Miracle-dz/UniFAR-FTUs huggingface dataset:
Tuning of viscosity and density of non-Newtonian fluids through mixing process using multimodal sensors, sensor fusion and models

The different models that were used to estimate the viscosity in this thesis were Fuzzy Logic model, Feedforward Artificial Neural Network model (ANN), Feedback Artificial Neural Network model and Support Vector Regression (SVR). The performance analysis of these models were done using simulation study and experimental study. Based on the simulation study, Sugeno type-1 Fuzzy Logic model, feedforward ANN model and SVR gives very good estimations compared to the feedback ANN models. For the experimental study, the experiments were done in the Venturi-rig in University College of Southeast Norway, Porsgrunn. The results were very similar to the simulation results, where the three models; Sugeno type-1 Fuzzy Logic, feedforward ANN and SVR had comparable predictions with some accuracy. Based on the analysis from simulation and experimental study, it seems that the empirical models that were developed is capable of estimating the viscosity of non-Newtonian drilling fluids. University College of Southeast Norway accepts no responsibility for results and conclusions presented in this report.
Neoadjuvant chemoradiotherapy followed by oesophagectomy may be the optimal treatment option for lower thoracic oesophageal cancer with supraclavicular lymph node metastasis: An inverse probability of treatment‐weighted analysis of SEER database

Whether supraclavicular lymph node (SCLN) metastasis in patients with oesophageal cancer belongs to regional disease is controversial, leading to heterogeneity in clinical treatment decisions. This study aimed to determine the optimal treatment for lower thoracic oesophageal cancer (LTOC) with SCLN metastasis.
Treated, hospital-onset Clostridiodes difficile infection: An evaluation of predictors and feasibility of benchmarking comparing 2 risk-adjusted models among 265 hospitals

Abstract Objectives: To evaluate the incidence of a candidate definition of healthcare facility-onset, treated Clostridioides difficile (CD) infection (cHT-CDI) and to identify variables and best model fit of a risk-adjusted cHT-CDI metric using extractable electronic heath data. Methods: We analyzed 9,134,276 admissions from 265 hospitals during 2015–2020. The cHT-CDI events were defined based on the first positive laboratory final identification of CD after day 3 of hospitalization, accompanied by use of a CD drug. The generalized linear model method via negative binomial regression was used to identify predictors. Standardized infection ratios (SIRs) were calculated based on 2 risk-adjusted models: a simple model using descriptive variables and a complex model using descriptive variables and CD testing practices. The performance of each model was compared against cHT-CDI unadjusted rates. Results: The median rate of cHT-CDI events per 100 admissions was 0.134 (interquartile range, 0.023–0.243). Hospital variables associated with cHT-CDI included the following: higher community-onset CDI (CO-CDI) prevalence; highest-quartile length of stay; bed size; percentage of male patients; teaching hospitals; increased CD testing intensity; and CD testing prevalence. The complex model demonstrated better model performance and identified the most influential predictors: hospital-onset testing intensity and prevalence, CO-CDI rate, and community-onset testing intensity (negative correlation). Moreover, 78% of the hospitals ranked in the highest quartile based on raw rate shifted to lower percentiles when we applied the SIR from the complex model. Conclusions: Hospital descriptors, aggregate patient characteristics, CO-CDI burden, and clinical testing practices significantly influence incidence of cHT-CDI. Benchmarking a cHT-CDI metric is feasible and should include facility and clinical variables.
Decreased Risk of Esophageal Adenocarcinoma After Gastric Bypass Surgery in a Cohort Study From 3 Nordic Countries

