bluuebunny/crossref_metadata_2025 huggingface dataset:
Isolation and Characterization of Cellulose Nanofibers from Wheat Straw and Their Application for the Supercapacitor
Authors: Wang Qing , Han Junying , Wang Xin , Zhao Yawei , Zhang Li , Liu Na , Huang Jihong , Zhai Dandan , Hui Ming
Published: August 2022

As a by-product of wheat planting, wheat straw is an abundant agricultural residue with the highest cellulose content of all agricultural fibers. Its resourceful utilization contributes to alleviating the environmental problems it caused. In this study, cellulose from wheat straw (WS) is used as a dispersing agent to prepare a novel multi-walled carbon nanotube-modified nickel foam (NF) electrode. The new electrode is investigated for electrochemical properties relevant to supercapacitors. The 2,2,6,6-tetramethylpiperidine-1-oxyl (TEMPO) oxidation is chosen to produce cellulose nanofibers (CNF) from wheat straw. The prepared CNF is used to facilitate the uniform dispersion of multi-walled carbon nanotubes (MWCNT) and favor the formation of a stable CNF-CNTs membrane on the nickel foam skeleton. The influence of dispersing materials and content of CNF on the electrochemical performance of electrodes is investigated. It is revealed that the incorporation of CNF can improve the electrochemical stability of electrodes. Moreover, it also exhibits optimum capabilities (70.2% capacitance retention from 1 to 40 mA cm−2) when CNF:MWCNT = 1:0.7. The areal capacity of the CNF-MWCNT/NF electrode for a scanning rate of 5 mV s−1 is twice that of the MWCNT/NF electrode and 30 times that of the NF electrode, indicating it is a promising candidate to ensure the synchronization of a green environment and energy development.
Morphology, Palynology and Molecular Phylogeny of Barleria cristata L. (Acanthaceae) Morphotypes from India
Authors: Tamboli Asif S. , Patil Suraj S. , Kadam Suhas K. , Choo Yeon-Sik , Lekhak Manoj M. , Pak Jae Hong
Published: August 2022

Barleria cristata L., commonly known as the Philippine violet, is native to South Asia. It is an ornamental plant and is also used for the treatment of a variety of diseases. In India, it is found throughout the country in many forms, varying in its floral attributes (calyx and corolla) and habitat. In order to understand the species limits in B. cristata, we studied morphological as well as palynological variation and assessed the phylogenetic relationships among five different morphotypes. The studied morphotypes (populations) came from three phytogeographical regions, namely the Western Ghats, the Deccan Peninsula and the Western Himalaya. The naturally occurring populations from the Deccan Peninsula and the Western Himalaya showed conspicuous differences in their morphology. All the morphotypes had oblate spheroidal, tri-brevicolporate and honey-combed pollen grains which differed only in their quantitative parameters. The distinct-looking morphotypes, namely, Nandi Hills, Uttarakhand and cultivated morphotypes, could not be separated based on pollen characters. Phylogenetic analyses based on chloroplast DNA sequences revealed that our samples formed a clade sister to the B. cristata specimen used in the previous study. The genetic variation within morphotypes was not enough for the genomic regions investigated; however, it revealed among morphotype genealogies in detail. Phylogenetic analyses showed that there were three monophyletic groups within the B. cristata complex that exhibited some morphological differences. Nevertheless, based on the present sampling, it is not possible to delimit these morphotypes at specific or infraspecific level. To reach such conclusions, further investigations like sampling this species across its distribution range in India and assessment of intraspecific relationships, and their cytogenetical characterization should be done.
Carica papaya L.: A Tropical Fruit with Benefits beyond the Tropics
Authors: Koul Bhupendra , Pudhuvai Baveesh , Sharma Chelsi , Kumar Arvind , Sharma Vinay , Yadav Dhananjay , Jin Jun-O
Published: August 2022

Carica papaya L. (family: Caricaceae), also known as ‘papaya,’ is a tropical American fruit tree. Due to the bioactive components (carpaines, BITC, benzyl glucosinolates, latex, papain, zeaxanthin, choline, etc.) in its seeds, leaves, and fruits, it is revered for its excellent antioxidant, digestive, and nutraceutical benefits. Papayas are high in vitamins A, B, C, E, and K, folate, pantothenic acid, zeaxanthin, lycopene, lutein, magnesium, copper, calcium, and potassium. Being rich in fiber, antioxidants, and vitamin C, it lowers the cholesterol in the arteries; prevents arthritis; reduces aging, cancer, macular degradation, risk of cardiovascular diseases, and stress; increases platelet count; controls dengue fever; facilitates digestion, and lowers body weight. Papaya leaf extract, with many in vitro and case studies in combination therapies with modern medicine, especially for cancers and many other viral diseases, has been found to be an efficient cure. Humans have cultivated papaya cultivars for millions of years because of their significant commercial, medicinal, and agronomic value. Several reports have been published on the genetic modification of papaya for resistance to abiotic (herbicide, Al toxicity, etc.) and biotic stressors (PRSV, mites, Phytophthora, etc.), delaying ripening, and improving shelf life. However, most of these traits have not been introduced globally to all commercial papaya varieties. Unraveling the genetics of papaya has shed light on various domestication impacts, evolutionary patterns, and sex determination in fruit tree crops. It also serves as a potential step toward developing new cultivars to fight climate-oriented stress. Furthermore, extensive research on the stability of the ‘transgene’ across generations, and the ‘yield-penalty’ caused by the transgene, is required. Thus, meticulous crop improvement research on commercial papaya cultivars is necessary for long-term food and health security. This review article encompasses information on the traditional and modern medicinal uses, nutritional properties, phytochemistry, diseases and etiology, post-harvest measures, genomics, biotechnological strategies (for papaya improvement), and value-added products of papaya for food and health security.
Comparison of Trophic Niche Position, Size, and Overlap in an Assemblage of Pacific Rockfish (Genus Sebastes) for Testing Community Composition Models
Authors: Suchomel Andrew D. , Belk Mark C.
Published: August 2022

