Miracle-dz/UniFAR-FTUs huggingface dataset:
Structures of broken ties: exploring unfollow behavior on twitter

This study investigates unfollow behavior in Twitter, i.e. people removing others from their Twitter following lists. Considering the interdependency and dynamics of unfollow decisions, we use actor-oriented modeling (SIENA) to examine the impacts of reciprocity, status, embeddedness, homophily, and informativeness on tie dissolution. Focusing on ordinary users in tightly-knitted user groups, the results show that relational properties play key roles in the emergence of unfollow behavior: mutual following relations and common followees reduce the likelihood of unfollowing. And unfollow tends to be reciprocal: when a user is unfollowed by someone, he or she will unfollow back. However, there is no evidence of the impacts of homophily based on common interests and informativeness of interactions. The findings suggest that Twitter has many heterogeneous user groups and relational and informational factors may not be applicable universally.
Advances in Brief NKX-3 . 1 Interacts with Prostate-derived Ets Factor and Regulates the Activity of the PSA Promoter 1

The NKX-3.1 homeobox gene maps to human chromosome 8p21, a region that undergoes frequent loss of heterozygosity in prostate tumors. Loss of Nkx-3.1 function in mice leads to epithelial overgrowth. To further elucidate the molecular basis of NKX-3.1 function, a genetic screen for proteins that interact with NKX-3.1 was performed. Prostate-derived Ets factor (PDEF) was identified as a potential partner of NKX-3.1. Coimmunoprecipitation analyses demonstrated that NKX-3.1 and PDEF are physically associated in prostate epithelial cells. Cotransfection analyses demonstrated that NKX-3.1 can abolish the transcriptional activation function of PDEF on the prostate-specific antigen (PSA) promoter. These data identify PSA as a target gene for NKX-3.1 and provide new insights into the function of this candidate tumor suppressor.
On Hofmann's bilinear estimate

Using the framework of a previous article joint with Axelsson and McIntosh, we extend to systems two results of S. Hofmann for real symmetric equations and their perturbations going back to a work of B. Dahlberg for Laplace's equation on Lipschitz domains, The first one is a certain bilinear estimate for a class of weak solutions and the second is a criterion which allows to identify the domain of the generator of the semi-group yielding such solutions.
The economics of information security investment

This article presents an economic model that determines the optimal amount to invest to protect a given set of information. The model takes into account the vulnerability of the information to a security breach and the potential loss should such a breach occur. It is shown that for a given potential loss, a firm should not necessarily focus its investments on information sets with the highest vulnerability. Since extremely vulnerable information sets may be inordinately expensive to protect, a firm may be better off concentrating its efforts on information sets with midrange vulnerabilities. The analysis further suggests that to maximize the expected benefit from investment to protect information, a firm should spend only a small fraction of the expected loss due to a security breach.
A REVIEW OF DIGITAL BREAST TOMOSYNTHESIS

While the principle of tomosynthesis has been known for almost a century, digital breast tomosynthesis (DBT) is a novel technology that owes its rapid development to the introduction of full-field digital mammography (FFDM). This review article covers the principles and design considerations of DBT, including system geometry. Further, the article provides an in-depth introduction to DBT dosimetry, and discusses recent studies on several breast imaging applications, which highlight the potential for clinical performance improvements due to DBT. Keywords— Tomosynthesis, breast imaging, mammography,
Characterization of the In Vivo Antiplatelet Activity of the Antihypertensive Agent Losartan

Objective: The purpose of this study is to investigate the potential in vivo antiplatelet and thromboprotective properties of the antihypertensive drug losartan in mice. Methods: Aggregometry studies were performed on platelets obtained from mice administered losartan for 5 days, via tail vein to examine the ex vivo effects (dose dependence) of this agent and to select an appropriate dose for the in vivo studies. Next, the tail bleeding time test and the time for occlusion in a carotid artery injury thrombosis model (ferric chloride) were also performed to assess the in vivo effects of losartan treatment. Results: These data indicate that the antihypertensive agent losartan exerts dose-dependent inhibition of the thromboxane receptor-mediated (U46619/agonist)-induced platelet aggregation (ex vivo), whereas it produced no detectable effects on aggregation triggered by adenosine diphosphate or the thrombin receptor activating peptide 4. Findings from the in vivo analysis revealed that tail bleeding time of losartan-treated mice was not different from vehicle-treated mice. On the other hand, in the carotid artery injury thrombosis model, it was found that the losartan-treated mice had significantly longer time for occlusion in comparison with those treated with vehicle control. Conclusions: These findings provide evidence that administration of the antihypertensive drug losartan into live mice produces thromboxane A2 receptor–specific antiplatelet effects. Furthermore, interestingly, this antiplatelet activity appears to translate into thromboprotective properties, without resulting in a bleeding phenotype. Consequently, aside from its potential use as an antithrombotic agent, losartan’s chemistry may provide a “blueprint” for designing or repurposing novel derivatives which may have the potential to serve as an antiplatelet and thromboprotective agents but are deprived of the usually concomitant bleeding adverse effects.
Localized recruitment and activation of RhoA underlies dendritic spine morphology in a glutamate receptor–dependent manner

