Recognition Of Components Research Articles

A Novel Whole-Cell Biosensor for Bioavailable Antimonite in Water and Sediments.

Antimony (Sb) is an emerging contaminant, and its on-site speciation analysis is central to the accurate evaluation of its bioavailability and toxicity. The whole-cell biosensors (WCBs) for Sb(III) are promising but challenging due to the lack of Sb(III)-specific recognition components. Here, we constructed a novel Sb(III)-specific WCB using an Sb(III) transcriptional regulator (antR) and its cognate promoter (Pant). To prevent the promoter leakage of Pant, an additional regulatory gene, antR, was inserted downstream of the Sb(III)-inducible promoter, improving the sensitivity of the WCB by an order of magnitude and reaching the detection limit at 0.009 μM, which is lower than the WHO drinking water standard of Sb. Moreover, the WCB with double antR showed a high specificity toward Sb(III) compared with interfering ions at 3 orders of magnitude higher concentrations. This WCB was capable of measuring Sb(III) bioavailability in natural waters and sediments on-site, and its results were not statistically different from the chemical analysis. The insights gained from this work demonstrate that the addition of regulatory genes prevents promoter leakage and improves the sensitivity of WCBs in field applications. IMPORTANCE Antimony (Sb) is a redox-sensitive pollutant ubiquitous in the environment. Sb(III) is dominant in the subsurface and is readily oxidized to less toxic Sb(V) upon exposure to air, and therefore, on-site Sb speciation analysis is essential to evaluate its bioavailability and toxicity. Dissolved Sb concentration and speciation can be determined accurately using on-site chemical sensors, but chemical sensors have difficulty determining the bioavailable Sb(III) that is taken up by the cells. Here, we constructed an Sb(III)-specific whole-cell biosensor (WCB) using double Sb(III) transcriptional regulators (antR) downstream of its cognate promoter Pant. With an additional antR, the sensitivity of the WCB was improved by approximately 10 times, and the promoter leakage commonly found in WCBs was inhibited. Integrated with a tea-bag design, the WCB is able to measure Sb(III) bioavailability in natural water and sediments on-site. This study demonstrates the importance of inserting one more regulatory gene to improve sensitivity.

A decomposition-based hybrid ensemble CNN framework for driver fatigue recognition

Electroencephalogram (EEG) has become increasingly popular in driver fatigue monitoring systems. Several decomposition methods have been attempted to analyze the EEG signals that are complex, nonlinear and non-stationary and improve the EEG decoding performance in different applications. However, it remains challenging to extract more distinguishable features from different decomposed components for driver fatigue recognition. In this work, we propose a novel decomposition-based hybrid ensemble convolutional neural network (CNN) framework to enhance the capability of decoding EEG signals. Four decomposition methods are employed to disassemble the EEG signals into components of different complexity. Instead of handcraft features, the CNNs in this framework directly learn from the decomposed components. In addition, a component-specific batch normalization layer is employed to reduce subject variability. Moreover, we employ two ensemble modes to integrate the outputs of all CNNs, comprehensively exploiting the diverse information of the decomposed components. Against the challenging cross-subject driver fatigue recognition task, the models under the framework all showed better performance than the strong baselines. Specifically, the performance of different decomposition methods and ensemble modes was further compared. The results indicated that discrete wavelet transform-based ensemble CNN achieved the highest average classification accuracy of 83.48% among the compared methods. The proposed framework can be extended to any CNN architecture and be applied to any EEG-related tasks, opening the possibility of extracting more beneficial features from complex EEG data.

