Analysis and Examination of the Sunni Commentators’ Views in Explaining the Temporal Extent of the Infallibility of the Prophets (PBUTH)

Sunni commentators have different views on the temporal extent of the infallibility of the prophets. While Some Ash'arites have expressed absolute infallibility, the Mu'tazilites believe that the Prophets (Peace Be Upon Them) have been infallible since the start of their prophethood. This study, by referring to Sunni interpretations, seeks analytical-critical processing of the method of Sunni commentators using the necessary tools and resources in expressing the time limit of the infallibility of the Prophets (PBUTH). Examination of the interpretators comments following verses about the infallibility of the prophets (PBUTH) shows that the opinon of the Sunni commentators on the fallibility of the Prophets before prophethood, lack using appropriate tools and is a claim without reason, and the cause of differences in views about the infallibility of the prophets after prophethood, is paying no attention to rational arguments and favoring religious beliefs by interpreting verses in order to prove one's opinion and imposing the mental background of the interpreter on the verses.

Characteristics of hail hazard in South Africa based on satellite detection of convective storms

Accurate estimates of hail risk to fixed and mobile assets such as crops, infrastructure and vehicles are required for both insurance pricing and preventive measures. Here we present an event catalog to describe hail hazard in South Africa guided by 14 years of geostationary satellite observations of convective storms. Overshooting cloud tops have been detected, grouped and tracked to describe the spatio-temporal extent of potential hail events. It is found that hail events concentrate mainly in the southeast of the country, along the Highveld and the eastern slopes. Events are most frequent from mid-November through February and peak in the afternoon, between 13 and 17 UTC. Multivariate stochastic modeling of event properties yields an event catalog spanning 25 000 years, aiming to estimate, in combination with vulnerability and exposure data, hail damage for return periods of 200 years.

Die Justinianische Pest

Of all known epidemics in Antiquity, the Justinianic Plague became the focus of attention in recent years - not least because it is the first for which the causative agent, the bacterium Yersinia pestis, could be unambiguously identified by palaeogeneticists. The reconstruction of ancient Y. pestis genomes is able to uncover the geographical and temporal extent of the pandemic beyond the limitations of written sources; and phylogenetic studies allow for inferences on the origin and spread of plague through time. But even the mere identification of plague victims in Late Antique and Early Medieval cemeteries offers insights in the crisis management and reactions of past societies to the irruption of the unfathomable, to which historical scholarship - generally based on written sources - has only limited access. However, attempts on the integration of natural scientific research on epidemics and climatic shifts in history are notoriously accused of determinism or an oversimplification of complex coherencies. Therefore, mutual understanding of methodologies and epistemologies of different disciplines is a fundamental prerequisite to avoid simplistic causal inferences from correlations and circular arguments, and lead to a better understanding of the Justinianic Plague and accompanying processes through an integrative approach.

On covariation between nasal consonant weakening and anticipatory vowel nasalization: Evidence from a Caribbean and a non-Caribbean dialect of Spanish

In this study, I examine co-variation between the word-final nasal consonant and anticipatory vowel nasalization in two dialects of Spanish. In Caribbean dialects of Spanish, nasalization has been proposed as allophonic (an intended feature of the vowel) but elsewhere it is presumably coarticulatory (a marker of nasal consonant weakening). I argue that, when differences in the phonological interpretation of nasalization are factored in, the temporal extent of nasalization cannot be exclusively attributed to weakening of the nasal consonant. Twenty-eight speakers from Santo Domingo (Dominican Republic) and twenty-six from Buenos Aires (Argentina) were recorded with a nasometer. Findings revealed that when the feature for nasality is phonologized in the representation of the vowel (Santo Domingo Spanish), earlier onset of nasalization can (and does) obtain with little (and arguably even without) weakening of the nasal. By analyzing nasal consonant weakening concurrently with anticipatory vowel nasalization, this study bridges the gap between the aforementioned sources of variation in nasalization.

Effect of Corona Virus Pandemic Lockdown to Chemical Composition of Peat Mosses

Sphagnum mosses are used for biomonitoring of air pollution. In 2019, samples were taken from two peat bogs in Germany and two in Slovenia to determine differences in their levels of potentially toxic elements (PTE). The Corona Virus Disease (COVID-19) lockdown caused global decrease in air pollution. Therefore, we repeated the monitoring in 2020 to see if this was also reflected in moss composition. Despite the variability within bogs and the areas, it is possible to distinguish the degree of air pollution between the two countries. The Harz mosses have higher contents of almost all elements and Slovenian Cr and Hg in 2020. Comparison of the PTE contents, their ratios to Sc and the enrichment factors show that the COVID-19 lockdown led to a decrease in long-range pollutants bound to finest particles and increased the influence of local soil dusting. The effect prevailed over lower precipitation in 2020 compared to 2019. Transport and industry continued to contribute significantly to contamination. Sphagnum mosses proved to be good indicators of the spatial and temporal extent of pollution. Even relatively short periods of lower air pollution are reflected in moss PTE contents.

