bluuebunny/crossref_metadata_2025 huggingface dataset:
ELINAC: Autoencoder Approach for Electronic Invoices Data Clustering
Authors: Schulte Johannes P. , Giuntini Felipe T. , Nobre Renato A. , Nascimento Khalil C. do , Meneguette Rodolfo I. , Li Weigang , Gonçalves Vinícius P. , Rocha Filho Geraldo P.
Published: March 2022

The most common method used to document monetary transactions in Brazil is by issuing electronic invoices (NF-e). The audit of electronic invoices is essential, and this can be improved by using data mining solutions, such as clustering and anomaly detection. However, applying these solutions is not a simple task because NF-e data contains millions of records with noisy fields and nonstandard documents, especially short text descriptions. In addition to these challenges, it is costly to extract information from short texts to identify traces of mismanagement, embezzlement, commercial fraud or tax evasion. Analyzing such data can be more effective when divided into well-defined groups. However, efficient solutions for clustering data with characteristics similar to NF-es have not yet been proposed in the literature. We developed ELINAC, a service for clustering short-text data in NF-es that uses an automatic encoder to cluster data. ELINAC aids in auditing transactions documented in NF-e, clustering similar data by short-text descriptions and making anomaly detection in numeric fields easier. For this, ELINAC explores how to model the automatic encoder without increasing the calculation costs to suppress a large number of short text data. In the worst case, the results show that ELINAC efficiently groups data while performing three times faster than solutions previously adopted in the literature.
Algorithms and Methods for Designing and Scheduling Smart Manufacturing Systems
Authors: Modrak Vladimir , Soltysova Zuzana
Published: March 2022

This Special Issue is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems [...]
A Benchmark Dataset for Evaluating Practical Performance of Model Quality Assessment of Homology Models
Authors: Takei Yuma , Ishida Takashi
Published: March 2022

Protein structure prediction is an important issue in structural bioinformatics. In this process, model quality assessment (MQA), which estimates the accuracy of the predicted structure, is also practically important. Currently, the most commonly used dataset to evaluate the performance of MQA is the critical assessment of the protein structure prediction (CASP) dataset. However, the CASP dataset does not contain enough targets with high-quality models, and thus cannot sufficiently evaluate the MQA performance in practical use. Additionally, most application studies employ homology modeling because of its reliability. However, the CASP dataset includes models generated by de novo methods, which may lead to the mis-estimation of MQA performance. In this study, we created new benchmark datasets, named a homology models dataset for model quality assessment (HMDM), that contain targets with high-quality models derived using homology modeling. We then benchmarked the performance of the MQA methods using the new datasets and compared their performance to that of the classical selection based on the sequence identity of the template proteins. The results showed that model selection by the latest MQA methods using deep learning is better than selection by template sequence identity and classical statistical potentials. Using HMDM, it is possible to verify the MQA performance for high-accuracy homology models.
Inherited Retinal Degeneration: PARP-Dependent Activation of Calpain Requires CNG Channel Activity
Authors: Yan Jie , Günter Alexander , Das Soumyaparna , Mühlfriedel Regine , Michalakis Stylianos , Jiao Kangwei , Seeliger Mathias W. , Paquet-Durand François
Published: March 2022

Inherited retinal degenerations (IRDs) are a group of blinding diseases, typically involving a progressive loss of photoreceptors. The IRD pathology is often based on an accumulation of cGMP in photoreceptors and associated with the excessive activation of calpain and poly (ADP-ribose) polymerase (PARP). Inhibitors of calpain or PARP have shown promise in preventing photoreceptor cell death, yet the relationship between these enzymes remains unclear. To explore this further, organotypic retinal explant cultures derived from wild-type and IRD-mutant mice were treated with inhibitors specific for calpain, PARP, and voltage-gated Ca2+ channels (VGCCs). The outcomes were assessed using in situ activity assays for calpain and PARP and immunostaining for activated calpain-2, poly (ADP-ribose), and cGMP, as well as the TUNEL assay for cell death detection. The IRD models included the Pde6b-mutant rd1 mouse and rd1*Cngb1−/− double-mutant mice, which lack the beta subunit of the rod cyclic nucleotide-gated (CNG) channel and are partially protected from rd1 degeneration. We confirmed that an inhibition of either calpain or PARP reduces photoreceptor cell death in rd1 retina. However, while the activity of calpain was decreased by the inhibition of PARP, calpain inhibition did not alter the PARP activity. A combination treatment with calpain and PARP inhibitors did not synergistically reduce cell death. In the slow degeneration of rd1*Cngb1−/− double mutant, VGCC inhibition delayed photoreceptor cell death, while PARP inhibition did not. Our results indicate that PARP acts upstream of calpain and that both are part of the same degenerative pathway in Pde6b-dependent photoreceptor degeneration. While PARP activation may be associated with CNG channel activity, calpain activation is linked to VGCC opening. Overall, our data highlights PARP as a target for therapeutic interventions in IRD-type diseases.
Expression Profile of CD157 Reveals Functional Heterogeneity of Capillaries in Human Dermal Skin
Authors: Michalak-Micka Katarzyna , Rütsche Dominic , Johner Lukas , Moehrlen Ueli , Biedermann Thomas , Klar Agnes S.
Published: March 2022

