Miracle-dz/UniFAR-FTUs huggingface dataset:
Standard‐dose anti‐CD20 antibody rituximab has efficacy in chronic lymphocytic leukaemia: results from a Nordic multicentre study

Abstract: Objectives: This prospective multicentre study was conducted to assess the efficacy of the monoclonal anti‐CD20 antibody rituximab in patients with chronic lymphocytic leukaemia (CLL). Secondary objectives were defined as the tolerability and feasibility of rituximab in patients with CLL. Methods: Twenty‐four heavily pretreated patients with CLL were treated with a standard dose of 375 mg m−2 of rituximab given once weekly for four doses. Results: The overall response rate was 35% and all the responses were partial as defined by the revised NCI criteria. In 17 (85%) of 20 patients with initially measurable peripheral lymph nodes the size of lymph nodes decreased by at least 50%, while an improvement of the bone marrow infiltration was observed only in two (11%) of 18 evaluable patients. The median duration of the overall response was 12.5 wk. Rituximab was relatively well tolerated. Although side‐effects were common (75%) they were usually mild or moderate. There was only one grade 3 adverse event and no grade 4 events. Conclusions: Standard‐dose rituximab has activity in heavily pretreated patients with CLL, although the response is mainly limited to the lymph nodes and of short duration. Since rituximab has in vitro synergism with chemotherapeutic agents and is well tolerated by CLL patients, it is reasonable to investigate rituximab in combination with other treatments.
A Fuzzy Classifier using Bank of Gabor Filters to Facial Images ’ Gender Classification

This paper explores a design-based method to use Gabor filter features and fuzzy system for improved texture recognition. In this article, we will present an unsupervised approach for facial image gender classification based on texture features. This system is 1-input, 1-output Mamdani type one, applies facial texture propeties as inputs and reveals the probability of being male face image in output. Choosing proper threshold value, the decision about gender is made. 85.5% obtained classification rate prove the efficiency of proposed method.
Chinese Semantic Role Labeling with Shallow Parsing

Most existing systems for Chinese Semantic Role Labeling (SRL) make use of full syntactic parses. In this paper, we evaluate SRL methods that take partial parses as inputs. We first extend the study on Chinese shallow parsing presented in (Chen et al., 2006) by raising a set of additional features. On the basis of our shallow parser, we implement SRL systems which cast SRL as the classification of syntactic chunks with IOB2 representation for semantic roles (i.e. semantic chunks). Two labeling strategies are presented: 1) directly tagging semantic chunks in one-stage, and 2) identifying argument boundaries as a chunking task and labeling their semantic types as a classification task. Lor both methods, we present encouraging results, achieving significant improvements over the best reported SRL performance in the literature. Additionally, we put forward a rule-based algorithm to automatically acquire Chinese verb formation, which is empirically shown to enhance SRL.
Correlation between Similarity Measures for Inter-Language Linked Wikipedia Articles

Wikipedia articles in different languages have been mined to support various tasks, such as Cross-Language Information Retrieval (CLIR) and Statistical Machine Translation (SMT). Articles on the same topic in different languages are often connected by inter-language links, which can be used to identify similar or comparable content. In this work, we investigate the correlation between similarity measures utilising language-independent and language-dependent features and respective human judgments. A collection of 800 Wikipedia pairs from 8 different language pairs were collected and judged for similarity by two assessors. We report the development of this corpus and inter-assessor agreement between judges across the languages. Results show that similarity measured using language independent features is comparable to using an approach based on translating non-English documents. In both cases the correlation with human judgments is low but also dependent upon the language pair. The results and corpus generated from this work also provide insights into the measurement of cross-language similarity.
Bayley Scales of Infant and Toddler Development

