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Although a much older concept, it is only within the decade of 2010–2019 that this term “social justice” came into prominence in school psychology. This chapter provides a combination of research analysis and a push to personalize and apply the concept of social justice. The chapter begins by defining social justice and describing why this concept is so critical for school psychologists. As part of this overview of social justice, the authors share some of their own stories as examples of how professionals might draw upon their own value systems and experiences to develop as agents of social justice. Readers are also provided with reflection questions to personalize the concept. The bulk of the chapter focuses on what it might look like to “fight” for social justice in school psychology, highlighting concepts such as developing critical self-awareness (with coverage of implicit bias and cultural humility) and using one’s leadership skills to work in an inclusive, participatory manner. A personal action plan template is provided. The chapter closes with a call to action, framing social justice as a mechanism for maximizing both the professional impact and personal satisfaction of one’s work as a school psychologist.

Forecasting the daily flows of rivers is a challenging task that have a significant impact on the environment, agriculture, and people life. This paper investigates the river flow forecasting problem using two types of Deep Neural Networks (DNN) structures, Long Short-Term Memory (LSTM) and Layered Recurrent Neural Networks (L-RNN) for two rivers in the USA, Black and Gila rivers. The data sets collected for a period of seven years for Black river (six years for training and one year for testing) and four years for Gila river (three years for training and one year for testing) were used for our experiments. An order selection method based partial auto-correlation sequence was employed to determine the appropriate order for the proposed models in both cases. Mean square errors (MSE), Root mean square errors (RMSE) and Variance (VAF) were used to evaluate to developed models. The obtained results show that the proposed LSTM is able to produce an excellent model in each case study.

Image clustering presents a hot topic that researchers have chased extensively. There is always a need to a promising clustering technique due to its vital role in further image processing steps. This paper presents a compelling clustering approach for brain tumors and breast cancer in Magnetic Resonance Imaging (MRI). Driven by the superiority of nature-inspired algorithms in providing computational tools to deal with optimization problems, we propose Flower Pollination Algorithm (FPA) and Crow Search Algorithm (CSA) to present a clustering method for brain tumors and breast cancer. Evaluation clustering results of CSA and FPA were judged using two apposite criteria and compared with results of K-means, fuzzy c-means and other metaheuristics when applied to cluster the same benchmark datasets. The clustering method-based CSA and FPA yielded encouraging results, significantly outperforming those obtained by K-means and fuzzy c-means and slightly surpassed those of other metaheuristic algorithms.

Sleep is an essential part of health and longevity persons. As people grow older, the quality of their sleep becomes vital. Poor sleep quality can make negative physiological, psychological, and social impacts on the elderly population, causing a range of health problems including coronary heart disease, depression, anxiety, and loneliness. Early detection, proper diagnosis, and treatments for sleep disorders can be achieved by identifying sleep patterns through long-term sleep monitoring. Although many studies developed sleep monitoring systems by using non-invasive measures such as body temperature, pressure, or body movement signal, research is still limited to detect sleep position changes by using a depth camera. The present study is intended (1) to identify concerns on the existing sleep monitoring system based on the literature review and (2) propose to developing a non-invasive sleep monitoring system using an infrared depth camera. For the literature review, various journal/conference papers have been reviewed to understand the characteristics, tools, and algorithms of the existing sleep monitoring systems. For the system development and validation, we collected data for the sleep positions from two subjects (35 years old man and 84 years old women) during the four-hour sleep. Kinect II depth sensor was used for data collection. We found that the averaged depth data is useful measure to notify the participants’ positional changes during the sleep.

The goal of the ambient intelligence system is not only to enhance the way people communicate with the surrounding environment but also to advance safety measures and enrich human lives. In this paper, we introduce an integrated ambient intelligence system (IAmIS) to perceive the presence of people, identify them, determine their locations, and provide suitable interaction with them. The proposed framework can be applied in various application domains such as a smart house, authorisation, surveillance, crime prevention, and many others. The proposed system has five components: body detection and tracking, face recognition, controller, monitor system, and interaction modules. The system deploys RGB cameras and Kinect depth sensors to monitor human activity. The developed system is designed to be fast and reliable for indoor environments. The proposed IAmIS can interact directly with the environment or communicate with humans acting on the environment. Thus, the system behaves as an intelligent agent. The system has been deployed in our research lab and can recognise lab members and guests to the lab as well as track their movements and have interactions with them depending upon their identity and location within the lab.

Police social workers are crucial components of police departments when individuals or communities experience crises. They perform essential tasks, including well-being checks, crisis intervention, de-escalation, mediation, safety planning, referrals to community services, and other preventative measures to stabilize clients in crisis. The chapter will define police social work and give the reader insight into the stabilization approaches used by police social workers to prepare clients for their next level of care. The chapter begins with a brief history of the evolution of police social workers within the context of public policy and their most recent call to action to address mental health crises. The authors utilize a multi-tier approach to highlight stabilization approaches used by police social workers with a focus on empowering individuals, families, and communities to collaborate on solutions. The chapter uses case scenarios drawn from the experiences of police social workers and interns to demonstrate stabilization approaches. A racial equity, culturally responsive, and trauma-informed lens informs the approach to stabilizing client systems in law enforcement settings. © 2023, IGI Global. All rights reserved.

