bluuebunny/crossref_metadata_2025 huggingface dataset:
Understanding the Role of Technology in Older Adults' Changing Social Support Networks
Authors: Wang Shengzhi , Carmeline Adoniah , Kolko Beth , Munson Sean A.
Published: April 2024

Technologies that facilitate communication between older adults and those around them have the potential to strengthen older adults' connections with their support network. In this paper, we present findings from interviews with 16 older adult participants in the United States about their social network composition and related technology use during a challenging life event, the COVID-19 pandemic, which saw a decrease of in-person meetings and increase in communication technology adoption. Using the convoy model of social relations, we sought to better understand the roles different technologies play in older adults' social connections. Participants chose what communication tools to use depending on social and situational contexts and overcame accessibility issues to adopt new technologies that supported continued engagement with their support networks. However, when others positioned technologies as ways for the older adults to receive social support, they resisted. A more comprehensive view of older adults' evolving social convoys can help designers and researchers better create technologies that help expand and maintain older adults' social support networks. Further, to facilitate older adults' social connectivity, the design of technology should encourage older adults' support networks to see those older adults as support providers, not just potential support recipients.
Using Speculative Design to Understand Preferred Futures for the Design and Use of Tracking Data in U.S. College Sport Teams
Authors: Kolovson Samantha , So Samuel , Munson Sean A.
Published: April 2024

US college sports teams are increasingly adopting personal data technologies, such as wearable sensors, with a goal of improving individual and team performance as well as individual safety. These tools can also reinforce the power that coaches hold over student-athletes and compromise student-athletes' needs for privacy and agency. To investigate preferred, and anti-preferred, approaches for navigating this complex sociotechnical challenge, we used a speculative design approach in which student athletes and technology design students developed three videos that portray tensions between student-athletes and coaches around the use of sports tracking technologies. We then shared these videos with 15 participants including student-athletes, coaches, and designers. Drawing on the perspectives of student-athletes, team staff, and designers embedded in the videos and expressed in reaction to the videos, we describe preferences for boundaries on tracking and sharing, how tracking data represent athletes, and for data practices. We also propose design requirements and recommendations for use to better align tracking technologies with these preferences.
Synthetiq: Fast and Versatile Quantum Circuit Synthesis
Authors: Paradis Anouk , Dekoninck Jasper , Bichsel Benjamin , Vechev Martin
Published: April 2024

To implement quantum algorithms on quantum computers it is crucial to decompose their operators into the limited gate set supported by those computers. Unfortunately, existing works automating this essential task are generally slow and only applicable to narrow use cases.We present Synthetiq, a method to synthesize quantum circuits implementing a given specification over arbitrary finite gate sets, which is faster and more versatile than existing works. Synthetiq utilizes Simulated Annealing instantiated with a novel, domain-specific energy function that allows developers to leverage partial specifications for better efficiency. Synthetiq further couples this synthesis method with a custom simplification pass, to ensure efficiency of the found circuits.

We experimentally demonstrate that Synthetiq can generate better implementations than were previously known for multiple relevant quantum operators including RCCCX, CCT, CCiSWAP, C√SWAP, and C√iSWAP. Our extensive evaluation also demonstrates Synthetiq frequently outperforms a wide variety of more specialized tools in their own domains, including (i) ‍the well-studied task of synthesizing fully specified operators in the Clifford+T gate set, (ii) ‍є-approximate synthesis of multi-qubit operators in the same gate set, and (iii) ‍synthesis tasks with custom gate sets. On all those tasks, Synthetiq is typically one to two orders of magnitude faster than previous state-of-the-art and can tackle problems that were previously out of the reach of any synthesis tool.
Finding Cross-Rule Optimization Bugs in Datalog Engines
Authors: Zhang Chi , Wang Linzhang , Rigger Manuel
Published: April 2024

Datalog is a popular and widely-used declarative logic programming language. Datalog engines apply many cross-rule optimizations; bugs in them can cause incorrect results. To detect such optimization bugs, we propose an automated testing approach called Incremental Rule Evaluation (IRE), which synergistically tackles the test oracle and test case generation problem. The core idea behind the test oracle is to compare the results of an optimized program and a program without cross-rule optimization; any difference indicates a bug in the Datalog engine. Our core insight is that, for an optimized, incrementally-generated Datalog program, we can evaluate all rules individually by constructing a reference program to disable the optimizations that are performed among multiple rules. Incrementally generating test cases not only allows us to apply the test oracle for every new rule generated—we also can ensure that every newly added rule generates a non-empty result with a given probability and eschew recomputing already-known facts. We implemented IRE as a tool named Deopt, and evaluated Deopt on four mature Datalog engines, namely Soufflé, CozoDB, μZ, and DDlog, and discovered a total of 30 bugs. Of these, 13 were logic bugs, while the remaining were crash and error bugs. Deopt can detect all bugs found by queryFuzz, a state-of-the-art approach. Out of the bugs identified by Deopt, queryFuzz might be unable to detect 5. Our incremental test case generation approach is efficient; for example, for test cases containing 60 rules, our incremental approach can produce 1.17× (for DDlog) to 31.02× (for Soufflé) as many valid test cases with non-empty results as the naive random method. We believe that the simplicity and the generality of the approach will lead to its wide adoption in practice.
Outcome Separation Logic: Local Reasoning for Correctness and Incorrectness with Computational Effects
Authors: Zilberstein Noam , Saliling Angelina , Silva Alexandra
Published: April 2024

