Correct Mode Research Articles

Full wavefield modeling and dispersion characteristics of underwater MASW

The underwater multichannel analysis of surface wave (UMASW) is becoming an essential tool for surveying subbottom shear wave velocity. Current practice is limited to interpretation based on the fundamental mode. This paper investigates the full dynamic response of the underwater-multilayered structure under two different types of sources (impact and explosion). Fundamental solutions in the transformed domain, after applying both Fourier transform and Fourier–Bessel transform, are derived utilizing the global stiffness matrix method, analogous to a 1-D finite element approach. Solutions in the physical domain are then obtained using the fast and accurate Fourier series and Fourier–Bessel series approach proposed in this paper. The most attractive feature of this novel approach is that the expansion coefficients (or Love numbers) can be pre-calculated, saved, and repeatedly used for other field points. Through numerical analyses, we quantitatively investigate the effect of the water depth and source/receiver types/locations on different wave features (i.e., Scholte, fast-guided, and acoustic modes) from different perspectives (i.e., dispersion curve, Green’s function, frequency-velocity spectrum (FVS), and waveform). We find that (1) unlike the impact source, stronger acoustic waves can be produced by the explosive source, which sometimes causes difficulty in identifying the Scholte waves. (2) The acoustic and interface-guided waves exhibit distinct behaviors depending on the source and receiver locations. Scholte waves and fast-guided waves are weakened when the source and receivers are elevated far from the water/soil interface. Moreover, (3) the response of the Scholte wave can be enhanced by muting the direct acoustic waves. However, (4) the fast-guided wave may also arise in underwater surveys when the Vs of the underlying half-space is much higher than those of the upper layers, exerting a significant influence on the shallow water scenarios and posing challenges for correct mode identification. With the ability to model the entire wavefield (or FVS) that takes into account all propagation modes and the actual survey configuration, inversion can be performed by fitting the entire FVS. This approach eliminates the need to pick dispersion curves and provides a more accurate and stronger model constraint.

Fan noise radial mode detection based on [formula omitted] regularization method

Radial mode detection has been widely employed in fan noise research. Many radial mode detection algorithms by conducting the convex L1 norm optimization have been proposed by taking advantage of the fact that the fan noise sound field is usually dominated by a limited set of radial modes. Nevertheless, L1 norm optimization has been shown to be suboptimal and cannot enforce further sparsity. A fan noise radial mode detection method based on L1/2 regularization algorithm is proposed in this paper to improve its robustness and dynamic range. This method employs the L1/2 regularization to directly solve the in-duct sound propagation model. Synthesized simulations indicates that the L1/2 regularization method can detect the correct radial mode order and amplitude under low signal-to-noise ratio. Moreover, the new method is insensitive to regularization parameter. An experimental system of radial rake is implemented to validate the new method. It is shown that the L-curve method, which do not require any prior information of the acoustic mode distribution or contaminating measurement noise, is an appropriate choice of the regularization parameter determination method for the L1/2 regularizer. It is demonstrated that the new L1/2 regularization method can enhance the mode sparsity, especially under low signal-to-noise ratio. Moreover, the resolution and dynamic range can be improved by the L1/2 regularization method, which makes it an effective and robust fan noise radial mode detection technique in practical applications.

On the Consistency of Stochastic Noise Properties and Velocity Estimations from Different Analysis Strategies and Centers with Environmental Loading and CME Corrections

The analysis of the Global NFavigation Satellite System (GNSS) time series provides valuable information for geodesy and geodynamics researcFh. Precise data analysis strategies are crucial for accurately obtaining the linear velocity of GNSS stations, enabling high-precision applications of GNSS time series. This study investigates the impact of different stochastic noise models on velocity estimations derived from GNSS time series, specifically under conditions of environmental loading correction and common mode error (CME) removal. By comparing data from various data centers, we find that post-correction, different analysis strategies exhibit high consistency in their noise characteristics and velocity estimation results. Across various analysis strategies, the optimal noise models were predominantly Power Law with White Noise (PLWN) and Fractional Noise with White Noise (FNWN), with the optimal noise models including COMB/JPL, COMB/SOPAC, and COMB/NGL for approximately 50% of the datasets. Most of the stations (approximately 80%) showed velocity differences below 0.3 mm/year and velocity estimation uncertainties below 0.1 mm/year. Nonetheless, variations in amplitudes and periodic signals persisted due to differences in the processing of raw GNSS observations. For instance, the NGL and JPL datasets, which were processed using GipsyX 2.1 software, showed higher amplitudes of the 5.5-day periodic signal. These findings provide a solid empirical foundation for advancing data analysis methods and enhancing the reliability of GNSS time series results in future research.

