Search

Passion fruit is known to be sensitive to drought, and in order to study the physiological and biochemical changes that occur in passion fruit seedlings under drought stress, a hypertonic polyethylene glycol (PEG) solution (5%, 10%, 15%, and 20%) was used to simulate drought stress in passion fruit seedlings. We explored the physiological changes in passion fruit seedlings under drought stress induced by PEG to elucidate their response to drought stress and provide a theoretical basis for drought-resistant cultivation of passion fruit seedlings. The results show that drought stress induced by PEG had a significant effect on the growth and physiological indices of passion fruit. Drought stress significantly decreased fresh weight, chlorophyll content, and root vitality. Conversely, the contents of soluble protein (SP), proline (Pro), and malondialdehyde (MDA) increased gradually with the increasing PEG concentration and prolonged stress duration. After nine days, the SP, Pro and MDA contents were higher in passion fruit leaves and roots under 20% PEG treatments compared with the control. Additionally, with the increase in drought time, the activities of antioxidant enzymes such as peroxidase (POD), superoxide dismutase (SOD) and catalase (CAT) showed an increasing trend and then a decreasing trend, and they reached the highest value at the sixth day of drought stress. After rehydration, SP, Pro and MDA contents in the leaves and roots of passion fruit seedlings was reduced. Among all the stress treatments, 20% PEG had the most significant effect on passion fruit seedlings. Therefore, our study demonstrated sensitive concentrations of PEG to simulate drought stress on passion fruit and revealed the physiological adaptability of passion fruit to drought stress.

Continuous cropping of eggplant threatened regional ecological sustainability by facilitating replanting problems under mono-cropping conditions. Therefore, alternative agronomic and management practices are required to improve crop productivity at low environmental cost for the development of sustainable agricultural systems in different regions. This study examined changes in soil chemical properties, eggplant photosynthesis, and antioxidant functioning in five different vegetable cropping systems over a 2-year period., 2017 and 2018. The results showed that welsh onion-eggplant (WOE), celery-eggplant (CE), non-heading Chinese cabbage-eggplant (NCCE), and leafy lettuce-eggplant (LLE) rotation systems significantly impacted growth, biomass accumulation, and yield than fallow-eggplant (FE). In addition, various leafy vegetable cropping systems, WOE, CE, NCCE, and LLT induced significant increases in soil organic matter (SOM), available nutrients (N, P, and K), and eggplant growth by affecting the photosynthesis and related gas exchange parameters with much evident effect due to CE and NCCE. Moreover, eggplant raised with different leafy vegetable rotation systems showed higher activity of antioxidant enzymes, resulting in lower accumulation of hydrogen peroxide and hence reduced oxidative damage to membranes. In addition, fresh and dry plant biomass was significantly increased due to crop rotation with leafy vegetables. Therefore, we concluded that leafy vegetable crop rotation is a beneficial management practice to improve the growth and yield of eggplant.

The enforcement of the Movement Control Order to curtail the spread of COVID-19 has affected home energy consumption, especially HVAC systems. Occupancy detection and estimation have been recognized as key contributors to improving building energy efficiency. Several solutions have been proposed for the past decade to improve the precision performance of occupancy detection and estimation in the building. Environmental sensing is one of the practical solutions to detect and estimate occupants in the building during uncertain behavior. However, the literature reveals that the performance of environmental sensing is relatively poor due to the poor quality of the training dataset used in the model. This study proposed a smart sensing framework that combined camera-based and environmental sensing approaches using supervised learning to gather standard and robust datasets related to indoor occupancy that can be used for cross-validation of different machine learning algorithms in formal research. The proposed solution is tested in the living room with a prototype system integrated with various sensors using a random forest regressor, although other techniques could be easily integrated within the proposed framework. The primary implication of this study is to predict the room occupation through the use of sensors providing inputs into a model to lower energy consumption. The results indicate that the proposed solution can obtain data, process, and predict occupant presence and number with 99.3% accuracy. Additionally, to demonstrate the impact of occupant number in energy saving, one room with two zones is modeled each zone with air condition with different thermostat controller. The first zone uses IoFClime and the second zone uses modified IoFClime using a design-builder. The simulation is conducted using EnergyPlus software with the random simulation of 10 occupants and local climate data under three scenarios. The Fanger model's thermal comfort analysis shows that up to 50% and 25% energy can be saved under the first and third scenarios.

