technological strides in AI, Extended Reality, 6G, and blockchain propel the Metaverse closer to realization, gradually transforming it from science fiction into an imminent reality. Nevertheless, the extensive deployment of the Metaverse faces substantial obstacles, primarily stemming from its potential to infringe on privacy and be susceptible to security breaches, whether inherent in its underlying technologies or arising from the evolving digital landscape. Metaverse security provisioning is poised to confront various foundational challenges owing to its distinctive attributes, encompassing immersive realism, hyper-spatiotemporally, sustainability, and heterogeneity. This article undertakes a comprehensive study of the security and privacy challenges facing the Metaverse, leveraging machine learning models for this purpose. In particular, our focus centers on an innovative distributed Metaverse architecture characterized by interactions across 3D worlds. Subsequently, we conduct a thorough review of the existing cutting-edge measures designed for Metaverse systems while also delving into the discourse surrounding security and privacy threats. As we contemplate the future of Metaverse systems, we outline directions for open research pursuits in this evolving landscape.
VORTEX : Visual phishing detectiOns aRe Through EXplanations
Authors: Charmet Fabien , Morikawa Tomohiro , Tanaka Akira , Takahashi Takeshi
Published: March 2024

Phishing attacks reached a record high in 2022, as reported by the Anti-Phishing Work Group, following an upward trend accelerated during the pandemic. Attackers employ increasingly sophisticated tools in their attempts to deceive unaware users into divulging confidential information. Recently, the research community has turned to the utilization of screenshots of legitimate and malicious websites to identify the brands that attackers aim to impersonate. In the field of Computer Vision, convolutional neural networks (CNNs) have been employed to analyze the visual rendering of websites, addressing the problem of phishing detection. However, along with the development of these new models, arose the need to understand their inner workings and the rationale behind each prediction. Answering the question, “How is this website attempting to steal the identity of a well-known brand?” becomes crucial when protecting end-users from such threats. In cybersecurity, the application of explainable AI (XAI) is an emerging approach that aims to answer such questions. In this article, we propose VORTEX, a phishing website detection solution equipped with the capability to explain how a screenshot attempts to impersonate a specific brand. We conduct an extensive analysis of XAI methods for the phishing detection problem and demonstrate that VORTEX provides meaningful explanations regarding the detection results. Additionally, we evaluate the robustness of our model against Adversarial Example attacks. We adapt these attacks to the VORTEX architecture and evaluate their efficacy across multiple models and datasets. Our results show that VORTEX achieves superior accuracy compared to previous models, and learns semantically meaningful patterns to provide actionable explanations about phishing websites. Finally, VORTEX demonstrates an acceptable level of robustness against adversarial example attacks.
TOMGPT: Reliable Text-Only Training Approach for Cost-Effective Multi-modal Large Language Model
Authors: Chen Yunkai , Wang Qimeng , Wu Shiwei , Gao Yan , Xu Tong , Hu Yao
Published: March 2024

Multi-modal large language models (MLLMs), such as GPT-4, exhibit great comprehension capabilities on human instruction, as well as zero-shot ability on new downstream multi-modal tasks. To integrate the different modalities within a unified embedding space, previous MLLMs attempted to conduct visual instruction tuning with massive and high-quality image-text pair data, which requires substantial costs in data collection and training resources. In this article, we propose TOMGPT (Text-Only training Multi-modal GPT), a cost-effective MLLM tuned solely on easily accessible text data with much fewer resources. Along with pre-trained visual-linguistic coupled modality space (e.g., CLIP and ALIGN model), a text-only training strategy is devised to further project the aligned multi-modal latent space to that of LLM, endowing the LLM with visual comprehension capabilities in an efficient manner. Instead of enormous image-text training data required by previous MLLMs, we find that TOMGPT can be well-tuned with fewer yet diverse GPT-generated free-form text data, as we establish the semantic connection between LLM and pre-trained vision-language model. A quantitative evaluation is conducted on both MME and LVLM, which are recently released and extensively utilized MLLM benchmarks. The experiments reveal that TOMGPT achieved reliable performance compared to numerous models trained on a large amount of image-text pair data. Case studies are also presented, demonstrating TOMGPT’s broad understanding and dialogue capabilities across diverse image categories.
One or Nothing: Anti-unification over the Simply-Typed Lambda Calculus
Authors: Cerna David M. , Buran Michal
Published: March 2024

