Miracle-dz/UniFAR-FTUs huggingface dataset:
Does information technology always lead to lower transaction costs?

This paper reconsiders the effect of information technology on transaction costs in view of IT externalities and coordination costs. The aim of the paper is to show that IT has ambivalent effects on the overall transaction costs. This analysis is based on the idea that IT externalities have both positive and negative effects on coordination and thus transaction costs. Two different strategies to use IT in an organizational setting are identified: one to increase the amount of information available to decision makers thus to reduce the uncertainty and hence transaction costs. The other to reduce the amount of available information to decrease the complexity faced and thus coordination and transaction costs. Finally, the effects of IT externalities impose the awareness that one strategy is not a substitute to the other rather that they can both coexist.
PTSD Growth and Substance Abuse Among a College Student Community: Coping Strategies after 2009 L’aquila Earthquake

Aim of the study was the assessment of coping strategies, specifically substance use and post-traumatic growth (PTG), in 411 college students two years after 2009 L’Aquila earthquake. Post-Traumatic Growth Inventory (PTGI) was used to assess PTG and one question about substance use (alcohol, tobacco, cannabis) was asked to verify if students had modified their use in the post-earthquake compared with the pre-earthquake period. The 77.1% of college students were exposed to L’Aquila earthquake. The PTGI mean score was 35.23, underlining low positive coping strategies among student community. About substance abuse, the 43.8% of college students reported a marked increase in alcohol use, 7.8% in cannabis and the 15.8% reported an increase in nicotine use in the post-earthquake period. Despite these data, 12.5 % of the students reported a decrease in alcohol use after the earthquake and 17.3% of the sample reported a PTG, showing positive behaviors and attitudes after the traumatic experience of the natural disaster (increase of social relationships, appreciation of new future possibilities, and development of a new deep meaning of life). Inferential analysis shows a strong negative correlation between direct earthquake exposure and PTGI total score. In post-disaster settings, a systematic framework of case identification, triage, and mental health interventions, including the improvement of positive coping strategies, like the PTG, should be integrated into emergency medicine and trauma care responses.
In Vitro Inhibitory and Cytotoxic Activity of MFM 501, a Novel Codonopsinine Derivative, against Methicillin-Resistant Staphylococcus aureus Clinical Isolates

28 new pyrrolidine types of compounds as analogues for natural polyhydroxy alkaloids of codonopsinine were evaluated for their anti-MRSA activity using MIC and MBC value determination assay against a panel of S. aureus isolates. One pyrrolidine compound, MFM 501, exhibited good inhibitory activity with MIC value of 15.6 to 31.3 μg/mL against 55 S. aureus isolates (43 MRSA and 12 MSSA isolates). The active compound also displayed MBC values between 250 and 500 μg/mL against 58 S. aureus isolates (45 MRSA and 13 MSSA isolates) implying that MFM 501 has a bacteriostatic rather than bactericidal effect against both MRSA and MSSA isolates. In addition, MFM 501 showed no apparent cytotoxicity activity towards three normal cell lines (WRL-68, Vero, and 3T3) with IC50 values of >625 µg/mL. Selectivity index (SI) of MFM 501 gave a value of >10 suggesting that MFM 501 is significant and suitable for further in vivo investigations. These results suggested that synthetically derived intermediate compounds based on natural products may play an important role in the discovery of new anti-infective agents against MRSA.
Technology Investment Radar: A Tool to Automatically Track Technology Maturation

In this paper, we present a prototype application -- the technology investment radar -- to systematically and continuously track the maturity of technologies using information on the Web to inform investment decisions. This prototype achieves this capability by integrating a variety of AI and semantic technologies in a novel way. These technologies include an inference engine, semantic models, and various NLP/NLU approaches. We evaluate the performance of this prototype through a pilot with Accenture's Wireless Community of Practice. The results from the pilot are encouraging as the Technology Investment Radar's maturity assessments for the technologies tracked are comparable to those given by the human analysts. We also assess the utility of the system from an end user perspective. Our assessment reveal that the majority of the analysts found the system to be useful and will continue to use it after the pilot, demonstrating the practical value of the system.
Activation of the Rab7 GTPase by the MON1-CCZ1 Complex Is Essential for PVC-to-Vacuole Trafficking and Plant Growth in Arabidopsis[C][W]

