Partial Matching Research Articles

Encoding Diagnostic Codes for Privacy-Preserving Record Linkage

IntroductionDiagnostic codes, such as the ICD-10, may be considered as sensitive information. If such codes have to be encoded using current methods for data linkage, all hierarchical information given by the code positions will be lost. We present a technique (HPBFs) for preserving the hierarchical information of the codes while protecting privacy. The new method modifies a widely used Privacy-preserving Record Linkage (PPRL) technique based on Bloom filters for the use with hierarchical codes.
 Objectives and ApproachAssessing the similarities of hierarchical codes requires considering the code positions of two codes in a given diagnostic hierarchy. The hierarchical similarities of the original diagnostic code pairs should correspond closely to the similarity of the encoded pairs of the same code.
 Furthermore, to assess the hierarchy-preserving properties of an encoding, the impact on similarity measures from differing code positions at all levels of the code hierarchy can be evaluated. A full match of codes should yield a higher similarity than partial matches.
 Finally, the new method is tested against ad-hoc solutions as an addition to a standard PPRL setup. This is done using real-world mortality data with a known link status of two databases.
 ResultsIn all applications for encoded ICD codes where either categorical discrimination, relational similarity or linkage quality in a PPRL setting is required, HPBFs outperform other known methods. Lower mean differences and smaller confidence intervals between clear-text codes and encrypted code pairs were observed, indicating better preservation of hierarchical similarities. Finally, using these techniques allows for much better hierarchical discrimination for partial matches.
 ConclusionThe new technique yields better linkage results than all other known methods to encrypt hierarchical codes. In all tests, comparing categorical discrimination, relational similarity and PPRL linkage quality, HPBFs outperformed methods currently used.

Quantum chaos in topologically massive gravity

We study quantum chaos of rotating BTZ black holes in Topologically Massive gravity (TMG). We discuss the relationship between chaos parameters including Lyapunov exponents and butterfly velocities from shock wave calculations of out-of-time-order correlators (OTOC) and from pole-skipping analysis. We find a partial match between pole-skipping and the OTOC results in the high temperature regime. We also find that the velocity bound puts a chaos constraint on the gravitational Chern-Simons coupling.

Isolation, Characterization and Structure Elucidation of a Novel Lantibiotic From Paenibacillus sp.

We have isolated and characterized a novel antibacterial peptide, CMB001, following an extensive screening effort of bacterial species isolated from diverse environmental sources. The bacterium that produces CMB001 is characterized as a Gram (+) bacillus sharing approximately 98.9% 16S rRNA sequence homology with its closest match, Paenibacillus kyungheensis. The molecule has been purified to homogeneity from its cell-free supernatant by a three-step preparative chromatography process. Based on its primary structure, CMB001 shares 81% identity with subtilin and 62% with nisin. CMB001 is active mainly against Gram-positive bacteria and Mycobacteriaceae but it is also active against certain Gram-negative bacteria, including multi-drug resistant Acinetobacter baumannii. It retains full antibacterial activity at neutral pH and displays a low propensity to select for resistance among targeted bacteria. Based on NMR and mass spectrometry, CMB001 forms a unique 3D-structure comprising of a compact backbone with one α-helix and two pseudo-α-helical regions. Screening the structure against the Protein Data Bank (PDB) revealed a partial match with nisin-lipid II (1WCO), but none of the lantibiotics with known structures showed significant structural similarity. Due to its unique structure, resistance profile, relatively broad spectrum and stability under physiological conditions, CMB001 is a promising drug candidate for evaluation in animal models of bacterial infection.

