bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fusion of energy sensors with missing values
Authors: Buonanno Amedeo , Di Gennaro Giovanni , Graditi Giorgio , Nogarotto Antonio , Palmieri Francesco A N , Valenti Maria 
Published: July 2023

AbstractIn Smart Energy Grids, the information flow used to make decisions is the result of fusion of different sources. Communication latency, possible sensor faults and inaccuracies, may negatively impact the data quality and hence the taken decisions. For these reasons, the construction of a robust representation of the input signals that replaces and/or corrects the inaccurate data is crucial for effective classification, anomaly detection and planning. Recent works on Data Fusion and data imputation suggest that the usage of other signals in the same context can empower the representation and can be a useful preprocessing task. In this work we describe an Autoencoder-based data fusion architecture with convolutional layers, skip connections and ad-hoc augmented training sets for data imputation applied to the power consumption measurements obtained by different sub-meters. Among the investigated architectures, the approach with the shared convolutional layers and an augmented dataset that consider missing data in the random positions and located in the central part (AE-A-ALL-CNN), is the most promising one. In presence of one half of the input signal, in the central part, completely erased, it improves the imputation capability, respect to two most employed approaches (denoising autoencoder and MICE) in the average of 12 %.
Bioaugmentation has temporary effect on anaerobic pesticide biodegradation in simulated groundwater systems
Authors: Aldas-Vargas Andrea , Kers Jannigje G. , Smidt Hauke , Rijnaarts Huub H. M. , Sutton Nora B. 
Published: July 2023

AbstractGroundwater is the most important source for drinking water in The Netherlands. Groundwater quality is threatened by the presence of pesticides, and biodegradation is a natural process that can contribute to pesticide removal. Groundwater conditions are oligotrophic and thus biodegradation can be limited by the presence and development of microbial communities capable of biodegrading pesticides. For that reason, bioremediation technologies such as bioaugmentation (BA) can help to enhance pesticide biodegradation. We studied the effect of BA using enriched mixed inocula in two column bioreactors that simulate groundwater systems at naturally occurring redox conditions (iron and sulfate-reducing conditions). Columns were operated for around 800 days, and two BA inoculations (BA1 and BA2) were conducted in each column. Inocula were enriched from different wastewater treatment plants (WWTPs) under different redox-conditions. We observed a temporary effect of BA1, reaching 100% removal efficiency of the pesticide 2,4-D after 100 days in both columns. In the iron-reducing column, 2,4-D removal was in general higher than under sulfate-reducing conditions demonstrating the influence of redox conditions on overall biodegradation. We observed a temporary shift in microbial communities after BA1 that is relatable to the increase in 2,4-D removal efficiency. After BA2 under sulfate-reducing conditions, 2,4-D removal efficiency decreased, but no change in the column microbial communities was observed. The present study demonstrates that BA with a mixed inoculum can be a valuable technique for improving biodegradation in anoxic groundwater systems at different redox-conditions.
Graphical abstract
Sustained and Universal Fertility Recuperation in Kazakhstan
Authors: Kan Maxim 
Published: July 2023

AbstractThe fertility rates of Kazakhstan have reversed to levels not seen for several decades. The striking fertility increase poses questions regarding the extent to which this new development is shared across socio-demographic groups and the nature of fertility recuperation. The current study employs UNICEF Multiple Indicator Cluster Survey data and event-history modelling to analyse parity progressions to one, two, three, and four children. The results suggest a sustained fertility increase that is not merely associated with the recuperation of delayed first births, but a genuine increase across all birth orders. This pattern is evident for both main ethnicities in Kazakhstan and across educational groups. The gradual increase of higher-order births, especially among ethnic Kazakhs, indicates a reversed fertility transition and also that the previous fertility decline in the 1990s was not part of a general transition towards below-replacement fertility but rather a reflection of economic crisis after the collapse of the Soviet Union.
The SIA Can’t Just Go with the FLO
Authors: Slater Joe 
Published: July 2023

