Is 'Not Different' Enough to Conclude Similar Cardiovascular Responses Across Sexes?

The number of research studies investigating whether similar or different cardiovascular responses or adaptations exist between males and females are increasing. Traditionally, difference-based statistical methods (e.g., t-test, ANOVA, etc.) have been implemented to compare cardiovascular function between males and females, with a P-value >0.05 used to denote similarity between sexes. However, an absence of evidence (i.e., large P-value) is not evidence of absence (i.e., no sex differences). Equivalence testing determines whether two measures or groups provide statistically equivalent outcomes, in that they differ by less than an 'ideally prespecified' smallest effect size of interest. Our perspective discusses the applicability and utility of integrating equivalence testing when conducting sex comparisons in cardiovascular research. An emphasis is placed on how cardiovascular researchers may conduct equivalence testing across multiple study designs (e.g., cross-sectional comparisons, repeated measures intervention, etc.). The strengths and weaknesses of this statistical tool are discussed. Equivalence analyses are relatively simple to conduct, may be used in conjunction with traditional hypothesis testing to interpret findings, and permits the determination of statistically equivalent responses between sexes. We recommend that cardiovascular researchers consider implementing equivalence testing to better our understanding of similar and different cardiovascular processes between sexes.

Community structure of benthic invertebrates in the Allipén River basin, North Patagonia, Araucania region (38º S, Chile)

One of the biological indicators most used to determine the health of a fluvial ecosystem are the benthic macroinvertebrates. The presence of recurrent species in a wide gradient of latitudes, dominates the biogeographic pattern of the benthic macroinvertebrates in Chilean fresh waters, nevertheless the knowledge on the communitarian ecology of these in the Chilean rivers continues to be scarce. Null models became a powerful statistical tool for describing the ecological mechanisms that drive the structure of an ecological community and the underlying patterns of diversity. The objective of this study was to determine the community structure of benthic invertebrates in the Allipén River by describing their composition, richness and abundance of species through richness models and null models based on presence/absence. The results reveal a high family richness and low diversity, three phyla, five classes, 11 orders and 28 families were identified in the study area during the four seasons of the year. The Arthropoda phylum was the most representative in abundance and richness. Regarding to richness, Trichoptera (7 families) and Diptera (6 families) followed by Ephemeroptera (3 families) were the orders that showed the greatest diversity of families, however, a low diversity with a H’≤ 1.5 nit was registered in the study area. We demonstrated through the null models, the randomization in the species associations corresponding to the three analyzed sites. The information provided here contributes to the understanding of the ecological patterns of the invertebrate communities in the Allipén River, establishing the basis for more complex ecological studies.

Statistical Tools Driven Science Policy Interface for Strengthening Biodiversity and Ecosystem Services

In lieu of ever so evolving landscapes, there is a constant pressure on biodiversity and the myriad of ecosystem services it offers. In order to strengthen science policy interface for biodiversity and ecosystem services for conservation of human well-being, nexus between biodiversity and conservation and sustainable development varied statistical tools are applied. Science policy interface with the Science Based Target Initiative is a evolving landscapes in ecosystem based restoration framework. Aligning it with statistical tools further adds to dynamics for ecosystem management. The statistical tool includes : Good Quality of Life (GQL) = Human Wellbeing and factor is under pressure and indicated as P* - Percentage of undernourished populace ; Nature Contributions to People (NCP) = Ecosystem Goods Services - impacted where in two factors are considered – being at risk, not at risk, unknown level of risk extinction.

