gebhart/patrepeval huggingface dataset:
Model-Agnostic Interpretability of Machine Learning (2016)

Understanding why machine learning models behave the way they do empowers both system designers and end-users in many ways: in model selection, feature engineering, in order to trust and act upon the predictions, and in more intuitive user interfaces. Thus, interpretability has become a vital concern in machine learning, and work in the area of interpretable models has found renewed interest. In some applications, such models are as accurate as non-interpretable ones, and thus are preferred for their transparency. Even when they are not accurate, they may still be preferred when interpretability is of paramount importance. However, restricting machine learning to interpretable models is often a severe limitation. In this paper we argue for explaining machine learning predictions using model-agnostic approaches. By treating the machine learning models as black-box functions, these approaches provide crucial flexibility in the choice of models, explanations, and representations, improving debugging, comparison, and interfaces for a variety of users and models. We also outline the main challenges for such methods, and review a recently-introduced model-agnostic explanation approach (LIME) that addresses these challenges.
Fibroid-related Menorrhagia: Treatment with Superselective Embolization of the Uterine Arteries and Midterm Follow-up (2000)

Superselective arterial embolization of the uterine arteries is an effective means of controlling symptomatic uterine leiomyoma. However, the ideal embolic regimen remains to be determined.
Spectral Analysis Of A Signal Driven Sampling Scheme (2006)

Publication in the conference proceedings of EUSIPCO, Florence, Italy, 2006
PD-L1 and CD8<sup>+</sup>PD1<sup>+</sup> lymphocytes exist as targets in the pediatric tumor microenvironment for immunomodulatory therapy (2015)

Recent monoclonal antibody trials targeting the PD1/PD-L1 immune-checkpoint pathway have shown remarkable success in treating adult malignancies, with PD-L1-expressing tumors showing the most objective response. However, little is known as to whether pediatric cancers have also adopted this immune evasion mechanism. We evaluated 115 pediatric tumors (taken at diagnosis) for PD-L1 expression and the presence of CD8+ tumor-infiltrating lymphocytes (TILs). Tumors with >5% PD-L1 membrane staining were scored positive. The presence of CD8+ TILs expressing PD-1 was assessed using dual-labeling immunohistochemistry. Data were evaluated against clinical demographics. The proportion of PD-L1+ tumors was 86% for alveolar rhabdomyosarcoma (12/14), 72% for high-risk neuroblastoma (31/43), 57% for Ewing's sarcoma (8/14), 50% for embryonal rhabdomyosarcoma (8/16) and 47% for osteosarcoma (7/15). Increased proportions of CD8+ TILs significantly correlated with PD-1 expression. When grouped by cancer type, those with the highest proportion of PD-L1 positivity showed poorest survival. PD-L1+ patients with a particularly high frequency of CD8+ TILs (but not those with low numbers CD8+ TILs) had significantly better survival compared to PD-L1 negative patients. This study reveals the presence of an active PD-L1 pathway in a high proportion of pediatric cancers, as demonstrated by strong PD-L1 positivity and the presence of PD-1 expressing CD8+ TILs. In addition, patients with high proportions of CD8+ TILs showed better survival, suggesting that bolstering CD8+ T-cell responses through PD-1/PD-L1 blockade would be a viable treatment strategy, providing support for expediting these targeted immunotherapies in children.
Segmentation of individual ribs from low-dose chest CT (2010)

Segmentation of individual ribs and other bone structures in chest CT images is important for anatomical analysis, as the segmented ribs may be used as a baseline reference for locating organs within a chest as well as for identification and measurement of any geometric abnormalities in the bone. In this paper we present a fully automated algorithm to segment the individual ribs from low-dose chest CT scans. The proposed algorithm consists of four main stages. First, all the high-intensity bone structure present in the scan is segmented. Second, the centerline of the spinal canal is identified using a distance transform of the bone segmentation. Then, the seed region for every rib is detected based on the identified centerline, and each rib is grown from the seed region and separated from the corresponding vertebra. This algorithm was evaluated using 115 low-dose chest CT scans from public databases with various slice thicknesses. The algorithm parameters were determined using 5 scans, and remaining 110 scans were used to evaluate the performance of the segmentation algorithm. The outcome of the algorithm was inspected by an author for the correctness of the segmentation. The results indicate that over 98% of the individual ribs were correctly segmented with the proposed algorithm.
Segmentation and classification of document images (1995)

