Miracle-dz/UniFAR-FTUs huggingface dataset:
Establishment of the TBX-code reveals aberrantly activated T-box gene TBX3 in Hodgkin lymphoma

T-box genes encode transcription factors which control basic processes in development of several tissues including cell differentiation in the hematopoietic system. Here, we analyzed the physiological activities of all 17 human T-box genes in early hematopoiesis and in lymphopoiesis including developing and mature B-cells, T-cells, natural killer (NK)-cells and innate lymphoid cells. The resultant expression pattern comprised six genes, namely EOMES, MGA, TBX1, TBX10, TBX19 and TBX21. We termed this gene signature TBX-code which enables discrimination of normal and aberrant activities of T-box genes in lymphoid malignancies. Accordingly, expression analysis of T-box genes in Hodgkin lymphoma (HL) patients using a public profiling dataset revealed overexpression of EOMES, TBX1, TBX2, TBX3, TBX10, TBX19, TBX21 and TBXT while MGA showed aberrant downregulation. Analysis of T-cell acute lymphoid leukemia patients indicated aberrant overexpression of six T-box genes while no deregulated T-box genes were detected in anaplastic large cell lymphoma patients. As a paradigm we focused on TBX3 which was ectopically activated in about 6% of HL patients analyzed. Normally, TBX3 is expressed in tissues like lung, adrenal gland and retina but not in hematopoiesis. HL cell line KM-H2 expressed enhanced TBX3 levels and was used as an in vitro model to identify upstream regulators and downstream targets in this malignancy. Genomic studies of this cell line showed focal amplification of the TBX3 locus at 12q24 which may underlie its aberrant expression. In addition, promoter analysis and comparative expression profiling of HL cell lines followed by knockdown experiments revealed overexpressed transcription factors E2F4 and FOXC1 and chromatin modulator KDM2B as functional activators. Furthermore, we identified repressed target genes of TBX3 in HL including CDKN2A, NFKBIB and CD19, indicating its respective oncogenic function in proliferation, NFkB-signaling and B-cell differentiation. Taken together, we have revealed a lymphoid TBX-code and used it to identify an aberrant network around deregulated T-box gene TBX3 in HL which promotes hallmark aberrations of this disease. These findings provide a framework for future studies to evaluate deregulated T-box genes in lymphoid malignancies.
3D Modeling of Interior Building Environments and Objects from Noisy Sensor Suites

In this dissertation, we present several techniques used to automatically generate virtual models of indoor building environments. The interior environment of a building is scanned by a custom hardware system, which provides raw laser and camera sensor readings used to develop these models. Our modeling techniques can be separated into three categories: 2D floor plan models, simplified 2.5D extruded models, and fully complex and detailed 3D models. All models are produced automatically from the output data of a backpack-mounted ambulatory scanning system, which can scan multiple floors of a building efficiently. We can capture the entirety of a large building in only a few hours, including staircases and other hard to reach locations, which improves upon the state-of-the-art static scanning by several orders of magnitude. Our algorithms are capable of producing many kinds of 3D virtual building models while traversing through a GPS-denied environment, including point clouds, 2D floor plans, and 3D building models.The novel contributions of this dissertation fall into three groups. First, we present multiple methods for producing 2D floor plans in a scalable fashion. We automatically partition these floor plans into separate building levels and separate rooms within each level. These floor plans can also be extruded into simplified 2.5D models of the building environment. Second, we present multiple techniques to produce complex 3D models of the scanned environment, capturing all observed detail. Third, we present several techniques that combine these two types of building models -- simple and complex -- to perform additional analysis of the building environment. Such analysis includes segmenting objects and furniture in the environment as separate models, reducing noise and artifacts within the models, and demonstrating novel visualization techniques. Additionally, we show several example datasets generated by the system in real-world environments, including buildings of over 40,000 square feet. We demonstrate how such building models are applicable in many fields of study, including architecture, building energy efficiency, virtual walk-throughs of buildings, indoor navigation, and augmented and virtual reality.
Osteoblast-derived EGFL6 couples angiogenesis to osteogenesis during bone repair

