Geographical distribution of radon and associated health risks in drinking water samples collected from the Mulazai area of Peshawar, Pakistan.

Geospatial methods, such as GIS and remote sensing, map radon levels, pinpoint high-risk areas and connect geological traits to radon presence. These findings direct health planning, focusing tests, mitigation, and policies where radon levels are high. Overall, geospatial analyses offer vital insights, shaping interventions and policies to reduce health risks from radon exposure. There is a formidable threat to human well-being posed by the naturally occurring carcinogenic radon (222Rn) gas due to high solubility in water. Under the current scenario, it is crucial to assess the extent of 222Rn pollution in our drinking water sources across various regions and thoroughly investigate the potential health hazards it poses. In this regard, the present study was conducted to investigate the concentration of 222Rn in groundwater samples collected from handpumps and wells and to estimate health risks associated with the consumption of 222Rn-contaminated water. For this purpose, groundwater samples (n = 30) were collected from handpumps, and wells located in the Mulazai area, District Peshawar. The RAD7 radon detector was used as per international standards to assess the concentration of 222Rn in the collected water samples. The results unveiled that the levels of 222Rn in the collected samples exceeded the acceptable thresholds set by the US Environmental Protection Agency (US-EPA) of 11.1 Bq L-1. Nevertheless, it was determined that the average annual dose was below the recommended limit of 0.1 mSv per year, as advised by both the European Union Council and the World Health Organization. In order to avoid the harmful effects of such excessive 222Rn concentrations on human health, proper ventilation and storage of water in storage reservoirs for a long time before use is recommended to lower the 222Rn concentration.

Correction: A novel association rule mining approach using TID intermediate itemset.

[This corrects the article DOI: 10.1371/journal.pone.0179703.].

A novel association rule mining approach using TID intermediate itemset.

Designing an efficient association rule mining (ARM) algorithm for multilevel knowledge-based transactional databases that is appropriate for real-world deployments is of paramount concern. However, dynamic decision making that needs to modify the threshold either to minimize or maximize the output knowledge certainly necessitates the extant state-of-the-art algorithms to rescan the entire database. Subsequently, the process incurs heavy computation cost and is not feasible for real-time applications. The paper addresses efficiently the problem of threshold dynamic updation for a given purpose. The paper contributes by presenting a novel ARM approach that creates an intermediate itemset and applies a threshold to extract categorical frequent itemsets with diverse threshold values. Thus, improving the overall efficiency as we no longer needs to scan the whole database. After the entire itemset is built, we are able to obtain real support without the need of rebuilding the itemset (e.g. Itemset list is intersected to obtain the actual support). Moreover, the algorithm supports to extract many frequent itemsets according to a pre-determined minimum support with an independent purpose. Additionally, the experimental results of our proposed approach demonstrate the capability to be deployed in any mining system in a fully parallel mode; consequently, increasing the efficiency of the real-time association rules discovery process. The proposed approach outperforms the extant state-of-the-art and shows promising results that reduce computation cost, increase accuracy, and produce all possible itemsets.

Two Hop Adaptive Vector Based Quality Forwarding for Void Hole Avoidance in Underwater WSNs.

Underwater wireless sensor networks (UWSNs) facilitate a wide range of aquatic applications in various domains. However, the harsh underwater environment poses challenges like low bandwidth, long propagation delay, high bit error rate, high deployment cost, irregular topological structure, etc. Node mobility and the uneven distribution of sensor nodes create void holes in UWSNs. Void hole creation has become a critical issue in UWSNs, as it severely affects the network performance. Avoiding void hole creation benefits better coverage over an area, less energy consumption in the network and high throughput. For this purpose, minimization of void hole probability particularly in local sparse regions is focused on in this paper. The two-hop adaptive hop by hop vector-based forwarding (2hop-AHH-VBF) protocol aims to avoid the void hole with the help of two-hop neighbor node information. The other protocol, quality forwarding adaptive hop by hop vector-based forwarding (QF-AHH-VBF), selects an optimal forwarder based on the composite priority function. QF-AHH-VBF improves network good-put because of optimal forwarder selection. QF-AHH-VBF aims to reduce void hole probability by optimally selecting next hop forwarders. To attain better network performance, mathematical problem formulation based on linear programming is performed. Simulation results show that by opting these mechanisms, significant reduction in end-to-end delay and better throughput are achieved in the network.

Need of cost-effective vaccines in developing countries: What plant biotechnology can offer?

To treat current infectious diseases, different therapies are used that include drugs or vaccines or both. Currently, the world is facing an increasing problem of drug resistance from many pathogenic microorganisms. In majority of cases, when vaccines are used, formulations consist of live attenuated microorganisms. This poses an additional risk of infection in immunocompromised patients and people suffering from malnutrition in developing countries. Therefore, there is need to improve drug therapy as well as to develop next generation vaccines, in particular against infectious diseases with highest mortality rates. For patients in developing countries, costs related to treatments are one of the major hurdles to reduce the disease burden. In many cases, use of prophylactic vaccines can help to control the incidence of infectious diseases. In the present review, we describe some infectious diseases with high impact on health of people in low and middle income countries. We discuss the prospects of plants as alternative platform for the development of next-generation subunit vaccines that can be a cost-effective source for mass immunization of people in developing countries.

A Fatigue Measuring Protocol for Wireless Body Area Sensor Networks.

As players and soldiers preform strenuous exercises and do difficult and tiring duties, they are usually the common victims of muscular fatigue. Keeping this in mind, we propose FAtigue MEasurement (FAME) protocol for soccer players and soldiers using in-vivo sensors for Wireless Body Area Sensor Networks (WBASNs). In FAME, we introduce a composite parameter for fatigue measurement by setting a threshold level for each sensor. Whenever, any sensed data exceeds its threshold level, the players or soldiers are declared to be in a state of fatigue. Moreover, we use a vibration pad for the relaxation of fatigued muscles, and then utilize the vibrational energy by means of vibration detection circuit to recharge the in-vivo sensors. The induction circuit achieves about 68 % link efficiency. Simulation results show better performance of the proposed FAME protocol, in the chosen scenarios, as compared to an existing Wireless Soccer Team Monitoring (WSTM) protocol in terms of the selected metrics.