Miracle-dz/UniFAR-FTUs huggingface dataset:
Boosted Categorical Restricted Boltzmann Machine for Computational Prediction of Splice Junctions

Splicing refers to the elimination of noncoding regions in transcribed pre-messenger ribonucleic acid (RNA). Discovering splice sites is an important machine learning task that helps us not only to identify the basic units of genetic heredity but also to understand how different proteins are produced. Existing methods for splicing prediction have produced promising results, but often show limited robustness and accuracy. In this paper, we propose a deep belief network-basedmethodology for computational splice junction prediction. Our proposal includes a novel method for training restricted Boltzmann machines for class-imbalanced prediction. The proposed method addresses the limitations of conventional contrastive divergence and provides regularization for datasets that have categorical features. We tested our approach using public human genome datasets and obtained significantly improved accuracy and reduced runtime compared to state-of-the-art alternatives. The proposed approach was less sensitive to the length of input sequences and more robust for handling false splicing signals. Furthermore,we could discover noncanonical splicing patterns that were otherwise difficult to recognize using conventional methods. Given the efficiency and robustness of our methodology, we anticipate that it can be extended to the discovery of primary structural patterns of other subtle genomic elements.
Neurocognitive endophenotypes in a multiplex multigenerational family study of schizophrenia.

OBJECTIVE Genetic factors contribute to the development of schizophrenia where cognitive dysfunction is a hallmark. The purpose of this article was to examine computerized neurocognitive measures as candidate endophenotypic markers of liability for schizophrenia in a genetically informative cohort. METHOD European Americans from 35 multiplex multigenerational families (N=349) and healthy participants (N=154) underwent clinical assessments and neurocognitive measurements and provided blood samples. The neurocognitive measures included performance (accuracy and speed) from a computerized battery that assessed abstraction/mental flexibility; attention; verbal, face, and spatial memory; spatial processing; sensorimotor processing; and emotion intensity discrimination. RESULTS Probands, relatives, and comparison subjects differed from each other in performance. Probands demonstrated greatest impairment relative to comparison subjects, followed by family members. Liability for schizophrenia affected the speed-accuracy tradeoff differently for specific neurocognitive domains. Significant heritability estimates were obtained for accuracy of verbal, facial, and spatial memory and spatial and emotion processing. For speed, estimates of heritability were significant for abstraction/mental flexibility, attention, face memory, and spatial and sensorimotor processing. CONCLUSIONS In a multigenerational multiplex design, the authors demonstrated that neurocognitive measures are associated with schizophrenia, differentiate unaffected relatives from comparison subjects, and may have significant presumed heritability. Therefore, they are endophenotypes suitable for genetic studies. Accuracy and speed can be differentially sensitive to presumed genetic liability.
Zero Resource Speaking Rate Estimation from Change Point Detection of Syllable-like Units

Speaking rate is an important attribute of the speech signal which plays a crucial role in the performance of automatic speech processing systems. In this paper, we propose to estimate the speaking rate by segmenting the speech into syllable-like units using end point detection algorithms which do not require any training and fine-tuning. Also, there are no predefined constraints on the expected number of syllabic segments. The acoustic subword units are obtained only from speech signal to estimate the speaking rate without any requirement of transcriptions or phonetic knowledge of the speech data. A recent theta-rate oscillator based syllabification algorithm is also employed for speaking rate estimation. The performance is evaluated on TIMIT corpus and spontaneous speech from Switchboard corpus. The correlation results are comparable to recent algorithms which are trained with specific training set and/or make use of the available transcriptions.
Trends in dolphin abundance estimated from fisheries data: A cautionary note