Classification of various sources of error in range assessment using proton radiography and neural networks in head and neck cancer patients

This study evaluates the suitability of convolutional neural networks (CNNs) to automatically process proton radiography (PR)-based images. CNNs are used to classify PR images impaired by several sources of error affecting the proton range, more precisely setup and calibration curve errors. PR simulations were performed in 40 head and neck cancer patients, at three different anatomical locations (fields A, B and C, centered for head and neck, neck and base of skull coverage). Field sizes were 26 × 26cm2 for field A and 4.5 × 4.5cm2 for fields B and C. Range shift maps were obtained by comparing an unperturbed reference PR against a PR where one or more sources of error affected the proton range. CT calibration curve errors in soft, bone and fat tissues and setup errors in the anterior–posterior and inferior–superior directions were simulated individually and in combination. A CNN was trained for each type of PR field, leading to three CNNs trained with a mixture of range shift maps arising from one or more sources of range error. To test the full/partial/wrong agreement between predicted and actual sources of range error in the range shift maps, exact, partial and wrong match percentages were computed for an independent test dataset containing range shift maps arising from isolated or combined errors, retrospectively. The CNN corresponding to field A showed superior capability to detect isolated and combined errors, with exact matches of 92% and 71% respectively. Field B showed exact matches of 80% and 54%, and field C resulted in exact matches of 77% and 41%. The suitability of CNNs to classify PR-based images containing different sources of error affecting the proton range was demonstrated. This procedure enables the detection of setup and calibration curve errors when they appear individually or in combination, providing valuable information for the interpretation of PR images.

Identification of important miRNAs in bubaline mammary gland at heifer stage - An in-silico approach

The present study was undertaken to identify the microRNAs (miRNAs) expressed in the mammary tissue of a bubaline heifer. Small RNAs were isolated from the mammary gland tissue and enriched for miRNA fraction. The linker-ligated small RNAs were reverse transcribed to synthesize cDNA and amplified by PCR. The PCR products were ligated to the pGEM-T Easy vector; cloned into DH5 alpha cells and sequenced. Sequencing of 40 clones, randomly chosen from this library, produced 115 concatemerized short sequences. The short sequences were checked for their matches with the help of refseq_rna database, EST database (NCBI) and Ensembl. The analysis was performed for more than 90% identity with miRNAs across different species in miRBase. Alignment of putative small RNA sequences with the bovine genome was attempted in GenBank (NCBI) and Ensembl using BLAST. The small RNA sequences with a partial matches within the bovine genome and/or with flanking sequences (upstream or downstream) were analyzed for hairpin structures using the Mfold web server. Reverse complements were also assessed for the homology search. miRNA sequences showing only a partial match with already reported sequences were considered as a putative bubaline miRNAs. Six developmentally important putative miRNA precursors were identified from this study using cloning and sequencing followed by the Bioinformatics approach. This study will help in the elucidation of pathways involving miRNAs in bubaline species at the heifer stage.

INVESTIGATION OF GROUNDWATER POTENTIALS IN IMAKUN OMI COMMUNITY USING ELECTRICAL RESISTIVITY METHOD

Groundwater is described as the water found beneath the surface of the earth in underground streams and aquifers and has become popular as a source of drinking potable water in Nigeria due to its quality when compared to other water sources. The Electrical resistivity method was employed in Imakun Omi Community, a coastal town in Ogun Waterside Local government area of Ogun State with the aim of determining the groundwater potential of the area. A total of twenty (20) Vertical Electrical Soundings (VES) points were carried out in the area using the Schlumberger configuration with maximum current electrode separation (AB) of 300m using the ABEM SAS 1000 Terrameter. The results obtained were interpreted quantitatively and qualitatively using partial curve matching and computer iteration programs WINRESIST and SURFER 11 for the interpretation from which the reflection coefficient was computed. The groundwater potential of the rock units were evaluated and 40% of the stations show high yield, 50% of the stations show medium yield and 10% of the stations was observed to have low yield. The aquifer thicknesses are very thick with values ranging from 6.9 m to 79.3 m, hence an average of 43.1mand overburden thicknesses ranging from 9.7m to 96.5 m, with an average of 53.1m

A Multicenter, Multicohort, Open-Label, Single-Arm per Cohort, Phase II Study to Assess the Efficacy and Safety of Tabelecleucel in Patients with EBV-Associated Diseases Using an Adaptive Two-Stage Study Design

