Affirmative Immunity: A Litigation-Based Approach to Curb Appellate Courts’ Raising Qualified Immunity Sua Sponte

Qualified immunity, to put it simply, provides public officials with immunity from civil lawsuits if they have violated an individual’s constitutional rights under their official authority and those rights were not “clearly established” at the time of the official’s actions. The doctrine has evolved into an elaborate framework that has plagued civil rights plaintiffs, as well as courts, for decades. Qualified immunity is an affirmative defense, and affirmative defenses are waived if not raised appropriately by the defendant. Moreover, issues that are not properly raised before the trial court, including affirmative defenses, are generally not considered for the first time on appeal. Nevertheless, courts have a long history of defying this general rule, and qualified immunity is no exception. This Note examines the historical development of and rationales for the qualified immunity doctrine, the purposes of affirmative defenses, and the reasons for the general rule that appellate courts do not consider issues for the first time on appeal. Additionally, this Note summarizes an inconsistent trend among appellate courts, some of which raise qualified immunity sua sponte, while others hold that qualified immunity is waived if not raised at the trial court appropriately. After recognizing that the original goal of qualified immunity was to prevent public officials from enduring the burdens of litigation and that appellate courts generally have discretion to consider issues for the first time on appeal, this Note proposes a two-part solution to balance these values. This Note’s proposed framework returns qualified immunity to its original purpose and resolves the current inconsistency among appellate courts, while allowing appellate courts to raise issues for the first time on appeal when they consider it appropriate. The framework also prevents appellate courts from raising qualified immunity sua sponte inappropriately, which can unduly burden civil rights plaintiffs and make it harder for them to recover damages if their constitutional rights have been violated

EMG-Controlled Prosthetic Hand with Fuzzy Logic Classification Algorithm

In recent years, researchers have conducted many studies on the design and control of prosthesis devices that take the place of a missing limb. Functional ability of prosthesis hands that mimic biological hand functions increases depending on the number of independent finger movements possible. From this perspective, in this study, six different finger movements were given to a prosthesis hand via bioelectrical signals, and the functionality of the prosthesis hand was increased. Bioelectrical signals were recorded by surface electromyography for four muscles with the help of surface electrodes. The recorded bioelectrical signals were subjected to a series of preprocessing and feature extraction processes. In order to create meaningful patterns of motion and an effective cognitive interaction network between the human and the prosthetic hand, fuzzy logic classification algorithms were developed. A five-fingered and 15-jointed prosthetic hand was designed via SolidWorks, and a prosthetic prototype was produced by a 3D printer. In addition, prosthetic hand simulator was designed in Matlab/SimMechanics. Pattern control of both the simulator and the prototype hand in real time was achieved. Position control of motors connected to each joint of the prosthetic hand was provided by a PID controller. Thus, an effective cognitive communication network established between the user, and the real-time pattern control of the prosthesis was provided by bioelectrical signals

The non-minimally coupled symmetric teleparallel gravity with electromagnetic field

We construct a symmetric teleparallel gravity model which is non-minimally coupled with electromagnetic field in four dimensions inspired by its Riemannian equivalent. We derive the field equations by taking the variation of this model, which is written here for the first time. Then, we find some classes of spherically symmetric static solutions by the coincident gauge of symmetric teleparallel spacetime.Comment: 16 page

‘Defeat, Victory, Repeat’: Russian Émigrés between the Spanish Civil War and Operation Barbarossa, 1936–1944

Tens of thousands of White Russians were forced to leave their country after 1920. Many of them were career officers and soldiers imbued with anti-communism, who were then hired by diverse armies. They acted as transnational soldiers of the counter-revolution during the interwar period. This article analyses the trajectory of some dozens of them, who volunteered for the Francoist army in 1936–8 during the Spanish Civil War. Afterwards, many of them joined the ranks of the Spanish ‘Blue Division’ as interpreters to take part in the invasion of their home country by the Germans. Their experience as occupiers was highly ambiguous and oscillated between disappointment and nostalgia once they perceived that the objective of the invasion was not to liberate Russia from communism, but to enslave the country and its inhabitants. However, once they returned to Spain, they cultivated a hero myth of their past experience and regarded themselves as winnersS

