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The conventional clustering methods assume a binary classification and establish a complete inclusive or exclusive type relation of an object with a cluster. In contrast, a three-way paradigm handles situations where an object may or may not belong to a cluster, i.e., uncertain. The objects belonging to the uncertainty region may lead to inclusion or exclusion after further processing and information. One of the use cases of the three-way paradigm is the overlapping region between different clusters. Effective computation of overlapping objects is crucial to the application’s overall success. In this paper, we employ a three-way clustering approach inspired by image blurring and sharpening operations that consider the objects in the inside or outside regions of a cluster to be non-overlapping. The objects belonging to the partial region of more than one cluster are considered overlapping. The experiment conducted on Birds, Scenes, and 20 newsgroups datasets indicates that the proposed approach improves the F1 measure and hamming loss up to 18.6% and 4.9%, respectively. Furthermore, the system’s robustness for overlapping regions is observed using typical clustering measures. The experimental results suggested that the proposed approach may improve the computation of overlapping regions effectively.

The explainable human–computer interaction (HCI) is about designing approaches capable of using cognitive characteristics like humans. One such characteristic is human vision and its accuracy. The accuracy measures the trust in that system. Therefore, improving accuracy in the authorization with identification process is a primary concern for a visual-based explainable human–computer interaction system. In this article, we propose a three-way decision based ensembled face recognition mechanism called E3FRM. The E3FRM uses a three-way approach to determine the match cases and the respective worth of the captured image with the match cases. Features are extracted using PCA/FLD, and the ensembled face recognition algorithms utilize the extracted features to process the image. Ensemble Face recognition approaches find the match cases based on a given threshold. Finally, the three-way decision model evaluates the suitability of the captured image for acceptance, rejection, or deferred cases with a dual verification mechanism. Experimental results on well-known eighteen datasets suggest improvements in commonly used metrics of F1, Accuracy and Recall by up to 0.8% to 12.8%, 1% to 9.6% and 1.2% to 13.9%, respectively, in comparison to the state-of-the-art methods available, including SPCA +, ML-EM, FLDA-SVD, DMMA, Fast-DMMA, LU, LPP, TDL, KCFT, RBF + DT, and NMF. Furthermore, the proposed approach is comparatively analyzed with ensembled face recognition methods that result in an outperformed F1, Accuracy and Recall by up to 1.1% to 10.3%, 0.1% to 7.3% and 0.9% to 10.5%, respectively. These results suggest that the proposed model may improve face recognition accuracy and the resulting trust in the machines.

OBJECTIVES Most obstructive airway disease medications are used via inhalers, and their proper use is significant for effectively treating these diseases. Most patients misuse it. However, some studies showed that many physicians also do not know the proper meter dose inhaler with the spacer technique. This study aimed to assess metered-dose inhalers with spacer technique among postgraduate trainee doctors. METHODOLOGY This cross-sectional study was carried out in the Khyber Teaching Hospital Peshawar. The total time was six months, from Dec 6 2020, to Jun 5 2021. Postgraduate trainee (PGT) doctors of either gender with an age range of 25 to 35 years were included in the study from different departments. Those with every use of inhalers were excluded from the study. Demographic details of PGTs, like age and gender, were recorded. RESULTS Among 96 patients, males were 85 (88.54%), and females were 11 (11.46%). The mean age was 30.02±1.84 years, and the mean training experience was 2.0521 ±0.89. Inhaler technique was Proper in 20 (20.83%), Improper in 51 (53.13%) and Poor in 25 (26.04%) doctors. Those with more training periods, pulmonology rotation, attended workshops on inhaler techniques and with relatives using inhalers were more acknowledged of proper meter dose inhalers (MDIs) with spacer technique. CONCLUSION Only one-fifth of the postgraduate trainees know proper MDIs techniques. The attendance of workshops and pulmonology rotation is encouraged to enhance the knowledge of physicians regarding MDIs techniques.

