Interrogation Strategies Research Articles

Mother-child engagement in a categorisation activity: implications for parental pedagogy and early education research

ABSTRACT Maternal support for children's cognitive competence has received considerable attention in the developmental and early childhood education literature. However, little research has examined the link between maternal behaviour and children’s categorisation performance. The current study explored the strategies that mothers and children used as they engaged in a categorisation task. Twenty-seven mother–child dyads from middle-class mothers and their three-to-five-year-old preschool children were videotaped while engaging in a categorisation activity. Total testing time, including video recordings, did not exceed one hour. The mother-child interaction codes were analysed using frequency analyses to extract empirical estimates. Certain maternal strategies (e.g. interrogative strategies) were positively related to children’s verbal responses. However, maternal stylistic (taxonomic and thematic) differences were not associated with children’s strategies. The study found that mothers use a variety of strategies to engage with their children in the categorisation activity. Theoretical perspectives and implications of the current research for parental pedagogy and early childhood education research are discussed.

Chronoamperometric interrogation of an electrochemical aptamer-based sensor with tetrahedral DNA nanostructure pendulums for continuous biomarker measurements

Tetrahedral DNA nanostructure (TDN) is highly promising in developing electrochemical aptamer-based (E-AB) sensors for biomolecular detection, owing to its inherit programmability, spatial orientation and structural robustness. However, current interrogation strategies applied for TDN-based E-AB sensors, including enzyme-based amperometry, voltammetry, and electrochemical impedance spectroscopy, either require complicated probe design or suffer from limited applicability or selectivity. In this study, a TDN pendulum-empowered E-AB sensor interrogated by chronoamperometry for reagent-free and continuous monitoring of a blood clotting enzyme, thrombin, was developed. TDN pendulums with extended aptamer sequences at three vertices were immobilized on a gold electrode via a thiolated double-stranded DNA (dsDNA) at the fourth vertex, and their motion is modulated by the bonding of target thrombin to aptamers. We observed a significantly amplified signalling output on our sensor based on the TDN pendulum compared to E-AB sensors modified with linear pendulums. Moreover, our sensor achieved highly selective and rapidly responsive measurement of thrombin in both PBS and artificial urine, with a wide dynamic range from 1 pM to 10 nM. This study shows chronoamperometry-enabled continuous biomarker monitoring on a sub-second timescale with a drift-free baseline, demonstrating a novel approach to accurately detect molecular dynamics in real time.

Humane Interrogation Strategies Are Associated With Confessions, Cooperation, and Disclosure: Evidence From a Field Study of Incarcerated Individuals in the United States

The techniques used to interrogate individuals suspected of a crime can profoundly impact their decisions to confess, cooperate, or disclose information. Research using different methods suggests that two prevailing interrogation approaches—accusatorial and information-gathering—differentially impact interrogation outcomes. However, confession, cooperation, and information disclosure are ultimately the suspected person’s decision, yet few studies directly examine their perspectives about how interrogation techniques affect their decisions, and none examine a U.S. sample. This study assessed how interrogation strategies characterized by humanity, rapport, confrontation, and dominance/control predicted interrogation outcomes in a sample of 249 individuals incarcerated in two U.S. jails. Respondents who reported experiencing humane strategies were more likely to confess, cooperate completely, and disclose incriminating information. Dominance/control-oriented strategies predicted partial confession (but not cooperation or disclosure), and rapport-based and confrontational techniques did not predict outcomes. Findings highlight humane interrogation strategies as likely the most productive strategies to adopt in criminal interrogations.