Threatening the global community is a wide variety of potential threats, most notably invasive pest species. Invasive pest species are non-native organisms that humans have either accidentally or intentionally spread to new regions. One of the most effective and first lines of control strategies for controlling pests is the application of insecticides. These toxic chemicals are employed to get rid of pests, but they pose great risks to people, animals, and plants. Pesticides are heavily used in managing invasive pests in the current era. Due to the overuse of synthetic chemicals, numerous invasive species have already developed resistance. The resistance development is the main reason for the failure to manage the invasive species. Developing pesticide resistance management techniques necessitates a thorough understanding of the mechanisms through which insects acquire insecticide resistance. Insects use a variety of behavioral, biochemical, physiological, genetic, and metabolic methods to deal with toxic chemicals, which can lead to resistance through continuous overexpression of detoxifying enzymes. An overabundance of enzymes causes metabolic resistance, detoxifying pesticides and rendering them ineffective against pests. A key factor in the development of metabolic resistance is the amplification of certain metabolic enzymes, specifically esterases, Glutathione S-transferase, Cytochromes p450 monooxygenase, and hydrolyses. Additionally, insect guts offer unique habitats for microbial colonization, and gut bacteria may serve their hosts a variety of useful services. Most importantly, the detoxification of insecticides leads to resistance development. The complete knowledge of invasive pest species and their mechanisms of resistance development could be very helpful in coping with the challenges and effectively developing effective strategies for the control of invasive species. Integrated Pest Management is particularly effective at lowering the risk of chemical and environmental contaminants and the resulting health issues, and it may also offer the most effective ways to control insect pests.

Study Design Retrospective cohort study. Objectives Intraoperative neurophysiological monitoring (IONM) is widely used in spinal neurosurgery, particularly for intramedullary tumours. However, its validity in intradural extramedullary (IDEM) spinal tumours is less clearly defined, this being the focus of this study. Methods We compared outcomes for patients that underwent resection of IDEM tumours with and without IONM between 2010 and 2020. Primary outcomes were postoperative American Spinal Injury Association (ASIA) scores. Other factors assessed were use of intraoperative ultrasound, drain placement, postoperative complications, postoperative Eastern Cooperative Oncology Group (ECOG) score, extent of resection, length of hospital stay, discharge location and recurrence. Results 163 patients were included, 71 patients in the IONM group and 92 in the non-IONM group. No significant differences were noted in baseline demographics. For preoperative ASIA D patients, 44.0% remained ASIA D and 49.9% improved to ASIA E in the IONM group, compared to 39.7% and 30.2% respectively in the non-IONM group. For preoperative ASIA E patients, 50.3% remained ASIA E and 44.0% deteriorated to ASIA D in the IONM group, compared to 30.2% and 39.7% respectively in the non-IONM group (all other patients deteriorated further). Length of inpatient stay was significantly shorter in the IONM group ( P = .043). There were no significant differences in extent of resection, postoperative complications, discharge location or tumour recurrence. Conclusions Research focusing on the use of IONM in IDEM tumour surgery remains scarce. Our study supports the use of IONM during surgical excision of IDEM tumours.