There is a significant and growing need to convert documents from printed paper to an electronic form. Document image analysis is concerned with the segmentation of the document image into regions of interest, their description, and the classification of the regions according to the type of their contents. A new unified approach to page segmentation and classification, based on the description of the background with tiles, is presented. The segmentation method is flexible to successfully analyse and describe regions in complicated layouts where other methods fail. Images with severe skew are handled equally well with no additional computations. The classification is based on textural features which are derived by simple calculations from the representation of space in the regions, produced during the segmentation process. This is a considerable advantage over previous methods where extra image accesses and lengthy computations are necessary. Overall, the whole approach of segmentation and classification by white tiles is fast and efficient as no time-consuming processes are required.
Implementing Signature Neural Networks with Spiking Neurons (2016)

<i>Spiking Neural Networks</i> constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed <i>Signature Neural Network</i> paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks.
Chaos computing for mitigating side channel attack (2018)

Chaos computing is an unconventional paradigm for computing where chaotic oscillators are used for computation. As chaotic oscillators dynamically produce a large number of unique patterns over time, a single oscillator can be configured to produce different logic gates. Even the same logic functionality can be implemented using the same chaos gate but with different configurations. Chaotic implementations of logic thus provides opportunities for building instances of computing system with similar hardware but different configurations of operation, thus being capable of mitigating side channel based reverse engineering attack. In this paper, we explore the opportunities of mitigating side channel power attack vulnerabilities of conventional digital computing systems using chaos based logic. We perform an instruction classification attack using side channel power profiles on arithmetic logic units (ALU), considered for different proportions of conventional logic gates and chaotic logic gates. Quantitative analysis based on a classification algorithm shows that an ALU implemented with even a small proportion of chaotic gates can be classified with significantly lower accuracy compared to conventional alternatives.
[The extra-hepatic bile ducts. Apropos of a new case of abnormalities]. (1988)

A double anomaly of extrahepatic biliary pathways was detected in the same patient. The first anomaly involved the cystic duct, which emptied into the third part of duodenum, the second anomaly the common bile duct which was implanted into the right side of the cystic duct one centimeter from the papilla. An anomaly of this type has not been reported previously in the literature and surgeons should be aware of its possible occurrence.
DNA Sequence Classification Using Compression-Based Induction (1995)

Inductive learning methods, such as neural networks and decision trees, have become a popular approach to developing DNA sequence identification tools. Such methods attempt to form models of a collection of training data that can be used to predict future data accurately. The common approach to using such methods on DNA sequence identification problems forms models that depend on the absolute locations of nucleotides and assume independence of consecutive nucleotide locations. This paper describes a new class of learning methods, called compression-based induction (CBI), that is geared towards sequence learning problems such as those that arise when learning DNA sequences. The central idea is to use text compression techniques on DNA sequences as the means for generalizing from sample sequences. The resulting methods form models that are based on the more important relative locations of nucleotides and on the dependence of consecutive locations. They also provide a suitable framework into which biological domain knowledge can be injected into the learning process. We present initial explorations of a range of CBI methods that demonstrate the potential of our methods for DNA sequence identification tasks.
A timestamp-based checkpointing protocol for long-lived distributed computations (2002)

The authors present a timestamp-based protocol for checkpointing the global state of a long-lived distributed computation in an environment in which processor clocks are approximately synchronized. The protocol is based on periodic checkpointing of local process states and logging of incoming messages during a short bounded interval. It tolerates process crash and performance failures as well as network omission and performance failures. The proposed approach has the advantage of optimistic logging protocols in that it does not require synchronous logging of each message on stable storage. The approach also has the advantage of pessimistic logging protocols in that it avoids the domino effect by recovering to the most recent successful local checkpoint.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Chemoattraction of macrophages by secretory molecules derived from cells expressing the signal peptide of eosinophil cationic protein (2012)

The increased expression and release of various cytokines triggered by ECPsp may attract macrophages to bronchia to purge damaged cells. Our approach, involving experimental and computational systems biology, predicts pathways and potential biological functions for further characterization of this novel function of ECPsp under inflammatory conditions.
Technology Advancements in Hearing Protection Circa 1995: Active Noise Reduction, Frequency/Amplitude-Sensitivity, and Uniform Attenuation (1996)

