A copy of Guangbo jiemu bao [Broadcast Program Report] was being passed from hand to hand among a group of young people eager to be the first to read the article introducing the program "What Is Revolutionary Love?" It said: "… Young friends, you are certainly very concerned about this problem'. So, we would like you to meet the young women workers Meng Xiaoyu and Meng Yamei and the older cadre Miss Feng. They are the three leading characters in the short story ‘The Place of Love.’ Through the description of the love lives of these three, the story induces us to think deeply about two questions that merit further examination.

This is How the Discussion Started

応用水文 = Applied hydrology

Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods. Therefore, earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters. In this study, we applied and assessed two new hybrid ensemble models, namely Dagging and Random Subspace (RS) coupled with Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin, the northern region of Bangladesh. The application of these models includes twelve flood influencing factors with 413 current and former flooding points, which were transferred in a GIS environment. The information gain ratio, the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors. For the validation and the comparison of these models, for the ability to predict the statistical appraisal measures such as Freidman, Wilcoxon signed-rank, and t-paired tests and Receiver Operating Characteristic Curve (ROC) were employed. The value of the Area Under the Curve (AUC) of ROC was above 0.80 for all models. For flood susceptibility modelling, the Dagging model performs superior, followed by RF, the ANN, the SVM, and the RS, then the several benchmark models. The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

Flood susceptibility modelling using advanced ensemble machine learning models

Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method.

Ticks and tick-borne pathogens (TTBP) are a major constraint to livestock production in Pakistan; despite a high prevalence of TTBPs, knowledge on the capacity of Pakistani ticks to carry pathogens and endosymbionts is limited. Furthermore, mixed infections with multiple microorganisms further complicate and limit the detection potential of traditional diagnostic methods. The present study investigated the tick-borne microorganisms in bovine ticks in Pakistan, employing a high-throughput microfluidic real-time PCR based technique. Ticks were collected from clinically healthy cattle (n = 116) and water buffaloes (n = 88) from 30 villages across six districts located in five agro-ecological zones (AEZs) of Pakistan from September to November 2017. The microfluidic real-time PCR was used to test the genomic DNA of individual ticks for the presence of 27 bacterial and eight parasitic microorganisms. Phylogenetic methods were used to assess the genetic relationship of DNA sequences determined herein. PCR detected DNA of at least one microorganism in each of 221 ticks tested (94.4%, 221/234). DNA-based detection inferred that single pathogens/endosymbionts were the most common (43.4%, 96/221) followed by double (38.9%, 86/221), triple (14.5%, 32/221), quadruple (2.3%, 5/221) and quintuple (0.9%, 2/221) mixed infections. Piroplasms (Babesia/Theileria spp.) were the most prevalent (31.6%, 74/234), followed by Ehrlichia spp. (20%, 47/234) and Anaplasma marginale (7.7%, 18/234). Anaplasma phagocytophilum, A. ovis, A. centrale, Babesia ovis, Borrelia spp., Rickettsia spp., R. massiliae, Bartonella spp. and Hepatozoon spp. were also detected. Endosymbionts such as Francisella-like (91.5%, 214/234) and Coxiella-like (1.3%, 3/234) organisms were also detected in ticks. The highest diversity of microorganisms was detected in Hyalomma anatolicum ticks (test-positive for 14/14 microorganisms), followed by Rhipicephalus microplus (4/14), Hy. hussaini (3/14) and Rh. annulatus (2/14). Ticks collected from cattle carried significantly more frequently piroplasms (41.2%, 54/131; P < 0.05) than those from buffaloes (19.4%, 20/103). However, the overall prevalence of microorganisms did not vary significantly among ticks from the two host species as well as across different AEZs. To our knowledge, this is the first study to investigate a wide range of tick-borne microorganisms in bovine ticks using a high-throughput diagnostic method from different AEZs in Pakistan. These findings will aid in establishing the distribution patterns and the control of tick-borne pathogens of bovines in Pakistan.

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Bovine ticks harbour a diverse array of microorganisms in Pakistan.

This main objective of this study is flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan. In the study region, flash flood is one of the horrific and recurrent hydro-meteorological disasters causing damages to human life, their properties, and infrastructure. Watershed modeling approach is implemented to delineate Panjkora Basin, its sub-basins, and extract drainage network by utilizing Advance Space borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model as an input data in geographic information system environment. A total of 30 sub-basins were delineated using threshold of 25 km2. The geo-morphometric parameters of each sub-basin were computed by applying Hortonian, Schumm, and Strahler Geo-morphological laws. The value of each parameter was normalized and aggregated into geo-morphometric ranking number depicting the degree of flash flood susceptibility. Surface run-off depth of each sub-basin is estimated by applying Natural Resource Conservation Service Curve Number hydrological model. Both models outputs were integrated by implementing weighted overlay analysis technique and susceptibility map is obtained. The resultant map was analyzed and zonated into very high, high, moderate, low, and very low flash flood susceptibility zones. These zones were spread over an area of 1441 km2 (27%), 1950 km2 (36.5%), 1252 km2 (23.4%), 604 km2 (11.3%), and 98 km2 (1.8%), respectively. Spatially, the very high susceptible zone is located in the upstream areas, characterized by snow covered peaks, steep gradient (> 30°), and high drainage density (> 1.7 km/km2), and geologically dominated by igneous and metamorphic lithological units. Analysis indicated that flash flood susceptibility is directly increases with increasing surface run-off and geo-morphometric ranking number. A new model is developed to geo-visualize the spatial pattern of flash flood susceptibility. Accuracy of the model is assessed using global positioning system-based primary data regarding past-flood damages and flood marks. The study results can facilitate Disaster Management Authorities and flood dealing line agencies to initiate location-specific flood-risk reduction strategies in highly susceptible areas of Panjkora Basin. Similarly, this methodological approach can be adapted for any highland river system.

Flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan

The paper assesses the damage caused by 2010 flash flood and its underlying causes in the upper zone of Panjkora River within district Dir Upper, Khyber Pakhtunkhwa (KP) Province in Pakistan. Floods in general and flash floods in particular are very common in the area, and the phenomenon has intensified in the wake of observed climatic changes in the region. Anticipating an increase in the multiplicity of causes and a rise in the human, livelihood, and property losses attributed to flash floods calls for a detailed study of affected communities in the region. Within the study area of District Dir Upper—within the band of 200 m on both sides of Panjkora River, three most affected communities, namely Barikot, Kalkot, and Sharingal, were picked on random basis to have detailed analysis of underlying causes and the quantification of damage assessment in the area. Questionnaire-based household survey and structured interviews were conducted to investigate physical and economic damages in the sample sites. Global positioning system (GPS) survey is also conducted to acquire absolute location of damages, and geographic information system is used to visualize land use, land cover, physical features, and GPS data. Monsoon winds interacted with the westerlies abnormally caused unprecedented high intensity rainfall in the valley. The steep topography of the area caused rainwater to accumulate rapidly in the Panjkora River channel, overpowering the withholding capacity of the river. The flash flood inflected heavy losses to life and properties of the local population. The infrastructure such as houses, roads, retaining walls, bridges, water supply schemes, and irrigation channels were destroyed severely in the whole area particularly in Kalkot. Three explored underlying causes of flash floods and the degree of damage due to 2010 flash floods in the region call for an enhanced realization for climatic change adaptability, flood risk management, and mitigation measures, better flood response through early warning systems, and improved rehabilitation and recovery efforts within flood prone areas such as district Dir Upper, KP, Pakistan.

Exploring underlying causes and assessing damages of 2010 flash flood in the upper zone of Panjkora River

Globally, flood is one of the devastating hydrometeorological disasters, causing human losses and damages to properties and infrastructure. There is a need to determine and geo-visualize flood risk to assist decision-making process for flood risk reduction. The current study is a local level pioneering attempt regarding the spatial appraisal of flood risk assessment and evaluation in Panjkora River Basin, eastern Hindu Kush. An integrated hydro-probabilistic approach is implemented by clubbing the results of Hydrologic Engineering Centre's River Analysis System (HEC-RAS) and Hydrologic Engineering Centre's Geographic River Analysis System (HEC-Geo-RAS) in geographic information system (GIS) environment. An Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model (GDEM) is used as input data to delineate the target basin and generation of river geometry. Hydraulic and hydrological data were used to estimate and geo-visualize vertical profile and spatial extent of various floods in the active floodplain of Panjkora River. Gumbel's frequency distribution model is applied in analyzing daily peak discharge recorded during the past 32 years, and 200-year flood magnitude (1392m3/sec), probable inundation (45.5 km2), and vertical profile (19 m) are modeled. Analysis revealed that likelihood of such flood has increased the risk of potential damages to roads (46 km), retaining walls (49 km), bridges (16), and culverts (46). The analysis further revealed that built-up area (10.4 km2) and agricultural land (20.2 km2) will also come under flood with life loss. The resultant flood risk zones and spatial appraisal will definitely help in bringing down the probable flood damages. Similarly, current study has potential to assist disaster managers, hydraulic engineers, and policy makers to understand the flood risk and implement location-specific effective flood risk reduction strategies.

Spatial appraisal of flood risk assessment and evaluation using integrated hydro-probabilistic approach in Panjkora River Basin, Pakistan

Bovine anaplasmosis is endemic in Pakistan where it reduces livestock productivity and leads to high mortality, especially in young animals. This study was aimed to identify the potential risk factors responsible for the occurrence and spread of anaplasmosis in cattle and buffaloes for the first time in Pakistan. A total of 900 (cattle = 479, buffalo = 421) blood samples were collected irrespective of age and sex from three distinct zones of Khyber Pakhtunkhhwa (KP) province of Pakistan. Polymerase chain reaction (PCR) technique was used for the molecular detection of anaplasmosis. Data collected on a piloted questionnaire including 11 predicting variables which were analyzed using R-statistical software, and association between the dependent and independent variables was assessed using univariable analysis. Automated and manual approaches were exercised, producing comparable models. Key risk factors identified in all the approaches included species of the animal, breed of animal, sex of animal, tick infestation status, previous tick history, tick control status, and acaricides used (odds ratio > 1). The 611 bp DNA fragment specific for 16S rRNA gene of Anaplasma spp. was produced from 165 samples. The samples were confirmed for anaplasmosis through sequencing and BLAST queries. The findings of the current study conclude that by enhancing the protective measures to control the identified risk factors can reduce the spread of anaplasmosis in Pakistan.

Molecular epidemiology of bovine anaplasmosis in Khyber Pakhtunkhwa, Pakistan.

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Shakeel Mahmood

Papers

Flash flood susceptibility modeling using geo-morphometric and hydrological approaches in Panjkora Basin, Eastern Hindu Kush, Pakistan

Exploring underlying causes and assessing damages of 2010 flash flood in the upper zone of Panjkora River

Spatial appraisal of flood risk assessment and evaluation using integrated hydro-probabilistic approach in Panjkora River Basin, Pakistan

Molecular epidemiology of bovine anaplasmosis in Khyber Pakhtunkhwa, Pakistan.

Distribution of Ixodid Tick Species and Associated Risk Factors in Temporal Zones of Khyber Pakhtunkhwa Province, Pakistan