bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Goethite Nanorods on Structural Changes and Transitions in Nematic Liquid Crystal E7
Authors: Bury Peter , Veveričík Marek , Černobila František , Tomašovičová Natália , Timko Milan , Kopčanský Peter , Agresti Filippo , Barison Simona
Published: January 2023

A composite ferronematic system based on the nematic liquid crystal E7, doped with lath-like goethite magnetic nanoparticles of volume concentrations 10−3, 5 × 10−4, and 10−5, was investigated. Both surface acoustic waves (SAWs) and the magneto-optical effect were used to study the influence of magnetic nanoparticles on ferronematic liquid crystals’ structural changes, focused above all on structural transitions. The responses of SAW attenuation and light transmission to external magnetic fields were investigated experimentally under linearly increasing/decreasing or jumped (time influence) magnetic fields, respectively. An investigation of temperature on structural changes was performed, as well. The experimental results validated the decrease in the threshold field of the ferronematic composites in comparison with the pure E7, as well as an increase in the transition temperature with the increasing volume fraction of nanoparticles. The effect of the nanoparticles’ concentration on both total structural changes and residual attenuations at the vanishing magnetic field was also registered. The light transmission measurements confirmed the effect of the concentration of goethite nanoparticles on the resultant magneto-optical behavior, concerning both its stability and switching time.
Fabrication of Effective Co-SnO2/SGCN Photocatalysts for the Removal of Organic Pollutants and Pathogen Inactivation
Authors: Javed Mohsin , Iqbal Sana , Qamar Muhammad Azam , Shariq Mohammad , Ahmed Inas A. , BaQais Amal , Alzahrani Hanan , Ali Syed Kashif , Masmali N. A. , Althagafi Talal M. , Shakir Khan Mohd.
Published: January 2023

Substantial improvement is needed in efficient and affordable decolorization and disinfection methods to solve the issues caused by dyes and harmful bacteria in water and wastewater. This work involves the photocatalytic degradation of methylene blue (MB) as well as gram-negative and gram-positive bacteria by cobalt-doped tin oxide (Co-SnO2) nanoparticles (NPs) and Co-SnO2/SGCN (sulfur-doped graphitic carbon nitride) nanocomposites (NCs) under sunlight. The coprecipitation approach was used to synthesize the photocatalysts. Maximum methylene blue (MB) photocatalytic degradation was seen with the 7% Co-SnO2 NPs compared to other (1, 3, 5, and 9 wt.%) Co-SnO2 NPs. The 7% Co-SnO2 NPs were then homogenized with different amounts (10, 30, 50, and 70 weight %) of sulfur-doped graphitic carbon nitride (SGCN) to develop Co-SnO2/SGCN heterostructures with the most significant degree of MB degradation. The synthesized samples were identified by modern characterization methods such as FT-IR, SEM, EDX, UV-visible, and XRD spectroscopies. The Co-SnO2/50% SGCN composites showed a significant increase in MB degradation and degraded 96% of MB after 150 min of sunlight irradiation. Both gram-negative (E. coli) and gram-positive (B. subtiles) bacterial strains were subjected to antibacterial activity. All samples were shown to have vigorous antibacterial activity against gram-positive and gram-negative bacteria, but the Co-SnO2/50% SGCN composites exhibited the maximum bactericidal action. Thus, the proposed NC is an efficient organic/inorganic photocatalyst that is recyclable and stable without lowering efficiency. Hence, Co-SnO2/50% SGCNNC has the potential to be employed in water treatment as a dual-functional material that simultaneously removes organic pollutants and eradicates bacteria.
Electro-Optic Effect of Laser Photobleaching on Viscoelastic Properties of Chiral Liquid Crystals
Authors: Dardas Dorota , Lalik Sebastian , Nowacka Zuzanna , Yevchenko Tetiana , Marzec Monika
Published: January 2023

Viscoelastic properties are one of the most fundamental properties of chiral liquid crystals. In general, their determination is not a straightforward task. The main problem is the multitude of physical parameters needed to determine the value of the elasticity and viscosity constants. It is also necessary to consider the character of a respective phase. This problem is particularly important in the case of chiral phases such as ferroelectric and antiferroelectric phases or in the blue phases. There are several experimental methods to measure viscosity and elasticity constants in chiral phases. These methods use various phenomena to detect deformation, e.g., light transmission, polarization current, light modulation, dielectric constant and helix deformation or helix unwinding. Commonly, an external electric field is used to induce deformation, the homogeneity of which inside the cell is essential. This study is focused on the analysis of the effect of laser photobleaching on the electro-optic properties of the antiferroelectric liquid crystal and on the homogeneity of the electric field. The results obtained by confocal microscopy as a function of the cell depth are presented. The influence of the stabilization procedure of the isolated region performed by controlled laser photobleaching on the electro-optic properties has been studied. The observation was conducted using a polarizing microscope, and numerical analysis of two-dimensional colored textures was performed. The obtained results suggest that laser photobleaching can produce an anchoring effect, which has a positive effect on the electro-optic properties of antiferroelectric liquid crystal.
Ab Initio Theoretical Study of DyScO3 at High Pressure
Authors: Zanardi Enrique , Radescu Silvana , Mujica Andrés , Rodríguez-Hernández Plácida , Muñoz Alfonso
Published: January 2023

