Miracle-dz/UniFAR-FTUs huggingface dataset:
Chained Lin-Kernighan for Large Traveling Salesman Problems

We discuss several issues that arise in the implementation of Martin, Otto, and Felten's Chained Lin-Kernighan heuristic for large-scale traveling salesman problems. Computational results are presented for TSPLIB instances ranging in size from 11,849 cities up to 85,900 cities; for each of these instances, solutions within 1% of the optimal value can routinely be found in under one CPU minute on a 300 MHz Pentium II workstation, and solutions within 0.5% of optimal can routinely be found in under ten CPU minutes. We also demonstrate the scalability of the heuristic, presenting results for randomly generated Euclidean instances having up to 25,000,000 cities. For the largest of these random instances, a tour within 1% of an estimate of the optimal value was obtained in under one CPU day on a 64-bit IBM RS6000 workstation.
Modelling and Control of an Interline Current Flow Controller for Meshed HVDC Grids

This paper focuses on the modelling and control of an interline current flow controller (CFC) for meshed HVDC grids. The operation states of the CFC are presented, and an average model is derived. The average model is used to perform steady-state analysis on a 3-terminal meshed grid, showing the current change capabilities and the benefits on the operation area. The converter control is designed using a linearized model. The system performance of the CFC is tested by means of simulation in a 3-terminal grid and in a 5-terminal grid.
Statistical clock skew analysis considering intra-die process variations

With shrinking cycle times, clock skew has become an increasingly difficult and important problem for high performance designs. Traditionally, clock skew has been analyzed using case-files which cannot model intra-die process variations and hence result in a very optimistic skew analysis. In this paper, we present a statistical skew analysis method to model intra-die process variations. We first present a formal model of the statistical clock skew problem and then propose an algorithm which is based on propagation of joint probability distribution functions in a bottom up fashion in a clock tree. The analysis accounts for topological correlations between path delays and has linear run time with the size of the clock tree. The proposed method was tested on several large clock tree circuits, including a clock tree from a large industrial high-performance microprocessor. The results are compared with Monte Carlo simulation for accuracy comparison and demonstrate the need for statistical analysis of clock skew.
Bilateral Filtering of Diffusion Tensor Magnetic Resonance Images

We extend the well-known scalar image bilateral filtering technique to diffusion tensor magnetic resonance images (DTMRI). The scalar version of bilateral image filtering is extended to perform edge-preserving smoothing of DT field data. The bilateral DT filtering is performed in the log-Euclidean framework which guarantees valid output tensors. Smoothing is achieved by weighted averaging of neighboring tensors. Analogous to bilateral filtering of scalar images, the weights are chosen to be inversely proportional to two distance measures: The geometrical Euclidean distance between the spatial locations of tensors and the dissimilarity of tensors. We describe the noniterative DT smoothing equation in closed form and show how interpolation of DT data is treated as a special case of bilateral filtering where only spatial distance is used. We evaluate different DT tensor dissimilarity metrics including the log-Euclidean, the similarity-invariant log-Euclidean, the square root of the J-divergence, and the distance scaled mutual diffusion coefficient. We present qualitative and quantitative smoothing and interpolation results and show their effect on segmentation, for both synthetic DT field data, as well as real cardiac and brain DTMRI data.
Nominal direction and direction spread estimation for slightly distributed scatterers using the SAGE algorithm

