Macabre ceremonies: How Los Zetas produces extreme violence to promote organizational cohesion

Why do some organized crime groups (OCGs) carry out face-to-face killings where perpetrators debase their victims and defile their bodies? Leading criminologists contend that OCGs carry out extreme killings deliberately to attain specific performance objectives. Conversely, psycho-sociological scholars argue that extreme killings only occur in situations that affect perpetrators’ reasoning and emotions. In their view, these situations are largely beyond OCGs’ control. I argue that analyzing extreme killings as organizational rituals can contribute to reconciling these seemingly conflicting views. More specifically, I contend that the OCG known as Los Zetas ritualizes executions to generate the conditions that make extreme violence possible. Through ritualization, Los Zetas influences executioners’ perceptions of extreme behavior from something abhorrent into something valued, desirable, and enjoyable. Once the conditions conducive to extreme violence emerge, Los Zetas exploits it to attain utilitarian objectives.

Why True Believers Make the Ultimate Sacrifice: Sacred Values, Moral Convictions, or Identity Fusion?

Recent research has identified three promising candidates for predicting extreme behavior: sacred values, moral convictions, and identity fusion. Each construct is thought to motivate extreme behavior in unique ways: Sacred values trigger extreme actions when people are asked to compromise cause-related values for personal gain; moral convictions trigger extreme actions when a cause is aligned with one’s moral compass; and identity fusion triggers extreme actions when a cause is inextricably associated (“fused”) with the personal self. In six studies, we asked which of the three constructs (either alone or in combination) was most predictive of sacrifice for a cause. We measured all three constructs with respect to either of two causes: gun rights (Studies 1–3) or abortion rights (4–6). The outcome measure was endorsement of fighting and dying for the cause. Although all three constructs were significant predictors of the outcome measure when considered separately, identity fusion consistently emerged as the strongest predictor of endorsement of self-sacrifice when all three were considered simultaneously. This pattern occurred regardless of the target cause (gun or abortion rights), the participant’s position on the cause (i.e., pro-gun or anti-gun, pro-choice, or pro-life), or nationality (American vs. Spanish). Also, there was no evidence that the predictors interacted to predict the outcome measure. Finally, a manipulation that threatened the validity of the personal self strengthened the relationship between endorsement of self-sacrifice and both (a) identity fusion and (b) moral convictions. The latter finding suggests that threats to the validity of one’s self-views may amplify the extreme behaviors of true believers.

Extremophilic Prokaryotic Endoxylanases: Diversity, Applicability, and Molecular Insights

Extremophilic endoxylanases grabbed attention in recent years due to their applicability under harsh conditions of several industrial processes. Thermophilic, alkaliphilic, and acidophilic endoxylanases found their employability in bio-bleaching of paper pulp, bioconversion of lignocellulosic biomass into xylooligosaccharides, bioethanol production, and improving the nutritious value of bread and other bakery products. Xylanases obtained from extremophilic bacteria and archaea are considered better than fungal sources for several reasons. For example, enzymatic activity under broad pH and temperature range, low molecular weight, cellulase-free activity, and longer stability under extreme conditions of prokaryotic derived xylanases make them a good choice. In addition, a short life span, easy cultivation/harvesting methods, higher yield, and rapid DNA manipulations of bacterial and archaeal cells further reduces the overall cost of the product. This review focuses on the diversity of prokaryotic endoxylanases, their characteristics, and their functional attributes. Besides, the molecular mechanisms of their extreme behavior have also been presented here.

Dynamic Panel Data Modeling and Surveillance of COVID-19 in Metropolitan Areas in the United States: Longitudinal Trend Analysis

Background The COVID-19 pandemic has had profound and differential impacts on metropolitan areas across the United States and around the world. Within the United States, metropolitan areas that were hit earliest with the pandemic and reacted with scientifically based health policy were able to contain the virus by late spring. For other areas that kept businesses open, the first wave in the United States hit in mid-summer. As the weather turns colder, universities resume classes, and people tire of lockdowns, a second wave is ascending in both metropolitan and rural areas. It becomes more obvious that additional SARS-CoV-2 surveillance is needed at the local level to track recent shifts in the pandemic, rates of increase, and persistence. Objective The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk and persistence, and weekly shifts, to better understand and manage risk in metropolitan areas. Existing surveillance measures coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until, and after, an effective vaccine is developed. Here, we provide values for novel indicators to measure COVID-19 transmission at the metropolitan area level. Methods Using a longitudinal trend analysis study design, we extracted 260 days of COVID-19 data from public health registries. We used an empirical difference equation to measure the daily number of cases in the 25 largest US metropolitan areas as a function of the prior number of cases and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results Minneapolis and Chicago have the greatest average number of daily new positive results per standardized 100,000 population (which we refer to as speed). Extreme behavior in Minneapolis showed an increase in speed from 17 to 30 (67%) in 1 week. The jerk and acceleration calculated for these areas also showed extreme behavior. The dynamic panel data model shows that Minneapolis, Chicago, and Detroit have the largest persistence effects, meaning that new cases pertaining to a specific week are statistically attributable to new cases from the prior week. Conclusions Three of the metropolitan areas with historically early and harsh winters have the highest persistence effects out of the top 25 most populous metropolitan areas in the United States at the beginning of their cold weather season. With these persistence effects, and with indoor activities becoming more popular as the weather gets colder, stringent COVID-19 regulations will be more important than ever to flatten the second wave of the pandemic. As colder weather grips more of the nation, southern metropolitan areas may also see large spikes in the number of cases.

