bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sustainability in surgical practice: a collaborative call toward environmental sustainability in operating rooms
Authors: Johnson Shaneeta M. , Marconi Stefania , Sanchez-Casalongue Manuel , Francis Nader , Huo Bright , Alseidi Adnan , Alimi Yewande R. , Pietrabissa Andrea , Arezzo Alberto , Frountzas Maximos , Bellato Vittoria , Potapov Oleksii , Barach Paul , Rems Miran , Bello Ricardo J. , Nijhawan Sheetal , Oslock Wendelyn M. , Sathe Tejas S. , Hall Ryan P. , Miller Benjamin , Samreen Sarah , Chung Jimmy , Marfo Nana , Lim Robert B. , Vandeberg Jonathan , Eussen Myrthe M. , Bouvy Nicole D. , Sylla Patricia 
Published: July 2024

Abstract
Background
The healthcare system plays a pivotal role in environmental sustainability, and the operating room (OR) significantly contributes to its overall carbon footprint. In response to this critical challenge, leading medical societies, government bodies, regulatory agencies, and industry stakeholders are taking measures to address healthcare sustainability and its impact on climate change. Healthcare now represents almost 20% of the US national economy and 8.5% of US carbon emissions. Internationally, healthcare represents 5% of global carbon emissions. US Healthcare is an outlier in both per capita cost, and per capita greenhouse gas emission, with almost twice per capita emissions compared to every other country in the world.

Methods
The Society of American Gastrointestinal and Endoscopic Surgeons (SAGES) and the European Association for Endoscopic Surgery (EAES) established the Sustainability in Surgical Practice joint task force in 2023. This collaborative effort aims to actively promote education, mitigation, and innovation, steering surgical practices toward a more sustainable future.

Results
Several key initiatives have included a survey of members' knowledge and awareness, a scoping review of terminology, metrics, and initiatives, and deep engagement of key stakeholders.

Discussion
This position paper serves as a Call to Action, proposing a series of actions to catalyze and accelerate the surgical sustainability leadership needed to respond effectively to climate change, and to lead the societal transformation towards health that our times demand.
Diagnostic value of transcranial doppler to predict delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage
Authors: van der Harst J. Joep , Elting Jan Willem J. , Hijlkema Johanna , Veeger Nic J. G. M. , van Donkelaar Carlina E. , van Dijk J. Marc C. , Uyttenboogaart Maarten 
Published: July 2024

Abstract

Background
Transcranial Doppler (TCD) is a technique to assess blood flow velocity in the cerebral arteries. TCD is frequently used to monitor aneurysmal subarachnoid hemorrhage (aSAH) patients. This study compares TCD-criteria for vasospasm and its association with Delayed Cerebral Ischemia (DCI). An overall score based on flow velocities of various intracranial arteries was developed and evaluated.

Methods
A retrospective diagnostic accuracy study was conducted between 1998 and 2017 with 621 patients included. Mean flow velocity (MFV) of the cerebral artery was measured between 2–5 days and between 6–9 days after ictus. Cutoff values from the literature, new cutoff values, and a new composite score (Combined Severity Score) were used to predict DCI. Sensitivity, specificity, and area under the curve (AUC) were determined, and logistic regression analysis was performed.

Results
The Combined Severity Score showed an AUC 0.64 (95%CI 0.56-.71) at days 2–5, with sensitivity 0.53 and specificity 0.74. The Combined Severity Score had an adjusted Odds Ratio of 3.41 (95CI 1.86–6.32) for DCI. MCA-measurements yielded the highest AUC to detect DCI at day 2–5: AUC 0.65 (95%CI 0.58–0.73). Optimal cutoff MFV of 83 cm/s for MCA resulted in sensitivity 0.73 and specificity 0.50 at days 2–5.

Conclusion
TCD-monitoring of aSAH patients may be a valuable strategy for DCI risk stratification. Lower cutoff values can be used in the early phase after the ictus (day 2–5) than are commonly used now. The Combined Severity Score incorporating all major cerebral arteries may provide a meaningful contribution to interpreting TCD measurements.
Early reduction of retinal thickness predicts physical and cognitive disability in newly diagnosed multiple sclerosis patients: results from a cross-sectional study
Authors: Toscano Simona , Chisari Clara Grazia , Biondi Alice , Patti Francesco 
Published: July 2024

Abstract
Introduction
Retinal nerve fiber layer (RNFL) thickness is a promising biomarker of axonal loss and a potential outcome predictor in Multiple Sclerosis (MS). Cognitive impairment (CoI) exhibits a high prevalence in patients with MS (pwMS), even in the early phases of the disease. Our aim was to explore the role of RNFL thickness as a predictor of physical and cognitive disability in pwMS.

