Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating Top-Down versus Bottom-Up Knowledge AcquisitionStrategies for use in Rule Based Models of Emotional Common Sense

1 Abstract Three ways to build rule based models of emotional common sense reasoning are described: a top-down approach, inspired by a popular theory in the eld, a bottom-up or demo driven approach, and a hybrid approach. A means of evaluating each of the models is described. One aspect of the evaluation involves comparing a given model's performance against an empirically derived benchmark of human behavior. The second aspect involves measuring computational and knowledge engineer resources required by a given approach in order to ascertain hypotheses made about the virtues of each approach. 2 Introduction Knowledge based systems can be constructed to exhibit functionalities that are useful for emotionally intelligent agents. As R. Pfeifer (1987) has indicated, the emotions are closely linked with common sense reasoning. In such systems the same bits of knowledge can be used to model the deductive processes, produce explanations for inferences the system makes, or abduce explanations for others' emotions. Furthermore, understanding emotional phenomena is an essential part of common sense reasoning. Unfortunately, knowledge acquisition is an extensive, labor intensive process (Rich & Knight, 1991). Given the tight coupling between common sense and the emotions, it is advantageous to use a system that contains large amount of common sense background knowledge. One such system is Cyc. Cyc contains a common sense knowledge base and an inference engine. The encoding such of everyday knowledge remains one of the central aims of the project (Lenat & Guha, 1988). The Cyc knowledge base (KB) contains a large number of common sense facts stated in a special logical language known as CycL. The English representation of such common sense facts include a vast range of statements including; mammals have fur. birds fly (except penguins). if it is daytime, it is light outside. Cyc is not the only such system in which to conduct a project such as this. The claims I make below are meant to be generic to any endeavor that involves a knowledge based approach to emotion. In what follows I propose a means of conducting a knowledge acquisition eeort that compares diierent approaches to emotional common sense knowledge acquisition. There are three beneets of such work: advancement of the state of the art in systems with emotional common sense, increased knowledge about the value of diierent approaches towards emotional knowledge acquisition, and theories of emotion with greater precision, clarity, and consistency.
First-Generation Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors in EGFR Mutation: Positive Non-small Cell Lung Cancer Patients

Small molecule tyrosine kinase inhibitors of the epidermal growth factor receptor (EGFR) are important agents in the treatment of non-small cell lung cancer (NSCLC) and have enhanced activity in the subpopulation of patients with NSCLC who harbor somatic activating mutations of the EGFR gene. This review summarizes the data describing the use of EGFR tyrosine kinase inhibitors in a genotype-directed population of NSCLC patients with EGFR mutations and discusses areas that require further study.
Optimal Clustering of Kinetic Patterns on Malignant Breast Lesions: Comparison between K-means Clustering and Three-time-points Method in Dynamic Contrast-enhanced MRI

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful for breast cancer diagnosis and treatment planning. Nevertheless, due to the multi-temporal nature of DCE-MRI data, the assessment of early stage breast cancer is a challenging task. In this study, we applied an unsupervised clustering approach and cluster validation technique to the analysis of malignant intral-tumoral kinetic curves in DCE-MRI. K-means cluster analysis was performed from real world malignant tumor cases and the data were transformed into an optimal number of reference patterns representative each cluster. The optimal number of clusters was estimated by a cluster validation index, which was calculated with the ratio of inter-class scatter to intra-class scatter. This technique then classifies tumor specific patterns from a given MRI data by measuring the vector distances from the reference pattern set, and compared the result from the k- means clustering with that from three-time-points (3TP) method, which represents a clinical standard protocol for analysis of tumor kinetics. The evaluation of twenty five cases indicates that optimal k-means clustering reflects partitioning intra-tumoral kinetic patterns better than the 3TP technique. This method will greatly enhance the capability of radiologists to identify and characterize internal kinetic heterogeneity and vascular change of a tumor in breast DCE-MRI.
On the Macroscopic Effects of Local Interactions in Multi-hop Wireless Networks

The objective of the paper is to provide qualitative insight into the global effects of distributed mechanisms, such as carrier sense multiple access (CSMA) and rate control, on the performance and stability of multi-hop wireless networks. Toward this end, we introduce a linear queueing network model where the service capacity of each node is modulated by the transmission state of its neighbor. We derive lower bounds on the steady-state utilization at each queue of such networks and demonstrate the existence of a phase transition phenomenon, whereby infinitesimal traffic increase at a single node in the network can suddenly render the entire network instable. We also present NS simulation results that show how this phenomenon can actually take place in IEEE 802.11 multi-hop wireless networks. Our results have direct bearing on rate control schemes, in that they indicate a minimum admissible threshold rate required to prevent network instability.
Deciphering Asthma Biomarkers with Protein Profiling Technology

