Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficient configurations for block ciphers with unified ENC/DEC paths

Block Ciphers providing the combined functionalities of encryption and decryption are required to operate in modes of operation like CBC and ELmD. Hence such architectures form critical building blocks for secure cryptographic implementations. Depending on the algebraic structure of a given cipher, there may be multiple ways of constructing the combined encryption/decryption circuit, each targeted at optimizing lightweight design metrics like area or power etc. In this paper we look at how the choice of circuit configuration affects the energy required to perform one encryption/decryption. We begin by analyzing 12 circuit configurations for the Advanced Encryption Standard (AES-128) cipher and establish some design rules for energy efficiency. We then extend our analysis to several lightweight block ciphers. In the second part of the paper we also investigate area optimized circuits for combined implementations of these ciphers.
Scalable , Reliable , Power-Efficient Communication for Hardware Transactional Memory

In a hardware transactional memory system with lazy versioning and lazy conflict detection, the process of transaction commit can emerge as a bottleneck. This is especially true for a large-scale distributed memory system where multiple transactions may attempt to commit simultaneously and co-ordination is required before allowing commits to proceed in parallel. In this paper, we propose novel algorithms to implement commit that are more scalable (in terms of delay and energy) and are free of deadlocks/livelocks. We show that these algorithms have similarities with the token cache coherence concept and leverage these similarities to extend the algorithms to handle message loss and starvation scenarios. The proposed algorithms improve upon the state-of-the-art by yielding up to a 7X reduction in commit delay and up to a 48X reduction in network messages. These translate into overall performance improvements of up to 66% (for synthetic workloads with average transaction length of 200 cycles), 35% (for average transaction length of 1000 cycles), 8% (for average transaction length of 4000 cycles), and 41% (for a collection of SPLASH-2 programs).
Nocturnal Blood Pressure Pattern Affects Left Ventricular Remodeling and Late Gadolinium Enhancement in Patients with Hypertension and Left Ventricular Hypertrophy

Background Left ventricular hypertrophy (LVH) is an independent predictor of cardiac mortality, regardless of its etiology. Previous studies have shown that high nocturnal blood pressure (BP) affects LV geometry in hypertensive patients. It has been suggested that continuous pressure overload affects the development of LVH, but it is unknown whether persistent pressure influences myocardial fibrosis or whether the etiology of LVH is associated with myocardial fibrosis. Comprehensive cardiac magnetic resonance (CMR) including the late gadolinium enhancement (LGE) technique can evaluate both the severity of changes in LV geometry and myocardial fibrosis. We tested the hypothesis that the nocturnal non-dipper BP pattern causes LV remodeling and fibrosis in patients with hypertension and LVH. Methods Forty-seven hypertensive patients with LVH evaluated by echocardiography (29 men, age 73.0±10.4 years) were examined by comprehensive CMR and 24-h ambulatory blood pressure monitoring (ABPM). Results and Conclusions Among the 47 patients, twenty-four had nocturnal non-dipper BP patterns. Patients with nocturnal non-dipper BP patterns had larger LV masses and scar volumes independent of etiologies than those in patients with dipper BP patterns (p = 0.035 and p = 0.015, respectively). There was no significant difference in mean 24-h systolic BP between patients with and without nocturnal dipper BP patterns (p = 0.367). Among hypertensive patients with LVH, the nocturnal non-dipper blood pressure pattern is associated with both LV remodeling and myocardial fibrosis independent of LVH etiology.
A 3-dimentional multiscale model to simulate tumor progression in response to interactions between cancer stem cells and tumor microenvironmental factors

The recent discovery of cancer stem cells (CSCs), or tumor initiating cells (TICs), in a variety of cancers, including breast cancer, provides a key to understand the processes of tumor initiation, progression and recurrence. Here, we present a three-dimensional (3D) multiscale model of the CSC-initiated tumor growth, which takes into account essential microenvironmental (mE) factors (e.g. nutrients, extracellular matrix) and some important biological traits (e.g. angiogenesis, cell apoptosis, and necrosis) and addresses tumor growth from three different levels, i.e. molecular, cellular and tissue levels. At the molecular level, mathematical diffusion-reaction equations are used to understand the dynamics of mE factors. At the cellular level, a cellular automaton is designed to simulate the life cycle and behaviors of individual cells. At the tissue level, a computer graphics method is used to illustrate the geometry of the whole tumor. The simulation study based on the proposed model indicates that the content of CSCs in a tumor mass plays an essential role in driving tumor growth. The simulation also highlights the significance of developing therapeutic agents that can deliver drug molecules into the interior of the tumor, where most of CSCs tend to reside. The simulation study on the breast cancer xenografts reveals that the mouse tumor initiated from a mixed population of human CSCs and other tumor cells show a faster growth rate, while a weaker proliferation and aggressiveness than that initiated from a pure human CSCs population. These simulation results are mostly consistent with our experimental observations. The mathematical model thus provides a new framework for the modeling and simulation studies of CSC-initiated cancer development.
Patient Satisfaction of Emergency Nursing Care in the United States, Slovenia, and Australia

