Miracle-dz/UniFAR-FTUs huggingface dataset:
Chromobox Homologue 7 Acts as a Tumor Suppressor in Both Lung Adenocarcinoma and Lung Squamous Cell Carcinoma via Inhibiting ERK/MAPK Signaling Pathway

Chromobox homologue 7 (CBX7) is a member of the polycomb group family that plays a pivotal role in regulating cellular processes in human cancers. This study aims to explore the function and underlying molecular mechanisms of CBX7 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). The expression of CBX7 in LUAD and LUSC tissues was analyzed by UALCAN and GEPIA based on the TCGA database. Cell viability and apoptosis were measured by CCK-8 and flow cytometry assays, respectively. Cell migration and invasion were detected by transwell assay. The functions of downregulated genes in LUAD were enriched via GO and KEGG pathway analyses. The mRNA expression of CBX7, ERK1/2, and p38 was determined by qRT-PCR, and the protein levels of CBX7, ERK1/2, p-ERK1/2, p38, and p-p38 were measured by Western blotting. Tumor xenograft model was established to validate the antitumor effect of CBX7. The expression of CBX7 and Ki-67 in tumor tissues was detected by immunohistochemistry. CBX7 was downregulated in the tissues and cells of both LUAD and LUSC. Low CBX7 expression was associated with a poor overall survival rate in LUAD patients. CBX7 overexpression inhibited the viability, migration, and invasion and promoted the apoptosis of LUAD and LUSC cells. In addition, the downregulated genes in LUAD were enriched in MAPK cascade (GO) and MAPK signaling pathway (KEGG). ERK/MAPK pathway was then determined as a downstream target of CBX7, which was inhibited by CBX7 overexpression in LUAD and LUSC cells. The overexpression of CBX7 inhibited the malignant progression of LUAD and LUSC cells probably via suppressing the ERK/MAPK signaling pathway in vitro and in vivo.
Innovation and Strategic Communication

We study innovation in decentralized ﬁrms. In each period, the principal chooses between a routine and an experimental project. Before implementing the project, the agent learns its state and communicates it to the principal in the form of cheap talk. Based on the report, the principal decides how much to invest in the project and which project to choose in the subsequent period. We show that experimentation and delegation are complements in that (i) a report-contingent project choice results in more informative communication as compared with a one-shot transaction and (ii) a decentralized ﬁrm experiments more than one in which the principal herself observes the project state each period. The latter result alleviates concerns that within-ﬁrm incentive problems might compound the underprovision of innovation in the economy (the free-rider problem). We also show that innovations in decentralized ﬁrms are less likely to be moderate and more likely to be either radical or incremental innovations, due to the constraints imposed by strategic communication.
Increasing stakeholder engagement with object cards

There exist several tools that enable domain experts to model a problem domain graphically. In this thesis, we investigated a selection of state-of-the-art graphical modeling tools to study their characteristics and to uncover their shortcomings regarding their support to engage multiple stakeholders. We observed that the existing graphical modeling solutions: (1) allow users to graphically specify domain entities and relationships between them, and (2) facilitate automatic code generation from the visual speciﬁcations. We observed limited support in selecting domain-speciﬁc graphical notations, and the code generation facilities offered by the existing tools are uni-directional only, i.e. , from speciﬁcation to code. Furthermore, we observed that the existing tools might be hard to master for non-technical stakeholders, as these tools require the user to have in-depth knowledge about the offered functionality. To tackle these limitations, we propose an approach to iteratively create domain models inside an integrated development environment (IDE). With our approach, non-technical stakeholders can graphically create actors of any domain as ﬁrst-class citizens and iteratively give them behavior. Developers create custom graphical notations suitable for non-technical stakeholders. We demonstrate a prototype implementation that demonstrates our approach in the Glam-orous Toolkit IDE with a case study.
Multistep Forecast Averaging with Stochastic and Deterministic Trends

