Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing for negative affect and critical reflection

Our research seeks to explore how technologies, their affordances, and related practices support transformative learning, a process through which individuals engage with feelings of discomfort and other negative emotions. During fall of 2013 the second author worked with graduate students in a course that employed decolonizing pedagogies. Throughout the course the students experienced, reflected upon and evaluated our efforts to encourage critical reflection, a crucial stage of the transformative learning process. They used a suite of tools that support different types of interaction, making for unique learning experiences because of their variation on private-public and individualistic-collective, and rhetorical-discursive continuums. Through this work we argue for continued expansion of how "user experience" is conceptualized within HCI, encouraging initiatives that address multi-faceted dimensions of the human experience.
Information failures and organizational disasters

Merck? s recent withdrawal of the arthritis drug Vioxx from the market and the warning signs leading up to the crisis are emblematic of how organizational disasters often incubate over long periods of time. The author asserts that organizational disasters can often be foreseen, but warning signs sometimes go unheeded for various reasons: Signals are not read properly because they seem consistent with organizational beliefs (as in the Enron collapse); signals are noticed but not acted upon (as in the failure of Barings Bank); or no one in an organization has the full range of information to see the situation as a whole (as in the recall of millions of Firestone ATX tires from drivers of Ford Explorers). The author presents several strategies that organizations can employ to help guard against such negligence. Employees must be aware of how biases affect judgment in crucial situations, and tendencies toward groupthink and group polarization must be controlled. In addition, companies must cultivate an information culture that not only recognizes and responds to unexpected warnings but also helps companies recover. Most important, ongoing conversations about safety and risk, backed by the will to act, are crucial to mitigating trouble and to helping organizations more easily recover from difficult situations.
Segmentation of historical lanna handwritten manuscripts

Lanna script is an archaic script not commonly used in today's world. People trying to read these archaic Lanna manuscripts have to find some form of translation help to understand what they said. Unfortunately, few people nowadays know how to read or write this language. Therefore, character recognition system must be put to use in order to translate the Lanna script to the commonly used script. The poor condition of the manuscripts and the writing style of the script make this problem very difficult to solve. The most difficult cases of the writing style problem are the touching and overlapping characters. Therefore, the first two stages of the character recognition process, which are image preprocessing and segmentation, need to be closely watched over so that the recognition accuracy is high. In this paper, two new techniques are proposed. The first proposed technique emphasizes on converting a grayscale image to a binary image. In this proposed technique, the concepts of the multithresholding method and Otsu's method are combined together. The second proposed technique emphasizes on the process of touching character segmentation. In doing this, the bounding box analysis is initially employed to segment the document image into images of isolated characters and images of touching characters. The thinning algorithm is applied to extract the skeleton of the touching characters. Next, by using the junction points as the separation points, the skeleton of the touching characters is separated into several pieces. Finally, the separated pieces of the touching characters are put back to reconstruct two isolated characters. The proposed algorithm achieves an accuracy of 86.67%.
Does microfinance have an impact? Three quantitative approaches in rural areas of Bangladesh and Andhra Pradesh, India

Microfinance has attracted, since its inception at the end of the seventies, the attention of many people and institutions, both at academic and donor levels. However, evidence is mixed so far and no definitive conclusion has yet emerged with respect to the positive effects of microfinance, in part because of the great differences among the different microfinance schemes but also because of methodological issues. This work aims to add some further evidence to the impact debate, with three studies in two different rural areas from Bangladesh and India. The first study is based on the second round of a survey in Bangladesh undertaken by the World Bank. A Propensity Score Matching approach was chosen to study the impact of borrowing on household income and expenditures per capita. In this case positive impact can only be seen in extraordinary expenditures, in particular in house extensions and investments in houses and land, but not in current expenditures or food expenditures. The second and third studies analyse a dataset collected in five districts of Andhra Pradesh, India. The former tries to answer the question of whether borrowing from Self-Help groups (SHGs) has any effect on income and income per capita at household level. Pooled ordinary least squares and difference in differences approaches are used to that end. A significant impact is found in this study on income and income per capita. In the last empirical work the main interest is focused on the distributional impact, on the understanding that anti-poverty measures should be focused on households at the bottom tail of income and income per capita distributions. Its analysis is based on quantile regression, with cross sectional and panel data approaches. Distributional impact shows, however, that the poorest might not be benefitting from these interventions as much as better-off or not-so-poor households
Comparing Backward Dispersion Scores

