Miracle-dz/UniFAR-FTUs huggingface dataset:
Outage performance analysis of cognitive relay networks with BRS and MMRS

In this paper, we consider a spectrum sharing system where a secondary user (SU) transmitter (SU-Tx) communicates with an SU receiver (SU-Rx) with the help of multiple secondary relays (SRs) in the presence of a single primary network link. In particular, the SU-Tx and SR are subject to their maximum transmit power limits and the timeout constraint of the primary user (PU). Moreover, we assume that the relay selection is based on either best relay selection (BRS) or max-max relay selection (MMRS). In BRS, a single relay having the best end-to-end channel condition among the SRs is selected for cooperation between the source and the destination. However, the selected relay may not experience the best source-relay channel and relay-destination channel at the same time. To overcome the limitation of selecting the same relay for both reception and transmission, MMRS uses the best relay of the SU-Tx→SR link for reception at the relay and the best relay of the SR→SU-Rx link for transmission to the destination. Specifically, we compare the performance for BRS and MMRS in terms of the outage probability, and study the impact of the number of SRs, PU transmit power and different channel mean powers of interference links on the secondary network performance. Furthermore, based on the performance of the MMRS and assuming that automatic repeat request (ARQ) is implemented for packet retransmission, we investigate the outage probability for delay limited applications. The numerical results indicate that the MMRS outperforms BRS when more than one SRs are deployed. The secondary network outage probability is reduced when the number of SRs and the number of retransmissions become large. It is also shown that the interference from the PU has a significant impact on the secondary network performance.
Epstein-Barr Virus with the Latent Infection Nuclear Antigen 3B Completely Deleted Is Still Competent for B-Cell Growth Transformation In Vitro

ABSTRACT The Epstein-Barr virus (EBV) nuclear antigen 3B (EBNA-3B) is considered nonessential for EBV-mediated B-cell growth transformation in vitro based on three virus isolates with EBNA-3B mutations. Two of these isolates could potentially express truncated EBNA-3B products, and, similarly, we now show that the third isolate, IB4, has a point mutation and in-frame deletion of 263 amino acids. In order to test whether a virus with EBNA-3B completely deleted can immortalize B-cell growth, we first cloned the EBV genome as a bacterial artificial chromosome (BAC) and showed that the BAC-derived virus was B-cell immortalization competent. Deletion of the entire EBNA-3B open reading frame from the EBV BAC had no adverse impact on growth of EBV-immortalized B cells, providing formal proof that EBNA-3B is not essential for EBV-mediated B-cell growth transformation in vitro.
Some Scaling Laws for MOOC Assessments

One problem that arises with the increasing numbers of students in Massive Open Online Courses (MOOCs) is that of student evaluation. The large number of students makes it infeasible for the instructors or the teaching assistants to grade all assignments, while the present auto-grading technology is not feasible for many topics of interest. As a result, there has recently been a great push for employing peergrading, where students grade each other, since the number of graders automatically scale with the number of students. However, in practice, peer-grading has been observed to have high error rates and has come under serious criticism. In this paper, we take a statistical approach towards understanding the feasibility of peer-grading for MOOCs. Under simple (yet general) models, we show that peer-grading as a standalone will not scale, i.e., as the number of students increases, the expected number of students misgraded will grow proportionately. We then consider a hybrid approach that combines peer-grading with auto-grading. In this setting, an automated approach is used for ‘dimensionality reduction’, a classical technique in statistics and machine learning, and peer-grading is employed to evaluate this lower dimensional set of answers. We show that this alternative approach has the potential to scale. While most current research on assessment in MOOCs is empirical, our more theoretical approach provides a fundamental understanding of the errors observed in current grading systems, and provides a direction for future research to overcome those errors.
IllumiRoom

IllumiRoom is a proof-of-concept system that surrounds a television with projected light, bringing video games, and film experiences out of the TV screen and into the real world. IllumiRoom uses 3D scanning and projected light to change the appearance of the room, induce apparent motion, extend the field of view, and enable entirely new gaming experiences. Our system is entirely self-calibrating and is designed to work in any room. We present a detailed exploration of the design space of possible projected visualizations and we demonstrate ways to trigger and drive these visualizations from gaming content. We also contribute specific feedback from two groups of target users (10 gamers and 15 game designers); providing insights for enhancing game and film experiences beyond the TV.
Searching for diversified landmarks by photo

