bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of a Single-Tube PCR Assay for the Detection of Haemophilus influenzae Serotypes a, c, d, e and f on the Epidemiological Surveillance in Greece
Authors: Xirogianni Athanasia , Georgakopoulou Theano , Patsourakos Vassileios , Magaziotou Ioanna , Papandreou Anastasia , Simantirakis Stelmos , Tzanakaki Georgina
Published: July 2022

Background: The decrease in the rate of meningitis due to Haemophilus influenzae type b after vaccine introduction and a possible change in epidemiology of H. influenzae disease highlights the need for continuous serotype surveillance. Methods: A single-tube multiplex PCR assay for serotyping of H. influenzae was developed and deployed. Results: During 2003–2020, 108 meningitis cases due to H. influenzae were notified; 86 (80%) were confirmed and serotyped by molecular methods. The overall specificity and sensitivity of the assay were estimated (100% PPV and NPV respectively). The overall mean annual reported incidence for H. influenzae was 0.02, while for Hib and non-b meningitis equaled 0.02 and 0.03 per 100 000, respectively. Analysis by age group revealed that H. influenzae peaks in toddlers and children 0–4 years and in adults >45 years old. Among the serotyped cases, 39.8% were identified as Hib, 46.3% as NTHi, and 0.9% and 2.8% as serotypes a (Hia) and f (Hif)) respectively. Conclusions: Low incidence due to Hib was observed while non-typeable H. influenzae (NTHi) and serotypes Hia and Hif seem to emerge. The application of the current assay discloses the ongoing change of invasive H. influenzae disease trends during the Hib post-vaccine era.
Raman Microscopic Analysis of Dry-Surface Biofilms on Clinically Relevant Materials
Authors: Tewes Thomas J. , Centeleghe Isabella , Maillard Jean-Yves , Platte Frank , Bockmühl Dirk P.
Published: July 2022

Moist/hydrated biofilms have been well-studied in the medical area, and their association with infections is widely recognized. In contrast, dry-surface biofilms (DSBs) on environmental surfaces in healthcare settings have received less attention. DSBs have been shown to be widespread on commonly used items in hospitals and to harbor bacterial pathogens that are known to cause healthcare-acquired infections (HAI). DSBs cannot be detected by routine surface swabbing or contact plates, and studies have shown DSBs to be less susceptible to cleaning/disinfection products. As DSBs are increasingly reported in the medical field, and there is a likelihood they also occur in food production and manufacturing areas, there is a growing demand for the rapid in situ detection of DSBs and the identification of pathogens within DSBs. Raman microspectroscopy allows users to obtain spatially resolved information about the chemical composition of biofilms, and to identify microbial species. In this study, we investigated Staphylococcus aureus mono-species DSB on polyvinylchloride blanks and stainless steel coupons, and dual-species (S. aureus/Bacillus licheniformis) DSB on steel coupons. We demonstrated that Raman microspectroscopy is not only suitable for identifying specific species, but it also enables the differentiation of vegetative cells from their sporulated form. Our findings provide the first step towards the rapid identification and characterization of the distribution and composition of DSBs on different surface areas.
Role of Host Small GTPases in Apicomplexan Parasite Infection
Authors: Paone Silvio , Olivieri Anna
Published: July 2022

The Apicomplexa are obligate intracellular parasites responsible for several important human diseases. These protozoan organisms have evolved several strategies to modify the host cell environment to create a favorable niche for their survival. The host cytoskeleton is widely manipulated during all phases of apicomplexan intracellular infection. Moreover, the localization and organization of host organelles are altered in order to scavenge nutrients from the host. Small GTPases are a class of proteins widely involved in intracellular pathways governing different processes, from cytoskeletal and organelle organization to gene transcription and intracellular trafficking. These proteins are already known to be involved in infection by several intracellular pathogens, including viruses, bacteria and protozoan parasites. In this review, we recapitulate the mechanisms by which apicomplexan parasites manipulate the host cell during infection, focusing on the role of host small GTPases. We also discuss the possibility of considering small GTPases as potential targets for the development of novel host-targeted therapies against apicomplexan infections.
Voltage-Dependent Emission Varying from Blue to Orange–Red from a Nondoped Organic Light-Emitting Diode with a Single Emitter
Authors: Yang Mingxue , Zhao Tian-Xiang , Ji Si-Chao , Tao Xiao-Dong , Chen Xu-Lin , Meng Lingyi , Liang Dong , Lu Can-Zhong
Published: July 2022

Organic light-emitting diodes (OLEDs) with tunable emission colors, especially white OLEDs, have rarely been observed with a single emitter in a single emissive layer. In this paper, we report a new compound featuring a D–A–D structure, 9,9′-(pyrimidine-2,5-diylbis(2,1-phenylene))bis(3,6-di-tert-butyl-9H-carbazole) (PDPC). A nondoped OLED using this compound as a single emitter exhibits unique voltage-dependent dual emission. The emission colors range from blue to orange–red with an increase in voltage, during which white electroluminescence with a Commission Internationale De L’Eclairage (CIE) coordinate of (0.35, 0.29) and a color render index (CRI) value of 93 was observed. A comparative study revealed that the dual emission simultaneously originates from the monomers and excimers of the emitter. This study provides insight into understanding the multimer-excited mechanism and developing novel color-tunable OLEDs.
Patients’ Opinions towards the Services of Pharmacists Based in General Practice
Authors: Sudeshika Thilini , Naunton Mark , Yee Kwang C. , Deeks Louise S. , Peterson Gregory M. , Kosari Sam
Published: July 2022

