bluuebunny/crossref_metadata_2025 huggingface dataset:
Photoredox-Catalyzed Acylation/Cyclization of 2-Isocyanobiaryls with Oxime Esters for the Synthesis of 6-Acyl Phenanthridines
Authors: Tang Boxiao , Ding Chuan , Ou Min , Liu Yu , Liu Junwei , Liu Yilin
Published: November 2022

An efficient acylation/cyclization reaction of 6-acyl phenanthridines with oxime esters using photoredox catalysis has been developed. This radical acyl transfer strategy enables a facile access to acyl-substituted phenanthridines with good yield and excellent selectivity. The developed method is redox neutral and has broad substrate scope and excellent functional group tolerance.
Effects of Sn Promoter on the Ordered Mesoporous Co3O4-Al2O3 Mixed Metal Oxide for Fischer–Tropsch Synthesis Reaction
Authors: Shen Dongming , Han Sang Beom , Wang Xu , Ali Mansoor , Bae Jong Wook
Published: November 2022

The highly ordered mesoporous Co3O4-Al2O3 bimetal oxide, prepared by a nano-casting method, was modified with Sn promoter (denoted as Sn/m-CoAlOx) to enhance selectivity to liquid-hydrocarbons as well as to suppress CO2 formation formed by a water gas-shift (WGS) reaction activity during CO hydrogenation to hydrocarbons (Fischer–Tropsch Synthesis (FTS) reaction). Based on the surface properties of the Sn/m-CoAlOx in the range of 0.25–0.65 wt%Sn, the Sn promoter generally decreased CO conversion and increased C5+ selectivity through its non-selective blockages of the active metallic cobalt sites, which were responsible for more difficult reducibility of cobalt nanoparticles with an increase of Sn content as well. In addition to those contributions of Sn promoter, the decreased CO2 and CH4 selectivity was clearly observed on the optimal Sn(2)/m-CoAlOx with only small decrease of CO conversion with 79.1% from 81.5% for the reference m-CoAlOx. Those phenomena were mainly attributed to the suppressed WGS reaction activity as well as the decreased hydrogenation activity to form CH4 due to the suppressed H2 adsorption capacity on the less reduced surface Co sites on the Sn(2)/m-CoAlOx.
Estrogen-Inducible LncRNA BNAT1 Functions as a Modulator for Estrogen Receptor Signaling in Endocrine-Resistant Breast Cancer Cells
Authors: Horie Kuniko , Takagi Kiyoshi , Takeiwa Toshihiko , Mitobe Yuichi , Kawabata Hidetaka , Suzuki Takashi , Ikeda Kazuhiro , Inoue Satoshi
Published: November 2022

Recent advances in RNA studies have revealed that functional long noncoding RNAs (lncRNAs) contribute to the biology of cancers. In breast cancer, estrogen receptor α (ERα) is an essential transcription factor that primarily promotes the growth of luminal-type cancer, although only a small number of lncRNAs are identified as direct ERα targets and modulators for ERα signaling. In this study, we performed RNA-sequencing for ER-positive breast cancer cells and identified a novel estrogen-inducible antisense RNA in the COL18A1 promoter region, named breast cancer natural antisense transcript 1 (BNAT1). In clinicopathological study, BNAT1 may have clinical relevance as a potential diagnostic factor for prognoses of ER-positive breast cancer patients based on an in situ hybridization study for breast cancer specimens. siRNA-mediated BNAT1 silencing significantly inhibited the in vitro and in vivo growth of tamoxifen-resistant ER-positive breast cancer cells. Notably, BNAT1 silencing repressed cell cycle progression whereas it promoted apoptosis. Microarray analysis revealed that BNAT1 silencing in estrogen-sensitive breast cancer cells repressed estrogen signaling. We showed that BNAT1 knockdown decreased ERα expression and repressed ERα transactivation. RNA immunoprecipitation showed that BNAT1 physically binds to ERα protein. In summary, BNAT1 would play a critical role in the biology of ER-positive breast cancer by modulating ERα-dependent transcription regulation. We consider that BNAT1 could be a potential molecular target for diagnostic and therapeutic options targeting luminal-type and endocrine-resistant breast cancer.
Lipid Dys-Homeostasis Contributes to APOE4-Associated AD Pathology
Authors: Lazar Adina-Nicoleta , Hanbouch Linda , Boussicaut Lydie , Fourmaux Baptiste , Daira Patricia , Millan Mark J. , Bernoud-Hubac Nathalie , Potier Marie-Claude
Published: November 2022

The association of the APOE4 (vs. APOE3) isoform with an increased risk of Alzheimer’s disease (AD) is unequivocal, but the underlying mechanisms remain incompletely elucidated. A prevailing hypothesis incriminates the impaired ability of APOE4 to clear neurotoxic amyloid-β peptides (Aβ) from the brain as the main mechanism linking the apolipoprotein isoform to disease etiology. The APOE protein mediates lipid transport both within the brain and from the brain to the periphery, suggesting that lipids may be potential co-factors in APOE4-associated physiopathology. The present study reveals several changes in the pathways of lipid homeostasis in the brains of mice expressing the human APOE4 vs. APOE3 isoform. Carriers of APOE4 had altered cholesterol turnover, an imbalance in the ratio of specific classes of phospholipids, lower levels of phosphatidylethanolamines bearing polyunsaturated fatty acids and an overall elevation in levels of monounsaturated fatty acids. These modifications in lipid homeostasis were related to increased production of Aβ peptides as well as augmented levels of tau and phosphorylated tau in primary neuronal cultures. This suite of APOE4-associated anomalies in lipid homeostasis and neurotoxic protein levels may be related to the accrued risk for AD in APOE4 carriers and provides novel insights into potential strategies for therapeutic intervention.
Lycopene Scavenges Cellular ROS, Modulates Autophagy and Improves Survival through 7SK snRNA Interaction in Smooth Muscle Cells
Authors: Shati Ayed A. , Eid Refaat A. , Zaki Mohamed Samir A. , Alqahtani Youssef A. , Al-Qahtani Saleh M. , Chandramoorthy Harish C.
Published: November 2022

