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Ishita Ray,1 Brandon D’Souza,2 Pallab Sarker,3 Pawan Agarwal4 1Department of Medicine, Mahatma Gandhi Memorial Medical College, Indore, India; 2Department of Medicine, Dr. D.Y. Patil Medical College, Pimpri-Chinchwad, India; 3Department of Medicine, Sher E Bangla Medical College, Barisal City, Bangladesh; 4Department of Surgery, Netaji Subhash Chandra Bose Medical College Jabalpur, Jabalpur, IndiaCorrespondence: Ishita Ray, Madan Mahal Hospital, Prem Nagar, Nagpur Road, Jabalpur, Madhya Pradesh, 482001, India, Tel +918959393344, Email ishitaray94@gmail.comPurpose: This systematic review endeavors to find an effective treatment protocol for subacute thyroiditis (SAT) to minimize side effects, recurrence and long-term hypothyroidism.Materials and Methods: We analyzed available original studies on treatment protocols for SAT. A thorough literature search was performed on the following online databases PubMed, Cochrane library nd Google Scholar using appropriate keywords for choosing relevant articles. Two reviewers assessed the methodological quality of selected articles independently using a critical appraisal instrument. The results were analyzed and synthesized qualitatively using the level of evidence method.Results: The literature search retrieved a total of 460 publications after abstract screening; out of which 36 articles met the inclusion criteria. After full text screening, 23 articles were further excluded as they were focusing on aspects of SAT other than management, the remaining 15 articles were investigated for both reliability and validity. Thirteen studies provided low-quality evidence, and two randomized control trials (RCT) provided a high quality of evidence. Steroid therapy was found to be the most effective for moderate to severe SAT and provided relief from acute symptoms but was found to not be a risk factor for recurrence. Low initial doses of steroid (15 mg) were preferred over high initial dosage (30– 40 mg). Furthermore, a look into the mode of steroid delivery (RCT) revealed that intrathyroidal steroid therapy can potentially become a safer and faster mode of therapy. The duration of tapering was found to be of significance as a short tapering period was linked with greater recurrence rates.Conclusion: Low initial doses of steroid along with an extended tapering period may help lower recurrence rates; also, intrathyroidal steroid injections are potentially a better alternative to oral prednisone (PSN) with regard to safety and speed of action. However, the evidence is of moderate quality and further investigation is required.Keywords: subacute thyroiditis, de Quervain thyroiditis, painful thyroiditis, steroid, NSAIDS, recurrence

Hot and rotating exotic 124Ce nucleus near proton drip line has been populated through fusion evaporation reaction of 32S and 92Mo. This exotic nucleus was de-excited by evaporating p, n, α and/or light nuclei etc and several exotic nuclei have been populated. The experimentally obtained relative population of those exotic nuclei have been compared with the statistical model calculation. Agreement between experimental and statistical model calculation have been observed for most of the evaporation channels. Huge enhancement in comparison to statistical model calculation have been observed fora few channels related to multiple proton evaporation which could not be explained by using default and modified input parameters in statistical calculation.

2.9 billion people lack access to clean cooking fuels and technologies. This review analyzes the literature on affordability as a barrier to adoption and consistent use of clean cooking stoves and fuels. We find diverse frameworks, definitions and metrics in use, and frequent discussions on stove price, fuel costs, microfinance, and smaller procurement quantities. We recommend that financing strategies to mitigate unaffordability be based on how low-income households actually earn, spend, and save their money, and that affordability frameworks be expanded to account for gender divides, rural/urban divides, and stove stacking behavior. Our review thus aims to reflect the nuances of a low-income household's ability to pay for clean fuels. Affordability must make sense within the lived experiences of the poor if clean cooking is to achieve universal access.

Developing decision-relevant science for adaptation requires the identification of climatic parameters that are both actionable for practitioners as well as tractable for modelers. In many sectors, these decision-relevant climatic metrics and the approaches that enable their identification remain largely unknown. “Co-production” of science with scientists and decision-makers is one potential way to identify these metrics, but there is little research describing specific and successful co-production approaches. This paper examines the negotiations and outcomes from Project Hyperion, wherein scientists and water managers jointly developed decision-relevant climatic metrics for adaptive water management. We identify successful co-production strategies by analyzing the project's numerous back-and-forth engagements and tracing the evolution of the science during these engagements. We found that effective mediation between scientists and managers needed dedicated “boundary spanners” with significant modeling expertise. Translating practitioners' information needs into tractable climatic metrics required direct and indirect methods of eliciting knowledge. We identified four indirect methods that were particularly salient for extracting tacitly held knowledge and enabling shared learning: developing a hierarchical framework linking management issues with metrics, starting discussions from the planning challenges, collaboratively exploring the planning relevance of new scientific capabilities, and using analogies of other “good” metrics. The decision-relevant metrics we developed provide insights into advancing adaptation-relevant climate science in the water sector. The co-production strategies we identified can be used to design and implement productive scientist-decision-maker interactions. Overall, the approaches and metrics we developed can help climate science to expand in new and more use-inspired directions.

