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This study scrutinizes the intricate challenges encountered by faculty members from diverse Indian states in engineering colleges in Hyderabad, with a specific focus on Cultural Intelligence (CQ) as perceived by teachers. While CQ is conventionally esteemed for fostering multicultural adaptability, the research reveals its underutilization and the ensuing challenges in teaching adaptability. Data, which is collected from 50 faculty members via focus group discussions, indicate that administrative involvement is pivotal but often lacking, thereby exacerbating the difficulties in leveraging CQ effectively. Moreover, the present study identifies the broader cultural ramifications of this underutilization beyond the academic setting. The paper underscores an urgent need for targeted interventions, advocating for administrative-backed cultural training programs aimed at harnessing faculty CQ to augment educational effectiveness. Also, the paper identifies five major factors that impact teaching adaptability in heterogeneous classrooms, thereby contributing a novel perspective to the existing literature on multicultural education and teaching efficacy. [ABSTRACT FROM AUTHOR]

Background: India's recent increase in urbanization alongside with feminization of rural agriculture could increase the existing gender disparities in dietary diversity. With many rural men migrating to urban areas, women have increased domestic burdens as well as productive burdens such as making informed crop production decisions so household members consume a diverse diet. Given the rapid and recent onset of this phenomenon, there is a need to explore gender differentials in diet diversity across urban and rural areas to assess if certain populations are being disproportionately impacted by this trend. There are limited established quantitative studies discussing this gender disparity with respect to urbanization. Therefore, this paper compares dietary diversity among adult men, adult women, adolescent males, and adolescent females in urban and peri-urban locations. The authors also assess if various sociodemographic factors correlate with dietary diversity. Methods: Analyses were conducted on dietary diversity data collected by the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) from selected urban (1108 individuals) and peri-urban (808 individuals) locations of Hyderabad, India. The total sample size of the population is n = 1816: 660 adult males, 662 adult females, 205 adolescent males, and 289 adolescent females. Results: Adult women and adolescent females have a higher diet disparity between peri-urban and urban areas when compared to adult males and adolescent males. Multivariate analyses followed by post hoc multiple comparisons testing further support that peri-urban adult women consume a less diverse diet compared to their urban counterparts and less than other peri-urban adult men and adolescent women. It was also found that marital status, type of household card owned, and the highest degree of education are statistically significant correlators of an individual's dietary diversity. Conclusions: Given that urbanization could negatively impact already vulnerable populations such as peri-urban adult women, who play a key role in children's nutrition, it is important to provide support to these populations. This paper suggests it is possible to do so through government subsidization of peri-urban farmers to grow more diverse crops, fortifying easily accessible foods with commonly lacking micronutrients, including Vitamin A, folic acid, and iron, market access, and affordable prices. [ABSTRACT FROM AUTHOR]

The present paper attempts to see the women and child worker in the old city of Hyderabad in the Bangle industry. Women make up a sizable portion of India's labour force, yet they are paid less and have less secure jobs than men. As a result, many of these mothers choose to earn an income for their families by working from home. Women who work in the informal sector work with minimum pay and hence the girl child is an easy prey to assist the mother in supplementing the income and helping in the household chores so that more time is left to pursue the trade for an income. Our sample includes 100 women respondents and 150 girls. Being in the unregulated, home-based informal sector has made it challenging to organize the employees, leaving the bulk of bangle-makers in precarious positions both at work and at home. The increasing number of children, especially girls, who are taking part in the production of bangles is also a cause for alarm. It would appear that the piece rate method of payment and the fact that the work may be done from home encourage the participation of family members, including children, in the labour force. [ABSTRACT FROM AUTHOR]

The essay utilises autoethnography while adopting an explorative research strategy. The PhD thesis project on randonneuring served as the inspiration for the paper. The article details the complete process in a chronological way. It is a reflection on the fieldwork experiences. The fieldwork was carried out between August 2015 and October 2018 in Hyderabad, India. It is divided into three stages. The paper presents a detailed descriptive account of how the researcher was moving through different stages of the study. In stage 1, I describe how I stepped into the cycling world. This stage is marked by learning about the cycle and getting acquainted with the city's cycling community. This includes more of commuting and leisure riding. In stage 2, I participate in local races and venture into longer rides and eventually become a randonneur, i.e., further improving my skills, training and gauging my fitness level. In Stage 3, I have participated in the randonneuring events as a randonneur completing the Super Randonneur series (i.e., 200, 300, 400 and 600kms rides). The article provides specific anecdotes to build a better context for understanding the subjective experience of the cycling culture. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to explore the impact of students' perceived academic stress on the quality of campus life of business schools in South India. A survey was conducted among the first and final-year MBA students from Chennai, Bengaluru, and Hyderabad business schools. Structured questionnaires designed through Google Forms were used to gather the primary data from a sample of 386 students. A cross-sectional study examined the significant academic stressors and how students perceive and manage these stressors. In addition, this paper also analyzes the impact of academic stress on the quality of campus life by examining the physical health, environmental health, mental health, and social relationships among students. Data was collected thrice in a semester, i.e., during the beginning of the semester, mid-semester, and end of the semester during examinations. The research outcome shows that all the academic stress factors identified in the study (stress perception, stressors, and stress management) significantly relate to the academic stress construct. Similarly, physical, environmental, and mental health and social relationship are positively associated with the quality of campus life. The results of the SEM also portray that the academic stress prevailing in the business schools results in negative perceptions towards the quality of campus life among the student community [ABSTRACT FROM AUTHOR]

In India, English occupies the position of a foreign language and is taught in many schools as a second/third language. However, a lot of importance is attached to the mastery of English, and it is necessary to determine the status of mastery of Listening, Speaking, Reading and Writing (LSRW) skills and the lacunae, if any. Of all the skills, writing is the most used skill by students pursuing higher education. This paper aims to find out the status of the overall writing ability and its elements in students studying English as a Foreign/Third Language. It also aims to diagnose the lacunae in the writing ability of the students studying English as a Foreign Language (EFL). The variables selected were gender, type of school (government/private) and medium of instruction. The results showed that there was no difference in students’ writing ability based on gender. The writing ability of private school students was better than that of government school students, and the writing ability of English medium students was better than that of Urdu and Telugu medium students. There was no significant difference in the writing ability of Urdu and Telugu medium students. In India, English occupies the position of a foreign language and is taught in many schools as a second/third language. However, a lot of importance is attached to the mastery of English, and it is necessary to determine the status of mastery of Listening, Speaking, Reading and Writing (LSRW) skills and the lacunae, if any. Of all the skills, writing is the most used skill by students pursuing higher education. This paper aims to find out the status of the overall writing ability and its elements in students studying English as a Foreign/Third Language. It also aims to diagnose the lacunae in the writing ability of the students studying English as a Foreign Language (EFL). The variables selected were gender, type of school (government/private) and medium of instruction. The results showed that there was no difference in students’ writing ability based on gender. The writing ability of private school students was better than that of government school students, and the writing ability of English medium students was better than that of Urdu and Telugu medium students. There was no significant difference in the writing ability of Urdu and Telugu medium students. [ABSTRACT FROM AUTHOR]

