bluuebunny/crossref_metadata_2025 huggingface dataset:
Faster and Better: How Anomaly Detection Can Accelerate and Improve Reporting of Head Computed Tomography
Authors: Finck Tom , Moosbauer Julia , Probst Monika , Schlaeger Sarah , Schuberth Madeleine , Schinz David , Yiğitsoy Mehmet , Byas Sebastian , Zimmer Claus , Pfister Franz , Wiestler Benedikt
Published: February 2022

Background: Most artificial intelligence (AI) systems are restricted to solving a pre-defined task, thus limiting their generalizability to unselected datasets. Anomaly detection relieves this shortfall by flagging all pathologies as deviations from a learned norm. Here, we investigate whether diagnostic accuracy and reporting times can be improved by an anomaly detection tool for head computed tomography (CT), tailored to provide patient-level triage and voxel-based highlighting of pathologies. Methods: Four neuroradiologists with 1–10 years of experience each investigated a set of 80 routinely acquired head CTs containing 40 normal scans and 40 scans with common pathologies. In a random order, scans were investigated with and without AI-predictions. A 4-week wash-out period between runs was included to prevent a reminiscence effect. Performance metrics for identifying pathologies, reporting times, and subjectively assessed diagnostic confidence were determined for both runs. Results: AI-support significantly increased the share of correctly classified scans (normal/pathological) from 309/320 scans to 317/320 scans (p = 0.0045), with a corresponding sensitivity, specificity, negative- and positive- predictive value of 100%, 98.1%, 98.2% and 100%, respectively. Further, reporting was significantly accelerated with AI-support, as evidenced by the 15.7% reduction in reporting times (65.1 ± 8.9 s vs. 54.9 ± 7.1 s; p < 0.0001). Diagnostic confidence was similar in both runs. Conclusion: Our study shows that AI-based triage of CTs can improve the diagnostic accuracy and accelerate reporting for experienced and inexperienced radiologists alike. Through ad hoc identification of normal CTs, anomaly detection promises to guide clinicians towards scans requiring urgent attention.
Recovery-Based Error Estimator for Natural Convection Equations Based on Defect-Correction Methods
Authors: Li Lulu , Su Haiyan , Feng Xinlong
Published: February 2022

In this paper, we propose an adaptive defect-correction method for natural convection (NC) equations. A defect-correction method (DCM) is proposed for solving NC equations to overcome the convection dominance problem caused by a high Rayleigh number. To solve the large amount of computation and the discontinuity of the gradient of the numerical solution, we combine a new recovery-type posteriori estimator in view of the gradient recovery and superconvergent theory. The presented reliability and efficiency analysis shows that the true error can be effectively bounded by the recovery-based error estimator. Finally, the stability, accuracy and efficiency of the proposed method are confirmed by several numerical investigations.
Questioning the Science: How Quantitative Methodologies Perpetuate Inequity in Higher Education
Authors: Arellano Lucy
Published: February 2022

Higher education is in a moment of pause, facing an opportunity to transform or continue to perpetuate the status quo. The COVID-19 pandemic, coupled with the recognition of racial violence, has created an opportunity for institutions to question their own policies and practices. The purpose of this inquiry is to question the science behind established statistical practices. Specifically, the question guiding this investigation is: How can higher education quantitative scholars (students and faculty) identify and be critical of statistical practices that perpetuate inequity, forms of oppression, and White supremacy? Using a QuantCrit framework, five examples are presented that illustrate multiple forms of oppression, subjectivity, and bias including: (a) comparing across groups, (b) eliminating outliers, (c) addressing non-response bias, (d) small sample sizes, and (e) theory development. Two recommendations are discussed that could help transform higher educational quantitative research and training into a more inclusive, equitable, and anti-racist educational environment.
Nebula: A Scalable and Flexible Accelerator for DNN Multi-Branch Blocks on Embedded Systems
Authors: Yang Dawei , Li Xinlei , Qi Lizhe , Zhang Wenqiang , Jiang Zhe
Published: February 2022

Deep neural networks (DNNs) are widely used in many artificial intelligence applications; many specialized DNN-inference accelerators have been proposed. However, existing DNN accelerators rely heavily on certain types of DNN operations (such as Conv, FC, and ReLU, etc.), which are either less used or likely to become out of date in future, posing challenges of flexibility and compatibility to existing work. This paper designs a flexible DNN accelerator from a more generic perspective rather than speeding up certain types of DNN operations. Our proposed Nebula exploits the width property of DNNs and gains a significant improvement in system throughput and energy efficiency over multi-branch architectures. Nebula is a first-of-its-kind framework for multi-branch DNNs.
Wireless Electromagnetic Radiation Assessment Based on the Specific Absorption Rate (SAR): A Review Case Study
Authors: Abdul-Al Mohamed , Amar Ahmed S. I. , Elfergani Issa , Littlehales Richard , Ojaroudi Parchin Naser , Al-Yasir Yasir , See Chan Hwang , Zhou Dawei , Zainal Abidin Zuhairiah , Alibakhshikenari Mohammad , Zebiri Chemseddine , Elmegri Fauzi , Abusitta Musa , Ullah Atta , Abdussalam Fathi M. A. , Rodriguez Jonathan , McEwan Neil J. , Noras James M. , Hodgetts Russell , Abd-Alhameed Raed A.
Published: February 2022