The ubiquitous use of artworks (e.g., paintings, music, films) in environmental activism has been shown to trigger specific cognitive processes as well as changes in personal values and behaviours. There is less understanding of whether (or how) gender-differentiated environmental claims and gender-transformative initiatives are voiced and promoted through art and cultural expressions. Using network analysis, this paper comprehensively reviews ninety-eight years of peer-reviewed literature on gender and environmental activism. We identify six avenues of gendered artistic activism (or ‘artivism’) on environmental issues that communities have pursued in the past. We present a non-prescriptive description of each avenue based on key references in the literature. A gendered lens on artistic activism makes visible the power of different groups to act, be they women, men, LGBTQ or other collectives, their chosen (or available) scopes of creative action when engaging with environmental protection and their thematic foci. A highlight of the study is the significant presence of younger demographics, including children and students in environmental artivism. Finally, we discuss how gendered artivism expands our understanding of environmental action, putting our results in conversation with well-known current environmentalism(s).

From 2016 to 2019, the Indian Pradhan Mantri Ujjwala Yojana (PMUY) distributed over 80 million liquefied petroleum gas (LPG) stoves, making it the largest clean cooking program ever. Yet, evidence shows widespread continued use of the traditional chulha, negating the potential health benefits of LPG. Here we use semi-structured interviews with female and male adults to understand the drivers of LPG usage in Mulbagal, Karnataka, the site of a proto-PMUY program. We find that respondents perceive the main value of LPG to be saving time, rather than better health. We also find that norms of low female power in the household, in addition to costs, delay saving for and ordering LPG cylinder refills. Namely, female cooks controlled neither the money nor the mobile phone required to order a timely refill. These factors together contribute to the ‘refill gap’: the period of non-use between refilling cylinders, which may range from days to even months. Our work reveals how gender norms can amplify affordability challenges in low-income households.

Development plans with insufficient knowledge about local realities, and that do not share technical or planning details with the target communities, bedevil development practice. This study used a form of participatory modelling in three fishing communities in Nicaragua to enable fishers to explore their economy and the potential impacts of fishery-based development projects. Co-designing a model of the fishing economy in the form of a board game created a forum in which facilitators and participants could arrive at a shared understanding of local fishing practices and the costs and benefits of strategies for addressing the fishers’ priorities.

Employingamatchedcohortresearchdesign,eight wardswithintermittentwatersupply arecomparedto eightwardsupgradedtocontinuous(24x7)supplyina demonstrationprojectinHubli–Dharwad,Karnataka, withrespecttotapwaterquality,childhealth, waterstoragepractices,andcopingcostsacross socio-economicstrata.Waterconsumptionandwastein theintermittentzones,andthepotentialforscale-upof continuoussupplytotheentirecity,areestimated.Itwas foundthatthe24x7projectimprovedwaterquality,did notimproveoverallchildhealth,butdidreduceserious waterborneillnessesinthelowest-incomestrata, reducedthecostsofwaiting,increasedmonthlywater bills,andpotentiallyreducedwatersecurityforsomeof thepooresthouseholds.

Urban service provision falls somewhere on the continuum of lower-cost, lower-quality, unreliable and intermittent to higher-cost, higher-quality, reliable and continuous. Piped water services in India are generally in the former category, but efforts are underway in some cities to shift to continuous supply. We use a matched-cohort research design to evaluate one such effort: an upgrade to continuous water service in a pilot zone of Hubli-Dharwad, India, while the rest of the city remained on intermittent services. We conducted a survey of ∼4000 households with four rounds of data collection over 15 months. We evaluated the household-level net benefits, the equity of their distribution, and the affordability of water access under continuous supply. We also evaluated the project at the system-level (household and utility), estimating the net present value of the upgrade and the feasibility of scale-up to the entire city. We found positive net benefits for households overall, but uneven distribution of these benefits across socio-economic strata. We also found that the costs of supply augmentation, a necessary step for scale-up, significantly reduced the project net present value. The potential for scale-up is thus unclear.