Actin is the major cytoskeletal source of dendritic spines, which are highly specialized protuberances on the neuronal surface where excitatory synaptic transmission occurs (Harris, K.M., and S.B. Kater. 1994. Annu. Rev. Neurosci. 17:341–371; Yuste, R., and D.W. Tank. 1996. Neuron. 16:701–716). Stimulation of excitatory synapses induces changes in spine shape via localized rearrangements of the actin cytoskeleton (Matus, A. 2000. Science. 290:754–758; Nagerl, U.V., N. Eberhorn, S.B. Cambridge, and T. Bonhoeffer. 2004. Neuron. 44:759–767). However, what remains elusive are the precise molecular mechanisms by which different neurotransmitter receptors forward information to the underlying actin cytoskeleton. We show that in cultured hippocampal neurons as well as in whole brain synaptosomal fractions, RhoA associates with glutamate receptors (GluRs) at the spine plasma membrane. Activation of ionotropic GluRs leads to the detachment of RhoA from these receptors and its recruitment to metabotropic GluRs. Concomitantly, this triggers a local reduction of RhoA activity, which, in turn, inactivates downstream kinase RhoA-specific kinase, resulting in restricted actin instability and dendritic spine collapse. These data provide a direct mechanistic link between neurotransmitter receptor activity and the changes in spine shape that are thought to play a crucial role in synaptic strength.
The role of the kidney in the etiology of renal hyperlipemia.

Progressive and continuous increases in plasma lipides after bilateral nephrectomy or ligation of the ureters have been demonstrated in cats (1), rabbits (2), dogs (3, 4) and monkeys (4). These findings led to the hypothesis that the kidney exerts a regulatory influence on plasma lipides (3). The observation that renal venous blood from normal rabbits counteracted the hyperlipemia following nephrectomy supported this concept (5). Peripheral venous or renal blood obtained from rabbits with damaged tubules did not counteract the lipemia, and it was therefore concluded that a lipide regulating factor was produced by normal tubular cells (5). Jimenez Diaz and CastroMendoza (6, 7) reported that a renal extract inhibited the hyperlipemia after bilateral nephrectomy or ureteral ligation in dogs. Svanborg (2), and Dimond, Marques Santos, Mundy, and Calderwood (8) failed to confirm these observations. Since the lipide alterations which occur in the nephrotic syndrome are associated with an increased incidence of atherosclerosis (9) and renal fatty degeneration, an explanation of the cause of hyperlipemia would be of value. The development of the intermittent peritoneal dialysis technique (10) as an effective means of maintaining excretory function provided an opportunity to evaluate further the role of the kidney in the etiology of renal hyperlipemia.
Bits through queues

Considers the following simple communication channel model: an error-free bit pipe leading to a buffer modeled by a single-server queue whose "packets" or "customers" are single bits. If the service rate is /spl mu/ bits/sec, common wisdom would indicate that the Shannon capacity of this communication link is /spl mu/ bits/sec. As we show in this paper, that intuition is wrong: the answer is actually higher than /spl mu/ bits/sec. How could we possibly transmit information at a rate faster than the service rate? After all, overdriving the queue with an arrival rate higher than p will not do, as the queue will become unstable and its output rate will not be higher than /spl mu/. The capacity is higher than /spl mu/ because information can be encoded into the arrival epochs. A simpler and more fundamental problem, namely the Shannon capacity of the single-server queue, is also considered. <<ETX>>
Jcb: Article Introduction

Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate. Part of the Oncology Commons This Article is brought to you for free and open access by the Jefferson Digital Commons. The Jefferson Digital Commons is a service of Thomas Jefferson University's Center for Teaching and Learning (CTL). The Commons is a showcase for Jefferson books and journals, peer-reviewed scholarly publications, unique historical collections from the University archives, and teaching tools. The Jefferson Digital Commons allows researchers and interested readers anywhere in the world to learn about and keep up to date with Jefferson scholarship.Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate.
From Frequency to Meaning: Vector Space Models of Semantics

