bluuebunny/crossref_metadata_2025_split huggingface dataset:
Adjusting the RAPID score with 2 additional variables significantly increases its predictive value in patients with empyema
Authors: Stüben B. O. , Plitzko G. A. , Urban F. , Kölzer H. , Kemper M. , Wakker J. , Izbicki J. R. , Bachmann K. 
Published: February 2023

AbstractPleural empyema is a serious condition leading to a significant burden on health care systems due to protracted hospitalisations. Treatment ranges from non-surgical interventions such as antibiotic therapy and chest tube placement to thoracoscopic or open surgery. Various risk factors which impact outcomes have been investigated. The RAPID (renal, age, purulence, infection source, and dietary factors) score is a clinical risk score which identifies patients at risk of death and may be used to formulate individual treatment strategies accordingly. All patients undergoing surgical interventions for empyema at a major tertiary medical centre in Germany from 2017 to 2020 were analysed. The aim was to identify perioperative risk factors which significantly impact treatment outcomes but are currently not included in the RAPID score. 245 patients with pleural empyema surgically treated at the Department of General, Visceral and Thoracic Surgery at the University Medical Centre, Hamburg, Germany (admitted from January 2017 to April 2020) were retrospectively analysed. All patients which received either minimally invasive or open thoracic surgery were included. Epidemiological as well as perioperative data was analysed to identify risk factors which impact long-term overall outcomes. 90-day mortality rate was the primary endpoint. The mean age was 59.4 years with a bimodal distribution. There was a male predominance across the cohort (71.4% compared to 28.6%), with no significant differences across ages below or above 60 years. 53 (21.6%) patients died within the first 90 days. Diabetes type 1 and 2, renal replacement therapy, immunosuppression, postoperative bleeding, intraoperative transfusion as well as microbiologically confirmed bacterial invasion of the pleura all led to higher mortality rates. Higher RAPID scores accurately predicted higher 90-day mortality rates. Modifying the RAPID score by adding the comorbidities diabetes and renal replacement therapy significantly increased the predictive value of the score. We demonstrated various perioperative and patient related risk-factors not included in the RAPID score which negatively impact postoperative outcome in patients receiving surgical treatment for pleural empyema. These should be taken into consideration when deciding on the best course of treatment. If confirmed in a prospective study including non-surgical patients with a significantly larger cohort, it may be worth considering expanding the RAPID score to include these.
Electromagnetic metamaterials to approach superconductive-like electrical conductivity
Authors: Danisi A. , Zannini C. 
Published: February 2023

AbstractThis paper explores the possibility of using electromagnetic metamaterials to synthesize an equivalent structure that approaches superconductive-like properties, i.e. extremely high electrical conductivity. The underlying electromagnetic model is formalized analytically using transmission line theory and supported by experimental measurements. This particular use of metamaterials could bring to the ground-breaking scenario of developing superconductive-like cavities and lossless guiding structures at ambient temperature.
Explainable AI for unveiling deep learning pollen classification model based on fusion of scattered light patterns and fluorescence spectroscopy
Authors: Brdar Sanja , Panić Marko , Matavulj Predrag , Stanković Mira , Bartolić Dragana , Šikoparija Branko 
Published: February 2023

AbstractPollen monitoring have become data-intensive in recent years as real-time detectors are deployed to classify airborne pollen grains. Machine learning models with a focus on deep learning, have an essential role in the pollen classification task. Within this study we developed an explainable framework to unveil a deep learning model for pollen classification. Model works on data coming from single particle detector (Rapid-E) that records for each particle optical fingerprint with scattered light and laser induced fluorescence. Morphological properties of a particle are sensed with the light scattering process, while chemical properties are encoded with fluorescence spectrum and fluorescence lifetime induced by high-resolution laser. By utilizing these three data modalities, scattering, spectrum, and lifetime, deep learning-based models with millions of parameters are learned to distinguish different pollen classes, but a proper understanding of such a black-box model decisions demands additional methods to employ. Our study provides the first results of applied explainable artificial intelligence (xAI) methodology on the pollen classification model. Extracted knowledge on the important features that attribute to the predicting particular pollen classes is further examined from the perspective of domain knowledge and compared to available reference data on pollen sizes, shape, and laboratory spectrofluorometer measurements.
Exploring a global interpretation mechanism for deep learning networks when predicting sepsis
Authors: Strickler Ethan A. T. , Thomas Joshua , Thomas Johnson P. , Benjamin Bruce , Shamsuddin Rittika 
Published: February 2023

