bluuebunny/crossref_metadata_2025_split huggingface dataset:
Personal AI, deception, and the problem of emotional bubbles
Authors: Mlonyeni Philip Maxwell Thingbø 
Published: May 2024

AbstractPersonal AI is a new type of AI companion, distinct from the prevailing forms of AI companionship. Instead of playing a narrow and well-defined social role, like friend, lover, caretaker, or colleague, with a set of pre-determined responses and behaviors, Personal AI is engineered to tailor itself to the user, including learning to mirror the user’s unique emotional language and attitudes. This paper identifies two issues with Personal AI. First, like other AI companions, it is deceptive about the presence of their emotions, which undermines the moral value of companionship. Second, Personal AI leads to a distinctly new form of deception concerning the origins of its emotions. Its emotional attitudes appear to belong to it, when in fact they are only reflections of the user. This results in what I dub “emotional bubbles”—the false impression that personal emotions are externally validated—which have at least two troubling implications. First, emotional bubbles prevent us from encountering emotional attitudes that differ from our own, which is likely to cripple emotional growth and the ability to form diverse social and emotional relationships. Second, if we assume, as some philosophers claim, that shared emotions are constitutive of shared values, it follows that Personal AI subverts joint moral deliberation. Users believe their personal values are externally validated, when they are only validated by themselves. Because of the absence of technovirtues able to handle this problem, I suggest that we proceed very cautiously with the development and marketing of Personal AI.
Acoustic resolvent analysis of turbulent jets
Authors: Bugeat Benjamin , Karban Ugur , Agarwal Anurag , Lesshafft Lutz , Jordan Peter 
Published: May 2024

Abstract
We perform a resolvent analysis of a compressible turbulent jet, where the optimisation domain of the response modes is located in the acoustic field, excluding the hydrodynamic region, in order to promote acoustically efficient modes. We examine the properties of the acoustic resolvent and assess its potential for jet-noise modelling, focusing on the subsonic regime. Resolvent forcing modes, consistent with previous studies, are found to contain supersonic waves associated with Mach wave radiation in the response modes. This differs from the standard resolvent in which hydrodynamic instabilities dominate. We compare resolvent modes with SPOD modes educed from LES data. Acoustic resolvent response modes generally have better alignment with acoustic SPOD modes than standard resolvent response modes. For the optimal mode, the angle of the acoustic beam is close to that found in SPOD modes for moderate frequencies. However, there is no significant separation between the singular values of the leading and sub-optimal modes. Some suboptimal modes are furthermore shown to contain irrelevant structure for jet noise. Thus, even though it contains essential acoustic features absent from the standard resolvent approach, the SVD of the acoustic resolvent alone is insufficient to educe a low-rank model for jet noise. But because it identifies the prevailing mechanisms of jet noise, it provides valuable guidelines in the search of a forcing model (Karban et al. in J Fluid Mech 965:18, 2023).

Graphical abstract
Compression of boundary integral operators discretized by anisotropic wavelet bases
Authors: Harbrecht Helmut , von Rickenbach Remo 
Published: May 2024

AbstractThe present article is devoted to wavelet matrix compression for boundary integral equations when using anisotropic wavelet bases for the discretization. We provide a compression scheme for boundary integral operators of order $$2q$$

2
q

on patchwise smooth and globally Lipschitz continuous mainfolds which amounts to only $$\mathcal {O}(N)$$

O
(
N
)

relevant matrix coefficients in the system matrix without deteriorating the accuracy offered by the underlying Galerkin scheme. Here, $$N$$
N
denotes the degrees of freedom in the related trial spaces. By numerical results we validate our theoretical findings.
Prediction and MDL for infinite sequences
Authors: Milovanov Alexey 
Published: May 2024