DyScO3 is a member of a family of compounds (the rare-earth scandates) with exceptional properties and prospective applications in key technological areas. In this paper, we study theoretically the behavior of DyScO3 perovskite under pressures up to about 65 GPa, including its structural and vibrational properties (with an analysis of the Raman and infrared activity), elastic response, and stability. We have worked within the ab initio framework of the density functional theory, using projector-augmented wave potentials and a generalized gradient approximation form to the exchange-correlation functional, including dispersive corrections. We compare our results with existing theoretical and experimental published data and extend the range of previous studies. We also propose a candidate high-pressure phase for this material.
Prospective Evaluation of MGMT-Promoter Methylation Status and Correlations with Outcomes to Temozolomide-Based Chemotherapy in Well-Differentiated Neuroendocrine Tumors
Authors: Brighi Nicole , Lamberti Giuseppe , Andrini Elisa , Mosconi Cristina , Manuzzi Lisa , Donati Giada , Lisotti Andrea , Campana Davide
Published: January 2023

Temozolomide (TEM) as a single agent or in combination with capecitabine (CAPTEM) is active in well-differentiated advanced neuroendocrine tumors (NETs) of gastro-entero-pancreatic and thoracic origin. The predictive role of MGMT-promoter methylation in this setting is controversial. We sought to prospectively evaluate the MGMT-promoter methylation status ability to predict outcomes to TEM-based chemotherapy in patients with NET. A single-center, prospective, observational study has been conducted at the ENETS Center-of-Excellence Outpatient Clinic of the IRCCS Policlinico Sant’Orsola-Malpighi in Bologna, Italy. Patients with advanced, gastro-entero-pancreatic or lung well-differentiated NETs candidate to TEM-based chemotherapy and with available tumor samples for MGMT-promoter methylation assessment were included. The MGMT-promoter methylation status was analyzed by using pyrosequencing. The primary endpoint was progression-free survival (PFS) by the MGMT-promoter methylation status. Secondary endpoints included overall survival (OS), objective response rate (ORR), disease control rate (DCR), and safety. Survival outcomes were compared by restricted mean survival time (RMST) difference. Of 26 screened patients, 22 were finally enrolled in the study. The most frequent NET primary sites were the pancreas (64%) and the lung (23%). MGMT promoter was methylated in five tumors (23%). At a median follow-up time of 47.2 months (95%CI 29.3–89.7), the median PFS was 32.8 months (95%CI 17.2–NA), while the median OS was not reached. Patients in the methylated MGMT group, when compared to those in the unmethylated MGMT group, had longer PFS (median not reached [95%CI NA–NA] vs. 30.2 months [95%CI 15.2–NA], respectively; RMST p = 0.005) and OS (median not reached [95%CI NA–NA] vs. not reached [40.1–NA], respectively; RMST p = 0.019). After adjusting for confounding factors, the MGMT-promoter methylation status was independently associated to the PFS. Numerically higher ORR (60% vs. 24%; p = 0.274) and DCR (100% vs. 88%; p = 1.00) were observed in the methylated vs. unmethylated MGMT group. TEM-based chemotherapy was well-tolerated (adverse events grade ≥3 < 10%). In this prospective study, MGMT-promoter methylation predicted better outcomes to TEM-based chemotherapy in patients with NET.
The Effect of European Bison (Bison bonasus) Translocations on the Persistence and Genetic Diversity of Ex Situ Herds—A Modelling Study
Authors: Kaczmarek-Okrój Magda , Olech Wanda
Published: January 2023

The conservation of the genetic diversity of the European bison population is carried out mainly in ex situ herds, constituting a functional metapopulation. The breeders have to balance between the available capacity of the reserves and the need to enrich the free and semi-free herds with appropriate individuals. If there are limitations (e.g., financial) in the transfer of individuals, breeders report a problem of surplus individuals. The aim of this study was to estimate the migration parameters in the wisent metapopulation ex situ to maintain genetic diversity in hypothetical herds. The analysis was a two-step process. The first part of this study was carried out between the years 1998 and 2017, based on information from the European Bison Pedigree Book about eight selected herds. The average annual share of exported and imported individuals in the chosen metapopulation were calculated (8.81% (SD: 11.51) and 0.75% (SD: 2.15), respectively). The proportion of males to females among the exported animals was close to 1:1. The sex ratio of imported animals was close to 2:1 (M:F). The majority of transports were exports of animals (92.1%). The share of individuals exported from different age–sex groups was calculated. On this basis, in the second part of the study, the proportion of exported surplus individuals in the smallest hypothetical herd was established as 5.89% of the adult females, or 8.98% of adult males, or 32.70% of females aged 1–3 years. In order to maintain the genetic sustainability of hypothetical herds it is crucial to import individuals (M/F: 1/1; interval: 10 years). The results of this study will provide necessary information to determine the tools of wisent population management in the enclosure.
Recent Updates on Corticosteroid-Induced Neuropsychiatric Disorders and Theranostic Advancements through Gene Editing Tools
Authors: Singh Manisha , Agarwal Vinayak , Jindal Divya , Pancham Pranav , Agarwal Shriya , Mani Shalini , Tiwari Raj Kumar , Das Koushik , Alghamdi Badrah S. , Abujamel Tukri S. , Ashraf Ghulam Md. , Jha Saurabh Kumar
Published: January 2023