Rockfish (genus Sebastes) assemblages can inform mechanisms of coexistence and maintenance of diversity in ecological communities. Coexistence theory characterizes ecological assemblages as following either a deterministic niche differentiation model, or a stochastic lottery model. We used natural abundances of carbon and nitrogen stable isotopes from the tissues of ten co-occurring species of rockfish to assess position, size, and overlap of trophic niches in this diverse assemblage. We created a stochastic null model and compared observed values against the null model to determine if patterns were consistent with a deterministic or a stochastic model. We classified rockfish species as either demersal or pelagic. Mean δ13C and δ15N values differed among pelagic and demersal rockfish species and mean position was more variable than what was predicted by our null model. All species had relatively small trophic niches compared to occupied trophic niche space for the entire assemblage and trophic niche size was smaller than what was predicted by our null model. Trophic niche overlaps varied from 32% to 189% but were substantially lower than predicted by our null mode. All observed trophic niche metrics were different than the stochastic null model. This rockfish assemblage follows a deterministic model of community composition.
Imperative Role of Machine Learning Algorithm for Detection of Parkinson’s Disease: Review, Challenges and Recommendations
Authors: Rana Arti , Dumka Ankur , Singh Rajesh , Panda Manoj Kumar , Priyadarshi Neeraj , Twala Bhekisipho
Published: August 2022

Parkinson’s disease (PD) is a neurodegenerative disease that affects the neural, behavioral, and physiological systems of the brain. This disease is also known as tremor. The common symptoms of this disease are a slowness of movement known as ‘bradykinesia’, loss of automatic movements, speech/writing changes, and difficulty with walking at early stages. To solve these issues and to enhance the diagnostic process of PD, machine learning (ML) algorithms have been implemented for the categorization of subjective disease and healthy controls (HC) with comparable medical appearances. To provide a far-reaching outline of data modalities and artificial intelligence techniques that have been utilized in the analysis and diagnosis of PD, we conducted a literature analysis of research papers published up until 2022. A total of 112 research papers were included in this study, with an examination of their targets, data sources and different types of datasets, ML algorithms, and associated outcomes. The results showed that ML approaches and new biomarkers have a lot of promise for being used in clinical decision-making, resulting in a more systematic and informed diagnosis of PD. In this study, some major challenges were addressed along with a future recommendation.
The Expression Levels and Concentrations of PD-1 and PD-L1 Proteins in Septic Patients: A Systematic Review
Authors: Sari Mutiara Indah , Ilyas Syafruddin
Published: August 2022

Sepsis is a series of life-threatening organ dysfunction caused by an impaired host response to infection. A large number of molecular studies of sepsis have revealed complex interactions between infectious agents and hosts that result in heterogeneous manifestations of sepsis. Sepsis can cause immunosuppression and increase the expression of checkpoint inhibitor molecules, including programmed death protein (PD-1) and programmed death ligand 1 (PD-L1), and thus PD-1 and PD-L1 are thought to be useful as diagnostic and prognostic tools for sepsis. PD-1 is an inhibitor of both adaptive and innate immune responses, and is expressed on activated T lymphocytes, natural killer (NK) cells, B lymphocytes, macrophages, dendritic cells (DCs), and monocytes, whereas PD-L1 is expressed on macrophages, some activated T and B cells, and mesenchymal stem cells as well as various non-hematopoietic cells. This systematic review aims to assess the PD-1 and PD-L1 protein expression levels and concentrations in septic and other infectious patients.
The Role of Fluorescence In Situ Hybridization in the Surveillance of Non-Muscle Invasive Bladder Cancer: An Updated Systematic Review and Meta-Analysis
Authors: Zheng Weitao , Lin Tianhai , Chen Zeyu , Cao Dehong , Bao Yige , Zhang Peng , Yang Lu , Wei Qiang
Published: August 2022

