bluuebunny/crossref_metadata_2025 huggingface dataset:
Experiences of Migrant People Living with HIV in a Multidisciplinary HIV Care Setting with Rapid B/F/TAF Initiation and Cost-Covered Treatment: The ‘ASAP’ Study
Authors: Arora Anish K. , Engler Kim , Lessard David , Kronfli Nadine , Rodriguez-Cruz Adriana , Huerta Edmundo , Lemire Benoit , Routy Jean-Pierre , Wittmer René , Cox Joseph , de Pokomandy Alexandra , Del Balso Lina , Klein Marina , Sebastiani Giada , Vedel Isabelle , Quesnel-Vallée Amélie ,   ASAP Migrant Advisory Committee, Lebouché Bertrand
Published: September 2022

This study aimed to explore the experiences of migrant people living with HIV (MLWH) enrolled in a Montreal-based multidisciplinary HIV care clinic with rapid antiretroviral treatment (ART) initiation and cost-covered ART. Between February 2020 and March 2022, 32 interviews were conducted with 16 MLWH at three time-points (16 after 1 week of ART initiation, 8 after 24 weeks, 8 after 48 weeks). Interviews were analyzed via the Framework Method. Thirty categories were identified, capturing experiences across the HIV care cascade. At diagnosis, most MLWH described “initially experiencing distress”. At linkage, almost all MLWH discussed “navigating the health system with difficulty”. At treatment initiation, almost all MLWH expressed “being satisfied with treatment”, particularly due to a lack of side effects. Regarding care retention, all MLWH noted “facing psychosocial or health-related challenges beyond HIV”. Regarding ART adherence, most MLWH expressed “being satisfied with treatment” with emphasis on their taking control of HIV. At viral suppression, MLWH mentioned “finding more peace of mind since becoming undetectable”. Regarding their perceived health-related quality of life, most MLWH indicated “being helped by a supportive social network”. Efficient, humanizing, and holistic approaches to care in a multidisciplinary setting, coupled with rapid and free ART initiation, seemed to help alleviate patients’ concerns, address their bio-psycho-social challenges, encourage their initial and sustained engagement with HIV care and treatment, and ultimately contribute to positive experiences.
Open-Source Hardware May Address the Shortage in Medical Devices for Patients with Low-Income and Chronic Respiratory Diseases in Low-Resource Countries
Authors: Farré Ramon , Gozal David , Nguyen Viet-Nhung , Pearce Joshua M. , Dinh-Xuan Anh Tuan
Published: September 2022

Respiratory diseases pose an increasing socio-economic burden worldwide given their high prevalence and their elevated morbidity and mortality. Medical devices play an important role in managing acute and chronic respiratory failure, including diagnosis, monitoring, and providing artificial ventilation. Current commercially available respiratory devices are very effective but, given their cost, are unaffordable for most patients in low- and middle-income countries (LMICs). Herein, we focus on a relatively new design option—the open-source hardware approach—that, if implemented, will contribute to providing low-cost respiratory medical devices for many patients in LMICs, particularly those without full medical insurance coverage. Open source reflects a set of approaches to conceive and distribute the comprehensive technical information required for building devices. The open-source approach enables free and unrestricted use of the know-how to replicate and manufacture the device or modify its design for improvements or adaptation to different clinical settings or personalized treatments. We describe recent examples of open-source devices for diagnosis/monitoring (measuring inspiratory/expiratory pressures or flow and volume in mechanical ventilators) and for therapy (non-invasive ventilators for adults and continuous positive airway pressure support for infants) that enable building simple, low-cost (hence, affordable), and high-performance solutions for patients in LMICs. Finally, we argue that the common practice of approving clinical trials by the local hospital ethics board can be expanded to ensure patient safety by reviewing, inspecting, and approving open hardware for medical application to maximize the innovation and deployment rate of medical technologies.
The Effect of Tax Fairness, Peer Influence, and Moral Obligation on Sales Tax Evasion among Jordanian SMEs
Authors: Al-Rahamneh Nayef Mohammad , Bidin Zainol
Published: September 2022

Tax evasion remains a complex issue for tax authorities, policymakers, and researchers. While socio-psychological factors have been researched, their impact on tax evasion among SMEs has not yet been determined. This paper empirically analyses the effects of tax fairness, peer influence and moral obligation, on sales tax evasion among Jordanian SME owners/managers. A survey was used to obtain data from three regions of Jordan (north, middle, south). Random sampling was utilized in selecting the prospective respondents from SMEs in three sectors (trade, service, manufacturing). A total of 212 usable questionnaires retrieved from the SMEs were analysed using Smart-PLS 3.0. The results revealed that tax fairness and moral obligation had a significant negative effect on sales tax evasion behaviour among SME owner-managers. On the other hand, peer influence positively and significantly impacted sales tax evasion behaviour. Thus, policymakers and tax authorities should incorporate these factors in developing effective strategies to reduce tax evasion in Jordan, which could result in an improvement in the country’s overall revenue collection. The findings also contribute to the scarcity of literature about the significance of socio-psychological factors in mitigating tax evasion by examining the effects of tax fairness, peer influence, and moral obligation on sales tax evasion.
Target Date Funds, Drawdown Risk, and Central Bank Intervention: Evidence during the COVID-19 Pandemic
Authors: Iyer Arjun K. , Hoelscher Seth A. , Mbanga Cédric L.
Published: September 2022