Insecticide resistance poses many challenges in insect pest control, particularly in the control of destructive pests such as red imported fire ants (Solenopsis invicta). In recent years, beta-cypermethrin and fipronil have been extensively used to manage invasive ants, but their effects on resistance development in S. invicta are still unknown. To investigate resistance development, S. invicta was collected from populations in five different cities in Guangdong, China. The results showed 105.71- and 2.98-fold higher resistance against fipronil and beta-cypermethrin, respectively, in the Guangzhou population. The enzymatic activities of acetylcholinesterase, carboxylases, and glutathione S-transferases significantly increased with increasing beta-cypermethrin and fipronil concentrations. Transcriptomic analysis revealed 117 differentially expressed genes (DEGs) in the BC-ck vs. BC-30 treatments (39 upregulated and 78 downregulated), 109 DEGs in F-ck vs. F-30 (33 upregulated and 76 downregulated), and 499 DEGs in BC-30 vs. F-30 (312 upregulated and 187 downregulated). Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that DEGs associated with insecticide resistance were significantly enriched in metabolic pathways, the AMPK signaling pathway, the insulin signaling pathway, carbon metabolism, peroxisomes, fatty acid metabolism, drug metabolism enzymes and the metabolism of xenobiotics by cytochrome P450. Furthermore, we found that DEGs important for insecticide detoxification pathways were differentially regulated under both insecticide treatments in S. invicta. Comprehensive transcriptomic data confirmed that detoxification enzymes play a significant role in insecticide detoxification and resistance development in S. invicta in Guangdong Province. Numerous identified insecticide-related genes, GO terms, and KEGG pathways indicated the resistance of S. invicta workers to both insecticides. Importantly, this transcriptome profile variability serves as a starting point for future research on insecticide risk evaluation and the molecular mechanism of insecticide detoxification in invasive red imported fire ants.

Purpose The coronavirus 2019 (COVID-19) pandemic has rapidly spread worldwide, with an ever-increasing number of confirmed positive cases and mortality rate. Moreover, frontline medical staff fighting with the COVID-19 infection have been infected and show psychological effects of the pandemic. This study presents an overview of the emerging literature on the safety challenges of frontline medical staff and how technology is being used to control the COVID-19 pandemic. Methods This study conducts a rapid review of available studies by following the “preferred reporting items for systematic reviews and meta-analyses” (PRISMA) guidelines. Sixty-three articles were selected for this rapid review paper from three popular digital data repositories. Results The majority of the studies chosen focused on the discussion of COVID-19 with regard to China, Singapore, Italy, and the USA. A previously proposed framework is used to synthesize the findings of this study. The results throw light on the several challenges faced by medical staff during the COVID-19 pandemic. Eleven major technologies have been identified in this paper. Conclusion This work concludes that technology helps in the prevention and detection of the COVID-19 infection, where it specifically helps in reducing the safety challenges of frontline medical staff and monitoring the COVID-19 patients.

Low temperature (LT) and high humidity (HH) are important environmental factors in greenhouses and plastic tunnels during the cold season, as they hamper plant growth and development. Here, we studied the effect of LT (day/night: 9/5 °C, 25/18 °C as control) and HH (95%, 80% as control) on young cucumber plants at the 2, 4 or 6 leaf stages. LT+HH stress resulted in a decline in shoot, root and total fresh and dry weights, and decreased Pn , gs , Tr , Fv /Fm , qP, ETR and chlorophyll, and increased MDA, H2 O2 , O2 - , NPQ and Ci as compared to the control at the 2 leaf stage. SOD, POD, CAT, APX and GR were upregulated under LT+HH stress as compared to the control at the 6 leaf stage. ABA and JA increased under LT+HH stress as compared to the control at the 6 leaf stage, while IAA and GA decreased under LT+HH stress as compared to the control at the 2 leaf stage. Our results show that LT+HH stress affects young cucumber plant photosynthetic efficiency, PSII activity, antioxidant defence system, ROS and hormone profile. Plants at the 6 leaf stage were more tolerant than at the 2 and 4 leaf stages under stress conditions.

