Miracle-dz/UniFAR-FTUs huggingface dataset:
MDM2 inhibition is synthetic lethal with PTEN loss in colorectal cancer cells via the p53-dependent mechanism

Colorectal cancer (CRC) driven by PTEN deficiency exhibits high risk of metastasis, advancement of tumor stages and chemotherapy resistance, where no effective therapy has been developed. In this study, we performed a synthetic lethal drug screening in CRC and found that PTEN-deficient CRC cells are highly vulnerable to MDM2 inhibition. MDM2 inhibitor treatment or its silencing selectively inhibited the growth of PTEN-deficient CRC in vitro and in mice models. Mechanistically, PTEN loss increased the level of active AKT and subsequently increased MDM2 phosphorylation, thereby limiting the p53 functions in PTEN-/- CRC cells. MDM2 inhibition in turn activated p53 in CRC, particularly in PTEN-/- CRC cells. The synthetic lethal effect of MDM2 inhibitor was largely dependent on p53, because p53 silenced cells or cells lacking p53 failed to exhibit synthetic lethality in PTEN-deficient cells. We further showed that MDM2 inhibition led to the p53-dependent reversal of Bcl2-Bax ratio, which contributed to mitochondria-mediated apoptotic cell death in PTEN-deficient CRC. This study suggests that pharmacological targeting of MDM2 could be a potential therapeutic strategy for PTEN-deficient CRC.
A Case Report on a Giant Hepatic Inflammatory Adenoma in a Young Female That Presented as Spontaneous Intrahepatic Hematoma

Among the extensive variety of disorders that can cause acute abdominal pain are hepatocellular adenomas (HCAs), pathological entities that otherwise are asymptomatic. Here, we describe a 33-year-old female who presented in the emergency department with acute abdominal pain and a history of liver focal nodular hyperplasia (FNH) diagnosed 10 years ago. An abdominal magnetic resonance imaging (MRI) revealed that the cause of the pain was an intrahepatic hematoma. The mass was surgically removed, and the biopsy revealed inflammatory adenomas, a subtype of HCA. Hepatic adenoma diagnosis remains challenging by clinical and imaging techniques, and usually, a biopsy is the main diagnostic tool. HCA should be differentiated from hepatocellular carcinoma (HCC), FNH, hepatic angioleiomyoma, and hepatic hemangioma. In our case, HCA was misdiagnosed in the past as FNH. HCA rarely may present as acute right abdomen pain, and a potential catastrophic hemorrhage or rupture must be excluded.
Sociophonetic variation of like in British dialects: effects of function, context and predictability 1

This study examines sociophonetic variation in different functions of like among adolescents in London and Edinburgh. It attempts to determine the factors that may explain this variation. Our results suggest that the function of like correlates primarily with contextual factors, rather than the phonetic factors of vowel quality, /l/ to vowel duration and /k/ realisation. In particular, the preceding and following segments and their bigram predictability emerge as highly significant, in addition to the boundary strength following like. In both London and Edinburgh, the vowel appears to be the only non-contextual feature that is sensitive to the function of like: quotative be like is more likely to be monophthongised than other functions of like. We argue that the more monophthongal nature of quotative like is due to the syntactic and prosodic context in which it occurs.
Uncertainty and accuracy of vision-based tracking concerning stereophotogrammetry and noise-floor tests