Evaluating Moderating Effect of Growth Need Intent on Relationship between Job Characteristics and Job Satisfaction amongst Garments Industry Workers in Pakistan

Purpose: The purpose of this research is to analyze the correlation between the job characteristics and satisfaction among production workers in the garments sector assembly line and also to examine the moderating impact of growth need intent on both variables. The five job characteristics were employed in this research. Design/Methodology/Approach: This research was carried out in seven garment factories in Lahore. Data has been collected from production workers of different departments; cutting, sewing, pattern making, washing, pressing, packaging, and quality checking of randomly selected factories. A structured questionnaire was used for data collection. Considering the sample size estimation, the ratio has not to be below 1:5. (Hair, Black, Babin & Anderson, 2010) and 125 have been selected by a convenient method of sampling. Smart PLS has been used as a statistical tool for data processing and testing the hypothesis. Findings: The research suggests two important findings. Firstly, the job characteristics significantly affect job satisfaction. Secondly, it shows that the relationship between job characteristics and satisfaction is significantly moderated by growth need intent. Implications/Originality/Value: This research will add value to the existing knowledge base and serve as a guideline for HR policymakers in the textile & garments industry to recognize the needs for the development of their workers.

In vivo anti-inflammatory activity of rhizome of Drynaria quercifolia (L.) J. Sm.

Inflammation is found as a common pathogenic process in many of the chronic diseases. To manage them drugs having multiple active principles is needed. Here comes the importance of easily available, potent herbal medicines. Drynaria quercifolia (L.) J. Sm., is a medicinal fern and its rhizome is an ingredient of some Ayurvedic formulations with inflammation. Through present study in vivo analysis of powder (choorna) of the drug were done. Wistar Albino rats were used for the purpose. One group was control (no treatment) and the other three were treated groups given with the suspension of powdered drug in half the calculated effective dose (0.108 gm/200 gm b. Wt.), calculated effective dose (0.216gm/200 gm b. Wt.) and double the calculated effective dose (0.432 gm/200 gm b. Wt.). Repeated measures ANNOVA with Tukey’s post hoc analysis was used as statistical tool to analyse results within the group and one way ANNOVA with Tukey’s post hoc analysis was used for between group analysis. In all the three treated groups significant reduction in paw oedema noted at 2nd hour and maximum reduction at 4th hour after drug administration. But a highly significant reduction in paw oedema at shortest time after drug intake was produced by group administered with double the calculated effective dose of the drug. This showed dose dependent anti-inflammatory action of powder of rhizome of Drynaria quercifolia (L.) J. Sm. This activity can be due to the presence of anti-inflammatory phytoconstituents in the rhizome such as naringin, quercetin, friedelin, betasitosterol, etc.

Determination of the Connectedness of Land Use, Land Cover Change to Water Quality Status of a Shallow Lake: A Case of Lake Kyoga Basin, Uganda

Catchments for aquatic ecosystems connect to the water quality of those waterbodies. Land use land cover change activities in the catchments, therefore, play a significant role in determining the water quality of the waterbodies. Research on the relationship between land use and land cover changes and water quality has gained global prominence. Therefore, this study aimed at determining land use, land cover changes in the catchments of L. Kyoga basin, and assessing their connectedness to the lake’s water quality. The GIS software was used to determine eight major land use and land cover changes for 2000, 2010, and 2020. Meanwhile, water quality data was obtained through both secondary and primary sources. Spearman correlation statistical tool in SPSS was used to correlate the land use, land cover changes, and water quality changes over the two-decade study period. The results showed that different land use and land cover activities strongly correlated with particular water quality parameters. For example, agriculture correlated strongly with nutrients like TP, TN, and nitrates and turbidity, TSS, BOD, and temp. The correlation with nitrates was statistically significant at 0.01 confidence limit. The findings of this study agreed with what other authors had found in different parts of the world. The results show that to manage the water quality of L. Kyoga, management of land use, land cover activities in the catchment should be prioritized. Therefore, the results are helpful to decision and policy makers and relevant stakeholders responsible for water management.