The previously published index of relative abundance of the northeastern offshore stock of spotted dolphins, the species most affected by the purse-seine fishery for tunas in the eastern Pacific Ocean, shows a decreasing trend in the last two decades despite dramatic reductions in incidental mortality since the early 1970s. To better understand the behaviour of this index, the effects of changes in data quality and methods of searching on estimation of relative abundance using current methodologies have been studied here. Changes in data quality since the late 1980s have led to a dramatic reduction in the proportion of sightings that are reported on or near the trackline. The decreasing trend in the index in the late 1970s and through the 1980s is strongly influenced by the fit of the detection function to the high proportion of sightings near the trackline that was present in the data during that time period. If this excess of sightings near the trackline is spurious, then much of the decreasing trend in the index over this time period is likely spurious. In addition, part of the decrease in the index in the late 1980s to mid-1990s is probably due to changes in data-collection biases that result from a dramatic increase in the amount of searching that is currently being carried out using helicopters as compared to high-powered binoculars. The results suggest that trends in bias associated with changes in data quality and fishery operations may have contributed to a trend in the index on the order of 1.0-1.5% per year, or approximately 25-33% of the maximum growth rate of the northeastern stock of offshore spotted dolphin. The pervasive nature of these sources of bias, and their potential magnitude relative to the maximum growth rates of the dolphin species involved, make use of this index in population growth models ill-advised. Fishery-derived indices such as these may be most useful for comparing trends in relative abundance between species, when the sources of biases are unlikely to be species-specific.
Mono-camera based localization using digital map

This paper reports an image-based localization for automated vehicle. The proposed method utilizes a mono-camera and a low-cost velocity and inertial sensor to estimate the vehicle pose. Image template matching is applied to provide a correlation distribution between the captured image and a vector structured digital map. A probability of the vehicle pose is then updated using the obtained correlation. The experiments were carried out for real driving data on an expressway. We evaluated the proposed method for daytime and nighttime driving data under different lighting conditions. The results have verified that the proposed method estimates reasonable positioning errors on real-time comparing with a low-cost GNSS/INS.
Multi-Objective Dynamic VAR Planning Against Short-Term Voltage Instability Using a Decomposition-Based Evolutionary Algorithm

Short-term voltage stability is an increasing concern in today's power systems due to the growing penetration of induction motors. This paper proposes a systematic method for optimal placement of dynamic VAR support against short-term voltage instability. The problem is formulated as a multi-objective optimization model minimizing two conflicting objectives: 1) the total investment cost and 2) the expected unacceptable short-term voltage performance subject to a set of probable contingencies. STATCOM is employed for its stronger dynamic VAR support capability. Indices for quantifying the short-term voltage stability and the related risk level are proposed for problem modeling. Candidate buses are selected based on the concept of trajectory sensitivity. Load dynamics are fully considered using a composite load model containing induction motor and other typical components. A relatively new and superior multi-objective evolutionary algorithm called MOEA/D is introduced and employed to find the Pareto optimal solutions of the model. The proposed method is verified on the New England 39-bus system using industry-grade models and simulation tool.
3D Measurement Based on Row-wise LT Matrix Estimation

3D Measurement is an essential element of robotics for industrial usage. Many methods have been proposed so far, but some objects with specular reﬂections or subsurface scatterings are diﬃcult to measure the shape accurately. We have developed a new method by using projector-camera Light Transport (LT) Matrix. LT Matrix is often used in computer graphics to make relighting images, light path understanding, and 3D measurement. It is useful for describing light paths on projector-camera system because it includes all light reﬂection information. However, it takes a long time to measure LT Matrix accurately. This paper ﬁrst proposes how to obtain 3D shape from LT Matrix. Then we propose fast LT Matrix estimation method by using its sparseness. Our method can estimate accurate LT Matrix to obtain 3D shape in short time. Finally, we compare our results and previous 3D measurement methods, and we conclude our methods performs much better than other methods for metallic or transparent objects
Dehiscence and fenestration in patients with different vertical growth patterns assessed with cone-beam computed tomography.

