bluuebunny/crossref_metadata_2025 huggingface dataset:
A deep embedded refined clustering approach for breast cancer distinction based on DNA methylation
Authors: Amor Rocío del , Colomer Adrián , Monteagudo Carlos , Naranjo Valery
Published: July 2021

Epigenetic alterations have an important role in the development of several types of cancer. Epigenetic studies generate a large amount of data, which makes it essential to develop novel models capable of dealing with large-scale data. In this work, we propose a deep embedded refined clustering method for breast cancer differentiation based on DNA methylation. In concrete, the deep learning system presented here uses the levels of CpG island methylation between 0 and 1. The proposed approach is composed of two main stages. The first stage consists in the dimensionality reduction of the methylation data based on an autoencoder. The second stage is a clustering algorithm based on the soft assignment of the latent space provided by the autoencoder. The whole method is optimized through a weighted loss function composed of two terms: reconstruction and classification terms. To the best of the authors’ knowledge, no previous studies have focused on the dimensionality reduction algorithms linked to classification trained end-to-end for DNA methylation analysis. The proposed method achieves an unsupervised clustering accuracy of 0.9927 and an error rate (%) of 0.73 on 137 breast tissue samples. After a second test of the deep-learning-based method using a different methylation database, an accuracy of 0.9343 and an error rate (%) of 6.57 on 45 breast tissue samples are obtained. Based on these results, the proposed algorithm outperforms other state-of-the-art methods evaluated under the same conditions for breast cancer classification based on DNA methylation data.
Tribute to Dr. Takuo Aoyagi, inventor of pulse oximetry
Authors: Miyasaka Katsuyuki , Shelley Kirk , Takahashi Shosuke , Kubota Hironami , Ito Kazumasa , Yoshiya Ikuto , Yamanishi Akio , Cooper Jeffrey B. , Steward David J. , Nishida Hiroshi , Kiani Joe , Ogino Hirokazu , Sata Yasuhiko , Kopotic Robert J. , Jenkin Kitty , Hannenberg Alex , Gawande Atul
Published: August 2021

Introduction

Dr. Takuo Aoyagi invented pulse oximetry in 1974. Pulse oximeters are widely used worldwide, most recently making headlines during the COVID-19 pandemic. Dr. Aoyagi passed away on April 18, 2020, aware of the significance of his invention, but still actively searching for the theory that would take his invention to new heights.

Method

Many people who knew Dr. Aoyagi, or knew of him and his invention, agreed to participate in this tribute to his work. The authors, from Japan and around the world, represent all aspects of the development of medical devices, including scientists and engineers, clinicians, academics, business people, and clinical practitioners.

Results

While the idea of pulse oximetry originated in Japan, device development lagged in Japan due to a lack of business, clinical, and academic interest. Awareness of the importance of anesthesia safety in the US, due to academic foresight and media attention, in combination with excellence in technological innovation, led to widespread use of pulse oximetry around the world.

Conclusion

Dr. Aoyagi’s final wish was to find a theory of pulse oximetry. We hope this tribute to him and his invention will inspire a new generation of scientists, clinicians, and related organizations to secure the foundation of the theory.
Revision surgery for incomplete resection or recurrence of cervical spine chordoma: a consecutive case series of 24 patients
Authors: Obid Peter , Fekete Tamás , Drees Philipp , Haschtmann Daniel , Kleinstück Frank , Loibl Markus , Jeszenszky Dezsö
Published: August 2021

Purpose

Chordomas are rare tumors with an annual incidence of approximately one per million. Chordomas rarely metastasize but show a high local recurrence rate. Therefore, these patients present a major clinical challenge, and there is a paucity of the literature regarding the outcome after revision surgery of cervical spine chordomas. Available studies suggest a significantly worse outcome in revision scenarios. The purpose of this study is to analyze the survival rate, and complications of patients that underwent revision surgery for local recurrence or incomplete resection of chordoma at the craniocervical junction or at the cervical spine.

Methods

24 consecutive patients that underwent revision surgery for cervical spine chordoma remnants or recurrence at a single center were reviewed retrospectively. We analyzed patient-specific surgical treatment strategies, complications, and outcome. Kaplan–Meier estimator was used to analyze five-year overall survival.

Results

Gross total resection was achieved in 17 cases. Seven patients developed dehiscence of the pharyngeal wall, being the most common long-term complication. No instability was observed. Postoperatively, four patients received proton beam radiotherapy and 12 patients had combined photon and proton beam radiotherapy. The five-year overall survival rate was 72.6%.

