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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.

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.

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.

The relationships between pheromone stimuli and neuropeptides are not well established in vertebrates due to the limited number of unequivocally identified pheromone molecules. The sea lamprey (Petromyzon marinus) is an advantageous vertebrate model to study the effects of pheromone exposure on neuropeptides since many pheromone molecules and neuropeptides have been identified in this species. Sexually mature male sea lamprey release pheromones 7α, 12α, 24-trihydroxy-5α-cholan-3-one 24-sulfate (3 keto-petromyzonol sulfate, 3kPZS) and 7α, 12α-dihydroxy-5α-cholan-3-one-24-oic acid (3-keto allocholic acid, 3kACA) that differentially regulate gonadotropin-releasing hormone (lGnRH) and steroid levels in sexually immature sea lamprey. However, the effects of these pheromones on gonadotropin-inhibitory hormones (GnIHs), hypothalamic neuropeptides that regulate lGnRH release, are still elusive. In this report, we sought to examine the effects of waterborne pheromones on lamprey GnIH-related neuropeptide levels in sexually immature sea lamprey. Ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) analyses revealed sex differences in GnIH-related neuropeptide levels in the brain and plasma of immature sea lamprey. Exposure to 3kPZS and 3kACA exerted differential effects on GnIH-related neuropeptide levels in both sexes, but the effects were more prominent in female brains. We conclude that sea lamprey pheromones regulate GnIH-related neuropeptide levels in a sexually dimorphic manner.

Use of the first fish pheromone biopesticide, 3-keto petromyzonol sulfate (3kPZS) in sea lamprey (Petromyzon marinus) control requires an understanding of both how the amount 3kPZS applied to a trap relates to catch, and how that relationship varies among stream types. By conducting 3kPZS dose-response experiments over two years and across six varied trapping contexts, we conclude (1) that 3kPZS application is best standardized by how much is emitted from the trap instead of the fully mixed concentration achieved downstream, and (2) that 3kPZS is more effective in wide streams (>30 m). In wide streams, emission of 3kPZS at 50 mg hr.−1 from the trap increased capture rate by 10–15% as sea lamprey were 25–50% more likely to enter the trap after encounter. However, in narrow streams (< 15 m), 50 mg hr.−1 3kPZS generally reduced probabilities of upstream movement, trap encounter, and entrance. While 3kPZS significantly influenced upstream movement, encounter, and capture probabilities, these behaviors were also highly influenced by water temperature, stream width, sea lamprey length, and sex. This study highlights that a pheromone component in a stream environment does not ubiquitously increase trap catch in all contexts, but that where, how, and when the pheromone is applied has major impacts on whether it benefits or hinders trapping efforts.

Sexual signals evolve via selective pressures arising from male–male competition and female choice, including those originating from unintended receivers that detect the signal. For example, males can acquire information from other males signaling to females and alter their own signal. Relative to visual and acoustic signals, less is known about how such communication networks influence chemical signaling among animals. In sea lamprey (Petromyzon marinus), the chemical communication system is essential for reproduction, offering a useful system to study a pheromone communication network that includes signalers and both intended and unintended receivers. Male sea lamprey aggregate on spawning grounds, where individuals build nests and signal to females using sex pheromones. We examined how exposure to a major component of the male pheromone, 3keto-petromyzonol sulfate (3kPZS), influenced male pheromone signaling, and whether females had a preference for males that altered their signal. Exposure to 3kPZS, at a concentration of 5×10−10 mol l−1, simulated the presence of other male(s) and led to increased 3kPZS release rates within 10 min, followed by a return to baseline levels within 30 min. Exposure also led to increases in hepatic synthesis and circulatory transport of pheromone components. In behavioral assays, females preferred the odor of males that had been exposed to 3kPZS; therefore, males likely benefit from upregulating 3kPZS release after detecting competition for mates. Here, we define how a specific pheromone component influences chemical signaling during intrasexual competition, and show a rare example of how changes in chemical signaling strategies resulting from male competition may influence mate choice.

As companies continue to put data and business analytics as their top priority, universities will need to supply students with the appropriate skill sets that meet this demand and offer future opportunities to their graduates. Although business analytics is a new field, many of the required competencies stem from already established areas such as Information/Computer Technology or Information Systems. Using a sample of 225 randomly selected AACSB accredited business schools this study examined the new developments in Business Analytics undergraduate academic programs, and determined the amount of overlap between the Business Analytics and the Information/Computer Technology degree programs. Our findings reveal that approximately 36 percent of the Business Analytics programs overlap with the Information/Computer Technology programs. In addition, the top three required courses in most Business Analytics programs include a Database course, predictive analytics course, and Introduction to Business Analytics. This research provides valuable insight for schools that haven't adopted a Business Analytics degree yet or are looking to improve their existing curriculum. In addition, colleges and universities can now utilize the appropriate Information Systems courses and include them as important foundation and part of their Business Analytics programs.

Southern Connecticut State University conducted its first year of excavations at the Henry Whitfield State Museum in Guilford, Connecticut in July, 2018. This research was a continuation of nearly fifty years of intermittent archaeological research at the Whitfield Museum property. The 2018 field season was spent exploring a previously uninvestigated locus. While we did find some evidence of 17th, 18th, and 19th century activities at this locus, the most exciting finds were related to the neocolonial revival of the museum property in the first half of the 20th century. In addition to a general report on findings from the 2018 excavations, we explore the historical context of the Whitfield House in the late 19th and early 20th centuries, especially its perceived emblematic association with colonial English descendant communities in light of the period’s social anxieties about immigration, shifting racial dynamics, and economic and religious change.