bluuebunny/crossref_metadata_2025_split huggingface dataset:
Construction motion data library: an integrated motion dataset for on-site activity recognition
Authors: Tian Yuanyuan , Li Heng , Cui Hongzhi , Chen Jiayu 
Published: November 2022

AbstractIdentifying workers’ activities is crucial for ensuring the safety and productivity of the human workforce on construction sites. Many studies implement vision-based or inertial-based sensors to construct 3D human skeletons for automated postures and activity recognition. Researchers have developed enormous and heterogeneous datasets for generic motion and artificially intelligent models based on these datasets. However, the construction-related motion dataset and labels should be specifically designed, as construction workers are often exposed to awkward postures and intensive physical tasks. This study developed a small construction-related activity dataset with an in-lab experiment and implemented the datasets to manually label a large-scale construction motion data library (CML) for activity recognition. The developed CML dataset contains 225 types of activities and 146,480 samples; among them, 60 types of activities and 61,275 samples are highly related to construction activities. To verify the dataset, five widely applied deep learning algorithms were adopted to examine the dataset, and the usability, quality, and sufficiency were reported. The average accuracy of models without tunning can reach 74.62% to 83.92%.
Cheminformatics analysis of chemicals that increase estrogen and progesterone synthesis for a breast cancer hazard assessment
Authors: Borrel Alexandre , Rudel Ruthann A. 
Published: November 2022

AbstractFactors that increase estrogen or progesterone (P4) action are well-established as increasing breast cancer risk, and many first-line treatments to prevent breast cancer recurrence work by blocking estrogen synthesis or action. In previous work, using data from an in vitro steroidogenesis assay developed for the U.S. Environmental Protection Agency (EPA) ToxCast program, we identified 182 chemicals that increased estradiol (E2up) and 185 that increased progesterone (P4up) in human H295R adrenocortical carcinoma cells, an OECD validated assay for steroidogenesis. Chemicals known to induce mammary effects in vivo were very likely to increase E2 or P4 synthesis, further supporting the importance of these pathways for breast cancer. To identify additional chemical exposures that may increase breast cancer risk through E2 or P4 steroidogenesis, we developed a cheminformatics approach to identify structural features associated with these activities and to predict other E2 or P4 steroidogens from their chemical structures. First, we used molecular descriptors and physicochemical properties to cluster the 2,012 chemicals screened in the steroidogenesis assay using a self-organizing map (SOM). Structural features such as triazine, phenol, or more broadly benzene ramified with halide, amine or alcohol, are enriched for E2 or P4up chemicals. Among E2up chemicals, phenol and benzenone are found as significant substructures, along with nitrogen-containing biphenyls. For P4up chemicals, phenol and complex aromatic systems ramified with oxygen-based groups such as flavone or phenolphthalein are significant substructures. Chemicals that are active for both E2up and P4up are enriched with substructures such as dihydroxy phosphanedithione or are small chemicals that contain one benzene ramified with chlorine, alcohol, methyl or primary amine. These results are confirmed with a chemotype ToxPrint analysis. Then, we used machine learning and artificial intelligence algorithms to develop and validate predictive classification QSAR models for E2up and P4up chemicals. These models gave reasonable external prediction performances (balanced accuracy ~ 0.8 and Matthews Coefficient Correlation ~ 0.5) on an external validation. The QSAR models were enriched by adding a confidence score that considers the chemical applicability domain and a ToxPrint assessment of the chemical. This profiling and these models may be useful to direct future testing and risk assessments for chemicals related to breast cancer and other hormonally-mediated outcomes.
Plasma host protein signatures correlating with Mycobacterium tuberculosis activity prior to and during antituberculosis treatment
Authors: Ndiaye Mame Diarra Bousso , Ranaivomanana Paulo , Rasoloharimanana Lova Tsikiniaina , Rasolofo Voahangy , Ratovoson Rila , Herindrainy Perlinot , Rakotonirina Julio , Schoenhals Matthieu , Hoffmann Jonathan , Rakotosamimanana Niaina 
Published: November 2022