Conclusion

With thorough preoperative planning, appropriate surgical techniques, and the addition of adjuvant radiotherapy, results similar to those in primary surgery can be achieved.
An Evertse–Ferretti Nevanlinna constant and its consequences
Authors: Ru Min , Vojta Paul
Published: August 2021

In this paper, we introduce the notion of an Evertse–Ferretti Nevanlinna constant and compare it with the birational Nevanlinna constant introduced by the authors in a recent joint paper. We then use it to recover several previously known results. This includes a 1999 example of Faltings from his Baker’s Garden article. We also extend the theory of these Nevanlinna constants to what we call “multidivisor Nevanlinna constants,” which allow the proximity function to involve the maximum of Weil functions for finitely many divisors.
Corrosion analysis of graphite sinter as bipolar plates in the low-temperature PEM fuel cell simulated environments
Authors: Włodarczyk Renata
Published: August 2021

The article presents the results of research and an analysis of the possibility of using sinters made of graphite powder as a material dedicated to the production of bipolar plates for low-temperature fuel cell. The use of powder metallurgy technology allows for the production of materials that meet the requirements for fuel cell elements for the construction of elements closing a single cell (bipolar or monopolar plates) or interconnectors. The morphological and chemical analysis of graphite powder, microstructural analysis of the produced graphite sinter, and the analysis of functional properties, i.e., porosity, roughness, and corrosion resistance under operating conditions of a low-temperature fuel cell, were performed. The corrosion resistance of the graphite sinter was tested in anodic conditions (in a corrosive environment saturated with hydrogen) and in cathodic conditions (in a corrosive environment saturated with oxygen). Graphite sinters show high resistivity in both tested corrosive environments, which allows the use of powder metallurgy technology for serial production of covers for low-temperature fuel cells.
Structural learning and estimation of joint causal effects among network-dependent variables
Authors: Castelletti Federico , Mascaro Alessandro
Published: August 2021

Bayesian networks in the form of Directed Acyclic Graphs (DAGs) represent an effective tool for modeling and inferring dependence relations among variables, a process known asstructural learning. In addition, when equipped with the notion ofintervention, acausalDAG model can be adopted to quantify the causal effect on a response due to a hypothetical intervention on some variable. Observational data cannot distinguish between DAGs encoding the same set of conditional independencies (Markov equivalent DAGs), which however can be different from acausalperspective. In addition, because causal effects depend on the underlying network structure, uncertainty around the DAG generating model crucially affects the causal estimation results. We propose a Bayesian methodology which combines structural learning of Gaussian DAG models and inference of causal effects as arising from simultaneous interventions on any given set of variables in the system. Our approach fully accounts for the uncertainty around both the network structure and causal relationships through a joint posterior distribution over DAGs, DAG parameters and then causal effects.
Attitudes to and experience of disease management programs in primary care—an exploratory survey of general practitioners in Germany
Authors: Wangler Julian , Jansky Michael
Published: August 2021

Background

Disease management programs (DMPs) were set up in Germany in 2003 to improve outpatient care of chronically ill patients. The present study looks at the attitudes and experiences of general practitioners (GPs) in relation to DMPs, how they rate them almost 20 years after their introduction and where they see a need for improvement.

Methods

A total of 1504 GPs in the Federal States of Rhineland Palatinate, Saarland and Hesse were surveyed between December 2019 and March 2020 using a written questionnaire.

Results

In total, 58% of respondents rate DMPs positively and regard them as making a useful contribution to primary care. The guarantee of regular, structured patient care and greater compliance are regarded as particularly positive aspects. It was also established that diagnostic and therapeutic knowledge was expanded through participation in DMPs. 57% essentially follow the DMP recommendations for (drug) treatment. Despite positive experiences of DMPs in patient care, the GPs surveyed mention various challenges (documentation requirements, frequent changes to the programmes, inflexibility). Univariant linear regression analysis revealed factors influencing the satisfaction with DMPs, such as improvement of compliance and clearly defined procedures in medical care.

Conclusion

Most of the GPs surveyed consider the combination of continuous patient care and evidence-based diagnosis and treatment to be a great advantage. To better adapt DMPs to the conditions of primary care, it makes sense to simplify the documentation requirements, to regulate cooperation with other healthcare levels more clearly and to give GPs more decision-making flexibility. Increased inclusion of GP experience in the process of developing and refining DMPs can be helpful.
Confidence interval for micro-averaged F1 and macro-averaged F1 scores
Authors: Takahashi Kanae , Yamamoto Kouji , Kuchiba Aya , Koyama Tatsuki
Published: July 2021

A binary classification problem is common in medical field, and we often use sensitivity, specificity, accuracy, negative and positive predictive values as measures of performance of a binary predictor. In computer science, a classifier is usually evaluated with precision (positive predictive value) and recall (sensitivity). As a single summary measure of a classifier’s performance, F1 score, defined as the harmonic mean of precision and recall, is widely used in the context of information retrieval and information extraction evaluation since it possesses favorable characteristics, especially when the prevalence is low. Some statistical methods for inference have been developed for the F1 score in binary classification problems; however, they have not been extended to the problem of multi-class classification. There are three types of F1 scores, and statistical properties of these F1 scores have hardly ever been discussed. We propose methods based on the large sample multivariate central limit theorem for estimating F1 scores with confidence intervals.
A comprehensive model and computational methods to improve Situation Awareness in Intelligence scenarios
Authors: Gaeta Angelo , Loia Vincenzo , Orciuoli Francesco
Published: July 2021

