Miracle-dz/UniFAR-FTUs huggingface dataset:
Consequential Life Cycle Assessment With Market‐Driven Design

This article describes the development of a consequential life cycle assessment (cLCA) with endogenous market‐driven design (MDD). Incorporation of MDD within cLCA (cLCA‐MDD) is beneficial because design decisions, influenced by market forces, are a major source of environmental emissions and resource consumption in many life cycle systems. cLCA‐MDD captures the environmental impact of these design responses resulting from industrial and policy decisions. We begin by developing the concept of cLCA‐MDD, then present a case study that demonstrates how design responses can be endogenously captured in a cLCA analysis. The case study is in two parts: First, we incorporate endogenous design responses into a cLCA of a mid‐size vehicle and, second, we conduct a policy analysis using a cLCA‐MDD approach. The case study illustrates that cLCA‐MDD can capture multiple “ripple effects” resulting from an industrial decision (e.g., downsizing a vehicle's engine) or a policy decision (e.g., raising gasoline taxes) and that these effects significantly influence results. A key challenge of the approach is appropriately managing and communicating uncertainties associated with the choice of economic parameters or models. We discuss sources of uncertainty in cLCA‐MDD and demonstrate a presentation scheme to facilitate communication of result sensitivity to uncertainties from input parameters, models, and model structure.
The Application of Microcapsule Technology in Dyeing and Finishing

It briefly described the exterior characteristics,release mechanism and preparation methods of microcapsule dyes,recounted the application of microcapsule dyes in textile in recent years.The microcapsule technology gave new and unique function and appearance for textile,and effectively solved the problems in textile printing,especially could bring about no fertilizer and avoid water dyeing.
General Hail Occurrence Frequency in Convective Storms Using mPING Data

While non-severe hail is perceived as having little direct societal impact, it can negatively impact the quantitative precipitation estimation (QPE), something that can have significant societal impact. Miscalculated QPE can lead to mismanagement of emergency services, poor hydrologic forecasts, and mismanagement of water resources. By determining the proportion of convective storms that are associated with any hail but, particularly small or non-severe, we can begin to understand the extent to which QPE is affected by small hail. The current hydrometeor classification algorithms have little skill at discriminating between small hail and large raindrops. Thus choosing a threshold at which to make adjustments to QPE due to hail is difficult. We can use meteorological Phenomena Identification near the Ground (mPING) crowd-sourced weather reports to make a rough estimate of how common small hail is at the surface within convective storms. By pairing mPING data with composite reflectivity within identified storms, no clear hail/no hail threshold emerges, and so adjusting QPE based on reflectivity values is unlikely to result in much improvement in QPE.
Efficient compilation of .NET programs for embedded systems

The overhead associated with object-oriented languages has been the major drawback in their adoption by the embedded world. In this paper, we propose a compilation approach based on the closed-world assumption (CWA) that should enable OO technologies such as . Net on small embedded systems. Our implementation is based on a type analysis algorithm, which extends RTA so that it eliminates some subtype tests due to array covariance, and coloring, which maintain single subtyping invariants under the CWA. The impact of our global optimizations has been evaluated on embedded applications written in C#. Preliminary results show a noticeable reduction of the code size, class hierarchy and object mechanisms such as virtual calls and subtype tests.
Rutin Isolated from Chrozophora tinctoria Enhances Bone Cell Proliferation and Ossification Markers

Osteoporosis is a chronic disease in which the skeleton loses a weighty proportion of its mineralized mass and mechanical pliability. Currently available antiosteoporotic agents suffer adverse effects that include elevated risk of thrombosis and cancer. Phytochemicals may constitute a safer and effective option. In the current work, six flavonoids were obtained from Chrozophora tinctoria and identified as amentoflavone (1), apigenin-7-O-β-d-glucopyranoside (2), apigenin-7-O-6′′-E-p-coumaroyl-β-d-glucopyranoside (3), acacetin-7-O-β-d-[α-l-rhamnosyl(1→6)]3′′-E-p-coumaroyl glucopyranoside (4), apigenin-7-O-(6′′-Z-p-coumaroyl)-β-d-glucopyranoside (5), and rutin (6). An extensive review of the literature as well as NMR and mass spectral techniques was employed in order to elucidate the compound structures. Proliferation was enhanced in MCF7, MG-63, and SAOS-2 cells after exposure to subcytotoxic levels of the tested flavonoids. Rutin was chosen for subsequent studies in SAOS-2 cells. Rutin was not found to cause any alteration in the index of proliferation of these cells, when examining the cell cycle distribution by DNA flowcytometric analysis. Rutin was, however, found to increase osteocyte and osteoblast-related gene expression and lower the expression of RUNX suppressor and osteoclast genes. When examining the influence of rutin on vitamin D levels and the activity of alkaline phosphatase enzyme, it was found to enhance both, while decreasing acid phosphatase which is a marker of osteoporosis. Thus, rutin enhances proliferation and ossification markers in bone cells.
Predicting Player Experience without the Player.: An Exploratory Study