The chance of survival rate and autophagy of smooth muscle cells under calcium stress were drastically improved with a prolonged inclusion of Lycopene in the media. The results showed an improved viability from 41% to 69% and a reduction in overall autophagic bodies from 7% to 3%, which was well in agreement with the LC3II and III mRNA levels. However, the proliferation was slow compared to the controls. The fall in the major inflammatory marker TNF-α and improved antioxidant enzyme GPx were regarded as significant restoration markers of cell survival. The reactive oxygen species (ROS) were reduced from 8 fold to 3 fold post addition of lycopene for 24 h. Further, the docking studies revealed binding of lycopene molecules with 7SK snRNA at 7.6 kcal/mol docking energy with 300 ns stability under physiological conditions. Together, these results suggest that Lycopene administration during ischemic heart disease might improve the functions of the smooth muscle cells and 7SK snRNA might be involved in the binding of lycopene and its antioxidant protective effects.
Clinical Value of Ultrasonography and Serum Markers in Preoperative N Staging of Thyroid Cancer
Authors: Wang Hui , Zhao Shanshan , Xu Chunyang , Yao Jincao , Yu Xiuhua , Xu Dong
Published: November 2022

We aimed to determine factors influencing lymph node metastasis (LNM) and develop a more effective method to assess preoperative N staging. Overall, data of 2130 patients who underwent thyroidectomy for thyroid cancer between 2018 and 2021 were retrospectively analysed. Patients were divided into groups according to pN0, pN1a, and pN1b stages. Pathology was used to analyse the correlation between preoperative serum marker indicators and LNM. Receiver operating characteristic curves were used to compare the diagnostic value of ultrasound (US) examination alone, serum thyroglobulin, age, and combined method for LNM. A significant moderate agreement was observed between preoperative US and postoperative pathology for N staging. Between the pN0 and pN1 (pN1a + pN1b) groups, the differences in free triiodothyronine, anti-thyroid peroxidase antibody, and serum thyroglobulin levels were statistically significant. Among the indicators, serum thyroglobulin was an independent predictor of LNM. The area under the receiver operating characteristic curve was 0.610 for serum thyroglobulin level for predicting LNM, 0.689 for US alone, and 0.742 for the combined method. Both preoperative US and serum thyroglobulin level provide a specific value when evaluating the N staging of thyroid cancer, and the combined method is more valuable in the diagnosis of LNM than US alone.
Decreased CSTB, RAGE, and Axl Receptor Are Associated with Zika Infection in the Human Placenta
Authors: Borges-Vélez Gabriel , Arroyo Juan A. , Cantres-Rosario Yadira M. , Rodriguez de Jesus Ana , Roche-Lima Abiel , Rosado-Philippi Julio , Rosario-Rodríguez Lester J. , Correa-Rivas María S. , Campos-Rivera Maribel , Meléndez Loyda M.
Published: November 2022

Zika virus (ZIKV) compromises placental integrity, infecting the fetus. However, the mechanisms associated with ZIKV penetration into the placenta leading to fetal infection are unknown. Cystatin B (CSTB), the receptor for advanced glycation end products (RAGE), and tyrosine-protein kinase receptor UFO (AXL) have been implicated in ZIKV infection and inflammation. This work investigates CSTB, RAGE, and AXL receptor expression and activation pathways in ZIKV-infected placental tissues at term. The hypothesis is that there is overexpression of CSTB and increased inflammation affecting RAGE and AXL receptor expression in ZIKV-infected placentas. Pathological analyses of 22 placentas were performed to determine changes caused by ZIKV infection. Quantitative proteomics, immunofluorescence, and western blot were performed to analyze proteins and pathways affected by ZIKV infection in frozen placentas. The pathological analysis confirmed decreased size of capillaries, hyperplasia of Hofbauer cells, disruption in the trophoblast layer, cell agglutination, and ZIKV localization to the trophoblast layer. In addition, there was a significant decrease in CSTB, RAGE, and AXL expression and upregulation of caspase 1, tubulin beta, and heat shock protein 27. Modulation of these proteins and activation of inflammasome and pyroptosis pathways suggest targets for modulation of ZIKV infection in the placenta.
Current Scenario of MXene-Based Nanomaterials for Wastewater Remediation: A Review
Authors: Saafie Nabilah , Zulfiqar Muhammad , Samsudin Mohamad Fakhrul Ridhwan , Sufian Suriati
Published: November 2022