Employing electromagnetic fields (EMFs) in new wireless communication and sensing technologies has substantially increased the level of human exposure to EMF waves. This paper presents a useful insight into the interaction of electromagnetic fields with biological media that is defined by the heat generation due to induced currents and dielectric loss. The specific absorption rate (SAR) defines the heating amount in a biological medium that is irradiated by an electromagnetic field value. The paper reviews the radio frequency hazards due to the SAR based on various safety standards and organisations, including a detailed investigation of previously published work in terms of modelling and measurements. It also summarises the most common techniques utilised between 1978 and 2021, in terms of the operational frequency spectrum, bandwidth, and SAR values.
Calculation of Magnetic Flux Density Harmonics in the Vicinity of Overhead Lines
Authors: Mujezinović Adnan , Turajlić Emir , Alihodžić Ajdin , Dedović Maja Muftić , Dautbašić Nedis
Published: February 2022

This paper considers the method for the calculation of magnetic flux density in the vicinity of overhead distribution lines which takes into account the higher current harmonics. This method is based on the Biot–Savart law and the complex image method. The considered method calculates the values of the magnetic flux density for each harmonic component of the current separately at all points of interest (usually lateral profile). In this way, it is possible to determine the contributions of individual harmonic components of the current intensity to the total value of magnetic flux density. Based on the contributions of individual harmonic components, the total (resultant) value of the magnetic flux density at points of interest is determined. Validation of the computational method is carried out by comparison of the results obtained by the considered calculation method with measurement results. Furthermore, the application of the calculation method was demonstrated by calculating magnetic flux density harmonics in the vicinity of two overhead distribution lines of typical phase conductor arrangements.
DeepKnuckle: Deep Learning for Finger Knuckle Print Recognition
Authors: Tarawneh Ahmad S. , Hassanat Ahmad B. , Alkafaween Esra’a , Sarayrah Bayan , Mnasri Sami , Altarawneh Ghada A. , Alrashidi Malek , Alghamdi Mansoor , Almuhaimeed Abdullah
Published: February 2022

Biometric technology has received a lot of attention in recent years. One of the most prevalent biometric traits is the finger-knuckle print (FKP). Because the dorsal region of the finger is not exposed to surfaces, FKP would be a dependable and trustworthy biometric. We provide an FKP framework that uses the VGG-19 deep learning model to extract deep features from FKP images in this paper. The deep features are collected from the VGG-19 model’s fully connected layer 6 (F6) and fully connected layer 7 (F7). After applying multiple preprocessing steps, such as combining features from different layers and performing dimensionality reduction using principal component analysis (PCA), the extracted deep features are put to the test. The proposed system’s performance is assessed using experiments on the Delhi Finger Knuckle Dataset employing a variety of common classifiers. The best identification result was obtained when the Artificial neural network (ANN) classifier was applied to the principal components of the averaged feature vector of F6 and F7 deep features, with 95% of the data variance preserved. The findings also demonstrate the feasibility of employing these deep features in an FKP recognition system.
Biochar Rescues Native Trees in the Biodiversity Hotspot of Mauritius
Authors: Sujeeun Leeladarshini , Thomas Sean C.
Published: February 2022

Many tropical invasive species have allelopathic effects that contribute to their success in native plant communities. Pyrolyzed biomass (“biochar”) can sorb toxic compounds, including allelochemicals produced by invasive plants, potentially reducing their inhibitory effects on native species. Strawberry guava (Psidium cattleianum) is among the most important allelopathic invasive species on tropical islands and recognized as the most serious threat among invasive species in the global biodiversity hotspot of Mauritius. We investigated the effects of additions of locally produced biochar on native tree species in a field experiment conducted in areas invaded by strawberry guava within Mauritius’ largest national park. Growth and survivorship of native tree species were monitored over 2.5 years in plots subjected to four treatments: non-weeded, weeded, weeded + 25 t/ha biochar, and weeded + 50 t/ha biochar. Native tree growth and survivorship were strongly suppressed by strawberry guava. Biochar treatments dramatically increased native tree performance, with more than a doubling in growth, and substantially increased native tree survivorship and species diversity, while suppressing strawberry guava regeneration, consistent with growth-promoting properties and sorption of allelochemicals. We conclude that biochars, including “sustainable biochars” produced from locally accessible biomass using low-tech pyrolysis systems, have considerable potential to counteract effects of allelopathic invaders and increase the capacity for native species regeneration in tropical island ecosystems.
Dateless Dendroarchaeology
Authors: Towner Ronald H.
Published: February 2022

The strength of dendrochronology is chronology. No other non-textual dating technique in the world provides the precision, accuracy, and resolution of dendrochronology. Indeed, dendrochronology is famous for dating prehistoric ruins, and Douglass’ “Bridging the Gap” is still considered one of the greatest achievements in archaeology anywhere, but what happens when samples don’t date? Should they simply be discarded as useless, stored until better chronologies and new techniques are available, or do they contain useful information for current research interests? Using undated collections from the southwestern US and northwestern Mexico, this paper discusses a variety of behavioral and environmental information present in samples, even if they cannot contribute to our chronological knowledge.
The siRNA Off-Target Effect Is Determined by Base-Pairing Stabilities of Two Different Regions with Opposite Effects
Authors: Kobayashi Yoshiaki , Tian Shen , Ui-Tei Kumiko
Published: February 2022