A key challenge of procedural content generation (PCG) is to evoke a certain player experience (PX), when we have no direct control over the content which gives rise to that experience. We argue that neither the rigorous methods to assess PX in HCI, nor specialised methods in PCG are sufficient, because they rely on a human in the loop. We propose to address this shortcoming by means of computational models of intrinsic motivation and AI game-playing agents. We hypothesise that our approach could be used to automatically predict PX across games and content types without relying on a human player or designer. We conduct an exploratory study in level generation based on empowerment, a specific model of intrinsic motivation. Based on a thematic analysis, we find that empowerment can be used to create levels with qualitatively different PX. We relate the identified experiences to established theories of PX in HCI and game design, and discuss next steps.
Effects of Phytochemically Characterized Extracts From Syringa vulgaris and Isolated Secoiridoids on Mediators of Inflammation in a Human Neutrophil Model

Aim of the study: The aim of the present study was to investigate the effects of phytochemically characterized extracts connected with the traditional use (infusions and ethanolic extracts) of different parts of Syringa vulgaris (common lilac) on the pro-inflammatory functions of neutrophils. Active compounds were isolated from the most promising extract(s) using bioassay-guided fractionation, and their activity and molecular mechanisms of action were determined. Methods: The extracts were characterized using a HPLC-DAD- MSn method. The effects on ROS, MMP-9, TNF-α, IL-8, and MCP-1 production by neutrophils were measured using luminol-dependent chemiluminescence and enzyme-linked immunosorbent assay (ELISA) methods. The effects on p38MAPK, ERK1/2, JNK phosphorylation, and NF-kB p65 translocation were determined using western blots. Results: The major compounds detected in the extracts and infusions belong to structural groups, including caffeic acid derivatives, flavonoids, and iridoids. All extracts and infusions were able to significantly reduce ROS and IL-8 production. Bioassay-guided fractionation led to the isolation of the following secoiridoids: 2″-epiframeroside, oleonuezhenide, oleuropein, ligstroside, neooleuropein, hydroxyframoside, and framoside. Neooleuropein appeared to be the most active compound in the inhibition of cytokine production by attenuating the MAP kinase pathways. Conclusion: The present study demonstrated that common lilac, which is a traditionally used medicinal plant in Europe, is a valuable source of active compounds, especially neooleuropein.
HIV Replication Is Not Controlled by CD8+ T Cells during the Acute Phase of the Infection in Humanized Mice

HIV replication follows a well-defined pattern during the acute phase of the infection in humans. After reaching a peak during the first few weeks after infection, viral replication resolves to a set-point thereafter. There are still uncertainties regarding the contribution of CD8+ T cells in establishing this set-point. An alternative explanation, supported by in silico modeling, would imply that viral replication is limited by the number of available targets for infection, i.e. CD4+CCR5+ T cells. Here, we used NOD.SCID. gc-/- mice bearing human CD4+CCR5+ and CD8+ T cells derived from CD34+ progenitors to investigate the relative contribution of both in viral control after the peak. Using low dose of a CCR5-tropic HIV virus, we observed an increase in viral replication followed by “spontaneous” resolution of the peak, similar to humans. To rule out any possible role for CD8+ T cells in viral control, we infected mice in which CD8+ T cells had been removed by a depleting antibody. Globally, viral replication was not affected by the absence of CD8+ T cells. Strikingly, resolution of the viral peak was equally observed in mice with or without CD8+ T cells, showing that CD8+ T cells were not involved in viral control in the early phase of the infection. In contrast, a marked and specific loss of CCR5-expressing CD4+ T cells was observed in the spleen and in the bone marrow, but not in the blood, of infected animals. Our results strongly suggest that viral replication during the acute phase of the infection in humanized mice is mainly constrained by the number of available targets in lymphoid tissues rather than by CD8+ T cells.
Improving Reliability, Security, and Efficiency of Reconfigurable Hardware Systems

In this treatise, my research on methods to improve efficiency, reliability, and security of reconfigurable hardware systems, i.e., FPGAs, through partial dynamic reconfiguration is outlined. The efficiency of reconfigurable systems can be improved by loading optimized data paths on-the-fly on an FPGA fabric. This technique was applied to the acceleration of SQL queries for large database applications as well as for image and signal processing applications. The focus was not only on performance improvements and resource efficiency, but also the energy efficiency has been significantly improved. In the area of reliability, countermeasures against radiation-induced faults and aging effects for long mission times were investigated and applied to SRAM-FPGA-based satellite systems. Finally, to increase the security of cryptographic FPGA-based implementations against physical attacks, i.e., side-channel and fault injection analysis as well as reverse engineering, it is proposed to transform static circuit structures into dynamic ones by applying dynamic partial reconfiguration.
Validation of a Scoring System to Identify Women with Near-Miss Maternal Morbidity