Generalization techniques have many applications, including template construction, argument generalization, and indexing. Modern interactive provers can exploit advancement in generalization methods over expressive type theories to further develop proof generalization techniques and other transformations. So far, investigations concerned with anti-unification (AU) over λ-terms and similar type theories have focused on developing algorithms for well-studied variants. These variants forbid the nesting of generalization variables, restrict the structure of their arguments, and are
unitary
. Extending these methods to more expressive variants is important to applications. We consider the case of nested generalization variables and show that the AU problem is
nullary
(using
capture-avoiding
substitutions), even when the arguments to free variables are severely restricted.
Exploring the Potential of Large Language Models (LLMs)in Learning on Graphs
Authors: Chen Zhikai , Mao Haitao , Li Hang , Jin Wei , Wen Hongzhi , Wei Xiaochi , Wang Shuaiqiang , Yin Dawei , Fan Wenqi , Liu Hui , Tang Jiliang
Published: March 2024

Learning on Graphs has attracted immense attention due to its wide real-world applications. The most popular pipeline for learning on graphs with textual node attributes primarily relies on Graph Neural Networks (GNNs), and utilizes shallow text embedding as initial node representations, which has limitations in general knowledge and profound semantic understanding. In recent years, Large Language Models (LLMs) have been proven to possess extensive common knowledge and powerful semantic comprehension abilities that have revolutionized existing workflows to handle text data. In this paper, we aim to explore the potential of LLMs in graph machine learning, especially the node classification task, and investigate two possible pipelines: LLMs-as-Enhancers and LLMs-as-Predictors. The former leverages LLMs to enhance nodes' text attributes with their massive knowledge and then generate predictions through GNNs. The latter attempts to directly employ LLMs as standalone predictors. We conduct comprehensive and systematical studies on these two pipelines under various settings. From comprehensive empirical results, we make original observations and find new insights that open new possibilities and suggest promising directions to leverage LLMs for learning on graphs. Our codes and datasets are available at: https://github.com/CurryTang/Graph-LLM .
Faster stepping cadence partially explains the higher metabolic cost of walking among females versus males
Authors: Rayner Sophie E. , Pellerine Liam P. , Wu Yanlin , Shivgulam Madeline E. , Petterson Jennifer L. , Kimmerly Derek S. , O’Brien Myles W.
Published: March 2024

Whether there are sex differences in the metabolic cost of walking (MCOW) and the factors that may contribute to these are unclear. We demonstrate that females exhibit a larger net MCOW than males. These differences were largely attenuated when normalized to stepping cadence. Free-living activity was not associated with MCOW. We demonstrate that stepping cadence, but not free-living activity, partially explains the higher MCOW in females than males.
Long‐Term Performance and Durability of Heat‐Treated Alkali‐Activated Slag Mortar Containing Silica Fume
Authors: Sameti Naser , Ghiasvand Ebrahim , Zeighami Ehsanollah , Mirhosseini Seyyed Mohammad
Published: March 2024

This study aimed to investigate the combined influence of heat curing and partial replacement of silica fume on the long‐term behavior of alkali‐activated slag (AAS) mortar. Silica fume replacement levels of 0%, 5%, and 10% were examined, with curing conducted at temperatures of 23 ± 2 and 80°C. The alkaline activator consisted of sodium hydroxide solution (4 M) mixed with sodium silicate in a 3 : 1 ratio by weight. The performance of the fabricated specimens was evaluated through compressive strength testing, mass change analysis, X‐ray diffraction, and scanning electron microscopy. Heat treatment resulted in improved performance of AAS mortars, while silica fume replacement also positively influenced mortar behavior. Notably, the 5% replacement rate yielded the most favorable outcomes. However, it was observed that the long‐term compressive strength of AAS mortar specimens decreased significantly. Potential adverse factors contributing to this decline were discussed. Furthermore, the durability of mortar samples exposed to adverse conditions was investigated. Results indicated that the combined use of heat curing and a 5% silica fume replacement level produced the best overall performance.
Incidence of Helminthic and Viral Coinfections in Malaria Patients in the Tertiary Care Hospital Setup
Authors: Mubaraki Murad A. , Hussain Mubbashir , Fozia Fozia , Ahmad Ijaz , Khan Shahid Niaz , Qadir Khan Abdul , Ziaullah Ziaullah
Published: March 2024

