Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECTIVENESS OF LESSON PLAN INSTRUMENTS ON LIVING CREATURES INTERACTIONS WITH ITS ENVIRONMENT THROUGH GUIDED INQUIRY BASED LEARNING

A survey result by Programme for International Student Assessment (PISA) in 2015 shows that Indonesia students are ranked on 62 of 70 countries on the natural science subject. On average, Indonesian students still have problems on answering questions that require the critical thinking ability. The Lesson Plan used by the teachers is in line with the 2013 Curriculum but shows no sign of developing the critical thinking ability and the learning results on the students. This research aims to determine the effectiveness of lesson plan set on the subject matter of living creatures’ interactions with its environment. This research used the Tessmer Model with the steps of self-evaluations, experts’ opinions, individual tests, small groups tests, and field tests as the research’s focus. The subjects are VII grade students of SMP Negeri 1 KertakHanyar . Data types including 1) critical thinking ability result, 2) cognitive learning result, 3) attitude assessment result, and 4) ability assessment result. The results of critical thinking ability are analyzed using LKPD with the quantitative rubric, the results of cognitive learning through tests are analyzed based on Minimum Completeness Criteria, the results of attitude assessment are analyzed using attitude assessment rubric. The result of RPP set is considered effective based on 1) the critical thinking ability result of the students is categorized as high, 2) the students’ learning result passed the classical completeness of 75% of the students, 3) the attitude assessment result is categorized as good, and 4) the ability assessment result is categorized as good. Article visualizations:
Corpus and Voices for Catalan Speech Synthesis

In this paper we describe the design and production of Catalan database for building synthetic voices. Two speakers, with 10 hours per speaker, have recorded 10 hours of speech. The speaker selection and the corpus design aim to provide resources for high quality synthesis. The resources have been used to build voices for the Festival TTS. Both the original recordings and the Festival databases are freely available for research and for commertial use.
Web effort estimation: the value of cross-company data set compared to single-company data set

This study investigates to what extent Web effort estimation models built using cross-company data sets can provide suitable effort estimates for Web projects belonging to another company, when compared to Web effort estimates obtained using that company's own data on their past projects (single-company data set). It extends a previous study (S3) where these same research questions were investigated using data on 67 Web projects from the Tukutuku database. Since S3 was carried out, data on other 128 Web projects was added to Tukutuku; therefore this study uses the entire set of 195 projects from the Tukutuku database, which now also includes new data from other single-company data sets. Predictions between cross-company and single-company models are compared using Manual Stepwise Regression+Linear Regression and Case-Based Reasoning. In addition, we also investigated to what extent applying a filtering mechanism to cross-company datasets prior to building prediction models can affect the accuracy of the effort estimates they provide. The present study corroborates the conclusions of S3 since the cross-company models provided much worse predictions than the single-company models. Moreover, the use of the filtering mechanism significantly improved the prediction accuracy of cross-company models when estimating single-company projects, making it comparable to that using single-company datasets.
Robust GaN Successive-Detection Logarithmic Video-Amplifier for EW applications

An innovative Successive-Detection Logarithmic Video-Amplifier for EW applications is proposed in this contribution, and a design procedure is described. A chip has been designed to explore GaN features in this field, leading to a 55 dB input dynamic range over the 3-17 GHz frequency band, and a ±1.7 dB logarithmic error at 10 GHz, with a deviation of ±0.9 dB over the whole frequency range.
Interprofessional Caregiver Education, Training, and Wellness in the Context of a Cohort Model for Aphasia Rehabilitation

Patient-centered care is extending the sphere of health care beyond the patient, focusing attention upon the family caregiver(s). In this context, patient–family relationships are at the center of consistent, well-developed interprofessional interventions that encompass caregiver education, training, and wellness. Cohort models of intervention include groups of patients who start and stop a program or intervention simultaneously. One such cohort-based service delivery model is an intensive comprehensive aphasia program (ICAP), which provides an ideal context in which to address holistic care for the person with aphasia and his or her family caregivers. The interprofessional family caregiver intervention program of the ICAP at the University of Montana is twofold: (1) speech–language pathologists and graduate student clinicians in speech–language pathology provide family caregiver education and resources, communication training, and psychosocial support and (2) a licensed professional counselor and counselor-in-training provide group counseling for family caregivers focusing on personal wellness, caregiving strategies, emotional health, and adaptation to significant life changes. The fusion of equitable interprofessional collaboration, along with the cohort model of the ICAP, allows for acquisition of knowledge, communication strategies, and coping skills along with the development of close, meaningful relationships with other caregivers and persons with aphasia.
Unsupervised State-Space Modeling Using Reproducing Kernels