Separation logic’s compositionality and local reasoning properties have led to significant advances in scalable static analysis. But program analysis has new challenges—many programs displaycomputational effectsand, orthogonally, static analyzers must handleincorrectnesstoo. We present Outcome Separation Logic (OSL), a program logic that is sound for both correctness and incorrectness reasoning in programs with varying effects. OSL has a frame rule—just like separation logic—but uses different underlying assumptions that open up local reasoning to a larger class of properties than can be handled by any single existing logic.

Building on this foundational theory, we also define symbolic execution algorithms that use bi-abduction to derive specifications for programs with effects. This involves a newtri-abductionprocedure to analyze programs whose execution branches due to effects such as nondeterministic or probabilistic choice. This work furthers the compositionality promised by separation logic by opening up the possibility for greater reuse of analysis tools across two dimensions: bug-finding vs verification in programs with varying effects.
AdoB: Bridging Benign and Byzantine Consensus with Atomic Distributed Objects
Authors: Honoré Wolf , Qiu Longfei , Kim Yoonseung , Shin Ji-Yong , Kim Jieung , Shao Zhong
Published: April 2024

Achieving consensus is a challenging and ubiquitous problem in distributed systems that is only made harder by the introduction of malicious byzantine servers. While significant effort has been devoted to the benign and byzantine failure models individually, no prior work has considered the mechanized verification of both in a generic way. We claim this is due to the lack of an appropriate abstraction that is capable of representing both benign and byzantine consensus without either losing too much detail or becoming impractically complex. We build on recent work on the atomic distributed object model to fill this void with a novel abstraction called AdoB. In addition to revealing important insights into the essence of consensus, this abstraction has practical benefits for easing distributed system verification. As a case study, we proved safety and liveness properties for AdoB in Coq, which are the first such mechanized proofs to handle benign and byzantine consensus in a unified manner. We also demonstrate that AdoB faithfully models real consensus protocols by proving it is refined by standard network-level specifications of Fast Paxos and a variant of Jolteon.
PROMPT: A Fast and Extensible Memory Profiling Framework
Authors: Xu Ziyang , Chon Yebin , Su Yian , Tan Zujun , Apostolakis Sotiris , Campanoni Simone , August David I.
Published: April 2024

Memory profiling captures programs’ dynamic memory behavior, assisting programmers in debugging, tuning, and enabling advanced compiler optimizations like speculation-based automatic parallelization. As each use case demands its unique program trace summary, various memory profiler types have been developed. Yet, designing practical memory profilers often requires extensive compiler expertise, adeptness in program optimization, and significant implementation effort. This often results in a void where aspirations for fast and robust profilers remain unfulfilled. To bridge this gap, this paper presents PROMPT, a framework for streamlined development of fast memory profilers. With PROMPT, developers need only specify profiling events and define the core profiling logic, bypassing the complexities of custom instrumentation and intricate memory profiling components and optimizations. Two state-of-the-art memory profilers were ported with PROMPT where all features preserved. By focusing on the core profiling logic, the code was reduced by more than 65% and the profiling overhead was improved by 5.3× and 7.1× respectively. To further underscore PROMPT’s impact, a tailored memory profiling workflow was constructed for a sophisticated compiler optimization client. In 570 lines of code, this redesigned workflow satisfies the client’s memory profiling needs while achieving more than 90% reduction in profiling overhead and improved robustness compared to the original profilers.
Enhancing Static Analysis for Practical Bug Detection: An LLM-Integrated Approach
Authors: Li Haonan , Hao Yu , Zhai Yizhuo , Qian Zhiyun
Published: April 2024

While static analysis is instrumental in uncovering software bugs, its precision in analyzing large and intricate codebases remains challenging. The emerging prowess of Large Language Models (LLMs) offers a promising avenue to address these complexities. In this paper, we present LLift, a pioneering framework that synergizes static analysis and LLMs, with a spotlight on identifying use-before-initialization (UBI) bugs within the Linux kernel. Drawing from our insights into variable usage conventions in Linux, we enhance path analysis using post-constraint guidance. This approach, combined with our methodically crafted procedures, empowers LLift to adeptly handle the challenges of bug-specific modeling, extensive codebases, and the unpredictable nature of LLMs. Our real-world evaluations identified four previously undiscovered UBI bugs in the mainstream Linux kernel, which the Linux community has acknowledged. This study reaffirms the potential of marrying static analysis with LLMs, setting a compelling direction for future research in this area.
Inductive Diagrams for Causal Reasoning
Authors: Castello Jonathan , Redmond Patrick , Kuper Lindsey
Published: April 2024

The Lamport diagram is a pervasive and intuitive tool for informal reasoning about “happens-before” relationships in a concurrent system. However, traditional axiomatic formalizations of Lamport diagrams can be painful to work with in a mechanized setting like Agda. We propose an alternative, inductive formalization — the
causal separation diagram
(CSD) — that takes inspiration from string diagrams and concurrent separation logic, but enjoys a graphical syntax similar to Lamport diagrams. Critically, CSDs are based on the idea that causal relationships between events are witnessed by the
paths
that information follows between them. To that end, we model “happens-before” as a dependent type of paths between events.