Background: Fluorescence in situ hybridization (FISH) has become a popular biomarker for subsequent monitoring the recurrence of non-muscle invasive bladder cancer (NMIBC), several studies have investigated the ability of FISH to detect recurrence in the surveillance of NMIBC. However, the results were inconsistent. Methods: We conducted a systematic literature search extensively on authenticated databases including PubMed/Medline, Embase, Web of Science, Ovid, and Cochrane Library. Meta-analysis was performed to find out the sensitivity and specificity of FISH in predicting recurrence of NMIBC. Results: 15 studies were ultimately included in this meta-analysis, a total of 2941 FISH evaluations from 2385 NMIBC patients were available. The pooled sensitivity of FISH was 68% (95% CI: 0.58–0.76), and the pooled specificity was 64% (95% CI: 0.53–0.74). Subgroup analyses were performed in 7 studies without Bacillus Calmette–Guerin (BCG) treatment, the pooled sensitivity was 82% (95% CI: 0.68–0.90), and the pooled specificity was 63% (95% CI: 0.37–0.82). And in 9 studies using “UroVysion standard” to define positive FISH results showed a pooled sensitivity of 60% (95% CI: 0.50–0.70) and specificity of 70% (95% CI: 0.61–0.78). Conclusions: The findings of this study indicate that FISH has a satisfactory sensitivity (68%) and specificity (64%) and could be a potential biomarker in the surveillance of NMIBC. Moreover, BCG treatment and different FISH methods may have an impact on the sensitivity and specificity, these factors should be taken into account when making clinical strategy.
Dentigerous Cysts with Diverse Radiological Presentation Highlighting Diagnostic Challenges
Authors: Perez Alexandre , Lenoir Vincent , Lombardi Tommaso
Published: August 2022

Dentigerous cyst is an odontogenic developmental cyst arising from the pericoronal tissue of an impacted tooth, and that may exhibit various radiological aspects. The aim of this article is to present four cases of histologically confirmed mandibular dentigerous cysts to highlight diverse radiological presentations: one of classical appearance (well-limited unilocular radiolucent lesion surrounding the crown) and three which have shown radiological peculiarities (one cyst displacing the adjacent tooth, with bone but no root resorption, one cyst presenting hallmarks of infection and one multilocular cyst with thin septa). Such radiologic diversity may, on occasion, suggest a clinical aggressive lesion such as an odontogenic keratocyst or ameloblastoma. The diagnosis of dentigerous cyst requires a thorough evaluation of the clinical presentation and accurate radiological studies.
Changes in Cystoscopic Findings after Intravesical Hyaluronic Acid Instillation Therapy in Patients with Interstitial Cystitis
Authors: Lin Chia-Ju , Liu Chih-Ku , Hsieh Hsiao-Yun , Chen Ming-Jer , Tsai Ching-Pei
Published: August 2022

(1) Background: Limited data showed changes in glomerulation in the bladder mucosa of patients with interstitial cystitis (IC) after intravesical hyaluronic acid (HA) bladder infusion. We aimed to investigate the above changes. (2) Methods: Medical records of IC patients were reviewed retrospectively, from January 2010 to October 2019. Patients who had received repeated cystoscopy after intravesical HA treatment were enrolled. The associations of multiple parameters, including the ages, symptoms, initial glomerulation stage, HA doses, and the interval period of repeated cystoscopy between the glomerulation change in the repeated cystoscopy were analyzed. (3) Results: Among the 35 patients, 9 cases (25.7%) showed better glomerulation grades in the repeated cystoscope (Group 1), 20 cases (57.1%) showed the same grades (Group 2), and 6 cases showed worse grades (Group 3). No difference was seen in the initial grades or treatment course among the three groups. The interval periods from the initial to the repeated cystoscopy of Group 1 were longer than Group 2 and Group 3 (p = 0.031). Group 3 presents an elder age trend than the other two groups. (4) Conclusion: Intravesical HA repaired bladder glomerulation in a small group of patients with IC. Prolonged treatment has potential benefits, while older age is possibly a negative factor. However, no strong correlation was found between the initial glomerulation grades or changes in glomerulation grades with clinical symptoms.
Imaging More than Skin-Deep: Radiologic and Dermatologic Presentations of Systemic Disorders
Authors: Shafiei Mehrzad , Shomal Zadeh Firoozeh , Mansoori Bahar , Pyle Hunter , Agim Nnenna , Hinojosa Jorge , Dominguez Arturo , Thomas Cristina , Chalian Majid
Published: August 2022

Background: Cutaneous manifestations of systemic diseases are diverse and sometimes precede more serious diseases and symptomatology. Similarly, radiologic imaging plays a key role in early diagnosis and determination of the extent of systemic involvement. Simultaneous awareness of skin and imaging manifestations can help the radiologist to narrow down differential diagnosis even if imaging findings are nonspecific. Aims: To improve diagnostic accuracy and patient care, it is important that clinicians and radiologists be familiar with both cutaneous and radiologic features of various systemic disorders. This article reviews cutaneous manifestations and imaging findings of commonly encountered systemic diseases. Conclusions: Familiarity with the most disease-specific skin lesions help the radiologist pinpoint a specific diagnosis and consequently, in preventing unnecessary invasive workups and contributing to improved patient care.
Custom 3D fMRI Registration Template Construction Method Based on Time-Series Fusion
Authors: Wang Zhongyang , Xin Junchang , Shen Huixian , Chen Qi , Wang Zhiqiong , Wang Xinlei
Published: August 2022