Purpose: The primary purpose of this research paper is to evaluate e-learning among employees of Information Technology (IT) companies based in Hyderabad, India. Design/methodology/approach: A survey was undertaken among the employees from different IT companies based in Hyderabad, India, to gauge the perception towards e-learning. The participants were selected randomly. The evaluation is based on a few factors: convenience, usefulness, course content, quality, effectiveness and benefits for employees and organizations. The responses were recorded online through a structured questionnaire. In total, 237 responses have been collected for this present study, of which 227 questionnaires were used for analysis. Findings: The surveyed employees perceived that e-learning helped them enhance their workplace competency in a flexible but effective manner. The e-learning also empowered the learners and ultimately contributed to the enhancement of organizational performance in some ways. Research limitations/implications: Limitation of the study – by examining the pris study was confined to employees working with IT companies based in Hyderabad City, India. The data is collected online, and there may be some insufficient responses. Implications of the study – the study results show a deep insight into the critical aspects of e-learning as a tool for employee training for the benefit of employees and organizational development. The surveyed respondents from the IT sector at Hyderabad perceived that keys to successful e-learning programs should give due consideration towards availability of internet bandwidth, making the course more interactive, providing more choices to the learners and user-friendly and personalized learning experience. The study also shows that the e-learning programs primarily benefit the employees as well as the organization in a manner, namely, improved productivity, helping to achieve business objectives of the firm, growth and advancement to the employees and enhancing the job-related knowledge. The study also discovered that e-learning improves employees' opportunities for professional growth and advancement inside and outside the organization by assisting them in learning new skills and enhancing job-related information. Practical implications: The internet penetration in recent years, as well as post-Covid-19, has given rise to online learning in the education and corporate sectors. The emergence of online or e-learning has been gaining ground in the corporate world by replacing the existing face-to-face or physical training model because of the cost factor and flexible learning to the learners. E-learning improves the learner's ability to adapt to the company's constantly changing business environment, which in turn helps the company increase departmental productivity and, ultimately, achieve its overall business goals. Social implications: The e-learning also empowered the learners and ultimately contributed to the enhancement of organizational performance in some ways. The e-learning also empowers the learner to perform better at his workplace and at the same time moving on the social ladder as the learning makes him/her confident at the job market. Originality/value: This study provides a valuable understanding of employee perceptions on the adoption and effectiveness of e-learning, which ultimately improves the benefits of the training and development department in realizing and enhancing the quality in corporate companies. [ABSTRACT FROM AUTHOR]

Trauma is a global challenge and India has one of the highest trauma deaths in the world. Despite the United Nations' target to halve the global number of deaths and injuries from road traffic crashes by 2030, death tolls from road traffic injuries (RTI) are rising in India. In the pediatric age group, falls from height add to the burden of trauma. Uncontrolled bleeding from exsanguination on scene is estimated to account for nearly 40% of RTI trauma related mortality. Stopping the bleeding in the first few minutes is crucial for meaningful survival and hence the role of training lay public who can reach the scene in minutes. Active bleeding control (ABC) pilot research project to simulation train the bystanders to stop the bleed showed promising outcomes in Hyderabad, India. This paper describes the ABC project and discusses the role of pediatricians in training the public to reduce morbidity and mortality from uncontrolled bleeding at the trauma scene. [ABSTRACT FROM AUTHOR]

Purpose: COVID-19 disrupted the usual way of working for many people across the globe, making full-time work from home and hybrid models two popular work arrangements. Despite the proliferation and high acceptance of the hybrid model, very little research has focused on the same. This study aims to compare the impact of transitions caused by remote work on work disengagement under two settings: remote work and hybrid model. Design/methodology/approach: The data is collected from three corporate hubs in India: Hyderabad, Gurgaon and Bangalore. This study's respondents represent two working models: full-time work from home and a hybrid model. Responses were collected using Google forms-based questionnaire, which resulted in the following usable responses: 356 (hybrid) and 398 (work from home). Findings: The findings reveal that the structural model for the hybrid sector explained 11% of the variance in work disengagement, while the same for work from home model accounted for 20% of the variance in work disengagement. The authors also tested for the moderation of individual resilience between work-home and home-to-work conflicts and home-to-work transitions and work-to-home conflict under full-time work-from and hybrid models. Based on 356 respondents from hybrid category and 398 from work from home, the study found that employees experience less work-to-home and home-to-work conflicts in the hybrid model and employees experience more work-to-home and home-to-work conflicts in the full-time work from home model. Originality/value: The study is also the first to examine the moderating role of individual resilience as a tool to bounce back and handle conflicts. As the full-time work from home model leads to more work-to-home and home-to-work conflicts, individuals have more scope to exhibit resilience, and thus, the moderating relationship is stronger in the full-time work from home model. The paper offers theoretical and managerial implications. [ABSTRACT FROM AUTHOR]

A novel 120 Gbps free space optics (FSO) is presented in this paper based on integrating three multiplexing techniques, namely, orthogonal frequency division multiplexing (OFDM), polarization division multiplexing (PDM), and optical code division multiple access (OCDMA). For PDM, two states are utilized, each of which carries three different OCDMA channels assigned with distinct Identity Column Shift Matrix (ISCM) code sequences. A 20 Gbps of information is modulated by OFDM and transmitted on each channel. The impact of inclement weather conditions on the FSO channel is investigated, focusing on hazy, rainy, and foggy weather. The performance evaluation includes analyzing parameters such as the bit error rate (BER), maximum FSO range, received optical power (ROP), and the constellation diagram. Furthermore, the applicability of this model in practical settings is discussed for two distinct cities: Alexandria, Egypt, and Hyderabad, India; each is characterized by unique geographical locations and correspondingly diverse weather conditions. The simulation results assure that the information signal can propagate over longer ranges of 5.8 and 5 km when applied in Alexandria and in the presence of light haze (LH), respectively, with BER below 10 - 3 and ROP ∼ −11.8 dBm. In contrast, the lower range of 0.91 km occurs in the presence of heavy fog (HF) due to the large attenuation caused by this weather condition. Accordingly, the proposed 120 Gbps (2 polarization states; each has 3 channels, and each channel carries 20 Gbps of information) FSO model is suggested to be used in high-speed transmission networks. [ABSTRACT FROM AUTHOR]