This demo focuses on the problem of searching for diversified landmarks with photos as input. More particularly, we propose a system called DLMSearch that allows a user to upload a photo as a query and searches for a diverse set of relevant landmarks in real time. It also presents a photo summary for each retrieved landmark, considering both visual representativeness and diversity. Our online demo is available at http://lm.apexlab. org/landmark/demo.
Cloning and Sequence Analysis of the Structural Gene for the bc 1-Type Rieske Iron-Sulfur Protein from Thermus thermophilus HB 8

The structural gene encoding the Rieske iron-sulfur protein from Thermus thermophilus HB8 has been cloned and sequenced. The gene encodes a protein of 209 amino acids that begins with a hydrophilic N-terminus followed by a stretch of 21 hydrophobic amino acids that could serve as a transmembrane helix. The remainder of the protein has a hydrophobicity pattern typical of a water-soluble protein. A phylogenetic analysis of 26 Rieske proteins that are part of bc\ or b6f complexes shows that they fall into three major groups: eubacterial and mitochondrial, cyanobacterial and plastid, and five highly divergent outliers, including that of Thermus. Although the overall homology with other Rieske proteins is very low, the C-terminal half of the Thermus protein contains the signature sequence CTHLGC-(13X)-CPCH that most likely provides the ligands of the [2Fe-2S] cluster. It is proposed that this region of the protein represents a small domain that folds independently and that the encoding DNA sequence may have been transferred during evolution to several unrelated genes to provide the cluster attachment site to proteins of different origin. The role of individual residues in this domain of the Thermus protein is discussed vis-a-vis the three-dimensional structure of the bovine protein (Iwata et al., 1996 Structure 4, 567-579).
Mechanisms of Contextual Risk for Adolescent Self-Injury: Invalidation and Conflict Escalation in Mother–Child Interactions

According to developmental theories of self-injury, both child characteristics and environmental contexts shape and maintain problematic behaviors. Although progress has been made toward identifying biological vulnerabilities to self-injury, mechanisms underlying psychosocial risk have received less attention. In the present study, we compared self-injuring adolescents (n = 17) with typical controls (n = 20) during a mother–child conflict discussion. Dyadic interactions were coded using both global and microanalytic systems, allowing for a highly detailed characterization of mother–child interactions. We also assessed resting state psychophysiological regulation, as indexed by respiratory sinus arrhythmia (RSA). Global coding revealed that maternal invalidation was associated with adolescent anger. Furthermore, maternal invalidation and coerciveness were both related to adolescent opposition/defiance. Results from the microanalytic system indicated that self-injuring dyads were more likely to escalate conflict, suggesting a potential mechanism through which emotion dysregulation is shaped and maintained over time. Finally, mother and teen aversiveness interacted to predict adolescent resting RSA. Low-aversive teens with highly aversive mothers had the highest RSA, whereas teens in high–high dyads showed the lowest RSA. These findings are consistent with theories that emotion invalidation and conflict escalation are possible contextual risk factors for self-injury.
Dynamic layer management in superpeer architectures

Superpeer unstructured P2P systems have been found to be very effective by dividing the peers into two layers, superlayer and leaf-layer, in which message flooding is only conducted among superlayer and all leaf-peers are represented by corresponding superpeers. However, current superpeer systems do not employ any effective layer management schemes, so the transient and low-capacity peers are allowed to act as superpeers. Moreover, the lack of an appropriate size ratio maintenance mechanism on superlayer to leaf-layer makes the system's search performance far from being optimal. We present one workload model aimed at reducing the weighted overhead of a network. Using our proposed workload model, a network can determine an optimal layer size ratio between leaf-layer and superlayer. We then propose a dynamic layer management algorithm, DLM, which can maintain an optimal layer size ratio and adaptively elect and adjust peers between superlayer and leaf-layer. DLM is completely distributed in the sense that each peer decides to be a superpeer or a leaf-peer independently without global knowledge. DLM could effectively help a superpeer P2P system maintain the optimal layer size ratio and designate peers with relatively long lifetime and large capacities as superpeers, and the peers with short lifetime and low capacities as leaf-peers under highly dynamic network situations. We demonstrate that the quality of a superpeer system is significantly improved under the DLM scheme by comprehensive simulations.
Analysis of the signal for attachment of a glycophospholipid membrane anchor