Conventional hearing protection devices represent a mature technology that has been widely used since the late 1950s. When worn consistently and correctly such devices can provide suitable hearing protection in many, if not most noise-hazardous or aurally annoying situations. However, such devices have often been implicated in compromised auditory perception, degraded signal detection, and reduced speech communication abilities. In some instances this can create hazards for the wearer, or at the very least, resistance to use by those in need of hearing protection. Recent technological developments have been used to augment hearing protectors in an attempt to alleviate these problems for the user while providing adequate attenuation. Operational characteristics, design alternatives, performance data, and applications for active noise reduction, active sound transmission, frequency selectivity, adjustable attenuation, amplitude sensitivity, and uniform attenuation features in hearing protectors are discussed, and recommendations are provided.
Monitoring of System Cleanliness Level in Hydraulic Systems (2015)

Monitoring of system cleanliness levels and counting of particulate contaminant are fundamental to achieving hydraulic system reliability as any departure from the specified cleanliness level is often a precursor to future failures. On-line monitoring of cleanliness levels has the advantage of giving data both very quickly and accurately as environmental influences are eliminated. In this way, corrective actions can be promptly implemented. Most on-line instruments are sensitive to system conditions to a greater or lesser extent, but Automatic Particle Counters (APCs) working on light extinction principles are especially sensitive to the presence of optical interfaces caused by such conditions as fluid mixtures, emulsions, free water and air bubbles. These conditions give erroneous data and can result in drawing incorrect conclusions, wasting maintenance time and ultimately, reduced user confidence in cleanliness monitoring. This paper describes such conditions and shows how the correct selection of the analysis technique can result in reliable cleanliness level data.
La salud ambienta: presente y futuro. Una perspectiva desde la Comunidad Autónoma del País Vasco (2002)

El ámbito de la salud ambiental es definido como el correspondiente a las actuaciones en relación con factores de riesgo ambientales, de nivel comunitario, dirigidas a la prevención primaria y en las que las poblaciones humanas estén implicadas de manera determinante. Se apuntan varias cuestiones clave en relación con las necesidades futuras de la salud ambiental. Por una parte, es necesario aclarar las funciones de los servicios de salud ambiental y promover el trabajo en equipo. Por otra, debe asegurarse que las actuaciones sean pertinentes y útiles, para lo que es imprescindible la planificación sanitaria de las mismas y seguir metodologías adecuadas. Se presenta un esquema de la organización de salud ambiental en la Comunidad Autónoma del País Vasco.
Control System for Unmanned Aerial Vehicles (2007)

An open project, dealing with autopilot design for autonomous Unmanned Aerial Vehicles is introduced in this paper. Networked hierarchical distributed control system is being proposed and its hardware and software structure is briefly described. Mathematical model of a small rotorcraft is presented and identification methodology and state estimation using Extended Kalman Filter are discussed. Control algorithms, based on PI, LQG and SDRE approaches, focused on rotorcraft UAVs are proposed, including a complex hierarchical autopilot design. Real data, measured during test-flights of an experimental UAV, are presented.
Depth Estimation of Face Images Based on the Constrained ICA Model (2011)

In this paper, we propose a novel and efficient algorithm to reconstruct the 3-D structure of a human face from one or a number of its 2-D images with different poses. In our proposed algorithm, the rotation and translation process from a frontal-view face image to a nonfrontal-view face image is at first formulated as a constrained independent component analysis (cICA) model. Then, the overcomplete ICA problem is converted into a normal ICA problem by incorporating a prior from the CANDIDE 3-D face model. Furthermore, the CANDIDE model is employed to construct a reference signal that is used in both the initialization and the objective function of the cICA model. Moreover, a model-integration method is proposed to improve the depth-estimation accuracy when multiple nonfrontal-view face images are available. An important advantage of the proposed algorithm is that no frontal-view face image is required for the estimation of the corresponding 3-D face structure. Experimental results on a real 3-D face image database demonstrate the feasibility and efficiency of the proposed method.
Feasibility of Raman spectroscopy as PAT tool in active coating (2010)

Raman spectroscopy is an appropriate process analytical technology too.
Induction of chromosome aberrations by fusarium T-2 toxin in cultured human peripheral blood lymphocytes and Chinese hamster fibroblasts (1986)

