Miracle-dz/UniFAR-FTUs huggingface dataset:
Cancer and inflammation studies using zebrafish cell lines

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. The molecular conservation between zebrafish and human liver tumors makes zebrafish a valuable model to study HCC. We established the first reported inducible oncogenic zebrafish cell model, in which oncogenic human Raf-1 can be post-transcriptionally activated in zebrafish liver cells by administration of 4-hydroxytamoxifen (4HT). The Raf-1 activation promoted zebrafish liver cell growth and proliferation, compensated the absence of growth factors, and inhibited apoptosis. The anti-apoptotic effect of Raf-1 was also observed in vivo in zebrafish embryos treated with 4HT after cell implantation. Gene expression profiling of cells treated by 4HT and a MEK-inhibitor identified Raf/MEK-dependent signature sets. This transcriptome response was compared to zebrafish and human liver cancer transcriptome responses and transcriptional markers of hepatocarcinogenesis were identified, showing that the ZFL-ΔRaf1-ER cell line is a valuable model for HCC.
Parsing prospectuses: A text-mining approach

Summary The EU Prospectus Regulation sets out strict requirements on how issuance prospectuses for securities like shares and bonds should be drafted and presented. Because of the importance of these documents for investors, it is useful to understand how actual prospectuses match up with these specific requirements. We aim to contribute to this question by applying natural language processing techniques to a unique dataset consisting of all prospectuses approved under the Prospectus Regulation between end-November 2020 and January 2022. After evaluating 593,000 pages of text, we find that prospectuses from issuers in the EU can pose challenges for those intending to use them: they contain substantial repetition of text, include broken hyperlinks, may present generic and imprecise risk factors, and may include unclear language regarding availability of working capital. In addition, we find statistical evidence that longer prospectuses, all else being equal, contribute to greater divergence among rating agency assessments of credit risk. This suggests that an abundance of material can present a challenge for even specialised readers to identify information that is key to assessing the product. Our findings are a contribution to assessing the content of issuance prospectuses by means of text mining, i.e. an advanced analytical technique which enables the enormous volumes of text that prospectuses entail to be more comprehensively assessed. Our study also illustrates the effectiveness of text mining as a supervisory technology tool.
Making Algorithms Public: Reimagining Auditing from Matters of Fact to Matters of Concern

Stakeholders concerned with bias, discrimination, and fairness in algorithmic systems are increasingly turning to audits, which typically apply generalizable methods and formal standards to investigate opaque systems. We discuss four attempts to audit algorithmic systems with varying levels of success—depending on the scope of both the system to be audited and the audit’s success criteria. Such scoping is contestable, negotiable, and political, linked to dominant institutions and movements to change them. Algorithmic auditing is typically envisioned as settling “matters-of-fact” about how opaque algorithmic systems behave: definitive declarations that (de)certify a system. However, there is little consensus about the decisions to be automated or about the institutions automating them. We reposition algorithmic auditing as an ongoing and ever-changing practice around “matters-of-concern. ” This involves building infrastructures for the public to engage in open-ended democratic understanding, contestation, and problem solving—not just about algorithms in themselves, but the institutions and power structures deploying them. Auditors must recognize their privilege in scoping to “relevant” institutional standards and concerns, especially when stakeholders seek to reform or reimagine them.
Analyzing geospatial variation in articulation rate using crowdsourced speech data

Most recent studies on the geographical distribution of acoustic features analyze comparatively few speakers and localities, both of which may be unrepresentative of the diversity found in larger or more spatially fragmented populations. In the present study we introduce a new paradigm that enables the crowdsourcing of acoustic features through smartphone devices. We used Dialäkt Äpp, a free iOS app that allows users to record themselves, to crowdsource audio data. Nearly 3,000 speakers from 452 localities in German-speaking Switzerland provided recordings; we measured articulation rates for these speakers using a metric based on duration intervals between consecutive vowel onsets. Results revealed distinct regional differences in articulation rate between major dialect regions and individual localities. The specification of 452 localities enabled analyses at an unprecedented spatial resolution. Results further revealed a robust effect of gender, with women articulating significantly more slowly than men. Both the geographical patterns and the effect of gender found in this study corroborate similar findings on Swiss German previously reported in a very limited set of localities, thus verifying the validity of the crowdsourcing framework. Given the application of this new framework, a large bulk of the discussion is devoted to discussing methodological caveats.
Design and Evaluation of a Micro-architecture for Streaming and Vector Computing

