bluuebunny/crossref_metadata_2025_split huggingface dataset:
Process-specific digital recording of construction site LCA-inventory to identify decarbonisation pathways
Authors: Wagner A , Ott S 
Published: December 2022

Abstract
In building life cycle assessment, construction site processes are currently hardly accounted for in detail. If considered, the emission values are determined by globally capturing effort values and by allocating them to individual work steps, equipment, or materials. To identify improvement potential to decarbonize construction activities, detailed process data must be captured for specific processes to determine the carbon dioxide emissions of single processes. The results can then be aggregated to larger process units e.g. to components or trades. To fully implement this approach, a recording of process-specific data at construction site is necessary. Therefore, the basic framework to record specific processes at construction site is developed in this article and LCA methodology to systematically link them to emissions is explained. Further, the method of computer vision for automated recording of construction site activities is being presented.
Distributed cyber-physical systems that enhance local-based frugal innovation toward a sustainable built environment
Authors: Yashiro Tomonari 
Published: December 2022

Abstract
The paper debates the comparison between centralized cyber-physical systems and distributed cyber-physical systems (CPS). Centralized CPS implies a system where a single player standardizes data format and protocol together with core services. Distributed CPS implies a system where varieties of digitalization systems by multiple vendors are interconnected to adapt to specific local contexts. Then the paper identifies that distributed CPS has practical advantages over centralized CPS. However, distributed CPS has potential disadvantages that threaten interconnectivity among digitalization systems by multiple vendors. The paper illustrates how such fragmentation could be avoided; it presents how interoperable linkage among multiple systems is realized. IoT-Hub, a sort of data conversion system, is an enabler of interoperability. The paper illustrates the framework of distributed CPS. That comprises several layers that could be managed autonomously by independent players regardless of activities in other layers. The paper exemplifies local-based frugal innovation by such distributed CPS. One example is IoT-based proactive energy demand control system. The system is composed of sensing systems, component systems and application software. The distributed CSP that deploys IoT-Hub enables adaptable coordination of building elements and digitalized systems respecting local specific contexts. In such a way, distributed CPS provides a comfortable indoor climate with optimized energy use. The other example is IoT-based inventory system for building materials. The system is composed of manufacturing process monitoring systems and logistics monitoring systems. The integrated system could provide reportable and verifiable inventory data of building materials. The system can facilitate responsible use of building materials by providing inventory data that is a piece of essential information for environmental declaration. Exemplified cases suggest how distributed CPS strategy has the potential to encourage a broad range of entrepreneurs to commit to frugal innovation toward a sustainable built environment.
0D to 2D carbon-based materials in flexible strain sensors: recent advances and perspectives
Authors: Liu Guodong , Zhang Zhuoqing , Li Zhijian , Guo Linghua , Ning Lulu 
Published: December 2022

Abstract
In the past decade, flexible strain sensors have attracted much attention in the fields of health care, soft robots and other flexible electronics due to their unique flexibility, high stability, and strong mechanical properties. To further meet the requirements of the excellent performance for electronic equipment, carbon-based conductive sensitive materials have become one of the first choice for the preparation of flexible strain sensors due to their excellent electrical conductivity, mechanical properties, and high compatibility. Herein, based on different strain behaviors, this paper analyzes the working mechanism of tensile and compressive strain sensors, focusing on the latest research progress of carbon-based conductive materials in strain sensors with different dimensions. The applications of carbon-based sensitive materials with multifunctional strain sensing in the areas of physiological information detection, human motion, human–machine interaction, and visual display have also been summarized. Furthermore, it has been attempted to discuss the current challenges of carbon-based strain sensors as well as the prospect of flexible strain sensors. This review is aimed to provide appropriate references for further exploitation of multi-functional flexible carbon-based strain sensors.
A sharp Poincaré inequality for functions in 𝐖^{1,∞}(Ω;ℝ)
Authors: Bevan Jonathan , Deane Jonathan , Zelik Sergey 
Published: December 2022

For each natural number

n
n

and any bounded, convex domain

Ω
⊂

R

n

\Omega \subset \mathbb {R}^n

we characterize the sharp constant

C
(
n
,
Ω
)