Pharmacists have been included in general practice teams to provide non-dispensing services for patients. In Australia, pharmacists’ role in general practice has been slowly expanding. However, there is a paucity of research to explore patients’ opinions toward pharmacist-led services in general practice. This study aimed to assess patient awareness, perceived needs, and satisfaction with these services. A cross-sectional survey was conducted with a purposeful sample of patients who visited six general practices in the Australian Capital Territory that included pharmacists in their team. The survey was informed by the literature and pre-tested. The survey was distributed to two samples: patients who had seen a pharmacist and those who had not seen a pharmacist. Of 100 responses received, 86 responses were included in the analysis: patients who had seen a pharmacist (n = 46) and patients who had not seen a pharmacist (n = 40). Almost all the patients who utilised pharmacist-led services were highly satisfied with those services. Among patients who had not seen a pharmacist, 50% were aware of the existence of general practice pharmacists. Patients who had visited the pharmacist rated higher scores for perceived needs. Patient satisfaction towards the pharmacist-led services in general practices was very high, and patients supported the expansion of these services. However, awareness of the availability of general practice pharmacist services could be improved.
Flavonoid-Rich Fractions of Bauhinia holophylla Leaves Inhibit Candida albicans Biofilm Formation and Hyphae Growth
Authors: da Fonseca Sara Thamires Dias , Teixeira Thaiz Rodrigues , Ferreira Jaqueline Maria Siqueira , Lima Luciana Alves Rodrigues dos Santos , Luyten Walter , Castro Ana Hortência Fonsêca
Published: July 2022

This study evaluated the effect of the extract and fractions of Bauhinia holophylla on Candida albicans planktonic growth, biofilm formation, mature biofilm, and hyphae growth. Three C. albicans strains (SC5314, ATCC 18804, and ATCC 10231) were tested. The crude extract and the fractions were obtained by exhaustive percolation and liquid–liquid partition, respectively. Phytochemical analyses of B. holophylla extract and fractions were performed using high-performance liquid chromatography coupled with a diode-array detector and mass spectrometry (HPLC-DAD-MS). A microdilution assay was used to evaluate the effect of the B. holophylla extract and fractions on C. albicans planktonic growth, and crystal violet staining was used to measure the total biomass of the biofilm. Hyphae growth was analyzed using light microscopy. Thirteen flavonoids were identified, with a predominance of the flavonol-3-O-glycoside type based on quercetin, myricetin, and kaempferol. Flavonoid-rich fractions of B. holophylla leaves displayed antifungal activity and inhibited both biofilm formation and hyphae growth in all the tested strains, but were not effective on C. albicans planktonic growth and mature biofilm. This study indicates that flavonoid-rich fractions from B. holophylla leaves interfere with the virulence of Candida species and support the use of Bauhinia spp. in folk medicine to treat infections.
Laser Doppler Velocimetry Test of Flow Characteristics in Draft Tube of Model Pump Turbine
Authors: Deng Wanquan , Li Zhen , Ji Lei , Shang Linmin , Liu Demin , Liu Xiaobing
Published: July 2022

For Francis pump turbines, the pressure pulsation characteristics of the draft tube are some of the key concerns during the operation of the units. The pressure pulsation characteristics of the draft tube are directly related to the draft tube spiral cavitating vortex rope. In this paper, the velocity distribution in the draft tube of a Francis pump turbine is tested by means of laser Doppler velocimetry. The velocity pulsation was found to be directly related to the pressure pulsation, while the velocity pulsation was also influenced by the cavitation coefficient. The main frequency of the velocity pulsation was close to the main frequency of the pressure pulsation and became larger as the cavitation factor increased.
Ameliorative Processes of Beta-Carotene in Streptozotocin-Induced Diabetic Vascular Dementia in Rats
Authors: Lim Khian Giap , Muthuraman Arunachalam
Published: July 2022

Beta-carotene (BC) is a precursor of vitamin A and an excellent antioxidant. It protects the vascular system. Vascular dementia (VaD) is one of the aging disorders causing memory dysfunction. The available medicines for the management of VaD are limited. The present study aimed to evaluate the ameliorative effect of BC in streptozotocin (STZ)-induced diabetic VaD in rats. Diabetic VaD was induced through the administration of nicotinamide (NA, 50 mg/kg; i.p.) and STZ (50 mg/kg; i.p.). The test compound BC (50 and 100 mg/kg; p.o.) and reference compound donepezil (1 mg/kg; p.o.) were administered for 15 consecutive days. Cognitive changes were assessed by transfer latency (TL) using the elevated plus maze (EPM) test. The changes in acetylcholinesterase (AChE) activity were estimated in the septohippocampal system of rat brains. The administration of STZ caused significant changes in cognitive functions (increased TL) as compared to the normal group. BC ameliorated the anxiety-related cognitive behavior and neurotransmitter (elevated AChE) changes provoked by diabetic VaD. Therefore, BC could be a potential therapeutic candidate in the management of VaD.
Sigmoid-like Event-Triggered Security Cruise Control under Stochastic False Data Injection Attacks
Authors: Zhang Pengfei , Sun Hongtao , Peng Chen , Tan Cheng
Published: July 2022