The inductive formulation of CSDs enables their
interpretation
into a variety of semantic domains. We demonstrate the interpretability of CSDs with a case study on properties of
logical clocks
, widely-used mechanisms for reifying causal relationships as data. We carry out this study by implementing a series of interpreters for CSDs, culminating in a generic proof of Lamport’s
clock condition
that is parametric in a choice of clock. We instantiate this proof on Lamport’s scalar clock, on Mattern’s vector clock, and on the matrix clocks of Raynal et al. and of Wuu and Bernstein, yielding verified implementations of each. The CSD formalism and our case study are mechanized in the Agda proof assistant.
Hydra: Generalizing Peephole Optimizations with Program Synthesis
Authors: Mukherjee Manasij , Regehr John
Published: April 2024

Optimizing compilers rely on peephole optimizations to simplify
combinations of instructions and remove redundant instructions.
Typically, a new peephole optimization is added when a compiler
developer notices an optimization opportunity---a collection of
dependent instructions that can be improved---and manually derives a
more general rewrite rule that optimizes not only the original code,
but also other, similar collections of instructions.
In this paper, we present Hydra, a tool that automates the process of
generalizing peephole optimizations using a collection of techniques
centered on program synthesis.
One of the most important problems we have solved is finding a version
of each optimization that is independent of the bitwidths of the
optimization's inputs (when this version exists).
We show that Hydra can generalize 75% of the ungeneralized missed
peephole optimizations that LLVM developers have posted to the LLVM
project's issue tracker.
All of Hydra's generalized peephole optimizations have been formally
verified, and furthermore we can automatically turn them into C++ code
that is suitable for inclusion in an LLVM pass.
Accurate Data Race Prediction in the Linux Kernel through Sparse Fourier Learning
Authors: Ryan Gabriel , Cetin Burcu , Lim Yongwhan , Jana Suman
Published: April 2024

Testing for data races in the Linux OS kernel is challenging because there is an exponentially large space of system calls and thread interleavings that can potentially lead to concurrent executions with races. In this work, we introduce a new approach for modeling execution trace feasibility and apply it to Linux OS Kernel race prediction. To address the fundamental scalability challenge posed by the exponentially large domain of possible execution traces, we decompose the task of predicting trace feasibility into independent prediction subtasks encoded as learning Boolean indicator functions for specific memory accesses, and apply a sparse fourier learning approach to learning each feasibility subtask.

Boolean functions that are sparse in their fourier domain can be efficiently learned by estimating the coefficients of their fourier expansion. Since the feasibility of each memory access depends on only a few other relevant memory accesses or system calls (e.g., relevant inter-thread communications), we observe that trace feasibility functions often have this sparsity property and can be learned efficiently. We use learned trace feasibility functions in conjunction with conservative alias analysis to implement a kernel race-testing system, HBFourier, that uses sparse fourier learning to efficiently model feasibility when making predictions. We evaluate our approach on a recent Linux development kernel and show it finds 44 more races with 15.7% more accurate race predictions than the next best performing system in our evaluation, in addition to identifying 5 new race bugs confirmed by kernel developers.
Exact Bayesian Inference for Loopy Probabilistic Programs using Generating Functions
Authors: Klinkenberg Lutz , Blumenthal Christian , Chen Mingshuai , Haase Darion , Katoen Joost-Pieter
Published: April 2024

We present an exact Bayesian inference method for inferring posterior distributions encoded by probabilistic programs featuring possibly
unbounded loops
. Our method is built on a denotational semantics represented by
probability generating functions
, which resolves semantic intricacies induced by intertwining discrete probabilistic loops with
conditioning
(for encoding posterior observations). We implement our method in a tool called Prodigy; it augments existing computer algebra systems with the theory of generating functions for the (semi-)automatic inference and quantitative verification of conditioned probabilistic programs. Experimental results show that Prodigy can handle various infinite-state loopy programs and exhibits comparable performance to state-of-the-art exact inference tools over loop-free benchmarks.
Functional Ownership through Fractional Uniqueness
Authors: Marshall Daniel , Orchard Dominic
Published: April 2024

Ownership and borrowing systems, designed to enforce safe memory management without the need for garbage collection, have been brought to the fore by the Rust programming language. Rust also aims to bring some guarantees offered by functional programming into the realm of performant systems code, but the type system is largely separate from the ownership model, with type and borrow checking happening in separate compilation phases. Recent models such as RustBelt and Oxide aim to formalise Rust in depth, but there is less focus on integrating the basic ideas into more traditional type systems. An approach designed to expose an essential core for ownership and borrowing would open the door for functional languages to borrow concepts found in Rust and other ownership frameworks, so that more programmers can enjoy their benefits.