In this paper, the SAGE (subspace-alternating generalized expectation-maximization) algorithm is derived using the generalized array manifold (GAM) model proposed in Asztely et al. (1997) (GAM-SAGE) to estimate the nominal directions, i.e. azimuths and elevations of slightly distributed scatterers (SDS). As byproducts estimates of the azimuth spreads (AS), elevation spreads (ES), and the azimuth-elevation correlation coefficients (AECC) of the SDS can be computed from the estimates of the GAM parameters. These parameters determine with close accuracy the direction spreads of SDS. Simulation studies show that in a single-SDS scenario, the GAM-SAGE algorithm outperforms the Spread-ESPRIT technique, and both of them outperform the SAGE algorithm derived with the conventional specular-scatterer (SS) model (SS-SAGE) when the output signal-to-noise ratio (SNR) is beyond a certain threshold which depends on the AS and ES of the SDS. In a two-SDS scenario with strong power imbalance between the SDS, provided the direction spacing between the SDS equals twice the intrinsic azimuth or elevation resolution of the array, the GAM-SAGE algorithm can estimate the nominal direction of the SDS with weakest power with tolerably small errors. The SS-SAGE algorithm returns high root mean squared estimation error (RMSEE) regardless of the direction separation. We also found that the AECC estimator needs to operate in high SNR in order for its bias and RMSEE to be tolerably small. The performance of the AECC estimator, as well as the AS and ES estimators can be improved by applying an array-size selection technique proposed in Yin et al. (2005).
Learning from Experience with Delayed Feedback

Many important settings in individual and organizational life involve allocating resources between different types of activities with different delays between allocation and results. Examples include factory managers choosing to spend time on production now or on process improvement that may boost output later, and individuals choosing to get a job now or stay in school to get a better job later. Empirical studies show that learning is difficult in dynamic systems and people often fail to learn from experience in the presence of delays. Understanding the processes that hinder learning from experience is central to improving learning and decisionmaking. We use a formal model to examine the effect of time delays on learning from experience. The model represents a decision-maker engaged in a continuous time allocation task who learns from his performance as he tries to improve the payoff determined by his own actions. Our analysis shows that in an easy learning task where the payoff landscape is smooth and has only a single peak, we can still observe sub-optimal performance. Moreover, the decision maker can learn to believe that the sub-optimal performance is really the best she can do.
Ice supersaturation in the ECMWF integrated forecast system

A parametrization for ice supersaturation is introduced into the ECMWF Integrated Forecast System (IFS), compatible with the cloud scheme that allows partial cloud coverage. It is based on the simple, but often justifiable, diagnostic assumption that the ice nucleation and subsequent depositional growth time‐scales are short compared to the model time step, thus supersaturation is only permitted in the clear‐sky portion of the grid cell.
Emergence of different macrophage populations in hepatic fibrosis following thioacetamide-induced acute hepatocyte injury in rats.

Macrophages may play a role in fibrogenesis. The kinetics and distribution of different macrophage populations were investigated immunohistochemically in hepatic lesions following acute hepatocyte injury induced in F344 rats by a single injection of thioacetamide (TAA) (300 mg/kg body weight, intraperitoneally). Hepatocyte degeneration or necrosis induced by TAA occurred mainly in the perivenular areas of hepatic lobules as early as post-injection (PI) days 1 and 3; fibrotic lesion development began in the damaged areas on day 1, and peaked on day 5; thereafter (PI days 7 and 10), the fibrotic areas decreased and were replaced by regenerated hepatocytes on PI days 15 and 20, indicating a remodelling process. In this rat model, the number of macrophages reacting with ED1 antibody (specific for exudate macrophages), ED2 (recognizing cell membrane antigens of resident macrophages, including Kupffer cells) and OX6 (recognizing MHC class II antigens expressed in antigen-presenting macrophages and dendritic cells) began to increase on PI day 1, peaking on PI day 3. The numbers gradually decreased on PI days 5 and 7; however, the statistically significant increase was maintained in respect of ED1-positive cells up to PI day 20, whereas no significant increase in ED2- and OX6-positive cells remained from PI day 10 onwards. Interestingly, of the ED1-, ED2- and OX6-positive cells, the OX6-positive cells were the least numerous. ED1- and OX6-positive cells appeared exclusively in the injured perivenular areas, whereas ED2-positive cells were present mainly in the mid-zonal areas and in smaller numbers in the perivenular areas. These findings indicated differences in kinetics and distribution between macrophage populations appearing in hepatic fibrosis. In addition, RT-PCR revealed that mRNA expression of osteopontin, a factor for induction and maintenance of macrophages in inflammation, was markedly increased on PI days 5, 7 and 10, suggesting a role in the pathogenesis of hepatic fibrosis.
Privacy-preserving interest-casting in opportunistic networks

