Miracle-dz/UniFAR-FTUs huggingface dataset:
A test between deindividuation and emergent norm theories of crowd aggression.

Deindividuation theory predicts that under the cover of anonymity, crowd members will be more aggressive than when identifiable. Emergent norm theory predicts that the most aggressive behavior will occur when an aggressive norm prevails in a crowd in which participants are identifiable to each other. These contrasting propositions were tested in a laboratory experiment involving a 2X2 factorial design. In groups of 6-8, subjects who were either anonymous or identifiable to each other acted as an audience to a pair of discussants. Subjects were given the opportunity to administer loud noise to the discussants. The response displayed to each group as an alleged average was manipulated so that subjects were led to believe that either an aggressive or a lenient norm had developed. As predicted by deindividuation theory, anonymous subjects administered significantly higher levels of noise than identifiable subjects. Anonymous subjects used equally loud noise regardless of group norm. Self-ratings provided evidence that the effects of anonymity were mediated by a psychological state of deindividuation, in addition to freedom from accountability for individual acts. There was no support for the crucial emergent norm theory prediction that aggression will be greatest when subjects who are identifiable to each other are exposed to an aggressive norm.
Do Values Share Universal Content and Structure? A South African Test

Schwartz recently proposed a new theory concerning the universal content and structure of values, a new value survey for measuring them and reported empirical support from 35 countries for many elements of the theory. In this article the validity of the theory is examined in two studies of diverse groups not previously tested using multiple value measurement instruments. In Study 1, 1364 subjects from the four major racial groupings completed the Rokeach Value Survey, a widely used values scale applicable to the theory, as part of a doctoral research project not previously analysed in this way. Study 2 subjects completed the new Schwartz Value Survey as part of a study of consumption patterns, media use, and leisure preferences of skilled labour, administrative and managerial staff commissioned by the Midrand Town Council. The results of both studies are consistent with the new theory and suggest important implications regarding value meaning in South Africa. The authors close by suggesting directions for future southern African values research.
Resource and Agreement Management in Dynamic Crowdcomputing Environments

Open Web-based and social platforms dramatically influence models of work. Today, there is an increasing interest in outsourcing tasks to crowd sourcing environments that guarantee professional processing. The challenge is to gain the customer's confidence by organizing the crowd's mixture of capabilities and structure to become reliable. This work outlines the requirements for a reliable management in crowd computing environments. For that purpose, distinguished crowd members act as responsible points of reference. These members mediate the crowd's workforce, settle agreements, organize activities, schedule tasks, and monitor behavior. At the center of this work we provide a hard/soft constraints scheduling algorithm that integrates existing agreement models for service-oriented systems with crowd computing environments. We outline an architecture that monitors the capabilities of crowd members, triggers agreement violations, and deploys counteractions to compensate service quality degradation.
Characterization of a polymer film optical fiber hydrophone for use in the range 1 to 20 MHz: A comparison with PVDF needle and membrane hydrophones

A small aperture wideband ultrasonic optical fiber hydrophone is described. The transduction mechanism is based on the detection of acoustically induced changes in the optical thickness of a 25-/spl mu/m thick parylene polymer film acting as a low finesse Fabry Perot (FP) interferometer that is deposited directly onto the end of a single mode optical fiber. The acoustic performance compares favorably with that of PVDF needle and membrane hydrophones with a peak noise-equivalent-pressure (without signal averaging) of 10 kPa over a 25-MHz measurement bandwidth, a wideband response to 20 MHz, and a near omnidirectional performance at 10 MHz. The dynamic range was 60 dB with an upper limit of linear detection of 11 MPa and a temporal stability of <5% over a period of 20 h. The hydrophone can also measure temperature changes with a resolution of 0.065/spl deg/C, offering the prospect of making simultaneous acoustic pressure and temperature measurements. The transduction parameters of the FP sensing element were measured, yielding an ultrasonic acoustic phase sensitivity of 0.075 rad/MPa and a temperature phase sensitivity of 0.077 rad//spl deg/C. The ability to achieve high acoustic sensitivity with small element sizes and to repeatably fabricate rugged sensor downleads using polymer deposition techniques suggests that this type of hydrophone can provide a practical alternative to piezoelectric hydrophone technology.
A Chloroacetamidine‐Based Inactivator of Protein Arginine Methyltransferase 1: Design, Synthesis, and In Vitro and In Vivo Evaluation