Introduction. This study determines the incidence of common viral and helminth coinfections with malaria in the tertiary care hospital set up in southern Khyber Pakhtunkhwa, Pakistan. Materials and Methods. The multidimensional research included malaria patients admitted to different hospitals of district Kohat during January and December 2021. Stool samples and blood were assembled from the patients. Giemsa-stained microscopy-positive samples were processed by the immunochromatography technique (ICT) to identify Plasmodium species. Common viral infections such as viral hepatitis (A, B, and C), HIV, and dengue (DENV) were analyzed by ICT kits while SARS-CoV-2 was confirmed through real-time PCR. Furthermore, the intestinal helminths were identified using the Kato-Katz thick smear method. Results. Among 1278 patients, 548 were diagnosed with malaria, 412 (75.2%) were positive for P. vivax infection, 115 (21%) for P. falciparum, and 21 (3.8%) for mixed malaria infection (P. vivax/P. falciparum), with a higher incidence among males (65.2%) than females (34.8%). Coinfection with helminths was positive in 215 (39.3%) malaria patients. The most common infections were caused by the Ascaris lumbricoides species (42.6%) followed by Enterobius vermicularis (31.7%) and hookworm. A total of 24.6% of malaria-positive cases were also coinfected with different viruses with higher frequencies of confection for HAV (8.2%) and DENV (6.2%), respectively. The patients revealed higher incidence of coinfections with P. falciparum (57%) as compared with P. vivax (39.2%) and mixed infections (3.7%). Conclusion. This study demonstrated that the study population exhibited a significant incidence of coinfections with intestinal helminth and viral malaria.
Genome Sequencing of Idiopathic Speech Delay
Authors: Eising Else , Vino Arianna , Mabie Heather L. , Campbell Thomas F. , Shriberg Lawrence D. , Fisher Simon E.
Published: March 2024

Genetic investigations of people with speech and language disorders can provide windows into key aspects of human biology. Most genomic research into impaired speech development has so far focused on childhood apraxia of speech (CAS), a rare neurodevelopmental disorder characterized by difficulties with coordinating rapid fine motor sequences that underlie proficient speech. In 2001, pathogenic variants of FOXP2 provided the first molecular genetic accounts of CAS aetiology. Since then, disruptions in several other genes have been implicated in CAS, with a substantial proportion of cases being explained by high-penetrance variants. However, the genetic architecture underlying other speech-related disorders remains less well understood. Thus, in the present study, we used systematic DNA sequencing methods to investigate idiopathic speech delay, as characterized by delayed speech development in the absence of a motor speech diagnosis (such as CAS), a language/reading disorder, or intellectual disability. We performed genome sequencing in a cohort of 23 children with a rigorous diagnosis of idiopathic speech delay. For roughly half of the sample (ten probands), sufficient DNA was also available for genome sequencing in both parents, allowing discovery of de novo variants. In the thirteen singleton probands, we focused on identifying loss-of-function and likely damaging missense variants in genes intolerant to such mutations. We found that one speech delay proband carried a pathogenic frameshift deletion in SETD1A, a gene previously implicated in a broader variable monogenic syndrome characterized by global developmental problems including delayed speech and/or language development, mild intellectual disability, facial dysmorphisms, and behavioural and psychiatric symptoms. Of note, pathogenic SETD1A variants have been independently reported in children with CAS in two separate studies. In other probands in our speech delay cohort, likely pathogenic missense variants were identified affecting highly conserved amino acids in key functional domains of SPTBN1 and ARF3. Overall, this study expands the phenotype spectrum associated with pathogenic SETD1A variants, to also include idiopathic speech delay without CAS or intellectual disability, and suggests additional novel potential candidate genes that may harbour high-penetrance variants that can disrupt speech development.
Colposcopy Referral and CIN3+ Risk of Human Papillomavirus Genotyping Strategies in Cervical Cancer Screening
Authors: Kroon Kelsi R. , Bogaards Johannes A. , Heideman Daniëlle A.M. , Meijer Chris J.L.M. , Berkhof Johannes
Published: March 2024

Background:

High-risk human papillomavirus (hrHPV)-based cervical cancer screening in the Netherlands led to a substantial increase in number of colposcopy referrals and low-grade lesions detected. Genotyping strategies may be employed to lower the screening-related burden.