This work proposes a systematic assessment of stereophotogrammetry and noise-ﬂoor tests to characterize and quantify the uncertainty and accuracy of a vision-based tracking system. Two stereophotogrammetry sets withdiﬀerentconﬁgurations,i.e.,someimagesaredesignedandtheirsensitivityisquantiﬁedbasedonseveral assessments. Theﬁrstassessmentevaluatestheimagecoordinates,stereoangleandreconstructionerrors resultingfromthestereophotogrammetryprocedure,andthesecondassessmentexpressestheuncertainty fromthevarianceandbiaserrorsmeasuredfromthenoise-ﬂoortest. Thesetwoassessmentsquantifythe uncertainty,whiletheaccuracyofthevision-basedtrackingsystemisassessedfromthreequasi-static testsonasmall-scaledspecimen. Thediﬀerenceineachstereophotogrammetrysetandconﬁguration,as indicatedbythestereophotogrammetryandnoise-ﬂoorassessment,leadstoasigniﬁcantresulthattheﬁrst stereophotogrammetrysetmeasurestheRMSEof3. 6mmwhilethesecondsetidentiﬁesonly1. 6mmof RMSE.Theresultsofthisworkrecommendacarefulandsystematicassessmentofstereophotogrammetry andnoise-ﬂoortestresultstoquantifytheuncertaintybeforetherealtesttoachieveahighdisplacement accuracyofthevision-basedtrackingsystem
A Deep Learning Approach to Intrusion Detection and Segmentation in Pellet Fuels Using Microscopic Images

Pellet fuels are nowadays commonly used as a heat source for food preparation. Unfortunately, they may contain intrusions which might be harmful for humans and the environment. The intrusions can be identified precisely using immersed microscopy analysis. The aim of this study is to investigate the possibility of autonomous identification of selected classes of intrusions using relatively simple deep learning models. The semantic segmentation was chosen as a method for impurity identification in the microscopic image. Three architectures of deep networks based on UNet architecture were examined. The networks contained the same depth as UNet but with a successively limited number of filters. The input image influence on the segmentation results was also examined. The efficiency of the network was assessed using the intersection over union index. The results showed an easily observable impact of the filter used on segmentation efficiency. The influence of the input image resolution is not so clear, and even the lowest (256 × 256 pixels) resolution used gave satisfactory results. The biggest (but still smaller than originally proposed UNet) network yielded segmentation quality good enough for practical applications. The simpler one was also applicable, although the quality of the segmentation decreased considerably. The simplest network gave poor results and is not suitable in applications. The two proposed networks can be used as a support for domain experts in practical applications.
Relationship marketing variation in multidyadic industrial channels with component supplier specification

Abstract Building strong relationships is central to the development and maintenance of effective industrial channels. However, while the relationship marketing literature is vast, our understanding of how multidyadic industrial channels impact relationship marketing models is limited. As many OEM supplier relationships are formed via component supplier specification by its industrial buyer, where freedom to enter and exit a relationship is externally restricted, the current relationship marketing literature is somewhat limited in explaining these relationships. This study examines the underlying differences in relationship marketing across the cases of component supplier specification and non-component supplier specification. We discuss key relationship variable differences across cases within the phases of relationship development, and the extant relationship marketing literature. We then present a research agenda for advancing our understanding of multidyadic industrial channels.
Extremal length boundary of the Teichmüller space contains non-Busemann points

We present an overview of the extremal length embedding of a Teichm¨uller space and its extremal length compactiﬁcation. For Teichm¨uller spaces of dimension at least two, we describe a large class of non-Busemann points on the metric boundary, that is, points that cannot be realized as limits of almost geodesic rays.
EFFECT OF MALATHION ON BLOOD BIOCHEMICAL PARAMETERS (UREA AND CREATININE) IN NILE TILAPIA (OREOCHROMIS NILOTICUS)

The present study was conducted to evaluate the serological changes (urea and creatinine) in the kidneys of Nile tilapia (Oreochromis niloticus) after acute exposure to Malathion. Four groups of 15 fish were made each and categorized as; Group A: (control group) and Groups B, C and D (experimental groups). The LC50 of Malathion was 2µg/L at 96 hours of exposure in Nile tilapia. The fish were exposed to sub-lethal concentrations of 0.5, 1.0 and 1.5 µg/L to group B, C and D respectively. Blood samples were collected after 48, 72 and 96 hours of exposure to Malathion. Serum was separated and analyzed for levels of urea and creatinine that was significantly enhanced after acute exposure to Malathion at 48, 72 and 96 hours. Moreover, morphological and behavioral changes and mortality rates were also recorded. The results revealed that the pesticide (Malathion) has an adverse effect on kidneys. High levels of Malathion result in kidney damage and serological alterations in Nile tilapia.
Epigenetic Reprogramming in Mice and Humans: From Fertilization to Primordial Germ Cell Development

