Effect of fire and post-fire management on soil microbial communities in a lower subtropical forest ecosystem after a mountain fire.

Wildfires and post-fire management exert profound effects on soil properties and microbial communities in forest ecosystems. Understanding microbial community recovery from fire and what the best post-fire management should be is very important but needs to be sufficiently studied. In light of these gaps in our understanding, this study aimed to assess the short-term effects of wildfire and post-fire management on both bacteria and fungi community composition, diversity, structure, and co-occurrence networks, and to identify the principal determinants of soil processes influencing the restoration of these communities. Specifically, we investigated soil bacterial and fungal community composition, diversity, structure, and co-occurrence networks in lower subtropical forests during a short-term (<3 years) post-fire recovery period at four main sites in Guangdong Province, southern China. Our results revealed significant effects of wildfires on fungal community composition, diversity, and co-occurrence patterns. Network analysis indicated reduced bacterial network complexity and connectivity post-fire, while the same features were enhanced in fungal networks. However, post-fire management effects on microbial communities were negligible. Bacterial diversity correlated positively with soil microbial biomass nitrogen, soil organic carbon, and soil total nitrogen. Conversely, based on the best random forest model, fungal community dynamics were negatively linked to nitrate-nitrogen and soil water content. Spearman's correlation analysis suggested positive associations between bacterial networks and soil factors, whereas fungal networks exhibited predominantly negative associations. This study elucidates the pivotal role of post-fire management in shaping ecological outcomes. Additionally, it accentuates the discernible distinctions between bacterial and fungal responses to fire throughout a short-term recovery period. These findings contribute novel insights that bear significance in evaluating the efficacy of environmental management strategies.

Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan.

Alteration in Land Use/Cover (LULC) considered a major challenge over the recent decades, as it plays an important role in diminishing biodiversity, altering the macro and microclimate. Therefore, the current study was designed to examine the past 30 years (1987−2017) changes in LULC and Land Surface Temperature (LST) and also simulated for next 30 years (2047). The LULC maps were developed based on maximum probability classification while the LST was retrieved from Landsat thermal bands and Radiative Transfer Equation (RTE) method for the respective years. Different approaches were used, such as Weighted Evidence (WE), Cellular Automata (CA) and regression prediction model for the year 2047. Resultantly, the LULC classification showed increasing trend in built-up and bare soil classes (13 km2 and 89 km2), and the decreasing trend in vegetation class (−144 km2) in the study area. In the next 30 years, the built-up and bare soil classes would further rise with same speed (25 km2 and 36.53 km2), and the vegetation class would further decline (−147 km2) until 2047. Similarly for LST, the temperature range for higher classes (27 -< 30 °C) increased by about 140 km2 during 1987−2017, which would further enlarge (409 km2) until 2047. The lower LST range (15 °C to <21 °C) showed a decreasing trend (−54.94 km2) and would further decline to (−20 km2) until 2047 if it remained at the same speed. Prospective findings will be helpful for land use planners, climatologists and other scientists in reducing the increasing LST associated with LULC changes.

Prevalence of measles in district Bannu.

This was a cross-sectional descriptive study for determining the effect of vaccination in children suffering from measles in district Bannu and FR regions. It was conducted at the Paediatric Unit of Women and Children Teaching Hospital, Bannu Medical College Bannu, from July 2015 to June 2016.A total of 7,200 children were examined both from indoor and OPD. Among these, 3,210 (44.58%), were males and 3990 (55.42) were females. Children upto 15 years, suffering from measles were included both from indoor and outdoor departments. Vaccination drives in various main councils of District Bannu showed that out of the total 7200, 3,210 (53.13%), were males and 3990 (46.87%) were females. Hospital study showed that out of total 7200 children, 578 children were found to be measles infected. Among 578 children, 24 were under 12 months, 194 children were in the age group 1 to 3 years, 254 in the age group 3-5 years, 70 patients in the age group of 5-8 years and 36 in the age group 8-15 years were found to be measles infected. For confirmation of vaccination status the patient's parents were advised to bring along with them vaccination card. Only 67 (11.60%) showed vaccination cards while 511 (88.40%) did not provide vaccination cards showing that these children were non-vaccinated. From the present study, it is strongly recommended that all the children must be immunized against measles.

Using online social networks to track a pandemic: A systematic review.

BACKGROUND: The popularity and proliferation of online social networks (OSNs) have created massive social interaction among users that generate an extensive amount of data. An OSN offers a unique opportunity for studying and understanding social interaction and communication among far larger populations now more than ever before. Recently, OSNs have received considerable attention as a possible tool to track a pandemic because they can provide an almost real-time surveillance system at a less costly rate than traditional surveillance systems. METHODS: A systematic literature search for studies with the primary aim of using OSN to detect and track a pandemic was conducted. We conducted an electronic literature search for eligible English articles published between 2004 and 2015 using PUBMED, IEEExplore, ACM Digital Library, Google Scholar, and Web of Science. First, the articles were screened on the basis of titles and abstracts. Second, the full texts were reviewed. All included studies were subjected to quality assessment. RESULT: OSNs have rich information that can be utilized to develop an almost real-time pandemic surveillance system. The outcomes of OSN surveillance systems have demonstrated high correlations with the findings of official surveillance systems. However, the limitation in using OSN to track pandemic is in collecting representative data with sufficient population coverage. This challenge is related to the characteristics of OSN data. The data are dynamic, large-sized, and unstructured, thus requiring advanced algorithms and computational linguistics. CONCLUSIONS: OSN data contain significant information that can be used to track a pandemic. Different from traditional surveys and clinical reports, in which the data collection process is time consuming at costly rates, OSN data can be collected almost in real time at a cheaper cost. Additionally, the geographical and temporal information can provide exploratory analysis of spatiotemporal dynamics of infectious disease spread. However, on one hand, an OSN-based surveillance system requires comprehensive adoption, enhanced geographical identification system, and advanced algorithms and computational linguistics to eliminate its limitations and challenges. On the other hand, OSN is probably to never replace traditional surveillance, but it can offer complementary data that can work best when integrated with traditional data.

