Investigation for Bioactive Compounds of Berberis Lyceum Royle and Justicia Adhatoda L.

In order to explore the medicinal values of plant species like Berberis lyceum and Justicia adhatoda, a study was conducted to analyze roots, leaves and fruits of both plant species for identification of various organic compounds. Chemical analysis as well as identification of organic compounds by chromatographic techniques were carried out. Results indicates that both plant species contained Proteins, Sugars, Lipids, Vitamin C, Sodium, Calcium, Sulphur, Iron, and Zinc.Whereas the alkaloids like Palmatine, Berberine, Vasicine and Vasicinone were also found in leaves and roots of these plant species. However, it was observed that roots of both plant species contained higher concentrations of these chemical compounds as compared to fruits and leaves except sugar and vitamin C those were high in fruits. Furthermore presence of such bioactive compounds in Berberis lyceum and Justicia adhatoda indicated their importance in the form of local medicines. This experiment will help to increase the importance of new raw material found in these plant species and their demand in the market will be increased in the future. The extract of roots and fruits of these plant species are being used against various infections and diseases in rural population of subcontinent since many centuries

Passivity and Immersion based-modified gradient estimator: A control perspective in parameter estimation

In this paper, a constructive and systematic strategy with more apparent degrees of freedom to achieve the accurate estimation of unknown parameters via a control perspective is proposed. By adding a virtual control in the final equation of the gradient dynamics, the Gradient Estimator (GE) and Memory Regressor and Extension (MRE) approaches are extended. The solution of the virtual control law is identified by the P&I approach. The P&I approach is based on the choice of an appropriate implicit manifold and the generation of a suitable passive output and a related storage function. This facilitates the virtual control law being obtained in a way that the parametric error converges asymptotically to zero. Because the above ideas connect with the P&I approach and GE, the developed methodology is labeled the passivity and immersion-based modified gradient estimator (MGE). The proposed P&I-based modified gradient estimator is extended via the MRE approach. This modification provides improved transient response and fast convergence. Based on certain PE and non-PE examples, a comparative analysis is carried out to show the efficacy of the proposed approaches

Randomize to Generalize: Domain Randomization for Runway FOD Detection

Tiny Object Detection is challenging due to small size, low resolution, occlusion, background clutter, lighting conditions and small object-to-image ratio. Further, object detection methodologies often make underlying assumption that both training and testing data remain congruent. However, this presumption often leads to decline in performance when model is applied to out-of-domain(unseen) data. Techniques like synthetic image generation are employed to improve model performance by leveraging variations in input data. Such an approach typically presumes access to 3D-rendered datasets. In contrast, we propose a novel two-stage methodology Synthetic Randomized Image Augmentation (SRIA), carefully devised to enhance generalization capabilities of models encountering 2D datasets, particularly with lower resolution which is more practical in real-world scenarios. The first stage employs a weakly supervised technique to generate pixel-level segmentation masks. Subsequently, the second stage generates a batch-wise synthesis of artificial images, carefully designed with an array of diverse augmentations. The efficacy of proposed technique is illustrated on challenging foreign object debris (FOD) detection. We compare our results with several SOTA models including CenterNet, SSD, YOLOv3, YOLOv4, YOLOv5, and Outer Vit on a publicly available FOD-A dataset. We also construct an out-of-distribution test set encompassing 800 annotated images featuring a corpus of ten common categories. Notably, by harnessing merely 1.81% of objects from source training data and amalgamating with 29 runway background images, we generate 2227 synthetic images. Subsequent model retraining via transfer learning, utilizing enriched dataset generated by domain randomization, demonstrates significant improvement in detection accuracy. We report that detection accuracy improved from an initial 41% to 92% for OOD test set.Comment: 29 pages, 9 figure

Assessing vulnerability for inhabitants of Dhaka City considering flood-hazard exposure