CD157 acts as a receptor, regulating leukocyte trafficking and the binding of extracellular matrix components. However, the expression pattern and the role of CD157 in human blood (BEC) and the lymphatic endothelial cells (LEC) of human dermal microvascular cells (HDMEC), remain elusive. We demonstrated constitutive expression of CD157 on BEC and LEC, in fetal and juvenile/adult skin, in situ, as well as in isolated HDMEC. Interestingly, CD157 epitopes were mostly localized on BEC, co-expressing high levels of CD31 (CD31High), as compared to CD31Low BEC, whereas the podoplanin expression level on LEC did not affect CD157. Cultured HDMEC exhibited significantly higher numbers of CD157-positive LEC, as compared to BEC. Interestingly, separated CD157− and CD157+ HDMEC demonstrated no significant differences in clonal expansion in vitro, but they showed distinct expression levels of cell adhesion molecules, before and after cytokine stimulation in vitro. In particular, we proved the enhanced and specific adherence of CD11b-expressing human blood myeloid cells to CD157+ HDMEC fraction, using an in vitro immune-binding assay. Indeed, CD157 was also involved in chemotaxis and adhesion of CD11b/c monocytes/neutrophils in prevascularized dermo–epidermal skin substitutes (vascDESS) in vivo. Thus, our data attribute specific roles to endothelial CD157, in the regulation of innate immunity during inflammation.
Benefit of Silver and Gold Nanoparticles in Wound Healing Process after Endometrial Cancer Protocol
Authors: Toczek Jakub , Sadłocha Marcin , Major Katarzyna , Stojko Rafał
Published: March 2022

It is intractable to manage the vast majority of wounds in a classical surgical manner, however if silver, likewise gold and its representative nanoparticles, can lead to the amelioration of the wound healing process after extensive procedures, they should be employed in the current gynecological practice as promptly as possible. Most likely due to its antimicrobial properties, silver is usually applied as an additional component in the wound healing process. In wound management, we obtained various aspects that can lead to impaired wound healing; the crucial aspect for the wound milieu is to prevent the offending agents from occurring. The greatest barrier to healing is represented by the bacterial biofilm, which can occur naturally or in other ways. Biofilm bacteria can produce extracellular polymers, which can then resist concentrated anti-bacterial treatment. The published literature on the use of silver nanoparticles’ utilization in wound healing becomes slightly heterogenous and requires us in difficult moments to set up proper treatment guidelines.
Towards Automated Construction Quantity Take-Off: An Integrated Approach to Information Extraction from Work Descriptions
Authors: Tang Shengxian , Liu Hexu , Almatared Manea , Abudayyeh Osama , Lei Zhen , Fong Alvis
Published: March 2022

Construction-oriented quantity take-off (QTO) refers to the process of determining the quantities for construction items or work packages in accordance with their descriptions. However, the current construction-oriented QTO practice relies on estimators’ manual interpretation of work descriptions and manual processes to look up proper building objects for quantity calculation. Hence, this research aims to develop natural language processing (NLP) and rule-based algorithms to automate the information extraction (IE) from work descriptions for QTO in building construction. Specifically, several named entity recognition (NER) models, including Hidden Markov Model (HMM), Conditional Random Field (CRF), Bidirectional-Long Short-Term Memory (Bi-LSTM), and Bi-LSTM+CRF, were developed to identify construction activities, material, building component, product features, measurement unit, and additional information (e.g., work scope) from work descriptions. Cost items in the RSMeans database are used to evaluate the developed models in terms of F1 scores. HMM was found to achieve a 5% higher F1 score in the NER than the other three algorithms. Then, labeling rules and active learning strategies were applied along with the HMM model, which improved F1 score by 3% and reduced the labeling efforts by 26%. The results showed that the proposed IE method successfully interprets the desired information from the work description for QTO. This research contributed to the body of knowledge by the NLP-based information extraction model integrating HMM and formalized labeling rules that automatically process work descriptions and lay a foundation for automated QTO and cost estimation.
Sneezing Aerosol Transport in an Indoor Farmers’ Market
Authors: Deng Jiawei , Yao Feng
Published: March 2022

The transportation and surface deposition of aerosols from sneezing in a small indoor farmers’ market are studied numerically. The effects of numbers and locations of the entrances and exits of the market are discussed under the condition of natural convection. The results indicate that aerosols leave the indoor environment more quickly when two doors are designed face to face on the walls perpendicular to the natural wind direction compared to other natural ventilation strategies. The concentrations of aerosols accumulated on the surfaces of the stalls and human bodies inside the market are also lower. In this case, the risk of contacting the virus is relatively low among susceptible individuals in the indoor farmers’ markets. Moreover, opening more doors on the walls parallel to the natural wind direction is not beneficial for the fast exhaust of aerosols.
Synthetic, Photosynthetic, and Chemical Strategies to Enhance Carbon Dioxide Fixation
Authors: Ray Supriyo , Abraham Jason , Jordan Nyiah , Lindsay Mical , Chauhan Neha
Published: March 2022

