Miracle-dz/UniFAR-FTUs huggingface dataset:
THE NATURE OF PRISMS: EXPLORING DATA QUALITY AND VAGUENESS IN DYNAMIC SPATIO-TEMPORAL CONSTRUCTS.

: Hagerstrand's minimalist representation of individual lives and opportunities as lifelines and prisms predates the technologies available to current GIScience but resonates with many emerging spatio-temporal data model describing human activity in space and time. It also offer strong synergies with the various approaches that use data sets representing the tracks of individuals in order to explore patterns in their movements and associated activities. Almost inevitably such tracking data sets utilise (x,y,t) and activity data (representing lifelines) which are sampled over time and space and are eventually embedded for analysis within a digital geospatial environment. There are clear issues of error in both the data defining the environment used for analysis and that defining the movement as sampled (x,y,t) points, and consequently specific properties of the interaction emerge which would be of interest to us. While the lifeline is one of a number of attempts to represent human (or any object's) presence in space-time the concept of the prism focuses more on interpolating where an object could be, or might be, when it is between two known points. This idea of prism is a derivative spatio-temporal construct which has a further dimension of vagueness and uncertainty attached to it. Such properties require both identification and representation. This paper explores two issues. The first is the nature of uncertainty and error in an actual or interpolated lifeline data models related to typical kinds of analysis of movement and activity within a digital representation of its embedding geography. The second examines the nature of any prism of opportunity that is inferred from partial lifeline data and then deployed in accessibility studies. Specifically it discusses how issues of spatio-temporal uncertainty in the derivation of prisms can be calculated, represented and analysed using the rod-field model proposed by McDowall. It contends that the personal prism is a legitimate and valuable construct within GI Science, but that allowing prisms to acquire appropriate qualities of continuity and vagueness is an important aspect of delivering information which is appropriately described as to nature and quality.
Conditional random fields for multi-agent reinforcement learning

Conditional random fields (CRFs) are graphical models for modeling the probability of labels given the observations. They have traditionally been trained with using a set of observation and label pairs. Underlying all CRFs is the assumption that, conditioned on the training data, the labels are independent and identically distributed (iid). In this paper we explore the use of CRFs in a class of temporal learning algorithms, namely policy-gradient reinforcement learning (RL). Now the labels are no longer iid. They are actions that update the environment and affect the next observation. From an RL point of view, CRFs provide a natural way to model joint actions in a decentralized Markov decision process. They define how agents can communicate with each other to choose the optimal joint action. Our experiments include a synthetic network alignment problem, a distributed sensor network, and road traffic control; clearly outperforming RL methods which do not model the proper joint policy.
The Relationship Among Adult Attachment Styles, Shame, Dissociation, and Abuse Characteristics in Women Survivors of Intrafamilial Child Sexual Abuse Perpetrated by a Parental-Figure

The consequences of intrafamilial child sexual abuse (CSA) often evolve beyond the termination of abuse and pervade into adulthood, posing complex and enduring consequences for survivors (Courtois, 1999; Briere, 1992; Herman, 1981, 1991; van der Kolk & Kadish, 1987; Chu & Dill, 1990). The concepts of attachment, shame, and dissociation- in the context of childhood sexual abuse-are significant areas of study when working with adult survivors. The present study included 49 women with a history of childhood sexual abuse perpetrated by a parental-figure. The purpose of the study was to identify the relationships among adult attachment styles, shame, dissociation, and specific CSA characteristics (age at onset, relationship to the perpetrator, duration of abuse, experience of other types of abuse). Participants voluntarily and anonymously participated in completing 4 self-administered measures on demographics, adult attachment styles, levels of shame, and levels of dissociation. Treatment variables were also investigated including type of treatment currently being received at the agency, frequency of this treatment, and overall duration of treatment to assess their possible relationships to adult attachment styles, levels of shame and dissociation, and CSA characteristics. The major findings suggest that the experience of earlier age at onset, having a father as the perpetrator, longer duration of abuse, and experience of other types of abuse lends to a greater likelihood towards fearful attachment style; adult survivors with fearful attachment styles are more likely to have high level of shame; and adult survivors with high level of shame have high level of dissociation. Additional findings of importance are that the experience of earlier age at onset, having a father as the perpetrator, longer duration of abuse, and experience of other types of abuse lends to a greater likelihood towards both high levels of shame and high levels of dissociation which in turn were related to more frequent treatment. The finding also suggests that adult survivors with a high level of dissociation stay longer in treatment.
Characterization of plaque components with intravascular ultrasound elastography in human femoral and coronary arteries in vitro.