Coupling Low-Frequency Ultrasound to a Crossflow Microfiltration Pilot: Effect of Ultrasonic Pulse Application on Sono-Microfiltration of Jackfruit Juice.

To reduce membrane fouling during the processing of highly pulpy fruit juices into clarified beverages, a crossflow Sono-Microfiltration (SMF) system was employed, strategically equipped with an ultrasonic probe for the direct application of low-frequency ultrasound (LFUS) to the juice just before the entrance to the ceramic membrane. Operating conditions were standardized, and the application of LFUS pulses in both corrective and preventive modes was investigated. The effect of SMF on the physicochemical properties and the total soluble phenol (TSP) content of the clarified juice was also evaluated. The distance of ultrasonic energy irradiation guided the selection of the LFUS probe. Amplitude conditions and ultrasonic pulses were more effective in the preventive mode and did not cause membrane damage, reducing the operation time of jackfruit juice by up to 50% and increasing permeability by up to 81%. The SMF did not alter the physicochemical parameters of the clarified juice, and the measured LFUS energy ranges did not affect the TSP concentration during the process. This study is the first to apply LFUS directly to the feed stream in a pilot-scale crossflow microfiltration system to reduce the fouling of ceramic membranes and maintain bioactive compounds in jackfruit juice.

Identification of the mode of evolution in incomplete carbonate successions

BackgroundThe fossil record provides the unique opportunity to observe evolution over millions of years, but is known to be incomplete. While incompleteness varies spatially and is hard to estimate for empirical sections, computer simulations of geological processes can be used to examine the effects of the incompleteness in silico.We combine simulations of different modes of evolution (stasis, (un)biased random walks) with deposition of carbonate platforms strata to examine how well the mode of evolution can be recovered from fossil time series, and how test results vary between different positions in the carbonate platform and multiple stratigraphic architectures generated by different sea level curves.ResultsStratigraphic architecture and position along an onshore-offshore gradient has only a small influence on the mode of evolution recovered by statistical tests. For simulations of random walks, support for the correct mode decreases with time series length.Visual examination of trait evolution in lineages shows that rather than stratigraphic incompleteness, maximum hiatus duration determines how much fossil time series differ from the original evolutionary process. Gradual directional evolution is more susceptible to stratigraphic effects, turning it into punctuated evolution. In contrast, stasis remains unaffected.Conclusions• Fossil time series favor the recognition of both stasis and complex, punctuated modes of evolution.• Not stratigraphic incompleteness, but the presence of rare, prolonged gaps has the largest effect on trait evolution. This suggests that incomplete sections with regular hiatus frequency and durations can potentially preserve evolutionary history without major biases. Understanding external controls on stratigraphic architectures such as sea level fluctuations is crucial for distinguishing between stratigraphic effects and genuine evolutionary process.

Exploring the Affordance Effect of Visual Properties Associated with Virtual Keyboard Buttons on Smartphones

Digital affordances exist on the touchscreen, but the affordance of virtual buttons on smartphones is unknown. Therefore, this study investigated the on-screen affordances by examining whether the visual properties of virtual keyboard buttons could afford possible clicking actions and affect the entry performance. This study employed a three-way within-subject design: 2 (Symbol Position: standard mode vs. corrective mode) × 2 (Button Border: bordered button vs. borderless button) × 26 (Button Position: 26 positions). In the serial tapping task, 30 university students tapped virtual keyboard buttons with four button types. The results confirmed that the symbol-position and button-border variables influenced clicking actions. When employing offset-correcting symbols, the entry accuracy of virtual keyboard buttons increased without the speed-accuracy tradeoff. Additionally, button borders improved the perceived usability of virtual keyboard buttons despite failing to enhance the entry accuracy and speed. However, the button position moderated the effects of the symbol-position and button-border variables.