AbstractThe purpose of this study is to identify additional clinical features for sepsis detection through the use of a novel mechanism for interpreting black-box machine learning models trained and to provide a suitable evaluation for the mechanism. We use the publicly available dataset from the 2019 PhysioNet Challenge. It has around 40,000 Intensive Care Unit (ICU) patients with 40 physiological variables. Using Long Short-Term Memory (LSTM) as the representative black-box machine learning model, we adapted the Multi-set Classifier to globally interpret the black-box model for concepts it learned about sepsis. To identify relevant features, the result is compared against: (i) features used by a computational sepsis expert, (ii) clinical features from clinical collaborators, (iii) academic features from literature, and (iv) significant features from statistical hypothesis testing. Random Forest was found to be the computational sepsis expert because it had high accuracies for solving both the detection and early detection, and a high degree of overlap with clinical and literature features. Using the proposed interpretation mechanism and the dataset, we identified 17 features that the LSTM used for sepsis classification, 11 of which overlaps with the top 20 features from the Random Forest model, 10 with academic features and 5 with clinical features. Clinical opinion suggests, 3 LSTM features have strong correlation with some clinical features that were not identified by the mechanism. We also found that age, chloride ion concentration, pH and oxygen saturation should be investigated further for connection with developing sepsis. Interpretation mechanisms can bolster the incorporation of state-of-the-art machine learning models into clinical decision support systems, and might help clinicians to address the issue of early sepsis detection. The promising results from this study warrants further investigation into creation of new and improvement of existing interpretation mechanisms for black-box models, and into clinical features that are currently not used in clinical assessment of sepsis.
Decadal decline in maternal body condition of a Southern Ocean capital breeder
Authors: Vermeulen Els , Thavar Terriann , Glarou Maria , Ganswindt Andre , Christiansen Fredrik 
Published: February 2023

AbstractThe changing physical properties of the Southern Ocean are known to impact the recruitment and survival of Antarctic krill (Euphausia superba). For oceanic krill predators, the resulting reduced energy intake may lead to population-level effects likely preceded by an alteration in the animals’ body condition. This is especially true for capital breeders that rely on stored energy for successful reproduction. One such Southern Ocean capital breeder, the southern right whale (Eubalaena australis), has been monitored over the past 43 years in their South African wintering ground. Changes in the population have been documented in the past decade, including a decreased reproductive rate and a shift in foraging strategy. To evaluate if a reduced foraging success is an underlying factor, we assessed the temporal variation in morphological body condition through aerial photogrammetry. Results showed a 23% reduction in maternal body condition, potentially contributing to the decreased reproductive rate of the population. To the best of our knowledge, this is the first study to quantify a decadal reduction in the body condition of a capital breeder dependent on Southern Ocean productivity. Understanding the bioenergetic consequences of environmental change is vital to predicting species’ resilience to climate change.
Study on the synthesis mechanism of sodalite, gismondine, and zeolite-P1 zeolite materials from ladle furnace slag and fly ash
Authors: Ma Wenqing , Yi Yuanrong , Fang Minghang , Li Chunhui , Li Jie , Liu Wei 
Published: February 2023