In 2013, manual scavenging, or the cleaning of "dry" latrines with unprotected hands, was abolished in India. Yet, millions of dry latrines are still manually serviced by Dalit labour. The Prime Minister's Swachh Bharat Mission has put little effort into the health and dignity of sanitation workers relative to its efforts on subsidising and encouraging latrine-building. A few days spent with the Valmiki community in Lucknow are recounted.

The rapid growth of bottled water use in low- and middle-income countries, and its normalization as a daily source of drinking water, does not provide a pathway to universal access. Generous and sustained investment in centralized and community utilities remains the most viable means for achieving safe water access for all.

Many policies and programs based on informational interventions hinge upon the assumption that providing citizens with information can help improve the quality of public services, or help citizens cope with poor services. We present a causal framework that can be used to identify leaks and blockages in the information production and dissemination process in such programs. We conceptualize the “information pipeline” as a series of connected nodes, each of which constitutes a possible point of blockage. We apply the framework to a field-experimental evaluation of a program that provided households in Bangalore, India, with advance notification of intermittently provided piped water. Our study detected no impacts on household wait times for water or on how citizens viewed the state, but found that notifications reduced stress. Our framework reveals that, in our case, noncompliance among human intermediaries and asymmetric gender relations contributed in large part to these null-to-modest results. Diagnostic frameworks like this should be used more extensively in development research to better understand the mechanisms responsible for program success and failure, to identify subgroups that actually received the intended treatment, and to identify potential leaks and blockages when replicating existing programs in new settings.

Decentralized technologies and city-based governance are being actively promoted for urban sanitation in low-income countries. At the same time, municipal agencies in developing countries have little technical or financial capacity for sanitation planning. This paper develops an approach to sanitation planning that leverages citizen engagement and fosters local capacities. It presents an empirical study from two small towns in India, where collaborations among the research team, local academics and students, and the municipal government, produced planning-oriented sanitary maps of each town. The maps were built upon a social and spatial understanding of the diverse sanitation practices that already exist, coupled with Google Earth and free GIS software. The ‘waste watersheds’ and ‘sanitation zones’ identified through the mapping process provide a basis on which sanitation interventions can be assessed and weighed, so that sustainable solutions can be prioritized. The paper identifies three features for system interventions: first, making local municipal government the locus of sanitation interventions; second, engaging community-based organizations and academic institutions to develop local capacity; and finally, recognizing the fragmented nature of cities by developing a socio-spatial approach to sanitation zoning.

India’s National Urban Sanitation Policy and its flagship programme, the Swachh Bharat Mission, strongly recommend mechanical technologies for safe faecal sludge management. But, how do septic tank cleaners live and work, and why are their practices not “safe”? An evening spent in observation of their work and in conversation with cleaners and truck drivers in Bengaluru is recounted.

Sustainable Development Goal 7, with the light bulb and power button as its symbols, in effect promotes the universal right to basic electricity services. Access for all demands both affordability and cost-recovery, and utilities (and donors) increasingly require users to shoulder the greater burden of cost-recovery. We argue that the electricity system is underpinned by a set of relationships among user, provider and the service itself: these relationships are mediated by the meter, the technology of commodification. Using a constant-comparison approach, and based on a year of interviews and document analysis, we compare postpaid and prepaid meter regimes in Unguja, Tanzania. We ask: what difference does the mode of payment make to the (residential) user, the utility, and to the prospects for meeting SDG 7? We find that the prepaid meter becomes reified with its automated monitoring and measurement mechanism, rendering the once-familiar meter reader obsolete, and shutting off the flow of electricity as soon as the customer's “units” have run down. Reification makes the utility more invisible to the customer, who now blames the meter rather than the utility for poor service or high bills. Our interviews reveal broad support for the prepaid meter, however, because economically vulnerable users expressed greater fear of debt than of the dark, and were willing to cede control of their consumption to the new meter. These findings undermine the common accusation of a “culture of nonpayment” in Africa. We also find that prepaid meters may incentivize the partial return to biomass-based fuels when cash is not available – exactly the behavior that universal access to electricity is supposed to prevent. We conclude that, if access to electricity in sub-Saharan Africa becomes entirely contingent on payment prior to use, this is not fully compatible with a commitment to universal basic access.

Significant development funding flows to informational interventions intended to improve public services. Such “transparency fixes” often depend on the cooperation of frontline workers who produce or disseminate information for citizens. This article examines frontline worker compliance with a transparency intervention in Bangalore's water sector. Why did compliance vary across neighborhoods, and why did workers exhibit modest rates of compliance overall? Drawing on ethnographic observation and an original data set, this article finds that variation in workers' family responsibilities and financial circumstances largely explains variation in compliance with the intervention. Furthermore, workers often prioritize long-standing responsibilities over new tasks seen as add-ons, leading to modest rates of compliance overall. Perceptions of “core” jobs can be sticky—especially when reaffirmed through interactions with citizens. This article represents one of the first multimethod companions to a field experiment, and illustrates how the analysis of qualitative and observational data can contribute to impact evaluation.