Comparison Analysis of Machine Learning Algorithms for Steel Plate Fault Detection

Metals are one of the most important building materials of modern times. Especially the production and metalworking process of flat metal sheets is very sensitive. Control of the manufacturing process affects not only the intermediate products but also the quality of final products. Early detection of defects on steel plate surfaces is an important task in industrial production. Process control and mistake detection have traditionally been done manually by experts. However, this method is not proper in terms of both time and cost. With the industrial revolution IR 4.0, machine learning (ML) techniques have been developed to solve fault detection problems in products. This study focuses on developing basic machine learning methods for the detection of six different error classes that may occur during production on steel surfaces. Five standard ML models: LD, KNN, DT, SVM, RF, and deep learning (DNN) model: one-dimensional DNN was developed for the classification problem. The UCI steel plate deformation data set was used as the experimental data set. Five performance criteria: Accuracy, Sensitivity, Specificity, Precision, and F1 value were used to determine the success of the methods. The success rates of LD, KNN, DT, SVM, RF and DNN classification methods were 90.136%, 91.7880%, 93.013%, 93.287%, 95.479%, 96.986%, respectively. The results show the significant impact of the machine learning approach on the steel plate fault diagnosis problem

Lunch: College of Arts and Sciences 50th Anniversary: Celebrating Liberal Arts and Sciences

Lunch and Opening Remarks: A Historical Perspective on Liberal Arts at NEIU by Dean Katrina Bell-Jordan, Dean of College of Arts and Sciences and Sandra Beyda, Dean of Graduate College of Education. Presentation: LIBERAL ARTS EDUCATION: ITS CONTINUING IMPORTANCE, by Cris Tofollo, Justice Studies and International Progra

Teachers’ views on the use of geometric patterns in Turkish architectural works in geometry instruction

Bu çalışmada, Türk mimari eserlerindeki geometrik desenlerin geometri öğretiminde kullanılabilirliğine yönelik ortaokul matematik öğretmenlerinin görüşlerini ortaya koymak amaçlanmıştır. Tarama modeli ile gerçekleştirilen çalışma 62 ortaokul matematik öğretmeni ile yürütülmüştür. Çalışmanın verileri araştırmacılar tarafından hazırlanan görüş formu aracılığıyla toplanmıştır. Bu form demografik özellikler, desenlerin ortaokul geometri kazanımları ile ilişkilendirilmesi ve bu desenlerin geometri öğretiminde kullanılabilirliği olmak üzere 3 bölümü içeren sorulardan oluşmuştur. Elde edilen veriler içerik analizi yapılarak incelenmiştir. Araştırmanın sonucunda, öğretmenlerin Türk mimari eserlerinde kullanılan beş farklı deseni ortaokul geometri kazanımları ile yüksek oranda ilişkilendirdikleri saptanmıştır. Bu desenlerin geometri öğretiminde kullanılmasının duyuşsal, bilişsel, farkındalık ve günlük hayata ilişkin olumlu etki edebileceği yönünde bildirilen görüşlerin yanında örnek seçimi, bireysel farklılıklar, zaman, maddiyat gibi olası güçlüklere de dikkat çekildiği görülmüştür.The aim of this study was to reveal the middle school mathematics teachers’ views about the use of geometric patterns in Turkish architectural works in geometry instruction. This research was carried out with the general survey model, including 62 middle school mathematics teachers. The data were collected by an interview form, prepared by the researchers. The form consisted of three parts, including demographic characteristics, the association of geometric patterns in architectural works with related learning outcomes and views about the use of geometric patterns in geometry instruction. The data were analyzed with content analysis. As a result of the research, it was found that the teachers highly associated five different patterns with middle school geometry learning outcomes. Also, they stated that the use of the patterns in geometry instruction could have positive effects on awareness, daily life, affective and cognitive variables. However, it was seen that they drew attention to the possible difficulties regarding the use of the patterns such as sample selection, the readiness of students, individual differences, finance and time