BACKGROUND The composition of plaque is a major determinant of coronary-related clinical syndromes. Intravascular ultrasound (IVUS) elastography has proven to be a technique capable of reflecting the mechanical properties of phantom material and the femoral arterial wall. The aim of this study was to investigate the capability of intravascular elastography to characterize different plaque components. METHODS AND RESULTS Diseased human femoral (n=9) and coronary (n=4) arteries were studied in vitro. At each location (n=45), 2 IVUS images were acquired at different intraluminal pressures (80 and 100 mm Hg). With the use of cross-correlation analysis on the high-frequency (radiofrequency) ultrasound signal, the local strain in the tissue was determined. The strain was color-coded and plotted as an additional image to the IVUS echogram. The visualized segments were stained on the presence of collagen, smooth muscle cells, and macrophages. Matching of elastographic data and histology were performed with the use of the IVUS echogram. The cross sections were segmented in regions (n=125) that were based on the strain value on the elastogram. The dominant plaque types in these regions (fibrous, fibro-fatty, or fatty) were obtained from histology and correlated with the average strain and echo intensity. The strain for the 3 plaque types as determined by histology differed significantly (P=0.0002). This difference was mainly evident between fibrous and fatty tissue (P=0.0004). The plaque types did not reveal echo-intensity differences in the IVUS echogram (P=0.882). CONCLUSIONS Different strain values are found between fibrous, fibro-fatty, and fatty plaque components, indicating the potential of intravascular elastography to distinguish different plaque morphologies.
K-MEAP: Multiple Exemplars Affinity Propagation With Specified $K$ Clusters

Recently, an attractive clustering approach named multiexemplar affinity propagation (MEAP) has been proposed as an extension to the single exemplar-based AP. MEAP is able to automatically identify multiple exemplars for each cluster associated with a superexemplar. However, if the cluster number is a prior knowledge and can be specified by the user, MEAP is unable to make use of such knowledge directly in its learning process. Instead, it has to rely on rerunning the process as many times as it takes by tuning parameters until it generates the desired number of clusters. The process of MEAP rerunning may be very time-consuming. In this paper, we propose a new clustering algorithm called Multiple Exemplars Affinity Propagation with Specified K Clusters which is able to generate specified K clusters directly while retaining the advantages of MEAP. Two kinds of new additional messages are introduced in K-MEAP in order to control the number of clusters in the process of message passing. Detailed problem formulation, derived messages, and in-depth analysis of the proposed K-MEAP are provided. Experimental studies on 11 real-world data sets with different kinds of applications demonstrate that K-MEAP not only generates K clusters directly and efficiently without tuning parameters but also outperforms related approaches in terms of clustering accuracy.
[Study of RASSF1A expression and promoter demethylation in Hep-2 cell line].

OBJECTIVE To investigate the effect of 5-Aza-dC and TSA to tumor suppressor gene RASSF1A expression and methylation level in Hep-2 cell line. METHOD Hep-2 cell line were cultured in vitro and handled with 5-Aza-dC and TSA. Detected RASSF1A expression and methylation level were detected before and after drug intervention using Realtime PCR and MSP. RESULT (1) Before intervention with drug, tumor suppressor gene RASSF1A was weakly expressed and methylated in Hep-2 cell line. (2) With the effect of 5-Aza-dC and TSA, the methylation of RASSF1A gene was reversed. And the effect of combination of 5-Aza-dC and TSA was similar with 5-Aza-dC alone. There was no obvious effect using TSA alone. (3) With the effect of 5-Aza-dC and TSA, the expression of RASSF1A was improved. And the effect of 5-Aza-dC was stronger than TSA. Synergetic effect was found when using 5-Aza-dC and TSA simultaneously. CONCLUSION In Hep-2 cell line, Promoter methylation of tumor suppressor RASSF1A may play a very important role in loss of gene expression, but it is not the only cause. 5-Aza-dC and TSA can improve RASSF1A expression by reversing DNA methylation and histone deacetylation.
Structural water as an essential comonomer in supramolecular polymerization

Water is an essential comonomer in a supramolecular polymer that is used as a recyclable, water-activated glue. Although the concept of structural water that is bound inside hydrophobic pockets and helps to stabilize protein structures is well established, water has rarely found a similar role in supramolecular polymers. Water is often used as a solvent for supramolecular polymerization, however without taking the role of a comonomer for the supramolecular polymer structure. We report a low–molecular weight monomer whose supramolecular polymerization is triggered by the incorporation of water. The presence of water molecules as comonomers is essential to the polymerization process. The supramolecular polymeric material exhibits strong adhesion to surfaces, such as glass and paper. It can be used as a water-activated glue, which can be released at higher temperatures and reused many times without losing its performance.
Bovine tuberculosis: the genetic basis of host susceptibility

