bluuebunny/crossref_metadata_2025 huggingface dataset:
The Semantics of Natural Objects and Tools in the Brain: A Combined Behavioral and MEG Study
Authors: Visani Elisa , Sebastiano Davide Rossi , Duran Dunja , Garofalo Gioacchino , Magliocco Fabio , Silipo Francesco , Buccino Giovanni
Published: January 2022

Current literature supports the notion that the recognition of objects, when visually presented, is sub-served by neural structures different from those responsible for the semantic processing of their nouns. However, embodiment foresees that processing observed objects and their verbal labels should share similar neural mechanisms. In a combined behavioral and MEG study, we compared the modulation of motor responses and cortical rhythms during the processing of graspable natural objects and tools, either verbally or pictorially presented. Our findings demonstrate that conveying meaning to an observed object or processing its noun similarly modulates both motor responses and cortical rhythms; being natural graspable objects and tools differently represented in the brain, they affect in a different manner both behavioral and MEG findings, independent of presentation modality. These results provide experimental evidence that neural substrates responsible for conveying meaning to objects overlap with those where the object is represented, thus supporting an embodied view of semantic processing.
Prediction and Visualization of Non-Enhancing Tumor in Glioblastoma via T1w/T2w-Ratio Map
Authors: Yamamoto Shota , Sanada Takahiro , Sakai Mio , Arisawa Atsuko , Kagawa Naoki , Shimosegawa Eku , Nakanishi Katsuyuki , Kanemura Yonehiro , Kinoshita Manabu , Kishima Haruhiko
Published: January 2022

One of the challenges in glioblastoma (GBM) imaging is to visualize non-enhancing tumor (NET) lesions. The ratio of T1- and T2-weighted images (rT1/T2) is reported as a helpful imaging surrogate of microstructures of the brain. This research study investigated the possibility of using rT1/T2 as a surrogate for the T1- and T2-relaxation time of GBM to visualize NET effectively. The data of thirty-four histologically confirmed GBM patients whose T1-, T2- and contrast-enhanced T1-weighted MRI and 11C-methionine positron emission tomography (Met-PET) were available were collected for analysis. Two of them also underwent MR relaxometry with rT1/T2 reconstructed for all cases. Met-PET was used as ground truth with T2-FLAIR hyperintense lesion, with >1.5 in tumor-to-normal tissue ratio being NET. rT1/T2 values were compared with MR relaxometry and Met-PET. rT1/T2 values significantly correlated with both T1- and T2-relaxation times in a logarithmic manner (p < 0.05 for both cases). The distributions of rT1/T2 from Met-PET high and low T2-FLAIR hyperintense lesions were different and a novel metric named Likeliness of Methionine PET high (LMPH) deriving from rT1/T2 was statistically significant for detecting Met-PET high T2-FLAIR hyperintense lesions (mean AUC = 0.556 ± 0.117; p = 0.01). In conclusion, this research study supported the hypothesis that rT1/T2 could be a promising imaging marker for NET identification.
OKN-007 Alters Protein Expression Profiles in High-Grade Gliomas: Mass Spectral Analysis of Blood Sera
Authors: Towner Rheal A. , Hocker James , Smith Nataliya , Saunders Debra , Battiste James , Hanas Jay
Published: January 2022

Current therapies for high-grade gliomas, particularly glioblastomas (GBM), do not extend patient survival beyond 16–22 months. OKN-007 (OKlahoma Nitrone 007), which is currently in phase II (multi-institutional) clinical trials for GBM patients, and has demonstrated efficacy in several rodent and human xenograft glioma models, shows some promise as an anti-glioma therapeutic, as it affects most aspects of tumorigenesis (tumor cell proliferation, angiogenesis, migration, and apoptosis). Combined with the chemotherapeutic agent temozolomide (TMZ), OKN-007 is even more effective by affecting chemo-resistant tumor cells. In this study, mass spectrometry (MS) methodology ESI-MS, mass peak analysis (Leave One Out Cross Validation (LOOCV) and tandem MS peptide sequence analyses), and bioinformatics analyses (Ingenuity® Pathway Analysis (IPA®)), were used to identify up- or down-regulated proteins in the blood sera of F98 glioma-bearing rats, that were either untreated or treated with OKN-007. Proteins of interest identified by tandem MS-MS that were decreased in sera from tumor-bearing rats that were either OKN-007-treated or untreated included ABCA2, ATP5B, CNTN2, ITGA3, KMT2D, MYCBP2, NOTCH3, and VCAN. Conversely, proteins of interest in tumor-bearing rats that were elevated following OKN-007 treatment included ABCA6, ADAMTS18, VWA8, MACF1, and LAMA5. These findings, in general, support our previous gene analysis, indicating that OKN-007 may be effective against the ECM. These findings also surmise that OKN-007 may be more effective against oligodendrogliomas, other brain tumors such as medulloblastoma, and possibly other types of cancers.
Building Geometry as a Variable in Energy, Comfort, and Environmental Design Optimization—A Review from the Perspective of Architects
Authors: Kistelegdi István , Horváth Kristóf Roland , Storcz Tamás , Ercsey Zsolt
Published: January 2022