The vast use of corticosteroids (CCSs) globally has led to an increase in CCS-induced neuropsychiatric disorders (NPDs), a very common manifestation in patients after CCS consumption. These neuropsychiatric disorders range from depression, insomnia, and bipolar disorders to panic attacks, overt psychosis, and many other cognitive changes in such subjects. Though their therapeutic importance in treating and improving many clinical symptoms overrides the complications that arise after their consumption, still, there has been an alarming rise in NPD cases in recent years, and they are seen as the greatest public health challenge globally; therefore, these potential side effects cannot be ignored. It has also been observed that many of the neuronal functional activities are regulated and controlled by genomic variants with epigenetic factors (DNA methylation, non-coding RNA, and histone modeling, etc.), and any alterations in these regulatory mechanisms affect normal cerebral development and functioning. This study explores a general overview of emerging concerns of CCS-induced NPDs, the effective molecular biology approaches that can revitalize NPD therapy in an extremely specialized, reliable, and effective manner, and the possible gene-editing-based therapeutic strategies to either prevent or cure NPDs in the future.
R4Alz-Revised: A Tool Able to Strongly Discriminate ‘Subjective Cognitive Decline’ from Healthy Cognition and ‘Minor Neurocognitive Disorder’
Authors: Poptsi Eleni , Moraitou Despina , Tsardoulias Emmanouil , Symeonidis Andreas L. , Papaliagkas Vasileios , Tsolaki Magdalini
Published: January 2023

Background: The diagnosis of the minor neurocognitive diseases in the clinical course of dementia before the clinical symptoms’ appearance is the holy grail of neuropsychological research. The R4Alz battery is a novel and valid tool that was designed to assess cognitive control in people with minor cognitive disorders. The aim of the current study is the R4Alz battery’s extension (namely R4Alz-R), enhanced by the design and administration of extra episodic memory tasks, as well as extra cognitive control tasks, towards improving the overall R4Alz discriminant validity. Methods: The study comprised 80 people: (a) 20 Healthy adults (HC), (b) 29 people with Subjective Cognitive Decline (SCD), and (c) 31 people with Mild Cognitive Impairment (MCI). The groups differed in age and educational level. Results: Updating, inhibition, attention switching, and cognitive flexibility tasks discriminated SCD from HC (p ≤ 0.003). Updating, switching, cognitive flexibility, and episodic memory tasks discriminated SCD from MCI (p ≤ 0.001). All the R4Alz-R’s tasks discriminated HC from MCI (p ≤ 0.001). The R4Alz-R was free of age and educational level effects. The battery discriminated perfectly SCD from HC and HC from MCI (100% sensitivity—95% specificity and 100% sensitivity—90% specificity, respectively), whilst it discriminated excellently SCD from MCI (90.3% sensitivity—82.8% specificity). Conclusion: SCD seems to be stage a of neurodegeneration since it can be objectively evaluated via the R4Alz-R battery, which seems to be a useful tool for early diagnosis.
Predictors of Remission in Severe Childhood Immune Thrombocytopenia
Authors: Cheng Chao-Neng , Yang Yuan-Ning , Yeh Yun-Hsuan , Chen Li-Wen , Chen Jiann-Shiuh , Lin Yung-Chieh
Published: January 2023

Childhood immune thrombocytopenia (ITP; platelet count < 100 × 109/L) is the most common bleeding disorder in children. A total of 3–5% of children with ITP face a greater risk of bleeding, resulting in significant morbidity and mortality. Childhood ITP is often benign and self-limited; however, children with severe ITP (platelet count < 30 × 109/L) require investigation and monitoring. In addition, 20% of ITP patients may not go into remission (platelet counts < 100 × 109/L by 12 months after diagnosis) and may develop chronic ITP. The early identifying predictors associated with the resolution of severe ITP at the time of diagnosis may be helpful for family guidance. However, there is still controversy about the associations between the clinical factors at the time of initial diagnosis and the definitions of disease remission assessed at different timepoints after diagnosis. This retrospective study aimed to analyze the shared clinical factors among the disease remission definitions at three arbitrarily set timepoints—3, 6, and 12 months after diagnosis. This study retrieved records for hospitalized children aged under 18 years and diagnosed with ITP from the hospital registry in a tertiary university hospital. Clinical variables were recorded by reviewing the medical records with structured data entry for ITP admission. The serial follow-up platelet counts within 12 months after diagnosis were recorded. The times of ITP remission were identified by experienced pediatric hematologists. Patients with mild-form ITP (platelet counts ≥ 30 × 109/L) at diagnosis or who were lost to follow-up within 3 months were excluded. From 1988 to 2019, 546 children were enrolled, and a total of 497 children with severe ITP were included in the further analysis. In total, one (0.2%) died of an intracranial hemorrhage, 363 (73.2%) children went into remission at 3 months, 40 (8.1%) went into remission between 6 and 12 months, and 104 (20.9%) developed chronic ITP. The shared significant predictors for remission by the third, sixth, and twelfth months included pre-adolescent age (<10 years) at diagnosis, abrupt onset (duration of symptoms prior to admission ≤ 2 weeks), and speedy recovery (platelet count > 100 × 109/L at 1 month post diagnosis). ITP patients with positive viral serology tests or vaccination within 4 weeks had trends of delayed remission. In conclusion, diagnosis before preadolescent age, abrupt onset, and speedy recovery may share favorable factors for the remission of childhood ITP assessed at different timepoints.
Absence of a Hernia Sack in Patients Undergoing Prenatal Repair of Spina Bifida Increases the Risk of Developing Shunt-Dependent Hydrocephalus
Authors: Pastuszka Agnieszka , Koszutski Tomasz , Horzelska Ewa , Marciniak Sylwia , Zamłyński Mateusz , Olejek Anita
Published: January 2023