Patient satisfaction with nursing care in the emergency department (ED) was measured in 616 patients in California and Kentucky in the United States, Slovenia, and rural and urban Victoria in Australia. Patients were almost equally divided between men and women, primarily white, with a mean age of 44. They responded to the caring and teaching subscales of the Consumer Emergency Care Satisfaction Scale (CECSS). While scores indicated no differences in caring, the US and Slovenian groups reported greater satisfaction with teaching than did the Australian group. The subscale alpha coefficients were . 87 for the caring subscale and . 92 for the teaching subscale.
Coronal Heating, Weak MHD Turbulence, and Scaling Laws

Long-time high-resolution simulations of the dynamics of a coronal loop in Cartesian geometry are carried out, within the framework of reduced magnetohydrodynamics (RMHD), to understand coronal heating driven by the motion of field lines anchored in the photosphere. We unambiguously identify MHD anisotropic turbulence as the physical mechanism responsible for the transport of energy from the large scales, where energy is injected by photospheric motions, to the small scales, where it is dissipated. As the loop parameters vary, different regimes of turbulence develop: strong turbulence is found for weak axial magnetic fields and long loops, leading to Kolmogorov-like spectra in the perpendicular direction, while weaker and weaker regimes (steeper spectral slopes of total energy) are found for strong axial magnetic fields and short loops. As a consequence we predict that the scaling of the heating rate with axial magnetic field intensity B0, which depends on the spectral index of total energy for given loop parameters, must vary from B for weak fields to B for strong fields at a given aspect ratio. The predicted heating rate is within the lower range of observed active region and quiet-Sun coronal energy losses.
Self-Organization as a Tool in Mammalian Tissue Engineering

The end goal of most efforts in tissue engineering is the production of an artificial tissue or organ that is as similar as possible to the corresponding natural structure. So far, most approaches to this have involved combining cells with artificially-sculpted, spun or printed scaffolds. The approach works well for anatomically-simple, matrix-rich structures such as connective tissue, both in culture and in vivo. The visually-striking example of an engineered ‘human ear’ on the back of a mouse (Cao et al., 1997) brought much public attention to the idea. Scaffold-based tissue engineering has since found valuable clinical use in the production of new cartilage (Andereya et al., 2006), ligaments (Vunjak-Novakovic et al., 2004), vessels (Lovett et al., 2010), bladder wall (Atala, 2011) and nipple (Cao et al., 1998). Some of the most significant clinical requirements for effective tissue engineering concern not matrix-rich, simple tissues such as connective tissue, but very intricately-arranged complex organs that consist of many cell types, precisely located and in intimate contact with one another. Outstanding amongst these, in terms of clinical urgency, is the kidney, a fragile organ that regenerates itself very poorly, and which is damaged irreversibly by a large range of toxins, including some medicines. The demand for transplantable kidneys far exceeds their supply: in the UK alone, there are about 6,500 people on the waiting list, many leading fairly miserable lives in which they spend many hours per week hooked up to a dialysis machine. Being able to engineer organs such as kidney and pancreas promises a very positive impact on the lives of many patients, particularly if the engineering could be done from the patient’s own stem cells. There are, though, significant problems in extending scaffold-based techniques to organs such as these. The kidney, for example, consists of at least sixty-four distinct cell types (Little et al., 2007) and these are arranged not haphazardly but in very precise order along intricately folded and branched tubules, vessels and stroma (Fig 1). Even if a scaffold could be laid down by some highly-developed three-dimensional printing process to pattern accurately the basement membranes of each of a hundred thousand nephrons, ten thousand collecting ducts and a corresponding number of vessels, it is difficult to see how cells would enter each tube in the appropriate order to populate each segment with the correct type of cell. Kidneys do not normally develop by cells moving into a pre-made scaffold, so there is no reason to suppose that their cells would have evolved the ability to do this even if a scaffold could be provided for them. In normal life, there may be some limited movement of cells along tubules
Design of a Microlecture Mobile Learning System Based on Smartphone and Web Platforms

This paper first analyzes the concept and features of microlecture, mobile learning, and ubiquitous learning, then presents the combination of microlecture and mobile learning, to propose a novel way of micro-learning through mobile terminals. Details are presented of a microlecture mobile learning system (MMLS) that can support multiplatforms, including PC terminals and smartphones. The system combines intelligent push, speech recognition, video annotation, Lucene full-text search, clustering analysis, Android development, and other technologies. The platform allows learners to access microlecture videos and other high-quality microlecture resources wherever and whenever they like, in whatever time intervals they have available. Teachers can obtain statistical analysis results of the microlecture in MMLS to provide teaching/learning feedback and an effective communication platform. MMLS promotes the development of microlecture and mobile learning. A statistical analysis of the implementation of the system shows that students using MMLS to assist their learning had improved results on their final exams and gave a higher evaluation of the curriculum than those who did not. The advantages and disadvantages of MMLS are also analyzed.
Forecasting Post-Extratropical Transition Outcomes for Tropical Cyclones Using Support Vector Machine Classifiers