Can Chat-GPT read and understand guidelines? An example using the S2k guideline intrauterine growth restriction of the German Society for Gynecology and Obstetrics

PurposeTo investigate the capacity of chat-generative pre-trained transformer (Chat-GPT) to understand the S2k guideline of the German Society for Gynecology and Obstetrics on intrauterine growth restriction.MethodsThe German-language free Chat-GPT version was used to test the ability of Chat-GPT to understand the definition of small for gestational age and intrauterine growth restriction, to indicate the correct time and place of delivery and to evaluate ist ability to recommend a spontaneous delivery versus a primary caesarean section in accordance with the guideline recommendations. In order to objectively evaluate the suggestions a simple three-color ‘traffic light’ evaluation system was employed.ResultsAlmost all Chat-GPT’s suggestions in the context of definition of small for gestational age/intrauterine growth restriction as well as correct time of delivery were adequate, whereas more than half of the suggestions made in terms of correct delivery mode needed reformulation or even correction.ConclusionChat-GPT appears to be a valuable form of artificial intelligence that could be integrated into everyday clinical practice.

Cross-sectional Study on the Awareness of Hiv among University of Cyberjaya Students

Background: Malaysia is currently confronting a significant Human Immunodeficiency Virus (HIV) epidemic, particularly among men who have sex with men (MSM) and the transgender community despite ongoing efforts to raise awareness about HIV. Objective: This study aims to assess knowledge and awareness level about HIV among University of Cyberjaya (UOC) students. Methods: A cross-sectional study done among students of University of Cyberjaya who fulfill the inclusion and exclusion requirement. Data collected via online questionnaires distributed to various faculty and were analyzed by using JASP. This study used a mean scoring system to check the awareness level and Pearsons’s correlation to find the relationship between their awareness level and socio-demographic status. Results: In this study, out of 200 respondent, majority of the participants were Female (64.0%), aged between 20-29 years old (88.0%), Malay (46.0%), Single (96.0%), MBBS students (79.5%) from Faculty of Medicine (79.5%), currently in their 4th year of studies (39.0%). Conclusion: Overall, our findings show most of the participants have a high level of awareness and knowledge on HIV as more than 90% of them are able to identify the correct mode of transmission for HIV. However, there was no significant correlation between their level of awareness and socio-demographic status. In this study, participants show a lack of knowledge on PrEP as 56.5% of them have heard of PrEP. Although the number reached more than half percent, they had never discussed PrEP with family, friends or healthcare workers.

Minute ventilation sensor-driven rate response as a part of cardiac resynchronization therapy optimization in older patients.

Chronotropic incompetence (CI) is common among elderly cardiac resynchronization therapy pacemaker (CRT-P) patients on optimal medical therapy. This study aimed to evaluate the impact of optimized rate-adaptive pacing utilizing the minute ventilation (MV) sensor on exercise tolerance. In a prospective, multicenter study, older patients (median age 76years) with a guideline-based indication for CRT were evaluated following CRT-P implantation. If there was no documented CI, requiring clinically rate-responsive pacing, the device was programmed DDD at pre-discharge. At 1month, a 6-min walk test (6MWT) was conducted. If the maximum heart rate was < 100bpm or < 80% of the age-predicted maximum, the response was considered CI. Patients with CI were programmed with DDDR. At 3months post-implant, the 6MWT was repeated in the correct respective programming mode. In addition, heart rate score (HRSc, defined as the percentage of all sensed and paced atrial events in the single tallest 10bpm histogram bin) was assessed at 1 and 3months. CI was identified in 46/61 (75%) of patients without prior indication at enrollment. MV sensor-based DDDR mode increased heart rate in CI patients similarly to non-CI patients with intrinsically driven heart rates during 6MWT. Walking distance increased substantially with DDDR (349 ± 132m vs. 376 ± 128m at 1 and 3months, respectively, p < 0.05). Furthermore, DDDR reduced HRSc by 14% (absolute reduction, p < 0.001) in those with more severe CI, i.e., HRSc ≥ 70%. Exercise tolerance in older CRT-P patients can be further improved by the utilization of an MV sensor.

Entertainment robots based on digital new media application in real-time error correction mode for Chinese English translation

With the assistance of digital new media technology, virtual entertainment robots, as a new learning experience mode, can effectively enhance the interactive process of e-learning learning. This article studies the application of entertainment robots based on digital new media in real-time error correction mode for Chinese English translation. Through experiments, it has been verified that the flexible use of deep learning technology can significantly improve user satisfaction and translation accuracy, and has already improved the level of error correction and positioning. This article first introduces the existing mainstream machine learning models, including supervised neural network models and attention mechanisms. On this basis, the system was optimized to further improve its performance. At the same time, this article proposes new improvement plans to address the shortcomings of current mainstream translation systems. We conducted comparative experiments on the error correction model of the proposed adaptive algorithm for specific error types, and also tested it using real datasets. Research has shown that using adaptive algorithms based on reinforcement deep learning can not only significantly optimize the error correction efficiency of our system, but also flexibly adapt to the needs of various optimization strategies.