AbstractHendricks (2018) has defended an argument that abortion is (usually) immoral, which he calls the impairment argument. This argument purports to apply regardless of the moral status of the fetus. It has recently been bolstered by several amendments from Blackshaw and Hendricks (2021a; 2021b). In this paper, three problems are presented for their Strengthened Impairment Argument (SIA). In the first, it is observed that even with the new modifications the argument, contrary to their insistence, does seem to depend on Marquis’ argument. In order for it not to do so, they would need to provide some other plausible reason why impairing a fetus is wrong that persists in cases of abortion. Because of the restrictions regarding what reasons can be used, they are not entitled to stipulate that some plausible reason can be found. In the second section, the use of an over-ridingness caveat – the most recent modification – is scrutinised. This is shown to either beg the question about the permissibility of abortion by assuming that opposing reasons are insufficient in most cases, or require an entirely separate argument to establish that such reasons are insufficient. Thirdly, I observe that the principle utilised in the latest version of the argument fails to account for undercutting reason, which suggest that the principle, in its current form, is false.
Support-vector classification of low-dose nitrous oxide administration with multi-channel EEG power spectra
Authors: Vrijdag Xavier C. E. , Hallum Luke E. , Tonks Emma I. , van Waart Hanna , Mitchell Simon J. , Sleigh Jamie W. 
Published: July 2023

AbstractSupport-vector machines (SVMs) can potentially improve patient monitoring during nitrous oxide anaesthesia. By elucidating the effects of low-dose nitrous oxide on the power spectra of multi-channel EEG recordings, we quantified the degree to which these effects generalise across participants. In this single-blind, cross-over study, 32-channel EEG was recorded from 12 healthy participants exposed to 0, 20, 30 and 40% end-tidal nitrous oxide. Features of the delta-, theta-, alpha- and beta-band power were used within a 12-fold, participant-wise cross-validation framework to train and test two SVMs: (1) binary SVM classifying EEG during 0 or 40% exposure (chance = 50%); (2) multi-class SVM classifying EEG during 0, 20, 30 or 40% exposure (chance = 25%). Both the binary (accuracy 92%) and the multi-class (accuracy 52%) SVMs classified EEG recordings at rates significantly better than chance (p < 0.001 and p = 0.01, respectively). To determine the relative importance of frequency band features for classification accuracy, we systematically removed features before re-training and re-testing the SVMs. This showed the relative importance of decreased delta power and the frontal region. SVM classification identified that the most important effects of nitrous oxide were found in the delta band in the frontal electrodes that was consistent between participants. Furthermore, support-vector classification of nitrous oxide dosage is a promising method that might be used to improve patient monitoring during nitrous oxide anaesthesia.
Science learning in 3- and 5-year-old children in the same free-choice learning environment on plant diversity
Authors: Sáez-Bondía María José , Mateo Ester , Martín-García Jorge 
Published: July 2023

AbstractThis study responds to the need to produce inviting learning environments that help to build intentional science learning in early childhood education. We present a free-choice science learning environment on plant diversity in the fall. From the moment it was implemented, we analyzed whether children of different educational levels acted in accordance with the objectives put forth in each activity of the environment when they are given free choice. We also explored the potential relationship between achieving the stated objectives and social interactions. The participants were 13 three-year-old children and 14 five-year-old children. The free-choice sessions were video recorded and supplemented with notes taken by three researchers in a field notebook. From the records, we categorized the data according to the actions we expected of the children in each activity, related to how they interacted with the materials and the social interactions that emerged. The results show the influence of social and material interactions, as well as the children’s previous knowledge, in attaining the objectives laid out in the design. Based on these results, we propose some principles and guidelines for designing, implementing and evaluating these learning environments in early childhood education, as well as future lines of research.
Discovery and recognition of formula concepts using machine learning
Authors: Scharpf Philipp , Schubotz Moritz , Cohl Howard S. , Breitinger Corinna , Gipp Bela 
Published: July 2023

