bluuebunny/crossref_metadata_2025_split huggingface dataset:
The influence of ergodicity on risk affinity of timed and non-timed respondents
Authors: Vanhoyweghen Arne , Verbeken Brecht , Macharis Cathy , Ginis Vincent 
Published: March 2022

AbstractExpected values are the metric most often used to judge human decision-making; when humans make decisions that do not optimize expected values, these decisions are considered irrational. However, while convenient, expected values do not necessarily describe the evolution of an individual after making a series of decisions. This dichotomy lies at the core of ergodicity breaking, where the expected value (ensemble average) differs from the temporal average of one individual. In this paper, we explore whether the intuition behind human decision-making optimizes for expected values or instead takes time growth rates into account. We do this using several stated choice experiments, where participants choose between two stochastic bets and try to optimize their capital. To evaluate the intuitive choice, we compare two groups, with and without perceived time pressure. We find a significant difference between the responses of the timed and the control group, depending on the dynamic of the choices. In an additive dynamic, where ergodicity is not broken, we observe no effect of time pressure on the decisions. In the non-ergodic, multiplicative setting, we find a significant difference between the two groups. The group that chooses under time pressure is more likely to make the choice that optimizes the experiment’s growth rate. The results of this experiment contradict the idea that people are irrational decision-makers when they do not optimize their expected value. The intuitive decisions deviate more from the expected value optimum in the non-ergodic part of our experiment and lead to more optimal decisions.
Genetic characteristics of 234 Italian patients with macular and cone/cone-rod dystrophy
Authors: Falsini Benedetto , Placidi Giorgio , De Siena Elisa , Chiurazzi Pietro , Minnella Angelo Maria , Savastano Maria Cristina , Ziccardi Lucia , Parisi Vincenzo , Iarossi Giancarlo , Percio Marcella , Piteková Barbora , Marceddu Giuseppe , Maltese Paolo Enrico , Bertelli Matteo 
Published: March 2022

AbstractTwo-hundred and thirty-four Italian patients with a clinical diagnosis of macular, cone and cone-rod dystrophies (MD, CD, and CRD) were examined using next-generation sequencing (NGS) and gene sequencing panels targeting a specific set of genes, Sanger sequencing and—when necessary—multiplex ligation-dependent probe amplification (MLPA) to diagnose the molecular cause of the aforementioned diseases. When possible, segregation analysis was performed in order to confirm unsolved cases. Each patient’s retinal phenotypic characteristics were determined using focal and full-field ERGs, perimetry, spectral domain optical coherence tomography and fundus autofluorescence. We identified 236 potentially causative variants in 136 patients representing the 58.1% of the total cohort, 43 of which were unpublished. After stratifying the patients according to their clinical suspicion, the diagnostic yield was 62.5% and 53.8% for patients with MD and for those with CD/CRD, respectively. The mode of inheritance of all cases confirmed by genetic analysis was 70% autosomal recessive, 26% dominant, and 4% X-linked. The main cause (59%) of both MD and CD/CRD cases was the presence of variants in the ABCA4 gene, followed by variants in PRPH2 (9%) and BEST1 (6%). A careful morpho-functional evaluation of the phenotype, together with genetic counselling, resulted in an acceptable diagnostic yield in a large cohort of Italian patients. Our study emphasizes the role of targeted NGS to diagnose MDs, CDs, and CRDs, as well as the clinical usefulness of segregation analysis for patients with unsolved diagnosis.
Lumped circuit model for inductive antenna spin-wave transducers
Authors: Vanderveken Frederic , Tyberkevych Vasyl , Talmelli Giacomo , Sorée Bart , Ciubotaru Florin , Adelmann Christoph 
Published: March 2022