Abstract Objective To validate a five-factor scoring system that identifies parturients who experience near-miss morbidity. Study Design and Setting This study was conducted in an urban, tertiary care hospital over a 2-year period. A narrative case summary was prepared for women with high potential for significant obstetric morbidity. The summary was then reviewed by three physicians, and the extent of morbidity was assigned based on subjective assessment. The same cases were then scored using the proposed five-factor scoring system previously described by Geller et al. Test characteristics of the scoring system were assessed. Results Eight hundred fifteen cases with a high potential for significant morbidity were identified. Subjective review and the scoring system classified 4.5% and 4.2% as near-miss morbidity, respectively, with the scoring system having a corresponding sensitivity of 81.1% (95% confidence interval 64.8 to 92.0%) and a specificity of 99.5% (95% confidence interval 98.7 to 99.9%). Conclusion The scoring system produced similar results to those obtained at its initial development and demonstrated acceptable sensitivity and specificity for identifying near-miss morbidity.
Efficient Discovery of Approximate Dependencies

Functional dependencies (FDs) and unique column combinations (UCCs) form a valuable ingredient for many data management tasks, such as data cleaning, schema recovery, and query optimization. Because these dependencies are unknown in most scenarios, their automatic discovery has been well researched. However, existing methods mostly discover only exact dependencies, i.e., those without violations. Real-world dependencies, in contrast, are frequently approximate due to data exceptions, ambiguities, or data errors. This relaxation to approximate dependencies renders their discovery an even harder task than the already challenging exact dependency discovery. To this end, we propose the novel and highly efficient algorithm P yro to discover both approximate FDs and approximate UCCs. P yro combines a separate-and-conquer search strategy with sampling-based guidance that quickly detects dependency candidates and verifies them. In our broad experimental evaluation, P yro outperforms existing discovery algorithms by a factor of up to 33, scales to larger datasets, and at the same time requires the least main memory.
A pr 2 01 8 The Web of False Information : Rumors , Fake News , Hoaxes , Clickbait , and Various Other Shenanigans

A new era of Information Warfare has arrived. Various actors, including state-sponsored ones, are weaponizing information on Online Social Networks to run false information campaigns with targeted manipulation of public opinion on specific topics. These false information campaigns can have dire consequences to the public: mutating their opinions and actions, especially with respect to critical world events like major elections. Evidently, the problem of false information on the Web is a crucial one, and needs increased public awareness, as well as immediate attention from law enforcement agencies, public institutions, and in particular, the research community. In this paper, we make a step in this direction by providing a taxonomy of the Web’s false information ecosystem, comprising various types of false information, actors, and their motives. We report a comprehensive overview of existing research on the false information ecosystem by identifying several lines of work: 1) how the public perceives false information; 2) understanding the propagation of false information; 3) detecting and containing false information on the Web; and 4) false information on the political stage. Finally, for each of these lines of work, we report several future research directions that can help us better understand and mitigate the emerging problem of false information dissemination on the Web.
Decision support with text-based emotion recognition: Deep learning for affective computing

Emotions widely affect the decision-making of humans and, hence, affective computing takes emotional states into account with the goal of tailoring decision support to individuals. However, the accurate recognition of emotions within narrative materials presents a challenging undertaking due to the complexity and ambiguity of language. Even though deep learning has evolved as the state-of-the-art in various tasks from text mining, its benefits with regard to affective computing are not yet understood. We thus propose the following innovations: (1) we adapt recurrent neural networks from the field of deep learning to affective computing. (2) We extend these networks for predicting the score of different affective dimensions. (3) We implement transfer learning for pre-training word embeddings. Analyzing the results, we find that deep learning consistently outperforms traditional machine learning with improvements of up to 21% in F1-score when labeling emotions and 6% in forecast errors when rating the intensity of emotions. Altogether, the findings have considerable implications for the use of affective computing in providing decision support.
Generating minimal living systems from non-living materials and increasing their evolutionary abilities

We review lessons learned about evolutionary transitions from a bottom-up construction of minimal life. We use a particular systemic protocell design process as a starting point for exploring two fundamental questions: (i) how may minimal living systems emerge from non-living materials? and (ii) how may minimal living systems support increasingly more evolutionary richness? Under (i), we present what has been accomplished so far and discuss the remaining open challenges and their possible solutions. Under (ii), we present a design principle we have used successfully both for our computational and experimental protocellular investigations, and we conjecture how this design principle can be extended for enhancing the evolutionary potential for a wide range of systems. This article is part of the themed issue ‘The major synthetic evolutionary transitions’.
Understanding Pathways to Usual Source of Care among Asian Americans