Background Epstein-Barr virus infection is associated with a variety of life-threatening malignant and non-malignant diseases. In immunocompromised individuals where T-cell function is impaired, loss of immune control of Epstein-Barr virus (EBV) can lead to proliferation of EBV-transformed B cells and result in immunodeficiency-associated lymphoproliferative diseases (IA-LPD). EBV-driven IA-LPDs are a heterogenous group of diseases with variable clinical and pathologic features, including primary immunodeficiency-associated LPD (EBV+ PID-LPD), acquired immunodeficiency-associated LPD (EBV+ AID-LPD), and post-transplant lymphoproliferative disorder (EBV+ PTLD). In addition, EBV-infection of mesenchymal cells can cause sarcomas, including leiomyosarcoma (EBV+ sarcoma). In rare instances, EBV viremia (ie, persistent EBV infection) can lead to non-malignant yet life-threatening complications such as chronic active EBV (CAEBV) or hemophagocytic lymphohistiocytosis (HLH). During the transition from primary EBV infection to latent state, only a subset of viral genes is expressed. The resulting latency proteins are a target of CD8+ T cells, making EBV+ malignancies good candidates for treatment with EBV-targeted cytotoxic lymphocytes. Tabelecleucel (tab-cel) is an off-the-shelf, partially human leukocyte antigen (HLA)-matched, allogeneic EBV-specific T-cell immunotherapy generated from screened EBV+ donors. Tabelecleucel is characterized by both HLA genotype and HLA restriction, the HLA allele(s) through which tab-cel exerts cytotoxic activity. Tab-cel is selected for each patient from an inventory based on the HLA restriction(s) and partial HLA matching. Initial safety and efficacy data support that tab-cel was well tolerated and showed clinical activity in patients with each of the EBV-associated diseases being proposed in study 205 [Nikiforow S et al. ESMO 2020; Kurlander LS et al. Ann Oncol 2018; Prockop S et al.JCI 2020]. These data encourage investigation to further evaluate the safety and efficacy of tab-cel in these populations. Study design and objectives This is a multicenter, multicohort, open-label, single-arm per cohort, phase II study to assess the efficacy and safety of tab-cel in patients with EBV-associated diseases (ATA129-EBV-205). The primary objective of the study is to assess the clinical benefit of tab-cel as measured by objective response rate. This study will also evaluate clinically relevant disease-specific outcomes and will characterize the safety profile of tab-cel in these patient populations. This study will enroll patients who are relapsed/refractory or newly diagnosed and ineligible for first-line therapy in the following cohorts: EBV+ AID-LPD, EBV+ PID-LPD, EBV+ sarcoma, including LMS, CAEBV/HLH and EBV+ PTLD with central nervous system [CNS]-involvement. In addition, a cohort of patients with previously untreated EBV+ PTLD where first-line therapy is not appropriate is planned to start enrollment in 2021. A Phase III study of tab-cel for solid organ or allogeneic hematopoietic cell transplant patients with EBV+ PTLD after failure of rituximab or rituximab plus chemotherapy (NCT03394365) is ongoing. Patients in each cohort will receive tab-cel in 35-day cycles. During each cycle, patients will receive intravenous tab-cel at a dose of 2 × 106 cells/kg on days 1, 8, and 15, followed by an observation period through day 35 (Figure 1). An adaptive two-stage design will be used for each cohort in this study, and for each, a maximum of eight patients will be enrolled in stage 1. The decision to move to stage 2 enrollment for any given cohort will be based on an analysis of the first eight evaluable patients in the cohort using investigator's assessment (per defined radiologic, clinical, and/or laboratory response criteria). If at least two among the first eight evaluable patients in stage 1 are responders W(ie, complete response or partial response), additional patients may be enrolled in stage 2 of that cohort. The number of patients enrolled in stage 2 will depend on the number of observed responders in stage 1 (Table 1). This design will allow for minimization of the expected number of patients required to evaluate the efficacy of tab-cel in each disease cohort independently. Figure 1. Study design schema Disclosures Prockop: Jasper Pharmaceuticals: Research Funding; Mesoblast: Consultancy, Research Funding; Atara Biotherapeutics: Research Funding; Memorial Sloan Kettering: Patents & Royalties: IP related to the development of third party viral specific T cells with all of my interests assigned to MSK. Dinavahi:Atara Biotherapeutics: Current Employment, Current equity holder in publicly-traded company. Navarro:Atara Biotherapeutics: Current Employment, Current equity holder in publicly-traded company. Guzman-Becerra:Atara Biotherapeutics: Current Employment, Current equity holder in publicly-traded company. Sun:Atara Biotherapeutics: Current Employment, Current equity holder in publicly-traded company. Gamelin:Atara Biotherapeutics: Current Employment, Current equity holder in publicly-traded company.