This work identifies the Arabidopsis MON1 and CCZ1 proteins as forming a dimeric complex that functions as a Rab5 effector and a Rab7 GEF to mediate Rab5-to-Rab7 conversion on PVCs. Arabidopsis Rab7 and mon1 mutants contained enlarged PVCs and fragmented vacuoles, and exhibited defects in vacuolar trafficking and retarded-growth phenotypes. Rab GTPases serve as multifaceted organizers during vesicle trafficking. Rab7, a member of the Rab GTPase family, has been shown to perform various essential functions in endosome trafficking and in endosome-to-lysosome trafficking in mammalian systems. The Arabidopsis thaliana genome encodes eight putative Rab7 homologs; however, the detailed function and activation mechanism of Rab7 in plants remain unknown. Here, we demonstrate that Arabidopsis RABG3f, a member of the plant Rab7 small GTPase family, localizes to prevacuolar compartments (PVCs) and the tonoplast. The proper activation of Rab7 is essential for both PVC-to-vacuole trafficking and vacuole biogenesis. Expression of a dominant-negative Rab7 mutant (RABG3fT22N) induces the formation of enlarged PVCs and affects vacuole morphology in plant cells. We also identify Arabidopsis MON1 (MONENSIN SENSITIVITY1) and CCZ1 (CALCIUM CAFFEINE ZINC SENSITIVITY1) proteins as a dimeric complex that functions as the Rab7 guanine nucleotide exchange factor. The MON1-CCZ1 complex also serves as the Rab5 effector to mediate Rab5-to-Rab7 conversion on PVCs. Loss of functional MON1 causes the formation of enlarged Rab5-positive PVCs that are separated from Rab7-positive endosomes. Similar to the dominant-negative Rab7 mutant, the mon1 mutants show pleiotropic growth defects, fragmented vacuoles, and altered vacuolar trafficking. Thus, Rab7 activation by the MON1-CCZ1 complex is critical for vacuolar trafficking, vacuole biogenesis, and plant growth.
Identification of genuine/authentic avian leptin: some answers and more questions.

The dogmatic adherence to “what is good for the goose is good for the gander” appears to pervade avian endocrinology research when it comes to vertebrate evolution of hormones and their physiological roles in birds. Thereappearstobeageneralacceptancethatspecifichormones, their cognate receptors, and their regulatory functions identified in other vertebrates should be present and serve the same function in birds. This has been largely the case for leptin (LEP) originally identified in mammals (1– 5), which has been vigorously sought for more than a decade in birds (6–10), and also more recently for kisspeptin (11, 12). But should we expect to find the same hormones and functions in birds as occurs in other vertebrates? Inorderforearlyreptilianbirdancestorstotaketo the air, phenomenal evolutionary changes in their physiology were required and presumably drove changes in the use of existing hormones and cognate receptors, their modification, or their abandonment. Yet many scientists take the view that major physiological systems present in tetrapods and fish should be present in birds and serve the same function and use of the same hormone/receptor regulators. Thisisclearlynotthecaseforsomemajorsystems,such as the genetics of sexual determination in birds and the high set point for body temperature (40°C), and for some major hormone regulators, such as the neuroendocrinology of the regulation of reproduction. The latter is characterizedbythetotalexcisionofkisspeptinandkisspeptin
Estimation techniques used in studies of copepod population dynamics - A review of underlying assumptions

Abstract The literature on zooplankton population dynamics provides more estimation techniques than reliable estimates of population parameters. In this review we show how different techniques relate to each other in terms of underlying models and assumptions. There are two main routes to parameter estimates. The vertical approaches utilize the stage-structure of samples taken at the same point in time. They require assumptions about the constancy in the parameters, but relax assumptions concerning advective influence. The horizontal approaches utilize information provided by the stage structure within samples, as well as information on temporal changes in abundance. They relax assumptions about the constancy of parameters, but advective influences may be introduced. Of the horizontal methods, variants of what are commonly termed cohort methods have been widely used. These provide mathematical simplicity, but are based on more restrictive assumptions than methods fitting predescribed models (delay differe.
Antigenic variation of influenza A virus nucleoprotein detected with monoclonal antibodies

Monoclonal antibodies were used to study antigenic variation in the nucleoprotein of influenza A viruses. We found that the nucleoprotein molecule of the WSN/33 strain possesses at least five different determinants. Viruses of other influenza A virus subtypes showed antigenic variation in these nucleoprotein determinants, although changes in only one determinant were detected in H0N1 and animal strains. The nucleoprotein of human strains isolated from 1933 through 1979 could be divided into six groups, based on their reactivities with monoclonal antibodies; these groups did not correlate with any particular hemagglutinin or neuraminidase subtype. Our results indicate that antigenic variation in the nucleoproteins of influenza A viruses proceeds independently of changes in the viral surface antigens and suggest that point mutations and genetic reassortment may account for nucleoprotein variability.
GROWING SMALL BRANDS : DOES A BRAND ’ S EQUITY AND GROWTH POTENTIAL AFFECT ITS LONG-TERM MARKETING PRODUCTIVITY ?