C(n,\Omega )

in the Poincaré inequality

‖
f
−

f
¯

Ω

‖

L

∞

(
Ω
;

R

)

≤
C
(
n
,
Ω
)
‖
∇
f

‖

L

∞

(
Ω
;

R

)

\| f - \bar {f}_{\Omega }\|_{L^{\infty }(\Omega ;\mathbb {R})} \leq C(n,\Omega ) \|\nabla f\|_{L^{\infty }(\Omega ;\mathbb {R})}

. Here,

f
¯

Ω

\bar {f}_{\Omega }

denotes the mean value of

f
f

over

Ω
\Omega

. In the case that

Ω
\Omega

is a ball

B
r

B_r

of radius

r
r

in

R

n

\mathbb {R}^n

, we calculate

C
(
n
,

B
r

)
=
C
(
n
)
r

C(n,B_r)=C(n)r

explicitly in terms of

n
n

and a ratio of the volumes of the unit balls in

R

2
n
−
1

\mathbb {R}^{2n-1}

and

R

n

\mathbb {R}^n

. More generally, we prove that

C
(
n
,

B

r
(
Ω
)

)
≤
C
(
n
,
Ω
)
≤

n

n
+
1

d
i
a
m

(
Ω
)

C(n,B_{r(\Omega )}) \leq C(n,\Omega ) \leq \frac {n}{n+1}\mathrm {diam}(\Omega )

, where

B

r
(
Ω
)

B_{r(\Omega )}

is a ball in

R

n

\mathbb {R}^n

with the same

n
−

n-

dimensional Lebesgue measure as

Ω
\Omega

. Both bounds are sharp, and the lower bound can be interpreted as saying that, among convex domains of equal measure, balls have the best, i.e. smallest, Poincaré constant.
Language Fluency Deficits in Post-treatment Lyme Disease Syndrome
Authors: Gorlyn Marianne , Keilp John G , Fallon Brian A 
Published: December 2022

Abstract

Objective
Recent neurocognitive studies of patients with post-treatment Lyme disease syndrome (PTLDS) find consistent deficits in memory and processing speed. Language fluency deficits are observed as well but may be secondary to poor memory and slowing rather than an independent deficit.

Method
This study performed a secondary analysis of data presented previously, including individuals with PTLDS and comparison samples of healthy volunteers (HC) and patients with major depressive disorder (MDD), to determine if language fluency deficits could be accounted for by poor performance in these other neurocognitive domains.

Results
Basic verbal abilities, memory, and processing speed were all significantly associated with fluency performance. MDD patients’ fluency deficits relative to HC were accounted for by these covariates. However, PTLDS patients’ poorer fluency performance relative to both other groups was not.

Conclusions
Language fluency appears to be an independent area of neurocognitive deficit within the constellation of PTLDS symptoms.
SCIBER: a simple method for removing batch effects from single-cell RNA-sequencing data
Authors: Gan Dailin , Li Jun 
Published: December 2022

AbstractMotivationIntegrative analysis of multiple single-cell RNA-sequencing datasets allows for more comprehensive characterizations of cell types, but systematic technical differences between datasets, known as ‘batch effects’, need to be removed before integration to avoid misleading interpretation of the data. Although many batch-effect-removal methods have been developed, there is still a large room for improvement: most existing methods only give dimension-reduced data instead of expression data of individual genes, are based on computationally demanding models and are black-box models and thus difficult to interpret or tune.ResultsHere, we present a new batch-effect-removal method called SCIBER (Single-Cell Integrator and Batch Effect Remover) and study its performance on real datasets. SCIBER matches cell clusters across batches according to the overlap of their differentially expressed genes. As a simple algorithm that has better scalability to data with a large number of cells and is easy to tune, SCIBER shows comparable and sometimes better accuracy in removing batch effects on real datasets compared to the state-of-the-art methods, which are much more complicated. Moreover, SCIBER outputs expression data in the original space, that is, the expression of individual genes, which can be used directly for downstream analyses. Additionally, SCIBER is a reference-based method, which assigns one of the batches as the reference batch and keeps it untouched during the process, making it especially suitable for integrating user-generated datasets with standard reference data such as the Human Cell Atlas.Availability and implementationSCIBER is publicly available as an R package on CRAN: https://cran.r-project.org/web/packages/SCIBER/. A vignette is included in the CRAN R package.Supplementary informationSupplementary data are available at Bioinformatics online.
Antigen-specific immunotherapy to restore antigen-specific tolerance in Type 1 diabetes and Graves’ disease
Authors: Zala Aakansha , Thomas Ranjeny 
Published: December 2022