As the brain standard template for medical image registration has only been constructed with an MRI template, there is no three-dimensional fMRI standard template for use, and when the subject’s brain structure is quite different from the standard brain structure, the registration to the standard space will lead to large errors. Registration to an individual space can avoid this problem. However, in the current fMRI registration algorithm based on individual space, the reference image is often selected by researchers or randomly selected fMRI images at a certain time point. This makes the quality of the reference image very dependent on the experience and ability of the researchers and has great contingency. Whether the reference image is appropriate and reasonable affects the rationality and accuracy of the registration results to a great extent. Therefore, a method for constructing a 3D custom fMRI template is proposed. First, the data are preprocessed; second, by taking a group of two-dimensional slices corresponding to the same layer of the brain in three-dimensional fMRI images at multiple time points as image sequences, each group of slice sequences are registered and fused; and finally, a group of fused slices corresponding to different layers of the brain are obtained. In the process of registration, in order to make full use of the correlation information between the sequence data, the feature points of each two slices of adjacent time points in the sequence are matched, and then according to the transformation relationship between the adjacent images, they are recursively forwarded and mapped to the same space. Then, the fused slices are stacked in order to form a three-dimensional customized fMRI template with individual pertinence. Finally, in the classic registration algorithm, the difference in the registration accuracy between using a custom fMRI template and different standard spaces is compared, which proves that using a custom template can improve the registration effect to a certain extent.
Special Issue: Next-Generation Sequencing in Tumor Diagnosis and Treatment II
Authors: Malapelle Umberto , Fassan Matteo , de Biase Dario
Published: August 2022

Next-generation sequencing (NGS) allows for the sequencing of multiple genes at a very high depth of coverage [...]
Unconventional Obturator Artery Nutrient Branch: Image of an Anatomical Variation
Authors: Bosse Benjamin L. , Palacios Victoria J. , Dutcher Dustin W. , Etter Emily J. , Lim Peter C. , Cobine Caroline A. , Moritz Gillian L.
Published: August 2022

Variations in vascular anatomy are of great concern to surgeons, as proper identification of aberrant arteries can reduce the risk of iatrogenic injury and improve patient outcomes. Several studies have highlighted the irregular branching pattern of pelvic arteries, with a recent focus on the obturator artery (OA). The OA has an inconstant origin from the internal iliac artery, external iliac artery, or inferior epigastric artery. Within the pelvis, the OA can give off muscular branches and nutrient vessels to the ilium and pubis. Though occasionally described in text, few resources employ images of human donors that depict branches arising from the OAs. Out of the 34 hemisected pelves studied, we identified 1 individual with a substantial nutrient vessel branching unilaterally from the OA. Herein, we present the first image of this unconventional nutrient artery. This vessel should be highlighted given that its size and course make it particularly vulnerable during intrapelvic surgeries such as pelvic lymph node dissection or in procedures requiring arterial embolization of the OA.
Assessment of Pulpal Status in Primary Teeth Following Direct Pulp Capping in an Experimental Canine Model
Authors: Igna Andreea , Igna Cornel , Miron Mariana Ioana , Schuszler Larisa , Dascălu Roxana , Moldovan Mihaela , Voicu Adrian Aristide , Todea Carmen Darinca , Boariu Marius , Mârțu Maria-Alexandra , Stratul Ștefan-Ioan
Published: August 2022

(1) Background: This study aimed to assess the pulpal response of primary teeth by pulse-oximetry (PO) in a canine model, following direct pulp capping (DPC). (2) Methods: Forty-eight primary teeth from eight canine subjects were divided into three treatment groups, based on the DPC material—calcium hydroxide (CH), MTA, BiodentineTM)—and three corresponding control groups. Data from PO pulp testing were correlated with laser Doppler flowmetry (LDF) testing, computer tomographic (CT) densitometry and histological analysis; the experiment lasted 14 days. (3) Results: SpO₂ recordings revealed statistically significant differences (p = 0.002, <0.05) between the treatment and control groups, and no significant differences (p = 0.257, >0.05) were observed between treatment groups. LDF recordings showed significant differences (p = 0.002, <0.05) between the treatment and control groups and identified significant differences between materials (p = 0.001, <0.05). CT densitometry indicated vital pulps in all teeth, with pulpal inflammation detected in 6/8 CH-capped teeth and 2/8 MTA-capped teeth. Histologic evaluation confirmed vital pulp in all specimens, with different degrees of inflammation. (4) Conclusions: Within its limitations, the present study confirms the diagnostic value of PO evaluation of pulpal status in primary teeth with histologic means after pulp-capping procedures in a canine model. However, various degrees of pulpal inflammation elicited by different pulp-capping materials seem not to correlate with the obtained PO values.
Advancing Brain Metastases Detection in T1-Weighted Contrast-Enhanced 3D MRI Using Noisy Student-Based Training
Authors: Dikici Engin , Nguyen Xuan V. , Bigelow Matthew , Ryu John L. , Prevedello Luciano M.
Published: August 2022

