Miracle-dz/UniFAR-FTUs huggingface dataset:
Middle East Respiratory Coronavirus Accessory Protein 4a Inhibits PKR-Mediated Antiviral Stress Responses

Middle East respiratory syndrome coronavirus (MERS-CoV) causes severe respiratory infections that can be life-threatening. To establish an infection and spread, MERS-CoV, like most other viruses, must navigate through an intricate network of antiviral host responses. Besides the well-known type I interferon (IFN-α/β) response, the protein kinase R (PKR)-mediated stress response is being recognized as an important innate response pathway. Upon detecting viral dsRNA, PKR phosphorylates eIF2α, leading to the inhibition of cellular and viral translation and the formation of stress granules (SGs), which are increasingly recognized as platforms for antiviral signaling pathways. It is unknown whether cellular infection by MERS-CoV activates the stress response pathway or whether the virus has evolved strategies to suppress this infection-limiting pathway. Here, we show that cellular infection with MERS-CoV does not lead to the formation of SGs. By transiently expressing the MERS-CoV accessory proteins individually, we identified a role of protein 4a (p4a) in preventing activation of the stress response pathway. Expression of MERS-CoV p4a impeded dsRNA-mediated PKR activation, thereby rescuing translation inhibition and preventing SG formation. In contrast, p4a failed to suppress stress response pathway activation that is independent of PKR and dsRNA. MERS-CoV p4a is a dsRNA binding protein. Mutation of the dsRNA binding motif in p4a disrupted its PKR antagonistic activity. By inserting p4a in a picornavirus lacking its natural PKR antagonist, we showed that p4a exerts PKR antagonistic activity also under infection conditions. However, a recombinant MERS-CoV deficient in p4a expression still suppressed SG formation, indicating the expression of at least one other stress response antagonist. This virus also suppressed the dsRNA-independent stress response pathway. Thus, MERS-CoV interferes with antiviral stress responses using at least two different mechanisms, with p4a suppressing the PKR-dependent stress response pathway, probably by sequestering dsRNA. MERS-CoV p4a represents the first coronavirus stress response antagonist described.
Urachal neoplasia: a case report

Diseases of urachal remnants are uncommon and generally located on the junction of the urachal remnant with the bladder dome. In most cases such diseases correspond to mucinous adenocarcinomas and present hematuria as their most common clinical finding. The authors report the case of a 62-year-old female patient undergoing follow-up due to macroscopic hematuria for three years. Ultrasonography and computed tomography findings are described.
Lightweight privacy for smart metering data by adding noise

With a Smart Metering infrastructure, there are many motivations for power providers to collect high-resolution data of energy usage from consumers. However, this collection implies very detailed information about the energy consumption of consumers being monitored. Consequently, a serious issue needs to be addressed: how to preserve the privacy of consumers but making the provision of certain services still possible? Clearly, this is a tradeoff between privacy and utility. There are approaches for preserving privacy in various ways, but many of them affect the data usefulness or are computationally expensive. In this paper, we propose and evaluate a lightweight approach for privacy and utility based on the addition of noise. Furthermore, using real consumers' data, we discuss the influence of the technique in various Smart Grid scenarios. Finally, we also design and evaluate possible attacks to our solution.
Using end-to-end data encryption to secure SIP device configuration

Security between the endpoints is an important requirement for network transmission. One existing solution of End-to-End security is based on the certificate of the third-party enterprise such as the authorization from ISP. And the other methods usually established a virtual private tunnel between the two endpoints. Considering the SIP device configuration basically used tftp protocol to transmit the configuration file, we proposed a free End-to-End security scheme using Application Gateway and data encryption to secure this transmission process. In this paper, Application Gateway used FastCGI programming to protect the HTTP server from attacking. On the other hand, the file encryption approach applied symmetrical encryption to ensure that only the authentic client could share the data from the server.
Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma

Two CT features were developed to quantitatively describe lung adenocarcinomas by scoring tumor shape complexity (feature 1: convexity) and intratumor density variation (feature 2: entropy ratio) in routinely obtained diagnostic CT scans. The developed quantitative features were analyzed in two independent cohorts (cohort 1: n = 61; cohort 2: n = 47) of patients diagnosed with primary lung adenocarcinoma, retrospectively curated to include imaging and clinical data. Preoperative chest CTs were segmented semi-automatically. Segmented tumor regions were further subdivided into core and boundary sub-regions, to quantify intensity variations across the tumor. Reproducibility of the features was evaluated in an independent test-retest dataset of 32 patients. The proposed metrics showed high degree of reproducibility in a repeated experiment (concordance, CCC≥0.897; dynamic range, DR≥0.92). Association with overall survival was evaluated by Cox proportional hazard regression, Kaplan-Meier survival curves, and the log-rank test. Both features were associated with overall survival (convexity: p = 0.008; entropy ratio: p = 0.04) in Cohort 1 but not in Cohort 2 (convexity: p = 0.7; entropy ratio: p = 0.8). In both cohorts, these features were found to be descriptive and demonstrated the link between imaging characteristics and patient survival in lung adenocarcinoma.
Fairer and more accurate, but for whom?

