Miracle-dz/UniFAR-FTUs huggingface dataset:
IMPACT OF A PROFESSIONAL DEVELOPMENT PROGRAM FOR AGRICULTURAL EDUCATION TEACHERS IN COSTA RICA

The purpose of this study was to assess the impact of a professional development program for agricultural education teachers in Costa Rica. This time series follow-up study assessed the impact of a five-day workshop that focused on agricultural and environmental topics at three points over a two-month period. The 13 participants in the workshop served as the population-sample. The results revealed that the workshop was beneficial to the participants. A majority of the participants felt “slightly prepared” or “better prepared” to teach the content to their students upon completion of the workshop. Participants reported that the lesson plans developed at the workshop were helpful and that they planned to use them. A majority of the participants felt “slightly prepared” or “better prepared” to share the workshop contents with their colleagues, and most of them had done so in some manner within two months after the workshop. Theoretical Framework Fifty-one agricultural high schools were started in Costa Rica in the 1970s. These schools officially called “Colegios Tecnicos Profesionales Agropecuarios” (CTPAs) were part of a larger system of technical high schools established throughout the country (Crawford & Gonzalez, 1978). Each CTPA provided the students with a basic education and a vocational education focus in agriculture as part of a plan to increase agricultural production nationally (World Bank, 1985). In 1992, the Costa Rican Ministry of Public Education initiated a new curriculum for the CTPAs to reflect changes in agriculture to be implemented by 1994. In addition to agricultural technology, the new curriculum emphasized agricultural diversification, sustainable agriculture, and preparation for employment in the service sector (Ministerio de Educacion Publica, 1992).
AES presidential address mind-body problems

In this article, I lay out some of the cultural assumptions in recent accounts of mind and brain in neuroscience, in which it is argued that human social activities can be reduced to neural processes in the brain. Since the current dominance of these accounts in the United States threatens the work of social and cultural anthropology and other non-reductionist disciplines, I develop some ways the arguments of their critics can be bolstered with insights from anthropology. I ask what social features of the present context could be inciting this turn to a hyper-rational, neuronal account of human consciousness, and explore fear of the newly valued irrational energy (akin to mania) often required by contemporary entrepreneurial capitalism as a possible source. To counter the forms of individual subjectivity encouraged by neuroreductionism, I argue that ethnography could contribute to a form of subjectivity that renders individuals thinkable only as social beings, [language, metaphor, cognitive science, neuroscience, manic depression, stock market, capitalism, United States]
An evaluation of automatic parameter tuning of a statistics‐based anomaly detection algorithm

We investigate an automatic and dynamic parameter tuning of a statistical method for detecting anomalies in network traffic (this tuning is referred to as parameter learning) towards real‐time detection. The main idea behind the dynamic tuning is to predict an appropriate parameter for upcoming traffic by considering the detection results of past τ traces of traffic. The τ is referred to as the learning period, and we discuss in particular the appropriate value of τ. This automatic tuning scheme is applied to parameter setting of an anomaly detection method based on Sketch and the multi‐scale gamma model, which is an unsupervised method and does not need predefined data. We analyze the tuning scheme with real traffic traces measured on a trans‐Pacific link over 9 years (15 min from 14:00 Japan Standard Time every day, and 24 consecutive hours for some dates on the same link). The detection results with parameter prediction are compared to those with ideal parameters that maximize the detection performance for upcoming traffic. We also analyze predictability of the ideal parameter considering the past changes in it. The main findings of this work are as follows: (1) the ideal parameter fluctuates day by day; (2) parameter learning with a longer τ is affected by significant events included in the period, and the appropriate τ is about three traces (days) for everyday 15 min traces and around 1.5 h for 24 h traces; (3) the degradation in detection performance caused by introducing parameter learning is 17% with τ = 3 for everyday 15 min traces; (4) the changes in the ideal parameter have no periodic correlation, and can be modeled as a random process followed by a normal distribution. We show that one cannot consistently use a fixed parameter in statistics‐based algorithms to detect anomalies in practice. Copyright © 2010 John Wiley & Sons, Ltd.
Optimizing Visual Search Reranking via Pairwise Learning