AbstractCitation-based Information Retrieval (IR) methods for scientific documents have proven effective for IR applications, such as Plagiarism Detection or Literature Recommender Systems in academic disciplines that use many references. In science, technology, engineering, and mathematics, researchers often employ mathematical concepts through formula notation to refer to prior knowledge. Our long-term goal is to generalize citation-based IR methods and apply this generalized method to both classical references and mathematical concepts. In this paper, we suggest how mathematical formulas could be cited and define a Formula Concept Retrieval task with two subtasks: Formula Concept Discovery (FCD) and Formula Concept Recognition (FCR). While FCD aims at the definition and exploration of a ‘Formula Concept’ that names bundled equivalent representations of a formula, FCR is designed to match a given formula to a prior assigned unique mathematical concept identifier. We present machine learning-based approaches to address the FCD and FCR tasks. We then evaluate these approaches on a standardized test collection (NTCIR arXiv dataset). Our FCD approach yields a precision of 68% for retrieving equivalent representations of frequent formulas and a recall of 72% for extracting the formula name from the surrounding text. FCD and FCR enable the citation of formulas within mathematical documents and facilitate semantic search and question answering, as well as document similarity assessments for plagiarism detection or recommender systems.
A Method to Correct Steady-State Relative Permeability Measurements for Inhomogeneous Saturation Profiles in One-Dimensional Flow
Authors: Zhang Guanglei , Foroughi Sajjad , Bijeljic Branko , Blunt Martin J. 
Published: July 2023

AbstractTraditionally, steady-state relative permeability is calculated from measurements on small rock samples using Darcy’s law and assuming a homogenous saturation profile and constant capillary pressure. However, these assumptions are rarely correct as local inhomogeneities exist; furthermore, the wetting phase tends to be retained at the outlet–the so-called capillary end effect. We have introduced a new method that corrects the relative permeabilities, analytically, for an inhomogeneous saturation profile along the flow direction. The only data required are the measured pressure drops for different fractional flow values, an estimate of capillary pressure, and the saturation profiles. An optimization routine is applied to find the range of relative permeability values consistent with the uncertainty in the measured pressure. Assuming a homogenous saturation profile systematically underestimates the relative permeability and this effect is most marked for media where one of the phases is strongly wetting with a noticeable capillary end effect. Relative permeabilities from seven two-phase flow experiments in centimetre-scale samples with different wettability were corrected while reconciling some hitherto apparently contradictory results. We reproduce relative permeabilities of water-wet Bentheimer sandstone that are closer to other measurements in the literature on larger samples than the original analysis. Furthermore, we find that the water relative permeability during waterflooding a carbonate sample with a wide range of pore sizes can be high, due to good connectivity through the microporosity. For mixed-wet media with lower capillary pressure and less variable saturation profiles, the corrections are less significant.
Improving the Removal of Anionic Surfactant in Cardboard Industry Wastewater by Coagulation/Flocculation: Process Optimization with Response Surface Methodology
Authors: Harif S. , Aboulhassan M. A. , Bammou L. , Baicha Zakarya , Fernández Francisco José Hernández 
Published: July 2023

AbstractResponse surface methodology (RSM) and Box–Behnken design (BBD) were investigated to optimize the coagulation–flocculation process (CF) of cardboard industry effluent using polyaluminum chloride (PAC) and cationic polyacrylamides (c-PAM). The aim is to identify the optimum combination of coagulant dose, pH, and flocculant dosage for the highest removal efficacy of chemical oxygen demand (COD) and anionic surfactant removal. According to the results, COD reduction was principally controlled by PAC and c-PAM, while anionic surfactant was affected by pH and PAC. In addition, COD and anionic surfactant removal models fitted well with the experimental results (R2 > 0.85). Coagulation/flocculation using optimum conditions of pH, PAC, and c-PAM led to the total removal of anionic surfactant and the reduction of more than 95% of COD.
Prediction of oxygen supplementation by a deep-learning model integrating clinical parameters and chest CT images in COVID-19
Authors: Kawata Naoko , Iwao Yuma , Matsuura Yukiko , Suzuki Masaki , Ema Ryogo , Sekiguchi Yuki , Sato Hirotaka , Nishiyama Akira , Nagayoshi Masaru , Takiguchi Yasuo , Suzuki Takuji , Haneishi Hideaki 
Published: July 2023

Abstract
Purpose
As of March 2023, the number of patients with COVID-19 worldwide is declining, but the early diagnosis of patients requiring inpatient treatment and the appropriate allocation of limited healthcare resources remain unresolved issues. In this study we constructed a deep-learning (DL) model to predict the need for oxygen supplementation using clinical information and chest CT images of patients with COVID-19.