A novel framework for the design of state-space models (SSMs) is proposed whereby the state-transition function of the model is parametrized using reproducing kernels. The nature of SSMs requires learning a latent function that resides in the state space and for which input-output sample pairs are not available, thus prohibiting the use of gradient-based supervised kernel learning. To this end, we then propose to learn the mixing weights of the kernel estimate by sampling from their posterior density using Monte Carlo methods. We first introduce an offline version of the proposed algorithm, followed by an online version which performs inference on both the parameters and the hidden state through particle filtering. The accuracy of the estimation of the state-transition function is first validated on synthetic data. Next, we show that the proposed algorithm outperforms kernel adaptive filters in the prediction of real-world time series, while also providing probabilistic estimates, a key advantage over standard methods.
Property Rights and the Nature of the Firm

This paper provides a framework for addressing the question of when transactions should be carried out within a firm and when through the market. Following Grossman and Hart, we identify a firm with the assets that its owners control. We argue that the crucial difference for party 1 between owning a firm (integration) and contracting for a service from another party 2 who owns this firm (nonintegration) is that, under integration, party 1 can selectively fire the workers of the firm (including party 2), whereas under nonintegration he can "fire" (i.e., stop dealing with) only the entire firm: the combination of party 2, the workers, and the firm's assets. We use this idea to study how changes in ownership affect the incentives of employees as well as those of owner-managers. Our framework is broad enough to encompass more general control structures than simple ownership: for example, partnerships and worker and consumer cooperatives all emerge as speical cases.
A practitioner's approach to evolving and remodeling large-scale WWW sites

Addresses the issues of evolving large-scale Web sites, in order to migrate them to more flexible forms for developing and managing content and applications. We first present an integrated process model for the life-cycle of a Web site. Next, we focus on specific steps of this model in order to (i) examine a layered, next-generation architecture for large Web sites, providing for content reuse and easier implementation of services and applications, and (ii) discuss the activities of remodeling our existing content infrastructure and applications, according to the specifications of this target architecture. In our case study, we apply the new architecture, through the remodeling activities, in the evolution of the official Web site of the Hellenic Ministry of Culture.
High Corticosterone After Olfactory Social Stimuli in a Rodent Model of Traumatic Stress

Posttraumatic stress disorder (PTSD) is characterized by recurrent recollections and avoidance of the traumatic event and general hyperarousal that affect some victims of life-threatening events. In addition to the important application of animal fear conditioning paradigms in psychobiological studies of the mnemonic aspect of PTSD, special attention should be devoted to the exaggerated emotional and hormonal reactions to unconditioned stimuli, hallmarks of PTSD. Overreacting to harmless stimuli that do not bear resemblance to learned threats may be the result of a process of fear sensitization, which is vastly maladaptive and may interfere with daily life. It is argued that fear sensitization can possibly underpin the emergence of unconditioned behavioral disturbances seen in PTSD. Social withdrawal is also seen in PTSD, and physiological reactions may exacerbate behavioral avoidance to social situations. In this regard, we have evaluated fear conditioning and several behavioral indexes of fear sensitization, characteristic of posttraumatic stress in rats. We hypothesized that exposure to novel social stimuli might be associated with high hormonal levels in rats previously submitted to an unpredictable and inescapable highly intense electric footshock, a model of severe stress. We found that, in addition to a robust contextual fear conditioning and a consistent behavioral overreactive state, the hormonal responsiveness to a socioenvironmental stimulus was also exacerbated in rats exposed to the traumatic stress, compared with control rats. Our data corroborate previous studies showing affective sequalae in PTSD animal models and provide additional information on physiological reactions associated with traumatic stress in rats.
Note on Equivalence Between Recurrent Neural Network Time Series Models and Variational Bayesian Models

We observe that the standard log likelihood training objective for a Recurrent Neural Network (RNN) model of time series data is equivalent to a variational Bayesian training objective, given the proper choice of generative and inference models. This perspective may motivate extensions to both RNNs and variational Bayesian models. We propose one such extension, where multiple particles are used for the hidden state of an RNN, allowing a natural representation of uncertainty or multimodality.
Massive Support Vector Regression

