bluuebunny/crossref_metadata_2025_split huggingface dataset:
Surface roughness optimization of hybrid PBF-LB/M-built Inconel 718 using in situ high-speed milling
Authors: Sommer David , Hornung Simon , Esen Cemal , Hellmann Ralf 
Published: March 2024

AbstractWe report on the optimization of the surface roughness of hybrid additive manufactured Ni superalloys, combining a conventional laser powder bed fusion process with in situ high-speed milling. This remarkable hybrid approach has only recently been applied to different steel types and barely to Ni superalloys which opposite to steel appear to be challenging for milling processes, particularly within the powderbed of laser powder bed fusion. Different influencing factors on the surface roughness are varied in this study, following the Taguchi method. Their effect is evaluated with respect to the average surface roughness and the maximum surface roughness. The signal-to-noise ratio for the varied parameters infeed, z-pitch, feed rate, and spindle speed is calculated, determining their relevance on the surface roughness, and defining an optimal parameter combination. As the surface quality is optimized to $$\varvec{R_a=0.47\, \mu m}$$

R
a

=
0.47

μ
m

, the definition of the optimal parameter combination is of the highest relevance for the application of this novel manufacturing approach for Inconel. Using linear regression, the resulting surface roughness of these parameters is predicted, getting validated by the experimental evaluation. Due to a further analysis, including EDX analysis and a quantitative element analysis at different positions of the flank of the milling cutter, wear characteristics as well as the dissipation of the coating of the milling cutter are detected. The flank wear and the resulting breakage of the cutting edge are defined as the main reasons of a rising surface roughness.
The influence of the physicochemical processes on the electrical response of Al/p-Si structure with etched surface
Authors: Badali Yosef , Azizian-Kalandaragh Yashar 
Published: March 2024

AbstractIn this paper, the electrochemical etching process is used for surface modification of the p-Si wafer, named as porous silicon (PS), in the metal–semiconductor (MS) type Schottky diode (SD) with a structure of Al/p-Si. Five regions of PS wafer with different etching rates are selected for comparison of them which are called P2, P3, P4, and P5 (P1 is the reference area without porosity). The morphological, structural, and electrical properties of the PS used in the MS-type SD are investigated using field-emission scanning electron microscope (FE-SEM) images, energy dispersive X-ray (EDX) analysis, and current–voltage (I–V) characteristics, respectively. The FE-SEM images show a meaningful effect on the porosity. The EDX spectrum demonstrates the importance of the chemical effects in addition to the physical changes in the porosity process of the p-Si wafer. The reverse-saturation current (I0), ideality factor (n), barrier height at zero-bias (ΦB0), and series/shunt electrical resistances are also computed and compared. Some of these parameters (n, Rs, BH) are determined using different methods, namely Thermionic emission (TE), Cheung functions, and modified Norde, and they exhibit strong agreement with each other. The energy-dependent profiles of surface states (Nss) are estimated from the I–V data by considering the voltage dependence of ΦB (V) and n(V). All the experimental findings indicate that the etching process of the p-Si wafer significantly influences the electrical performance of the Al/p-Si Schottky diode by increasing the extent of etching.
Fluorescence guidance using near-infrared fluorescent clips in robotic rectal surgery: a case series
Authors: Narihiro Satoshi , Nakashima Syunsuke , Kazi Mutsumi , Kumamoto Tomotaka , Kitagawa Kazuo , Toya Naoki , Eto Ken 
Published: March 2024

Abstract
Purpose
Tattoo markings are often used as preoperative markers for colorectal cancer. However, scattered ink markings adversely affect tumor site recognition intraoperatively; therefore, interventions for rectal cancer may lead to an inaccurate distal resection margin (DRM) and incomplete total mesorectal excision (TME). This is the first case series of fluorescence-guided robotic rectal surgery in which near-infrared fluorescence clips (NIRFCs) were used to localize rectal cancer lesions.