Computers understand very little of the meaning of human language. This profoundly limits our ability to give instructions to computers, the ability of computers to explain their actions to us, and the ability of computers to analyse and process text. Vector space models (VSMs) of semantics are beginning to address these limits. This paper surveys the use of VSMs for semantic processing of text. We organize the literature on VSMs according to the structure of the matrix in a VSM. There are currently three broad classes of VSMs, based on term-document, word-context, and pair-pattern matrices, yielding three classes of applications. We survey a broad range of applications in these three categories and we take a detailed look at a specific open source project in each category. Our goal in this survey is to show the breadth of applications of VSMs for semantics, to provide a new perspective on VSMs for those who are already familiar with the area, and to provide pointers into the literature for those who are less familiar with the field.
From movable type to moving type - evolution in technological mediated typography

Written texts are more and more consumed in a multitude of different environments and media: on screens or device displays, at home, in offices or in public spaces, in quiet, private places or in noisy surroundings; mediated by new technologies such as mobile phones or personal digital assistants. This paper traces the development of typography from Gutenberg’s invention of movable type to today’s dynamic moving texts. It proposes and explores the argument that the typographic landscape we engage with is experienced rather than read. From the Crystal Goblet approach in typography to the often playful interactions with type in new media, a ‘new reader’ emerges, who is at the same time reader in a classic sense but also viewer of a typographic performance and and finally user or even creator (see Apple’s ‘LiveType’ for instance) of technological mediated typography.
Modeling the Emergence of Circadian Rhythms in a Clock Neuron Network

Circadian rhythms in pacemaker cells persist for weeks in constant darkness, while in other types of cells the molecular oscillations that underlie circadian rhythms damp rapidly under the same conditions. Although much progress has been made in understanding the biochemical and cellular basis of circadian rhythms, the mechanisms leading to damped or self-sustained oscillations remain largely unknown. There exist many mathematical models that reproduce the circadian rhythms in the case of a single cell of the Drosophila fly. However, not much is known about the mechanisms leading to coherent circadian oscillation in clock neuron networks. In this work we have implemented a model for a network of interacting clock neurons to describe the emergence (or damping) of circadian rhythms in Drosophila fly, in the absence of zeitgebers. Our model consists of an array of pacemakers that interact through the modulation of some parameters by a network feedback. The individual pacemakers are described by a well-known biochemical model for circadian oscillation, to which we have added degradation of PER protein by light and multiplicative noise. The network feedback is the PER protein level averaged over the whole network. In particular, we have investigated the effect of modulation of the parameters associated with (i) the control of net entrance of PER into the nucleus and (ii) the non-photic degradation of PER. Our results indicate that the modulation of PER entrance into the nucleus allows the synchronization of clock neurons, leading to coherent circadian oscillations under constant dark condition. On the other hand, the modulation of non-photic degradation cannot reset the phases of individual clocks subjected to intrinsic biochemical noise.
CANS: Composable, Adaptive Network Services Infrastructure

Ubiquitous access to sophisticated internet services from diverse end devices across heterogeneous networks requires the injection of additional functionality into the network to handle protocol conversion, data transcoding, and in general bridge disparate network portions. Several researchers have proposed infrastructures for injecting such functionality; however, many challenges remain before these can be widely deployed. CANS is an application-level infrastructure for injecting application-specific components into the network that focuses on three such challenges: (a) efficient and dynamic composition of individual components; (b) distributed adaptation of injected components in response to system conditions; and (c) support for legacy applications and services. The CANS network view comprises applications, stateful services, and data paths built from mobile soft-state objects called drivers. Both services and data paths can be dynamically created and reconfigured: a planning and event propagation model assists in distributed adaptation, and a flexible type-based composition model dictates how new services and drivers are integrated with existing components. Legacy components plug into CANS using an interception layer that virtualizes network bindings and a delegation model. This paper describes the CANS architecture, and a case study involving a shrink-wrapped client application in a dynamically changing network environment where CANS improves overall user experience.
Screening Strategies for Thyroid Disorders in the First and Second Trimester of Pregnancy in China