One strategy for managing memory in a functional setting is through uniqueness types, but these offer a coarse-grained view: either a value has exactly one reference, and can be mutated safely, or it cannot, since other references may exist. Recent work demonstrates that linear and uniqueness types can be combined in a single system to offer restrictions on program behaviour and guarantees about memory usage. We develop this connection further, showing that just as graded type systems like those of Granule and Idris generalise linearity, a Rust-like ownership model arises as a graded generalisation of uniqueness. We combine fractional permissions with grading to give the first account of ownership and borrowing that smoothly integrates into a standard type system alongside linearity and graded types, and extend Granule accordingly with these ideas.
VeriEQL: Bounded Equivalence Verification for Complex SQL Queries with Integrity Constraints
Authors: He Yang , Zhao Pinhan , Wang Xinyu , Wang Yuepeng
Published: April 2024

The task of SQL query equivalence checking is important in various real-world applications (including query rewriting and automated grading) that involve complex queries with integrity constraints; yet, state-of-the-art techniques are very limited in their capability of reasoning about complex features (e.g., those that involve sorting, case statement, rich integrity constraints, etc.) in real-life queries. To the best of our knowledge, we propose the first SMT-based approach and its implementation, VeriEQL, capable of proving and disproving bounded equivalence of complex SQL queries. VeriEQL is based on a new logical encoding that models query semantics over symbolic tuples using the theory of integers with uninterpreted functions. It is simple yet highly practical -- our comprehensive evaluation on over 20,000 benchmarks shows that VeriEQL outperforms all state-of-the-art techniques by more than one order of magnitude in terms of the number of benchmarks that can be proved or disproved. VeriEQL can also generate counterexamples that facilitate many downstream tasks (such as finding serious bugs in systems like MySQL and Apache Calcite).
Safety and Community Context: Exploring a Transfeminist Approach to Sapphic Relationship Platforms
Authors: DeVito Michael Ann , Feuston Jessica L. , Melder Erika , Malloy Christen , Ponder Cade , Brubaker Jed R.
Published: April 2024

Relationship platforms (e.g., dating apps) are crucial tools for sapphics (trans women, cisgender women, and nonbinary people who are attracted to other sapphics). However, current platforms are not designed in a way that accounts for sapphic lived experience, especially the lived experience of sapphics who hold multiple marginalized identity characteristics. Even on platforms that do exist for sapphics, transgender women and nonbinary people are often subject to discrimination, fetishization, and stigmatization. To aid in the design of platforms that better serve the needs of multiply marginalized sapphics, we engaged a diverse group of 25 sapphics in six rounds of community discussion on key topics for relationship platform design. Based on participant discussions, we identify key challenges when designing for multiply marginalized sapphics around relationship structures, gender and sexuality classification, and safety priorities for interaction. We present two design priorities alongside community-sourced design directions which can help future designers address these challenges: identity-centric safety and community-based information formats.
How Platform Exchange and Safeguards Matter: The Case of Sexual Risk in Airbnb and Couchsurfing
Authors: Wang Skyler
Published: April 2024

Recent work in CHI and CSCW has devoted increasing attention to how the design of network hospitality platforms shapes user experiences and relational outcomes. In this article, I interrogate how different risk factors emerge based on the type of exchanges these platforms facilitate. To do so, I juxtapose two prominent network hospitality platforms-one facilitating negotiated exchange (i.e., Airbnb) with another facilitating reciprocal exchange (i.e., Couchsurfing). Homing in on sexual risk, an underexplored form of platform danger, and drawing on interviews with 40 female dual-platform users, I argue that Airbnb's provision of binding negotiated exchange and institutional safeguards reduces risk through three mechanisms: casting initial guest-host relation into a buyer-seller arrangement, stabilizing interactional scripts, and formalizing sexual violence recourse. Conversely, Couchsurfing's focus on reciprocal exchange and lack of safeguards increase sexual precarity for users both on- and off-platform. This study demonstrates how platforms with strong prosocial motivations can jeopardize sociality and concludes with design implications for protecting vulnerable user populations.
Learning Domain Specific Sub-layer Latent Variable for Multi-Domain Adaptation Neural Machine Translation
Authors: Huang Shuanghong , Feng Chong , Shi Ge , Li Zhengjun , Zhao Xuan , Li Xinyan , Wang Xiaomei
Published: April 2024

Domain adaptation proves to be an effective solution for addressing inadequate translation performance within specific domains. However, the straightforward approach of mixing data from multiple domains to obtain the multi-domain neural machine translation (NMT) model can give rise to the parameter interference between domains problem, resulting in a degradation of overall performance. To address this, we introduce a multi-domain adaptive NMT method aimed at learning domain specific sub-layer latent variable and employ the Gumbel-Softmax reparameterization technique to concurrently train both model parameters and domain specific sub-layer latent variable. This approach facilitates learning private domain-specific knowledge while sharing common domain-invariant knowledge, effectively mitigating the parameter interference problem. The experimental results show that our proposed method significantly improved by up to 7.68 and 3.71 BLEU compared with the baseline model in English-German and Chinese-English public multi-domain datasets, respectively.
A Survey of Graph Neural Networks for Social Recommender Systems
Authors: Sharma Kartik , Lee Yeon-Chang , Nambi Sivagami , Salian Aditya , Shah Shlok , Kim Sang-Wook , Kumar Srijan
Published: April 2024

Social recommender systems (SocialRS) simultaneously leverage the user-to-item interactions as well as the user-to-user social relations for the task of generating item recommendations to users. Additionally exploiting social relations is clearly effective in understanding users’ tastes due to the effects of homophily and social influence. For this reason, SocialRS has increasingly attracted attention. In particular, with the advance of graph neural networks (GNN), many GNN-based SocialRS methods have been developed recently. Therefore, we conduct a comprehensive and systematic review of the literature on GNN-based SocialRS.