Methods
All newly diagnosed pwMS referred to the MS centre of the University-Hospital “Policlinico-San Marco” between 2015–2019 were evaluated at baseline and at 3 years. RNFL and ganglion cell layer (GCL) thickness for right (r.e.) and left eyes (l.e.) were measured with Optical Coherence Tomography (OCT). Disability level and cognitive profile were assessed, using the Expanded Disability Status Scale (EDSS) and the Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) battery, respectively.

Results
We consecutively enrolled 487 pwMS, including 68 (14.0%) with primary progressive MS (PPMS). At baseline, RNFL and GCL were bilaterally thinner in PPMS (r.e. 90.4 ± 12.7; l.e. 90.2 ± 13.5, and r.e. 80.1 ± 11.2; l.e. 80.3 ± 12.6, respectively) compared to relapsing–remitting MS (RRMS) (r.e. 94.6 ± 13.1; l.e. 94.3 ± 14.8, and r.e. 85.1 ± 9.5; l.e. 84.9 ± 9.3, respectively) (p < 0.01). Both groups exhibited reduced RNFL and GCL thickness, worse cognitive performance and higher EDSS scores at 3-years follow-up compared with baseline. RNFL thickness ≤ 88.0 μm was an independent predictor of CoI (OR = 5.32; 95% CI = 1.84–9.12; p = 0.02) and disability worsening (OR = 3.18; 95% CI = 1.21–10.33; p = 0.05).

Discussion
RNFL thickness, as a biomarker of neurodegeneration, could be considered a predictive biomarker of cognitive degeneration and physical disability in MS.
Perturbations of non-autonomous second-order abstract Cauchy problems
Authors: Budde C. , Seifert C. 
Published: July 2024

AbstractIn this paper we present time-dependent perturbations of second-order non-autonomous abstract Cauchy problems associated to a family of operators with constant domain. We make use of the equivalence to a first-order non-autonomous abstract Cauchy problem in a product space, which we elaborate in full detail.
As an application we provide a perturbed non-autonomous wave equation.
Effects on fatty acids, biochemical composition and growth of rotifer (Brachionus plicatilis) fed with different concentrations of Nannochloropsis sp.
Authors: Osmanoğlu Mustafa İbrahim , Elp Mahmut , Durmaz Yaşar 
Published: July 2024

AbstractThe density of microalgae and nutrient content have impact on the population growth rate, egg rate and nutritional values of rotifers. The aim of this study was to investigate the effects of different concentrations of the alga Nannochloropsis sp. (N10: 10x106, N20: 20x106, N30: 30x106 cells mL-1) on the growth, egg rate, biochemical composition and fatty acid profile of the rotifer Brachionus plicatilis. To maintain a consistent algae density, an equivalent quantity was supplemented to compensate for any reduction. The study was started with three replicates, each with an initial inoculation density of 200 Brachionus individuals mL-1 . The investigation spanned 5 days, during which population parameters (total number of individuals, proportion of individuals with eggs and growth rate) were calculated. After the study period, rotifers were harvested for subsequent biochemical and fatty acid analyses. Notably, the N30 group showed the highest proportions of crude protein (54.41%) and crude lipid (34.5%). The N20 group displayed the most substantial content of total fatty acids, recording a value of 70.69%. Consequently, the N30 group, with a concentration of 30x106 cells mL-1, emerged as the most proficient group, demonstrating superior performance in both population growth and biochemical composition.
The defocalizing effect of international courts: Evidence from maritime delimitation practices
Authors: Yildiz Ezgi , Yüksel Umut 
Published: July 2024

AbstractCan international courts influence state policies and facilitate interstate cooperation? Existing literature argues that they can. Courts can make cooperative outcomes easier for states by formulating or endorsing rules around which state expectations and practice can converge. While it is widely assumed that court rulings may become focal points and play a role in harmonizing state practices, we know little about the conditions under which they have such an effect. We suggest that court rulings can often have an opposite, defocalizing effect, which may durably harm the prospects of convergence around what the law requires. We introduce defocalization as a process and discuss its possible types and implications. We argue that defocalization may be driven by incongruence of court rulings with existing treaty law and state practice and inconsistency of rulings over time. We illustrate our argument by examining the effect of key judicial rulings on the convergence of state views about the appropriate maritime delimitation rules by relying on an original dataset. Our findings show how defocalization unfolds and suggest that complexity can accumulate over time through legal rulings that are incongruent with existing state practice or treaty law, and can be maintained through inconsistent court decisions.
Elusive collaboration? The determinants of lead donorship in international development
Authors: Williams Miles D. 
Published: July 2024

