bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rights, Wronging, and Equality of Status
Authors: Fornaroli Giulio 
Published: June 2024

Abstract
Two problems about rights have received so far little attention. One is the problem of identifying a general value in the practice of rights. The second is to see when, if at all, rights violations wrong the right-holder, in a morally significant sense. In the present essay, I address the first question by investigating the second. I first show that if we commit to the two ideas, common in the contemporary philosophy of rights, that claim-rights always correlate with directed duties and that rights aspire to protect interests of the right-holder, we make it hard to explain why rights violations, in general, wrong right-holders. In the final section, I present what I see as a promising solution to the puzzle. I describe a particular social environment (the society of equals) where interacting with others through rights is indeed valuable because respecting rights communicates that one takes seriously others’ equal moral status. In such a society and only in such a society, I conclude, moral agents are required to treat all rights violations as wrongs perpetrated against the right-holder.
Which ‘Intensional Paradoxes’ are Paradoxes?
Authors: Tennant Neil 
Published: June 2024

AbstractWe begin with a brief explanation of our proof-theoretic criterion of paradoxicality—its motivation, its methods, and its results so far. It is a proof-theoretic account of paradoxicality that can be given in addition to, or alongside, the more familiar semantic account of Kripke. It is a question for further research whether the two accounts agree in general on what is to count as a paradox. It is also a question for further research whether and, if so, how the so-called Ekman problem bears on the investigations here of the intensional paradoxes. Possible exceptions to the proof-theoretic criterion are Prior’s Theorem and Russell’s Paradox of Propositions—the two best-known ‘intensional’ paradoxes. We have not yet addressed them. We do so here. The results are encouraging. §1 studies Prior’s Theorem. In the literature on the paradoxes of intensionality, it does not enjoy rigorous formal proof of a Gentzenian kind—the kind that lends itself to proof-theoretic analysis of recondite features that might escape the attention of logicians using non-Gentzenian systems of logic. We make good that lack, both to render the criterion applicable to the formal proof, and to see whether the criterion gets it right. Prior’s Theorem is a theorem in an unfree, classical, quantified propositional logic. But if one were to insist that the logic employed be free, then Prior’s Theorem would not be a theorem at all. Its proof would have an undischarged assumption—the ‘existential presupposition’ that the proposition $$\forall p(Qp\!\rightarrow \!\lnot p)$$

∀
p
(
Q
p

→

¬
p
)

exists. Call this proposition $$\vartheta $$
ϑ
. §2 focuses on $$\vartheta $$
ϑ
. We analyse a Priorean reductio of $$\vartheta $$
ϑ
along with the possibilitate $$\Diamond \forall q(Qq\!\leftrightarrow \!(\vartheta \!\leftrightarrow \! q))$$

◊
∀
q
(
Q
q

↔

(
ϑ

↔

q
)
)

. The attempted reductio of this premise-pair, which is constructive, cannot be brought into normal form. The criterion says we have not straightforward inconsistency, but rather genuine paradoxicality. §3 turns to problems engendered by the proposition $$\exists p(Qp\wedge \lnot p)$$

∃
p
(
Q
p
∧
¬
p
)

(call it $$\eta $$
η
) for the similar possibilitate $$\Diamond \forall q(Qq\!\leftrightarrow \!(\eta \!\leftrightarrow \! q))$$

◊
∀
q
(
Q
q

↔

(
η

↔

q
)
)

. The attempted disproof of this premise-pair—again, a constructive one—cannot succeed. It cannot be brought into normal form. The criterion says the premise-pair is a genuine paradox. In §4 we show how Russell’s Paradox of Propositions, like the Priorean intensional paradoxes, is to be classified as a genuine paradox by the proof-theoretic criterion of paradoxicality.
X-Detect: explainable adversarial patch detection for object detectors in retail
Authors: Hofman Omer , Giloni Amit , Hayun Yarin , Morikawa Ikuya , Shimizu Toshiya , Elovici Yuval , Shabtai Asaf 
Published: June 2024