Background In 2016, the Centers for Disease Control found that more than 1.5 million people develop sepsis each year and about 250,000 Americans die from it. Early identification and treatment of sepsis can decrease mortality and morbidity, yet studies have shown student nurses are not prepared to rescue deteriorating patients. Method The purpose of this pilot study was to create and test a response to rescue simulation for use with undergraduate nursing students. The simulation depicted a patient deteriorating from sepsis. The Martinez Sepsis Competency Evaluation Tool (MSCET) developed to rate student behaviors during the simulation. Promoting Excellence and Reflective Learning in Simulation (PEARLS) debriefing model was used post simulation. Results The overall content validity of the MSCET was 0.88. Each item that scored a I-CVI of 0.78 or less were revised. The total percentage of behaviors met was 68 %. The inter-rater reliability of the MSCET conciseness was 0.47 (X = 67.508, df = 48, p ≤ .05). Conclusion The results indicate the simulation based experience was effective in preparing students to care for patients with early signs of sepsis. Students were complimentary about the experience, and preliminary data on the MSCET psychometrics were positive. Limitations of the study and recommendations for further revision of the simulation were made.

Older adults with hearing loss have greater difficulty recognizing target speech in multi-talker environments than young adults with normal hearing, especially when target and masker speech streams are perceptually similar. A difference in fundamental frequency (f0) contour depth is an effective stream segregation cue for young adults with normal hearing. This study examined whether older adults with varying degrees of sensorineural hearing loss are able to utilize differences in target/masker f0 contour depth to improve speech recognition in multi-talker listening. Speech recognition thresholds (SRTs) were measured for speech mixtures composed of target/masker streams with flat, normal, and exaggerated speaking styles, in which f0 contour depth systematically varied. Computational modeling estimated differences in energetic masking across listening conditions. Young adults had lower SRTs than older adults; a result that was partially explained by differences in audibility predicted by the model. However, audibility differences did not explain why young adults experienced a benefit from mismatched target/masker f0 contour depth, while in most conditions, older adults did not. Reduced ability to use segregation cues (differences in target/masker f0 contour depth), and deficits grouping speech with variable f0 contours likely contribute to difficulties experienced by older adults in challenging acoustic environments.

Speech-in-speech recognition can be challenging, and listeners vary considerably in their ability to accomplish this complex auditory-cognitive task. Variability in performance can be related to intrinsic listener factors as well as stimulus factors associated with energetic and informational masking. The current experiments characterized the effects of short-term audibility of the target, differences in target and masker talker sex, and intrinsic listener variables on sentence recognition in two-talker speech and speech-shaped noise. Participants were young adults with normal hearing. Each condition included the adaptive measurement of speech reception thresholds, followed by testing at a fixed signal-to-noise ratio (SNR). Short-term audibility for each keyword was quantified using a computational glimpsing model for target+masker mixtures. Scores on a psychophysical task of auditory stream segregation predicted speech recognition, with stronger effects for speech-in-speech than speech-in-noise. Both speech-in-speech and speech-in-noise recognition depended on the proportion of audible glimpses available in the target+masker mixture, even across stimuli presented at the same global SNR. Short-term audibility requirements varied systematically across stimuli, providing an estimate of the greater informational masking for speech-in-speech than speech-in-noise recognition and quantifying informational masking for matched and mismatched talker sex.

Quantifying transgenerational effects of stress is important to predict outcomes of anthropogenic disturbances for wildlife species. Maternal stress can programme physiological and behavioural phenotypes in offspring, which may be maladaptive if maternal and offspring environments are mismatched. We investigated effects of a match and mismatch between egg cortisol and offspring stress levels in lake sturgeon, Acipenser fulvescens, using artificially elevated egg cortisol levels (simulating maternal stress) and a chronic unpredictable stress regime for offspring after hatch. Offspring cortisol levels were quantified at baseline and after an acute stressor. Multiple measures of offspring swimming activity were assessed in behaviour trials. Individuals that experienced elevated egg cortisol and high offspring stress exhibited a diminished cortisol response to an acute stressor, but responses varied among offspring from different families. Results suggest that the interaction between maternal and offspring experience may cue an offspring phenotype that is adaptive in high-stress conditions. Principal components analysis characterizing interindividual variation in offspring behavioural variables showed that treatment significantly affected multivariate offspring response along the PC1 axis (associated with inactivity), and both treatment and family significantly affected response along the PC2 axis (associated with shorter distance moved). The largest differences for PC1 occurred between the ‘mismatch’ treatments (high egg cortisol and low offspring stress exhibiting lower activity; low egg cortisol and high offspring stress exhibiting higher activity), indicating that the combination of egg cortisol and offspring stress is more important in determining offspring behaviour than is egg cortisol or offspring stress alone. Findings suggest that family effects, such as genetic components or maternal experience, may mediate how the interaction of maternal and offspring stress influences offspring physiological and behavioural outcomes, and indicate the need for further research into environmental factors experienced by females that influence how offspring respond to egg cortisol and early life stress.

Population control of invasive sea lamprey relies heavily on lampricide treatment of infested streams. The lampricide 3-trifluoromethyl-4-nitrophenol (TFM) is thought to impair mitochondrial ATP production through uncoupling oxidative phosphorylation. However, the effect of TFM on the entire electron transport chain (complexes I to V) in the mitochondria is not clear. In addition, TFM is reduced in phase I metabolism by sea lamprey at higher levels than in other fish species. The effects of these TFM reductive metabolites on mitochondria have not been explored. In this study, we sought to examine the effects of TFM and its reductive metabolite amino-TFM (TFMa) on cardiac mitochondrial oxygen consumption and membrane potential to delineate potential mechanisms for toxicity. To determine if molecules with similar structure also exhibit similar effects on mitochondria, we used 4-nitro-3-methylphenol (NMP) and its reductive metabolites 4-amino-3-methylphenol (NMPa) and 4-nitroso-3-methylphenol (NMPn) for comparisons. We found that mitochondrial bioenergetics was heavily affected with increasing concentrations of TFM, NMP, and NMPa when complexes I and II of the electron transport chain were examined, indicating that the toxic action of these compounds was exerted not only by uncoupling complex V, but also affecting complexes I and II.