AbstractLead donorship is a condition of sustained outsized responsibility by one foreign aid donor country for giving aid to a developing country. Prior research argues that lead donorship can either be a product of donors collaborating to carve out spheres of influence to maximize non-development foreign policy goals or else of donors buck-passing responsibility for addressing recipient needs. Which is it? This study seeks to answer this question using theory-driven expectations about when and where lead donorship should arise if donors cooperate or systematically fail to do so. It further develops novel measures of foreign aid’s public goods characteristics and donors’ marginal returns from giving aid that should help triangulate conditions under which we can expect lead donorship to arise due to cooperation or else its absence. Estimates from a flexible semi-parametric modeling strategy show that when and where lead donorship has the highest probability of occurring is consistent with systematic cooperation failure in the allocation of foreign aid. Various robustness checks are done and alternative explanations are also discussed. These findings provide insight into ongoing policy debates about donor cooperation and aid effectiveness and raise questions about what deeper strategic logics preclude donor cooperation.
Improvement of drought forecasting by means of various machine learning algorithms and wavelet transformation
Authors: Tuğrul Türker , Hinis Mehmet Ali 
Published: July 2024

Abstract
Drought, which is defined as a decrease in average rainfall amounts, is one of the most insidious natural disasters. When it starts, people may not be aware of it, which is why droughts are difficult to monitor. Scientists have long been working to predict and monitor droughts. For this purpose, they have developed many methods, such as drought indices, one of which is the Standardized Precipitation Index (SPI). In this study, SPI was used to detect droughts, and machine learning algorithms, including support vector machines (SVM), artificial neural networks, random forest, and decision tree, were used to predict droughts. In addition, 3 different statistical criteria, which are correlation coefficient (r), root mean square error (RMSE), and Nash–Sutcliffe efficiency (NSE), were used to investigate model performance values. The wavelet transform (WT) was also applied to improve model performance. One of the areas most impacted by droughts in Turkey is the Konya Closed Basin, which is geographically positioned in the center of the country and is among the top grain-producing regions in Turkey. The Apa Dam is one of the most significant water resources in the area. It provides water to many fertile fields in its vicinity and is affected by droughts which is why it was selected as a study area. Meteorological data, such as monthly precipitation, that could represent the region were obtained between 1955 and 2020 from the general directorate of state water works and the general directorate of meteorology. According to the findings, the M04 model, whose input structure was developed using SPI, various time steps, data delayed up to 5 months, and monthly precipitation data from the preceding month (time t − 1), produced the best results out of all the models examined using machine learning algorithms. Among machine learning algorithms, SVM has achieved the most successful results not only before applying WT but also after WT. The best results were obtained from M04, in which SVM with WT was used (NSE = 0.9942, RMSE = 0.0764, R = 0.9971).
Long-term outcomes of high-dose-rate brachytherapy and external beam radiotherapy without hormone therapy for high-risk localized prostate cancer
Authors: Kamitani Nobuhiko , Watanabe Kenta , Ikeda Naoki , Kawata Yujiro , Tokiya Ryoji , Hayashi Takafumi , Miyaji Yoshiyuki , Tamada Tsutomu , Katsui Kuniaki 
Published: July 2024

Abstract
Purpose
Until March 2018, patients with high-risk localized prostate cancer had been administered high-dose-rate brachytherapy (HDR-BT) combined with external beam radiotherapy (EBRT) without additional hormone therapy (HT) at our institution. In this study, we aimed to evaluate long-term outcomes of this treatment.

Materials and methods
Patients with prostate cancer who received HDR-BT and EBRT between April 1997 and March 2021 and who were followed up for at least 6 months were included in the study. High-risk groups were classified into five levels according to the National Comprehensive Cancer Network guidelines. The EBRT and HDR-BT doses were 39–45 Gy/13–25 fractions. and 16.5–22 Gy/2–4 fractions, respectively. None of the patients received HT during initial treatment. The Kaplan–Meier method was used to estimate biochemical freedom from failure (bFFF), cause-specific survival (CSS), and overall survival (OS) rates. Biochemical failure was also determined.