This paper presents a comprehensive model for representing and reasoning on situations to support decision makers in Intelligence analysis activities. The main result presented in the paper stems from a work of refinement and abstraction of previous results of the authors related to the use of Situation Awareness and Granular Computing for the development of analysis methods and techniques to support Intelligence. This work made it possible to derive the characteristics of the model from previous case studies and applications with real data, and to link the reasoning techniques to concrete approaches used by intelligence analysts such as, for example, the Structured Analytic Techniques. The model allows to represent an operational situation according to three complementary perspectives: descriptive, relational and behavioral. These three perspectives are instantiated on the basis of the principles and methods of Granular Computing, mainly based on the theories of fuzzy and rough sets, and with the help of further structures such as graphs. As regards the reasoning on the situations thus represented, the paper presents four methods with related case studies and applications validated on real data.
Adult cold tolerance and potential North American distribution of Myllocerus undecimpustulatus undatus (Coleoptera: Curculionidae)
Authors: Neal Anita S. , Diaz Rodrigo , Qureshi Jawwad A. , Cave Ronald D.
Published: July 2021

Cold tolerance and potential distribution of Myllocerus undecimpustulatus undatus Marshall, a polyphagous pest in the United States, were investigated. Adult survivorship after 2 days at 0 °C and − 5 °C averaged 60% and 18%, respectively. Four days of exposure resulted in survivorship of 11% at 0 °C and 4% at − 5 °C, respectively. Summer-collected weevils at − 5 °C through repeated cold exposure of 2 h survived 3 times longer than those subjected to sustained cold period of 10 h. Leaf consumption did not differ among summer-collected weevils at constant 20 °C and repeated cold exposure treatments; weevils under sustained cold exposure consumed less than weevils in repeated cold exposure treatments. Leaf area consumed after cold exposure was 2–4 times greater in winter-collected weevils compared to summer-collected weevils. Leaf consumption by winter-collected weevils decreased as the number of repeated cold exposure periods increased. Locality data from collections in Florida during 2000–2012 were used to produce a correlative model complemented by a mechanistic model from the cold tolerance data to project the potential distribution of M. undecimpustulatus undatus in North America. The models support the hypothesis that M. undecimpustulatus undatus could spread to areas of the southeastern and western United States. The predicted northern distribution followed an isothermal line about 33° North. The niche model defined an area along the western Gulf Coast as unsuitable for the weevil, possibly because the area receives greater annual rainfall than other areas of the southeastern United States and has aquic or udic soil unlike the well-drained sandy soil of peninsular Florida.
Complete genome sequence and phylogenomic analysis of the first N4-like lytic bacteriophage vB_Ppp_A38 (ϕA38) infecting Pectobacterium parmentieri
Authors: Czajkowski Robert , Rabalski Lukasz , Kosinski Maciej , Smolarska Anna
Published: July 2021

Pectobacterium parmentieri (former Pectobacterium wasabiae) is an emerging pectinolytic bacterial pathogen causing losses in potato (Solanum tuberosum L.) worldwide. Until now, there are no effective measures to protect crops from infections caused by P. parmentieri. Likewise, little is known about lytic bacteriophages that can infect and kill P. parmentieri, and that could be used in the (bio)control of this pathogen in agricultural applications. A novel lytic bacteriophage vB_Ppp_A38 (ϕA38), belonging to the order Caudovirales, was isolated and characterised in our previous studies. This report provides information about its complete genome sequence and accompanying phylogenomics. The genome of vB_Ppp_A38 consists of 75,764-bp-length, linear, double-stranded DNA with an average GC content of 48.7% and is predicted to have 97 open reading frames (ORFs), with an average length of 732 nucleotides. The open reading frames were classified into functional groups, including structural units, packing, DNA metabolism, regulation and additional (miscellaneous) functions. Comparative genomic analyses based on the whole-genome sequence indicated that the phage vB_Ppp_A38 is most similar to N4-like viruses of the family Schitoviridae, genus Cbunavirus, sharing more than 90% identity with the phages vB_PatP_CB1, vB_PatP_CB3 and vB_PatP_CB4 infecting P. atrosepticum. The bacteriophage vB_Ppp_A38 is the first Cbunavirus bacteriophage infecting other Pectobacterium spp. hosts than P. atrosepticum. As vB_Ppp_A38 is a lytic virus able to kill plant-pathogenic P. parmentieri, it can be used in the biological control of this pathogen in agricultural applications.
Increasing Human Papillomavirus Vaccination in a Federally Qualified Health Center Organization Using a Systems-Based Intervention Integrating EHR and Statewide Immunization Information System
Authors: Vinci Debra M. , Ryan Jessica , Howard Maureen , Snider Dallas , Strahan Brandy , Smith Gregg , McClain Rebecca
Published: July 2021

Public acceptance of the HPV vaccine has not matched that of other common adolescent vaccines, and HPV vaccination rates remain below the Healthy People 2020 target of 80% compliance. The purpose of this study was to evaluate the capacity of nine pediatric clinics in a Federally Qualified Health Center organization to implement a systems-based intervention targeting office staff and providers using EHRs and a statewide immunization information system to increase HPV vaccination rates in girls and boys, ages 11 to 16 over a 16-month period. System changes included automated HPV prompts to staff, postcard reminders to parents when youths turned 11 or 12 years old, and monthly assessment of provider vaccination rates.