In RNA interference (RNAi), small interfering RNA (siRNA) suppresses the expression of its target mRNA with a perfect complementary sequence. In addition, siRNA also suppresses the expression of unintended mRNAs with partially complementary sequences mainly within the siRNA seed region (nucleotides 2–8). This mechanism is highly similar to microRNA (miRNA)-mediated RNA silencing, and known as the siRNA-mediated off-target effect. Previously, we revealed that the off-target effect is induced through stable base-pairing between the siRNA seed region and off-target mRNAs, but not induced through unstable base-pairing. However, in our recent study, we found that the siRNA seed region consists of two functionally different domains: nucleotides 2–5, essential for off-target effects, and nucleotides 6–8, involved in both RNAi and off-target effects. In this study, we investigated the most responsible region for the off-target effect by conducting a comprehensive analysis of the thermodynamic properties of all possible siRNA subregions that involved a machine learning technique using a random sampling procedure. As a result, the thermodynamic stability of nucleotides 2–5 showed the highest positive correlation with the off-target effect, and nucleotides 8–14 showed the most negative correlation. Thus, it is revealed that the siRNA off-target effect is determined by the base-pairing stabilities of two different subregions with opposite effects.
Pancreatic Cancer with Mutation in BRCA1/2, MLH1, and APC Genes: Phenotype Correlation and Detection of a Novel Germline BRCA2 Mutation
Authors: Vietri Maria Teresa , D’Elia Giovanna , Caliendo Gemma , Albanese Luisa , Signoriello Giuseppe , Napoli Claudio , Molinari Anna Maria
Published: February 2022

Pancreatic ductal adenocarcinoma (PDAC) is the seventh leading cause of cancer death worldwide; most of cases are sporadic, however about 5% to 10% report a hereditary predisposition. Several hereditary syndromes have been associated with familial pancreatic cancer (FPC) onset, including hereditary breast and ovarian cancer syndrome (HBOC), Lynch syndrome (LS), Familial atypical multiple mole melanoma (FAMMM), Familial adenomatous polyposis (FAP), Li–Fraumeni syndrome (LFS), Peutz–Jeghers syndrome (PJS), and Hereditary pancreatitis (HP).The aim of this study was to determine the mutational status of a cohort of 56 HBOC families, 7 LS families, 3 FAP and FAMMM families, and 1 LFS family with at least one case of PDAC. Mutation analysis of BRCA1/2, ATM, CHEK2, PALB2, RAD51C, RAD51D, NBN, CDH1, TP53, MLH1, MSH2, MSH6, and PMS2 genes, showedmutation in BRCA1/2, MLH1, and APC genes. We founda high mutation rate in patients belong HBOC and LS families, with a percentage of 28.6% in both syndromes and prevalence in HBOC of BRCA2 mutations with one case of double mutation in BRCA2 gene. In FAP family, we found a pathogenic mutation in APC gene in 1/3 families. We observed an early onset of PDAC and a lower survival in PDAC patients belonging to mutated families, while no evidence of possible pancreatic cancer cluster regions was found. Moreover, we identified a novel BRCA2 germline mutation, c.5511delT (p.Phe1837LeufsX3), not reported in any database, that segregated with disease in HBOC patients. Mutational analysis was extended to family membersof mutated patients, both healthy and cancer affected, which revealed 23 unaffected family members that inherited the proband’s mutation. Although correlative by its nature, the presence of a BRCA mutation in PDAC patients may have benefits in terms of optimized treatment and longer outcome.
Machine Learning for Screening Microvascular Complications in Type 2 Diabetic Patients Using Demographic, Clinical, and Laboratory Profiles
Authors: Rashid Mamunur , Alkhodari Mohanad , Mukit Abdul , Ahmed Khawza Iftekhar Uddin , Mostafa Raqibul , Parveen Sharmin , Khandoker Ahsan H.
Published: February 2022

Microvascular complications are one of the key causes of mortality among type 2 diabetic patients. This study was sought to investigate the use of a novel machine learning approach for predicting these complications using only the patient demographic, clinical, and laboratory profiles. A total of 96 Bangladeshi participants with type 2 diabetes were recruited during their routine hospital visits. All patient profiles were assessed by using a chi-squared (χ2) test to statistically determine the most important markers in predicting three microvascular complications: cardiac autonomic neuropathy (CAN), diabetic peripheral neuropathy (DPN), and diabetic retinopathy (RET). A machine learning approach based on logistic regression, random forest (RF), and support vector machine (SVM) algorithms was then developed to ensure automated clinical testing for microvascular complications in diabetic patients. The highest prediction accuracies were obtained by RF using diastolic blood pressure, albumin–creatinine ratio, and gender for CAN testing (98.67%); microalbuminuria, smoking history, and hemoglobin A1C for DPN testing (67.78%); and hemoglobin A1C, microalbuminuria, and smoking history for RET testing (84.38%). This study suggests machine learning as a promising automated tool for predicting microvascular complications in diabetic patients using their profiles, which could help prevent those patients from further microvascular complications leading to early death.
Conditioning Regimens in Patients with β-Thalassemia Who Underwent Hematopoietic Stem Cell Transplantation: A Scoping Review
Authors: Mulas Olga , Mola Brunella , Caocci Giovanni , La Nasa Giorgio
Published: February 2022