Spina bifida aperta (SBA), with (myelomeningocele) or without (myeloschisis) a hernia sack, is the most common congenital defect of the central nervous system. Prenatal surgical closure of SBA lowers the risk for developing shunt-dependent hydrocephalus, which offers a chance at improved motor, urinary, and gastrointestinal function. A total of 96 patients who had undergone open surgery prenatal repair for SBA were analyzed. The patients were divided into two groups: Group I—12 patients (12.5%)—without a hernia sack (myeloschisis) and Group II—84 patients (87.5%)—with a hernia sack (myelomeningocele). In this study, we demonstrated that prenatal SBA repair was statistically significantly less often associated with the need for ventriculoperitoneal shunting (p > 0.00001). The shunting was statistically significantly more often required in patients from Group I (p > 0.004). The absence of a hernia sack increases the risk for developing shunt-dependent hydrocephalus in patients after prenatal SBA repair. However, as prenatal SBA repair is associated with better motor, urinary, and gastrointestinal function, increased risk of developing shunt-dependent hydrocephalus in fetuses without a hernia sack should not be treated as a contraindication to prenatal intervention.
A Review of Endoscopic Ultrasound-Guided Chemoablative Techniques for Pancreatic Cystic Lesions
Authors: Koehler Bryn , Ryoo Da Yeon , Krishna Somashekar G.
Published: January 2023

Pancreatic cystic lesions (PCLs) are known precursors to pancreatic cancer, one of the deadliest types of cancer worldwide. Surgical removal or pancreatectomies remain the central approach to managing precancerous high-risk PCLs. Endoscopic ultrasound (EUS)-guided therapeutic management of PCLs is a novel management strategy for patients with prohibitive surgical risks. Various ablation techniques have been explored in previous studies utilizing EUS-guided fine needle injection (FNI) of alcohol and chemotherapeutic agents. This review article focuses on EUS-FNI and chemoablation, encompassing the evolution of chemoablation, pancreatic cyst selection, chemotherapy drug selection, including novel agents, and a discussion of its safety and efficacy.
Development of an Artificial Intelligence-Based Breast Cancer Detection Model by Combining Mammograms and Medical Health Records
Authors: Trang Nguyen Thi Hoang , Long Khuong Quynh , An Pham Le , Dang Tran Ngoc
Published: January 2023

Background: Artificial intelligence (AI)-based computational models that analyze breast cancer have been developed for decades. The present study was implemented to investigate the accuracy and efficiency of combined mammography images and clinical records for breast cancer detection using machine learning and deep learning classifiers. Methods: This study was verified using 731 images from 357 women who underwent at least one mammogram and had clinical records for at least six months before mammography. The model was trained on mammograms and clinical variables to discriminate benign and malignant lesions. Multiple pre-trained deep CNN models to detect cancer in mammograms, including X-ception, VGG16, ResNet-v2, ResNet50, and CNN3 were employed. Machine learning models were constructed using k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), Artificial Neural Network (ANN), and gradient boosting machine (GBM) in the clinical dataset. Results: The detection performance obtained an accuracy of 84.5% with a specificity of 78.1% at a sensitivity of 89.7% and an AUC of 0.88. When trained on mammography image data alone, the result achieved a slightly lower score than the combined model (accuracy, 72.5% vs. 84.5%, respectively). Conclusions: A breast cancer-detection model combining machine learning and deep learning models was performed in this study with a satisfactory result, and this model has potential clinical applications.
Similar Sensitivity of SARS-CoV-2 Detection in Oropharyngeal/Nasopharyngeal and Saliva Samples on the Hologic Panther Platform
Authors: Vahidnia Ali , Souverein Dennis , Euser Sjoerd M. , Haverkort Milly , Noordhuis Elise , van Zijl Thomas Z. I. , Kalpoe Jayant , Sinnige Jan C. , Herpers Bjorn L.
Published: January 2023

Background: Oropharyngeal (OP) and nasopharyngeal (NP) sampling has historically been considered the reference specimen type used for respiratory virus detection. Saliva could be a less invasive alternative for SARS-CoV-2 detection, but limited evidence is available. Methods: The technical and clinical performance of saliva was compared to OP/NP on the Hologic Panther platform with two Aptima assays, the End-Point Transcription-Mediated Amplification assay (EP-TMA) and Real-Time Transcription-Mediated Amplification assay (RT-TMA). The samples were collected at the Public Health Service Testing Site XL location in Schiphol Amsterdam Airport. At the site, the Regional Public Health Laboratory Kennemerland (RPHLK) has a fully equipped laboratory facility. Results: A total of 374 samples (187 OP/NP swabs and 187 saliva samples) were collected from 187 unique patients. The Real-Time Transcription-Mediated Amplification assay (RT-TMA) resulted in comparable sensitivities for the detection of SARS-CoV-2 in both the OP/NP swabs (88.3%; 113/128) and saliva samples (87.5%; 112/128). The End-Point Transcription-Mediated Amplification assay (EP-TMA) analyses showed a similar sensitivity (86.7%; 111/128) in the OP/NP swabs but a lower sensitivity in the saliva samples (80.5%; 103/128). Within the discordant analyses, we found no associations in the symptoms, earlier SARS-CoV-2 infections and eating, smoking, drinking and tooth brushing habits within one hour before testing. Conclusions: The Hologic Panther platform Real-Time Transcription-Mediated Amplification assay (RT-TMA) yields a sensitivity for the detection of SARS-CoV-2 in saliva that is comparable to the OP/NP swabs derived from participants presenting themselves at a public health testing facility with minimal or mild symptoms.
A Novel Medical Image Enhancement Algorithm for Breast Cancer Detection on Mammography Images Using Machine Learning
Authors: Avcı Hanife , Karakaya Jale
Published: January 2023