SummaryType 1 diabetes and Graves’ disease are chronic autoimmune conditions, characterized by a dysregulated immune response. In Type 1 diabetes, there is beta cell destruction and subsequent insulin deficiency whereas in Graves’ disease, there is unregulated excessive thyroid hormone production. Both diseases result in significant psychosocial, physiological, and emotional burden. There are associated risks of diabetic ketoacidosis and hypoglycaemia in Type 1 diabetes and risks of thyrotoxicosis and orbitopathy in Graves’ disease. Advances in the understanding of the immunopathogenesis and response to immunotherapy in Type 1 diabetes and Graves’ disease have facilitated the introduction of targeted therapies to induce self-tolerance, and subsequently, the potential to induce long-term remission if effective. We explore current research surrounding the use of antigen-specific immunotherapies, with a focus on human studies, in Type 1 diabetes and Graves’ disease including protein-based, peptide-based, dendritic-cell-based, and nanoparticle-based immunotherapies, including discussion of factors to be considered when translating immunotherapies to clinical practice.
Is Mpox a Sexually Transmitted Infection? Why Narrowing the Scope of This Disease May Be Harmful
Authors: Hazra Aniruddha , Cherabie Joseph N 
Published: December 2022

AbstractThe 2022 multinational mpox outbreak has been characterized by unprecedented spread among men who have sex with men outside of sub-Saharan Africa. Close contact during sex and intimacy has been well established as a key pathway for human-to-human transmission in the current outbreak. Discussions on whether to assign this illness as a sexually transmitted infection (STI) have been ongoing since the initiation of the outbreak. While sexual contact certainly appears to be a primary means of spread, classifying mpox as an STI is inaccurate based on its known transmission dynamics, yields potential unintended consequences, and ignores the historical impact of the disease in Central and West Africa. Rather than focusing our energy on disease categorization, more effort should be placed on destigmatizing this illness and empowering communities at risk to protect themselves from mpox.
Two-Dimensional Block Trees
Authors: Brisaboa Nieves R , Gagie Travis , Gómez-Brandón Adrián , Navarro Gonzalo 
Published: December 2022

Abstract
The Block Tree is a data structure for representing repetitive sequences in compressed space, which reaches space comparable with that of Lempel–Ziv compression while retaining fast direct access to any position in the sequence. In this paper, we generalize Block Trees to two dimensions, in order to exploit repetitive patterns in the representation of images, matrices and other kinds of bidimensional data. We demonstrate the practicality of the two-dimensional Block Trees (2D-BTs) in representing the adjacency matrices of Web graphs, and raster images in GIS applications. For this purpose, we integrate our 2D-BT with the $k^2$-tree—an efficient structure that exploits clustering and sparseness to compress adjacency matrices—so that it also exploits repetitive patterns. Our experiments show that this structure uses 60–80% of the space of the original $k^2$-tree, while being 30% faster to three times slower when accessing cells.
Invasive Plants Have Higher Resistance to Native Generalist Herbivores Than Exotic Noninvasive Congeners
Authors: Wu Shan , Chen Li , Zhou Yue , Xiao Feng , Liu Danfeng , Wang Yi 
Published: December 2022

AbstractResearch on the invasive plant Phytolacca americana (L.) mostly focuses on its medicinal value and enrichment of heavy metals. However, little is known regarding its impact on native herbivorous insects. In this study, we explored the effects of P. americana and the exotic noninvasive Phytolacca icosandra (L.) on the Spodoptera litura (Fabricius) (native tobacco cutworm) via bioassay, oviposition preference, detoxifying enzyme activity analysis, and phytochemical determination. We found that the oviposition preference index (OPI) of S. litura feeding on P. icosandra was higher than that of P. americana. The developmental duration of S. litura feeding on P. icosandra was shorter than that of P. americana. Additionally, the Acetylcholinesterase (AchE) and Glutathione-S-transferase (GST) activities of S. litura feeding on P. americana were higher than that of S. litura feeding on artificial diets or P. icosandra. The content of lignin and flavonoids in P. americana was relatively high, whereas starch content was relatively low. These findings suggest invasive plants have higher resistance to herbivores, thereby suffering less damage than exotic noninvasive plants.
Multi-category classification of left ventricle ejection fraction using a convolutional neural network
Authors: Carter R , Hardway H , Johnson P , Douglass E , Adedinsewo D 
Published: December 2022