Communities reliant on subsistence and small-scale production are typically more vulnerable than others to disasters such as earthquakes. We study the earthquakes that struck Nepal in the spring of 2015 to investigate their impacts on smallholder communities and the diverse trajectories of recovery at the household and community levels. We focus on the first year following the earthquakes because this is when households were still devastated, yet beginning to recover and adapt. Through survey questionnaires, focus group discussions, open-ended interviews, and observations at public meetings we analyze physical impacts to farming systems and cropping cycles. We investigate respondent reports of loss and recovery through a new social-ecological recovery assessment instrument and find that diversification of livelihoods and access to common resources, alongside robust community institutions, were critical components of coping and recovery. There was widespread damage to subsistence farming infrastructure, which potentially accelerated ongoing transitions to cash crop adoption. We also find that perceptions of recovery varied widely among and within the typical predictors of recovery, such as caste and farm size, in sometimes unexpected ways. Although postdisaster recovery has material and psychosocial dimensions, our work shows that these may not change in the same direction.

Environmental disasters, such as hurricanes, landslides, and earthquakes, are pervasive and disproportionately affect rural and poor populations. The concept of resilience is typically used in disaster scenarios to describe how a community or person is able to “bounce back” from a disaster event. At the same time, resilience theory also contends that disasters, or environmental shocks, can produce or initiate profound changes in social and ecological systems. This case uses a post-disaster resilience assessment to examine how the series of earthquakes that hit central Nepal in 2015 impacted farming communities. Mid-montane smallholder farming communities near the epicenters of the earthquakes were the most affected and the associated damages impeded traditional and subsistence agricultural practices. Our results show how some aspects of the Nepali farming social-ecological system (SES) bounced back more quickly than others and how farmers used various types of coping strategies, including the adoption of labor-saving cash crops as part of their post-disaster recovery. The increased interest in cash crops after the earthquake accelerates an ongoing transition toward more market activities in subsistence communities and illustrates the potential of environmental shocks to transform and change SESs.

Measurements of household water consumption are extremely difficult in intermittent water supply (IWS) regimes in low- and middle-income countries, where water is delivered for short durations, taps are shared, metering is limited, and household storage infrastructure varies widely. Nonetheless, consumption estimates are necessary for utilities to improve water delivery. We estimated household water use in Hubli-Dharwad, India, with a mixed-methods approach combining (limited) metered data, storage container inventories, and structured observations. We developed a typology of household water access according to infrastructure conditions based on the presence of an overhead storage tank and a shared tap. For households with overhead tanks, container measurements and metered data produced statistically similar consumption volumes; for households without overhead tanks, stored volumes underestimated consumption because of significant water use directly from the tap during delivery periods. Households that shared taps consumed much less water than those that did not. We used our water use calculations to estimate waste at the household level and in the distribution system. Very few households used 135 L/person/d, the Government of India design standard for urban systems. Most wasted little water even when unmetered, however, unaccounted-for water in the neighborhood distribution systems was around 50%. Thus, conservation efforts should target loss reduction in the network rather than at households.

This paper uses Long Short-Term Memory (LSTM) networks to predict the stock prices of the Yuanta Taiwan Top 50 ETF (ETF50). To improve the accuracy of the model's predictions, a calibration procedure called "Short-Term Bias Compensation" (STBC) is proposed to adjust the predicted stock prices. In STBC, the daily prediction error is calculated to estimate the short-term bias (STB) in prediction. Then, the predicted price of its next day will be corrected if this STB has exceeded a certain threshold. In this paper, we apply Genetic Algorithms (GAs) to optimize the parameters used in STBC for providing more confidence in its estimation. Based on these predicted stock prices, we propose a Genetic Fuzzy System (GFS) to determine the trading strategy, with trading points for buying and selling stocks. In GFS, various technical indicators are used to establish the fuzzy rules of the trading strategy, and GAs are used to evolve the best parameters for these fuzzy rules. Our experiments cover over 17 years of data (from 2003 to 2020) for ETF50 to consider black swan events such as the 2020 COVID-19 pandemic, the 2018 US–China trade war, and the 2011 US debt crisis. The first 90% of the data is used as training data, and the last 10% is used as testing data. We use 12 technical indicators of these data as the input of LSTM. The predicted values of LSTM are corrected using STBC and compared to the uncorrected prices. We use Mean Square Error (MSE) to evaluate the prediction accuracy. The results show that STBC can nearly reduce 90% of the prediction error (where MSE drops from 11.5758 to 1.2687). By using GFS with STBC to determine trading points, we achieve a return rate of 32.0%. [ABSTRACT FROM AUTHOR]