This paper presents a Sigmoid-like event-triggered scheme (Sigmoid-like ETS) for security cruise control systems (CCSs) under stochastic false data injection (FDI) attacks. In order to improve the sensitivity of the ETS, a Sigmoid-like function is first proposed to adjust the event-triggered threshold, dynamically. In what follows, by considering a class of stochastic FDI attacks which obey Bernoulli distribution, the Sigmoid-like event-triggered security control strategy is proposed to ensure both the security and resource saving of the CCSs. Thus, a sufficient stability and stabilization criterion is well derived to present the co-design of an H∞ control and event-triggered parameter. Finally, some simulation experiments are conducted to verify the effectiveness of the proposed Sigmoid-like event-triggered security cruise control for networked vehicles.
Experimental and Numerical Study on the Dynamic and Flow Characteristics of a Reciprocating Pump Valve
Authors: Li Ran , Wei Wenshu , Liu Hao , Ye Jian , Wang Dalong , Li Shoubin , Wang Wei
Published: July 2022

The structure and dynamics of a reciprocating pump liquid end affect the volumetric efficiency and net positive suction head. To match the kinematics with theoretical parameters, reciprocating pump valve motion and flow visualization tests and computational fluid dynamics (CFD) analyses were performed on a wing-guided bevel discharge valve in a horizontal quintuple single-acting reciprocating pump. The valve motion test results showed that the maximum pump valve displacement and the pump valve opening and closing durations were approximately 8.3 mm, 29 ms, and 38 ms, respectively. The corresponding flow visualization test results were 11.4 mm, 9.5 ms, and 35.5 ms. The valve closing durations obtained from the valve motion and flow visualization tests are approximately twice as high as the U-Adolph prediction. The maximum displacement obtained from the valve motion test is consistent with the U-Adolph prediction. Three-dimensional CFD analyses were performed to investigate the flow states, pressure, and velocity characteristics of the discharge valve opening. Finally, the proposed method was applied to develop a new horizontal quintuple single-acting reciprocating pump with a rated flow rate of 1250 L/min and pressure of 40 MPa. This developed pump exhibited good performance and excellent reliability.
Development of Chitosan-Coated PLGA-Based Nanoparticles for Improved Oral Olaparib Delivery: In Vitro Characterization, and In Vivo Pharmacokinetic Studies
Authors: Anwer Md. Khalid , Ali Essam A. , Iqbal Muzaffar , Ahmed Mohammed Muqtader , Aldawsari Mohammed F. , Saqr Ahmed Al , Alalaiwe Ahmed , Soliman Gamal A.
Published: July 2022

Olaparib (OLP) is an orally active poly (ADP-ribose) polymerase enzyme inhibitor, approved for treatment for the metastatic stage of prostate, pancreatic, breast and ovarian cancer. Due to its low bioavailability, an increase in dose and frequency is required to achieve therapeutic benefits, which also results in associated toxicity in patients. In the current study, OLP-loaded poly (d,l-lactide-co-glycolide) (PLGA) nanoparticles (NPs) (OLP-PLGA NPs) and a coating of OLP-PLGA NPs with chitosan (CS) (OLP-CS-PLGA NPs) were prepared successfully in order to improve the dissolution rate and bioavailability. The developed OLP-PLGA NPs were evaluated for hydrodynamic particle size (392 ± 5.3 nm), PDI (0.360 ± 0.03), ZP (−26.9 ± 2.1 mV), EE (71.39 ± 5.5%) and DL (14.86 ± 1.4%), and OLP-CS-PLGA NPs, hydrodynamic particle size (622 ± 9.5 nm), PDI (0.321 ± 0.02), ZP (+36.0 ± 1.7 mV), EE (84.78 ± 6.3%) and DL (11.05 ± 2.6%). The in vitro release profile of both developed NPs showed a sustained release pattern. Moreover, the pharmacokinetics results exhibited a 2.0- and 4.75-fold increase in the bioavailability of OLP-PLGA NPs and OLP-CS-PLGA NPs, respectively, compared to normal OLP suspension. The results revealed that OLP-CS-PLGA NPs could be an effective approach to sustaining and improving the bioavailability of OLP.
Preparation of Aqueous Propolis Extracts Applying Microwave-Assisted Extraction
Authors: Juodeikaitė Dovaldė , Žilius Modestas , Briedis Vitalis
Published: July 2022

Water-based propolis extracts usually contain up to 10-fold lower quantities of active ingredients due to poor solubility in water of propolis bioactive compounds when compared with ethanol-based extracts. Since ethanol-based extracts are of limited use, water-based extracts are preferred nowadays. The application of alternative extraction techniques should be evaluated to improve extraction efficiency. Aqueous propolis extracts were prepared using purified water and propylene glycol, 2-hydroxypropyl-beta-cyclodextrin and sodium bicarbonate aqueous solutions. A microwave-assisted extraction method was applied in cycles. The total concentration of hydroxycinnamic acids in aqueous propolis extract produced by four extraction cycles was determined to be 1502.1 ± 130.1 μg/mL and 20% propylene glycol, 10% 2-hydroxypropyl-beta-cyclodextrin and 5% sodium bicarbonate aqueous solutions, increasing the total concentration of hydroxycinnamic acids by 1.6, 1.7 and 1.9-fold, respectively. An application of microwave-assisted extraction method and the procedure of repeating extraction cycles reliably increased the quantity of hydroxycinnamic acids in aqueous propolis extracts. Similarly, the presence of propylene glycol, 2-hydroxypropyl-β-cyclodextrin and sodium bicarbonate increased the concentration of the hydroxycinnamic acids in propolis extracts.
Examining the Experiences of US Dentists during the First Wave of the COVID-19 Pandemic: Implications for Policy and Practice
Authors: Simonovich Jordan R. , Simonovich Shannon D.
Published: July 2022