A Study on Interrogation Strategies based on Suspect’s Psychological Motives

A Study on Interrogation Strategies based on Suspect’s Psychological Motives

The effect of confirmation bias and racial stereotypes on perceptions of guilt and interrogation strategy decisions

AbstractWe examined whether racial stereotypes and guilt bias could affect perceptions of suspects and decisions in investigations. In three studies, participants read about a case, provided guilt judgments, and suggested questions they would ask a suspect. In all studies we manipulated race‐based stereotypes and guilt bias using different methods and operationalizations to provide a robust test of our hypotheses. In Experiment 1, we found that participants asked more guilt‐presumptive questions to the subject they decided was guilty. In Experiment 2, we found that when presented with more incriminating evidence, participants perceived suspects as more guilty and chose/generated more guilt‐presumptive questions. In Experiment 3, we found that those with less incriminating evidence reported lower levels of guilt and chose more coercive techniques. Our findings highlight the complexity of racial stereotypes and confirmation bias within investigation decision‐making.

The use of artificial intelligence in interrogation: lies and truth

Following the development of artificial intelligence technology, a new trend has emerged in which this technology is increasingly used in case investigations. In this study, we developed a lie detection system that can instantly determine whether an interrogee is lying depending on their emotional responses to specific questions. Investigators then use these data, in addition to their personal experiences and case information, to adjust their interrogation strategies and techniques, thereby leading the interrogee to confess and accelerating the investigation process. Our system collects data using OpenFace and performs deep learning using gcForest. Deep learning training was performed using a real-life trial dataset, the Miami University Deception Detection Database, and a bag-of-lies dataset, and their corresponding trained systems achieved a detection accuracy of 95.11%, 90.83%, and 88.19%, respectively.

The Relative Frequency of True and False Confessions and Denials in an Experimental Paradigm Designed to Investigate Deception Detection

ABSTRACT Truth-default theory (TDT) proposes that deception is infrequent relative to honesty and that deception requires a motive. TDT further lists confessed deception as a viable method of improving deception detection accuracy. Findings from the experimental literature on false confessions conflict with TDT predictions suggesting that confessions might be an important boundary condition for the theory. Data from various versions of a cheating experiment (N = 485) were reexamined for the rates of true and false confessions and denials under different types of interrogation strategies including accusatory questioning and false evidence ploys. Frequent honest but not false confessions were observed. Demand effects, communication goals, and deception motives are proposed as potential explanations for the conflicting findings. The results are interpreted and framed within TDT. Suggestions are provided for practitioners and for future research.

It's all about time: the influence of behaviour and timelines on suspect disclosure during investigative interviews

ABSTRACT Research on confession has usually focused on showing that it is significantly associated with individual, crime-related, and situational/contextual variables and is both a static event and a dichotomous indicator of interview success. Recent work, however, suggests that investigative interviews are a dynamic process in which interrogation strategies change over time. Using a Game Theory perspective, this study looks at the impact of behaviours of both players (interviewer and suspect) on the production of investigation-relevant information (IRI). The sub-objective is to demonstrate the usefulness of applying Game Theory to the study of investigative interviews by considering time and interaction between players as an integrative part of the analysis. Videotaped interviews related to online child sexual exploitation (n = 130) were analysed and the different behaviours of suspects and interviewers were analysed to determine if they involved (1) rapport building/active denial, (2) collaboration, (3) confrontation, (4) emotion/response, and (5) elicitation of information related to the case. Results showed that information relevant to the investigation is often provided shortly after a suspect has offered additional information or given responses that meet emotional needs (e.g. justifications). The interviewer's use of available evidence increases the likelihood that additional information will be provided, while the ability to build a rapport with the suspect is effective in the longer term, even if a positive effect is not immediately observed. Using a dynamic process approach in analysing investigative interviews provides a starting point for the creation of practical guidelines to help practitioners increase suspect collaboration during investigative interviews.