With advances in social development and economic growth, remote sensing technology has been attracted greater attention in monitoring the earth data using radar and optical sensors on satellite platforms for a wide range of applications in different fields such as coastal, hazard and natural resources. Satellite images could play a greater role in improving classification accuracy with high spatial resolution and rich spectral information for land cover classification. However, existing image fusion methods achieves low accuracy due to large-scale feature space. To focus on these issues, a deep learning network structure needs to classify different classes with high spatial resolution and rich spectral information to obtain higher accuracy. In this paper, a feature-based classification approach is proposed namely Multi-Fusion based Dense Transpose Convolutional layer in Fully Convolutional Network with Feature Alignment framework (MF-DTCFCN) to label and categorizes the label region in Remote Sensing Images (RSI). Initially, a multi-fusion feature framework is designed by adding a point-wise addition structure to handle large-scale feature space for high-resolution images. Secondly, the optimized features are pre-trained to classify the labels comprised of the most discriminative features in the pre-training network. The density of output label maps are improved by introducing dense transpose convolution in the network. Then combine the output to the feature alignment with point-wise addition is employed to balance the different features and similarities to achieve additional performance for classification. Here, the Land Use/land Cover (LULC) satellite image dataset namely, Sentinel-2 were used to classify the urban areas of Hyderabad city, India. Experimental results depict that the MF-DTCFCN approach outperforms an accurate improvement in classification accuracy than existing methods. [ABSTRACT FROM AUTHOR]

A novel free space optics (FSO) communication system based on integration of two different multiplexing techniques i.e., orbital angular momentum (OAM) multiplexing and optical code division multiple access (OCDMA), are proposed in this paper for enhancing the transmission capacity. Four distinct OAM beams are used; each transporting 10 Gbps information of three different OCDMA channels. These channels are assigned with diagonal permutation shift (DPS) code. Various atmospheric conditions are considered in evaluating the performance of our suggested design in FSO communication system. These weather conditions are snowy and dusty in addition to the average intensity rainfall rates in Saudi Arabia cities (Riyadh and Jeddah) and Indian cities (Hyderabad, Pune, Chennai, and Mumbai). Received optical power (ROP), Quality (Q) factor, maximum FSO link range, and eye diagrams are used for evaluating the performance. The simulation results show successful transmission of 4 OAM × 3 OCDMA channels × 10 Gbps = 120 Gbps overall capacity with good ROP, Q-factor, and BER values. The maximum FSO link range achieved is 600 m under wet snow (WS), 140 m under dry snow (DS), and 400, 132, and 52 m, respectively, under low dust (LD), medium dust (MD), and heavy dust (HD) storms. Consequently, this proposed FSO transmission model is suggested to be used as high-speed connectivity for end users in adverse weather conditions. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had many impacts on the environment worldwide. This paper examines the effects of this pandemic on the air pollution in the four major cities (Delhi, Kolkata, Mumbai, and Hyderabad) of India. The research reveals the impact on the levels of the various pollutants and the Air Quality Index. This paper contrasts the four phases' behaviour during the nationwide lockdown, imposed to control the pandemic, and reports the behaviour of air pollutants and the air quality index compared to 2019. [ABSTRACT FROM AUTHOR]

High Blood Pressure (HBP) is one of the major significant medical concerns of many people around the globe today. HBP is so common symptom many people across the globe are experiencing, irrespective of age, gender, region, and religion. HBP prediction ahead of time can help the person to avoid the consequences such as heart stroke, kidney failure, eye damage, sexual dysfunction, and even death. HBP prediction in advance is a challenging issue as it is associated with many biopsychosocial factors. Heuristic and meta-heuristic-based Machine Learning Models (MLM) exclusively supervised machine learning techniques are becoming part and parcel of medical data diagnosis. However, the reliability of outcome, usability, and understandability of such stand-alone models in processing medical data in real-time are not up to the mark. To overcome such limitations, in this paper we proposed an intelligent majority voting and heuristic-based user-friendly hybrid classifier to predict HBP (An Intelli MOC). The model considers AA-AOC (Anger level, Anxiety level-Age, Obesity level, and Cholesterol level) of a person to predict the HBP of a person. The proposed model is said to be majority vote-based and hybrid as it considers the output of three classifiers and assigns the count for each decision class. The model is said to be heuristic-based as it uses a mathematical and Fuzzy approach in obtaining the fuzzified values of each attribute in AA-AOC. The experiments are conducted on real-time data set collected from a medical diagnostic center Doctor C, Hyderabad, India. The model is executed on 1200 data records, 65% of data is used to train the model and 35% of data is used to test the model. The output of the model proved that the proposed model outperformed in terms of accuracy, precision, recall, and F-measure compared with all available state-of-the-art, existing MLM. [ABSTRACT FROM AUTHOR]

This paper presents the step-by-step development and implementation of real-time data transmission from a distant Observatory. Using Python programming language, we have developed an algorithm for automated data transmission of high resolution real-time magnetic data from Choutuppal (CPL) and Hyderabad (HYB), India to INTERMAGNET Edinburgh GIN, with minimal internet services. We have designed a system to transfer the data in a secured and encrypted pattern with SSH keys and save the same dataset in the local server at CSIR-NGRI. Both the Observatories data are transmitted to GIN in real-time with a time frame of less than 300 s. After successfully transmitting real-time 1 min geomagnetic data from CPL and HYB Observatories to Edinburgh GIN, CPL's 1 s real-time data is also initiated and is one of the first Indian observatories to transmit real-time 1 s data to GIN. The details of algorithm development, function libraries and the challenges faced for 1 s and 1 min data transmission at both the Observatories are discussed. [ABSTRACT FROM AUTHOR]

This paper revisits the violent annexation of the erstwhile princely state of Hyderabad by the Indian army in 1948 as an inaugural moment of dispossession to reconstruct Hyderabad's twentieth century past along the axes of Muslim belonging and memory. I argue that we must situate twentieth and twenty-first century Hyderabadi Muslim migration in relation to Partition-related displacements and attempts to overcome them through economic conditions provided by migration. The partition of India prompted waves of migration—such as the later migration of Hyderabadi Muslims to the Persian Gulf in the wake of 1970s oil boom—and their sense of displacement persisted long past the mid-twentieth century, reshaping Muslim notions of belonging. The use of the nation-state as the dominant framework to analyze these shifts is insufficient for understanding Hyderabadi Muslims' sense of belonging and citizenship, which must be also contextualized in terms of upward class mobility along the axes of global and local contexts. [ABSTRACT FROM AUTHOR]