Abstract

Background
Screening for left ventricular (LV) systolic dysfunction (defined as ejection fraction ≤35%) based on data from a standard 12-lead electrocardiogram (ECG) has become well established when standard digital ECGs are available–8 independent leads sampled at least 250 hertz for 10 seconds. As the algorithm has been incorporated into various clinical scenarios and ancillary research projects, a limitation of the binary classification at 35% has become apparent.

Purpose
The objective of this study was to develop and validate a deep learning-based algorithm that would classify LVEF into three categories based on only the digital ECG input.

Methods
After IRB approval, native digital resting ECGs acquired between 1/1/2010 and 12/31/2021 on patients seen in Mayo Clinic in Jacksonville were extracted from the institutional electronic ECG database management system (MUSE, GE Healthcare). These ECGs were matched with transthoracic echocardiograms obtained up to four days prior or 30 days after the ECGs acquisition. A convolutional neural network consisting of 8 layers of convolutions, batch normalization and pooling was trained using Keras and Tensorflow with hyper-parameter optimization for L1 and L2 regularization, learning rate adjustments, and class weights to predict three classes of LVEF: ≤35%, 36–51%, and ≥52% based on clinical relevance. The primary measure of overall performance was the detection of LVEF ≤35%; however, the triad of model predictions was also considered in translating the model output to human interpretable findings.

Results
A total of 30,153 patients (60,169 ECG pairings; mean age 63 years; 48% male) were randomly split at the patient level into training (24,172 patients), validation (2,973 patients) and testing (3,008 patients). The trained model provided robust discrimination in the withheld testing data – AUROC of 0.941 (95% CI: 0.931 to 0.950). Using the optimal model threshold based on Youden's index from the validation data (0.186), sensitivity and specificity were estimated to be 87.9% (95% CI: 83.8% to 91.2%) and 86.3% (95% CI: 85.4% to 87.2%) in the testing data. In instances where discordant predictions were observed, the posterior distribution of model probabilities provide additional insights into the possible underlying value of LVEF (Figure 1).

Conclusions
The utilization of a multi-category deep learning classification model for the detection of reduced ejection fraction adds new dimensions to the use of AI technologies on digital ECGs. This work shows high discrimination can still be obtained when using three classes of LVEF.

Funding Acknowledgement
Type of funding sources: None.
Activation of the HeartLogic algorithm on top of heart failure care: a multicenter propensity-matched cohort analysis
Authors: Feijen M , Beles M , Than Y Z , Cordon A , Dupont M , Treskes R W , Caputo M , Mullens W , Van Bokstal K , Auricchio A , Egorova A D , Maes E , Beeres S L M A , Heggermont W A 
Published: December 2022

Abstract

Background
Hospitalization for decompensated heart failure may be prevented by early detection of fluid retention. The multisensory HeartLogic™ algorithm, incorporated in a cardiac implantable electronic device (CIED) aims to detect impending fluid retention and thereby enables timely adjustment of medical therapy. However, it is to be investigated whether HeartLogic™ provides clinical benefit compared to heart failure care with conventional telemonitoring. This analysis investigates the effects of activating HeartLogic™ on top of heart failure care with telemonitoring on the number of episodes with fluid retention and heart failure related hospitalizations.

Methods
Heart failure patients with a CIED were recruited from the outpatient clinics of four European cardiology departments. All patients were included from January 2017 until December 2020, and followed-up for 365 days. Patients with a CIED and an activated HeartLogic™ algorithm were compared to a 1:1 propensity score-based matched control group consisting of patients with CIED on routine telemonitoring. Data of all episodes of (impending) fluid retention with ≥2 signs and symptoms of congestion were included for analyses.