Managers often hope to obtain long-term benefits with temporary marketing actions, especially for brands that are currently small. However, academic research implies their chances are slim: fewer than 5% of marketing actions generate permanent sales effects. Yet extant research has examined brands with similar characteristics, thus implicitly assuming that the brand itself carries no influence over whether its marketing actions attain long-term sales effects. In contrast, recent studies in marketing strategy show that the resources available to a brand influence the returns to its marketing mix actions. Therefore, we argue that brand-specific resources and characteristics will influence the permanent and cumulative effects of their marketing actions. Using panel data for 7 years from 43 brands in three product categories, we employ a two-stage approach in which we first estimate the long-term marketing effectiveness with persistence modeling, and then relate those effectiveness estimates to brand-specific resources. Overall, results indicate that long-term marketing productivity is higher for brands with higher equity and for brands with greater potential for growth (i.e., lower market share, narrower product line, or more new product introductions). These results offer new insight into the potential for long-run marketing effectiveness.
Asymptotics of Visibility in the Hyperbolic Plane

At each point of a Poisson point process of intensity λ in the hyperbolic plane, center a ball of bounded random radius. Consider the probability P r that, from a fixed point, there is some direction in which one can reach distance r without hitting any ball. It is known (see Benjamini, Jonasson, Schramm and Tykesson (2009)) that if λ is strictly smaller than a critical intensity λ gv thenP r does not go to 0 as r → ∞. The main result in this note shows that in the case λ=λ gv, the probability of reaching a distance larger than r decays essentially polynomially, while if λ>λ gv, the decay is exponential. We also extend these results to various related models and we finally obtain asymptotic results in several situations.
Approximate rate quantization of Adaptive Modulation and Coding with near-optimum throughput

In this paper, we consider optimum rate quantization of Adaptive Modulation and Coding (AMC) systems by jointly designing the MCS levels and intervals. Optimum quantization leads to coupled non-algebraic equations, and is generally not amenable for analysis. Here, we propose two approximate AMC rate quantization methods, which are based on an observation of the optimal condition and the numerical results in the literature. The numerical results show that both proposed methods are near-optimum in expected throughput.
Setting low-level vision parameters

As vision systems become more and more complex there is an increasing need to understand the interaction between the various modules that these systems are composed of. In this paper we attempt to answer the question of how a high-level module can feed back its knowledge to a low-level module to improve the performance of the overall system. In particular we consider a system model consisting of a single low-level module that takes a set of low-level parameters as input and a single high-level module that estimates a set of high-level model parameters. We consider the task of setting the low-level parameters to maximize the performance of the overall system. Previous approaches to this problem include setting the parameters by hand, empirical evaluation, learning, and updating the parameters using the previous image in a video. We propose an approach based on simultaneous optimization of the high-level and low-level parameters. After outlining the approach, we demonstrate it on three examples: (1) color-blob tracking, (2) colorbased lane tracking, and (3) edge-based lane tracking.
Gathering validity evidence in the use of multiple mini-interviews as an admission tool for dental students: Preliminary evidence from Saudi Arabia*

Abstract Aims: This study examined the validity evidence of noncognitive skills of incoming students in the Faculty of Dentistry at King Abdulaziz University using multiple mini-interviews (MMI). Validity evidence in response process, internal structure and relationship to other variables was investigated. Methods: A total of 146 students were interviewed by faculty members over a two-day period. The interviews took the form of an MMI, which consisted of six objective structure clinical examination (OSCE) stations with two faculty interviewers per station. Each student rotated through the six stations and were asked 4–5 structured questions per station. Each student was rated on a three-point rating scale. Results: The majority of dental students were rated to be acceptable. The inter-rater reliability was 0.91 which was significantly high (range: 0.87–0.94). The total MMI score for all stations was 73.47 (SD = 8.49) with female students scoring significantly higher than males did (p < 0.001). Generalizability study results indicated good reliability (Φ-coefficient = 0.73; G-coefficient = 0.75). Moderate association was found between total MMI score and foundation year GPA (r = 0.30, p ≤ 0.001). Conclusions: Preliminary validity evidence supports the use of MMI scores as an admission tool for dental students, with respect to its response process, internal structure and relationship to other variables.
Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain

An usual task in large data set analysis is searching for an appropriate data representation in a space of fewer dimensions. One of the most efficient methods to solve this task is factor analysis. In this paper, we compare seven methods for Boolean factor analysis (BFA) in solving the so-called bars problem (BP), which is a BFA benchmark. The performance of the methods is evaluated by means of information gain. Study of the results obtained in solving BP of different levels of complexity has allowed us to reveal strengths and weaknesses of these methods. It is shown that the Likelihood maximization Attractor Neural Network with Increasing Activity (LANNIA) is the most efficient BFA method in solving BP in many cases. Efficacy of the LANNIA method is also shown, when applied to the real data from the Kyoto Encyclopedia of Genes and Genomes database, which contains full genome sequencing for 1368 organisms, and to text data set R52 (from Reuters 21578) typically used for label categorization.
Tweeting Cameras for Event Detection

