Miracle-dz/UniFAR-FTUs huggingface dataset:
The alc-GR System. A Modified alc Gene Switch Designed for Use in Plant Tissue Culture1[w]

The ALCR/alcA (alc) two-component, ethanol-inducible gene expression system provides stringent control of transgene expression in genetically modified plants. ALCR is an ethanol-activated transcription factor that can drive expression from the ALCR-responsive promoter (alcA). However, the alc system has been shown to have constitutive expression when used in plant callus or cell suspension cultures, possibly resulting from endogenous inducer produced in response to lowered oxygen availability. To widen the use of the alc system in plant cell culture conditions, the receptor domain of the rat glucocorticoid receptor (GR) was translationally fused to the C terminus of ALCR to produce ALCR-GR, which forms the basis of a glucocorticoid-inducible system (alc-GR). The alc-GR switch system was tested in tobacco (Nicotiana tabacum) Bright Yellow-2 suspension cells using a constitutively expressed ALCR-GR with four alternative alcA promoter-driven reporter genes: β-glucuronidase, endoplasmic reticulum-targeted green fluorescent protein, haemagglutinin, and green fluorescent protein-tagged Arabidopsis (Arabidopsis thaliana) Arath;CDKA;1 cyclin-dependent kinase. Gene expression was shown to be stringently dependent on the synthetic glucocorticoid dexamethasone and, in cell suspensions, no longer required ethanol for induction. Thus, the alc-GR system allows tight control of alcA-driven genes in cell culture and complements the conventional ethanol switch used in whole plants.
Modifying 5-HT1A Receptor Gene Expression as a New Target for Antidepressant Therapy

Major depression is the most common form of mental illness, and is treated with antidepressant compounds that increase serotonin (5-HT) neurotransmission. Increased 5-HT1A autoreceptor levels in the raphe nuclei act as a “brake” to inhibit the 5-HT system, leading to depression and resistance to antidepressants. Several 5-HT1A receptor agonists (buspirone, flesinoxan, ipsapirone) that preferentially desensitize 5-HT1A autoreceptors have been tested for augmentation of antidepressant drugs with mixed results. One explanation could be the presence of the C(−1019)G 5-HT1A promoter polymorphism that prevents gene repression of the 5-HT1A autoreceptor. Furthermore, down-regulation of 5-HT1A autoreceptor expression, not simply desensitization of receptor signaling, appears to be required to enhance and accelerate antidepressant action. The current review focuses on the transcriptional regulators of 5-HT1A autoreceptor expression, their roles in permitting response to 5-HT1A-targeted treatments and their potential as targets for new antidepressant compounds for treatment-resistant depression.
Brain regional differences in the expansion of a CAG repeat in the spinocerebellar ataxias: Dentatorubral‐pallidoluysian atrophy, machado‐joseph disease, and spinocerebellar ataxia type 1

Three autosomal dominant spinocerebellar ataxias, dentatorubral‐pallidoluysian atrophy (DRPLA), Machado‐Joseph disease (MJD), and spinocerebellar ataxia type 1 (SCA1), are associated with the expansion of a CAG repeat in the respective genes. To investigate the association between CAG repeat expansion and neuropathological findings, we analyzed several brain regions from 9 cases of DRPLA, 3 cases of MJD, and 1 case of SCA1. We found that the expanded alleles were smaller in the cerebellar cortex than in other brain regions, such as the frontal cortex, in these three diseases. The discrepancy in the expanded CAG repeat length between cerebellar cortex and other tissues was most prominent in DRPLA, and especially in cases of adult‐onset DRPLA. A significant correlation was found between the age at onset of DRPLA and the size of the CAG repeat expansion. Cerebella of DRPLA patients were microscopically dissected into three layers, the molecular and granularlayers and the white matter, which were analyzed separately. The lower level of CAG repeat expansion in DRPLA cerebella was representative of CAG repeat expansion in the granule cells. The microdissected samples of the granular layer of the hippocampal formation, which is densely packed with neuronal cells, revealed that the degree of CAG repeat expansion in this layer was similar to that in the cerebellum. These observations suggest that granule cells in the cerebellum and hippocampus have low levels of CAG repeat expansion, and that other types of cells exhibit a higher level of CAG repeat expansion, in spinocerebellar ataxias.
DISTRIBUTION OF HEAVY METALS IN PLANT AND MEDIA SAMPLES FROM A VOLCANIC REGION IN HATAY, TURKEY