The success of transplant procedures in patients with beta-thalassemia major (β-thalassemia) goes hand-in-hand with improvements in disease knowledge, better supportive care, discoveries in immunogenetics, increase in stem cell sources, and enhancement of conditioning regimens. The aim of this scoping review was to report the evolution of conditioning regimes for β-thalassemia hematopoietic stem cell transplantation. We performed a systematic search for all relevant articles published before July 2021, using the following Medical Subject Headings: “bone marrow transplantation”, “stem cell transplantation”, “allogeneic”, “thalassemia”, “β-thalassemia”, and “thalassemia major”. The final analysis included 52 studies, published between 1988 and 2021, out of 3877 records. The most common conditioning regimen was a combination of busulfan and cyclophosphamide, with successive dose adjustments or remodulation based on patient characteristics. Pre-transplant treatments, reductions in cyclophosphamide dosage, or the adoption of novel agents such as treosulphan all improved overall survival and thalassemia-free survival in transplant-related mortality high-risk patients. Conditioning regimes were modulated for those without a suitable fully matched sibling or unrelated donor, with encouraging results. Hematopoietic stem cell transplantation with haploidentical donors is currently available to virtually all patients with β-thalassemia. However, disparities in outcome are still present around the world. In developing and limited-resource countries, where most diagnoses are focused, transplants are not always available. Therefore, more efforts are needed to close this treatment gap.
Symptomatic Young Adults with ST-Segment Elevation—Acute Coronary Syndrome or Myocarditis: The Three-Factor Diagnostic Model
Authors: Wieczorkiewicz Paulina , Przybylak Katarzyna , Supel Karolina , Kidawa Michal , Zielinska Marzenna
Published: February 2022

Myocarditis may mimic myocardial infarction (MI) due to a similar clinical presentation, including chest pain, electrocardiography changes, and laboratory findings. The purpose of the study was to investigate the diagnostic value of clinical, laboratory, and electrocardiography characteristics of patients with acute coronary syndrome - like myocarditis and MI. We analysed 90 patients (≤45 years old) with an initial diagnosis of ST-segment elevation myocardial infarction; 40 patients (44.4%), through the use of cardiac magnetic resonance, were confirmed to have myocarditis, and 50 patients (55.6%) were diagnosed with MI. Patients with myocarditis were younger and had fewer cardiovascular risk factors than those with MI. The cutoff value distinguishing between myocarditis and MI was defined as the age of 36 years. The history of recent infections (82.5% vs. 6%) and C-reactive protein (CRP) levels on admission (Me 45.9 vs. 3.4) was more associated with myocarditis. Further, the QTc interval was inversely correlated with the echocardiographic ejection fraction in both groups but was significantly longer in patients with MI. Non-invasive diagnostics based on clinical features and laboratory findings are basic but still essential tools for differentiation between MI and myocarditis. The three-factor model including the criteria of age, abnormal CRP, and history of recent infections might become a valuable clinical indication.
A Selective Histamine H4 Receptor Antagonist, JNJ7777120, Role on glutamate Transporter Activity in Chronic Depression
Authors: Yeni Yesim , Cakir Zeynep , Hacimuftuoglu Ahmet , Taghizadehghalehjoughi Ali , Okkay Ufuk , Genc Sidika , Yildirim Serkan , Saglam Yavuz Selim , Calina Daniela , Tsatsakis Aristidis , Docea Anca Oana
Published: February 2022

Glutamate release and reuptake play a key role in the pathophysiology of depression. glutamatergic nerves in the hippocampus region are modulated by histaminergic afferents. Excessive accumulation of glutamate in the synaptic area causes degeneration of neuron cells. The H4 receptor is defined as the main immune system histamine receptor with a pro-inflammatory role. To understand the role of this receptor, the drug JNJ7777120 was used to reveal the chronic depression-glutamate relationship. We have important findings showing that the H4 antagonist increases the glutamate transporters’ instantaneous activity. In our experiment, it has been shown that blocking the H4 receptor leads to increased neuron cell viability and improvement in behavioral ability due to glutamate. Therefore, JNJ can be used to prevent neurotoxicity, inhibit membrane phospholipase activation and free radical formation, and minimize membrane disruption. In line with our findings, results have been obtained that indicate that JNJ will contribute to the effective prevention and treatment of depression.
IL4Rα and IL13Rα1 Are Involved in the Development of Human Gallbladder Cancer
Authors: Ahn Sung Woo , Lee Chang Min , Kang Mi-Ae , Hussein Usama Khamis , Park Ho Sung , Ahn Ae-Ri , Yu Hee Chul , Yang Jae Do , Yang Yung-Hun , Park Kyungmoon , Lee Jongsung , Jang Kyu Yun , Park See-Hyoung
Published: February 2022