The detection of brain metastases (BM) in their early stages could have a positive impact on the outcome of cancer patients. The authors previously developed a framework for detecting small BM (with diameters of <15 mm) in T1-weighted contrast-enhanced 3D magnetic resonance images (T1c). This study aimed to advance the framework with a noisy-student-based self-training strategy to use a large corpus of unlabeled T1c data. Accordingly, a sensitivity-based noisy-student learning approach was formulated to provide high BM detection sensitivity with a reduced count of false positives. This paper (1) proposes student/teacher convolutional neural network architectures, (2) presents data and model noising mechanisms, and (3) introduces a novel pseudo-labeling strategy factoring in the sensitivity constraint. The evaluation was performed using 217 labeled and 1247 unlabeled exams via two-fold cross-validation. The framework utilizing only the labeled exams produced 9.23 false positives for 90% BM detection sensitivity, whereas the one using the introduced learning strategy led to ~9% reduction in false detections (i.e., 8.44). Significant reductions in false positives (>10%) were also observed in reduced labeled data scenarios (using 50% and 75% of labeled data). The results suggest that the introduced strategy could be utilized in existing medical detection applications with access to unlabeled datasets to elevate their performances.
A Scoping Review of Empirical Literature on People with Intellectual Disability in Nigeria
Authors: Sango Precious Nonye , Deveau Roy
Published: August 2022

Intellectual disability (ID) is an emerging field of research in Nigeria. This review seeks to identify what has been published in order to describe the evidence and to identify the major gaps in knowledge and practice. A systematic search of five databases and an African disability journal yielded 15 papers that reported on empirical studies related to people with ID in Nigeria. Fifteen studies across the databases and journal searched met the inclusion criteria. The participants included adults and children with ID and their families. Twelve of the papers employed quantitative methods, two were qualitative and one was a mixed methods study. There is a paucity of empirical research on people with ID in Nigeria, thus emphasising the need for more primary research about people with ID living in Nigeria. Nigeria is estimated to have the largest population of people with disabilities in Africa; however, this review found limited empirical work regarding their lives, prevalence and care. This limited evidence hinders the understanding of the challenges people with an intellectual disability face and potentially inhibit the creation of policy-oriented solutions to their plights in a globalised world.
Oral Hygiene Practices among Adults with Intellectual Disabilities—A Pilot Study
Authors: Abdullah Muhammad Afif Hakimin , Sa’idah Ishak Nurul , Knights Joe , Dhaliwal Sachinjeet Kaur Sodhi , Ming Long Chiau , Dhaliwal Jagjit Singh
Published: August 2022

It is known that the oral health status of people with intellectual disabilities (IDs) is likely to be compromised as compared with the general population. Until recently, the trend of oral hygiene among the adult population with intellectual disabilities in Brunei Darussalam had yet to be studied. Thus, the aim of this study was to determine the oral hygiene practices, oral health knowledge and dental appointment patterns among the adult population with IDs in Brunei Darussalam. A cross-sectional study was conducted at different service providers in Brunei Darussalam for adults with IDs. An easy-to-read questionnaire was distributed to the participants. The responses of the questionnaire for IDs were analyzed. A total of 34 participants were recruited. It was found that all participants were practicing their daily oral hygiene routine. In terms of dental visits, more than half visit the dentist at least once a year. The majority of the participants agreed that visiting the dentist every 6 months was essential. This study showed that adults with IDs in Brunei Darussalam were aware of the importance of oral health and were maintaining their daily oral hygiene, although not with the ideal method. It is important for clinicians to not only educate the individuals with IDs but also their carer(s) when it comes to oral health knowledge, as carers play a key role in the oral health of the people under their care.
Task Allocation of Multiple Unmanned Aerial Vehicles Based on Deep Transfer Reinforcement Learning
Authors: Yin Yongfeng , Guo Yang , Su Qingran , Wang Zhetao
Published: August 2022

With the development of UAV technology, the task allocation problem of multiple UAVs is remarkable, but most of these existing heuristic methods are easy to fall into the problem of local optimization. In view of this limitation, deep transfer reinforcement learning is applied to the task allocation problem of multiple unmanned aerial vehicles, which provides a new idea about solving this kind of problem. The deep migration reinforcement learning algorithm based on QMIX is designed. The algorithm first compares the target task with the source task in the strategy base to find the task with the highest similarity, and then migrates the network parameters obtained from the source task after training, stored in the strategy base, so as to accelerate the convergence of the QMIX algorithm. Simulation results show that the proposed algorithm is significantly better than the traditional heuristic method of allocation in terms of efficiency and has the same running time.
Weld Seam Identification and Tracking of Inspection Robot Based on Deep Learning Network
Authors: Li Jie , Li Beibei , Dong Linjie , Wang Xingsong , Tian Mengqian
Published: August 2022