The problem of tolerant data fitting by a nonlinear surface, induced by a kernel-based support vector machine [19], is formulated as a linear program with fewer number of variables than that of other linear programming formulations [17]. A generalization of the linear programming chunking algorithm [1] for arbitrary kernels [10] is implemented for solving problems with very large datasets wherein chunking is performed on both data points and problem variables. The proposed approach tolerates a small error, which is adjusted parametrically, while fitting the given data. This leads to improved fitting of noisy data as demonstrated computationally. Comparative numerical results indicate an average time reduction as high as 26.0%, with a maximal time reduction of 79.7%. Additionally, linear programs with as many as 16,000 data points and more than a billion nonzero matrix elements are solved.
WWW sits the SAT: Measuring Relational Similarity on the Web

Measuring relational similarity between words is important in numerous natural language processing tasks such as solving analogy questions and classifying noun-modifier relations. We propose a method to measure the similarity between semantic relations that hold between two pairs of words using a web search engine. First, each pair of words is represented by a vector of automatically extracted lexical patterns. Then a Support Vector Machine is trained to recognize word pairs with similar semantic relations. We evaluate the proposed method on SAT multiple-choice word-analogy questions. The proposed method achieves a score of 40% which is comparable with relational similarity measures which use manually created resources such as WordNet. The proposed method significantly reduces the time taken by previously proposed computationally intensive methods, such as latent relational analysis, to process 374 analogy questions from 8 days to less than 6 hours.
Identifying Global Common Concepts of DBpedia Ontology to Enhance Multilingual Ontologized Space Expansion

The amount of data on the Web has recently increased, accompanied by a paradigm shift from the publishing of isolated data to the publishing of interlinked data. Linked Open Data (LOD) provides structured access and enables the easy extension of knowledge, thus allowing data from different knowledge sources to be connected. However, the vocabularies used in LOD are biased toward English. Moreover, the DBpedia ontology, a prominent multilingual ontology regarded as a de facto reference vocabulary because of its popularity, has limitations as a multilingual mediator. The DBpedia ontology is built using only the English Wikipedia, leading to the limitation of other languages’ adaptation of the DBpedia ontology to local language knowledge resources. This paper aims to identify highly reusable concepts of the DBpedia ontology by using different rank aggregations across various editions of Wikipedia and DBpedia. The proposed method is called “concept significance rank aggregation across languages” (CS-RAL). CS-RAL takes as its inputs an ontology and its knowledge sources and computes the consensus rank of the concepts of the ontology based on the harmonization of different language-created knowledge sources. Experimental results demonstrate that CS-RAL identifies a significant part of the DBpedia ontology for different languages.
CX3CR1-Fractalkine Expression Regulates Cellular Mechanisms Involved in Adhesion, Migration, and Survival of Human Prostate Cancer Cells

Chemokines and their receptors might be involved in the selection of specific organs by metastatic cancer cells. For instance, the CXCR4-SDF-1α pair regulates adhesion and migration of breast as well as prostate cancer cells to metastatic sites. In this study, we present the first evidence for the expression of CX3CR1—the specific receptor for the chemokine fractalkine—by human prostate cancer cells, whereas human bone marrow endothelial cells and differentiated osteoblasts express fractalkine. The adhesion of prostate cancer cells to human bone marrow endothelial cells in flow conditions is significantly reduced by a neutralizing antibody against fractalkine, and they migrate toward a medium conditioned by osteoblasts, which secrete the soluble form of the chemokine. Finally, fractalkine activates the PI3K/Akt survival pathway in human prostate cancer cells.
Super VLAN Technique Applied to Network Reform

With the Internet and Intranet popularization and the broadband technology development, the number of network node in large and medium-scale enterprise's network or university's network is increasingly swift increase. But, network virus and attacks, especially, such as network loop, ARP spoofing and DHCP attack result in network fault frequently happened, even cause network paralysis. For solving these troubles, it not only consumes a lot of time and manpower of network management department, and but also delays user to use network. Thus, the network management department hopes to overcome and solve these problems as possibly by optimizing and reforming network architecture. The paper simply describes advantage and disadvantage of network architecture with layer 2 and layer 3 switch technologies, and compares several often used reform methods. In allusion to the layer 3 network architecture used by most LAN, the paper especially illustrates the predominance of adopting Super VLAN technology to reform traditional network architecture. The practice proves that the solution with Super VLAN technology not only solves the problems but also saves cost and engineering quantity, at the same time, protects the profit of previous investment.
A fast string searching algorithm