Objective: The objective of this study was to test the hypothesis that bariatric surgery decreases the risk of esophageal and cardia adenocarcinoma. Background: Obesity is strongly associated with esophageal adenocarcinoma and moderately with cardia adenocarcinoma, but whether weight loss prevents these tumors is unknown. Methods: This population-based cohort study included patients with an obesity diagnosis in Sweden, Finland, or Denmark. Participants were divided into a bariatric surgery group and a nonoperated group. The incidence of esophageal and cardia adenocarcinoma (ECA) was first compared with the corresponding background population by calculating standardized incidence ratios (SIR) with 95% CIs. Second, the bariatric surgery group and the nonoperated group were compared using multivariable Cox regression, providing hazard ratios (HR) with 95% CI, adjusted for sex, age, comorbidity, calendar year, and country. Results: Among 748,932 participants with an obesity diagnosis, 91,731 underwent bariatric surgery, predominantly gastric bypass (n=70,176; 76.5%). The SIRs of ECA decreased over time after gastric bypass, from SIR=2.2 (95% CI, 0.9–4.3) after 2 to 5 years to SIR=0.6 (95% CI, <0.1–3.6) after 10 to 40 years. Gastric bypass patients were also at a decreased risk of ECA compared with nonoperated patients with obesity [adjusted HR=0.6, 95% CI, 0.4–1.0 (0.98)], with decreasing point estimates over time. Gastric bypass was followed by a strongly decreased adjusted risk of esophageal adenocarcinoma (HR=0.3, 95% CI, 0.1–0.8) but not of cardia adenocarcinoma (HR=0.9, 95% CI, 0.5–1.6), when analyzed separately. There were no consistent associations between other bariatric procedures (mainly gastroplasty, gastric banding, sleeve gastrectomy, and biliopancreatic diversion) and ECA. Conclusions: Gastric bypass surgery may counteract the development of esophageal adenocarcinoma in morbidly obese individuals.
The transcription regulator ChpA affects the global transcriptome including quorum sensing‐dependent genes in Ralstonia pseudosolanacearum strain OE1‐1

Abstract The gram‐negative plant‐pathogenic β‐proteobacterium Ralstonia pseudosolanacearum strain OE1‐1 produces methyl 3‐hydroxymyristate as a quorum sensing (QS) signal through methyltransferase PhcB and senses the chemical via the sensor histidine kinase PhcS. This leads to activation of the LysR family transcription regulator PhcA, which regulates the genes (QS‐dependent genes) responsible for QS‐dependent phenotypes, including virulence. The transcription regulator ChpA, which possesses a response regulator receiver domain and also a hybrid sensor histidine kinase/response regulator phosphore‐acceptor domain but lacks a DNA‐binding domain, is reportedly involved in QS‐dependent biofilm formation and virulence of R. pseudosolanacearum strain GMI1000. To explore the function of ChpA in QS of OE1‐1, we generated a chpA‐deletion mutant (ΔchpA) and revealed that the chpA deletion leads to significantly altered QS‐dependent phenotypes. Furthermore, ΔchpA exhibited a loss in its infectivity in xylem vessels of tomato plant roots, losing virulence on tomato plants, similar to the phcA‐deletion mutant (ΔphcA). Transcriptome analysis showed that the transcript levels of phcB, phcQ, phcR, and phcA in ΔchpA were comparable to those in OE1‐1. However, the transcript levels of 89.9% and 88.9% of positively and negatively QS‐dependent genes, respectively, were significantly altered in ΔchpA compared with OE1‐1. Furthermore, the transcript levels of these genes in ΔchpA were positively correlated with those in ΔphcA. Together, our results suggest that ChpA is involved in the regulation of these QS‐dependent genes, thereby contributing to the behaviour in host plant roots and virulence of OE1‐1.
HS‐CRP Modifies the Prognostic Value of Platelet Count for Clinical Outcomes After Ischemic Stroke