Developing a late fusion of multi facial components for facial recognition with a voting method and global weights

Developing a late fusion of multi facial components for facial recognition with a voting method and global weights

MOF/COF heterostructure hybrid composite-based molecularly imprinted photoelectrochemical sensing platform for determination of dibutyl phthalate: A further expansion for MOF/COF application

A novel metal-organic framework (MOF)/covalent-organic framework (COF) heterostructure hybrid composite (NH2-UiO-66/TpPa-1-COF) with excellent photoactivity was developed, which further acted as the photoelectrochemical sensitized layer of a molecularly imprinted photoelectrochemical (MIP-PEC) sensor for extremely sensitive and selective determination of dibutyl phthalate (DBP). The NH2-UiO-66/TpPa-1-COF was synthesized using a simple one-step solvothermal method, which showed improved photocurrent response owing to heterojunction formation, favorable energy-band configuration and strong light absorption capacity. To improve the sensing performance, molecularly imprinted polymer (MIP) was developed by sol-gel polymerization method as the recognition component of PEC sensor. The specific binding of imprinting sites towards DBP could block the electron transfer, causing decreased photocurrent response of the MIP-PEC sensor. The MIP-PEC sensor showed a wide detection range from 0.1 nmol L−1 to 100 μmol L−1 with a limit of detection of 3.0 × 10−11 mol L−1 under optimal conditions. Meanwhile, the proposed MIP-PEC sensor showed good stability, selectivity, reproducibility, and applicability in real samples. This is the first attempt to apply MOF/COF heterostructure hybrid composite for MIP-PEC sensor construction, providing new insight into the potential applications of microporous crystalline framework heterostructure hybrid composite in the sensing field.

Teknik Pengenalan Wajah Menggunakan Model Ekstraksi Fitur Citra Digital

The use of information technology has been widely encountered in our daily life. Not only to process data, to record tools but also to identify and recognize human characteristics. This is called biometric technology. This technology identifies the unique and permanent parts of the human body such as fingerprints, eyes, and the shape of the human face. To identify and recognize human faces, use facial image processing and analysis, such as determining the component regions of the human face and their characteristics. Splitting the face image into facial components, then extracting it into the features of the eyes, nose, mouth, and chin. The distance between each component is measured, then combined with other features to form facial semantics. The face can be categorized into the T Zone which consists of the forehead, eyes, nose and mouth. Eyes, nose, and mouth are the most unique facial components for facial recognition because they have unique facial recognition features. For the distance of the eye and mouth triangle feature, J1 – J3 shows that there are 140 unique data with the percentage value is 93.33%. The feature distance J4 – J6 also shows that there are 126 unique face images with a percentage value of 85%. Keyword: face image, eiginfaces, image extraction, face recognition.

Идея признания в работе В.В. Бибихина «Энергия»

The article deals with the concept of "energem", developed by A.F. Losev and developed by V.V. Bibikhin. Bibikhin, in the context of social recognition. Losev defined energeme as an essence in the modus of a certain comprehension, in the modus of a revealed, expressed essence. Bibikhin extends Losev's definition by characterizing energeme as a "quantum of activity. Based on the two understandings of energeme, the article proves the thesis that confession and energeme are similar in their structure, from which we can conclude that energeme is a special case of confession. The key common structural components of recognition and energeme are meaning, openness, dependence, grasping the essence and its reflection. Losev defined energema as "the subject meaning of the name," which in turn confirms the hypothesis expressed that energema is recognition, because to recognize means to give a name, i.e. to grasp the essence of a thing or person, to call it by its names. The energeme is the meaning (the essence of the thing), the recognition reflects the meaning, allows to reveal it, objectively existing, but not actualized until the recognition took place. Losev indicates such a property of energeme as manifestation, which coincides with the property of recognition – articulateness, which implies that during recognition the participant of the dialogue verbally expresses what he acknowledges the Other to be and substantiates what he acknowledges.

DDEL-08. NOVEL COMBINATION THERAPY USING PI3KINASE INHIBITION AND IMMUNE BASED THERAPY FOR THE TREATMENT OF GLIOBLASTOMA MULTIFORME

