Mountain gorillas are particularly inbred compared to other gorillas and even the most inbred human populations. As mountain gorilla skeletal material accumulated during the 1970s, researchers noted their pronounced facial asymmetry and hypothesized that it reflects a population-wide chewing side preference. However, asymmetry has also been linked to environmental and genetic stress in experimental models. Here, we examine facial asymmetry in 114 crania from three Gorilla subspecies using 3D geometric morphometrics. We measure fluctuating asymmetry (FA), defined as random deviations from perfect symmetry, and population-specific patterns of directional asymmetry (DA). Mountain gorillas, with a current population size of about 1000 individuals, have the highest degree of facial FA (explaining 17% of total facial shape variation), followed by Grauer gorillas (9%) and western lowland gorillas (6%), despite the latter experiencing the greatest ecological and dietary variability. DA, while significant in all three taxa, explains relatively less shape variation than FA does. Facial asymmetry correlates neither with tooth wear asymmetry nor increases with age in a mountain gorilla subsample, undermining the hypothesis that facial asymmetry is driven by chewing side preference. An examination of temporal trends shows that stress-induced developmental instability has increased over the last 100 years in these endangered apes.

Sociologists widely agree that poverty is the effect of structural factors; however, understanding the ways in which poverty is experienced and constructed with reference to culture remains a compelling area of scholarship. In a society where culture of poverty ideas retain popularity, attributing meanings and behavior to people in poverty is complicated and contentious. Many scholars adroitly navigate these waters, but we lack clear guidelines on how to examine the behavior and perceptions of people in poverty without misrepresenting and potentially stigmatizing research subjects. I argue that to avoid problems of overgeneralization and what I call “unacknowledged comparison,” we must engage with multiple points of observation and empirical comparisons. In addition, it makes sense to center sets of circumstances that affect behavior rather than generalizing the behavior or the culture that influences that behavior. Finally, I argue that the unit of analysis should be at the relational level rather than the individual level. The implications of failing to attend to these issues include continued misunderstanding of and unwarranted stigmatization of people in poverty.

Big Data combines information from diverse sources to create knowledge, make better predictions and tailor services. This article analyzes Big Data both as a technology and an industrial activity, and identifies the points of weakness and ethical concerns created by current business practices. Potential solutions for these concerns are proposed in order to build and maintain business practices respecting ethical standards as a prerequisite for a sustainable Big Data industry. This article covers both the usage of Big Data by industry and the development of a sustainable Big Data services industry.

This paper focuses on a mathematical background of an individual health status monitoring system to empower young people to manage their health. The proposed health status monitoring system uses symptoms observed with mobile sensing devices and prior information about health and environment (provided it exists) to define individual physical and psychological status. It assumes that a health status identification process is influenced by many parameters and conditions. It has a flexible logical inference system providing positive psychological influence on young people since full acceptance of recommendations on their behavioral changes towards healthy lifestyles is reached and a correct interpretation is guaranteed. The model and algorithms of the individual health status monitoring system are developed based on the composition inference rule in Zadeh's fuzzy logic. The model allows us to include in the algorithms of logical inference the possibility of masking (by means of a certain health condition) the symptoms of other health situations as well as prior information (if it exists) regarding health and environment. The algorithms are generated by optimizing the truth of a single natural “axiom”, which connects an individual health status (represented by classes of health situations) with symptoms and matrices of influence of health situations on symptoms and masking of symptoms. The new algorithms are fairly different from traditional algorithms, in which the result is produced in the course of numerous single processing rules. Therefore, the use of a composition inference rule makes a health status identification process faster and the obtained results more precise and efficient comparing to traditional algorithms.

