Microfinance Customer (Borrower) Experience towards the Effectiveness of MFIS in Bangladesh: An Exploratory Analysis

Microfinance initiative is widely acclaimed as an approach to raise income level, alleviate poverty and bring about development, but recently the effectiveness of the microfinance programs has been appeared to be a focus of debate in microfinance literature. An exploratory survey was conducted to analyze the microfinance customers’ (borrowers’) perception about the microfinance schemes adopted by different microfinance institutes (MFIs) in Bangladesh. This study covered only three MFIs such as Grameen Bank (GB), Bangladesh Rural Advancement Committee (BRAC) and Association for Social Advancement (ASA). Convenience sampling technique was adopted in data collection process. The customers were asked to evaluate different objects selected in the questionnaire. The respondents ranked the attributes on a number of itemized five-point scale ratings bounded at each end by one of two bipolar adjectives. Based on the study, borrowers’ experience suggests that income level has not been increased. This implies that MFIs are not effective to achieve their objectives of raising income and reducing poverty. It also shows that the factors such as membership criteria, costs of credit, income level and religious restrictions are observed significant to affect microfinance consumer experience in Bangladesh

Calli Essential Oils Synergize with Lawsone against Multidrug Resistant Pathogens.

The fast development of multi-drug resistant (MDR) organisms increasingly threatens global health and well-being. Plant natural products have been known for centuries as alternative medicines that can possess pharmacological characteristics, including antimicrobial activities. The antimicrobial activities of essential oil (Calli oil) extracted from the Calligonum comosum plant by hydro-steam distillation was tested either alone or when combined with lawsone, a henna plant naphthoquinone, against MDR microbes. Lawsone showed significant antimicrobial activities against MDR pathogens in the range of 200-300 µg/mL. Furthermore, Calli oil showed significant antimicrobial activities against MDR bacteria in the range of 180-200 µg/mL, Candida at 220-240 µg/mL and spore-forming Rhizopus fungus at 250 µg/mL. Calli oil's inhibition effect on Rhizopus, the major cause of the lethal infection mucormycosis, stands for 72 h, followed by an extended irreversible white sporulation effect. The combination of Calli oil with lawsone enhanced the antimicrobial activities of each individual alone by at least three-fold, while incorporation of both natural products in a liposome reduced their toxicity by four- to eight-fold, while maintaining the augmented efficacy of the combination treatment. We map the antimicrobial activity of Calli oil to its major component, a benzaldehyde derivative. The findings from this study demonstrate that formulations containing essential oils have the potential in the future to overcome antimicrobial resistance

Selective harmonic elimination in awide modulation range using modified Newton-raphson and pattern generation methods for a multilevel inverter

Considering the aim of having low switching losses, especially in medium-voltage and high-power converters, the pre-programmed pulse width modulation technique is very useful because the generated harmonic content can be known in advance and optimized. Among the different low switching frequency techniques, the Selective Harmonics Elimination (SHE) modulation method is most suitable because of its direct control over the harmonic spectrum. This paper proposes a method for obtaining multiple solutions for selectively eliminating specific harmonics in a wide range of modulation indices by using modified Newton-Raphson (NR) and pattern generation techniques. The different pattern generation and synthesis approach provide more degrees of freedom and a way to operate the converter in a wide range of modulation. The modified Newton-Raphson technique is not complex and ensures fast convergence on a solution. Moreover, multiple solutions are obtained by keeping a very small increase in the modulation index. In the previous methods, solutions were not obtainable at all modulation indices. In this paper, only exact solutions to the low-order harmonics elimination for Cascaded H-bridge inverter are reported for all modulation indices. Analytical and simulation results prove the robustness and correctness of the technique proposed in this paper. 2018 by the authors.Acknowledgments: This (publication, report, etc.) was made possible by NPRP grant # [X-033-2-007] from the Qatar National Research Fund (a member of Qatar Foundation).Scopu

NEW HIDING TECHNIQUE IN DIGITAL SIGNATURE BASED ON ZIGZAG TRANSFORM AND CHAOTIC MAPS

Abstract This paper presents a novel approach to digital signature by integrating the ElGamal or Schnorr digital signature algorithms, chaotic systems, and scanning techniques. Briefly, ZZBCRP is a zigzag transformation that is used firstly to construct a permuted transaction, which technique starts from any random position and intersects in both directions, which is more complex than zigzag transform techniques. Then using ElGamal or Schnorr signature schemes based on chaotic maps. This modification aims to make private key and random number dependent on discrete chaotic maps. Even if the private key chosen is small, it is easy by using the huge amount of points in chaotic maps 2-D or 3-D to extract strong and unique key. This change complicates the relationship between the private key, public key and the transaction signature. A two-dimensional trigonometric discrete chaotic map is used that integrated Logistic-sine-cosine maps, and a three-dimensional hyperchaotic map (3-D SCC) which are based on a sine map. Our performance analysis shows that compared to schemes; this scheme not only improves the level of efficiency but also assures safety. The performance analysis shows that our scheme is not only more efficient compared to other related systems, but also safer