This paper presents a new approach to constructing multistep combination forecasts in a nonstationary framework with stochastic and deterministic trends. Existing forecast combination approaches in the stationary setup typically target the in-sample asymptotic mean squared error (AMSE), relying on its approximate equivalence with the asymptotic forecast risk (AFR). Such equivalence, however, breaks down in a nonstationary setup. This paper develops combination forecasts based on minimizing an accumulated prediction errors (APE) criterion that directly targets the AFR and remains valid whether the time series is stationary or not. We show that the performance of APE-weighted forecasts is close to that of the optimal, infeasible combination forecasts. Simulation experiments are used to demonstrate the finite sample efficacy of the proposed procedure relative to Mallows/Cross-Validation weighting that target the AMSE as well as underscore the importance of accounting for both persistence and lag order uncertainty. An application to forecasting US macroeconomic time series confirms the simulation findings and illustrates the benefits of employing the APE criterion for real as well as nominal variables at both short and long horizons. A practical implication of our analysis is that the degree of persistence can play an important role in the choice of combination weights.
Tumor Immunity toward a Type 2 Response Suppressor Cells and Macrophages Subverts Cross-Talk between Myeloid-Derived

Although the immune system has the potential to protect against malignancies, many individuals with cancer are immunosup-pressed. Myeloid-derived suppressor cells (MDSC) are elevated in many patients and animals with tumors, and contribute to immune suppression by blocking CD4 (cid:1) and CD8 (cid:1) T cell activation. Using the spontaneously metastatic 4T1 mouse mammary carcinoma, we now demonstrate that cross-talk between MDSC and macrophages further subverts tumor immunity by increasing MDSC production of IL-10, and by decreasing macrophage production of IL-12. Cross-talk between MDSC and macrophages requires cell-cell contact, and the IL-12 decrease is dependent on MDSC production of IL-10. Treatment with the chemothera-peutic drug gemcitabine, which reduces MDSC, promotes rejection of established metastatic disease in IL-4R (cid:2) (cid:3) / (cid:3) mice that produce M1 macrophages by allowing T cell activation, by maintaining macrophage production of IL-12, and by preventing increased production of IL-10. Therefore, MDSC impair tumor immunity by suppressing T cell activation and by interacting with macrophages to increase IL-10 and decrease IL-12 production, thereby promoting a tumor-promoting type 2 response, a process that can be partially reversed by gemcitabine. The Journal of Immunology, 2007, 179: 977–983.
High-Level Type-Safe Effect Handlers in C++

Effect handlers allow the programmer to implement computational effects, such as custom error handling, various forms of lightweight concurrency, and dynamic binding, inside the programming language. We introduce cpp-effects , a type-and memory-safe C++ library for effect handlers with a high-level, object-oriented interface. We demonstrate that effect handlers can be successfully applied in imperative systems programming languages with manual memory management. Through a collection of examples, we explore how to program effectively with effect handlers in C++, discuss the intricacies and challenges of the implementation, and show that despite its limitations, cpp-effects performance is competitive and in some circumstances even outperforms state-of-the-art approaches such as C++20 coroutines and the libmprompt library for multiprompt delimited control.
Memory Utilization-Based Dynamic Bandwidth Regulation for Temporal Isolation in Multi-Cores

Temporal isolation is one of the key challenges for co-running mixed-criticality applications on Commercial Off-The-Shelf (COTS) multi-core platforms. In particular, the main memory subsystem is one of the most prominent causes of interference and loss of isolation. Existing mechanisms for memory bandwidth regulation are limited to conservative bandwidth reservation, use pessimistic worst-case execution time (WCET) estimations or require dedicated hardware that is not feasible in COTS multi-core platforms.In this paper, we propose a novel mechanism for memory interference control that uses feedback-based control to dynamically regulate memory accesses of individual cores in a multicore platform. Our mechanism directly regulates the source of interference by leveraging information about memory utilization, acquired from existing hardware performance counters provided by modern COTS-based memory controllers. The proposed solution is implemented on Linux as a loadable kernel module. The results of evaluating our approach with real and synthetic benchmarks on a COTS multi-core (NXP S32V234) platform demonstrate that it is able to provide temporal isolation with up to 4x and 2x more overall throughput for non-real-time applications compared to static and dynamic memory bandwidth-based regulation approaches, respectively, while maintaining guarantees for applications running on the real-time core.
Detecting Sarcomere Structures in Cardiomyocytes Experiments on biomedical images using deep learning algorithms