Rationale: Angiogenesis and osteogenesis are highly coupled processes which are indispensable to bone repair. However, the underlying mechanism(s) remain elusive. To bridge the gap in understanding the coupling process is crucial to develop corresponding solutions to abnormal bone healing. Epidermal growth factor-like protein 6 (EGFL6) is an angiogenic factor specifically and distinctively up-regulated during osteoblast differentiation. In contrast with most currently known osteoblast-derived coupling factors, EGFL6 is highlighted with little or low expression in other cells and tissues. Methods: In this study, primary bone marrow mesenchymal stem cells (MSCs) and osteoblastic cell line (MC3T3-E1) were transduced with lentiviral silencing or overexpression constructs targeting EGFL6. Cells were induced by osteogenic medium, followed by the evaluation of mineralization as well as related gene and protein expression. Global and conditional knockout mice were established to examine the bone phenotype under physiological condition. Furthermore, bone defect models were created to investigate the outcome of bone repair in mice lacking EGFL6 expression. Results: We show that overexpression of EGFL6 markedly enhances osteogenic capacity in vitro by augmenting bone morphogenic protein (BMP)-Smad and MAPK signaling, whereas downregulation of EGFL6 diminishes osteoblastic mineralization. Interestingly, osteoblast differentiation was not affected by the exogenous addition of EGFL6 protein, thereby indicating that EGFL6 may regulate osteoblastic function in an intracrine manner. Mice with osteoblast-specific and global knockout of EGFL6 surprisingly exhibit a normal bone phenotype under physiological conditions. However, EGFL6-deficiency leads to compromised bone repair in a bone defect model which is characterized by decreased formation of type H vessels as well as osteoblast lineage cells. Conclusions: Together, these data demonstrate that EGFL6 serves as an essential regulator to couple osteogenesis to angiogenesis during bone repair.
Core genes involved in the regulation of acute lung injury and their association with COVID-19 and tumor progression: A bioinformatics and experimental study

Acute lung injury (ALI) is a specific form of lung damage caused by different infectious and non-infectious agents, including SARS-CoV-2, leading to severe respiratory and systemic inflammation. To gain deeper insight into the molecular mechanisms behind ALI and to identify core elements of the regulatory network associated with this pathology, key genes involved in the regulation of the acute lung inflammatory response (Il6, Ccl2, Cat, Serpine1, Eln, Timp1, Ptx3, Socs3) were revealed using comprehensive bioinformatics analysis of whole-genome microarray datasets, functional annotation of differentially expressed genes (DEGs), reconstruction of protein-protein interaction networks and text mining. The bioinformatics data were validated using a murine model of LPS-induced ALI; changes in the gene expression patterns were assessed during ALI progression and prevention by anti-inflammatory therapy with dexamethasone and the semisynthetic triterpenoid soloxolone methyl (SM), two agents with different mechanisms of action. Analysis showed that 7 of 8 revealed ALI-related genes were susceptible to LPS challenge (up-regulation: Il6, Ccl2, Cat, Serpine1, Eln, Timp1, Socs3; down-regulation: Cat) and their expression was reversed by the pre-treatment of mice with both anti-inflammatory agents. Furthermore, ALI-associated nodal genes were analysed with respect to SARS-CoV-2 infection and lung cancers. The overlap with DEGs identified in postmortem lung tissues from COVID-19 patients revealed genes (Saa1, Rsad2, Ifi44, Rtp4, Mmp8) that (a) showed a high degree centrality in the COVID-19-related regulatory network, (b) were up-regulated in murine lungs after LPS administration, and (c) were susceptible to anti-inflammatory therapy. Analysis of ALI-associated key genes using The Cancer Genome Atlas showed their correlation with poor survival in patients with lung neoplasias (Ptx3, Timp1, Serpine1, Plaur). Taken together, a number of key genes playing a core function in the regulation of lung inflammation were found, which can serve both as promising therapeutic targets and molecular markers to control lung ailments, including COVID-19-associated ALI.
Neue baubetriebswirtschaftliche Verfahren zur Ermittlung der Höhe der AGK bei Mehrvergütungsansprüchen nach § 2 Abs. 5 und 6 sowie § 6 Abs. 6 VOB/B – Teil 1

Insbesondere bei Behinderungsansprüchen nach der VOB/B gibt es in der Fachliteratur bezüglich der Berücksichtigung der Höhe der Allgemeinen Geschäftskosten (AGK) keine einheitliche Meinungsbildung; ein wesentlicher Grund hierfür ist, dass komplexe juristische, kostentheoretische und baubetriebswirtschaftliche Anforderungen zu berücksichtigen sind.
The Versatility of the Medial Thigh Flap for Coverage of Large Perineoscrotal Defects

Objective: To study the versatility, aesthetic and functional outcome of medial thigh flap for coverage of large perineoscrotal defects Design: Prospective Setting: Al-Babtain Center for Burns and Plastic Surgery (State Government Institute) Subjects: Seven patients with Fournier’s gangrene seen between July 2005 and October 2006 at Al-Babtain Center for Burns and Plastic Surgery Intervention: Reconstructive surgery for coverage of scrotal and perineal defects after debridement of Fournier’s gangrene. Nine medial thigh fasciocutaneuos flaps were performed under general anesthesia. Main Outcome Measures: General aesthetic and functional results in the form of the range of motion of both hip joints. Results: All flaps survived well with good aesthetic and functional results, with the exception of partial distal necrosis in two cases. This was managed conservatively in one case, while the other case needed debridement and minimal advancement of the flap. Conclusion: The medial thigh fasciocutaneuos flap offers a good option for coverage of perineoscrotal defects. The flap provided a single stage, stable, well vascularized soft tissue coverage in our patients with no significant complications.
Genetic Contributions to Prostate Cancer Disparities in Men of West African Descent

Prostate cancer (PCa) is the second most frequently diagnosed malignancy and the second leading cause of death in men worldwide, after adjusting for age. According to the International Agency for Research on Cancer, continents such as North America and Europe report higher incidence of PCa; however, mortality rates are highest among men of African ancestry in the western, southern, and central regions of Africa and the Caribbean. The American Cancer Society reports, African Americans (AAs), in the United States, have a 1.7 increased incidence and 2.4 times higher mortality rate, compared to European American’s (EAs). Hence, early population history in west Africa and the subsequent African Diaspora may play an important role in understanding the global disproportionate burden of PCa shared among Africans and other men of African descent. Nonetheless, disparities involved in diagnosis, treatment, and survival of PCa patients has also been correlated to socioeconomic status, education and access to healthcare. Although recent studies suggest equal PCa treatments yield equal outcomes among patients, data illuminates an unsettling reality of disparities in treatment and care in both, developed and developing countries, especially for men of African descent. Yet, even after adjusting for the effects of the aforementioned factors; racial disparities in mortality rates remain significant. This suggests that molecular and genomic factors may account for much of PCa disparities.
A Simulative Comparison of AODV and DSR On-Demand Routing Protocols for Mobile Ad-Hoc Networks

Article history: Background: Mobile Ad-hoc NETwork is a collection of two or more mobile nodes that has no infrastructure support, and every mobile node can work as a router. In MANET mobile nodes can move arbitrarily, consequently the system topology changes in random manner. Practically, in order to allow mobile nodes to communicate with each other, a routing protocol is desired to discover routes between nodes, and determines how information is transmitted from a source node to a destination node. Basically, MANET routing protocols are classified into two categories: On-demand and Table-driven. On-demand protocols are utilized whenever a communication is needed. The most widely researched on-demand MANET protocols: DSR (Dynamic Source Routing protocol) and AODV (Ad hoc On-demand Distance Vector protocol). Objective: The main aim of this paper is to simulation based analysis of DSR and AODV protocols on the basis of different performance metrics which are packet delivery fraction (PDF), routing overheads (RO), and end-to-end delay. The simulation is performed through the simulation tool Global Mobile Simulator due to its open source simplicity and free availability. Results: in considered mobility scenarios, AODV gives better PDF than DSR, while DSR gives better RO and End-to-End delay in most mobility scenarios. Conclusion: In this article, an effort has been made to concentrate on the comparative study of well known on-demand protocols (AODV and DSR). Consequently, a single MANET routing protocol cannot accomplish best in all circumstances. Therefore, the preference of MANET routing protocol should be done carefully according to the conditions of the definite application.
Can Pre-trained Language Models be Used to Resolve Textual and Semantic Merge Conflicts?

Program merging is standard practice when developers integrate their individual changes to a common code base. When the merge algorithm fails, this is called a merge conflict. The conflict either manifests in textual merge conflicts where the merge fails to produce code, or semantic merge conflicts where the merged code results in compiler or test breaks. Resolving these conflicts for large code projects is expensive because it requires developers to manually identify the sources of conflict and correct them. In this paper, we explore the feasibility of automatically repairing merge conflicts (both textual and semantic) using k-shot learning with large neural language models (LM) such as GPT-3. One of the challenges in leveraging such language models is to fit the examples and the queries within a small prompt (2048 tokens). We evaluate LMs and k-shot learning for two broad applications: (a) textual and semantic merge conflicts for a divergent fork Microsoft Edge, and (b) textual merge conflicts for a large number of JavaScript projects in GitHub. Our results are mixed: one one-hand, LMs provide the state-of-the-art (SOTA) performance on semantic merge conflict resolution for Edge compared to earlier symbolic approaches; on the other hand, LMs do not yet obviate the benefits of fine-tuning neural models (when sufficient data is available) or the design of special purpose domain-specific languages (DSL) for restricted patterns for program synthesis.
Research on Influencing Mechanism of Industrial Carbon Emissions in Hebei Province

This paper calculates carbon emissions in Hebei Province based on energy consumption and carbon coefficients and adopts the index decomposition model to analyze the influence of value-added industries and carbon emissions per unit added value on carbon emissions.The results indicate that the increase of value-added industries in Hebei Province is the main factor affecting the growth of carbon emissions, but the decrease of carbon emissions per unit added value induces carbon emissions to a lesser reducing. The conclusions can offer the decision basis for reducing carbon emissions.
Pricing cryptocurrencies : Modelling the ETHBTC spot-quotient variation as a diffusion process

This research proposes a model for the intraday variation between the ETHBTC spot and the quotient of ETHUSDT and BTCUSDT traded on Binance. Under conditions of no-arbitrage, perfect accuracy and no microstructure effects, the variation must be equal to its theoretically computed value of 0. We conduct our research on 4 years of data. We find that the variation is not constantly 0. The variation shows a fluctuating behaviour on either side of 0. Furthermore, the deviations tend to be larger in the first year than the rest of the years. We test the sample for the nature of diffusion where we find evidence of meanreversion. We model the variation using an Ornstein-Uhlenbeck process. A maximum likelihood estimation procedure is used. From the accuracy of the sampling distribution of the parameters obtained, we conclude that the variation may be accurately modelled as an Ornstein-Uhlenbeck process. From the parameters obtained, the long-term mean is shown to have a negative sign and differs from the theoretical value of 0 at 1e-05 precision. We take note of the results in light of efficiency of the markets to price publicly known information.
On the Casimir effect from the zero-point energy: a tangential force and its properties

We investigate the Casimir effect in the systems that consist of parallel but misaligned finite-size plates from the point of view of zero-point energy. We elaborate that the zero-point energies of the radiation field in the perfect conductor systems would generate a tangential Casimir force, and explore the properties and consequences of this tangential force in various conductor systems. Thereafter, we generalize our discussion to dielectrics. After calculating the total zero-point energies of the surface modes in the multilayered systems, we show that the tangential force also exists in dielectrics. We obtain the finite-conductivity corrections to the tangential force for imperfectly conducting plates, and calculate the finite-temperature corrections to the force. The typical strength of the tangential force suggests it might be observable.
Semi-nonparametric estimation of operational risk capital with extreme loss events

Bank operational risk capital modeling using the Basel II advanced measurement approach (AMA) often lead to a counter-intuitive capital estimate of value at risk at 99.9% due to extreme loss events. To address this issue, a flexible semi-nonparametric (SNP) model is introduced using the change of variables technique to enrich the family of distributions to handle extreme loss events. The SNP models are proved to have the same maximum domain of attraction (MDA) as the parametric kernels, and it follows that the SNP models are consistent with the extreme value theory peaks over threshold method but with different shape and scale parameters from the kernels. By using the simulation dataset generated from a mixture of distributions with both light and heavy tails, the SNP models in the Frechet and Gumbel MDAs are shown to fit the tail dataset satisfactorily through increasing the number of model parameters. The SNP model quantile estimates at 99.9 percent are not overly sensitive towards the body-tail threshold change, which is in sharp contrast to the parametric models. When applied to a bank operational risk dataset with three Basel event types, the SNP model provides a significant improvement in the goodness of fit to the two event types with heavy tails, yielding an intuitive capital estimate that is in the same magnitude as the event type total loss. Since the third event type does not have a heavy tail, the parametric model yields an intuitive capital estimate, and the SNP model cannot provide additional improvement. This research suggests that the SNP model may enable banks to continue with the AMA or its partial use to obtain an intuitive operational risk capital estimate when the simple non-model based Basic Indicator Approach or Standardized Approach are not suitable per Basel Committee Banking Supervision OPE10 (2019).
Sym(n)- and Alt(n)-modules with an additive dimension

We revisit, clarify, and generalise classical results of Dickson and (much later) Wagner on minimal Sym(n)- and Alt(n)-modules. We present a new, natural notion of 'modules with an additive dimension' covering at once the classical, finitary case as well as modules definable in an o-minimal or finite Morley rank setting; in this context, we fully identify the faithful Sym(n)- and Alt(n)-modules of least dimension.
Degree-preserving graph dynamics - a versatile process to construct random networks

Real-world networks evolve over time via additions or removals of vertices and edges. In current network evolution models, vertex degree varies or grows arbitrarily. A recently introduced degree-preserving network growth (DPG) family of models preserves vertex degree, resulting in structures significantly different from and more diverse than previous models ([Nature Physics 2021, DOI: 10.1038/s41567-021-01417-7]). Despite its degree preserving property, the DPG model is able to replicate the output of several well-known real-world network growth models. Simulations showed that many well-studied real-world networks can be constructed from small seed graphs. Here we start the development of a rigorous mathematical theory underlying the DPG family of network growth models. We prove that the degree sequence of the output of some of the well-known, real-world network growth models can be reconstructed via the DPG process, using proper parametrization. We also show that the general problem of deciding whether a simple graph can be obtained via the DPG process from a small seed (DPG feasibility) is, as expected, NP-complete. It is an important open problem to uncover whether there is a structural reason behind the DPG-constructibility of real-world networks.
Variance Reduction in Deep Learning: More Momentum is All You Need

Variance reduction (VR) techniques have contributed significantly to accelerating learning with massive datasets in the smooth and strongly convex setting (Schmidt et al., 2017; Johnson & Zhang, 2013; Roux et al., 2012). However, such techniques have not yet met the same success in the realm of large-scale deep learning due to various factors such as the use of data augmentation or regularization methods like dropout (Defazio & Bottou, 2019). This challenge has recently motivated the design of novel variance reduction techniques tailored explicitly for deep learning (Arnold et al., 2019; Ma & Yarats, 2018). This work is an additional step in this direction. In particular, we exploit the ubiquitous clustering structure of rich datasets used in deep learning to design a family of scalable variance reduced optimization procedures by combining existing optimizers (e.g., SGD+Momentum, Quasi Hyperbolic Momentum, Implicit Gradient Transport) with a multi-momentum strategy (Yuan et al., 2019). Our proposal leads to faster convergence than vanilla methods on standard benchmark datasets (e.g., CIFAR and ImageNet). It is robust to label noise and amenable to distributed optimization. We provide a parallel implementation in JAX.