Background: Gallbladder cancer is commonly associated with inflammation, which indicates that inflammation-related cytokines and cytokine receptors are related to the progression of gallbladder cancers. Interleukin 4 (IL4) is a well-known cytokine that promotes the differentiation of naive helper T cells (Th0) to T helper type 2 cells (Th2). IL13 is a cytokine that is secreted by Th2 cells. IL4 and IL13 are closely related in immune responses. However, the role of IL4Rα and IL13Rα1 signaling pathway has not been fully understood in the development of gallbladder cancer. Methods: In human gallbladder carcinomas, the expression of IL4Rα and IL13Rα1 were evaluated with immunohistochemical staining in tissue microarray tissue sections. After knockdown of IL4Rα or IL13Rα1, cell assays to measure the proliferation and apoptosis and Western blotting analysis were conducted in SNU308 human gallbladder cancer cells. Since Janus kinases2 (JAK2) was considered as one of the down-stream kinases under IL4Rα and IL13Rα1 complex, the same kinds of experiments were performed in SNU308 cells treated with AZD1480, Janus-associated kinases2 (JAK2) inhibitor, to demonstrate the cytotoxic effect of AZD1480 in SNU308 cells. Results: Immunohistochemical expression of IL4Rα was significantly associated with the expression of IL13Rα1 in human carcinoma tissue. In univariate analysis, nuclear expression of IL4Rα, cytoplasmic expression of IL4Rα, nuclear expression of IL13Rα1, and cytoplasmic expression of IL13Rα1 were significantly associated with shorter overall survival and shorter relapse-free survival. Multivariate analysis revealed nuclear expression of IL4Rα as an independent poor prognostic indicator of overall survival and relapse-free survival. Then, we found that knockdown of IL4Rα or IL13Rα1 decreased viability and induced apoptosis in SNU308 cells via activation of FOXO3 and similarly, AZD1480 decreased viability and induced apoptosis in SNU308 cells with dose dependent manner. Conclusions: Taken together, our results suggest that IL4Rα and IL13Rα1 might be involved in the development of human gallbladder cancer cells and IL4Rα and IL13Rα1 complex/JAK2 signaling pathway could be efficient therapeutic targets for gallbladder cancer treatment.
Polymorphisms in DNA Repair and Xenobiotic Biotransformation Enzyme Genes and Lung Cancer Risk in Coal Mine Workers
Authors: Minina Varvara , Timofeeva Anna , Torgunakova Anastasya , Soboleva Olga , Bakanova Marina , Savchenko Yana , Voronina Elena , Glushkov Andrey , Prosekov Alexander , Fucic Aleksandra
Published: February 2022

Background: Currently coal mining employs over 7 million miners globally. This occupational setting is associated with exposure to dust particles, heavy metals, polycyclic aromatic hydrocarbons and radioactive radon, significantly increasing the risk of lung cancer (LC). The susceptibility for LC is modified by genetic variations in xenobiotic detoxification and DNA repair capacity. The aim of this study was to investigate the association between GSTM1 (deletion), APEX1 (rs1130409), XPD (rs13181) and NBS1 (rs1805794) gene polymorphisms and LC risk in patients who worked in coal mines. Methods: The study included 639 residents of the coal region of Western Siberia (Kemerovo region, Russia): 395 underground miners and 244 healthy men who do not work in industrial enterprises. Genotyping was performed using real-time and allele-specific PCR. Results: The results show that polymorphisms of APEX1 (recessive model: ORadj = 1.87; CI 95%: 1.01–3.48) and XPD (log additive model: ORadj = 2.25; CI 95%: 1.59–3.19) genes were associated with increased LC risk. GSTM1 large deletion l was linked with decreased risk of LC formation (ORadj = 0.59, CI 95%: 0.36–0.98). The multifactor dimensionality reduction method for 3-loci model of gene–gene interactions showed that the GSTM1 (large deletion)—APEX1 (rs1130409)—XPD (rs13181) model was related with a risk of LC development. Conclusions: The results of this study highlight an association between gene polymorphism combinations and LC risks in coal mine workers.
Promoting Exercise Training Remotely
Authors: Robinson Stephanie A. , Moy Marilyn L.
Published: February 2022

There has been increased incentivization to develop remote exercise training programs for those living with chronic respiratory diseases, such as chronic obstructive pulmonary disease (COPD). Remote programs offer patients an opportunity to overcome barriers to accessing traditional in-person programs, such as pulmonary rehabilitation (PR). Methods to deliver exercise training remotely range in complexity and types of technological modalities, including phone calls, real-time video conferencing, web- and app-based platforms, video games, and virtual reality (VR). There are a number of studies demonstrating the effectiveness of these programs on exercise capacity, dyspnea, and health-related quality of life (HRQL). However, there is great variation in these programs, making it difficult to assess findings across studies. Other aspects that contribute to the effectiveness of these programs include stakeholder perceptions, such as motivation and willingness to engage, and adherence. Finally, while the intent of these remote programs is to overcome barriers to access, they may inadvertently exacerbate access disparities. Future program development efforts should focus on standardizing how remote exercise training is delivered, engaging stakeholders early on to develop patient-centered programs that patients will want to use, and understanding the heterogeneous preferences and needs of those living with chronic respiratory disease in order to facilitate engagement with these programs.
Hitting Distribution of a Correlated Planar Brownian Motion in a Disk
Authors: Marchione Manfred Marvin , Orsingher Enzo
Published: February 2022

In this article, we study the hitting probability of a circumference CR for a correlated Brownian motion B̲(t)=B1(t),B2(t), ρ being the correlation coefficient. The analysis starts by first mapping the circle CR into an ellipse E with semiaxes depending on ρ and transforming the differential operator governing the hitting distribution into the classical Laplace operator. By means of two different approaches (one obtained by applying elliptic coordinates) we obtain the desired distribution as a series of Poisson kernels.
Recent Advances in Mixed-Matrix Membranes for Light Hydrocarbon (C1–C3) Separation
Authors: Chuah Chong Yang , Bae Tae-Hyun
Published: February 2022