AbstractObject detection models, which are widely used in various domains (such as retail), have been shown to be vulnerable to adversarial attacks. Existing methods for detecting adversarial attacks on object detectors have had difficulty detecting new real-life attacks. We present X-Detect, a novel adversarial patch detector that can: (1) detect adversarial samples in real time, allowing the defender to take preventive action; (2) provide explanations for the alerts raised to support the defender’s decision-making process, and (3) handle unfamiliar threats in the form of new attacks. Given a new scene, X-Detect uses an ensemble of explainable-by-design detectors that utilize object extraction, scene manipulation, and feature transformation techniques to determine whether an alert needs to be raised. X-Detect was evaluated in both the physical and digital space using five different attack scenarios (including adaptive attacks) and the benchmark COCO dataset and our new Superstore dataset. The physical evaluation was performed using a smart shopping cart setup in real-world settings and included 17 adversarial patch attacks recorded in 1700 adversarial videos. The results showed that X-Detect outperforms the state-of-the-art methods in distinguishing between benign and adversarial scenes for all attack scenarios while maintaining a 0% FPR (no false alarms) and providing actionable explanations for the alerts raised. A demo is available.
Improving interpretability via regularization of neural activation sensitivity
Authors: Moshe Ofir , Fidel Gil , Bitton Ron , Shabtai Asaf 
Published: June 2024

AbstractState-of-the-art deep neural networks (DNNs) are highly effective at tackling many real-world tasks. However, their widespread adoption in mission-critical contexts is limited due to two major weaknesses - their susceptibility to adversarial attacks and their opaqueness. The former raises concerns about DNNs’ security and generalization in real-world conditions, while the latter, opaqueness, directly impacts interpretability. The lack of interpretability diminishes user trust as it is challenging to have confidence in a model’s decision when its reasoning is not aligned with human perspectives. In this research, we (1) examine the effect of adversarial robustness on interpretability, and (2) present a novel approach for improving DNNs’ interpretability that is based on the regularization of neural activation sensitivity. We evaluate the interpretability of models trained using our method to that of standard models and models trained using state-of-the-art adversarial robustness techniques. Our results show that adversarially robust models are superior to standard models, and that models trained using our proposed method are even better than adversarially robust models in terms of interpretability.(Code provided in supplementary material.)
Lattice cohomology and subspace arrangements: the topological and analytic cases
Authors: Ágoston Tamás 
Published: June 2024

AbstractIn this paper we consider the (topological) lattice cohomology $$\mathbb {H}^*$$

H

∗

of a surface singularity with rational homology sphere link. In particular, we will be studying two sets of (topological) invariants related to it: the weight function $$\upchi $$
χ
that induces the cohomology and the topological subspace arrangement $$T(\ell ,I)$$

T
(
ℓ
,
I
)

at each lattice point $$\ell $$
ℓ
— the latter of which is the weaker of the two. We shall prove that the two are in fact equivalent by establishing an algorithm to compute $$\upchi $$
χ
from the subspace arrangement. Replacing the topological arrangements with the analytic, we get another formula — one that connects them with the analytic lattice cohomology introduced and studied in our earlier papers. In fact, this connection served as the original motivation for the definition of the latter. Aside from the historical interest, this parallel also provides us with tools to study more easily the connection between the two cohomologies.
Modeling NP-problems with families of extended graph-based reaction systems
Authors: Kreowski Hans-Jörg , Lye Aaron 
Published: June 2024

AbstractIn this paper, we continue the investigation of graph-based reaction systems. We extend the notion by input and output states as well as admitted context sequences to model explicitly input–output relations and decision problems on the inputs. Moreover, we combine extended graph-based reaction systems into families to cover infinite input–output relations and decision problems on infinite sets of graphs. This is used to model NP-problems on graphs and reductions between them as well as to prove their correctness.
Incidence of brain metastasis according to patient race and primary cancer origin: a systematic review
Authors: Gomez David , Feng Jeffrey J. , Cheok Stephanie , Shah Ishan , Dicharry Holly , Cote David J. , Briggs Robert G. , Guerra Gage A. , Peterson Racheal , Salhia Bodour , Neman Josh , Attenello Frank , Chow Frances , Musabelliu Erion K. , Zada Gabriel 
Published: June 2024

Abstract
Purpose
A systematic review was conducted to investigate differences in incidence and primary origin of synchronous brain metastasis (sBM) in varying racial groups with different primary cancers.