Accurate forecasting of inbound visitor numbers is crucial for effective planning and resource allocation in the tourism industry. Preceding forecasting algorithms primarily focused on time series analysis, often overlooking influential factors such as economic conditions. Regression models, on the other hand, face challenges when dealing with high-dimensional data. Previous autoencoders for feature selection do not simultaneously incorporate feature and target information simultaneously, potentially limiting their effectiveness in improving predictive performance. This study presents a novel approach that combines a target-concatenated autoencoder (TCA) with ensemble learning to enhance the accuracy of tourism demand predictions. The TCA method integrates the prediction target into the training process, ensuring that the learned feature representations are optimized for specific forecasting tasks. Extensive experiments conducted on the Taiwan and Hawaii datasets demonstrate that the proposed TCA method significantly outperforms traditional feature selection techniques and other advanced algorithms in terms of the mean absolute percentage error (MAPE), mean absolute error (MAE), and coefficient of determination (R2). The results show that TCA combined with XGBoost achieves MAPE values of 3.3947% and 4.0059% for the Taiwan and Hawaii datasets, respectively, indicating substantial improvements over existing methods. Additionally, the proposed approach yields better R2 and MAE metrics than existing methods, further demonstrating its effectiveness. This study highlights the potential of TCA in providing reliable and accurate forecasts, thereby supporting strategic planning, infrastructure development, and sustainable growth in the tourism sector. Future research is advised to explore real-time data integration, expanded feature sets, and hybrid modeling approaches to further enhance the capabilities of the proposed framework. [ABSTRACT FROM AUTHOR]

In IoT systems, the goal of multiview detection for multiple visual sensor networks is to use multiple camera perspectives to address occlusion challenges with multiview aggregation being a crucial component. In these applications, data from various interconnected cameras are combined to create a detailed ground plane feature. This feature is formed by projecting convolutional feature maps from multiple viewpoints and fusing them using uniform weighting. However, simply aggregating data from all cameras is not ideal due to different levels of occlusion depending on object positions and camera angles. To overcome this, we introduce QMVDet, a new query-based learning multiview detector, which incorporates an innovative camera-aware attention mechanism for aggregating multiview information. This mechanism selects the most reliable information from various camera views, thus minimizing the confusion caused by occlusions. Our method simultaneously utilizes both 2D and 3D data while maintaining 2D–3D multiview consistency to guide the multiview detection network's training. The proposed approach achieves state-of-the-art accuracy on two leading multiview detection benchmarks, highlighting its effectiveness for IoT-based multiview detection scenarios. [ABSTRACT FROM AUTHOR]

With the development of sensor and communication technologies, the Internet of Things (IoT) subsystem is gradually becoming a crucial part in vehicles. It can effectively enhance functionalities of vehicles. However, new attack types are also emerging. For example, a driver with the smart key in their pocket can push the start button to start a car. At the same time, security issues in the push-to-start scenario are pervasive, such as smart key forgery. In this study, we propose a vehicle Passive Entry Passive Start (PEPS) system that adopts deep learning algorithms to recognize the driver using the electrocardiogram (ECG) signals measured on the driver's smart watch. ECG signals are used for personal identification. Smart watches, serving as new smart keys of the PEPS system, can improve convenience and security. In the experiment, we consider commercial smart watches capable of sensing ECG signals. The sample rate and precision are typically lower than those of a 12-lead ECG used in hospitals. The experimental results show that Long Short-Term Memory (LSTM) models achieve the best accuracy score for identity recognition (91%) when a single ECG cycle is used. However, it takes at least 30 min for training. The training of a personalized Auto Encoder model takes only 5 min for each subject. When 15 continuous ECG cycles are sensed and used, this can achieve 100% identity accuracy. As the personalized Auto Encoder model is an unsupervised learning one-class recognizer, it can be trained using only the driver's ECG signal. This will simplify the management of ECG recordings extremely, as well as the integration of the proposed technology into PEPS vehicles. A FIDO (Fast Identify Online)-like environment for the proposed PEPS system is discussed. Public key cryptography is adopted for communication between the smart watch and the PEPS car. The driver is first verified on the smart watch via local ECG biometric authentication, and then identified by the PEPS car. Phishing attacks, MITM (man in the middle) attacks, and replay attacks can be effectively prevented. [ABSTRACT FROM AUTHOR]