Streaming and vector operations are pervasive in many important scientiﬁc and engineering computations. While conﬁgurable architectures can be customized to support these operations, the resulting design solutions are commonly inﬂexible or too low-level to be targeted by high-level compilation and synthesis tools, in eﬀect hampering their use in computing accelerators. This article describes a micro-architecture that greatly facilitates the design of custom reconﬁgurable processors supporting streaming and vector computations. The micro-architecture combines custom data-paths with parallel ports for accessing memory operands and uses a micro-coded sequencer supporting nested looping and streaming. Each port includes a programmable address generator and vector index translator that feeds the data-path inputs from on-chip memories. We evaluate this micro-architecture for two examples: one widely-used image processing kernel and a core function extracted from a UAV navigation application. The performance of the resulting hardware outperform their software implementations by more than an order of
Analysis of Cancer Cases Presented in The National Tumor Board of Bahrain Between 2016 and 2020

The Bahrain National Tumor Board (NTB) was established by a decree issued by the Bahrain Supreme Health Council. Cancer cases are regularly referred to the NTB from all health facilities across the Kingdom. Our aim is to investigate the epidemiological trends of cancer in Bahrain during the period be-tween 2016 and 2020
Coordinating Charitable Donations

Charity is typically carried out by individual donors, who donate money to charities they support, or by centralized organizations such as governments or municipalities, which collect individual contributions and distribute them among a set of charities. Individual charity respects the will of the donors, but may be inefficient due to a lack of coordination; centralized charity is potentially more efficient, but may ignore the will of individual donors. We present a mechanism that combines the advantages of both methods for donors with Leontief preferences (i.e., each donor seeks to maximize an individually weighted minimum of all contributions across the charities). The mechanism distributes the contribution of each donor efficiently such that no subset of donors has an incentive to redistribute their donations. Moreover, it is group-strategyproof, satisfies desirable monotonicity properties, maximizes Nash welfare, can be computed efficiently via convex programming, and can be attained by natural best-response spending dynamics.
ASSESSMENT OF THE VALUE OF SERUM CHOLINESTERASE AS A LIVER FUNCTION TEST IN PATIENT WITH LIVER DISEASES

Background: Liver function is influenced by cholinesterase enzymes, which hydrolyse acetylcholine to choline and acetic acid. Serum cholinesterase activity decreases with liver dysfunction due to reduced synthesis, suggesting that it may be a more specific indicator of liver dysfunction than traditional liver function tests. This study aimed to assess serum cholinesterase levels and liver function, examine the correlation, and grade the severity of liver dysfunction based on cholinesterase levels in patients with chronic liver disease. Materials and Methods: A cross-sectional observational study was conducted in Government Rajaji Hospital Madurai on 50 chronic liver diseases of outpatients and inpatients for six months, from March 2021 to August 2021. After selecting the cases, thorough history-taking and clinical examination were performed. Tests including serum albumin, serum globulin, prothrombin time, INR, ultrasonography of the abdomen, upper GI endoscopy, blood count, erythrocyte sedimentation rate, and C-reactive protein were performed. Result: Chronic liver disease was more common among patients aged 31–40 years, and it was more common in males. High bilirubin levels, coagulopathy, and elevated INR levels were significantly positively correlated with serum albumin and serum cholinesterase levels. Conversely, patients with lower albumin levels have lower serum cholinesterase levels. Serum cholinesterase levels also correlate with the severity of chronic liver disease, with patients with reduced cholinesterase levels having elevated SGOT levels. SGPT levels are also significantly correlated with low serum cholinesterase levels. Conclusion: The present study concludes that Serum cholinesterase can be considered an alternative biomarker for diagnosing and assessing the severity and prognosis of patients with chronic liver diseases.
Strathprints Institutional Repository