The dynamic behavior of web services is critical for researchers to determine their performance at different times. Many existing studies present the static information of web services that are not so effective for estimating web services' future performance. This research article reveals the acquisition of throughput metric dataset for thirty timestamps by a simulation technique. A simulated setup has been proposed to acquire the dynamic throughput data of benchmark web services from workload modeling. The proposed method is aimed to collect dynamic web services metrics data of five web services (WS1–WS5), which are randomly selected from WS-Dream dataset. Additionally, the collected data has been verified by measuring computer resource usage metrics in four experiments. Experiment results indicate that the varying ‘Central Processing Unit’ (CPU) resource usage metrics do not show changes in the collected ‘Quality of Service’ QoS metric values. The experiment results showed that the proposed method achieves the consistent average response time and throughput metric values. The collected simulated data can be further applied to improve the quality of web services.

Background: Diaphyseal fractures of the tibia currently account for approximately 2% of all fractures presenting to orthopedic surgeons. Epidemiology has changed markedly during the last two decades with overcrowding and related to improved road safety. In comparison to young population majority of these fracture occur predominantly in females as compared to males in old population. Objectives: To determine the outcome of diaphysis fractures of tibia in elderly patients Methods: This study was carried out in department of orthopaedic Jinnah hospital Lahore from 2014-2017. One hundred and twenty patients both males and females in the age range of 65 to 80years, having diaphyseal fractures of tibia were included in the study. The patients with poly-trauma and with peri-prosthetic fractures were excluded from the study. After detailed medical history, clinical examination, the x-rays of tibia fibula AP and Lateral views including joint above and below were done to determine the configuration of the fracture. Each patient was followed at 1st, 2nd and at 6th week and then at 3rd month, 4th month, 6th month and later at 1 year. Data was entered and analyzed in SPSS ver: 21.0 and was presented and frequency and percentages. Cross tabulation was done for open and closed fracture for outcome and Chi Square test was used to assess statistical significance with p value of ≤0.05. Results: 62.5% were females and 37.5% were males with mean age of 72 + 5.45 years. The mode of injury in most of the patients was slip and fall 85% and 70 % of patients had closed fractures. Reamed intra medullary nailing was done in 80 patients and 25 patients with open fracture were treated with external fixator. In the remaining 5 patients we applied the POP cast. Nonunion was labeled at 9 months and was seen in 10.0% of patients while the delayed union was seen in 33.0% (40) of the patients. Among the patients who had nonunion 5 patients were treated with intramedullary nailing and 7 patients were treated with external fixator. Infection was seen in 10.0% (12) of patients and this happened in the patient with open fracture. No patient was lost in follow-up during the study. Overall mortality rate was 30% in the 1st year.

Currently building structure sector takes lead in energy consumption across the globe and is expected to increase by 2% every year. Consequently, being a major energy consumer, it's required to make effort for energy conservation as well. However, this energy conservation has to be in line with occupant thermal comfort. Recent advancement in the Internet of Things concepts attempts to transform residential areas into an energy-aware environment with aimed to reduce energy waste and automate home activities. To identify research trends and challenges in this area the study adopted the Kincham approach to performing review analysis. Our study reveals despite the benefit of this innovation, only resident with two or more unit building structure is mostly benefiting from this opportunity. Out of 94 studies considered 67 are proposed solutions. To find the trend of the research we classified the proposed solution into the topic domain (architecture, algorithm, platform, framework, and model) and it shows that trends moving toward proposing an algorithm to optimize energy consumption in the smart building structure. The study also performed an analytical evaluation on a proposed solution to assess their quality attributes and our evaluation reveals none of the studies considered security in their solution. Finally, the study identifies challenges that bottleneck the development and acceptance of this innovation into societies.