A Bank of CD30.CAR-Modified, Epstein-Barr Virus-Specific T Cells That Lacks Host Reactivity and Resists Graft Rejection for Patients with CD30-Positive Lymphoma

While autologous T cell therapies can effectively treat B-cell leukemia and lymphoma, the personalized manufacturing process is difficult to scale, expensive and may fail. Even when autologous products are successfully manufactured, they are not immediately available to acutely ill patients. "Off-the-shelf" T cell products derived from healthy donors that can rapidly be administered, would improve accessibility and reduce the cost of T cell therapy. However, major obstacles to successful allogeneic T cell products include their potential for graft-versus-host disease (GVHD) and graft rejection, mediated by host and recipient alloreactive T cells respectively. To address GVHD, we are using Epstein-Barr Virus-specific T cells (EBVSTs) as our platform since they are virus specific rather than allospecific and have not produced GVHD in more than 300 allogeneic recipients. To prevent graft rejection we have introduced into these EBVSTs, a chimeric antigen receptor for CD30 (CD30.CAR). CD30 is upregulated during the activation of alloreactive T cells, which leads to them becoming targets. The CD30.CAR provides the additional advantage of targeting CD30-positive lymphoma and has proved safe and effective in prior clinical trials (NCT02917083) using autologous CAR-T cells. Hence, we expect off-the-shelf CD30.CAR EBVSTs to eliminate the alloreactive T cells they elicit in allogeneic hosts, and therefore persist for sufficient time to eliminate CD30-positive lymphoma, without causing GVHD. Here we show that CD30.CAR-EBVSTs resist fratricide by masking their own CD30 molecules expressed in cis, but are nonetheless protected from rejection when co-cultured with alloreactive T cells expressing CD30 in trans. Notably, CD30.CAR EBVSTs preserve the function of both their TCR and the CD30.CAR, with retention of EBV specificity and the ability to eliminate CD30-positive tumor cells. We have manufactured a bank of clinical grade CD30.CAR EBVSTs from donors with HLA types designed to provide a partial HLA match for our diverse recipients. Clinical grade CD30.CAR EBVST cultures readily expanded to sufficient numbers for a planned clinical trial and expressed the CD30.CAR on 77% to 99% of cells. All of the lines passed functional release criteria of having greater than 100 IFNɣ spot-forming units (SFU) per 105 cells in response to both latent and lytic EBV antigens, and greater than 20% specific cytolysis against a CD30-positive Hodgkin lymphoma cell line, HDLM2, at an effector to target ratio of 20:1. Although CD30.CAR killing is not HLA restricted, we will select the CD30.CAR EBVST product for each recipient, based on the best HLA class I and class II match. This will allow endogenous EBV to boost the in vivo activity of CD30.CAR EBVSTs, and will provide additional reactivity for patients with CD30-positive and EBV-positive tumors. The IND for the clinical trial (NCT04288726) has been approved and we will recruit patients with CD30-positive lymphomas including Hodgkin lymphoma, diffuse large B cell lymphoma and NK/T cell lymphoma. In summary, we present an approach to making an off-the-shelf T cell therapy that can rapidly translate to the clinic, requires no gene editing, and can serve as a platform for other CAR/TCRs to target a multiplicity of malignancies. Disclosures Quach: Tessa Therapeutics: Research Funding. Brenner:Memmgen: Membership on an entity's Board of Directors or advisory committees; Allogene: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Walking Fish: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Maker Therapeutics: Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Other: Founder; Tessa Therapeutics: Membership on an entity's Board of Directors or advisory committees, Other: Founder; Tumstone: Membership on an entity's Board of Directors or advisory committees; Bluebird Bio: Membership on an entity's Board of Directors or advisory committees. Heslop:Tessa Therapeutics: Consultancy, Research Funding; Novartis: Consultancy; Gilead Biosciences: Consultancy; PACT Pharma: Consultancy; Kiadis: Consultancy; AlloVir: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees; Marker Therapeutics: Current equity holder in publicly-traded company, Membership on an entity's Board of Directors or advisory committees. Ramos:Novartis: Membership on an entity's Board of Directors or advisory committees; Tessa Therapeutics: Research Funding; Kuur Therapeutics: Research Funding. Rouce:Tessa Therapeutics: Other, Research Funding; Novartis: Honoraria. Rooney:Marker Therapeutics: Current equity holder in publicly-traded company, Other: co-founder; Tessa Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Allovir: Current equity holder in publicly-traded company, Other: co-founder.

