Stability indicating HPLC method for the simultaneous determination of moxifloxacin and prednisolone in pharmaceutical formulations

BACKGROUND: A simple, specific, and fast stability indicating reverse phase liquid chromatographic method was established for instantaneous determination of moxifloxacin and prednisolone in bulk drugs and pharmaceutical formulations. RESULTS: Optimum chromatographic separations among the moxifloxacin, prednisolone and stress-induced degradation products were achieved within 10 minutes by use of BDS Hypersil C8 column (250 X 4.6 mm, 5 μm) as stationary phase with mobile phase consisted of a mixture of phosphate buffer (18 mM) containing 0.1% (v/v) triethylamine, at pH 2.8 (adjusted with dilute phosphoric acid) and methanol (38:62 v/v) at a flow rate of 1.5 mL min(-1). Detection was performed at 254 nm using diode array detector. The method was validated in accordance with ICH guidelines. Response was a linear function of concentrations over the range of 20–80 μg mL(-1) for moxifloxacin (r2 ≥ 0.998) and 40–160 μg mL(-1) for prednisolone (r2 ≥ 0.998). The method was resulted in good separation of both the analytes and degradation products with acceptable tailing and resolution. The peak purity index for both the analytes after all types of stress conditions was ≥ 0.9999 indicated a complete separation of both the analyte peaks from degradation products. The method can therefore, be regarded as stabilityindicating. CONCLUSIONS: The developed method can be applied successfully for simultaneous determination of moxifloxacin and prednisolone in pharmaceutical formulations and their stability studies

Interactions of short chain phenylalkanoic acids within ionic surfactant micelles in aqueous media

% SDS KR nema Solubilization and interactions of phenylalkanoic acids induced by cationic surfactant, cetyltrimethylammonium bromide (CTAB) and an anionic surfactant, sodium dodecyl sulfate (SDS) was investigated spectrophotometrically at 25.0°C. The UV spectra of the additives (acids) were measured with and without surfactant above and below critical micelle concentration (cmc) of the surfactant. The presence of alkyl chain in phenylalkanoic acids is responsible for hydrophobic interaction resulting in shift of the spectra towards longer wavelength (red shift). The value of partition coefficient (Kx) between the bulk water and surfactant micelles and in turn standard free energy change of solubilization (ΔGpº) were also estimated by measuring the differential absorbance (ΔA) of the additives in micellar solutions

Prevalence and factors associated with irritable bowel syndrome among medical students of Karachi, Pakistan: A cross-sectional study

BACKGROUND: Irritable bowel syndrome (IBS) and its association with stress, has not been studied among university students in Pakistan. We investigated the prevalence and the pattern of anxiety related IBS symptoms among medical students of Karachi. FINDINGS: An observational case–control study was carried out at three medical colleges of Karachi, Pakistan. Random sampling was done on 360 medical students. Data was collected using validated tools “Rome III Criteria” and “Generalized Anxiety Disorder Questionnaire”. Participants with IBS were diagnosed on the criteria having experienced abdominal discomfort at least 2–3 days/month associated with high level of anxiety. The apparent prevalence of IBS was found to be 28.3%, with a predominance of 87 (85.29%) females (85.29%) over males (14.71%). The psychological symptoms of anxiety were encountered in 57 (55.8%) participants with IBS, among which males were 15.7% and females 84.2% respectively. CONCLUSION: Students who more frequently suffer with mental stress and anxiety are more associated with IBS

IoT-MQTT based denial of service attack modelling and detection

Internet of Things (IoT) is poised to transform the quality of life and provide new business opportunities with its wide range of applications. However, the bene_ts of this emerging paradigm are coupled with serious cyber security issues. The lack of strong cyber security measures in protecting IoT systems can result in cyber attacks targeting all the layers of IoT architecture which includes the IoT devices, the IoT communication protocols and the services accessing the IoT data. Various IoT malware such as Mirai, BASHLITE and BrickBot show an already rising IoT device based attacks as well as the usage of infected IoT devices to launch other cyber attacks. However, as sustained IoT deployment and functionality are heavily reliant on the use of e_ective data communication protocols, the attacks on other layers of IoT architecture are anticipated to increase. In the IoT landscape, the publish/- subscribe based Message Queuing Telemetry Transport (MQTT) protocol is widely popular. Hence, cyber security threats against the MQTT protocol are projected to rise at par with its increasing use by IoT manufacturers. In particular, the Internet exposed MQTT brokers are vulnerable to protocolbased Application Layer Denial of Service (DoS) attacks, which have been known to cause wide spread service disruptions in legacy systems. In this thesis, we propose Application Layer based DoS attacks that target the authentication and authorisation mechanism of the the MQTT protocol. In addition, we also propose an MQTT protocol attack detection framework based on machine learning. Through extensive experiments, we demonstrate the impact of authentication and authorisation DoS attacks on three opensource MQTT brokers. Based on the proposed DoS attack scenarios, an IoT-MQTT attack dataset was generated to evaluate the e_ectiveness of the proposed framework to detect these malicious attacks. The DoS attack evaluation results obtained indicate that such attacks can overwhelm the MQTT brokers resources even when legitimate access to it was denied and resources were restricted. The evaluations also indicate that the proposed DoS attack scenarios can signi_cantly increase the MQTT message delay, especially in QoS2 messages causing heavy tail latencies. In addition, the proposed MQTT features showed high attack detection accuracy compared to simply using TCP based features to detect MQTT based attacks. It was also observed that the protocol _eld size and length based features drastically reduced the false positive rates and hence, are suitable for detecting IoT based attacks