Chemotherapy induced hart problems are undesirable when treating cancer patients. Yet cardiotoxicity is a serious adverse eﬀect of many conventional anti cancer drugs. In this study we explore cardiotoxicity through observation of sarcomere structures in cardiomyocytes. We notice these adverse eﬀects through malformations or a reduced number of sarcomeres. We use a high-throughput microscope to gather the input images. Our aim is to develop a method for delineating sarcomere structures using a deep learning algorithm. Usually, sarcomere structures are annotated using a set of imaging ﬁlters on microscopic images of cardiomyocytes. This kind of analysis reaches an 80% accuracy. Our approach involves experimenting with a set of deep learning algorithms that might be capable of more accurate results. We ﬁnd that U-Net is very good at this task and and can reach to a comparable performance as rule-based method. In the future we want to compare our results against a small set of manually delineated sarcomeres as ground truth.
JagWorks@USA JagWorks@USA Enhancing System Security Using Dynamic Hardware Enhancing System Security Using Dynamic Hardware

Alabama, May 2022. Enhancing System Security Using Dynamic Hardware. Chair of Committee: Todd, Andel, Ph.D. Within the ever-advancing field of computing, there is significant research into the many facets of cyber security. However, there is very little research to support the concept of using a Field Programmable Gate Array (FPGA) to increase the security of a system. While its most common use is to provide efficiency and speedup of processes, this research considers the use of an FPGA to mitigate vulnerabilities in both software and hardware. This paper proposes circuit variance within an FPGA as a method of Moving Target Defense (MTD) and investigates its effect on side-channels. We hypothesize that although the functionality of native and variant circuits is the same, their subsequent side-channel characterizations will differ thus creating unique electromagnetic signatures. The investigation and observations of the study include circuit variant construction, side channel attacks and analyses, and subsequent comparisons of electromagnetic signatures. We found that in the analysis of variant DES implementations, there are small but present differences in side channel depictions from native to variant.
Can the risky investment game predict real world investments?

The incentivized risky investment game has become a popular tool in lab-in-the-field exper- iments for its simplicity and ease of comprehension compared to some of the more complex Multiple Choice List approaches that have been more commonly used in laboratory experiments. we find substantial measurement error and low correlation when the game is repeated one year later for the same subjects. Measurement error is so large in our sample that the “obviously related instrumental variable” (ORIV) approach of Gillen, Snowberg and Yariv (2019) could not remedy the problem. Second, the game appears to suffer from low asset integration due to narrow bracketing, explaining its limited predictive power and the failure to detect attenuation bias due to measurement error. Subjects’ cognitive memory of the game played one year earlier is strongly positively related to investment intensity in the game and this result is much enhanced when correcting for the endogeneity of cognitive memory.
Reduction-of-quality attacks on adaptation mechanisms

One important consideration in realizing dependable computing systems and networks is to uncover vulnerabilities in their designs to adversarial attacks. Currently, the designs of these systems employ different forms of adaptation mechanisms in order to optimize their performance by ensuring that desirable properties, such as stability, efficiency and fairness, are not compromised. This thesis discovers and studies a new type of adversarial attacks that target such adaptation mechanisms by exploiting their dynamics of operation--- i.e., the characteristics of their transient behavior. We coin this new breed of adversarial attacks, Reduction of Quality (RoQ) attacks. The premise of RoQ attacks is to keep an adaptive mechanism constantly in a transient state, effectively depriving the system from much of its capacity and significantly reducing its service quality. In this thesis we develop a general control-theoretic framework that provides a unified approach to modeling and vulnerability assessment of the dynamics underlying RoQ exploits. Within this framework, we introduce and formalize the notion of an attack "Potency" that capitalizes on the attacker's best incentive: maximizing the marginal utility of its attack traffic. Unlike traditional brute-force Denial of Service attacks that aim to take down a system at any cost, RoQ attacks aim to maximize the damage inflicted on a system through consuming an innocuous, small fraction of that system's hijacked capacity. We instantiate our framework using detailed analytical models and associated metrics on a series of adaptation mechanisms that are commonly used in networking protocols, endsystem admission controllers and load balancers. We assess the impact of RoQ attacks using analysis, simulations, and Internet experiments. We identify key factors that expose the tradeoffs between resilience and susceptibility to RoQ attacks. These factors could be used to harden adaptation mechanisms against RoQ exploits, in addition to developing new forms of countermeasures and defense mechanisms.
A cloud-based workflow for the integration of BIM to DEVS

