Miracle-dz/UniFAR-FTUs huggingface dataset:
Putative biomarkers of vedolizumab resistance and underlying inflammatory pathways involved in IBD

Objectives Characterise the circulating inflammatory cytokine pattern among patients failing consecutive anti-tumour necrosis factor (anti-TNF) and anti-integrin treatments to identify predictors of response. Methods A retrospective single-centre cohort study of 28 patients with inflammatory bowel disease (IBD) receiving anti-integrin therapy (vedolizumab) subsequent to the failure of anti-TNF treatment was conducted. Blood samples were obtained immediately prior to initiation of vedolizumab therapy, and the response to treatment was evaluated after completion of the 14-week induction regimen. Multiplex ELISA was applied to quantify 47 preselected plasma proteins based on their putative involvement in the inflammatory process in IBD. Results Anti-TNF and vedolizumab non-responders (n=20) had significantly higher levels of circulating interleukin (IL)-6 than anti-TNF non-responders with subsequent response to vedolizumab (n=8): median 9.5 pg/mL versus 5.9 pg/mL, p<0.05. Following stratification by diagnosis, patients with Crohn’s disease who failed vedolizumab therapy (n=7) had higher soluble CD40 ligand (sCD40L) than responders (n=4): 153.0 pg/mL versus 45.5 pg/mL, p<0.01; sensitivity 100% (95% CI 59% to 100%), specificity 100% (95% CI 40% to 100%). Osteocalcin was higher among patients with ulcerative colitis responding to vedolizumab (n=4) compared with those not responding (n=13): 4219 pg/mL versus 2823 pg/mL, p=0.01; sensitivity 85% (95% CI 55% to 98%), specificity 100% (95% CI 40% to 100%). Conclusions Patients with IBD failing vedolizumab induction and anti-TNF therapy have persistent IL-6 pathway activity, which could be a potential alternative treatment target. sCD40L, osteocalcin and the IL-6 pathway activity might be predictors for response to vedolizumab.
Active distribution network and microgrid integration strategy

Power system dynamics is changing partly due to the large scale deployment of renewable energy sources into the electric grid. Integration of distributed energy resources (DERs), energy storage, and microgrid have introduced new challenges and opportunities for managing power system operation. Source and load control at the distribution level is quickly becoming a key requirement of this evolving system. Voltage regulation, frequency response baselining, anti-islanding, voltage ride through, and reactive margin support are amongst the technical challenges in the Smart Grid era. Microgrids can be used in conjunction with large scale DER deployment using asynchronous interconnection to the main ac grid. This approach helps to create frequency islands facilitating distributed frequency control and can be helpful in a grid with large scale renewable resources. Centralized protection and control (CPC) within a microgrid can provide significant benefits in achieving this objective. These industry initiatives require a renewed attention to protection, automation and control strategies. This paper discusses the benefit of CPC for more DER integration using microgrid as a component of the solution.
Performance evaluation of cloud computing simulation tools

Cloud computing experiments can be conducted on simulators before they are tested on real data centre infrastructure. However, the validation of cloud system simulations is not a well-investigated topic in the literature. It can be difficult to select the suitable tools of simulation to predict infrastructure performance due to the variety of existing cloud computing simulators and their varying levels of accuracy. This paper applies an approach to evaluate any cloud simulator through a comparative validation method against micro data centre infrastructure. We have extended earlier work in evaluating cloud computing simulators by applying the method we used to evaluate CloudSim on other tools. We present the level of accuracy for the GreenCloud simulator and Mininet platforms by applying the comparative validation method and sensitivity analysis for the results on actual and simulated performance. According to our findings, GreenCloud currently does not predict the energy consumption for a micro datacenter accurately. On the other hand, Mininet shows reasonable accuracy in modelling the network performance.
The forecast on the customers of the member point platform built on the blockchain technology by ARIMA and LSTM