Traditional Herbal Remedies among the Bhilalas of West Nimar District, M.P, India

Traditional herbal remedies common among the Bhilalas of West Nimar district of Madhya Pradesh are reported. In all 29 species belonging to 28 genera and 21 families are recorded. Their correct scientific names, local names, parts used and mode of administration are mentioned for each plant.

The sociological assessment of psycho-emotional status after mastectomy as one of main indicators of life quality of women with breast cancer: ways of correction

The psycho-emotional status of women after radical surgery for breast cancer was assessed. The international questionnaire FACT-G and module FACT-B module were applied to investigate life quality of 186 women under dispensary monitoring concerning breast cancer of stage I-II. The respondents were aged 30-40, 41-50, 51-60, 61-70 and 71 years and older. In women who underwent radical surgery for breast cancer, psycho-emotional status is manifested most vividly as compared with other perceptions in the postoperative period and decreases quality of life. The overwhelming majority of women with breast removal experiences feeling of inferiority and depression, despair, fear of health deterioration and death that increase with age. The percentage of women satisfied with their coping with illness is 64.8% among 30-41 years old, 45.8% among 51-60 years old and 4.2% among 70 years and older. The impact of stress on disease is most felt in women of 51-60 years old (63,6%) and 61-70 years old (58,8%). No reliable differences in level of emotional condition of urban and rural respondents was established. The attitude of women to methods of postoperative correction through formation of breast lost depends on their age, place of residence, level of education. More than 60% of respondents under age of 50 years consider solution of aesthetic problem in endoprosthesis replacement with implants. Among respondents aged 51-60 years, 25.0% preferred simultaneous mastectomy and breast reconstruction and 10.1% - breast plastic surgery. The endoprosthesis replacement is more often resorted by women older 60 years and rural residents. The choice of mode of breast correction often depends on financial possibilities of patients. The study of quality of life of women with post-mastectomy syndrome is valuable component of integrated approach to dispensary monitoring that individualizes rehabilitation measures. The effectiveness of psychological rehabilitation of women requires involvement of clinical psychologists and medical social services.

An Insight into Knowledge, Perspective, and Practices of Indian Optometrists towards Childhood Myopia.

The current understanding of clinical approaches and barriers in managing childhood myopia among Indian optometrists is limited. This research underscores the necessity and relevance of evidence-based practice guidelines by exploring their knowledge, attitude, and practice towards childhood myopia. A self-administered internet-based 26-item survey was circulated online among practicing optometrists in India. The questions assessed the demographics, knowledge, self-reported clinical practice behavior, barriers, source of information guiding their management, and extent of adult caregiver engagement for childhood myopia. Of 393 responses, a significant proportion of respondents (32.6-92.4%) were unaware of the ocular complications associated with high myopia, with less than half (46.5%) routinely performing ocular biometry in clinical practice. Despite the growing awareness of emerging myopia management options, the uptake remains generally poor, with single-vision distance full-correction spectacles (70.3%) being the most common mode of vision correction. Barriers to adopting optimal myopia care are medicolegal concerns, absence of clinical practice guidelines, and inadequate consultation time. Own clinical experience and original research articles were the primary sources of information supporting clinical practice. Most (>70%) respondents considered involving the adult caregiver in their child's clinical decision-making process. While practitioners' awareness and activity of newer myopia management strategies are improving, there is plenty of scope for its enhancement. The importance of evidence-based practice guidelines and continuing education on myopia control might help practitioners enhance their clinical decision-making skills.

Swing-phase detection of locomotive mode transitions for smooth multi-functional robotic lower-limb prosthesis control.