To accurately rank various web services can be a very challenging task depending on the evaluation criteria used, however, it can play an important role in performing a better selection of web services afterward. This paper proposes an approach to evaluate trust prediction and confusion matrix to rank web services from throughput and response time. AdaBoostM1 and J48 classifiers are used as binary classifiers on a benchmark web services dataset. The trust score (TS) measuring method is proposed by using the confusion matrix to determine trust scores of all web services. Trust prediction is calculated using 5-Fold, 10-Fold, and 15-Fold cross-validation methods. The reported results showed that the web service 1 (WS1) was most trusted with (48.5294%) TS value, and web service 2 (WS2) was least trusted with (24.0196%) TS value by users. Correct prediction of trusted and untrusted users in web services invocation has improved the overall selection process in a pool of similar web services. Kappa statistics values are used for the evaluation of the proposed approach and for performance comparison of the two above-mentioned classifiers.

Web services have emerged as an accessible technology with the standard 'Extensible Mark Up' (XML) language, which is known as 'Web Services Description Language' WSDL. Web services have become a promising technology to promote the interrelationship between service providers and users. Web services users' trust is measured by quality metrics. Web service quality metrics vary in many benchmark datasets used in the existing studies. The selection of a benchmark dataset is problematic to classify and retest web services. This paper proposes a method to rank web services quality metrics for the selection of benchmark web services datasets. To measure the diversity in quality metrics, factor analysis with Varimax rotation and scree plot is a well-established method. We use factor analysis to determine percentage variance among principal factors of four benchmark datasets. Our results showed that the two-factor solution explained 94.501, 76.524, and 45.009% variances in datasets A, B, and D, respectively. A three-factor solution explained 85.085% variance in dataset C. Reliability, and response time quality metrics were predicted as the most dominating quality metrics that contributed to explain the percentage variance in four datasets. Our proposed web metric ranking (WMR) method resulted in reliability as the top-most web metric with (57.62%) score and latency web metric at the bottom-most with (3.60%) score. The proposed WMR method showed a high (96.17%) ranking precision. Obtained results verified that factor solutions after reducing the dimensions could be generalized and used in the quality improvement of web services. In future works, the authors plan to focus on a dataset with dominating quality metrics to perform regression testing of web services.

Vegetable production under plastic sheds severely threatens regional eco-sustainability via anthropogenic activities (excessive use of agrochemicals, pesticides) and problems associated with replanting. Long-term successive cropping across growing seasons induces continuous cropping stress, whose effects manifest as diminished plant growth. Therefore, it is imperative that we develop environmentally sustainable approaches, such as replacing agrochemicals with vegetable waste like dry raw garlic stalk (DRGS) or use biofertilizers like arbuscular mycorrhizal fungi (AMF) (e.g., Diversispora epigaea). In this study, the influence of AMF on the growth, biochemical attributes, antioxidant defense system, phytohormones, accumulation of osmolytes, phenols, and mineral elements in eggplant grown on DRGS-amended soils under continuous monocropping (CMC) was studied. The results showed that inoculation with AMF or the DRGS amendment could improve the pigments’ content, photosynthesis, and antioxidant defense system; augmented phytohormones synthesis (except for ABA), and increased the leaves’ mineral nutrients. These parameters were enhanced most by the combined application of AMF and DRGS, which also increased the concentration of osmolytes, including proline, sugars, and free amino acids in eggplant when compared with the control. Furthermore, either AMF and DRGS alone, or in combination, ameliorated the induced stress from continuous cropping by reducing the incidence of Fusarium wilt and production of ROS (reactive oxygen species); lipid peroxidation underwent maximal reduction in plants grown under the combined treatments. The AMF, DRGS, and AMF + DRGS exhibited a lower disease severity index (33.46, 36.42, and 43.01%), respectively, over control. Hence, inoculation with AMF coupled with DRGS amendment alters the photosynthetic attributes in eggplant through the upregulation of its antioxidant system and greater accumulation of osmolytes, which led to the improved growth and yield of eggplant.