We present a new parallelised controller for steering an arbitrary geometric region of a molecular dynamics (MD) simulation towards a desired thermodynamic and hydrodynamic state. We show that the controllers may be applied anywhere in the domain to set accurately an initial MD state, or solely at boundary regions to prescribe non-periodic boundary conditions (PBCs) in MD simulations. The mean molecular structure and velocity autocorrelation function remain unchanged (when sampled a few molecular diameters away from the constrained region) when compared with those distributions measured using PBCs. To demonstrate the capability of our new controllers, we apply them as non-PBCs in parallel to a complex MD mixing nano-channel and in a hybrid MD continuum simulation with a complex coupling region. The controller methodology is easily extendable to polyatomic MD ﬂuids.
Emergent software systems

Contemporary software systems often have millions of lines of code that interact over complex infrastructures. The development of such systems is very challenging due to the increasing complexity of services and the high level of dynamism of current operating environments. In order to support the development and management of such systems, autonomic computing concepts have gained significant importance. The majority of autonomic computing approaches show significant levels of expert dependency in designing adaptive solutions. These approaches usually rely on human-made models and policies to support and guide software adaptation at runtime. These approaches mainly suffer from: i) a significant upfront effort demanded to create such solutions, which adds to the complexity of creating autonomous systems, and ii) unreliability given the high levels of uncertainty in current operating environments, leading the system to degraded performance and error states when subjected to unpredicted operating conditions and unexpected software interactions. Motivated by the problems and limitations of state-of-the-art autonomic computing solutions, this thesis introduces the concept of Emergent Software Systems. These systems are autonomously composed at runtime from discovered components, and are autonomously optimised based on the operating conditions, being able to build their own understanding of their environment and constituent parts. This thesis defines Emergent Software Systems, presenting the challenges of implementing such approach, and presents a fully functioning emergent systems framework that demonstrates this concept in real-world, fully functioning datacentre-based software.
Smith ScholarWorks Smith ScholarWorks

This article serves as the guest editors’ introduction to the Television and New Media special issue dedicated to gender and sexuality in live streaming. Live streaming is a key part of the contemporary digital media landscape; it sits at the center of wide-reaching shifts in how culture, entertainment, and labor are expressed and experienced online today. Gender and sexuality are crucial elements of live streaming. Across live streaming’s many forms, these elements manifest in myriad ways: from gendered performances to gender-based harassment, from LGBTQ community building to real-time sex work. This special issue models an interdisciplinary approach to studying gender and sexuality in live streaming, featuring scholarship from the humanities, social sciences, and human-computer interaction. It also serves as an impassioned call to those who study technological tools and platforms like live streaming to pay attention to the crucial roles that identity, power, embodiment, and intimacy play in these technologies. There can be no full cultural understanding of live streaming that does not address its entanglements with sexuality and gender.
Insights into early pathogenesis of sporadic Alzheimer’s disease: role of oxidative stress and loss of synaptic proteins