Message forwarding is a fundamental brick to spread information among users in opportunistic networks. In this paper, we consider the recently proposed interest-casting networking primitive for opportunistic networks, according to which a packet generated by a sender should be delivered to all users in the network - potentially unknown to the sender - sharing similar interests. However, the current implementation of interest-casting assume users exchange their interest profiles to take forwarding decisions, thus revealing very sensitive information to strangers. In this work, we approach for the first time the problem of designing an interest-casting protocol while not revealing sensitive information during the forwarding and message delivery process. In particular, we present a privacy-preserving mechanism based on the well-known Millionaires' problem allowing users to discover whether they have similar interests without disclosing private information. Based on this mechanism, we propose four different privacy-preserving forwarding protocols to realise interest-casting in opportunistic networks, and we compare their performance on a real-world mobility trace.
Differential evolution with adaptive parameter setting for multi-objective optimization

Control parameter settings influence the convergence probability and convergence speed of evolutionary algorithms but it is often not obvious how to choose them. In this work an adaptive approach for setting the control parameters of a multi-objective differential evolution algorithm is presented. The adaptive approach is based on methods from design of experiments, so it is able to detect significant performance differences of individual parameters as well as interaction effects between parameters. It is evaluated based on 13 test functions and several performance measures.
Dynamic Instruction Cache Locking in Hard Real-Time Systems

Cache memories have been widely used in order to bridge the gap between high speed processors and relatively slower main memories, and thus to improve the overall performance of systems. However in the context of hard real-time systems, they are a source of predictability problems. A lot of progress has been achieved to model caches to statically determine safe and precise bounds on the worst-case execution times (WCETs) estimates of tasks on architectures with caches. Nonetheless cache-aware WCET analysis techniques may not always be applicable or may be too pessimistic, because some memory accesses are unknown statically. Another reason may come from a poorly documented or non-deterministic cache line replacement policy. An alternative approach is to lock cache lines so as to make memory access times entirely predictable. In this paper, we consider an instruction cache and a task. We propose a an algorithm which partitions the task into a set of regions. Each region owns statically a locked cache contents determined
The Genome of Burkholderia cenocepacia J2315, an Epidemic Pathogen of Cystic Fibrosis Patients

ABSTRACT Bacterial infections of the lungs of cystic fibrosis (CF) patients cause major complications in the treatment of this common genetic disease. Burkholderia cenocepacia infection is particularly problematic since this organism has high levels of antibiotic resistance, making it difficult to eradicate; the resulting chronic infections are associated with severe declines in lung function and increased mortality rates. B. cenocepacia strain J2315 was isolated from a CF patient and is a member of the epidemic ET12 lineage that originated in Canada or the United Kingdom and spread to Europe. The 8.06-Mb genome of this highly transmissible pathogen comprises three circular chromosomes and a plasmid and encodes a broad array of functions typical of this metabolically versatile genus, as well as numerous virulence and drug resistance functions. Although B. cenocepacia strains can be isolated from soil and can be pathogenic to both plants and man, J2315 is representative of a lineage of B. cenocepacia rarely isolated from the environment and which spreads between CF patients. Comparative analysis revealed that ca. 21% of the genome is unique in comparison to other strains of B. cenocepacia, highlighting the genomic plasticity of this species. Pseudogenes in virulence determinants suggest that the pathogenic response of J2315 may have been recently selected to promote persistence in the CF lung. The J2315 genome contains evidence that its unique and highly adapted genetic content has played a significant role in its success as an epidemic CF pathogen.
Influence of low amounts of nanostructured silica and calcium carbonate fillers on the large-area dielectric breakdown performance of bi-axially oriented polypropylene