High-performance buildings and smart cities focus on reducing energy consumption while improving occupant comfort. An efficient building performance analysis would consider performance evaluation for the whole system than parts of the system. Advancement in technology has increased the need to integrate the energy and communication system for effective building performance. The integration of these systems is complex, and we propose using the Discrete Event Specification System (DEVS) to Building Information Modeling (BIM) for complex simulations. We describe a method to model these complex systems through DEVS and build a prototype implementation to integrate DEVS and BIM. The paper showcases two case studies highlighting BIM to DEVS integration and how it opens other design experiences through gamification or virtual reality.
Is diminishing impatience in time-dated risky prospects explained by probability weighting?

We use a ﬁeld experiment and a within-subject design based on multiple Choice Lists (CLs) that integrate time and risk. Diminishing impatience with extended time horizons is studied by varying time horizons from one week to two years. Time-dated risky prospects are constant within CLs and are always compared with time-dated certain amounts to identify time-dated Certainty Equivalents. Non-linear probability weighting is modeled with a 2-parameter Prelec function. First, we identify a strong diminishing impatience associated with longer time delay between prospects. Second, we test whether non-linear probability weighting can explain and reduce the observed diminishing impatience by replacing linear probability weighting with an estimated inverted S-shaped Prelec function. We ﬁnd that this does not reduce the observed degree of diminishing impatience. We conclude that the observed diminishing impatience is neither explained by the combination of present bias and certainty bias nor by non-linear weighting of risk in future prospects.
Occupancy-SLAM: Simultaneously Optimizing Robot Poses and Continuous Occupancy Map

—In this paper, we propose an optimization based SLAM approach to simultaneously optimize the robot trajectory and the occupancy map using 2D laser scans (and odometry) information. The key novelty is that the robot poses and the occupancy map are optimized together, which is significantly different from existing occupancy mapping strategies where the robot poses need to be obtained first before the map can be estimated. In our formulation, the map is represented as a continuous occupancy map where each 2D point in the environment has a corresponding evidence value. The Occupancy-SLAM problem is formulated as an optimization problem where the variables include all the robot poses and the occupancy values at the selected discrete grid cell nodes. We propose a variation of Gauss-Newton method to solve this new formulated problem, obtaining the optimized occupancy map and robot trajectory together with their uncertainties. Our algorithm is an offline approach since it is based on batch optimization and the number of variables involved is large. Evaluations using simulations and publicly available practical 2D laser datasets demonstrate that the proposed approach can estimate the maps and robot trajectories more accurately than the state-of-the-art techniques, when a relatively accurate initial guess is provided to our algorithm. The video shows the convergence process of the proposed Occupancy-SLAM and comparison of results to Cartographer can be found at https://youtu.be/4oLyVEUC4iY.
Oestrogen receptor (cid:1) increases p21 WAF1/CIP1 gene expression and the antiproliferative activity of histone deacetylase inhibitors in human breast cancer cells

