Miracle-dz/UniFAR-FTUs huggingface dataset:
Modelling and reasoning with chain event graphs in health studies

The Chain Event Graph (CEG) is a new class of graphical model, first introduced in Smith and Anderson [2008], which is derived from a probability tree by merging vertices whose associated conditional probabilities are the same. It is proving to be a useful framework for modelling asymmetric problems and further generalises the Bayesian Network (BN), by allowing for context-specific dependence structures between the variables of the problem. This thesis provides a first demonstration of the value of using the CEG in real-world applications and the new techniques developed here are motivated by problems that arise from two health studies; the Christchurch Health and Development Study (CHDS) and the UK Cerebral Palsy (UKCP) Cohort Study. A direct comparison of the BN and CEG on the CHDS demonstrates that the CEG can lead to significantly higher scoring models than the BN and further that it enables additional conclusions to be drawn on the health study directly from the topology of its graph. An extension of the CEG, the Ordinal CEG, is developed in this thesis, which further enhances the graphical representation of the CEGs for studies with a binary outcome. Motivated by the UKCP this thesis further investigates how missing data structures can be explicitly represented by a CEG and how its graph can consequently provide a precise understanding of the influence of missingness. Finally, a dynamic version of the CEG is developed and it is demonstrated how this new class of models generalises the Dynamic BN and is further closely linked to (semi-) Markov processes. The expressiveness of this model is illustrated through a fictional example.
Influence of electrical excitation on the optical pulse generated by gain-switched semiconductor lasers

Gain switched semiconductor laser system is a simple method to generate ultrashort optical pulses. It has been widely used in optical fiber communication, precision machining, precision measurement, biomedical and other fields. In order to advance the research on gain-switched semiconductor lasers, the effects of external electrical excitation signals on the optical pulses output from the gain-switched semiconductor lasers (GS-LD) were studied by simulation and experiment. The research included the influence of bias current, power and frequency of the modulation signal on the optical pulse, respectively. In addition, the reasons for these influences were analyzed. Selecting the appropriate bias current and modulation signal parameters can make the laser output high-quality picosecond pulses with narrow pulse width and small tailing. The results and analysis presented in this paper have implications for the study of the optimal operation state of gain-switched semiconductor lasers and subsequent research on it.
Antileishmanial Anthracene Endoperoxides: Efficacy In Vitro, Mechanisms and Structure-Activity Relationships

Leishmaniasis is a vector-borne disease caused by protozoal Leishmania parasites. Previous studies have shown that endoperoxides (EP) can selectively kill Leishmania in host cells. Therefore, we studied in this work a set of new anthracene-derived EP (AcEP) together with their non-endoperoxidic analogs in model systems of Leishmania tarentolae promastigotes (LtP) and J774 macrophages for their antileishmanial activity and selectivity. The mechanism of effective compounds was explored by studying their reaction with iron (II) in chemical systems and in Leishmania. The correlation of structural parameters with activity demonstrated that in this compound set, active compounds had a LogPOW larger than 3.5 and a polar surface area smaller than 100 Å2. The most effective compounds (IC50 in LtP < 2 µM) with the highest selectivity (SI > 30) were pyridyl-/tert-butyl-substituted AcEP. Interestingly, also their analogs demonstrated activity and selectivity. In mechanistic studies, it was shown that EP were activated by iron in chemical systems and in LtP due to their EP group. However, the molecular structure beyond the EP group significantly contributed to their differential mitochondrial inhibition in Leishmania. The identified compound pairs are a good starting point for subsequent experiments in pathogenic Leishmania in vitro and in animal models.
A Stepwise Discrimination Method of Multi-Index in Landslide Stability Monitoring

