Miracle-dz/UniFAR-FTUs huggingface dataset:
Visual detection of occluded crop: For automated harvesting

This paper presents a novel crop detection system applied to the challenging task of field sweet pepper (capsicum) detection. The field-grown sweet pepper crop presents several challenges for robotic systems such as the high degree of occlusion and the fact that the crop can have a similar colour to the background (green on green). To overcome these issues, we propose a two-stage system that performs per-pixel segmentation followed by region detection. The output of the segmentation is used to search for highly probable regions and declares these to be sweet pepper. We propose the novel use of the local binary pattern (LBP) to perform crop segmentation. This feature improves the accuracy of crop segmentation from an AUC of 0.10, for previously proposed features, to 0.56. Using the LBP feature as the basis for our two-stage algorithm, we are able to detect 69.2% of field grown sweet peppers in three sites. This is an impressive result given that the average detection accuracy of people viewing the same colour imagery is 66.8%.
Evaluating the Benefits and Challenges of Owning a Pet Dog at a Residential Psychiatric Rehabilitation Facility From the Perspective of Staff and Clients

Abstract This qualitative study evaluated benefits and challenges of the occupation of owning a communal pet dog living permanently at an adult psychiatric rehabilitation facility. Twenty-three participants (12 staff, 11 clients) completed surveys, interviews, and focus groups. Data were analyzed through multiple coding, member checking, and triangulation. Three major themes emerged: (a) positive emotional experiences, (b) challenges of dog ownership, and (c) supporting engagement in meaningful occupation. While experiences of participant’s were broadly positive, challenges with adopting a dog in its puppy stage of development were acknowledged. A novel finding recognizing positive impacts on the well-being of staff was found.
Detecting duplicates with shallow and parser-based methods

Identifying duplicate texts is important in many areas like plagiarism detection, information retrieval, text summarization, and question answering. Current approaches are mostly surface-oriented (or use only shallow syntactic representations) and see each text only as a token list. In this work however, we describe a deep, semantically oriented method based on semantic networks which are derived by a syntactico-semantic parser. Semantically identical or similar semantic networks for each sentence of a given base text are efficiently retrieved by using a specialized semantic network index. In order to detect many kinds of paraphrases the current base semantic network is varied by applying inferences: lexico-semantic relations, relation axioms, and meaning postulates. Some important phenomena occurring in difficult-to-detect duplicates are discussed. The deep approach profits from background knowledge, whose acquisition from corpora like Wikipedia is explained briefly. This deep duplicate recognizer is combined with two shallow duplicate recognizers in order to guarantee high recall for texts which are not fully parsable. The evaluation shows that the combined approach preserves recall and increases precision considerably, in comparison to traditional shallow methods. For the evaluation, a standard corpus of German plagiarisms was extended by four diverse components with an emphasis on duplicates (and not just plagiarisms), e.g., news feed articles from different web sources and two translations of the same short story.
Increased Gamma Brainwave Amplitude Compared to Control in Three Different Meditation Traditions

Despite decades of research, effects of different types of meditation on electroencephalographic (EEG) activity are still being defined. We compared practitioners of three different meditation traditions (Vipassana, Himalayan Yoga and Isha Shoonya) with a control group during a meditative and instructed mind-wandering (IMW) block. All meditators showed higher parieto-occipital 60–110 Hz gamma amplitude than control subjects as a trait effect observed during meditation and when considering meditation and IMW periods together. Moreover, this gamma power was positively correlated with participants meditation experience. Independent component analysis was used to show that gamma activity did not originate in eye or muscle artifacts. In addition, we observed higher 7–11 Hz alpha activity in the Vipassana group compared to all the other groups during both meditation and instructed mind wandering and lower 10–11 Hz activity in the Himalayan yoga group during meditation only. We showed that meditation practice is correlated to changes in the EEG gamma frequency range that are common to a variety of meditation practices.
Channel estimation with amplitude constraint: Superimposed training or conventional training ?