AbstractIn this study, geopolymers were prepared using ladle furnace slag (LFS) and fly ash (FA), and hydrothermal treatment was then used to synthesize bulk zeolite molecular sieves with gismondine, zeolite-P1, and sodalite phases. The effect of the synthesis conditions on the crystalline phases of the zeolite molecular sieves was investigated by XRD. The results showed that the best zeolite molecular sieves were prepared with an LFS: FA ratio of 4: 6, a curing temperature of 40 °C, a curing time of 12 h, a sodium silicate modulus (Ms) of 1.4, a NaOH concentration of 4 mol/L, a hydrothermal temperature of 120 °C, and a hydrothermal time of 12 h. On this basis, the products were analyzed by SEM, N2 adsorption, and FT-IR. The results showed that the synthesized zeolite molecular sieves had mesoporous properties, and the degree of polymerization and cross-linking of the silica-aluminate gel were enhanced after hydrothermal treatment. In addition, the formation mechanism of the zeolite molecular sieves was explored through the changes of the silica-alumina during zeolite formation. This paper is the first to use the hydrothermal conversion of zeolite molecular sieves from LFS-FA based polymers to provide some guidance for the resource utilization of LFS and FA.
Impact of activation energy and variable properties on peristaltic flow through porous wall channel
Authors: Rafiq Maimona , Shaheen Asma , Trabelsi Youssef , Eldin Sayed M. , Khan M. Ijaz , Suker Dhia Kadhm 
Published: February 2023

AbstractThe current study discusses the peristaltic flow of Jeffrey fluid through a porous wall channel. Magnetohydrodynamic (MHD) effects are also considered while formulating the problem. Heat and mass transfers are discussed in the presence of activation energy and constant heat source/sink effects. A chemical reaction is also part of the analysis. The Lubrication approach is adopted for the simplification of resulting non-linear equations. MATHEMATICA command, NDSolve, is used to discuss the results graphically for various flow parameters like Hartman number$$(M)$$(M), porosity parameter$$(k)$$(k), slip parameters ($$\gamma ,{\gamma }_{1},{\gamma }_{2}$$γ,γ1,γ2), Schmidt$$(Sc)$$(Sc), Soret$$(Sr)$$(Sr)and Prandtl$$(Pr)$$(Pr)numbers, and many others. Parabolic behavior for velocity and sinusoidal nature for heat transfer and pressure gradient is noticed. Results indicate that the velocity is greatly affected by varying values of slip parameters (γ′s) and Hartman number$$(H)$$(H). Enhancing the viscoelastic nature of fluid causes an increase in velocity. Similar behavior is noticed for velocity and temperature profiles. The decreasing trend is shown by concentration when the value of the chemical reaction and temperature ratio parameters is enhanced. Thus, the study presented in the current analysis can be used to study many human physiological systems especially, the blood flow. Since Jeffrey's fluid exhibits the same characteristics as observed for blood.
The impact of inconsistent human annotations on AI driven clinical decision making
Authors: Sylolypavan Aneeta , Sleeman Derek , Wu Honghan , Sim Malcolm 
Published: February 2023