In this review, advances in the understanding of epigenetic reprogramming from fertilization to the development of primordial germline cells in a mouse and human embryo are discussed. To gain insights into the molecular underpinnings of various diseases, it is essential to comprehend the intricate interplay between genetic, epigenetic, and environmental factors during cellular reprogramming and embryonic differentiation. An increasing range of diseases, including cancer and developmental disorders, have been linked to alterations in DNA methylation and histone modifications. Global epigenetic reprogramming occurs in mammals at two stages: post-fertilization and during the development of primordial germ cells (PGC). Epigenetic reprogramming after fertilization involves rapid demethylation of the paternal genome mediated through active and passive DNA demethylation, and gradual demethylation in the maternal genome through passive DNA demethylation. The de novo DNA methyltransferase enzymes, Dnmt3a and Dnmt3b, restore DNA methylation beginning from the blastocyst stage until the formation of the gastrula, and DNA maintenance methyltransferase, Dnmt1, maintains methylation in the somatic cells. The PGC undergo a second round of global demethylation after allocation during the formative pluripotent stage before gastrulation, where the imprints and the methylation marks on the transposable elements known as retrotransposons, including long interspersed nuclear elements (LINE-1) and intracisternal A-particle (IAP) elements are demethylated as well. Finally, DNA methylation is restored in the PGC at the implantation stage including sex-specific imprints corresponding to the sex of the embryo. This review introduces a novel perspective by uncovering how toxicants and stress stimuli impact the critical period of allocation during formative pluripotency, potentially influencing both the quantity and quality of PGCs. Furthermore, the comprehensive comparison of epigenetic events between mice and humans breaks new ground, empowering researchers to make informed decisions regarding the suitability of mouse models for their experiments.
Calcitonin Gene-Related Peptide mRNA Synthesis in Trigeminal Ganglion Neurons after Cortical Spreading Depolarization

Migraine is a debilitating neurovascular disorder characterized by recurrent headache attacks of moderate to severe intensity. Calcitonin gene-related peptide (GGRP), which is abundantly expressed in trigeminal ganglion (TG) neurons, plays a crucial role in migraine pathogenesis. Cortical spreading depolarization (CSD), the biological correlate of migraine aura, activates the trigeminovascular system. In the present study, we investigated CGRP mRNA expression in TG neurons in a CSD-based mouse migraine model. Our in situ hybridization analysis showed that CGRP mRNA expression was observed in smaller-sized neuronal populations. CSD did not significantly change the density of CGRP mRNA-synthesizing neurons in the ipsilateral TG. However, the cell sizes of CGRP mRNA-synthesizing TG neurons were significantly larger in the 48 h and 72 h post-CSD groups than in the control group. The proportions of CGRP mRNA-synthesizing TG neurons bearing cell diameters less than 14 μm became significantly less at several time points after CSD. In contrast, we found significantly greater proportions of CGRP mRNA-synthesizing TG neurons bearing cell diameters of 14–18 μm at 24 h, 48, and 72 h post-CSD. We deduce that the CSD-induced upward cell size shift in CGRP mRNA-synthesizing TG neurons might be causative of greater disease activity and/or less responsiveness to CGRP-based therapy.
Kevlar®, Nomex®, and VAR Modification by Small Organic Molecules Anchoring: Transfusing Antibacterial Properties and Improving Water Repellency

The surface modification of fabrics composed of Kevlar®, Nomex®, or VAR was extensively investigated. Kevlar® and Nomex® are widely-utilized aramid materials, whereas VAR is a technical fabric comprising 64% viscose, 24% para-aramid (Kevlar®), 10% polyamide, and 2% antistatic fibers. Both aramid materials and cellulose/viscose exhibit exceptional mechanical properties that render them valuable in a wide range of applications. For the herein studied modification of Kevlar®, Nomex®, and VAR, we used small organic molecules 3-allyl-5,5-dimethylhydantoin (ADMH) and 3-(acrylamidopropyl)trimethylammonium chloride (APTAC), which were anchored onto the materials under study via graft polymerization. By doing so, excellent antibacterial properties were induced in the three studied fabrics. Their water repellency was improved in most cases as well. Extensive characterization studies were conducted to probe the properties of the modified materials, employing Raman and FTIR spectroscopies, Scanning Electron Microscopy (SEM), and thermogravimetric analysis (TGA).
Dynamic learning from adaptive neural control for flexible joint robot with tracking error constraints using high-gain observer