Target Date Funds (TDFs) have become the default investment choice in retirement accounts for most households. Later-dated TDFs (e.g., further away from the present day) allocate a more significant percentage of each dollar invested into equities relative to fixed income. As the TDF moves closer to the designated retirement date, the TDF embarks on its’ glide path. We study the impact of the COVID-19 Pandemic and Federal Reserve intervention on the max drawdowns experienced by TDFs during 2020. Later-dated funds experienced more significant drawdowns relative to near-dated funds. Moving out one target date fund increased the drawdown by approximately 1.90%. Approximately 80% of TDFs experienced their max drawdown on 23 March 2020. The max drawdowns of the TDFs are then studied in the following three sub-periods: (1) before the first Federal Reserve Intervention (2 March 2020), (2) after the first intervention and before the second intervention (16 March 2020), and (3) the period after the second intervention. TDFs experienced the greatest drawdowns after the first intervention by the Federal Reserve (approximately 19%) relative to the other two periods (approximately 7%). Fees associated with the TDFs tend not to influence the drawdowns except for the near-dated funds, where the low-fee funds performed better. Finally, near-dated funds recovered from their max drawdowns around September 2020, whereas later-dated funds did not fully recover until December 2020.
The Economic Spatial Structure Evolution of Urban Agglomeration under the Impact of High-Speed Rail Construction: Is There a Difference between Developed and Developing Regions?
Authors: He You , Sherbinin Alex de , Shi Guoqing , Xia Haibin
Published: September 2022

It is foreseeable that the next few decades will be the golden age of high-speed rail (HSR) development, with many new construction plans emerging. The construction of the HSR will inevitably cause an impact on the economic spatial structure of urban agglomeration, but it is still unclear whether the impacts differ between economically developed and developing areas. How and to what extent do such differences exist? Based on the modified gravity model, this paper employs a social network analysis method and selects the Yangtze River Delta and Sichuan-Chongqing (Chuanyu) urban agglomeration as the research area to analyze the differences. The main conclusions are as follows. With the construction of HSR: (1) The network density and the average economic connection of urban agglomerations have shown a trend of gradual increase. (2) The number of core areas in developed regions has gradually increased, but there were no changes in the center of developing regions. (3) In developed regions, the new metropolitan areas are the cities that have benefited the most from the HSR construction. In developing regions, the central city with difficult topography benefits the most. (4) The network structure of developed regions tends to be more balanced. The edge cities in developing regions are getting farther from the center.
Multisource Remote Sensing Monitoring and Analysis of the Driving Forces of Vegetation Restoration in the Mu Us Sandy Land
Authors: Wang Zhao , Zhang Tinglong , Pei Chenyang , Zhao Xiaonan , Li Yingying , Hu Shuai , Bu Chongfeng , Zhang Qingfeng
Published: September 2022

The Mu Us Sandy Land is a key region of man-made desert control and farmland to forest (grass) return in China. Despite global change and the strong influence of human activities, the vegetation in this region has been significantly improved and restored. In this study, multisource remote sensing data and multiple indicators were used to quantitatively monitor and evaluate the vegetation restoration status in this area. The driving factors were also analysed. The results show that in the past 20 years, nearly the entire Mu Us Sandy Land significantly and substantively recovered. The regional fractional vegetation cover increased, with an average annual growth rate of 0.59% and obvious spatial heterogeneity. The nine most important driving factors could comprehensively account for 58.38% of the spatial distribution of the vegetation coverage. Factors such as land use and land cover, the aridity index, and gross domestic product had the most significant impact, followed by precipitation and temperature. The results confirmed that the vegetation was restored and improved in the Mu Us Sandy Land and determined the main driving factors, which is helpful for vegetation restoration and ecological improvement on sandy land similar to the Mu Us Sandy Land.
The Role of the Social Licence to Operate in the Emerging Bioeconomy—A Case Study of Short-Rotation Coppice Poplar in Slovakia
Authors: Pichler Christine , Fürtner Daniela , Hesser Franziska , Schwarzbauer Peter , Ranacher Lea Maria
Published: September 2022

Wood plays a key role in the endeavours of the EU to establish a circular bioeconomy based on renewable biological resources. Today, forestry on its own cannot sustainably satisfy the demand for woody biomass. Short-Rotation Coppice (SRC) represents a possible alternative production system where fast-growing tree species are cultivated on agricultural land. Thus far, lacking engagement from farmers and public opposition against other bioenergy projects have hindered the expansion of SRC. At the same time, society does not consider wood unconditionally sustainable anymore. The Social License to Operate (SLO) describes the dynamic relationship between industries, their communities, and other stakeholders. The present study adapted a quantitative SLO model based on integrative socio-psychological relationship modelling and applied it to a case study in Slovakia. The roles of trust, fairness, impact assessment, and governance hold for the establishment of social acceptance were analysed with Structural Equation Modelling (SEM). The model revealed the perception of individual benefits as the strongest predictor for social acceptance. The average level of social acceptance was found to be between “Acceptance” and “Approval”. The results thus show that SRC currently must not face societal pressure in Slovakia. However, the SLO is not static and must be constantly re-evaluated.
Application of Lactobaillus salivarius WB21 to the Oral Care of Healthy Older Adults: A Randomized, Double-Blind, Placebo-Controlled Crossover Comparative Study
Authors: Kijima Satoko , Suzuki Nao , Hanioka Takashi , Yoneda Masahiro , Tanabe Kazunari , Hirofuji Takao
Published: September 2022