AbstractWe combine Solomonoff’s approach to universal prediction with algorithmic statistics and suggest to use the computable measure that provides the best “explanation” for the observed data (in the sense of algorithmic statistics) for prediction. In this way we keep the expected sum of squares of prediction errors bounded (as it was for the Solomonoff’s predictor) and, moreover, guarantee that the sum of squares of prediction errors is bounded along any Martin-Löf random sequence. An extended abstract of this paper was presented at the 16th International Computer Science Symposium in Russia (CSR 2021) (Milovanov 2021).
Apparent diffusion coefficient and tissue stiffness are associated with different tumor microenvironment features of hepatocellular carcinoma
Authors: Chen Jie , Wu Zhenru , Zhang Zhen , Chen Yidi , Yin Meng , Ehman Richard L. , Yuan Yuan , Song Bin 
Published: May 2024

Abstract
Objectives
To investigate associations between tissue diffusion, stiffness, and different tumor microenvironment features in resected hepatocellular carcinoma (HCC).

Methods
Seventy-two patients were prospectively included for preoperative magnetic resonance (MR) diffusion-weighted imaging and MR elastography examination. The mean apparent diffusion coefficient (ADC) and stiffness value were measured on the central three slices of the tumor and peri-tumor area. Cell density, tumor-stroma ratio (TSR), lymphocyte-rich HCC (LR-HCC), and CD8 + T cell infiltration were estimated in resected tumors. The interobserver agreement of MRI measurements and subjective pathological evaluation was assessed. Variables influencing ADC and stiffness were screened with univariate analyses, and then identified with multivariable linear regression. The potential relationship between explored imaging biomarkers and histopathological features was assessed with linear regression after adjustment for other influencing factors.

Results
Seventy-two patients (male/female: 59/13, mean age: 56 ± 10.2 years) were included for analysis. Inter-reader agreement was good or excellent regarding MRI measurements and histopathological evaluation. No correlation between tumor ADC and tumor stiffness was found. Multivariable linear regression confirmed that cell density was the only factor associated with tumor ADC (Estimate = −0.03, p = 0.006), and tumor-stroma ratio was the only factor associated with tumor stiffness (Estimate = −0.18, p = 0.03). After adjustment for fibrosis stage (Estimate = 0.43, p < 0.001) and age (Estimate = 0.04, p < 0.001) in the multivariate linear regression, intra-tumoral CD8 + T cell infiltration remained a significant factor associated with peri-tumor stiffness (Estimate = 0.63, p = 0.02).

Conclusions
Tumor ADC surpasses tumor stiffness as a biomarker of cellularity. Tumor stiffness is associated with tumor-stroma ratio and peri-tumor stiffness might be an imaging biomarker of intra-tumoral immune microenvironment.

Clinical relevance statement
Tissue stiffness could potentially serve as an imaging biomarker of the intra-tumoral immune microenvironment of hepatocellular carcinoma and aid in patient selection for immunotherapy.

Key Points

Apparent diffusion coefficient reflects cellularity of hepatocellular carcinoma.

Tumor stiffness reflects tumor-stroma ratio of hepatocellular carcinoma and is associated with tumor-infiltrating lymphocytes.

Tumor and peri-tumor stiffness might serve as imaging biomarkers of intra-tumoral immune microenvironment.
Long-term outcome of patients with Ménière’s disease following cochlear implantation: a comprehensive outcome study with validated assessment tools
Authors: Yılmaz Topçuoğlu Miray-Su , Plinkert Peter K. , Praetorius Mark , Euteneuer Sara 
Published: May 2024