The weld seams of large spherical tank equipment should be regularly inspected. Autonomous inspection robots can greatly enhance inspection efficiency and save costs. However, the accurate identification and tracking of weld seams by inspection robots remains a challenge. Based on the designed wall-climbing robot, an intelligent inspection robotic system based on deep learning is proposed to achieve the weld seam identification and tracking in this study. The inspection robot used mecanum wheels and permanent magnets to adsorb metal walls. In the weld seam identification, Mask R-CNN was used to segment the instance of weld seams. Through image processing combined with Hough transform, weld paths were extracted with a high accuracy. The robotic system efficiently completed the weld seam instance segmentation through training and learning with 2281 weld seam images. Experimental results indicated that the robotic system based on deep learning was faster and more accurate than previous methods, and the average time of identifying and calculating weld paths was about 180 ms, and the mask average precision (AP) was about 67.6%. The inspection robot could automatically track seam paths, and the maximum drift angle and offset distance were 3° and 10 mm, respectively. This intelligent weld seam identification system will greatly promote the application of inspection robots.
Multiobjective Optimization of a Fed-Batch Bienzymatic Reactor for Mannitol Production
Authors: Maria Gheorghe , Renea Laura , Maria Cristina
Published: August 2022

Enzymatic reactions can successfully replace complex chemical syntheses using milder reaction conditions and generating less waste. The developed model-based numerical analysis turned out to be a beneficial tool to determine the optimal operating policies of complex multienzymatic reactors. As proved, for such cases, the determination of a Fed-Batch Reactor (FBR) optimal operating policy results in a difficult multiobjective optimization problem. Exemplification is made for the bienzymatic reduction of D-fructose to mannitol by using MDH (mannitol dehydrogenase) and nicotinamide adenine dinucleotide (NADH) cofactor with the in situ continuous regeneration of NADH at the expense of formate degradation in the presence of FDH (formate dehydrogenase). For such a coupled system, the model-based engineering evaluations must account for multiple competing (opposable) optimization objectives. Among the multiple novelty elements: i) an optimally operated FBR with a tightly controlled variable feeding (of the time stepwise type) during the batch can lead to higher performance; ii) the optimally operated FBR reported better performance compared to an optimally single or cyclic BR, or to optimally serial batch-to-batch reactors (SeqBR), when considering a multiobjective optimization; iii) the concomitant variable feeding with substrate, enzymes, and cofactor during the FBR “time-arcs” is an option seldom approached in the literature but which is proved here, leading to consistent economic benefits.
Modeling Dual-Drive Gantry Stages with Heavy-Load and Optimal Synchronous Controls with Force-Feed-Forward Decoupling
Authors: Xie Hanjun , Wang Qinruo
Published: August 2022

The application of precision dual-drive gantry stages in intelligent manufacturing is increasing. However, the loads of dual drive motors can be severely inconsistent due to the movement of heavy loads on the horizontal crossbeam, resulting in synchronization errors in the same direction movement of dual-drive motors. This phenomenon affects the machining accuracy of the gantry stage and is an critical problem that should be immediately solved. A novel optimal synchronization control algorithm based on model decoupling is proposed to solve the problem. First, an accurate physical model is established to obtain the essential characteristics of the heavy-load dual-drive gantry stage in which the rigid-flexible coupling dynamic is considered. It includes the crossbeam’s linear motion and rotational motion of the non-constant moment of inertia. The established model is verified by using the actual system. By defining the virtual centroid of the crossbeam, the cross-coupling force between dual-drive motors is quantified. Then, the virtual-centroid-based Gantry Synchronization Linear Quadratic Regulator (GSLQR) optimal control and force-Feed-Forward (FF) decoupling control algorithm is proposed. The result of the comparative experiment shows the effectiveness and superiority of the proposed algorithm.
Linear Full Decoupling, Velocity Correction Method for Unsteady Thermally Coupled Incompressible Magneto-Hydrodynamic Equations
Authors: Zhang Zhe , Su Haiyan , Feng Xinlong
Published: August 2022

We propose and analyze an effective decoupling algorithm for unsteady thermally coupled magneto-hydrodynamic equations in this paper. The proposed method is a first-order velocity correction projection algorithms in time marching, including standard velocity correction and rotation velocity correction, which can completely decouple all variables in the model. Meanwhile, the schemes are not only linear and only need to solve a series of linear partial differential equations with constant coefficients at each time step, but also the standard velocity correction algorithm can produce the Neumann boundary condition for the pressure field, but the rotational velocity correction algorithm can produce the consistent boundary which improve the accuracy of the pressure field. Thus, improving our computational efficiency. Then, we give the energy stability of the algorithms and give a detailed proofs. The key idea to establish the stability results of the rotation velocity correction algorithm is to transform the rotation term into a telescopic symmetric form by means of the Gauge–Uzawa formula. Finally, numerical experiments show that the rotation velocity correction projection algorithm is efficient to solve the thermally coupled magneto-hydrodynamic equations.
Environment-Assisted Modulation of Heat Flux in a Bio-Inspired System Based on Collision Model
Authors: Pedram Ali , Çakmak Barış , Müstecaplıoğlu Özgür E.
Published: August 2022