Influence of low amounts (1.0-2.0wt-%) of nanostructured silica and calcium carbonate fillers on the large-area dielectric breakdown performance of bi-axially oriented polypropylene (BOPP) is analyzed. A multi-breakdown measurement method based on the self-healing breakdown capability of metallized film is utilized for the breakdown characterization in order to cover relatively large total film areas, thus leading to results of higher relevance from the practical point-of-view. The dispersion and distribution qualities of filler particles at the nanoscale are evaluated with transmission electron microscopy (TEM) imaging. Weibull statistical analysis suggests that the breakdown distribution homogeneity can be improved with both the filler types. The 1.0wt-% silica-BOPP composite also shows a shift of the weakest points towards higher dielectric strength in comparison to the neat BOPP. However, with increasing filler content, new failure modes are introduced into the nanocomposites, hence decreasing the overall breakdown performance in the >5% breakdown probability region in comparison to the un-filled reference BOPP film.
CLEAR VISmmiTY AND THE DIMENSION OF KERNELS OF STARSHAPED SETS

This paper will use the concept of clearly visible to obtain a Krasnosel'skii-type theorem for the dimension of the kernel of a starshaped set, and the following result will be proved: For each fc and n, 1 < k < n, let f(n,n) = n -\1 and /(n, fc) = 2n if 1 < fc < n — 1. Let S be a nonempty compact set in Rn. Then for a fc with 1 < fc < n, dim ker S > fc if and only if every f(n, fc) points of bdry S are clearly visible from a common fc-dimensional subset of S. If fc = 1 or fc = n, the result is best possible. Moreover, if S is a compact, connected, nonconvex set in Ft2, then bdry S may be replaced by lnc S in the theorem.
Diosgenin Modulates Vascular Smooth Muscle Cell Function by Regulating Cell Viability, Migration, and Calcium Homeostasis

In this study, we compared the potencies of diosgenin, a plant-derived sapogenin structurally similar to estrogen and progesterone, on vascular smooth muscle functions ranging from contraction and migration to apoptosis. The effects of diosgenin on vascular smooth muscle cell viability and migration were measured using a primary mouse aortic smooth muscle cell culture. The effects of diosgenin on smooth muscle cell contraction and calcium signaling were investigated in the isolated mouse aorta using wire myography and confocal microscopy, respectively. Here, we report that in cultured cells diosgenin (≥25 μM) induces apoptosis as measured by the number of annexin V-positive cells and caspase-3 cleavage, while decreasing cell viability as indicated by protein kinase B/Akt phosphorylation. In addition, diosgenin blocks smooth muscle cell migration in a transwell Boyden chamber in response to serum treatment and response to injury in a cell culture system. Diosgenin (≥25 μM) also significantly blocks receptor-mediated calcium signals and smooth muscle contraction in the isolated aorta. There is no difference in the inhibitory effects of diosgenin on vascular smooth muscle contraction between the endothelium-intact and endothelium-denuded aortic segments, indicating that they are caused by altered smooth muscle activity. Our findings suggest that over the concentration range of 10 to 15 μM diosgenin may provide overall beneficial effects on diseased vascular smooth muscle cells by blocking migration and contraction without any significant cytopathic effects, implying a potential therapeutic value for diosgenin in vascular disorders.
High and low flow nitrate distribution and its implications for nitrate retention in Navigation Pool 8, Upper Mississippi River (UMR), and in a high-nitrate tributary, the Root River, USA

Excessive nitrate transport from large, agriculturallydominated watersheds to estuaries and coastal waters is an emerging national (USA; HOWARTH et al. 1996) and global problem. In the United States high nitrate transport from the Mississippi River has been implicated in development of a large hypoxic zone in the Gulf of Mexico (GooLSBY et al. 2001, RABALAIS et al. 2002). The primary nitrate source (40%) is the Upper Mississippi River Basin (UMRB), defined as the upstream portion o f the watershed north of Cairo Illinois (STRAUSS et al. 2004, RICHARDSON et al: 2004).
HLAC Approach to Automatic Object Counting