Definition/Introduction Bayley Scales of Infant and Toddler Development is an extensive formal developmental assessment tool for diagnosing developmental delays in early childhood. BSID is the commonly used abbreviation for Bayley Scales of Infant and Toddler Development. BSID scores are from a norm-referenced assessment of early childhood development. Nancy Bayley published the first BSID in 1969. The current BSID in use is BSID 4, published in 2019. BSID 4 is time-saving, has greater clinical sensitivity and accuracy when compared to BSD 3. It takes about 30 to 70 minutes to complete the test. Infant and Childhood Development Infant and childhood development comprises physical, cognitive, social-emotional, linguistic, and behavioral milestones. The differences in cultural, environmental, and genetic factors influence development. The development process is rapid and cumulative. Developmental disabilities are common and are reported 1 in 6 children in the United States. The number of children with select developmental disabilities (autism, attention deficit hyperactivity disorder, and other developmental delays) has increased, requiring more health and education services. [1] Developmental Assessments An estimated 5 to 10% of the pediatric population has a developmental disability. [2] There are three different strategies to detect developmental delay.
Prevalence and Correlates of Sexting Behavior in Adolescents

The purpose of this study was to assess the prevalence of sexting among sixth through twelfth grade students and its correlations with other risk behaviors. The survey was conducted in 35 different schools in a midwestern state. Overall, 17% of students engaged in sexting, which varied significantly by age (3% of 12-year-olds to 32% of 18-year-olds). Adjusted odds ratios found statistically significant correlations between sexting and sexual behaviors, substance use behaviors, emotional health behaviors, and time spent texting. Sexting should be addressed by parents, teachers, and mental health professionals who interact with adolescents.
Transplantation of organs is transplantations of donor DNA: fate of DNA disseminated in recipient

Microchimerism after allogeneic organ transplantation has been widely documented using DNA identification techniques. However, the question as to whether the detected donor DNA is present in the surviving donor passenger cells, recipient macrophages phagocytizing rejected donor cells, or dendritic cells (DC) internalizing donor apoptotic bodies or cell fragments has not been answered. We provide evidence that allogeneic organ transplantation is followed not only by cellular microchimerism caused by release of graft passenger cells but also dissemination of donor DNA from the ischemic rejecting graft cells and its internalization in recipient DC. The high levels of donor DNA at the time of heart rejection were inversely proportional to the concentration of donor passenger cells detected with use of flow cytometry. Depending on the type of graft, the kinetics of DNA distribution in recipient tissues were different. Immunosuppressive drugs attenuated the rejection reaction and release of DNA from grafts. Allogeneic but not syngeneic donor DNA fragments were found in recipient splenic DC‐enriched population. Interestingly, that donor DNA fragments could be detected in recipient tissue at high levels on day 30. This challenges the notion that fragments of DNA are immediately cleaved by cell plasmatic enzymes. The biologic significance of our findings is not clear. We speculate that donor DNA fragments in recipient DC may play a, so far unknown, role in the immunization/tolerance process to allogeneic antigens.
Joint and Distributed Linear Precoding for Centralised and Decentralised Multicell Processing

Linear precoding techniques are designed for both joint and distributed Multi-Cell Processing (MCP), where both centralised and decentralised Channel State Information (CSI) exchange scenarios are considered. The outage rate of various linear precoding techniques is investigated in the cell-edge area of a practical three-cell based cooperative scenario under both fully-loaded and lightly-loaded system configurations, when encountering either no tier-one Co-Channel Interference (CCI) or full tier-one CCI. The numerical results demonstrate the superiority of the low-complexity, yet scalable decentralised Distributed Signal-to-Leakage-Noise-Ratio (DSLNR) based linear precoding technique under realistic CSI quantisation and channel-induced feedback error conditions when full tier-one CCI is considered.
Towards the Mental Health Ontology