Due to negative environmental impacts caused by the building industry, sustainable buildings have recently become one of the most investigated fields in research. As the design technique itself is mainly responsible for building performance, building energy design optimization is of particular interest. Several studies concentrate on systems, operation, and control optimization, complemented by passive strategies, specifically related to the envelope. In building physics, different architectural considerations, in particular, the building’s shape, are essential variables, as they greatly influence the performance of a building. Most scientific work that takes into consideration building geometry explores spaces without any energy optimization or calculates optimization processes of a few basic variables of simplified space geometries. Review studies mainly discuss the historic development of optimization algorithms, building domains, and the algorithm-system and software framework performance with coupling issues. By providing a systemized clustering of different levels of shape integration intensities, space creation principals, and algorithms, this review explores the current status of sustainability related shape optimization. The review proves that geometry design variable modifications and, specifically, shape generation techniques offer promising optimization potential; however, the findings also indicate that building shape optimization is still in its infancy.
Seismic Fragility Analysis of Low-Rise RC Buildings with Brick Infills in High Seismic Region with Alluvial Deposits
Authors: Adhikari Rabindra , Rupakhety Rajesh , Giri Prajwal , Baruwal Rewati , Subedi Ramesh , Gautam Rajan , Gautam Dipendra
Published: January 2022

Most of the reinforced concrete buildings in Nepal are low-rise construction, as this type of construction is the most dominant structural form adopted to construct residential buildings in urban and semi-urban neighborhoods throughout the country. The low-rise residential constructions generally follow the guidelines recommended by the Nepal Building Code, especially the mandatory rules of thumb. Although low-rise buildings have brick infills and are randomly constructed, infill walls and soil–structure interaction effects are generally neglected in the design and assessment of such structures. To this end, bare frame models that are used to represent such structures are questionable, especially when seismic vulnerability analysis is concerned. To fulfil this gap, we performed seismic vulnerability analysis of low-rise residential RC buildings considering infill walls and soil–structure interaction effects. Considering four analysis cases, we outline comparative seismic vulnerability for various analysis cases in terms of fragility functions. The sum of observations highlights that the effects of infills, and soil–structure interaction are damage state sensitive for low-rise RC buildings. Meanwhile, the design considerations will be significantly affected since some performance parameters are more sensitive than the overall fragility. We also observed that the analytical fragility models fundamentally overestimate the actual seismic fragility in the case of low-rise RC buildings.
Exploring Response to Immunotherapy in Non-Small Cell Lung Cancer Using Delta-Radiomics
Authors: Barabino Emanuele , Rossi Giovanni , Pamparino Silvia , Fiannacca Martina , Caprioli Simone , Fedeli Alessandro , Zullo Lodovica , Vagge Stefano , Cittadini Giuseppe , Genova Carlo
Published: January 2022

Delta-radiomics is a branch of radiomics in which features are confronted after time or after introducing an external factor (such as treatment with chemotherapy or radiotherapy) to extrapolate prognostic data or to monitor a certain condition. Immune checkpoint inhibitors (ICIs) are currently revolutionizing the treatment of non-small cell lung cancer (NSCLC); however, there are still many issues in defining the response to therapy. Contrast-enhanced CT scans of 33 NSCLC patients treated with ICIs were analyzed; altogether, 43 lung lesions were considered. The radiomic features of the lung lesions were extracted from CT scans at baseline and at first reassessment, and their variation (delta, Δ) was calculated by means of the absolute difference and relative reduction. This variation was related to the final response of each lesion to evaluate the predictive ability of the variation itself. Twenty-seven delta features have been identified that are able to discriminate radiologic response to ICIs with statistically significant accuracy. Furthermore, the variation of nine features significantly correlates with pseudo-progression.
Implant Survival, Clinical Outcome and Complications of Megaprosthetic Reconstructions Following Sarcoma Resection
Authors: Theil Christoph , Schwarze Jan , Gosheger Georg , Moellenbeck Burkhard , Schneider Kristian Nikolaus , Deventer Niklas , Klingebiel Sebastian , Grammatopoulos George , Boettner Friedrich , Schmidt-Braekling Tom
Published: January 2022

Megaprosthetic reconstruction of segmental bone defects following sarcoma resection is a frequently chosen surgical approach in orthopedic oncology. While the use of megaprostheses has gained popularity over the last decades and such implants are increasingly used for metastatic reconstructions and in non-tumor cases, there still is a high risk of long-term complications leading to revision surgery. This article investigates current implant survivorship, frequency and types of complications as well as functional outcomes of upper and lower limb megaprosthetic reconstructions.
Noncoding RNAs and Deep Learning Neural Network Discriminate Multi-Cancer Types
Authors: Wang Anyou , Hai Rong , Rider Paul J. , He Qianchuan
Published: January 2022