The high energy transfer efficiency of photosynthetic complexes has been a topic of research across many disciplines. Several attempts have been made in order to explain this energy transfer enhancement in terms of quantum mechanical resources such as energetic and vibration coherence and constructive effects of environmental noise. The developments in this line of research have inspired various biomimetic works aiming to use the underlying mechanisms in biological light harvesting complexes for the improvement of synthetic systems. In this article, we explore the effect of an auxiliary hierarchically structured environment interacting with a system on the steady-state heat transport across the system. The cold and hot baths are modeled by a series of identically prepared qubits in their respective thermal states, and we use a collision model to simulate the open quantum dynamics of the system. We investigate the effects of system-environment, inter-environment couplings and coherence of the structured environment on the steady state heat flux and find that such a coupling enhances the energy transfer. Our calculations reveal that there exists a non-monotonic and non-trivial relationship between the steady-state heat flux and the mentioned parameters.
Price Transmission Analysis of the International Soybean Market in a Trade War Context
Authors: Barboza Martignone Gustavo , Behrendt Karl , Paparas Dimitrios
Published: August 2022

This study analysed the dynamics of the international soybean market using econometric techniques and economic models to study the impacts of the US–China trade war. It considered the analysis of “spatial” (horizontal) price transmission during an approximately ten-year period from September 2009 to May 2019 using monthly time-series data. The research focused on the leaders in the international soybean market, namely, China, the USA, the EU, Brazil and Argentina. Several econometric techniques were employed. The stationarity of the price time series was determined using the augmented Dickey–Fuller (ADF) unit root test. Structural breaks were inferred using the ADF test with a breaks test and a Bai–Perron multiple break test. The long-term relation/cointegration amongst the series was determined using the Johansen cointegration test (1988), with the previous breaks input as dummy variables. The direction of the causality was inferred using the Granger causality test (1969). The long-term and short-term causal relations were determined using the vector autoregression model (VAR) and the vector error correction model (VECM). The results showed a highly efficient and cointegrated market. The incidents of the trade war, as represented by tariffs and subsidies, had minor effects on the market efficacy, cointegration and price transmission. The arbitrage process of the studied market managed to get around the tariffs. In other words, there was no empirical evidence to support the claim that the law of one price (LOOP) did not hold.
Pursuing Social Justice in Educational Robotics
Authors: Wallace Manolis , Poulopoulos Vassilis
Published: August 2022

In educational systems that make their first attempt to incorporate STEAM concepts in their teaching, educational robotics is typically the place to start; robotics kits are purchased, and a small group of pupils is typically selected to develop a project and perhaps to also take part in some local or national robotics competition. Whilst this can be a very stimulating and rewarding experience for the participating pupils, it does little to introduce STEAM to the rest of the pupils in the school. In this article, we present our work towards a more fair and socially just approach to educational robotics. Compared with the conventional approach to educational robotics, our work introduces the following novelties: (A) shorter educational programs so that equipment can be re-used, (B) out-of-school implementation so that the programs are accessible to pupils from all schools, even from those schools that do not have teachers willing to be involved in STEAM programs and (C) scaling via the training of teachers who then act as multipliers of our action. The approach was applied, before being interrupted by the COVID-19 pandemic, in a specially developed innovation hub, and the initial results are reported herein. Based on those findings, the potential of our approach to achieve a broader societal impact is highlighted.
Digital Brick: Enhancing the Student Experience Using Blockchain, Open Badges and Recommendations
Authors: Mainetti Luca , Paiano Roberto , Pedone Matteo , Quarta Marco , Dervishi Elton
Published: August 2022

The main purpose of this work is to describe the process of design and implementation of a novel e-Learning platform, named Digital Brick, intended to enhance the students’ experience in obtaining formal certifications of their competencies. The research method we followed starts form a deep study of the state of the art that showed us the need to invest more research effort on delivering open and flexible online environments to enable students in finding and passing courses with final formal certifications of learning. To reach this goal, we (i) designed a complete system architecture around a standard (SCORM compliant) learning management system in order the approach should be reusable as much as possible. We (ii) introduced specific modules to separate responsibilities on the definition and issuing of formal certifications using digital badges according to the IMS Open Badges standard. We (iii) exploited blockchain technology to make the sharing of badges among actors more secure, transparent and open. Finally, we (iv) introduced a new recommendation algorithm based on machine learning techniques to give advice to students about study materials and learning paths. We spent a significant part of our effort carrying out both a functional and quantitative validation of our proposal. The obtained results are presented through a laboratory case study that involves all the components of the architecture, and the outcomes are discussed providing numerical performance indicators. In conclusion, the resulting platform introduces digital badges and blockchain as tools to share recognized achievements among earners and issuers, and machine learning algorithms to provide students with recommendations on the learning material, learning objects, courses and learning paths more suitable for their learning styles.
Hybrid E-Service Learning Practice during COVID-19: Promoting Dog Adoption in Philosophy of Life Course in Taiwan
Authors: Huang Din-Yuang
Published: August 2022