Self-Vernier Effect-Assisted Optical Fiber Sensor Based on Microwave Photonics and Its Machine Learning Analysis

Optical Vernier effect has been recently demonstrated as a tool to enhance the sensitivity of optical fiber interferometric sensors and has become a hot topic in the last few years. The generation of the Vernier effect relies on the superposition of interferograms of two interferometers (a sensing one and a reference one) with marginally different optical path differences (OPDs), where an amplitude modulation-like signal is sustained in the output spectrum. The Vernier modulation envelope exhibits significantly magnified sensitivity in response to external perturbations, compared to the individual sensing interferometer, providing a new route to new generations of ultra-sensitive optical fiber sensors. However, the construction of a Vernier effect-based sensor needs careful integration of two interferometers with a precise OPD deviation, which is challenging if not impossible sometimes. Additionally, the interrogation of a Vernier effect-based sensor requires the acquisition of its spectrum in a broad wavelength (frequency) window with a large number of sampling points, followed by cumbersome processing for the extraction of the Vernier envelope signal. In this article, we propose a new concept of the self-Vernier effect for the sensitivity improvement of optical fiber sensors. A proof-of-concept demonstration is performed using a single low-coherent microwave-photonic Fabry-Perot interferometer (FPI) with an addition of an auxiliary delay path. The self-Vernier effect is obtained by the overlap between the microwave interferogram of the FPI and its slightly time-delayed one. Detailed analyses regarding the principle, mathematical modeling, and experimental investigation are given. Moreover, we propose and demonstrate a new demodulation approach to the Vernier effect-based sensor through machine learning analysis by directly and statistically learning the embedded relation between the measurand of interest and the output spectrum. It is appreciated that the necessity of the frequency observation window and the number of sampling points can be remarkably reduced through machine learning analysis. The present interrogation strategy is highly generalizable and can be readily applied to optical-domain Vernier effect-based optical fiber sensors.

Improved in situ sequencing for high-resolution targeted spatial transcriptomic analysis in tissue sections

Spatial transcriptomics enables the study of localization-indexed gene expression activity in tissues, providing the transcriptional landscape that in turn indicates the potential regulatory networks of gene expression. In situ sequencing (ISS) is a targeted spatial transcriptomic technique, based on padlock probe and rolling circle amplification combined with next-generation sequencing chemistry, for highly multiplexed in situ gene expression profiling. Here, we present improved in situ sequencing (IISS) that exploits a new probing and barcoding approach, combined with advanced image analysis pipelines for high-resolution targeted spatial gene expression profiling. We develop an improved combinatorial probe anchor ligation chemistry using a 2-base encoding strategy for barcode interrogation. The new encoding strategy results in higher signal intensity as well as improved specificity for in situ sequencing, while maintaining a streamlined analysis pipeline for targeted spatial transcriptomics. We show that IISS can be applied to both fresh frozen tissue and formalin-fixed paraffin-embedded tissue sections for single-cell level spatial gene expression analysis, based on which the developmental trajectory and cell-cell communication networks can also be constructed.

Ventral pallidal regulation of motivated behaviors and reinforcement.

The interconnected nuclei of the ventral basal ganglia have long been identified as key regulators of motivated behavior, and dysfunction of this circuit is strongly implicated in mood and substance use disorders. The ventral pallidum (VP) is a central node of the ventral basal ganglia, and recent studies have revealed complex VP cellular heterogeneity and cell- and circuit-specific regulation of reward, aversion, motivation, and drug-seeking behaviors. Although the VP is canonically considered a relay and output structure for this circuit, emerging data indicate that the VP is a central hub in an extensive network for reward processing and the regulation of motivation that extends beyond classically defined basal ganglia borders. VP neurons respond temporally faster and show more advanced reward coding and prediction error processing than neurons in the upstream nucleus accumbens, and regulate the activity of the ventral mesencephalon dopamine system. This review will summarize recent findings in the literature and provide an update on the complex cellular heterogeneity and cell- and circuit-specific regulation of motivated behaviors and reinforcement by the VP with a specific focus on mood and substance use disorders. In addition, we will discuss mechanisms by which stress and drug exposure alter the functioning of the VP and produce susceptibility to neuropsychiatric disorders. Lastly, we will outline unanswered questions and identify future directions for studies necessary to further clarify the central role of VP neurons in the regulation of motivated behaviors. Significance: Research in the last decade has revealed a complex cell- and circuit-specific role for the VP in reward processing and the regulation of motivated behaviors. Novel insights obtained using cell- and circuit-specific interrogation strategies have led to a major shift in our understanding of this region. Here, we provide a comprehensive review of the VP in which we integrate novel findings with the existing literature and highlight the emerging role of the VP as a linchpin of the neural systems that regulate motivation, reward, and aversion. In addition, we discuss the dysfunction of the VP in animal models of neuropsychiatric disorders.