Detecting cancers at early stages can dramatically reduce mortality rates. Therefore, practical cancer screening at the population level is needed. To develop a comprehensive detection system to classify multiple cancer types, we integrated an artificial intelligence deep learning neural network and noncoding RNA biomarkers selected from massive data. Our system can accurately detect cancer vs. healthy objects with 96.3% of AUC of ROC (Area Under Curve of a Receiver Operating Characteristic curve), and it surprisingly reaches 78.77% of AUC when validated by real-world raw data from a completely independent data set. Even validating with raw exosome data from blood, our system can reach 72% of AUC. Moreover, our system significantly outperforms conventional machine learning models, such as random forest. Intriguingly, with no more than six biomarkers, our approach can easily discriminate any individual cancer type vs. normal with 99% to 100% AUC. Furthermore, a comprehensive marker panel can simultaneously multi-classify common cancers with a stable 82.15% accuracy rate for heterogeneous cancerous tissues and conditions. This detection system provides a promising practical framework for automatic cancer screening at population level. Key points: (1) We developed a practical cancer screening system, which is simple, accurate, affordable, and easy to operate. (2) Our system binarily classify cancers vs. normal with >96% AUC. (3) In total, 26 individual cancer types can be easily detected by our system with 99 to 100% AUC. (4) The system can detect multiple cancer types simultaneously with >82% accuracy.
CDK5RAP3, a New BRCA2 Partner That Regulates DNA Repair, Is Associated with Breast Cancer Survival
Authors: Minguillón Jordi , Ramírez María José , Rovirosa Llorenç , Bustamante-Madrid Pilar , Camps-Fajol Cristina , Ruiz de Garibay Gorka , Shimelis Hermela , Montanuy Helena , Pujol Roser , Hernandez Gonzalo , Bogliolo Massimo , Castillo Pau , Soucy Penny , Martrat Griselda , Gómez Antonio , Cuadras Daniel , García María J. , Gayarre Javier ,   CIMBA, Lázaro Conxi , Benítez Javier , Couch Fergus J. , Pujana Miquel Angel , Surrallés Jordi
Published: January 2022

BRCA2 is essential for homologous recombination DNA repair. BRCA2 mutations lead to genome instability and increased risk of breast and ovarian cancer. Similarly, mutations in BRCA2-interacting proteins are also known to modulate sensitivity to DNA damage agents and are established cancer risk factors. Here we identify the tumor suppressor CDK5RAP3 as a novel BRCA2 helical domain-interacting protein. CDK5RAP3 depletion induced DNA damage resistance, homologous recombination and single-strand annealing upregulation, and reduced spontaneous and DNA damage-induced genomic instability, suggesting that CDK5RAP3 negatively regulates double-strand break repair in the S-phase. Consistent with this cellular phenotype, analysis of transcriptomic data revealed an association between low CDK5RAP3 tumor expression and poor survival of breast cancer patients. Finally, we identified common genetic variations in the CDK5RAP3 locus as potentially associated with breast and ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. Our results uncover CDK5RAP3 as a critical player in DNA repair and breast cancer outcomes.
Current Challenges in Head and Neck Cancer Management
Authors: Starzyńska Anna , Sobocki Bartosz Kamil , Alterio Daniela
Published: January 2022

More than 500,000 new cases of head and neck cancer (HNC) occur each year worldwide [...]
Decellularized Colorectal Cancer Matrices as Bioactive Scaffolds for Studying Tumor-Stroma Interactions
Authors: Marques-Magalhães Ângela , Cruz Tânia , Costa Ângela Margarida , Estêvão Diogo , Rios Elisabete , Canão Pedro Amoroso , Velho Sérgia , Carneiro Fátima , Oliveira Maria José , Cardoso Ana Patrícia
Published: January 2022

More than a physical structure providing support to tissues, the extracellular matrix (ECM) is a complex and dynamic network of macromolecules that modulates the behavior of both cancer cells and associated stromal cells of the tumor microenvironment (TME). Over the last few years, several efforts have been made to develop new models that accurately mimic the interconnections within the TME and specifically the biomechanical and biomolecular complexity of the tumor ECM. Particularly in colorectal cancer, the ECM is highly remodeled and disorganized and constitutes a key component that affects cancer hallmarks, such as cell differentiation, proliferation, angiogenesis, invasion and metastasis. Therefore, several scaffolds produced from natural and/or synthetic polymers and ceramics have been used in 3D biomimetic strategies for colorectal cancer research. Nevertheless, decellularized ECM from colorectal tumors is a unique model that offers the maintenance of native ECM architecture and molecular composition. This review will focus on innovative and advanced 3D-based models of decellularized ECM as high-throughput strategies in colorectal cancer research that potentially fill some of the gaps between in vitro 2D and in vivo models. Our aim is to highlight the need for strategies that accurately mimic the TME for precision medicine and for studying the pathophysiology of the disease.
Metastatic Progression of Osteosarcomas: A Review of Current Knowledge of Environmental versus Oncogenic Drivers
Authors: Odri Guillaume Anthony , Tchicaya-Bouanga Joëlle , Yoon Diane Ji Yun , Modrowski Dominique
Published: January 2022

Metastases of osteosarcomas are heterogeneous. They may grow simultaneously with the primary tumor, during treatment or shortly after, or a long time after the end of the treatment. They occur mainly in lungs but also in bone and various soft tissues. They can have the same histology as the primary tumor or show a shift towards a different differentiation path. However, the metastatic capacities of osteosarcoma cells can be predicted by gene and microRNA signatures. Despite the identification of numerous metastasis-promoting/predicting factors, there is no efficient therapeutic strategy to reduce the number of patients developing a metastatic disease or to cure these metastatic patients, except surgery. Indeed, these patients are generally resistant to the classical chemo- and to immuno-therapy. Hence, the knowledge of specific mechanisms should be extended to reveal novel therapeutic approaches. Recent studies that used DNA and RNA sequencing technologies highlighted complex relations between primary and secondary tumors. The reported results also supported a hierarchical organization of the tumor cell clones, suggesting that cancer stem cells are involved. Because of their chemoresistance, their plasticity, and their ability to modulate the immune environment, the osteosarcoma stem cells could be important players in the metastatic process.
Treatment of Intrahepatic Cholangiocarcinoma—A Multidisciplinary Approach
Authors: Krenzien Felix , Nevermann Nora , Krombholz Alina , Benzing Christian , Haber Philipp , Fehrenbach Uli , Lurje Georg , Pelzer Uwe , Pratschke Johann , Schmelzle Moritz , Schöning Wenzel
Published: January 2022