The prevalence of bovine tuberculosis (BTB) in the UK remains a significant economic burden and problem for the agri-food industry. Much effort has been directed towards improving diagnostics, finding vaccine candidates and assessing the usefulness of badger culling. The contribution that host genotype makes to disease outcome has, until recently, been overlooked; yet, it is biologically untenable that genetic variation does not play a role. In this review, we highlight the evidence, past and present, for a role of host genetics in determining susceptibility to BTB in livestock. We then address some of the major issues surrounding the design of future studies tasked with finding the exact causative genetic variation underpinning the TB susceptibility phenotype. Finally, we discuss some of the potential future benefits, and problems, that a knowledge of the genetic component to BTB resistance/susceptibility may bring to the agricultural industries and the wider scientific community.
High-resolution 60-GHz DCOs with reconfigurable distributed metal capacitors in passive resonators

Mm-wave digitally-controlled oscillators (DCOs) with reconfigurable passive resonators are proposed, which achieve wide tuning range (>;10%) and fine frequency resolution (<;1 MHz) simultaneously. Two 60-GHz implementations: a fine-resolution inductor-based DCO (L-DCO) and a transformer-based DCO (T-DCO) are demonstrated in 90-nm CMOS, exploiting metal capacitors only for frequency tuning. Both DCOs obtain >;9.7% linear tuning range and phase noise lower than -90.5 dBc/Hz at 1-MHz offset across the 56-62 GHz range. The T-DCO achieves fine frequency tuning step of 2.5 MHz, whereas that of the L-DCO is better than 160 kHz. The L-DCO and T-DCO consume 10 mA and 12 mA, respectively, from a 1.2-V supply. The core size of each DCO is 0.4×0.4 mm2.
Towards an automatic music arrangement framework using score reduction

Score reduction is a process that arranges music for a target instrument by reducing original music. In this study we present a music arrangement framework that uses score reduction to automatically arrange music for a target instrument. The original music is first analyzed to determine the type of arrangement element of each section, then the phrases are identified and each is assigned a utility according to its type of arrangement element. For a set of utility-assigned phrases, we transform the music arrangement into an optimization problem and propose a phrase selection algorithm. The music is arranged by selecting appropriate phrases satisfying the playability constraints of a target instrument. Using the proposed framework, we implement a music arrangement system for the piano. An approach similar to Turing test is used to evaluate the quality of the music arranged by our system. The experiment results show that our system is able to create viable music for the piano.
Size Isn't All that Matters: Noticing Differences in Size and Temporal Order

The ability to represent time and size is essential for thought and action. These domains have traditionally been investigated independently. However, the processing of events in time and space is postulated to have considerable anatomical and behavioral overlap. Here we formally tested for associations and dissociations of abilities in these domains. We examined patterns of impairments in temporal order and relative size judgments in 40 patients with unilateral brain lesions and 20 age-matched control participants. While brain damage can impair both size and temporal order judgments (TOJ), we did not find evidence for global hemispheric differences. When patients were analyzed individually compared to control subjects, we found double dissociations in performances on both kinds of judgments. Voxel lesion symptom mapping allowed us to investigate shared and unique contributions of brain damage to deficits in judgments noticing differences in temporal order and in spatial extent. We found that size and temporal order estimations have overlapping cortical vulnerabilities within the left inferior frontal gyrus, left superior temporal cortex, and bilateral inferior parietal lobule. However, vulnerability unique to TOJ occurred with damage predominantly in left lateralized regions involving inferior and middle frontal cortex and inferior parietal lobule. Conversely, vulnerability unique to size judgments occurred with damage predominantly in right lateralized regions in the supramarginal gyrus and superior temporal cortex. These data provide evidence for interactions between the processing of spatial extent and temporal order; however, they do not provide evidence for right lateralized systems.
Human Achilles tendon plasticity in response to cyclic strain: effect of rate and duration

High strain magnitude and low strain frequency are important stimuli for tendon adaptation. Increasing the rate and duration of the applied strain may enhance the adaptive responses. Therefore, our purpose was to investigate the effect of strain rate and duration on Achilles tendon adaptation. The study included two experimental groups (N=14 and N=12) and a control group (N=13). The participants of the experimental groups exercised according to a reference protocol (14 weeks, four times a week), featuring a high strain magnitude (~6.5%) and a low strain frequency (0.17 Hz, 3 s loading/3 s relaxation) on one leg and with either a higher strain rate (one-legged jumps) or a longer strain duration (12 s loading) on the other leg. The strain magnitude and loading volume were similar in all protocols. Before and after the interventions, the tendon stiffness, Young's modulus and cross-sectional area were examined using magnetic resonance imaging, ultrasound and dynamometry. The reference and long strain duration protocols induced significantly increased (P<0.05) tendon stiffness (57% and 25%), cross-sectional area (4.2% and 5.3%) and Young's modulus (51% and 17%). The increases in tendon stiffness and Young's modulus were higher in the reference protocol. Although region-specific tendon hypertrophy was also detected after the high strain rate training, there was only a tendency of increased stiffness (P=0.08) and cross-sectional area (P=0.09). The control group did not show any changes (P=0.86). The results provide evidence that a high strain magnitude, an appropriate strain duration and repetitive loading are essential components for an efficient adaptive stimulus for tendons.
Balancing Selection Maintains a Form of ERAP2 that Undergoes Nonsense-Mediated Decay and Affects Antigen Presentation