AbstractThere is a need for rapid non-sputum-based tests to identify and treat patients infected with Mycobacterium tuberculosis (Mtb). The overall objective of this study was to measure and compare the expression of a selected panel of human plasma proteins in patients with active pulmonary tuberculosis (ATB) throughout anti-TB treatment (from baseline to the end of treatment), in Mtb-infected individuals (TBI) and healthy donors (HD) to identify a putative host-protein signature useful for both TB diagnosis and treatment monitoring. A panel of seven human host proteins CLEC3B, SELL, IGFBP3, IP10, CD14, ECM1 and C1Q were measured in the plasma isolated from an HIV-negative prospective cohort of 37 ATB, 24 TBI and 23 HD. The protein signatures were assessed using a Luminex xMAP® to quantify the plasmatic levels in unstimulated blood of the different clinical group as well as the protein levels at baseline and at three timepoints during the 6-months ATB treatment, to compare the plasma protein levels between culture slow and fast converters that may contribute to monitor the TB treatment outcome. Protein signatures were defined using the CombiROC algorithm and multivariate models. The studied plasma host proteins showed different levels between the clinical groups and during the TB treatment. Six of the plasma proteins (CLEC3B, SELL, IGFBP3, IP10, CD14 and C1Q) showed significant differences in normalised median fluorescence intensities when comparing ATB vs HD or TBI groups while ECM1 revealed a significant difference between fast and slow sputum culture converters after 2 months following treatment (p = 0.006). The expression of a four-host protein markers (CLEC3B-ECM1-IP10-SELL) was significantly different between ATB from HD or TBI groups (respectively, p < 0.05). The expression of the same signature was significantly different between the slow vs the fast sputum culture converters after 2 months of treatment (p < 0.05). The results suggest a promising 4 host-plasma marker signature that would be associated with both TB diagnostic and treatment monitoring.
Non‐local neural networks combined with local importance‐based pooling for space‐time video super‐resolution
Authors: Zhang Dacheng , Lei Weimin , Zhang Wei , Chen Xinyi 
Published: November 2022

AbstractCompared with convolutional operation, non‐local operation can directly capture long‐range dependencies and thus has a larger receptive field. However, the computation and memory consumption of non‐local operation is much higher than convolutional operation, so it cannot be used repeatedly as a general component directly. In this paper, in order to balance the accuracy and computational complexity of non‐local enhancement, the non‐local operation is simplified based on local importance‐based pooling, which can dynamically extract discriminative features during the down‐sampling process by learning adaptive weights. Such simplified non‐local enhancement is able to prevent unacceptable computational consumption caused by directly processing the entire feature maps containing a large number of features. In order to verify the effectiveness of the proposed method, 2D and 3D feature extraction blocks are constructed based on the simplified non‐local operations, and they are stacked as feature extraction networks for space‐time video super‐resolution task, which aims to increase resolution in both time and space simultaneously. Extensive experiments demonstrate that the proposed simplified non‐local networks can effectively improve the performance of space‐time video super‐resolution task both quantitatively and qualitatively.
GhostCount: A lightweight convolution network based on high‐altitude video for vehicle instantaneous counting in dense traffic scenes
Authors: Cao Qianxia , Shan Zhenyu , Long Kejun , Wang Zhengwu 
Published: November 2022

AbstractInstantaneous vehicle counting of traffic scenes based on high‐altitude video is an important way for real‐time traffic information collection in intelligent transportation systems (ITS). However, vehicle counts based on high‐altitude video are susceptible to problems such as denseness, occlusion and small size. The mainstream method is to use a Convolutional Neural Network (CNN) to output density maps and obtain vehicle count results. However, most CNNs are computationally expensive and have poor real‐time performance. Therefore, we propose a lightweight CNN named GhostCount, specially designed for high‐accuracy vehicle counts on edge devices. First, we combine ResNet‐18 and Lightweight RefineNet to build an encoder–decoder network architecture to effectively extract vehicle features in complex traffic scenes. Next, we replace the ordinary convolutional layers in ResNet‐18 with Ghost modules to lighten the network. Finally, a binary cross‐entropy loss function is introduced to suppress background noise. We demonstrate GhostCount on public datasets (TRANCOS, CARPK, PUCPR+) and our self‐built dataset (CSCAR). Results show that GhostCount can perform instantaneous vehicle counting with higher accuracy and faster inference speed than other representative lightweight CNNs. The method we propose would provide new solutions and ideas for ITS applications such as traffic information collection and smart parking management.
Wissenschaftliche Produktivität der universitären Orthopädie und Unfallchirurgie in der DACH-Region
Authors: Schömig Friederike , Palmowski Yannick , Schitz Florian , Winkler Tobias , Perka Carsten , Pumberger Matthias 
Published: November 2022