Intrahepatic cholangiocarcinoma (iCC) is distinguished as an entity from perihilar and distal cholangiocarcinoma and gallbladder carcinoma. Recently, molecular profiling and histopathological features have allowed further classification. Due to the frequent delay in diagnosis, the prognosis for iCC remains poor despite major technical advances and multimodal therapeutic approaches. Liver resection represents the therapeutic backbone and only curative treatment option, with the functional residual capacity of the liver and oncologic radicality being deciding factors for postoperative and long-term oncological outcome. Furthermore, in selected cases and depending on national guidelines, liver transplantation may be a therapeutic option. Given the often advanced tumor stage at diagnosis or the potential for postoperative recurrence, locoregional therapies have become increasingly important. These strategies range from radiofrequency ablation to transarterial chemoembolization to selective internal radiation therapy and can be used in combination with liver resection. In addition, adjuvant and neoadjuvant chemotherapies as well as targeted therapies and immunotherapies based on molecular profiles can be applied. This review discusses multimodal treatment strategies for iCC and their differential use.
Continuous Production of Fumaric Acid with Immobilised Rhizopus oryzae: The Role of pH and Urea Addition
Authors: Swart Reuben Marc , Ronoh Dominic Kibet , Brink Hendrik , Nicol Willie
Published: January 2022

Fumaric acid is widely used in the food and beverage, pharmaceutical and polyester resin industries. Rhizopus oryzae is the most successful microorganism at excreting fumaric acid compared to all known natural and genetically modified organisms. It has previously been discovered that careful control of the glucose feed rate can eliminate the by-product formation of ethanol. Two key parameters affecting fumaric acid excretion were identified, namely the medium pH and the urea feed rate. A continuous fermentation with immobilised R. oryzae was utilised to determine the effect of these parameters. It was found that the selectivity for fumaric acid production increased at high glucose consumption rates for a pH of 4, different from the trend for pH 5 and 6, achieving a yield of 0.93 gg−1. This yield is higher than previously reported in the literature. Varying the urea feed rate to 0.255 mgL−1h−1 improved the yield of fumaric acid but experienced a lower glucose uptake rate compared to higher urea feed rates. An optimum region has been found for fumaric acid production at pH 4, a urea feed rate of 0.625 mgL−1h−1 and a glucose feed rate of 0.329 gL−1h−1.
Adsorption and Sensing Properties of Dissolved Gas in Oil on Cr-Doped InN Monolayer: A Density Functional Theory Study
Authors: Qian Guochao , Hu Jin , Wang Shan , Dai Weiju , Zhou Qu
Published: January 2022

Dissolved gas analysis (DGA) is recognized as one of the most reliable methods in transformer fault diagnosis technology. In this paper, three characteristic gases of transformer oil (CO, C2H4, and CH4) were used in conjunction with a Cr-decorated InN monolayer according to first principle calculations. The adsorption performance of Cr–InN for these three gases were studied from several perspectives such as adsorption structures, adsorption energy, electron density, density of state, and band gap structure. The results revealed that the Cr–InN monolayer had good adsorption performance with CO and C2H4, while the band gap of the monolayer slightly changed after the adsorption of CO and C2H4. Additionally, the adsorption property of the Cr–InN monolayer on CH4 was acceptable and a significant response was simultaneously generated. This paper provides the first insights regarding the possibility of Cr-doped InN monolayers for the detection of gases dissolved in oil.
Pigmentation and Scaring Management after Hypodermoclysis, a Case Report
Authors: Alhallak Kamal , Abdulhafid Adel , Tomi Salem , Omran Dima
Published: January 2022

Hypodermoclysis is the continuous subcutaneous infusion of a parenteral solution into dermal tissue, which is typically associated with skin lesions and cosmetic issues in the majority of patients. Scarring and pigmentation are two of the potential skin lesions after hypodermoclysis. The way skin diseases and cosmetic issues are treated has altered dramatically as a result of laser technology. This is the first article to our knowledge that describes the treatment of pigmentation and scarring produced by Hypodermoclysis cutaneous damage by using laser treatment. It was vital to select the appropriate endpoint, technology, and configuration parameters. The lesion was completely resolved after five months of treatment with four laser sessions. The first session used a fractional Er-Yag laser to perform cold ablation. The remaining sessions used 1064 and 585 nm Nd-Yag Q-switch lasers to operate in the nanosecond region. To minimize the danger of post-inflammatory hyperpigmentation (PIH), the treated region was prepped between laser treatments with 4% hydroquinone (HQ) cream. Our protocol may reduce scars and pigmentation while minimizing adverse effects and downtime.
Clues for Improving the Pathophysiology Knowledge for Endometriosis Using Plasma Micro-RNA Expression
Authors: Dabi Yohann , Suisse Stéphane , Jornea Ludmila , Bouteiller Delphine , Touboul Cyril , Puchar Anne , Daraï Emile , Bendifallah Sofiane
Published: January 2022