The present human population is more than three times what it was in 1950. With that, there is an increasing demand for the consumption of fossil fuels for various anthropogenic activities. This consumption is the major source of carbon dioxide emission causing greenhouse effects leading to global warming. The dependency on fossil fuels around the globe is such that it would be hard to move away from it any time soon. Hence, we must work on strategies to improve carbon dioxide fixation as we are making advancements in clean energy technology. This review explores the natural carbon dioxide fixation pathways in plants and various microorganisms and discusses their limitations and alternative strategies. It explains what necessitates the exploration of synthetic pathways and discusses strategies and matrices to consider while evaluating various pathways. This review also discusses the recent breakthroughs in the field of nanosciences that could accelerate chemical methods of carbon dioxide fixation.
Biomarkers and Genetic Markers of Hepatocellular Carcinoma and Cholangiocarcinoma—What Do We Already Know
Authors: Baj Jacek , Bryliński Łukasz , Woliński Filip , Granat Michał , Kostelecka Katarzyna , Duda Piotr , Flieger Jolanta , Teresiński Grzegorz , Buszewicz Grzegorz , Furtak-Niczyporuk Marzena , Portincasa Piero
Published: March 2022

Hepatocellular carcinoma (HCC) is the most common primary liver cancer with an increasing worldwide mortality rate. Cholangiocarcinoma (CCA) is the second most common primary liver cancer. In both types of cancers, early detection is very important. Biomarkers are a relevant part of diagnosis, enabling non-invasive detection and control of cancer recurrence, as well as in the application of screening tests in high-risk groups. Furthermore, some of these biomarkers are useful in controlling therapy and treatment selection. Detection of some markers presents higher sensitivity and specificity in combination with other markers when compared with a single detection. Some gene aberrations are also prognostic markers in the two types of cancers. In the following review, we discuss the most common biomarkers and genetic markers currently being used in the diagnosis of hepatocellular carcinoma and cholangiocarcinoma.
The Role of Conventional TACE (cTACE) and DEBIRI-TACE in Colorectal Cancer Liver Metastases
Authors: Vogl Thomas J. , Lahrsow Maximilian
Published: March 2022

Colorectal cancer (CRC) is one of the most common tumor entities worldwide and a common cause of cancer-associated death. Colorectal cancer liver metastases (CRLM) thereby constitute a severe life-limiting factor. The therapy of CRLM presents a major challenge and surgical resection as well as systemic chemotherapy remain the first-line treatment options. Over the years several locoregional, vascular- and image-based treatments offered by interventional radiologists have emerged when conventional therapies fail, or metastases recurrence occurs. Among such options is the conventional/traditional transarterial chemoembolization (cTACE) by local injection of a combination of chemotherapeutic- and embolic-agents. A similar treatment is the more recent irinotecan-loaded drug-eluting beads TACE (DEBIRI-TACE), which are administered using the same approach. Numerous studies have shown that these different types of chemoembolization can be applied in different clinical settings safely. Furthermore, such treatments can also be combined with other local or systemic therapies. Unfortunately, due to the incoherent patient populations of studies investigating TACE in CRLM, critics state that the definite evidence supporting positive patient outcomes is still lacking. In the following article we review studies on conventional and DEBIRI-TACE. Although highly dependent on the clinical setting, prior therapies and generally the study population, cTACE and DEBIRI-TACE show comparable results. We present the most representative studies on the different chemoembolization procedures and compare the results. Although there is compelling evidence for both approaches, further studies are necessary to determine which patients profit most from these therapies. In conclusion, we determine TACE to be a viable option in CRLM in different clinical settings. Nevertheless, a multidisciplinary approach is desired to offer patients the best possible care.
Electrocatalytic Isomerization of Allylic Alcohols: Straightforward Preparation of β-Aryl-Ketones
Authors: Li Anding , Zheng Nan , Guo Kai , Zhang Zhongchao , Yang Zhen
Published: March 2022

Electrochemical synthesis has been rapidly developing over the past few years. Here, we report a practical and eco-friendly electrocatalytic isomerization of allylic alcohols to their corresponding carbonyl compounds. This reaction can be carried out in undivided cells without the addition of external chemical oxidants and metal catalysts. Moreover, this reaction features a broad substrate scope including challenging allylic alcohols bearing tri- and tetra-substituted olefins and affords straightforward access to diverse β-aryl-ketones. Mechanistic investigations suggest that the reactions proceed through a radical process. This study represents a unique example in which electrochemistry enables hydrogen atom transfer in organic allylic alcohol substrates using a simple organocatalyst.
Biosynthesized Bimetallic (ZnOSnO2) Nanoparticles for Photocatalytic Degradation of Organic Dyes and Pharmaceutical Pollutants
Authors: Mahlaule-Glory Louisah M. , Mathobela Sarah , Hintsho-Mbita Nomso C.
Published: March 2022