Fiber Bragg Grating Interrogation System Based on the Laser Wavelength Modulation in a Digital Supermode -Distributed Bragg Reflector Laser

In this paper, we propose a Fiber Bragg Grating (FBG) interrogation system based on the modulation of the laser wavelength. Key component of the interrogation scheme is in a Digital Supermode -Distributed Bragg Reflector (DS-DBR) Laser. The DS-DBR features a large spectral range and a fast modulation capability in a low cost device. When the laser spans over the FBG spectral range, the power of the reflected signal changes over time according the FBG spectral shape. The information on the Bragg wavelength can be extracted from the modulated signal reflected by the FBG in the time domain. We implemented the proposed interrogation scheme by discrete components demonstrating its capability to retrieve the Bragg wavelength of one or more FBGs. The interrogation system features an intrinsic tradeoff between spectral resolution and interrogation speed. A Bragg wavelength resolution of 1.5 pm has been obtained using 1 kHz modulating frequency. The proposed interrogation system is particular suited in applications in which an adaptive interrogation strategy can be conveniently adopted.

Interrogative Constructions in Guaraní: Grammatical, Pragmatic and Typological Aspects

This article is set in the framework of typological and functional studies on interrogativity, and focuses on the study of Guaraní, based on primary data collected in Formosa (Argentina). Interrogative constructions encode the speaker’s request for information, and their intention to confirm the underlying statement of the information that is the focus of the question. This topic has been partially addressed in previous descriptive works on Guaraní. There are, however, aspects in this domain yet to be explored. One involves the functions and meanings of the different interrogative strategies this language exhibits and the semantic particularities of their combination. In this regard, we analyze the distribution, meaning and pragmatic function of clitics =pa and =piko in polar and content questions. Furthermore, a preliminary analysis of tag questions (as a subtype of polar questions) is advanced here. Finally, we also discuss the way how the concurrence of interrogative words and clitics in Guarani is pragmatically and semantically motivated by the speaker’s epistemic attitude when posing the question.

Advantages, Pitfalls, and Developments of All Optical Interrogation Strategies of Microcircuits in vivo.

The holy grail for every neurophysiologist is to conclude a causal relationship between an elementary behaviour and the function of a specific brain area or circuit. Our effort to map elementary behaviours to specific brain loci and to further manipulate neural activity while observing the alterations in behaviour is in essence the goal for neuroscientists. Recent advancements in the area of experimental brain imaging in the form of longer wavelength near infrared (NIR) pulsed lasers with the development of highly efficient optogenetic actuators and reporters of neural activity, has endowed us with unprecedented resolution in spatiotemporal precision both in imaging neural activity as well as manipulating it with multiphoton microscopy. This readily available toolbox has introduced a so called all-optical physiology and interrogation of circuits and has opened new horizons when it comes to precisely, fast and non-invasively map and manipulate anatomically, molecularly or functionally identified mesoscopic brain circuits. The purpose of this review is to describe the advantages and possible pitfalls of all-optical approaches in system neuroscience, where by all-optical we mean use of multiphoton microscopy to image the functional response of neuron(s) in the network so to attain flexible choice of the cells to be also optogenetically photostimulated by holography, in absence of electrophysiology. Spatio-temporal constraints will be compared toward the classical reference of electrophysiology methods. When appropriate, in relation to current limitations of current optical approaches, we will make reference to latest works aimed to overcome these limitations, in order to highlight the most recent developments. We will also provide examples of types of experiments uniquely approachable all-optically. Finally, although mechanically non-invasive, all-optical electrophysiology exhibits potential off-target effects which can ambiguate and complicate the interpretation of the results. In summary, this review is an effort to exemplify how an all-optical experiment can be designed, conducted and interpreted from the point of view of the integrative neurophysiologist.