Plants, being sessile, have developed complex signaling and response mechanisms to cope with biotic and abiotic stressors. Recent investigations have revealed the significant contribution of phytohormones in enabling plants to endure unfavorable conditions. Among these phytohormones, jasmonic acid (JA) and its derivatives, collectively referred to as jasmonates (JAs), are of particular importance and are involved in diverse signal transduction pathways to regulate various physiological and molecular processes in plants, thus protecting plants from the lethal impacts of abiotic and biotic stressors. Jasmonic acid has emerged as a central player in plant defense against biotic stress and in alleviating multiple abiotic stressors in plants, such as drought, salinity, vernalization, and heavy metal exposure. Furthermore, as a growth regulator, JA operates in conjunction with other phytohormones through a complex signaling cascade to balance plant growth and development against stresses. Although studies have reported the intricate nature of JA as a biomolecular entity for the mitigation of abiotic stressors, their underlying mechanism and biosynthetic pathways remain poorly understood. Therefore, this review offers an overview of recent progress made in understanding the biosynthesis of JA, elucidates the complexities of its signal transduction pathways, and emphasizes its pivotal role in mitigating abiotic and biotic stressors. Moreover, we also discuss current issues and future research directions for JAs in plant stress responses.

In this work, an energy-saving smart light controlling system has been proposed that can maintain the desired intensity of light in a room automatically. Unlike the conventional light controlling system, the proposed system splits a large room into several zones and analyzes the light intensity of each zone; hence, the controlling unit adjusts the light intensity to the desired level. The main controlling unit consists of a light sensor, a motion sensor, a relay with a driver unit, an LCD display, etc. for controlling light efficiently to reduce the power waste. The sensors measure the intensity of light, based on the standard light intensity data chart the controller units make a decision how many light bulbs are needed to be switched ON/OFF in a particular zone. Moreover, the system automatically switched-OFF all light bulbs when there is nobody in the room. Proteus design suite 8.0 is used to design and simulation of the proposed system. Moreover, the PCB layout is designed using ExpressPCB version 7.5.0. The proposed system is capable of minimizing the power loss by up to 44% in comparison to the conventional light management system.

Non-invasive genotyping methods provide valuable information on insect populations. However, poor DNA amplification and time-consuming sampling procedures limit these methods, especially for small insects. An efficient and convenient method was developed for non-invasive, non-lethal genotyping of a large insect, Mythimna separata, and a small insect, Drosophila melanogaster, by amplification of endogenous and exogenous, nuclear and mitochondrial genes from insect frass, exuviae, and food waste. For M. separata, the chitin synthesis gene MsCHSB and the COI gene were successfully detected by PCR from exuviae DNA. However, a COI fragment could not be detected directly by PCR from frass, probably due to DNA degradation. To improve the detection rate, DNA from frass was first amplified by Multiple Displacement Amplification with phi29 DNA polymerase, after which the COI fragment was detected from all samples by PCR. For D. melanogaster, second instar larvae were reared individually for three days and then DNA was extracted from food waste of each individual. The endogenous fragment serendipity α (sryα), exogenous transgene ΦC31 integrase, and the kl-5 gene, a Y-chromosome-located male-specific marker gene were successfully detected from most samples. We developed a simple, non-invasive, non-lethal method to determine gender and identify transgenic individuals early in the larval stage. This universal method is applicable to most insects and has potential application in genetic and ecological studies of insects and other arthropods.

The increased usage and misuse of antibiotics cause antimicrobial resistance, which makes it necessary to develop new antibiotic agents. Antimicrobial peptides (AMPs) could be a significant solution to addressing this issue. Antimicrobial temporin 1Ta and temporin 1Tb peptides, derived from frog skin secretions, exhibit notable activity against Gram (+) bacteria; on the other hand, apidaecin 1b peptide, obtained from honeybees, is effective against Gram (−) bacteria. In this study, hybrid AMPs were synthesized by merging temporin 1Ta and temporin 1Tb with apidaecin 1b to produce peptides that are active against a broad spectrum of microorganisms. Furthermore, the hybrid peptides were mixed with polyvinyl alcohol (PVA) polymer to produce bioactive nanofibers by electrospinning. The synthesized peptides and the nanofibers were tested on various Gram (+) and Gram (−) bacteria (E. coli ATCC 25922, P. aeruginosa ATCC 27853, S. aureus ATCC 29213, and E. faecalis ATCC 29212). As a result, the hybrid peptides were found to have a reasonable antibacterial effect on both bacterial groups. In addition, peptide‐containing nanofibers preserved the antibacterial activity as well. The hemolytic activities of the peptides were also examined, and it was found that the hybrid peptides were not lethal to red blood cells at a concentration of 16 μM. [ABSTRACT FROM AUTHOR]