Methods:

We evaluated 14 triage strategies with genotyping (HPV16/18 or HPV16/18/31/33/45/52/58) for hrHPV-positive borderlineormilddyskaryosis (BMD)ornormal cytology,usingdata from a population-based hrHPV-based screening trial with 5-year interval (POBASCAM). We considered colposcopy referral at baseline, after 6-month repeat cytology and after 5-year hrHPV testing. Performance was evaluated by one-round positive and negative predictive value (PPVandNPV) for CIN3+ and by two-roundcolposcopy referral rate. To identify efficient strategies, they were ordered by the one-round colposcopy referral rate. Adjacent strategies were compared by the marginal PPV for detecting one additional CIN3+ (mPPV).

Results:

The most conservative strategy (repeat cytology after BMD and HPV16/18/31/33/45/52/58-positive normal cytology, next round otherwise) yielded an mPPV of 28%, NPV of 98.2%, and two-round colposcopy referral rate of 47.2%. Adding direct referral after BMD or genotype-positive BMD yielded an mPPV ≤ 8.2%, NPV ≥ 98.5% and an increase in colposcopy referral rate of 1.9% to 6.5%. Adding direct referral after HPV16/18-positive normal cytology yielded an mPPV ≤ 3.5%, NPV ≥ 99.5% and an increase in colposcopy referral rate of 13.9%.

Conclusions:

Direct colposcopy referral of women with BMD or normal cytology is unlikely to be efficient, but genotype-guided direct referral after BMD may be considered because the increase in colposcopies is limited.

Impact:

hrHPV screening programs can become very efficient when immediate colposcopy referral is limited to women at highest CIN3+ risk.

See related In the Spotlight, p. 979
PIGA Mutations and Glycosylphosphatidylinositol Anchor Dysregulation in Polyposis-Associated Duodenal Tumorigenesis
Authors: Meuser Elena , Chang Kyle , Walters Angharad , Hurley Joanna J. , West Hannah D. , Perry Iain , Mort Matthew , Reyes-Uribe Laura , Truscott Rebekah , Jones Nicholas , Lawrence Rachel , Jenkins Gareth , Giles Peter , Dolwani Sunil , Al-Sarireh Bilal , Hawkes Neil , Short Emma , Williams Geraint T. , Taggart Melissa W. , Luetchford Kim , Lynch Patrick M. , Terlouw Diantha , Nielsen Maartje , Walton Sarah-Jane , Latchford Andrew , Clark Susan K. , Sampson Julian R. , Vilar Eduardo , Thomas Laura E.
Published: March 2024

The pathogenesis of duodenal tumors in the inherited tumor syndromes familial adenomatous polyposis (FAP) and MUTYH-associated polyposis (MAP) is poorly understood. This study aimed to identify genes that are significantly mutated in these tumors and to explore the effects of these mutations. Whole exome and whole transcriptome sequencing identified recurrent somatic coding variants of phosphatidylinositol N-acetylglucosaminyltransferase subunit A (PIGA) in 19/70 (27%) FAP and MAP duodenal adenomas, and further confirmed the established driver roles for APC and KRAS. PIGA catalyzes the first step in glycosylphosphatidylinositol (GPI) anchor biosynthesis. Flow cytometry of PIGA-mutant adenoma-derived and CRISPR-edited duodenal organoids confirmed loss of GPI anchors in duodenal epithelial cells and transcriptional profiling of duodenal adenomas revealed transcriptional signatures associated with loss of PIGA.