Complex statistical machine learning models are increasingly being used or considered for use in high-stakes decision-making pipelines in domains such as financial services, health care, criminal justice and human services. These models are often investigated as possible improvements over more classical tools such as regression models or human judgement. While the modeling approach may be new, the practice of using some form of risk assessment to inform decisions is not. When determining whether a new model should be adopted, it is therefore essential to be able to compare the proposed model to the existing approach across a range of task-relevant accuracy and fairness metrics. Looking at overall performance metrics, however, may be misleading. Even when two models have comparable overall performance, they may nevertheless disagree in their classifications on a considerable fraction of cases. In this paper we introduce a model comparison framework for automatically identifying subgroups in which the differences between models are most pronounced. Our primary focus is on identifying subgroups where the models differ in terms of fairness-related quantities such as racial or gender disparities. We present experimental results from a recidivism prediction task and a hypothetical lending example.
Limited trophic partitioning among sympatric delphinids off a tropical oceanic atoll

Understanding trophic relationships among marine predators in remote environments is challenging, but it is critical to understand community structure and dynamics. In this study, we used stable isotope analysis of skin biopsies to compare the isotopic, and thus, trophic niches of three sympatric delphinids in the waters surrounding Palmyra Atoll, in the Central Tropical Pacific: the melon-headed whale (Peponocephala electra), Gray’s spinner dolphin (Stenella longirostris longirostris), and the common bottlenose dolphin (Tursiops truncatus). δ15N values suggested that T. truncatus occupied a significantly higher trophic position than the other two species. δ13C values did not significantly differ between the three delphinds, potentially indicating no spatial partitioning in depth or distance from shore in foraging among species. The dietary niche area—determined by isotopic variance among individuals—of T. truncatus was also over 30% smaller than those of the other species taken at the same place, indicating higher population specialization or lower interindividual variation. For P. electra only, there was some support for intraspecific variation in foraging ecology across years, highlighting the need for temporal information in studying dietary niche. Cumulatively, isotopic evidence revealed surprisingly little evidence for trophic niche partitioning in the delphinid community of Palmyra Atoll compared to other studies. However, resource partitioning may happen via other behavioral mechanisms, or prey abundance or availability may be adequate to allow these three species to coexist without any such partitioning. It is also possible that isotopic signatures are inadequate to detect trophic partitioning in this environment, possibly because isotopes of prey are highly variable or insufficiently resolved to allow for differentiation.
The Neuropsychiatric Aspects of Porphyria*

&NA; The neuropsychiatric features of porphyria, together with the neuropathologic processes, are outlined. Ten cases histories, three with the neuropathologic findings at autopsy, are given; of these, six are cases of porphyria and four of porphyria without porphyrinuria. Certain features of the neuropsychiatric symptomatology are emphasized.
Long-Term Fluoxetine Treatment Modulates Cannabinoid Type 1 Receptor-Mediated Inhibition of Adenylyl Cyclase in the Rat Prefrontal Cortex through 5-Hydroxytryptamine1A Receptor-Dependent Mechanisms

Increasing data indicate that brain endocannabinoid system plays a role in the effects of antidepressant medications. Here we examined the effect of in vivo exposure to the selective serotonin uptake inhibitor fluoxetine on cannabinoid type 1 (CB1) receptor density and functionality in the rat prefrontal cortex (PFC) and cerebellum. Long-term treatment with fluoxetine (10 mg/kg/day) enhanced CB1 receptor inhibition of adenylyl cyclase (AC) in the PFC and reduced it in the cerebellum without altering receptor density and agonist stimulation of guanosine 5′-O-(3-[35S]thio) triphosphate ([35S]GTPγS) in either area. Analysis of [35S]GTPγS-labeled Gα subunits allowed for the detection of up-regulated CB1 receptor coupling to Gαi2, Gαi3 in the PFC, and reduced coupling to Gαi3 in the cerebellum of fluoxetine-treated rats. Concomitant administration of the 5-HT1A receptor antagonist N-[2-[4- (2-methoxyphenyl)-1-piperazinyl]ethyl]-N-2-pyridinylcyclohexanecarboxamide maleate (WAY100635; 0.1 mg/kg/day) reduced fluoxetine-induced modulation of CB1 receptor coupling to Gα subunits and AC in the PFC but not in the cerebellum. These results indicate that increased CB1 receptor signaling at the Gαi-AC transduction level is a long-term adaptation induced by fluoxetine in the PFC and point to a role for 5-HT1A receptors in this effect. Basal AC activity, protein kinase A (PKA) catalytic subunit expression, and phospho-cAMP response element-binding protein (pCREB)/CREB ratio were also up-regulated in the PFC of fluoxetine-treated animals, whereas no differences were detected in the cerebellum. It is interesting that long-term Δ9-tetrahydrocannabinol treatment did not elicit antidepressant-like effects or modulated behavioral responses of fluoxetine in an animal model of depression (olfactory bulbectomy). These data suggest that altered signal transduction through CB1 receptors in the PFC may participate in the regulation of the AC-PKA-CREB cascade induced by fluoxetine in this brain area.
Individual Subjective Discounting : Form , Context , Format , and Noise