(1) Background: As an emerging topic, no known study to date has described interviews with US dentists regarding their experiences during the beginning of the coronavirus disease 2019 (COVID-19) with regard to office closures and their implications for both the dentists and the patients they serve, especially among dentists in their first decade of work and new to practice ownership roles. Therefore, the purpose of this study was to describe the experiences of early-career US dentists during the initial stages of the COVID-19 pandemic. (2) Methods: This study utilized a semi-structured interview protocol and employed qualitative descriptive methodology. SPSS 26 and NVivo12 were utilized for data analysis. (3) Results: In April 2020, a total of 12 early-career US dentists completed the interview study protocol. The study sample majority was male (67%), with a mean age of 32 (range = 30–37) and an average of 6 years of dental practice experience (range = 5–10). Participants completed phone interviews with the research team. In summary, three organizing themes emerged: (1) Dentistry during COVID-19: Experiences during the first wave, (2) Long-term concerns regarding COVID-19, and (3) COVID-19 professional communication and dental research. (4) Conclusions: The chief findings of this study are dentists’ long-term concerns for the profession post-COVID-19. Research must still determine how to best prepare for future infectious disease outbreaks with regards to safeguarding the health of the dental workforce and maintaining the oral health of patient populations.
Chemical Conversion of Fischer–Tropsch Waxes and Plastic Waste Pyrolysis Condensate to Lubricating Oil and Potential Steam Cracker Feedstocks
Authors: Neuner Philipp , Graf David , Netsch Niklas , Zeller Michael , Herrmann Tom-Carlo , Stapf Dieter , Rauch Reinhard
Published: July 2022

The global economy and its production chains must move away from petroleum-based products, to achieve this goal, alternative carbon feedstocks need to be established. One area of concern is sustainable production of synthetic lubricants. A lubricating oil can be described as a high boiling point (>340 °C) liquid with solidification at least below room temperature. Historically, many lubricants have been produced from petroleum waxes via solvent or catalytic dewaxing. In this study, catalytic dewaxing was applied to potential climate neutral feedstocks. One lubricant was produced via Fischer–Tropsch (FT) synthesis and the other lubricant resulted from low temperature pyrolysis of agricultural waste plastics. The waxes were chosen because they each represented a sustainable alternative towards petroleum, i.e., FT waxes are contrivable from biomass and CO2 by means of gasification and Power-to-X technology. The pyrolysis of plastic is a promising process to complement existing recycling processes and to reduce environmental pollution. Changes in cloud point, viscosity, and yield were investigated. A bifunctional zeolite catalyst (SAPO-11) loaded with 0.3 wt% platinum was used. The plastic waste lubricants showed lower cloud points and increased temperature stability as compared with lubricants from FT waxes. There was a special focus on the composition of the naphtha, which accumulated during cracking. While the plastic waste produced higher amounts of naphtha, its composition was quite similar to those from FT waxes, with the notable exception of a higher naphthene content.
Pandemic Disruptions of Older Adults’ Meaningful Connections: Linking Spirituality and Religion to Suffering and Resilience
Authors: McFadden Susan H.
Published: July 2022

The COVID-19 pandemic has upended the lives of persons of all ages throughout the world. Older adults have been particularly susceptible to the virus and have died at higher rates than any other age group. Starting from the early days of the pandemic, gerontologists rallied to address a wide variety of issues affecting older people’s lives. This paper reviews gerontological research that began shortly after the pandemic was declared and examines how a model of meaningful connectedness undergirding spiritual and religious experiences sheds light on the suffering and the resilience of older people during the pandemic. It notes that despite over four decades of research on the role of religion and spirituality in older people’s lives, there has been little mention in major gerontology journals of the role of elders’ religiousness and spirituality in their responses to the pandemic. The paper concludes with a call for gerontologists to pay closer attention to elder religiousness and spirituality and the many questions that need to be addressed regarding older people’s experiences during the pandemic.
Sources of Japanese Buddhist Philosophy of Education: Saichō (最澄, 766/7–822) on Study, Reflection, and Cultivation
Authors: Kusumoto Ryotaro
Published: July 2022

Recent studies on the Buddhist threefold wisdom model and its suggested potentialities have warranted a rediscovery of the model in different historical and cultural contexts. Saichō (最澄, 766/7–822), founder of Japanese Tendai Buddhism, references the three wisdoms in his documents outlining the Tendai monastic education curriculum. Through modification of translation and analysis of related original texts by Saichō, and an interview with the current dean of the Tendai monastic education institution, this paper aims to (1) uncover Sino-Japanese history of expressions of threefold wisdom and Buddhist education, (2) clarify the content of Saichō’s curriculum, and (3) examine the role of compassion in said curriculum. This paper argues that the threefold wisdom served as a foundational framework of Saichō’s education; he envisioned that his graduates would develop into religious leaders of the nation who would benefit all sentient beings through their own training, preaching the Dharma, and contributing to social work. At the same time, it became clear that compassionate attitudes were considered to be fundamental to all practices of the three wisdoms at Mount Hiei, which makes Saichō’s curriculum a captivating case of a theological application of the threefold wisdom.
Body-Powered and Portable Soft Hydraulic Actuators as Prosthetic Hands
Authors: Kandasamy Sivakumar , Teo Meiying , Ravichandran Narrendar , McDaid Andrew , Jayaraman Krishnan , Aw Kean
Published: July 2022