In this paper the K-Nearest Neighbor (KNN) model which is one of machine learning (ML) algorithm is applied to distinguish between the four distinct Hermite Gaussian (HG) beams (HG00, HG01, HG02, and HG03) in mode division multiplexed (MDM)-free space optics (FSO) communication system. First, the performance of the FSO system using these different HG beams is investigated for rainy weather conditions in various Indian cities having distinct geographical locations. Transmission performance is evaluated in terms of quality (Q)-factor, signal-to-noise ratio (SNR), bit error rate (BER), and eye diagrams. Then, the values of the BER for the different HG beams are applied to the KNN ML model as to classify between them. HG modes are used for capacity enhancement. Results indicate that 80 Gbps can be transmitted over 1000 m in Hyderabad, 800 m in Pune, 580 m in Chennai, and 475 m in Mumbai at log (BER) ~ 10 - 15 , Q-factor less than 8, and SNR ~ 10 dB. Additionally, the K-Nearest Neighbor (KNN) ML model shows 94% classification accuracy between four HG beams. [ABSTRACT FROM AUTHOR]

Now-a-days managing the traffic in major cities is a challenging task. One of the ways is to construct flyovers over intersections and to ensure smooth signal less traffic flow. The design philosophy has now become the design norm for most of the structural systems. To provide Reinforced Concrete Flyover Bridge is very essential in all major cities like Hyderabad, Chennai, and Mumbai etc. Our study is mainly focused on design and analysis of concrete bridge pier. The present study focuses on pier of an elevated bridge which is conventionally based on force based approach. The main focus of the present study is to perform an optimal design of a reinforced concrete pier which carries the deck of the flyover. The traffic flow is taken for 2 lane flyover on each side of the median. An Isogeometric topology optimization algorithm is used to determine the outline of the bridge pier. The bridge pier is then modeled in AutoCAD and imported to IDEA StatiCa® software. The reinforcement is calculated using Indian Standard (IS) code with all the necessary checks. The distribution of material within the given domain is determined. Shear strength, bending strength and crushing strength are calculated manually for checking strength compatibility. The static analysis and buckling analysis is performed using Idea Statica® software and the results are obtained. [ABSTRACT FROM AUTHOR]

Disturbance to the moving traffic, such as on-street parking and bus stop on carriageway normally called as side friction in the literature, is one of the major problems that impact the vehicular speed on urban arterials in developing countries like India. Regression model to study the mode-wise vehicular speeds using side friction and other influencing variables faces the problem of multicollinearity as there is a strong correlation between the independent variables which results in high R2 and high p values. Instead of dropping the highly correlated variables which is the conventional practice to deal with multicollinearity, we proposed an approach of taking a linear combination and ratio of independent variables. To test the applicability of the proposed approach, traffic data from five locations in Hyderabad and Vellore in India having a wide variety of geometric and traffic characteristics with one or more side frictions were collected and regression models were built. It was found that the proposed approach of taking linear combination and ratio worked very well as the models exhibited a high R2, low p values and low variance inflation factor. The regression models also forecast speeds with good and reasonable accuracy. For better understanding of the impact of side friction, the present study proposed an index called side friction index and it was found that the number of side friction elements and their impact are directly proportional. Also, the impact is not uniform across the different vehicle types. Though the present study focussed on side friction problem, the approach that we proposed in this paper to deal with multicollinearity can be applied in other fields as well. [ABSTRACT FROM AUTHOR]

Total electron data (TEC) from GPS nowadays can be used as a tool for understanding the space weather phenomena. The development of prediction model for TEC is quiet crucial and challenging due to the dynamic behavior of the ionosphere, since it depends on different factors such as seasonal, diurnal and spatial variations, solar geomagnetic conditions etc. In this paper, an attempt is made for predicting the GPS derived TEC values for different GNSS stations over India using a hybrid method based on Ensemble empirical mode decomposition (EEMD) and Long Short-Term Memory (LSTM) deep learning method. The daily TEC time series data from the IISc Bangalore (Latitude 13.021, Longitude 77.570), Lucknow (Latitude 26.912, Longitude 80.956) and Hyderabad (Latitude 17.417, Longitude 78.551) stations over India during the period 2008 to 2015 of solar cycle 23 and 24 is used for analysis. The assessment of model performance for testing predicted output compared with LSTM and EMD-LSTM models, and their comparison results show that the hybrid EEMD-LSTM model presents better than the other models. [ABSTRACT FROM AUTHOR]

How does data visibility affect vulnerable communities that face uncertainty over land tenure? Can data justice be realised in settings of acute resource injustice? These are the overarching questions that our case study interrogates by opening up the black box of the community in the volatile and fast-transforming peri-urban fringe of Hyderabad, India. We examine the unfolding of data and information processes through the lens of enumeration and community mapping exercises conducted in a low-income neighbourhood. We argue that the realisation of data justice is mediated by 'information politics', i.e., the ways in which informational resources, as well as the risks and rewards associated with them, are distributed across individual actors and identity groups within the community. The democratising potential of emerging digital technologies is severely constrained by structural inequities across gender, caste, class, and even linguistic lines. Our case study underlines the importance of such a structural understanding of data justice and also suggests directions for embedding justice in data processes. Our findings reveal an arena of stark informational disparities between vulnerable, indigent populations and the increasingly sophisticated digital data apparatuses used to encode them. Efforts to promote data justice must take explicit cognisance of these disparities and fragmentation and recognise the internal structural differentiation of vulnerable communities. We argue for an explicit mapping of the information flows and associated information politics that characterise such settings. [ABSTRACT FROM AUTHOR]

The study encompassed the elements’ that impact the employee’s positive relationship towards the organization which is reflected in their Organizational Citizenship Behavior (OCB). The paper examines the positive employee engagement and the OCB which are interconnected with fair performance management system in the firms. The research is conducted in the recent trends of IT and ITEs employment firms which are in three metropolitan cities in India viz., Bangalore, Chennai & Hyderabad. This analysis helps to determine whether justice in performance appraisal would lead to trust in the organization and further would lead to Organizational Citizenship Behavior. The study found that by establishing a positive relationship with performance appraisal system, there is an increase in the employee’s trust inventory towards the organization. [ABSTRACT FROM AUTHOR]