Protein arginine methyltransferases (PRMTs) catalyze the post-translational methylation of arginine residues. PRMT1 is the predominant mammalian isozyme, and is responsible for generating the majority of the asymmetrically dimethylated arginine found in vivo. The dysregulation of this enzyme has been implicated in heart disease and cancer; thus, its inhibition would be useful in the treatment of these diseases. Herein, we describe the most potent PRMT1 inhibitor described to date. This compound, denoted C21, is a chloroacetamidine-containing peptide that is able to irreversibly bind and inactivate the enzyme selectively. We have also shown that the coactivator activity of PRMT1 is selectively inhibited by the compound in cellulo.
Foundations of Secure Deductive Databases

We develop a formal logical foundation for secure deductive databases. This logical foundation is based on an extended logic involving several modal operators. We develop two models of interaction between the user and the database called "yes-no" dialogs, and "yes-no-don't know" dialogs. Both dialog frameworks allow the database to lie to the user. We develop an algorithm for answering queries using yes-no dialogs and prove that secure query processing using yes-no dialogs is NP-complete. Consequently, the degree of computational intractability of query processing with yes-no dialogs is no worse than for ordinary databases. Furthermore, the algorithm is maximally cooperative to user in the sense that lying is resorted to only when absolutely necessary. For Horn databases, we show that secure query processing can be achieved in linear time-hence, this is no more intractable than the situation in ordinary databases. Finally, we identify necessary and sufficient conditions for the database to be able to preserve security. Similar results are also obtained for yes-no-don't know dialogs. >
Rapid biotyping of Haemophilus influenzae and Haemophilus parainfluenzae with PathoTec strips and spot biochemical tests

PathoTec strips and spot biochemical tests were evaluated for the ability to biotype Haemophilus influenzae and Haemophilus parainfluenzae. Indole, urease, and ornithine decarboxylase reactions were tested. The results of PathoTec strips compared favorably with those conventional methods; the percent agreements were as follows: indole, 100; urease, 99.5; and ornithine, 95.5. Spot tests were simple and rapid, and the results also compared favorably with those of conventional tests; the percent agreements were as follows: indole, 99; urease, 100; and ornithine, 96.
Recommendations for Secure IC ’ s and ASIC ’ s

For the last ten years, security of integrated circuits has attracted a greater attention from the cryptographic community. Several sources of information leakage within the circuits have been emphasized. Power consumption based attacks have been mounted successfully against various types of circuits like ASIC, smartcards or FPGA. To counter them, specific high level solutions were developed, but none of them achieved a total prevention of such attacks. Circuit and transistor level solutions have also been developed with better results. We present here an interesting alternative to those solutions, using Dynamic Current Mode Logic. This type of logic style gives the same security margins as the other proposed alternatives to CMOS, with better performances in terms of power, delay, complexity of implemented functions and the possibility of an asynchronous mode of the signal propagation.
Modeling the Ultrasonic Softening Effect for Robust Copper Wire Bonding

In power electronics, ultrasonic wire bonding is used to connect the electrical terminals of power modules. To implement a self-optimization technique for ultrasonic wire bonding machines, a model of the process is essential. This model needs to include the so called ultrasonic softening effect. It is a key effect within the wire bonding process primarily enabling the robust interconnection between the wire and a substrate. However, the physical modeling of the ultrasonic softening effect is notoriously difficult because of its highly non-linear character and the absence of a proper measurement method. In a first step, this paper validates the importance of modeling the ultrasonic softening by showing its impact on the wire deformation characteristic experimentally. In a second step, the paper presents a data-driven model of the ultrasonic softening effect which is constructed from data using machine learning techniques. A typical caveat of data-driven modeling is the need for training data that cover the considered domain of process parameters in order to achieve accurate generalization of the trained model to new process configurations. In practice, however, the space of process parameters can only be sampled sparsely. In this paper, a novel technique is applied which enables the integration of prior knowledge about the process into the datadriven modeling process. It turns out that this approach results in accurate generalization of the data-driven model to novel process parameters from sparse data.
Mobilouds: An Energy Efficient MCC Collaborative Framework With Extended Mobile Participation for Next Generation Networks

Given the emergence of mobile cloud computing (MCC), its associated energy implications are witnessed at larger scale. With offloading computationally intensive tasks to the cloud datacentres being the basic concept behind MCC, most of the mobile terminal resources participating in the MCC collaborative execution are wasted as they remain idle until the mobile terminals receive responses from the datacentres. This is an additional wastage of resources alongside the cloud resources are already being addressed as massive energy consumers. Though the energy consumed of the idle mobile resources is insignificant in comparison with the cloud counterpart, such consumptions have drastic impacts on the mobile devices causing unnecessary battery drains. To this end, this paper proposes Mobilouds which encompass a multi-tier processing architecture with various levels of process cluster capacities and a software application to manage energy efficient utilization of such process clusters. Our proposed Mobilouds framework encourages the mobile device participation in the MCC collaborative execution, thereby reduces the presence of idle mobile resources and utilizes such idle resources in the actual task execution. Our performance evaluation results demonstrate that the Mobilouds framework offers the most energy-time balancing process clusters for task execution by effectively utilizing the available resources, in comparison with an entire cloud offloading strategy using 5G/4G networks.
Review of fault injection mechanisms and consequences on countermeasures design