Results
Seventy-two patients were enrolled in the study, with a median follow-up of 91.9 months. The median age and initial prostate-specific antigen (iPSA) level were 71 years and 10.95 ng/mL, respectively. The median biologically effective dose for HDR-BT plus EBRT was 270.3 Gy. The 5- and 7-year bFFF, CSS, and OS rates were 85.2 and 74.2%, 100 and 100%, and 95.7 and 91.9%, respectively. Only the iPSA ≤ 20 group was associated with the higher bFFF rate. The 7-year bFFF rates in the groups with iPSA ≤ 20 and iPSA > 20 were 86.6 and 48.6%, respectively.

Conclusion
HDR-BT plus EBRT without HT might be an alternative treatment option for patients with high-risk localized prostate cancer and iPSA levels ≤ 20. Further studies are required to validate the efficacy of this treatment strategy.
Harmonic Morphisms from Fefferman Spaces
Authors: Dragomir Sorin , Esposito Francesco , Loubeau Eric 
Published: July 2024

AbstractWe study a ramification of a phenomenon discovered by Baird and Eells (in: Looijenga et al (eds) Geometry Symposium Utrecht 1980. Lecture Notes in Mathematics, Springer, Berlin, 1981) i.e. that non-constant harmonic morphisms $$\Phi : {{\mathfrak {M}}}^{\textrm{N}} \rightarrow N^2$$

Φ
:

M

N

→

N
2

from a $$\mathrm N$$
N
-dimensional ($$\textrm{N} \ge 3$$

N
≥
3

) Riemannian manifold $${{\mathfrak {M}}}^{\textrm{N}}$$

M

N

, into a Riemann surface $$N^2$$

N
2

, can be characterized as those horizontally weakly conformal maps having minimal fibres. We recover Baird–Eells’ result for $$S^1$$

S
1

invariant harmonic morphisms $$\Phi : {{\mathfrak {M}}}^{2n+2} \rightarrow N^2$$

Φ
:

M

2
n
+
2

→

N
2

from a class of Lorentzian manifolds arising as total spaces $${{\mathfrak {M}}} = C(M)$$

M
=
C
(
M
)

of canonical circle bundles $$S^1 \rightarrow {{\mathfrak {M}}} \rightarrow M$$

S
1

→
M
→
M

over strictly pseudoconvex CR manifolds $$M^{2n+1}$$

M

2
n
+
1

. The corresponding base maps $$\phi : M^{2n+1} \rightarrow N^2$$

ϕ
:

M

2
n
+
1

→

N
2

are shown to satisfy $$\lim _{\epsilon \rightarrow 0^+} \, \pi _{{{\mathscr {H}}}^\phi } \, \mu ^{{{\mathscr {V}}}^\phi }_\epsilon = 0$$

lim

ϵ
→

0
+

π

H

ϕ

μ
ϵ

V

ϕ

=
0

, where $$\mu ^{{{\mathscr {V}}}^\phi }_\epsilon $$

μ
ϵ

V

ϕ

is the mean curvature vector of the vertical distribution $${{\mathscr {V}}}^\phi = \textrm{Ker} (d \phi )$$

V

ϕ

=
Ker

(
d
ϕ
)

on the Riemannian manifold $$(M, \, g_\epsilon )$$

(
M
,

g
ϵ

)

, and $$\{ g_\epsilon \}_{0< \epsilon < 1}$$

{

g
ϵ

}

0
<
ϵ
<
1

is a family of contractions of the Levi form of the pseudohermitian manifold $$(M, \, \theta )$$

(
M
,

θ
)

.
Expanding the cacao group: three new species of Theobroma sect. Herrania (Malvaceae: Byttnerioideae) from the Western Amazon Basin
Authors: Colli-Silva Matheus , Richardson James Edward , Michelangeli Fabián A. , Pirani José Rubens 
Published: July 2024

SummaryDuring the preparation of a taxonomic revision of Theobroma sensu lato (Malvaceae, Byttnerioideae), three new species of T. sect. Herrania were found: Theobroma globosum, T. nervosum and T. schultesii, which are described herein. Theobroma globosum and T. nervosum belong to T. sect. Herrania subsect. Subcymbicalyx, with species mostly found in the Amazon Basin, characterised, among other features, by petal ligules at least ten times longer than the petal claws. Theobroma schultesii is from T. sect. Herrania subsect. Herrania, with species with petal ligules less than ten times longer than the claw and is mainly found in the southern parts of the Caribbean Sea, the Pacific Ocean, western Colombia, and northern Ecuador. Theobroma globosum is diagnosed by the combination of spherical fruits with smaller leaflets and midrib proportions when compared to other species from the same region. Theobroma nervosum is identified by its toothed, obovate leaflets with secondary veins protruding beyond the leaflet margins, forming elongated projections across the entire leaflet. Theobroma schultesii exhibits a unique set of features in T. sect. Herrania subsect. Herrania, having both petiolulate leaflets and a cupuliform calyx.
Amodal Completion: Mental Imagery or 3D Modeling?
Authors: Gauker Christopher 
Published: July 2024