This study investigates the response of solar (S) tidal signatures on the horizontal component of the geomagnetic field at two observatories in India during 1980–2002 over solar cycles (SC) 21–23: Hyderabad (HYB), located in the low-latitude region, and Ettaiyapuram (ETT), situated at the magnetic equator. HYB represents the characteristics of solar quiet (Sq), while ETT is under the equatorial electrojet (EEJ) effect. Our results show the additional information about ter (S3), and quarta-diurnal (S4) tidal signatures of Sq and EEJ, along with diurnal (S1) and semi-diurnal (S2) at both observatories. In Sq solar tide, the average amplitude of S1 tide is consistently higher than that of EEJ tide by ~ 10%. During the same period, the S2, S3, and S4 tidal signatures of Sq are weaker than EEJ by ~ 2%, 5%, and 2.5%, respectively. During solar cycle maxima, the amplitude of the Sq tide is higher in SC-21 than in SC-22 and SC-23 by ~ 13% and 16%, while SC-22 has higher EEJ tidal amplitudes than other SCs by ~ 9%. We observe that the tidal signatures of Sq and EEJ closely follow the trend of solar radio flux ( F 10.7 ), except for S4 of Sq. The Pearson correlation coefficients (P) between F 10.7 and Sq/EEJ tidal amplitudes exhibit negative to positive correlation coefficients during different phases of SCs. The solar tidal amplitudes of Sq/EEJ (S1-S4) with F 10.7 during D, E, and J seasons have varying correlation coefficients, indicating that each tide has a distinct response on the geomagnetic field. Key Points : During SC-21, stronger amplitudes of Sq solar tides are observed, for EEJ it is SC-22. The weak correlation between tidal amplitude and F 10.7 may be related to the high occurrence rate of CEJs. Except S4 of Sq tide, the remaining tidal amplitudes of Sq and EEJ follow the trend of F 10.7 . [ABSTRACT FROM AUTHOR]

„Green Marketing" is process where the manufacturers sell their products based on the impact of that product on the environment. It includes the basic features of the products, usage, or packing of the product, which have minimal impact on the environment. Increasing in the awareness among the consumers about the environment is motivating them to buy the products that are environmental friendly. The other side manufacturers are trying to design new products and process or modifying the existing products to suit the new customer and environmental requirements. Detergents are an integral part of civilised society. Though some of the detergent manufacturing companies are following green marketing strategies, like water saving detergents, there are no specific studies conducted to know the impact of these strategies on consumer buying behaviour. This study was conducted in five metro cities, Kolkata, Bangalore, Chennai, Hyderabad, and Mumbai with a sample size of 370. The study found that green marketing claims made by the detergent companies is one of the important factors that motivates the consumers to buy a particular brand. [ABSTRACT FROM AUTHOR]

Students in Hyderabad, India, explain the "freshmen's Composting Initiative", a project they undertook as a part of their environmental science course. The initiative puts a strong emphasis on problem-based learning (PBL) and real-world sustainability. It emphasizes the significance of giving pupils the knowledge and abilities necessary for environmental responsibility as well as the connection between human wellbeing and the natural world. The all-India Council for Technical Education's (AICTE) decision to include "Environmental Science" in the first-year B.Tech. Curriculum served as the impetus for the effort. Although sustainability is emphasized in policies, there is frequently a gap in actual application, which this research seeks to fill. This research helps students comprehend sustainable business practices and environmental issues while also giving them a foundation for putting sustainability into reality. It illustrates the transformative potential of PBL and the part that students play in bridging the sustainability gap between theory and practice. In conclusion, the "Freshmen's Composting Initiative" shows how first-year engineering students may actively support sustainability through practical projects, aligning with the increased emphasis on environmental education and the real-world application of sustainable ideas. [ABSTRACT FROM AUTHOR]

This paper analyses the transferability of freight generation (FG) models to provide guidance on the direction of transfer, the degree of transfer, and how to determine the sample size required for new regions. A set of FG models are developed for four regions in India, i.e., Hyderabad, Jaipur, North Kerala, and Central Kerala. Models are assessed for naïve transferability across these regions to know the direction and degree of transfer. Using multidimensionality scaling, we identified new regions similar to the study regions based on geographical characteristics like population density, number of establishments, land value, road density, and seaport proximity. The identical regions are further grouped into four different clusters using the K-means clustering algorithm. In order to determine the sample size of a new region, the transferability results are interpolated to these geographically linked regions with the same demographics. This research is crucial for saving survey resources in terms of money and time. The policymakers and stakeholders can borrow the strategies already under implementation in a region with topographic similarity with the novel methodology proposed. Furthermore, industrialists can take the case study of the establishments in geographically similar regions in strategizing the resource and capacity allocation for efficient and responsive supply chain design. [ABSTRACT FROM AUTHOR]

This study developed a travel time congestion index (TTCI) keyed to the differences in actual versus desired travel times for various types of roadways, and found that the TTCI is influenced by traffic and geometric characteristics of the roadway other than volume and capacity. The TTCI provides a continuous scale for assessing the level of congestion in the network. In general, the measurement of the level of service (LOS) across the roadway sections is adopted to measure the level of congestion. However, measuring LOS alone does not provide better insight into the reasons for congestion other than the volume-to-capacity ratio. Therefore, we developed the TTCI by employing traffic and geometric parameters to measure the congestion along the roadways on the urban road network. In addition to the development of the TTCI, level of service is measured and compared with the TTCI values for the selected road sections. The results indicate that employing all the variables together in a single technique yields much better and more-reliable values for congestion indexes. The results indicate that providing grade-separated intersections reduces traffic congestion to a great extent. The results also were found to be in line with the field conditions. This study also proposes using TTCI values to design the cordon lines for delaminating the congestion zones and estimating the level of service of the roadway. The findings of this study can be used by policymakers and transportation planners to design effective countermeasures for decongesting urban roadways. [ABSTRACT FROM AUTHOR]

The escalating prevalence of Type 2 Diabetes Mellitus (T2DM) globally necessitates a deeper understanding of its complex metabolic interactions, particularly concerning homocysteine, a known cardiovascular risk marker. This study aims to elucidate the role of homocysteine in the management of hyperglycemia in T2DM patients. Conducted as a cross-sectional study at Osmania Hospital, Hyderabad, India, it involved 30 T2DM patients without prior cardiovascular disease (CVD) complications and 30 age and sex-matched controls. Participants were subjected to comprehensive blood analyses to measure homocysteine, HbA1C, fasting, and post-lunch blood sugar levels. The study employed an independent sample t-test to determine significant differences in these biochemical parameters between T2DM patients and controls, with a significance threshold set at <0.05 and <0.001. Additionally, Pearson Correlation tests were applied to assess the relationship between homocysteine levels and the glycemic profile of the participants. The findings of this study are pivotal in understanding the interplay between homocysteine and hyperglycemia in T2DM. They offer insights into the potential role of homocysteine in T2DM management and its implications for cardiovascular risk in these patients. The results are expected to contribute to the evolving landscape of T2DM management, highlighting the importance of considering homocysteine levels in the holistic care and treatment strategies for T2DM patients. This study not only adds to the existing body of knowledge but also opens avenues for future research in this domain, particularly in developing targeted interventions for better management of T2DM and associated risks. [ABSTRACT FROM AUTHOR]