Based on the current blockchain technology, a new member point platform was built jointly by the companies from different industries this year. In order to make this platform more efficiently, we should make arrangement for logistics, current funds and supply-chain management system in advance. Therefore, the forecast on the customers of the platform is important for a system. In this paper, we showed the time series dataset abstracted from the member point platform system, gave a comparison of the long short-term memory (LSTM) neural network model and the autoregressive integrated moving average (ARIMA) model with the prediction effectiveness on the number of new increased users on this platform, and analyzed both disadvantages and advantages of the two models.
Location Privacy Violation via GPS-Agnostic Smart Phone Car Tracking

Smart phones nowadays are equipped with global positioning systems (GPS) chips to enable navigation and location-based services. A malicious app with the access to GPS data can easily track the person who carries the smart phone. People may disable the GPS module and turn it on only when necessary to protect their location privacy. However, in this paper, we demonstrate that an attacker is still able to track a person by using the embedded magnetometer sensor in victim's smart phone, even when the GPS module is disabled all the time. Moreover, this attack neither requests user permissions related to locations for installation, nor does its operation rely on wireless signals like WiFi positioning or suffer from signal propagation loss. Only the angles of a car's turning measured by the magnetometer sensor of a driver's smart phone are utilized. Without loss of generality, we focus on car tracking, since cars are popular transportation tools in developed countries, where smart phones are commonly used. Inspired by the intuition that a car may exhibit different turning angles at different road intersections, we find that an attacker can match car turning angles to a map to infer the actual path that the driver takes. We address technical challenges about car turn angle extraction, map database construction, and path matching algorithm design to make this attack practical and efficient. We also perform an evaluation using real-world driving paths to verify the relationship between the numbers of turns and the time cost of the matching algorithm. The results show that it is possible for attacker to precisely pinpoint the actual path when the driving path includes 11 turns or more. More simulations are performed to demonstrate the attack with lager selected local areas.
PMSG based wind power generation for an isolated irrigation system with inbuilt frequency regulation capability

This paper proposes a robust wind and battery storage power system for remote induction motor as irrigation load under islanded operation. A direct torque control (DTC) of permanent magnet synchronous generator (PMSG) is used as wind energy conversion system and the battery is supported at the dc-link of back to back voltage source converter (VSC). The battery energy storage system (BESS) need to fulfill two objective, one is to support dc-link voltage and to remove the secondary frequency drop issue during the rotor speed restoration. A coordinated control technique is adopted in this work and which will ensure smooth operation of complete system. The battery storage system along with irrigation pump side converters are able to control and maintain the active power balance during over and under generation conditions as well as sudden load changes. A direct torque control method is used for controlling the induction motor drive. A suitable LC filter is used to avoid the effect of switching voltage on the irrigation load. Using simulation studies, it has been verified that the proposed PMSG and BESS systems are able to regulate the load side voltage and frequency within the acceptable limits even during the rotor speed restoration period. An experimental prototype of 2.5 kW rating is built in the laboratory to verify the proposed strategy and their associated control strategies have been developed using TMS320F240 processor.
PROCEDURES FOR CORRECTING DIGITAL CAMERA IMAGERY ACQUIRED BY THE AGGIEAIR REMOTE SENSING PLATFORM

V PUBLIC ABSTRACT VII ACKNOWLEDGMENTS VIII LIST OF TABLES IX LIST OF FIGURES X INTRODUCTION 1 PREVIOUS WORK – LITERATURE REVIEW 3 MATERIALS 9 UAV and Payload Description 9 Digital Cameras 10 Reflectance Panel and Neutral Density Filters 12 Study Site 13 Ground Truthing Sampling 13 METHODOLOGY 15 Generate Orthorectified Mosaics 17 Corrected Brightness Value 18 1. Visual Color Imagery CBV 18 2. Near Infrared Imagery CBV 22 White Panel Reflectance Factors 23 Reflectance Images and Layer Stacking 25 1. RGB Reflectance Model 25 2. NIR Reflectance Model 28 Supervised Classification 30 RESULTS 34 DISCUSSION 36 RECOMMENDATIONS FOR FURTHER RESEARCH 38 Continuous Panel Method vs. Modified Reflectance Mode Method 38 Post-Flight Imagery Processing 38 Vignetting Correction Research 39
On the Path to Decarbonization: Electrification and Renewables in California and the Northeast United States