Methods
Adhering to PRISMA 2020 guidelines a search was conducted using PubMed and Ovid databases for publications from January 2000 to January 2023, with search terms including combinations of “brain metastasis,” “race,” “ethnicity,” and “incidence.” Three independent reviewers screened for inclusion criteria encompassing studies clearly reporting primary cancer sites, patient demographics including race, and synchronous BM (sBM) incidence.

Results
Of 806 articles, 10 studies comprised of mainly adult patients from the United States met final inclusion for data analysis. Higher sBM incidence proportions were observed in American Indian/Alaska native patients for primary breast (p < 0.001), colorectal (p = 0.015), and esophageal cancers (p = 0.024) as well as in Asian or Pacific islanders for primary stomach (p < 0.001), thyroid (p = 0.006), and lung/bronchus cancers (p < 0.001) yet higher proportions in White patients for malignant melanoma (p < 0.001). Compared to White patients, Black patients had higher sBM incidence likelihood in breast cancer (OR = 1.27, p = 0.01) but lower likelihood in renal (OR = 0.46, p < 0.001) and esophageal cancers (OR = 0.31, p = 0.005). American Indian/Alaska native patients had a higher sBM likelihood (OR = 3.78, p = 0.004) relative to White patients in esophageal cancer.

Conclusions
These findings reveal several comparative racial differences in sBM incidence arising from different primary cancer origins, underscoring a need for further research to explain these variations. Identifying the factors contributing to these disparities holds the potential to promote greater equity in oncological care according to cancer type.
A Single Image High-Perception Super-Resolution Reconstruction Method Based on Multi-layer Feature Fusion Model with Adaptive Compression and Parameter Tuning
Authors: Zhang Rui , Ren Wenyu , Pan Lihu , Bai Xiaolu , Li Ji 
Published: June 2024

AbstractWe propose a simple image high-perception super-resolution reconstruction method based on multi-layer feature fusion model with adaptive compression and parameter tuning. The aim is to further balance the high and low-frequency information of an image, enrich the detailed texture to improve perceptual quality, and improve the adaptive optimization and generalization of the model in the process of super-resolution reconstruction. First, an effective multi-layer fusion super-resolution (MFSR) basic model is constructed by the design of edge enhancement, refine layering, enhanced super-resolution generative adversarial network and other sub-models, and effective multi-layer fusion. This further enriches the image representation of features of different scales and depths and improves the feature representation of high and low-frequency information in a balanced way. Next, a total loss function of the generator is constructed with adaptive parameter tuning performance. The overall adaptability of the model is improved through adaptive weight distribution and fusion of content loss, perceptual loss, and adversarial loss, and improving the error while reducing the edge enhancement model. Finally, a fitness function with the evaluation perceptual function as the optimization strategy is constructed, and the model compression and adaptive tuning of MFSR are carried out based on the multi-mechanism fusion strategy. Consequently, the construction of the adaptive MFSR model is realized. Adaptive MFSR can maintain high peak signal to noise ratio and structural similarity on the test sets Set5, Set14, and BSD100, and achieve high-quality reconstructed images with low learned perceptual image patch similarity and perceptual index, while having good generalization capabilities.
The shutdown problem: an AI engineering puzzle for decision theorists
Authors: Thornley Elliott 
Published: June 2024

AbstractI explain and motivate the shutdown problem: the problem of designing artificial agents that (1) shut down when a shutdown button is pressed, (2) don’t try to prevent or cause the pressing of the shutdown button, and (3) otherwise pursue goals competently. I prove three theorems that make the difficulty precise. These theorems suggest that agents satisfying some innocuous-seeming conditions will often try to prevent or cause the pressing of the shutdown button, even in cases where it’s costly to do so. I end by noting that these theorems can guide our search for solutions to the problem.
Powers, persistence, and the problem of temporary intrinsics
Authors: Allen Sophie R. 
Published: June 2024