Oxidative stress, induced by impaired insulin signaling in the brain contributes to cognitive loss in sporadic Alzheimer’s disease (sAD). This study evaluated early hippocampal oxidative stress, pre- and post-synaptic proteins in intraperitoneal (IP) and intracerebroventricular (ICV) streptozotocin (STZ) models of impaired insulin signaling. Adult male Wistar rats were injected with STZ, IP, or ICV, and sacrificed 1-, 3-, or 6-weeks post injection. Rat’s cognitive behavior was assessed using Morris water maze (MWM) tests at weeks 3 and 6. Hippocampal synaptosomal fractions were examined for oxidative stress markers and presynaptic [synapsin I, synaptophysin, growth-associated protein-43 (GAP-43), synaptosomal-associated protein-25 (SNAP-25)] and postsynaptic [drebrin, synapse-associated protein-97 (SAP-97), postsynaptic density protein-95 (PSD-95)] proteins. IP-STZ and ICV-STZ treatment impaired rat’s cognition, decreased the levels of reduced glutathione (GSH) and increased the levels of thiobarbituric acid reactive species (TBARS) in a time dependent manner. In addition, it reduced the expression of pre- and post-synaptic proteins in the hippocampus. The decline in cognition is significantly correlated with the reduction in synaptic proteins in the hippocampus. In conclusion, impaired insulin signaling in the brain is deleterious in causing early synaptosomal oxidative damage and synaptic loss that exacerbates with time and correlates with cognitive impairments. Our data implicates oxidative stress and synaptic protein loss as an early feature of sAD and provides insights into early biochemical and behavioral changes during disease progression.
Association of Uric Acid to Creatinine Ratio with Metabolic Dysfunction-Associated Fatty Liver in Non-Obese Individuals Without Type 2 Diabetes Mellitus

Introduction Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most common chronic liver disease, which is usually associated with type 2 diabetes mellitus (T2DM) and obesity. However, the incidence of MALFD in non-obese individuals without T2DM is increasing, and the pathogenesis is unclear. Serum uric acid to creatinine ratio (sUA/Cr) can reflect overall metabolic status. This study aims to observe the association between sUA/Cr and MAFLD in non-obese individuals without T2DM. Methods A total of 21,996 individuals were included in this study. The subjects were divided into four subgroups: non-obese patients without T2DM, obese patients without T2DM, non-obese patients with T2DM, and obese patients with T2DM. Logistic regression analyzed the correlation between sUA/Cr and MAFLD subgroups. Receiver operating characteristics analyzed the predictive value of sUA/Cr for MAFLD subgroups. The stratified analyses by sex and age were performed. Results Non-obese MAFLD individuals without T2DM had higher sUA/Cr levels than their counterparts. sUA/Cr was significantly correlated positively with MAFLD in non-obese patients. Similar results were observed in both males and females and in populations at all age stages (all p<0.01). sUA/Cr was capable of discriminating MAFLD in non-obese individuals without T2DM (AUC: 0.667), especially for patients over 60 years old (AUC: 0.704). Conclusion The sUA/Cr ratio was correlated with MAFLD in non-obese patients without T2DM. The predictive value of sUA/Cr for MAFLD was observed. Hence, the sUA/Cr ratio might be given more concern for the risk of MAFLD in non-obese individuals without T2DM.
Individual variation in plant traits drives species interactions, ecosystem functioning, and responses to global change

Education 2011-2016 University of Tennessee, Knoxville, TN Ph.D., Ecology and Evolutionary Biology Dissertation: “Individual variation in plant traits drives species interactions, ecosystem functioning, and responses to global change” Advisor: Dr. Nathan Sanders Short courses: Boreal Forest Ecology (Swedish University of Agricultural Sciences) and Fundamentals of Ecosystem Ecology (Cary Institute of Ecosystem Studies)
Positron spectroscopy of γ-flashes in the earth atmoshear

The registration of the fast thermonuclear transformation in Earth’s atmosphere is considered. One of them is γ-flashes from thunder lightning. The atmospheric chemical composition and bound conditions in the thunder lightning plasma tubes were associated with thermonuclear transformation. Nuclear reaction channel cross-sections were selected for the calculation of the γ-ray spectra. It was found that under existing conditions the γ-spectrum is formed due to the formation of unstable proton-excess nuclei with their further decay. It has been shown that electron-atom collisions are important and only initiate the formation of proton and fully ionized He (after sufficient acceleration, we call them α-particles) current flows. In this case, protons and α-particles initiate nuclear transformation after collisions with atmospheric He, C, N, O, and Ne atoms. The time scale of γ-fluorescence is estimated and related to observation with traditional γ-ray detectors. Separately calculated contribution of pollution admixture from dust into γ-spectra.
Hand Gesture Recognition Using FSK Radar Sensors