During the intervention, 8960 patients (11–16 yo) were followed, with 48.8% girls (n = 4370) and 51.2% boys (n = 4590). For this study period, 80.5% of total patients received the first dose of the HPV vaccine and 47% received the second dose. For the first dose, 55.5% of 11 year old girls and 54.3% of 11 year old boys were vaccinated. For ages 12 to 16, first dose vaccination rates ranged from the lowest rate of 84.5% for 14 yo girls up to the highest rate of 90.5% for 13 yo boys. Logistic regression showed age was highly significantly associated with first dose completion (OR 1.565, 95% CI 1.501, 1.631) while males did not have a significant association with first dose completion compared to females. The intervention increased overall counts of first and second HPV vaccination rates.
In silico screening of neurokinin receptor antagonists as a therapeutic strategy for neuroinflammation in Alzheimer’s disease
Authors: Satarker Sairaj , Maity Swastika , Mudgal Jayesh , Nampoothiri Madhavan
Published: July 2021

Neuroinflammation is one of the detrimental factors leading to neurodegeneration in Alzheimer’s disease (AD) and other neurodegenerative disorders. The activation of microglial neurokinin 1 receptor (NK1R) by substance P (SP) enhances neuroinflammation which is mediated through pro-inflammatory pathways involving NFkB, ERK1/2, and P38 and thus projects the scope and importance of NK1R inhibitors. Emphasizing the inhibitory role of N Acetyl l Tryptophan (l-NAT) on NK1R, this is the first in silico screening of l-NAT mediated NK1R antagonism. In addition, FDA- approved ligands were screened for their potential NK1R antagonism. The l-NAT was docked in XP (Extra Precision) mode while FDA-approved ligands were screened in HTVS (High Throughput Virtual Screening), SP (Standard Precision), and XP mode onto NK1R (PDB:6HLO). The l-NAT and top 3 compounds FDA-approved ligands were subjected to molecular dynamics (MD) studies of 100 ns simulation time. The XP docking of l-NAT, indacaterol, modafinil and alosetron showed good docking scores. Their 100 ns MD showed brief protein–ligand interactions with an acceptable root mean square deviation. The protein–ligand contacts depicted pi-pi stacking, pi-cation, hydrogen bonds, and water bridges with the amino acids necessary for NK1R inhibition. The variable colour band intensities on the protein–ligand contact map indicated their binding strength with amino acids. The molecular mechanics/generalized born surface area (MM-GBSA) scores suggested favourable binding free energy of the complexes. Thus, our study predicted the ability of l-NAT, indacaterol, modafinil, and alosetron as capable NK1R inhibitors that can aid to curb neuroinflammation in conditions of AD which could be further ascertained in subsequent studies.

Graphic Abstract
Schizophrenia, Temporality, and Affection
Authors: Sul Jae Ryeong
Published: July 2021

Temporal experience and its radical alteration in schizophrenia have been one of the central objects of investigation in phenomenological psychopathology. Various phenomenologically oriented researchers have argued that the change in the mode of temporal experience present in schizophrenia can foreground its psychotic symptoms of delusion. This paper aims to further the development of such a phenomenological investigation by highlighting a much-neglected aspect of schizophrenic temporal experience, i.e., its non-emotional affective characteristic. In this paper, it denotes the type of an experience wherein an afflicted individual experiences a pervasive pull or attraction coming from the past, present, and future. By employing Husserl’s account of affection, I argue that such an affectively prominent temporal experience is not yet another abnormality that happens to be present in schizophrenia. Instead, it is indicative of the core disturbance that underpins the schizophrenic temporal mode of experience. I identify such a disturbance as ‘affective modification dysfunction’ and employ it as a core concept with which I synthesize and organise heterogeneous components of schizophrenic temporal experience in their conceptual unity. For the sake of clear description, I organise those components into the following categories: 1.) Time Stop 2.) Ante-festum 3.) Déjà vu/vécu and 4.) Time Fragmentation. I conclude by demonstrating how approaching schizophrenic temporal experience from its affective dimension can further help us better understand its pre-psychotic phase known to precipitate schizophrenic primary delusion, i.e., delusional mood.
Efficient Experimental and Data-Centered Workflow for Microstructure-Based Fatigue Data
Authors: Durmaz A. R. , Hadzic N. , Straub T. , Eberl C. , Gumbsch P.
Published: August 2021

Background

Early fatigue mechanisms for various materials are yet to be unveiled for the (very) high-cycle fatigue (VHCF) regime. This can be ascribed to a lack of available data capturing initial fatigue damage evolution, which continues to adversely affect data scientists and computational modeling experts attempting to derive microstructural dependencies from small sample size data and incomplete feature representations.

Objective

The aim of this work is to address this lack and to drive the digital transformation of materials such that future virtual component design can be rendered more reliable and more efficient. Achieving this relies on fatigue models that comprehensively capture all relevant dependencies.

Methods

To this end, this work proposes a combined experimental and data post-processing workflow to establish multimodal fatigue crack initiation and propagation data sets efficiently. It evolves around fatigue testing of mesoscale specimens to increase damage detection sensitivity, data fusion through multimodal registration to address data heterogeneity, and image-based data-driven damage localization.

Results

A workflow with a high degree of automation is established, that links large distortion-corrected microstructure data with damage localization and evolution kinetics. The workflow enables cycling up to the VHCF regime in comparatively short time spans, while maintaining unprecedented time resolution of damage evolution. Resulting data sets capture the interaction of damage with microstructural features and hold the potential to unravel a mechanistic understanding.