Light hydrocarbons, obtained through the petroleum refining process, are used in numerous applications. The separation of the various light hydrocarbons is challenging and expensive due to their similar melting and boiling points. Alternative methods have been investigated to supplement cryogenic distillation, which is energy intensive. Membrane technology, on the other hand, can be an attractive alternative in light hydrocarbon separation as a phase change that is known to be energy-intensive is not required during the separation. In this regard, this study focuses on recent advances in mixed-matrix membranes (MMMs) for light hydrocarbon (C1–C3) separation based on gas permeability and selectivity. Moreover, the future research and development direction of MMMs in light hydrocarbon separation is discussed, considering the low intrinsic gas permeability of polymeric membranes.
Mechanical Behavior of Fe- and Co-Based Amorphous Alloys after Thermal Action
Authors: Permyakova Inga , Glezer Alex
Published: February 2022

The effect of heat treatment on the structure and mechanical properties of Co-Fe-Cr-Si-B/Fe-Cr-B/Fe-Ni-B amorphous alloys has been studied systematically. Melt-quenching (spinning method) was used for production of investigated amorphous alloys. The transmission electron microscopy (TEM) was used to study the structure transformations. The effect of temperature on deformation behavior (plasticity, microhardness, crack resistance, and the density and average length of shear bands) of the amorphous alloys was studied by bending and microindentation. It is shown that the ductile–brittle transition, which occurs at the stage of structure relaxation in amorphous alloys, is caused by two factors: a decrease in the susceptibility of the amorphous matrix to plastic flow and an abrupt decrease in the resistance to the development of quasibrittle cracks. It is established that the transition to a two-phase amorphous–nanocrystalline state upon annealing leads to substantial strengthening of the alloys and a partial recovery of their plasticity. It is proved that the strengthening of amorphous alloys at the initial stages of crystallization can be initiated by the difference in the elastic moduli of the amorphous matrix and the precipitated nanocrystals, as well as by the specific features of the interaction between nanocrystalline phase particles and shear bands propagating under external actions. It is established that the phenomenon of plasticization in amorphous alloys (the crack resistance can increase after annealing in a certain temperature range) is due to the effective retardation of cracks on nanoparticles.
Machining Stability Categorization and Prediction Using Process Model Guided Machine Learning
Authors: Ko Jeong Hoon
Published: February 2022

The time-domain dynamic process model is used to generate data and guides the stability criteria for machine learning, saving the experimental costs for a number of required data for the metal process. Fourier transformation of vibration data simulated using a dynamic process model generates the feature lists including multiple frequencies and amplitudes at each process condition. The feature lists for milling stability are analyzed for training the machine learning algorithm. The amplitude and frequency distributions may change according to the dynamic pattern of the machining stability. The vibration patterns are grouped into stable, chatter, and boundary conditions by performing data training using support vector machines and gradient tree boosting. In the high-speed milling of Al6061-T6 with 6000 to 18,000 RPM and variations of axial and radial depths of cuts, 2400 data sets of the time domain data were trained and tested. Actual experimental tests are carried out for new process conditions with the range of 9890 to 28,470 RPM and 989 to 2847 mm/min. The experimental stability outcomes are compared with predictions from the algorithms. Stability is accurately predicted over new conditions with around 0.9 prediction accuracy, which means the methodology can be used to predict, categorize, and monitor stability in end milling processes.
Correction: Zheng et al. Correlating Prior Austenite Grain Microstructure, Microscale Deformation and Fracture of Ultra-High Strength Martensitic Steels. Metals 2021, 11, 1013
Authors: Zheng Xinzhu , Ghassemi-Armaki Hassan , Hartwig Karl T. , Srivastava Ankit
Published: February 2022

In the original article [...]
Systematic Evaluation of HILIC Stationary Phases for Global Metabolomics of Human Plasma
Authors: Hosseinkhani Farideh , Huang Luojiao , Dubbelman Anne-Charlotte , Guled Faisa , Harms Amy C. , Hankemeier Thomas
Published: February 2022

Polar hydrophilic metabolites have been identified as important actors in many biochemical pathways. Despite continuous improvement and refinement of hydrophilic interaction liquid chromatography (HILIC) platforms, its application in global polar metabolomics has been underutilized. In this study, we aimed to systematically evaluate polar stationary phases for untargeted metabolomics by using HILIC columns (neutral and zwitterionic) that have been exploited widely in targeted approaches. To do so, high-resolution mass spectrometry was applied to thoroughly investigate selectivity, repeatability and matrix effect at three pH conditions for 9 classes of polar compounds using 54 authentic standards and plasma matrix. The column performance for utilization in untargeted metabolomics was assessed using plasma samples with diverse phenotypes. Our results indicate that the ZIC-c HILIC column operated at neutral pH exhibited several advantages, including superior performance for different classes of compounds, better isomer separation, repeatability and high metabolic coverage. Regardless of the column type, the retention of inorganic ions in plasma leads to extensive adduct formation and co-elution with analytes, which results in ion-suppression as part of the overall plasma matrix effect. In ZIC-c HILIC, the sodium chloride ion effect was particularly observed for amino acids and amine classes. Successful performance of HILIC for separation of plasma samples with different phenotypes highlights this mode of separation as a valuable approach in global profiling of plasma sample and discovering the metabolic changes associated with health and disease.
3D Bioprinting of an In Vitro Model of a Biomimetic Urinary Bladder with a Contract-Release System
Authors: Chae Suhun , Kim Jaewook , Yi Hee-Gyeong , Cho Dong-Woo
Published: February 2022