We are living in a world of big sensor data. Due to the widespread prevalence of visual sensors (e.g. surveillance cameras) and social sensors (e.g. Twitter feeds), many events are implicitly captured in real-time by such heterogeneous "sensors". Combining these two complementary sensor streams can significantly improve the task of event detection and aid in comprehending evolving situations. However, the different characteristics of these social and sensor data make such information fusion for event detection a challenging problem. To tackle this problem, we propose an innovative multi-layer tweeting camera framework integrating both physical sensors and social sensors to detect various concepts of real-world events. In this framework, visual concept detectors are applied on camera video frames and these concepts can be construed as "camera tweets" posted regularly. These tweets are represented by a unified probabilistic spatio-temporal (PST) data structure which is then aggregated to a concept-based image (Cmage) as the common representation for visualization. To facilitate event analysis, we define a set of operators and analytic functions that can be applied on the PST data by the user to discover occurrences of events and to analyse evolving situations. We further leverage on geo-located social media data by mining current topics discussed on Twitter to obtain the high-level semantic meaning of detected events in images. We quantitatively evaluate our framework with a large-scale dataset containing images from 150 New York real-time traffic CCTV cameras, university foodcourt camera feeds and Twitter data, which demonstrates the feasibility and effectiveness of the proposed framework. Results of combining camera tweets and social tweets are shown to be promising for detecting real-world events.
GazeTouchPIN: protecting sensitive data on mobile devices using secure multimodal authentication

Although mobile devices provide access to a plethora of sensitive data, most users still only protect them with PINs or patterns, which are vulnerable to side-channel attacks (e.g., shoulder surfing). How-ever, prior research has shown that privacy-aware users are willing to take further steps to protect their private data. We propose GazeTouchPIN, a novel secure authentication scheme for mobile devices that combines gaze and touch input. Our multimodal approach complicates shoulder-surfing attacks by requiring attackers to ob-serve the screen as well as the user’s eyes to and the password. We evaluate the security and usability of GazeTouchPIN in two user studies (N=30). We found that while GazeTouchPIN requires longer entry times, privacy aware users would use it on-demand when feeling observed or when accessing sensitive data. The results show that successful shoulder surfing attack rate drops from 68% to 10.4%when using GazeTouchPIN.
Incorporating Relational Knowledge into Word Representations using Subspace Regularization

Incorporating lexical knowledge from semantic resources (e.g., WordNet ) has been shown to improve the quality of distributed word representations. This knowledge often comes in the form of relational triplets ( x, r, y ) where words x and y are connected by a relation type r . Existing methods either ignore the relation types, essentially treating the word pairs as generic related words, or employ rather restrictive assumptions to model the relational knowledge. We propose a novel approach to model relational knowledge based on low-rank subspace regularization, and conduct experiments on standard tasks to evaluate its effectiveness.
Achieving cost efficiency using CaaS model in the cloud

Caching has become the key technology used for bridging the performance gap across memory hierarchies via temporal or spatial localities; in particular, the effect is prominent in disk storage systems. Applications that involve heavy I/O activities, which are common in the cloud, probably benefit the most from caching. The use of local volatile memory as cache might be a natural alternative, but many well-known restrictions, such as capacity and the utilization of host machines, hinder its effective use. We present the cache as a service (CaaS) model as an optional service to typical infrastructure service offerings. Specifically, the cloud provider sets aside a large pool of memory that can be dynamically partitioned and allocated to standard infrastructure services as disk cache. We first investigate the feasibility of providing CaaS with the proof-of-concept elastic cache system (using dedicated remote memory servers) built and validated on the actual system, and practical benefits of CaaS for both users and providers (i.e., performance and profit, respectively) are thoroughly studied with a novel pricing scheme. Our CaaS model helps to leverage the cloud economy greatly in that 1) the extra user cost for I/O performance gain is minimal if ever exists, and 2) the provider's profit increases due to improvements in server consolidation resulting from that performance gain. Through extensive experiments with eight resource allocation strategies, we show that our CaaS model can be a promising cost-efficient solution for both users and providers.
Behavioral Journalism for HIV Prevention: Community Newsletters Influence Risk-Related Attitudes and Behavior

Research teams in five cities used behavioral journalism to promote condom use and injection hygiene (use of bleach to clean shared injection equipment) among subpopulations at risk for human immunodeficiency virus (HIV) infection. For three years, HIV-prevention campaigns were conducted in which newsletters containing stories about peer models were distributed in selected communities. We report exposure to the campaigns across time, the cognitive and behavioral effects of increasing degrees of exposure, and the degree to which other sources of HIV information reached these communities. After one year, campaigns reached approximately 40 percent to 80 percent of the intended audiences. The reported number of campaign exposures was associated with theoretical cognitive determinants of behavior change and with risk-reduction behavior in communities that were not being effectively reached by other HIV prevention messages.