Conclusions

The proposed workflow lays the foundation for future data mining and data-driven modeling of microstructural fatigue by providing statistically meaningful data sets extendable to a wide range of materials.
Prediction of Particle Properties in Plasma Spraying Based on Machine Learning
Authors: Bobzin K. , Wietheger W. , Heinemann H. , Dokhanchi S. R. , Rom M. , Visconti G.
Published: August 2021

Thermal spraying processes include complex nonlinear interdependencies among process parameters, in-flight particle properties and coating structure. Therefore, employing computer-aided methods is essential to quantify these complex relationships and subsequently enhance the process reproducibility. Typically, classic modeling approaches are pursued to understand these interactions. While these approaches are able to capture very complex systems, the increasingly sophisticated models have the drawback of requiring considerable calculation time. In this study, two different Machine Learning (ML) methods, Residual Neural Network (ResNet) and Support Vector Machine (SVM), were used to estimate the in-flight particle properties in plasma spraying in a much faster manner. To this end, data sets comprising the process parameters such as electrical current and gas flow as well as the in-flight particle velocities, temperatures and positions have been extracted from a CFD simulation of the plasma jet. Furthermore, two Design of Experiments (DOE) methods, Central Composite Design (CCD) and Latin Hypercube Sampling (LHS), have been employed to cover a set of representative process parameters for training the ML models. The results show that the developed ML models are able to estimate the trends of particle properties precisely and dramatically faster than the computation-intensive CFD simulations.
Internal bracing in the treatment of elbow instabilities
Authors: Ellwein Alexander , Lill Helmut , Smith Tomas , DeyHazra Rony-Orijit , Warnhoff Mara , Jensen Gunnar
Published: August 2021

Internal bracing is an augmentation of ligament repair or reconstruction using a non-absorbable suture tape. The suture reinforcement of the ligament is intended to absorb the forces applied to the joint while the ligament repair or reconstruction underneath is healing. The rigidity of the construct is expected to improve primary stability, which should facilitate and accelerate postoperative mobilization and rehabilitation. Nevertheless, internal bracing is a novel treatment and data is limited. Therefore, this review describes the surgical techniques and provides an overview of the current literature regarding acute and chronic instabilities of the medial and lateral elbow treated with internal bracing.
Fruit maturity and location identification of beef tomato using R-CNN and binocular imaging technology
Authors: Hsieh Kuang-Wen , Huang Bo-Yu , Hsiao Kai-Ze , Tuan Yu-Hao , Shih Fu-Pang , Hsieh Li-Cheng , Chen Suming , Yang I-Chang
Published: August 2021

The objective of this study was to identify the maturity and position of tomatoes in greenhouse. Three parts have been included in this study: building the model of image capturing and object detection, position identification of mature fruits and prediction of the size of the mature fruits. For the first part, image capturing in different time and object detection will be conducted in the greenhouse for identification of mature fruits. For the second part, the relative 3D position of the mature fruits calculated by the binocular vision was compared with the actual measured position. For the third part, the size of the bounding box from the object detection was compared with the actual size of the mature fruit, and the correlation was calculated in order to pre-adjust the width of the gripper for plucking operation in the future. The precision and the recall of the mature fruits of this study are over 95%. The average error of the 3D position is 0.5 cm. The actual size of the fruits and the R-squared of the size of the bounding box are over 0.9.
Robotic versus laparoscopic right hemicolectomy: a case-matched study
Authors: Hannan Enda , Feeney Gerard , Ullah Mohammad Fahad , Ryan Claire , McNamara Emma , Waldron David , Condon Eoghan , Coffey John Calvin , Peirce Colin
Published: August 2021

The current gold standard surgical treatment for right colonic malignancy is the laparoscopic right hemicolectomy (LRH). However, laparoscopic surgery has limitations which can be overcome by robotic surgery. The benefits of robotics for rectal cancer are widely accepted but its use for right hemicolectomy remains controversial. The aim of this study was to compare outcomes in patients undergoing robotic right hemicolectomy (RRH) and LRH in a university teaching hospital. Demographic, perioperative and postoperative data along with early oncological outcomes of patients who underwent RRH and LRH with extracorporeal anastomosis (ECA) were identified from a prospectively maintained database. A total of 70 patients (35 RRH, 35 LRH) were identified over a 4-year period. No statistically significant differences in estimated blood loss, conversion to open surgery, postoperative complications, anastomotic leak, 30-day reoperation, 30-day mortality, surgical site infection or lengths of stay were demonstrated. Surgical specimen quality in both groups was favourable. The mean duration of surgery was longer in RRH (p <  < 0.00001). A statistically significant proportion of RRH patients had a higher BMI and ASA grade. The results demonstrate that RRH is safe and feasible when compared to LRH, with no statistical difference in postoperative morbidity, mortality and early oncological outcomes. A difference was noted in operating time, however was influenced by training residents in docking the robot and a technically challenging cohort of patients. Operative time has shortened with further experience. Incorporating an intracorporeal anastomosis technique in RRH offers the potential to improve outcomes compared to LRH.
A Review of Secondary Aluminum Production and Its Byproducts
Authors: Padamata Sai Krishna , Yasinskiy Andrey , Polyakov Peter
Published: July 2021