There is a volcanic area in Hatay, Turkey with currently limited agricultural activities; however, its ecological prop- erties make it a plausible choice for protected fruit and vegetable production. The different soil properties of the area might be useful for plant growing in the future. In this study, we determined selected plant nutrients and heavy metal concentrations of eight soil and rock types from the region, along with those of ten different species of fruits and vegetables representing the region's flora and agricul- tural activities. We found significant differences in all the micronutrients and heavy metal concentrations among the media samples. Overall, the highest concentrations were recovered from growing media. For example, one medium had the highest concentrations of Cu, Cd and Zn. Similarly, the plant samples had significant differences in micronu- trients and heavy metal concentrations. Almond leaf sam- ples were in the highest mean groups for Mg, Na, Fe, Al and Cr, while cucumber had the highest values for Zn and Ni. The highest Pb levels were recovered from uncultivated olive. Comparisons of our results to those of others in the related literature indicated that only two of our results were above the accepted levels: the almond Fe and holy oak B concentrations. In conclusion, our samples from the vol- canic area in Hatay were not dangerously contaminated with heavy metals, and utilization of this area for agricultural purposes poses no apparent threat.
E-Commerce Websites: a Qualitative Evaluation

E-commerce is considered an excellent alternative for companies to reach new customers. However, many e-commerce websites have a short life because they don’t meet the minimal software quality requirements. To help the development of quality e-commerce websites, this work identifies and ranks the main quality attributes to this application domain. The survey of the attributes was based on the specialized literature and on the analysis of significant websites.
High-efficiency protection solution for off-chip memory in embedded systems

This paper proposes a complete hardware solution for embedded systems that fully protects off-chip memory. Our security core is based on one-time pad (OTP) encryption and a CRC32 integrity check module. These modules safeguard external memories for embedded processors against a series of well-known attacks, including replay attacks, spoofing attacks and relocation attacks. The implementation limits memory space overhead to about 18.75% and reduces memory latency from 14 cycles for a alternate approach to 3 clock cycles. A FPGA-based implementation of the security core has been completed to gauge the security overhead and to compare our approach with existing solutions.
A Study on Multi-Attribute Database Indexing on Cloud System 1

Recent years, the Cloud computing technologies have become more and more important for many existing database applications. The Cloud platform provides an ease to use interface between providers and users, allow providers to develop and provide software and databases for users over locations. Currently, there are many Cloud platform providers support large-scale database services. However, most of these Cloud platform architectures only support simple keywordbased queries and can’t response complex query efficiently due to lack of efficient in multi-attribute index techniques. Existing Cloud platform providers seek to improve performance of indexing techniques for complex queries. In this paper, we evaluate the existing multi-attribute indexing structures for Cloud platform. We conclude our experimental results to suggest the more efficient and scalable multi-attribute index structure for Cloud platform. Index Terms — Cloud computing, multi-attribute index,
Paragraph text reading using a pixelized prosthetic vision simulator: parameter dependence and task learning in free-viewing conditions.