A remarkable characteristic of the human major histocompatibility complex (MHC) is its extreme genetic diversity, which is maintained by balancing selection. In fact, the MHC complex remains one of the best-known examples of natural selection in humans, with well-established genetic signatures and biological mechanisms for the action of selection. Here, we present genetic and functional evidence that another gene with a fundamental role in MHC class I presentation, endoplasmic reticulum aminopeptidase 2 (ERAP2), has also evolved under balancing selection and contains a variant that affects antigen presentation. Specifically, genetic analyses of six human populations revealed strong and consistent signatures of balancing selection affecting ERAP2. This selection maintains two highly differentiated haplotypes (Haplotype A and Haplotype B), with frequencies 0.44 and 0.56, respectively. We found that ERAP2 expressed from Haplotype B undergoes differential splicing and encodes a truncated protein, leading to nonsense-mediated decay of the mRNA. To investigate the consequences of ERAP2 deficiency on MHC presentation, we correlated surface MHC class I expression with ERAP2 genotypes in primary lymphocytes. Haplotype B homozygotes had lower levels of MHC class I expressed on the surface of B cells, suggesting that naturally occurring ERAP2 deficiency affects MHC presentation and immune response. Interestingly, an ERAP2 paralog, endoplasmic reticulum aminopeptidase 1 (ERAP1), also shows genetic signatures of balancing selection. Together, our findings link the genetic signatures of selection with an effect on splicing and a cellular phenotype. Although the precise selective pressure that maintains polymorphism is unknown, the demonstrated differences between the ERAP2 splice forms provide important insights into the potential mechanism for the action of selection.
Automatic energy management controller design for hybrid electric vehicles

Due to strict CO2 emission limits, the optimal design of controllers for hybrid cars is an increasingly important topic for the automotive industry. Most current approaches to controller design rely solely on engineering knowledge. Utilizing technologies from computational intelligence is not yet common practice. In this work we evaluate how simple controllers can automatically be extracted from optimal control strategies computed by Dynamic Programming. We compare artificial neural network and decision tree based controllers in terms of performance (fuel consumption), stability, robustness, and interpretability, and we investigate the dependency on specific drive cycles used for generating optimal control. Our findings indicate that automatically derived controllers can result in a performance 1–2% below optimal fuel economy, but we observe a large variety in performance and in the controller structure for different drive cycles, thus, underlining the relevance of the correct choice of the drive cycles used for controller development. We also outline the impact of typical learning related issues like overfitting on the practical development process.
Quantitative Measures in Support of Latent Print Comparison

Latent prints of friction ridge impressions have long been useful in identification, and the methodology of examining latent prints, known as ACE-V (analysis, comparison, evaluation and verification), has been welldocumented. The need to quantify confidences within ACE-V has been articulated in several recent influential reports to strengthen the science of friction ridge analysis. This research addresses the evaluation of three quantitative measures: rarity of features, confidence of opinion and a probabilistic measure of similarity. The first of these, useful in the analysis phase of ACE-V, is to determine the rarity of observed features. Rarity is difficult to compute due to the large number of variables and high data requirements. The proposed solution uses probabilistic graphical models to represent spatial distributions of fingerprints represented at level 2 detail (minutiae). First, the minutia coordinate system is transformed into standard position based on a point of high curvature, viz., core point; statistical regression (based on a Gaussian process formulation and a training set of latent prints) is used to estimate the core point. A directed probabilistic graphical model is constructed using inter-minutia dependencies and minutia confidences. The resulting model is used to determine the probability of random correspondence of the evidence in a database of n prints. The method is validated using statistical goodness-of-fit tests and illustrated using: (i) a simple configuration of minutiae, (ii) randomly selected latent fingerprints in a database, and (iii) a well-known case of erroneous identification. The second quantitative measure addressed is that of determining confidence of opinion– which is relevant to the evaluation phase of ACE-V. The proposed computation determines a likelihood ratio as a product of rarity and the probability of similarity under the identification hypothesis. The third area concerns measuring similarity probabilistically, in a manner analogous to cognition. A Markov random field is used to jointly model the minutiae in both the evidence and the known. The algorithms developed are based on statistical machine learning using several publicly available fingerprint data sets for parameter learning and testing. The developed methods can be of potential use in examiner training, presentation of opinion and validating examination procedures. This document is a research report submitted to the U.S. Department of Justice. This report has not been published by the Department. Opinions or points of view expressed are those of the author(s) and do not necessarily reflect the official position or policies of the U.S. Department of Justice.