The development of curative therapy for bladder dysfunction is usually hampered owing to the lack of reliable ex vivo human models that can mimic the complexity of the human bladder. To overcome this issue, 3D in vitro model systems offering unique opportunities to engineer realistic human tissues/organs have been developed. However, existing in vitro models still cannot entirely reflect the key structural and physiological characteristics of the native human bladder. In this study, we propose an in vitro model of the urinary bladder that can create 3D biomimetic tissue structures and dynamic microenvironments to replicate the smooth muscle functions of an actual human urinary bladder. In other words, the proposed biomimetic model system, developed using a 3D bioprinting approach, can recreate the physiological motion of the urinary bladder by incorporating decellularized extracellular matrix from the bladder tissue and introducing cyclic mechanical stimuli. The results showed that the developed bladder tissue models exhibited high cell viability and proliferation rate and promoted myogenic differentiation potential given dynamic mechanical cues. We envision the developed in vitro bladder mimicry model can serve as a research platform for fundamental studies on human disease modeling and pharmaceutical testing.
Suppressive Effect of Bioactive Extracts of Bacillus sp. H8-1 and Bacillus sp. K203 on Tomato Wilt Caused by Clavibacter michiganensis subsp. michiganensis
Authors: Jang Hwajin , Kim Sang Tae , Sang Mee Kyung
Published: February 2022

Tomatoes are cultivated worldwide, and are economically important. Clavibacter michiganensis subsp. michiganensis (Cmm) is a pathogen that causes canker and wilting in tomatoes, resulting in serious damage to tomato plants. We aimed to control Cmm proliferation using substances produced by useful microorganisms. The water extracts of strains H8-1 and K203 inhibited wilting caused by Cmm and slowed the pathogenic colonization in tomato plants. The relative expressions of celA, celB, pat1, and pelA of Cmm treated with the bacterial water extracts were reduced by 0.41-, 0.01-, 0.15-, and 0.14-fold for H8-1, respectively, and 0.45-, 0.02-, 0.13-, and 0.13-fold for K203, respectively, compared to controls at 72 h after treatments. In tomato plants inoculated with Cmm, when water extracts of H8-1 and K203 were treated, relative expression of ACO encoding 1-aminocyclopropane-1-carboxylic acid oxidase was suppressed by 0.26- and 0.23-fold, respectively, while PR1a was increased by 1.94- and 2.94-fold, respectively; PI2 expression was increased by 3.27-fold in water extract of H8-1-treated plants. As antioxidant enzymes of plants inoculated with Cmm, peroxidase and glutathione peroxidase levels were increased in K203-water-extract-treated plants, and catalase was increased in the case of the H8-1 water extract at 10 days after inoculation. In terms of soil enzyme activity, each water extract tended to increase urease activity and microbial diversity; in addition, K203 water extract increased plant growth. Thus, H8-1 and K203 water extracts can be used as potential biocontrol agents against Cmm.
Comparison and Mechanism Analysis of Three-Phase Contact Formation onto Hydrophilic/Hydrophobic Mineral Surfaces in the Presence of Cationic/Anionic Surfactants during Flotation Process
Authors: Li Xianyuan , Gao Ya , Li Mei , Jiang Hao , Xie Jiahui , Xiang Guoyuan
Published: February 2022

This article presents the dynamic process of the three-phase contact (TPC) formation by colliding bubbles onto muscovite and talc surfaces in water and two types of solutions including cationic CTAC surfactant (cetyltrimethyl ammoniumchloride) and anionic NaOL surfactant (sodium oleate). The TPC formation process was observed through the high-speed camera between bubbles and layered silicate minerals (hydrophilic muscovite and hydrophobic talc). It was found that the rupture of the liquid film between the bubbles and the mineral surface is a prerequisite for TPC formation. In the case of muscovite, TPC was formed only with cationic CTAC, and as the surfactant concentration increased, the time needed for TPC formation was shortened. Due to electrostatic repulsion, TPC did not occur in water and NaOL. However, for talc, TPC occurred both in water and in surfactant solutions. In contrast to muscovite, the time of TPC formation on the talc surface was prolonged with the increase in the surfactant concentration. It was concluded that hydrophobic attraction and electrostatic attraction between mineral surfaces and bubbles can significantly promote the localized foam film rupture, which was the main reason for the TPC appearance in water and surfactants. For the hydrophilic muscovite, CTAC adsorption improved the surface hydrophobicity; I3/I1 in fluorescence spectroscopy increased, and the micro-polarity faded, making TPC formation need more time. However, for the natural hydrophobic talc, the increasing surfactant adsorption decreased I3/I1 values and enhanced the local micro-polarity, causing the extension of time for TPC. Therefore, TPC formation for different minerals resulted from different reasons.
Flocculation and Settlement Characteristics of Ultrafine Tailings and Microscopic Characteristics of Flocs
Authors: Han Chongchong , Tan Yuye , Chu Lishen , Song Weidong , Yu Xin
Published: February 2022