Robotic lower-limb prostheses, with their actively powered joints, may significantly improve amputee users' mobility and enable them to obtain healthy-like gait in various modes of locomotion in daily life. However, timely recognition of the amputee users' locomotive mode and mode transition still remains a major challenge in robotic lower-limb prosthesis control. In the paper, the authors present a new multi-dimensional dynamic time warping (mDTW)-based intent recognizer to provide high-accuracy recognition of the locomotion mode/mode transition sufficiently early in the swing phase, such that the prosthesis' joint-level motion controller can operate in the correct locomotive mode and assist the user to complete the desired (and often power-demanding) motion in the stance phase. To support the intent recognizer development, the authors conducted a multi-modal gait data collection study to obtain the related sensor signal data in various modes of locomotion. The collected data were then segmented into individual cycles, generating the templates used in the mDTW classifier. Considering the large number of sensor signals available, we conducted feature selection to identify the most useful sensor signals as the input to the mDTW classifier. We also augmented the standard mDTW algorithm with a voting mechanism to make full use of the data generated from the multiple subjects. To validate the proposed intent recognizer, we characterized its performance using the data cumulated at different percentages of progression into the gait cycle (starting from the beginning of the swing phase). It was shown that the mDTW classifier was able to recognize three locomotive mode/mode transitions (walking, walking to stair climbing, and walking to stair descending) with 99.08% accuracy at 30% progression into the gait cycle, well before the stance phase starts. With its high performance, low computational load, and easy personalization (through individual template generation), the proposed mDTW intent recognizer may become a highly useful building block of a prosthesis control system to facilitate the robotic prostheses' real-world use among lower-limb amputees.

Diagnosis and prognosis of abnormal cardiac scintigraphy uptake suggestive of cardiac amyloidosis using artificial intelligence: a retrospective, international, multicentre, cross-tracer development and validation study

The diagnosis of cardiac amyloidosis can be established non-invasively by scintigraphy using bone-avid tracers, but visual assessment is subjective and can lead to misdiagnosis. We aimed to develop and validate an artificial intelligence (AI) system for standardised and reliable screening of cardiac amyloidosis-suggestive uptake and assess its prognostic value, using a multinational database of 99mTc-scintigraphy data across multiple tracers and scanners. In this retrospective, international, multicentre, cross-tracer development and validation study, 16 241 patients with 19 401 scans were included from nine centres: one hospital in Austria (consecutive recruitment Jan 4, 2010, to Aug 19, 2020), five hospital sites in London, UK (consecutive recruitment Oct 1, 2014, to Sept 29, 2022), two centres in China (selected scans from Jan 1, 2021, to Oct 31, 2022), and one centre in Italy (selected scans from Jan 1, 2011, to May 23, 2023). The dataset included all patients referred to whole-body 99mTc-scintigraphy with an anterior view and all 99mTc-labelled tracers currently used to identify cardiac amyloidosis-suggestive uptake. Exclusion criteria were image acquisition at less than 2 h (99mTc-3,3-diphosphono-1,2-propanodicarboxylic acid, 99mTc-hydroxymethylene diphosphonate, and 99mTc-methylene diphosphonate) or less than 1 h (99mTc-pyrophosphate) after tracer injection and if patients' imaging and clinical data could not be linked. Ground truth annotation was derived from centralised core-lab consensus reading of at least three independent experts (CN, TT-W, and JN). An AI system for detection of cardiac amyloidosis-associated high-grade cardiac tracer uptake was developed using data from one centre (Austria) and independently validated in the remaining centres. A multicase, multireader study and a medical algorithmic audit were conducted to assess clinician performance compared with AI and to evaluate and correct failure modes. The system's prognostic value in predicting mortality was tested in the consecutively recruited cohorts using cox proportional hazards models for each cohort individually and for the combined cohorts. The prevalence of cases positive for cardiac amyloidosis-suggestive uptake was 142 (2%) of 9176 patients in the Austrian, 125 (2%) of 6763 patients in the UK, 63 (62%) of 102 patients in the Chinese, and 103 (52%) of 200 patients in the Italian cohorts. In the Austrian cohort, cross-validation performance showed an area under the curve (AUC) of 1·000 (95% CI 1·000-1·000). Independent validation yielded AUCs of 0·997 (0·993-0·999) for the UK, 0·925 (0·871-0·971) for the Chinese, and 1·000 (0·999-1·000) for the Italian cohorts. In the multicase multireader study, five physicians disagreed in 22 (11%) of 200 cases (Fleiss' kappa 0·89), with a mean AUC of 0·946 (95% CI 0·924-0·967), which was inferior to AI (AUC 0·997 [0·991-1·000], p=0·0040). The medical algorithmic audit demonstrated the system's robustness across demographic factors, tracers, scanners, and centres. The AI's predictions were independently prognostic for overall mortality (adjusted hazard ratio 1·44 [95% CI 1·19-1·74], p<0·0001). AI-based screening of cardiac amyloidosis-suggestive uptake in patients undergoing scintigraphy was reliable, eliminated inter-rater variability, and portended prognostic value, with potential implications for identification, referral, and management pathways. Pfizer.