PURPOSE To investigate the feasibility of adequate reading by recipients of future prosthetic visual implants through simulation in sighted observers. METHODS Four normally sighted subjects used a video headset to view short-story segments at a sixth grade reading level, presented in 6- to 11-word paragraphs through a pixelizing grid defined by five parameters (dot size, grid size, dot spacing, random dropout percentage, and gray-scale resolution). Grid parameters were varied individually, and four character sizes and two contrast levels were used. RESULTS Reading speeds of 30 to 60 words per minute without errors were recorded for some parameter combinations. In general, reading accuracy and speed were influenced by all parameters. Reading accuracy exceeded 90% if the following conditions were met: At least 3 dots/charwidth were presented, and dropout did not exceed 50%. Reading speed deteriorated below 20 words per minute if accuracy fell below 90% and at low contrast if the grid spanned less than two characters. CONCLUSIONS It is uncertain whether and to what extent retinal reorganization may limit the perception of multiple phosphenes by blind prosthesis recipients. If distinct phosphenes can be perceived, these results suggest that a 3 x 3-mm2 prosthesis with 16 x 16 electrodes should allow paragraph reading. The effects of stabilizing the dot grid on the retina must be investigated further.
A measurement study on the impact of routing events on end-to-end internet path performance

Extensive measurement studies have shown that end-to-end Internet path performance degradation is correlated with routing dynamics. However, the root cause of the correlation between routing dynamics and such performance degradation is poorly understood. In particular, how do routing changes result in degraded end-to-end path performance in the first place? How do factors such as topological properties, routing policies, and iBGP configurations affect the extent to which such routing events can cause performance degradation? Answers to these questions are critical for improving network performance.In this paper, we conduct extensive measurement that involves both controlled routing updates through two tier-1 ISPs and active probes of a diverse set of end-to-end paths on the Internet. We find that routing changes contribute to end-to-end packet loss significantly. Specifically, we study failover events in which a link failure leads to a routing change and recovery events in which a link repair causes a routing change. In both cases, it is possible to experience data plane performance degradation in terms of increased long loss burst as well as forwarding loops. Furthermore, we find that common routing policies and iBGP configurations of ISPs can directly affect the end-to-end path performance during routing changes. Our work provides new insights into potential measures that network operators can undertake to enhance network performance.
Computational vulnerability analysis for information survivability

The Infrastructure of modern society is controlled by software systems. These systems are vulnerable to attacks; several such attacks, launched by "recreation hackers" have already led to severe disruption. However, a concerted and planned attack whose goal is to reap harm could lead to catastrophic results (for example, by disabling the computers that control the electrical power grid for a sustained period of time). The survivability of such information systems in the face of attacks is therefore an area of extreme importance to society.This paper is set in the context of self-adaptive survivable systems: software that judges the trustworthiness of the computational resources in its environment and which chooses how to achieve its goals in light of this trust model. Each self-adaptive survivable system detects and diagnoses compromises of its resources, taking whatever actions are necessary to recover from attack. In addition, a long-term monitoring system collects evidence from intrusion detectors, firewalls and all the self-adaptive components, building a composite trust-model used by each component. Self-adaptive surviable systems contain models of their intended behavior, models of the required computational resources, models of the ways in which these resources may be compromised and finally, models of the ways in which a system may be attacked and how such attacks can lead to compromises of the computational resources.In this paper we focus on Computational Vulnerability Analysis: a system that, given a description of a computational environment, deduces all of the attacks that are possible. In particular its goal is to develop multi-stage attack models in which the compromise of one resource is used to facilitate the compromise of other, more valuable resources. Although our ultimate aim is to use these models online as part of a self-adaptive system, there are other offline uses as well which we are deploying first to help system administrators assess the vulnerabilitities of their computing environment.
Bipolar Disorder for the Primary Care Physician

• Objective: To review the diagnosis and treatment of bipolar disorder. • Methods: Qualitative assessment of the literature. • Results: Bipolar disorder is a major cause of morbidity and mortality. Due to the incidence and nature of the disorder, it is important to screen any patient presenting with depression for a history of mood swings and manic symptoms. The presence of psychosis or a family history of bipolar disorder can be helpful. First-line treatment for a depressive episode includes lithium or lamotrigine. The addition of an antipsychotic or an antidepressant may be necessary or useful in some cases. Evidence supports avoiding monotherapy with an antidepressant as this is likely to induce mania or rapid cycling. Treatment of severe manic or mixed episodes includes lithium or valproic acid with an atypical antipsychotic. Mild to moderate episodes may be managed with lithium, valproic acid, or an antipsychotic alone. Valproate may be more effective than lithium for some variants. An atypical antipsychotic may be the best choice for management of mild to moderate episodes in primary care settings. • Conclusion: Appropriate diagnosis and treatment of bipolar disorder will help improve outcomes for patients with this potentially devastating but often manageable illness.
Satellite microwave observations of polar lows