This paper utilizes a general superimposed training based transmission scheme that includes superimposed training and pilot symbol assisted modulation (PSAM) as special cases. The channel estimator of the scheme is the linear minimum mean square error (LMMSE) estimator. By taking into account errors of this method, we derive the closed-form lower bound of the data throughput under the constraint of limited amplitude for each symbol. Our study shows that with the constraint of total amplitude for each symbol, the conventional PSAM performs better in the high signal-to-noise ratio (SNR) region while at low SNR, the superimposed scheme performs better.
Prophylactic Effect of Lamivudine for Chemotherapy-Induced Hepatitis B Reactivation in Breast Cancer: A Meta-Analysis

Background Three strategies using lamivudine have been proposed to prevent chemotherapy-induced HBV (hepatitis B virus) reactivation in the clinical setting. The purpose of this meta-analysis is to evaluate the efficacy of the early preemptive strategy, deferred preemptive strategy and therapeutic strategy in patients with HBsAg-positive breast cancer during chemotherapy. Methods Clinical studies published from database inception until Nov 1, 2014, were included for analysis. The primary outcomes were overall survival, rate of chemotherapy disruption and virological and clinical reactivation. The secondary outcomes were the rates of HBV-related chemotherapy disruption, HBV-related mortality, YMDD mutations and withdrawal hepatitis. Results Four hundred and thirty patients in four studies that compared the early preemptive strategy with a therapeutic strategy were included. Application of early preemptive lamivudine was superior in reducing HBV recurrence (pooled OR: 0.12, 95% CI, 0.04 to 0.31, P< 0.0001), the incidence of HBV-related hepatitis (pooled OR: 0.13, 95% CI, 0.04 to 0.37, P< 0.0001) and the rate of chemotherapy disruption (pooled OR: 0.37, 95% CI, 0.23 to 0.60, P< 0.0001). In these two groups, no significant difference was found in overall mortality (P = 0.32), YMDD mutant rate (P = 0.13) or incidence of withdrawal hepatitis (P = 0.38). Of the two studies that compared the efficacy of an early and a deferred preemptive strategy, one showed that an early preemptive strategy significantly reduced the incidence of hepatitis (P = 0.046), whereas the other showed no significant difference (P = 0.7). Conclusions An early preemptive strategy is superior to a therapeutic strategy in decreasing the incidence of HBV reactivation, incidence of HBV-related hepatitis and rate of chemotherapy disruption in patients with breast cancer. A deferred preemptive strategy might be an alternative approach to controlling viral replication.
A causal approach to hierarchical decomposition in reinforcement learning

Reinforcement learning provides a means for autonomous agents to improve their action selection strategies without the need for explicit training information provided by an informed instructor. Theoretical and empirical results indicate that reinforcement learning algorithms can efficiently determine optimal or approximately optimal policies in tasks of limited size. However, as the size of a task grows, reinforcement learning algorithms become less consistent and less efficient at determining a useful policy. A key challenge in reinforcement learning is to develop methods that facilitate scaling reinforcement learning algorithms up to larger, more realistic tasks. We present a series of algorithms that take advantage of task structure to make reinforcement learning more efficient in realistic tasks that display such structure. In each algorithm, we assume that the state space of a task is factored; i.e., states are collections of values of a set of state variables. Our work combines hierarchical decomposition and state abstraction to reduce the size of a task prior to applying reinforcement learning. Hierarchical decomposition breaks a task into several subtasks that can be solved separately. For hierarchical decomposition to simplify learning, it is critical that each subtask is easier to solve than the overall task. To achieve the goal of simplifying the subtasks, we perform state abstraction separately for each subtask. We begin by presenting an algorithm that uses experience from the environment to dynamically perform state abstraction for each subtask in an existing hierarchy of subtasks. Since our goal is to automate hierarchical decomposition as well as state abstraction, a second algorithm uses a dynamic Bayesian network action representation to automatically decompose a task into a hierarchy of subtasks. In addition, the algorithm provides an efficient way to perform state abstraction for each resulting subtask. A third algorithm constructs compact representations of activities that represent solutions to the subtasks. These compact representations enable the use of planning to efficiently approximate solutions to higher-level subtasks without interacting with the environment. Our fourth and final algorithm provides a means to learn a dynamic Bayesian network representation of actions from experience in tasks for which the representation is not available prior to learning. The dissertation provides a detailed description of each algorithm as well as some theoretical results. We also present empirical results of each algorithm in a series of experiments. In tasks that display certain types of structure, the simplifications introduced by our algorithms significantly improve the performance of reinforcement learning. The results indicate that our algorithms provide a promising approach to make reinforcement learning better suited to solve realistic tasks in which these types of structure are present.
Thinking in emergence control for complex system

Emergence as the characteristics of complex system is ubiquitous, and it has practical significance to make expected function emerged through the emergence control. Based on the discussion of generating mechanism on emergence, the general definition and research category of emergence control are presented, and the basic approach to emergence control is discussed. From the viewpoint of interaction between system and “individuals”, a wider range of general definition of emergence of complex system is presented to explain research scope of emergence control clearly, and the control approach to system emergence is further discussed by analyzing the necessary condition and basic principle.
Young children's expressions of spirituality : an ethnographic case study