Implications:

PIGA somatic mutation in duodenal tumors from patients with FAP and MAP and loss of membrane GPI-anchors may present new opportunities for understanding and intervention in duodenal tumorigenesis.
Diffuse Large B-Cell Lymphoma with Aberrant Coexpression of CD5 and CD8 T-Cell Markers
Authors: Fan Janet , Thanedar Sarita , Ovechko Vasily , Jana Bagi
Published: March 2024

Introduction: The expression of T-cell-associated antigens on diffuse large B-cell lymphoma (DLBCL) is uncommon. The coexpression of ≥2 T-cell-associated antigens on DLBCL is even rarer. This has been reported in the literature only a few times, most commonly coexpression of either CD5 or CD8 and a second, different T-cell marker. Case Presentation: This case report features a patient who presented with a rapidly evolving head and neck mass that displayed coexpression of CD5 and CD8. Conclusion: In this case report, we present the first case to our knowledge of DLBCL with coexpression of only CD5 and CD8.
Introducing Exome Sequencing as Part of the Diagnostic Algorithm for Pediatric Nephrology Patients in Bulgaria: A Single-Center Experience
Authors: Beltcheva Olga , Kamenarova Kunka , Zlatanova Galia , Mihova Kalina , Roussinov Dimitar , Kachakova Darina , Georgiev Martin , Nikolova Elena , Gaydarova Maria , Mitev Vanio , Kaneva Radka
Published: March 2024

Introduction: In pediatric kidney patients, where clinical presentation is often not fully developed, and renal biopsy is too risky or inconclusive, it may be difficult to establish the underlying pathology. In cases such as these, genetic diagnosis may be used to guide treatment, prognosis, and counseling. Given the large number of genes involved in kidney disease, introducing next-generation sequencing with extended gene panels as part of the diagnostic algorithm presents a viable solution. Methods: A cohort of 87 consecutive independent cases (83 children and 4 terminated pregnancies) with renal disease was recruited. Exome sequencing with MiSeq or NovaSeq 6000 (Illumina) platforms and analysis of extended gene panels were used for genetic testing. Results: Depending on the presenting pathology, the cases were grouped as patients with glomerular disease, ciliopathies, congenital anomalies, renal electrolyte imbalances, and chronic/acute kidney disease. The overall diagnostic yield was approximately 42% (37 out of 87), with most disease-causing mutations found in COL4A3, COL4A4, COL4A5, and PKHD1 genes. A change or clarification of preliminary diagnosis or adjustment of initial treatment plan based on the results of the genetic testing was made for approximately one-third of the children with meaningful genetic findings (11 out of 37). Discussion: Our results prove the value of targeted exome sequencing as a non-invasive, versatile, and reliable diagnostic tool for pediatric renal disease patients. Providing genetic diagnosis will help for a better understanding of disease etiology and will give the basis for optimal clinical management and insightful genetic counseling.
Trigenic COL4A3/COL4A4/COL4A5 Pathogenic Variants in Alport Syndrome: A Case Report
Authors: Rao Dipti , Maas Rutger , Cornelissen Marlies , Wetzels Jack , van Geel Michel
Published: March 2024

Alport syndrome (AS) is a hereditary kidney disorder of type IV collagen caused by pathogenic variants in the COL4A3, COL4A4, and COL4A5 genes. Previously several cases of digenic AS, caused by two pathogenic variants in two of the three COL4A genes, have been reported. Patients with digenic AS may present with a more severe phenotype compared to patients with single variants, depending on the percentage affected type IV trimeric collagen chain. We report a newly discovered case of trigenic AS. A 52-year-old female presented with hematuria at the age of 24 years and developed hypertension by the age of 30. Over the years, she developed chronic kidney disease; the most recent eGFR was 44 mL/min/1.73 m2. She has symmetric high-tone sensorineural hearing loss. Full genetic analysis revealed a heterozygous pathogenic variant c.2691del in COL4A3, a heterozygous pathogenic variant c.1663dup in COL4A4, and a complete heterozygous deletion of COL4A5. We describe the first patient with AS caused by pathogenic variants in all three COL4A genes, designated trigenic AS. This case report emphasizes the importance of examining all three COL4A genes, even in patients with a mild Alport phenotype, for optimal follow-up of the patient and adequate genetic counseling of family members.
A experiência de visita de famílias à exposição virtual “Aedes: que mosquito é esse?” do Museu da Vida (RJ)
Authors: Ribeiro Alice , Carneiro Jéssica Beck , Araujo Juliana Magalhães de , Silva Juliane Barros da , Massarani Luisa , Scalfi Graziele Aparecida de Moraes
Published: March 2024