Asthma is a chronic inflammatory disease of the airways, resulting in bronchial hyperresponsiveness with every allergen exposure. It is now clear that asthma is not a single disease, but rather a multifaceted syndrome that results from a variety of biologic mechanisms. Asthma is further problematic given that the disease consists of many variants, each with its own etiologic and pathophysiologic factors, including different cellular responses and inflammatory phenotypes. These facets make the rapid and accurate diagnosis (not to mention treatments) of asthma extremely difficult. Protein biomarkers can serve as powerful detection tools in both clinical and basic research applications. Recent endeavors from biomedical researchers have developed technical platforms, such as cytokine antibody arrays, that have been employed and used to further the global analysis of asthma biomarker studies. In this review, we discuss potential asthma biomarkers involved in the pathophysiologic process and eventual pathogenesis of asthma, how these biomarkers are being utilized, and how further testing methods might help improve the diagnosis and treatment strain that current asthma patients suffer.
Effects of mindful-attention and compassion meditation training on amygdala response to emotional stimuli in an ordinary, non-meditative state

The amygdala has been repeatedly implicated in emotional processing of both positive and negative-valence stimuli. Previous studies suggest that the amygdala response to emotional stimuli is lower when the subject is in a meditative state of mindful-attention, both in beginner meditators after an 8-week meditation intervention and in expert meditators. However, the longitudinal effects of meditation training on amygdala responses have not been reported when participants are in an ordinary, non-meditative state. In this study, we investigated how 8 weeks of training in meditation affects amygdala responses to emotional stimuli in subjects when in a non-meditative state. Healthy adults with no prior meditation experience took part in 8 weeks of either Mindful Attention Training (MAT), Cognitively-Based Compassion Training (CBCT; a program based on Tibetan Buddhist compassion meditation practices), or an active control intervention. Before and after the intervention, participants underwent an fMRI experiment during which they were presented images with positive, negative, and neutral emotional valences from the IAPS database while remaining in an ordinary, non-meditative state. Using a region-of-interest analysis, we found a longitudinal decrease in right amygdala activation in the Mindful Attention group in response to positive images, and in response to images of all valences overall. In the CBCT group, we found a trend increase in right amygdala response to negative images, which was significantly correlated with a decrease in depression score. No effects or trends were observed in the control group. This finding suggests that the effects of meditation training on emotional processing might transfer to non-meditative states. This is consistent with the hypothesis that meditation training may induce learning that is not stimulus- or task-specific, but process-specific, and thereby may result in enduring changes in mental function.
ConSUS: a scalable approach to conditioned slicing

Conditioned slicing can be applied to reverse engineering problems which involve the extraction of executable fragments of code in the context of some criteria of interest. This paper introduces ConSUS, a conditioner for the Wide Spectrum Language, WSL. The symbolic executor of ConSUS prunes the symbolic execution paths, and its predicate reasoning system uses the FermaT simplify transformation in place of a more conventional theorem prover We show that this combination of pruning and simplification-as-reasoner leads to a more scalable approach to conditioning.
Classifying Violent versus Non-Violent Offending in a Diverse Sample of Adolescent Juvenile Delinquents

The purpose of the study was to examine whether a set of theoretically and empirically established risk factors could contribute to the classification of violent versus non-violent offending in an ethnically diverse sample of male and female adolescent juvenile delinquents. Variables examined included economic disadvantage, grade point average (GPA), sex, dependency involvement, special education diagnosis, specific learning disability diagnosis, emotional disability diagnosis, history of illegal substance violation, and recidivism. Observed versus expected frequencies of violent versus nonviolent offending across different ethnicity categories were also examined. It was hypothesized that economic disadvantage and grade point average would not significantly contribute to the classification of violent versus non-violent offense group membership in juvenile delinquents. It was hypothesized that sex, dependency involvement, special education diagnosis, specific learning disability diagnosis, emotional disability diagnosis, history of illegal substance violation, and recidivism would significantly contribute to the classification of violent versus non-violent offense group membership in juvenile delinquents. It was also hypothesized that there would be no significant differences between observed versus expected frequency of violent versus non-violent offending across ethnicity categories. A discriminant analysis retained five of nine variables in the final stepwise model, including recidivism, illegal substance violation history, special education diagnosis, emotional disability diagnosis, and specific learning disability diagnosis. While variables in the analysis significantly contributed to the classification of non-violent group
Spoken Content Retrieval Using Distance Combination and Spoken Term Detection Using Hash Function for NTCIR10 SpokenDoc2 Task