Rapid urban and industrial sectors generate massive amounts of wastewater, creating severe ecological disruption and harming living organisms. The number of harmful pollutants such as dyes, heavy metals, antibiotics, phenolic compounds, and volatile and several organic chemicals discharged into aquatic systems varies depending on the effluent composition of various sectors. MXene-based composites with unique characteristics were spotlighted as newly developed nanomaterials specifically for environmental-related applications. Therefore, this review broadly discusses the properties, basic principles of MXene, and synthesis routes for developing different MXene-based nanomaterials. The most current strategies on the energy and environmental applications of MXene-based nanomaterials, particularly in photocatalysis, adsorption, and water splitting, were deeply explored for the remediation of different pollutants and hydrogen (H2) evolution from wastewater. The detailed mechanism for H2 evolution and the remediation of industrial pollutants via photocatalysis and adsorption processes was elaborated. The multi-roles of MXene-based nanomaterials with their regeneration possibilities were emphasized. Several essential aspects, including the economic, toxicity and ecological power of MXene-based nanomaterials, were also discussed regarding their opportunity for industrialization. Finally, the perspectives and challenges behind newly developed MXene and MXene-based nanomaterials for environmental pollution were reviewed.
Recent Advances in Gas Sensing Technology Using Non-Oxide II-VI Semiconductors CdS, CdSe, and CdTe
Authors: Ando Masanori , Kawasaki Hideya , Tamura Satoru , Haramoto Yoshikazu , Shigeri Yasushi
Published: November 2022

In recent years, there has been an increasing need and demand for gas sensors to detect hazardous gases in the atmosphere, as they are indispensable for environmental monitoring. Typical hazardous gas sensors that have been widely put to practical use include conductometric gas sensors, such as semiconductor gas sensors that use the change in electrical resistance of metal oxide semiconductors, catalytic combustion gas sensors, and electrochemical gas sensors. However, there is a growing demand for gas sensors that perform better and more safely, while also being smaller, lighter, less energy-demanding, and less costly. Therefore, new gas sensor materials are being explored, as well as optical gas sensor technology that expresses gas detection not electrically but optically. Cadmium sulfide (CdS), cadmium selenide (CdSe), and cadmium telluride (CdTe) are typical group II-VI non-oxide semiconductors that have been used as, for example, electronic materials. Recently, they have attracted attention as new gas sensor materials. In this article, recent advances in conductometric and optical gas sensing technologies using CdS, CdSe, and CdTe are reviewed.
Feasibility of Mouth-to-Mouth Ventilation through FFP2 Respirator in BLS Training during COVID-19 Pandemic (MOVERESP Study): Simulation-Based Study
Authors: Kosinová Martina , Štourač Petr , Prokopová Tereza , Vafková Tereza , Vafek Václav , Barvík Daniel , Skříšovská Tamara , Dvořáček Jan , Djakow Jana , Klučka Jozef , Jarkovský Jiří , Plevka Pavel
Published: November 2022

Background: Due to the COVID-19 pandemic, Basic Life Support (BLS) training has been limited to compression-only or bag–mask ventilation. The most breathable nanofiber respirators carry the technical possibility for inflation of the mannequin. The aim of this study was to assess the efficacy of mouth-to-mouth breathing through a FFP2 respirator during BLS. Methods: In the cross-over simulation-based study, the medical students performed BLS using a breathable nanofiber respirator for 2 min on three mannequins. The quantitative and qualitative efficacy of mouth-to-mouth ventilation through the respirator in BLS training was analyzed. The primary aim was the effectivity of mouth-to-mouth ventilation through a breathable respirator. The secondary aims were mean pause, longest pause, success in achieving the optimal breath volume, technique of ventilation, and incidence of adverse events. Results: In 104 students, effective breath was reached in 951 of 981 (96.9%) attempts in Adult BLS mannequin (Prestan), 822 of 906 (90.7%) in Resusci Anne, and 1777 of 1857 (95.7%) in Resusci Baby. In Resusci Anne and Resusci Baby, 28.9%/15.9% of visible chest rises were evaluated as low-, 33.0%/44.0% as optimal-, and 28.8%/35.8% as high-volume breaths. Conclusions: Mouth-to-mouth ventilation through a breathable respirator had an effectivity greater than 90%.
Quality of Ventilations during Infant Resuscitation: A Simulation Study Comparing Endotracheal Tube with Face Mask
Authors: Santos-Folgar Myriam , Lafuente-Filgueira Paula , Otero-Agra Martín , Fernández-Méndez Felipe , Barcala-Furelos Roberto , Trastoy-Quintela Javier , Aranda-García Silvia , Fernández-Méndez María , Rodríguez-Núñez Antonio
Published: November 2022

Background: There are few studies that analyze ventilation volume and pressure during CPR carried out on infants. The aim of this study was to evaluate the quality of the ventilations administered using a self-inflating bag with an endotracheal tube and a face mask in manikins. Methods: a quasi-experimental simulation study with a randomized case crossover design [endotracheal tube (ET) vs. face mask (FM)] was performed. Sixty participants who were previously trained nursing students participated in the study. The estimated air volumes breathed, and the pressure generated during each ventilation were assessed and the quality of the chest compressions was recorded. Results: the ET test presented a higher percentage of ventilations that reached the lungs (100% vs. 86%; p < 0.001), with adequate volume (60% vs. 28%; p < 0.001) in comparison to FM. Both tests presented peak pressures generated in the airway greater than 30 cm H2O (ET: 22% vs. FM: 31%; p = 0.03). Conclusions: performing quality CPR ventilations on an infant model is not an easy skill for trained nursing students. Both tests presented a significant incidence of excessive peak pressure during ventilations. Specific training, focused on quality of ventilations guided by a manometer attached to the self-inflating bag, must be considered in life support training for pediatric providers.
Role of Crystallographic Orientation of β-Sn Grain on Electromigration Failures in Lead-Free Solder Joint: An Overview
Authors: Bashir Muhammad Nasir , Butt Sajid Ullah , Mansoor Muhammad Adil , Khan Niaz Bahadur , Bashir Shahid , Wong Yew Hoong , Alamro Turki , Eldin Sayed Mohamed , Jameel Mohammed
Published: November 2022