Mammography is the most preferred method for breast cancer screening. In this study, computer-aided diagnosis (CAD) systems were used to improve the image quality of mammography images and to detect suspicious areas. The main contribution of this study is to reveal the optimal combination of various pre-processing algorithms to enable better interpretation and classification of mammography images because pre-processing algorithms significantly affect the accuracy of segmentation and classification methods. In this study, the effect of combinations of different preprocessing methods in differentiating benign and malignant breast lesions was investigated. All image processing algorithms used for lesion detection were used in the mini-MIAS database. In the first step, label information and pectoral muscle resulting from the acquisition of mammography images were removed. In the second step, median filter (MF), contrast limited adaptive histogram equalization (CLAHE), and unsharp masking (USM) algorithms with different combinations of the resolution and visibility of images are increased. In the third step, suspicious regions are extracted from the mammograms using the k-means clustering technique. Then, features were extracted from the obtained ROIs. Finally, feature datasets were classified as normal/abnormal, and benign/malign (two class classification) using Machine Learning algorithms. Test performance measures of the classification methods were examined. In both classifications made in the study, lower classification performance values were obtained when the CLAHE algorithm was used alone as a pre-processing method compared to other pre-processing combinations. When the median filter and unsharp masking algorithms are added to the CLAHE algorithm, the performance of the classification methods has increased. In terms of classification success, Support Vector Machines, Random Forest, and Neural Networks showed the best performance. It was found by comparing the performances of the classification methods that different preprocessing algorithms were effective in detecting the presence of breast lesions and distinguishing benign and malignant.
Effect of the Hematocrit and Storage Temperature of Dried Blood Samples in the Serological Study of Mumps, Measles and Rubella
Authors: Rodríguez-Mateos Mariano , Jaso Javier , Martínez de Aguirre Paula , Carlos Silvia , Fernández-Ciriza Leire , Holguín África , Reina Gabriel
Published: January 2023

Dried blood spots (DBSs) are an economical and convenient alternative to serum/plasma, which allow for the serological and molecular study of different pathogens. Sixty-four blood samples were collected by venipuncture and spotted onto Whatman™ 903 cards to evaluate the utility of DBSs and the effect of the storage temperature for 120 days after sample collection to carry out serological diagnosis. Mumps, measles and rubella IgG were investigated from DBSs and plasma using an automated chemiluminescent immunoassay. Using a calculated optimal cut-off value, the serological evaluation of mumps, measles and rubella using DBSs achieved high sensitivity (100%, 100% and 82.5%, respectively) and specificity (100%, 87.5% and 100%, respectively). The correlation observed between the plasma and the DBSs processed after sample collection was high (0.914–0.953) for all antibodies studied, both considering hematocrit before sample elution or not. For the different storage conditions, the correlation with plasma was high at 4 °C (0.889–0.925) and at −20 °C (0.878–0.951) but lower at room temperature (0.762–0.872). Measles IgG results were more affected than other markers when DBSs were stored at any temperature for 120 days. To summarize, hematocrit does not affect the processing of DBSs in the study of serological markers of mumps, measles and rubella. DBS stability for serological diagnosis of mumps and rubella is adequate when samples are stored at −20 °C or 4 °C, but not at room temperature, for a period of 4 months.
Physiological Femoral Condylar Morphology in Adult Knees—A MRI Study of 517 Patients
Authors: Meier Marc-Pascal , Hochrein Yara , Saul Dominik , Seitz Mark-Tilmann , Roch Paul Jonathan , Jäckle Katharina , Seif Amir Hosseini Ali , Lehmann Wolfgang , Hawellek Thelonius
Published: January 2023

Background: In the age of individualised arthroplasty, the question arises whether currently available standard implants adequately consider femoral condylar morphology (FCM). Therefore, physiological reference values of FCM are needed. The aim was to establish physiological reference values for anterior (ACO) and posterior condylar offset (PCO) as well as for the length of the medial (LMC) and lateral femoral condyles (LLC). Methods: The knee joints of 517 patients (mean age: 52.3 years (±16.8)) were analysed retrospectively using MRI images. Medial (med) and lateral (lat) ACO and PCO, as well as LMC and LLC, were measured. All FCM parameters were examined for association with age, gender, side and osteoarthritis. Results: Mean ACOmed was 2.8 mm (±2.5), mean ACOlat was 6.7 mm (±2.3), mean PCOmed was 25.7 mm (±4.6), mean PCOlat was 23.6 mm (±3.0), mean LMC was 63.7 mm (±5.0) and mean LLC was 64.4 mm (±5.0). Except for PCOmed, the mean values of all other FCM parameters were significantly higher in male knees compared to female knees. ACOmed and PCOmed showed significant side-specific differences. There were no significant differences in relation to age and osteoarthritis. Conclusion: The study showed significant differences in FCM side- and gender-specifically in adult knees. These aspects should be considered in the discussion of individual and gender-specific knee joint replacement.
Ultra-Low Dose CT Chest in Acute COVID-19 Pneumonia: A Pilot Study from India
Authors: Garg Mandeep , Devkota Shritik , Prabhakar Nidhi , Debi Uma , Kaur Maninder , Sehgal Inderpaul S. , Dhooria Sahajal , Bhalla Ashish , Sandhu Manavjit Singh
Published: January 2023