PPM-Decay: A computational model of auditory prediction with memory decay.

Statistical learning and probabilistic prediction are fundamental processes in auditory cognition. A prominent computational model of these processes is Prediction by Partial Matching (PPM), a variable-order Markov model that learns by internalizing n-grams from training sequences. However, PPM has limitations as a cognitive model: in particular, it has a perfect memory that weights all historic observations equally, which is inconsistent with memory capacity constraints and recency effects observed in human cognition. We address these limitations with PPM-Decay, a new variant of PPM that introduces a customizable memory decay kernel. In three studies-one with artificially generated sequences, one with chord sequences from Western music, and one with new behavioral data from an auditory pattern detection experiment-we show how this decay kernel improves the model's predictive performance for sequences whose underlying statistics change over time, and enables the model to capture effects of memory constraints on auditory pattern detection. The resulting model is available in our new open-source R package, ppm (https://github.com/pmcharrison/ppm).

Wavelet‐based Heat Kernel Derivatives: Towards Informative Localized Shape Analysis

AbstractIn this paper, we propose a new construction for the Mexican hat wavelets on shapes with applications to partial shape matching. Our approach takes its main inspiration from the well‐established methodology of diffusion wavelets. This novel construction allows us to rapidly compute a multi‐scale family of Mexican hat wavelet functions, by approximating the derivative of the heat kernel. We demonstrate that this leads to a family of functions that inherit many attractive properties of the heat kernel (e.g. local support, ability to recover isometries from a single point, efficient computation). Due to its natural ability to encode high‐frequency details on a shape, the proposed method reconstructs and transfers ‐functions more accurately than the Laplace‐Beltrami eigenfunction basis and other related bases. Finally, we apply our method to the challenging problems of partial and large‐scale shape matching. An extensive comparison to the state‐of‐the‐art shows that it is comparable in performance, while both simpler and much faster than competing approaches.

Geoelectrical and geotechnical investigation of foundation failure in and around Oroke high school, Akungba- Akoko, southwestern Nigeria

Engineering structures are designed and constructed with an air of lifelong expectancy. Moreover, building foundation may experience failure due to presence of concealed geologic features such as cavity and shear zones which can lead to subsurface subsidence. Hence, it is imperative, prior to building construction, to investigate the physical properties of foundation soils and determine its suitability for design and construction of building structures. In the light of this, a geoelectric survey, involving three (3) electrical dipole - dipole array and geotechnical analysis methods were carried out around a distressed building at Oroke High School, opposite Adekunle Ajasin University, Akungba Akoko to establish the cause of failure for the structures foundation via delineating the subsurface structural features. The field electrical data were plotted on log –log graph sheets and the resulting curves were interpreted qualitatively by visual inspection, and quantitatively via partial curve matching and computer iteration techniques. For the geotechnical analysis, a total of twelve (12) soil samples were taken from different locations of about 30 meters intervals, at the depth of 1.5 meters. The pseudo – section and electrical sections indicate that the subsurface is heterogeneous in geological composition. The 2D dipole- dipole resistivity and pseudo – section delineated zones having resistivity values ranging from 200 to 700ohm meter, and those approaching infinity all within a depth of 0-5 m, the resistivity values of 27 to 139ohm meter suggest the presence of clay. The geoelectric section identified three subsurface geologic layers comprising clay /sandy, clay top soil / sub grade soil, clay / sandy clay and sand weathered layer and the basement (fresh) beneath the failed segment. Additionally, prominent fractures were discovered within some areas on the pseudo-sections. The results of the laboratory tests also included those of natural moisture content, specific gravity, grain size distribution curves, Atterberg limit, compaction test and California Bearing Ratio (CBR). In conclusion, electrical resistivity method was found to be an effective measure or tool in the site characterization. The soil/rock in these zones may require reinforcement in order to enhance its bearing capacity and increase the life span of the engineering foundation. Â