Due to the miniaturization of electronic devices, electromigration became one of the serious reliability issues in lead-free solder joints. The orientation of the β-Sn grain plays an important role in electromigration failures. Several studies have been carried out to investigate the effect of Sn grain orientation on electromigration. The efforts involve the influence of β-Sn grain orientation on the migration of Cu, Sn, and Ni atoms, on the morphology of the solder joint, and on the formation of Cu6Sn5 and (Cu, Ni)6Sn6 in the lead-free solder joint during electromigration. The current review provides a detailed review of past studies which were conducted to investigate the influence of β-Sn grain orientation on electromigration failures in lead-free solder joints.
Annealing Effect on the Structural, Magnetic, Electrical, Optic Property, Nanomechanical, and Adhesive Characteristics of Co60Fe20Yb20 Thin Films on Glass Substrate
Authors: Liu Wen-Jen , Chang Yung-Huang , Chen Yuan-Tsung , Chiu Po-Chun , Wang Yu-Zhi , Lin Shih-Hung , Chi Po-Wei
Published: November 2022

In this study, X-ray diffraction (XRD) analysis showed the amorphous nature of the Co60Fe20Yb20 films deposited at room temperature (RT), 100 °C, and 200 °C. The body-centered cubic (BCC) CoFe (110) characteristic peak was visible at 44.7° after annealing films of 40 nm and 50 nm at 300 °C. The highest alternating current magnetic susceptibility (χac) value was 0.21 at 50 Hz in a 50 nm, and the lowest resistivity value was 1.02 (×10−2 Ω·cm) in a 50 nm. In terms of nano-indication measurement, the highest value of hardness was 9.29 GPa at 300 °C in a 50 nm. When the thickness increased from 10 nm to 50 nm, the hardness and Young’s modulus of the Co60Fe20Yb20 film also showed a saturation trend. The Co60Fe20Yb20 film had the maximum surface energy at 50 nm after 300 °C annealing. The transmittance of Co60Fe20Yb20 films decreased when the thickness was increased because the thickness effect suppresses the photon signal. Due to high χac, low electrical performance, strong nano-mechanical properties, and high adhesion, it was discovered in this work that 50 nm with annealing at 300 °C was the ideal condition for the magnetic and adhesive capabilities of Co60Fe20Yb20 film. More importantly, replacing the CoFeB seed or buffer layer with a thin CoFeYb film improved the thermal stability, making CoFeYb films attractive for practical magnetic tunnel junction (MTJ) applications. Furthermore, the specific properties of Co60Fe20Yb20 films were compared to those of Co60Fe20Y20 films, demonstrating that the specific properties of these two materials may be compared.
Characterization of Secondary Metabolites Responsible for the Resistance of Local Tomato Accessions to Whitefly (Bemisia tabaci, Gennadius 1889) Hemiptera in Tanzania
Authors: Mrosso Secilia E. , Ndakidemi Patrick A. , Mbega Ernest R.
Published: November 2022

Plants have developed mechanisms to cope with stresses in their environments as they grow in diverse settings. Such means include releasing plant defense compounds upon attacks by pests or other stressors. Plants with these characteristics are essential as a plant germplasm source for breeding resistance against herbivores and insect pests. Therefore, this study aimed to screen germplasms for whitefly resistance and characterize the secondary metabolites responsible for this. Thirty local tomato accessions were screened for resistance against whiteflies (Bemisia tabaci Gennadius) in the screen house located at Tanzania Plant Health and Pesticides Authority (PTHPA) between January and April 2021. From this screening, seven local tomato cultivars: TZA3729, TZA5554, TZA5545, TZA5562, TZA5552, TZA3177 and TZA5157, showed resistance, and one accession (TZA5496) that showed susceptibility to whiteflies (negative control) and accession V1030462 that was a standard (positive control) were selected for the subsequent experiments. The experiment was conducted in July–October 2021 in the screen house at TPHPA and repeated in January–April 2022 using a completely randomized block design with three replications. From this experiment, three accessions: TZA3729, TZA5562 and TZA5157, showed resistance against whiteflies. However, accession TZA3729 was more resistant than TZA5562 and TZA5157 when compared to the resistant accession V1030462. Therefore, these accessions were further screened for secondary metabolites responsible for resistance against herbivores and insect pests—in this case, whiteflies. The GS-MS methanol extract results showed accession TZA3729 to possess a wide array of secondary plant metabolites responsible for plant self-defenses, such as diterpenes, Tetraterpenes, alkaloids, carotenoids and fatty acid esters. Therefore, the study recommends accession TZA3729 as a source of tomato plant germplasm for breeding tomatoes resistant to whiteflies.
Microstructure Evolution during Mechanical Alloying of a Biodegradable Magnesium Alloy
Authors: Raducanu Doina , Cojocaru Vasile Danut , Nocivin Anna , Hendea Radu Emil , Ivanescu Steliana , Stanciu Doina , Trisca-Rusu Corneliu , Serban Nicolae , Drob Silviu Iulian , Campian Radu Septimiu
Published: November 2022