The COOH terminus of decay accelerating factor (DAF) contains a signal that directs attachment of a glycophospholipid (GPI) membrane anchor. To define this signal we deleted portions of the DAF COOH terminus and expressed the mutant cDNAs it CV1 origin-deficient SV-40 cells. Our results show that the COOH-terminal hydrophobic domain (17 residues) is absolutely required for GPI anchor attachment. However, when fused to the COOH terminus of a secreted protein this hydrophobic domain is insufficient to direct attachment of a GPI anchor. Additional specific information located within the adjacent 20 residues appears to be necessary. We speculate that by analogy with signal sequences for membrane translocation, GPI anchor attachment requires both a COOH- terminal hydrophobic domain (the GPI signal) as well as a suitable cleavage/attachment site located NH2 terminal to the signal.
Evolution of mating isolation between populations of Drosophila ananassae

Prezygotic mating isolation has been a major interest of evolutionary biologists during the past several decades because it is likely to represent one of the first stages in the transition from populations to species. Mate discrimination is one of the most commonly measured forms of prezygotic isolation and appears to be relatively common among closely related species. In some cases, it has been used as a measure to distinguish populations from subspecies, races, and sister species, yet the influences of various evolutionary mechanisms that may generate mate discrimination are largely unknown. In this study, we measured the level and pattern of mate discrimination among 18 populations of a cosmopolitan drosophilid species, Drosophila ananassae, from throughout its geographical range and its sister species, Drosophila pallidosa, which has a restricted geographical distribution in the South Pacific Islands. In addition, we measured genetic differentiation between all 18 populations using mitochondrial DNA polymorphism data. Mate discrimination varies considerably throughout the species range, being higher among populations outside the ancestral Indonesian range, and highest in the South Pacific. Our results suggest that colonization and genetic differentiation may have an influence on the evolutionary origin of mate discrimination. Our phylogeographical approach clarifies the ancestral relationships of several populations from the South Pacific that show particularly strong mate discrimination and suggests that they may be in the early stages of speciation. Furthermore, both the genetic and behavioral results cast doubt on the status of D. pallidosa as a good species.
Evaluation of Range-based Methods for Localization in Grain Storages

Monitoring biomass storages by using wireless sensor networks with localization capabilities can help prevent economic losses during storage, help to improve the grain quality and lower costs during drying. In this article, the received signal strength was used to perform localization of wireless sensor nodes embedded in a grain storage. A path loss model that takes into account the temperature and moisture content of the grain at each sensor node was used for estimating distance based on received signal strength. The average error of the position estimates was 6.3 m. Tests using near-field electromagnetic ranging were performed to evaluate the performance of the method. It was found that the experimental setup worked best between 2 - 7 m where the average error was 4.9% of the actual distance.
Alternating-time temporal logic with finite-memory strategies

Model-checking the alternating-time temporal logics ATL and ATL* with incomplete information is undecidable for perfect recall semantics. However, when restricting to memoryless strategies the model-checking problem becomes decidable. In this paper we consider two other types of semantics based on finite-memory strategies. One where the memory size allowed is bounded and one where the memory size is unbounded (but must be finite). This is motivated by the high complexity of model-checking with perfect recall semantics and the severe limitations of memoryless strategies. We show that both types of semantics introduced are different from perfect recall and memoryless semantics and next focus on the decidability and complexity of model-checking in both complete and incomplete information games for ATL/ATL*. In particular, we show that the complexity of model-checking with bounded-memory semantics is Delta_2p-complete for ATL and PSPACE-complete for ATL* in incomplete information games just as in the memoryless case. We also present a proof that ATL and ATL* model-checking is undecidable for n >= 3 players with finite-memory semantics in incomplete information games.
Virtual Ruler: Mobile Beacon Based Distance Measurements for Indoor Sensor Localization

In sensor localization, ultrasound based distance measurements will have large errors if line-of-sight paths are blocked between pairwise sensors. Because these outliers, once mixed together with other correct distance measurements, are difficult for localization algorithms to identify, we propose to exclude the outliers in the first step of distance measurement. Although the distance between pairwise sensors measured by ultrasound can have multiple values due to the multipath effect, our experiments find that a sensor's incorrect position, estimated from the distance measurement along a reflected path instead of a straight line, is always mirrored to the sensor's correct position. Based on this phenomena, we propose to use mobile beacons to measure the distance between pairwise sensors from multiple perspectives and filter incorrect values through a statistical approach. Our performance evaluation shows that the proposed algorithm can achieve better localization results than previous approaches in an indoor environment where multipath effects cannot be avoided
Leveraging commonsense reasoning and multimodal perception for robot spoken dialog systems