Abstract Hurdles to effective treatments for glioblastoma multiforme (GBM), the most aggressive form of brain cancer, are resistance to chemotherapy, radiation, and immune checkpoint inhibitors. GBMs, like other “difficult to treat” tumors, often over-utilize the phosphatidyl inositol 3 kinase (PI3K) pathway for survival, cell growth, and cell division, conferring both chemotherapy and radiation resistance. Furthermore, the PI3K pathway has been shown to modulate expression of Major Histocompatibility Complex (MHC) molecules, key components of immune recognition. Based on these observations, we examined the potential of a novel, small molecule PI3K inhibitor GCT.Glio.1 (NPT520-337), which was designed to cross the blood brain barrier, to increase the sensitivity of GBM to immune based therapies and radiation. We hypothesized that targeting PI3K would result in growth arrest and increase cell surface expression of MHC molecules and the PD-L1 checkpoint target. Treatment of GL261 mouse and human U251 GBM cell lines with GCT.Glio.1 caused growth arrest at the G2/M checkpoint, increased the cell surface expression of PD-L1 and MHC class II, and synergized with radiation to cause growth arrest and cell death. Based on these results we designed and performed in vivo animal studies, implanting luciferase-flagged GL261 into the caudate nucleus of C57BL6 mice. We treated the animals orally with GCT.Glio.1 followed 24 hours later by anti-PD1 therapy in repeating cycles. The treatments significantly delayed progression of the tumor when compared to no treatment or either treatment alone, with several animals exhibiting complete regression as measured by MRI and bioluminescence. In conclusion, these results indicate that GCT.Glio.1 may sensitize GBM to immune checkpoint inhibitor and/or radiation therapies. Based on our encouraging pre-clinical data and early results from pre-clinical pharmacology and safety studies, we anticipate filing a pre-Investigational New Drug application (pre-IND) as the next step toward our goal of a clinical trial using this combination therapy.

Structure-based drug design of potential inhibitors of FBXW8, the substrate recognition component of Cullin-RING ligase 7.

FBXW8 plays an irreplaceable role in the substrate recognition of ubiquitin-dependent proteolysis, which further regulates cell cycle progression and signal transduction. However, the abnormal expression of FBXW8 triggers malignancy, inflammation, and autophagy irregulation. FBXW8 is considered as an effective therapeutic target for Cullin-RING ligase 7 (CRL7)-related cancers. Still, the lack of selective inhibitors hinders further therapeutic development and limits the exploration of its biological mechanism. This study constructed an integrated protocol that combines pharmacophore modeling, structure-based virtual screening, and Molecular Dynamic Simulation. It was then used as a screening query to identify hit compounds targeted at the substrate recognition site of FBXW8 from a large-scale compound database including 120 million compounds. Then, ten lead compounds were retrieved by using molecular docking analysis and ADMET prediction. Finally, MD simulations were performed to validate the binding stability of selected drug candidates. The result indicated that three newly obtained compounds, namely ZINC96179876, ZINC72174069, and ZINC97730272, might be potent FBXW8 inhibitors against CRL7-related cancers such as endometrial cancer.

Recognizing Odysseus, reading Penelope: theanagnōrisisin the 23rd book of theOdyssey

AbstractThe article argues that Penelope recognizes Odysseus atOdyssey23.32–33, not, as is usually held, at 205–06. Recognition is here analysed as a multi-componential process, in which Penelope’s coming to know Odysseus’ identity must be distinguished from her letting on that she knows, and in which her recognition of the man before her as her long-lost husband does not automatically entail the immediate rekindling of all the old emotions. The narrative ofOdyssey23.1–230 is shown to be interested in tracing Penelope’s progression through the various components of recognition (knowledge, acknowledgement, emotional reconnection). The article explores the reasons why Penelope may consent to full reunion with Odysseus a good deal later than she has actually recognized him. Among these reasons, as well as the need for emotional attunement between Odysseus and Penelope, is Penelope’s need to ‘manage face’vis-à-visEurycleia, Telemachus and Odysseus. It is argued, further, that the narrative of theOdysseycharacteristically requires us to read the minds of its characters, above all Penelope in book 23. A mind-reading approach to the poem is justified in principle and grounded in a detailed reading ofOdyssey23.1–230. The wider interpretative implications for the poetics of the poem as whole are also explored.