Forensic Psychology: How Can Psychology Help Law Enforcement?

Aim: In this article, I would like to show how psychology, especially its forensic field, can help investigative authorities effectively detect individual crimes. Although most law enforcement psychologists work as primary care professionals, basically conducting psychological aptitude tests of colleagues and creating mental well-being, it is important to see that the science of psychology can be applied to law enforcement in a much more complex way.Methodology: Both domestic and international studies make researches with this topic, although in some criminal psychology and forensic psychology are used to be synonyms. In the present study, I review the literature on the means by which forensic psychology can assist in effective detection.Findings: Although the methodology of profiling specific offenders is not new, the procedure was developed primarily for the detection of serial crimes, but it has a great relevance in the detection of individual crimes. Furthermore, in addition to crimes against life, it can be used well in the analytical assessment of sexual offenses, as well as in the design of interrogation strategies.Value: In the present study, two methodological elements of forensic psychology, profiling and interrogation strategy, are analyzed in the light of sexual offenses.

On question words in Czech Sign Language

Abstract This paper investigates content questions and the paradigm of question words in Czech Sign Language (český znakový jazyk – ČZJ). While this topic has been investigated for a fair number of other sign languages, a comprehensive study for ČZJ is still missing. Our aim is to fill this gap. In the absence of a representative corpus for ČZJ, we use data from the most extensive electronic dictionary database (Dictio), developed at the Masaryk University in Brno. We offer a basic description of the ČZJ interrogative strategies for content questions. In doing so, we also situate the language within the typology of sign language interrogatives: we classify ČZJ as a language with a rich paradigm of question words, and we identify the basic syntactic position of question words as sentence-final. Furthermore, we outline three morphological types of ČZJ question words: simple, complex, and derived.

Predicting surgical outcomes for chronic exertional compartment syndrome using a machine learning framework with embedded trust by interrogation strategies

Chronic exertional compartment syndrome (CECS) is a condition occurring most frequently in the lower limbs and often requires corrective surgery to alleviate symptoms. Amongst military personnel, the success rates of this surgery can be as low as 20%, presenting a challenge in determining whether surgery is worthwhile. In this study, the data of 132 fasciotomies for CECS was analysed and using combinatorial feature selection methods, coupled with input from clinicians, identified a set of key clinical features contributing to the occupational outcomes of surgery. Features were utilised to develop a machine learning model for predicting return-to-work outcomes 12-months post-surgery. An AUC of 0.85 ± 0.08 was achieved using a linear-SVM, trained using 6 features (height, mean arterial pressure, pre-surgical score on the exercise-induced leg pain questionnaire, time from initial presentation to surgery, and whether a patient had received a prior surgery for CECS). To facilitate trust and transparency, interrogation strategies were used to identify reasons why certain patients were misclassified, using instance hardness measures. Model interrogation revealed that patient difficulty was associated with an overlap in the clinical characteristics of surgical outcomes, which was best handled by XGBoost and SVM-based models. The methodology was compiled into a machine learning framework, termed AITIA, which can be applied to other clinical problems. AITIA extends the typical machine learning pipeline, integrating the proposed interrogation strategy, allowing to user to reason and decide whether to trust the developed model based on the sensibility of its decision-making.