Our distance-score methodology for constructing backward-dispersion scores is an improvement over the counting methodology that the Hall, et al. (2001) measures use because (a) it captures the effects of newly-synthesized technological-class codes that are different than the technology-class codes of a focal patent’s claims, and (b) it adjusts for dynamics in technological convergence that we track over time. Our backward-dispersion V-Score is positively-related to return on assets, return on sales and costs per patents. Results show that the backward-dispersion score of Hall, et al. (2001) has negative relationships with return on assets, return on sales and is not significant in our tests of costs per patent. Both versions of the backward-dispersion score have negative relationships with Tobin’s q ratios ― a result which may indicate that investors are not as eager to bet on the rewards of out-of-the box inventions within the communications-services industry as some managers are.
Interpreting asymmetries of projection in children's inductive reasoning

1 2/8/2006 Interpreting Asymmetries of Projection in Children’s Inductive Reasoning Douglas L. Medin and Sandra Waxman Northwestern University I. Introduction Like adults, children use categories as a basis for inductive inference. Having learned that some property is true of some individual (e.g., “My dog, Magic, likes marshmallows”), a child might assume both that other members of the same category (dogs) share this property and that members of other, similar categories (e.g. cats) might also share this property. In short, inductive inference may be guided by and reflect categorical relationships, hence the term, category –based induction or CBI. Cognitive and developmental researchers have used this paradigm to not only to study the use of categories in reasoning but also to draw inferences from patterns of reasoning about the nature of conceptual structures themselves (Carey, 1985, Keil, Inagaki & Hatano, 2002; Hatano & Inagaki, 1994; Johnson & Carey, 1998; Gutheil, et al, 2004; Atran et al, 2001, Ross et al 2003.; Gelman & Markman, 1986; Waxman et al., 1997). One of the most influential examples of the use of pattern of inductive project to draw inferences about conceptual organization comes from research in the domain of folkbiology involving categories of living things, including humans, non-human animals, and plants. Developmental evidence has revealed, in particular, certain systematic
Amplified B Lymphocyte CD40 Signaling Drives Regulatory B10 Cell Expansion in Mice

Background Aberrant CD40 ligand (CD154) expression occurs on both T cells and B cells in human lupus patients, which is suggested to enhance B cell CD40 signaling and play a role in disease pathogenesis. Transgenic mice expressing CD154 by their B cells (CD154TG) have an expanded spleen B cell pool and produce autoantibodies (autoAbs). CD22 deficient (CD22−/−) mice also produce autoAbs, and importantly, their B cells are hyper-proliferative following CD40 stimulation ex vivo. Combining these 2 genetic alterations in CD154TGCD22−/− mice was thereby predicted to intensify CD40 signaling and autoimmune disease due to autoreactive B cell expansion and/or activation. Methodology/Principal Findings CD154TGCD22−/− mice were assessed for their humoral immune responses and for changes in their endogenous lymphocyte subsets. Remarkably, CD154TGCD22−/− mice were not autoimmune, but instead generated minimal IgG responses against both self and foreign antigens. This paucity in IgG isotype switching occurred despite an expanded spleen B cell pool, higher serum IgM levels, and augmented ex vivo B cell proliferation. Impaired IgG responses in CD154TGCD22−/− mice were explained by a 16-fold expansion of functional, mature IL-10-competent regulatory spleen B cells (B10 cells: 26.7×106±6 in CD154TGCD22−/− mice; 1.7×106±0.4 in wild type mice, p<0.01), and an 11-fold expansion of B10 cells combined with their ex vivo-matured progenitors (B10+B10pro cells: 66×106±3 in CD154TGCD22−/− mice; 6.1×106±2 in wild type mice, p<0.01) that represented 39% of all spleen B cells. Conclusions/Significance These results demonstrate for the first time that the IL-10-producing B10 B cell subset has the capacity to suppress IgG humoral immune responses against both foreign and self antigens. Thereby, therapeutic agents that drive regulatory B10 cell expansion in vivo may inhibit pathogenic IgG autoAb production in humans.
Exploring the Social Network Relationships on Hostility Behaviors

How to determine who is the one that you are willing to express your emotion? Emotion expression and behavior responses are highly related to the subjective judgment of the target user, especially the negative emotions (e.g., anger/ hostility). This study is to explore how the hostility dimensions are distributed in various relationship types, including power-dependences, closeness distance, mutual expectations, and cooperation/competition. This study used semi-structured in-depth interviews for a six-minute anger recall task that asked the participants to recall and report an anger event that happened in the past six months. There were 75 participants recruited to attend this study. The results indicate the dynamic social network types of power-dependences, closeness distance, and cooperation/competition are key factors to impact negative emotional behaviors and determine the hostility behaviors significantly. Although mutual expectations could also leads to higher anger level, but there is no significant difference on statistic analysis.
Facial expression classification using Support Vector Machine based on bidirectional Local Binary Pattern Histogram feature descriptor