Which Is More Effective in Label Noise Cleaning, Correction or Filtering?

Most noise cleaning methods adopt one of the correction and filtering modes to build robust models. However, their effectiveness, applicability, and hyper-parameter insensitivity have not been carefully studied. We compare the two cleaning modes via a rebuilt error bound in noisy environments. At the dataset level, Theorem 5 implies that correction is more effective than filtering when the cleaned datasets have close noise rates. At the sample level, Theorem 6 indicates that confident label noises (large noise probabilities) are more suitable to be corrected, and unconfident noises (medium noise probabilities) should be filtered. Besides, an imperfect hyper-parameter may have fewer negative impacts on filtering than correction. Unlike existing methods with a single cleaning mode, the proposed Fusion cleaning framework of Correction and Filtering (FCF) combines the advantages of different modes to deal with diverse suspicious labels. Experimental results demonstrate that our FCF method can achieve state-of-the-art performance on benchmark datasets.

BAGAIL: Multi-modal imitation learning from imbalanced demonstrations

Expert demonstrations in imitation learning often contain different behavioral modes, e.g., driving modes such as driving on the left, keeping the lane, and driving on the right in the driving tasks. Although most existing multi-modal imitation learning methods allow learning from demonstrations of multiple modes, they have strict constraints on the data of each mode, generally requiring a near data ratio of all modes. Otherwise, it tends to fall into a mode collapse or only learn the data distribution of the mode that has the largest data volume. To address the problem, an algorithm that balances real-fake loss and classification loss by modifying the output of the discriminator, referred to as BAlanced Generative Adversarial Imitation Learning (BAGAIL), is proposed. With this modification, the generator is only rewarded for generating real trajectories with correct modes. BAGAIL is therefore able to deal with imbalanced expert demonstrations and carry out efficient learning for each mode. The learning process of BAGAIL is divided into a pre-training stage and an imitation learning stage. During the pre-training stage, BAGAIL initializes the generator parameters by means of conditional Behavioral Cloning, laying the foundation for the direction of parameter optimization. During the imitation learning stage, BAGAIL optimizes the parameters by using the adversary between the generator and the modified discriminator so that the finally obtained policy can successfully learn the distribution of imbalanced expert data. The experiments showed that BAGAIL accurately distinguished different behavioral modes with imbalanced demonstrations. What is more, the learning result of each mode is close to the expert standard and more stable than other multi-modal imitation learning methods.

Phytochemistry and Biological Assessment of Thuja articulata Trunk Barks: HPLC-PDA-ESI-MS Analysis, Bioevaluation, and Molecular Docking

Background: Thuja articulata is a Mediterranean forest species from the Cupressaceae family, it has been used in popular medicine to treat several diseases. Various studies have been carried out in vitro using diverse T. articulata extracts to understand its traditional use. Methods: In this study, the ethyl acetate extract of T. articulata trunk barks was chemically identified using HPLC-PDA-ESI-MS, then examined in vitro for its antioxidant and α-amylase inhibitory effects. A molecular docking study was also performed to reinforce the noted bioactivities. Results: HPLC-PDA-ESI-MS analysis led to the identification of 22 polyphenolic compounds in the ethyl acetate extract of T. articulata trunk barks. This extract revealed interesting in vitro antioxidant properties and a significant α-amylase inhibitory action (IC50 = 16.08 ± 1.27 μg/mL). In silico analysis was found to agree with the in vitro studies in which major constituents of the ethyl acetate extract revealed low binding energy and a correct mode of interaction in the active pocket of the enzyme (PDB: 7TAA). The anti-a-amylase potential could be due either to a synergistic or individual action of certain constituents present in this extract. Conclusion: This study illustrates that the ethyl acetate extract of T. articulata trunk barks has potent sources of antioxidants and α-amylase inhibitors to be explored.