T-2 toxin is an important representative of trichothecenes produced by various species of imperfect fungi, mainly Fusarium genus. It is a naturally occurring toxin that can cause severe diseases in human and animals. No definite data demonstrating the carcinogenic potential of T-2 toxin had been reported up to now. We demonstrated that T-2 toxin reproducibly induced chromosomal structural aberrations both in cultured human peripheral blood lymphocytes as well as in V79 Chinese hamster fibroblasts. The mean percentage of cells with aberration of human lymphocytes from normal individuals induced by T-2 toxin is 49-fold (9.8%) of the mean percentage of corresponding control cultures without T-2 toxin (0.2%). T-2 toxin induced chromosome type (76%) as well as chromatid type (24%) of aberrations; among them, acentric fragment (46%) was the most common type, and chromatid gap, deletion, and chromosome gap were the next most common. T-2 toxin can induce aberrations in cells at different phases of the cell cycle. There are definite dose-effect relationships within a certain range of dosage of T-2 toxin in experiments with both human peripheral blood lymphocytes and V79 cells. T-2 toxin exhibited three types of effects on cells, namely, mitogenic at lowest concentration, clastogenic (chromosome aberration) at median concentration, and cytotoxic at higher concentration. The dose-effect curves of these three effects are partly overlapping. There is some interindividual difference in sensitivity of response for the clastogenic effect of T-2 toxin, but no resistant individual was observed. Sex or age effect was not observed. The above results suggest that T-2 toxin has carcinogenic potentials. The dosage of aflatoxin that can induce chromosomal aberration of human peripheral blood lymphocytes is thousands-fold of the dosage of T-2 toxin as shown in this report. T-2 toxin might have more hazardous potentials than had been previously considered. The carcinogenic potential of T-2 toxin and related trichothecenes and their possible roles in carcinogenesis of upper gastrointestinal (G.I.) tract cancers need to be further investigated.
Neuronal beacon (2013)

The controlled navigation of the axonal growth cone of a neuron toward the dendrite of its synaptic partner neuron is the fundamental process in forming neuronal circuitry. While a number of technologies have been pursued for axonal guidance over the past decades, they are either invasive or not controllable with high spatial and temporal resolution and are often limited by low guidance efficacy. Here, we report a neuronal beacon based on light for highly efficient and controlled guidance of cortical primary neurons.
Revising the range of Rocky Mountain tailed frog, <i>Ascaphus montanus</i>, in British Columbia, Canada, using environmental DNA methods (2020)

Abstract The Rocky Mountain tailed frog, Ascaphus montanus , is a species at‐risk in Canada. Based upon time‐ and area‐constrained physical search surveys completed between 1996 and 2004, its Canadian distribution was defined as occurring in 19 tributaries and reaches within the Yahk and west side Flathead River Basins of British Columbia. We undertook a five‐year (2014–2018 inclusive) environmental DNA (eDNA) survey to reassess the distribution of Rocky Mountain tailed frog, focusing on tributaries proximal to known extant occurrence records. Seventeen days of field sampling were performed over the five‐year period. Targeted qPCR‐based eDNA approaches proved more effective than conventional physical search methods for detecting tailed frogs due to relatively rapid field collection, low cost of filter materials, elimination of observer bias, and higher detection probabilities compared to conventional time‐constrained survey methods. One hundred and forty sites were examined (138 for eDNA plus two visual only). Thirty‐two of the 138 sites (23%) tested positive for Rocky Mountain tailed frog DNA, including from the four extant populations sampled, whereas visual observations occurred at only seven of the sites (5%) during the survey. During the study, we evaluated two tailed frog tests and the mitigation of false negatives through testing for qPCR inhibition and sample degradation, and we demonstrate their utility in evaluating eDNA data quality. These results expand the extant range of Rocky Mountain tailed frog in the Flathead, Wigwam, and Yahk watersheds and add two new watersheds (Moyie and Tepee) by identifying five newly recorded occupied drainages in Canada: Elder Creek, Upper Wigwam River, Tepee Creek, Gilnockie Creek, and Elmer Creek. These data are important to refine and augment wildlife habitat conservation areas for Rocky Mountain tailed frog.
A Spatiotemporal Saliency Framework (2006)

This paper presents a novel bio-inspired spatiotemporal saliency framework. The framework incorporates spatial feature detection, feature tracking and motion prediction in order to generate a spatiotemporal saliency map. Experimental results demonstrate its ability and robustness to produce saliency responses to motion pop-up phenomena that are in line with humans responses. Moreover, the limited storage requirements permit real-time implementations of the proposed framework.