In this paper, two class emotion detection and multi class facial expression classification using Support Vector Machine (SVM) is presented. Facial feature vectors in dual form are obtained using Local Binary Pattern (LBP) Histogram by tracing the bins in clockwise and anticlockwise direction. The Histogram feature descriptors are calculated from LBP images in dual form which are then concatenated to obtain features of complete face image. The proposed algorithm is tested using standard Japanese Female Facial Expression Database and Taiwanese facial Expression Database and results are verified using locally developed Indian face database of students. The proposed algorithm significantly outperforms the classical LBP based algorithms.
University-industry technological links in Malaysia: commercialisation of university research

In Malaysia, university-industry links, particularly through commercialisation of research results, has been put higher in the national science and technology policy agenda since the mid1990s. University-industry links feature significantly in a series of development plans and policy documents over the past decade, including Knowledge-based Economy Master Plan and Second National Science and Technology Policy and Plan of Action (ISIS, 2002; MOSTE, 2003). Closer relationships between universities and industry, especially in research and technological activities, had been encouraged by the government in the belief that they can enhance the nation's competitiveness by promoting innovative activities in industry and entrepreneurial activities in universities; and by improving the nation's indigenous technological capability and capacity. Commercialisation of research results, in particular, can contribute directly to the creation of wealth and economic development.
An intelligent admission control scheme for next generation wireless systems using distributed genetic algorithms

A different variety of services requiring different levels of quality of service (QoS) need be addressed for mobile users of the next generation wireless system (NGWS). An efficient handoff technique with intelligent admission control can accomplish this aim. In this paper, a new, intelligent handoff scheme using distributed genetic algorithms (DGA) is proposed for NGWS. This scheme uses DGA to achieve high network utilization, minimum cost and handoff latency. A performance analysis is provided to assess the efficiency of the proposed DGA scheme. Simulation results show a significant improvement in handoff latencies and costs over traditional genetic algorithms and other admission control schemes.
Murine Splenic Natural Killer Cells Do Not Develop Immunological Memory after Re-Encounter with Mycobacterium bovis BCG

Several lines of evidence have recently suggested that natural killer (NK) cells develop immunological memory against viral infections. However, there is no apparent evidence that NK cells acquire specific memory against Mycobacterium bovis bacillus Calmette—Guérin (BCG), the only currently licensed vaccine for preventing tuberculosis. In the present study, we investigated whether murine splenic NK cells can be activated by BCG in a dendritic cell (DC)-independent or -dependent manner, and furthermore examined whether these NK cells acquire specific memory following BCG vaccination. NK cells isolated from spleens of BCG-immunized mice produced interferon (IFN)γ through direct BCG stimulation in the absence of antigen-presenting cells; however, NK cells from control animals similarly directly responded to BCG, and the response level was not statistically significant between the immunized and the naïve NK cells. When purified NK cells that had been exposed to BCG were cocultured with RAW murine macrophages infected with BCG, the antibacterial activity of the macrophages was strongly enhanced; however, its level was similar to that by naïve NK cells, which had not been exposed to BCG. When splenocytes harvested from BCG-immunized mice were stimulated with purified protein derivative (PPD) derived from Mycobacterium tuberculosis, a specific IFNγ response was clearly observed, mainly attributed to NK cells and memory CD4+ T cells. To investigate whether these NK cells as well as the T cells are activated by cell−cell interaction with DCs presenting mycobacterial antigens, NK cells isolated from BCG-immunized mice were cocultured with splenocytes harvested from naïve mice in the presence of PPD stimulation. However, no IFNγ response was found in the NK cells. These results suggest that murine splenic NK cells do not develop BCG-specific immunological memory in either a DC-independent or -dependent manner.
Protected Organic Acid Blends as an Alternative to Antibiotics in Finishing Pigs

A total of 120 finishing pigs ([Yorkshire×Landrace]×Duroc) with an average body weight (BW) of 49.72 ±1.72 kg were used in 12-wk trial to evaluate the effects of protected organic acids on growth performance, nutrient digestibility, fecal micro flora, meat quality and fecal gas emission. Pigs were randomly allotted to one of three dietary treatments (10 replication pens with 4 pigs per pen) in a randomly complete block design based on their initial BW. Each dietary treatment consisted of: Control (CON/basal diet), OA1 (basal diet+0.1% organic acids) and OA2 (basal diet+0.2% organic acids). Dietary treatment with protected organic acid blends linearly improved (p<0.001) average daily gain during 0 to 6 week, 6 to 12 week as well as overall with the increase in their inclusion level in the diet. The dry matter, N, and energy digestibility was higher (linear effect, p<0.001) with the increase in the dose of protected organic acid blends during 12 week. During week 6, a decrease (linear effect, p = 0.01) in fecal ammonia contents was observed with the increase in the level of protected organic acid blends on d 3 and d 5 of fermentation. Moreover, acetic acid emission decreased linearly (p = 0.02) on d7 of fermentation with the increase in the level of protected organic acid blends. During 12 weeks, linear decrease (p<0.001) in fecal ammonia on d 3 and d 5 and acetic acid content on d 5 of fermentation was observed with the increase in the level of protected organic acid blends. Supplementation of protected organic acid blends linearly increased the longissimus muscle area with the increasing concentration of organic acids. Moreover, color of meat increased (linear effect, quadratic effect, p<0.001, p<0.002 respectively) and firmness of meat showed quadratic effect (p = 0.003) with the inclusion of increasing level of protected organic acid in the diet. During the 6 week, increment in the level of protected organic acid blends decreased (linear effect, p = 0.01) Escherichia coli (E. coli) counts and increased (linear effect, p = 0.004) Lactobacillus counts. During 12-wk of experimental trial, feces from pigs fed diet supplemented with organic acid blends showed linear reduction (p<0.001) of E. coli counts and the tendency of linear increase (p = 0.06) in Lactobacillus count with the increase in the level of organic acid blends. In conclusion, 0.2% protected organic acids blends positively affected growth performance, nutrient digestibility, fecal gas emission and meat quality in finishing pigs without any adverse effects on blood parameters.
Bandwidth-satisfied multicast routing in wireless mesh networks