The aim of the present work was to apply a mechanical alloying method to obtain a Mg-10Zn-0.5Zr-0.8Ca powder-alloy with morphological and dimensional characteristics, proper for subsequent selective laser melting (SLM) processing. The mechanical alloying process was applied at different values of the milling time. Thus, the evolution of the main morphological and dimensional characteristics of the experimented powder-alloy could be studied. The conclusion of this study is that mechanical alloying possesses good potential to obtain powder-alloy with almost rounded morphology and fine dimensions, proper for further additive manufacturing procedures such as selective laser melting.
Enhancement of the LeanDfX Product Development Framework and Application to the Design of an AGV Structure
Authors: Carneiro Tomás , Oliveira João , Baptista António J. , de Castro Paulo M. S. T.
Published: November 2022

A product development framework called LeanDfX has been conceived at INEGI, aiming at organizing the product design and development process benefitting from lean thinking and DfX paradigms. The design of the metallic structure for an automated guided vehicle (AGV) focusing on its static, dynamic and fatigue characteristics was a recent opportunity to enhance and further develop the framework through the consideration and integration into the process of several existing tools such as FMEA (failure mode and effect analysis), QFD (quality function deployment) or fuzzy logic. This paper describes the integration of those tools in the LeanDfX framework and an application to the design of an AGV structure. The methodology presented involves systematic consideration of a substantial number of design requirements and more detailed product specification characterization. Such a number might be seen as delaying the development process, but the present case study showed that the inverse was true, thanks to the structured systematic approach and timely elimination of less desirable alternatives.
Reduction of Hippocampal High-Frequency Activity in Wag/Rij Rats with a Genetic Predisposition to Absence Epilepsy
Authors: Sitnikova Evgenia , Perevozniuk Dmitrii , Rutskova Elizaveta , Uzakov Shukhrat , Korshunov Viktor A.
Published: November 2022

In temporal lobe epilepsy, high frequency oscillations serve as electroencephalographic (EEG) markers of epileptic hippocampal tissue. In contrast, absence epilepsy and other idiopathic epilepsies are known to result from thalamo-cortical abnormalities, with the hippocampus involvement considered to be only indirect. We aimed to uncover the role of the hippocampus in absence epilepsy using a genetic rat model of absence epilepsy (WAG/Rij rats), in which spike-wave discharges (SWDs) appear spontaneously in cortical EEG. We performed simultaneous recordings of local field potential from the hippocampal dentate gyrus using pairs of depth electrodes and epidural cortical EEG in freely moving rats. Hippocampal ripples (100–200 Hz) and high frequency oscillations (HFO, 50–70 Hz) were detected using GUI RIPPLELAB in MatLab (Navarrete et al., 2016). Based on the dynamics of hippocampal ripples, SWDs were divided into three clusters, which might represent different seizure types in reference to the involvement of hippocampal processes. This might underlie impairment of hippocampus-related cognitive processes in some patients with absence epilepsy. A significant reduction to nearly zero-ripple-density was found 4–8 s prior to SWD onset and during 4 s immediately after SWD onset. It follows that hippocampal ripples were not just passively blocked by the onset of SWDs, but they were affected by spike-wave seizure initiation mechanisms. Hippocampal HFO were reduced during the preictal, ictal and postictal periods in comparison to the baseline. Therefore, hippocampal HFO seemed to be blocked with spike-wave seizures. All together, this might underlie impairment of hippocampus-related cognitive processes in some patients with absence epilepsy. Further investigation of processes underlying SWD-related reduction of hippocampal ripples and HFO oscillations may help to predict epileptic attacks and explain cognitive comorbidities in patients with absence epilepsy.
Validation of Existing Clinical Prediction Tools for Primary Aldosteronism Subtyping
Authors: Kološová Barbora , Waldauf Petr , Wichterle Dan , Kvasnička Jan , Zelinka Tomáš , Petrák Ondřej , Krátká Zuzana , Forejtová Lubomíra , Kaván Jan , Widimský Jiří , Holaj Robert
Published: November 2022

The new clinical prediction score (SCORE) has been recently proposed for primary aldosteronism (PA) subtyping prior to adrenal vein sampling (AVS). This study aimed to compare that SCORE with previously published scores and their validation using a cohort of patients at our center who had had positive SIT confirming PA and had been diagnosed with either bilateral PA according to AVS or unilateral PA if biochemically cured after an adrenalectomy. Final diagnoses were used to evaluate the diagnostic performance of the proposed clinical prediction tools. Only Kamemura’s model (with a maximum score of 4 points) and Kobayashi’s score (with a maximum score of 12 points) reached 100% reliability for prediction of bilateral PA; however, with sensitivity of only 3%. On the other hand, the values of SCORE = 3 (with sensitivity of 48%), the SPACE score ≥18 (with sensitivity of 35%), the Kobayashi’s score ≤2 (with sensitivity of 28%), and the Kocjan’s score = 3 (with sensitivity of 28%) were able to predict unilateral PA with 100% probability. Furthermore, Umakoshi’s and Young’s models both reached 100% reliability for a unilateral PA with score = 4 and both predictive factors together respectively; however, the sensitivity was lower compared with previous models; 4% and 14%, respectively. None of the clinical prediction tools applied to our cohort predicted unilateral and bilateral subtypes together with the expected high diagnostic performance, and therefore can only be used for precisely defined cases.
CT-Guided Radiofrequency Thermal Ablation for the Treatment of Atypical, Early-Onset Osteoid Osteoma in Children Younger than 4 Years Old: Single-Institution Experience and Literature Review
Authors: Papalexis Nicolas , Peta Giuliano , Ponti Federico , Tuzzato Gianmarco , Colangeli Marco , Facchini Giancarlo , Spinnato Paolo
Published: November 2022