The quest for eco-friendly synthetic routes that can be used for the development of multifunctional materials, in particular for water treatment, has reinforced the use of plant extracts as replacement solvents. In this study, bimetallic ZnOSnO2 nanoparticles of different ratios were synthesized using the Sutherlandia frutescens (S. frutescens) plant and tested for the degradation of methylene blue dye and the antibiotics sulfisoxazole and sulfamethoxazole. From the analysis, FTIR confirmed the formation of bimetallic nanoparticles in all ratios within the fingerprint region. SEM revealed homogenous and heterostructures of tubular and spherical structures, with the size distribution ranging from 5–60 nm, respectively. XRD confirmed the formation and the crystallinity of the bimetallic nanoparticles, UV-Vis confirmed the optical properties of the materials and the bandgap values were found between 3.08 and 3.3 eV. From the surface area analysis, type III isotherm and mesoporous structures were confirmed. The photocatalytic activity of these ratios was investigated against MB dye and the antibiotics SSX and SMX. The highest degradation of 88% for MB was obtained using the 50:50 loading ratio at 150 min with a fast kinetic rate of 0.0008 min−1. Furthermore, the holes were the species found to be responsible for the degradation of MB. The SSX and SMX antibiotics exhibited a 66% and 70% degradation, respectively. From this analysis, it can be noted that it is possible to synthesize environmentally safe materials that can be used to degrade various pollutants in our water streams.
Bioenergetic Aspects of Mitochondrial Actions of Thyroid Hormones
Authors: Cioffi Federica , Giacco Antonia , Goglia Fernando , Silvestri Elena
Published: March 2022

Much is known, but there is also much more to discover, about the actions that thyroid hormones (TH) exert on metabolism. Indeed, despite the fact that thyroid hormones are recognized as one of the most important regulators of metabolic rate, much remains to be clarified on which mechanisms control/regulate these actions. Given their actions on energy metabolism and that mitochondria are the main cellular site where metabolic transformations take place, these organelles have been the subject of extensive investigations. In relatively recent times, new knowledge concerning both thyroid hormones (such as the mechanisms of action, the existence of metabolically active TH derivatives) and the mechanisms of energy transduction such as (among others) dynamics, respiratory chain organization in supercomplexes and cristes organization, have opened new pathways of investigation in the field of the control of energy metabolism and of the mechanisms of action of TH at cellular level. In this review, we highlight the knowledge and approaches about the complex relationship between TH, including some of their derivatives, and the mitochondrial respiratory chain.
Obstructive Sleep Apnea in Neonates
Authors: Chandrasekar Indira , Tablizo Mary Anne , Witmans Manisha , Cruz Jose Maria , Cummins Marcus , Estrellado-Cruz Wendy
Published: March 2022

Neonates have distinctive anatomic and physiologic features that predispose them to obstructive sleep apnea (OSA). The overall prevalence of neonatal OSA is unknown, although an increase in prevalence has been reported in neonates with craniofacial malformations, neurological disorders, and airway malformations. If remained unrecognized and untreated, neonatal OSA can lead to impaired growth and development, cardiovascular morbidity, and can even be life threatening. Polysomnography and direct visualization of the airway are essential diagnostic modalities in neonatal OSA. Treatment of neonatal OSA is based on the severity of OSA and associated co-morbidities. This may include medical and surgical interventions individualized for the affected neonate. Based on this, it is expected that infants with OSA have more significant healthcare utilization.
Managing Skin Ageing as a Modifiable Disorder—The Clinical Application of Nourella® Dual Approach Comprising a Nano-Encapsulated Retinoid, Retilex-A® and a Skin Proteoglycan Replacement Therapy, Vercilex®
Authors: Wadstein Jan , Alvarez Israel Sánchez , López Lidia Bernal
Published: March 2022

Skin ageing is a progressive, but modifiable, multi-factorial disorder that involves all the skin’s tissues. Due to its wide range of physiological and psychosocial complications, skin ageing requires rigorous clinical attention. In this review, we aim to encourage clinicians to consider skin ageing as a disorder and suggest a novel, dual approach to its clinical treatment. Topical retinoids and per-oral proteoglycans are promising, non-invasive, therapeutic modalities. To overcome the low bioavailability of conventional free retinoids, Nourella® cream with Retilex-A® (Pharma Medico, Aarhus, Denmark) was developed using a proprietary nano-encapsulation technology. The nano-encapsulation is a sophisticated ‘permeation/penetration enhancer’ that optimises topical drug delivery by increasing the surface availability and net absorption ratio. Treatment adherence is also improved by minimising skin irritation. Interventional evidence suggests the greater efficacy of Retilex-A® in improving skin thickness and elasticity compared with conventional free forms. It is also reported that the rejuvenating efficacy of Retilex-A® and tretinoin are comparable. Another skin anti-ageing approach is proteoglycan replacement therapy (PRT) with Vercilex®. Vercilex® in Nourella® tablet form has the potential to ameliorate proteoglycan dysmetabolism in aged skin by activating skin cells and improving collagen/elastin turnover. Replicated clinical trials evidenced that PRT can significantly enhance the density, elasticity and thickness of both intrinsically aged and photoaged skin. Evidently, Vercilex® and Retilex-A® share a range of bioactivities that underlie their synergistic activity, as observed in a clinical trial. Dual therapy with Nourella® tablets and cream produced greater effects on skin characteristics than monotherapy with each of the two treatments. In conclusion, Nourella® cream and tablets are safe and effective treatments for skin ageing; however, combining the two in a ‘dual skin rejuvenation system’ significantly improves treatment outcomes.
Early Discharge from a Newborn Nursery in the United States during the COVID-19 Pandemic
Authors: Wood Kelly E. , Schmitz Anna , Bhoojhawon Guru
Published: March 2022