AbstractIn supervised learning model development, domain experts are often used to provide the class labels (annotations). Annotation inconsistencies commonly occur when even highly experienced clinical experts annotate the same phenomenon (e.g., medical image, diagnostics, or prognostic status), due to inherent expert bias, judgments, and slips, among other factors. While their existence is relatively well-known, the implications of such inconsistencies are largely understudied in real-world settings, when supervised learning is applied on such ‘noisy’ labelled data. To shed light on these issues, we conducted extensive experiments and analyses on three real-world Intensive Care Unit (ICU) datasets. Specifically, individual models were built from a common dataset, annotated independently by 11 Glasgow Queen Elizabeth University Hospital ICU consultants, and model performance estimates were compared through internal validation (Fleiss’ κ = 0.383 i.e., fair agreement). Further, broad external validation (on both static and time series datasets) of these 11 classifiers was carried out on a HiRID external dataset, where the models’ classifications were found to have low pairwise agreements (average Cohen’s κ = 0.255 i.e., minimal agreement). Moreover, they tend to disagree more on making discharge decisions (Fleiss’ κ = 0.174) than predicting mortality (Fleiss’ κ = 0.267). Given these inconsistencies, further analyses were conducted to evaluate the current best practices in obtaining gold-standard models and determining consensus. The results suggest that: (a) there may not always be a “super expert” in acute clinical settings (using internal and external validation model performances as a proxy); and (b) standard consensus seeking (such as majority vote) consistently leads to suboptimal models. Further analysis, however, suggests that assessing annotation learnability and using only ‘learnable’ annotated datasets for determining consensus achieves optimal models in most cases.
Arabidopsis histone H3 lysine 9 methyltransferases KYP/SUVH5/6 are involved in leaf development by interacting with AS1-AS2 to repress KNAT1 and KNAT2
Authors: Hung Fu-Yu , Feng Yun-Ru , Hsin Kuan-Ting , Shih Yuan-Hsin , Chang Chung-Han , Zhong Wenjian , Lai You-Cheng , Xu Yingchao , Yang Songguang , Sugimoto Keiko , Cheng Yi-Sheng , Wu Keqiang 
Published: February 2023

AbstractThe Arabidopsis H3K9 methyltransferases KRYPTONITE/SUPPRESSOR OF VARIEGATION 3–9 HOMOLOG 4 (KYP/SUVH4), SUVH5 and SUVH6 are redundantly involved in silencing of transposable elements (TEs). Our recent study indicated that KYP/SUVH5/6 can directly interact with the histone deacetylase HDA6 to synergistically regulate TE expression. However, the function of KYP/SUVH5/6 in plant development is still unclear. The transcriptional factors ASYMMETRIC LEAVES1 (AS1) and AS2 form a transcription complex, which is involved in leaf development by repressing the homeobox genes KNOTTED-LIKE FROM ARABIDOPSIS THALIANA 1 (KNAT1) and KNAT2. In this study, we found that KYP and SUVH5/6 directly interact with AS1-AS2 to repress KNAT1 and KNAT2 by altering histone H3 acetylation and H3K9 dimethylation levels. In addition, KYP can directly target the promoters of KNAT1 and KNAT2, and the binding of KYP depends on AS1. Furthermore, the genome-wide occupancy profile of KYP indicated that KYP is enriched in the promoter regions of coding genes, and the binding of KYP is positively correlated with that of AS1 and HDA6. Together, these results indicate that Arabidopsis H3K9 methyltransferases KYP/SUVH5/6 are involved in leaf development by interacting with AS1-AS2 to alter histone H3 acetylation and H3K9 dimethylation from KNAT1 and KNAT2 loci.
Characterizing Communicative Participation in Multilingual Jamaican Preschoolers
Authors: Kokotek Leslie E. , Washington Karla N. 
Published: February 2023

Purpose:
This study characterized communicative participation and related aspects of functional communication for Jamaican Creole (JC)-English–speaking preschoolers with and without functionally defined speech sound disorders (fSSDs). This study included parent reports and direct assessment measures from an existing corpus of baseline data collected prior to the COVID-19 pandemic.

Method:

The communicative participation of typically developing (TD;
n
= 226) bilingual JC-English–speaking preschoolers and those with fSSDs (
n
= 39) was documented using the Focus on the Outcomes of Communication Under Six (FOCUS). Functional speech intelligibility was recorded using the Intelligibility in Context Scale (ICS) in English and JC (ICS-JC). Objective measures of speech production were collected through direct child assessment in both languages and then transcribed and calculated for percent of consonants (PCC), vowels (PVC), and phonemes correct (PPC). Within-group relationships were explored using association testing, and differences between groups were explored through multivariate analyses.