In this survey, we first identify 84 papers on GNN-based SocialRS after annotating 2,151 papers by following the PRISMA framework (preferred reporting items for systematic reviews and meta-analyses). Then, we comprehensively review them in terms of their inputs and architectures to propose a novel taxonomy: (1) input taxonomy includes five groups of input type notations and seven groups of input representation notations; (2) architecture taxonomy includes eight groups of GNN encoder notations, two groups of decoder notations, and 12 groups of loss function notations. We classify the GNN-based SocialRS methods into several categories as per the taxonomy and describe their details. Furthermore, we summarize benchmark datasets and metrics widely used to evaluate the GNN-based SocialRS methods. Finally, we conclude this survey by presenting some future research directions. GitHub repository with the curated list of papers are available at
https://github.com/claws-lab/awesome-GNN-social-recsys
Breaking Through the Noisy Correspondence: A Robust Model for Image-Text Matching
Authors: Shi Haitao , Liu Meng , Mu Xiaoxuan , Song Xuemeng , Hu Yupeng , Nie Liqiang
Published: April 2024

Unleashing the power of image-text matching in real-world applications is hampered by noisy correspondence. Manually curating high-quality datasets is expensive and time-consuming, and datasets generated using diffusion models are not adequately well-aligned. The most promising way is to collect image-text pairs from the Internet, but it will inevitably introduce noisy correspondence. To reduce the negative impact of noisy correspondence, we propose a novel model that first transforms the noisy correspondence filtering problem into a similarity distribution modeling problem by exploiting the powerful capabilities of pre-trained models. Specifically, we use the Gaussian Mixture model to model the similarity obtained by CLIP as clean distribution and noisy distribution, to filter out most of the noisy correspondence in the dataset. Afterward, we used relatively clean data to fine-tune the model. To further reduce the negative impact of unfiltered noisy correspondence, i.e., a minimal part where two distributions intersect during the fine-tuning process, we propose a distribution-sensitive dynamic margin ranking loss, further increasing the distance between the two distributions. Through continuous iteration, the noisy correspondence gradually decreases and the model performance gradually improves. Our extensive experiments demonstrate the effectiveness and robustness of our model even under high noise rates.
Central Banks, Stock Markets, and the Real Economy
Authors: Caballero Ricardo J. , Simsek Alp
Published: April 2024

In this article, we summarize empirical research on the interaction between monetary policy and asset markets and review our previous theoretical work that captures these interactions. We present a concise model in which monetary policy impacts the aggregate asset price, which in turn influences economic activity with lags. In this context, the following occurs: (a) the central bank (the Fed, for short) stabilizes the aggregate asset price in response to financial shocks, using large-scale asset purchases if needed (the Fed put); (b) when the Fed is constrained, negative financial shocks cause demand recessions; (c) the Fed's response to aggregate demand shocks increases asset price volatility, but this volatility plays a useful macroeconomic stabilization role; (d) the Fed's beliefs about the future aggregate demand and supply drive the aggregate asset price; (e) macroeconomic news influences the Fed's beliefs and asset prices; (f) more precise news reduces output volatility but heightens asset market volatility; and (g) disagreements between the market and the Fed provide a microfoundation for monetary policy shocks and generate a policy risk premium.
Diversifying Gender Categories and the Sex/Gender System
Authors: Ridgeway Cecilia L. , Saperstein Aliya
Published: April 2024

The growing visibility of transgender and nonbinary people raises important sociological questions about how the structure of sex and gender is shifting and underscores necessary changes to research practice. We review what is known about emerging gender identities and their implications for sociological understandings of the relationship between sex and gender and the maintenance of the sex/gender system of inequality. Transgender and nonbinary identities are increasingly common among younger cohorts and improved survey measurements of sex and gender are expanding information about these changes. In the United States, an additional gender category seems to be solidifying in public usage even as the higher status of masculinity over femininity persists. The continuing power of the normative binary contributes to both violent backlash and characteristic patterns of discrimination against gender diverse people; yet, underlying support for nondiscrimination in the workplace is stronger than commonly recognized. New, more consistent efforts to account for gender diversity in social science research are needed to fully understand these changes.
Controlling Much? Viral Control of Host Chromatin Dynamics
Authors: Kelnhofer-Millevolte Laurel E. , Arnold Edward A. , Nguyen Daniel H. , Avgousti Daphne C.
Published: April 2024