Forgetting rate for the familiarity and recollection components of recognition in amnestic mild cognitive impairment: A longitudinal study

Here we aimed to investigate the rate of forgetting of the familiarity and recollection components of recognition in patients at the onset of medial temporal lobe (MTL) pathology and destined to convert to Alzheimer’s disease (AD). For this purpose, we conducted a longitudinal study of 13 patients who were diagnosed with amnestic mild cognitive impairment (a-MCI) at the first assessment and followed-up for 3 years. During this time, five patients converted to AD and eight remained in a stable condition of cognitive impairment. A group of 15 healthy subjects were enrolled as the control group (HC). In order to separately quantify the contribution of recollection and familiarity to recognition memory performance, the experimental sample was submitted to a modified version of Huppert and Piercy’s procedure that included a Remember/Know paradigm. Data demonstrated that both stable and converter a-MCI patients forgot memory traces relative to the familiarity components of recognition at the same rate as HC. Conversely, converter a-MCI patients showed accelerated long-term forgetting specifically for the recollection component of recognition compared to stable a-MCI and HC. This is the first empirical demonstration that familiarity and recollection components of declarative memory are subject to different rates of forgetting in a-MCI patients as a function of their longitudinal clinical outcome. Our finding of accelerated long-term forgetting of the recollection component of recognition disclosed by converter a-MCI patients suggests that atrophy in the MTL not only interferes with the storage aspects but also disrupts the consolidation of memory traces.

An insight into the multifarious applications of biosensors and the way forward

A biosensor is a self-reliant integrated device that is proficient in providing specific quantitative or semi-quantitative analytical information. It has been using a biological recognition component that is in direct spatial contact with a transduction component. It is an appliance that consists of two main parts: a bioreceptor and a transducer. Bioreceptor is a biological component that recognizes the objective of an analyte and a transducer. A physicochemical detector component has also been employed that converts the recognition incident into a measurable signal. All the biological materials including enzymes, antibodies, nucleic acids, hormones, receptors, organelles, or whole cells can be used as sensors or detectors in a device. Biosensors can provide low-priced and highly capable devices for being used in other day-to-day applications. It has multifarious potential applications of various types such as monitoring of treatment, disease progression, drug discovery, food control, and environmental monitoring as well as it continues to play a crucial role across numerous fields including biomedical diagnosis. In this review, we give a general introduction to biosensors and their applications, including a brief historical overview.
 Keywords: Biosensor, Bio-receptor, Transducer, Analyte, Detector.

Validating the decent work scale incorporated with a social recognition component among young adult social workers.

The decent work notion has sparkled a keen academic interest in studying the psychological influence of decent work on workers in organizational contexts. Duffy’s decent work notion has left a window for addressing the interpersonal barriers on or factors for enhancing people’s equal access to decent work, which may enhance the capacity of the decent work notion and the psychology of working theory to promote inclusiveness within the organizational context through leveraging the interpersonal mechanisms. Against this backdrop, a across-sectional study was conducted to validate a decent work scale incorporated with a social recognition component among young adult social workers aged 21–29 in Hong Kong (N = 362). The results of confirmatory factor analyses supported the six-factor-higher-order model of the decent work scale incorporated with a social recognition component. Decent work incorporated with social recognition correlated with job demands, job resources, and work engagement in the expected directions, and the results of average variance extracted analyses supported the discriminant validity of the decent work scale incorporated with social recognition. The value added by decent work in enhancing work engagement after controlling the effects of job resources justifies the concurrent validity of the concept. The expanded notion of decent work incorporated with the social recognition component is deemed applicable to informing further research and practice.

Deep Learning Model for Dynamic Hand Gesture Recognition for Natural Human-Machine Interface on End Devices

As end devices have become ubiquitous in daily life, the use of natural human-machine interfaces has become an important topic. Many researchers have proposed the frameworks to improve the performance of dynamic hand gesture recognition. Some CNN models are widely used to increase the accuracy of dynamic hand gesture recognition. However, most CNN models are not suitable for end devices. This is because image frames are captured continuously and result in lower hand gesture recognition accuracy. In addition, the trained models need to be efficiently deployed on end devices. To solve the problems, the study proposes a dynamic hand gesture recognition framework on end devices. The authors provide a method (i.e., ModelOps) to deploy the trained model on end devices, by building an edge computing architecture using Kubernetes. The research provides developers with a real-time gesture recognition component. The experimental results show that the framework is suitable on end devices.