Background We examined whether the relationship between baseline platelet count and clinical outcomes is modulated by HS‐CRP (high‐sensitivity C‐reactive protein) in patients with ischemic stroke. Methods and Results A total of 3267 patients with ischemic stroke were included in the analysis. The primary outcome was a combination of death and major disability at 1 year after ischemic stroke. Secondary outcomes included major disability, death, vascular events, composite outcome of vascular events or death, and an ordered 7‐level categorical score of the modified Rankin Scale at 1 year. Multivariate logistic regression and Cox proportional hazards regression models were used to assess the association between the baseline platelet count and clinical outcomes stratified by HS‐CRP levels when appropriate. There was an interaction effect of platelet count and HS‐CRP on the adverse clinical outcomes after ischemic stroke (all P interaction<0.05). The elevated platelet count was significantly associated with the primary outcome (odds ratio [OR], 3.14 [95% CI, 1.77–5.58]), major disability (OR, 2.07 [95% CI, 1.15–3.71]), death (hazard ratio [HR], 2.75 [95% CI, 1.31–5.79]), and composite outcome of vascular events or death (HR, 2.57 [95% CI, 1.38–4.87]) among patients with high HS‐CRP levels (all P trend<0.05). Conclusions The HS‐CRP levels had a modifying effect on the association between platelet count and clinical outcomes in patients with ischemic stroke. Elevated platelet count was significantly associated with adverse clinical outcomes in patients with ischemic stroke with high HS‐CRP levels, but not in those with low HS‐CRP levels. These findings suggest that strategies for anti‐inflammatory and antiplatelet therapy should be developed according to the results of both platelet and HS‐CRP testing.
Sex and stress hormone dysregulation as clinical manifestations of hypothalamic function in migraine disorder: A meta‐analysis

Migraine is a leading cause of disability in young adults. It occurs more frequently in females, often comorbidly with stress disorders, suggesting an association with hypothalamic sex and stress hormonal function and a likely interaction with autonomic nervous system activation. Thus, this study aimed to meta‐analyse current literature pertaining to female and male sex hormones (estrogen, progesterone and testosterone concentration), hypothalamic–pituitary–adrenal axis (HPA axis) cortisol responses and heart rate variability (HRV) in migraineurs and controls aged 13–65 years. A systematic search of MEDLINE, Embase, PsycINFO, PubMed, CINAHL and Web of Science databases on 29/08/2022 identified 29 studies for meta‐analysis (encompassing 719 migraineur and 592 control participants) that met inclusion and NHLBI risk of bias criteria. Results demonstrated that estrogen concentrations of female migraineurs were reduced (g = −.60, 95% CI [−.91, −.29], p < .001) in the luteal phase of the menstrual cycle, compared to controls. No differences were found in progesterone levels overall in female migraineurs, nor in testosterone levels in male migraineurs compared to controls. Further, early diurnal cortisol concentrations were elevated (g = .32, 95% CI [.00, .63], p = .036) in female and male migraineurs compared to controls, though no differences were found in HRV of female or male migraineurs compared to controls. These findings of dysregulation of estrogen in females and cortisol dysregulation in female and male migraineurs indicate perturbed hypothalamic function and highlight the association of migraine with stress and the need for further rigorous investigation of hypothalamic neuroendocrine functions in migraineurs of both sexes.
Association of the Polymorphism rs3918242 of the Matrix Metalloproteinase-9 Gene with Coronary Artery Disease in a Younger Population

Abstract Coronary artery disease (CAD) is a complex disease resulting from the interaction of numerous so-called traditional risk factors and comorbid conditions on the one side (such as dyslipidemia, smoking, obesity, diabetes, hypertension) and genetic factors on the other. The evidence of a genetic contribution to the development of CAD, especially in the last 2 decades is consistent. It is important that a number of established gene polymorphisms in the younger CAD population are in the genes involved in the inflammatory response and tissue maintenance and remodeling processes. The aim of this study is to investigate the association of the rs3918242 polymorphism of the matrix metal-loproteinase 9 (MMP9) gene with the coronary artery disease in the younger population. In this observational genetic-association study of cases and controls, the demographic, clinical, laboratory and genetic data of the younger population in a group of selected 70 CAD patients aged up to 45 years were analyzed, of which 35 patients have negative and 35 have positive coronary angiography finding, and 43 are men and 27 are women. The analysis of the genotypic and allelic frequency determined an association of the polymorphism and the occurrence of the positive coronary angiographic findings in the population of patients under the age of 45. The carriers of the heterozygous genotype CT have almost 5 times higher probability of having a positive coronary angiography finding compared to the carriers of the reference homozygous genotype CC (p=0.012). Thus, this parameter could be used for clinical risk assessment for the development of CAD.
Novel role for peptidoglycan carboxypeptidases in maintaining the balance between bacterial cell wall synthesis and degradation