Results:

FOCUS scores and ICS and ICS-JC scores were found to be minimally to moderately related for Jamaican preschoolers in the TD group (
r
= .28–.34,
p
< .002) and strongly related in the fSSD group (
r
= .56–.60,
p
< .002). No relations were observed between the FOCUS scores and PCC/PVC/PPC in either language. There was a statistically significant difference between all FOCUS scores for Jamaican preschoolers in the TD and fSSD groups (
p
≤ .002).

Conclusions:
These findings provide additional evidence for using the FOCUS beyond documenting change in communicative participation to support clinical decision-making in planning and developing speech-language interventions. This study also documents an important characterization of JC-English–speaking children with and without fSSDs, offering data on children's abilities that can be used in future comparisons of communicative participation and speech functioning observed during the COVID-19 pandemic and beyond.
A Preliminary Study of Speech Rhythm Differences as Markers of Stuttering Persistence in Preschool-Age Children
Authors: Erdemir Aysu , Walden Tedra A. , Tilsen Sam , Mefferd Antje S. , Jones Robin M. 
Published: February 2023

Purpose:
The purpose of this study was twofold: (a) to determine whether there are speech rhythm differences between preschool-age children who stutter that were eventually diagnosed as persisting (CWS-Per) or recovered (CWS-Rec) and children who do not stutter (CWNS), using empirical spectral analysis and empirical mode decomposition of the speech amplitude envelope, and (b) to determine whether speech rhythm characteristics close to onset are predictive of later persistence.

Method:
Fifty children (3–4 years of age) participated in the study. Approximately 2–2.5 years after the experimental testing took place, children were assigned to the following groups: CWS-Per (nine boys, one girl), CWS-Rec (18 boys, two girls), and CWNS (18 boys, two girls). All children produced a narrative based on a text-free storybook. From the audio recordings of these narratives, fluent utterances were selected for each child from which seven envelope-based measures were extracted. Group-based differences on each measure as well as predictive analyses were conducted to identify measures that discriminate CWS-Per versus CWS-Rec.

Results:
CWS-Per were found to have a relatively higher degree of power in suprasyllabic oscillations and greater variability in the timing of syllabic rhythms especially for longer utterances. A logistic regression model using two speech rhythm measures was able to discriminate the eventual outcome of recovery versus persistence, with 80% sensitivity and 75% specificity.

Conclusion:
Findings suggest that envelope-based speech rhythm measures are a promising approach to assess speech rhythm differences in developmental stuttering, and its potential for identification of children at risk of developing persistent stuttering should be investigated further.
Residual charge effects on partial discharges' response to varying sub‐kHz voltage frequencies
Authors: Nyamupangedengu Cuthbert , Venge Tapiwa 
Published: February 2023

AbstractPartial discharges (PD) are the ‘cancer’ of electrical insulation. Insulation design and mitigation of PD‐induced degradation should be based on good knowledge of PD phenomena. In that regard, a significant body of knowledge has been built up from concerted research across the world in past decades and on various aspects of PD phenomena under various conditions. However, the work is far from being complete as new challenges arise. One such challenge is that electric power equipment insulation is becoming more exposed to non‐power frequency voltages. Examples are the proliferation of invertor‐based grid‐tied renewable energy sources and other technologies such as high‐frequency power electronic transformers. Questions that are driving continued research in this regard include the reasons for lack of consensus on the findings on how PD characteristics respond to variations in the voltage frequency. This paper presents results of how residual charge influences PD characteristics' response to voltage frequency changes from 1 to 200 Hz. The study approach is implementing the extended 3‐capacitor PD model in MATLAB® Simulink® and validating the findings using the relevant experimental results that are available in literature. The PD type studied is that of an air cavity encapsulated in a polyethylene dielectric. Highlights of the findings are that the extent of the influence of residual charge on PD characteristics depends on the relative magnitude of the residual charge as well as the voltage frequency. The relationships however exhibit non‐monotonous trends. Such results further confirm similar findings and conclusions by other researchers and could be signalling the establishment of a more solid knowledge base for design of insulations that operate at non‐power frequencies.