Soft robotic actuators are highly flexible, compliant, dexterous, and lightweight alternatives that can potentially replace conventional rigid actuators in various human-centric applications. This research aims to develop a soft robotic actuator that leverages body movements to mimic the function of human fingers for gripping and grasping tasks. Unlike the predominantly used chamber-based actuation, this study utilizes actuators made from elastomers embedded with fiber braiding. The Young’s modulus of the elastomer and braiding angles of the fiber highly influenced the bending angle and force generated by these actuators. In this experiment, the bending and force profiles of these actuators were characterized by varying the combinations of elastomeric materials and braiding angles to suit hand manipulation tasks. Additionally, we found that utilizing water, which is relatively more incompressible than air, as the actuation fluid enabled easier actuation of the actuators using body movements. Lastly, we demonstrated a body-powered actuator setup that can provide comfort to patients in terms of portability, standalone capability, and cost effectiveness, potentially allowing them to be used in a wide range of wearable robotic applications.
Estimation of Leaf Area Index with a Multi-Channel Spectral Micro-Sensor for Wireless Sensing Networks
Authors: Comella Laura Maria , Bregler Florian , Hager Eiko , Anys Markus , Klueppel Johannes , Rupitsch Stefan J. , Werner Christiane , Woias Peter
Published: July 2022

The leaf area index (LAI) is a key parameter in the context of monitoring the development of tree crowns and plants in general. As parameters such as carbon assimilation, environmental stress on carbon, and the water fluxes within tree canopies are correlated to the leaves surface, this parameter is essential for understanding and modeling ecological processes. However, its continuous monitoring using manual state-of-the-art measurement instruments is still challenging. To address this challenge, we present an innovative sensor concept to obtain the LAI based on the cheap and easy to integrate multi-channel spectral sensor AS7341. Additionally, we present a method for processing and filtering the gathered data, which enables very high accuracy measurements with an nRMSE of only 0.098, compared to the manually-operated state-of-the-art instrument LAI-2200C (LiCor). The sensor that is embedded on a sensor node has been tested in long-term experiments, proving its suitability for continuous deployment over an entire season. It permits the estimation of both the plant area index (PAI) and leaf area index (LAI) and provides the first wireless system that obtains the LAI solely powered by solar cells. Its energy autonomy and wireless connectivity make it suitable for a massive deployment over large areas and at different levels of the tree crown. It may be upgraded to allow the parallel measurement of photosynthetic active radiation (PAR) and light quality, relevant parameters for monitoring processes within tree canopies.
Ultrasensitive Electrochemical Detection and Plasmon-Enhanced Photocatalytic Degradation of Rhodamine B Based on Dual-Functional, 3D, Hierarchical Ag/ZnO Nanoflowers
Authors: Sebastian Neethu , Yu Wan-Chin , Balram Deepak
Published: July 2022

The sensitive detection and degradation of synthetic dyes are pivotal to maintain safety owing to the adverse side effects they impart on living beings. In this work, we developed a sensitive electrochemical sensor for the nanomolar-level detection of rhodamine B (RhB) using a dual-functional, silver-decorated zinc oxide (Ag/ZnO) composite-modified, screen-printed carbon electrode. The plasmon-enhanced photocatalytic degradation of organic pollutant RhB was also performed using this nanocomposite prepared by embedding different weight percentages (1, 3, and 5 wt%) of Ag nanoparticles on the surface of a three-dimensional (3D), hierarchical ZnO nanostructure based on the photoreduction approach. The structure and morphology of an Ag/ZnO nanocomposite were characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), elemental mapping, ultraviolet-visible (UV-vis) spectroscopy, and X-ray diffraction (XRD). The electrochemical sensor exhibited a very high sensitivity of 151.44 µAµM−1cm−2 and low detection limit of 0.8 nM towards RhB detection. The selectivity, stability, repeatability, reproducibility, and practical feasibility were also analyzed to prove their reliability. Furthermore, the photocatalysis results revealed that 3 wt% of the Ag/ZnO hybrid nanostructure acquired immense photostability, reusability, and 90.5% degradation efficiency under visible light. Additionally, the pseudo-first-order rate constant of Ag-3/ZnO is 2.186 min−1 suggested promising activity in visible light photocatalysis.
CAFS: An Attention-Based Co-Segmentation Semi-Supervised Method for Nasopharyngeal Carcinoma Segmentation
Authors: Chen Yitong , Han Guanghui , Lin Tianyu , Liu Xiujian
Published: July 2022