The aim of our study is to report our experience on CT-guided radiofrequency ablation (RFA) for osteoid osteoma (OO) in children under 4 years of age and to review the literature regarding this atypical, early onset of the disease. We retrospectively reviewed the clinical and radiological records of the patients treated with CT-guided RFA for OO at our institution (2006–2021), including those under 4 years of age. Data regarding technical success, clinical success, and biopsy diagnostic yield were collected. Moreover, we performed a literature review including previous articles on early-onset OO. We found only 12 patients that were under 4 years of age (12/842–1.4%) at the time of RFA treatment: 4 F and 8 M, mean age at the time of the treatment 35.3 months (range 22–46 months). The mean follow-up was 22.8 months (range 6–96 months). Technical success was achieved in all cases (12/12). In all patients (12/12), a complete remission of the pain symptoms was achieved at clinical follow-up controls. No recurrence of pain or complications were documented. The histopathological diagnosis was confirmed in 4 patients (4/12–33.3%). Moreover, we found another 9 articles in the literature with a main focus on early-onset OO (<4 years old), with a total of 12 patients included; 6 of those patients (6/12–50%) were treated with CT-guided RFA, with success reported 5 cases (5/6–83.3%). Our series of cases treated at a single institution, together with the existing data from the literature, confirms that CT-guided RFA is effective and safe for the treatment of osteoid osteoma, even in atypical, early onset in children under 4 years of age.
Is the Tea Bag Index (TBI) Useful for Comparing Decomposition Rates among Soils?
Authors: Mori Taiki
Published: November 2022

The Bag Index (TBI) is a novel approach using standardized materials (i.e., commercial tea bags) to evaluate organic matter decomposition by determining two indexes: the early stage decomposition constant k (k_TBI) and litter stabilization factor S (S_TBI). k_TBI is defined as the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea, whereas S is the ratio of the stabilized to total hydrolysable fractions of green tea. However, it was recently revealed that both k_TBI and S_TBI deviate from the actual S and k values accurately determined by fitting an asymptote model to the time series mass of green and rooibos teas remaining (k_fitting and S_fitting, respectively). Nevertheless, k_TBI and S_TBI, which can be determined in a cost- and labor-effective manner, might indicate the relative values of k_fitting and S_fitting across different soils and be useful for comparative analyses. Therefore, this study investigated the positive correlations of k_TBI and S_TBI with k_fitting and S_fitting, respectively, in which case these indexes are useful for comparative analyses. However, the result showed that k_TBI was negatively correlated with k_fitting. This study underscores the importance of obtaining time-series data for accurately determining the decomposition constant of an asymptote model describing the decomposition curve of rooibos tea. S_TBI was positively correlated with S_fitting, implying that S_TBI can be used as an indicator of S.
Assessment of Chemical Properties, Heavy Metals, and Metalloid Contamination in Floodplain Soils under the Influence of Copper Mining: A Case Study of Sibay, Southern Urals
Authors: Suleymanov Ruslan , Dorogaya Ekaterina , Gareev Aufar , Minnegaliev Aleksandr , Gaynanshin Mansur , Zaikin Sergey , Belan Larisa , Tuktarova Iren , Suleymanov Azamat
Published: November 2022

The ecotoxicological condition of soils around mining areas is most often unsatisfactory, which affects entire ecosystems and human health. This research sought to analyze the morphological, agrochemical properties, and content of heavy metals (Cd, Cu, Zn) and metalloids (As) of soils located in a floodplain. The study was conducted within the city of Sibay (Republic of Bashkortostan, Russia). The soil samples were collected from the floodplains of the rivers Karagayly and Khudolaz. According to morphological studies, the soil cover was represented by the Lithic Leptosols, Stagnic Phaeozems, and Fluvisols. The results showed that the soils were characterized by high values of organic matter, potassium, and low levels of phosphorus. Soils that were located away from the city in the Karagayly River were not contaminated. However, the floodplain areas pertaining to the urban district and located near the quarries were characterized by severe anthropogenic soil pollution, disrupted integrity of the soil cover, decreased vegetation, and accumulating labile forms of heavy metals and metalloids. The highest degree of pollution was observed in the floodplain soil of the river Khudolaz where all elements exceeded the maximum permissible concentration (MPC) level. Soils in the floodplain of the Karagayly river were marked by an increased degree of contamination of Zn: exceeding MPC by 1.6 times. With the trend toward an arid climate, the ecotoxicological condition of floodplain soils is an important challenge.
The Lawson’s Test for Scientific Reasoning as a Predictor for University Formative Success: A Prospective Study
Authors: Sapia Peppino , Napoli Federica , Bozzo Giacomo
Published: November 2022

Scientific Seasoning skills are crucial, both for successful learning in STEM areas and for the development of citizenship-oriented scientific literacy. The Lawson Test for Scientific Reasoning (LTSR) has been credited in the past for predicting the formative success of university students. In this context, we conducted a prospective study on a cohort (N = 1015) of university freshmen enrolled in science or engineering bachelor’s degrees, following them over three years. The freshmen were administered LTSR at the beginning of their university careers. At the end of the regular degree path duration, their formative achievement was measured. The descriptive statistical and correlational analysis of the collected data suggest a significant predictivity of the LTSR of formative success, in particular, for the people who scored highly in the test, while a low score performance does not seem correlated to a reduced formative success. Differentiated correlations are observed for the five conceptual dimensions that were explored by LTSR. The results presented could be useful in inspiring secondary school educational paths specifically aimed to promote students’ skills in the various conceptual dimensions of the Scientific Reasoning. Moreover, the possible predictivity for post-secondary educational success could make LTSR a useful operational tool for effective outgoing guidance actions in high schools.
Editorial for Special Issue on Regulation and Ethical Practice for Educational Research
Authors: Busher Hugh , Fox Alison
Published: November 2022