Lots of research have been done within the mental health domain, but exact causes of mental illness are still unknown. Concerningly, the number of people being affected by mental conditions is rapidly increasing and it has been predicted that depression would be the world's leading cause of disability by 2020. Most mental health information is found in electronic form. Application of the cutting-edge information technologies within the mental health domain has the potential to greatly increase the value of the available information. Specifically, ontologies form the basis for collaboration between research teams, for creation of semantic Web services and intelligent multi-agent systems, for intelligent information retrieval, and for automatic data analysis such as data mining. In this paper, we present mental health ontology which can be used to underpin a variety of automatic tasks and positively transform the way information is being managed and used within the mental health domain.
Approaching neuropsychological tasks through adaptive neurorobots

Neuropsychological phenomena have been modelized mainly, by the mainstream approach, by attempting to reproduce their neural substrate whereas sensory-motor contingencies have attracted less attention. In this work, we introduce a simulator based on the evolutionary robotics platform Evorobot* in order to setting up in silico neuropsychological tasks. Moreover, in this study we trained artificial embodied neurorobotic agents equipped with a pan/tilt camera, provided with different neural and motor capabilities, to solve a well-known neuropsychological test: the cancellation task in which an individual is asked to cancel target stimuli surrounded by distractors. Results showed that embodied agents provided with additional motor capabilities (a zooming/attentional actuator) outperformed simple pan/tilt agents, even those equipped with more complex neural controllers and that the zooming ability is exploited to correctly categorising presented stimuli. We conclude that since the sole neural computational power cannot explain the (artificial) cognition which emerged throughout the adaptive process, such kind of modelling approach can be fruitful in neuropsychological modelling where the importance of having a body is often neglected.
Brain-Derived Neurotrophic Factor Prevents Low-Frequency Inputs from Inducing Long-Term Depression in the Developing Visual Cortex

Brain-derived neurotrophic factor (BDNF) is reported to enhance synaptic transmission and to play a role in long-term potentiation in hippocampus and neocortex. If so, a shortage or blockade of BDNF might lead to another form of synaptic plasticity, long-term depression (LTD). To test this possibility and to elucidate mechanisms if it is the case, EPSCs evoked by test stimulation of layer IV were recorded from layer II/III neurons in visual cortical slices of young rats in the whole-cell voltage-clamp mode. LTD was induced by low-frequency stimulation (LFS) at 1 Hz for 10–15 min if each pulse of the LFS was paired with depolarization of neurons to −30 mV but was not induced if their membrane potentials were kept at −70 mV. Such an LTD was blocked by exogenously applied BDNF, probably through presynaptic mechanisms. Suppression of endogenous BDNF activity by the anti-BDNF antibody or an inhibitor for BDNF receptors made otherwise ineffective stimuli (LFS without postsynaptic depolarization) effective for LTD induction, suggesting that endogenous BDNF may prevent low-frequency inputs from inducing LTD in the developing visual cortex.
Fat Detection: Taste, Texture, and Post Ingestive Effects