ABSTRACT This paper presents dynamic learning from adaptive neural control with prescribed tracking error performance for flexible joint robot (FJR) included unknown dynamics. Firstly, a system transformation method is introduced to convert the original FJR system into a normal system. As a result, only one neural network (NN) approximator is used to identify the uncertain system nonlinear dynamics and the verification on the convergence of neural weights is simplified extremely. To further solve the predefined performance issue, a performance function is introduced to describe a tracking error constraint and a error transformation technique is used to convert the constrained tracking control problem into the unconstrained stabilization of error system. By combining a high-gain observer and the backsteppig method, the adaptive neural controller is presented to stabilize the unconstrained error system. Under the satisfaction of the partial persistent excitation condition, the adaptive neural controller is shown to be capable of achieving unknown dynamics acquisition, expression and storage. Furthermore, a neural learning control with using the stored NN weights is proposed for the same or similar control task so that a time-consuming NN online adjustment process can be avoided and a better control performance can be obtained. Simulation results demonstrate the effectiveness of the proposed control method.
Turbulence near a sandbar island in the lower Missouri River

River turbulence is spatially variable due to interactions between morphology of rivers and physical mechanics of flowing water. Understanding the variation of turbulence in rivers is important for characterizing transport processes of soluble and particulate materials in these systems. We present an exploratory effort to understand ecologically relevant flow patterns using measurements of mean flow and turbulence in a highly engineered river channel around an island in the lower Missouri River. Specifically, the profiles of mean river velocities were investigated to examine the logarithmic relation and associated parameters, including shear velocity and bed roughness. Turbulence intensity and Reynolds shear stress were compared with classic open‐channel profiles and previously reported river data in the hydraulics literature. With the capability of pulse‐to‐pulse coherent Doppler velocity profiling in high spatial resolution, we estimated the profiles of turbulence dissipation rate using resolved one‐dimensional velocity spectra. These measurement data allow us to examine the validity of turbulence production‐dissipation balance and the classic open‐channel profiles of turbulence statistics, including turbulence intensity, Reynolds shear stress, dissipation rate, and eddy viscosity. The field data show a strong variation of turbulence profiles in close vicinity of the river island. In shallow water depths close to the island, turbulence is substantially enhanced in comparison with classic open‐channel profiles. Such turbulence enhancement is likely attributed to non‐uniformity of the flow structures.
Stability and Stabilization of T–S Fuzzy Systems With a Periodic Variable Delay via Monotone Delay-Interval-Based Functional

The stability and stabilization problems for T–S fuzzy systems with a periodic variable delay are analyzed in this article. First, an improved delay-dependent reciprocally convex inequality is presented to deal with the periodic variable delay, which contains some existing results. Second, according to the monotonicity of the delay interval, the interval of each period is divided into a monotonically increasing interval and a monotonically decreasing interval, and different looped functionals are constructed on the two intervals. A new monotone delay-interval-based functional is presented to introduce more delay information and system state information on the basis of augmented functional and looped functional methods. Then, a generalized memory controller is designed to assure robust stabilization of the system by considering the variable delay and its bounds, which is more general than conventional controllers. Finally, some examples are shown to elaborate on the feasibility and validity of the obtained results.
Free vibration analysis of size-dependent functionally graded porous cylindrical microshells in thermal environment