The pathophysiology of endometriosis remains poorly understood. The aim of the present study was to investigate functions and pathways associated with the various miRNAs differentially expressed in patients with endometriosis. Plasma samples of the 200 patients from the prospective “ENDO-miRNA” study were analyzed and all known human miRNAs were sequenced. For each miRNA, sensitivity, specificity, and ROC AUC values were calculated for the diagnosis of endometriosis. miRNAs with an AUC ≥ 0.6 were selected for further analysis. A comprehensive review of recent articles from the PubMed, Clinical Trials.gov, Cochrane Library, and Web of Science databases was performed to identify functions and pathways associated with the selected miRNAs. In total, 2633 miRNAs were found in the patients with endometriosis. Among the 57 miRNAs with an AUC ≥ 0.6: 20 had never been reported before; one (miR-124-3p) had previously been observed in endometriosis; and the remaining 36 had been reported in benign and malignant disorders. miR-124-3p is involved in ectopic endometrial cell proliferation and invasion and plays a role in the following pathways: mTOR, STAT3, PI3K/Akt, NF-κB, ERK, PLGF-ROS, FGF2-FGFR, MAPK, GSK3B/β–catenin. Most of the remaining 36 miRNAs are involved in carcinogenesis through cell proliferation, apoptosis, and invasion. The three main pathways involved are Wnt/β–catenin, PI3K/Akt, and NF–KB. Our results provide evidence of the relation between the miRNA profiles of patients with endometriosis and various signaling pathways implicated in its pathophysiology.
Early Routine Biomarkers of SARS-CoV-2 Morbidity and Mortality: Outcomes from an Emergency Section
Authors: Ceci Flavio Maria , Fiore Marco , Gavaruzzi Francesca , Angeloni Antonio , Lucarelli Marco , Scagnolari Carolina , Bonci Enea , Gabanella Francesca , Di Certo Maria Grazia , Barbato Christian , Petrella Carla , Greco Antonio , Vincentiis Marco De , Ralli Massimo , Passananti Claudio , Poscia Roberto , Minni Antonio , Ceccanti Mauro , Tarani Luigi , Ferraguti Giampiero
Published: January 2022

Background. COVID-19 is a severe acute respiratory disease caused by SARS-CoV-2, a virus belonging to the Coronaviridae family. This disease has spread rapidly around the world and soon became an international public health emergency leading to an unpredicted pressure on the hospital emergency units. Early routine blood biomarkers could be key predicting factors of COVID-19 morbidity and mortality as suggested for C-reactive protein (CRP), IL-6, prothrombin and D-dimer. This study aims to identify other early routine blood biomarkers for COVID-19 severity prediction disclosed directly into the emergency section. Methods. Our research was conducted on 156 COVID-19 patients hospitalized at the Sapienza University Hospital “Policlinico Umberto I” of Rome, Italy, between March 2020 and April 2020 during the paroxysm’s initial phase of the pandemic. In this retrospective study, patients were divided into three groups according to their outcome: (1) emergency group (patients who entered the emergency room and were discharged shortly after because they did not show severe symptoms); (2) intensive care unit (ICU) group (patients who attended the ICU after admission to the emergency unit); (3) the deceased group (patients with a fatal outcome who attended the emergency and, afterward, the ICU units). Routine laboratory tests from medical records were collected when patients were admitted to the emergency unit. We focused on Aspartate transaminase (AST), Alanine transaminase (ALT), Lactate dehydrogenase (LDH), Creatine kinase (CK), Myoglobin (MGB), Ferritin, CRP, and D-dimer. Results. As expected, ANOVA data show an age morbidity increase in both ICU and deceased groups compared with the emergency group. A main effect of morbidity was revealed by ANOVA for all the analyzed parameters with an elevation between the emergency group and the deceased group. Furthermore, a significant increase in LDH, Ferritin, CRP, and D-dimer was also observed between the ICU group and the emergency group and between the deceased group and ICU group. Receiver operating characteristic (ROC) analyses confirmed and extended these findings. Conclusions. This study suggests that the contemporaneous presence of high levels of LDH, Ferritin, and as expected, CRP, and D-dimer could be considered as potential predictors of COVID-19 severity and death.
On the Depth of Decision Trees with Hypotheses
Authors: Moshkov Mikhail
Published: January 2022

In this paper, based on the results of rough set theory, test theory, and exact learning, we investigate decision trees over infinite sets of binary attributes represented as infinite binary information systems. We define the notion of a problem over an information system and study three functions of the Shannon type, which characterize the dependence in the worst case of the minimum depth of a decision tree solving a problem on the number of attributes in the problem description. The considered three functions correspond to (i) decision trees using attributes, (ii) decision trees using hypotheses (an analog of equivalence queries from exact learning), and (iii) decision trees using both attributes and hypotheses. The first function has two possible types of behavior: logarithmic and linear (this result follows from more general results published by the author earlier). The second and the third functions have three possible types of behavior: constant, logarithmic, and linear (these results were published by the author earlier without proofs that are given in the present paper). Based on the obtained results, we divided the set of all infinite binary information systems into four complexity classes. In each class, the type of behavior for each of the considered three functions does not change.
Investigation of AlGaN Channel HEMTs on β-Ga2O3 Substrate for High-Power Electronics
Authors: Revathy A. , Boopathi C. S. , Khalaf Osamah Ibrahim , Romero Carlos Andrés Tavera
Published: January 2022