Accurate segmentation of nasopharyngeal carcinoma is essential to its treatment effect. However, there are several challenges in existing deep learning-based segmentation methods. First, the acquisition of labeled data are challenging. Second, the nasopharyngeal carcinoma is similar to the surrounding tissues. Third, the shape of nasopharyngeal carcinoma is complex. These challenges make the segmentation of nasopharyngeal carcinoma difficult. This paper proposes a novel semi-supervised method named CAFS for automatic segmentation of nasopharyngeal carcinoma. CAFS addresses the above challenges through three mechanisms: the teacher–student cooperative segmentation mechanism, the attention mechanism, and the feedback mechanism. CAFS can use only a small amount of labeled nasopharyngeal carcinoma data to segment the cancer region accurately. The average DSC value of CAFS is 0.8723 on the nasopharyngeal carcinoma segmentation task. Moreover, CAFS has outperformed the state-of-the-art nasopharyngeal carcinoma segmentation methods in the comparison experiment. Among the compared state-of-the-art methods, CAFS achieved the highest values of DSC, Jaccard, and precision. In particular, the DSC value of CAFS is 7.42% higher than the highest DSC value in the state-of-the-art methods.
Evaluation of Simple Algorithms for Proportional Control of Prosthetic Hands Using Intramuscular Electromyography
Authors: Malesevic Nebojsa , Björkman Anders , Andersson Gert S. , Cipriani Christian , Antfolk Christian
Published: July 2022

Although seemingly effortless, the control of the human hand is backed by an elaborate neuro-muscular mechanism. The end result is typically a smooth action with the precise positioning of the joints of the hand and an exerted force that can be modulated to enable precise interaction with the surroundings. Unfortunately, even the most sophisticated technology cannot replace such a comprehensive role but can offer only basic hand functionalities. This issue arises from the drawbacks of the prosthetic hand control strategies that commonly rely on surface EMG signals that contain a high level of noise, thus limiting accurate and robust multi-joint movement estimation. The use of intramuscular EMG results in higher quality signals which, in turn, lead to an improvement in prosthetic control performance. Here, we present the evaluation of fourteen common/well-known algorithms (mean absolute value, variance, slope sign change, zero crossing, Willison amplitude, waveform length, signal envelope, total signal energy, Teager energy in the time domain, Teager energy in the frequency domain, modified Teager energy, mean of signal frequencies, median of signal frequencies, and firing rate) for the direct and proportional control of a prosthetic hand. The method involves the estimation of the forces generated in the hand by using different algorithms applied to iEMG signals from our recently published database, and comparing them to the measured forces (ground truth). The results presented in this paper are intended to be used as a baseline performance metric for more advanced algorithms that will be made and tested using the same database.
Modeling Method to Abstract Collective Behavior of Smart IoT Systems in CPS
Authors: Song Junsup , Karagiannis Dimitris , Lee Moonkun
Published: July 2022

This paper presents a new modeling method to abstract the collective behavior of Smart IoT Systems in CPS, based on process algebra and a lattice structure. In general, process algebra is known to be one of the best formal methods to model IoTs, since each IoT can be represented as a process; a lattice can also be considered one of the best mathematical structures to abstract the collective behavior of IoTs since it has the hierarchical structure to represent multi-dimensional aspects of the interactions of IoTs. The dual approach using two mathematical structures is very challenging since the process algebra have to provide an expressive power to describe the smart behavior of IoTs, and the lattice has to provide an operational capability to handle the state-explosion problem generated from the interactions of IoTs. For these purposes, this paper presents a process algebra, called dTP-Calculus, which represents the smart behavior of IoTs with non-deterministic choice operation based on probability, and a lattice, called n:2-Lattice, which has special join and meet operations to handle the state explosion problem. The main advantage of the method is that the lattice can represent all the possible behavior of the IoT systems, and the patterns of behavior can be elaborated by finding the traces of the behavior in the lattice. Another main advantage is that the new notion of equivalences can be defined within n:2-Lattice, which can be used to solve the classical problem of exponential and non-deterministic complexity in the equivalences of Norm Chomsky and Robin Milner by abstracting them into polynomial and static complexity in the lattice. In order to prove the concept of the method, two tools are developed based on the ADOxx Meta-Modeling Platform: SAVE for the dTP-Calculus and PRISM for the n:2-Lattice. The method and tools can be considered one of the most challenging research topics in the area of modeling to represent the collective behavior of Smart IoT Systems.
Enhanced Perception for Autonomous Driving Using Semantic and Geometric Data Fusion
Authors: Florea Horatiu , Petrovai Andra , Giosan Ion , Oniga Florin , Varga Robert , Nedevschi Sergiu
Published: July 2022

Environment perception remains one of the key tasks in autonomous driving for which solutions have yet to reach maturity. Multi-modal approaches benefit from the complementary physical properties specific to each sensor technology used, boosting overall performance. The added complexity brought on by data fusion processes is not trivial to solve, with design decisions heavily influencing the balance between quality and latency of the results. In this paper we present our novel real-time, 360∘ enhanced perception component based on low-level fusion between geometry provided by the LiDAR-based 3D point clouds and semantic scene information obtained from multiple RGB cameras, of multiple types. This multi-modal, multi-sensor scheme enables better range coverage, improved detection and classification quality with increased robustness. Semantic, instance and panoptic segmentations of 2D data are computed using efficient deep-learning-based algorithms, while 3D point clouds are segmented using a fast, traditional voxel-based solution. Finally, the fusion obtained through point-to-image projection yields a semantically enhanced 3D point cloud that allows enhanced perception through 3D detection refinement and 3D object classification. The planning and control systems of the vehicle receives the individual sensors’ perception together with the enhanced one, as well as the semantically enhanced 3D points. The developed perception solutions are successfully integrated onto an autonomous vehicle software stack, as part of the UP-Drive project.
Multi-Agent Dynamic Resource Allocation in 6G in-X Subnetworks with Limited Sensing Information
Authors: Adeogun Ramoni , Berardinelli Gilberto
Published: July 2022