Evaluation of a Concept Mapping Task Using Named Entity Recognition and Normalization in Unstructured Clinical Text

In this pilot study, we explore the feasibility and accuracy of using a query in a commercial natural language processing engine in a named entity recognition and normalization task to extract a wide spectrum of clinical concepts from free text clinical letters. Editorial guidance developed by two independent clinicians was used to annotate sixty anonymized clinic letters to create the gold standard. Concepts were categorized by semantic type, and labels were applied to indicate contextual attributes such as negation. The natural language processing (NLP) engine was Linguamatics I2E version 5.3.1, equipped with an algorithm for contextualizing words and phrases and an ontology of terms from Intelligent Medical Objects to which those tokens were mapped. Performance of the engine was assessed on a training set of the documents using precision, recall, and the F1 score, with subset analysis for semantic type, accurate negation, exact versus partial conceptual matching, and discontinuous text. The engine underwent tuning, and the final performance was determined for a test set. The test set showed an F1 score of 0.81 and 0.84 using strict and relaxed criteria respectively when appropriate negation was not required and 0.75 and 0.77 when it was. F1 scores were higher when concepts were derived from continuous text only. This pilot study showed that a commercially available NLP engine delivered good overall results for identifying a wide spectrum of structured clinical concepts. Such a system holds promise for extracting concepts from free text to populate problem lists or for data mining projects.

An extended regularized adjusted plus-minus analysis for lineup management in basketball using play-by-play data

AbstractIn this work we analyse basketball play-by-play data in order to evaluate the efficiency of different five-man lineups employed by teams. Starting from the adjusted plus-minus framework, we present a model-based strategy for the analysis of the result of partial match outcomes, extending the current literature in two main directions. The first extension replaces the classical response variable (scored points) with a comprehensive score that combines a set of box score statistics. This allows various aspects of the game to be separated. The second extension focuses on entire lineups rather than individual players, using a suitable extended model specification. The model fitting procedure is Bayesian and provides the necessary regularization. An advantage of this approach is the use of posterior distributions to rank players and lineups, providing an effective tool for team managers. For the empirical analysis, we use the 2018/2019 regular season of the Turkish Airlines Euroleague Championship, with play-by-play and box scores for 240 matches, which are made available by the league website. The results of the model fitting can be used for several investigations as, for instance, the comparative analysis of the effects of single players and the estimation of total and synergic effects of lineups monitoring. Moreover, the behaviour of players and lineups during the season, updating the estimation results after each gameday, can represent a rather useful tool.

FAME: 3D Shape Generation Via Functionality-Aware Model Evolution.

We introduce a modeling tool which can evolve a set of 3D objects in a functionality-aware manner. Our goal is for the evolution to generate large and diverse sets of plausible 3D objects for data augmentation, constrained modeling, as well as open-ended exploration to possibly inspire new designs. Starting with an initial population of 3D objects belonging to one or more functional categories, we evolve the shapes through part recombination to produce generations of hybrids or crossbreeds between parents from the heterogeneous shape collection. Evolutionary selection of offsprings is guided both by a functional plausibility score derived from functionality analysis of shapes in the initial population and user preference, as in a design gallery. Since cross-category hybridization may result in offsprings not belonging to any of the known functional categories, we develop a means for functionality partial matching to evaluate functional plausibility on partial shapes. We show a variety of plausible hybrid shapes generated by our functionality-aware model evolution, which can complement existing datasets as training data and boost the performance of contemporary data-driven segmentation schemes, especially in challenging cases. Our tool supports constrained modeling, allowing users to restrict or steer the model evolution with functionality labels. At the same time, unexpected yet functional object prototypes can emerge during open-ended exploration owing to structure breaking when evolving a heterogeneous collection.