Effects of Liquid Fertilizers on Growth Performances of Ipomoea aquatica in Coir-Based Growing Media

In the process of crop management, fertilization must be practiced in an appropriate way to maintain the sustainability. Hence, the right type of fertilizer and the correct mode of application is crucial. The source and the physical nature of the fertilizer is having a significant effect on the performance of plants. In that context, liquid fertilizers are generally a convenient and effective way to enhance the nutrients availability. Hence, the present study was conducted to evaluate the effect of several liquid fertilizers on the growth performance of the popular leafy vegetable Ipomoea aquatica. Plants were established in coir grow blocks and treated with five different commonly known and available liquid fertilizers namely, Albert’s solution (T1), Compost tea (T2), Vermiwash (T3), Sanstha liquid fertilizer (T4) and Gliricidia leaf extract (T5) once a week by applying a constant volume of 100 mL. The experiment was arranged in a randomized complete block design (RCBD) inside a semi protected plant house. The growth parameters of the plants (plant height, number of leaves, leaf area, fresh weight, and dry weight) were recorded up to 60 days. One-way Analysis of Variance (ANOVA) was used for statistical comparisons. According to the results all the parameters denoted significant differences among the treatments (P&lt;0.05), except for chlorophyll content. However, T1 denoted the highest mean values for the vegetative parameters including, plant height, number of leaves, leaf area, fresh weight, and dry weight while T3 (Vermiwash) reported the second highest values for the respective parameters. Regarding the chlorophyll content the highest mean value was recorded by T2 (Compost tea) followed by T5 (Gliricidia leaf extract). The results of the present study indicated that liquid fertilizers can be used effectively for the production of I. aquatica in coir-based media. It suggested Albert’s solution and vermiwash as high potential liquid fertilizers while vermiwash can be recognized as a nutrient supplement for organic production of Ipomoea aquatica in coir-based media.&#x0D; &#x0D; Keywords: Compost tea, Ipomoea aquatica, Liquid fertilizer, Vermiwash&#x0D;

The Bi–O edge wavefront sensor

Context. Direct detection of exoplanets around nearby stars requires advanced adaptive optics (AO) systems. High-order systems are needed to reach a high Strehl ratio (SR) in near-infrared and optical wavelengths on future giant segmented-mirror telescopes (GSMTs). Direct detection of faint exoplanets with the European Southern Observatory (ESO) Extremely Large Telescope (ELT) will require some tens of thousands of correction modes. The resolution and sensitivity of the wavefront sensor (WFS) are key requirements for this science case. We present a new class of WFSs, the bi-orthogonal Foucault knife-edge sensors (or Bi–O edge), that is directly inspired by the Foucault knife-edge test. The idea consists of using a beam-splitter producing two foci, each of which is sensed by an edge with a direction orthogonal to the other focus. Aims. We describe two implementation concepts: The Bi–O edge sensor can be realised with a sharp edge and a tip-tilt modulation device (sharp Bi–O edge) or with a smooth gradual transmission over a grey edge (grey Bi–O edge). A comparison of the Bi–O edge concepts and the four-sided classical pyramid wavefront sensor (PWS) gives some important insights into the nature of the measurements. Methods. We analytically computed the photon noise error propagation, and we compared the results to end-to-end simulations of a closed-loop AO system. Results. Our analysis shows that the sensitivity gain of the Bi–O edge with respect to the PWS depends on the system configuration. The gain is a function of the number of control modes and the modulation angle. We found that for the sharp Bi–O edge, the gain in reduction of propagated photon noise variance approaches a theoretical factor of 2 for a large number of control modes and small modulation angle, meaning that the sharp Bi–O edge only needs half of the photons of the PWS to reach similar measurement accuracy. In contrast, the PWS is twice more sensitive than the Bi–O edge in the case of very low order correction and/or large modulation angles. Preliminary end-to-end simulations illustrate some of the results. The grey version of the Bi–O edge opens the door to advanced amplitude filtering, which replaces the need for a tip-tilt modulator while keeping the same dynamic range. We show that an additional factor of 2 in reduction of propagated photon noise variance can be obtained for high orders, such that the theoretical maximum gain of a factor of 4 in photon efficiency can be obtained. A diffractive Fourier model that accurately includes the effect of modulation and control modes shows that for the extreme AO (XAO) system configuration of the ELT, the overall gain will well exceed one magnitude in guide-star brightness when compared to the modulated PWS. Conclusions. We conclude that the Bi–O edge is an excellent candidate sensor for future very high order Adaptive Optics systems, in particular on GSMTs.