The deep displacement monitoring can directly reflect the deformation information inside the slope and can provide an important evidence for the identification of landslide stability. Based on the monitoring data on deep displacement of borehole, there are many monitoring indicators that can reflect the slope state. However, these indicators have their own applicability, and they are independent of each other, which cannot fully reflect the true movement state of the landslide. Therefore, it is necessary to establish a scientific method to give full play to the strengths of each monitoring index and improve the accuracy of identification for landslide stability. Here, the near-surface accumulative displacement, displacement rate, kinetic energy, and the rate of change of kinetic energy are selected as main monitoring indicators to establish a multi-index stepwise discrimination method for landslide stability in this study. This method analyzes the total deformation characteristics and movement trend of landslide from three aspects: surface displacement, internal displacement rate, and slope energy. Relied on the monitoring data on deep displacement of borehole of a landslide in Wushan County, Chongqing, China, this study finds that a single index is easily disturbed by external factors, causing the abnormal mutation in curve which affects analysis of landslide deformation. The variation characteristics of curve among multiple indexes can be mutually corroborated, effectively identify the abnormal fluctuation of the curve, and avoid the identification errors of landslide movement state. In addition, we also found that when there is an obvious sliding surface on the slope, the displacement rate curve will cluster at the sliding surface along the depth direction in this study. And this feature can be used as an important basis for the identification of sliding surface. The method proposed in this study can provide reference and suggestions for the actual treatment of landslide and monitoring data on deep displacement mining.
Micro-CT Evaluation of Different Root Canal Irrigation Protocols on the Removal of Accumulated Hard Tissue Debris: A Systematic Review and Meta-Analysis

Accumulated hard tissue debris (AHTD) is an inevitable by-product during endodontic treatment and is difficult to remove completely using traditional syringe and needle irrigation (SNI). Adjunctive irrigation is proposed to assist the clean-up of AHTD. This systematic review and meta-analysis aimed to evaluate the AHTD removal efficacy of different root canal irrigation devices using micro-computed tomography (Micro-CT). A literature search was carried out within the main scientific databases until 20 June 2022. All results were screened with detailed eligibility criteria. Eleven studies were included for analysis. SNI, passive ultrasonic irrigation (PUI), negative pressure systems, sonically activated irrigation (SAI), mechanical-activated system and laser-activated irrigation (LAI) were assessed. PUI is superior to SNI for debris removal and LAI has better AHTD removal performance than PUI. The negative pressure system and mechanical-activated system were proved to be less effective. Registration: PROSPERO (CRD42021273892).
Comparing the COVID-19 Mortality Rate in Cancer Patients with and Without a History of Chemotherapy

Background: Patients with cancer are potentially vulnerable to COVID-19 infection due to the immune-compromised state of cancer or its treatment complications. Objectives: This study compared the COVID-19 mortality rate in cancer patients with and without a history of chemotherapy. Methods: This registry-based cohort study launched from March 2020 to March 2021 contains 2350 records in which 64 COVID-19 patients with cancer were included, of which 27 patients underwent the chemotherapy plan within eight weeks before confirmed COVID-19. In addition, age and sex were matched in patients without a history of cancer as a control group. Two groups of cancer patients with and without a history of chemotherapy compared to the control group using cox proportional hazard regression models in Stata.10 software. Results: Patients with cancer had a higher hazard for in-hospital mortality from COVID-19 infection (adjusted HR; 2.27, 95% CI: 1.25 - 4.13, P = 0.007) after adjusting for age, sex, body mass index (BMI), and co-morbidities. Our result showed no significant association between chemotherapy and control groups (adjusted HR; 1.65, 95% CI: 0.60 - 4.56, P = 0.33). Conclusions: Patients with cancer faced a risk of mortality from COVID-19 two times higher than those without cancer. However, chemotherapy did not increase the mortality following COVID-19 infection.
Isolation and characterization of a rare polar carotenoid 1’-OH-4-keto-ϒ-carotene from an indigenously isolated Rhodococcus kroppenstedtii MH715196