AyaTEC

The absence of publicly available reusable test collections for Arabic question answering on the Holy Qur’an has impeded the possibility of fairly comparing the performance of systems in that domain. In this article, we introduce AyaTEC , a reusable test collection for verse-based question answering on the Holy Qur’an, which serves as a common experimental testbed for this task. AyaTEC includes 207 questions (with their corresponding 1,762 answers) covering 11 topic categories of the Holy Qur’an that target the information needs of both curious and skeptical users. To the best of our effort, the answers to the questions (each represented as a sequence of verses) in AyaTEC were exhaustive—that is, all qur’anic verses that directly answered the questions were exhaustively extracted and annotated. To facilitate the use of AyaTEC in evaluating the systems designed for that task, we propose several evaluation measures to support the different types of questions and the nature of verse-based answers while integrating the concept of partial matching of answers in the evaluation.

Study of the structural curvature in Mo2C derived carbons with contrast matched small-angle neutron scattering

The influence of the synthesis conditions on the formation of the porous and the graphitic structure of carbon materials was investigated on Mo2C-derived carbon materials synthesized at different temperatures (Tsyn from 700 to 1000 °C). Contrast matched small-angle neutron scattering method was used to obtain explicit information about the pore and pore wall structure of the carbons. It was found that carbons formed at lower Tsyn exhibit prevalently nano-scale cylindrical geometry and an increase in Tsyn promotes the formation of slit-like structures. Additionally, partial contrast matching was used, which effectively made the pore walls wider, enabled to „hide“ the smaller pores, exposing in greater detail the geometries of larger mesopores. The geometry of larger structures (e.g. pores and pore walls) changes from mixed cylindrical and slit-like to completely slit-like with the increase of Tsyn. The observed change of the geometries, expressed by the increase in the dimensionality parameter, that increases from 1.2 to 1.8, empirically correlates with the decrease in the disorder between graphitic layers. Thus, we conclude that the cylindrical structures are caused by the curvature in graphitic layers formed at lower Tsyn (≤800 °C).

Sentinel lymph node detection differs when comparing lymphoscintigraphy to lymphography using water soluble iodinated contrast medium and digital radiography in dogs.

Sentinel lymph node (SLN) mapping by various means has become standard of care in certain types of human cancers and is receiving more attention in veterinary oncology. Current SLN mapping techniques can be costly and often require advanced imaging equipment. The objective of this prospective, method comparison study was to compare an SLN mapping protocol of lymphoscintigraphy to lymphography using water soluble iodinated contrast medium (WIC) and digital radiography for identification of an SLN. Lymphoscintigraphy and lymphography were performed on eight healthy purpose-bred dogs using technetium-99m sulfur colloid and WIC injected into the subcutaneous tissues in a four-quadrant technique around a predefined area of skin on the brachium. Images were obtained using a gamma camera and digital radiography at different time points post-injection. Image sequences were evaluated by one of two American College of Veterinary Radiology board-certified veterinary radiologists. Data obtained were compared between methods using descriptive statistics. An SLN was identified in all dogs with lymphoscintigraphy and seven of eight dogs with lymphography. Agreement between results of the lymphoscintigraphy and lymphography studies was a complete match in three dogs, a partial match in four dogs, and no match in one dog. The SLN detected differed based on the imaging modality used.