Background Thyroid dysfunction during pregnancy is associated with multiple adverse outcomes, but whether all women should be screened for thyroid disorders during pregnancy remains controversial. Objective To evaluate the effectiveness of the targeted high risk case-finding approach for identifying women with thyroid dysfunction during the first and second trimesters of pregnancy. Methods Levels of thyroid stimulating hormone (TSH), free thyroxine (FT4), and thyroid peroxidase antibodies (TPOAb) were measured in 3882 Chinese women during the first and second trimester of pregnancy. All tested women were divided into the high risk or non-high risk groups, based on their history, findings from physical examination, or other clinical features suggestive of a thyroid disorder. Diagnosis of thyroid disorders was made according to the standard trimester-specific reference intervals. The prevalence of thyroid disorders in each group was determined, and the feasibility of a screening approach focusing exclusively on high risk women was evaluated to estimate the ability of finding women with thyroid dysfunction. Results The prevalence of overt hypothyroidism or hyperthyroidism in the high risk group was higher than in the non-high risk group during the first trimester (0.8% vs 0, χ2 = 7.10, p = 0.008; 1.6% vs 0.2%, χ2 = 7.02, p = 0.008, respectively). The prevalence of hypothyroxinemia or TPOAb positivity was significantly higher in the high risk group than in the non-high risk group during the second trimester (1.3% vs 0.5%, χ2 = 4.49, p = 0.034; 11.6% vs 8.4%, χ2 = 6.396, p = 0.011, respectively). The total prevalence of hypothyroidism or hyperthyroidism and the prevalence of subclinical hypothyroidism or hyperthyroidism were not statistically different between the high risk and non-high risk groups, for either the first or second trimester. Conclusion The high risk screening strategy failed to detect the majority of pregnant women with thyroid disorders. Therefore, we recommend universal screening of sTSH, FT4, and TPOAb during the first trimester and second trimester of pregnancy.
Role of phenolic compounds in peptic ulcer: An overview

Peptic ulcer is the most common gastrointestinal tract (GIT) disorder in clinical practice, which affects approximately 5-10% of the people during their life. The use of herbal drugs for the prevention and treatment of various diseases is constantly developing throughout the world. This is particularly true with regard to phenolic compounds that probably constitute the largest group of plants secondary metabolites. Phenolic compounds have attracted special attention due to their health-promoting characteristics. In the past ten years a large number of the studies have been carried out on the effects of phenolic compounds on human health. Many studies have been carried out that strongly support the contribution of polyphenols to the prevention of cardiovascular diseases, cancer, osteoporosis, neurodegenerative diseases, and diabetes mellitus, and suggest a role in the prevention of peptic ulcer. Polyphenols display a number of pharmacological properties in the GIT area, acting as antisecretory, cytoprotective, and antioxidant agents. The antioxidant properties of phenolic compounds have been widely studied, but it has become clear that their mechanisms of action go beyond the modulation of oxidative stress. Various polyphenolic compounds have been reported for their anti-ulcerogenic activity with a good level of gastric protection. Besides their action as gastroprotective, these phenolic compounds can be an alternative for the treatment of gastric ulcers. Therefore, considering the important role of polyphenolic compounds in the prevention or reduction of gastric lesions induced by different ulcerogenic agents, in this review, we have summarized the literature on some potent antiulcer plants, such as, Oroxylum indicum, Zingiber officinale, Olea europaea L. , Foeniculum vulgare, Alchornea glandulosa, Tephrosia purpurea, and so on, containing phenolic compounds, namely, baicalein, cinnamic acid, oleuropein, rutin, quercetin, and tephrosin, respectively, as active constituents.
Identification of Linear Climate Models from the CMIP3 Multimodel Ensemble

Abstract In this paper, we investigate an ensemble of atmosphere–ocean general circulation models (AOGCMs) participating in phase 3 of the Coupled Model Intercomparison Project (CMIP3), and whose dynamic behavior is emulated by the reduced-complexity climate model MAGICC6. Using a superimposed impulse in solar radiative forcing for the purposes of system identification, we identify 12 AOGCMs in the CMIP3 ensemble for which low-order linear, time-invariant (LTI) models are able to very closely approximate MAGICC6 surface temperature projections under each of the four greenhouse gas (GHG) emission scenarios known as the Representative Concentration Pathways (RCPs) in the IPCC Fifth Assessment Report (AR5), even when extended to centennial timescales. The linear climate models identified in this paper are suitable for the analysis of feedback-based approaches to mitigation aimed at stabilizing global-mean surface temperature, and will inform future quantitative assessment of closed-loop approaches to geoengineering of the climate based on solar radiation management (SRM).
Towards Activity Databases: Using Sensors and Statistical Models to Summarize People's Lives

Automated reasoning about human behavior is a central goal of artificial intelligence. In order to engage and intervene in a meaningful way, an intelligent system must be able to understand what humans are doing, their goals and intentions. Furthermore, as social animals, people’s interactions with each other underlie many aspects of their lives: how they learn, how they work, how they play and how they affect the broader community. Understanding people’s interactions and their social networks will play an important role in designing technology and applications that are “socially-aware”. This paper introduces some of the current approaches in activity recognition which use a variety of different sensors to collect data about users’ activities, and probabilistic models and relational information that are used to transform the raw sensor data into higher-level descriptions of people’s behaviors and interactions. The end result of these methods is a richly structured dataset describing people’s daily patterns of activities and their evolving social networks. The potential applications of such datasets include mapping patterns of information-flow within an organization, predicting the spread of disease within a community, monitoring the health and activity-levels of elderly patients as well as healthy adults, and allowing “smart environments” to respond proactively to the needs and intentions of their users.