OBJECTIVE To test the null hypothesis that the presence of alveolar defects (dehiscence and fenestration) was not different among patients with different vertical growth patterns. MATERIALS AND METHODS A total of 1872 teeth in 26 hyper-divergent (mean age: 24.4 ± 4.8 years), 27 hypo-divergent (mean age: 25.1 ± 4.5 years), and 25 normo-divergent (mean age: 23.6 ± 4.1 years) patients with no previous orthodontic treatment were evaluated using cone-beam computed tomography. Axial and cross-sectional views were evaluated with regard to whether dehiscence and/or fenestration on buccal and lingual surfaces existed or not. For statistical analysis, the Pearson chi-square test was used at a P < . 05 significance level. RESULTS According to the statistical analysis, the hypo-divergent group (6.56%) had lower dehiscence prevalence than the hyper-divergent (8.35%) and normo-divergent (8.18%) groups (P = .004). Higher prevalences of dehiscence and fenestration were found on buccal sides in all vertical growth patterns. While fenestration was a common finding for the maxillary alveolar region, dehiscence was a common finding in the mandible in all groups. CONCLUSION The null hypothesis was rejected. Although the prevalence of fenestrations was not different, significant differences for dehiscences were found in patients with different vertical growth patterns.
SOME CONSIDERATIONS ABOUT STABILITY STUDY DESIGN

The aim of a stability study is to check whether or not a drug maintains its initial properties (over a given range) in a period of time. There are many parameters considered in a stability study, but in this paper only the active content will be considered. Evaluation of this parameter is performed by measuring the content of the active ingredient in the drug at different times and on expiration to see if it is within specification [1]. The problem also involves estimating whether the drug will perform satisfactorily and maintain its initial properties in the future. In this paper, we provide a criterion for the evaluation of experimental design used in a stability study for predicting the content of an active ingredient in a drug, starting from the confidence limit calculated following International Conference on Harmonisation of Technical Requirements for the Registration of Pharmaceuticals for Human Use (ICH) recommendations. The point of view adopted is akin to hypothesis testing. The main question is this: “If the drug fulfills the requirements at a given time in the future, what is the probability that the data collected for that drug will show its suitability? ” For this purpose, two concepts are used—producer gain and consumer loss—which are defined as follows: producer gain is the advantage (for the producer) of recognizing a drug as “good” (provided it is good and within specification); consumer loss is the loss (for the consumer) when the drug is no longer good, but the data collected indicate that it is good. The aim of the experimental design in this study is to increase the probability of producer gain and maximize it on the basis of a given consumer loss.
Nicotine treatment for ulcerative colitis.

Ulcerative colitis and Crohn’s disease are chronic inflammatory bowel diseases of unknown aetiology which, although similar in various aspects, exhibit some contrasting features. A typical example is their relationship with cigarette smoking. While smoking appears to exert deleterious effects in Crohn’s disease [1, 2], there is overwhelming epidemiological evidence that smoking protects against ulcerative colitis, the risk of developing the disease being significantly lower in smokers than in non-smokers or former smokers [2, 3]. The fact that patients with ulcerative colitis who resume or start smoking often experience clinical improvement [4] prompted attempts to verify the hypothesis that nicotine might be the active component of smoking responsible for the beneficial effects on the course of the disease. Preliminary, uncontrolled observations employing nicotine gum, a pharmaceutical form generally poorly tolerated, yielded encouraging but inconclusive results [5]. The introduction of transdermal nicotine in the market made it possible to assess the potential therapeutic role of nicotine in a more extensive way.
Metabolic Fingerprinting of Pseudomonas putida DOT-T1E Strains: Understanding the Influence of Divalent Cations in Adaptation Mechanisms Following Exposure to Toluene