The secret keys handled by cryptographic devices can be extracted using fault attacks associated with cryptanalysis techniques. These faults can be induced by different means such as laser exposure, voltage or clock glitches, electromagnetic perturbation, etc. This paper provides a detailed insight into the physics and mechanisms involved in several fault injection processes. The paper also highlights the difficulty to design countermeasures while even hardware duplication, usually considered as secure, has proved to show flaws against low cost fault injection means.
Economics, Business Principles and Moral Sentiments

Abstract: This essay discusses the place of business principles and of moral sentiments in economic success, and examines the role of cultures in influencing norms of business behavior. Two presumptions held in standard economic analysis are disputed: the rudimentary nature of business principles (essentially restricted, directly or indirectly, to profit maximization), and the allegedly narrow reach of moral sentiments (often treated to be irrelevant to business and economics). In contrast, the author argues for the need to recognize the complex structure of business principles and the extensive reach of moral sentiments by using theoretical considerations, a thorough analysis of Adam Smith’s work, and a careful interpretation of Japan’s remarkable economic success. Referring to the economic corruption in Italy and the “grabbing culture” in Russia, he further shows how deeply the presence or absence of particular features of business ethics can influence the operation of the economy, and even the nature of the society and its politics. Being an Indian himself, he warns against grand generalizations like the superiority of “Asian values” over traditional Western morals. To conclude, it is diversity—over space, over time, and between groups —that makes the study of business principles and moral sentiments a rich source of understanding and explanation.
Building the Foundations for Data-Based Decision Making: Creating Consensus on Language and Concepts, 13(5)

Data Based Decision Making (DBDM), the process of gathering, analyzing, applying, and sharing data in order to promote school improvement, has recently become a prominent process in the quest to assist students in attaining educational success and helping schools meet accountability benchmarks (Wayman, 2005; Poynton & Carey, 2006). This manuscript presents a pilot study undertaken in a Mid-Atlantic state to discern foundational understandings of DBDM by school staff. Results from the study reveal a lack of clarity on the foundational underpinnings of DBDM, as well as a lack of assessment literacy.
Analysis of clinical effect of high-intensity focused ultrasound on liver cancer.

AIM To evaluate the clinical effect of high-intensity focused ultrasound (HIFU) in the treatment of patients with liver cancer. METHODS HIFU treatment was performed in 100 patients with liver cancer under general anesthesia and by a targeted ultrasound. Evaluation of efficacy was made on the basis of clinical symptoms, liver function tests, AFP, MRI or CT before and after the treatment. RESULTS After HIFU treatment, clinical symptoms were relieved in 86.6%(71/82) of patients. The ascites disappeared in 6 patients. ALT (95+/-44) U/L and AST (114+/-58) U/L before HIFU treatment were reduced to normal in 83.3%(30/36) and 72.9%(35/48) patients, respectively, after the treatment. AFP was lowered by more than 50% in 65.3%(32/49) patients. After HIFU treatment, MRI or CT findings indicated coagulation necrosis and blood supply reduction or disappearance of tumor in the target region. CONCLUSION HIFU can efficiently treat the patients with liver cancer. It will offer a significant noninvasive therapy for local treatment of liver tumor.
The yeast UME5 gene regulates the stability of meiotic mRNAs in response to glucose

We reported previously that early meiotic transcripts are highly unstable. These mRNAs exhibit half-lives of approximately 3 min when expressed during vegetative growth in glucose medium and are stabilized twofold during sporulation in acetate medium. Two genes, UME2 and UME5, that regulate the stability of meiosis-specific transcripts have been identified. The wild-type UME5 gene, which has been analyzed in detail, decreases the stability of all meiotic mRNAs tested approximately twofold when expressed during vegetative growth but has no effect on the half-lives of a number of vegetative mRNAs examined. The UME5 gene is dispensable for mitotic and meiotic development. Cells in which the entire UME5 gene has been deleted are viable, although the generation time is slightly longer and sporulation is less efficient. The UME5 transcript is constitutively expressed, and its stability is not autoregulated. The UME5 gene encodes a predicted 63-kDa protein with homology to the family of CDC28 serine/threonine-specific protein kinases. The kinase activity appears to be central to the function of the UME5 protein, since alteration of a highly conserved amino acid in the kinase domain results in a phenotype identical to that of a ume5 deletion. Genetic epistasis studies suggest that the UME2 and UME5 gene products act in the same pathway to regulate meiotic transcript stability. This pathway is independent of deadenylation and translation, two factors known to be important in regulating mRNA turnover. Significantly, the UME5-mediated destabilization of meiotic mRNAs occurs in glucose- but not in acetate-containing medium. Thus, the UME5 gene appears to participate in a glucose signal transduction pathway governing message stability.
Snap and share your photobooks