Historically the fostering of children's spirituality or spiritual development has been embedded in English education legislation. The underpinning principles of the Early Years Foundation Stage (EYFS) framework (DC SF, 2008), for children from birth to five years, made explicit reference to a spiritual dimension of young children's wellbeing. Yet spirituality receives scant acknowledgement in practice and there is little research focusing on exploring young children's spirituality in pre-school contexts. Located within an interpretive paradigm, this ethnographic case study of children aged two and three years in a day nursery, explores the language(s) of spiritual expression. A socio-cultural (Vygotsky, 1978) perspective of the child underpins the study that recognizes children's agency (Dahlberg et aI., 1999) in constructing meanings about the spiritual through their relationships and participation in everyday activities and interactions. Multi-layered data collection methods for listening to young children were chosen including direct observation, participant and non-participant observation, audio recording and digital photographs. A hermeneutic approach underpins the analysis and interpretation of the data. Findings reveal the multi-dimensional nature of young children's spirirual languages expressed in relational and imaginative spaces through creativity, reflection and embodied meaning making. This thesis argues for a broader situating of spirituality in English early childhood education that recognises the cross-curricular potential for learning imbued with the spiritual. A model of the multi-dimensional language of spirituality is presented to support practitioners in recognising young children's expressions of the spiritual separate to any association with religion or a belief system.
Re-considering participation in social media designs

This short paper reports from a museum innovation project using small-scale design experiments with mobile and social technologies to explore the participative museum along the Akerselva River in Oslo. We reflect upon what insights social media requires for design to engage people in participation in public and urban settings. The paper focuses on the micro-level of engagement in these media, and asks how a focus on language, semiotic and social practices may represent new possibilities for PD processes, using these media as design tools. It suggests that perspectives from cultural studies can be adapted to stage social media-based participatory design processes to reach communities that are dispersed over time and space.
Accio: A Data Set for Face Track Retrieval in Movies Across Age

Video face recognition is a very popular task and has come a long way. The primary challenges such as illumination, resolution and pose are well studied through multiple data sets. However there are no video-based data sets dedicated to study the effects of aging on facial appearance. We present a challenging face track data set, Harry Potter Movies Aging Data set (Accio1), to study and develop age invariant face recognition methods for videos. Our data set not only has strong challenges of pose, illumination and distractors, but also spans a period of ten years providing substantial variation in facial appearance. We propose two primary tasks: within and across movie face track retrieval; and two protocols which differ in their freedom to use external data. We present baseline results for the retrieval performance using a state-of-the-art face track descriptor. Our experiments show clear trends of reduction in performance as the age gap between the query and database increases. We will make the data set publicly available for further exploration in age-invariant video face recognition.
Wound Healing Potential of Topical Amlodipine in Full Thickness Wound of Rabbit

Background: Wound healing is a complicated and integrated process. Researches have indicated the wound healing effects of calcium channel blockers in animal models in recent years. Objectives: The aim of this study was to evaluate the wound-healing activity of amlodipine as a calcium channel blocker and combination of amlodipine with phenytoin on excisional cutaneous wound models in rabbit. Materials and Methods: Animals were divided into 5 groups (n = 5). The control group was treated topically with eucerin. The untreated control group received no healing agent. The reference standard group was treated with phenytoin1%. A treatment group was treated with amlodipine 1%. The last group was treated with combination of amlodipine1% and phenytoin 1%. Results: Results indicated significant difference between days needed for complete healing in both of the treatment groups. Wound closure was completed on 13th day and 9th day in amlodipine and combination groups respectively. Conclusions: In conclusion, calcium channel blockers can be used to enhance wound healing, especially if this treatment becomes with phenytoin. Further studies are needed to find out the mechanism of this healing effect.
Evaluating the Labor Market Performance of Veterans Using a Matched Comparison Group Design

The effect of active-duty service on civilian earnings is estimated using the Reserve Components Surveys, permitting a matched comparison between reservists who are veterans and reservists without active-duty service. Estimated treatment effects control for selection by the military and individuals, due in part to identical active-duty and reserve entrance requirements. The average impact of active-duty service on civilian earnings is 3 percent among the reservist population, reflecting effects of essentially zero for enlisted personnel and 10 percent for officers. Among white enlisted personnel veteran effects are negative but small, while averaging about 5 percent among African-Americans. Wage penalties resulting from Vietnam-era service are larger for white draftees than volunteers, while African-American draftees and volunteers realized gains.
"This Wooden Shack Place": The Logic of an Unconventional Reading. Occasional Paper No. 22.

