Enhancing questioning skills through child avatar chatbot training with feedback

Training child investigative interviewing skills is a specialized task. Those being trained need opportunities to practice their skills in realistic settings and receive immediate feedback. A key step in ensuring the availability of such opportunities is to develop a dynamic, conversational avatar, using artificial intelligence (AI) technology that can provide implicit and explicit feedback to trainees. In the iterative process, use of a chatbot avatar to test the language and conversation model is crucial. The model is fine-tuned with interview data and realistic scenarios. This study used a pre-post training design to assess the learning effects on questioning skills across four child interview sessions that involved training with a child avatar chatbot fine-tuned with interview data and realistic scenarios. Thirty university students from the areas of child welfare, social work, and psychology were divided into two groups; one group received direct feedback (n = 12), whereas the other received no feedback (n = 18). An automatic coding function in the language model identified the question types. Information on question types was provided as feedback in the direct feedback group only. The scenario included a 6-year-old girl being interviewed about alleged physical abuse. After the first interview session (baseline), all participants watched a video lecture on memory, witness psychology, and questioning before they conducted two additional interview sessions and completed a post-experience survey. One week later, they conducted a fourth interview and completed another postexperience survey. All chatbot transcripts were coded for interview quality. The language model’s automatic feedback function was found to be highly reliable in classifying question types, reflecting the substantial agreement among the raters [Cohen’s kappa (κ) = 0.80] in coding open-ended, cued recall, and closed questions. Participants who received direct feedback showed a significantly higher improvement in open-ended questioning than those in the non-feedback group, with a significant increase in the number of open-ended questions used between the baseline and each of the other three chat sessions. This study demonstrates that child avatar chatbot training improves interview quality with regard to recommended questioning, especially when combined with direct feedback on questioning

Infected pancreatic necrosis: outcomes and clinical predictors of mortality. A post hoc analysis of the MANCTRA-1 international study

: The identification of high-risk patients in the early stages of infected pancreatic necrosis (IPN) is critical, because it could help the clinicians to adopt more effective management strategies. We conducted a post hoc analysis of the MANCTRA-1 international study to assess the association between clinical risk factors and mortality among adult patients with IPN. Univariable and multivariable logistic regression models were used to identify prognostic factors of mortality. We identified 247 consecutive patients with IPN hospitalised between January 2019 and December 2020. History of uncontrolled arterial hypertension (p = 0.032; 95% CI 1.135-15.882; aOR 4.245), qSOFA (p = 0.005; 95% CI 1.359-5.879; aOR 2.828), renal failure (p = 0.022; 95% CI 1.138-5.442; aOR 2.489), and haemodynamic failure (p = 0.018; 95% CI 1.184-5.978; aOR 2.661), were identified as independent predictors of mortality in IPN patients. Cholangitis (p = 0.003; 95% CI 1.598-9.930; aOR 3.983), abdominal compartment syndrome (p = 0.032; 95% CI 1.090-6.967; aOR 2.735), and gastrointestinal/intra-abdominal bleeding (p = 0.009; 95% CI 1.286-5.712; aOR 2.710) were independently associated with the risk of mortality. Upfront open surgical necrosectomy was strongly associated with the risk of mortality (p < 0.001; 95% CI 1.912-7.442; aOR 3.772), whereas endoscopic drainage of pancreatic necrosis (p = 0.018; 95% CI 0.138-0.834; aOR 0.339) and enteral nutrition (p = 0.003; 95% CI 0.143-0.716; aOR 0.320) were found as protective factors. Organ failure, acute cholangitis, and upfront open surgical necrosectomy were the most significant predictors of mortality. Our study confirmed that, even in a subgroup of particularly ill patients such as those with IPN, upfront open surgery should be avoided as much as possible. Study protocol registered in ClinicalTrials.Gov (I.D. Number NCT04747990)

Visual Sentiment Analysis from Disaster Images in Social Media

The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on visual sentiment analysis in a societally important domain, namely disaster analysis in social media. To this aim, we propose a deep visual sentiment analyzer for disaster-related images, covering different aspects of visual sentiment analysis starting from data collection, annotation, model selection, implementation, and evaluations. For data annotation and analyzing people’s sentiments towards natural disasters and associated images in social media, a crowd-sourcing study has been conducted with a large number of participants worldwide. The crowd-sourcing study resulted in a large-scale benchmark dataset with four different sets of annotations, each aiming at a separate task. The presented analysis and the associated dataset, which is made public, will provide a baseline/benchmark for future research in the domain. We believe the proposed system can contribute toward more livable communities by helping different stakeholders, such as news broadcasters, humanitarian organizations, as well as the general public

A centralized architecture for inventory management using RFID

The paper presents Radio Frequency Identification (RFID) based solution for inventory management reported by the researchers in various case studies of warehouses. Limitations and challenges faced by companies in monitoring and managing inventory are highlighted. To cope with the associated complexities, a centralized architecture with four different configurations is proposed. The presented configurations help to manage inventory of warehouse in an efficient and accurate manner. The final proposed configuration over-performs among previous configurations in terms of minimizing human assistance. It automates the inventory management system by making it capable of real time monitoring and construction of projects demanding simultaneous execution. It allows to meet with projects budget and deadlines. The paper also critically presents a comparative analysis of the two relevant technologies i.e. RFID and barcode