The wider bandgap AlGaN (Eg > 3.4 eV) channel-based high electron mobility transistors (HEMTs) are more effective for high voltage operation. High critical electric field and high saturation velocity are the major advantages of AlGaN channel HEMTs, which push the power electronics to a greater operating regime. In this article, we present the DC characteristics of 0.8 µm gate length (LG) and 1 µm gate-drain distance (LGD) AlGaN channel-based high electron mobility transistors (HEMTs) on ultra-wide bandgap β-Ga2O3 Substrate. The β-Ga2O3 substrate is cost-effective, available in large wafer size and has low lattice mismatch (0 to 2.4%) with AlGaN alloys compared to conventional SiC and Si substrates. A physics-based numerical simulation was performed to investigate the DC characteristics of the HEMTs. The proposed HEMT exhibits sheet charge density (ns) of 1.05 × 1013 cm−2, a peak on-state drain current (IDS) of 1.35 A/mm, DC transconductance (gm) of 277 mS/mm. The ultra-wide bandgap AlGaN channel HEMT on β-Ga2O3 substrate with conventional rectangular gate structure showed 244 V off-state breakdown voltage (VBR) and field plate gate device showed 350 V. The AlGaN channel HEMTs on β-Ga2O3 substrate showed an excellent performance in ION/IOFF and VBR. The high performance of the proposed HEMTs on β-Ga2O3 substrate is suitable for future portable power converters, automotive, and avionics applications.
Daily Living Activity Recognition In-The-Wild: Modeling and Inferring Activity-Aware Human Contexts
Authors: Ehatisham-ul-Haq Muhammad , Murtaza Fiza , Azam Muhammad Awais , Amin Yasar
Published: January 2022

Advancement in smart sensing and computing technologies has provided a dynamic opportunity to develop intelligent systems for human activity monitoring and thus assisted living. Consequently, many researchers have put their efforts into implementing sensor-based activity recognition systems. However, recognizing people’s natural behavior and physical activities with diverse contexts is still a challenging problem because human physical activities are often distracted by changes in their surroundings/environments. Therefore, in addition to physical activity recognition, it is also vital to model and infer the user’s context information to realize human-environment interactions in a better way. Therefore, this research paper proposes a new idea for activity recognition in-the-wild, which entails modeling and identifying detailed human contexts (such as human activities, behavioral environments, and phone states) using portable accelerometer sensors. The proposed scheme offers a detailed/fine-grained representation of natural human activities with contexts, which is crucial for modeling human-environment interactions in context-aware applications/systems effectively. The proposed idea is validated using a series of experiments, and it achieved an average balanced accuracy of 89.43%, which proves its effectiveness.
RDPVR: Random Data Partitioning with Voting Rule for Machine Learning from Class-Imbalanced Datasets
Authors: Hassanat Ahmad B. , Tarawneh Ahmad S. , Abed Samer Subhi , Altarawneh Ghada Awad , Alrashidi Malek , Alghamdi Mansoor
Published: January 2022

Since most classifiers are biased toward the dominant class, class imbalance is a challenging problem in machine learning. The most popular approaches to solving this problem include oversampling minority examples and undersampling majority examples. Oversampling may increase the probability of overfitting, whereas undersampling eliminates examples that may be crucial to the learning process. We present a linear time resampling method based on random data partitioning and a majority voting rule to address both concerns, where an imbalanced dataset is partitioned into a number of small subdatasets, each of which must be class balanced. After that, a specific classifier is trained for each subdataset, and the final classification result is established by applying the majority voting rule to the results of all of the trained models. We compared the performance of the proposed method to some of the most well-known oversampling and undersampling methods, employing a range of classifiers, on 33 benchmark machine learning class-imbalanced datasets. The classification results produced by the classifiers employed on the generated data by the proposed method were comparable to most of the resampling methods tested, with the exception of SMOTEFUNA, which is an oversampling method that increases the probability of overfitting. The proposed method produced results that were comparable to the Easy Ensemble (EE) undersampling method. As a result, for solving the challenge of machine learning from class-imbalanced datasets, we advocate using either EE or our method.
Construction and Analysis of Integral User-Oriented Trustworthiness Metrics
Authors: Novikova Evgenia , Doynikova Elena , Gaifulina Diana , Kotenko Igor
Published: January 2022

Trustworthiness metrics help users to understand information system’s or a device’s security, safety, privacy, resilience, and reliability level. These metrics have different types and natures. The challenge consists of the integration of these metrics into one clear, scalable, sensitive, and reasonable metric representing overall trustworthiness level, useful for understanding if the users can trust the system or for the comparison of the devices and information systems. In this research, the authors propose a novel algorithm for calculation of an integral trustworthiness risk score that is scalable to any number of metrics, considers their criticality, and does not perform averaging in a case when all metrics are of equal importance. The obtained trustworthiness risk score could be further transformed to trustworthiness level. The authors analyze the resulting integral metric sensitivity and demonstrate its advantages on the series of experiments.
Synthesizing Nuclear Magnetic Resonance (NMR) Outputs for Clastic Rocks Using Machine Learning Methods, Examples from North West Shelf and Perth Basin, Western Australia
Authors: Rezaee Reza
Published: January 2022