The sharing of photos with others, friends and family, has become even more popular with digital photography and Internet applications such as email or Web albums. At the same time, the physical touch of printed photos is still appreciated and customers use different services to print their photos on post cards, calendars or photobooks, often to give them as a present or to create a physical souvenir. Once printed, however, the sharing of photos with others becomes difficult as there is no link back from the now physical item to its digital counterpart. With Bookmarkr, we developed a system that employs a mobile camera phone to bridge the gap between the printed photo and its digital counterpart. The user takes an image of a photo in a photobook with the mobile phone's camera. The image is transmitted to a photobook server, which employs image analysis techniques to retrieve the corresponding photo. The photo is sent back to the user and establishes the digital-physical match. Bookmarkr allows the user to interact with printed photos in a similar way as interacting with digital photos by using a point-and-shoot metaphor. Our performance evaluation shows that the system is able to return the correct photo in up to 99% of all cases. A conducted user study revealed that the designed interaction is suitable for the participants and their printed photobooks.
THE RELATIONSHIP BETWEEN PERSONALITY TRAIT AND MINDFULNESS DIMENSIONS IN PRIMARY SCHOOLS IN THAILAND

Personality trait and mindfulness are associated with a way we understand ourselves and those around us and consequentially be able to demonstrate skills to react in society peacefully. These skills are, for example, working with others, solving problems, making decisions, and adapting to change. The present study proposes a conceptual framework to examine relationship between personality trait and mindfulness dimension of students in primary schools in Thailand. School administrators, expert teachers, and parents have provided information about mindfulness activities and training conducted in schools and at home. Participating students aged between 7 and 12 will response to questionnaires measuring mindfulness dimensions and personality trait. The expected result will include the following: first, an analysis of mindfulness training activities classified based on mindfulness dimensions and personality trait, and, second, a statistic test on the relationship between personality trait and mindfulness dimensions in students. Then the classification of mindfulness training activities will be matched with relationship to recommend mindfulness training that can enhance the chosen mindfulness dimensions and personality trait.
Designing Computer Architecture Research Workloads

Although architectural simulators model microarchitectures at a high abstraction level, the increasing complexity of both the microarchitectures themselves and the applications that run on them make simulator use extremely time-consuming. Simulators must execute huge numbers of instructions to create a workload representative of real applications, creating an unreasonably long simulation time and stretching the time to market. Using reduced input sets instead of reference input sets helps to solve this problem. The authors have developed a methodology that reliably quantifies program behavior similarity to verify if reduced input sets result in program behavior similar to the reference inputs.
Transferring Pre-Trained Deep CNNs for Remote Scene Classification with General Features Learned from Linear PCA Network

Deep convolutional neural networks (CNNs) have been widely used to obtain high-level representation in various computer vision tasks. However, in the field of remote sensing, there are not sufficient images to train a useful deep CNN. Instead, we tend to transfer successful pre-trained deep CNNs to remote sensing tasks. In the transferring process, generalization power of features in pre-trained deep CNNs plays the key role. In this paper, we propose two promising architectures to extract general features from pre-trained deep CNNs for remote scene classification. These two architectures suggest two directions for improvement. First, before the pre-trained deep CNNs, we design a linear PCA network (LPCANet) to synthesize spatial information of remote sensing images in each spectral channel. This design shortens the spatial “distance” of target and source datasets for pre-trained deep CNNs. Second, we introduce quaternion algebra to LPCANet, which further shortens the spectral “distance” between remote sensing images and images used to pre-train deep CNNs. With five well-known pre-trained deep CNNs, experimental results on three independent remote sensing datasets demonstrate that our proposed framework obtains state-of-the-art results without fine-tuning and feature fusing. This paper also provides baseline for transferring fresh pretrained deep CNNs to other remote sensing tasks.
Modeling Earnings Measurement Error: A Multiple Imputation Approach

Recent survey validation studies suggest that measurement error in earnings data is pervasive and violates classical measurement error assumptions, and therefore may bias estimation of cross-section and longitudinal earnings models. We model the structure of earnings measurement error using data from the Panel Study of Income Dynamics Validation Study (PSDIVS). We then use Rubin's (1987) multiple imputation techniques to estimate consistent earnings equations under non-classical earnings measurement error in the PSID. Our technique is readily generalized, and the empirical results demonstrate the potential importance of correcting for measurement error in earnings and related data, particularly during recessions.