The COVID-19 pandemic changed birth hospitalization, with many hospitals implementing restrictions. Little is known about the impact of the COVID-19 pandemic on rates of early newborn discharge and length of stay (LOS). The primary objective was to compare rates of early discharge before and after the start of the COVID-19 pandemic. Secondary objectives included 28-day readmissions and LOS. A single-center retrospective cohort study was undertaken of all live newborns discharged from a well newborn nursery in the United States between 1 July 2015 and 18 June 2021. The pre-COVID-19 era was defined as 1 July 2015 to 29 February 2020, and the COVID-19 era as 1 March 2020 to 18 June 2021, based on the first case reported in our state. Early discharge was defined as less than or equal to 24 h. A total of 10,589 newborns were included: 8094 before and 2495 after the COVID-19 pandemic started. Overall, 43 newborns (0.41%) were discharged early. In the COVID-19 era, early discharges significantly increased from 0.23% (n = 19) to 0.96% (n = 24) (p < 0.001). Median LOS declined from 52.0 (IQR, 43.0–64.0) to 45.0 (IQR, 37.0–56.0) hours (p < 0.001). The 28-day readmission rate decreased from 2.3% (n = 182) to 1.3% (n = 33) (p < 0.01). Since the start of the COVID-19 pandemic, the number of early discharges has significantly increased at our institution without an increase in readmissions. Additionally, overall decrease in length of stay for the birth hospitalization was observed. Potential reasons include changes in hospital unit policies including visitor limitations to reduce COVID-19 infection risk to patients and staff and/or parental concern for iatrogenic acquisition of the virus.
Skeletal Infections Caused by Coccidioides Species
Authors: Koutserimpas Christos , Naoum Symeon , Raptis Konstantinos , Vrioni Georgia , Samonis George , Alpantaki Kalliopi
Published: March 2022

Background: Coccidioidomycosis represents an endemic and challenging disease, with rare extrapulmonary manifestations. The present review of all published cases of core and extremities osseous coccidioidomycosis aims to describe epidemiology, patients’ characteristics, symptoms as well as medical and surgical treatment options and their effectiveness. Methods: A thorough review of all published skeletal core and extremity infections due to Coccidioides species was conducted. Information regarding demographics, causative fungus, antifungal treatment (AFT), surgical management as well as the infection outcome was recorded. Results: A total of 92 cases of Coccidioides spp. skeletal infections were recorded in 87 patients. The patients’ mean age was 35.3 years. The most common site of infection was the spine (82.6%), followed by the foot (6.5%), while the predominant symptom upon presentation was pain (29.9%). Immunosuppressive conditions and/or medications were observed in 21 patients (24.1%). Regarding imaging methods, indicating diagnosis, plain X-rays or CT scans were performed in most patients (50.6%), followed by magnetic resonance imaging (MRI) (47.1%). Most cases were diagnosed through histopathology (62; 71.3%), followed by serology testing (36; 42.4%) and by cultures (35; 40.2%). In 32 cases (36.8%), Coccidioides immitis was cultured, while in the remaining 55 cases (63.2%) the fungus was not further characterized. Regarding AFT, amphotericin B was the preferred agent (52.9%), followed by fluconazole (43.3%). In most cases (78.2%) surgical treatment was also performed. Treatment was successful in 80.5% of cases. Conclusions: Skeletal core and extremity infections due to Coccidioides spp. represent a severe disease. With the available data, the combination of prolonged proper AFT with surgical intervention seems to be the optimal current therapeutic approach.
The Value of 18F-FDG-PET-CT Imaging in Treatment Evaluation of Colorectal Liver Metastases: A Systematic Review
Authors: Bijlstra Okker D. , Boreel Maud M. E. , van Mossel Sietse , Burgmans Mark C. , Kapiteijn Ellen H. W. , Oprea-Lager Daniela E. , Rietbergen Daphne D. D. , van Velden Floris H. P. , Vahrmeijer Alexander L. , Swijnenburg Rutger-Jan , Mieog J. Sven D. , de Geus-Oei Lioe-Fee
Published: March 2022

(1) Background: Up to 50% of patients with colorectal cancer either have synchronous colorectal liver metastases (CRLM) or develop CRLM over the course of their disease. Surgery and thermal ablation are the most common local treatment options of choice. Despite development and improvement in local treatment options, (local) recurrence remains a significant clinical problem. Many different imaging modalities can be used in the follow-up after treatment of CRLM, lacking evidence-based international consensus on the modality of choice. In this systematic review, we evaluated 18F-FDG-PET-CT performance after surgical resection, thermal ablation, radioembolization, and neoadjuvant and palliative chemotherapy based on current published literature. (2) Methods: A systematic literature search was performed on the PubMed database. (3) Results: A total of 31 original articles were included in the analysis. Only one suitable study was found describing the role of 18F-FDG-PET-CT after surgery, which makes it hard to draw a firm conclusion. 18F-FDG-PET-CT showed to be of additional value in the follow-up after thermal ablation, palliative chemotherapy, and radioembolization. 18F-FDG-PET-CT was found to be a poor to moderate predictor of pathologic response after neoadjuvant chemotherapy. (4) Conclusions: 18F-FDG-PET-CT is superior to conventional morphological imaging modalities in the early detection of residual disease after thermal ablation and in the treatment evaluation and prediction of prognosis during palliative chemotherapy and after radioembolization, and 18F-FDG-PET-CT could be considered in selected cases after neoadjuvant chemotherapy and surgical resection.
Arsenic in Groundwater Sources from Selected Communities Surrounding Taal Volcano, Philippines: An Exploratory Study
Authors: Apostol Geminn Louis C. , Valenzuela Sary , Seposo Xerxes
Published: March 2022