The fractures of the hyoid bone in the neck are one of the important indicators of any pressure over the neck. The present study includes a huge sample size of mechanical asphyxiation deaths (791 cases) to study the incidence of hyoid bone fractures in hanging, ligature strangulation, and throttling. Fractures of the hyoid bone were noticed in a total of 12 cases, 9 male and 3 female with 33.33% incidence in the 41-50 years age group. Throttling dominated the strangulation group in our study with a share of 42.85%. A total of 6 (5 male, 1 female) cases showed hyoid bone fractures in the strangulation group wherein the predominant incidence is seen in 41-50 years(50%). In our study, right cornu fractures are frequent in hanging and throttling. Except for one outward compression fracture in a hanging instance, all of the fractures identified in our investigation are inward compression fractures. The present study adds to the existing literature that hyoid bone fractures are less common in hanging than throttling and any fracture of hyoid bone is common after the age of 40 years because of calcification. [ABSTRACT FROM AUTHOR]

First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping earlycareer researchers promote themselves alongside their papers. Ajay Singh is first author on ' Local DNA synthesis is critical for DNA repair during oocyte maturation', published in JCS. Ajay is a postdoc in the lab of Dr H. B. D. Prasada Rao at the National Institute of Animal Biotechnology, Hyderabad, India, investigating the quality of and lifespan-determining factors of mature oocytes in mammals. [ABSTRACT FROM AUTHOR]

Global climate change is anticipated to have a profound impact on drought occurrences, leading to detrimental consequences for the environment, socioeconomic relations, and ecosystem services. In order to evaluate the extent of drought impact, a comprehensive study was conducted in the Hyderabad–Karnataka region, India. Precipitation data from 31 stations spanning a 50-year period (1967–2017) were analyzed using the standardized precipitation index (SPI) based on gamma distribution. The findings reveal that approximately 15% of the assessed years of experienced drought conditions, with a range of influence between 41% and 76% under SPI_3, and between 43% and 72% under SPI_6. Examining the timescale magnitude frequency provided insights into variations in the severity of drought events across different locations and timescales. Notably, the Ballari (−8.77), Chitapur (−8.22), and Aland (−7.40) regions exhibited the most significant magnitudes of drought events for SPI_3 with a 5-year return period. The heightened risk of recurrent droughts in the study area emphasizes the necessity of integrating SPI in decision-making processes, as such integration can markedly contribute to the development of reliable and sustainable long-term water management strategies at regional and national levels. [ABSTRACT FROM AUTHOR]

To investigate the prevalence, causes and impact of unilateral visual impairment (UVI) on visual function in the elderly in 'home for the aged' in Hyderabad, India. Participants aged ≥60 years were recruited from 41 'homes for the aged'. All participants had complete eye examinations including visual acuity assessment, refraction, slit-lamp and fundus examination. Unilateral visual impairment (UVI) was defined as presenting VA worse than 6/18 in one eye and presenting VA 6/18 or better in the other eye. Indian Vision Function Questionnaire (INDVFQ) was used for assessing visual functioning. Of the total 1,513 elderly participants enumerated, 1,182 (78.1%) were examined. After excluding 356 participants with VI in the better eye, data were analysed for the remaining 826 participants. The mean age (standard deviation) of these participants was 74.4 ± 8.4 years; 525 (63.6%) were women, and 111 (13.4%) had no schooling. The prevalence of unilateral VI was 38.1% (95% CI: 34.8–41.5; n = 315). Cataract (37.5%; n = 118) was the leading cause of UVI followed by Uncorrected Refractive Error (22.2%; n = 70) and posterior capsular opacification (18.4%; n = 58). The overall INDVFQ score was higher among those with UVI than those without UVI (37.7 versus 34.5; p <.01) suggestive of poor visual functioning. UVI was common and largely due to avoidable causes among the elderly in residential care with an adverse impact on visual functioning. Screening for vision loss in 'homes for the aged' and the provision of appropriate services should become a routine practice to achieve the goal of healthy aging in India. [ABSTRACT FROM AUTHOR]

Satellite-based rainfall estimates are a great resource for data-scarce regions, including urban regions, because of its finer resolution. Integrated Multi-satellitE Retrievals for GPM (IMERG) is a widely used product and is evaluated at a city scale for the Hyderabad region using two different ground truths, i.e., India Meteorological Department (IMD) gridded rainfall and Telangana State Development Planning Society (TSDPS) automatic weather station (AWS) measured rainfall. The IMERG rainfall estimates are evaluated on multiple spatial and temporal scales as well as on a rainfall event scale. Both continuous and categorical verification metrics suggest good performance of IMERG on the daily scale; however, relatively decreased performance was observed on the hourly scale. Underestimated and overestimated IMERG estimates with respect to IMD gridded rainfall and AWS measured rainfall, respectively, suggest the performance depends on type of ground truth. Unlike categorical metrics, RMSE and PBIAS have a pattern implying a systematic error with respect to rainfall amount. Further, sample size, diurnal variations, and season are found to have a role in IMERG estimates' performance. Temporal aggregation of hourly to daily time scales showed the improved IMERG performance; however, no spatial-scale dependence was observed among zonewise and Hyderabad region–wise rainfall estimates. Comparison of raw and bias-corrected IMERG rainfall-based intensity–duration–frequency (IDF) curves with corresponding hourly rain gauge IDF curves showcases the value addition via simple bias correction techniques. Overall, the study suggests the IMERG estimates can be used as an alternative data source, and it can be further improved by modifying the retrieval algorithm. Significance Statement: Many urban regions are typically data sparse, which limits scientific understanding and reliable engineering designs of various urban hydrometeorology-relevant tasks, including climatological and extreme rainfall characterization, flood hazard assessment, and stormwater management systems. Satellite rainfall estimates come as a great resource and Integrated Multi-satellitE Retrievals for GPM (IMERG) acts as a best alternative. The Hyderabad region, the sixth-largest metropolitan area in India, is selected to analyze the widely used satellite estimates, i.e., retrievals for GPM. The study observed inaccuracies in the IMERG estimates that varied with rainfall magnitudes and space and time scales; nonetheless, the estimates can be used as an alternative data source for decision-making such as whether rain exceeds a certain threshold or not. [ABSTRACT FROM AUTHOR]

During seed health testing of 160 accessions of safflower, we observed some fungal growth on seed surface of four accessions i.e., IC337954, IC338197, EC182199 and EC181301 which were received from Hyderabad, Telangana, India for long‐term conservation in the National Genebank, ICAR‐National Bureau of Plant Genetic Resources, New Delhi, India. The associated fungus was morphologically identified as Diaporthe helianthi. Later on, the identity was confirmed as Diaporthe helianthi (Desm.) Grove by the sequencing of internal transcribed spacer (ITS) region (GenBank Id: KM979906.1). During seed health testing, seed infection of 30.0 to 70.0 per cent was recorded with no seed germination in infected seeds. Previous findings revealed that D. helianthi is host‐specific pathogen causing stem canker to sunflower only and the fungus is seed‐borne. As a destructive pathogen causing substantial yield losses, especially to sunflower, it may be a serious threat to safflower cultivation in the country and anywhere else. Therefore, the detection and identification of D. helianthi can be helpful in alarming the threat at an early stage thereby minimizing the probable damage to safflower cultivation in near future. [ABSTRACT FROM AUTHOR]