Viruses are exemplary molecular biologists and have been integral to scientific discovery for generations. It is therefore no surprise that nuclear replicating viruses have evolved to systematically take over host cell function through astoundingly specific nuclear and chromatin hijacking. In this review, we focus on nuclear replicating DNA viruses—herpesviruses and adenoviruses—as key examples of viral invasion in the nucleus. We concentrate on critical features of nuclear architecture, such as chromatin and the nucleolus, to illustrate the complexity of the virus-host battle for resources in the nucleus. We conclude with a discussion of the technological advances that have enabled the discoveries we describe and upcoming steps in this burgeoning field.
Corrigendum: Binder-Free Flexible Chickpea Pod Derived Activated Carbon-Carbon Nanofiber Composite for Supercapacitor Application [ECS J. Solid State Sci. Technol.,
13, 011104 (2024)]
Authors: Malothu Usha Rani , Donthula Kiran , Kakunuri Manohar , Nageswara Rao G.V.S.
Published: April 2024

The published paper was produced from a poorly-edited file which resulted in numerous typographical and grammatical errors, leading to confusion about the experiments and results reported. The paper has been edited and the corrected version is shown here.

In the present study, a novel carbon-carbon composite electrode was prepared by embedding activated carbon derived from chickpea pods and evaluating its potential as an electrode for supercapacitors. A simple, single-step electrospinning technique was used for the synthesis of activated carbon-carbon nanofiber composite. The synthesized activated carbon-carbon nanofiber composite electrode is flexible and binder-free with high specific surface area, micro and meso pores, interconnected fiber-to-flake morphology, and possesses high graphitization. Additionally, rapid electrolyte diffusion has resulted in a low charge transfer resistance due to interconnected morphology. In 6 M KOH electrolyte, the composite binder-free electrode shows a specific capacitance of 147 F g−1 at 0.5 A g−1 compared to activated carbon electrodes that showed a specific capacitance of 120 F g−1 at 0.5 A g−1. It exhibits an energy density of 13 Wh k g−1 at 0.366 W k g−1 power density and also shows impressive cyclic stability by retaining 93.5% of initial capacitance till 1200 cycles at 1 A g−1. Overall, the study presents an easy-to-use, low-cost, eco-friendly, and flexible electrode for supercapacitors that is free of binder.
Acute effects of a ketone monoester, whey protein, or their coingestion on mTOR trafficking and protein-protein colocalization in human skeletal muscle
Authors: Hannaian Sarkis J. , Lov Jamie , Cheng-Boivin Zacharie , Abou Sawan Sidney , Hodson Nathan , Gentil Benoit J. , Morais José A. , Churchward-Venne Tyler A.
Published: April 2024

We explored the effects of a ketone monoester (KET), whey protein (PRO), or their coingestion (KET + PRO) on mTOR-related protein-protein colocalization and intracellular trafficking in human muscle. All treatments decreased TSC2-Rheb colocalization at 120 minutes; however, KET + PRO sustained the decrease at 300 min. Only PRO and KET + PRO increased mTOR-Rheb colocalization; however, the increase at 300 min was greater in KET + PRO. Treatment intake increased mTOR-WGA colocalization, suggesting translocation to the fiber periphery. Ketone bodies influence the spatial regulation of mTOR.
Mogrol-mediated enhancement of radiotherapy sensitivity in non-small cell lung cancer: a mechanistic study
Authors: Yin Zhongbo , Zhang Xuedong , Sun Xiao , Huo Yunlong , Ji Nan , Chen Keyan
Published: April 2024

Mogrol enhances non-small cell lung cancer (NSCLC) cell sensitivity to radiotherapy by downregulating USP22 through the ERK/CREB pathway, reducing COX2 expression. These findings highlight mogrol’s potential as an adjunct to improve NSCLC radiotherapy and open avenues for further research and clinical applications.
Communication Self-Efficacy and Job Satisfaction among Nurses during the COVID-19 Pandemic
Authors: Ghahremani Leila , Khoramaki Zakieh , Kaveh Mohammad Hossein , Karimi Masoud , Nazari Mahin , Orgambídez Ramos Alejandro
Published: April 2024

Introduction. The outbreak of COVID-19 has led to various challenges for healthcare workers, including nurses. Nurses play a critical role in the fight against this disease, and their communication of self-efficacy and job satisfaction has garnered significant attention. This study aimed to investigate the relationship between communication self-efficacy and job satisfaction of Iranian nurses during the COVID-19 pandemic. Methods. This study was conducted using a cross-sectional design. A total of 500 nurses working in hospitals in Iran were selected using a convenience sampling method. The communication self-efficacy scale and the job satisfaction scale were used to collect data. Results. The study found that nurses with higher communication self-efficacy exhibited better performance and job satisfaction in various work challenges (r = 0.56, p<0.001). However, nurses holding a master’s degree or higher reported the lowest average communication self-efficacy and job satisfaction scores during the COVID-19 epidemic. The study also explored the impact of shift work on job satisfaction among nurses and found that nurses working exclusively on the morning shift reported the highest average job satisfaction score. Conclusion. The findings of this study suggest that communication self-efficacy is an important factor in predicting job satisfaction among Iranian nurses during the COVID-19 pandemic. Therefore, it is recommended that healthcare organizations provide effective communication training sessions and mental health interventions to enhance nurses’ communication self-efficacy and job satisfaction. This can ultimately lead to improved performance and better patient outcomes.
Homotherapy for Heteropathy: A Molecular Mechanism of Poria Sini Decoction for Treatment of Liver Cancer and Chronic Heart Failure
Authors: Zhao Zhe , Yue Huiying , Cui Xiaohua
Published: April 2024