Middle School Discipline Practices

This chapter discusses the challenges middle schools face when dealing with extreme behavior issues and provides real-world examples of one administrator's experience in the face of these situations. Looking at the newest trends in discipline strategies, including those of social-emotional learning and restorative practices, the authors provide an overview of their school-wide implementation. The authors also provide recommendations for educators who are facing similar situations and how to develop practices that support lasting cultural changes within schools and districts.

Homoclinic breather waves, rouge waves and multi-soliton waves for a (2+1)-dimensional Mel’nikov equation

Purpose The purpose of this paper is to study the homoclinic breather waves, rogue waves and multi-soliton waves of the (2 + 1)-dimensional Mel’nikov equation, which describes an interaction of long waves with short wave packets. Design/methodology/approach The author applies the Hirota’s bilinear method, extended homoclinic test approach and parameter limit method to construct the homoclinic breather waves and rogue waves of the (2 + 1)-dimensional Mel’nikov equation. Moreover, multi-soliton waves are constructed by using the three-wave method. Findings The results imply that the (2 + 1)-dimensional Mel’nikov equation has breather waves, rogue waves and multi-soliton waves. Moreover, the dynamic properties of such solutions are displayed vividly by figures. Research limitations/implications This paper presents efficient methods to find breather waves, rogue waves and multi-soliton waves for nonlinear evolution equations. Originality/value The outcome suggests that the extreme behavior of the homoclinic breather waves yields the rogue waves. Moreover, the multi-soliton waves are constructed, including the new breather two-solitary and two-soliton solutions. Meanwhile, the dynamics of these solutions will greatly enrich the diversity of the dynamics of the (2 + 1)-dimensional Mel’nikov equation.

Dynamic Panel Data Modeling and Surveillance of COVID-19 in U.S. Metropolitan Areas (Preprint)

BACKGROUND The COVID-19 pandemic has had profound and differential impacts on metropolitan areas across the United States and around the world. Within the United States, metropolitan areas that were hit earliest with the pandemic and reacted with scientifically based health policy were able to contain the virus by late Spring. For other areas that kept businesses open the ‘first wave’ in the US hit in mid-summer. As the weather turns colder, Universities resume classes, and people tire of lockdowns, a second wave is ascending in both metropolitan and rural areas. It becomes more obvious that additional SARS-CoV-2 surveillance is needed at the local level to track recent shifts in the pandemic, rates of increase, and persistence. OBJECTIVE The goal of this study is to provide advanced surveillance metrics for COVID-19 transmission that account for speed, acceleration, jerk and persistence, and weekly shifts, to better understand and manage risk at the metropolitan area scale. Existing surveillance measures coupled with our dynamic metrics of transmission will inform health policy to control the COVID-19 pandemic until, and after, an effective vaccine is developed. Here, we provide metropolitan area values for novel indicators to measure the transmission of disease. METHODS Using a longitudinal trend analysis study design, we extracted 260 days of COVID data from public health registries. We use an empirical difference equation to measure the daily number of cases in the 25 largest U.S. metropolitan areas as a function of the prior number of cases and weekly shift variables based on a dynamic panel data model that was estimated using the generalized method of moments (GMM) approach by implementing the Arellano-Bond estimator in R. RESULTS Most recently, Minneapolis and Chicago have the greatest average number of daily new positive results per standardized 100,000 population, which we call speed. Extreme behavior in Minneapolis showed speed jumping from 17 to 30 (67%) in one week. The jerk and acceleration calculated for these areas also showed extreme behavior. The Dynamic Panel Data Model shows that Minneapolis, Chicago, and Detroit have the largest persistence effects, meaning that new cases one week are statistically attributable to new cases from the prior week. CONCLUSIONS Three of the metropolitan areas with historically early and harsh winters have the highest persistence effects out of the top 25 most populous metropolitan areas in the US at the beginning of their cold weather season. With these persistence effects, and indoor activities becoming more popular as weather gets colder, stringent COVID-19 regulations will be more important than ever to flatten the second wave of the pandemic. As colder weather grips more of the nation, southern metropolitan areas may also see large spikes in the number of cases.

EXTREMISM AS A THREAT TO NATIONAL SECURITY

В статье рассматривается феномен экстремизма на территории постсоветского пространства, а также социально-психологический облик группы людей, склонной к проявлению элементов экстремального поведения. The article examines the phenomenon of extremism on the territory of the former Soviet Union, as well as the socio-psychological appearance of a group of people who are prone to displaying elements of extreme behavior.