Pseudomonas putida strains can adapt and overcome the activity of toxic organic solvents by the employment of several resistant mechanisms including efflux pumps and modification to lipopolysaccharides (LPS) in their membranes. Divalent cations such as magnesium and calcium play a crucial role in the development of solvent tolerance in bacterial cells. Here, we have used Fourier transform infrared (FT-IR) spectroscopy directly on cells (metabolic fingerprinting) to monitor bacterial response to the absence and presence of toluene, along with the influence of divalent cations present in the growth media. Multivariate analysis of the data using principal component-discriminant function analysis (PC-DFA) showed trends in scores plots, illustrating phenotypic alterations related to the effect of Mg2+, Ca2+ and toluene on cultures. Inspection of PC-DFA loadings plots revealed that several IR spectral regions including lipids, proteins and polysaccharides contribute to the separation in PC-DFA space, thereby indicating large phenotypic response to toluene and these cations. Finally, the saturated fatty acid ratio from the FT-IR spectra showed that upon toluene exposure, the saturated fatty acid ratio was reduced, while it increased in the presence of divalent cations. This study clearly demonstrates that the combination of metabolic fingerprinting with appropriate chemometric analysis can result in practicable knowledge on the responses of important environmental bacteria to external stress from pollutants such as highly toxic organic solvents, and indicates that these changes are manifest in the bacterial cell membrane. Finally, we demonstrate that divalent cations improve solvent tolerance in P. putida DOT‑T1E strains.
A Web-based approach to interactive visualization in context

This paper proposes a framework for easily integrating and controlling information visualization (infoVis) components within web pages to create powerful interactive “live” documents, or LiveDocs. The framework includes a set of infoVis components which can be placed and linked within a standard HTML document, initialized to focus on key analysis results, and directly manipulated by readers to explore and analyze data further. In addition, authors can script the manipulation of views at the user interaction level (e.g., to set view options, select items within a view, or animate a view). We illustrate our approach with a sample analysis of a real-life data set.
Changes in protein expression in the salt marsh mussel Geukensia demissa: evidence for a shift from anaerobic to aerobic metabolism during prolonged aerial exposure

During aerial exposure (emersion), most sessile intertidal invertebrates experience cellular stress caused by hypoxia, and the amount and types of hypoxia-induced stress will differ as exposure time increases, likely leading to altered metabolic responses. We examined proteomic responses to increasing emersion times and decreasing recovery (immersion) times in the mussel Geukensia demissa, which occurs in salt marshes along the east coast of North America. Individuals are found above mean tide level, and can be emersed for over 18 h during spring tides. We acclimated mussels to full immersion at 15°C for 4 weeks, and compared changes in gill protein expression between groups of mussels that were continually immersed (control), were emersed for 6 h and immersed during recovery for 18 h (6E/18R), were emersed for 12 h and recovered for 12 h (12E/12R), or were emersed for 18 h with a 6 h recovery (18E/6R). We found clear differences in protein expression patterns among the treatments. Proteins associated with anaerobic fermentation increased in abundance in 6E/18R but not in 12E/12R or 18E/6R. Increases in oxidative stress proteins were most apparent in 12E/12R, and in 18E/6R changes in cytoskeletal protein expression predominated. We conclude that G. demissa alters its strategy for coping with emersion stress over time, relying on anaerobic metabolism for short- to medium-duration exposure, but switching to an air-gaping strategy for long-term exposure, which reduces hypoxia stress but may cause structural damage to gill tissue.
Bilingual Autoencoders with Global Descriptors for Modeling Parallel Sentences

Parallel sentence representations are important for bilingual and cross-lingual tasks in natural language processing. In this paper, we explore a bilingual autoencoder approach to model parallel sentences. We extract sentence-level global descriptors (e.g. min, max) from word embeddings, and construct two monolingual autoencoders over these descriptors on the source and target language. In order to tightly connect the two autoencoders with bilingual correspondences, we force them to share the same decoding parameters and minimize a corpus-level semantic distance between the two languages. Being optimized towards a joint objective function of reconstruction and semantic errors, our bilingual antoencoder is able to learn continuous-valued latent representations for parallel sentences. Experiments on both intrinsic and extrinsic evaluations on statistical machine translation tasks show that our autoencoder achieves substantial improvements over the baselines.
[Influence of institutional factors in neurological, medical and geriatric departments on length of stay in patients with stroke].