Mitigation of greenhouse gas (GHGs) emissions and improving soil health using biochar (BC) shall help achieving the UN-Sustainable Development Goals. The impacts of walnut shells biochar (WSB) pyrolyzed at different temperatures on CO

AIMS 5-ALA (Gliolan©) is a valuable surgical tool used predominantly in high grade tumours, which utilises tissue fluorescence to improve the visualisation of the brain-tumour interface. This ensures safe maximal resection, while preserving healthy brain. While Gliolan© use in low grade tumours has previously been reported with variable results, reports of its use and success in the context of SEGA are extremely rare. This report highlights the use of Gliolan© in a patient presenting with a Subependymal Giant Cell Astrocytoma (in a background of tuberous sclerosis), facilitating maximal safe resection and preserving eloquent tissue. METHOD Tumour resection was performed with pre-operative DTI-fiber tracking and mapping. A transsulcal minimal invasive parafascicular approach (tsMIPS) was carried out with assistance of NICO BrainPath© tubular retractor system (60x13.5), neuronaviagtion, Gliolan©, intra-operative neuro monitoring (IONM), and ultrasound guidance RESULTS The tumour was found to have both bright and pale fluorescence in the cystic and solid components respectively. Resection was limited to the soft cystic component only, as the solid tumour component showed anatomical attachment to the subgenual area and the fornix. No fluorescence was perceived at the end of resection. The patient made a good recovery with no post-operative deficits. Histopathology confirmed subependymal giant cell astrocytoma (SEGA, WHO grade I). No adjuvant treatment was required CONCLUSION This reports suggests 5-ALA may be beneficial in the safe resection of SEGAs. Further studies and technological advances in the area of photodynamics, imaging, and intra-operative mapping may be helpful to fully evaluate the efficacy of 5-ALA in SEGAs and other low-grade tumours.

Regression testing, as an important part of the software life cycle, ensures the validity of modified software. Researchers’ focus of this research is on functional requirement-based ‘Test Case Prioritization’ (TCP) because requirement specifications help keep the software correctness on customers’ perceived priorities. This research study is aimed to investigate requirement-based TCP approaches, regression testing aspects, applications regarding the validation of proposed TCP approaches, systems’ size under regression testing, test case size and relevant revealed faults, TCP related issues, TCP issues and types of primary studies. Researchers of this paper examined research publications, which have been published between 2009 and 2019, within the seven most significant digital repositories. These repositories are popular, and mostly used for searching papers on topics in software engineering domain. We have performed a meticulous screening of research studies and selected 35 research papers through which to investigate the answers to the proposed research questions. The final outcome of this paper showed that functional requirement-based TCP approaches have been widely covered in primary studies. The results indicated that fault size and the number of test cases are mostly discussed as regression testing aspects within primary studies. In this review paper, it has been identified that iTrust system is widely examined by researchers in primary studies. This paper’s conclusion indicated that most of the primary studies have been demonstrated in the real-world settings by respective researchers of focused primary studies. The findings of this “Systematic Literature Review” (SLR) reveal some suggestions to be undertaken in future research works, such as improving the software quality, and conducting evaluations of larger systems.

Occupancy-driven application research has been active research for a decade that focuses on improving or replacing new building infrastructure to improve building energy efficiency. Existing approaches for HVAC energy saving are putting more emphasis on occupancy detection, estimation, and localization to trade-off between energy consumption and thermal comfort satisfaction. In a non-intrusive approach, various sensors, actuators, and analytic data methods are commonly used to process data from occupant surroundings and trigger appropriate action to achieve the task. However, the performance of the non-intrusive approach reported in the literature is relatively poor due to the lack of quality of dataset used in model training and expropriate choice of machine learning model. This study proposed a non-intrusive approach that to improve the collection and quality of dataset using data pre-processing. The study collected a training dataset using various sensors installed in the building and developed a model using five machine learning models to determine occupant’s presence and estimate their number in the building. The proposed solution is tested in the living room with a prototype system integrated with various sensors designed to obtain occupant surrounding environmental datasets. The model’s prediction results obtained indicate that it is possible for the proposed solution to obtain data, process, and predict the occupant number with high accuracy (73.6 -99.7% using random forest).