In this article, I track a housing scheme introduced in Hyderabad, India, to redevelop slums (in situ) into two-bedroom apartments. Drawing on ethnographic fieldwork, I argue that existing forms of governance cyclically enact a suspension of poor people's lives and often dispossess the poor of one set of rights in the process of delivering another set. In their own descriptions of these schemes, displaced communities emphatically account for the forms of suffering they repeatedly incur, which are unaccounted for in the records of the state. In their experience, governance is not only arbitrary and labyrinthine, but it also entails necessary experiences of dispossession that ironically accompany schemes for their development. This regime of dispossession that chronically underlies schemes for poverty alleviation is what I call 'cruel governance'. Over time, this mode of development accompanied by dispossession has resulted in cynical realignments of subaltern politics towards the state and its projects. [ABSTRACT FROM AUTHOR]

The rapid urbanization and industrialization in many parts of the world have made air pollution a global public health problem. A study conducted by the Swiss organization IQAir indicated that 22 of the top 30 most polluted cities in the world are in India. This creates the problem of air pollution, which is very relevant to India as well. Exposure to air pollutants has both acute (short-term) and chronic (long-term) impacts on health. Among the major air pollutants, particulate matter 2.5 (PM2.5) is the most harmful, and its long-term exposure can impair lung functions. Pollutant concentrations vary temporally and are dependent on the local meteorology and emissions at a given geographic location. PM2.5 forecasting models have the potential to develop strategies for evaluating and alerting the public regarding expected hazardous levels of air pollution. Accurate measurement and forecasting of pollutant concentrations are critical for assessing air quality and making informed strategic decisions. Recently, data-driven machine learning algorithms for PM2.5 forecasting have received a lot of attention. In this work, a spatiotemporal analysis of air quality was first performed for Hyderabad, indicating that average PM2.5 concentrations during the winter were 68% higher than those during the summer. Following that, PM2.5 modelling was done using three different techniques: multilinear regression, K-nearest neighbours (KNN), and histogram-based gradient boost (HGBoost). Among these, the HGBoost regression model, which used both pollution and meteorological data as inputs, outperformed the other two techniques. During testing, the model acquired an amazing R² value of 0.859, suggesting a significant connection with the actual data. Additionally, the model exhibited a minimum Mean Absolute Error (MAE) of 5.717 μg/m³ and a Root Mean Square Error (RMSE) of 7.647 μg/m³, further confirming its accuracy in predicting PM2.5 concentrations. In our investigation, we discovered that the HGBoost3 model beat other PM2.5 modelling models by having the lowest error and the highest R² value. This study made a substantial addition by incorporating the spatiotemporal relationship between air pollutants and meteorological variables in predicting air quality. This method has the potential to improve the creation of more precise air pollution forecast models. [ABSTRACT FROM AUTHOR]

Purpose: This study was conducted to report on the pattern of spectacles use and compliance among the elderly (aged ≥60 years) in homes for the aged in Hyderabad region in Telangana State, India. Methods: Participants were recruited from 41 homes for the aged centres for comprehensive eye health assessments. A questionnaire was used to collect information on current and past use of spectacles, type of spectacles, spectacles provider and amount paid for the spectacles. For those that reported using spectacles in the past, information was collected on the reasons for their discontinuation. Compliance with spectacles use was assessed after eight months of provision of the spectacles. Results: A total of 1182/1513 participants were examined from 41 homes for the aged in Hyderabad, India. The mean age of the participants examined was 75 years (standard deviation (SD): 8.8 years; range: 60–108 years); 764 (64.6%) of them were women and 240 participants (20.3%) had no formal education. The prevalence of spectacles use was 69.9% (95% confidence interval [CI]: 67.1–72.4; n = 825). Bifocals were the most commonly used type of spectacles (86.7%) followed by single vision glasses for distance vision (7.4%). Private eye clinics were the largest service provider (85.5%) followed by local optical outlets (6.9%) and other service providers (7.7%). The prevalence of spectacles compliance was 81.5% (211/259). Conclusion: Use of spectacles and compliance are high among the elderly living in residential care homes in the Hyderabad region. Spectacles use can be further improved by periodic eye assessments along the lines similar to school eye programs, which can immensely benefit this vulnerable, aged population. [ABSTRACT FROM AUTHOR]

When the Indian government declared the first lockdown on 25 March 2020 to control the increasing number of COVID-19 cases, people were forced to stay and work from home. The aim of this study is to quantify the impact of stay-at-home orders on residential Air Conditioning (AC) energy and household electricity consumption (excluding AC energy). This was done using monitored data from 380 homes in a group of five buildings in Hyderabad, India. We gathered AC energy and household electricity consumption data at a 30-min interval for each home individually in April 2019 and April 2020. Descriptive and inferential statistical analysis was done on this data. To offset the difference in temperatures for the month of April in 2019 and 2020, only those weekdays were selected where the average temperature in 2019 was same as the average temperature in 2020. The study establishes that the average number of hours the AC was used per day in each home increased in the range 4.90–7.45% depending on the temperature for the year 2020. Correspondingly, the overall AC consumption increased in the range 3.60–4.5%, however the daytime (8:00 AM to 8:00 PM) AC energy consumption increased in the range 22–26% and nighttime (8:00 PM to 8:00 AM) AC energy consumption decreased by 5–7% in the year 2020. The study showed a rise in household electricity consumption of about 15% for the entire day in the year 2020. The household electricity consumption increased during daytime by 22- 27.50% and 1.90- 6.6% during the nighttime. It was observed that the morning household electricity peak demand shifted from 7:00 AM in 2019 to 9:00 AM in 2020. Conversely, the evening peak demand shifted from 9:00 PM in 2019 to 7:00 PM in 2020. An additional peak was observed during afternoon hours in the lockdown. [ABSTRACT FROM AUTHOR]

Air Conditioners (ACs) have become a major contributor to residential electricity consumption in India. Non-intrusive Load Monitoring (NILM) can be used to understand residential AC use and its contribution to electricity consumption. NILM techniques use ground truth information along with meter readings to train disaggregation algorithms. There are datasets available for disaggregation, but no dataset is available for a hot tropical country like India especially for AC event detection. Our dataset's primary objective is to help train NILM algorithms for AC event detection and compressor operations. The dataset comprises of home-level electrical current consumption and manually tagged AC ground truth (ON/OFF status) data at 1-min interval, indoor environment temperature and relative humidity readings at 5-min interval and dwelling, AC and household characteristics. The data was collected from 11 homes located in a composite climate zone-Hyderabad, India for 19 summer days (May) 2019. The dataset consists of 1.6 million data points and 450 AC cycles with each cycle having a runtime of more than 60 min (> 2000 compressor ON/OF cycles). Public availability of such a dataset will allow researchers to develop, train and test NILM algorithms that recognize AC and identify compressor operations. [ABSTRACT FROM AUTHOR]

