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The purpose of this paper is to understand the effect of airflow dynamics on vortices for different flow rates using the human nose three-dimensional model.

Olfaction originates with air particles travelling from an external environment to the upper segment of the human nose. This phenomenon is generally understood by using the nasal airflow dynamics, which enhances the olfaction by creating the vortices in the human nose. An anatomical three-dimensional model of the human nasal cavity from computed tomography (CT) scan images using the MIMICS software (Materialise, USA) was developed in this study. Grid independence test was performed through volume flow rate, pressure drop from nostrils and septum and average velocity near the nasal valve region using a four computational mesh model. Computational fluid dynamics (CFD) was used to examine the flow pattern and influence of airflow dynamics on vortices in the nasal cavity. Numerical simulations were conducted for the flow rates of 7.5, 10, 15 and 20 L/min using numerical finite volume methods.

At coronal cross-sections, dissimilar nasal airflow patterns were observed for 7.5, 10, 15 and 20 L/min rate of fluid flow in the human nasal cavity. Vortices that are found at the boundaries with minimum velocity creates deceleration zone in the nose vestibule region, which is accompanied by flow segregation. Maximum vortices were observed in the nasal valve region and the posterior end of the turbinate region, which involves mixing and recirculation and is responsible for enhancing the smelling process.

The proposed analysis is applicable to design the sensor chamber for electronic noses.

In this paper, the influence of airflow dynamics on vortices in the human nasal cavity is discussed through numerical simulations.

The purpose of this paper is to prepare and optimize the preparation conditions of some new hydrogels and in addition, evaluate their water absorbance at different mediums and their ability to remove ions from aqueous solutions.

Cellulose was extracted from depithed bagasse at two different pulping conditions; 3 and 6 hours cooking times, pulp (I) and (II), respectively. These pulps, in addition to cotton linter for comparison, were grafted with acrylamide followed by cross‐linking with glutaraldehyde. The networks were partially hydrolyzed and the structures of products (before and after hydrolysis) were studied using FTIR, SEM, TGA and X‐ray. The optimum preparation conditions were identified, before and after hydrolysis, to achieve maximum absorbance and the ability of prepared hydrogels to remove ions from solutions was investigated.

Maximum level of absorption was recorded using hydrogels prepared with monomer concentration =0.8 mol/l, cross‐linker concentration =0.01 mol/l, reaction time =2 hours and temperature =65°C. Hydrogels prepared using pulp (I) showed the best absorbance behavior and a tendency to remove ions from water.

The ability of the prepared gels to remove ions from water could be further investigated to evaluate the ability of their use in a multi‐filtration system for water treatment.

This piece of work has suggested a simple way to convert an agricultural waste to hydrogel able to remove metal ions from water.

Consuming this type of waste reduces the risks resulting from its burning in some countries, such as Egypt, that produce large amounts of it.

In this paper, low cost hydrogels, with expected value in water treatment, were prepared using agricultural wastes. They have shown better reactivity than gels prepared using pure cellulosic materials (cotton linter).

The purpose of this paper is to improve the performance of E-nose in the detection of wound infection. Feature extraction and selection methods have a strong impact on the performance of pattern classification of electronic nose (E-nose). A new hybrid feature matrix construction method and multi-objective binary quantum-behaved particle swarm optimization (BQPSO) have been proposed for feature extraction and selection of sensor array.

A hybrid feature matrix constructed by maximum value and wavelet coefficients is proposed to realize feature extraction. Multi-objective BQPSO whose fitness function contains classification accuracy and a number of selected sensors is used for feature selection. Quantum-behaved particle swarm optimization (QPSO) is used for synchronization optimization of selected features and parameter of classifier. Radical basis function (RBF) network is used for classification.

E-nose obtains the highest classification accuracy when the maximum value and db 5 wavelet coefficients are extracted as the hybrid features and only six sensors are selected for classification. All results make it clear that the proposed method is an ideal feature extraction and selection method of E-nose in the detection of wound infection.

The innovative concept improves the performance of E-nose in wound monitoring, and is beneficial for realizing the clinical application of E-nose.

This paper aims to present the methods of improving selectivity and sensitivity of resistance gas sensors.

This paper compares various methods of improving gas sensing by temperature modulation, UV irradiation or fluctuation-enhanced sensing. The authors analyze low-frequency resistance fluctuations in commercial Taguchi gas sensors and the recently developed tungsten trioxide (WO₃) gas-sensing layers, exhibiting a photo-catalytic effect.

The efficiency of using low-frequency fluctuations to improve gas detection selectivity and sensitivity was confirmed by numerous experimental studies in commercial and prototype gas sensors.

A more advanced measurement setup is required to record noise data but it will reduce the number of gas sensors necessary for identifying the investigated gas mixtures.

Fluctuation-enhanced sensing can reduce the energy consumption of gas detection systems and assures better detection results.

A thorough comparison of various gas sensing methods in resistance gas sensors is presented and supported by exemplary practical applications.

Part A – to identify the challenges of inducting and nurturing next-gen leaders, to outline the building blocks for the successful induction of the next generation into the family business and to spell the importance of mentoring conversations as a tool for successful induction in the family business. Part B – to define the basic tenets of effective communication-goal setting, planning and action using the goals, plans and action framework, to build a “listening” environment through understanding the hearing, understanding, remembering, interpreting, evaluating, and responding mode and to relate the importance of “questioning” in diagnosing a problem and reading both verbal and non-verbal cues in communication.