Photoperiod is dominant environmental factor that controls plant growth and development. Even though research on plants response to photoperiod is significant in agriculture, molecular mechanisms of garlic in response to photoperiod remain largely unknown. In the current investigation, 3 months old garlic plants were treated with long day (LD) and short day (SD) for 10 and 20 days after treatment (DAT). Liquid chromatography-mass spectrometry (LC-MS) analysis of phytohormones exhibited that indole-3-acetic acid (IAA), zeatin riboside (ZR) and salicylic acid (SA) were observed maximum under LD at 10 DAT, whereas abscisic acid (ABA), gibberellic acid 3 (GA3), zeatin (ZT) and jasmonic acid (JA) were observed maximum under LD at 20 DAT. Transcriptome sequencing analysis was done to evaluate the transcriptional response to LD and SD. Differentially expressed genes (DEGs) were detected to have pathway enrichment. i.e., DNA binding transcription factor activity, transcription regulator activity, transferase activity, transferring hexosyl groups, and sequence specific-DNA binding activity, plant hormone signal transduction, circadian rhythm-plant, biosynthesis of amino acids, phenylpropanoid biosynthesis, and starch and sucrose metabolism. Furthermore, 28 and 40 DEGs were identified related to photoperiod and hormone signaling, respectively and their interaction in response to LD and SD were discussed in detail. Outcomes of current investigation might be useful to provide novel resources for garlic bulb formation in response to photoperiod.

Aqueous garlic extracts (AGE) and garlic allelochemical diallyl disulfide (DADS) have been recently reported to bear bioactive properties to stimulate plant growth and development and alter defense-related physiology. We, therefore, performed a bioassay to study these chemicals as possible biostimulants for defense against Verticillium dahliae in eggplant seedlings. AGE and DADS were applied as a foliar application to the eggplants and samples were collected before and after pathogen inoculation at various intervals to analyze the defense mechanism. The obtained data revealed that with the application of AGE and DADS, the seedlings showed responses including activation of antioxidant enzymes, an abundance of chlorophyll contents, alteration of photosynthesis system, and accumulation of plant hormones compared to the control plants. Furthermore, the microscopic analysis of the AGE or DADS treated plants showed high variability in pathogen density within the root crown at 28 days post-inoculation. The low abundance of reactive oxygen species was noticed in AGE or DADS treated plants, which indicates that the plants were able to successfully encounter pathogen attacks. The AGE and DADS treated plants exhibited a lower disease severity index (32.4% and 24.8% vs 87.1% in controls), indicating successful defense against Verticillium infection. Our results were therefore among the first to address the biostimulatory effects of AGE or DADS to induce resistance in eggplant seedlings against V. dahliae and may be used to establish preparation for garlic-derived bioactive compounds to improve growth and defense responses of eggplants under-protected horticultural situations such as glasshouse or plastic tunnels system.

Wearable technology refers to the next generation of the digital revolution that connects items with embedded sensors to the Internet so as to enhance the quality of human life. Wearables have shifted the focus of the healthcare sector toward prevention programs that empower individuals to be active and liable for their own health. Although the number of smart wearable users has grown significantly, there is still a lack of academic researches on what motivates and prevents the continued usage of these devices. Hence, the main objectives of this study are, namely: to explain the impediments and affecting factors in deciding to use smart wellness wearables from a user’s perspective; and to propose a unified model to explore the impact of these factors on an individual’s behavioral intentions. Accordingly, the “Unified Theory of Acceptance and Use of Technology 2” and the “Value-based Adoption Model” were integrated with two additional factors, namely perceived trust and perceived health increase. Following this, a survey was conducted among students and 100 reliable responses were received. As a result of this study, the Confirmatory Factor Analysis from the developed instrument is presented. The findings have confirmed the validity and reliability of the developed instrument. This paper also presents the theoretical understanding of the involved factors in the proposed model.