In this paper we describe a spoken content retrieval (SCR) and a spoken term detection (STD) which were used in the 2nd round of the IR (Information Retrieval) for Spoken Documents (SpokenDoc2) task. Our SCR method maps the target documents into multiple vector spaces, which include a word-based vector space for word-based speech recognition results and a syllable-based vector space for syllablebased speech recognition results. The syllable-based space is spanned by axes extracted using latent semantic indexing (LSI). We also apply query expansion and morpheme weighting to the word-based space. Finally, the distance between the query and the documents in each vector space are combined and ranked for retrieving the documents. On the other hand, our STD method extracts sub-sequences from the target documents and converts them into bit sequences using the hash function. The query is also converted into a bit sequence in the same way. Candidates are detected by calculating the hamming distance between the bit sequence of the query and that of the target documents. Then, our method calculates the distances between the query and the candidates using DP (Dynamic Programming) matching. To evaluate the proposed methods, we conducted spoken document retrieval experiments using the SpokenDoc task from the NTCIR-9 meeting. Using these experimental results to set our parameters, we submitted the results for the SpokenDoc2 task at NTCIR-10.
Increasing of Syncytial Knot and Fibrinoid Deposit in High-Cd Accumulated Human Placentas

Un metal toxico, el cadmio (Cd), se puede acumular en organos humanos. La placenta se utiliza, por lo general, como organo indicador de la exposicion a Cd. Nuestro objetivo fue investigar la diferente morfologia placentaria entre las placentas con baja y alta acumulacion de Cd. Las muestras fueron recolectadas de 14 mujeres embarazadas que residian areas con alta (grupo H-Cd) y baja contaminacion por Cd (grupo L-Cd). Las concentraciones de Cd en la sangre (B- Cd), orina (U-Cd) y placentas (P-Cd) se midieron por ICP-MS y AAS. La apariencia morfologica de las placentas fue examinada usando cortes histologicos tenidos con H-E. Los resultados mostraron que los niveles de B-Cd, U-Cd y P-Cd fueron significativamente mayores en el grupo H-Cd (p= 0,001). Por otra parte, el B-Cd se correlaciono positivamente con las concentraciones de U-Cd (rs= 0,854, p = 0,000 ) y P-Cd (rs= 0,823, p = 0,000). Las apariciones de nodos sinciciales (NS) y depositos fibrinoides (Fd) fueron mayores en el grupo H-Cd (rs= 0,007, p= 0,026). Los ND se correlacionaron positivamente con los Fd (rs= 0,572, p= 0,032) y la concentracion de P-Cd (rs= 0,766, p = 0,001). Aunque caracteristicas de corioamnitis e inflamacion de la decidua se encontraron en ambos grupos, su aparicion en el grupo H-Cd parecio ser mas grave que en el grupo L-Cd. A partir de estos resultados, sugerimos que el nivel alto de Cd en la placenta puede estar involucrado en los cambios morfologicos, especialmente el aumento de NS y Fd, los que probablemente alteran la relacion entre la circulacion materna y fetal.
Data Oriented Software Security Testing

With the fast developing of Internet and intelligent device, information security issue is becoming much more important every day. More and more researchers are attracted to software security testing study. Most of them put their works on software access control model based testing, which takes into account information mainly on multi-dimensions, like roles, permissions and contexts. But the key disadvantage of access control model based testing is its model are hard to be built in many circumstance, for example, to describe requirement "picture A is only allowed to be copied twice outside terminal B", researcher has to extend the original model with hierarchy status and priority sub models. To overcome this disadvantage, this paper present a framework of data oriented access control testing method, which focus mainly on data and its actions instead of role, permission and contexts. Though experiments, this paper also proves that the method is much more instructive than access control model in test cases automatic generating.
Automatic event extraction and video summaries from soccer games

Bagadus is a prototype of a soccer analysis application which integrates a sensor system, a video camera array and soccer analytics annotations. The current prototype is installed at Alfheim Stadium in Norway, and provides a large set of new functions compared to existing solutions. One important feature is to automatically extract video events and summaries from the games, i.e., an operation that traditionally consumes a huge amount of time. In this demo, we demonstrate how our integration of subsystems enable several types of summaries to be generated automatically, and we show that the video summaries are displayed with a response time around one second.
Towards a Group Theoretic Quantum Encryption Scheme Based on Generalized Hidden Subgroup Problem

This paper introduces a completely new approach to encryption based on group theoretic quantum framework. Quantum cryptography has essentially focused only on key distribution and proceeded with classical encryption algorithm with the generated key. Here, we present a first step towards a quantum encryption scheme based on the solution for the hidden subgroup problem. The shared secret key K from QKD evolves as a generator for a subgroup H of a group G, in combination of the plain text data modeled as group elements. The key K helps in regeneration of the plain data on the receiver's side based on subgroup reconstruction. This paper models all quantum computations using group representations. A non-constructive proof is attempted towards the security of the encryption scheme. We also address the issues involved in a such a venture into the realms of Quantum data encryption.
Keeping returns optimal: gain control exerted through sensitivity adjustments in the harbour porpoise auditory system

