Miracle-dz/UniFAR-FTUs huggingface dataset:
A dissimilarity-based approach to predictive maintenance with application to HVAC systems

The goal of predictive maintenance is to forecast the occurrence of faults of an appliance, in order to proactively take the necessary actions to ensure its availability. In many application scenarios, predictive maintenance is applied to a set of homogeneous appliances. In this paper, we firstly review taxonomies and main methodologies currently used for condition-based maintenance; secondly, we argue that the mutual dissimilarities of the behaviours of all appliances of this set (the "cohort") can be exploited to detect upcoming faults. Specifically, inspired by dissimilarity-based representations, we propose a novel machine learning approach based on the analysis of concurrent mutual differences of the measurements coming from the cohort. We evaluate our method over one year of historical data from a cohort of 17 HVAC (Heating, Ventilation and Air Conditioning) systems installed in an Italian hospital. We show that certain kinds of faults can be foreseen with an accuracy, measured in terms of area under the ROC curve, as high as 0.96.
Optimization of Extraction of Phenolic Compounds from Avicennia marina (Forssk.)Vierh using Response Surface Methodology

Optimization of extraction of phenolic compounds from Avicennia marina using response surface methodology was carried out during the present study. Five levels, three factors rotatable design (CCRD) was utilized to examine the optimum combination of extraction variables based on the TPC of Avicennia marina leaves. The best combination of response function was 78.41 °C, drying temperature; 26.18°C; extraction temperature and 36.53 minutes of extraction time. However, the procedure can be promptly extended to the study of several others pharmaceutical processes like purification of bioactive substances, drying of extracts and development of the pharmaceutical dosage forms for the benefit of consumers. Keywords—Avicennia marina, Central Composite Rotatable Design (CCRD), Response Surface Methodology, Total Phenolic contents (TPC)
Adaptive fuzzy systems for backing up a truck-and-trailer

Fuzzy control systems and neural-network control systems for backing up a simulated truck, and truck-and-trailer, to a loading dock in a parking lot are presented. The supervised backpropagation learning algorithm trained the neural network systems. The robustness of the neural systems was tested by removing random subsets of training data in learning sequences. The neural systems performed well but required extensive computation for training. The fuzzy systems performed well until over 50% of their fuzzy-associative-memory (FAM) rules were removed. They also performed well when the key FAM equilibration rule was replaced with destructive, or ;sabotage', rules. Unsupervised differential competitive learning (DCL) and product-space clustering adaptively generated FAM rules from training data. The original fuzzy control systems and neural control systems generated trajectory data. The DCL system rapidly recovered the underlying FAM rules. Product-space clustering converted the neural truck systems into structured sets of FAM rules that approximated the neural system's behavior.
Guided Internet-delivered cognitive behavioural treatment for insomnia: a randomized trial

Background Insomnia is a prevalent problem with a high burden of disease (e.g. reduced quality of life, reduced work capacity) and a high co-morbidity with other mental and somatic disorders. Cognitive behavioural therapy (CBT) is effective in the treatment of insomnia but is seldom offered. CBT delivered through the Internet might be a more accessible alternative. In this study we examined the effectiveness of a guided Internet-delivered CBT for adults with insomnia using a randomized controlled trial (RCT). Method A total of 118 patients, recruited from the general population, were randomized to the 6-week guided Internet intervention (n = 59) or to a wait-list control group (n = 59). Patients filled out an online questionnaire and a 7-day sleep diary before (T0) and after (T1) the 6-week period. The intervention group received a follow-up questionnaire 3 months after baseline (T2). Results Almost three-quarters (72.9%) of the patients completed the whole intervention. Intention-to-treat (ITT) analysis showed that the treatment had statistically significant medium to large effects (p < 0.05; Cohen's d between 0.40 and 1.06), and resulted more often in clinically relevant changes, on all sleep and secondary outcomes with the exception of sleep onset latency (SOL) and number of awakenings (NA). There was a non-significant difference in the reduction in sleep medication between the intervention (a decrease of 6.8%) and control (an increase of 1.8%) groups (p = 0.20). Data on longer-term effects were inconclusive. Conclusions This study adds to the growing body of literature that indicates that guided CBT for insomnia can be delivered through the Internet. Patients accept the format and their sleep improves.
Sound event detection using non-negative dictionaries learned from annotated overlapping events