Debate about the appropriate value for any single social discount rate for public projects stems in part from our lack of knowledge about how individual discount rates vary across people and across choice contexts. It would be valuable to be able to estimate aggregate willingness to pay for a public project as a function of heterogeneous individual discount rates. We could then contemplate a strategy of counterfactual simulation of aggregate willingness to pay for the same project under the systematically lower discount rates that are often argued to be compatible with the normative goal of intergenerational equity. Using a sample of roughly 15,000 choices by over 2000 individuals, we estimate prototype utility-theoretic models concerning private tradeoffs involving money over time that reveal individual-specific discount rates. Statistically significant heterogeneity in discount rates is quantified along many dimensions for an exponential discounting model, a competing hyperbolic model, and a generalized hyperbolic model. We control for experimentally differentiated choice scenarios and elicitation formats, for sociodemographic heterogeneity, and for complex forms of heteroscedasticity. JEL Classifications: D91, H4, C25, C35
Using High-Probability Instructional Sequences and Explicit Instruction to Teach Multiplication Facts

Students with learning disabilities often struggle with math fact fluency and require specialized interventions to recall basic facts. Deficits in math fact fluency can result in later difficulties when learning higher-level mathematical computation, concepts, and problem solving. The response-to-intervention (RTI) and multitiered-systems-of-support (MTSS) approaches for delivering research-based interventions to struggling learners provide educators with the structural frameworks necessary for planning tiered interventions to address skill deficits. Some schools have been implementing RTI/MTSS for years, while others have recently started using these frameworks. Regardless of the number of years delivering tiered interventions, educators benefit from learning about additional interventions they can implement for students requiring tertiary supports (i.e., Tier 3). This article provides readers with a detailed explanation of a Tier 3 multiplication fact fluency intervention that involves the use of high-probability instructional sequences and explicit, systematic, intensive instruction to increase motivation and fluency development.
A low power selector-less crossbar array with complementary resistive-switching memory

In this paper, we propose a selector-less crossbar array structure with complementary resistive memory cell pair for low power consumption. Although the crossbar array structure is useful for taking advantages of emerging resistive memory devices, it is impossible to avoid the sneak current problem. The proposed complementary cell array structure eliminates the pattern dependency of the sneak current systematically. Furthermore, the proposed circuits show better performance, such as large sensing margin, pattern independency and high current efficiency. We also suggest the write scheme which stores data on complementary cell pair at once. The performance of the proposed circuits is estimated with ReRAM Verilog-A modeling and 65nm CMOS process in the cases of various array size and cell on/off ratio.
A visual representation for knowledge structures

Knowledge-based systems often represent their knowledge as a network of interrelated units. Such networks are commonly presented to the user as a diagram of nodes connected by lines. These diagrams have provided a powerful visual metaphor for knowledge representation. However, their complexity can easily become unmanageable as the knowledge base (KB) grows. This paper describes an alternate visual representation for navigating knowledge structures, based on a virtual museum metaphor. This representation uses nested boxes rather than linked nodes to represent relations. The intricate structure of the knowledge base is conveyed by a combination of position, size, color, and font cues, MUE (Museum Unit Editor) was implemented using this representation to provide a graphic front end for the Cyc knowledge base.
Input switched high performance single phase single switch Ćuk AC-DC converter

Single phase full wave bridge rectifier draws non sinusoidal current from a sinusoidal voltage source which causes low performance of the rectifier. Switching mode regulators are used to improve the shape of current and power factor of the input side. In this paper a different type of single phase single switch AC-DC converter using Ćuk topology is reported. Input current is chopped in this converter at high frequency during both cycles by a single switch to get step up/step down conversion. Comparison is made between reported and conventional circuit under same load and operating conditions. This proposed circuit shows better performance. The efficiency of this converter is also high. Any other control scheme is not required to achieve these advantages.
Cluster-based two-step target localization with incremental cooperation