The rapid increase in the number of CT acquisitions during the COVID-19 pandemic raised concerns about increased radiation exposure to patients and the resultant radiation-induced health risks. It prompted researchers to explore newer CT techniques like ultra-low dose CT (ULDCT), which could improve patient safety. Our aim was to study the utility of ultra-low dose CT (ULDCT) chest in the evaluation of acute COVID-19 pneumonia with standard-dose CT (SDCT) chest as a reference standard. This was a prospective study approved by the institutional review board. 60 RT-PCR positive COVID-19 patients with valid indication for CT chest underwent SDCT and ULDCT. ULDCT and SDCT were compared in terms of objective (noise and signal-to-noise ratio) and subjective (noise, sharpness, artifacts and diagnostic confidence) image quality, various imaging patterns of COVID-19, CT severity score and effective radiation dose. The sensitivity, specificity, positive and negative predictive value, and diagnostic accuracy of ULDCT for detecting lung lesions were calculated by taking SDCT as a reference standard. The mean age of subjects was 47.2 ± 10.7 years, with 66.67% being men. 90% of ULDCT scans showed no/minimal noise and sharp images, while 93.33% had image quality of high diagnostic confidence. The major imaging findings detected by SDCT were GGOs (90%), consolidation (76.67%), septal thickening (60%), linear opacities (33.33%), crazy-paving pattern (33.33%), nodules (30%), pleural thickening (30%), lymphadenopathy (30%) and pleural effusion (23.33%). Sensitivity, specificity and diagnostic accuracy of ULDCT for detecting most of the imaging patterns were 100% (p < 0.001); except for GGOs (sensitivity: 92.59%, specificity: 100%, diagnostic accuracy: 93.33%), consolidation (sensitivity: 100%, specificity: 71.43%, diagnostic accuracy: 93.33%) and linear opacity (sensitivity: 90.00%, specificity: 100%, diagnostic accuracy: 96.67%). CT severity score (range: 15–25) showed 100% concordance on SDCT and ULDCT, while effective radiation dose was 4.93 ± 1.11 mSv and 0.26 ± 0.024 mSv, respectively. A dose reduction of 94.38 ± 1.7% was achieved with ULDCT. Compared to SDCT, ULDCT chest yielded images of reasonable and comparable diagnostic quality with the advantage of significantly reduced radiation dose; thus, it can be a good alternative to SDCT in the evaluation of COVID-19 pneumonia.
White Blood Cells Classification Using Entropy-Controlled Deep Features Optimization
Authors: Ahmad Riaz , Awais Muhammad , Kausar Nabeela , Akram Tallha
Published: January 2023

White blood cells (WBCs) constitute an essential part of the human immune system. The correct identification of WBC subtypes is critical in the diagnosis of leukemia, a kind of blood cancer defined by the aberrant proliferation of malignant leukocytes in the bone marrow. The traditional approach of classifying WBCs, which involves the visual analysis of blood smear images, is labor-intensive and error-prone. Modern approaches based on deep convolutional neural networks provide significant results for this type of image categorization, but have high processing and implementation costs owing to very large feature sets. This paper presents an improved hybrid approach for efficient WBC subtype classification. First, optimum deep features are extracted from enhanced and segmented WBC images using transfer learning on pre-trained deep neural networks, i.e., DenseNet201 and Darknet53. The serially fused feature vector is then filtered using an entropy-controlled marine predator algorithm (ECMPA). This nature-inspired meta-heuristic optimization algorithm selects the most dominant features while discarding the weak ones. The reduced feature vector is classified with multiple baseline classifiers with various kernel settings. The proposed methodology is validated on a public dataset of 5000 synthetic images that correspond to five different subtypes of WBCs. The system achieves an overall average accuracy of 99.9% with more than 95% reduction in the size of the feature vector. The feature selection algorithm also demonstrates better convergence performance as compared to classical meta-heuristic algorithms. The proposed method also demonstrates a comparable performance with several existing works on WBC classification.
Software Development for Processing and Analysis of Data Generated by Human Eye Movements
Authors: Kraleva Radoslava , Kralev Velin
Published: January 2023

This research focuses on a software application providing opportunities for the processing and analysis of data generated by a saccade sensor with human eye movements. The main functional opportunities of the developed application are presented as well. According to the methodology of the experiments, three experiments were prepared. The first was related to visualization of the stimuli on a stimulation computer display that was integrated into the developed application as a separate module. The second experiment was related to an interactive visualization of the projection of the eye movement of the participants in the experiment onto the stimulation computer display. The third experiment was related to an analysis of aggregated data on the decision time and the number of correct responses given by the participants to visual tasks. The tests showed that the application can be used as a stimulation center to visualize the stimuli and to recreate the experimental sessions. The summary of the results led to the conclusion that the number of correct responses to the visual tasks depended both on the type of motion of the stimuli and on the size of displacement from the center of the aperture.
Phased Array Antenna Calibration Method Experimental Validation and Comparison
Authors: Pan Chong , Ba Xinran , Tang Yuanhua , Zhang Fengchun , Zhang Yusheng , Wang Zhengpeng , Fan Wei
Published: January 2023