We analysed the antiproliferative activity of various histone deacetylase (HDAC) inhibitors such as trichostatin A (TSA) on human breast cancer cells. We observed a lower sensitivity to HDAC inhibition for oestrogen receptor negative (ER (cid:1) ) versus positive (ER+) cell lines. This di ﬀ erential response was associated neither with a modiﬁcation of drug e ﬄ ux via the multidrug resistance system nor with a global modiﬁcation of histone acetyltransferase (HAT)/HDAC activities. In contrast, we demonstrated that in ER+ breast cancer cells the p21 WAF1/CIP1 gene was more sensitive to TSA regulation and was expressed at higher levels. These di ﬀ erences were observed both in transient transfection experiments and on the endogenous p21 WAF1/CIP1 gene. The Sp1 transcription factor, which was shown to interact in vitro with both class I and class II HDACs, is su ﬃ cient to confer the di ﬀ erential sensitivity to TSA and participated in the control of p21 WAF1/CIP1 basal expression. Finally, re-expression of ER (cid:1) following adenoviral infection of ER (cid:1) breast cancer cells increased both p21 WAF1/CIP1 protein accumulation and the growth inhibitory activity of TSA. Altogether, our results highlight the key role of ER (cid:1) and p21 WAF1/CIP1 gene expression in the sensitivity of breast cancer cells to hyperacetylating agents.
Endothelial progenitor cell-derived extracellular vesicles protect from complement-mediated mesangial injury in experimental anti-Thy1.1

progenitor cell-derived extracellular vesicles protect from complement-mediated mesangial injury in experimental anti-Thy1.1 Abstract Background Endothelial progenitor cells (EPCs) are known to induce tissue repair by paracrine mechanisms including the release of growth factors and extracellular vesicles (EVs), nanoparticles able to carry proteins and genetic information to target cells. The aim of this study was to evaluate whether EVs derived from EPCs may protect from complement ‐ mediated mesangial injury in experimental anti ‐ Thy1.1 glomerulonephritis. Methods EVs were isolated by serial ultracentrifugation from supernatants of cultured human EPCs and characterized for their protein and RNA content. In vivo , EVs were injected i.v. in the experimental rat model of mesangiolytic anti ‐ Thy1.1 glomerulonephritis evaluating renal function, proteinuria, complement activity and histological lesions. In vitro , the biological effects of EPC ‐ derived EVs were studied in cultured rat mesangial cells incubated with anti ‐ Thy1.1 antibody and rat or human serum as complement source. Results After i.v. injection in Thy1.1 ‐ treated rats, EVs localized within injured glomeruli and inhibited mesangial cell activation, leucocyte infiltration and apoptosis, decreased proteinuria, increased serum complement haemolytic activity (CH50) and ameliorated renal function. EV treatment decreased intraglomerular deposition of the membrane attack complex (MAC or C5b ‐ 9) and expression of smooth muscle cell actin and preserved the endothelial antigen RECA ‐ 1 and the podocyte marker synaptopodin. The protective effect of EVs was significantly reduced by pre ‐ treatment with a high dose of RNase (1 U/mL), suggesting a key role for EV ‐ carried RNAs in these mechanisms. Indeed, EPC ‐ derived EVs contained different mRNAs coding for several anti ‐ apoptotic molecules and for the complement inhibitors Factor H, CD55 and CD59 and the related proteins. The in vitro experiments aimed to investigate the mechanisms of EV protection indicated that EVs transferred to mesangial cell mRNAs coding for Factor H, CD55 and CD59 and inhibited anti ‐ Thy1.1 antibody/complement ‐ induced apoptosis and C5b ‐ 9/C3 mesangial cell deposition. Conclusions EVs derived from EPCs exert a protective effect in Thy1.1 glomerulonephritis by inhibition of antibody ‐ and complement ‐ mediated injury of mesangial cells.
User Experience Evaluation of a Student Information System

Today's academic environment, many students use technology as an integral aspect of their studies; as a result, higher education (HE) institutions have been compelled to design student information systems (SIS) that can facilitate students' online learning processes. However, SIS must be aligned with user needs and should provide a pleasant user experience (UX) that enables students to attain their goals. The current research looked at how students rated an SIS. The study was based on the responses of 307 students at Kuwait's College of Business Studies (CBS) provided within a questionnaire. The survey's findings revealed that students had a generally favourable impression of the SIS, with perceptions of the pragmatic quality of the system being somewhat higher than the perceptions of hedonic quality. The findings of this research may be valuable to authorities working to design improved SIS, particularly in terms of the hedonic system components.