Objective: A randomized, double-blind, placebo-controlled crossover comparative study was conducted in a healthy older population to assess the usefulness of Lactobacillus salivarius WB21 (WB21) ingestion for oral self-care. Methods: The study population included 33 healthy older individuals who were randomly divided into two groups (A and B). Group A consumed WB21 tablets during the first two months and placebo tablets during the following two months. Group B consumed placebo tablets during the first two months and WB21 tablets during the following two months. Before and after ingestion, oral examination, mouth odor test, and saliva collection were performed a total of four times. In addition, health conditions were obtained from a questionnaire survey at the study’s midpoint. Results: Two people in group A and one person in group B dropped out of the study. Thus, 15 people in group A and 15 people in group B were included in the analysis. Over two months of WB21 ingestion, salivary secretory IgA increased significantly (p = 0.047) and tongue coating score decreased significantly (p = 0.013). The plaque index, bleeding on probing, and mouth odor levels (H2S and CH3SH concentrations) did not change. During the 6-month study period, no caries, deterioration of periodontitis, or changes in oral health or systemic subjective symptoms were observed. Conclusion: Continuous ingestion of WB21-containing tablets may promote self-care of the teeth and mouths of healthy older adults. Trial registration: R000028335 (UMIN-CTR).
Functional Organic Materials for Photovoltaics: The Synthesis as a Tool for Managing Properties for Solid State Applications
Authors: Cardone Antonio , Capodilupo Agostina Lina
Published: September 2022

The continuous increase in the global energy demand deeply impacts the environment. Consequently, the research is moving towards more sustainable forms of energy production, storage and saving. Suitable technologies and materials are fundamental to win the challenge towards a greener and more eco-friendly society. Organic π-conjugated materials, including small molecules, oligomers and polymers are a wide and versatile class of functional materials with great potentiality, as they can be used as active matrixes in the fabrication of lightweight, flexible, cheap and large area devices. Their chemical and physical properties, both at a molecular level and mainly in the solid state, are a result of many factors, strictly related to the conjugated structure and functional groups on the backbone, which control the intermolecular forces driving solid state aggregations. The synthesis, through the molecular design, the choice of conjugated backbone and functionalization, represents the first and most powerful tool for finely tuning the chemico-physical properties of organic materials tailored for specific applications. In the present review, we report an overview of our works focused on synthetic methodologies, characterization, structure-properties correlation studies and applications of organic materials designed for energy-involving solid-state applications, organic photovoltaics in particular. The impact of functionalization on electro-optical properties and performance in device are discussed, also in relation to the specific applications.
A Fukui Analysis of an Arginine-Modified Carbon Surface for the Electrochemical Sensing of Dopamine
Authors: Revanappa Santhosh Kumar , Soni Isha , Siddalinganahalli Manjappa , Jayaprakash Gururaj Kudur , Flores-Moreno Roberto , Bananakere Nanjegowda Chandrashekar
Published: September 2022

Amino acid-modified carbon interfaces have huge applications in developing electrochemical sensing applications. Earlier reports suggested that the amine group of amino acids acted as an oxidation center at the amino acid-modified electrode interface. It was interesting to locate the oxidation centers of amino acids in the presence of guanidine. In the present work, we modeled the arginine-modified carbon interface and utilized frontier molecular orbitals and analytical Fukui functions based on the first principle study computations to analyze arginine-modified CPE (AMCPE) at a molecular level. The frontier molecular orbital and analytical Fukui results suggest that the guanidine (oxidation) and carboxylic acid (reduction) groups of arginine act as additional electron transfer sites on the AMCPE surface. To support the theoretical observations, we prepared the arginine-modified CPE (AMCPE) for the cyclic voltammetric sensing of dopamine (DA). The AMCPE showed excellent performance in detecting DA in blood serum samples.
The Influence of Gingival Exposure on Smile Attractiveness as Perceived by Dentists and Laypersons
Authors: Negruțiu Bianca , Moldovan Andrada , Staniș Claudia , Pusta Claudia , Moca Abel , Vaida Luminița , Romanec Cristian , Luchian Ionut , Zetu Irina , Todor Bianca
Published: September 2022