Methods
We enrolled 20 consecutive patients who underwent robotic surgery for rectal cancer between December 2022 and December 2023 in the current study. The primary endpoints were the rate of intraoperative clip detection and its usefulness for marking the tumor site. Secondary endpoints were oncological assessments, including DRM and the number of lymph nodes.

Results
Clip locations were confirmed in 17 of 20 (85%) patients. NIRFCs were not detected in 3 out of 7 patients who underwent preoperative chemoradiation therapy. No adverse events, including bleeding or perforation, were observed at the time of clipping, and no clips were lost. The median DRM was 55 mm (range, 22–86 mm) for rectosigmoid (Rs), 33 mm (range, 16–60 mm) for upper rectum (Ra), and 20 mm (range, 17–30 mm) for low rectum (Rb). The median number of lymph nodes was 13 (range, 10–21).

Conclusion
The rate of intraoperative clip detection, oncological assessment, including DRM, and the number of lymph nodes indicate that the utility of fluorescence-guided methods with NIRFCs is feasible for rectal cancer.
“Dirty Dry Eye”– A waste volume analysis from topical therapy in keratoconjunctivitis sicca
Authors: Schilcher Alexandra V. , Roth Mathias , Steindor Friedrich A. , Helweh Ranya , Geerling Gerd 
Published: March 2024

Abstract
Purpose
The healthcare system is responsible for around 5% of CO2 emissions globally and in Germany. So far, there are no data on the amount of waste from dry eye disease (DED) therapy in ophthalmology. The aim of this project was to evaluate the amount and type of waste from single- and multi-dose units (SDU/MDU) generated by eyedrops used to treat DED in Germany.

Methods
The net waste weight (outer/inner packaging, instruction leaflet, empty container) from factory-sealed products was determined using a precision scale. Based on prescription data from PharMaAnalyst, a database of medical prescriptions from over 70 million patients in Germany, the total annual waste volume for 2016–2021 and the net weight of a 30-day treatment were calculated.

Results
The total annual waste volume increased significantly (p < 0.0001) from 7.13 tons in 2016 to 20.64 tons in 2021. A 30-day treatment with MDUs (without/with filter) results in a significantly lower mean waste volume (paper: SDU 24.3 ± 18.7 g; MDU 4.8 ± 1.7 g/8.8 g ± 1.7 g; SDU/MDU p = 0.0003, with filter p = 0.0034; plastic: SDU 35.0 ± 4.0, MDU 6.6 ± 0.7 g/ 15.1 g ± 5.8 g, SDU/MDU p < 0.0001, with filter p < 0.0001).

Conclusion
Prescription-based treatment of DED in Germany causes an increasing and substantial waste volume. The use of SDUs is considerably more resource-intensive than MDUs. Due to the large and rising number of patients suffering from DED improvements in packaging could considerably reduce the CO2 footprint of DED treatment.
An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases
Authors: Zucca S. , Nicora G. , De Paoli F. , Carta M. G. , Bellazzi R. , Magni P. , Rizzo E. , Limongelli I. 
Published: March 2024

AbstractIdentifying disease-causing variants in Rare Disease patients’ genome is a challenging problem. To accomplish this task, we describe a machine learning framework, that we called “Suggested Diagnosis”, whose aim is to prioritize genetic variants in an exome/genome based on the probability of being disease-causing. To do so, our method leverages standard guidelines for germline variant interpretation as defined by the American College of Human Genomics (ACMG) and the Association for Molecular Pathology (AMP), inheritance information, phenotypic similarity, and variant quality. Starting from (1) the VCF file containing proband’s variants, (2) the list of proband’s phenotypes encoded in Human Phenotype Ontology terms, and optionally (3) the information about family members (if available), the “Suggested Diagnosis” ranks all the variants according to their machine learning prediction. This method significantly reduces the number of variants that need to be evaluated by geneticists by pinpointing causative variants in the very first positions of the prioritized list. Most importantly, our approach proved to be among the top performers within the CAGI6 Rare Genome Project Challenge, where it was able to rank the true causative variant among the first positions and, uniquely among all the challenge participants, increased the diagnostic yield of 12.5% by solving 2 undiagnosed cases.
The illegal trade in rosewood in Indonesia
Authors: Nijman Vincent 
Published: March 2024

