Stationary states in two lane traffic: insights from kinetic theory

Kinetics of dilute heterogeneous traffic on a two lane road is formulated in the framework of the Ben-Naim Krapivsky model and stationary state properties are analytically derived in the asymptotic limit. The heterogeneity is introduced as a quenched disorder in desired speeds of vehicles. The model assumes that each vehicle/platoon in a lane moves ballistically until it approaches a slow moving vehicle/platoon and then joins it. Vehicles in a platoon are assumed to escape the platoon at a constant rate by changing lanes. Each lane is assumed to have a different escape rate. As the stationary state is approached, the platoon density in the two lanes become equal, whereas the vehicle densities and fluxes are higher in the lane with lower escape rate. A majority of the vehicles enjoy a free-flow if the harmonic mean of the escape rates of the lanes is comparable to average initial flux on the road. The average platoon size is close to unity in the free-flow regime. If the harmonic mean is lower than the average initial flux, then vehicles with desired speeds lower than a characteristic speed $v^*$ still enjoy free-flow while those vehicles with desired speeds that are greater than $v^*$ experience congestion and form platoons behind the slower vehicles. The characteristic speed depends on the mean of escape times $(R=(R_1+R_{-1})/2)$ of the two lanes (represented by 1 and -1) as $v^* \sim R^{-\frac{1}{\mu+2}}$, where $\mu$ is the exponent of the quenched disorder distribution for desired speed in the small speed limit. The average platoon size in a lane, when $v^* \ll 1$, is proportional to $R^{\frac{\mu+1}{\mu+2}}$ plus a lane dependent correction. Equations for the kinetics of platoon size distribution for two-lane traffic are also studied. It is shown that a stationary state with platoons as large as road length can occur only if the mean escape rate is independent of platoon size

Reasons for the possible incomprehensibility of some verses of three translations of the meaning of the Holy Quran into English

Translations of the meaning of the Quran in English are becoming amongst the most read books in the world. Unfortunately, almost all the existing renditions fail to transfer the original clearly into the target language. They suffer from serious shortcomings that cause incomprehensibility in parts of the text. These renditions contain some elements that make the target reader struggle to understand the meaning. This research aims to contribute to overcoming the shortcomings of existing translations. It discusses the reasons why the English target reader of the Quran struggles to follow and comprehend the meaning of some of its verses, and attempts to find a workable methodology for translating the meaning of the Quran. It tries to find new methods to help tackle the weaknesses in the translations of the meaning of the Quran and provides suggestions for improving them. It is hoped this methodology will lead to producing a more accurate and comprehensible translation of the meaning of the Quran in which the meaning is transferred clearly in a natural-sounding targetlanguage text, and that will improve comprehensibility for both Muslim and non- Muslim native speakers of English. This research also studies the role and importance of the translator in achieving a good translation, and tries to establish a set of criteria for the attributes and conditions of the translator of the Quran.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Learning New Tricks from Old Dogs -- Inter-Species, Inter-Tissue Domain Adaptation for Mitotic Figure Assessment

For histopathological tumor assessment, the count of mitotic figures per area is an important part of prognostication. Algorithmic approaches - such as for mitotic figure identification - have significantly improved in recent times, potentially allowing for computer-augmented or fully automatic screening systems in the future. This trend is further supported by whole slide scanning microscopes becoming available in many pathology labs and could soon become a standard imaging tool. For an application in broader fields of such algorithms, the availability of mitotic figure data sets of sufficient size for the respective tissue type and species is an important precondition, that is, however, rarely met. While algorithmic performance climbed steadily for e.g. human mammary carcinoma, thanks to several challenges held in the field, for most tumor types, data sets are not available. In this work, we assess domain transfer of mitotic figure recognition using domain adversarial training on four data sets, two from dogs and two from humans. We were able to show that domain adversarial training considerably improves accuracy when applying mitotic figure classification learned from the canine on the human data sets (up to +12.8% in accuracy) and is thus a helpful method to transfer knowledge from existing data sets to new tissue types and species.Comment: 5 pages, submission to BVM 202

A comprehensive multi-domain dataset for mitotic figure detection

The prognostic value of mitotic figures in tumor tissue is well-established for many tumor types and automating this task is of high research interest. However, especially deep learning-based methods face performance deterioration in the presence of domain shifts, which may arise from different tumor types, slide preparation and digitization devices. We introduce the MIDOG++ dataset, an extension of the MIDOG 2021 and 2022 challenge datasets. We provide region of interest images from 503 histological specimens of seven different tumor types with variable morphology with in total labels for 11,937 mitotic figures: breast carcinoma, lung carcinoma, lymphosarcoma, neuroendocrine tumor, cutaneous mast cell tumor, cutaneous melanoma, and (sub)cutaneous soft tissue sarcoma. The specimens were processed in several laboratories utilizing diverse scanners. We evaluated the extent of the domain shift by using state-of-the-art approaches, observing notable differences in single-domain training. In a leave-one-domain-out setting, generalizability improved considerably. This mitotic figure dataset is the first that incorporates a wide domain shift based on different tumor types, laboratories, whole slide image scanners, and species

Actual online shopping behavior among Jordanian customers

Internet technology is becoming increasingly important in our daily life in general and in business world particularly.This increased role of the Internet encourages the researchers to investigate the customer behavior in this emerging market. The aim of this study is to examine the factors that give rise to the formation of the actual online shopping behavior of Jordanian customers.The study analyses the predictor variables of planned behavior among 313 university academic staff selected on the basis of probability sampling.Structural equation modeling (SEM) was used to analyze the causal relationships in accordance with the theory of planned behavior (TPB).The findings depicted that subjective norm and perceived behavioral control to have significant positive effects on intention. Attitude has no direct significant impact on online shopping intention.Online shopping intention also has a positive and significant impact on actual online shopping behavior.The practical implication of the research is discusse

Nitroheterocyclic drugs cure experimental <i>Trypanosoma cruzi</i> infections more effectively in the chronic stage than in the acute stage

The insect-transmitted protozoan parasite Trypanosoma cruzi is the causative agent of Chagas disease, and infects 5-8 million people in Latin America. Chagas disease is characterised by an acute phase, which is partially resolved by the immune system, but then develops as a chronic life-long infection. There is a consensus that the front-line drugs benznidazole and nifurtimox are more effective against the acute stage in both clinical and experimental settings. However, confirmative studies have been restricted by difficulties in demonstrating sterile parasitological cure. Here, we describe a systematic study of nitroheterocyclic drug efficacy using highly sensitive bioluminescence imaging of murine infections. Unexpectedly, we find both drugs are more effective at curing chronic infections, judged by treatment duration and therapeutic dose. This was not associated with factors that differentially influence plasma drug concentrations in the two disease stages. We also observed that fexinidazole and fexinidazole sulfone are more effective than benznidazole and nifurtimox as curative treatments, particularly for acute stage infections, most likely as a result of the higher and more prolonged exposure of the sulfone derivative. If these findings are translatable to human patients, they will have important implications for treatment strategies