Peptidoglycan (PG) is the main component of the bacterial cell wall; it maintains cell shape while protecting the cell from internal osmotic pressure and external environmental challenges. PG synthesis is essential for bacterial growth and survival, and a series of PG modifications are required to allow expansion of the sacculus. Endopeptidases (EPs), for example, cleave the crosslinks between adjacent PG strands to allow the incorporation of newly synthesized PG. EPs are collectively essential for bacterial growth and must likely be carefully regulated to prevent sacculus degradation and cell death. However, EP regulation mechanisms are poorly understood. Here, we used TnSeq to uncover novel EP regulation factors in Vibrio cholerae. This screen revealed that the carboxypeptidase DacA1 (PBP5) alleviates EP toxicity. dacA1 is essential for viability on LB medium, and this essentiality was suppressed by EP overexpression, revealing that EP toxicity both mitigates, and is mitigated by, a defect in dacA1. A subsequent suppressor screen to restore viability of ΔdacA1 in LB medium was answered by hypomorphic mutants in the PG synthesis pathway, as well as mutations that promote PG degradation. Our data thus reveal a key role of DacA1 in maintaining the balance between PG synthesis and degradation.
Cotton Microbiome Profiling and Cotton Leaf Curl Disease (CLCuD) Suppression through Microbial Consortia associated with Gossypium arboreum

The failure of breeding strategies has caused scientists to shift to other means where the new approach involves exploring the microbiome to modulate plant defense mechanisms against CLCuD. The cotton microbiome of CLCuD-resistant varieties may harbor a multitude of bacterial genera that significantly contribute to disease resistance and provide information on metabolic pathways that differ between the susceptible and resistant varieties. The current study aimed to explore the microbiome of CLCuD-susceptible Gossypium hirsutum and CLCuD-resistant Gossypium arboreum. Microbial community surveys performed using 16S rRNA gene amplification revealed that Pseudomonas inhabited the rhizosphere while Bacillus was predominantly found in the phyllosphere of CLCuV-tolerant G. arboreum. The study was done for the leaf endophyte, leaf epiphyte, rhizosphere, and root endophyte of the two cotton species. Furthermore, our disease incidence assay using pot experiments has revealed mechanistic insights through salicylic acid-producing Serratia spp. and Fictibacillus spp. isolated from CLCuD-resistant G. arboreum, which exhibited viral disease suppression and induced systemic resistance in CLCuD susceptible G. hirsutum.
The h-current controls cortical recurrent network activity through modulation of dendrosomatic communication

A fundamental feature of the cerebral cortex is the ability to rapidly turn on and off maintained activity within ensembles of neurons through recurrent excitation balanced by inhibition. Here we demonstrate that reduction of the h-current, which is especially prominent in pyramidal cell dendrites, strongly increases the ability of local cortical networks to generate maintained recurrent activity. Reduction of the h-current resulted in hyperpolarization and increase in input resistance of both the somata and apical dendrites of layer 5 pyramidal cells, while strongly increasing the dendrosomatic transfer of low (<20 Hz) frequencies, causing an increased responsiveness to dynamic clamp-induced recurrent network-like activity injected into the dendrites and substantially increasing the duration of spontaneous Up states. We propose that modulation of the h-current may strongly control the ability of cortical networks to generate recurrent persistent activity and the formation and dissolution of neuronal ensembles.
Probing of dark energy properties in the Universe using astrophysical observations