AbstractIntensity changes following the multistage process of extratropical transition have proven to be especially difficult to forecast because of the extremely similar storm evolutions prior to and during the first stages of the transformation from a warm-cored axisymmetric tropical storm to a cold-cored asymmetrical extratropical low pressure system. In this study, differences in surrounding synoptic environments between dissipating and reintensifying extratropical transitioning tropical cyclones are used to develop a predictive technique for extratropical transition intensity change that can be used to enhance the standard numerical guidance. Using a set of all historical transitioning storms between 2000 and 2008 in the western North Pacific, common differences between 850-hPa potential temperature fields surrounding extratropical transition intensifiers and extratropical transition dissipaters, respectively, were identified. These features were then used as inputs into a support vector machine clas.
Enabling Mobility between Context-Aware Smart Spaces

This paper presents "ConServ", a web service for context management. ConServ allows smart spaces to access user's context data according to user-defined policies. This web service addresses the sharing and management of context data between smart spaces and as a result facilitates the creation of new smart spaces and the enhancement of old ones. Data related to a user's location, calendar, habits, relationships and privacy policy are combined to provide rich context data while users are provided with a single place where they can control the access of all smart spaces to their context data. ConServ provides a set of ontologies, which leverage existing popular ontologies, to model user's context data and the interacting smart spaces.
Reliability of Data Collection Methods in Social Media Research

In this paper we argue for the systematic assessment and reporting of the reliability of data collection methods that rely on the automated collection of data from third party social media sites, where the researcher does not have direct access to meaning or control over data quality. Building on a long tradition of reliability assessment in the sciences and specifically in social science, we propose methods for the assessment of reliability, also for textual data that is increasingly mined from social media for the purposes of studying online populations.
Logical and Computational Properties of the Description Logic Mirtl

In recent years a number of positive (i.e. tractability and decidability) results have been found concerning the computational complexity of Description Logics (DLs) [Buchheit et al., 1993; Donini et al., 1991; Donini et al., 1992a; Donini et al., 1992b; SchmidtSchaus and Smolka, 1991; Sebastiani and Straccia, 1991]. Unfortunately, also negative results have appeared, e.g. showing that some DLs (e.g. NIKL [Patel-Schneider, 1989] and KL-ONE [Schmidt-Schaus, 1989]) are undecidable. This work contributes to this latter literature by showing a negative result for another DL (called Mirtl) which had not been previously studied from the standpoint of computational complexity, and which is not directly related to the ones already shown undecidable; in more standard DL terminology, Mirtl is the ALEN logic plus the I operator for inverse roles and the O1 operator for singleton concepts. We have recently been investigating the use of Mirtl for modelling multimedia information retrieval (see [Meghini et al., 1993; Sebastiani, 1994]). Given the requirements imposed by this application domain, and given the well-known negative results on the computational complexity of more powerful DLs, we had deemed Mirtl the best compromise between expressivity and tractability for our purposes. Somehow encouraged by the fact that the standard reasoning problems in the related logics ALCNR [Buchheit et al., 1993], ALCO [Schaerf, 1994] and ALNI (also known as PL1) [Donini et al., 1991] are all decidable, and considering that the wellknown algorithms based on constraint propagation for reasoning on them tend to be easily customizable to a
Galo: a Deployable Framework for Providing Better than Best-Effort Quality of Service

In this paper we propose a deployable approach to improving QoS by using a generic, extendable, overlay architecture; the Generalized Application Layer Overlay (GALO). The goals of this work are to 1) create an overlay architecture which allows us to sample specific path quality metrics among different paths; 2) utilize the proposed overlay architecture in order to implement our proposed QoS-based routing schemes, Application Layer Switching (ALSW) and Application Layer Striping (ALST). Perhaps the most significant contribution of this research is that we are able to achieve better than best-effort QoS without modifying intermediate nodes (i.e., routers), thus encouraging immediate deployment. Additionally, this research is performed on an actual wide area network (WAN) testbed, comprised of universities across the nation. Also, we assemble this architecture as a peer-to-peer framework, encouraging collaborating individuals with average workstations to improve the QoS of their traffic.
(μ-Acetato){μ-1,3-bis[2-(2-oxidobenzylideneamino)ethyl]-2-(2-oxidophenyl)-1,3-imidazolidine}dizinc(II) ethanol disolvate dihydrate

In the title binuclear compound, [Zn2(C27H27N4O3)(C2H3O2)]·2CH3CH2OH·2H2O, both Zn cations adopt distorted ZnO3N2 trigonal-bipyramidal geometries with one N atom in a axial site and one N atom in an equatorial site, arising from coordination by the N,N,N,N,O,O,O-heptadentate ligand and a bridging acetate ion. In the crystal, intermolecular O—H⋯O hydrogen bonds link the component units into a three-dimensional network. Two short C—H⋯O contacts are also seen.
Enhancing cardiac stem cell differentiation into cardiomyocytes.