Addressing collision avoidance and nonholonomic constraints of a wheeled robot: Modeling and simulation

This paper presents kinematic model of two configurations of a wheeled mobile robot. Two-wheeled robot with castor and four-wheeled robot are considered for modeling. Kinematic equations, modeled in MATLAB/Simulink, represent the position and angle of the mobile robots. Simulation results illustrate the actual trajectory followed by the 'soft' robot. The potential use of the derived kinematic model is two folds; in research as well as in academia. The model can be employed to test and validate advanced algorithms related with mobile robots e.g. for collision avoidance, path-planning, navigation etc while in an educational environment, it can assist students to study the behavior and nonholonomic constraints of their robots prior to their fabrication for competitions. As a case study to demonstrate the application of the developed model, the present research proposed a novel collision avoidance algorithm named as Intelligent Bug Algorithm (IBA). Preliminary comparative results dictate that IBA outperforms the reported Bug algorithms. © 2014 IEEE

A review of biodegradable natural polymer-based nanoparticles for drug delivery applications

Biodegradable natural polymers have been investigated extensively as the best choice for encapsulation and delivery of drugs. The research has attracted remarkable attention in the pharmaceutical industry. The shortcomings of conventional dosage systems, along with modified and targeted drug delivery methods, are addressed by using polymers with improved bioavailability, biocompatibility, and lower toxicity. Therefore, nanomedicines are now considered to be an innovative type of medication. This review critically examines the use of natural biodegradable polymers and their drug delivery systems for local or targeted and controlled/sustained drug release against fatal diseases

Visual Sentiment Analysis from Disaster Images in Social Media

The increasing popularity of social networks and users’ tendency towards sharing their feelings, expressions, and opinions in text, visual, and audio content have opened new opportunities and challenges in sentiment analysis. While sentiment analysis of text streams has been widely explored in the literature, sentiment analysis from images and videos is relatively new. This article focuses on visual sentiment analysis in a societally important domain, namely disaster analysis in social media. To this aim, we propose a deep visual sentiment analyzer for disaster-related images, covering different aspects of visual sentiment analysis starting from data collection, annotation, model selection, implementation, and evaluations. For data annotation and analyzing people’s sentiments towards natural disasters and associated images in social media, a crowd-sourcing study has been conducted with a large number of participants worldwide. The crowd-sourcing study resulted in a large-scale benchmark dataset with four different sets of annotations, each aiming at a separate task. The presented analysis and the associated dataset, which is made public, will provide a baseline/benchmark for future research in the domain. We believe the proposed system can contribute toward more livable communities by helping different stakeholders, such as news broadcasters, humanitarian organizations, as well as the general public

Dynamic Compressive Mechanical Behavior and Microstructure Evolution of Rolled Fe-28Mn-10Al-1.2C Low-Density Steel

In this study, the quasi-static and dynamic compressive mechanical behavior of a rolled Fe-28Mn-10Al-1.2C steel (low-density) was investigated. X-ray diffraction, optical microscopy, electron backscattered diffraction and transmission electron microscopy were conducted to characterize the microstructure evolution. The results displayed that the steel has remarkable strain rate sensitivity and strong strain hardenability under high strain rate compression. Most specifically, the deformation behavior was changed with the increase in the strain rate. A feasible mathematical analysis for the calculation of stacking fault energies and the critical resolve shear stresses for twinning was employed and discussed the nucleation of the twinning. The microband-induced plasticity and twinning-induced plasticity controlled the deformation under high strain rate compression and provided a strong strain hardening effect. The higher mechanical response can increase the broad use of low-density steel in automobile applications

The prokinetic, laxative, and antidiarrheal effects of morus nigra: possible muscarinic, Ca(2+) channel blocking, and antimuscarinic mechanisms

Abstract Morus nigra Linn. (black mulberry) is used in gastrointestinal ailments. This study demonstrates gut modulatory properties of M. nigra. The prokinetic, laxative, and antidiarrheal activities of M. nigra were assessed in mice, while isolated rabbit jejunum and guinea-pig ileum were used to explore insight into mechanism(s). At 30 and 70 mg/kg, the crude extract of M. nigra (Mn.Cr) exhibited atropine-sensitive prokinetic and laxative effects, similar to carbachol (CCh). While at higher doses (100, 300, and 500 mg/kg), Mn.Cr offered protection against castor oil-induced diarrhea. In rabbit jejunum, Mn.Cr and its chloroform fraction inhibited CCh-induced contractions more potently compared with high K(+) (80 mm). Conversely, petroleum fraction was more potent against high-K(+) -induced contractions. At 0.01 mg/mL, Mn.Cr caused a parallel shift in acetylcholine concentration-response curves (CRCs) followed by a non-parallel shift at 0.03 mg/mL, similar to dicyclomine. At further tested concentrations, Mn.Cr (0.1 and 0.3 mg/mL) and petroleum fraction suppressed Ca(2+) CRCs, similar to verapamil. In guinea-pig ileum, Mn.Cr, its aqueous and ethyl acetate fractions exhibited atropine-sensitive gut stimulant activity along with additional uncharacterized excitatory response in the aqueous fraction only. These results suggest that black mulberry possesses prokinetic, laxative, and antidiarrheal effects, putatively mediated through cholinomimetic, antimuscarinic, and Ca(2+) antagonist mechanisms, respectively. Copyright © 2016 John Wiley & Sons, Ltd