Ultrastructure of antennal sensillae of the samsum ant, Pachycondyla sennaarensis (Hymenoptera: Formicidae)

Black ant (Samsum), Pachycodyla sennarrensis, stings and injects venom and inflicts allergy (a rare clinical problem) due to its local and systemic reaction, which is considered as a health hazard amongst Saudi society. Thus, black ant is a source of serious concern for the government and experts as well.  Ultramorphological variations, distribution, differential sensillae counts (DSC) and total sensillae counts (TSC), were identified and estimated as a complementary part of the peripheral nervous system on the antennae of worker samsum ant, P. sennarrensis in order to understand its behavioral ecology. Based on scanning electron micrographs, four types of sensillae constituted with three trichoid types, which is an abundant form with a high distribution density at the apex, but a low density at subsequent proximal flagellomere of the antenna and a placoid type of sensillae (a rare form mostly found in the middle of the flagellum, that is, on the 4th, 5th and 6th flagellomere) were categorised. It is documented that nonporous trichoid type of sensillae are mechanoreceptors and thermoreceptors, whereas, the placoid types are olfactory receptors. Present findings in an indigenous species in Saudi Arabia may help in understanding the ecological behaviour of the ant, which subsequently may form the basis in producing its effective control measure in future.Key words: Samsum ants, Pachycondyla sennarrensis, ultrastructure, antenna, sensillae

A systematic review of physiological signals based driver drowsiness detection systems.

Driving a vehicle is a complex, multidimensional, and potentially risky activity demanding full mobilization and utilization of physiological and cognitive abilities. Drowsiness, often caused by stress, fatigue, and illness declines cognitive capabilities that affect drivers' capability and cause many accidents. Drowsiness-related road accidents are associated with trauma, physical injuries, and fatalities, and often accompany economic loss. Drowsy-related crashes are most common in young people and night shift workers. Real-time and accurate driver drowsiness detection is necessary to bring down the drowsy driving accident rate. Many researchers endeavored for systems to detect drowsiness using different features related to vehicles, and drivers' behavior, as well as, physiological measures. Keeping in view the rising trend in the use of physiological measures, this study presents a comprehensive and systematic review of the recent techniques to detect driver drowsiness using physiological signals. Different sensors augmented with machine learning are utilized which subsequently yield better results. These techniques are analyzed with respect to several aspects such as data collection sensor, environment consideration like controlled or dynamic, experimental set up like real traffic or driving simulators, etc. Similarly, by investigating the type of sensors involved in experiments, this study discusses the advantages and disadvantages of existing studies and points out the research gaps. Perceptions and conceptions are made to provide future research directions for drowsiness detection techniques based on physiological signals. [Abstract copyright: © The Author(s), under exclusive licence to Springer Nature B.V. 2022. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Enhancing Cricket Performance Analysis with Human Pose Estimation and Machine Learning

Cricket has a massive global following and is ranked as the second most popular sport globally, with an estimated 2.5 billion fans. Batting requires quick decisions based on ball speed, trajectory, fielder positions, etc. Recently, computer vision and machine learning techniques have gained attention as potential tools to predict cricket strokes played by batters. This study presents a cutting-edge approach to predicting batsman strokes using computer vision and machine learning. The study analyzes eight strokes: pull, cut, cover drive, straight drive, backfoot punch, on drive, flick, and sweep. The study uses the MediaPipe library to extract features from videos and several machine learning and deep learning algorithms, including random forest (RF), support vector machine, k-nearest neighbors, decision tree, linear regression, and long short-term memory to predict the strokes. The study achieves an outstanding accuracy of 99.77% using the RF algorithm, outperforming the other algorithms used in the study. The k-fold validation of the RF model is 95.0% with a standard deviation of 0.07, highlighting the potential of computer vision and machine learning techniques for predicting batsman strokes in cricket. The study’s results could help improve coaching techniques and enhance batsmen’s performance in cricket, ultimately improving the game’s overall quality

Perspectives for a mixed two-qubit system with binomial quantum states

The problem of the relationship between entanglement and two-qubit systems in which it is embedded is central to the quantum information theory. This paper suggests that the concurrence hierarchy as an entanglement measure provides an alternative view of how to think about this problem. We consider mixed states of two qubits and obtain an exact solution of the time-dependent master equation that describes the evolution of two two-level qubits (or atoms) within a perfect cavity for the case of multiphoton transition. We consider the situation for which the field may start from a binomial state. Employing this solution, the significant features of the entanglement when a second qubit is weakly coupled to the field and becomes entangled with the first qubit, is investigated. We also describe the response of the atomic system as it varies between the Rabi oscillations and the collapse-revival mode and investigate the atomic inversion and the Q-function. We identify and numerically demonstrate the region of parameters where significantly large entanglement can be obtained. Most interestingly, it is shown that features of the entanglement is influenced significantly when the multi-photon process is involved. Finally, we obtain illustrative examples of some novel aspects of this system and show how the off-resonant case can sensitize entanglement to the role of initial state setting.Comment: 18 pages, 9 figure