Zusammenfassung
Hintergrund Trotz Errungenschaften wie der Entwicklung der Hüftprothese ist die wissenschaftliche Produktivität im Bereich der Orthopädie und Unfallchirurgie kaum untersucht. Ziel unserer Studie war es, den Zusammenhang zwischen dem H-Index und dem akademischen Rang von Ärzten/-innen in Führungspositionen in der Orthopädie und Unfallchirurgie in Deutschland, Österreich und der Schweiz (DACH-Region) zu ermitteln, um festzustellen, inwieweit dieser objektive Maßstab der wissenschaftlichen Leistung mit der klinischen Position korreliert.
Material und Methoden Alle Ärzte/-innen in leitender Funktion an einem Universitätsklinikum für Orthopädie und Unfallchirurgie in der DACH-Region wurden eingeschlossen. Im Zeitraum September bis November 2020 wurden das Jahr der Habilitation, die Anzahl der Publikationen und Zitationen sowie der H-Index erhoben.
Ergebnisse Insgesamt wurden 844 leitende Ärzte/-innen aus 46 Universitätskliniken eingeschlossen. Professoren/-innen publizierten mit 117,4 ± 124,8 die größte Anzahl an Artikeln und wiesen mit 20,1 ± 10,1 den größten H-Index auf (p < 0,001). Zwischen den Ländern zeigten sich signifikante Unterschiede in der Gesamtanzahl an Publikationen (p = 0,001), den Publikationen in den letzten 3 Jahren (p < 0,001) und dem H-Index (p < 0,001), wobei alle Parameter jeweils in der Schweiz am höchsten waren.
Schlussfolgerung Unsere Arbeit zeigt, dass eine hohe wissenschaftliche Produktivität mit akademischem Erfolg assoziiert ist. Die aufgezeigten Unterschiede in der DACH-Region legen den Rückschluss nahe, dass die Bedeutung der wissenschaftlichen Arbeit im klinischen Alltag signifikant variiert.
Intensivverlegungen in der COVID-19-Pandemie – eine Analyse aus einem landesweit koordinierten Intensivverlegungssystem
Authors: Flemming Andreas , Otto Andreas , Ruff Simone , Reinhardt Karsten , Ringe Bastian , Reifferscheid Florian 
Published: November 2022

Zusammenfassung
Zusammenfassung Diese Analyse untersucht den Einfluss der COVID-19-Pandemie auf ein landesweites Intensivverlegungssystem.
Material und Methoden Um die Auswirkungen der COVID-19-Intensivtransporte zu analysieren, wurden retrospektiv 2 17-monatige Betrachtungszeiträume ausgewählt.
Ergebnisse Im Untersuchungszeitraum wurden 5291 Intensivtransporte durchgeführt. Von diesen Transporten waren 525 Intensivtransporte mit COVID-19, wovon 474 (90,3%) per ITW und 51
(9,7%) mittels Luftrettungsmitteln durchgeführt worden sind.
Diskussion Die Gesamteinsatzzahlen wiesen einen initialen Rückgang auf, der sich im Verlauf wieder umkehrte. Es zeigte sich, dass die bodengebundenen Intensivtransporte anstiegen,
während die Einsatzzahlen in der Luftrettung im gesamten Zeitraum signifikant unter dem Niveau des Vergleichszeitraums lagen. Insgesamt fand sich in der Subgruppe der COVID-19-Patienten
eine erhöhte Erkrankungsschwere und intensivmedizinischer Versorgungsaufwand.
Preventing Poor Outcomes for Neurosurgical Patients
Authors: Klavansky Dana , Kellner Christopher , Ghatan Saadi , Nelson Sarah 
Published: November 2022