Materials and methods
We retrospectively enrolled 738 patients with COVID-19 for whom clinical information (patient background, clinical symptoms, and blood test findings) was available and chest CT imaging was performed. The initial data set was divided into 591 training and 147 evaluation data. We developed a DL model that predicted oxygen supplementation by integrating clinical information and CT images. The model was validated at two other facilities (n = 191 and n = 230). In addition, the importance of clinical information for prediction was assessed.

Results
The proposed DL model showed an area under the curve (AUC) of 89.9% for predicting oxygen supplementation. Validation from the two other facilities showed an AUC > 80%. With respect to interpretation of the model, the contribution of dyspnea and the lactate dehydrogenase level was higher in the model.

Conclusions
The DL model integrating clinical information and chest CT images had high predictive accuracy. DL-based prediction of disease severity might be helpful in the clinical management of patients with COVID-19.
Incidence and risk factors of cancers in acromegaly: a Chinese single-center retrospective study
Authors: Xiao Tongxin , Jiao Rui , Yang Shengmin , Wang Yi , Bai Xue , Zhou Jingya , Li Ran , Wang Linjie , Yang Hongbo , Yao Yong , Deng Kan , Gong Fengying , Pan Hui , Duan Lian , Zhu Huijuan 
Published: July 2023

Abstract
Purpose
To evaluate the incidence of malignancies in acromegaly and to identify risk factors for newly-diagnostic cancers, especially the excessive growth hormone (GH) and insulin-like growth factor-1 (IGF-1).

Methods
A retrospective cohort including 1738 consecutive hospitalized patients with acromegaly in a single referral center between 2012 and 2020 (mean follow-up 4.3 years). A gender- and age-matched case-control study (280 patients from the cohort) was performed for risk factor analysis.

Results
One hundred thirteen malignancies (67 diagnosed after acromegaly) were observed. The overall newly-diagnostic cancer risk of acromegaly was higher than the general population (standardized incidence ratio (SIR) 2.81; 95% CI 2.18–3.57). The risk of thyroid cancer (n = 33, SIR 21.42; 95% CI 13.74–30.08) and colorectal cancer (n = 8, SIR 3.17; 95% CI 1.37–6.25) was elevated. In the overall cohort, IGF-1 (ULN: 1.27 vs. 0.94, p = 0.057), GH (1.30 vs. 1.00 ng/ml, p = 0.12), and disease-controlled rate (34.9% vs. 45.9%, p = 0.203) at the last visit did not reach significance between patients with and without post-diagnostic cancer. In the case-control study, GH (1.80 vs. 0.90 ng/ml, p = 0.018) and IGF-1 (ULN: 1.27 vs. 0.91, p = 0.003) at the last visit were higher in patients with post-diagnostic cancers, with a lower disease-controlled rate. Elder age was a risk factor for cancer. Other metabolic comorbidities and the size of pituitary tumors were similar.

Conclusion
The risk of malignancies, especially thyroid cancer, was increased in patients with acromegaly in our center. More cancer screening should be considered when managing acromegaly, especially in patients with higher posttreatment GH and IGF-1.
Finite element-based geotechnical risk analysis for anchor-supported deep excavations
Authors: Bozkurt Sinem , Akbas Sami Oguzhan 
Published: July 2023

AbstractEvaluation of the reliability of deep excavation support systems requires the inclusion of the soil variability in conjunction with probabilistic analysis. This is often considered a complicated process; therefore, the method is usually not followed in routine engineering practice. Recent developments in finite element modelling now enable probabilistic analyses to be performed more conveniently. As an illustrative example, the case history of a 20 m-deep excavation supported by anchored drilled shafts in the Sogutozu district of Ankara was investigated. Experimental results indicate that saturated sand-gravel bands, which are common within Ankara Clay, have the potential to cause a significant decrease in the anchor capacity. Ergo the excavation performance, including structural capacity and wall lateral displacements, was evaluated taking into regard the probabilistic nature of the effect of these bands and the variability of the soil parameters. Back-analysis was performed and compared with inclinometer readings to examine the capability of the numerical model to simulate the field behaviour. Later, additional finite element analyses were carried out through Python scripting software to investigate the reliability of the excavation. Geotechnical parameters of the Ankara Clay produced by Monte Carlo simulation method were used in these analyses. The results were evaluated within the context of recommended acceptable reliability levels. The reliability of the system was determined to be relatively low when taking into account the adverse impact of sand and gravel bands.
Hybridizable discontinuous Galerkin method with mixed-order spaces for non-linear diffusion equations with internal jumps
Authors: Musch Markus , Rupp Andreas , Aizinger Vadym , Knabner Peter 
Published: July 2023