Climate change threatens our quality of life and the habitability of planet Earth for many species. The Intergovernmental Panel on Climate Change estimates that, to reduce the risk that global temperature increases more than 2 &deg;C above preindustrial levels, greenhouse gas (GHG) emissions in developed countries must fall by approximately 80% below 1990 levels by 2050. A number of states and regions in the United States have committed to reducing long-term GHG emissions by this level, including California, New York, and New England. Several studies have evaluated the U.S. and state-specific long-term paths to achieving an 80% reduction in GHG emissions by 2050. Less attention, however, has been given to the midterm transition challenges associated with meeting these long-term climate goals.
Effect of High Oxygen Partial Pressure on Carrier Transport Mechanism in a-InGaZnO TFTs

In this paper, the influence of oxygen partial pressure (<inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula>) during physical vapor deposition on the field-effect mobility of amorphous InGaZnO (IGZO) thin-film transistor (TFT) is investigated in a wide range of <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula>. The field-effect mobility reduced from 12 to 0.1 cm<inline-formula> <tex-math notation="LaTeX">$^{\textsf {2}}/\textsf {V}~\cdot $ </tex-math></inline-formula> s when the <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula> is increased from 0.3 to 1.5 mTorr. Temperature-dependent TFT measurements suggest that carrier transport in the TFTs deposited at the <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula> of 0.3 mTorr can be described according to the multiple trap and release/percolation model. However, the carrier transport in the TFTs deposited at the <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula> of 1.5 mTorr conforms to Mott’s variable-range hopping model. The elastic recoil detection analysis indicates that hydrogen concentration in the IGZO film increased with <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula>. The X-ray photoelectron spectroscopy results indicate that In vacancy (<inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {In}}$ </tex-math></inline-formula>) defects formed in the IGZO film deposited at high <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula>. Scattering induced by hydrogen and pinning of Fermi level below the conduction band edge by <inline-formula> <tex-math notation="LaTeX">${V}_{\textsf {In}}$ </tex-math></inline-formula> are plausible reasons for the low field-effect mobility in TFTs deposited at high <inline-formula> <tex-math notation="LaTeX">${P}_{\textsf {O2}}$ </tex-math></inline-formula>.
Utopia: Near-optimal Coflow Scheduling with Isolation Guarantee

Performance and service isolation come as two top objectives for coflow scheduling. However, the common wisdom is that these two objectives are often conflicting with each other and cannot be achieved simultaneously. Existing coflow scheduling frameworks either focus only on minimizing the average coflow completion time (CCT) (e.g., Varys), or providing optimal isolation between contending coflows by means of fair network sharing (e.g., HUG). In this paper, we make an attempt to achieve the best of both worlds through a novel coflow scheduler, Utopia, to attain near-optimal performance with provable isolation guarantee. This is particularly challenging given the correlation of bandwidth demands across multiple links from coflows. We show that Utopia is capable of reducing the average CCT dramatically, while still guaranteeing that no coflow will ever be delayed beyond a constant time than its CCT in a fair scheme. Both trace-driven simulation and EC2 deployment confirm that Utopia outperforms the fair sharing policy by 1.8 × in terms of average CCT, while producing no completion time delay for a single coflow. Even compared with performance-optimal Varys, Utopia speeds up average coflow completion by 9%.
Mutual Information Generative Adversarial Networks InfoGAN Information Theory Kullback-Liebler Divergence Jensen-Shannon Divergence