Arsenic (As) is a highly toxic, carcinogenic trace metal that can potentially contaminate groundwater sources in volcanic regions. This study provides the first comparative documentation of As concentrations in groundwater in a volcano-sedimentary region in the Philippines. Matched, repeated As measurements and physico-chemical analyses were performed in 26 individual wells from 11 municipalities and city in Batangas province from July 2020 to November 2021. Using the electrothermal atomic absorption spectrometric method, analysis of the wells revealed that in 2020, 23 out of 26 (88.46%) had As levels above the WHO limit of >10 ppb while 20 out of 26 wells (76.92%) had persistently high As levels a year later. Using a Wilcoxon signed-rank test, levels of As were found to be statistically elevated compared to the national safe limit of 10 pbb in the 26 matched sampling sites in both 2020 (p-value < 0.001) and 2021 (p-value = 0.013). Additionally, a two-paired Wilcoxon signed-rank test revealed that As levels were statistically higher in 2020 than in 2021 (p-value = 0.003), suggesting that As levels may be higher in years when there is more volcanic activity; however, this remains to be further elucidated with suitable longitudinal data, as this study is still in its preliminary stages. The data was also analyzed using a bivariable regression, which showed no evidence of a significant relationship between As levels and distance from the danger zone (Taal volcano crater); however, results showed an inverse but statistically insignificant relationship between As levels and elevation. Due to the toxic profile and persistence of As in groundwater in Batangas Province, continuous groundwater As monitoring, timely public health risk communication, and the provision of alternative water sources to affected populations are recommended.
A New Fully Closed-Loop, High-Precision, Class-AB CCII for Differential Capacitive Sensor Interfaces
Authors: Barile Gianluca , Centurelli Francesco , Ferri Giuseppe , Monsurrò Pietro , Pantoli Leonardo , Stornelli Vincenzo , Tommasino Pasquale , Trifiletti Alessandro
Published: March 2022

The use of capacitive sensors has advantages in different industrial applications due to their low cost and low-temperature dependence. In this sense, the current-mode approach by means of second-generation current conveyors (CCIIs) allows for improvements in key features, such as sensitivity and resolution. In this paper, a novel architecture of CCII for differential capacitive sensor interfaces is presented. The proposed topology shows a closed-loop configuration for both the voltage and the current buffer, thus leading to better interface impedances at terminals X and Z. Moreover, a low power consumption of 600 µW was obtained due to class-AB biasing of both buffers, and the inherent drawbacks in terms of linearity under the mismatch of class-AB buffering are overcome by its closed-loop configuration. The advantages of the novel architecture are demonstrated by circuit analysis and simulations; in particular, very good robustness under process, supply voltage and temperature variations and mismatches were obtained due to the closed-loop approach. The CCII was also used to design a capacitive sensor interface in integrated CMOS technology, where it was possible to achieve a sensitivity of 2.34 nA/fF, with a full-scale sensor variation of 8 pF and a minimum detectable capacitance difference of 40 fF.
Automatic Face Mask Detection System in Public Transportation in Smart Cities Using IoT and Deep Learning
Authors: Kumar Tamilarasan Ananth , Rajmohan Rajendrane , Pavithra Muthu , Ajagbe Sunday Adeola , Hodhod Rania , Gaber Tarek
Published: March 2022

The World Health Organization (WHO) has stated that the spread of the coronavirus (COVID-19) is on a global scale and that wearing a face mask at work is the only effective way to avoid becoming infected with the virus. The pandemic made governments worldwide stay under lock-downs to prevent virus transmissions. Reports show that wearing face masks would reduce the risk of transmission. With the rise in population in cities, there is a greater need for efficient city management in today’s world for reducing the impact of COVID-19 disease. For smart cities to prosper, significant improvements to occur in public transportation, roads, businesses, houses, city streets, and other facets of city life will have to be developed. The current public bus transportation system, such as it is, should be expanded with artificial intelligence. The autonomous mask detection and alert system are needed to find whether the person is wearing a face mask or not. This article presents a novel IoT-based face mask detection system in public transportation, especially buses. This system would collect real-time data via facial recognition. The main objective of the paper is to detect the presence of face masks in real-time video stream by utilizing deep learning, machine learning, and image processing techniques. To achieve this objective, a hybrid deep and machine learning model was designed and implemented. The model was evaluated using a new dataset in addition to public datasets. The results showed that the transformation of Convolution Neural Network (CNN) classifier has better performance over the Deep Neural Network (DNN) classifier; it has almost complete face-identification capabilities with respect to people’s presence in the case where they are wearing masks, with an error rate of only 1.1%. Overall, compared with the standard models, AlexNet, Mobinet, and You Only Look Once (YOLO), the proposed model showed a better performance. Moreover, the experiments showed that the proposed model can detect faces and masks accurately with low inference time and memory, thus meeting the IoT limited resources.
Traffic Prediction of Space-Integrated Ground Information Network Using the GTCN Algorithm
Authors: Pan Chengsheng , Wang Yufu , Yang Li
Published: March 2022