Secondary aluminum production is required for the conservation of the environment. It can significantly reduce greenhouse gas emissions and energy consumption and reduce the consumption of alumina, a source of primary aluminum. Secondary aluminum production requires sorting processes for the metal scrap before starting the refining process. Salt slags generated from both primary and secondary aluminum production need to be recycled/treated as they are considered hazardous byproducts. This review paper discusses the methods used for sorting and refining aluminum waste and managing and utilizing slag cakes/slag from recycling techniques.
Verification of Trail Making Test in Elderly People with Behavioral and Psychological Symptoms of Dementia
Authors: Toda Atsushi , Nagami Shinsuke , Katsumata Ayako , Fukunaga Shinya
Published: July 2021

In Alzheimer's disease (AD), attention and executive dysfunction occur early in the disease. However, little is known about the relationship between these disorders and behavioral and psychological symptoms of dementia (BPSD). This study investigated the relationship between BPSD and attention and execution functions. Twenty-five patients with mild cognitive impairment (MCI) and early AD were included. Neuropsychological tests, mini-mental state examination (MMSE), Raven’s colored progressive materials (RCPM), and trail making test (TMT) were conducted for patients with dementia. The dementia behavior disturbance scale (DBD) was used for psychological and behavioral evaluations of patients with dementia. The AD group showed significantly lower MMSE, DBD, and TMT-B scores than the MCI group. Multiple regression analyses revealed a significant correlation between DBD score, MMSE, and TMT-B.Conclusion: BPSD is associated with cognitive function severity in patients with MCI and early AD, suggesting that attentional and executive functions are independent risk factors for these neural substrates.
Integrated backscatter-intravascular ultrasound and modification of plaque during excimer laser coronary angioplasty
Authors: Sasaki Satoru , Nakajima Kenji , Watanabe Keizo , Nozaki Yudai , Yuguchi Tadashi , Sano Hiroyuki , Matsutera Ryo , Murai Naoki , Abe Hiroaki , Takaoka Hideyuki
Published: July 2021

This study aims to test the hypothesis that the effect of excimer laser coronary angioplasty (ELCA) not only vaporizes thrombi and their underlying coronary plaque, it also changes their quality. We performed a series of cross-sectional analyses in 52 lesions in 51 patients before and after ELCA with integrated backscatter-intravascular ultrasound (IB-IVUS). The constituent parts of the plaque can be assessed by IB-IVUS (i.e., calcified, fibrous, lipid) according to integrated backscatter values. Minimum lumen diameter, lumen volume and vessel volume expanded after ELCA, while plaque volume did not significantly decrease. There was also a decrease of ‘lipid’ component (35.4–30.3%, P < 0.001) and an increase of IB-IVUS-derived ‘fibrous’ part (34.5–38.3%, P < 0.001). These results may help in understanding plaque change after ELCA. Excimer laser coronary angioplasty seems to contribute to the modification of coronary plaque composition in addition to debulking it.
Philosophy of sustainability experimentation _ experimental legacy, normativity and transfer of evidence
Authors: Stojanovic Milutin
Published: July 2021

The recent proliferation of types and accounts of experimentation in sustainability science still lacks philosophical reflection. The present paper introduces this burgeoning topic to the philosophy of science by identifying key notions and dynamics in sustainability experimentation, by discussing taxonomies of sustainability experimentation and by focusing on barriers to the transfer of evidence. It integrates three topics: the philosophy of experimentation; the sustainability science literature on experimentation; and discussions on values in science coming from the general philosophy of science, the social sciences, and sustainability science. The aim is to improve understanding of how sustainability experimentation has evolved, from a broader picture of the history and philosophy of science, with a specific focus on understanding evidence production and how evidence traveling in and from sustainability experiments can be improved, particularly in the context of complex and pervasive normative commitments of the research. By engaging in these topics, this research is one of the first philosophical accounts of sustainability experimentation, contributing both to the knowledge on specific philosophies of science and to the further development of an evidence-based sustainability science through a better understanding of the barriers to more relevant and usable knowledge.
Jordan triple homomorphisms on $${\mathcal {T}}_\infty (F)$$
Authors: Słowik Roksana
Published: August 2021

Let$${\mathcal {T}}_\infty (F)$$T∞(F)be the algebra of all$${\mathbb {N}}\times {\mathbb {N}}$$N×Nupper triangular matrices defined over a fieldFof characteristic different from 2. We consider the Jordan triple homomorphisms of$${\mathcal {T}}_\infty (F)$$T∞(F), i.e. the additive maps that satisfy the condition$$\phi (xyx)=\phi (x)\phi (y)\phi (x)$$ϕ(xyx)=ϕ(x)ϕ(y)ϕ(x)for all$$x,y\in {\mathcal {T}}_\infty (F)$$x,y∈T∞(F). For the case whenFis a prime field we find the form of all such maps$$\phi $$ϕ. For the general case we present the form of the surjective maps$$\phi $$ϕ.
Fatigue assessment of additively manufactured AlSi10Mg structures using effective stress concepts based on the critical distance approach
Authors: Schnabel Kai , Baumgartner Jörg , Möller Benjamin , Scurria Matilde
Published: August 2021