ABSTRACT In this article, the free vibration analysis of a functionally graded (FG) porous cylindrical microshell subjected to a thermal environment is investigated on the basis of the first-order shear deformation shells and the modified couple stress theories. The material properties are assumed to be temperature dependent and are graded in the thickness direction. The equations of motion and the related boundary conditions are derived using the principle of minimum potential energy and they are solved analytically. The model is validated by comparing the benchmark results with the obtained ones. The effects of material length scale parameter, temperature changes, volume fraction of the porosity, FG power index, axial and circumferential wave number, and length on the vibration behavior of the FG porous cylindrical microshell are studied. The results can have many applications such as in modeling of microrobots and biomedical microsystems.
A Comprehensive Survey of 3D Dense Captioning: Localizing and Describing Objects in 3D Scenes

Three-Dimensional (3D) dense captioning is an emerging vision-language bridging task that aims to generate multiple detailed and accurate descriptions for 3D scenes. It presents significant potential and challenges due to its closer representation of the real world compared to 2D visual captioning, as well as complexities in data collection and processing of 3D point cloud sources. Despite the popularity and success of existing methods, there is a lack of comprehensive surveys summarizing the advancements in this field, which hinders its progress. In this paper, we provide a comprehensive review of 3D dense captioning, covering task definition, architecture classification, dataset analysis, evaluation metrics, and in-depth prosperity discussions. Based on a synthesis of previous literature, we refine a standard pipeline that serves as a common paradigm for existing methods. We also introduce a clear taxonomy of existing models, summarize technologies involved in different modules, and conduct detailed experiment analysis. Instead of a chronological order introduction, we categorize the methods into different classes to facilitate exploration and analysis of the differences and connections among existing techniques. We also provide a reading guideline to assist readers with different backgrounds and purposes in reading efficiently. Furthermore, we propose a series of promising future directions for 3D dense captioning by identifying challenges and aligning them with the development of related tasks, offering valuable insights and inspiring future research in this field. Our aim is to provide a comprehensive understanding of 3D dense captioning, foster further investigations, and contribute to the development of novel applications in multimedia and related domains.
Backstepping Technique Based on Error

Backstepping technique usually adopts back step design to construct the Lyapunov function gradually, and then to design the corresponding virtue controller. The backstepping technique based on error also adopts back step design process, but the design of virtue controllers depends on the corresponding errors which are designed to satisfy some expected behaviors. Six different error equations are deduced by changing the results of the virtue controls arbitrarily while guaranteeing the system behaviors such as stability, and an example shows the effectiveness of these six versions. Simulated results illustrate that these six versions of backstepping technique based on error are effective.
Performance Evaluation of Graphene Nanofluid to Mitigate the Wear of a Diamond Tool in Micro-Machining of Ti6Al4V Alloy

Diamond tools are extensively used in ultra-precision machining due to their exceptional performance. However, when machining challenging materials like Ti6Al4V, diamond tools experience significant wear due to poor machining properties and catalytic effects. Tool wear not only impacts machining quality but also escalates machining costs and energy consumption. Cutting fluids are commonly employed to mitigate interfacial reactions and suppress tool wear. However, traditional cutting fluids are difficult to penetrate the cutting area and have limited lubrication and cooling capabilities. Therefore, in this paper, a technique combining graphene nanofluid and minimum-quantity lubrication (MQL) is used to suppress diamond tool wear. Firstly, micro-milling experiments for Ti6Al4V alloy are conducted using diamond tools in the graphene nanofluid MQL and under a dry environment. The experimental results show that tool wear is effectively suppressed by graphene nanofluids. Subsequently, the cutting process in both environments (graphene nanofluid MQL, dry) is simulated. The suppression mechanism of graphene nanofluid MQL for diamond tool wear is evaluated from phase transition, atomic transfer process, and amorphous behavior of diamond structure. The simulation results show that the contact characteristics, cutting force, and cutting temperature are improved by graphene nanofluids. Tool wear is effectively reduced. In addition, the removal efficiency of workpiece materials has also been improved. This work provides a technical basis for exploring the application of graphene nanofluids in diamond tool damage suppression and micro-milling.
Revisiting the role of

Analytic modeling of ice shelf flow began when Weertman derived an expression for the strain rates within an unconfined shelf, of uniform thickness, extending only in one direction. Nearly two decades later, Thomas generalized Weertman’s analysis to ice shelvesof nonuniform thickness, deriving one of the most well-known analytic models in glaciology