The traffic data of the intelligent network with the Space-Integrated Ground Information Network have the characteristics of robust traffic burst, large traffic data, and high volatility compared with the ground traffic. We propose a Gated Temporal Convolution Network (GTCN) algorithm to solve the above problems, the algorithm segments the traffic time series into equal length according to the autocorrelation of the network traffic, and creates the feature sequence by extracting the segmented features using Temporal Convolution Network (TCN), to learn the burst and fluctuation of the intelligent network traffic of the Space-Integrated Ground Information Intelligent Network and to improve the processing efficiency of the traffic time series. Then, the feature sequences of each subsection data are stored, screened, and retained through the gated unit. Finally, the network traffic data are accurately predicted using the characteristics of the sequences stored by the TCN and the gating unit. The simulation experiments showed that, compared with the comparison algorithms, the accuracy of the proposed algorithm is improved by at least 58.72%, the training speed of the algorithm is improved by 84.05%, and the algorithm execution speed is improved by 71.92%, which meet the requirements of the accuracy and timeliness of the traffic prediction model of the Space-Integrated Ground Information Intelligent Network.
HRER: A New Bottom-Up Rule Learning for Knowledge Graph Completion
Authors: Liang Zongwei , Yang Junan , Liu Hui , Huang Keju , Cui Lin , Qu Lingzhi , Li Xiang
Published: March 2022

Knowledge graphs (KGs) are collections of structured facts, which have recently attracted growing attention. Although there are billions of triples in KGs, they are still incomplete. These incomplete knowledge bases will bring limitations to practical applications. Predicting new facts from the given knowledge graphs is an increasingly important area. We investigate the models based on logic rules in this paper. This paper proposes HRER, a new bottom-up rule learning for knowledge graph completion. First of all, inspired by the observation that the known information of KGs is incomplete and unbalanced, HRER modifies the indicators for screening based on the existing relation rule mining methods. The new metric HRR is more effective than traditional confidences in filtering Horn rules. Besides, motivated by the differences between the embedding-based methods and the methods based on logic rules, HRER proposes entity rules. The entity rules make up for the limited expression of Horn rules to some extent. HRER needs a few parameters to control the number of rules and can provide the explanation for prediction. Experiments show that HRER achieves the state-of-the-art across the standard link prediction datasets.
A Novel Extensional Bulk Mode Resonator with Low Bias Voltages
Authors: Jia Qianqian , Chen Zeji , Liu Wenli , Yang Jinling , Zhu Yinfang , Yang Fuhua
Published: March 2022

This paper presents a novel Π-shaped bulk acoustic resonator (ΠBAR) with low bias voltages. Concave flanges were coupled with straight beams to effectively enlarge the transduction area. A silicon-on-insulator(SOI)-based fabrication process was developed to produce nanoscale spacing gaps. The tether designs were optimized to minimize the anchor loss. With a substantially improved electromechanical coupling coefficient, the high-stiffness ΠBAR can be driven into vibrations with low bias voltages down to 3 V. The resonator, vibrating at 20 MHz, implements Q values of 3600 and 4950 in air and vacuum, respectively. Strategies to further improve the resonator performance and robustness were investigated. The resonator has promising IC compatibility and could have potential for the development of high-performance timing reference devices.
Atrous Pyramid GAN Segmentation Network for Fish Images with High Performance
Authors: Zhou Xiaoya , Chen Shuyu , Ren Yufei , Zhang Yan , Fu Junqi , Fan Dongchen , Lin Jingxian , Wang Qing
Published: March 2022

With the development of computer science technology, theory and method of image segmentation are widely used in fish discrimination, which plays an important role in improving the efficiency of fisheries sorting and biodiversity studying. However, the existing methods of fish images segmentation are less accurate and inefficient, which is worthy of in-depth exploration. Therefore, this paper proposes an atrous pyramid GAN segmentation network aimed at increasing accuracy and efficiency. This paper introduces an atrous pyramid structure, and the GAN module is added before the CNN backbone in order to augment the dataset. The Atrous pyramid structure first fuses the input and output of the dilated convolutional layer with a small sampling rate and then feeds the fused features into the subsequent dilated convolutional layer with a large sampling rate to obtain dense multiscale contextual information. Thus, by capturing richer contextual information, this structure improves the accuracy of segmentation results. In addition to the aforementioned innovation, various data enhancement methods, such as MixUp, Mosaic, CutMix, and CutOut, are used in this paper to enhance the model’s robustness. This paper also improves the loss function and uses the label smoothing method to prevent model overfitting. The improvement is also tested by extensive ablation experiments. As a result, our model’s F1-score, GA, and MIoU were tested on the validation dataset, reaching 0.961, 0.981, and 0.973, respectively. This experimental result demonstrates that the proposed model outperforms all the other contrast models. Moreover, in order to accelerate the deployment of the encapsulated model on hardware, this paper optimizes the execution time of the matrix multiplication method on Hbird E203 based on Strassen’s algorithm to ensure the efficient operation of the model on this hardware platform.
Analysis of Fluid-Structure Coupling Dynamic Characteristics of Centrifugal Pump Rotor System
Authors: Yuan Jianping , Shi Jiali , Fu Yanxia , Chen Huilong , Lu Rong , Hou Xueliang
Published: March 2022