BACKGROUND Length of hospital stay (LOS) is determined not only by medical procedures or complications but also by institutional factors. We examined the influence of various institutional factors in neurological, medical and geriatric departments on LOS in patients with ischemic stroke. METHODS We used data of 12,410 patients from the Westphalian Stroke Register for the years 2000 and 2001. Forty-two centres including 24 neurological, 13 medical and five geriatric departments participated in the register. The register is based on a standardized data assessment, including patient-related sociodemographic and clinical items, diagnostic and treatment procedures, complications, and status at discharge. RESULTS 7855 patients with ischemic stroke from 37 centres (median age: 73 years, 51 % female) were included in the analysis. In neurological departments, the LOS decreased with increasing numbers of stroke patients treated per centre and year, presence of a stroke unit or a rehabilitation unit. Conversely, the ratio beds to number of physicians was positively associated with LOS. In geriatric departments, a significant decrease in LOS with an increasing number of stroke cases and availability of a rehabilitation unit was also observed. In departments of medicine, no significant influence on LOS was found for the institutional factors analysed. CONCLUSIONS Institutional factors have a significant influence on LOS in patients with stroke. In this analysis, the influence varied between the different medical specialties. Institutional factors gain importance in the management of stroke patients, when Diagnosis Related Groups (DRG) are introduced.
Software versus hardware shared-memory implementation: a case study

Compares the performance of software-supported shared memory on a general-purpose network to hardware-supported shared memory on a dedicated interconnect. Up to eight processors, the results are based on the execution of a set of application programs on a SGI 4D/480 multiprocessor and on TreadMarks, a distributed shared memory system that runs on a Fore ATM LAN of DECstation-5000/240s. Since the DECstation and the 4D/480 use the same processor, primary cache, and compiler, the shared-memory implementation is the principal difference between the systems. Beyond eight processors, the results are based on execution-driven simulation. Specifically, the authors compare a software implementation on a general-purpose network of uniprocessor nodes, a hardware implementation using a directory-based protocol on a dedicated interconnect, and a combined implementation using software to provide shared memory between multiprocessor nodes with hardware implementing shared memory within a node. <<ETX>>
Molecular, pharmacological, and signaling properties of octopamine receptors from honeybee (Apis mellifera) brain

G protein‐coupled receptors are important regulators of cellular signaling processes. Within the large family of rhodopsin‐like receptors, those binding to biogenic amines form a discrete subgroup. Activation of biogenic amine receptors leads to transient changes of intracellular Ca2+‐([Ca2+]i) or 3′,5′‐cyclic adenosine monophosphate ([cAMP]i) concentrations. Both second messengers modulate cellular signaling processes and thereby contribute to long‐lasting behavioral effects in an organism. In vivo pharmacology has helped to reveal the functional effects of different biogenic amines in honeybees. The phenolamine octopamine is an important modulator of behavior. Binding of octopamine to its receptors causes elevation of [Ca2+]i or [cAMP]i. To date, only one honeybee octopamine receptor that induces Ca2+ signals has been molecularly and pharmacologically characterized. Here, we examined the pharmacological properties of four additional honeybee octopamine receptors. When heterologously expressed, all receptors induced cAMP production after binding to octopamine with EC50s in the nanomolar range. Receptor activity was most efficiently blocked by mianserin, a substance with antidepressant activity in vertebrates. The rank order of inhibitory potency for potential receptor antagonists was very similar on all four honeybee receptors with mianserin >> cyproheptadine > metoclopramide > chlorpromazine > phentolamine. The subroot of octopamine receptors activating adenylyl cyclases is the largest that has so far been characterized in arthropods, and it should now be possible to unravel the contribution of individual receptors to the physiology and behavior of honeybees.