Detection of overlapping sound events generally requires training class models either from separate data for each class or by making assumptions about the dominating events in the mixed signals. Methods based on sound source separation are currently used in this task, but involve the problem of assigning separated components to sources. In this paper, we propose a method which bypasses the need to build separate sound models. Instead, non-negative dictionaries for the sound content and their annotations are learned in a coupled sense. In the testing stage, time activations of the sound dictionary columns are estimated and used to reconstruct annotations using the annotation dictionary. The method requires no separate training data for classes and in general very promising results are obtained using only a small amount of data.
Delft University of Technology An Experience Report on Applying Passive Learning in a Large-Scale Payment

Passive learning techniques infer graph models on the behavior of a system from large trace logs. The research community has been dedicating great effort in making passive learning techniques more scalable and ready to use by industry. However, there is still a lack of empirical knowledge on the usefulness and applicability of such techniques in large scale real systems. To that aim, we conducted action research over nine months in a large payment company. Throughout this period, we iteratively applied passive learning techniques with the goal of revealing useful information to the development team. In each iteration, we discussed the findings and challenges to the expert developer of the company, and we improved our tools accordingly. In this paper, we present evidence that passive learning can indeed support development teams, a set of lessons we learned during our experience, a proposed guide to facilitate its adoption, and current research challenges. Keywords-passive learning, experience report, dfasat.
18F-FluoroDeoxyGlucose Uptake of Bone and Soft Tissue Sarcomas in Pediatric Patients

A high 18F-fluorodeoxyglucose (FDG) uptake by positron emission tomography/computed tomography (PET/CT) imaging in sarcomas of adults has been reported. The current study aimed at defining the degree of 18F-FDG uptake of pediatric sarcomas. This retrospective study included 29 patients (23 males, 6 females; mean age 14 ± 5 years) with soft tissue (n = 9) or bone (n = 20) sarcomas. Twenty-two patients (76%) underwent 18F-FDG PET/CT and 7 (24%) had dedicated 18F-FDG PET studies. Tumor 18F-FDG uptake was quantified by standard uptake value (SUV)max and tumor-to-liver ratios (SUV ratios; tumor SUVmax/liver SUVmean). Tumor SUVmax and SUV ratios were correlated with tumor Ki-67 expression. SUVmax ranged from 1.4 to 24 g/mL (median 2.5 g/mL) in soft tissue sarcomas and 1.6 to 20.4 g/mL (median 6.9 g/mL) in bone sarcomas (P = .03), and from 1.6 to 9.2 g/mL (median 3.9 g/mL) and 3.5 to 20.4 g/mL (median 12 g/mL) in Ewing sarcoma and osteosarcoma, respectively (P = .009). Tumor SUV ratios ranged from 0.8 to 8.7 (median 1.9) in soft tissue sarcomas and 1.4 to 8.9 (median 3.8) in bone sarcomas (P = .08). Ewing sarcoma had a significantly lower tumor SUV ratio than osteosarcoma (P = .01). Ki-67 expression correlated significantly with the 18F-FDG uptake in bone but not in soft tissue sarcomas. All sarcomas were visualized by 18F-FDG PET/CT imaging. A higher 18F-FDG uptake was observed in osteosarcoma than in Ewing and soft tissue sarcomas. The results of this study suggest that the degree of tumor 18F-FDG uptake is sufficient to allow for monitoring of therapeutic responses in pediatric sarcomas.
Bacterial evolution through the selective loss of beneficial Genes. Trade-offs in expression involving two loci.