Visual search reranking is defined as reordering visual documents (images or video clips) based on the initial search results or some auxiliary knowledge to improve the search precision. Conventional approaches to visual search reranking empirically take the “classification performance” as the optimization objective, in which each visual document is determined relevant or not, followed by a process of increasing the order of relevant documents. In this paper, we first show that the classification performance fails to produce a globally optimal ranked list, and then we formulate reranking as an optimization problem, in which a ranked list is globally optimal only if any arbitrary two documents in the list are correctly ranked in terms of relevance. This is different from existing approaches which simply classify a document as “relevant” or not. To find the optimal ranked list, we convert the individual documents to “document pairs,” each represented as a “ordinal relation. ” Then, we find the optimal document pairs which can maximally preserve the initial rank order while simultaneously keeping the consistency with the auxiliary knowledge mined from query examples and web resources as much as possible. We develop two pairwise reranking methods, difference pairwise reranking (DP-reranking) and exclusion pairwise reranking (EP-reranking), to obtain the relevant relation of each document pair. Finally, a round robin criterion is explored to recover the final ranked list. We conducted comprehensive experiments on an automatic video search task over TRECVID 2005-2007 benchmarks, and showed consistent improvements over text search baseline and other reranking approaches.
Personality Traits Predict Current and Future Functioning Comparably for Individuals With Major Depressive and Personality Disorders

Axes I and II were separated in DSM-III to encourage the consideration of the influence of both personality and psychopathology on patient behavior, on the assumption that an understanding of personality would increment syndromal diagnosis in treatment decisions. However, in practice the distinction between Axis I and Axis II is less clear. The current report investigates one aspect on which Axis I and Axis II might be expected to differ, that being the the significance of normative personality traits as an influence on functional status. In this study, the contribution of normative personality traits to functioning is presented for 2 groups of patients, one with major depression and a second with personality disorders. The data suggest that personality traits are significant and equally relevant predictors of functioning for both groups. The utility of assessing personality traits for individuals with both Axis I and II disorders is thus supported.
Design of an exact data deduplication cluster

Data deduplication is an important component of enterprise storage environments. The throughput and capacity limitations of single node solutions have led to the development of clustered deduplication systems. Most implemented clustered inline solutions are trading deduplication ratio versus performance and are willing to miss opportunities to detect redundant data, which a single node system would detect. We present an inline deduplication cluster with a joint distributed chunk index, which is able to detect as much redundancy as a single node solution. The use of locality and load balancing paradigms enables the nodes to minimize information exchange. Therefore, we are able to show that, despite different claims in previous papers, it is possible to combine exact deduplication, small chunk sizes, and scalability within one environment using only a commodity GBit Ethernet interconnect. Additionally, we investigate the throughput and scalability limitations with a special focus on the intra-node communication.
ACE: A Framework for Optimizing Music Classification

This paper presents ACE (Autonomous Classification Engine), a framework for using and optimizing classifiers. Given a set of feature vectors, ACE experiments with a variety of classifiers, classifier parameters, classifier ensembles and dimensionality reduction techniques in order to arrive at a good configuration for the problem at hand. In addition to evaluating classification methodologies in terms of success rates, functionality is also being incorporated into ACE allowing users to specify constraints on training and classification times as well as on the amount of time that ACE has to arrive at a solution. ACE is designed to facilitate classification for those new to pattern recognition as well as provide flexibility for those with more experience. ACE is packaged with audio and MIDI feature extraction software, although it can certainly be used with existing feature extractors. This paper includes a discussion of ways in which existing general-purpose classification software can be adapted to meet the needs of music researchers and shows how these ideas have been implemented in ACE. A standardized XML format for communicating features and other information to classifiers is proposed. A special emphasis is placed on the potential of classifier ensembles, which have remained largely untapped by the MIR community to date. A brief theoretical discussion of ensemble classification is presented in order to promote this powerful approach.
CO2 Pneumoperitoneum Preserves β-Arrestin 2 Content and Reduces High Mobility Group Box-1 (HMGB-1) Expression in an Animal Model of Peritonitis