In this paper, we investigate dynamic resource selection in dense deployments of the recent 6G mobile in-X subnetworks (inXSs). We cast resource selection in inXSs as a multi-objective optimization problem involving maximization of the minimum capacity per inXS while minimizing overhead from intra-subnetwork signaling. Since inXSs are expected to be autonomous, selection decisions are made by each inXS based on its local information without signaling from other inXSs. A multi-agent Q-learning (MAQL) method based on limited sensing information (SI) is then developed, resulting in low intra-subnetwork SI signaling. We further propose a rule-based algorithm termed Q-Heuristics for performing resource selection based on similar limited information as the MAQL method. We perform simulations with a focus on joint channel and transmit power selection. The results indicate that: (1) appropriate settings of Q-learning parameters lead to fast convergence of the MAQL method even with two-level quantization of the SI, and (2) the proposed MAQL approach has significantly better performance and is more robust to sensing and switching delays than the best baseline heuristic. The proposed Q-Heuristic shows similar performance to the baseline greedy method at the 50th percentile of the per-user capacity and slightly better at lower percentiles. The Q-Heuristic method shows high robustness to sensing interval, quantization threshold and switching delay.
Security and Privacy Analysis of Smartphone-Based Driver Monitoring Systems from the Developer’s Point of View
Authors: Levshun Dmitry , Chechulin Andrey , Kotenko Igor
Published: July 2022

Nowadays, the whole driver monitoring system can be placed inside the vehicle driver’s smartphone, which introduces new security and privacy risks to the system. Because of the nature of the modern transportation systems, the consequences of the security issues in such systems can be crucial, leading to threat to human life and health. Moreover, despite the large number of security and privacy issues discovered in smartphone applications on a daily basis, there is no general approach for their automated analysis that can work in conditions that lack data and take into account specifics of the application area. Thus, this paper describes an original approach for a security and privacy analysis of driver monitoring systems based on smartphone sensors. This analysis uses white-box testing principles and aims to help developers evaluate and improve their products. The novelty of the proposed approach lies in combining various security and privacy analysis algorithms into a single automated approach for a specific area of application. Moreover, the suggested approach is modular and extensible, takes into account specific features of smartphone-based driver monitoring systems and works in conditions of lack or inaccessibility of data. The practical significance of the approach lies in the suggestions that are provided based on the conducted analysis. Those suggestions contain detected security and privacy issues and ways of their mitigation, together with limitations of the analysis due to the absence of data. It is assumed that such an approach would help developers take into account important aspects of security and privacy, thus reducing related issues in the developed products. An experimental evaluation of the approach is conducted on a car driver monitoring use case. In addition, the advantages and disadvantages of the proposed approach as well as future work directions are indicated.
Laser-Induced Breakdown Spectroscopy Associated with the Design of Experiments and Machine Learning for Discrimination of Brachiaria brizantha Seed Vigor
Authors: Cioccia Guilherme , Pereira de Morais Carla , Babos Diego Victor , Milori Débora Marcondes Bastos Pereira , Alves Charline Z. , Cena Cícero , Nicolodelli Gustavo , Marangoni Bruno S.
Published: July 2022

Laser-induced breakdown spectroscopy (LIBS) associated with machine learning algorithms (ML) was used to evaluate the Brachiaria seed physiological quality by discriminating the high and low vigor seeds. A 23 factorial design was used to optimize the LIBS experimental parameters for spectral analysis. A total of 120 samples from two distinct cultivars of Brachiaria brizantha seeds exhibiting high vigor (HV) and low vigor (LV) in standard tests were studied. The raw LIBS spectra were normalized and submitted to outlier verification, previously to the reduction data dimensionality from principal component analysis. Supervised machine learning algorithm parameters were chosen by leave-one-out cross-validation in the test samples, and it was tested by external validation using a new set of data. The overall accuracy in external validation achieved 100% for HV and LV discrimination, regardless of the cultivar or the classification algorithm.
Study on TLS Point Cloud Registration Algorithm for Large-Scale Outdoor Weak Geometric Features
Authors: Li Chen , Xia Yonghua , Yang Minglong , Wu Xuequn
Published: July 2022

With the development of societies, the exploitation of mountains and forests is increasing to meet the needs of tourism, mineral resources, and environmental protection. The point cloud registration, 3D modeling, and deformation monitoring that are involved in surveying large scenes in the field have become a research focus for many scholars. At present, there are two major problems with outdoor terrestrial laser scanning (TLS) point cloud registration. First, compared with strong geometric conditions with obvious angle changes or symmetric structures, such as houses and roads, which are commonly found in cities and villages, outdoor TLS point cloud registration mostly collects data on weak geometric conditions with rough surfaces and irregular shapes, such as mountains, rocks, and forests. This makes the algorithm that set the geometric features as the main registration parameter invalid with uncontrollable alignment errors. Second, outdoor TLS point cloud registration is often characterized by its large scanning range of a single station and enormous point cloud data, which reduce the efficiency of point cloud registration. To address the above problems, we used the NARF + SIFT algorithm in this paper to extract key points with stronger expression, expanded the use of multi-view convolutional neural networks (MVCNN) in point cloud registration, and adopted GPU to accelerate the matrix calculation. The experimental results have demonstrated that this method has greatly improved registration efficiency while ensuring registration accuracy in the registration of point cloud data with weak geometric features.
Misfire Detection in Automotive Engines Using a Smartphone through Wavelet and Chaos Analysis
Authors: Rodrigues Nayara Formiga , Brito Alisson V. , Ramos Jorge Gabriel Gomes Souza , Mishina Koje Daniel Vasconcelos , Belo Francisco Antonio , Lima Filho Abel Cavalcante
Published: July 2022