Texture analysis using local ternary pattern for face anti-spoofing

This paper proposes a new face anti-spoofing approach based on analysis of texture characteristics. Photo images are used for spoofing the face recognition and verification system. These photos are similar to the images of a live person which are exhibiting quite different contrast and texture characteristics when compared to real face images. Various feature extraction methods for texture classification including local Binary Patterns emerge as one of the most popular method because of its simplicity and classification accuracy. However, in homogenous regions, the order of the pixel with respect to its neighbors is quite noisy which can affect the performance of Local Binary Pattern. This paper demonstrates the use of local Ternary Pattern (LTP) in face liveness detection system to overcome this problem. The LTP approach is tested on three publicly available NUAA Photograph Imposter database, CASIA Face Anti -Spoofing Database and REPLAY-ATTACK database. Moreover, different experiments are performed by applying different sizes of neighbor pixels and radius of the patches. The test results are compared with the LBP operator and other state-of art work. The proposed face anti-spoofing method performs better than conventional texture based methods

A survey of eMedia-delivered interventions for schizophrenia used in randomized controlled trials

Background: Randomized trials evaluating electronic Media (eMedia) delivery of interventions are increasingly frequent in mental health. Although a number of reviews have reported efficacy of these interventions, none has reviewed the type of eMedia interventions and quality of their description. We therefore decided to conduct a survey of eMedia-delivered interventions for schizophrenia. Methods: We surveyed all relevant trials reliably identified in the Cochrane Schizophrenia Group’s comprehensive register of trials by authors working independently. Data were extracted regarding the size of the trial, interventions, outcomes and how well the intervention was described. Results: eMedia delivery of interventions is increasingly frequent in trials relevant to the care of people with schizophrenia. The trials varied considerably in sample sizes (mean =123, median =87, range =20–507), and interventions were diverse, rarely evaluating the same approaches and were poorly reported. This makes replication impossible. Outcomes in these studies are limited, have not been noted to be chosen by end users and seem unlikely to be easy to apply in routine care. No study reported on potential adverse effects or cost, end users satisfaction or ease of use. None of the papers mentioned the use of CONSORT eHealth guidelines. Conclusion: There is a need to improve reporting and testing of psychosocial interventions delivered by eMedia. New trials should comply with CONSORT eHealth guidance on design, conduct and reporting, and existing CONSORT should be updated regularly, as the field is constantly evolving

Ontology: Core Process Mining and Querying Enabling Tool

Ontology permits the addition of semantics to process models derived from mining the various data stored in many information systems. The ontological schema enables for automated querying and inference of useful knowledge from the different domain processes. Indeed, such conceptualization methods particularly ontologies for process management which is currently allied to semantic process mining trails to combine process models with ontologies, and are increasingly gaining attention in recent years. In view of that, this chapter introduces an ontology-based mining approach that makes use of concepts within the extracted event logs about domain processes to propose a method which allows for effective querying and improved analysis of the resulting models through semantic labelling (annotation), semantic representation (ontology) and semantic reasoning (reasoner). The proposed method is a semantic-based process mining approach that is able to induce new knowledge based on previously unobserved behaviours, and a more intuitive and easy way to represent and query the datasets and the discovered models compared to other standard logical procedures. To this end, the study claims that it is possible to apply effective reasoning methods to make inferences over a process knowledge-base (e.g. the learning process) that leads to automated discovery of learning patterns and/or behaviour

Beyond preparatory year composition: applying e-portfolio to lead EFL students toward writing empowerment in Saudi Arabia

Writing is a crucial output skill that requires various sub-skills, including thinking, analysis, reasoning, arguing, processing, drafting, and concluding. Better writing skills empower a person to convey their message successfully and present or systematically record their ideas. Teachers can teach writing skills as a process rather than a product, which cannot be developed in a semester or program. Teaching writing skills in Saudi Arabia can be challenging due to cultural and linguistic differences (Al-Seghayer,2019). However, paper-based and electronic portfolios can be valuable tools for students to develop their writing skills (Al Badi et al., 2020). The Preparatory Year Program (PYP) at Royal Commission Colleges & Institutes (RCYCI) emphasises writing skills for EFL students and has transitioned from paper-based to online e-portfolios using Blackboard learning platforms. This study involved 970 first-year, second-semester ENG 002 students from the English Department of the RCYCI. Students received writing training using a paper-based portfolio (pre-mid-term) and an e-portfolio (post-mid-term) on Blackboard software. The quantitative data analysis revealed that students’ writing quality significantly improved when taught using the Blackboard-assisted e-portfolio compared to the paper-based portfolio class

Gender Inequality: Work Place Issues

Women have always been a most integral part of workforce. If we stretch back to the eighteenth century women not only used to work at their homes but also outside their houses, mostly as a maid. After the industrial revolution number of women entering in to the workforce increases and this change further increases with the time. However, this increase didn’t assure them that they will have equal rights or will be treated on fair basis rather than on gender basis.  Today when we are living in a fast paced technological era, females are still facing problems at workplace in many different ways. This paper is intended to cover all those issues which has been identified in different studies moreover, an analysis on factors behind them.  The first part of this paper will briefly discuss the historical background of women participation at workplace, then this part will be followed by discussion on different researches and studies. In this paper six different studies are discussed that reveals six or more factors that cause inequality and discrimination on gender basis at workplace. Each study is discussed and analyzed with the help of its finding. The statistics provided by those researches help to understand the real picture of the issue. The last part, conclusion, summarizes the whole research. It roundup and highlights the main issues which is discussed in the earlier part. It will be helpful for the reader to find the work of the current research done in this particular area of study. Keywords: Discrimination, Workforce, Inequality, Industrial Revolution DOI: 10.7176/JESD/11-20-05 Publication date:October 31st 202