Neste estudo, analisamos as interações de seis famílias em visita à exposição virtual “Aedes: que mosquito é esse?”, do Museu da Vida (RJ). Os objetivos foram: identificar as interações com a exposição e as conversas mais relevantes dos membros da família entre si durante as visitas; analisar aspectos de usabilidade e navegabilidade; e identificar especificidades do público familiar no que concerne à visitação virtual a museus e centros de ciências. A coleta de dados foi feita por meio de aplicação de questionário on-line e por gravação da tela e dos dados audiovisuais da família, com o uso do programa de livre acesso Flashback Recorder Express, durante a realização da visita, além de realização de entrevista semiestruturada on-line após a visita. Os dados foram categorizados e analisados, no caso dos dados audiovisuais, utilizando-se o software Dedoose. Os resultados indicaram valoração positiva da experiência de visitação, com protagonismo das crianças. Notamos que os membros da família conversam entre si para descobrir como se locomover e executar ações no ciberespaço; valorizam a possibilidade de interatividade e de aprendizado, sendo os totens interativos os que mais despertam interesse e emoções positivas; e buscam os textos expositivos de forma parcial, apesar do desinteresse na leitura. Quanto ao aspecto da virtualidade, além de barreiras associadas ao não funcionamento, o caráter imersivo é acompanhado por dificuldades com a usabilidade e navegabilidade, que, ainda que superáveis intuitivamente, associam-se a emoções negativas e poderiam ser minimizadas com o fornecimento de mais informações aos usuários
Praça do Derby, o pitoresco jardim recifense
Authors: Silva Joelmir Marques da , Silva Jônatas Souza Medeiros da , Ferreira Italo Cintra , Silva Pollyana Martins da
Published: March 2024

Derby Square is a relevant public space in Recife, recognized as a historic garden and Brazilian cultural heritage due to Burle Marx’s intervention in the 1930s. However, its construction dates back to the 1920s, the period of modernization of the city, with scarce discussions, until now, about its initial design. This article aims to contribute to the historiographical process of Derby Square, focusing mainly on the 1920s and 1930s, ranging from its construction to Burle Marx’s remodeling. To this end, the technique of indirect documentation was adopted, using primary written and visual sources not yet discussed or published, allowing an investigation, recording, analysis, and interpretation of events and the formulation of a new narrative. With this research, it is understood that Derby Square can be interpreted as a palimpsest, in which the elements of the different periods that make up its history are also responsible for highlighting this garden as cultural heritage.
Eu sei o que esse medicamento fez no verão passado: a farmacovigilância como um mecanismo de proteção ao consumidor
Authors: Raposo Vera Lúcia
Published: March 2024

Os medicamentos são, por sua própria natureza, produtos especialmente arriscados, em especial aqueles que acabaram de chegar ao mercado e foram desenvolvidos em um curto espaço de tempo, como as vacinas contra a covid-19. Os possíveis riscos que esses produtos podem apresentar para os pacientes/consumidores exigem medidas adicionais de proteção ao consumidor, além da estrutura jurídica geral de responsabilidade do fabricante. Este artigo se concentrou em uma dessas medidas adicionais: a farmacovigilância, ou seja, o monitoramento pós-comercialização de produtos farmacêuticos, sob a perspectiva da legislação europeia. O objetivo deste estudo foi demonstrar o papel da farmacovigilância na prevenção de danos causados por medicamentos defeituosos e na consequente proteção do consumidor, destacando seus benefícios e falhas. A farmacovigilância não é uma solução milagrosa e tem suas falhas. Entretanto, pode ser uma ferramenta útil para o gerenciamento da relação risco-benefício a fim de garantir o uso adequado de medicamentos após a comercialização. A responsabilidade por produtos defeituosos trata apenas da indenização por danos já ocorridos, enquanto a farmacovigilância intervém ex-ante para evitar a ocorrência de alguns desses danos.
Editorial
Authors: Machado Daniel
Published: March 2024

Geologia USP. Série Científica - Revista do Instituto de Geociências, USP.