Background and Objectives: Smile is an important mark of beauty, and smile attractiveness can be influenced by various factors, one of these being the amount of gingival exposure. The aim of this research was to evaluate the perception of an ideal gingival exposure in smile in a sample of Romanian dentists and laypersons, and to find out what is the most important aspect that influences the smile perception for the respondents included in the study sample. Materials and Methods: An online survey was conducted between 3 February 2020 and 31 October 2020. The authors developed a short questionnaire consisting of 7 items. The first four items investigated the respondents’ age, gender, profession and whether or not they underwent an orthodontic treatment in the past. For items 5 and 6, participants had to choose the most and the least attractive amount of gingival exposure, and for the last item they had to choose the factor that mostly influences the smile attractiveness in their opinion. Results: 235 questionnaires remained in the study. The sample consisted of 194 women and 41 men, 162 laypersons and 73 dentists. The average value for the most attractive amount of gingival exposure was −0.57 ± 2.407 mm, with a median value of 0 mm while the average value for the least attractive amount of gingival exposure was 1.43 ± 3.785 mm, with a median value of 4 mm. The differences between the most or least attractive gingival exposure perceived by the participants were not significant according to gender or professional category (p > 0.05), but, when compared between having or not having an orthodontic treatment in the past the differences were statistically significant (p < 0.05). As such, participants who had an orthodontic treatment in the past perceived a significantly higher value for the most attractive gingival exposure, and a significantly higher value for the least attractive gingival exposure (p = 0.026) than the participants who didn’t have an orthodontic treatment in the past. As for the factor that mainly influences smile attractiveness, laypersons chose significantly more frequent white teeth or aligned teeth (96%, 71.7%) while dentists chose significantly more frequent a gingival exposure between 0–3 mm (70.4%) as smile factors for an aesthetic smile (p < 0.001). Conclusions: In this study sample, the respondents considered that the most attractive smile involved a covering of 0.57 mm (in average) of the upper incisors by the upper lip. Although smile attractiveness did not appear to be influenced by gender or profession in this study population, it was influenced by previous orthodontic treatment. The participants’ roles of dentist or layperson influenced the factors chosen for an aesthetic smile.
Should We Void Lactate in the Pathophysiology of Delayed Onset Muscle Soreness? Not So Fast! Let’s See a Neurocentric View!
Authors: Sonkodi Balázs
Published: September 2022

The pathophysiology of delayed onset muscle soreness is not entirely known. It seems to be a simple, exercise-induced delayed pain condition, but has remained a mystery for over 120 years. The buildup of lactic acid used to be blamed for muscle fatigue and delayed onset muscle soreness; however, studies in the 1980s largely refuted the role of lactate in delayed onset muscle soreness. Regardless, this belief is widely held even today, not only in the general public, but within the medical and scientific community as well. Current opinion is highlighting lactate’s role in delayed onset muscle soreness, if neural dimension and neuro-energetics are not overlooked. By doing so, lactate seems to have an essential role in the initiation of the primary damage phase of delayed onset muscle soreness within the intrafusal space. Unaccustomed or strenuous eccentric contractions are suggested to facilitate lactate nourishment of proprioceptive sensory neurons in the muscle spindle under hyperexcitation. However, excessive acidosis and lactate could eventually contribute to impaired proprioception and increased nociception under pathological condition. Furthermore, lactate could also contribute to the secondary damage phase of delayed onset muscle soreness in the extrafusal space, primarily by potentiating the role of bradykinin. After all, neural interpretation may help us to dispel a 40-year-old controversy about lactate’s role in the pathophysiology of delayed onset muscle soreness.
Special Issue: Advance in Energy Harvesters/Nanogenerators and Self-Powered Sensors
Authors: Shi Qiongfeng , Zhu Jianxiong
Published: September 2022

Internet of things (IoT) technologies are greatly promoted by the rapidly developed 5G-and-beyond networks, which have spawned diversified applications in the new era including smart homes, digital health, sports training, robotics, human–machine interaction, metaverse, smart manufacturing and industry 4 [...]
Electrochemical Reduction and Preparation of Cu-Se Thermoelectric Thin Film in Solutions with PEG
Authors: Qi Yanling , Li Yuanyuan , Wang Wei
Published: September 2022

Investigation of Cu(II) and Se(IV) electrochemical reduction processes in solutions with poly(ethylene glycol) (PEG) provides important theoretical guidance for the preparation of Cu-Se alloy films with stronger thermoelectric properties. The results reveal that PEG adsorbing on the electrode surface does not affect the electrochemical reduction mechanism of Cu(II), Se(IV), and Cu(II)-Se(IV), but inhibits the electrochemical reduction rates. The surface morphology and composition change with a negative shift in the deposition potentials. The Cu-Se alloy film, which was prepared at 0.04 V, was α-Cu2Se as-deposited and P-type thermoelectric material after annealing. The highest thermoelectric properties were as follows: Seebeck coefficient (α) was +106 μV·K−1 and 1.89 times of Cu-Se alloy film electrodeposited in Cu(II)-Se(IV) binary solution without PEG; resistivity (ρ) was 2.12 × 10−3 Ω·cm, and the calculated power factor (PF) was 5.3 μW·cm−1K−2 and 4.07 times that without PEG.
Carbon Material-Based Aerogels for Gas Adsorption: Fabrication, Structure Design, Functional Tailoring, and Applications
Authors: Zhang Lianming , Lei Yu , He Peng , Wu Hao , Guo Lei , Wei Gang
Published: September 2022