Laparoscopy (LS) has been shown to decrease the inflammatory sequelae of endotoxemia. β-arrestin 2 plays an important function in signal transduction pathway of TLR4. High mobility group box-1 (HMGB-1) is involved in the delayed systemic inflammatory response. We investigated the effects of CO2 insufflation on liver, lung, and kidney expression of both β-arrestin 2 and HMGB-1 during sepsis. Cecal ligation and puncture (CLP) was performed in male rats and 6 h later the animals were randomly assigned to receive a CO2 pneumoperitoneum or laparotomy. Animals were euthanized; liver, lung, and kidney were removed for the evaluation of β-arrestin 2 and HMGB-1 expression. Immunohistochemical detection of myeloperoxidase (MPO) was investigated in lung and liver and bacterial load was determined in the peritoneal fluid. CO2 pneumoperitoneum reduced peritoneal bacterial load, increased the expression of β-arrestin 2, and blunted the expression of the potent proinflammatory HMGB-1 in liver, lung, and kidney compared with laparotomy. Liver and lung MPO was markedly reduced in rats subjected to LS compared with laparotomy. We believe that CO2 exerts an early protective effect by reducing bacterial load and likely toll-like receptor activation which in turn leads to a preserved β-arrestin 2 expression and a reduced HMGB-1 expression.
Secondary relaxation in o-terphenyl glass.

We have measured the dielectric response, e(ω), in o-terphenyl due to the secondary relaxations that occur below the glass-transition temperature. We have found that the imaginary part of e(ω) has a log-normal shape that can be ascribed to a Gaussian distribution of barrier heights. The width of this distribution increases slightly as the temperature is lowered. The peak position shifts in an Arrhenius manner with temperature as was reported previously by Johari and Goldstein. The data appear to be of different origin from what has also been called β relaxation in mode-coupling theories and light-scattering experiments
Is use of the Nintendo Wii Fit in physiotherapy as effective as conventional physiotherapy training for hospitalised older adults?

While there has been wide uptake of the Nintendo Wii Fit as a therapy tool in hospital and aged care settings there is a lack of evidence regarding the effectiveness and safety of this approach when used with older people. This pilot study compared the effect of a physiotherapist providing activities from the Wii Fit with conventional therapy on mobility, activities of daily living and safety. The study used a randomized controlled design with masked outcome assessment. A total of 44 participants were recruited from a Geriatric Evaluation and Management (GEM) Unit and randomized to either therapy using the Wii Fit (n=22) or conventional physiotherapy (n=22). Therapy sessions were 25 minutes per workday for the duration of the participant's stay on the unit. Assessment measures were taken at baseline, post intervention (on discharge from the unit) and one month after discharge. The primary outcome used was the Timed Up and Go Test and additional measures included balance and activities of daily living function. Adverse events were recorded. Preliminary analyses of results showed that both groups improved however there was a small significant difference between groups on balance and the Timed Up and Go Test with the Wii Fit appearing to be a more effective approach to balance and mobility training in hospitalized older people.
Course in General Linguistics