Although the prevailing conceptual model for health care access is the Andersen Behavioral Model of Health Service Use, researchers have not evaluated empirically whether model pathways are appropriate for Asian Americans (AAs). Using path analysis with 2009 California Health Interview Survey data, we tested pathways among predisposing, enabling, and need factors and acculturation factors for having a usual source of care (USC) among AA adults. Pathway differences among ethnic subgroups (Chinese, Koreans, and Vietnamese) were also examined. The model adequately predicted USC among AAs. As expected, insurance was the key predictor but higher education levels were associated with lower income and lower income with having a USC. English proficiency also contributed significantly to the AA model. Ethnic subgroup models varied significantly. Findings suggest that the Andersen behavioral model is appropriate for studying USC among AAs though pathways vary by ethnicity. Pathways for education and English proficiency must be better understood.
Mutation Mechanisms of Human Breast Cancer

Cancer is a class of diseases caused by the accumulation of gene mutations. All mutated genes constitute a genetic network for cancer progression. It is very helpful for tumor diagnosis and therapy if we know how many mutated genes are needed for human breast cancer. In this article, we investigate the mutation mechanisms of human breast cancer by modeling the data of surveillance, epidemiology, and end results registry. The data are age-specific incidence rates of breast cancer of females in the United States. We set up stochastic multistage models to estimate the age-specific incidence rates by using several coupled ordinary differential equations derived from the Kolmogorov backward equations. Our results suggest that 2-14 mutations in the genome of breast stem cells are required for normal breast stem cells to become a malignant cell, and 3 gene mutations are most likely to occur in the development of female breast cancer.
Salvianolic Acid Exerts Cardioprotection through Promoting Angiogenesis in Animal Models of Acute Myocardial Infarction: Preclinical Evidence

Radix Salviae miltiorrhizae, danshen root (danshen), is one of the widely used Chinese herbal medicines in clinics, containing rich phenolic compounds. Salvianolic acid is the main active compound responsible for the pharmacologic effects of danshen. Here, we aimed to evaluate the effects of salvianolic acid on cardioprotection through promoting angiogenesis in experimental myocardial infarction. Studies of salvianolic acid in animal models of myocardial infarction were obtained from 6 databases until April 2016. The outcome measures were vascular endothelium growth factor (VEGF), blood vessel density (BVD), and myocardial infarct size. All the data were analyzed using Rev-Man 5.3 software. Ultimately, 14 studies were identified involving 226 animals. The quality score of studies ranged from 3 to 6. The meta-analysis of six studies showed significant effects of salvianolic acid on increasing VEGF expression compared with the control group (P < 0.01). The meta-analysis of the two salvianolic acid A studies and three salvianolic acid B studies showed significantly improving BVD compared with the control group (P < 0.01). The meta-analysis of five studies showed significant effects of salvianolic acid for decreasing myocardial infarct size compared with the control group (P < 0.01). In conclusion, these findings demonstrated that salvianolic acid can exert cardioprotection through promoting angiogenesis in animal models of myocardial infarction.
Controllability of Discrete Time Bilinear Systems in Finite and Infinite Dimensional Spaces

In the first instance, we prove that in a Banach state space of infinite dimensional; discrete bilinear systems are uncontrollable and we examine the control of the projections of the state on finite-dimensional subspaces. Then we generalize finite-dimensional results on near-controllability established by Tie and Cai in [21] and [22]. Finally, we provide illustrative examples.
Decomposition of postural movements in individuals with mild TBI while reaching to intercept a moving virtual target

ABSTRACT The study analyzed postural and arm movement coordinations in patients with traumatic brain injury (TBI) while standing and reaching for a target moving in a 3D virtual environment. Thirteen individuals with mild TBI and 13 height, sex, and age-matched healthy control individuals were involved. While standing in front of the screen, the participants interacted with the projected environment by reaching for virtual targets. Coordination was analyzed as the percentage of reach-to-intercept cycle time during which their movement toward the target was decomposed with 0% indicating simultaneous motion in three planes or 100% indicating motion in one or two planes only. Decomposition was calculated for the postural movements (DIp), arm movements (DIa), and arm-postural coordination (DIa-p). The latter index represented the percentage of reach-to-intercept cycle time during which either the posture or arm moved alone. DIp and DIa-p were larger in the TBI group compared to the control group (p < 0.01). In the TBI group, DIp and DIa-p correlated negatively with postural stability (r = – 0.71 and r = – 0.60; p < 0.01). Results suggest that individuals with TBI decompose postural and arm-postural coordinations during a reach-to-intercept task. This may be either a result of impaired postural control or an effort to compensate for instability. These abnormalities should be taken into consideration while planning physical therapy programs for individuals after brain injury.