Carbon material-based aerogels (CMBAs) have three-dimensional porous structure, high specific surface area, low density, high thermal stability, good electric conductivity, and abundant surface-active sites, and, therefore, have shown great application potential in energy storage, environmental remediation, electrochemical catalysis, biomedicine, analytical science, electronic devices, and others. In this work, we present recent progress on the fabrication, structural design, functional tailoring, and gas adsorption applications of CMBAs, which are prepared by precursor materials, such as polymer-derived carbon, carbon nanotubes, carbon nanofibers, graphene, graphene-like carbides, fullerenes, and carbon dots. To achieve this aim, first we introduce the fabrication methods of various aerogels, and, then, discuss the strategies for regulating the structures of CMBAs by adjusting the porosity and periodicity. In addition, the hybridization of CMBAs with other nanomaterials for enhanced properties and functions is demonstrated and discussed through presenting the synthesis processes of various CMBAs. After that, the adsorption performances and mechanisms of functional CMBAs towards CO2, CO, H2S, H2, and organic gases are analyzed in detail. Finally, we provide our own viewpoints on the possible development directions and prospects of this promising research topic. We believe this work is valuable for readers to understand the synthesis methods and functional tailoring of CMBAs, and, meanwhile, to promote the applications of CMBAs in environmental analysis and safety monitoring of harmful gases.
Li-Ion Conductive Li1.3Al0.3Ti1.7(PO4)3 (LATP) Solid Electrolyte Prepared by Cold Sintering Process with Various Sintering Additives
Authors: Vinnichenko Mykola , Waetzig Katja , Aurich Alf , Baumgaertner Christoph , Herrmann Mathias , Ho Chang Won , Kusnezoff Mihails , Lee Chang Woo
Published: September 2022

The density, microstructure, and ionic conductivity of solid electrolyte Li1.3Al0.3Ti1.7(PO4)3 (LATP) ceramics prepared by cold sintering using liquid and solid sintering additives are studied. The effects of both liquid (water and water solutions of acetic acid and lithium hydroxide) and solid (lithium acetate) additives on densification are investigated. The properties of cold-sintered LATP are compared to those of conventionally sintered LATP. The materials cold-sintered at temperatures 140–280 °C and pressures 510–600 MPa show relative density in the range of 90–98% of LATP’s theoretical value, comparable or higher than the density of conventionally sintered ceramics. With the relative density of 94%, a total ionic conductivity of 1.26 × 10−5 S/cm (room temperature) is achieved by cold sintering at the temperature of 200 °C and uniaxial pressure of 510 MPa using water as additive. The lower ionic conductivities of the cold-sintered ceramics compared to those prepared by conventional sintering are attributed to the formation of amorphous secondary phases in the intergranular regions depending on the type of additives used and on the processing conditions selected.
Parallel Propagation of Toxoplasma gondii In Vivo, In Vitro and in Alternate Model: Towards Less Dependence on the Mice Model
Authors: Gargaté Maria João , Vilares Anabela , Ferreira Idalina , Reis Tânia , Martins Susana , Mendonça Joana , Borges Vítor , Gomes João Paulo
Published: September 2022

Toxoplasma gondii is an obligate intracellular protozoan. In pregnant women, it can lead to severe birth defects or intrauterine death of the fetus. Most of what is currently know on cell biology of T. gondii comes from studies relying on the RH strain propagated in mice. According to the recommendations concerning the animal welfare, we assayed in vitro/in vivo procedures to replace, or at least reduce, the demanding animal model for strain propagation. We evaluated the genetic and phenotypic stability of the RH strain throughout its parallel continuous propagation in mice, in human foreskin fibroblasts (HFF) and in an alternate fashion of these two procedures. We also assessed the virulence impact on the RH strain after different periods of its long-term propagation strictly in cells. The RH strain completely lost its virulence after long-term passage in HFF. Nevertheless, we obtained a successful outcome with the alternate passaging of the parasite in HFF and in mice as this approach enabled T. gondii to maintain the evaluated phenotypic properties, mainly its virulence potential. Also, no genetic changes were observed in genes known to be highly polymorphic or involved in pathoadaptation. In conclusion, the alternate model seems to be a feasible method for T. gondii propagation and maintenance, strongly impacting the number of sacrificed mice.
Influence of Morphostructural Elements for Buckwheat (Fagopyrum esculentum Moench) Productivity in Different Agricultural Systems
Authors: Romanovskaja Danuta , Razukas Almantas , Asakaviciute Rita
Published: September 2022

The research was carried out at Vokė Branch of the Institute of Agriculture of Lithuanian Research Centre for Agriculture and Forestry in 2018–2019. The objective of this study was to determine the influence of the relative proportion of stems, leaves and flowers on biomass formation and grain yield in organic and conventional farming systems. The study found that buckwheat produced one-third more biomass in the conventional farming system than in the organic farming system. Differences between buckwheat cultivars were more distinct due to biomass formation than grain yield. The research determined that the productivity (biomass and grain yields) of buckwheat was dependent on the proportion of morphological elements in plants and the process of biomass formation and grain yield in organic and conventional agricultural systems. Biomass yields depended on the relative number of stems in both farming systems. Grain yield depended on the ratio of flowers in the morphostructure; however, statistically significant correlations were found only in the organic farming system.
New Insight into Ornamental Applications of Cannabis: Perspectives and Challenges
Authors: Hesami Mohsen , Pepe Marco , Baiton Austin , Salami Seyed Alireza , Jones Andrew Maxwell Phineas
Published: September 2022