Introduction to the Bloomsbury Revelations Edition Preface to the First Edition Preface to the Second Edition Preface to the Third Edition Editor's Introduction, Roy Harris Introduction 1. A Brief Survey of the History of Linguistics 2. Data and Aims of Linguistics: Connexions with Related Sciences 3. The Object of Study 4. Linguistics of Language Structure and Linguistics of Speech 5. Internal and External Elements of a Language 6. Representation of a Language by Writing 7. Physiological Phonetics Appendix: Principles of Physiological Phonetics 1. Sound Types 2. Sounds in Spoken Sequences Part One: General Principles 1. Nature of the Linguistic Sign 2. Invariability and Variability of the Sign 3. Static Linguistics and Evolutionary Linguistics Part Two: Synchronic Linguistics 1. General Observations 2. Concrete Entities of a Language 3. Identities, Realities, Values 4. Linguistic Value 5. Syntagmatic Relations and Associative Relations 6. The Language Mechanism 7. Grammar and Its Subdivisions 8. Abstract Entities in Grammar Part Three: Diachronic Linguistics 1. General Observations 2. Sound Changes 3. Grammatical Consequences of Phonetic Evolution 4. Analogy 5. Analogy and Evolution 6. Popular Etymology 7. Agglutination 8. Diachronic Units,Identities and Realities Appendices Part Four: Geographical Linguistics 1. On the Diversity of Languages 2. Geographical Diversity: Its Complexity 3. Causes of Geographical Diversity 4. Propagation of Linguistic Waves Part Five: Questions of Retrospective Linguistics Conclusion 1. The Two Perspectives of Diachronic Linguistics 2. Earliest Languages and Prototypes 3. Reconstructions 4. Linguistic Evidence in Anthropology and Prehistory 5. Language Families and Linguistic Types Index
HLA‐A2 class I antigens in couples with recurrent spontaneous abortions

Class I human leukocyte antigen (HLA) antigens, locus A and B, were typed in fertile and infertile couples in cases where one of the spouses carried the HLA‐A2 antigen. HLA‐class I typing data were obtained from 282 participants, 63 fertile couples and 78 infertile couples with recurrent spontaneous abortions (RSA). Locus A antigens were grouped into eight broad specificities (A1, A2, A3, A9, A10, A11, A19, A28) and locus B antigens were grouped, according to HLA epitopes, in two classes (BW4 and BW6). Although the number of cases is small, significant differences in the distribution of locus A antigens were found between HLA‐A2–positive (A2+) women from fertile and infertile couples. HLA‐A3, A11 and A28 cross‐reacting antigens were absent in women from fertile couples and present in women from infertile couples. HLA‐A19, which is associated with amino acid triplets of low immunogenicity, was significantly more often observed in A2+ fertile than in infertile women. An excess of the BW4 epitope was found in A2− husbands from infertile couples compared to fertile ones. The results of this study support the idea that in the presence of the HLA‐A2 molecule the distribution of HLA‐A and B loci antigens may be different in fertile couples compared to couples with recurrent spontaneous abortions. It can be suggested that the HLA‐A2 molecule, in context with specific genotypes, may contribute to the overall maternal immune response in normal and disturbed pregnancy.
A Grid-facilitated AIS-based Network Scheme for Many-objective Optimization

Artificial Immune Systems (AIS), one of the promising artificial intelligence methods, has been widely adopted in the optimization domain. However, their application to many-objective domain is rather scattered. In this respect, we extend the AIS-based algorithm to many-objective situations using the immune network theory facilitated by the grid technique. The network operations are employed not only for managing the diversity, but also to strengthen the exploitation and exploration pressure. The suppression-triggered activation and the archive-driven activation are both introduced in this study to exploit the promising region and to explore along the local Pareto-front. In addition, Grid technique is introduced to reduce the computation complexity in the identification process of the sensory range. Coupled with the grid-facilitated network scheme, the proposed algorithm improves the exploitation and exploration capability in many-objective optimization problem.
Prion Replication in the Hematopoietic Compartment Is Not Required for Neuroinvasion in Scrapie Mouse Model

Fatal neurodegenerative prion diseases are caused by the transmissible PrPSc prion agent whose initial replication after peripheral inoculation takes place in follicular dendritic cells present in germinal centers of lymphoid organs. However, prion replication also occurs in lymphoid cells. To assess the role of the hematopoietic compartment in neuroinvasion and prion replication, we generated chimeric mice, on a uniform congenic C57/BL6J background, by bone marrow replacement with hematopoietic cells expressing different levels of PrP protein. Nine different types of chimeric mice were inoculated intraperitoneally either with the lymphotropic Rocky Mountain Laboratory (RML) strain or the non lymphotropic ME-7 scrapie strain, at different doses. Here, we clearly demonstrate that overexpression of PrP by the hematopoietic system, or the lack of PrP expression by the bone marrow derived cells, does not change the incubation time period of the disease, even when the mice are infected at limiting doses. We conclude that the hematopoietic compartment is more or less permissive to prion replication, both for RML and ME-7, but does not play a role in neuroinvasion.
Interactive Exploration of Developer Interaction Traces using a Hidden Markov Model