Hand gesture recognition, which is one of the fields of human–computer interaction (HCI) research, extracts the user’s pattern using sensors. Radio detection and ranging (RADAR) sensors are robust under severe environments and convenient to use for hand gestures. The existing studies mostly adopted continuous-wave (CW) radar, which only shows a good performance at a fixed distance, which is due to its limitation of not seeing the distance. This paper proposes a hand gesture recognition system that utilizes frequency-shift keying (FSK) radar, allowing for a recognition method that can work at the various distances between a radar sensor and a user. The proposed system adopts a convolutional neural network (CNN) model for the recognition. From the experimental results, the proposed recognition system covers the range from 30 cm to 180 cm and shows an accuracy of 93.67% over the entire range.
Addition of Exogenous Organic Ameliorants Mediates Soil Bacteriome and Microbial Community Carbon Source Utilization Pattern in Coastal Saline–Alkaline Soil

Knowledge regarding how abiotic and biotic environmental factors operate in soil microbiome reassembly remains rudimentary in coastal saline–alkaline soils amended by different organic ameliorants. In this study, field trials were conducted to investigate the impacts and underlying mechanisms of sewage sludge (S) and sludge-based vermicompost (V) at the application amounts of 0, 50, and 100 t ha−1 on soil physicochemical characteristics, carbon source utilization pattern, and bacteriome in coastal saline–alkaline soils. Results revealed that impacts of the organic ameliorants on soil’s physicochemical and microbial attributes were highly dependent upon the carbon types and amounts applied. Unsurprisingly, applying sewage sludge and vermicompost significantly alleviated environmental constraints, such as saline–alkaline stress and nutrient deficiency, with lower pH, salinity, and higher soil organic carbon content observed in organics-amended soils. Specifically, higher microbial substrate metabolic activity, but lower diversity was observed in saline–alkaline soils amended by organic ameliorants. In addition, reassembled bacteriomes harboring distinguishable core and unique community profiles were observed in reclaimed soils as compared to unamended saline–alkaline soil. Procrustes analysis showed that the soil microbial utilization pattern of carbon sources was significantly related to the alterations in their physicochemical property and bacterial core microbiome. Additionally, Redundancy Analysis (RDA) revealed that soil core bacteriome reassembly was dominated by the integrated impacts of soil salinity, successively followed by carbohydrates, amino acids, polymers, pH, soil organic carbon (SOC), and available nitrogen (AN). Overall, this study provides a comprehensive understanding of soil abiotic and biotic determinants in bacteriome assembly in coastal saline–alkaline soil remediation mediated by organic ameliorants.
Neurovascular Relationships in AGEs-Based Models of Proliferative Diabetic Retinopathy

Diabetic retinopathy affects more than 100 million people worldwide and is projected to increase by 50% within 20 years. Increased blood glucose leads to the formation of advanced glycation end products (AGEs), which cause cellular and molecular dysfunction across neurovascular systems. These molecules initiate the slow breakdown of the retinal vasculature and the inner blood retinal barrier (iBRB), resulting in ischemia and abnormal angiogenesis. This project examined the impact of AGEs in altering the morphology of healthy cells that comprise the iBRB, as well as the effects of AGEs on thrombi formation, in vitro. Our results illustrate that AGEs significantly alter cellular areas and increase the formation of blood clots via elevated levels of tissue factor. Likewise, AGEs upregulate the expression of cell receptors (RAGE) on both endothelial and glial cells, a hallmark biomarker of inflammation in diabetic cells. Examining the effects of AGEs stimulation on cellular functions that work to diminish iBRB integrity will greatly help to advance therapies that target vision loss in adults.