AbstractWe derive a lumped circuit model for inductive antenna spin-wave transducers in the vicinity of a ferromagnetic medium. The model considers the antenna’s Ohmic resistance, its inductance, as well as the additional inductance due to the excitation of ferromagnetic resonance or spin waves in the ferromagnetic medium. As an example, the additional inductance is discussed for a wire antenna on top of a ferromagnetic waveguide, a structure that is characteristic for many magnonic devices and experiments. The model is used to assess the scaling properties and the energy efficiency of inductive antennas. Issues related to scaling antenna transducers to the nanoscale and possible solutions are also addressed.
YB1 associates with oncogenetic roles and poor prognosis in nasopharyngeal carcinoma
Authors: Zhan Yuting , Chen Xianyong , Zheng Hongmei , Luo Jiadi , Yang Yang , Ning Yue , Wang Haihua , Zhang Yuting , Zhou Ming , Wang Weiyuan , Fan Songqing 
Published: March 2022

AbstractNasopharyngeal carcinoma (NPC) is the malignant tumor arising from the nasopharynx epithelium with ethnic and geographical distribution preference. Y-box binding protein-1 (YB1) is the highly expressed DNA/RNA-binding protein with cold shock domain, and enhanced YB1 expression was proved to be associated with many kinds of malignant tumors. There is no systematic study about the regulation of YB1 and cell proliferation, migration, invasion and stress granules (SGs) in NPC, and the relationship between YB1 expression and clinical characteristics and prognosis of NPC patients. We analyzed the mRNA expression of YBX1 in head and neck squamous carcinoma (HNSC) and NPC in databases, investigated the functions of YB1 in cell proliferation, migration and invasion and SGs formation of NPC cells, and detected expression of YB1 protein in a large scale of NPC samples and analyzed their association with clinicopathological features and prognostic significance of NPC patients. YBX1 mRNA was significantly high expression in HNSC and NPC by bioinformatic analysis, and higher expression of YBX1 mRNA indicated poorer prognosis of HNSC patients. Clinically, the expression of YB1 in NPC tissues was significantly higher than these in the control nasopharyngeal epithelial tissues. We further found that the expression of YB1 had an evidently positive relation with advanced clinical stages of patients with NPC. The overall survival rates (OS) were significantly lower for NPC patients with positive expression of YB1. Multivariate analysis confirmed that positive expression of YB1 was the independent poorer prognostic factor for patients with NPC. Moreover, compared with the immortalized nasopharyngeal epithelial cell line (NP69), the basal level of YB1 in NPC cell lines was significantly higher. Knocking down YB1 may inhibit Akt/mTOR pathway in NPC cells. Knocking down YB1 by small interfering RNAs can reduce the ability of proliferation, migration, invasion and SGs formation of NPC cells. The expression of YB1 in NPC cell lines or patients with NPC was significantly higher. The high expression of YB1 protein may act as one valuable independent biomarker to predict poor prognosis for patients with NPC. Knocking down YB1 may release the malignant phenotype of NPC cells.
Vibrational spectroscopy to study ancient Roman funerary practices at the “Hypogeum of the Garlands” (Italy)
Authors: Festa G. , Rubini M. , Zaio P. , Gozzi A. , Libianchi N. , Parker S. F. , Romanelli G. , de Carvalho L. A. E. Batista , Marques M. P. M. 
Published: March 2022

AbstractThe “Hypogeum of the Garlands” is a sepulchral site, recently found in Grottaferrata (Lazio, Italy), dating back to the first-second century AD. Two sarcophagi were discovered inside, hosting the human remains of Aebutia Quarta, a rich Roman woman, and her son Carvilius Gemellus. While the body of Carvilius is exceptionally well-preserved, following its embalming and perfect sealing of the sarcophagus, in the case of Aebutia only the bones were preserved because of the sarcophagus’s seal breaking down, although she was covered with perfectly preserved flower garlands. Embalming of the body was a rare ritual in the Imperial Roman times when corpses were more often cremated. The remains of Aebutia showed possible traces of heating. Burned bones from a third individual were discovered on the chamber’s floor and preliminary anthropological survey showed that this individual was a male of 40–50 years old. Here, a combination of spectroscopic techniques, including non-destructive inelastic neutron scattering and Raman spectroscopy, and minimally destructive Fourier transform infrared spectroscopy, were applied to the analysis of these bone samples to give information about ancient Roman funerary practices. The temperature and burning conditions were thus determined, showing that Aebutia Quarta was exposed to mild temperatures (200 °C) only in the upper part of the body, while the third individual was likely cremated as its bones were exposed to temperatures up to 900 °C in quasi-anaerobic conditions.
Anti-pulling force and displacement deformation analysis of the anchor pulling system of the new debris flow grille dam
Authors: Wang Yongsheng , Lv Baohong , Liu Jianshe , Zhang Xiaobin 
Published: March 2022