Acknowledgements . iii List of Tables . vii List of Figures . viii
The new frontier of communications research: smart grid and smart metering

This paper discusses some of the challenges and opportunities of communications research in the area of smart grids and smart metering. It is clear that the communications research community has been actively seeking the 'next big thing' after interests in recent hot topics such as cognitive radio, cooperative communications, and MIMO have more or less peaked. We argue that the new initiative on smart grid worldwide provides an ideal opportunity for communication and networking researchers to apply various existing technologies as well as inventing new ones in this exciting area.
The Demand for Disaster Microinsurance for Small Businesses in Urban Slums: The Results of Surveys in Three Indian Cities

Background: Small informal businesses make up the core markets for many poor urban communities, providing essential goods, services, and livelihoods. Many of these communities and businesses exist in hazardous locations. In most cases, these business owners do not have access to proper coping mechanisms including risk transfer and lack resilience to shocks. Access to risk-transfer in the form of insurance for these small businesses is extremely limited. This demand survey is the first phase of an intervention to test disaster microinsurance for these businesses. Previous research has examined the demand for and value of microinsurance to protect poor households but not micro- and medium-sized informal urban businesses. Objective: This study investigates knowledge about and demand for microinsurance among small informal business owners in three different cities of India. Methods: Survey of all informal business owners (n=4919) identified through purposive sampling of the most vulnerable in three proposed study sites: Guwahati in Assam (n=1622), Puri in Odisha (n=1551) and Cuddalore in Tamil Nadu (n=1746). Results: Our findings reflect that while small business owners largely did not know about disaster microinsurance, after describing it, a vast majority wanted to subscribe to such a program. Without it, they often rely on personal savings, forgo basic necessities, or take out costly loans that trap them in debt to cope with disasters. Discussion: This research supports the need for more experiments on actual adoption patterns, feasibility studies, and innovative trial programs by governments, non-governmental organizations, and insurance providers.
Combined model-based 3D object recognition

This paper presents a combined model-based 3D object recognition method motivated by the robust properties of human vision. The human visual system (HVS) is very efficient and robust in identifying and grabbing objects, in part because of its properties of visual attention, contrast mechanism, feature binding, multiresolution and part-based representation. In addition, the HVS combines bottom-up and top-down information effectively using combined model representation. We propose a method for integrating these aspects under a Monte Carlo method. In this scheme, object recognition is regarded as a parameter optimization problem. The bottom-up process initializes parameters, and the top-down process optimizes them. Experimental results show that the proposed recognition model is feasible for 3D object identification and pose estimation.
The Novel Chk1 Inhibitor MK-8776 Sensitizes Human Leukemia Cells to HDAC Inhibitors by Targeting the Intra-S Checkpoint and DNA Replication and Repair