Investment is closely associated with the risk and opportunities. Without risk, there is no profit. However, one should develop analytical abilities, study various factors influencing market conditions and then invest accordingly. This is because there are a number of global, national, local, socio-economic conditions, reforms, government decisions influencing markets from time to time. The present article aims to evaluate the key factors influencing the buying behaviour and the decision-making process of investors in Hyderabad city. The author had conducted the primary study by collecting the responses from the investors in the financial market by using the questionnaire with the deployment of open and close ended questions in the survey. For this purpose, the author had used the non-probabilistic convenient sampling technique in this regard. Total, 100 samples were collected from the different investors belonging to the banks, financial institutions and broking agencies. To study the background of the investors the author had used the frequency distribution method, for the factors that are influencing the buying behaviour of investors for the decision making process of investors in the Hyderabad city they had used the descriptive statistic of mean value and to find out the difference of opinion among the investors regarding the factors influencing buying behaviour and decision making process of investors in Hyderabad the author had used the non-parametric test called Kruskal Wallis Test and it had been found that there is a significant difference of opinion among the investors for the factors influencing buying behaviour of investors in the Hyderabad. [ABSTRACT FROM AUTHOR]

Introduction: Breast Self-examination (BSE) is the simplest and easiest way to look for abnormalities. It's an inexpensive and easy procedure that needs to be implemented from a young age. BSE will help in early diagnosis and treatment of benign and malignant tumours. Inadequate knowledge about BSE was seen usually in non affluent women. Though, affluent individuals have access to good and better healthcare, still there seems to be a lack. Aim: To understand the reasons and barriers among affluent women concerning BSE. Materials and Methods: This descriptive cross-sectional study was conducted in the field area of Ayaan Institute of Medical Sciences, Hyderabad, India, from March 2021 to February 2022. A total of 250 women were included in the study between the ages of 21-49 years. Data was collected using a predesigned pretested questionnaire to evaluate socio-demographic, reasons and barriers to BSE. Data were presented in numbers and percentages. Results: The mean age of the study population was 34.60±8.31 years. All 250 women were educated and with the majority being graduates (n=176, 70.4%), only 140 (56%) had a working occupation and the 205 (82%) were married. The feeling of mass in either of the breast (123, 49.2%), followed by family history of breast cancer (99, 39.6%) and breast pain (92, 36.8%) were the common reasons for performing SBE. The barriers to self-examination were majorly due to lack of knowledge (164, 65.6%), lack of breast complaints (164, 65.6%), absence of lump (130, 52%), followed by 115 (46%) who did not like to touch their breast. Forgetfulness was seen in 93 (37.2%) subjects. Conclusion: Poor awareness of the BSE practice exists even among affluent women. There is an urgent need for awareness about screening techniques, including BSE, in media and health facilities. [ABSTRACT FROM AUTHOR]

• The proposed model predicts residential load demand for future lockdown tenure of COVID-19 pandemic. • The load prediction model used Recurrent Neural Network with Long Short Term Memory (RNN-LSTM) technique with real-time residential load data collected during lockdown period from the installed smart meters. • Load predictions were carried out for two different residential load circles with different data scaling techniques and parameter data and the results were compared. • The results obtained RNN-LSTM method is compared with a benchmarking method of Auto Regressive Integrated Moving Average (ARIMA) to highlight the prediction superiority of the proposed. • The predicted model yields a correlation factors of 96%, 92% without temperature data and 90%, 91% with temperature for two residential colonies under consideration. Covid-19 pandemic and resulting lockdown has created a wide impact on social life, including sudden rise in residential load demand. Utilities, for better load scheduling and economic operations, rely on different prediction models among which neural networks proved to be more appropriate. For such unforeseen situations, the non-availability of prior predictions elevated the utility challenges. Moreover, the stringency of lockdowns caused due to mutated COVID-19 virus, necessitates accurate lockdown load predictions. This paper proposes a Recurrent Neural Network based Long Short-Term Memory (RNN-LSTM) model, trained to produce such predictions for two areas of residential sector. The model uses real-time residential load data from the year 2020, with and without weather parameters. The correlation factor (R) of proposed method 0.9683 outperformed the ARIMA's value 0.703. The model is evaluated with correlation factors of 0.9683 and 0.9235 without temp; 0.90361 and 0.913662 with temperature for Apurupa and Jyothi colonies respectively located in Hyderabad, India. In addition, the error metrics namely, Mean absolute percentage error (MAPE) and Mean absolute error (MAE) are 2.0464 and 138.576 for Apurupa colony; 0.015 and 201.648 for Jyothi colony respectively. However, the prediction error metrics increased slightly with temperature data. The proposed framework will assist utilities for effective load predictions during situations such as pandemic lockdown. [ABSTRACT FROM AUTHOR]

Like many other developing countries, urban sprawl is a growing phenomenon in India, which poses socio-economic and environmental challenges that worryingly affect urban sustainability. In this study, a latent class clustering approach was used to investigate perceptions of urban sprawl among 622 urban and peri-urban dwellers in Hyderabad. The empirical results clustered the respondents into three distinct classes based on their perceptions of urban sprawl impacts: 'undecided respondents', 'negative perceivers', and 'opportunity perceivers'. The majority of respondents were undecided with no strong views towards the impacts of urban sprawl, which may increase their vulnerability and hinder effective adaptation to the adverse economic, social and environmental effects of urban sprawl. This also provokes concerns about the effectiveness of government interventions to build public awareness of urban development and its impacts on the city. With regard to the role of demographic and socio-economic characteristics in shaping the perception of the respondents, the results revealed that social caste plays a determining role in forming dwellers' perception. In particular, members of marginalised social castes were more likely to form positive perceptions of the impacts of urban sprawl as urban expansion generates better and stable income that improve their social status. In addition, individuals with higher levels of education were more likely to form negative or positive perceptions, implying that efforts to raise social capital could be a useful means for mitigating the impacts of urban sprawl. Finally, membership in community development organisations was a key factor in dictating membership of the negative perceivers' class. Overall, our findings suggest that an appropriate policy framework and specific programmes are needed for enhancing dwellers' perception towards the impacts of urban sprawl, which can enhance the design, acceptance, and implementation of a more sustainable governance of urbanisation and contribute to achieving urban sustainability in developing countries. [ABSTRACT FROM AUTHOR]