Accelerated CRISPR/Cas12a-based small molecule detection using bivalent aptamer

CRISPR/Cas holds great promise for biosensing applications, however, restricted to nucleic acid targets. Here, we broaden the sensing target of CRISPR/Cas to small molecules via integrating a bivalent aptamer as a recognition component. Using adenosine 5′-triphosphate (ATP) as a model molecule, we found that a bivalent aptamer we selected could shorten the binding time between the aptamer and ATP from 30 min to 3 min, thus dramatically accelerating the detection of ATP. The accelerated bivalent aptamer binding to ATP was mainly ascribed to the extended conformation of the aptamer, which was stabilized through linking with a 5 T bases connector on specific loops of the monovalent aptamer. To facilitate on-site detection, we integrated lateral flow assay (LFA) with the CRISPR/Cas sensing strategy (termed BA-CASLFA) to serve as a visual readout of the presence of ATP. In addition, in the CASLFA platform, due to the unique characteristics of LFA, the thermal step of Cas12a inactivation can be omitted. The BA-CASLFA could output a colorimetric “TURN ON” signal for ATP within 26 min, which could be easily discriminated by the naked eye and sensitively quantified by the portable reader. Furthermore, we showed the versatility of BA-CASLFA for detecting kanamycin using a kanamycin bivalent aptamer obtained through the same design as the ATP bivalent aptamer. Therefore, this strategy is amenable to serve as a general sensing strategy for small molecular targets. The above work opened a new way in developing CRISPR-based on-site sensors for clinic diagnosis, food safety, and environmental analysis.

Real-time kinetics and affinity analysis of the interaction between protein A and immunoglobulins G derived from different species on silica colloidal crystal films

Kinetic and affinity analysis of protein interactions reveals information on their related activities in biological processes. Herein, we established a system for evaluating the kinetics and affinity of the interaction between protein A and various IgG species on the surface of silica spheres of silica colloidal crystal (SCC) films by the extraordinary optical interference capabilities of 190 nm silica spheres after self-assembly. The equilibrium association constant (KA) was calculated by the equilibrium Langmuir model and nonlinear least-squares analysis of time-dependent data. The relative protein A/IgG binding affinity is human > rabbit >cow >goat. In addition, the competitive interaction of distinct species of IgG with protein A at the interface of SCC films was studied and performed. These findings may help with the use of protein A and other recognition components in a number of sensor types. Furthermore, this research might offer a novel approach to determining the kinetics and affinity of proteins on the surface of spheres particles, which may contribute to the development of the application of spheres particles in pharmaceutical science, biomedical engineering, and other techniques.

Nursing students' decision-making regarding postpartum hemorrhage: An exploration using the recognition-primed decision model

AimTo explore the knowledge content and structure of nursing students' decision-making in a high-stake clinical situation of postpartum hemorrhage using the Recognition-Primed Decision Model. BackgroundAccording to research on clinical judgment, a nurse’s expectations for a patient situation are central to the clinical decision-making process. However, little research has addressed the expectation concept and its relationship with the nurse’s knowledge. Grounded in the naturalistic decision-making paradigm, the Recognition-Primed Decision Model provides a potential framework to describe the content and structure of nurses’ knowledge and expectations as they unfold in high-stake clinical situations, such as postpartum hemorrhage. As it is typically used in studies of expert decision-making, it is crucial to test the adequacy of the Model with a student population and refine the research methods for using this framework. DesignDescriptive design where qualitative data were analyzed using qualitative and quantitative methods. MethodsA convenience sample of 53 students enrolled in a maternal and child health course in the Fall of 2021 was formed. As part of an online exercise to prepare for a simulation, they read a vignette presenting the story of a woman experiencing postpartum hemorrhage and recorded their answers to questions designed to probe their decision-making. Recordings were transcribed and subjected to content analysis based on the four components of recognition according to the Recognition-Primed Decision Model (i.e., cues, expectations, goals and actions). FindingsAll participants recognized the postpartum hemorrhage. Their knowledge was organized into clusters representing the potential causes (i.e., tone, trauma, tissue and thrombin) and consequences (i.e., hemodynamic instability) of postpartum hemorrhage, as well as other potential issues (e.g., pain and comfort, baby and partner, infection). Although students could identify relevant cues and actions, they had difficulties articulating their longer-term goals and expectations for the mother and care outcomes. ConclusionsThis study showed the potential of the Recognition-Primed Decision Model to organize the content and structure of the knowledge that supported nursing students' decision-making in a high-stake situation. The findings suggest that their knowledge disproportionately focuses on the cause-and-effect relations between cues and actions. They invite further consideration of longer-term goals and expectations in nursing education to prepare students to anticipate events and assess patient responses appropriately.