Globalna opasnost od poplave postupno se povećava. Iako ih je nemoguće izbjeći, gubici i šteta od opasnosti (npr. poplave, cikloni i potresi) mogu se učinkovito smanjiti smanjenjem ranjivosti kućanstava odgovarajućim mjerama. Cilj ove studije je kvantitativno mjerenje ranjivosti kućanstava obzirom na opasnosti od poplave kao alata za njihovo ublažavanje. Također je predložen jedinstveni pristup za kvantificiranje ugroženosti kućanstava obzirom na opasnosti od poplave, a kao primjer predstavljena je primjena u gradu Dhaki sklonom poplavama. Podaci su prikupljeni i sa siromašnih i bogatih područja kako bi bilo pokriveno cijelo urbano područje te kako bi se usporedila razina ugroženosti od poplava. Ukupno 300 kućanstava anketirano je strukturiranim upitnikom na temelju pet čimbenika (ekonomskih, socijalnih, okolišnih, strukturnih i institucionalnih) ugroženosti od poplava. Analitički hijerarhijski postupak (AHP) primijenjen je za mjerenje pojedinačnih rezultata ranjivosti kućanstva korištenjem relativne težine varijabli i pokazatelja uz pravilnu standardizaciju. Analitički rezultati pokazali su da je 63,06% siromašnih kućanstava i 20,02% bogatih kućanstava vrlo osjetljivo na poplave. Uz to, ovaj je rad utvrdio i procijenio čimbenike odgovorne za ranjivost kućanstava u Dhaki. Što se tiče strukturne ranjivosti, rezultati su pokazali da je 82% kućanstava u siromašnim krajevima bilo visoko ranjivo, a 95,3% kućanstava koja nisu iz siromašnih četvrti bilo je umjereno ranjivo. Društveno, 67,3% siromašnih i 78,7% kućanstava koja nisu iz siromašnih naselja bila su umjereno i slabo ranjiva. Većina kućanstava u siromašnoj i nesiromašnoj četvrti (84%, odnosno 59,3%) pokazala je visoku i umjerenu ekonomsku ranjivost. Štoviše, za 69,3% siromašnih i 65,3% nesiromašnih kućanstava institucionalna ranjivost je bila visoka. Od stanovnika siromašnih naselja, 63,3% je bilo izloženo ekološkom riziku, a 78% staništa koja nisu u siromašnim područjima bilo je u kategoriji niske ranjivosti. Uz odgovarajuću prilagodbu ovdje predložen učinkoviti alat za mjerenje ranjivosti koji je ovdje prilagođen specifičnoj lokaciji, primjenjiv je i za mjerenje ranjivosti drugih gradova u svijetu. Na temelju ove studije moglo bi se provesti buduće istraživanje s više čimbenika, varijabli i pokazatelja ljudske ranjivosti na prirodne ili umjetne opasnosti / katastrofe. Budući rad mogao bi pružiti bolju sliku stanja ranjivosti od pojedinačne / višestruke opasnosti / katastrofe.Global flood hazard is gradually increasing. Though it is impossible to avoid them, losses and damage of hazards (e.g., floods, cyclones, and earthquakes) could be efficiently reduced by reducing household vulnerability with appropriate measures. This study aims to quantitatively measure the household vulnerability of flood hazards as a mitigation tool. It also proposed a unique approach to quantify flood-hazard household vulnerability, and shows its application in the flood prone city of Dhaka as an example case. Data were collected from both slum and non-slum areas to cover the entire urban habitat, and to compare their level of flood vulnerability. A total of 300 households were surveyed by structured questionnaire on the basis of five factors (economic, social, environmental, structural, and institutional) of flood vulnerability. The analytical hierarchy process (AHP) was applied to measure individual household vulnerability scores by using the relative weightage of variables and indicators with proper standardisation. Analytical results demonstrated that 63.06% slum and 20.02% non-slum households were highly vulnerable to floods. In addition, this paper determined and assessed responsible factors for household flood vulnerability in Dhaka. For structural vulnerability, results exhibited that 82% of slum households were highly vulnerable, and 95.3% of non-slum households were moderately vulnerable. Socially, 67.3% of slum and 78.7% of non-slum households were moderately and low-vulnerable. The majority of slum and non-slum households (84% and 59.3%, respectively) showed high and moderate vulnerability with respect to economic vulnerability. Moreover, 69.3% of slum and 65.3% of nonslum household institutional vulnerability levels were high. Of slum inhabitants, 63.3% were environmentally at high risk, and 78% of non-slum habitats were in the low-vulnerability category. However, as an effective tool to measure location-specific vulnerability, it is applicable for the measuring vulnerability of other cities in the world with proper customisation. On the basis of this study, future research could be conducted with more factors, variables, and indicators of human vulnerability to natural or artificial hazards/disasters. Future work may provide a better reflection of the vulnerability status of single/multiple hazard(s)/disaster(s)

Combining regenerative medicine strategies to provide durable reconstructive options: auricular cartilage tissue engineering

Recent advances in regenerative medicine place us in a unique position to improve the quality of engineered tissue. We use auricular cartilage as an exemplar to illustrate how the use of tissue-specific adult stem cells, assembly through additive manufacturing and improved understanding of postnatal tissue maturation will allow us to more accurately replicate native tissue anisotropy. This review highlights the limitations of autologous auricular reconstruction, including donor site morbidity, technical considerations and long-term complications. Current tissue-engineered auricular constructs implanted into immune-competent animal models have been observed to undergo inflammation, fibrosis, foreign body reaction, calcification and degradation. Combining biomimetic regenerative medicine strategies will allow us to improve tissue-engineered auricular cartilage with respect to biochemical composition and functionality, as well as microstructural organization and overall shape. Creating functional and durable tissue has the potential to shift the paradigm in reconstructive surgery by obviating the need for donor sites

Search for eccentric black hole coalescences during the third observing run of LIGO and Virgo

Despite the growing number of confident binary black hole coalescences observed through gravitational waves so far, the astrophysical origin of these binaries remains uncertain. Orbital eccentricity is one of the clearest tracers of binary formation channels. Identifying binary eccentricity, however, remains challenging due to the limited availability of gravitational waveforms that include effects of eccentricity. Here, we present observational results for a waveform-independent search sensitive to eccentric black hole coalescences, covering the third observing run (O3) of the LIGO and Virgo detectors. We identified no new high-significance candidates beyond those that were already identified with searches focusing on quasi-circular binaries. We determine the sensitivity of our search to high-mass (total mass M>70 M⊙) binaries covering eccentricities up to 0.3 at 15 Hz orbital frequency, and use this to compare model predictions to search results. Assuming all detections are indeed quasi-circular, for our fiducial population model, we place an upper limit for the merger rate density of high-mass binaries with eccentricities 0<e≤0.3 at 0.33 Gpc−3 yr−1 at 90\% confidence level

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects