Miracle-dz/UniFAR-FTUs huggingface dataset:
Epigenetic changes in autoimmune monocytes contribute to disease and can be targeted by JAK inhibition

How the local inflammatory environment regulates epigenetic changes in the context of autoimmune diseases remains unclear. Here we assessed the transcriptional and active enhancer profile of monocytes derived from the inflamed joints of Juvenile Idiopathic Arthritis (JIA) patients, a model well-suited for studying autoimmune diseases. RNA-sequencing analysis demonstrated that synovial-derived monocytes display an activated phenotype, characterized by increased expression of surface activation markers and multiple chemokines and cytokines. This increased expression is regulated on the epigenetic level, as ChIP-sequencing indicated increased H3K27 acetylation of genes upregulated in synovial monocytes. IFN signaling-associated genes are increased and epigenetically altered in synovial monocytes, suggesting a role for IFN in establishing the inflammatory phenotype. Treatment of human synovial monocytes with the Janus-associated kinase (JAK) inhibitor Ruxolitinib, which inhibits IFN signaling, transformed the activated enhancer landscape and reduced disease-associated gene expression, thereby inhibiting the inflammatory phenotype. Taken together, these data provide novel insight into epigenetic regulation of autoimmune disease-patient derived monocytes and suggest that altering the epigenetic profile can be a therapeutic approach for the treatment of autoimmune diseases.
3D Semantic Label Transfer in Human-Robot Collaboration

We tackle two practical problems in robotic scene understanding. First, the computational requirements of current semantic segmentation algorithms are prohibitive for typical robots. Second, the viewpoints of ground robots are quite different from the typical human viewpoints of training datasets which may lead to misclassified objects from robot viewpoints. We present a system for sharing and reusing 3D semantic information between multiple agents with different viewpoints. We first co-localize all agents in the same coordinate system. Next, we create a 3D dense semantic model of the space from human viewpoints close to real time. Finally, by re-rendering the model’s semantic labels (and/or depth maps) from the ground robots’ own estimated viewpoints and sharing them over the network, we can give 3D semantic understanding to simpler agents. We evaluate the reconstruction quality and show how tiny robots can reuse knowledge about the space collected by more capable peers.
Simulation studies of damage location in Tsing Ma Bridge deck

This paper addresses the identification of damage region and location in the Tsing Ma Suspension Bridge deck using modal data. A two-stage identification method is proposed and implemented through numerical simulation for damage detection of the bridge deck. In the first stage, the main span deck of 1377 m length is divided into seventy-six segments and the target in this stage is to determine the deck segment that contains damaged member(s). An index vector derived from mode shape curvatures in both intact and damaged states is presented to identify the damage region (segment). In the second stage, the specific damaged member(s) within the damage region is identified by means of a neural network technique. The combined modal parameters in terms of natural frequencies and a few incomplete modal vectors are adopted as input vector to the neural networks. Two back-propagation networks are trained for the damage location detection. The simulation results show that despite very low modal sensitivity of the bridge to deck member damage, the developed method can still locate the damage at longitudinal structural members such as bottom chords, top chords, and diagonal members.
A case study of snow plow routing using an adaptive large hood search metaheuristic

Abstract Snow plow routing is related to the rural post-man problem. Different constraints can be considered according to the site and the authority in charge. This paper considers the workload balance, partial area coverage, heterogeneous vehicles, road/vehicle dependences, the network hierarchy, and turn restrictions. It also introduces a network based on a case study conducted in a city in the province of Quebec, Canada. This is the first time that a network with both urban and rural characteristics has been solved. This work also innovates by using an adaptive large neighborhood search (ALNS) metaheuristic on a large network (1924 road segments) while considering all the constraints above. The algorithm was used to design new routes for the city and to measure the impact of having fewer vehicles.
Empowerment of Semi Formal and Informal Sector in Realizing A Cheap and Environmentally Friendly Alternative Energy of PLTSa Sumur Batu Business Process

The development of PLTSa has become a government priority program to overcome electricity needs and reduce the amount of waste in Indonesia. However, the program also harms informal groups who earn a living and survive through collecting plastic waste. The objective of this paper is to design a PLTSa business process that not only aims to generate electrical energy and overcome the problem of landfills but also accommodate the needs of informal groups. The situational analysis is conducted using PESTLE and SWOT to enhance a business process canvas that is beneficial to all stakeholders by recommending business innovation for PLTSa. Society as a source of waste is entitled to sort out the waste according to the specified category. The Semiformal group of workers assist the government in the process of collecting, recycling the waste, and finally selling it to third parties. In addition to building PLTSa, government should provide waste management facilities and infrastructure and simultaneously developing an application for elaborating B2B and B2C business processes including collecting waste and selling recycled products. PLN is appointed to be in charge of buying electricity generated by PLTSa and selling it to the community at a reasonable price. The semi-formal groups of workers are expected can improve their business performance and willing to realize environment waste free. The community will be supported with the cheaper electricity bill, while the government will not be burdened with the operational costs of PLTSa.
Acute and subacute toxicity studies of hydroethanolic extract of Baillonella toxisperma Pierre fruit pulp

Baillonella toxisperma Pierre, fruit pulp is largely used in traditional medicine. No toxicity study was done on this fruit pulp. The purpose of this study was to assess the acute and subacute toxicity of the hydroethanolic extract of the fruit pulp of B. toxisperma. An acute toxicity study was conducted at 2000 mg/kg of body weight as a 14-day limit test in Wistar albino rats. Throughout the experiment, general signs of toxicity were noted. Subsequently, a subacute toxicity study was performed at a dose of 400 mg/kg of body weight for 28 days. General signs of toxicity were also noted, after animal sacrifice, histological, hematological, and biochemical analyses (ALAT, ASAT, triglycerides, total cholesterol, total proteins, creatinine) were performed. At LD50? 2000 mg/kg, no general signs of toxicity were noted in either acute or subacute conditions. No signs of toxicity were noted histologically, while slight increases in granulocytes and decreases in lymphocytes were noted hematologically. Biochemically, while no renal observations were made, the extract caused hepatic cytolysis. The fruit pulp of B. toxisperma P could be hepatotoxic at high doses. Key words: Hydroethanolic extract of Baillonella toxisperma Pierre fruit pulp, acute toxicity, subacute toxicity.
On Fault-Tolerant Low-Diameter Clusters in Graphs

Cliques and their generalizations are frequently used to model “tightly knit” clusters in graphs and identifying such clusters is a popular technique used in graph-based data mining. One such model is the s-club, which is a vertex subset that induces a subgraph of diameter at most s. This model has found use in a variety of fields because low-diameter clusters have practical significance in many applications. As this property is not hereditary on vertex-induced subgraphs, the diameter of a subgraph could increase upon the removal of some vertices and the subgraph could even become disconnected. For example, star graphs have diameter two but can be disconnected by removing the central vertex. The pursuit of a fault-tolerant extension of the s-club model has spawned two variants that we study in this article: robust s-clubs and hereditary s-clubs. We analyze the complexity of the verification and optimization problems associated with these variants. Then, we propose cut-like integer programming formulations for both variants whenever possible and investigate the separation complexity of the cut-like constraints. We demonstrate through our extensive computational experiments that the algorithmic ideas we introduce enable us to solve the problems to optimality on benchmark instances with several thousand vertices. This work lays the foundations for effective mathematical programming approaches for finding fault-tolerant s-clubs in large-scale networks.
A new method for measuring cholesterol efflux capacity uses stable isotope-labeled, not radioactive-labeled, cholesterol[S]

The incidence of cardiovascular events correlates inversely with cholesterol efflux capacity (CEC) more than with HDL-cholesterol level. The measurement of CEC is used to qualify cardiovascular disease risk and is conventionally performed with radioisotope (RI)-labeled cholesterol. Here, we established a CEC measurement technique using stable isotope-labeled cholesterol as an alternative, and we compared the new method with RI and fluorescence (boron dipyrromethene difluoride-cholesterol) methods in cells and in patient serum. We incubated J774 cells labeled with [d7]cholesterol ([d7]C) with patient serum depleted of apoB, and [d7]C extracted from the culture medium was quantified by liquid chromatography/quadrupole time-of-flight mass spectrometry. [d7]C efflux increased with greater apoB-depleted serum concentration and longer incubation time. The assay coefficient of variation (CV) of five consecutive measurements of three sets of samples ranged from 7.3% to 9.5%, and the interassay CV determined by measuring three samples four times ranged from 4.1% to 8.5%, both indicating good precision. We then measured CEC levels of 41 outpatients with serum HDL-cholesterol levels between 36 and 94 mg/dl (mean: 61.7 ± 18.0 mg/dl); in the presence of cAMP, we observed a significant, positive correlation between CEC levels determined with the stable isotope and RI methods that was stronger than the correlation between measurements obtained by the fluorescence and RI methods (r = 0.73, P < 0.0001 vs. r = 0.55, P < 0.001). Therefore, our stable isotope method can be considered useful as a non-RI method and thus deserves evaluation in future clinical studies.
Consumer Attitudes Toward Fashion Counterfeits: Application of the Theory of Planned Behavior

This study examines consumer motivations that can explain attitudes toward purchasing fashion counterfeit goods and tests the underlying mechanism of intent to purchase fashion counterfeits based on the theory of planned behavior. A random sample of female college students (N = 336) participate in this study. Product appearance, past purchase behavior, value consciousness, and normative susceptibility are significant predictors of attitude toward buying fashion counterfeit goods. Attitude, subjective norm, and perceived behavioral control are significantly related to intent to purchase fashion counterfeit goods. This research extends the theory of planned behavior and tests two additional paths that significantly improve explanatory power of the theory and prediction of consumer intent to buy fashion counterfeit goods.
MULTIPLE PARAMETER ANALYSIS ON WIRELESS NETWORK USING SPATIAL REUSABILITY

: The selection of optimal route from source node to destination node that guarantees a high end-to-end throughput, is the main issue of routing in multi hop wireless network especially in a multi objective and heterogeneous scenario. As the environment is heterogeneous and various parameters affect the system performance in varying scale, the issue seems to be much complex, most of the solutions end with local optimum because those algorithms mostly fail to ensure not only end to end throughput, but also other parameters of routing like delay, congestion control, energy of nodes etc. By considering spatial reusability of wireless networks, all these parameters of wireless multi hop remote systems can be enhanced significantly. To achieve the expected performance, Spatial-reusability Aware Single-path Routing (SASR) algorithm is proposed and to analyze the performance the same is compared with existing single path routing protocol. Assessment shows that proposed protocol shows significant improvement in comparison with existing protocols.
The Response of Towers and Other Structures to Nearby Lightning

This study describes an attempt to evaluate the potentially hazardous effects on tall structures from nearby cloud-to-ground flashes by conducting measurements of currents and ground potentials on structures during thunderstorms. The analysis of these measurements has shown that the layout of the elements of ground structures and their connections within a grounding grid of the installation have profound effects on magnitudes and polarities of induced currents and voltages. Understanding of the factors affecting the response of tall ground structures to nearby lightning flashes, and therefore correct interpretation of induced lightning effects on a particular installation is crucial for improving the design of grounding systems of the installations.
An Improved Approach for Mining Sequential Pattern Based on Tree for Transaction Databases

: Data mining is the process of extracting useful information from a large volume of data. Sequential pattern mining is very important technique in the field of data mining. Sequential pattern mining is used to find sequential pattern that occurs in large database. In real world massive amount of data are collected and stored everyday in the databases. Many industries are interested to find useful information in the form of sequential patterns from these databases. Sequential pattern mining is used in various applications such as weblog analysis, DNA sequences, stock market analysis, shopping sequence etc. There are mainly two approaches in sequential pattern mining, first is Apriori based approach and Second is Pattern growth-based approach. This paper introduces a new concept of tree based approach, in which database is scanned only once and all the frequent items and itemssets are arranged as a node of tree, All the frequent items and itemsets are assigned row_id and seq_id. The tree based algortihm used here reduces scan time and minimizes memory overhead.
ENHANCED APPROACH TO OPTIMIZED CLOUD RELIABILITY BY USING REDUNDANCY HANDLING AND OPTIMIZED VM SELECTION POLICY

: The developing reliance of clients via web-based networking media, media transmission administrations, portable applications and other cloud services requires an arrangement that mitigates inescapable failures and guarantees the dependably on access to these services. So there must be a way to handle these failures during migration and adoption of cloud without any redundancy. This paper proposes migration way to deal with managing benefit conveyance upon a sudden failure, a virtual machine (VM) over-burden, or support. It builds up a combined redundancy handling FTC programming model that limits the movement downtime that is based on VM memory pages and the reliable situation of the VM. Experimental results shows that proposed system is much reliable than existing systems. The results are calculated in terms of make span, energy consumption and fault tolerance rate during VM migration resource allocation.
Do Contributory Pension Programs Crowd Out Labor Supply in Developing Countries? Evidence from Rural China†

In response to rapid population aging, developing countries have introduced pension schemes to provide income security in late adulthood. However, such programs may create labor market disincentives and induce early labor market withdrawal. This study investigates the impact of an oldage defined contribution scheme, the New Rural Pension Scheme (NRPS), on labor supply decisions in China. Using a regression discontinuity design (RD) and individual-level data, supplemented with administrative records detailing program implementation, we estimate the impacts on the labor market outcomes of people around the benefits eligibility cut-off of age 60. We find robust evidence that the NRPS both reduces labor supply and the receipt of NRPS benefits lowers labor force participation by approximately nine percent. (JEL J14, J22, J26, J32, O12, H55)
Lost in translation? Some issues encountered in transferring village design statements from England to Ireland

The erosion of the distinctive character of smaller rural settlements in England has been addressed with some success through the preparation of Village Design Statements (VDS) by local communities. Adopting a more or less unmodified version of the English VDS model, the Heritage Council introduced a VDS programme in Ireland in 2000. This paper reports on an evaluation of that programme and indicates that VDSs in Ireland have had very limited success to date in terms of their stated objectives. The paper reflects on some of the difficulties experienced in transferring an established community-led initiative from one cultural, political and institutional context to another, and concludes that aspects of that context need to be addressed before VDSs are likely to redress the loss of distinctiveness in villages in Ireland or elsewhere. Further, it concludes that in many situations a community-led instrument embracing broader social, economic and environmental matters might be more appropriate than a VDS.
ROBUST: Deep Learning for Malware Detection under Changing Environments

Malware is one of the most notorious security threats in cyberspace today, and Artificial Intelligence is playing a major role in pushing its design to the next level. Although several malware detection systems (MDS) based on machine learning have recently been designed to cope with the updated malware nature, most of these systems are still not mature enough to capture the modified malware using anti-analysis techniques. Moreover, the patterns extracted and adopted by a machine learning-based MDS are limited to the specific environment and infrastructure. Hence, they are not fully effective against anti-analysis techniques (e.g., obfuscation techniques) and/or when tested in different execution environments (e.g., different machines). Motivated by this fact, this paper presents a new framework for detecting malware in non-stationary environments by leveraging deep learning techniques to extract useful features that are robust against changing environments. More specifically, the framework is based on a special version of an Autoencoder, called a Denoising Autoencoder, which is adopted as a building block in an adaptable deep neural network. The experimental results using a real-world dataset show that the framework improves the detection accuracy compared to existing methods.
Marine biogenic aerosols and their effects on aerosol-cloud interactions over the Southern Ocean: a review

The Southern Ocean (SO) plays an important role in the global climate system. Changes in SO biogeochemistry and marine ecosystems may influence the distribution of atmospheric aerosols and clouds and impact the climate system. We reviewed current knowledge on the interactions between marine aerosols and clouds over the SO. We focused on marine primary and secondary organic aerosols and summarized their characteristics, processes and roles as cloud condensation nuclei and ice nuclei. We described in detail the interactions between the marine ecosystem, aerosols and clouds. We discussed marine productivity, formation of marine biogenic aerosols and interactions between aerosols, clouds and climate. We explored the impact of climate change on SO marine ecosystem productivity and aerosol–cloud–climate feedback. Marine biogenic aerosols could impact the radiation budget and oceanic low-level clouds over the SO. This study contributes towards an improved understanding of marine productivity, aerosol-cloud interactions and climate change in the SO. The SO may respond to climate change in varying degrees. More studies are urgently needed to support accurate forecasts of future changes in the SO. Citation : Xu Y F, Xu G J, Chen L Q, et al. Marine biogenic aerosols and their effects on aerosol-cloud interactions over the Southern Ocean: a review. Adv Polar Sci, 2021, 32(3):195-209, doi: 10.13679/j.advps. 2021.0007
Single element injector testing for STME injector technology

An oxidizer-swirled coaxial element injector is being developed for application in the liquid oxygen/gaseous hydrogen Space Transportation Main Engine (STME) for the National Launch System (NLS) vehicle. This paper reports on the first two parts of a four part single injector element study for optimization of the STME injector design. Measurements of Rupe mixing efficiency and atomization characteristics are reported for single element versions of injection elements from two multielement injectors that have been recently hot fire tested. Rather than attempting to measure a definitive mixing efficiency or droplet size parameters of these injector elements, the purpose of these experiments was to provide a baseline comparison for evaluating future injector element design modifications. Hence, all the experiments reported here were conducted with cold flow simulants to nonflowing, ambient conditions. Mixing experiments were conducted with liquid/liquid simulants to provide economical trend data. Atomization experiments were conducted with liquid/gas simulants without backpressure. The results, despite significant differences from hot fire conditions, were found to relate to mixing and atomization parameters deduced from the hot fire testing, suggesting that these experiments are valid for trend analyses. Single element and subscale multielement hot fire testing will verify optimized designs before committing to fullscale fabrication.