Abstract
David Lewis uses the problem of temporary intrinsics to motivate a perdurantist account of persistence in which four-dimensional individuals consist of temporal parts. Other philosophers use his argument to conclude that apparently persisting individuals are collections of temporal stages. In this paper, I investigate whether this argument is as effective in an ontology in which properties are causal powers and thus how seriously the problem should be taken. I go back to first principles to examine the ways in which individuals can change within an ontology of powers and then consider whether any of these ways are compatible with Lewis’s problem. I conclude that if powers are intrinsic, they are not temporary; and if they are temporary, they are not fully intrinsic. However, the situation with respect to changes in which powers are manifesting is not so clear cut, and so I explore how different conceptions of manifestation affect whether the problem of temporary intrinsics applies and what the powers theorist may say about them.
A Bayesian multilevel model for populations of networks using exponential-family random graphs
Authors: Lehmann Brieuc , White Simon 
Published: June 2024

AbstractThe collection of data on populations of networks is becoming increasingly common, where each data point can be seen as a realisation of a network-valued random variable. Moreover, each data point may be accompanied by some additional covariate information and one may be interested in assessing the effect of these covariates on network structure within the population. A canonical example is that of brain networks: a typical neuroimaging study collects one or more brain scans across multiple individuals, each of which can be modelled as a network with nodes corresponding to distinct brain regions and edges corresponding to structural or functional connections between these regions. Most statistical network models, however, were originally proposed to describe a single underlying relational structure, although recent years have seen a drive to extend these models to populations of networks. Here, we describe a model for when the outcome of interest is a network-valued random variable whose distribution is given by an exponential random graph model. To perform inference, we implement an exchange-within-Gibbs MCMC algorithm that generates samples from the doubly-intractable posterior. To illustrate this approach, we use it to assess population-level variations in networks derived from fMRI scans, enabling the inference of age- and intelligence-related differences in the topological structure of the brain’s functional connectivity.
Grab to fill the gap: key factors influencing Reynoutria japonica germination and seedling establishment in the secondary distribution range
Authors: Kadlecová Martina , Vojík Martin , Vacula Jaroslav , Berchová Bímová Kateřina 
Published: June 2024

AbstractReynoutria japonica (Japanese knotweed) is a highly invasive female plant that primarily reproduces through vegetative regeneration during secondary distribution. Despite producing a substantial number of viable hybrid seeds, the occurrence of seedlings and young plants in the wild remains rare; the reasons for this rarity are unclear. Environmental intolerance and chromosomal anomalies during hybridisation can impede seedling development. This study evaluates the combined impact of these factors by examining substrate, temperature, and light effects on germination, as well as assessing seedling genome sizes and viability. Seeds were cultivated in both natural and controlled environments to manage external influences. Flow cytometry was employed to evaluate chromosomal arrangements. The final germination was notably high at 99%, and 68% of seedlings thrived under controlled conditions, emphasising hybrid seedling viability regardless of highly polyploid levels ranging from pentaploid to aneuploid (2C DNA genome size from 5.17 to 11.95 pg). Thus, it is evident that seeds can germinate and produce vital seedlings despite various chromosomal sets. Even fluctuating temperatures and type of substrate do not limit seed germination. However, these results were obtained under laboratory conditions, with seeds and seedlings receiving regular irrigation. A significant seedling mortality rate (99%) was observed in the field experiment, and the final germination was also low there (15%). Observations suggest that water stress might be the cause of this mortality. Further research on water stress is necessary because it could be the primary factor limiting the successful generative spread of the knotweeds.
BrainLossNet: a fast, accurate and robust method to estimate brain volume loss from longitudinal MRI
Authors: Opfer Roland , Krüger Julia , Buddenkotte Thomas , Spies Lothar , Behrendt Finn , Schippling Sven , Buchert Ralph 
Published: June 2024

Abstract
Purpose
MRI-derived brain volume loss (BVL) is widely used as neurodegeneration marker. SIENA is state-of-the-art for BVL measurement, but limited by long computation time. Here we propose “BrainLossNet”, a convolutional neural network (CNN)-based method for BVL-estimation.