An Implementation of Voice Assistant for Hospitality

Voice user interface has gained popularity in the recent years. A chatbot is a machine with the ability to answer automatically through a conversational interface. Instead of using mouse and keyboards as input and screen as output, a chatbot with extra voice user interface feature improve the system and enhance the user experience. A chatbot is considered as one of the most exceptional and promising expressions of human computer interaction. Voice-based chatbots or artificial intelligence (AI) devices transform humancomputer bidirectional interactions that allow users to navigate an interactive voice response (IVR) system with their voice generally using natural language. In this paper, we focus on voice based chatbots for mediating interactions between hotels and guests from both the hospitality technology providers’ and guests’ perspectives. A hotel web application with voice user interface was implemented which provides voice input/output interface to enhance the user experience. Speech recognition component was used to dictate the user voice input to text. Speech synthesis API was used for text to voice conversion. A closed domain question answering (cdQA) Natural Language Processing (NLP) solution was used for processingof query and return the best answer possible.

Sensitive fluorescent aptasensing of tobramycin on graphene oxide coupling strand displacement amplification and hybridization chain reaction

An ultrasensitive biosensor was designed and constructed for tobramycin detection. As a target recognition component, the DNA probe consists of an aptamer region for tobramycin binding and a template for amplification. In the absence of tobramycin, the probe was locked to form a stem–loop structure. In the presence of the target, the binding of tobramycin led to a conformational change in the probe. The released 3′ end was used as a primer for the strand displacement amplification (SDA) to produce a large amount of single-stranded trigger DNA, which then efficiently initiated the following hybridization chain reaction (HCR) to produce a long duplex DNA with many fluorophores. The signals were detected after the addition of graphene oxide (GO) to quench the fluorescence from excess hairpin DNA. Through sequence and reaction condition optimization, the biosensor exhibited high selectivity for tobramycin. The linearity range and limit of detection (LOD) were 0.5–30 nM and 0.06 nM, respectively. Moreover, the application of detecting tobramycin in milk and lake water samples showed that this method is reliable and could be further used in food safety control and environmental monitoring.

Acoustic Modelling from Raw Source and Filter Components for Dysarthric Speech Recognition

Acoustic Modelling from Raw Source and Filter Components for Dysarthric Speech Recognition

Effectiveness of educational package based on lateral dominance in visual recognition, visual memory and visual completion of 7-12-year-old children with learning disorders

Introduction: Weakness in visual perception is one of the cases noticed in children with learning disorders, and strengthening this weakness improves their academic performance. Aim: The present study was conducted to determine the effectiveness of the educational package based on lateral dominance in visual recognition, visual memory and visual completion of 7-12-year-old children with learning disorders. Method: The research method was quasi-experimental with a pretest-posttest design and a control group. A total of 30 children (18 female and 12 male subjects) from elementary school children diagnosed with learning disorders in the psychological clinics of Tehran, Iran, in 2020 were conveniently and voluntarily selected and then randomly assigned to two experimental (n=15) and control (n=15) groups. The Edinburg Handedness Inventory (1970), Delacato’s Neurodevelopmental Table (1997) and Gardner’s Visual Perception Test (1982) were used to collect the data. The SPSS-25, descriptive-inferential indices, univariate analysis of covariance and multivariate analysis of covariance were used to analyze the data. Results: The results showed that the educational package based on lateral dominance affected the visual recognition (P<0.01, F=31.38) and visual memory (P<0.1, F=14.68) components of children with learning disorders in the experimental group and did not affect the visual completion component. Conclusion: Lateral dominance exercises help students perform better in visual perception. Therefore, it is suggested to include lateral dominance exercises in the treatment program for children with learning disorders to improve their visual perception.