The Education Sciences Special Issue, Regulation and Ethical Practice for Educational Research, focuses on the ethical aspects of the generation of knowledge in educational research to examine learning, the relationships between learners, educators, organizational leaders and other stakeholders and how those relationships are affected by people’s social and cultural backgrounds and contexts. It argues that democratic and situated approaches to research are needed for researchers to consider critically the power imbalances bound up in their relationships with participants and other stakeholders in their projects. This involves finding ways to hear and compare the different voices and perspectives of those in these relationships to address the power imbalance that are inherent when carrying out research.
Health Monitoring of Conveyor Belt Using UHF RFID and Multi-Class Neural Networks
Authors: Zohra Fatema Tuz , Salim Omar , Masoumi Hossein , Karmakar Nemai C. , Dey Shuvashis
Published: November 2022

Conveyor belts in mining sites are prone to cracks, which leads to dramatic degradation of overall system performance and the breakdown of operation. Crack detection using radio frequency identification (RFID) sensing technology is recently proposed to provide robust and low-cost health monitoring systems for conveyor belts. The intelligent machine learning (ML) technique is one of the most promising solutions for crack detection and successful implementation within the IoT paradigm. This paper presents a conveyor belt structural health monitoring (SHM) model using ML and Internet of Things (IoT) connectivity. The model is extensively tested, and the classification is conducted based on simulated data obtained from an Ultra High Frequency (UHF) RFID sensor. Here, the sensor is laid on a belt, and the data are obtained at different crack orientations of vertical, horizontal, and diagonal cracks, for varying crack widths of 0.5 to 5 mm at 10 different locations on the sensor. The ML model is tested with different input features and training algorithms, and their performances are compared and analysed to identify the superior input feature and training algorithm. This method produces high accuracy in determining crack width, orientation, and location. The findings show that the proposed detection system based on ML modelling could detect cracks with 100% accuracy. The proposed system can also distinguish between vertical, horizontal, and diagonal cracks with an accuracy of 83.9%, and has a significant identification rate of 84.4% accuracy for detecting crack-width as narrow as 0.5 mm. Moreover, the model can predict the region of the crack with an accuracy of 95.5%. Overall, the results show that the proposed model is very robust and can perform SHM of conveyor belts with high accuracy for a range of parameters and classification scenarios. The method has huge industrial significance in coal mines.
Remote Heart Rate Estimation by Pulse Signal Reconstruction Based on Structural Sparse Representation
Authors: Han Jie , Ou Weihua , Xiong Jiahao , Feng Shihua
Published: November 2022

In recent years, the physiological measurement based on remote photoplethysmography has attracted wide attention, especially since the epidemic of COVID-19. Many researchers paid great efforts to improve the robustness of illumination and motion variation. Most of the existing methods divided the ROIs into many sub-regions and extracted the heart rate separately, while ignoring the fact that the heart rates from different sub-regions are consistent. To address this problem, in this work, we propose a structural sparse representation method to reconstruct the pulse signals (SSR2RPS) from different sub-regions and estimate the heart rate. The structural sparse representation (SSR) method considers that the chrominance signals from different sub-regions should have a similar sparse representation on the combined dictionary. Specifically, we firstly eliminate the signal deviation trend using the adaptive iteratively re-weighted penalized least squares (Airpls) for each sub-region. Then, we conduct the sparse representation on the combined dictionary, which is constructed considering the pulsatility and periodicity of the heart rate. Finally, we obtain the reconstructed pulse signals from different sub-regions and estimate the heart rate with a power spectrum analysis. The experimental results on the public UBFC and COHFACE datasets demonstrate the significant improvement for the accuracy of the heart rate estimation under realistic conditions.
N-Beats as an EHG Signal Forecasting Method for Labour Prediction in Full Term Pregnancy
Authors: Jossou Thierry Rock , Tahori Zakaria , Houdji Godwin , Medenou Daton , Lasfar Abdelali , Sanya Fréjus , Ahouandjinou Mêtowanou Héribert , Pagliara Silvio M. , Haleem Muhammad Salman , Et-Tahir Aziz
Published: November 2022

The early prediction of onset labour is critical for avoiding the risk of death due to pregnancy delay. Low-income countries often struggle to deliver timely service to pregnant women due to a lack of infrastructure and healthcare facilities, resulting in pregnancy complications and, eventually, death. In this regard, several artificial-intelligence-based methods have been proposed based on the detection of contractions using electrohysterogram (EHG) signals. However, the forecasting of pregnancy contractions based on real-time EHG signals is a challenging task. This study proposes a novel model based on neural basis expansion analysis for interpretable time series (N-BEATS) which predicts labour based on EHG forecasting and contraction classification over a given time horizon. The publicly available TPEHG database of Physiobank was exploited in order to train and test the model, where signals from full-term pregnant women and signals recorded after 26 weeks of gestation were collected. For these signals, the 30 most commonly used classification parameters in the literature were calculated, and principal component analysis (PCA) was utilized to select the 15 most representative parameters (all the domains combined). The results show that neural basis expansion analysis for interpretable time series (N-BEATS) forecasting can forecast EHG signals through training after few iterations. Similarly, the forecasting signal’s duration is determined by the length of the recordings. We then deployed XG-Boost, which achieved the classification accuracy of 99 percent, outperforming the state-of-the-art approaches using a number of classification features greater than or equal to 15.
Environmental Sound Classification Algorithm Based on Region Joint Signal Analysis Feature and Boosting Ensemble Learning
Authors: Jin Weiyun , Wang Xiao , Zhan Yi
Published: November 2022