Target localization is one of the momentous research subjects in wireless sensor networks (WSNs). Several methods have been initiated so far for the aim of target (e.g. sniper) localization using the acoustic signals produced, such as muzzle blast and shock wave in WSNs. One of the preeminent available methods is maximum likelihood estimation (MLE) algorithm, using time difference of arrival (TDOA) of the target signal received at sensor nodes. Although the MLE algorithm is asymptotically optimum and obtains high level of accuracy in comparison with other methods, nevertheless, using MLE has two major challenges. Firstly, the crucial need of this method to begin with a proper initial guess, and secondly, the possibility of not converging to a global minimum. Moreover, employing WSNs constrains the amount of power consumption that is practically possible. In this paper, to overcome the aforementioned obstacles, a two-step algorithm is proposed which in first step, a fast spherical interpolation (SI) method is utilized to prepare an appropriate initial guess for the MLE algorithm. In the second step, a clustering-based network is described to attain less power consumption across the WSN. Furthermore, to increase the probability of convergence, a cooperative incremental cluster-based estimation strategy is proposed. In addition, major issues that can affect the performance of the proposed method are investigated. Simulation results prove the capability of this method and support the claims.
Okul Yöneticilerinin Seçme Ve Yetiştirme Uygulamalarına Yönelik Öğretmen Ve Yönetici Görüşleri

The goal of thestudy is to describe the chosing and growing the school administrators of National Education Ministry (NEM) in accordance with views of educators. This study may be guide for NEM. Case study design wasused fort the current study. Researchers of the study involve 20 educators working at NEM institutions. Halfstructured interview is used to collect data. Data are divided into three categories: Chosing the school administrator; growing the administrators; and performance expectations of the school administrators. Chosing part includes 15 themes whereas growing and performance expectations part include 10 and 6 themes respectively. Participantsare are of the opinion that the policy of NEM for chosing and growing administrators is insuffcient. However, the policy about this subject is of higher importance all over the World. The exam systems run in our counteru is well behind its counterparts in the World. Results of the study show that school administrators may need to have a master’s degree in school management.
Do Funds Make More When They Trade More?

We find that active mutual funds perform better after trading more. This time-series relation between a fund’s turnover and its subsequent benchmarkadjusted return is especially strong for small, high-fee funds. These results are consistent with high-fee funds having greater skill to identify time-varying profit opportunities and with small funds being more able to exploit those opportunities. In addition to this novel evidence of managerial skill and fund-level decreasing returns to scale, we find evidence of industry-level decreasing returns: The positive turnover-performance relation weakens when funds act more in concert. We also identify a common component of fund trading that is correlated with mispricing proxies and helps predict fund returns.
Black Box Anomaly Detection: Is It Utopian?

Automatic identification of anomalies on network data is a problem of fundamental interest to ISPs to diagnose incipient problems in their networks. ISPs gather diverse data sources from the network for monitoring, diagnostics or provisioning tasks. Finding anomalies in this data is a huge challenge due to the volume of the data collected, the number and diversity of data sources and the diversity of anomalies to be detected. In this paper we introduce a framework for anomaly detection that allows the construction of a black box anomaly detector. This anomaly detector can be used for automatically finding anomalies with minimal human intervention. Our framework also allows us to deal with the different types of data sources collected from the network. We have developed a prototype of this framework, TrafficComber, and we are in the process of evaluating it using the data in the warehouse of a tier-1 ISP.
Towards Activity-Aware Tool Support for Change Tasks

To complete a change task, software developers perform a number of activities, such as locating and editing the relevant code. While there is a variety of approaches to support developers for change tasks, these approaches mainly focus on a single activity each. Given the wide variety of activities during a change task, a developer has to keep track of and switch between the different approaches. By knowing more about a developer's activities and in particular by knowing when she is working on which activity, we would be able to provide better and more tailored tool support, thereby reducing developer effort.In our research we investigate the characteristics of these activities, whether they can be identified, and whether we can use this additional information to improve developer support for change tasks. We conducted two exploratory studies with a total of 21 software developers collecting data on activities in the lab and field. An empirical analysis of the data shows, amongst other results, that activities comprise a consistently small amount of code elements across all developers and tasks (approx. 8.7 elements). Further analysis of the data shows, that we can automatically detect the boundaries and types of activities, and that the information on activity types can be used to improve the identification of relevant code elements.
Invariant spatial parametrization of human thoracohumeral kinematics: A feasibility study

In this paper, we present a novel kinematic framework using hybrid twists, that has the potential to improve the reliability of estimated human shoulder kinematics. This is important as the functional aspects of the human shoulder are evaluated using the information embedded in thoracohumeral kinematics. We successfully demonstrate in our results, that our approach is invariant of the body-fixed coordinate definition, is singularity free and has high repeatability; thus resulting in a flexible user-specific kinematic tracking not restricted to bony landmarks.