AbstractRosewoods are among the most valuable traded hardwoods, and there is a significant illegal trade. From 2017 onwards the international trade in all species of Dalbergia rosewood is regulated through the Convention on International Trade in Endangered Species of Wild Fauna and Flora. I focus on two species of rosewood that occur in parts of Indonesia, Dalbergia latifolia and D. sissoo, to assess the extent of the illegal trade and to analyse geographical and temporal patterns of wildlife crime. Based on 67 seizure reports from 2014 to 2022 I show that (a) 117 logs of D. sissoo and 4,285 logs of D. latifolia were confiscated, (b) seizures occurred on the islands of Sumatra (16 seizures; 1,190 logs), Java (43; 1,780 logs), and Bali, Lombok, Sumbawa and Timor (8; 1,408 logs), (c) while there was an increase in the number of seizures per year, there were no seasonal differences in seizure activities. For 10% of the logs there was supporting evidence that they were taken from State managed forests and 18% was taken from conservation areas, thus causing more damage than just the removal of individual trees. Seizures in Indonesia over this period equals 0.12 ± 0.04% of the legal rosewood export. The illegal trade is dominated by Indonesians rather than foreign nationals and the direction of trade is towards Java from where > 95% will be exported to China. While policies are in place concerning rosewood seizures and stockpiling (including auctioning or destruction) in practise it is unclear where seized rosewood ends up. When used with caution, analysis of seizure data offers a valuable means to gain insights in illicit activities that normally remain hidden from view.
A review of convolutional neural networks in computer vision
Authors: Zhao Xia , Wang Limin , Zhang Yufei , Han Xuming , Deveci Muhammet , Parmar Milan 
Published: March 2024

AbstractIn computer vision, a series of exemplary advances have been made in several areas involving image classification, semantic segmentation, object detection, and image super-resolution reconstruction with the rapid development of deep convolutional neural network (CNN). The CNN has superior features for autonomous learning and expression, and feature extraction from original input data can be realized by means of training CNN models that match practical applications. Due to the rapid progress in deep learning technology, the structure of CNN is becoming more and more complex and diverse. Consequently, it gradually replaces the traditional machine learning methods. This paper presents an elementary understanding of CNN components and their functions, including input layers, convolution layers, pooling layers, activation functions, batch normalization, dropout, fully connected layers, and output layers. On this basis, this paper gives a comprehensive overview of the past and current research status of the applications of CNN models in computer vision fields, e.g., image classification, object detection, and video prediction. In addition, we summarize the challenges and solutions of the deep CNN, and future research directions are also discussed.
Review on PID, fuzzy and hybrid fuzzy PID controllers for controlling non-linear dynamic behaviour of chemical plants
Authors: Mohindru Pankaj 
Published: March 2024

AbstractThe chemical production process is tedious due to the integration of different types of equipment and variables. Designing the controller is crucial in the chemical industry due to the interactive and non-linear system behaviour. An intelligent autonomous controller can improve the operating efficiency of the industry. Although several controllers have been developed, different system failures are frequently reported. Hence, controllers such as proportional integral derivative (PID), fuzzy logic controller (FLC), and hybrid fuzzy PID (F-PID) applied in the chemical industries are critically reviewed in the paper. Initially, the PID controller-based approaches are reviewed for different purposes in the chemical industry. After that, the FLC-based controllers-based papers are reviewed. In order to satisfy the issues in both controllers, the H-PID controllers have been reviewed. This review paper will provide an effective solution for operation control in the chemical industry under different operating conditions.
Protecting commonplace biodiversity under international conservation law
Authors: Amos Rob 
Published: March 2024