In the last decade, Additive Manufacturing (AM) technologies have been considered by both the automotive and aerospace industries for the production of end-use metallic parts, with a main focus on Powder Bed Fusion – Laser Beam / metallic (PBF-LB/M) technologies. However, AM parts present features that are deleterious to their cyclic properties. For a reliable design in terms of fatigue strength, existing influencing variables must be identified and transferred to a numerical model. In particular, different types of defects, as well as their distribution, should be taken into account. In addition to the identification of relevant parameters based on literature data, an AlSi10Mg component-like structure is assessed based on results from notched specimens and a linear-elastic assessment concept using effective stresses.
A Review of Coccidioides Research, Outstanding Questions in the Field, and Contributions by Women Scientists
Authors: Gorris Morgan E. , Caballero Van Dyke Marley C. , Carey Adrienne , Hamm Paris S. , Mead Heather L. , Uehling Jessie K.
Published: August 2021

Purpose of Review

Coccidioidomycosis is an infectious disease that gained clinical significance in the early 20th century. Many of the foundational contributions to coccidioidomycosis research, including the discovery of the fungal disease agent, Coccidioides spp., were made by women. We review recent progress in Coccidioides research and big questions remaining in the field, while highlighting some of the contributions from women.

Recent Findings

New molecular-based techniques provide a promising method for detecting Coccidioides, which can help determine the dominate reservoir host and ideal environmental conditions for growth. Genetic and genomic analyses have allowed an understanding of population structure, species level diversity, and evolutionary histories. We present a current, comprehensive genome list, where women contributed many of these entries. Several efforts to develop a coccidioidomycosis vaccine are underway.

Women continue to pioneer research on Coccidioides, including the relationships between the fungi and the environment, genetics, and clinical observations. Significant questions remain in the field of Coccidioides, including the main host reservoir, the relationships between genotypic and phenotypic variation, and the underlying cause for chronic clinical coccidioidomycosis cases.
ML-based group method of data handling: an improvement on the conventional GMDH
Authors: Amiri Mehdi , Soleimani Seyfollah
Published: July 2021

Machine learning (ML) has been recognized as a feasible and reliable technique for the modeling of multi-parametric datasets. In real applications, there are different relationships with various complexities between sets of inputs and their corresponding outputs. As a result, various models have been developed with different levels of complexity in the input–output relationships. The group method of data handling (GMDH) employs a family of inductive algorithms for computer-based mathematical modeling grounded on a combination of quadratic and higher neurons in a certain number of variable layers. In this method, a vector of input features is mapped to the expected response by creating a multistage nonlinear pattern. Usually, each neuron of the GMDH is considered a quadratic partial function. In this paper, the basic structure of the GMDH technique is adapted by changing the partial functions to enhance the complexity modeling ability. To accomplish this, popular ML models that have shown reasonable function approximation performance, such as support vector regression and random forest, are used, and the basic polynomial functions in the GMDH are replaced by these ML models. The regression feasibility and validity of the ML-based GMDH models are confirmed by computer simulation.
The innovation gender gap in transition countries
Authors: Biscione Antonella , Boccanfuso Dorothée , Caruso Raul , de Felice Annunziata
Published: August 2021

This paper investigates the sources of the possible gender ownership gap in innovativeness in a set of Transition economies by means of firm-level data coming from the Business Environment and Enterprise Performance Survey (BEEPS V) conducted in 2012–2014. Through the Blinder-Oaxaca decomposition we highlight the factors explaining the differences in the propensity to innovate between female-owned and male-owned firms. We find that the innovation disparity between firms with females among their owners and those having only male owners is mainly due to the differences in endowment effects. Tangible and intangible assets affect the innovation gap between the two groups of firms.
Eine Krise in der Krise: Corona-Krisenkommunikation von Bürgermeister*innen in Deutschland
Authors: Habscheid Stephan , Vogel Friedemann
Published: August 2021

Das politische System in Deutschland wird gegenwärtig durch eine zweifache Krise herausgefordert: Zum einen gilt es, die Bedrohung durch die Pandemie und deren gesellschaftliche Folgen durch praktische und kommunikative Maßnahmen zu bewältigen, wobei der Rechtsstaat und das Regierungshandeln in diversen Politikfeldern an ihre Grenzen kommen. Zum anderen stellen bereits seit geraumer Zeit politische Akteure, die für »das Volk« zu sprechen beanspruchen und als »Populisten« bezeichnet werden, in Frage, dass in der etablierten repräsentativen Demokratie eine ausreichende Repräsentation der Bürger bzw. eines völkisch gedachten Kollektivs gewährleistet sei. Von dieser zweifachen Krise, die in öffentlichen Corona-Protesten kulminiert, betroffen sind nicht zuletzt auch Bürgermeister*innen, die – im Idealfall – kommunikativ in verschiedenen Aufgabenfeldern des demokratischen Rechtsstaats agieren. Der Beitrag gibt erste Einblicke in ein Forschungsprojekt, das sich der Kommunikation von, mit und über Bürgermeister*innen systematisch widmet. Exemplarisch untersucht wird im vorliegenden Beitrag erstens, wie Bürgermeister*innen im Kontext der doppelten Krise in Sozialen Medien sprachlich agieren können und welche Anschlusskommunikation mit und unter Bürger*innen sich in den Kommentarlisten entwickelt. Zweitens wird danach gefragt, wie sich das abstrakte Bild der Bürgermeister*innen in der Presseberichterstattung gestaltet und im Zuge der Corona-Krise entwickelt. Zum Zweck des Vergleichs sowie im Hinblick auf Verflechtungen zwischen den beiden Gegenstandsbereichen werden Methoden der linguistischen Praxeologie, der interaktionalen Schriftlinguistik, der Analyse von Textkommunikation und der Korpus- und Imagelinguistik kombiniert.
A proposed method of sample preparation and homogenization of hemp for the molecular analysis of cannabinoids
Authors: Morehouse Zachary P. , Ryan Gabriella L. , Proctor Caleb M. , Okparanta Akelachi , Todd Will , Bunting Derrick , White Taylor , Parez Steven , Miller Blessida , Colon Veronica , Easparro Brandon , Atwood James , Park YoungChul , Nash Rodney J.
Published: July 2021