Using IDE usage data to analyze the behavior of software developers in the field, during the course of their daily work, can lend support to (or dispute) laboratory studies of devel- opers. This paper describes a technique that leverages Hidden Markov Models (HMMs) as a means of mining high-level developer behavior from low-level IDE interaction traces of many developers in the field. HMMs use dual stochastic processes to model higher-level hidden behavior using observable input sequences of events. We propose an interactive approach of mining interpretable HMMs, based on guiding a human expert in building a high quality HMM in an iterative, one state at a time, manner. The final result is a model that is both representative of the field data and captures the field phenomena of interest. We apply our HMM construction approach to study debugging behavior, using a large IDE interaction dataset collected from nearly 200 developers at ABB, Inc. Our results highlight the different modes and constituent actions in debugging, exhibited by the developers in our dataset.
The hierarchical linear relationship among structured on-the-job training activities, trainee characteristics, trainer characteristics, training environment characteristics, and organizational characteristics of workers in small and medium-sized enterprises

The purpose of this study was to identify the hierarchical linear relationship among structured on-the-job training (S-OJT) activities, trainee characteristics, trainer characteristics, training environment characteristics, and organizational characteristics of workers in small and medium-sized enterprises (SMEs). A total of 296 questionnaires from trainees and 70 questionnaires from trainers from 70 SMEs were used for the hierarchical linear modelling analysis. The major conclusions of this study were as follows: first, the level of S-OJT activities is differentiated according to organizations and such differences are caused by skilled trainers, training environment, and organizational context as well as trainees’ individual characteristics. Second, the level of S-OJT activities becomes higher when workers in SMEs meet their job requirements and the rewards from the job matching their needs. Further, the level of S-OJT activities is strengthened by the intrinsic characteristics of learning agility and self-efficacy of the workers’ active learning in strange work environments. Third, the S-OJT activities are facilitated when trainers try to share and deliver their expertise with pride and self-esteem for training activities rather than with monetary rewards alone. Fourth, the S-OJT activities are facilitated when organizations provide both physical and psychological supports in order to achieve the training goals.
Geometrical Feature Extraction for Cuneiforms

Cuneiform writing is one of the earliest methods of writing in human history. It is based on pressing a stylus (reed) on clay tablets, resulting in wedge marks (cuneiforms) which, when combined, provide meaningful symbols. Applying modern machine learning methods to the study of ancient cuneiform tablets is a fascinating task. In the present paper we describe a method for extracting geometrical features of the wedges imprinted by the stylus that is used for writing. We introduce two independent feature extraction methods to describe the wedges. The data for this study come from precise optical scans of three tablets, originating from different historical periods. We use these tablets to demonstrate the validity of our extracted features, and to demonstrate the accuracy of classifying the different tablets.
Sediment Bioassays for NAVSTA San Diego Dredging Project.

Abstract : Bioassays were conducted on sediments from 13 sites associated with Navy activities in San Diego Bay using liquid, particulate, and solid phase test solutions. Sediments were pre-sampled to determine the most contaminated area at each site based on the relative concentration of cadmium, chromium, copper, and mercury. Five different marine species representing a variety of phylogenetic levels and feeding types were used in the toxicity tests with the most contaminated sediments including copepods, mysids, fish, clams, and worms. The results of the bioassays suggest that dredged material from Navy Piers 1, 2, 3, 4, 5, 6, 8, 10, 11, 12, 13, JK, and Chollas Creek Channel should not have a significantly adverse effect on the marine environment during disposal operations. (Author)