The catabolic diversity and biocatalytic potential in members of genus Rhodococcus makes it an ideal industrial workhouse for metabolite production. Despite their applicability, Rhodococci are least explored for carotenoids, located in their cell membrane. The goal of the present study was to identify the carotenoids of Rhodococcus kroppenstedtii MH715196. UV-Vis spectral data and molecular mass estimates showed that the principal carotenoid extracted from R. kroppenstedtii MH715196 was 1’-OH-4-keto-ϒ-carotene. Biosynthetic route of 1’-OH-4-keto-ϒ-carotene in R. kroppenstedtii MH715196 was postulated on the basis of molecular mass estimates in co-relation with putative carotenoid biosynthetic genes identified in the genome of the reference strains of R. kroppenstedtii. Three key enzymes, were then considered for phylogenetic analysis to establish the phylogenetic relationship across the Rhodococcus genus leading the way for carotenoid identification in other Rhodococcus species. The present study would be the first report on identification of a rare polar carotenoid from R. kroppenstedtii MH715196 which could be potentially explored as a food colorant in hydrophilic food matrices like jams, jellies, beverages etc.
Mesenchymal stem cells to treat female infertility; future perspective and challenges: A review

Abstract Infertility negatively impacts the overall health and social life of affected individuals and couples. Female infertility is their inability to perceive pregnancy. To date, polycystic ovary syndrome, primary ovarian insufficiency, fallopian tube obstruction, endometriosis, and intrauterine synechiae have been identified as the primary causes of infertility in women. However, despite the mutual efforts of clinicians and research scientists, the development of an effective treatment modality has met little success in combating female infertility. Intriguingly, significant research has demonstrated mesenchymal stem cells as an optimal source for treating infertility disorders. Therefore, here we attempted to capsulize to date available studies to summarize the therapeutic potential of mesenchymal stem cells in combating infertility in women by focusing on the underlying mechanism through which stem cells can reduce the effects of ovarian disorders. Furthermore, we also discussed the preclinical and clinical application of stem cell therapy, their limitation, and the future perspective to minimize these limitations.
Analysis of the Anti-Inflammatory and Anti-Osteoarthritic Potential of Flonat Fast®, a Combination of Harpagophytum Procumbens DC. ex Meisn., Boswellia Serrata Roxb., Curcuma longa L., Bromelain and Escin (Aesculus hippocastanum), Evaluated in In Vitro Models of Inflammation Relevant to Osteoarthrit

Osteoarthritis (OA) is a joint disease characterized by inflammation of the synovium, angiogenesis, cartilage degradation, and osteophyte formation. Harpagophytum Procumbens DC. ex Meisn. , Boswellia Serrata Roxb. , Curcuma longa L. , Bromelain and Escin (Aesculus hippocastanum) are plants which extracts, together to Bromelain and Escin (Aesculus hippocastanum) are traditionally used in OA. However, their mechanistic role remains unclear. We aimed to investigate whether these bioactives alone or in combination (as in Flonat Fast®) can suppress TNF-α-induced inflammation, angiogenesis, and osteophyte formation using two cell models involved in OA: endothelial cells and monocytes. Each plant extract was evaluated for its polyphenol content, antioxidant activity, and toxicity. In endothelial cells and monocytes, expression of genes involved in OA was assessed, functional assays for inflammation and angiogenesis were performed, and impairment of reactive oxygen species production (ROS) was evaluated. Exposure of cells to the bioactives alone and in combination before cytokine stimulation resulted in differential counterregulation of several gene and protein expressions, including those for cyclooxygenases-2, metalloproteinase-9, transforming growth factor β1, and bone morphogenic protein-2. We demonstrated that these bioactives modulated monocyte adhesion to endothelial cells as well as cell migration and endothelial angiogenesis. Consistent with radical scavenging activity in the cell-free system, the bioactives curbed TNF-α-stimulated intracellular ROS production. We confirmed the potential anti-inflammatory and antiangiogenic effects of the combination of Harpagophytum procumbens, Boswellia, Curcuma, Bromelain, and Escin and provided new mechanistic evidence for their use in OA. However, further clinical studies are needed to evaluate the true clinical utility of these bioactives as supportive, preventive, and therapeutic agents.
Interacting bosons in one dimension and the applicability of Luttinger-liquid theory as revealed by path-integral quantum Monte Carlo calculations