Counting (identical) objects in images is a simple yet fundamental recognition task that requires exhaustive human effort. Automation of this task would reduce the human load significantly. In this paper, we propose a statistical method to automatically count objects in an image sequence by using higher-order local auto-correlation (HLAC) based image features and multiple regression analysis (MRA). This method is based on a simple computation, which enables fast and automatic object counting in real time. We propose several methods that have different preprocessing and image features and conduct comparative experiments of counting objects (ducks in this paper) in images captured by outdoor monitoring cameras. The experimental results demonstrated the effectiveness of the proposed methods.
Understanding the migration phenomenon: the romanian roma in Sweden

Since Romania joined the European Union (EU) in 2007, other EU member countries have started to experience an influx of migrants from Romania, specifically the Roma community. The Roma population has been a discriminated group for centuries. In Romania, their social exclusion has been related to a wide range of factors such as ethnic origin, poor living conditions, or the limited access to education and employment. These factors are not mutually exclusive and they usually come together. This paper is aimed to describe the migration phenomenon of Romanian Romani people in Stockholm, Sweden through the eyes of the migrants themselves. The main goal is to get first-hand knowledge about the Roma community and truly understand the characteristics of their mobility process. The study is primarily based on qualitative research, which gives a clearer insight of the Romani migration. Six semi-structured interviews aresupporting the bibliographical reviews.
Myelin basic protein gene contains separate enhancers for oligodendrocyte and Schwann cell expression

The DNA sequence between position +36 and -1907 of the murine myelin basic protein gene contains the enhancer and promoter elements necessary for abundant and cell specific expression in transgenic mice. Surprisingly, the pattern of expression promoted by this DNA fragment is a subset of that exhibited by the endogenous myelin basic protein (MBP) gene. Fusion genes prepared with this promoter/enhancer and a Lac Z reporter gene are expressed only in oligodendrocytes and not in Schwann cells, whereas the endogenous MBP gene is expressed in both cell types. The level of transgene expression measured by nuclear run- on experiments is very substantial and rivals that of the endogenous MBP gene. Furthermore, this 1.9-kb DNA fragment directs transcription on the same (or very similar) developmental schedule as the endogenous gene. These results indicate that the MBP promoter/enhancer sequences are at least tripartite: a core promoter, the oligodendrocyte enhancer elements, and a third component that either expands the specificity of the oligodendrocyte enhancer to include Schwann cells or acts independently to specifically stimulate transcription in Schwann cells.
HopLand: single-cell pseudotime recovery using continuous Hopfield network-based modeling of Waddington’s epigenetic landscape

Motivation: The interpretation of transcriptional dynamics in single‐cell data, especially pseudotime estimation, could help understand the transition of gene expression profiles. The recovery of pseudotime increases the temporal resolution of single‐cell transcriptional data, but is challenging due to the high variability in gene expression between individual cells. Here, we introduce HopLand, a pseudotime recovery method using continuous Hopfield network to map cells to a Waddington's epigenetic landscape. It reveals from the single‐cell data the combinatorial regulatory interactions among genes that control the dynamic progression through successive cell states. Results: We applied HopLand to different types of single‐cell transcriptomic data. It achieved high accuracies of pseudotime prediction compared with existing methods. Moreover, a kinetic model can be extracted from each dataset. Through the analysis of such a model, we identified key genes and regulatory interactions driving the transition of cell states. Therefore, our method has the potential to generate fundamental insights into cell fate regulation. Availability and implementation: The MATLAB implementation of HopLand is available at https://github.com/NetLand‐NTU/HopLand. Contact: zhengjie@ntu.edu. sg