The characteristic growth habit, abundant green foliage, and aromatic inflorescences of cannabis provide the plant with an ideal profile as an ornamental plant. However, due to legal barriers, the horticulture industry has yet to consider the ornamental relevance of cannabis. To evaluate its suitability for introduction as a new ornamental species, multifaceted commercial criteria were analyzed. Results indicate that ornamental cannabis would be of high value as a potted-plant or in landscaping. However, the readiness timescale for ornamental cannabis completely depends on its legal status. Then, the potential of cannabis chemotype Ⅴ, which is nearly devoid of phytocannabinoids and psychoactive properties, as the foundation for breeding ornamental traits through mutagenesis, somaclonal variation, and genome editing approaches has been highlighted. Ultimately, legalization and breeding for ornamental utility offers boundless opportunities related to economics and executive business branding.
Synthesis of Good Electrical Conductivity of CoCe-BTC/PEDOT for Ultrahigh Selectivity of NO2 Detection
Authors: Zha Xiaoting , Xi Runhui , Wu Yuanyuan , Xu Jianhua , Yang Yajie
Published: September 2022

Metal–organic frameworks (MOFs) have broad application prospects in the development of efficient, sensitive and single select gas sensors. However, in order to construct a chemical resistance gas sensor based on MOFs, the problem of poor conductivity of MOFs must be solved. In this work, we synthesized CoCe-BTC, which based on the organic ligands of trimesic acid (H3BTC) by the water bath method and prepared CoCe-BTC/PEDOT composite film on an interdigital electrode by the spin coating process. Compared with pure MOF material, the conductivity of CoCe-BTC/PEDOT is significantly improved. Under a dry room temperature environment and N2 as the carrier gas, the response of the sensor to NO2 is about 1.2 times that of pure PEDOT and has a shorter response time. It has great repeatability and selectivity and shows a dynamic response with the change of NO2 gas concentration (5–50 ppm).
Assessing Cognitive Workload Using Cardiovascular Measures and Voice
Authors: Magnusdottir Eydis H. , Johannsdottir Kamilla R. , Majumdar Arnab , Gudnason Jon
Published: September 2022

Monitoring cognitive workload has the potential to improve both the performance and fidelity of human decision making. However, previous efforts towards discriminating further than binary levels (e.g., low/high or neutral/high) in cognitive workload classification have not been successful. This lack of sensitivity in cognitive workload measurements might be due to individual differences as well as inadequate methodology used to analyse the measured signal. In this paper, a method that combines the speech signal with cardiovascular measurements for screen and heartbeat classification is introduced. For validation, speech and cardiovascular signals from 97 university participants and 20 airline pilot participants were collected while cognitive stimuli of varying difficulty level were induced with the Stroop colour/word test. For the trinary classification scheme (low, medium, high cognitive workload) the prominent result using classifiers trained on each participant achieved 15.17 ± 0.79% and 17.38 ± 1.85% average misclassification rates indicating good discrimination at three levels of cognitive workload. Combining cardiovascular and speech measures synchronized to each heartbeat and consolidated with short-term dynamic measures might therefore provide enhanced sensitivity in cognitive workload monitoring. The results show that the influence of individual differences is a limiting factor for a generic classification and highlights the need for research to focus on methods that incorporate individual differences to achieve even better results. This method can potentially be used to measure and monitor workload in real time in operational environments.
Methodology for Sound Quality Analysis of Motors for Automotive Interior Parts through Subjective Evaluation
Authors: Kim Sung-Yuk , Ryu Sang-Chul , Jun Yong-Du , Kim Young-Choon , Oh Jong-Seok
Published: September 2022

With the development of autonomous vehicles, activities in the indoor spaces of autonomous vehicles are diversifying. Therefore, as the operating range of the interior parts increases, the occupant becomes sensitive to the operating noise of autonomous vehicles. Therefore, to reduce operating noise, it is necessary to analyze the causal relationship between the mechanical/electrical noise characteristics of the motor and sound quality. In this paper, we propose a methodology to analyze the relationship between the noise frequency components and the sound quality of small motors used in automobile interior parts. Two types of motors were selected for this study, and noise measurements and analyses were performed by applying the design proposed in this study. Subjective sound quality evaluations were conducted using the 12 pairs of adjectives extracted from the survey. The results suggest that subjective sound quality evaluation scores should be converted to Z-scores to ensure the reliability of the statistical analysis. In addition, we present a critical sound quality value that can be used as a criterion for determining whether the sound quality is positive (good quality) or negative (bad quality). Sound quality regression models explain the causal relationship between rotational frequency components of the motor and subjective sound quality characteristics. Thus, a method for analyzing the effect of the rotational frequency component of the motor on the sound quality is presented, which suggests that it can be used as basic research data to improve the noise performance of the motor.
LR-AKAP: A Lightweight and Robust Security Protocol for Smart Home Environments
Authors: Haseeb-ur-rehman Rana Muhammad Abdul , Liaqat Misbah , Aman Azana Hafizah Mohd , Almazroi Abdulwahab Ali , Hasan Mohammad Kamrul , Ali Zeeshan , Ali Rana Liaqat
Published: September 2022