An experimental science is only as strong as the veracity of its experiments – when experiments are not reproducible, researchers struggle to place their work on solid footing and progress is hampered. Many fields have had reproducibility crises [5][8][3]. Some have recently recognized this as a problem in machine learning as well [12] [11]. One way to make research more reproducible is to make it easier to develop a deep understanding of the fundamentals underlying machine learning research papers. In this work, we present a new pedagogy, Depth First Learning, that addresses the challenges in understanding these fundamentals. In Depth First Learning, papers are studied down to their core conceptual dependencies, with additional material such as exercises and reproductions in code. We have used this approach in classes and codified our curricula as an open-source website available at http://www.depthfirstlearning. com.
A Random Walk DNA Algorithm for the 3-SAT Problem

We present a randomized DNA algorithm for the 3-SAT problem based on the probabilistic algorithm proposed by Schoning. The basic idea of our algorithm is that the read of information is performed in linear DNA molecules, while the rewrite information is implemented in plasmid DNAs. Compared with previous works, our algorithm performs the flip of a variable’s value more easily and reliably, and the time complexity is also reduced to O(mn), where m is the number of clauses and n is the number of variables. Moreover, Schoning’s algorithm has been further improved recently for the case of 3-SAT by Hofmeister. We also demonstrate how to adapt this improvement in our new algorithm and the space complexity of our algorithm is then reduced to O[(4/3)n-3m’ (7/3)m’], where m’ is the number of the maximal independent clauses. Up to now, this is the most volume-efficient algorithm for the 3-SAT based on DNA computing.
Query-oriented text summarization using sentence extraction technique

Today there is a huge amount of information from a lot of various resources such as World Wide Web, news articles, e-books and emails. On the one hand, human beings face a shortage of time, and on the other hand, due to the social and occupational needs, they need to obtain the most important information from various resources. Automatic text summarization enables us to access the most important content in the shortest possible time. In this paper a query-oriented text summarization technique is proposed by extracting the most informative sentences. To this end, a number of features are extracted from the sentences, each of which evaluates the importance of the sentences from an aspect. In this paper 11 of the best features are extracted from each of the sentences. This paper has shown that use of more suitable features leads to improved summaries generated. In order to evaluate the automatic generated summaries, the ROUGE criterion has been used.
Biochemical and Functional Characterization of Mouse Mammary Tumor Virus Full-Length Pr77Gag Expressed in Prokaryotic and Eukaryotic Cells

The mouse mammary tumor virus (MMTV) Pr77Gag polypeptide is an essential retroviral structural protein without which infectious viral particles cannot be formed. This process requires specific recognition and packaging of dimerized genomic RNA (gRNA) by Gag during virus assembly. Most of the previous work on retroviral assembly has used either the nucleocapsid portion of Gag, or other truncated Gag derivatives—not the natural substrate for virus assembly. In order to understand the molecular mechanism of MMTV gRNA packaging process, we expressed and purified full-length recombinant Pr77Gag-His6-tag fusion protein from soluble fractions of bacterial cultures. We show that the purified Pr77Gag-His6-tag protein retained the ability to assemble virus-like particles (VLPs) in vitro with morphologically similar immature intracellular particles. The recombinant proteins (with and without His6-tag) could both be expressed in prokaryotic and eukaryotic cells and had the ability to form VLPs in vivo. Most importantly, the recombinant Pr77Gag-His6-tag fusion proteins capable of making VLPs in eukaryotic cells were competent for packaging sub-genomic MMTV RNAs. The successful expression and purification of a biologically active, full-length MMTV Pr77Gag should lay down the foundation towards performing RNA–protein interaction(s), especially for structure-function studies and towards understanding molecular intricacies during MMTV gRNA packaging and assembly processes.
Analysis of genotype/phenotype correlations in Japanese patients with dyschromatosis symmetrica hereditaria