AbstractEnsuring that patients with neurosurgical conditions have the best possible outcome requires early diagnosis, monitoring, and interventions to prevent complications and optimize care. Here, we review several neurosurgical conditions and the measures taken to prevent complications and optimize outcomes. We hope that the practical tips provided herein prove helpful in caring for neurosurgical patients.
Sexting and sexual behaviour in Australian adolescents
Authors: Falconer Tasha A. , Kauer Sylvia , Fisher Christopher M. 
Published: November 2022

Background Previous studies have tried to determine the relationship between sexting and risky behaviour to discover whether sexting fits into a deviance or normalcy discourse. This study investigated the relationship between sexting and sexual risk behaviours, contraception use and gender. Methods The design was a cross-sectional analysis of data from the sixth National Survey of Secondary Student and Adolescent Sexual Health, collected in 2018. There were 8263 Australian adolescents (aged 14–18 years). Participants were fairly evenly split by gender, and 73% identified as heterosexual. Participants were asked a series of questions about their engagement in sexting, sexual behaviour and sexual health behaviours. Results A total of 52% of participants had sent a sext in the previous 2 months, with most being text-based sexts. Sexters were 3.29 times more likely to have engaged in anal or vaginal intercourse, and 2.88 times more likely to have gotten pregnant than non-sexters. Sexters (M = 2.76) had significantly more partners than non-sexters (M = 2.35), t(3763) = −10.99, P < 0.001. There were no significant differences in STI rates, X2(1) = 0.38, P = 0.535, or contraceptive use based on sexting status. Conclusions Sexters are more likely to have engaged in sexual intercourse and have more partners than non-sexters. Sexting is not strongly associated with other risky behaviours. Evidence for differences between sexters and non-sexters in protecting against STIs and pregnancy was not found, as there were no significant differences in contraceptive use.
Communication between the multidisciplinary team and families regarding nutrition and hydration for people with severe dementia in acute hospitals: a qualitative study
Authors: Anantapong Kanthee , Davies Nathan , Sampson Elizabeth L 
Published: November 2022

Abstract

Background
When a person with severe dementia is in hospital and has eating and drinking difficulties, communication between the multidisciplinary team and families can be challenging and lead to suboptimal care.

Objective
To gain in-depth understanding about the experiences, views and needs of family carers and hospital staff, regarding communication and conversations about nutrition and hydration, for hospital patients with severe dementia.

Design
Qualitative semi-structured interview study.

Setting
Acute hospital in England.

Methods
From January to May 2021, semi-structured interviews were conducted with 29 family carers and hospital staff. Interviews were transcribed verbatim and analysed using reflexive thematic methods.

Results
Four overarching themes were developed: (i) prerequisites to initiating communication about eating and drinking; (ii) communication aiming to develop agreed care plans; (iii) difficulty discussing palliative and end-of-life care; and (iv) needs of information and plans about future eating and drinking difficulties. Families tended to wait for hospital staff to initiate discussions but usually experienced frustration with delays and repeated conversations with different staff. Some staff felt unprepared to manage these conversations and found it challenging to work across the multidisciplinary team. During discharge processes, key information and care plans about eating and drinking were not regularly passed on to people involved to avoid unnecessary readmissions.

Conclusions
In acute hospitals, family carers and hospital staff can have disjointed communications and conversations about nutrition and hydration for persons with severe dementia. Timely reassurance, ongoing discussions and clear information sharing will support communication between those involved.
Self-perceived functioning and (instrumental) activities of daily living questionnaires after a hip fracture: Do they tell the same story?
Authors: Ravensbergen Willeke M , Timmer Irie L , Gussekloo Jacobijn , Blom Jeanet W , van Eijk Monica , Achterberg Wilco P , Evers Andrea W M , van Dijk Sandra , Drewes Yvonne M 
Published: November 2022

Abstract

Background
(Instrumental) activities of daily living ((I)ADL) questionnaires are often used as a measure of functioning for different purposes. Depending on the purpose, a measurement of functioning that includes subjective patient perspectives can be relevant. However, it is unclear to what extent (I)ADL instruments capture self-perceived functioning.

Objective
Explore what functioning means to older persons after a hip fracture and assess the extent to which (I)ADL instruments align with self-perceived functioning.

Design
Qualitative interview study with framework analysis.

Setting
Prospective cohort study on recovery after a hip fracture among older persons in a hospital in a large city in the west of the Netherlands.