Harmonically trapped ultracold atoms and $^{4}\text{H}\text{e}$ in nanopores provide different experimental realizations of bosons in one dimension, motivating the search for a more complete theoretical understanding of their low-energy properties. Worm algorithm path-integral quantum Monte Carlo results for interacting bosons restricted to the one dimensional continuum are compared to the finite temperature and system size predictions of Luttinger-liquid theory. For large system sizes at low temperature, excellent agreement is obtained after including the leading irrelevant interactions in the Hamiltonian which are determined explicitly.
A Case Study in Formal Testing and an Algorithm for Automatic Test Case Generation with Symbolic Transition Systems

We present a case study of two black-box testing techniques. We compare constraint logic programming with symbolic transition systems. Both techniques generate automatically test cases out of the specification of an algorithm. After our case study we decided to design an algorithm to improve the technique using symbolic transition systems with a way to generate test cases automatically based on a coverage criterion. Because we do black-box testing and we have no access to the implementation of the algorithm, we apply this coverage criterion to the specification. Our algorithm attempts to cover all states of the symbolic transition system that models the specification of the algorithm. This task is complicated due to nondeterminism and symbolic constraints in the model. We use an external constraint solver to solve these constraints. We try to simplify them as much as possible because constraint solvers only have limited power and often use a great amount of computational resources.
A transfer learning-based system for grading breast invasive ductal carcinoma

Breast carcinoma is a sort of malignancy that begins in the breast. Breast malignancy cells generally structure a tumour that can routinely be seen on an x-ray or felt like a lump. Despite advances in screening, treatment, and observation that have improved patient endurance rates, breast carcinoma is the most regularly analyzed malignant growth and the subsequent driving reason for malignancy mortality among ladies. Invasive ductal carcinoma is the most boundless breast malignant growth with about 80% of all analyzed cases. It has been found from numerous types of research that artiﬁcial intelligence has tremendous capabilities, which is why it is used in various sectors, especially in the health-care domain. In the initial phase of the medical ﬁeld, mammography is used for diagnosis, and ﬁnding cancer in the case of a dense breast is challenging. The evolution of deep learning and applying the same in the ﬁndings are helpful for earlier tracking and medication. The authors have tried to utilize the deep learning concepts for grading breast invasive ductal carcinoma using Transfer Learning in the present work. The authors have used ﬁve transfer learning approaches here, namely VGG16, VGG19, InceptionReNetV2, DenseNet121, and DenseNet201 with 50 epochs in the Google Colab platform which has a single 12GB NVIDIA Tesla K80 graphical processing unit (GPU) support that can be used up to 12 h continuously. The dataset used for this work can be openly accessed from http://databiox.com. The experimental results that the authors have received regarding the algorithm’s accuracy are as follows: VGG16 with 92.5%, VGG19 with 89.77%, InceptionReNetV2 with 84.46%, DenseNet121 with 92.64%, DenseNet201 with 85.22%. From the experimental results, it is clear that the DenseNet121 gives the maximum accuracy in terms of cancer grading, whereas the InceptionReNetV2 has minimal accuracy.
Probing the surface magnetic field structure in RX J1856.5-3754

The evolution of magnetic field in isolated neutron stars is one of the most important ingredients in the attempt to build a unified description of these objects. A prediction of field evolution models is the existence of an equilibrium configuration, in which the Hall cascade vanishes. Recent calculations have explored the field structure in this stage, called the Hall attractor. We use X-ray data of near-by, cooling neutron stars to probe this prediction, as these sources are surmised to be close to or at Hall attractor phase. We show that the source RX J1856.5-3754 might be closer to the attractor than other sources of its class. Our modelling indicates that the properties of surface thermal emission, assuming that the star is in the Hall attractor, are in contradiction with the spectral data of RX J1856.5-3754.
Impact of the strong electromagnetic field on the QCD effective potential for homogeneous Abelian gluon field configurations

The one-loop quark contribution to the QCD effective potential for the homogeneous Abelian gluon field in the presence of an external strong electromagnetic field is evaluated. The structure of extrema of the potential as a function of the angles between chromoelectric, chromomagnetic, and electromagnetic fields is analyzed. In this setup, the electromagnetic field is considered as an external one while the gluon field represents domain structured nonperturbative gluon configurations related to the QCD vacuum in the confinement phase. Two particularly interesting gluon configurations, (anti-)self-dual and crossed orthogonal chromomagnetic and chromoelectric fields, are discussed specifically. Within this simplified framework it is shown that the strong electromagnetic fields can play a catalyzing role for a deconfinement transition. At the qualitative level, the present consideration can be seen as a highly simplified study of an impact of the electromagnetic fields generated in relativistic heavy ion collisions on the strongly interacting hadronic matter.
Exciton-phonon scattering and photoexcitation dynamics in J-aggregate microcavities