The loss of preexisting genes or gene activities during evolution is a major mechanism of ecological specialization. Evolutionary processes that can account for gene loss or inactivation have so far been restricted to one of two mechanisms: direct selection for the loss of gene activities that are disadvantageous under the conditions of selection (i.e., antagonistic pleiotropy) and selection-independent genetic drift of neutral (or nearly neutral) mutations (i.e., mutation accumulation). In this study we demonstrate with an evolved strain of Escherichia coli that a third, distinct mechanism exists by which gene activities can be lost. This selection-dependent mechanism involves the expropriation of one gene's upstream regulatory element by a second gene via a homologous recombination event. Resulting from this genetic exchange is the activation of the second gene and a concomitant inactivation of the first gene. This gene-for-gene expression tradeoff provides a net fitness gain, even if the forfeited activity of the first gene can play a positive role in fitness under the conditions of selection.
Detecting cell-in-cell structures in human tumor samples by E-cadherin/CD68/CD45 triple staining

Although Cell-in-cell structures (CICs) had been documented in human tumors for decades, it is unclear what types of CICs were formed largely due to low resolution of traditional way such as H&E staining. In this work, we employed immunofluorescent method to stain a panel of human tumor samples simultaneously with antibodies against E-cadherin for Epithelium, CD68 for Macrophage and CD45 for Leukocytes, which we termed as “EML method” based on the cells detected. Detail analysis revealed four types of CICs, with tumor cells or macrophage engulfing tumor cells or leukocytes respectively. Interestingly, tumor cells seem to be dominant over macrophage (93% vs 7%) as the engulfer cells in all CICs detected, whereas the overall amount of internalized tumor cells is comparable to that of internalized CD45+ leukocytes (57% vs 43%). The CICs profiles vary from tumor to tumor, which may indicate different malignant stages and/or inflammatory conditions. Given the potential impacts different types of CICs might have on tumor growth, we therefore recommend EML analysis of tumor samples to clarify the correlation of CICs subtypes with clinical prognosis in future researches.
Assimilation of agile practices in use

Agile method use in information systems development (ISD) has grown dramatically in recent years. The emergence of these alternative approaches was very much industry‐led at the outset, and while agile method research is growing, the vast majority of these studies are descriptive and often lack a strong theoretical and conceptual base. Insights from innovation adoption research can provide a new perspective on analysing agile method use. This paper is based on an exploratory study of the application of the innovation assimilation stages to understand the use of agile practices, focusing in particular on the later stages of assimilation, namely acceptance, routinisation and infusion. Four case studies were conducted, and based on the case study findings, the concepts of acceptance, routinisation and infusion were adapted and applied to agile software development. These adapted concepts were used to glean interesting insights into agile practice use. For example, it was shown that the period of use of agile practices does not have a proportional effect on their assimilation depths. We also reflected on the sequential assumption underlying the assimilation stages, showing that adopting teams do not always move through the assimilation stages in a linear manner.
A Novel Fuzzy Histogram Based Estimation of Distribution Algorithm for Global Numerical Optimization

Applying Estimation of Distribution Algorithms (EDAs) to solve continuous problems is a significant and challenging task in the field of evolutionary computation. So far, various continuous EDAs have been developed based on different probability models. Initially, the EDAs based on a single Gaussian probability model are widely used but they have trouble in solving multimodal problems. Later EDAs based on a mixture model and on a clustering technique are then introduced to conquer such drawback. However, they are either time consuming or need prior knowledge of the problems. Recently, the histogram has begun to be used in continuous EDAs, but the histogram based EDAs (HEDAs) usually need too much time and space to gain a highly accurate solution. On the basis of pioneering contributions, this paper proposes a fuzzy histogram based EDA (FHEDA) for continuous optimization. In the FHEDA, the estimated range of the fuzzy histogram is adjusted adaptively by the current promising solutions, which leads the algorithm to search good solutions efficiently. A mutation mechanism is also introduced in the sampling operation to avoid being trapped in local optima. The performance of the proposed FHEDA is evaluated by testing seven benchmark functions with different characteristics. Two Gaussian based EDAs and the sur-shr-HEDA are studied for comparison. The results show that among all experimental algorithms, the FHEDA can give comparatively satisfying performance on unimodal and multimodal functions.
The Arabidopsis C 3 H 2 C 3-Type RING E 3 Ubiquitin Ligase AtAIRP 1 Is a Positive Regulator of an Abscisic Acid-Dependent Response to Drought Stress 1 [ C ] [ W ] [ OA ]