AbstractPurposePatients suffering from Ménière’s disease (MD) experience vertigo, and impairments in hearing and quality of life (QoL). This study aims to investigate the impact of cochlear implantation (CI) on various aspects affecting patients with MD.MethodsA single tertiary centre’s CI database for CI recipients with MD between 2014 and 2022 was screened retrospectively. Hearing, vertigo, tinnitus symptoms, and hearing-related QoL were assessed. Pre- and postoperative hearing tests in conjunction with subjective outcome measures by visual analogue scale (VAS) and validated tools such as the Dizziness Handicap Inventory (DHI), Tinnitus Handicap Inventory (THI) and Nijmegen Cochlear Implant Questionnaire (NCIQ), as well as the assessment of the pre- and postoperative Functional Level Scale (FLS) were examined.ResultsEleven ears were included (median age: 59 years at implantation). Following implantation, there was a significant enhancement in Word Recognition Scores at sound levels of 65 dB and 80 dB compared to before treatment (preop vs. 12 months postop: p = 0.012). However, no significant enhancement was observed for 50 dB. MD-related impairments improved significantly postoperatively, as measured by the VAS (vertigo: p = 0.017; tinnitus: p = 0.042), DHI (p = 0.043), THI (p = 0.043) and NCIQ (p < 0.001). The FLS improved significantly (p = 0.020).ConclusionCI has positive effects on all areas examined in our cohort. However, discrimination of speech at low sound pressure levels remained problematic postoperatively. In patients suffering from MD, the prioritized treatment goals include not only improved hearing but also the rehabilitation of vertigo and tinnitus, as well as the enhancement of QoL. Validated instruments are useful screening tools.
Time, valence, and imagination: a comparative study of thoughts in restricted and unrestricted mind wandering
Authors: Li Halleyson , Hills Thomas 
Published: May 2024

AbstractWilliam James’ “stream of thought” is a key component of human cognition. Such thoughts arise in both restricted and unrestricted contexts, either with or without the presence of a secondary task. This study examines the similarities and differences in thoughts produced in these two contexts, which we call restricted and unrestricted mind wandering. Participants performed a mindfulness task representing restricted mind wandering and an unrestricted thought task where they spontaneously explored thoughts, reporting them as they arose. Participants then self-rated their thoughts based on valence, temporal orientation (past/present/future), and reality orientation (imaginary vs. real). Participants’ emotional states were also evaluated using the Emotion Recall Task (ERT) and the PANAS questionnaire. Unrestricted mind wandering generated more thoughts, which were more positive and future-oriented than those in restricted mind wandering. Additionally, participants’ thought valence correlated with their PANAS and ERT scores. Approximately 1 out of 4 thoughts in both restricted and unrestricted mind wandering were imaginary, with increased future orientation linked to more imaginative thought. Despite the statistical differences separating restricted and unrestricted thought, effect sizes were predominantly small, indicating that the thoughts arise during these two types of mind wandering are largely of the same kind.
A novel tRNA-derived fragment tRF-17-18VBY9M works as a potential diagnostic biomarker for gastric cancer
Authors: Mao Chunyan , Zhang Zhihan , Fang Ronghua , Yuan Wentao , Wu Yi , Cong Hui 
Published: May 2024

Abstract
Background
Gastric cancer (GC) is one of the most prevalent malignant tumors worldwide. The low effectiveness of common biomarkers for the detection of early GC makes it essential to seek new biomarkers to improve diagnostic efficacy. tsRNAs (transfer RNA-derived small RNAs) are related to the growth of malignant tumors. In this article, we focused on whether tsRNAs may be employed as biomarkers for GC.

Methods
tRF-17-18VBY9M was screened in the tsRFun database as a research object. The methodological efficacy of tRF-17-18VBY9M was evaluated using Sanger sequencing, agarose gel electrophoresis assays, and gradient dilution. The χ2 test was applied to assess the interaction between tRF-17-18VBY9M expression and clinicopathologic characteristics. The receiver operating characteristic (ROC) curve was utilized to investigate the clinical efficiency of tRF-17-18VBY9M in GC.

Results
The Chi-square test demonstrated that high-expressed tRF-17-18VBY9M was closely associated with the T stage, tumor node metastasis stage (TNM), lymph node metastasis, and neurological/vascular invasion. ROC curve analysis revealed that the diagnostic value of tRF-17-18VBY9M in GC was superior to carcinoembryonic antigen (CEA), carbohydrate antigen 199 (CA199), and carbohydrate antigen 724 (CA724).