This paper investigates the calibration methods appropriate to the phased array calibration in practical measurement setups. The rotating element electric field vector (REV) method, fast amplitude-only calibration method, and complex amplitude calibration method are compared and analyzed in the same measurement setup. The objective is to investigate the robustness of the discussed algorithms with different measurement ranges, with or without the support of array element on/off operation. A 4×8 uniform rectangular array (URA) is used to validate the three different calibration methods. The measurement results indicate that array element on/off measurement in the far field is suitable to be a reference calibration method in practical setup. The REV and complex amplitude calibration methods present comparable accuracy while fast amplitude-only calibration method provides less accurate calibration results in this measurement. Further, it was demonstrated that with element on/off data available, same calibration accuracy can be achieved either in small or large measurement ranges for the three different calibration methods. However, when the element on/off data is not available, the array calibration accuracy deteriorates with small measurement range. This paper presents the method to calibrate the phased array antenna in near-field by using the element on/off data. This is a very useful method in massive production line calibration. The calibration errors of different calibration methods are analyzed. Furthermore, this paper also analyzes the uncertainty of each method.
A Multi-Strategy Adaptive Particle Swarm Optimization Algorithm for Solving Optimization Problem
Authors: Song Yingjie , Liu Ying , Chen Huayue , Deng Wu
Published: January 2023

In solving the portfolio optimization problem, the mean-semivariance (MSV) model is more complicated and time-consuming, and their relations are unbalanced because they conflict with each other due to return and risk. Therefore, in order to solve these existing problems, multi-strategy adaptive particle swarm optimization, namely APSO/DU, has been developed to solve the portfolio optimization problem. In the present study, a constraint factor is introduced to control velocity weight to reduce blindness in the search process. A dual-update (DU) strategy is based on new speed, and position update strategies are designed. In order to test and prove the effectiveness of the APSO/DU algorithm, test functions and a realistic MSV portfolio optimization problem are selected here. The results demonstrate that the APSO/DU algorithm has better convergence accuracy and speed and finds the least risky stock portfolio for the same level of return. Additionally, the results are closer to the global Pareto front (PF). The algorithm can provide valuable advice to investors and has good practical applications.
KryptosChain—A Blockchain-Inspired, AI-Combined, DNA-Encrypted Secure Information Exchange Scheme
Authors: Mukherjee Pratyusa , Pradhan Chittaranjan , Tripathy Hrudaya , Gaber Tarek
Published: January 2023

Today’s digital world necessitates the adoption of encryption techniques to ensure secure peer-to-peer communication. The sole purpose of this paper is to conglomerate the fundamentals of Blockchain, AI (Artificial Intelligence) and DNA (Deoxyribonucleic Acid) encryption into one proposed scheme, KryptosChain, which is capable of providing a secure information exchange between a sender and his intended receiver. The scheme firstly suggests a DNA-based Huffman coding scheme, which alternatively allocates purines—Adenine (A) and Guanine (G), and pyrimidines—Thymine (T) and Cytosine (C) values, while following the complementary rule to higher and lower branches of the resultant Huffman tree. Inculcation of DNA concepts makes the Huffman coding scheme eight times stronger than the traditional counterpart based on binary—0 and 1 values. After the ciphertext is obtained, the proposed methodology next provides a Blockchain-inspired message exchange scheme that achieves all the principles of security and proves to be immune to common cryptographic attacks even without the deployment of any smart contract, or possessing any cryptocurrency or arriving at any consensus. Lastly, different classifiers were engaged to check the intrusion detection capability of KryptosChain on the NSL-KDD dataset and AI fundamentals. The detailed analysis of the proposed KryptosChain validates its capacity to fulfill its security goals and stands immune to cryptographic attacks. The intrusion possibility curbing concludes that the J84 classifier provides the highest accuracy of 95.84% among several others as discussed in the paper.
Agent-Based Models Assisted by Supervised Learning: A Proposal for Model Specification
Authors: Platas-López Alejandro , Guerra-Hernández Alejandro , Quiroz-Castellanos Marcela , Cruz-Ramírez Nicandro
Published: January 2023

Agent-based modeling (ABM) has become popular since it allows a direct representation of heterogeneous individual entities, their decisions, and their interactions, in a given space. With the increase in the amount of data in different domains, an opportunity to support the design, implementation, and analysis of these models, using Machine Learning techniques, has emerged. A vast and diverse literature evidences the interest and benefits of this symbiosis, but also exhibits the inadequacy of current specification standards, such as the Overview, Design concepts and Details (ODD) protocol, to cover such diversity and, in consequence, its lack of use. Given the relevance of standard specifications for the sake of reproducible ABMs, this paper proposes an extension to the ODD Protocol to provide a standardized description of the uses of Machine Learning (ML) in supporting agent-based modeling. The extension is based on categorization, a result of a broad, but integrated, review of the literature, considering the purpose of learning, the moment when the learning process is executed, the components of the model affected by learning, and the algorithms and data used in learning. The proposed extension of the ODD protocol allows orderly and transparent communication of ML workflows in ABM, facilitating its understanding and potential replication in other investigations. The presentation of a full-featured agent-based model of tax evasion illustrates the application of the proposed approach where the adoption of machine learning results in an error statistically significantly lower, with a p-value of 0.02 in the Wilcoxon signed-rank test. Furthermore, our analysis provides numerical estimates that reveal the strong impact of the penalty and tax rate on tax evasion. Future work considers other kinds of learning applications, e.g., the calibration of parameters and the analysis of the ABM results.
Challenges in Sewer System Maintenance
Authors: Obradović Dino , Šperac Marija , Marenjak Saša
Published: January 2023