Aiming to solve the problems related to the slow settling speed and the long-term consumption of ultra-fine tailings in mine filling, the effect of flocculant type on the flocculation and settling performance of ultra-fine tailings was studied through static sedimentation experiments on tailings. The microstructure of the flocculation was observed and analyzed using an electron microscope. On this basis, the selection of the optimum flocculant type and dosage parameters was carried out. The results show that the best addition amount of the AZ9020 anionic flocculant was 30 g/t, a solution concentration of 0.3%, and a stirring time of more than 45 min. The floc structure of the full-tailings flocculation solution was formed by the AZ9020 anionic flocculant. Moreover, the size of less than 0.1 μm was still relatively large; thus, the overall size of the structure was small and uniformly dispersed. The floc solution had the smallest porosity, the fractal dimension was the largest, the molecular weight of the floc was the largest, and the floc was the most compact, making it appropriate for the rapid removal of floc structures from water. Sedimentation is also the best flocculant for flocculation and sedimentation. The size of the flocs decreased as the height of the flocculation sediment bed increased during flocculation and sedimentation. The research results provide a microscopic view for the selection of the best flocculant type.
Does Soil Drying in a Lab Affect Arsenic Speciation in Strongly Contaminated Soils?
Authors: Karczewska Anna , Dradrach Agnieszka , Gałka Bernard , Szopka Katarzyna
Published: February 2022

This study examined the changes in extractability and fractionation of arsenic (As) that can be caused by the drying of strongly polluted anoxic soil samples. Two untreated and manure-amended soils were incubated for 7 and 21 days in flooded conditions. Thereafter, As water- and 1 M NH4NO3-extractability and As fractionation in a 5-step sequential extraction according to Wenzel were examined in fresh, oven-dried and air-dried samples. Soil treatment with manure considerably affected the results of the sequential extraction. Air-drying caused a significant decrease in As extractability with 1 M NH4NO3 and in As concentrations in the F1 fraction. The highest reduction of extractability (30–41%) was found in manure-treated soils. Oven-drying resulted in a smaller reduction (5–34%) of As extractability. These effects were explained by opposing processes of As mobilization and immobilization. Sequential extraction did not allow for balancing As redistribution due to drying, as As loss from the F1 fraction was smaller than the confidence intervals in the other fractions. The results showed that for the precise determination of As extractability in anoxic soils, fresh samples should be analyzed. However, oven-dried samples may be used for a rough assessment of environmental risk, As the order of magnitude of easily soluble As did not change due to drying.
Rheological Properties of Engine Oil with Nano-Additives Based on MoS2 Materials
Authors: Makowski Łukasz , Bojarska Zuzanna , Rożeń Antoni
Published: February 2022

To enhance oil’s tribological and rheological properties, various nano-additives are used. An example of such a nano-additive is nanosized molybdenum disulfide (MoS2). Due to its unique properties, MoS2-based materials used as lubricants have attracted significant attention. In our previous work, we developed a novel, scalable, and low-cost method for MoS2-based materials production using an impinging jet reactor. Hybrid nanostructures based on MoS2 and carbon nanomaterials (MoS2/CNMs) decreased the friction factor of the base oil. In the present study, a mathematical model that accounts for the viscous heating effects in rheograms was formulated. The model was used to interpret the results of rheological measurements conducted for the base oil 10W40 and its mixtures with different nanosized lubricant additives. The model of the non-isothermal Couette flow allowed us to correct the rheograms of the engine oils in the region of high shear rates where viscous heating effects become significant. The temperature correlations for the consistency and flow behavior indexes were proposed. The nanohybrid suspensions of MoS2 in the base oil were found to have the lowest apparent viscosity at low temperatures, typical for the cold engine startup.
Fabrication and Integration of Functionalized N-rGO-Ni/Ag and N-rGO-Ni/Co Nanocomposites as Synergistic Oxygen Electrocatalysts in Fuel Cells
Authors: Arif Muhammad , Bilal Salma , Shah Anwar ul Haq Ali
Published: February 2022

Fabrication of composites by developing simple techniques can be an efficient way to modify the desire properties of the materials. This paper presents a detailed study on synthesis of low cost and efficient nitrogen doped reduced graphene oxide nickle-silver (N-rGO-Ni/Ag) and nickel-cobalt (N-rGO-Ni/Co) nanocomposites as electrocatalysts in fuel cell using one-pot blended reflux condensation route. An admirable correlation in the structures and properties of the synthesized nanocomposites was observed. The Oxygen Reduction Reaction (ORR) values for N-rGO-Ni/Ag and N-rGO-Ni/Co calculated from the onset potential, using Linear Sweep Voltammetry (LSV), were found to be 1.096 and 1.146. While the half wave potential were determined to be 1.046 and 1.106, respectively, N-rGO-Ni/Ag and N-rGO-Ni/Co. The Tafel and bi-functional (ORR/OER) values were calculated as 76 and 35 mV/decade and 1.23 and 1.12 V, respectively, for N-rGO-Ni/Ag and N-rGO-Ni/Co. The lower onset and half wave potential, low charge transfer resistance (Rct = 1.20 Ω/cm2) and internal solution resistance (Rs = 8.84 × 10−1 Ω/cm2), lower Tafel values (35 mV), satisfactory LSV measurements and mass activity (24.5 at 1.056 V for ORR and 54.9 at 1.056 for OER) demonstrate the remarkable electrocatalytic activity of N-rGO-Ni/Co for both ORR and OER. The chronamperometric stability for synthesized nanocomposites was found satisfactory up to 10 h.