A case study examined the logic of a student's unconventional interpretation of a poem. The subject, an outgoing and well-spoken student from the lower-middle class enrolled in a remedial composition class at the University of California, offered an unconventional reading of a poem by a contemporary Japanese-American writer. Data consisted of recordings of teacher-student conferences concentrating on the interpretation of the poem, a stimulated-recall session, and a follow-up interview. A "conventional" reading of the poem was constructed by asking six readers socialized in American literature departments (two senior English majors, two graduate students, and two English professors) to interpret the lines in question. Results indicated that while the subject's interpretation of the physical environment of the poem (that the character does not live in the wooden shacks and that she is really not poor) differed from the "conventional" reading, his interpretation was coherent and logical. Results also indicated that teacher talk in the conference was often qualified, challenged, and interrupted and that teacher expectations were often unfulfilled. Findings suggest that the laudable goal of facilitating underprepared students' entry into the academic community is actually compromised by a conversational pattern that channels students like the subject discussed here into more "efficient" discourse. (Excerpts from the teacher-student conference are included.) (RS) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. *********************************************************************** Center for the Study of Writing Occasional Paper No. 22 "THIS WOODEN SHACK PLACE": ME LOGIC OF AN UNCONVENTIONAL READING Glynda Hull Mike Rose
ELF as a translational Lingua Franca: reciprocal influences between ELF and translation

ABSTRACT The spread of English as a language of international communication has led to a variety of approaches within various schools of thought. However, one of the areas in which the influence of English as a Lingua Franca (ELF) is particularly significant, and nevertheless under-researched, is professional translation and interpreting. The impact of ELF on translation is manifold, particularly due to the hybridity of source texts. Furthermore, the supposedly simplified nature and universality of ELF as a code intended to facilitate communication – and translation – ties in with discourses encouraging the use of online translation tools and non-professional translation. Drawing on ELF studies and Translation Studies, I argue for a conceptualization of ELF as being marked by an intrinsic translation process related to the fluidity of languages. The translational character of ELF is testified to by the hybridity of texts produced by international organizations and written by non-native speakers of English, which are inevitably affected by the languages and cultures of their authors. Furthermore, I will show how views about the universality and transparency of a lingua franca cannot be separated from its translation, concluding that translators, translation scholars and international institutions have a responsibility to reveal ELF’s translational nature.
Performance of phonemically targeted processing in conjunction with compression processing with spectral enhancement.

The goal of the present study is to test, individually and in combination, two signal-processing strategies designed to improve both consonant and vowel perception. In the first strategy, specific consonants were targeted for processing to increase amplitude and duration. For consonants with a duration increase, the adjacent vowel was decreased proportionately in order to maintain overall word and sentence duration. Second, Coliga, an adaptive compression-processing strategy incorporating spectral enhancement, was used to process stimuli. Hearing-in-noise-test sentences were presented monaurally to normal-hearing and hearing-impaired adults in the presence of speech-shaped noise. For normal-hearing listeners, it appears that Coliga is improving intelligibility in certain conditions. Conservative amounts of duration and amplitude processing need to be applied in combination rather than when applied independently in order to provide benefit. For the hearing-impaired listeners, Coliga with spectral enhancement resulted in poorer performance than without, for all conditions except for the Coliga-only conditions, where the intelligibility was the same. It appears that phonemically-targeted speech processing and Coliga are working antagonistically due to either 1) the processing method negating the benefits when the two are combined, or 2) combining the duration and amplitude components leading to no benefit despite documented benefit of each when employed individually.
Improving Verb Metaphor Detection by Propagating Abstractness to Words, Phrases and Individual Senses

Abstract words refer to things that can not be seen, heard, felt, smelled, or tasted as opposed to concrete words. Among other applications, the degree of abstractness has been shown to be a useful information for metaphor detection. Our contribution to this topic are as follows: i) we compare supervised techniques to learn and extend abstractness ratings for huge vocabularies ii) we learn and investigate norms for larger units by propagating abstractness to verb-noun pairs which lead to better metaphor detection iii) we overcome the limitation of learning a single rating per word and show that multi-sense abstractness ratings are potentially useful for metaphor detection. Finally, with this paper we publish automatically created abstractness norms for 3million English words and multi-words as well as automatically created sense specific abstractness ratings