This article describes ubiquitous sensing devices, enabled by wireless sensor network (WSN) technologies, now cut across every area of modern day living, affecting individuals and businesses and offering the ability to obtain and measure environmental indicators. Proliferation of these devices in a communicating-actuating network creates an Internet of Things (IoT). The IoT provides the tools to establish a major, global data-driven ecosystem that also enables Big Data techniques to be used. New business models may focus on the provision of services, i.e., the Internet of Services (IoS). These models assume the presence and development of the necessary IoT measurement and control instruments, communications infrastructure, and easy access to the data collected and information generated. Different business models may support opportunities to create revenue and value for various types of customers. This article contributes to the literature by considering, a first, knowledge-based management practices, business models, strategic implications and business opportunities for third-party data analysis services.

The paper recommends new methods to estimate effectively the probabilities of buffer overflow in high-speed communication networks. The frequency of buffer overflow in queuing system is very small; therefore the overflow is defined as rare event and can be estimated using rare event simulation with continuous-time Markov chains. First, a two-node queuing system is considered and the buffer overflow at the second node is studied. Two efficient rare event simulation algorithms, based on the Importance sampling and Cross-entropy methods, are developed and applied to accelerate the buffer overflow simulation with Markov chain modeling. Then, the buffer overflow in self-similar queuing system is studied and the simulations with long-range dependent self-similar traffic source models are conducted. A new efficient simulation algorithm, based on the RESTART method with limited relative error technique, is developed and applied to accelerate the buffer overflow simulation with SSM/M/1/B modeling using different parameters of arrival processes and different buffer sizes. Numerical examples and simulation results are provided for all methods to estimate the probabilities of buffer overflow, proposed in this paper.

Is mathematics taught in one country different from another one? How do concepts such as division, multiplication or facts like pi or mathematical conventions such PEMDAS/BODMAS compare from one country to another? True that mathematical content is the same regardless of the global location. The context and method used to present the concepts may vary from one place to another but the idea and notion stays the same. Aside from content, there are other learning found in mathematics classrooms that are not cognitive-oriented but very crucial and fundamental in preparing students to thrive as citizens of their nation and beyond. This presentation highlights the non-cognitive skill sets or soft skills, found in the US and in Kenyan math curricula—talk describes the attributes of the soft skills found in both countries as well as compares and contrasts these curricula. Presently, Kenya is on its fifth year of implementing competency-based curriculum where one of its main foci is on building capacity in communication and collaboration, self-efficacy, critical thinking and problem solving, creativity and imagination, citizenship, digital literacy, and learning to learn. The discussion explores how these seven non-content based core competencies look like in mathematics classrooms plus their implications in education. On the other hand, currently several US States have adapted the Common Core mathematics, which has two types of standards; that is, the mathematical content standards and standards for mathematical practice (SMP). The SMP are soft skills and core practices that Pre-K up to grade 12 students must be well versed in by the time they move to tertiary education. There are eight SMPs, which the presentation will focus on. The SMPs include: make sense of problems and persevere in solving them; reason abstractly and quantitatively; construct viable arguments and critique the reasoning of others; model with mathematics; use appropriate tools strategically; attend to precision; look for and make use of structure and look for and express regularity in repeated reasoning. The presentation shades light on these important soft skills, by making them more explicit. Note that the non-cognitive skillsets embedded in math classrooms carries more significant weight of learning; way much more than mere memorizing of procedural routine of finding an answer to a math problem. For instance, the aftermath of solving a math problem to its end to a solution set, is crucial since the ensuing attributes of endurance, determination and resiliency are examples of non-cognitive skill sets that will carry one outside the mathematics classroom, or in problem solving real life opportunities and challenges or in service to a country.