Subjects
Eighteen home-dwelling older persons (≥70 years) who had a hip fracture 6–12 months ago.

Methods
Telephone interviews about functioning before and after the hip fracture were coded and analysed using the framework method.

Results
The activities mentioned by participants to be part of their self-perceived functioning could be split into activities necessary to maintain the desired level of independence, and more personal activities that were of value to participants. Both the ‘independence activities’ and the ‘valued activities’ mentioned went beyond the activities included in (I)ADL questionnaires. Due to various coping strategies, limitations in activities that are measured in the (I)ADL questionnaires did not necessarily lead to worse self-perceived functioning.

Conclusion
Self-perceived functioning differs from functioning measured with (I)ADL questionnaires in the items included and the weighing of limitations in activities. Thus, (I)ADL instruments alone are not enough to measure functioning from the perspective of the older person.
Adherence to antimicrobial agent recommendations and utilization during drug shortages
Authors: Urban Victoria , Lee Brian R , Goldman Jennifer L , Duty Ashley , Wirtz Ann L 
Published: November 2022

Abstract

Purpose
Antimicrobial shortages occur frequently, but the impact on antimicrobial use is not well defined. The study objectives were to characterize utilization of antimicrobial agents with established restrictions during a medication shortage, assess utilization of shortage antimicrobials following shortage resolution, and examine use of recommended alternative antimicrobials during the shortage period.

Methods
Five antimicrobials were restricted due to shortages from 2015 through 2020. Chart review of inpatients receiving a shortage medication during each restriction period was performed to determine factors influencing adherence to established restriction criteria. To assess antimicrobial utilization during shortages and following shortage resolution, days of therapy per 1,000 patient days were analyzed for each shortage and alternative antimicrobial.

Results
Across 266 patients receiving shortage antimicrobials, antimicrobial use was adherent to restriction criteria for 151 patients (57%). Meropenem, ampicillin/sulbactam, and piperacillin/tazobactam had the greatest adherence. Median duration of therapy was shorter in the nonadherent group than in the adherent group (4 vs 2 days, P &lt; 0.0001). Shortage antimicrobial use was more likely to be nonadherent for indications such as sepsis rule out, surgical prophylaxis, and urinary tract infection. Adherence increased with use of visual cues in the chart (99% vs 94%, P = 0.03). Utilization of shortage agents decreased during shortage and restriction periods. After shortage resolution, utilization exceeded baseline usage for all agents except meropenem and metronidazole, for which usage returned to baseline. Utilization of 1 to 2 recommended alternative agents for each shortage agent significantly increased during the shortage and restriction periods.

Conclusion
Current strategies for restriction significantly decreased utilization of shortage antimicrobials, but additional opportunities exist. Identifying alternative agents and providing visual cues increased adherence.
Adaptive risk-aware sharable and individual subspace learning for cancer survival analysis with multi-modality data
Authors: Zhao Zhangxin , Feng Qianjin , Zhang Yu , Ning Zhenyuan 
Published: November 2022

AbstractBiomedical multi-modality data (also named multi-omics data) refer to data that span different types and derive from multiple sources in clinical practices (e.g. gene sequences, proteomics and histopathological images), which can provide comprehensive perspectives for cancers and generally improve the performance of survival models. However, the performance improvement of multi-modality survival models may be hindered by two key issues as follows: (1) how to learn and fuse modality-sharable and modality-individual representations from multi-modality data; (2) how to explore the potential risk-aware characteristics in each risk subgroup, which is beneficial to risk stratification and prognosis evaluation. Additionally, learning-based survival models generally refer to numerous hyper-parameters, which requires time-consuming parameter setting and might result in a suboptimal solution. In this paper, we propose an adaptive risk-aware sharable and individual subspace learning method for cancer survival analysis. The proposed method jointly learns sharable and individual subspaces from multi-modality data, whereas two auxiliary terms (i.e. intra-modality complementarity and inter-modality incoherence) are developed to preserve the complementary and distinctive properties of each modality. Moreover, it equips with a grouping co-expression constraint for obtaining risk-aware representation and preserving local consistency. Furthermore, an adaptive-weighted strategy is employed to efficiently estimate crucial parameters during the training stage. Experimental results on three public datasets demonstrate the superiority of our proposed model.