A sewer system is an important infrastructure of every settlement. A sewer system is a set of construction facilities used for the quick removal of wastewater from the humans’ immediate environment and its transport to a wastewater treatment plant or direct discharge into an appropriate recipient. In order for the sewer system to perform its purpose properly, its proper maintenance is required. Maintenance of a sewer system is very demanding since the system is mostly underground which makes it difficult to be accessed and maintained. The maintenance of a sewer system can be preventive (regular) or corrective (reactive). The regular maintenance occurs at certain intervals, whereas the reactive maintenance occurs in the case of some unforeseen event. This paper presents the history of sewer systems, as well as basic and alternative types of sewer systems. Furthermore, challenges that arise during sewer system maintenance and difficulties that maintenance employees face in their work are presented in this paper, as well as the ways in which sewer systems are maintained.
A Comparison of Artificial Neural Network and Time Series Models for Timber Price Forecasting
Authors: Kożuch Anna , Cywicka Dominika , Adamowicz Krzysztof
Published: January 2023

The majority of the existing studies on timber price forecasting are based on ARIMA/SARIMA autoregressive moving average models, while vector autoregressive (VAR) and exponential smoothing (ETS) models have been employed less often. To date, timber prices in primary timber markets have not been forecasted with ANN methodology. This methodology was used only for forecasting lumber futures. Low-labor-intensive and relatively simple solutions that can be used in practice as a tool supporting decisions of timber market participants were sought. The present work sets out to compare RBF and MLP artificial neural networks with the Prophet procedure and with classical models (i.e., ARIMA, ETS, BATS, and TBATS) in terms of their suitability for forecasting timber prices in Poland. The study material consisted of quarterly time series of net nominal prices of roundwood (W0) for the years 2005–2021. MLP was found to be far superior to other models in terms of forecasting price changes and levels. ANN models exhibited a better fit to minimum and maximum values as compared to the classical models, which had a tendency to smooth price trends and produce forecasts biased toward average values. The Prophet procedure led to the lowest quality of projections. Ex-post error-based measures of prediction accuracy revealed a complex picture. The best forecasts for alder wood were obtained using the ETS model (with RMSE and MAE values of approx. 0.38 € m−3). ETS also performed well with respect to beech timber, although in this case BATS was just as good in terms of RMSE, while the difference between ETS and neural models amounted to as little as 0.64 € m−3. Birch timber prices were most accurately predicted with BATS and TBATS models (MAE 0.86 € m−3, RMSE 1.04 € m−3). The prices of the most popular roundwood types in Poland, i.e., Scots pine, Norway spruce, and oaks, were best forecasted using ANNs, and especially MLP models. Among the neural models for oak (MAE 4.74 € m−3, RMSE 8.09 € m−3), pine (MAE 2.21 € m−3, RMSE 2.83 € m−3), beech (MAE 2.31 € m−3, RMSE 2.70 € m−3), alder (MAE 1.88 € m−3, RMSE 2.40 € m−3), and spruce (MAE 2.44 € m−3, RMSE 2.58 € m−3), the MLP model was the best (the RBF model for birch). Of the seven models used to forecast the prices of six types of wood, the worst results were obtained for oak wood, while the best results were obtained for alder.
Pure and Co-Fermentation of Quinoa Seeds by Limosilactobacillus fermentum and Lacticaseibacillus rhamnosus: Bioactive Content, Antidiabetic and Antioxidant Activities
Authors: Jafarpour Dornoush , Hashemi Seyed Mohammad Bagher
Published: January 2023

In this study, Limosilactobacillus fermentum PTCC 1638 and Lacticaseibacillus rhamnosus PTCC 1637 were used alone and in combination to ferment quinoa seeds, and the effect of fermentation (37 °C; 24 h) on the pH, total phenols, tocopherols, vitamin C, antioxidant activity, and enzymes inhibition (α-amylase and α-glucosidase; antidiabetic effect) was investigated. The results showed that with the increase in the fermentation time, the bacterial population, total phenols, antioxidant activity, and enzymes inhibition increased, which showed the greatest increase for the co-culture of L. rhamnosus and L. fermentum compared to the pure culture of each strain. Due to the increase in the fermentation time, the tocopherol isomers (α, β, γ, and δ), vitamin C, and pH decreased, and the largest decrease was related to the co-culture of the strains, followed by L. rhamnosus and L. fermentum. The results of this study showed that the co-culture and pure culture of bacteria can have different effects on the physicochemical properties and bioactive compounds of quinoa seeds.
Acknowledgment to the Reviewers of Fermentation in 2022
Authors:   Fermentation Editorial Office
Published: January 2023

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