The two-part case describes the role of communication amongst young family business scions and a mentor’s role in shaping such communication. Part A traces the induction of Aditya Gandhi, a fourth-generation scion of Gandhi Gems and Jewels, a 110-year old Indian family business dealing in precious gems and jewels. It deals with the challenges of mentoring and successful induction of the next-generation into family business Part B of the case describes the communication between Aditya Gandhi and the proprietor of Gandhi Gems and Jewels’ key client, Ghanshyam Das. It deals with the tenets of effective communication as should be understood by young next-generation family members.

The case can be used in an executive programme for owners of family businesses or in an undergraduate or post-graduate programme in general business administration or family business management.

Teaching Notes are available for educators only.

CSS 11: Strategy.

In particular, this paper aims to systematically analyze a few prominent wireless sensor network (WSN) clustering routing protocols and compare these different approaches according to the taxonomy and several significant metrics.

In this paper, the authors have summarized recent research results on data routing in sensor networks and classified the approaches into four main categories, namely, data-centric, hierarchical, location-based and quality of service (QoS)-aware, and the authors have discussed the effect of node placement strategies on the operation and performance of WSNs.

Performance-controlled planned networks, where placement and routing must be intertwined and everything from delays to throughput to energy requirements is well-defined and relevant, is an interesting subject of current and future research. Real-time, deadline guarantees and their relationship with routing, mac-layer, duty-cycles and other protocol stack issues are interesting issues that would benefit from further research.

The main purpose of this study is to assess the impact of small-scale irrigation on the total income of small farm households. Additionally, it aims to identify the factors influencing the total income of households who have adopted small-scale irrigation methods.

The study utilized cross-sectional data sourced directly from primary channels. Primary data collection was facilitated through the administration of semi-structured questionnaires and conducting in-depth interviews. Both propensity score matching (PSM) and an ordinary least squares (OLS) model were employed to assess the impact of small-scale irrigation on total income and to identify factors affecting the effectiveness of SSI. In order to ensure that the PSM model’s findings were consistent, we used instrumental variables (IV) estimation, which was conducted using two stages least squares (2SLS) regression.

The study findings reveal that small-scale irrigation adopters earn, on average, 12,947.32 Birr more than non-adopters. The PSM model reveals that households engaged in small-scale irrigation experience a significant increase in total income compared to non-irrigating households. The study underscores the need to address key factors influencing the treatment effect on household income, including distance to farm training centers, proximity to water sources, access to transportation, availability of family labor and frequency of extension contact.

This paper only examines the effect of small-scale irrigation on small farm households’ total income. This study encourages future studies to investigate the effects of small-scale irrigation on small farm household food security, total spending, poverty reduction, welfare and net earnings in the study area.

Most studies only analyze how small-scale irrigation affects the total income of small-scale farm households. This study fills a knowledge gap by identifying the key elements that influence the extent of the impact on user households.

The purpose of this paper is to examine the market integration and direction of causality of wholesale and retail prices for the chickpea legume in major chickpea markets in India.

In this paper, the authors employ the Johansen co-integration test, Granger causality test, vector autoregression (VAR), and vector error correction model (VECM) to examine the integration of markets. The authors use monthly wholesale and retail price data of the chickpea crop from select markets in India spanning January 2003–December 2020.

The results of this study strongly confirm the co-integration and interdependency of the selected chickpea markets in India. However, the speed of adjustment of prices in the wholesale market is weakest in Bikaner, followed by Daryapur and Narsinghpur; it is relatively moderate in Gulbarga. In contrast, the speed of adjustment is negative for Bhopal and Delhi, weak for Nasik, and moderate for retail market prices in Bangalore. The results of the causality test show that the Narsinghpur, Daryapur, and Gulbarga markets are the most influential, with bidirectional relations in the case of wholesale market prices. Meanwhile, the Bangalore market is the most connected and effective retail market among the selected retail markets. It has bidirectional price transmission with two other markets, i.e. Bhopal and Nasik.

This paper calls for forthcoming studies to investigate the impact of external and internal factors, such as market infrastructure; government policy regarding self-reliant production; product physical characteristics; and rate of utilization indicating market integration. They should also focus on strengthening information technology for the regular flow of market information to help farmers increase their incomes.

Very few studies have explored market efficiency and direction of causality using both linear and nonlinear techniques for wholesale and retail prices of chickpea in India.

Water soluble vehicles based on unsaturated fatty acids and oils have been prepared which have gloss and are air‐drying. Resin blends have also been prepared to improve certain characteristics. Comparison of the prepared compositions regarding their evaluation as a paint vehicle has also been taken into consideration.

The purpose of this study is to develop a systematic approach by demonstrating the Design for Six Sigma (DFSS) approach for reliability improvement of moulded case circuit breaker (MCCB) (current rating 250A).

In this study, the Define, Measure, Analyze, Design and Verify (DMADV) methodology of DFSS has been used to improve the reliability of MCCB. Mechanical endurance test (MET), project risk management, customer-based product development (PD), and other tools and techniques are used appropriately in DMADV methodology for improving the reliability of MCCB.

It has been observed that the reliability of MCCB has been improved from 61.76% to 98.17% for 20,000 operating cycles by implementing suggested improvement measures and the Weibull distribution is the most suitable distribution for reliability analysis of collected data.

This study considered only the aspects of DMADV methodology of the DFSS approach and does not cover other PD approaches such as lean and green PD.

This study clearly shows an enhancement in the reliability of MCCB which further leads to an increase in the warranty period. This will attract more customers and enhance business.

The improvement in the reliability of MCCB would significantly reduce fatal accidents ensuring workplace safety in the industry.

The originality of this study is the reliability assessment using degradation analysis in the design phase of the DMADV process to predict failure during design verification.