Conclusion
tRF-17-18VBY9M is up-regulated in both GC sera and tissues. Differential tRF-17-18VBY9M expression distinguishes GC patients from healthy donors and gastritis patients, which suggests tRF-17-18VBY9M could act as a diagnostic biomarker in GC.
Machine learning identifies the role of SMAD6 in the prognosis and drug susceptibility in bladder cancer
Authors: Chen Ziang , Ou Yuxi , Ye Fangdie , Li Weijian , Jiang Haowen , Liu Shenghua 
Published: May 2024

Abstract
Background
Bladder cancer (BCa) is among the most prevalent malignant tumors affecting the urinary system. Due to its highly recurrent nature, standard treatments such as surgery often fail to significantly improve patient prognosis. Our research aims to predict prognosis and identify precise therapeutic targets for novel treatment interventions.

Methods
We collected and screened genes related to the TGF-β signaling pathway and performed unsupervised clustering analysis on TCGA-BLCA samples based on these genes. Our analysis revealed two novel subtypes of bladder cancer with completely different biological characteristics, including immune microenvironment, drug sensitivity, and more. Using machine learning classifiers, we identified SMAD6 as a hub gene contributing to these differences and further investigated the role of SMAD6 in bladder cancer in the single-cell transcriptome data. Additionally, we analyzed the relationship between SMAD6 and immune checkpoint genes. Finally, we performed a series of in vitro assays to verify the function of SMAD6 in bladder cancer cell lines.

Results
We have revealed two novel subtypes of bladder cancer, among which C1 exhibits a worse prognosis, lower drug sensitivity, a more complex tumor microenvironment, and a ‘colder’ immune microenvironment compared to C2. We identified SMAD6 as a key gene responsible for the differences and further explored its impact on the molecular characteristics of bladder cancer. Through in vitro experiments, we found that SMAD6 promoted the prognosis of BCa patients by inhibiting the proliferation and migration of BCa cells.

Conclusion
Our study reveals two novel subtypes of BCa and identifies SMAD6 as a highly promising therapeutic target.
Quantitative assessment of the troCarWash™ system for automated laparoscopic camera cleaning
Authors: Ahmed Maaz , Gowda Ashok , Alavi Naini Fatemeh , Le Alexander , Treffalls John , Torres Robin , Burt Bryan M. 
Published: May 2024

Abstract
Background
Soilage of the surgical endoscope occurs frequently during minimally invasive surgery. The resultant impairment of visualization of the surgical field compromises patient safety, prolongs operative times, and frustrates surgeons. The standard practice for cleaning the surgical camera involves a disruption in the conduct of surgery by completely removing the endoscope from the field, manually cleaning its lens, treating it with a surfactant, and reinserting it into the patient; after which the surgeon resumes the procedure.

Methods
We developed an automated solution for in vivo endoscope cleaning in minimally invasive surgery- a port that detects the position of the endoscope in its distal lumen, and precisely and automatically delivers a pressurized mist of cleaning solution to the lens of the camera. No additions to the scope and minimal user interaction with the port are required. We tested the efficacy of this troCarWash™ device in a porcine model of laparoscopy. Four board-certified general surgeons were instructed to soil and then clean the laparoscope using the device. Representative pre- and post-clean images were exported from the surgical video and clarity was graded (1) digitally by a canny edge detection algorithm, and (2) subjectively by 3 blinded, unbiased observers using a semi-quantitative scale.

Results
We observed statistically significant improvements in clarity by each method and for each surgeon, and we noted significant correlation between digital and subjective scores.

Conclusion
Based on these data, we conclude that the troCarWash™ effectively restored impaired visualization in a large animal model of laparoscopy.
The relationship between quality of life and sex role of women with gynecological cancers undergoing brachytherapy
Authors: Cerit Esin , Arslan Dilek Efe , Aslan Dicle 
Published: May 2024

Abstract
Purpose
This study aims to analyze the relationship between the quality of life and sex roles of women diagnosed with cancer and undergoing brachytherapy.

Methods
The research is a cross-sectional descriptive study. The sample of the study included 116 women over 35 years old who were diagnosed with a gynecologic cancer and underwent intracavitary brachytherapy at the Radiation Oncology Department of a university hospital. Personal information form, SF-36 the Quality of Life Scale, and BEM Sex Role Inventory were used in the study. The researcher collected the data through face-to-face interview. The data were collected in the nurses’ room after 3 different brachytherapy treatments that patients received weekly.