The astrophysical data of the last two decades have allowed cosmologists to conclude that the present Universe is accelerating. The research carried out to find the origin of this phenomenon has led to the creation of a vast number of dark energy and modified gravity theories, of which the simplest is the ΛCDM model. The latter is, however, plagued with very difficult problems awaiting a solution. The work here presented seeks to contribute to the discussion of the possible explanation for the Cosmos’ acceleration and other important questions in modern cosmology using the newest astrophysical observations available. This thesis starts by exploring a dark energy model dubbed thawing quintessence which is characterised by allowing a non constant ratio of pressure to density for dark energy that is however still close to −1 for most of the cosmological evolution, shifting away from this value when the domination of the radiation and matter components fades away. The findings are the most up-to-date constraints for which this model gives a viable theory for dark energy, including a bound on the equation of state at present of w < −0.88. This exact approach was contrasted with the use of an approximate equation-of-state parametrisation for thawing theories. The analysis also includes different parametrisation choices, and comments on the accuracy of the constraints imposed by CMB anisotropies alone. Next, the cosmology of hybrid metric-Palatini gravity is presented. This is a type of Modified Gravity theory in which the Lagrangian density for the gravitational action is a function of the Ricci scalars of both the connection and the metric. The background evolution of two models of this kind is examined explicitly showing the recovery of standard General Relativity at late times. The maximum deviation from the gravitational constant G at early times is constrained using a combination of geometrical data, finding it to be around 1%.
Unsupervised Image Classification of Fish Without the Inference of Cluster Number

—We aim to implement a deep learning based clustering algorithm (DeepDPM) for clustering fish images into different classes. Unlike other unsupervised methods this is a non-parametric method that does not require specifying of the number of clusters at the beginning as the algorithm infers it during the learning. We have replicated the results of DeepDPM algorithm on the MNIST, Fashion-MNIST, USPS, STL10, and ImageNet datasets as showcased by them. We now plan to implement the algorithm on the Fish4-Knowledge dataset consisting of unlabelled fish images of 23 different species in order to cluster rare fish group. This work will help enable automated monitoring and detection of unknown species of fish around commercial infrastructure.
24 Internalized Devaluation and Situational Threat

In this chapter, we consider research and theory on the idea that prejudice and discrimination lower the self-esteem of people with stigmatized identities. We describe how studies of the effects of stigma on self-esteem progressively evolved to (a) examine moderators of the effects of social stigma on self- esteem; (b) examine how situational variables shape the meaning of prejudice, stereotypes, and stigma; (c) frame social stigma as a situational predicament with which targets of stigma actively cope; and (d) view the stigmatized as caught between protecting self-esteem at the cost of learning, relationships, and/or motivation versus sustaining learning, motivation, and relationships at the cost of self-esteem. We argue that situational cues, personal beliefs, and collective representations trigger a self-focused motivational orientation, which has undesirable consequences. Initial evidence shows that shifting from self-image goals to compassionate goals can protect the self-esteem of targets of stigma, and help create positive relationships between people with stigmatized and nonstigmatized identities.
COMPARATIVE STUDY OF AUTOENCODER AND DENSENET – 121 IN CRIME PREDICTION

A purposeful action that results in harm to one's person, harm to one's property, or both constitutes a crime. Depending on the offense's seriousness, the state or other authorities may punish the offender. Authorities are being forced to devise effective preventive measures due to the worrisome rise in both the quantity and types of criminal activity. In the current climate, where crime has sharply increased, traditional crime resolution approaches are sluggish and ineffectual. Hence, it will lessen the strain on the police and aid in crime prevention if you can figure out a means to foresee crime, predict it in detail before it occurs, or develop a "machine" that can support police personnel. The sole goal of this research is to determine how government agencies, including law enforcement, may use computer vision and machine learning to spot, stop, and combat crime. In conclusion, advancements in computer vision and machine learning can speed up the growth of law businesses. The proposed research uses neural networks with autonomous coding, decoding, and Artificial Intelligence to learn condensed versions of raw inputs, autoencoder-style neural network kinds can be employed. The branch of AI known as computer vision teaches computers to extract and decipher information from picture and video data. By altering the typical CNN design and streamlining the connecting pattern between layers, DenseNet - 121 finds a solution to this issue. Based on a comparison of autoencoder and DenseNet - 121 for crime prediction, this suggested work was created.
A class of primal-dual interior-point methods for convex quadratic optimization based on a parametric kernel function with a trigonometric barrier term

In this paper, a class of large- and small-update primal-dual interior-point methods for convex quadratic optimization based on a parametric kernel function with a trigonometric barrier term is proposed. By utilizing the feature of the parametric kernel function, we establish the worst case iteration bounds for both versions of the kernel-based interior-point methods, namely,   3 2 O n log(n / ) andO n log(n / ) , respectively. These results match the ones obtained in the linear optimization case.