Results
Data of 127 patients with an activated HeartLogic™ algorithm were adequately matched with 127 heart failure patients with a CIED on routine telemonitoring. Median age was 68 [59–75], majority of patients were male (80%), 46% had an ischemic etiology of heart failure. Total follow-up consisted of 254 patient years. During follow up, 77 (61%) individual patients with HeartLogic™ experienced an episode of fluid retention, compared to 85 (67%) induvial patients on routine telemonitoring. Patients with an activated HeartLogic™ algorithm had 1.62±1.78 events of fluid retention per patient year (PPY) compared to 2.61±3.71 events PPY in patients on routine telemonitoring, p&lt;0.01 (Figure 1). Hospitalization for fluid retention occurred in 7 (6%) HeartLogic™ patients (0.06±0.27 hospitalizations PPY) compared to 13 (10%) patients on routine telemonitoring (0.15±0.45 PPY), p=0.07 (Figure 2A). Mean length of hospitalization in days PPY was 0.29±1.46 in patients with HeartLogic™ and 1.59±6.30 in patients on routine telemonitoring, p=0.02 (Figure 2B).

Conclusion
In a real-world multicenter heart failure population, activation of the HeartLogic™ algorithm was associated with a lower number of episodes of fluid retention per patient and a shorter duration of hospitalization for congestive heart failure.

Funding Acknowledgement
Type of funding sources: None.
Clinical relevance of the single-lead ECG of the Apple Watch
Authors: Pepplinkhuizen S , Hoeksema W F , Van Der Stuijt W , Smeding L , Wilde A A M , Knops R E 
Published: December 2022

Abstract

Introduction
The Apple Watch (AW) is one of the first commercially available wearable with built-in electrocardiogram (ECG) electrodes to perform a single-lead ECG to detect atrial fibrillation (AF). The AW ECG application showed to have a high rate of unclassifiable notifications. The interpretation of the single-lead ECG by a physician can possibly reduce the total of unclassifiable notifications and contribute to the overall accuracy to detect AF.

Methods
This was a prospective, non-randomized, single center observational study to evaluate the accuracy and interrater agreement of the single-lead ECG of the AW. Patients scheduled for cardioversion for atrial fibrillation were asked for participation. The AW series 6 was used with WatchiOS 7.2 or 7.3 and ECG algorithm version 2.0. A single-lead ECG was obtained pre-conversion and, when cardioversion was successful, post-conversion. All single-lead ECGs and 12-lead ECGs were adjudicated by two physicians, agreement was reached by consensus. The AW single-lead ECG notification was compared to the physicians “gold-standard” interpretation of the 12-lead ECG. Sensitivity and specificity of the AW single-lead ECG and Kappa coefficient were calculated.

Results
In total, 74 patients were included. Mean age was 67.1±12.3 years and 20.3% were female. In total 65 AF and 64 sinus rhythm (SR) single-lead ECG measurements were obtained. Of these measurements, 27.9% (36/129) showed an unclassifiable notification. The AW ECG notification showed a sensitivity of 93.5% to detect AF and a specificity of 100% to detect SR (K= 0.94). After adjudication of the unclassifiable notifications by two independent physicians 1.6% (2/129) of the measurements remained unclassifiable. When including the by the physicians adjudicated unclassifiable recordings the sensitivity to diagnose AF was 89.2% and the specificity to detect SR was 93.8% (K=0.83). The adjudication of all single-lead ECGs by the two physicians showed a sensitivity of 90.6% to detect AF and specificity of 95.2% to detect SR (K= 0.83) (Table 1). All SR and AF notification by the AW were similarly adjudicated by the two physicians. The kappa coefficient for interrater agreement between both physicians was 0.69 for all single-lead ECGs and 0.58 for unclassifiable notifications specific.

Conclusion
Unclassifiable notifications of the AW can be reduced by physicians interpretation of the single-lead ECG, however the interrater agreement is only moderate. The physicians interpretation of the single-lead ECGs did not increase the accuracy to detect AF and the clinical relevance of the single-lead ECG, in addition to the AW notification, should therefore be questioned.

Funding Acknowledgement
Type of funding sources: None.