Results
It was found that the average score of the physical functioning subscale was 32.80 ± 24.33, the average score of role physical was 15.43 ± 28.78, the average score of role emotional was 17.81 ± 28.96, the average score of vitality was 39.13 ± 16.12, the average score of social functioning was 43.53 ± 20.55, the score average of pain was 50.0 ± 20.09, the average score of general health was 42.67 ± 14.61, and the general health of mental health was 55.86 ± 16.12. In the BEM sex roles scale, the average score of BEM femininity was 105.56 ± 13.95, and the average score of BEM masculinity was 80.61 ± 12.77. In our study, a very low, negative, and significant relationship was determined between the role of femininity and emotional role limitation, physical functionality, social functionality, and general health perception in the women undergoing brachytherapy (p < 0.05).

Conclusions
Based on the findings of the present study, we can state that an increase in the “role of femininity” in women undergoing brachytherapy was effective in the decrease in the quality of lives of women. It can be claimed that the results will be a guidance for the nurses who will play an important role in increasing the quality of lives of the women undergoing brachytherapy.
Multi-class vulnerability prediction using value flow and graph neural networks
Authors: McLaughlin Connor , Lu Yi 
Published: May 2024

AbstractIn recent years, machine learning models have been increasingly used to detect security vulnerabilities in software, due to their ability to achieve high performance and lower false positive rates compared to traditional program analysis tools. However, these models often lack the capability to provide a clear explanation for why a program has been flagged as vulnerable, leaving developers with little reasoning to work with. We present a new method which not only identifies the presence of vulnerabilities in a program, but also the specific type of error, considering the whole program rather than just individual functions. Our approach utilizes graph neural networks that employ inter-procedural value flow graphs, and instruction embedding from the LLVM Intermediate Representation, to predict a class. By mapping these classes to the Common Weakness Enumeration list, we provide a clear indication of the security issue found, saving developers valuable time which would otherwise be spent analyzing a binary vulnerable/non-vulnerable label. To evaluate our method’s effectiveness, we used two datasets: one containing memory-related errors (out of bound array accesses), and the other a range of vulnerabilities from the Juliet Test Suite, including buffer and integer overflows, format strings, and invalid frees. Our model, implemented using PyTorch and the Gated Graph Sequence Neural Network from Torch-Geometric, achieved a precision of 96.35 and 91.59% on the two datasets, respectively. Compared to common static analysis tools, our method produced roughly half the number of false positives, while identifying approximately three times the number of vulnerable samples. Compared to recent machine learning systems, we achieve similar performance while offering the added benefit of differentiating between classes. Overall, our approach represents a meaningful improvement in software vulnerability detection, providing developers with valuable insights to better secure their code.
Object search by a concept-conditioned object detector
Authors: Rigoni Davide , Serafini Luciano , Sperduti Alessandro 
Published: May 2024

AbstractObject detectors are used for searching all objects belonging to a pre-defined set of categories contained in a given picture. However, users are often not interested in finding all objects, but only those that pertain to a small set of categories or concepts. Nowadays, the standard approach to solve this task involves initially employing an object detector to identify all objects within the image, followed by refining the outcomes to retain only the ones of interest. Nevertheless, the object detector does not take advantage of the user’s prior intent that, when used, can potentially improve the detection performance of the model. This work presents a method to condition an existing object detector with the user’s intent, encoded as one or more concepts from the WordNet graph, to find just those objects of interest. The proposed approach takes advantage of existing datasets for object detection without the need for new annotations, and it allows to adapt the already existing object detector models with minor changes. The evaluation, performed on the COCO and the Visual Genome datasets considering several object detector architectures, shows that conditioning the search on concepts is actually beneficial. The code and the pre-trained model weights are released at: https://github.com/drigoni/Concept-Conditioned-Object-Detector.