AbstractIn amodal completion the mind in some sense completes the visual perceptual representation of a scene by representing parts of the scene hidden behind other objects. Cognitive science has had a lot to say about how amodal completion occurs but has had little to say about the format of the representations involved and the way in which they represent. Some philosophers hold that amodal completions take the form of sensory imaginings of the occluded portions. This theory poses a puzzle for both philosophy and neuroscience about how the occluded parts are imagined to be located relative to the unoccluded parts. A better theory begins with the observation that for many purposes it is useful to suppose that the mind contains mental models of three-dimensional structure. Visual perceptions and mental images may be conceived as mental models that represent external scenes by virtue of homomorphism and which possess both a deep aspect, representing both visible and occluded three-dimensional structure, and a perspectival aspect, representing only an arrangement of visible surfaces. In these terms we can explain various problem-solving abilities, such as the ability to imagine what a scene will look like from another point of view. Amodal completions can be treated as deep perceptual representations of three-dimensional structure. Thus amodal completions do not consist of mental imagery, but they can be used to generate mental imagery representing how a scene would look from alternative points of view.
Global semantics correlation transmitting and learning for sketch-based cross-domain visual retrieval
Authors: Jiao Shichao , Han Xie , Kuang Liqun , Xiong Fengguang , He Ligang 
Published: July 2024

AbstractSketch-based cross-domain visual data retrieval is the process of searching for images or 3D models using sketches as input. Achieving feature alignment is a significantly challenging task due to the high heterogeneity of cross-domain data. However, the alignment process faces significant challenges, such as domain gap, semantic gap, and knowledge gap. The existing methods adopt different ideas for sketch-based image and 3D shape retrieval tasks, one is domain alignment, and the other is semantic alignment. Technically, both tasks verify the accuracy of extracted features. Hence, we propose a method based on the global feature correlation and the feature similarity for multiple sketch-based cross-domain retrieval tasks. Specifically, the data from various modalities are fed into separate feature extractors to generate original features. Then, these features are projected to the shared subspace. Finally, domain consistency learning, semantic consistency learning, feature correlation learning and feature similarity learning are performed jointly to make the projected features modality-invariance. We evaluate our method on multiple benchmark datasets. Where the MAP in Sketchy, TU-Berlin, SHREC 2013 and SHREC 2014 are 0.466, 0.473, 0.860 and 0.816. The extensive experimental results demonstrate the superiority and generalization of the proposed method, compared to the state-of-the-art approaches. The in-depth analyses of various design choices are also provided to gain insight into the effectiveness of the proposed method. The outcomes of this research contribute to advancing the field of sketch-based cross-domain visual data retrieval and are expected to be applied to a variety of applications that require efficient retrieval of cross-domain domain data.
An end-to-end hand action recognition framework based on cross-time mechanomyography signals
Authors: Zhang Yue , Li Tengfei , Zhang Xingguo , Xia Chunming , Zhou Jie , Sun Maoxun 
Published: July 2024

AbstractThe susceptibility of mechanomyography (MMG) signals acquisition to sensor donning and doffing, and the apparent time-varying characteristics of biomedical signals collected over different periods, inevitably lead to a reduction in model recognition accuracy. To investigate the adverse effects on the recognition results of hand actions, a 12-day cross-time MMG data collection experiment with eight subjects was conducted by an armband, then a novel MMG-based hand action recognition framework with densely connected convolutional networks (DenseNet) was proposed. In this study, data from 10 days were selected as a training subset, and the remaining data from another 2 days were used as a test set to evaluate the model’s performance. As the number of days in the training set increases, the recognition accuracy increases and becomes more stable, peaking when the training set includes 10 days and achieving an average recognition rate of 99.57% (± 0.37%). In addition, part of the training subset is extracted and recombined into a new dataset and the better classification performances of models can be achieved from the test set. The method proposed effectively mitigates the adverse effects of sensor donning and doffing on recognition results.