Wireless mesh network (WMN) has recently emerged as a promising technology for next-generation wireless network. In WMNs, many important applications, such as audio/video conferencing and distance education, require the support of multicast communication with quality-of-service (QoS) guarantee. In this paper, we investigate the issues of QoS multicast routing in wireless mesh networks. The paper studies TDMA-based timeslot allocation, and presents an effective heuristic algorithm for calculating end-to-end bandwidth on a path. We also propose a novel source-based multicasting routing algorithm to build a multicast tree among all the multicast members. Simulation results show that compared with MAODV, our proposed QoS routing algorithm can significantly improve the performance of QoS multicast routing in WMNs in terms of success ratio and network cost.
A Reliable Protocol for In situ microRNAs Detection in Feeding Sites Induced by Root-Knot Nematodes

Galls induced by Meloidogyne spp. in plant roots are a complex organ formed by heterogeneous tissues; within them there are 5–8 giant cells (GCs) that root-knot nematodes use for their own nurturing. Subtle regulatory mechanisms likely mediate the massive gene repression described at early infection stages in galls, particularly in giant cells. Some of these mechanisms are mediated by microRNAs (miRNAs); hence we describe a reliable protocol to detect miRNAs abundance within the gall tissues induced by Meloidogyne spp. Some methods are available to determine the abundance of specific miRNAs in different plant parts; however, galls are complex organs formed by different tissues. Therefore, detection of miRNAs at the cellular level is particularly important to understand specific regulatory mechanisms operating within the GCs. In situ hybridization (ISH) is a classical, robust and accurate method that allows the localization of specific RNAs directly on plant tissues. We present for the first time an adapted and standardized ISH protocol to detect miRNAs in GCs induced by nematodes based on tissue embedded in paraffin and on-slide ISH of miRNAs. It can be adapted to any laboratory with no more requirements than a microtome and an optical microscope and it takes 10 days to perform once plant material has been collected. It showed to be very valuable for a quick detection of miRNAs expression pattern in tomato. We tested the protocol for miR390, as massive sequencing analysis showed that miR390 was induced at 3 dpi (days post-infection) in Arabidopsis galls and miR390 is 100% conserved between Arabidopsis and tomato. Successful localization of miR390 in tomato GCs constitutes a validation of this method that could be easily extended to other crops and/or syncytia induced by cyst nematodes. Finally, the protocol also includes guidance on troubleshooting.
PATH MATRIX USING LINEAR CONGESTION TO INCREASE THE QUALITY OF SERVICE THROUGH WARSHALS ALGORITHM

-In this paper a practically efficient quality of service algorithm is proposed . Here we have a WARSHALS CONGESTION BASED algorithm for congestion path matrix to be retrieved . The algorithm provides the shortest congestion path matrix due to the congestion that is available in between the different vertex . The algorithm provides an alternate solution to the problem available using constant congestion constants and finding an optimal path matrix based over the congestion occurring over the graph. **
sv(M)kmeans: a hybrid feature selection technique for reducing false positives in network anomaly detection

Feature Selection in large multi-dimensional data sets is becoming increasingly important for several real world applications. One such application, used by network administrators, is Network Intrusion Detection. The major problem with anomaly based intrusion detection systems is high number of false positives. Motivated by such a requirement, we propose sv(M)kmeans: a two step hybrid feature selection technique. The proposed technique applies classification on false-positives and true positives; and on false-positives and true-negatives after an initial round of clustering. Specifically, SVM-RFE is applied on the results obtains from MK-Means. sv(M)kmeans is evaluated for its real world applicability using the benchmark NSL-KDD data set. We show the feature subset to significantly reduce the false positive rate and increase the accuracy in network anomaly detection.