A cardiac electrical activity model based on a cellular automata system in comparison with neural network model.

Cardiac Electrical Activity is commonly distributed into three dimensions of Cardiac Tissue (Myocardium) and evolves with duration of time. The indicator of heart diseases can occur randomly at any time of a day. Heart rate, conduction and each electrical activity during cardiac cycle should be monitor non-invasively for the assessment of "Action Potential" (regular) and "Arrhythmia" (irregular) rhythms. Many heart diseases can easily be examined through Automata model like Cellular Automata concepts. This paper deals with the different states of cardiac rhythms using cellular automata with the comparison of neural network also provides fast and highly effective stimulation for the contraction of cardiac muscles on the Atria in the result of genesis of electrical spark or wave. The specific formulated model named as "States of automaton Proposed Model for CEA (Cardiac Electrical Activity)" by using Cellular Automata Methodology is commonly shows the three states of cardiac tissues conduction phenomena (i) Resting (Relax and Excitable state), (ii) ARP (Excited but Absolutely refractory Phase i.e. Excited but not able to excite neighboring cells) (iii) RRP (Excited but Relatively Refractory Phase i.e. Excited and able to excite neighboring cells). The result indicates most efficient modeling with few burden of computation and it is Action Potential during the pumping of blood in cardiac cycle.

Consanguinity ratio in b-thalassemia major patients in District Bannu.

OBJECTIVE: To assess the frequency of consanguinity in b-thalassemia major patients and its association with age, gender and hepatitis C virus antibody positivity. METHODS: The cross-sectional study was conducted from June 2013 to July 2014 at various hospitals of district Bannu in the North Western Khyber Pakhtunkhwa province of Pakistan. Data was recorded on a predesigned questionnaire. RESULTS: Out of 180 subjects, 133(74%) parents were cousins, while 47(26%) were unrelated. The frequency of anti-hepatitis C virus antibody positivity was 14(7.77%). CONCLUSIONS: High prevalence of the disease in the study region was due to consanguineous marriages.

Comparative study and effects of urban green scape on the land surface temperature of a large metropolis and green city.

Previous studies have provided valuable insights into the impact of green space (GS) on land surface temperature (LST). However, there is a need for in-depth comparative research on changing landscape patterns in cities and their effects on the urban thermal environment. This study investigates the spatial arrangement of GS and the influence of impervious surfaces on LST in urban areas, examining their cooling and warming effects in the urban landscapes of Beijing and Islamabad. The study aims to assess the impact of the spatial arrangement of GS on LST using a moving window of 1 km2 to analyze the overall effect of landscape patterns on the urban environment. Using Gaofen (GF-2) and Landsat-8 satellite data, we examined the biophysical surface properties of core urban areas. The results indicate a significant difference in the mean LST of 5.44 °C and 3.31 °C between impervious surfaces and GS in Beijing and Islamabad, respectively. The barren land and GS in Islamabad experience a higher LST of 3.39 °C compared to Beijing, which accounts for 1.39 °C. In Beijing, configuration metrics show no significant effect on urban LST, while edge density (ED) exhibits a slightly negative trend. In contrast, in the city of Islamabad, the landscape shape index (LSI), patch density (PD), and number of patches (NP) metrics have a significant influence on LST. The cooling effect of GS patches (0.1-0.5 ha) is more pronounced, while that of GS patches of 15-20 ha shows no significant effect on LST. The temperature difference (TD) of 5.01 °C was observed from the edge of GS in Beijing and 3.3 °C in Islamabad. Considering Islamabad's lush green scape compared to Beijing, this study suggests that Islamabad may experience an increase in LST in the future due to urbanization. This study's findings may assist urban policy-makers in designing sustainable green city layouts that effectively address future planning considerations.

The Distribution and Accessibility of Urban Parks in Beijing, China: Implications of Social Equity.

As public service facilities, urban parks offer many benefits for daily life and social activities for residents. However, the accessibility of public parks to urban residents is often unevenly distributed in spaces that cannot be utilized fully. Here, we used the urban parks in Beijing, China as a case study and examined the relationship between urban park accessibility and population distribution at different administrative levels. Gini coefficient and Lorenz curve were used to evaluate the social equity of urban park accessibility, and the location quotient was used to identify the spatial difference between urban parks and resident population. The results of our study show that the urban park accessibility varies at district and subdistrict levels and that places with more urban parks usually have higher accessibility. Very importantly, the spatial equity is different from the social equity, a mismatch exists between the spatial distribution of urban parks and population, particularly for the elderly residents. These results generate valuable insights, as, in China and many developing countries, current urban public green space planning only uses the ratio of public green space to urban construction land and the per capita public green area.