IMPORTANCE OF DIETARY FAT Evolutionary Perspectives on Fat Ingestion and Metabolism in Humans, William R. Leonard, J. Josh Snodgrass, and Marcia L. Robertson Pathophysiology and Evolutionary Aspects of Dietary Fats and Long-Chain Polyunsaturated Fatty Acids across the Life Cycle, Frits A.J. Muskiet TASTE OF FAT: FROM DETECTION TO BEHAVIOR Gustatory Mechanisms for Fat Detection, Timothy A. Gilbertson, Tian Yu, and Bhavik P. Shah Role of the Gustatory System in Fatty Acid Detection in Rats, David W. Pittman Peripheral Gustatory Processing of Free Fatty Acids, Jennifer M. Stratford and Robert J. Contreras Orosensory Factors in Fat Detection, James C. Smith Fat Taste in Humans: Is It a Primary? Richard D. Mattes NEURAL REPRESENTATIONS OF DIETARY FAT STIMULI Neural Representation of Fat Texture in the Mouth, Edmund T. Rolls Advantageous Object Recognition for High-Fat Food Images, Ulrike Toepel, Jean-Francois Knebel, Julie Hudry, Johannes le Coutre, and Micah M. Murray SENSORY APPEAL OF THE FAT-RICH DIET Preference for High-Fat Food in Animals, Yasuko Manabe, Shigenobu Matsumura, and Tohru Fushiki Human Perceptions and Preferences for Fat-Rich Foods, Adam Drewnowski and Eva Almiron-Roig CONTROL OF FOOD INTAKE AS A FUNCTION OF FAT Oral and Postoral Determinants of Dietary Fat Appetite, Karen Ackroff and Anthony Sclafani Control of Fat Intake by Striatal Opioids, Brian A. Baldo, Wayne E. Pratt, and Ann E. Kelley Fat-Rich Food Palatability and Appetite Regulation, Charlotte Erlanson-Albertsson Fats and Satiety, Rania Abou Samra GENETIC FACTORS INFLUENCING FAT PREFERENCE AND METABOLISM Heritable Variation in Fat Preference, Danielle R. Reed Dietary, Physiological, and Genetic Impacts on Postprandial Lipid Metabolism, Jose Lopez-Miranda and Carmen Marin LIPIDS AND DISEASE Control of Fatty Acid Intake and the Role of Essential Fatty Acids in Cognitive Function and Neurological Disorders, Kiran S. Panickar and Sam J. Bhathena What Is the Link between Docosahexaenoic Acid, Cognitive Impairment, and Alzheimer's Disease in the Elderly? Michel E. Begin, Melanie Plourde, Fabien Pifferi, and Stephen C. Cunnane Hypothalamic Fatty Acid Sensing in the Normal and Disease States, Madhu Chari, Carol K.L. Lam, and Tony K.T. Lam Dietary Fat and Carbohydrate Composition: Metabolic Disease, Marc A. Brown, Len H. Storlien, Xu-Feng Huang, Linda C. Tapsell, Paul L. Else, Janine A. Higgins, and Ian L. Brown Food Intake and Obesity: The Case of Fat, Jennifer T. Smilowitz, J. Bruce German, and Angela M. Zivkovic Index
Rigor and Proof in Mathematics: A Historical Perspective

21 am well aware that in dealing with a nearly 4000-year span of mathematical history one can hardly do justice to topics deserving more thorough treatment. On the other hand, since I am attempting to survey major trends, I touch on issues with which some readers are well acquainted. Nevertheless, I hope the overall survey will be of interest to readers. The references (they are, for ease of access, to secondaiy sources) should serve as entry points for further study.
Multi-Language Named-Entity Recognition System based on HMM

We introduce a multi-language named-entity recognition system based on HMM. Japanese, Chinese, Korean and English versions have already been implemented. In principle, it can analyze any other language if we have training data of the target language. This system has a common analytical engine and it can handle any language simply by changing the lexical analysis rules and statistical language model. In this paper, we describe the architecture and accuracy of the named-entity system, and report preliminary experiments on automatic bilingual named-entity dictionary construction using the Japanese and English named-entity recognizer.
Homology modelling of Drosophila cytochrome P450 enzymes associated with insecticide resistance.

BACKGROUND Overexpression of the cytochrome P450 gene Cyp6g1 confers resistance against DDT and a broad range of other insecticides in Drosophila melanogaster Meig. In the absence of crystal structures of CYP6G1 or complexes with its substrates, structural studies rely on homology modelling and ligand docking to understand P450-substrate interactions. RESULTS Homology models are presented for CYP6G1, a P450 associated with resistance to DDT and neonicotinoids, and two other enzymes associated with insecticide resistance in D. melanogaster, CYP12D1 and CYP6A2. The models are based on a template of the X-ray structure of the phylogenetically related human CYP3A4, which is known for its broad substrate specificity. The model of CYP6G1 has a much smaller active site cavity than the template. The cavity is also 'V'-shaped and is lined with hydrophobic residues, showing high shape and chemical complementarity with the molecular characteristics of DDT. Comparison of the DDT-CYP6G1 complex and a non-resistant CYP6A2 homology model implies that tight-fit recognition of this insecticide is important in CYP6G1. The active site can accommodate differently shaped substrates ranging from imidacloprid to malathion but not the pyrethroids permethrin and cyfluthrin. CONCLUSION The CYP6G1, CYP12D1 and CYP6A2 homology models can provide a structural insight into insecticide resistance in flies overexpressing P450 enzymes with broad substrate specificities.
RELIABILITY AND STATE MACHINES IN AN ADVANCED NETWORK TESTBED