Myocardial infarction results in the loss of cardiomyocytes, scar formation, ventricular remodelling, and eventually heart failure. In recent years, cell therapy has emerged as a potential new strategy for patients with ischaemic heart disease. Cell therapy potentially includes embryonic and bone marrow-derived stem cells.1 Recently, the existence of cardiac stem cells that reside in the heart itself was demonstrated. The discovery of cardiac stem cells has sparked intense hope for myocardial regeneration with cells that are obtained from the heart itself and are thereby inherently programmed to reconstitute cardiac tissue. These cardiac stem cells can be detected by several surface markers (e.g. c-kit, Sca-1, MDR1, and Isl-1). 2 Both in vitro and in vivo differentiation into cardiomyocytes, endothelial and vascular smooth muscle cells has been demonstrated. Early animal studies showed promising results on improvement or preservation of left ventricular function after cell injections. Gaetani et al. 3 present their interesting results in this issue of Cardiovascular Research , introducing a new strategy to enhance cardiac differentiation of stem cells without any pharmacological or genetic manipulation. Studies on stem cell transplantation therapy are mainly focused on the use of undifferentiated stem cells. However, it has been postulated that some degree of cardiomyogenic differentiation of stem cells in vitro , prior to transplantation, would yield better results.4 This approach … *Corresponding author. Tel: +31 88 7559801; fax: +31 30 2516396. E-mail address : p.doevendans{at}umcutrecht.nl
How Does Socioeconomic Development Affect COPD Mortality? An Age-Period-Cohort Analysis from a Recently Transitioned Population in China

Background Chronic obstructive pulmonary disease (COPD) is a leading cause of death, particularly in developing countries. Little is known about the effects of economic development on COPD mortality, although economic development may potentially have positive and negative influences over the life course on COPD. We took advantage of a unique population whose rapid and recent economic development is marked by changes at clearly delineated and identifiable time points, and where few women smoke, to examine the effect of macro-level events on COPD mortality. Methods We used Poisson regression to decompose sex-specific COPD mortality rates in Hong Kong from 1981 to 2005 into the effects of age, period and cohort. Results COPD mortality declined strongly over generations for people born from the early to mid 20th century, which was particularly evident for the first generation to grow up in a more economically developed environment for both sexes. Population wide COPD mortality decreased when air quality improved and increased with increasing air pollution. COPD mortality increased with age, particularly after menopause among women. Conclusions Economic development may reduce vulnerability to COPD by reducing long-lasting insults to the respiratory system, such as infections, poor nutrition and indoor air pollution. However, some of these gains may be offset if economic development results in increasing air pollution or increasing smoking.
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor

Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise and data complexity. The differences between scRNA-seq and bulk RNA-seq data mean that the analysis of the former cannot be performed by recycling bioinformatics pipelines for the latter. Rather, dedicated single-cell methods are required at various steps to exploit the cellular resolution while accounting for technical noise. This article describes a computational workflow for low-level analyses of scRNA-seq data, based primarily on software packages from the open-source Bioconductor project. It covers basic steps including quality control, data exploration and normalization, as well as more complex procedures such as cell cycle phase assignment, identification of highly variable and correlated genes, clustering into subpopulations and marker gene detection. Analyses were demonstrated on gene-level count data from several publicly available datasets involving haematopoietic stem cells, brain-derived cells, T-helper cells and mouse embryonic stem cells. This will provide a range of usage scenarios from which readers can construct their own analysis pipelines.
SwiDeN: Convolutional Neural Networks For Depiction Invariant Object Recognition

Current state of the art object recognition architectures achieve impressive performance but are typically specialized for a single depictive style (e.g. photos only, sketches only). In this paper, we present SwiDeN: our Convolutional Neural Network (CNN) architecture which recognizes objects regardless of how they are visually depicted (line drawing, realistic shaded drawing, photograph etc.). In SwiDeN, we utilize a novel `deep' depictive style-based switching mechanism which appropriately addresses the depiction-specific and depiction-invariant aspects of the problem. We compare SwiDeN with alternative architectures and prior work on a 50-category Photo-Art dataset containing objects depicted in multiple styles. Experimental results show that SwiDeN outperforms other approaches for the depiction-invariant object recognition problem.