There are several models for e-service learning, from traditional (without any online content) to extreme online service learning (without any actual interactive elements) which suggested by L. S. Waldner. In Type III, (hybrid) e-service learning, the instruction or service can be offered partially onsite and partially online. Waldner cites four successful case studies to prove such a model can work. Teachers should prepare students to participate in service learning during other disasters that may occur anytime, and offer servification dimensions for teaching. Using the Waldner Type III model, this paper aims to promote and stimulate service learning in shelters, as well as onsite and online, for the adoption of animals. Considering this paper is the leading research on the project’s application, we employ a qualitative research method, observing the students’ reflection work to clarify the basic proposition, and to describe what happened when we changed the model of hybrid e-service learning from Type III to Type I during the epidemic.
Creation of Immersive Resources Based on Virtual Reality for Dissemination and Teaching in Chemical Engineering
Authors: Díaz Manuel J. , Mantell Casimiro , Caro Ildefonso , de Ory Ignacio , Sánchez Jezabel , Portela Juan R.
Published: August 2022

Chemical Engineering is a complex discipline that is mainly applied to the industrial context, which makes it difficult to approach real equipment and systems in the classroom to students. Nevertheless, Information and Communication Technologies (ICTs) are particularly useful to encourage active and autonomous learning, normally associated with deeper levels of engagement and understanding of the subjects taught. In this way, several studies have demonstrated that immersion has the potential to increase learning experiences and improve creativity and engagement, Virtual Reality (VR) being a remarkable example. In this context, we created and shared with students two immersive resources based on VR: (a) a laboratory 360° video tour, which was used to disseminate the Chemical Engineering Degree in an Open Door Days organized for high school students; and (b) an experiential learning tool integrated with Moodle, which was available previously to face-to-face practical lessons of the subject Separation Operations. In both cases, the feedback from the participant students was positive. High school students increased their interest in Chemical Engineering Degree after viewing the 360° video, meanwhile undergraduate students found the immersive tool useful in the subsequent performance of real practical activities. From the perspective of professors, creation of these resources required purchase of equipment, time and effort, but they were highly valued as a tool for disseminating and supporting teaching, being an initial starting point for the creation of more enhanced VR-based materials.
Social Differences in Health Behaviours among Jordanian Adolescents
Authors: Alshammari Abdullah S. , Piko Bettina F. , Berki Tamás , Fitzpatrick Kevin M.
Published: August 2022

Social differences are evident in both developed and developing countries. During adolescence, there are limited differences in morbidity and mortality, but differences do appear in terms of health behaviours. This study aims to examine the relationship(s) between social differences and students’ health behaviours. A cross-sectional study was conducted in 2020 with a sample of high school students (N = 2741, aged 13–18 years) in Jordan. Besides descriptive statistics, bivariate logistic regression analysis was used to detect the odds risk for each social difference indicator. Females were engaged in more healthy dietary and hygienic behaviours and less engaged in smoking. Males were more physically active. Adolescents with a higher parental education level were more engaged in healthy behaviours; however, they drank carbonated soft drinks and ate fast food more often. Higher SES (socioeconomic status) self-evaluation was positively associated with eating breakfast and fruit and vegetables, being physically active, drinking carbonated soft drinks, eating fast food, and smoking. Our findings suggest that socioeconomic differences are important to understanding Jordanian adolescents’ health behaviours. While females tend to engage in more healthy behaviours, the role of parental education and perceived family affluence is not always beneficial in terms of adolescents’ dietary habits, hygienic behaviour, or smoking.
Hardware Acceleration of Identifying Barcodes in Multiplexed Nanopore Sequencing
Authors: Hu Wenjie , Zhang Yuxin , Zhang Hongrui , Chen Weigang
Published: August 2022

In multiplexed sequencing, the identification of DNA sequencing barcodes can effectively reduce the probability of sample misassignment. However, the great quantity of sequence data requires a high-throughput identification method. Therefore, based on a barcode identification scheme combining cyclic shifting with dynamic programming (DP), this paper proposes, implements and tests a hardware accelerator that can accelerate barcode identification. In the accelerator, considering that the computational complexity of the DP algorithm can be expressed as the multiplication of the lengths of both involved sequences, we design a systolic array structure with simplified processing element (PE) and a parallel circuit architecture to identify the insertion and deletion errors based on the traceback. The accelerator is implemented on a field-programmable gate array (FPGA), and its performance is compared with that of software implemented on a general-purpose computer. The experimental results indicate that, compared with the software implementation, the accelerator can achieve speedups of two orders of magnitude for longer barcodes.
Broadband Ultra-Thin High-Efficiency Linear Polarizer Based on Metasurfaces
Authors: Li Peixuan , Wang Yuxiang , He Jiahao , Huang Xiaojun
Published: August 2022

In this paper, an ultra-wideband (UWB) polarizer with high performance based on the metasurface is designed and demonstrated, which is composed of a dielectric substrate with a double-gap circular pattern and metal film. Multiple strong resonance points enable the design to achieve the conversion from incident linearly polarized waves to cross-polarized waves at 6.49–11.64 GHz, with a fractional bandwidth of 56.8% and a corresponding polarization conversion rate (PCR) of 90%. The PCR remains above 90% at 6.49–11.52 GHz when the electromagnetic wave is obliquely incident between 0° and 30°. Furthermore, the surface current distribution of the polarizer is discussed to explain the physical mechanism. The sample is fabricated for microwave validation. Compared with previous reports, the proposed polarizer has a larger bandwidth and higher efficiency and is expected to be used in microwave communications, antennas, radar cross section reduction, and other fields.