Methods
BrainLossNet uses CNN-based non-linear registration of baseline(BL)/follow-up(FU) 3D-T1w-MRI pairs. BVL is computed by non-linear registration of brain parenchyma masks segmented in the BL/FU scans. The BVL estimate is corrected for image distortions using the apparent volume change of the total intracranial volume. BrainLossNet was trained on 1525 BL/FU pairs from 83 scanners. Agreement between BrainLossNet and SIENA was assessed in 225 BL/FU pairs from 94 MS patients acquired with a single scanner and 268 BL/FU pairs from 52 scanners acquired for various indications. Robustness to short-term variability of 3D-T1w-MRI was compared in 354 BL/FU pairs from a single healthy men acquired in the same session without repositioning with 116 scanners (Frequently-Traveling-Human-Phantom dataset, FTHP).

Results
Processing time of BrainLossNet was 2–3 min. The median [interquartile range] of the SIENA-BrainLossNet BVL difference was 0.10% [− 0.18%, 0.35%] in the MS dataset, 0.08% [− 0.14%, 0.28%] in the various indications dataset. The distribution of apparent BVL in the FTHP dataset was narrower with BrainLossNet (p = 0.036; 95th percentile: 0.20% vs 0.32%).

Conclusion
BrainLossNet on average provides the same BVL estimates as SIENA, but it is significantly more robust, probably due to its built-in distortion correction. Processing time of 2–3 min makes BrainLossNet suitable for clinical routine. This can pave the way for widespread clinical use of BVL estimation from intra-scanner BL/FU pairs.
Powder bed fusion factory productivity increases using discrete event simulation and genetic algorithm
Authors: Al-zqebah Ruba , Guertler Matthias , Clemon Lee 
Published: June 2024

Abstract
Powder bed fusion is importance is growing with uses across industries in both polymer and metallic components, particularly in mass individualization. However, due to the relatively slow mass deposition speed compared to conventional methods, scheduling and production planning play a crucial role in scaling up additive manufacturing productivity to higher volumes. This paper introduces a framework combining discrete event simulation and a genetic algorithm showing makespan improvement opportunities for multiple powder bed fusion factories varying workers, jobs and available equipment. The results show that bottlenecks move among workstations based on worker and capital equipment availability, which depend on the size of the facility indicating a resource-driven constraint for makespan. A makespan reduction of 78% is achieved in the simulation. This shows the trade-off of worker and capital equipment to achieve makespan improvements. The addition of personnel or equipment increases production with further gains achieved by scheduling optimization. Two levels of job demands are analyzed showing productivity gains of 45% makespan improvement when adding the first worker and additional savings with scheduling optimization using a genetic algorithm up to 11%. Most research on additive manufacturing production has focused on the quality of produced parts and printing technology rather than factory level management. This is the first application of this methodology to varying sizes of these potential factories. The method developed here will help decision-makers to determine the appropriate number of resources to meet their customer demand on time, additionally, finding the optimal route for jobs before starting the production process.
Influence of the carbon fiber plate curvature of advanced footwear technology on the running energetic cost and 3000-m performance
Authors: Ruiz-Alias Santiago A. , Pérez-Castilla Alejandro , Soto-Hermoso Víctor M. , García-Pinillos Felipe 
Published: June 2024

AbstractThis study aimed to explore the effect of two similar commercialized advanced footwear technology models differing mainly in their plate geometry (i.e., low and high curvature plate) on the running energetic cost in both non-fatigued and fatigued states. It also sought to determine their impacts on 3000-m performance. Twelve highly trained male athletes performed four 5-min trials (two advanced technology models, two trials). In each experimental session, athletes completed a 3000-m trial which was followed by a 5-min trial to test the running energetic cost when fatigued. Athletes exhibited a lower running energetic cost when wearing the low curvature plate in a non-fatigued state (P = 0.034; − 1.13 [− 1.92 to − 0.11] %), which persisted with better performance in the 3000-m trial (P = 0.017; − 0.42 [− 0.74 to − 0.09] %). However, in a fatigued state, non-significant differences were reported (P = 0.207). The low curvature plate seems to be more effective than the high curvature plate when running at low intensity in a fresh state as well as in a maximal high-intensity effort. However, non-significant differences between plate geometries were observed when fatigue was increased.