Poria sini decoction (PSD), a significant traditional Chinese herbal formula, is effective in liver cancer (LC) and chronic heart failure (CHF); however, little is known about its concurrent targeting mechanism. Methods. This study analyzed the potential molecular mechanism of PSD against the two distinct diseases using network pharmacology approaches, including multidatabase search, pharmacokinetic screening, network construction analysis, Gene Ontology (GO) enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and molecular docking to elaborate the active components, signaling pathways, and potential mechanisms of PSD in the treatment of both LC and CHF. Results. A total of 155 active components and 193 potential targets in PSD were identified. Bioinformatics analysis revealed that quercetin, isorhamnetin, and naringenin, etc. may be potential candidate agents. TNF, AKT1, and IL6, etc. could become potential therapeutic targets. TNF-α, NF-κB, PI3K-AKT, and TRP signaling pathways might play an important role in PSD against LC and CHF. Molecular docking results showed that most screened active compounds could embed itself into target proteins with a high binding affinity, and the hydrogen bonds number ≥3 indicated a more stable conformation of the compounds and target proteins. Overall, quercetin and isorhamnetin were the main active components, and TNF and AKT1 were the primary targets for PSD treatment of LC and CHF. Conclusions. This study illustrated that quercetin contained in PSD played an important role in the treatment of LC and CHF by acting on the key gene of TP53 and downregulating the PI3K-AKT signaling pathway.
Interest of a Hospital-Based Geriatric Living Lab among Inpatients with Neurocognitive Disorders: The ALLEGRIA Cross-Sectional Study
Authors: Noublanche Frédéric , Ben-Sadoun Grégory , Carcreff Lena , Gautier Jennifer , Allain Philippe , Annweiler Cédric
Published: April 2024

Introduction: The objectives of this study were to determine the participation rates, levels of engagement, and abilities to answer User eXperience (UX) questionnaires according to the presence and severity of major neurocognitive disorders (MNCD) among participants involved in gerontechnological experimentations within a hospital-based geriatric clinical living lab. Methods: Cross-sectional analysis examining all consecutive geriatric patients involved in the Allegro living lab experimentations, separated according to the presence and severity of MNCD. Participation rates were assessed using the “Task-Based Experiment”-type User eXperience (TBE-UX). Participation was considered successful if patients fully completed the TBE-UX experimental procedure. Engagement level was characterized using a five-point scale: interactive, constructive, active, passive, and disengaged. The abilities to answer UX questionnaires were characterized using a five-point scale from “no completion” to “completion in autonomy.” Results: 313 patients were included. All patients without MNCD and with mild MNCD fully completed the TBE-UX procedures. Their engagement behaviors were rather active and constructive. All patients without MNCD and 88% of those with mild MNCD were able to fully complete the UX questionnaires. 96.2% of the patients with moderate MNCD fully followed the TBE-UX procedures. Their engagement behaviors were mainly active or passive. 64.2% were able to fully complete the UX questionnaires. 76.5% of the patients with severe MNCD fully followed the TBE-UX procedures. Their engagement behaviors were mainly passive or disengaged. 35.3% were able to fully complete the UX questionnaires. Conclusion: Living lab experimentations appear feasible with older adults, even with those with MNCD. Task support can be offered to those with severe MNCD.
The Risk of Metastatic Recurrence after Non-Curative Endoscopic Resection with Negative Deep Margins for Early Colorectal Cancer: Two-Center Retrospective Cohort Study
Authors: Yamauchi Kenji , Inaba Tomoki , Morimoto Takeshi , Aya Yusuke , Colvin Hugh Shunsuke , Nagahara Teruya , Ishikawa Shigenao , Wato Masaki , Imagawa Atsushi
Published: April 2024