Learning Interrogation Strategies while Considering Deceptions in Detective Interactive Stories

The strategies for interactive characters to select appropriate dialogues remain as an open issue in related research areas. In this paper we propose an approach based on reinforcement learning to learn the strategy of interrogation dialogue from one virtual agent toward another. The emotion variation of the suspect agent is modeled with a hazard function, and the detective agent must learn its interrogation strategies based on the emotion state of the suspect agent. The reinforcement learning reward schemes are evaluated to choose the proper reward in the dialogue. Our contribution is twofold. Firstly, we proposed a new framework of reinforcement learning to model dialogue strategies. Secondly, background knowledge and emotion states of agents are brought into the dialogue strategies. The resulted dialogue strategy in our experiment is sensitive in detecting lies from the suspect, and with it the interrogator may receive more correct answer.

Developments in Understanding Diffuse Noxious Inhibitory Controls: Pharmacological Evidence from Pre-Clinical Research.

Bulbospinal pathways regulate nociceptive processing, and inhibitory modulation of nociception can be achieved via the activity of diffuse noxious inhibitory controls (DNIC), a unique descending pathway activated upon application of a conditioning stimulus (CS). Numerous studies have investigated the effects of varied pharmacological systems on the expression status of a) DNIC (as measured in anaesthetised animals) and b) the descending control of nociception (DCN), a surrogate measure of DNIC-like effects in conscious animals. However, the complexity of the underlying circuitry that governs initiation of a top-down inhibitory response in reaction to a CS, coupled with the methodological limitations associated with using pharmacological tools for its study, has often obscured the exact role(s) of a given drug. In this literature review, we discuss the pharmacological manipulation interrogation strategies that have hitherto been used to examine the functionality of DNIC and DCN. Discreet administration of a substance in the spinal cord or brain is considered in the context of action on one of four hypothetical systems that underlie the functionality of DNIC/DCN, where interpreting the outcome is often complicated by overlapping qualities. Systemic pharmacological modulation of DNIC/DCN is also discussed despite the fact that the precise location of drug action(s) cannot be pinpointed. Chiefly, modulation of the noradrenergic, serotonergic and opioidergic transmission systems impacts DNIC/DCN in a manner that relates to drug class, route of administration and health/disease state implicated. The advent of increasingly sophisticated interrogation tools will expedite our full understanding of the circuitries that modulate naturally occurring pain-inhibiting pathways.

Interrogation of Electrochemical Aptamer-Based Sensors via Peak-to-Peak Separation in Cyclic Voltammetry Improves the Temporal Stability and Batch-to-Batch Variability in Biological Fluids.

Electrochemical, aptamer-based (E-AB) sensors support continuous, real-time measurements of specific molecular targets in complex fluids such as undiluted serum. They achieve these measurements by using redox-reporter-modified, electrode-attached aptamers that undergo target binding-induced conformational changes which, in turn, change electron transfer between the reporter and the sensor surface. Traditionally, E-AB sensors are interrogated via pulse voltammetry to monitor binding-induced changes in transfer kinetics. While these pulse techniques are sensitive to changes in electron transfer, they also respond to progressive changes in the sensor surface driven by biofouling or monolayer desorption and, consequently, present a significant drift. Moreover, we have empirically observed that differential voltage pulsing can accelerate monolayer desorption from the sensor surface, presumably via field-induced actuation of aptamers. Here, in contrast, we demonstrate the potential advantages of employing cyclic voltammetry to measure electron-transfer changes directly. In our approach, the target concentration is reported via changes in the peak-to-peak separation, ΔEP, of cyclic voltammograms. Because the magnitude of ΔEP is insensitive to variations in the number of aptamer probes on the electrode, ΔEP-interrogated E-AB sensors are resistant to drift and show decreased batch-to-batch and day-to-day variability in sensor performance. Moreover, ΔEP-based measurements can also be performed in a few hundred milliseconds and are, thus, competitive with other subsecond interrogation strategies such as chronoamperometry but with the added benefit of retaining sensor capacitance information that can report on monolayer stability over time.