AbstractA contemporary appraisal of the extent to which international conservation law provides for the protection of commonplace biodiversity. It is argued that in light of the current extinction crisis, biodiversity would be better served if the law focused more on protecting common species rather than just the rare and endangered. Particular attention is paid to the rationales behind conservation regulation and how different understandings of the value have influenced the law’s development. Key conservation mechanisms, namely area-based management, species-focused mechanisms and the ecosystem approach, are analysed in relation to how they protect commonplace biodiversity, before a case study on the legal protection of plants is presented. What is suggested is that international conservation law has failed to keep pace with key developments in conservation science, resulting in a regulatory system that appears structurally incapable of halting biodiversity loss. Reforming the law so that it provides greater protection to commonplace biodiversity would be an important first step in responding to this.
Human disturbance and habitat structure drive eurasian otter habitat selection in heavily anthropized river basins
Authors: Tolrà Arnau , Ruiz-Olmo Jordi , Riera Joan Lluís 
Published: March 2024

AbstractAssessing habitat selection is essential to protecting threatened species but also to understand what factors influence species that, although globally not currently in decline, act as flagships of their ecosystems and remain highly vulnerable to human impacts, such as the Eurasian otter. This paper examines otter habitat selection at the river reach scale in two heavily anthropized river basins. Both river basins encompass a wide spectrum of human pressures and biogeographic units, which offers an excellent opportunity to assess otter responses to anthropogenic activities in different scenarios. Through two modelling approaches (structure-agnostic way and a priori hypothesized habitat factors) we demonstrate that otters currently inhabiting these human-dominated landscapes show a trade-off between a preference for highly productive areas and for well-structured and safe areas. We suggest that habitat simplification and human disturbance, which were of minor relevance to the dramatic decline of otter populations in the 20th century, are emerging as potential threats in the context of worldwide increasing land use intensification. Furthermore, we found that otter habitat requirements were remarkably more stringent for breeding site selection than for occurrence, particularly concerning variables related to human disturbance. The results of this work provide tools for integrating ecological criteria oriented to effective otter conservation into river management in human-dominated landscapes, as well as serving as methodological support for lowland river restorations. Our results suggest that long-term otter conservation in anthropized rivers will depend on ensuring the availability of habitat patches that maintain sufficient structural complexity away from intensely outdoor recreational activities.
Soil nitrogen cycling in forests invaded by the shrub Rosa multiflora: importance of soil moisture and invasion density
Authors: Moore Eric R. , Pouyat Richard V. , Trammell Tara L. E. 
Published: March 2024

AbstractInvasive plants often alter ecosystem function and processes, especially soil N cycling. In eastern United States forests, the shrub Rosa multiflora (“rose”) is a dominant invader, yet potential effects on N cycling are poorly understood. Moreover, invasive plant management can impact soil N cycling by decreasing plant N uptake and disturbing the soil. The objectives of this study were to evaluate N cycling along a gradient of rose invasion (observational) and investigate potential changes to N cycling (manipulative) under four different management strategies: (1) do nothing (the control), (2) invasive plant removal, (3) removal followed by native seed mix addition, (4) removal, native seed mix, and chipped rose stem addition. We selected three forest sites experiencing a Low, Medium, or High amount of shrub invasion, and measured N cycling in the early (June) and late (September) growing seasons. We found N was immobilized in June and mineralized in September. One year after experimental management, removal alone had no effect on N cycling compared to control plots, but addition of native seed mix and chipped stems reduced early-season nitrification in our Medium invasion site. Our findings suggest that rose invasion may increase N cycling rates when soils are dry, which may occur more frequently with future climate change. In addition, N cycling responds differentially to management in the year following invasive plant removal, but most noticeably under moderate rose invasion.
Discordance interpretation of left ventricular size between echocardiography and cardiac magnetic resonance in pediatric patients with aortic/mitral regurgitation
Authors: Barros Anastasia , Udine Michelle , Spurney Chris , Olivieri Laura , Loke Yue-Hin 
Published: March 2024

Abstract
Purpose
This study investigated discordance between echocardiography (echo) and cardiac magnetic resonance (CMR) measurements of the left ventricle (LV) in pediatric patients with aortic and/or mitral regurgitation (AR/MR).