Besides the failures that cause accidents, there are the ones responsible for preventing the car’s motion capacity. These failures cause inconveniences to the passengers and expose them to the dangers of the road. Although modern vehicles are equipped with a failure detection system, it does not provide an online approach to the drivers. Third-party devices and skilled labor are necessary to manage the data for failure characterization. One of the most common failures in engines is called misfire, and it happens when the spark is weak or inexistent, compromising the whole set. In this work, two algorithms are compared, based on Wavelet Multiresolution Analysis (WMA) and another using an approach performing signal analysis based on Chaos using the density of maxima (SAC-DM) to identify misfare in a combustion engine of a working automotive vehicle. Experimental tests were carried out in a car to validate the techniques for the engine without failure, with failure in one piston, and with two failed pistons. The results made it possible to obtain the failure diagnosis for 100% of the cases for both WMA and SAC-DM methods, but a shorter time window when using the last one.
Proactive Caching in D2D Assisted Multitier Cellular Network
Authors: Ahmad Fawad , Ahmad Ayaz , Hussain Irshad , Muhammad Ghulam , Uddin Zahoor , AlQahtani Salman A.
Published: July 2022

Cache-enabled networks suffer hugely from the challenge of content caching and content delivery. In this regard, cache-enabled device-to-device (D2D) assisted multitier cellular networks are expected to relieve the network data pressure and effectively solve the problem of content placement and content delivery. Consequently, the user can have a better opportunity to get their favored contents from nearby cache-enabled transmitters (CETs) through reliable and good-quality links; however, as expected, designing an effective caching policy is a challenging task due to the limited cache memory of CETs and uncertainty in user preferences. In this article, we introduce a joint content placement and content delivery technique for D2D assisted multitier cellular networks (D2DMCN). A support vector machine (SVM) is employed to predict the content popularity to determine which content is to be cached and where it is to be cached, thereby increasing the overall cache hit ratio (CHR). The content request is satisfied either by the neighboring node through the D2D link or by the cache-enabled base stations (BSs) of the multitier cellular networks (MCNs). Similarly, to solve the problem of optimal content delivery, the Hungarian algorithm is employed aiming to improve the quality of satisfaction. The simulation results indicate that the proposed content placement strategy effectively optimizes the overall cache hit ratio of the system. Similarly, an effective content delivery approach reduces the request content delivery delay and power consumption.
Year-Round Thermal Error Modeling and Compensation for the Spindle of Machine Tools Based on Ambient Temperature Intervals
Authors: Wei Xinyuan , Ye Honghan , Feng Xugang
Published: July 2022

The modeling and compensation method is a common method for reducing the influence of thermal error on the accuracy of machine tools. The prediction accuracy and robustness of the thermal error model are two key performance measures for evaluating the compensation effect. However, it is difficult to maintain the prediction accuracy and robustness at the desired level when the ambient temperature exhibits strong seasonal variations. Therefore, a year-round thermal error modeling and compensation method for the spindle of machine tools based on ambient temperature intervals (ATIs) is proposed in this paper. First, the ATIs applicable to the thermal error prediction models (TEPMs) under different ambient temperatures are investigated, where the C-Means clustering algorithm is utilized to determine ATIs. Furthermore, the prediction effect of different numbers of ATIs is analyzed to obtain the optimal number of ATIs. Then, the TEPMs corresponding to different ATIs in the annual ambient temperature range are established. Finally, the established TEPMs of ATIs are used to predict the experimental data of the entire year, and the prediction accuracy and robustness of the proposed ATI model are analyzed and compared with those of the low and high ambient temperature models. The prediction accuracies of the ATI model are 20.6% and 41.7% higher than those of the low and high ambient temperature models, respectively, and the robustness is improved by 48.8% and 62.0%, respectively. This indicates that the proposed ATI method can achieve high prediction accuracy and robustness regardless of the seasonal temperature variations throughout the year.
Design and Research of an Articulated Tracked Firefighting Robot
Authors: Zhao Jianwei , Zhang Zhiwei , Liu Shengyi , Tao Yuanhao , Liu Yushuo
Published: July 2022

Aiming to improve the situation where a firefighting robot is affected by conditions of space and complex terrain, a small four-track, four-drive articulated tracked fire-extinguishing robot is designed, which can flexibly perform fire detection and fire extinguishing tasks in a narrow space and complex terrain environment. Firstly, the overall structure of the robot is established. Secondly, the mathematical model of the robot’s motion is analyzed. On this basis, the kinematics simulation is carried out by using ADAMS, and the motion of the robot is analyzed when it overcomes obstacles. Finally, the prototype was produced and tested experimentally. The robot has good obstacle-surmounting ability and excellent stability, is a reasonable size, and can perform various firefighting tasks well.