For the betterment of human life, smart Internet of Things (IoT)-based systems are needed for the new era. IoT is evolving swiftly for its applications in the smart environment, including smart airports, smart buildings, smart manufacturing, smart homes, etc. A smart home environment includes resource-constrained devices that are interlinked, monitored, controlled, and analyzed with the help of the Internet. In a distributed smart environment, devices with low and high computational power work together and require authenticity. Therefore, a computationally efficient and secure protocol is needed. The authentication protocol is employed to ensure that authorized smart devices communicate with the smart environment and are accessible by authorized personnel only. We have designed a novel, lightweight secure protocol for a smart home environment. The introduced novel protocol can withstand well-known attacks and is effective with respect to computation and communication complexities. Comparative, formal, and informal analyses were conducted to draw the comparison between the introduced protocol and previous state-of-the-art protocols.
Efficient Matching-Based Parallel Task Offloading in IoT Networks
Authors: Malik Usman Mahmood , Javed Muhammad Awais , Frnda Jaroslav , Rozhon Jan , Khan Wali Ullah
Published: September 2022

Fog computing is one of the major components of future 6G networks. It can provide fast computing of different application-related tasks and improve system reliability due to better decision-making. Parallel offloading, in which a task is split into several sub-tasks and transmitted to different fog nodes for parallel computation, is a promising concept in task offloading. Parallel offloading suffers from challenges such as sub-task splitting and mapping of sub-tasks to the fog nodes. In this paper, we propose a novel many-to-one matching-based algorithm for the allocation of sub-tasks to fog nodes. We develop preference profiles for IoT nodes and fog nodes to reduce the task computation delay. We also propose a technique to address the externalities problem in the matching algorithm that is caused by the dynamic preference profiles. Furthermore, a detailed evaluation of the proposed technique is presented to show the benefits of each feature of the algorithm. Simulation results show that the proposed matching-based offloading technique outperforms other available techniques from the literature and improves task latency by 52% at high task loads.
Reflection Characteristics Measurements of Indoor Wireless Link in D-Band
Authors: Wang Mingxu , Wang Yanyi , Li Weiping , Ding Junjie , Bian Chengzhen , Wang Xinyi , Wang Chao , Li Chao , Zhong Zhimeng , Yu Jianjun
Published: September 2022

For the millimeter wave (mm-Wave) and terahertz (THz) indoor wireless communication system, the reflection channels need to be characterized and modeled. In this paper, the reflection measurements of the parallel polarized wave are carried out under multiple incident angles and five kinds of materials in the D-band (110–170 GHz). A modified reflection model with two parameters estimated by the minimum mean square error (MMSE) criterion is proposed. The results show that the measurements are in good agreement with the proposed model. Furthermore, a set of measured properties is demonstrated and it can be concluded that both the reflection coefficients and relative permittivity gradually decrease, whereas the surface roughness increases slightly with the increasing frequency, indicating a weak frequency dependence. Interestingly, the concrete board with high surface roughness, which means more power loss in a specular direction, has the lowest reflection loss at a certain frequency and incident angle. It implies that the reflection characteristics of indoor building materials are determined not only by surface roughness, but also by many other factors, such as relative permittivity, frequency, and incident angle. Our work suggests that the reflection measurements of indoor D-band wireless links have a prospective application for future indoor wireless communication systems.
Deep Learning-Based Feature Extraction of Acoustic Emission Signals for Monitoring Wear of Grinding Wheels
Authors: González D. , Alvarez J. , Sánchez J. A. , Godino L. , Pombo I.
Published: September 2022

Tool wear monitoring is a critical issue in advanced manufacturing systems. In the search for sensing devices that can provide information about the grinding process, Acoustic Emission (AE) appears to be a promising technology. The present paper presents a novel deep learning-based proposal for grinding wheel wear status monitoring using an AE sensor. The most relevant finding is the possibility of efficient feature extraction form frequency plots using CNNs. Feature extraction from FFT plots requires sound domain-expert knowledge, and thus we present a new approach to automated feature extraction using a pre-trained CNN. Using the features extracted for different industrial grinding conditions, t-SNE and PCA clustering algorithms were tested for wheel wear state identification. Results are compared for different industrial grinding conditions. The initial state of the wheel, resulting from the dressing operation, is clearly identified for all the experiments carried out. This is a very important finding, since dressing strongly affects operation performance. When grinding parameters produce acute wear of the wheel, the algorithms show very good clustering performance using the features extracted by the CNN. Performance of both t-SNE and PCA was very much the same, thus confirming the excellent efficiency of the pre-trained CNN for automated feature extraction from FFT plots.
Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM
Authors: Alsharekh Mohammed F. , Habib Shabana , Dewi Deshinta Arrova , Albattah Waleed , Islam Muhammad , Albahli Saleh
Published: September 2022