Introduction: Non-curative endoscopic resection of T1 colorectal cancer (CRC) carries a substantial risk of recurrence. However, previous studies have reported a significant proportion of cases in which the deep margin of endoscopic resection was positive for cancer due to the technical difficulties of colorectal endoscopic submucosal dissection (ESD). With the advancement of endoscopic technology and techniques resulting in the reduction of positive resection margins, it is important to reassess the long-term prognosis and major risk factors for recurrence in cases of negative deep margins. Methods: We conducted a retrospective cohort study of consecutive patients with T1 CRC who underwent endoscopic resection between January 2006 and December 2021 with negative deep margins. The histological findings of the resected specimens were analyzed to determine the risk factors associated with the primary outcomes of this study, including recurrence and cancer-related deaths. Results: The median age of the 190 patients was 70 years, of which 63% were male, and endoscopic treatment was performed in 64% by endoscopic mucosal resection and 36% by ESD. Eighty-two patients were in the curative resection (CR) group and 108 were in the non-curative resection (NCR) group, wherein the latter comprised 79 patients who underwent additional surgery (AS) and 29 patients who did not receive AS. Five-year recurrence-free survival rates were 98.4% (95% CI: 89.3–99.8) for CR, 98.3% (95% CI: 88.8–99.8) for NCR with AS, and 73.7% (95% CI: 46.5–88.5) for NCR without AS. Lymphatic invasion and budding grade 2/3 were the major risk factors for recurrence, with hazard ratios of 40.7 (p < 0.001) and 23.1 (p = 0.007), respectively. Of the patients in the NCR group without AS, the 5-year recurrence-free rate was 85.6% (95% CI: 52.5–96.3) if there were no major risk factors (i.e., no lymphatic invasion or budding grade 2/3) (n = 21), whereas the prognosis was poor in the presence of one or more of the major risk factors, with a median recurrence-free survival and disease-specific survival of 2.5 and 3.1 years, respectively (n = 8). Discussion: In endoscopically resected T1 CRC with negative deep margins, lymphatic invasion or budding grade 2/3 may indicate a higher risk of recurrence when followed up without AS.
18q Deletion Syndrome-Associated Schizophrenia: A Case Report
Authors: Colijn Mark A. , Crockford David N.
Published: April 2024

Introduction: 18q deletion syndrome is a rare genetic disorder characterized by various neurodevelopmental anomalies and medical issues. Although the occurrence of psychosis has been reported in a small number of cases, details regarding the nature of such symptoms and their response to treatment have not been described. Case Presentation: We describe a 31-year-old male with a history of speech delays, autistic features, a tethered spinal cord, bilateral vertical talus, subaortic stenosis and aortic regurgitation, recurrent otitis media, mild hearing loss, and hypospadias, who experienced a first episode of psychosis in his late 20s. His psychotic symptoms included auditory hallucinations, various delusions, and disorganization of thought. Although his presentation is atypical in certain ways (e.g., exhibiting highly fluctuant symptoms), he nonetheless meets criteria for schizophrenia. Given his overall clinical picture, chromosomal microarray analysis was completed, which revealed a 19.78 Mb deletion at 18q21.32 from nucleotide 58,226,713 to 78,015,180 (GRCh37). Despite exhibiting a somewhat idiosyncratic response to numerous antipsychotic medications, he eventually achieved partial remission of symptoms with improved insight on relatively low dose oral aripiprazole therapy. Conclusion: This is the first in-depth description of 18q deletion syndrome-associated schizophrenia. While our patient’s atypical presentation and idiosyncratic response to treatment may be mediated by his comorbid diagnosis of autism, his unusual psychiatric phenotype may alternatively be directly related to his underlying genetic disorder. The description of additional cases in the future will hopefully help clarify matters further.
Lusutrombopag Reduces the Risk of Hemoperitoneum Caused by Percutaneous Radiofrequency Ablation for Hepatocellular Carcinoma Compared with Platelet Transfusion
Authors: Taki Shinya , Ida Yoshiyuki , Tamai Hideyuki , Maeshima Shuya , Shimizu Ryo , Shingaki Naoki , Maekita Takao , Iguchi Mikitaka , Kitano Masayuki
Published: April 2024

Introduction: Patients with liver cirrhosis develop thrombocytopenia and an increased risk of bleeding events after invasive procedures. Lusutrombopag, a thrombopoietin receptor agonist, can increase the platelet count. This study assessed whether lusutrombopag reduces the risk of hemoperitoneum following percutaneous radiofrequency ablation for hepatocellular carcinoma, compared with platelet transfusion. Methods: Participants in the present study comprised patients with severe thrombocytopenia (platelet count <50,000/μL) enrolled between November 2012 and March 2020, excluding patients with idiopathic thrombocytopenia or anticoagulant use. Hemoperitoneum rate, hemostasis rate, hemoglobin reduction rate, rate of achieving a platelet count ≥50,000/μL, and increases in platelet count and factors contributing to hemoperitoneum were retrospectively analyzed. Results: This study enrolled 41 patients, comprising 18 patients administered lusutrombopag and 23 patients who received platelet transfusion. The major hemoperitoneum rate after RFA was tend to be lower in the lusutrombopag group (0%) than in the platelet transfusion group (21.7%). All of the major hemoperitoneum was observed in the platelet transfusion group. Hemoglobin reduction rate was lower in the lusutrombopag group (−0.17%) than in the platelet transfusion group (6.79%, p = 0.013). Hemostasis rate was lower in the lusutrombopag group (0%) than in the platelet transfusion group (21.7%, p = 0.045). The rate of achievement of platelet counts ≥50,000/μL the day after RFA was higher in the lusutrombopag group (100%) than in the platelet transfusion group (60.9%, p = 0.005). Conclusion: Lusutrombopag may be able to perform RFA more safely with respect to the hemoperitoneum caused by percutaneous radiofrequency ablation compared with platelet transfusion.