Methods
Retrospective cohort study of pediatric patients. The cohorts were comprised of patients with AR/MR vs. non-AR/MR. Left ventricular end diastolic volume (LVEDV) by CMR and left ventricular internal diameter diastolic (LVIDd) by echo were obtained from clinical reports then echo images were reviewed to remeasure LVEDV by bullet method. Left ventricular internal diameter systolic (LVIDs) and left ventricular ejection fraction (LVEF) measurements by echo and LVEF by CMR were obtained from clinical reports. Fractional shortening (FS%) was recalculated. Z-scores were calculated using normative data. Correlation between echo and CMR LV measurements was assessed using correlation coefficients. Bland-Altman plots assessed bias between imaging modalities. Receiver operator characteristic (ROC) analysis was performed for detection of LV enlargement and LV dysfunction.

Results
AR/MR patients had greater discrepancy in LV size interpretation by Z-score compared to non-AR/MR patients. This discrepancy persisted when the bullet method short axis measurements were incorporated. There was negative bias in echo-based measurements compared to CMR. The diagnostic performance of echo in identifying moderate LV enlargement was worse for AR/MR pediatrics patients.

Conclusion
The discordant interpretation of LV size by echo compared to CMR is worse in pediatric patients with AR/MR when compared to patients without AR/MR even when short axis measurements are incorporated. This finding suggests non-uniform geometrical changes in the LV as it enlarges due to AR/MR.
Introducing the 3MT_French dataset to investigate the timing of public speaking judgements
Authors: Biancardi Beatrice , Chollet Mathieu , Clavel Chloé 
Published: March 2024

AbstractIn most public speaking datasets, judgements are given after watching the entire performance, or on thin slices randomly selected from the presentations, without focusing on the temporal location of these slices. This does not allow to investigate how people’s judgements develop over time during presentations. This contrasts with primacy and recency theories, which suggest that some moments of the speech could be more salient than others and contribute disproportionately to the perception of the speaker’s performance. To provide novel insights on this phenomenon, we present the 3MT_French dataset. It contains a set of public speaking annotations collected on a crowd-sourcing platform through a novel annotation scheme and protocol. Global evaluation, persuasiveness, perceived self-confidence of the speaker and audience engagement were annotated on different time windows (i.e., the beginning, middle or end of the presentation, or the full video). This new resource will be useful to researchers working on public speaking assessment and training. It will allow to fine-tune the analysis of presentations under a novel perspective relying on socio-cognitive theories rarely studied before in this context, such as first impressions and primacy and recency theories. An exploratory correlation analysis on the annotations provided in the dataset suggests that the early moments of a presentation have a stronger impact on the judgements.
"Approaches to sentiment analysis of Hungarian political news at the sentence level"
Authors: Ring Orsolya , Szabó Martina Katalin , Guba Csenge , Váradi Bendegúz , Üveges István 
Published: March 2024

AbstractAutomated sentiment analysis of textual data is one of the central and most challenging tasks in political communication studies. However, the toolkits available are primarily for English texts and require contextual adaptation to produce valid results—especially concerning morphologically rich languages such as Hungarian. This study introduces (1) a new sentiment and emotion annotation framework that uses inductive approaches to identify emotions in the corpus and aggregate these emotions into positive, negative, and mixed sentiment categories, (2) a manually annotated sentiment data set with 5700 political news sentences, (3) a new Hungarian sentiment dictionary for political text analysis created via word embeddings, whose performance was compared with other available sentiment dictionaries. (4) Because of the limitations of sentiment analysis using dictionaries we have also applied various machine learning algorithms to analyze our dataset, (5) Last but not least to move towards state-of-the-art approaches, we have fine-tuned the Hungarian BERT-base model for sentiment analysis. Meanwhile, we have also tested how different pre-processing steps could affect the performance of machine-learning algorithms in the case of Hungarian texts.