AbstractTo avoid waste from a large section space structure layout and deep burial, improve the structural strength and stability. Anchor technology is introduced, and combined with the advantages of the supporting wall, a new debris-flow grille dam is proposed. Starting from the force process and damage mechanism of the new debris-flow grille dam, the computation formula for the anti-pulling force and the total displacement is given. The anti-pulling force includes the sidewall frictional resistance of the anchor pier and the positive pressure of the front end face of the anchor pier. The total displacement includes three parts: the elastic deformation of the cable, the relative shear displacement between the anchor pier and the surrounding soil, and the compression deformation of the soil at the front of the anchor pier. Finally, the influence of soil parameters and anchor pier size on the anti-pulling force and displacement deformation of the anchor-pulling system is analyzed by examples, and the results are compared with the numerical results. The results show that the displacement deformation decreases gradually with increasing elastic modulus of the soil around the anchor pier and increases with increasing Poisson's ratio. The change in elastic modulus mainly affects the relative shear displacement of the anchor pier and soil and the compressive deformation of the soil at the front end of the anchor pier. Poisson's ratio has the greatest influence on the relative shear displacement of the anchor pier and soil. A larger anchor pier is not better; thus, it is wise to choose the economic design dimension. Theoretical and numerical simulation results are consistent, showing a linear growth trend. The results of this paper can further improve the theoretical calculation method of the new debris-flow grille dam, thus making it widely used in more debris flow control projects.
Predictions of cervical cancer identification by photonic method combined with machine learning
Authors: Kruczkowski Michał , Drabik-Kruczkowska Anna , Marciniak Anna , Tarczewska Martyna , Kosowska Monika , Szczerska Małgorzata 
Published: March 2022

AbstractCervical cancer is one of the most commonly appearing cancers, which early diagnosis is of greatest importance. Unfortunately, many diagnoses are based on subjective opinions of doctors—to date, there is no general measurement method with a calibrated standard. The problem can be solved with the measurement system being a fusion of an optoelectronic sensor and machine learning algorithm to provide reliable assistance for doctors in the early diagnosis stage of cervical cancer. We demonstrate the preliminary research on cervical cancer assessment utilizing an optical sensor and a prediction algorithm. Since each matter is characterized by refractive index, measuring its value and detecting changes give information about the state of the tissue. The optical measurements provided datasets for training and validating the analyzing software. We present data preprocessing, machine learning results utilizing four algorithms (Random Forest, eXtreme Gradient Boosting, Naïve Bayes, Convolutional Neural Networks) and assessment of their performance for classification of tissue as healthy or sick. Our solution allows for rapid sample measurement and automatic classification of the results constituting a potential support tool for doctors.
Discovery of antimicrobials by massively parallelized growth assays (Mex)
Authors: Koch Philipp , Schmitt Steven , Cardner Mathias , Beerenwinkel Niko , Panke Sven , Held Martin 
Published: March 2022

AbstractThe number of newly approved antimicrobial compounds has been steadily decreasing over the past 50 years emphasizing the need for novel antimicrobial substances. Here we present Mex, a method for the high-throughput discovery of novel antimicrobials, that relies on E. coli self-screening to determine the bioactivity of more than ten thousand naturally occurring peptides. Analysis of thousands of E. coli growth curves using next-generation sequencing enables the identification of more than 1000 previously unknown antimicrobial peptides. Additionally, by incorporating the kinetics of growth inhibition, a first indication of the mode of action is obtained, which has implications for the ultimate usefulness of the peptides in question. The most promising peptides of the screen are chemically synthesized and their activity is determined in standardized susceptibility assays. Ten out of 15 investigated peptides efficiently eradicate bacteria at a minimal inhibitory concentration in the lower µm or upper nm range. This work represents a step-change in the high-throughput discovery of functionally diverse antimicrobials.
Neoadjuvant therapy of metformin is associated with good tumor response after preoperative concurrent chemoradiotherapy for rectal cancer
Authors: Han Jeonghee , Kim Jong Ho , Lee Jin-Won , Han Sang Hyup , Kim Haesung 
Published: March 2022

AbstractMetformin is associated with good tumor response in preoperative concurrent chemoradiotherapy (CCRT) for rectal cancer. This study aims to demonstrate that the timing of metformin is related to the tumor response on preoperative CCRT for rectal cancer. From January 2010 to December 2017, 232 patients who underwent curative resection after preoperative CCRT were reviewed. Patients were divided into groups with or without diabetes or metformin. The timing of metformin administration was divided based on before and from initiation of CCRT. Multivariate logistic regression analysis was used to identify predictors for tumor response. Tumor downstaging (p = 0.02) and good response rates of tumor regression grade (TRG) (p = 0.008) were significantly higher in the group administered metformin before CCRT than other groups. In the multivariate analysis, metformin administration before CCRT was a significant factor in predicting tumor downstaging [odds ratio (OR) 10.31, 95% confidence interval (CI) 1.76–102.08, p = 0.02] and good TRG (OR 12.55, 95% CI 2.38–80.24, p = 0.004). In patients with rectal cancer who underwent preoperative CCRT, neoadjuvant therapy of metformin before CCRT was significantly associated with good tumor response.
Higher heart rate variability as a predictor of atrial fibrillation in patients with hypertension
Authors: Kim San Ha , Lim Kyoung Ree , Seo Jeong-Hun , Ryu Dong Ryeol , Lee Bong-Ki , Cho Byung-Ryul , Chun Kwang Jin 
Published: March 2022

AbstractThe autonomic nervous system (ANS) plays an important role in the initiation and maintenance of atrial fibrillation (AF). However, the meaning of higher heart rate variability (HRV) in predicting AF remains unclear. Among 2100 patients in the Holter registry, a total of 782 hypertensive patients were included in this study. Baseline HRV was measured by time domain and frequency domain methods using 24-h Holter monitoring. The primary outcome was the development of AF. During an average follow-up of 1.1 years, 44 patients developed AF. Higher HRV parameters including high-frequency (P < 0.001), the square root of the mean squared differences of successive NN intervals (P < 0.001), and the percentage of NN intervals that are more than 50 ms different from the previous interval (P < 0.001) were associated with the occurrence of AF in univariate analysis. Premature atrial contractions burden, lower baseline heart rate, age, hemodialysis, coronary artery disease, and chronic heart failure were also associated with AF. In Cox regression analysis, higher HRV (representing excessive autonomic fluctuation) was an independent risk factor for AF. Excessive autonomic fluctuation represented by higher HRV in patients with hypertension was associated with an increased risk of AF.
Predicting individual perceptual scent impression from imbalanced dataset using mass spectrum of odorant molecules
Authors: Debnath Tanoy , Nakamoto Takamichi 
Published: March 2022

AbstractPredicting odor impression is considered an important step towards measuring the quality of scent in the food, perfume, and cosmetic industries. In odor impression identification and classification, the main target is to predict scent impression while identifying non-target odor impressions are less significant. However, the effectiveness of predictive models depends on the quality of data distribution. Since it is difficult to collect large scale sensory data to create an evenly distributed positive (target odor) and negative (non-target odor) samples, a method is necessary to predict the individual characteristics of scent according to the number of positive samples. Moreover, it is required to predict large number of individual odor impressions from such kind of imbalanced dataset. In this study, we used mass spectrum of flavor molecules and their corresponding odor impressions which have a very disproportioned ratio of positive and negative samples. Thus, we used One-class Classification Support Vector Machine (OCSVM) and Cost-Sensitive MLP (CSMLP) to precisely classify target scent impression. Our experimental results show satisfactory performance in terms of AUCROC to detect the olfactory impressions of 89 odor descriptors from the mass spectra of flavor molecules.
A population-based study of mortality due to muscular dystrophies across a 36-year period in Spain
Authors: Llamosas-Falcón Laura , Sánchez-Díaz Germán , Gallego Elisa , Villaverde-Hueso Ana , Arias-Merino Greta , Posada de la Paz Manuel , Alonso-Ferreira Verónica 
Published: March 2022