AbstractWe formulate a hybridizable discontinuous Galerkin method for parabolic equations with non-linear tensor-valued coefficients and jump conditions (Henry’s law). The analysis of the proposed scheme indicates the optimal convergence order for mildly non-linear problems. The same order is also obtained in our numerical studies for simplified settings. A series of numerical experiments investigate the effect of choosing different order approximation spaces for various unknowns.
Sacral nerve modulation for patients with fecal incontinence: long-term outcome and effects on sexual function
Authors: Brusciano Luigi , Brillantino Antonio , Pellino Gianluca , Marinello Franco , Baeten Coen IM , Digesu Alex , Naldini Gabriele , Gambardella Claudio , Lucido Francesco Saverio , Sturiale Alessandro , Gualtieri Giorgia , Riss Stefan , Docimo Ludovico 
Published: July 2023

AbstractSacral nerve modulation has become an established treatment for fecal and urinary incontinence, and sexual disorders. The objective of this study was to evaluate the long-term outcome of sacral neuromodulation in patients with fecal or combined fecal and urinary incontinence (double incontinence), assessing its safety, efficacy, and impact on quality of life and sexual function. This was a multicentric, retrospective, cohort study including patients with fecal or double incontinence who received sacral neuromodulation at seven European centers between 2007 and 2017 and completed a 5-year follow-up. The main outcome measures included improvements of incontinence symptoms and quality of life compared with baseline, evaluated using validated tools and questionnaires at 1-, 6-, 12-, 36- and 60-month follow-up. 108 (102 women, mean age 62.4 ± 13.4 years) patients were recruited, of whom 88 (81.4%) underwent definitive implantation of the pacemaker. Patients’ baseline median Cleveland Clinic Incontinence Score was 15 (10–18); it decreased to 2 (1–4) and 1 (1–2) at the 12- and 36-month follow-up (p < 0.0001), remaining stable at the 5-year follow-up. Fecal incontinence quality of life score improved significantly. All patients with sexual dysfunction (n = 48) at baseline reported symptom resolution at the 5-year follow-up. The study was limited by the retrospective design and the relatively small patient sample. Sacral nerve modulation is an effective treatment for fecal and double incontinence, achieving satisfactory long-term success rates, with resolution of concomitant sexual dysfunction.
Undeserved authorship in surgical research: an underestimated bias with potential side effects on academic careers
Authors: Picciariello Arcangelo , Dezi Agnese , Altomare Donato F. 
Published: July 2023

AbstractThe incidence of courtesy authorship in research over time has probably increased due to the enormous pressure to publish to increase the bibliometric indexes necessary to achieve an academic role. The aim of this survey was to quantify and characterize this research malpractice among a very selected group of surgeons from different surgical specialties belonging to the European Association of Surgery (ESA). E-mail addresses for the invitation to take part to the survey were collected by the Twenty-eighth Annual Meeting final program. Five-item were designed and developed by the authors using an online platform. Eighty-six members from 21 countries completed the survey (female/male ratio: 0.09). In the last 10 years, almost half of the responders (41, 47.7%, 37 academics) have included colleagues for courtesy authorship. The most common reason of courtesy authorships was to support the academic career of another researcher (62.5%). Other reasons were fear of retaliation (12.5%), reciprocal authorship (12.5%) or support for a partner (10%). This survey showed that undeserved authorship is sadly confirmed to be a common research misconduct across any countries and medical specialties, even among a very selected group of surgeons with international reputation irrespective of the academic position.