Fabrication and Evaluation of Herbal Hair Gel containing Zizipus jujuba, Hibiscus and Piper nigrum

Hair is an imperative part of human body. Various synthetic compounds, chemicals, and their derivatives have been proved to cause destructive effects. A number of herbal principles have been commended with hair growth promoting action and formulating them into appropriate cosmeceuticals can be well acknowledged as far as the patient compliance is concerned. The objective of the present research work was to develop a hair gel formulation with Black pepper (Piper nigrum) which is often used in Ayurvedic medicines and it stimulates hair follicles causing growth, and with Hibiscus leaves extract which is known as a hair growth promoter and a hair conditioner as well. The formulations also contain Ziziphus jujuba leaves extract, which has been reported possessing antibacterial activity which makes it beneficial against dandruff and scalp infections. Along with extracts of Ziziphus jujuba and Hibiscus leaves and Black Pepper seeds (3% w/w each). All the ingredients used to prepare the hair gel was found harmless and the physicochemical assessment showed ideal results, but advance research is required to perceive its hair growth promotion property. Keywords:  Ziziphus jujuba, Piper nigrum , Hibiscus, Hair Ge

Effectiveness of community-based health education and home support program to reduce blood pressure among patients with uncontrolled hypertension in Nepal : a cluster-randomized trial

Background Hypertension is a major global public health problem. Elevated blood pressure can cause cardiovascular and kidney diseases. We assessed the effectiveness of health education sessions and home support programs in reducing blood pressure among patients with uncontrolled hypertension in a suburban community of Nepal. Methods We conducted a community-based, open-level, parallel-group, cluster randomized controlled trial in Birendranagar municipality of Surkhet, Nepal. We randomly assigned four clusters (wards) into intervention and control arms. We provided four health education sessions, frequent home and usual care for intervention groups over six months. The participants of the control arm received only usual care from health facilities. The primary outcome of this study was the proportion of controlled systolic blood pressure (SBP). The analysis included all participants who completed follow-up at six months. Results 125 participants were assigned to either the intervention (n = 63) or the control (n = 62) group. Of them, 60 participants in each group completed six months follow-up. Theproportion of controlled SBP was significantly higher among the intervention participants compared to the control (58.3% vs. 40%). Odds ratio of this was 2.1 with 95% CI: 1.01–4.35 (p = 0.046) and that of controlled diastolic blood pressure (DBP) was 1.31 (0.63–2.72) (p = 0.600). The mean change (follow-up minus baseline) in SBP was significantly higher in the intervention than in the usual care (-18.7 mmHg vs. -11.2 mmHg, p = 0.041). Such mean change of DBP was also higher in the intervention (-10.95 mmHg vs. -5.53 mmHg, p = 0.065). The knowledge score on hypertension improved by 2.38 (SD 2.4) in the intervention arm, which was significantly different from that of the control group, 0.13 (1.8) (p<0.001). Conclusions Multiple health education sessions complemented by frequent household visits by health volunteers can effectively improve knowledge on hypertension and reduce blood pressure among uncontrolled hypertensive patients at the community level in Nepal

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM

Inbound Incoterm Conversion

Most organizations spend significant time on improving the processes and systems related to outbound movement of goods, i.e., cargo moving from the production site to customers. This focus often ignores the other aspect of the supply chain, namely inbound cargo movement, which refers to the shipments coming from the suppliers to either the purchasing organization or the production site of the organization. This capstone project investigates the various material buying arrangements (which primarily differ in operational setup and risk) that the buying entity will take on. This capstone project focuses on a selected group of twelve products from two suppliers with different characteristics such as origin, volume, price, supplier relationship, etc. Total logistics costs including the transport cost, purchase cost, and inventory costs are calculated. Risk is also included per incoterm option to give an overview for business managers on how to approach the buying decisions. In general, if the company would like to convert from C&D to E&F incoterms, it would mean that the buying organization is taking more risk upon itself and hence needs to have a solid operational setup (inhouse or outsourced) to manage the ownership responsibilities that come with changing incoterms. The end result is a matrix of selected scenarios which will allow the buyer to understand the risk associated with each incoterm under a set of conditions and the expected cost difference. The section ends up with opportunities that might be presented if the organization starts buying more under E&F incoterms instead of C&D incoterms along with the potential risk rating under each scenario

HAND GESTURE RECOGNITION USING MACHINE LEARNING

In order to offer new possibilities to interact with machine and to design more natural and more intuitive interactions with computing machines, this research aims at the automatic interpretation of gestures based on computer vision. One such technique can be used for detecting and understanding various human gestures as it would make the human-machine communication effective.This could make the conventional input devices like touchscreens, mouse pad, and keyboards redundant. In this project we will design a hand gesture recognition system which will perform defined task. Here we are using classroom as an application. Instead of classroom any other applications can be also used

HAND GESTURE RECOGNITION USING MACHINE LEARNING

In order to offer new possibilities to interact with machine and to design more natural and more intuitive interactions with computing machines, this research aims at the automatic interpretation of gestures based on computer vision. One such technique can be used for detecting and understanding various human gestures as it would make the human-machine&nbsp; communication effective.This could make the conventional input devices like touchscreens, mouse pad, and keyboards redundant. In this project we will design a hand gesture recognition system which will perform defined task. Here we areusing classroom as an application. Instead of classroom any other applications can be also used

ROBUST TEXT DETECTION AND EXTRACTION IN NATURAL SCENE IMAGES USING CONDITIONAL RANDOM FIELD MODEL AND OCR

In Natural Scene Image, Text detection is important tasks which are used for many content based image analysis. A maximally stable external region based method is used for scene detection .This MSER based method includes stages character candidate extraction, text candidate construction, text candidate elimination &amp; text candidate classification. Main limitations of this method are how to detect highly blurred text in low resolution natural scene images. The current technology not focuses on any text extraction method. In proposed system a Conditional Random field (CRF) model is used to assign candidate component as one of the two classes (text&amp; Non Text) by Considering both unary component properties and binary contextual component relationship. For this purpose we are using connected component analysis method. The proposed system also performs a text extraction using OCR