A nuclear magnetic resonance (NMR) logging tool can provide important rock and fluid properties that are necessary for a reliable reservoir evaluation. Pore size distribution based on T2 relaxation time and resulting permeability are among those parameters that cannot be provided by conventional logging tools. For wells drilled before the 1990s and for many recent wells there is no NMR data available due to the tool availability and the logging cost, respectively. This study used a large database of combinable magnetic resonance (CMR) to assess the performance of several well-known machine learning (ML) methods to generate some of the NMR tool’s outputs for clastic rocks using typical well-logs as inputs. NMR tool’s outputs, such as clay bound water (CBW), irreducible pore fluid (known as bulk volume irreducible, BVI), producible fluid (known as the free fluid index, FFI), logarithmic mean of T2 relaxation time (T2LM), irreducible water saturation (Swirr), and permeability from Coates and SDR models were generated in this study. The well logs were collected from 14 wells of Western Australia (WA) within 3 offshore basins. About 80% of the data points were used for training and validation purposes and 20% of the whole data was kept as a blind set with no involvement in the training process to check the validity of the ML methods. The comparison of results shows that the Adaptive Boosting, known as AdaBoost model, has given the most impressive performance to predict CBW, FFI, permeability, T2LM, and SWirr for the blind set with R2 more than 0.9. The accuracy of the ML model for the blind dataset suggests that the approach can be used to generate NMR tool outputs with high accuracy.
Variation and Genetic Control of the Heartwood, Sapwood, Bark, Wood Color Parameter, and Physical and Mechanical Properties of Dipteryx panamensis in Costa Rica
Authors: Rodríguez-Pérez Dalina , Moya Róger , Murillo Olman , Gaitán-Álvarez Johana , Badilla-Valverde Yorleny
Published: January 2022

The Dipteryx genus has a natural distribution throughout several tropical countries in Latin America. This taxon has several tree species, all recognized for their high-density wood. The objective of this research was to study the variation and genetic control of several wood properties, including bark, sapwood, heartwood, green density (GD), specific gravity (SG), moisture content in green condition (MC-G), and mechanical properties, in a Dipteryx panamensis provenance/progeny test at 8 years old. The results showed that bark varied little among families and provenances, but heartwood (diameter and percentage) showed high genetic variation. SG and MC-G showed significant variation between provenances and families, while GD showed little variation. Among the mechanical properties evaluated, the greatest genetic variation was observed in the MOR in bending and shear stress. Families from the Coope San Juan provenance registered the highest values in all wood properties investigated, and families from Puerto Viejo obtained the lowest. Family heritability and the coefficient of genetic variation exhibited high values in heartwood/sapwood and the MOR in bending (h2 > 0.9 and CV > 20%) and lower values in SG, MC-G, compression stress, and shear stress. D. panamensis wood properties have a high potential to be improved through breeding programs.
Anaerobic Digestion, Codigestion of Food Waste, and Chicken Dung: Correlation of Kinetic Parameters with Digester Performance and On-Farm Electrical Energy Generation Potential
Authors: Jaman Khairina , Amir Nurjannah , Musa Mohammed Ali , Zainal Afifi , Yahya Liyana , Abdul Wahab Abdul Malek , Suhartini Sri , Tuan Mohd Marzuki Tuan Nurfarhana , Harun Razif , Idrus Syazwani
Published: January 2022

Valorization of agro-food waste through anaerobic digestion (AD) is gaining prominence as alternative method of waste minimization and renewable energy production. The aim of this study was to identify the key parameters for digester performance subjected to kinetic study and semicontinuous operation. Biochemical methane potential (BMP) tests were conducted in two different operating conditions: without mixing (WM) and continuous mixing (CM). Three different substrates, including food waste (FW), chicken dung (CD), and codigestion of FW and CD (FWCD) were used. Further kinetic evaluation was performed to identify mixing’s effect on kinetic parameters and correlation of the kinetic parameters with digester performance (volatile solid removal (VS%) and specific methane production (SMP)). The four models applied were: modified Gompertz, logistic, first-order, and Monod. It was found that the CM mode revealed higher values of Rm and k as compared to the WM mode, and the trend was consistently observed in the modified Gompertz model. Nonetheless, the logistic model demonstrated good correlation of kinetic parameters with VS% and SMP. In the continuous systems, the optimum OLR was recorded at 4, 5, and 7 g VS/L/d for FW, CD, and FWCD respectively. Therefore, it was deduced that codigestion significantly improved digester performance. Electrical energy generation at the laboratory scale was 0.002, 0.003, and 0.006 kWh for the FW, CD, and FWCD substrates, respectively. Thus, projected electrical energy generation at the on-farm scale was 372 kWh, 382 kWh, and 518 kWh per day, respectively. Hence, the output could be used as a precursor for large-scale digester-system optimization.
Characterization of Tensile Properties of Cola lepidota Fibers
Authors: Ndoumou Rémy Legrand , Soulat Damien , Labanieh Ahmad Rashed , Ferreira Manuela , Meva’a Lucien , Atangana Ateba Jean
Published: January 2022

Plant fibers are being increasingly explored for their use in engineering polymers and composites, and many works have described their properties, especially for flax and hemp fibers. Nevertheless, the availability of plant fibers varies according to the geographical location on the planet. This study presents the first work on the mechanical properties of a tropical fiber extracted from the bast of Cola lepidota (CL) plant. After a debarking step, CL fibers were extracted manually by wet-retting. The tensile properties are first identified experimentally at the fibers scale, and the analysis of the results shows the great influence of the cross-section parameters (diameter, intrinsic porosities) on these properties. Tensile properties of CL fibers are also predicted by the impregnated fiber bundle test (IFBT). At this scale of bundles, a hackling step, which reduces shives and contributes to the parallelization of the fibers within bundles, improves tensile properties predicted by IFBT. The comparison with the properties of plant fibers given in the literature shows that CL fibers have tensile properties in the same range as kenaf, flax or hemp fibers.
Serum Metabolomics Analysis for Biomarkers of Lactobacillus plantarum FRT4 in High-Fat Diet-Induced Obese Mice
Authors: Cai Hongying , Wen Zhiguo , Xu Xin , Wang Jiaxin , Li Xuan , Meng Kun , Yang Peilong
Published: January 2022

Lactobacillus plantarum is considered a potential probiotic supplementation for treating obesity. However, the underlying molecular mechanism is poorly understood. Our previous study displayed that L. plantarum FRT4 alleviated obesity in mice fed a high-fat diet (HFD) through ameliorating the HFD-induced gut microbiota dysbiosis. To explore the roles of FRT4 in obesity prevention, in this study, we investigated changes in serum metabolomic phenotype by ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF/MS) and analyzed the pathway of HFD-fed Kunming female mice orally administered with FRT4 for eight weeks. Using orthogonal partial least squares discriminant analysis (OPLS-DA), metabolite patterns with significant changes were observed. 55 metabolites including phosphatidylcholine, lysophophatidylcholine, sphingomyelin, serotonin, indole-3-methyl aceta, indole-3-carbinol, indole-5,6-quino, 11,12-DHET, prostaglandin B2, leukotriene B4, and 3-hydroxybenzoic acid were identified as potential biomarkers associated with obesity, which were mainly involving in glycerophospholipid metabolism, tryptophan metabolism, and arachidonic acid metabolism. Perturbations of 14 biomarkers could be regulated by FRT4 intervention. These metabolites may serve as valuable biomarkers to understand the mechanisms by which intake of diets containing FRT4 contributes to the treatment or prevention of obesity. Thus, FRT4 can be a promising dietary supplement for the prevention of HFD-induced obesity.
Reuse of Wasted Bread as Soil Amendment: Bioprocessing, Effects on Alkaline Soil and Escarole (Cichorium endivia) Production
Authors: Cacace Claudio , Rizzello Carlo Giuseppe , Brunetti Gennaro , Verni Michela , Cocozza Claudio
Published: January 2022

In an era characterized by land degradation, climate change, and a growing population, ensuring high-yield productions with limited resources is of utmost importance. In this context, the use of novel soil amendments and the exploitation of plant growth-promoting microorganisms potential are considered promising tools for developing a more sustainable primary production. This study aimed at investigating the potential of bread, which represents a large portion of the global food waste, to be used as an organic soil amendment. A bioprocessed wasted bread, obtained by an enzymatic treatment coupled with fermentation, together with unprocessed wasted bread were used as amendments in a pot trial. An integrated analytical plan aimed at assessing (i) the modification of the physicochemical properties of a typical Mediterranean alkaline agricultural soil, and (ii) the plant growth-promoting effect on escarole (Cichorium endivia var. Cuartana), used as indicator crop, was carried out. Compared to the unamended soils, the use of biomasses raised the soil organic carbon content (up to 37%) and total nitrogen content (up to 40%). Moreover, the lower pH and the higher organic acid content, especially in bioprocessed wasted bread, determined a major availability of Mn, Fe, and Cu in amended soils. The escaroles from pots amended with raw and bioprocessed bread had a number of leaves, 1.7- and 1.4-fold higher than plants cultivated on unamended pots, respectively, showing no apparent phytotoxicity and thus confirming the possible re-utilization of such residual biomasses as agriculture amendments.
High Pressure Processing Impact on Emerging Mycotoxins (ENNA, ENNA1, ENNB, ENNB1) Mitigation in Different Juice and Juice-Milk Matrices
Authors: Pallarés Noelia , Sebastià Albert , Martínez-Lucas Vicente , Queirós Rui , Barba Francisco J. , Berrada Houda , Ferrer Emilia
Published: January 2022

The aim of the present study was to investigate the potential of high-pressure processing (HPP) (600 MPa during 5 min) on emerging mycotoxins, enniatin A (ENNA), enniatin A1 (ENNA1), enniatin B (ENNB), enniatin B1 (ENNB1) reduction in different juice/milk models, and to compare it with the effect of a traditional thermal treatment (HT) (90 °C during 21 s). For this purpose, different juice models (orange juice, orange juice/milk beverage, strawberry juice, strawberry juice/milk beverage, grape juice and grape juice/milk beverage) were prepared and spiked individually with ENNA, ENNA1, ENNB and ENNB1 at a concentration of 100 µg/L. After HPP and HT treatments, ENNs were extracted from treated samples and controls employing dispersive liquid-liquid microextraction methodology (DLLME) and determined by liquid chromatography coupled to ion-trap tandem mass spectrometry (HPLC-MS/MS-IT). The results obtained revealed higher reduction percentages (11% to 75.4%) when the samples were treated under HPP technology. Thermal treatment allowed reduction percentages varying from 2.6% to 24.3%, at best, being ENNA1 the only enniatin that was reduced in all juice models. In general, no significant differences (p > 0.05) were observed when the reductions obtained for each enniatin were evaluated according to the kind of juice model, so no matrix effects were observed for most cases. HPP technology can constitute an effective tool in mycotoxins removal from juices.