ABSTRACT Dyschromatosis symmetrica hereditaria (DSH) is one of the genetic pigmentation disorders and shows characteristic mixture of hyper- and hypo-pigmented small macules on the extremities. Heterozygous mutations in the adenosine deaminase acting on RNA1 gene (ADAR1) cause DSH. In the present study, we report five cases of DSH and identify a distinct known mutation in each patient. Furthermore, we review previously described cases with the five ADAR1 mutations found in the present study. We reviewed clinical and molecular findings in the present and previously reported cases and found an identical mutation can result in various phenotypic severities, even in one family. We found novel phenotype-genotype correlations between the presence/absence of facial lesions and the ADAR1 mutation c.3286C>T. The absence of freckle-like macules in the face was found to be more commonly associated with the mutation c.3286C>T than with the other 4 ADAR1 mutations (odds ratio = 0.056 [95% CI: 0.007–0.47, p < 0.005]). We objectively evaluated the severity of skin manifestations in the extremities using our definition of severity levels for such manifestations. This is the first semi-quantitative evaluation of skin manifestations in DSH. Using our definition, we found that patients with facial lesions with or without hypopigmented macules tend to show more severe symptoms on the extremities than patients without facials lesions show. Furthermore, no significant difference in the severity of the skin lesions was observed between the upper and the lower extremities, suggesting that sun exposure does not affect significantly the pathogenesis of DSH skin lesions.
Restricted Boltzmann Machine-Based Approaches for Link Prediction in Dynamic Networks

Link prediction in dynamic networks aims to predict edges according to historical linkage status. It is inherently difficult because of the linear/non-linear transformation of underlying structures. The problem of efficiently performing dynamic link inference is extremely challenging due to the scale of networks and different evolving patterns. Most previous approaches for link prediction are based on members’ similarity and supervised learning methods. However, research work on investigating hidden patterns of dynamic social networks is rarely conducted. In this paper, we propose a novel framework that incorporates a deep learning method, i.e., temporal restricted Boltzmann machine, and a machine learning approach, i.e., gradient boosting decision tree. The proposed model is capable of modeling each link’s evolving patterns. We also propose a novel transformation for input matrix, which significantly reduces the computational complexity and makes our algorithm scalable to large networks. Extensive experiments demonstrate that the proposed method outperforms the existing state-of-the-art algorithms on real-world dynamic networks.
The Quest for Energy-Efficient I$ Design in Ultra-Low-Power Clustered Many-Cores

High performance and extreme energy efficiency are strong requirements for a fast-growing number of edge-node Internet of Things (IoT) applications. While traditional Ultra-Low-Power designs rely on single-core micro-controllers (MCU), a new generation of architectures leveraging fully programmable tightly-coupled clusters of near-threshold processors is emerging, joining the performance gain of parallel execution over multiple cores with the energy efficiency of low-voltage operation. In this work, we tackle one of the most critical energy-efficiency bottlenecks for these architectures: instruction memory hierarchy. Exploiting the instruction locality typical of data-parallel applications, we explore two different shared instruction cache architectures, based on energy-efficient latch-based memory banks: one leveraging a crossbar between processors and single-port banks (SP), and one leveraging banks with multiple read ports (MP). We evaluate the proposed architectures on a set of signal processing applications with different executable sizes and working-sets. The results show that the shared cache architectures are able to efficiently execute a much wider set of applications (including those featuring large memory footprint and irregular access patterns) with a much smaller area and with much better energy efficiency with respect to the private cache. The multi-port cache is suitable for sizes up to a few kB, improving performance by up to 40 percent, energy efficiency by up to 20 percent, and energy <inline-formula><tex-math notation="LaTeX">$\times$</tex-math><alternatives> <inline-graphic xlink:href="loi-ieq1-2769046.gif"/></alternatives></inline-formula> area efficiency by up to 30 percent with respect to the private cache. The single-port solution is more suitable for larger cache sizes (up to 16 kB), providing up to 20 percent better energy <inline-formula><tex-math notation="LaTeX">$\times$</tex-math><alternatives> <inline-graphic xlink:href="loi-ieq2-2769046.gif"/></alternatives></inline-formula> area efficiency than the multi-port, and up to 30 percent better energy efficiency than private cache.