Customers’ Perception towards CRM Practices in reference to Organized Retail in India

Retailing being one of the fastest growing sectors is facing tremendous competition from domestic as well as foreign players. Customer retention is an area of serious concern for online as well as offline retailers in the Indian economy, driving players in the Indian business scenario to bring radical change in their CRM practices which affects their customers perception. Retailers are highly concerned in identifying the key drivers of service execution that model customer shopping satisfaction and enhance loyalty. Customer satisfaction & loyalty is an outcome of sound customer relationship management practices. Thus, to ensure the prolong survival in the highly aggressive retail business environment customer centric approach is hour’s need. This paper critically analyses Customer’s perception towards CRM practices with reference to organized retail in India. Major parameters such as reliability, product attributes, customer service, convenience and ambience are identified to evaluate the customer perception towards CRM practices. The relevance of each parameter is analyzed with special reference to both the formats of organized retailing i.e., online & offline. For in-depth analysis of each parameter in both the formats of retail, they are further divided into sub-parameters. A survey is conducted for collecting data about customers perception towards these parameters. A statistical tool two-way ANOVA is used to analyze the variation in customer perception between online and offline retail. Based on analysis and major findings of research a conceptual model is also being proposed to get a pictorial view of how these parameters are affecting customers perception towards online & offline retail.

Service Quality in Natural Gas Distribution: A Study

Purpose: Using the SERVQUAL model in the Natural Gas Distribution business context, the research paper examines and compares the quality of service parameters of two City Gas Distribution (CGD) companies engaged in Piped Natural Gas (PNG) distribution- one from public and other from the private sector. Research Design/Approach: Mapping of various activities pertaining to domestic (household) PNG service on the SERVQUAL dimensions was undertaken. Based on the mapping, a relevant data collection tool was deployed to collect the data on PNG service quality parameters from the respondents, who were current consumers of these companies. Hypotheses regarding various components of SERVQUAL model were tested towards the comparison of service quality of these companies. Data were analyzed by employing an appropriate statistical tool. Findings: Statistical results reveal a significant difference between the companies in terms of the quality of services offered by them. Interpretation of study results, managerial implications and suggestions have been discussed in the paper. Practical Implications: The study shall help in designing and implementing the quality of service parameters and subsequently devising or revising Service Level Agreements (SLA) for the domestic PNG customers of CGD companies. Originality/Value: Not much relevant research work on service quality issues has been undertaken in the CGD Sector in general and in the domestic Piped Natural Gas (PNG) sub-sector in particular. One of the outcomes of the study is also the mapping of various activities pertaining to domestic PNG service on the SERVQUAL dimensions.

The Classification of Heartbeats from Two-Channel ECG Signals Using Layered Hidden Markov Model

Purpose: Cardiac arrhythmia is one of the most common heart diseases that can have serious consequences. Thus, heartbeat arrhythmias classification is very important to help diagnose and treat. To develop the automatic classification of heartbeats, recent advances in signal processing can be employed. The Hidden Markov Model (HMM) is a powerful statistical tool with the ability to learn different dynamics of the real time-series such as cardiac signals. Materials and Methods: In this study, a hierarchy of HMMs named Layered HMM (LHMM) was presented to classify heartbeats from the two-channel electrocardiograms. For training in the first layer, the morphology of the heartbeats was used as observations, while observations in the second layer were the inference results of the first layer. The performance of the proposed LHMM was evaluated in classifying three types of heartbeat arrhythmias (Atrial premature beats (A), Escape beats (E), Left bundle branch block beats (L)) using fifteen records of the MIT-BIH arrhythmia database. Furthermore, the obtained results of the proposed model were compared with other HMM generalizations. Results: The best average accuracy was achieved 97.10±1.63%. The best sensitivity of 96.8±1.24%, 98.85±0.52%, and 95.64±1.41 were obtained for A, E, and L, respectively. Furthermore, the results of the proposed method were better than other HMM generalizations. Conclusion: Extracting information from time-series dynamics by HMM-based methods has good classification results. The proposed model shows that applying a two-layered HMM can lead to better extraction of information from the observations; therefore, the classification performance of cardiac arrhythmias has been improved using LHMM.