Ubiquitination is a eukaryotic posttranslational protein modification that is mediated by the cascade of E1, E2, and E3 ubiquitin (Ub) ligases and is involved in regulating numerous cellular functions. In this study, we obtained 100 different Arabidopsis (Arabidopsis thaliana) T-DNA insertion mutant plants in which RING E3 Ub ligase genes were suppressed and monitored their phenotypes in the presence of exogenous abscisic acid (ABA), a plant stress hormone. One of these loss-of-function mutants displayed ABA-insensitive phenotypes at the germination stage and was named atairp1 (for Arabidopsis ABA-insensitive RING protein 1). AtAIRP1 encodes a cytosolic protein containing a single C3H2C3-type RING motif with in vitro E3 Ub ligase activity. AtAIRP1 was significantly induced by ABA and drought stress. In contrast to atairp1 mutant plants, AtAIRP1overexpressing transgenic plants (35S:AtAIRP1-sGFP) were hypersensitive to exogenous ABA in terms of radicle emergence, cotyledon development, root elongation, and stomatal closure. Ectopic expression of AtAIRP1-sGFP in atairp1 effectively rescued the loss-of-function ABA-insensitive phenotype. Both 35S:AtAIRP1-sGFP and atairp1/35S:AtAIRP1-sGFP plants accumulated higher amounts of hydrogen peroxide in response to exogenous ABA than did wild-type and atairp1 mutant plants. AtAIRP1 overexpressors were markedly tolerant to severe drought stress, as opposed to atairp1, which was highly susceptible. The levels of drought stress-related genes and basic leucine zipper transcription factor genes were up-regulated in the 35S:AtAIRP1-sGFP lines relative to wild-type and atairp1 mutant plants in response to ABA. Overall, these results suggest that AtAIRP1, a C3H2C3-type RING E3 Ub ligase, is a positive regulator in the Arabidopsis ABA-dependent drought response.
AvrPto-dependent Pto-interacting proteins and AvrPto-interacting proteins in tomato.

The plant-intracellular interaction of the avirulence protein AvrPto of Pseudomonas syringae pathovar tomato, the agent of bacterial speck disease, and the corresponding tomato resistance protein Pto triggers responses leading to disease resistance. Pto, a serine/threonine protein kinase, also interacts with a putative downstream kinase, Pto-interactor 1, as well as with members of a family of transcription factors Pto-interactors 4, 5, and 6. These proteins are likely involved, respectively, in a phosphorylation cascade resulting in hypersensitive cell death, and in defense gene activation. The mechanism by which the interaction of AvrPto and Pto initiates defense response signaling is not known. To pursue the hypothesis that tertiary interactions are involved, we modified the yeast two-hybrid protein interaction trap and conducted a search for tomato proteins that interact with Pto only in the presence of AvrPto. Five classes of AvrPto-dependent Pto interactors were isolated, and their interaction specificity confirmed. Also, to shed light on a recently demonstrated virulence activity of AvrPto, we conducted a standard two-hybrid screen for tomato proteins in addition to Pto that interact with AvrPto: i.e., potential virulence targets or modifiers of AvrPto. By constructing an N-terminal rather than a C-terminal fusion of AvrPto to the LexA DNA binding domain, we were able to overcome autoactivation by AvrPto and identify four classes of specific AvrPto-interacting proteins.
Visualizing the "Big Picture" of Change in NCIt's Biological Processes

The National Cancer Institute thesaurus (NCIt) is a large and complex ontology. NCIt is frequently updated; a new release is made available approximately every month. Tracking structural changes in NCIt is important for the editors of its content. In this paper we describe a methodology and tool using diff partial-area taxonomies to visually summarize structural changes between two NCIt releases. Diff partial-area taxonomies provide a comprehensible view of the overall impact of the changes. This methodology is illustrated using the Biological Process hierarchy. Specifically, we illustrate how diff partial-area taxonomies reflect change that occurred due to major restructuring of this hierarchy between September 2004 and December 2004. During this time the hierarchy nearly doubled in size and a large portion of the classes were extensively modified. Several kinds of change patterns are identified and discussed. Keywords— ontology change; ontology visualization; ontology big picture; NCIt; abstraction network
Murine model of chronic human asthma