Safety and reliable operation is one of the most important research areas for centrifugal pump systems, due to the interaction of complex flow, large structural load, and vibration caused by the operation of the impeller. To analyze the internal flow and impeller deformation of the centrifugal pump, the single-stage single-suction centrifugal pump titled IS100-80-160 was selected as the research object. Under the principle of single variable, the turbulent flow and structural response of three impellers designed by different parameters were calculated by CFX and ANSYS Workbench. A numerical simulation of steady flow at different flow rates of the centrifugal pump was carried out, and its hydraulic performance is consistent with the corresponding experimental results. By comparing the deformation of the impeller rotor system, it was found that the closed impeller has the worst stability with the best hydraulic performance; the impeller with split blades has the worst stability with the best hydraulic performance. This study could enhance the understanding of impeller FSI on centrifugal pump stability and provide a reference for improving the operational stability of centrifugal pumps.
Economic Integration of Renewable and Conventional Power Sources—A Case Study
Authors: Awan Muhammad Mateen Afzal , Javed Muhammad Yaqoob , Asghar Aamer Bilal , Ejsmont Krzysztof , Zia-ur-Rehman
Published: March 2022

In this study, we have presented an optimal microgrid design that ensures the uninterrupted energy supply to Mirpur University of Engineering and Technology (MUST), Azad Jammu and Kashmir AJK, Pakistan at the cheapest price by using reliable energy resources. The availability of energy resources, environmental viability, and economic feasibility are the key parameters of design. The available resources for the MUST site include the National grid, Solar photovoltaic (SPV), Battery bank, and Diesel generator. The data of electrical load, solar illumination, atmospheric temperature at the university, diesel fuel cost, SPV module lifetime, SPV degradation factor, SPV efficiency, SPV cost, battery cost, battery life, national grid energy price, load shedding and toxic emissions have been considered valuables in designing the hybrid micro-grid. The difference in net present cost (NPC) of the optimal design and the worst design is calculated by considering the above parameters. The proposed optimal microgrid design supplies energy to the load using SPV, Diesel generator, and battery bank with NPC of $250,546 and the renewable fraction of 99%. Whereas the worst design includes the Diesel generator and battery bank as energy supplying sources with the NPC of $2.14 M and a renewable fraction of 0%. Simulations performed using HOMER Pro software (HOMER Energy, HOMER Pro-3.11, Boulder, CO, USA) proved that after considering all the data and requirements mentioned above, out of 979 feasible designs, the proposed hybrid microgrid design is best suitable for MUST.
Analysis of the Financing Options for Pro-Ecological Projects
Authors: Bijańska Jolanta , Wodarski Krzysztof , Aleksander Aneta
Published: March 2022

The implementation of pro-ecological projects, including those in the field of renewable energy sources, should bring the desired effects, not only environmental or social, but also economic and financial. Although the latter should not prejudge the implementation of such projects, investors, who are primarily enterprises, need information on whether financing the project from specific, available sources is effective and when the incurred financial expenses will pay off. The publication presents a model that reflects the procedure in the analysis of financing opportunities for pro-ecological projects, aimed at maximizing their financial effects, with a consideration of specific risk factors and limitations. The result of the application of this model is information that supports making rational decisions about the implementation of a specific pro-ecological project. The model was positively verified within a case study concerning the purchase and assembly of a photovoltaic installation by a medium-sized company in Poland.
Minimum-Cost Fast-Charging Infrastructure Planning for Electric Vehicles along the Austrian High-Level Road Network
Authors: Golab Antonia , Zwickl-Bernhard Sebastian , Auer Hans
Published: March 2022

Given the ongoing transformation of the transport sector toward electrification, expansion of the current charging infrastructure is essential to meet future charging demands. The lack of fast-charging infrastructure along highways and motorways is a particular obstacle for long-distance travel with battery electric vehicles (BEVs). In this context, we propose a charging infrastructure allocation model that allocates and sizes fast-charging stations along high-level road networks while minimizing the costs for infrastructure investment. The modeling framework is applied to the Austrian highway and motorway network, and the needed expansion of the current fast-charging infrastructure in place is modeled under different future scenarios for 2030. Within these, the share of BEVs in the car fleet, developments in BEV technology and road traffic load changing in the face of future modal shift effects are altered. In particular, we analyze the change in the requirements for fast-charging infrastructure in response to enhanced driving range and growing BEV fleets. The results indicate that improvements in the driving range of BEVs will have limited impact and hardly affect future costs of the expansion of the fast-charging infrastructure. On the contrary, the improvements in the charging power of BEVs have the potential to reduce future infrastructure costs.