We have developed a model accounting for the photo-excitation dynamics and the photoluminescence of strongly coupled J-aggregate microcavities. Our model is based on a description of the J-aggregate film as a disordered Frenkel exciton system in which relaxation occurs due to the presence of a thermal bath of molecular vibrations. In a strongly coupled microcavity exciton-polaritons are formed, mixing superradiant excitons and cavity photons. The calculation of the microcavity steady-state photoluminescence, following a CW non resonant pumping, is carried out. The experimental photoluminescence intensity ratio between upper and lower polariton branches is accurately reproduced. In particular both thermal activation of the photoluminescence intensity ratio and its Rabi splitting dependence are a consequence of the bottleneck in the relaxation, occurring at the bottom of the excitonic reservoir. The effects due to radiative channels of decay of excitons and to the presence of a paritticular set of discrete optical molecular vibrations active in relaxation processes are investigared.
Prenatal, lactation and postnatal effects of lead acetate on histological, histochemical and hepatic indices of liver of male offspring wistar rats

The aim of this study was to investigate the possible effects of maternal administration to lead acetate on the morphological structure of the liver; AST, ALT, ALP and GGT levels and glycogen content of hepatocytes of male offspring wistar rats. Female rats were exposed to 0.2% lead acetate in drinking water and the study was performed on their male offspring (7 groups). To evaluate the levels of liver enzymes, blood samples were taken from rats after anesthesia. After dissection, to study its morphological structure and glycogen content of hepatocytes, liver tissue was isolated and transferred to 10% formalin. To measure the levels of hepatic enzymes; AST, ALT, ALP and GGT; serum samples were evaluated. For histological examinations, liver tissue samples were embedded in paraffin after tissue processing and 3 μm thickness sections were prepared from them and then H&E and PAS staining was performed. The results showed that exposure to 0.2% lead acetate induced significant changes in liver enzyme levels in different experimental groups.
INSIGHTS TO 11 SMART CITIES OF UTTAR PRADESH, INDIA THROUGH SPATIAL PATTERN ANALYSIS OF LAND USE/ LAND COVER

Abstract. Urban planning of a smart city needs to be done in conjunction to Urban Green Spaces (UGS). Landscape Metrics are one of the efficient ways to analyze the patterns of Land use/Land cover (LU/LC) in a study area. Spatio-temporal change in the urban dynamics of the 11 smart cities of Uttar Pradesh state of India namely "Agra", "Aligarh", "Bareilly", "Jhansi", "Kanpur", "Lucknow", "Moradabad", "Prayagraj", "Rampur", "Saharanpur" and "Varanasi" are studied using Landscape Metrics with the help of publically available classified data such as, for years 1985, 1995 and 2005, Decadal Land use data of India and for year 2015, Copernicus Global Land service Dynamic Land Cover layers (CGLS-LC100 products). Landscape Shape Index (LSI), Largest Patch Index (LPI), Mean Euclidean Nearest Neighbor Distance (ENN_MN) and Aggregation Index (AI) are 4 general metrics used to map LU/LC patterns. Results indicate high positive relationship between LSI and AI values but negligible relationship between LPI and ENN_MN values of built-up and vegetation patches in study area. LPI and LSI show increase in values over the years with LSI showing more steep change in duration, but values of ENN_MN and AI show gradual decreasing trend over the years. Among 11 smart cities, only “Kanpur”, “Agra” and “Moradabad” are most similar in values at higher, average and lower side of metrics with “Lucknow” showing highest complexity for both classes. In general, a heterogenous growth of patches appear in the study area with “Rampur” being the most consistent in metrics while “Jhansi” and “Saharanpur” being most inconsistent.