Interactions between the novel Chk1 inhibitor MK-8776 and the histone deacetylase (HDAC) inhibitor (HDACI) vorinostat were examined in human leukemia cells harboring wild-type (wt) or deficient p53. MK-8776 synergistically potentiated vorinostat-mediated apoptosis in various p53-wt or -deficient leukemia cell lines, whereas p53 knockdown by short hairpin RNA (shRNA) sensitized p53-wt cells to lethality of this regimen. Leukemia cell lines carrying FLT3-ITD were also sensitive to the MK-8776/vorinostat regimen. Synergistic interactions were associated with inhibition of Chk1 activity, interference with the intra-S-phase checkpoint, disruption of DNA replication, and downregulation of proteins involved in DNA replication (e.g., Cdt1) and repair (e.g., CtIP and BRCA1), resulting in sharp increases in DNA damage, reflected by enhanced γ-H2A.X formation, and apoptosis. Moreover, leukemia cells expressing kinase-dead Chk1 (D130A) or Chk1 shRNA were significantly more sensitive to HDACIs compared with their wt counterparts and displayed downregulation of CtIP and BRCA1 phosphorylation following HDACI exposure. Finally, the MK-8776/vorinostat regimen was active in primary acute myelogenous leukemia (AML) blasts, particularly against the CD34+/CD38−/CD123+ population enriched for leukemia-initiating cells. In contrast, identical regimens were relatively sparing toward normal cord blood CD34+ cells. Together, these findings indicate that the novel Chk1 inhibitor MK-8776 markedly potentiates HDACI lethality in leukemia cells displaying various genetic backgrounds through mechanisms involving disruption of the intra-S checkpoint, DNA replication, and DNA repair. They also argue that leukemic cells, including those bearing oncogenic mutations associated with poor prognosis, for example, p53 deletion/mutation or FLT3-ITD, may also be susceptible to this strategy. Mol Cancer Ther; 12(6); 878–89. ©2013 AACR.
Rhizobia and their bio-partners as novel drivers for functional remediation in contaminated soils

Environmental pollutants have received considerable attention due to their serious effects on human health. There are physical, chemical, and biological means to remediate pollution; among them, bioremediation has become increasingly popular. The nitrogen-fixing rhizobia are widely distributed in the soil and root ecosystems and can increase legume growth and production by supplying nitrogen, resulting in the reduced need for fertilizer applications. Rhizobia also possess the biochemical and ecological capacity to degrade organic pollutants and are resistant to heavy metals, making them useful for rehabilitating contaminated soils. Moreover, rhizobia stimulate the survival and action of other biodegrading bacteria, thereby lowering the concentration of pollutants. The synergistic action of multiple rhizobial strains enhances both plant growth and the availability of pollutants ranging from heavy metals to persistent organic pollutants. Because phytoremediation has some restrictions, the beneficial interaction between plants and rhizobia provides a promising option for remediation. This review describes recent advances in the exploitation of rhizobia for the rehabilitation of contaminated soil and the biochemical and molecular mechanisms involved, thereby promoting further development of this novel bioremediation strategy into a widely accepted technique.
Long‐range Dependence: Revisiting Aggregation with Wavelets

The aggregation procedure is a natural way to analyse signals which exhibit long‐range‐dependent features and has been used as a basis for estimation of the Hurst parameter, H. In this paper it is shown how aggregation can be naturally rephrased within the wavelet transform framework, being directly related to approximations of the signal in the sense of a Haar multiresolution analysis. A natural wavelet‐based generalization to traditional aggregation is then proposed: ‘a‐aggregation’. It is shown that a‐aggregation cannot lead to good estimators of H, and so a new kind of aggregation, ‘d‐aggregation’, is defined, which is related to the details rather than the approximations of a multiresolution analysis. An estimator of H based on d‐aggregation has excellent statistical and computational properties, whilst preserving the spirit of aggregation. The estimator is applied to telecommunications network data.
Distributional semantics and unsupervised clustering for sensor relevancy prediction

The logging of Activities of Daily Living (ADLs) is becoming increasingly popular mainly thanks to wearable devices. Currently, most sensors used for ADLs logging are queried and filtered mainly by location and time. However, in an Internet of Things future, a query will return a large amount of sensor data. Therefore, existing approaches will not be feasible because of resource constraints and performance issues. Hence more fine-grained queries will be necessary. We propose to filter on the likelihood that a sensor is relevant for the currently sensed activity. Our aim is to improve system efficiency by reducing the amount of data to query, store and process by identifying which sensors are relevant for different activities during the ADLs logging by relying on Distributional Semantics over public text corpora and unsupervised hierarchical clustering. We have evaluated our system over a public dataset for activity recognition and compared our clusters of sensors with the sensors involved in the logging of manually-annotated activities. Our results show an average precision of 89% and an overall accuracy of 69%, thus outperforming the state of the art by 5% and 32% respectively. To support the uptake of our approach and to allow replication of our experiments, a Web service has been developed and open sourced.