Animals that use echolocation (biosonar) listen to acoustic signals with a large range of intensities, because echo levels vary with the fourth power of the animal's distance to the target. In man-made sonar, engineers apply automatic gain control to stabilize the echo energy levels, thereby rendering them independent of distance to the target. Both toothed whales and bats vary the level of their echolocation clicks to compensate for the distance-related energy loss. By monitoring the auditory brainstem response (ABR) during a psychophysical task, we found that a harbour porpoise (Phocoena phocoena), in addition to adjusting the sound level of the outgoing signals up to 5.4 dB, also reduces its ABR threshold by 6 dB when the target distance doubles. This self-induced threshold shift increases the dynamic range of the biosonar system and compensates for half of the variation of energy that is caused by changes in the distance to the target. In combination with an increased source level as a function of target range, this helps the porpoise to maintain a stable echo-evoked ABR amplitude irrespective of target range, and is therefore probably an important tool enabling porpoises to efficiently analyse and classify received echoes.
Importance of Time Spent Standing for Those at Risk of Diabetic Foot Ulceration

OBJECTIVE Despite the high cumulative plantar stress associated with standing, previous physical activity reports of diabetic patients at risk of foot ulceration have not taken this activity into account. This study aimed to monitor spontaneous daily physical activity in diabetic peripheral neuropathy (DPN) patients and examine both walking and standing activities as important foot-loading conditions. RESEARCH DESIGN AND METHODS Thirteen DPN patients were asked to wear a body-worn sensor for 48 h. Body postures (sitting, standing, and lying) and locomotion (walking, number of steps, and postural transition) were extracted. RESULTS Patients daily spent twice as much time standing (13 ± 5%) as walking (6 ± 3%). They spent 37 ± 6% of time sitting and 44 ± 8% lying down. The average number of steps per day was 7,754 ± 4,087, and the number of walking episodes was 357 ± 167 with maximum duration of 3.9 ± 3.8 min. CONCLUSIONS The large portion of DPN patients' time spent standing with the feet loaded requires further consideration when treating and preventing foot ulcers.
On the U.S. and the Overthrow of Allende: A Reply to Professor Sigmund's Criticism

Fundamental issues are raised in Sigmund's attack on our book, concerns that pertain to what has probably become one of the most controversial policy debates in recent times: the role of the U.S. in the overthrow of the Allende government. Measured by the amount of time and space devoted to the issue by Congress, the media, and academia, this question certainly requires careful consideration. Unfortunately, Sigmund presently and in the past has not dealt adequately with either the pertinent questions or the relevant data. The numerous errors and distortions require a thorough response.
ntimalarial herbal remedies of Msambweni , Kenya

Malaria is a serious cause of mortality globally. The disease is of regional concern in Africa and of national interest in Kenya due to its high morbidity and mortality as a result of development of resistant strains of Plasmodium falciparum to many existing drugs such as chloroquine. Alternative medicine using herbal remedies are commonly used to treat malaria in Kenya. However, plants used in some rural areas in Kenya are not documented. Many antimalarial drugs have been derived from plants. This study was conducted to document medicinal plants that are traditionally used by the Msambweni community of Kenyan South Coast to treat malaria, where the disease is endemic. Herbalists were interviewed by administration of semistructured questionnaires in order to obtain information on medicinal plants traditionally used for the treatment of malaria. Focused group discussions held with the herbalists supplemented the interview and questionnaire survey. Twenty-seven species of plants in 24 genera distributed in 20 families were reported to be used in this region for the treatment of malaria. Labiatae, Rutaceae and Liliaceae families had each eleven percent of the plant species reported and represented the species that are most commonly used. Thirteen plant species, namely; Aloe deserti Berger (Liliaceae), Launea cornuta (Oliv and Hiern) C. Jeffrey (Compositae), Ocimum bacilicum L. (Labiatae), Teclea simplicifolia (Eng) Verdoon (Rutaceae), Gerranthus lobatus (Cogn.) Jeffrey (Cucurbitaceae), Grewia hexaminta Burret. (Tiliaceae), Canthium glaucum Hiern. (Rubiaceae), Amaranthus hybridus L. (Amaranthaceae), Combretum padoides Engl and Diels. (Combretaceae), Senecio syringitolius O. Hoffman. (Compositae), Ocimum suave Willd (Labiatae), Aloe macrosiphon Bak. (Liliaceae) and Laudolphia buchananii (Hall.f) Stapf. (Apocynaceae) are documented from this region for the first time for the treatment of malaria. These results become a basis for selection of plants for further pharmacological, toxicological and phytochemical studies in developing new plant based antimalarial drugs.