AbstractMuscular dystrophies (MD) are a group of rare hereditary degenerative diseases. Our aim was to analyze the mortality pattern in Spain from 1981 to 2016 to assess the temporal trend and discern possible geographic differences using population-based data. Annual deaths related to MD were obtained from the National Statistics Institute with codes 359.1 of the ICD-9 (1981–1998) and G71.0 of the ICD-10 (1999–2016). Age-adjusted mortality rates were calculated and changes in mortality trends were identified. The standardized mortality ratios (SMR) and their respective 95% confidence intervals were calculated by district for 1999–2016. Smoothed SMRs and posterior probability were also assessed and then mapped to look for patterns or geographic distribution. All rates were expressed per 1,000,000 inhabitants. A total of 2,512 deaths (73.8% men) were identified. The age-adjusted mortality rates varied from 0.63 (95% CI 0.40–0.95) in 1981 to 1.51 (95% CI 1.17–1.93) in 2016. MD mortality showed a significant increase of 8.81% per year (95% CI 5.0–12.7) from 1981 to 1990, remaining stable afterwards. Areas with risk of death higher than expected for Spain as a whole were identified, not showing a specific regional pattern. In conclusion, the rising trend in MD mortality might be attributable to advanced improvements in diagnostic techniques leading to a rise in prevalence. Further research on the districts with the highest mortality would be necessary.
Exploring agricultural land-use and childhood malaria associations in sub-Saharan Africa
Authors: Shah Hiral Anil , Carrasco Luis Roman , Hamlet Arran , Murray Kris A. 
Published: March 2022

AbstractAgriculture in Africa is rapidly expanding but with this comes potential disbenefits for the environment and human health. Here, we retrospectively assess whether childhood malaria in sub-Saharan Africa varies across differing agricultural land uses after controlling for socio-economic and environmental confounders. Using a multi-model inference hierarchical modelling framework, we found that rainfed cropland was associated with increased malaria in rural (OR 1.10, CI 1.03–1.18) but not urban areas, while irrigated or post flooding cropland was associated with malaria in urban (OR 1.09, CI 1.00–1.18) but not rural areas. In contrast, although malaria was associated with complete forest cover (OR 1.35, CI 1.24–1.47), the presence of natural vegetation in agricultural lands potentially reduces the odds of malaria depending on rural–urban context. In contrast, no associations with malaria were observed for natural vegetation interspersed with cropland (veg-dominant mosaic). Agricultural expansion through rainfed or irrigated cropland may increase childhood malaria in rural or urban contexts in sub-Saharan Africa but retaining some natural vegetation within croplands could help mitigate this risk and provide environmental co-benefits.
Automated pancreas segmentation and volumetry using deep neural network on computed tomography
Authors: Lim Sang-Heon , Kim Young Jae , Park Yeon-Ho , Kim Doojin , Kim Kwang Gi , Lee Doo-Ho 
Published: March 2022

AbstractPancreas segmentation is necessary for observing lesions, analyzing anatomical structures, and predicting patient prognosis. Therefore, various studies have designed segmentation models based on convolutional neural networks for pancreas segmentation. However, the deep learning approach is limited by a lack of data, and studies conducted on a large computed tomography dataset are scarce. Therefore, this study aims to perform deep-learning-based semantic segmentation on 1006 participants and evaluate the automatic segmentation performance of the pancreas via four individual three-dimensional segmentation networks. In this study, we performed internal validation with 1,006 patients and external validation using the cancer imaging archive pancreas dataset. We obtained mean precision, recall, and dice similarity coefficients of 0.869, 0.842, and 0.842, respectively, for internal validation via a relevant approach among the four deep learning networks. Using the external dataset, the deep learning network achieved mean precision, recall, and dice similarity coefficients of 0.779, 0.749, and 0.735, respectively. We expect that generalized deep-learning-based systems can assist clinical decisions by providing accurate pancreatic segmentation and quantitative information of the pancreas for abdominal computed tomography.