Automatic Traffic Queue-End Identification using Location-Based Waze User Reports

Traffic queues, especially queues caused by non-recurrent events such as incidents, are unexpected to high-speed drivers approaching the end of queue (EOQ) and become safety concerns. Though the topic has been extensively studied, the identification of EOQ has been limited by the spatial-temporal resolution of traditional data sources. This study explores the potential of location-based crowdsourced data, specifically Waze user reports. It presents a dynamic clustering algorithm that can group the location-based reports in real time and identify the spatial-temporal extent of congestion as well as the EOQ. The algorithm is a spatial-temporal extension of the density-based spatial clustering of applications with noise (DBSCAN) algorithm for real-time streaming data with an adaptive threshold selection procedure. The proposed method was tested with 34 traffic congestion cases in the Knoxville,Tennessee area of the United States. It is demonstrated that the algorithm can effectively detect spatial-temporal extent of congestion based on Waze report clusters and identify EOQ in real-time. The Waze report-based detection are compared to the detection based on roadside sensor data. The results are promising: The EOQ identification time of Waze is similar to the EOQ detection time of traffic sensor data, with only 1.1 min difference on average. In addition, Waze generates 1.9 EOQ detection points every mile, compared to 1.8 detection points generated by traffic sensor data, suggesting the two data sources are comparable in respect of reporting frequency. The results indicate that Waze is a valuable complementary source for EOQ detection where no traffic sensors are installed.

A Landscape Persistence Assessment of Częstochowa Upland: A Case Study of Ogrodzieniec, Poland

Landscape permanence is understood as the temporal extent of the dominance of a given type of landscape, expressed by the temporal continuity of its use. This issue, already being the subject of much research, is important in proper landscape protection and management. In this paper, spatial landscape persistence and persistence of particular landscape types are presented for the Ogrodzieniec municipality, Częstochowa Upland, Poland. In addition, a background of landscape types and their changes in the Częstochowa Upland has been presented. Based on current and historical topographic maps, landscape types (forest, agriculture, settlement, fortified and industrial) were identified for the following studied periods: 1831, 1944, 1965, 2007, 2014 and 2020. After overlapping the maps, the persistence index was calculated, and isochrones of landscape persistence were determined. The term ‘landscape isochrones’ introduced in this paper is defined as theoretical lines of equal landscape time duration (iso-persistence line). The results show that the landscape of Ogrodzieniec can be considered to be persistent. The largest area of the municipality is occupied by the most permanent landscapes dating from before 1831. The most persistent is the fortified landscape. The method applied is important for planning sustainable development of the region, which is currently under intense tourist and economic pressure.

Mapping the plague through natural language processing

Plague has caused three major pandemics with millions of casualties in the past centuries. There is a substantial amount of historical and modern primary and secondary literature about the spatial and temporal extent of epidemics, circumstances of transmission or symptoms and treatments. Many quantitative analyses rely on structured data, but the extraction of specific information such as the time and place of outbreaks is a tedious process. Machine learning algorithms for natural language processing (NLP) can potentially facilitate the establishment of datasets, but their use in plague research has not been explored much yet. We investigated the performance of five pre-trained NLP libraries (Google NLP, Stanford CoreNLP, spaCy, germaNER and Geoparser.io) for the extraction of location data from a German plague treatise published in 1908 compared to the gold standard of manual annotation. Of all tested algorithms, we found that Stanford CoreNLP had the best overall performance but spaCy showed the highest sensitivity. Moreover, we demonstrate how word associations can be extracted and displayed with simple text mining techniques in order to gain a quick insight into salient topics. Finally, we compared our newly digitised plague dataset to a re-digitised version of the famous Biraben plague list and update the spatio-temporal extent of the second pandemic plague mentions. We conclude that all NLP tools have their limitations, but they are potentially useful to accelerate the collection of data and the generation of a global plague outbreak database.

Lake thermal structure drives interannual variability in summer anoxia dynamics in a eutrophic lake over 37 years

The concentration of oxygen is fundamental to lake water quality and ecosystem functioning through its control over habitat availability for organisms, redox reactions, and recycling of organic material. In many eutrophic lakes, oxygen depletion in the bottom layer (hypolimnion) occurs annually during summer stratification. The temporal and spatial extent of summer hypolimnetic anoxia is determined by interactions between the lake and its external drivers (e.g., catchment characteristics, nutrient loads, meteorology) as well as internal feedback mechanisms (e.g., organic matter recycling, phytoplankton blooms). How these drivers interact to control the evolution of lake anoxia over decadal timescales will determine, in part, the future lake water quality. In this study, we used a vertical one-dimensional hydrodynamic–ecological model (GLM-AED2) coupled with a calibrated hydrological catchment model (PIHM-Lake) to simulate the thermal and water quality dynamics of the eutrophic Lake Mendota (USA) over a 37 year period. The calibration and validation of the lake model consisted of a global sensitivity evaluation as well as the application of an optimization algorithm to improve the fit between observed and simulated data. We calculated stability indices (Schmidt stability, Birgean work, stored internal heat), identified spring mixing and summer stratification periods, and quantified the energy required for stratification and mixing. To qualify which external and internal factors were most important in driving the interannual variation in summer anoxia, we applied a random-forest classifier and multiple linear regressions to modeled ecosystem variables (e.g., stratification onset and offset, ice duration, gross primary production). Lake Mendota exhibited prolonged hypolimnetic anoxia each summer, lasting between 50–60 d. The summer heat budget, the timing of thermal stratification, and the gross primary production in the epilimnion prior to summer stratification were the most important predictors of the spatial and temporal extent of summer anoxia periods in Lake Mendota. Interannual variability in anoxia was largely driven by physical factors: earlier onset of thermal stratification in combination with a higher vertical stability strongly affected the duration and spatial extent of summer anoxia. A measured step change upward in summer anoxia in 2010 was unexplained by the GLM-AED2 model. Although the cause remains unknown, possible factors include invasion by the predacious zooplankton Bythotrephes longimanus. As the heat budget depended primarily on external meteorological conditions, the spatial and temporal extent of summer anoxia in Lake Mendota is likely to increase in the near future as a result of projected climate change in the region.