Probabilistic graphical models, such as partially observable Markov decision processes (POMDPs), have been used in stochastic spoken dialog systems to handle the inherent uncertainty in speech recognition and language understanding. Such dialog systems suffer from the fact that only a relatively small number of domain variables are allowed in the model, so as to ensure the generation of good-quality dialog policies. At the same time, the non-language perception modalities on robots, such as vision-based facial expression recognition and Lidar-based distance detection, can hardly be integrated into this process. In this paper, we use a probabilistic commonsense reasoner to “guide” our POMDP-based dialog manager, and present a principled, multimodal dialog management (MDM) framework that allows the robot's dialog belief state to be seamlessly updated by both observations of human spoken language, and exogenous events such as the change of human facial expressions. The MDM approach has been implemented and evaluated both in simulation and on a real mobile robot using guidance tasks.
Strong coupling constant with flavor thresholds at four loops in the MS scheme

We present in analytic form the matching conditions for the strong-coupling constant alpha_s^(n_f)(mu) at the flavor thresholds to four loops in the modified minimal-subtraction scheme. Taking into account the present knowledge on the coefficient beta_4 of the Callan-Symanzik beta function of quantum chromo-dynamics, we thus derive a five-loop formula for alpha_s^(n_f)(mu) together with appropriate relationships between the asymptotic scale parameters Lambda^(n_f) for different numbers of flavors n_f.
An Adaptive Loss Differentiation Algorithm Based on Queue Management

It is important for TCP to provide a mechanism to differentiate between congestion losses and wireless random losses in wired/wireless hybrid networks, because the latter may cause a severe throughput degradation if TCP sender misinterprets such losses and reduces its window size. Being different from other approaches based on end-to-end metrics, BQM is an efficient loss differentiation algorithm based on queue management. This paper points that BQM discriminator can not be fit to different network states and proposes an adaptive BQM, whose key idea is to adjust the primary parameters according to network events and track the dropping pattern on routers. The simulation results show that the accuracy of A BQM discriminator is higher than that of BQM in different network states and A BQM can adjust itself adaptively according to network states.
High-resolution holocene environmental changes in the thar desert, northwestern india

Sediments from Lunkaransar dry lake in northwestern India reveal regional water table and lake level fluctuations over decades to centuries during the Holocene that are attributed to changes in the southwestern Indian monsoon rains. The lake levels were very shallow and fluctuated often in the early Holocene and then rose abruptly around 6300 carbon-14 years before the present (14C yr B.P.). The lake completely desiccated around 4800 (14)C yr B.P. The end of this 1500-year wet period coincided with a period of intense dune destabilization. The major Harrapan-Indus civilization began and flourished in this region 1000 years after desiccation of the lake during arid climate and was not synchronous with the lacustral phase.
Is post-smoking-cessation weight-gain a significant trigger for relapse?

While the Surgeon General's Consumer Guide lists weight-gain as an important relapse trigger, the 2001 Surgeon General's Report on Women and Smoking concludes, paradoxically, that actual weight-gain during cessation does not appear to predict relapse. This dichotomous view reflects longstanding scientific uncertainty about the role of weight-gain in triggering relapse. This scientific uncertainty, which stems from mixed clinical trial results, is problematic for insurance coverage decisions such as state Medicaid programme decisions to cover or exclude smoking-cessation and weight-control pharmaceuticals. Analysts hypothesize that selection bias may explain the inconsistency between the negative clinical results and the persistent view that weight-gain triggers relapse, if weight-concern is both a key determinant of the transition from ‘smoker’ to ‘ex-smoker,’ and a key moderating variable in the relationship between weight-gain and relapse. We therefore use the nationally representative 1997 National Longitudinal Survey of Youth (NLSY97) to test the relapse-trigger hypothesis, and conclude that post-smoking-cessation weight-gain triggers relapse among weight-concerned white women, but it is associated with quitting success among Hispanic women. In addition, our results do not support the hypothesis that the mixed clinical trial results reflect selection bias based on weight-concern.
A Multiple Perspectives Approach to supplier Selection

Purpose – The purpose of this paper is to change the traditional supplier selection methods by shifting the emphasis from using a single model to using multiple models in the unstructured decision‐making context and to provide a tool for decision makers to make informed decisions of supplier selection in the multiple perspectives.Design/methodology/approach – There are various supplier selection models available in the literature. However, using the result of a single model as a basis for making the final decision could lead to a biased decision given the fact that any model has its limitations. The qualities of the decision‐making process and the decision itself increase by applying a multiple perspectives approach rather than a single model. The multiple perspectives decision‐making allows collaboration and knowledge sharing among the participants which leads to a less‐biased decision. This study examines commonly applied supplier selection models, formulates general perspectives of these models, and pr.