The use of Cannabis sativa, or Hemp, in commercial, recreational, and pharmacological applications is on the rise in the United States and worldwide. Many of these applications have guidelines associated with them dependent on the concentration of cannabinoid molecules that keep the products classified as hemp versus marijuana or that allow the producer to comment on the purity and potency of their product. Herein, we propose a method for homogenization of hemp that results in small particle sizes, uniform samples, and does not alter the cannabinoid concentrations during processing, allowing for optimal and reproducible potency testing. Using a novel “active grinding media” we homogenized commercially available hemp to analyze approximately 100 mg samples of homogenate via sieve analysis and high-performance liquid chromatography to assess the resulting size and potency of the sample when using this methodology. When processing hemp samples with our proposed methodology, we have demonstrated the ability to produce 60.2% of all particles < 1.25 mm with increased cannabinoid recovery compared to homogenates with larger average particle sizes. Maintaining sample temperatures below 35 °C during processing, we showed that our method does not thermally induce decarboxylation reactions that would result in major cannabinoid profile changes. We have developed a method for hemp processing via homogenization that does not alter the cannabinoid profile during processing, while consistently producing small particle sizes in a uniformly processed sample. This method allows for optimal and reproducible hemp processing when evaluating hemp and hemp-based products being brought to commercial markets.
Terahertz broadband polarization converter based on the double-split ring resonator metasurface
Authors: Xu Zhenhua , Sheng Hongyu , Wang Qiaolian , Zhou Liuping , Shen Yanchun
Published: August 2021

A terahertz broadband polarization converter based on the metasurface of a double-split ring resonator is proposed. The structural parameters of this device have been optimized in numerical simulations. The results show that in the frequency range from 0.49 to 1.88 THz (bandwidth of 1.39 THz) the proposed device rotates incident linearly polarized waves through 90°. The polarization conversion rate is more than 80%. The coefficient of reflection for cross polarization is greater than 90% with a transmission loss of 1 dB. The surface current distribution of this structure was simulated and analyzed at three frequencies that give high conversion rates of the polarization. The mechanism underlying this high conversion rate is presented, and the dependence of the conversion rate on incident angle and polarization angle is stimulated and analyzed. The results show that the conversion performance of this device is good for incidence angles ranging from 0 to 30° and polarization angles ranging from − 10 to 10°. Compared with previous designs, the polarization converter has a simple structure and a broad operational bandwidth. It has potential applications in the field of terahertz polarization modulation.
Cryptocurrency volatility markets
Authors: Woebbeking Fabian
Published: August 2021

By computing a volatility index (CVX) from cryptocurrency option prices, we analyze this market’s expectation of future volatility. Our method addresses the challenging liquidity environment of this young asset class and allows us to extract stable market implied volatilities. Two alternative methods are considered to compute volatilities from granular intra-day cryptocurrency options data, which spans over the COVID-19 pandemic period. CVX data therefore capture ‘normal’ market dynamics as well as distress and recovery periods. The methods yield two cointegrated index series, where the corresponding error correction model can be used as an indicator for market implied tail-risk. Comparing our CVX to existing volatility benchmarks for traditional asset classes, such as VIX (equity) or GVX (gold), confirms that cryptocurrency volatility dynamics are often disconnected from traditional markets, yet, share common shocks.
An inter-disciplinary approach to the energy transition in South Africa
Authors: Todd Iain , McCauley Darren
Published: July 2021

The compelling need to tackle climate change is well-established. It is a challenge which is being faced by all nations. This requires an approach which is truly inter-disciplinary in nature, drawing on the expertise of politicians, social scientists, and technologists. We report how the pace of the energy transition can be influenced significantly by both the operation of societal barriers, and by policy actions aimed at reducing these effects. Using the case study of South Africa, a suite of interviews has been conducted with diverse energy interests, to develop and analyse four key issues pertinent to the energy transition there. We do so primarily through the lens of delivering energy justice to that society. In doing so, we emphasise the need to monitor, model, and modify the dynamic characteristic of the energy transition process and the delivery of energy justice; a static approach which ignores the fluid nature of transition will be insufficient. We conclude that the South African fossil fuel industry is still impeding the development of the country’s renewable resources, and the price of doing so is being met by those living in townships and in rural areas.