Environmental sound classification is an important branch of acoustic signal processing. In this work, a set of sound classification features based on audio signal perception and statistical analysis are proposed to describe the signal from multiple aspects of the time and frequency domain. Energy features, spectral entropy features, zero crossing rate (ZCR), and mel-frequency cepstral coefficient (MFCC) are combined to form joint signal analysis (JSA) features to improve the signal expression of the features. Then, based on the JSA, a novel region joint signal analysis feature (RJSA) for environment sound classification is also proposed. It can reduce feature extraction computation and improve feature stability, robustness, and classification accuracy. Finally, a sound classification framework based on the boosting ensemble learning method is provided to improve the classification accuracy and model generalization. The experimental results show that compared with the highest classification accuracy of the baseline algorithm, the environmental sound classification algorithm based on our proposed RJSA features and ensemble learning methods improves the classification accuracy, and the accuracy of the LightGBM-based sound classification algorithm improves by 14.6%.
Study of Multiple Discontinuous Conduction Modes in SEPIC, Ćuk, and Zeta Converters
Authors: Murillo-Yarce Duberney , Restrepo Carlos , Lamar Diego G. , Hernando Marta M. , Sebastián Javier
Published: November 2022

In this paper, we studied the discontinuous conduction modes (DCMs) of modified versions of the SEPIC, Ćuk, and Zeta converters. The modified versions of these converters were obtained by adding an extra diode to the classical versions of these converters; thus, we obtained converters with multiple DCMs. In the case of the SEPIC and Ćuk converters, the additional diode was added in series with the inductor placed at the input port, thus resembling the connection of a four-diode bridge rectifier at the input (where these converters work as power factor correctors in AC/DC conversion). The 2 diodes of the modified versions of these converters define 4 possible conduction modes: 1 continuous conduction mode (CCM) and 3 DCMs. In this paper, the 4 conduction modes were exhaustively studied, calculating their voltage conversion ratios and the equations of the curves that define the borders between conduction modes in both open- and closed-loop operations. The conduction modes and the straight line that describes the converter operation are represented in a plane called the “k1k2 plane”. As in the case of other characteristics exhibited by the SEPIC, Ćuk, and Zeta converters, the conduction modes, the voltage conversion ratios in each conduction mode, and the boundaries between conduction modes, coincide for the three studied converters. Finally, all theoretical predictions resulting from the analysis were verified experimentally through a reconfigurable converter prototype, working as both modified SEPIC and modified Ćuk converters.
Food Recognition and Food Waste Estimation Using Convolutional Neural Network
Authors: Lubura Jelena , Pezo Lato , Sandu Mirela Alina , Voronova Viktoria , Donsì Francesco , Šic Žlabur Jana , Ribić Bojan , Peter Anamarija , Šurić Jona , Brandić Ivan , Klõga Marija , Ostojić Sanja , Pataro Gianpiero , Virsta Ana , Oros (Daraban) Ana Elisabeta , Micić Darko , Đurović Saša , De Feo Giovanni , Procentese Alessandra , Voća Neven
Published: November 2022

In this study, an evaluation of food waste generation was conducted, using images taken before and after the daily meals of people aged between 20 and 30 years in Serbia, for the period between 1 January and 31 April in 2022. A convolutional neural network (CNN) was employed for the tasks of recognizing food images before the meal and estimating the percentage of food waste according to the photographs taken. Keeping in mind the vast variates and types of food available, the image recognition and validation of food items present a generally very challenging task. Nevertheless, deep learning has recently been shown to be a very potent image recognition procedure, while CNN presents a state-of-the-art method of deep learning. The CNN technique was implemented to the food detection and food waste estimation tasks throughout the parameter optimization procedure. The images of the most frequently encountered food items were collected from the internet to create an image dataset, covering 157 food categories, which was used to evaluate recognition performance. Each category included between 50 and 200 images, while the total number of images in the database reached 23,552. The CNN model presented good prediction capabilities, showing an accuracy of 0.988 and a loss of 0.102, after the network training cycle. The average food waste per meal, in the frame of the analysis in Serbia, was 21.3%, according to the images collected for food waste evaluation.
Accelerated Chambolle Projection Algorithms for Image Restoration
Authors: Wei Wenyang , Feng Xiangchu
Published: November 2022

In this paper, the accelerated Chambolle projection algorithms based on Frank–Wolfe have been proposed. For solving the image restoration under the additive Gaussian noise, the Chambolle projection method (CP) is widely used. However, the projection operator has a large computational cost and complex form. By means of the Frank–Wolfe method, this projection operation can be greatly simplified. We propose two new algorithms, called Chambolle projection based on Frank–Wolfe (CP–FW) and Chambolle projection based on accelerated Frank–Wolfe (CP–AFW). They have a fast convergence rate and low computation cost. Furthermore, we extend the new algorithms to deal with the Poisson noise. The convergence of the new algorithms is discussed, and results of the experiment show their effectiveness and efficiency.