Multistep power consumption forecasting is smart grid electricity management’s most decisive problem. Moreover, it is vital to develop operational strategies for electricity management systems in smart cities for commercial and residential users. However, an efficient electricity load forecasting model is required for accurate electric power management in an intelligent grid, leading to customer financial benefits. In this article, we develop an innovative framework for short-term electricity load forecasting, which includes two significant phases: data cleaning and a Residual Convolutional Neural Network (R-CNN) with multilayered Long Short-Term Memory (ML-LSTM) architecture. Data preprocessing strategies are applied in the first phase over raw data. A deep R-CNN architecture is developed in the second phase to extract essential features from the refined electricity consumption data. The output of R-CNN layers is fed into the ML-LSTM network to learn the sequence information, and finally, fully connected layers are used for the forecasting. The proposed model is evaluated over residential IHEPC and commercial PJM datasets and extensively decreases the error rates compared to baseline models.
Classification of Skin Cancer Lesions Using Explainable Deep Learning
Authors: Zia Ur Rehman Muhammad , Ahmed Fawad , Alsuhibany Suliman A. , Jamal Sajjad Shaukat , Zulfiqar Ali Muhammad , Ahmad Jawad
Published: September 2022

Skin cancer is among the most prevalent and life-threatening forms of cancer that occur worldwide. Traditional methods of skin cancer detection need an in-depth physical examination by a medical professional, which is time-consuming in some cases. Recently, computer-aided medical diagnostic systems have gained popularity due to their effectiveness and efficiency. These systems can assist dermatologists in the early detection of skin cancer, which can be lifesaving. In this paper, the pre-trained MobileNetV2 and DenseNet201 deep learning models are modified by adding additional convolution layers to effectively detect skin cancer. Specifically, for both models, the modification includes stacking three convolutional layers at the end of both the models. A thorough comparison proves that the modified models show their superiority over the original pre-trained MobileNetV2 and DenseNet201 models. The proposed method can detect both benign and malignant classes. The results indicate that the proposed Modified DenseNet201 model achieves 95.50% accuracy and state-of-the-art performance when compared with other techniques present in the literature. In addition, the sensitivity and specificity of the Modified DenseNet201 model are 93.96% and 97.03%, respectively.
Space-Time Adaptive Processing Based on Modified Sparse Learning via Iterative Minimization for Conformal Array Radar
Authors: Ren Bing , Wang Tong
Published: September 2022

Space-time adaptive processing (STAP) is a well-known technique for slow-moving target detection in the clutter spreading environment. For an airborne conformal array radar, conventional STAP methods are unable to provide good performance in suppressing clutter because of the geometry-induced range-dependent clutter, non-uniform spatial steering vector, and polarization sensitivity. In this paper, a knowledge aided STAP method based on sparse learning via iterative minimization (SLIM) combined with Laplace distribution is proposed to improve the STAP performance for a conformal array. The proposed method can avoid selecting the user parameter. the proposed method constructs a dictionary matrix that is composed of the space-time steering vector by using the prior knowledge of the range cell under test (CUT) distributed in clutter ridge. Then, the estimated sparse parameters and noise power can be used to calculate a relatively accurate clutter plus noise covariance matrix (CNCM). This method could achieve superior performance of clutter suppression for a conformal array. Simulation results demonstrate the effectiveness of this method.
Domain Feature Mapping with YOLOv7 for Automated Edge-Based Pallet Racking Inspections
Authors: Hussain Muhammad , Al-Aqrabi Hussain , Munawar Muhammad , Hill Richard , Alsboui Tariq
Published: September 2022

Pallet racking is an essential element within warehouses, distribution centers, and manufacturing facilities. To guarantee its safe operation as well as stock protection and personnel safety, pallet racking requires continuous inspections and timely maintenance in the case of damage being discovered. Conventionally, a rack inspection is a manual quality inspection process completed by certified inspectors. The manual process results in operational down-time as well as inspection and certification costs and undiscovered damage due to human error. Inspired by the trend toward smart industrial operations, we present a computer vision-based autonomous rack inspection framework centered around YOLOv7 architecture. Additionally, we propose a domain variance modeling mechanism for addressing the issue of data scarcity through the generation of representative data samples. Our proposed framework achieved a mean average precision of 91.1%.
A Personalized User Authentication System Based on EEG Signals
Authors: Stergiadis Christos , Kostaridou Vasiliki-Despoina , Veloudis Simos , Kazis Dimitrios , Klados Manousos A.
Published: September 2022

Conventional biometrics have been employed in high-security user-authentication systems for over 20 years now. However, some of these modalities face low-security issues in common practice. Brainwave-based user authentication has emerged as a promising alternative method, as it overcomes some of these drawbacks and allows for continuous user authentication. In the present study, we address the problem of individual user variability, by proposing a data-driven Electroencephalography (EEG)-based authentication method. We introduce machine learning techniques, in order to reveal the optimal classification algorithm that best fits the data of each individual user, in a fast and efficient manner. A set of 15 power spectral features (delta, theta, lower alpha, higher alpha, and alpha) is extracted from three EEG channels. The results show that our approach can reliably grant or deny access to the user (mean accuracy of 95.6%), while at the same time poses a viable option for real-time applications, as the total time of the training procedure was kept under one minute.