An alternative method in triaxial tests to obtain cross-anisotropic elastic parameters

A new, alternative approach in a triaxial set-up to fully determine small-strain cross-anisotropic elastic parameters is proposed, which requires neither radial strain sensors nor a radial loading process. This was made possible by additionally measuring pore water pressure responses during undrained axial loading, and inputting them into theoretical expressions derived based on cross-anisotropic elasticity theory. Although the method is intended for saturated soils, slight undersaturation in the system is accounted for by incorporating the pore water pressure coefficient B into the parameter deduction process. Being free from the cumbersome radial sensors and ultra-precise cell pressure controlling devices/operations, the proposed method is applicable even in less specialised laboratories. Four different deduction routes of elastic parameters were applied to results from tests on two reconstituted fine-grained soils. The horizontal Young's modulus obtained with the newly proposed method is consistent not only with those based on radial measurements, but also with those directly measured by axial loading on horizontally cut specimens. A challenge is still open for precisely determining Poisson's ratios, which exhibited only partial matching between different measurement methods. Overall, however, the proposed method is consistent with those adopting full local instrumentation.

Estimating diet costs: Bridging the gap between food supply price databases and dietary intake data

Abstract Introduction The cost of food is a key influence on diet. The majority of diet cost studies match intake data from population-based surveys to a single source of food supply prices such as the Consumer Price Index (CPI). Our aim was to examine the nutritional significance of using food supply data to price dietary intakes in Canada. Methods We examined food groups and nutrients in dietary intakes captured by the CPI. For prices, we used 2015 Canadian CPI average monthly item prices. For dietary intakes, we used reported intakes from the 2015 Canadian Community Health Survey (CCHS)-Nutrition, 1st 24-hour recall (n = 20,487). i) 2015 CPI item prices ($/g) were matched to the 156 food items from the 2015 CCHS-Nutrition as full, partial, or non-match; ii) CPI capture (full or partial match) per total intake (g), without water, was calculated for each respondent; iii) descriptive statistics and quantile regression (α = 0.05) were used to compare intakes of Canadian Nutrient File food groups and nutrients by quantile of CPI capture. Results The CPI captured on average 74% of total dietary intake (g) without water. A greater proportion of protein and fat intake was captured by the CPI as compared to carbohydrate, sodium, fibre, and sugar intake. Intakes of beef, poultry, sausages, pork, and breakfast foods had among the best match; snack foods, nuts, veal, and alcoholic beverages had among the worst. Individuals in the poorest CPI capture quantile consumed the greatest fibre (g), carbohydrates (g), total sugar (g), fat (g), protein (g), and energy (kcal) as compared to those with best CPI capture. Conclusions The poorest quantile of CPI capture reflects individuals with high intakes of nutrients of concern including fat, carbohydrates, and sugar; potential bias in estimating fibre and protein intake was also detected. Researchers and decision makers should attend to differential misclassification bias and opportunities for tailored datasets to price dietary intakes. Key messages Given the proliferation of diet cost studies using food supply prices, this novel study highlights the importance of understanding the biases in using food supply data to price dietary intakes. Nutrition researchers and decision makers can use these findings to strengthen food supply price data to support the monitoring of diet costs in relation to diet quality and health outcomes.

Hydrogeophysical and aquifer vulnerability zonation of a typical basement complex terrain: A case study of Odode Idanre southwestern Nigeria

An approach engaging Vertical Electrical Sounding (VES) and remote sensing data was carried out with a view to developing groundwater potential and aquifer vulnerability maps of the study area. One hundred and one (101) depth sounding data were acquired using Schlumberger array, with half maximum current electrode separation (AB/2) of 100 m. The VES were quantitatively interpreted using partial curve matching and computer aided iteration to determine the geoelectrical parameters of each station. The remote sensing data were processed using the application of Geographic Information System-based multi-criteria technique ArcGIS software. Eight (8) parameters namely lineament density, drainage density, slope, transmissivity, hydraulic conductivity, coefficient of anisotropy, aquifer thickness and resistivity were used to produce the groundwater potential model while five (5) parameters namely, lineament density, slope, longitudinal conductance, hydraulic conductivity and thickness of layer overlying the delineated aquifer were also used to produce the vulnerability model. The final output of overlay parameters for estimating the groundwater potential gave an index that ranged from 1-5. The zone categorised as low groundwater potential covered about 80% of the area. The majority of the area falls within low (about 80%) vulnerability and low groundwater potential rating while being relatively protected from potential contaminants infiltrating from the surface. The prediction accuracy of the groundwater potential model was established via existing hand-dug well correlation analysis.