An algorithm is presented that searches for the location, “<italic>i</italic>l” of the first occurrence of a character string, “<italic>pat</italic>,” in another string, “<italic>string</italic>. ” During the search operation, the characters of <italic>pat</italic> are matched starting with the last character of <italic>pat</italic>. The information gained by starting the match at the end of the pattern often allows the algorithm to proceed in large jumps through the text being searched. Thus the algorithm has the unusual property that, in most cases, not all of the first <italic>i</italic> characters of <italic>string</italic> are inspected. The number of characters actually inspected (on the average) decreases as a function of the length of <italic>pat</italic>. For a random English pattern of length 5, the algorithm will typically inspect <italic>i</italic>/4 characters of <italic>string</italic> before finding a match at <italic>i</italic>. Furthermore, the algorithm has been implemented so that (on the average) fewer than <italic>i</italic> + <italic>patlen</italic> machine instructions are executed. These conclusions are supported with empirical evidence and a theoretical analysis of the average behavior of the algorithm. The worst case behavior of the algorithm is linear in <italic>i</italic> + <italic>patlen</italic>, assuming the availability of array space for tables linear in <italic>patlen</italic> plus the size of the alphabet. 3~
Research on distributed data skew join algorithm based on VGFR model

The join operation is one of the core content of complex analysis tasks dealing with massive data. How to dealing with the data skew occurred in the join process effectively is a big challenge to us. But join algorithm based on the fragment and replicate in the current Shared-Nothing distributed architecture, which on the one hand, introduced a large data transmission overhead when a large amount of data is used to copy, the other hand, can not be adjusted dynamically according to the real-time load. In this paper, we propose and implement a grouping fragment and replicate join strategy based on virtual node (VGFR), aimed at robustness in terms of the size of both join sides. at the same time, the mapping relationship between virtual node and actual node is dynamically determined according to the system's real-time load, which can not only solve the problem of data skew effectively but also guarantee load balancing capability of the fine grained. Experimental results demonstrate that the optimizationThe join operation is one of the core content of complex analysis tasks dealing with massive data. How to dealing with the data skew occurred in the join process effectively is a big challenge to us. But join algorithm based on the fragment and replicate in the current Shared-Nothing distributed architecture, which on the one hand, introduced a large data transmission overhead when a large amount of data is used to copy, the other hand, can not be adjusted dynamically according to the real-time load. In this paper, we propose and implement a grouping fragment and replicate join strategy based on virtual node (VGFR), aimed at robustness in terms of the size of both join sides. at the same time, the mapping relationship between virtual node and actual node is dynamically determined according to the system's real-time load, which can not only solve the problem of data skew effectively but also guarantee load balancing capability of the fine grained. Experimental results demonstrate that the optimization technique can improve the performance of join operation effectively and has the adaptability. technique can improve the performance of join operation effectively and has the adaptability.
Run-time Composition and Adaptation of Mismatching Behavioural Transactions

Reuse of software entities such as components or web services raise composition issues since, most of the time, they present mismatching behavioural interfaces. Here, we particularly focus on systems for which the number of transactions is unbounded, and unknown in advance. This is typical in pervasive systems where a new client may show up at any moment to request or access a specific service. Hence, we advocate for the use of the pi-calculus to specify component interfaces. The pi-calculus is particularly suitable for creating new component instances and channels dynamically. The unbounded number of transactions and the use of the pi-calculus obliges to apply the composition at run-time. In this paper, we propose a run-time composition engine that solves existing mismatches.
Imaging biomarkers in multiple sclerosis

Recent years have witnessed impressive advances in the use of magnetic resonance imaging (MRI) for the assessment of patients with multiple sclerosis (MS). Complementary to the clinical evaluation, conventional MRI provides crucial pieces of information for the diagnosis of MS. However, the correlation between the burden of lesions observed on conventional MRI scans and the clinical manifestations of the disease remains weak. The discrepancy between clinical and conventional MRI findings in MS is explained, at least partially, by the limited ability of conventional MRI to characterize and quantify the heterogeneous features of MS pathology. Other quantitative MR‐based techniques, however, have the potential to overcome such a limitation of conventional MRI. Indeed, magnetization transfer MRI, diffusion tensor MRI, proton MR spectroscopy, and functional MRI are contributing to elucidate the mechanisms that underlie injury, repair, and functional adaptation in patients with MS. Such techniques are likely to benefit from the use of high‐field MR systems and thus allow in the near future providing additional insight into all these aspects of the disease. This review summarizes how MRI is dramatically changing our understanding of the factors associated with the accumulation of irreversible disability in MS and highlights the reasons why they should be used more extensively in studies of disease evolution and clinical trials. J. Magn. Reson. Imaging 2010;31:770–788. ©2010 Wiley‐Liss, Inc.