Complex distributed systems have many components that fail from time to time, adversely affecting the system’s overall reliability. Our advanced network testbed, Emulab, also known as Netbed, is a complex timeand space-shared distributed system, composed of thousands of hardware and software components. Early versions of the Emulab system had reliability problems, could support experiments of only limited size, and were inefficient in resource use. Our thesis is that enhancing Emulab with better monitoring and control through a flexible framework based on state machines improves the reliability, scalability, performance, efficiency, and generality of the system. Reliability is key, because of its effect on scalability, performance and efficiency. Any solution used to address these issues must be general across a variety of workloads, and portable across different software and hardware configurations. Our results show improvement through faster error detection and recovery, better monitoring of testbed nodes, and prevention of race conditions. The state machine framework has also contributed to Emulab’s generality and portability by expanding the accepted workload, providing graceful degradation for less capable node configurations, and making it easier to add new node types to the testbed. For my family, past, present, and future
Indonesian perspective on massive open online courses: Opportunities and challenges

There are two indications that Indonesia needs to improve its education quality. The first is the Human Development Index (HDI), which is still at the medium level, and the second is the enrollment rate in higher education, which is also at the low level. MOOCs have the potential to solve both problems. However, implementing MOOCs in a developing country needs a specific analysis to determine the opportunities and challenges. This study aims to identify the opportunities and challenges in implementing MOOCs from an Indonesian perspective. We observed four local MOOCs and analyzed various documents, including literature and government regulations. As a result, this study identified seven opportunities and seven challenges in implementing MOOCs in Indonesia. Recommendations are also provided.
[Isolation and identification of steroidal saponins from Dioscorea panthaica Prain et Burkill].

AIM To investigate the chemical constituents of the rhizomes of Dioscorea panthaica Prain et Burkill and look for new active compounds. METHODS The compounds were isolated with silica gel and HPLC, and their structures were elucidated on the basis of chemical evidences and spectral analysis (IR, ESI-MS, 1HNMR, 13CNMR, DEPT, 1H-1H COSY, HMQC, HMBC, NOESY). RESULTS Three steroidal saponins were isolated from the rhizomes of Dioscorea panthaica. They were elucidated as 26-O-beta-D-glucopyranosyl-3 beta, 26-diol-23(S)-methoxy-25(R)-delta 5,20(22)-diene-furosta-3-O-[alpha-L-rhamnopyranosyl-(1-->2)- O-alpha-L-rhamnopyranosyl-(1-->4)]-beta-D-glucopyranoside (I), pseudoprotodioscin (II), 26-O-beta-D-glucopyranosyl-3 beta, 26-diol-25 (R)-delta 5,20(22)-diene-furosta-3-O-alpha-L-rhamnopyranosyl- (1-->2)-O-beta-D-glucopyranoside (III). CONCLUSION Compound I is a new steroidal saponin and was named as dioscoreside C. Compound II and III were obtained from this genus for the first time.
Multi-Agent Based Scheduling for Batch Process

A new approach to schedule batch process using a cooperative multi-agent system was proposed. The architecture of the system was developed and the cooperative problem solving process for online batch process scheduling using the multi-agent system was described. Finally, a practical application of the system was present. Research work shows that the proposed method can find an optimal scheduling plan according to the requirements posed by customer and can modify the scheduling plan online.