The Faculty Fellows (previously called Administrative Fellows) Program is a pilot program in Academic Affairs that addresses faculty leadership, institutional needs, and collaboration. It provides professional development opportunities for those who are considering administrative roles, by developing focused projects. The projects are addressing SUNY Oneonta’s mission critical goals in experiential learning, student engagement and retention, and inclusivity/diversity. The faculty fellows are an interdisciplinary team that strengthen the roles and offices of the academic deans and library director by integrating the academic schools/units. The 2021-2022 cohort includes Brendan Aucoin (Milne Library), Jacqueline (Bruscella) Bishop (Communication and Media), Leigh M. Fall (Earth and Atmospheric Sciences), and Maria Cristina Montoya (Foreign Languages and Literatures). Brendan is working on a series of projects related to highlighting SUNY Oneonta research and scholarship in the Milne Library. Among these are the development of the Library Special Researcher program for students and creating more opportunities to showcase faculty scholarship in the library. Jackie is working on a series of interrelated initiatives centered on experiential learning. Through cross-campus collaborations. Jackie's project seeks to a) increase access to on-campus and local internship opportunities, b) improve student, faculty, and site-supervisor understanding and use of Handshake, and c) strengthen career readiness programming for students, particularly those studying in the liberal arts. Leigh is working on two projects for the School of Sciences. One project is researching mechanisms of how interdisciplinary and multidisciplinary courses and research happens within the school, highlighting potential barriers and opportunities. The other project is researching past and current STEM experiential learning opportunities to help faculty provide productive experiences for students. MC is working on three projects: first the internationalization of the School of EHESS, including a focus on Collaborative Online International Learning (COIL) as a platform; second, developing the curricula and partnerships for the Bilingual Education graduate program; third, diverse faculty retention.

This presentation will describe SUNY Oneonta’s PRODiG program, demonstrate program success, and spotlight PRODiG faculty. The purpose of PRODiG is to increase the representation of historically underrepresented faculty at SUNY, including underrepresented minority (URM) faculty and women faculty of all races in science, technology, engineering, and mathematics fields (WSTEM). PRODiG is envisioned as part of our broader campus diversity and inclusion initiatives. In our second year of participation, SUNY Oneonta formalized a strong working committee, the PRODiG Steering Committee, with the charge to move forward action items toward our goals to: increase representation of URM/WSTEM faculty through hiring and retention; enhance the pipeline of URM/WSTEM students pursuing and entering graduate school and URM/WSTEM graduates to academic careers; and improve the campus climate for diversity, equity, and inclusion. To date, SUNY has approved four PRODIG Faculty at SUNY Oneonta: Cohort I (2019-2020) - Dr. Angela Migues, Chemistry & Biochemistry, and Dr. Elio Santos, Psychology; Cohort II (2020-2021) - Dr. Kimberly Cossey, Chemistry & Biochemistry, and Dr. Valerie Rapson, Physics & Astronomy; and one PRODiG Pre/Post-Doctoral Fellow - Dr. Casey Coomes, Biology. In addition to Co-Chairs Tracy Allen and Bernadette Tiapo, members of the PRODiG Steering Committee include Kelly Gallagher (Chemistry & Biochemistry), Tracy Hartwell (Human Resources), Shahin Kachwala (Women’s & Gender Studies), Kathy Meeker (Grants Development Office), Diana Moller (College Assistance Migrant Program), Joshua Nelson (Institutional Assessment), Rhea Nowak (Faculty Center), Andrew Stammel (Student Development), and Napoleon Tipao (Academic Affairs).

Self-censorship, mistrust, loss of morale, resentment, isolation, burnout, headaches, hair loss, sleep problems, eating disorders, stomach ulcers, coronary heart disease, chronic health conditions, panic attacks, anxiety, clinical depression, PDSD, suicidal ideation. These are not things one hopes for when earning a living; however, they can be just a few of the very real consequences of workplace psychological abuse. Despite the plethora of documented evidence of the long-lasting damage done to targets, witnesses, and organizations, workplace psychological abuse, in any of its manifestations, is prevalent and pervasive in many workplaces, including on college campuses. Since its launch on September 27, 2021, the library guide Resources on Bullying, Mobbing, and Other Forms of Workplace Psychological Violence has received 196 views, indicating that the topic is of considerable interest on this campus. The guide and my presentation are inspired by an extensive literature review, my own personal experiences with mobbing, a desire to help others, and a strong determination to encourage awareness in everyone.