Human asthma is associated with acute and chronic inflammation of the airway mucosa, accompanied by airway wall remodelling. Experimental models of acute allergic bronchopulmonary inflammation in mice are useful for investigation of immunological mechanisms and of cellular recruitment, but have significant limitations because they fail to reproduce a number of characteristic lesions of human asthma, while usually being associated with marked alveolitis. We have developed an improved murine model of asthma that exhibits almost all of the morphological and functional changes that typify the human disease, without any confounding alveolitis. This model has considerable potential for the investigation of pathogenetic mechanisms and potential treatments of chronic human asthma.
Analysis of the stress state in an Iosipescu sheartest specimen

The state of stress in an Iosipescu shear test specimen is analyzed, utilizing a finite element computer program. The influence of test fixture configuration on this stress state is included. Variations of the standard specimen configuration, including notch depth, notch angle, and notch root radius are modeled. The purpose is to establish guidelines for a specimen geometry which will accommodate highly orthotropic materials while minimizing stress distribution nonuniformities. Materials ranging from isotropic to highly orthotropic are considered. An optimum specimen configuration is suggested, along with changes in the test fixture.
The voice-hearer

Background For 25 years, the international Hearing Voices Movement and the UK Hearing Voices Network have campaigned to improve the lives of people who hear voices. In doing so, they have introduced a new term into the mental health lexicon: “the voice-hearer. ” Aims This article offers a “thick description” of the figure of “the voice-hearer. ” Method A selection of prominent texts (life narratives, research papers, videos and blogs), the majority produced by people active in the Hearing Voices or consumer/survivor/ex-patient movements, were analysed from an interdisciplinary medical humanities perspective. Results “The voice-hearer” (i) asserts voice-hearing as a meaningful experience, (ii) challenges psychiatric authority and (iii) builds identity through sharing life narrative. While technically accurate, the definition of “the voice-hearer” as simply “a person who has experienced voice-hearing or auditory verbal hallucinations” fails to acknowledge that this is a complex, politically resonant and value-laden identity. Conclusions The figure of “the voice-hearer” comes into being through a specific set of narrative practices as an “expert by experience” who challenges the authority and diagnostic categories of mainstream psychiatry, especially the category of “schizophrenia. ”
Characteristic of Textual Information in Video Data from the Perspective of Natural Language Processing

1. EXTENDED ABSTRACT Due to the recent advances in computing, storage and network technologies, a vast amount of digital information in forms of text, images, audio and videos are widely distributed to users on demand. In order to efficiently retrieve an interesting portion of information, semantic knowledge extraction is essential. To this end, we are exploring semantic knowledge extraction from a large amount of video data, called “video data mining” [5, 6, 7]. Our objective at this symposium is to discuss with NLP experts how we could manage and exploit textual information in video data.
Motion of nanobeads proximate to plasma membranes during single particle tracking

Drag and torque on nanobeads translating within the pericellular layer while attached to glycolipids of the plasma membrane are calculated by a novel hydrodynamic model. The model considers a bead that translates proximate to a rigid planar interface that separates two distinct Brinkman media. The hydrodynamic resistance is calculated numerically by a modified boundary integral equation formulation, where the pertinent boundary conditions result in a hybrid system of Fredholm integrals of the first and second kinds. The hydrodynamic resistance on the translating bead is calculated for different combinations of the Brinkman screening lengths in the two layers, and for different viscosity ratios. Depending on the bead-membrane separation and on the hydrodynamic properties of both the plasma membrane and the pericellular layer, the drag on the bead may be affected by the properties of the plasma membrane. The Stokes-Einstein relation is applied for calculating the diffusivity of probes (colloidal gold nanobeads attached to glycolipids) in the plasma membrane. This approach provides an alternative way for the interpretation of in vitro observations during single particle tracking procedure, and predicts new properties of the plasma membrane structure.