Role confusion in rural schools

Resource teachers must examine their role conceptions

What Every Teacher Education Professor Needs to Know About Differentiated Instruction

Even though differentiated instruction is considered best practice for addressing student diversity, preservice teachers may not be receiving the training they need to plan differentiated lessons and utilize a wide variety of teaching strategies. Teacher education programs are not effective in inculcating the principles of differentiated instruction. because preservice teachers do not observe, experience or implement differentiated instruction in the preservice courses or their practicum experiences. MSU-Billings faculty are addressing differentiated instruction in their own teaching to test the premise that modeling differentiation may be a more effective way of assisting preservice teachers to understand and implement differentiation in their own teaching

Comparison of laboratory and immediate diagnosis of coagulation for patients under oral anticoagulation therapy before dental surgery

BACKGROUND: Dental surgery can be carried out on patients under oral anticoagulation therapy by using haemostyptic measures. The aim of the study was a comparative analysis of coagulation by laboratory methods and immediate patient diagnosis on the day of the planned procedure. METHODS: On the planned day of treatment, diagnoses were carried out on 298 patients for Prothrombin Time (PT), the International Normalised Ratio (INR), and Partial Thromboplastin Time (PTT). The decision to proceed with treatment was made with an INR < 4.0 according to laboratory results. RESULTS: Planned treatment did not go ahead in 2.7% of cases. Postoperatively, 14.8% resulted in secondary bleeding, but were able to be treated as out-patients. 1.7% had to be treated as in-patients. The average error between the immediate diagnosis and the laboratory method: 95% confidence interval was -5.8 ± 15.2% for PT, -2.7 ± 17.9 s for PTT and 0.23 ± 0.80 for INR. The limits for concordance were 9.4 and -21.1% for PT, 15.2 and -20.5 s for PTT, and 1.03 and -0.57 for INR. CONCLUSION: This study showed a clinically acceptable concordance between laboratory and immediate diagnosis for INR. Concordance for PT and PTT did not meet clinical requirements. For patients under oral anticoagulation therapy, patient INR diagnosis enabled optimisation of the treatment procedure when planning dental surgery

Optimierte Ladung von Elektrofahrzeugen als Markow Entscheidungsprozess mittels maschineller Lernalgorithmen

Die Elektromobilität mit teils hohen Ladeleistungen ist für den sicheren Betrieb der elektrischen Verteilnetze zukünftig eine Herausforderung. Zur Reduzierung von Überlastungen in der Niederspannung werden daher Steueralgorithmen benötigt, um die Ladeleistung der Fahrzeuge zu steuern. Hierbei ergibt sich allerdings das Problem, dass die Niederspannungsnetze in der Regel messtechnisch nicht überwacht werden und so Eingangsdaten für Steueralgorithmen fehlen. In der Arbeit wird die Kombination von zwei maschinellen Lernalgorithmen untersucht. Die Steuerung der Ladeleistung von Elektrofahrzeugen ist als Markow-Entscheidungsprozess definiert, der mittels dem bestärkten Lernen gelöst wird. Für die Bereitstellung der Eingangsdaten wird ein künstliches neuronales Netz verwendet, das den Zustand eines Niederspannungsnetzes abschätzt. Durch das Zusammenspiel beider Algorithmen können die durch die Ladung von Elektrofahrzeugen ausgelösten Netzüberlastungen reduziert werden.The expansion of renewable energies and the charging of electric vehicles, in some cases with high power, pose a new challenge for the safe operation of electrical distribution grids in the future and, in some cases, today. Therefore, algorithms for controlling the charging power of electric vehicles are needed to prevent and reduce low-voltage equipment overloads. However, when implementing a control algorithm for the charging power of electric vehicles, the fact that low-voltage grids are not typically monitored by measurement technology, due to historical reasons, presents a problem. Therefore, it is necessary to be able to precisely estimate the condition of the low-voltage grid. This thesis presents an autonomous control of the charging power of distributed private electric vehicles to prevent and reduce equipment overloads in the low-voltage grid while maintaining a short charging time. This control utilizes a Markov decision process. Machine learning algorithms were used to solve the Markov decision process and generate its state. An artificial neural network was used to estimate the node voltage in real time and as a state for the Markov decision process. To solve the Markov decision process, reinforcement learning in a decentralized approach as a multiagent system was used as a machine learning algorithm. Each charging point was assigned a so-called agent that, using a defined reward function and action vector for controlling the charging power of the respective charging point, attempted to achieve the optimal balance between reducing equipment overload in the low-voltage grid and minimizing the charging time of electric vehicles. The estimation of node voltage and the autonomous decentralized control of electric vehicles using machine learning algorithms were validated and analyzed in three different scenarios of a grid model. This thesis investigates how the estimation of the node voltage as a state of the Markov decision process, which is subject to inaccuracies, affects the efficacy of the autonomous control. It also explores whether increasing the percentage of electric vehicles without expanding primary resources using the system of linear learning algorithms described is possible

A Strategy for Eliciting Antibodies against Cryptic, Conserved, Conformationally Dependent Epitopes of HIV Envelope Glycoprotein

Novel strategies are needed for the elicitation of broadly neutralizing antibodies to the HIV envelope glycoprotein, gp120. Experimental evidence suggests that combinations of antibodies that are broadly neutralizing in vitro may protect against challenge with HIV in nonhuman primates, and a small number of these antibodies have been selected by repertoire sampling of B cells and by the fractionation of antiserum from some patients with prolonged disease. Yet no additional strategies for identifying conserved epitopes, eliciting antibodies to these epitopes, and determining whether these epitopes are accessible to antibodies have been successful to date. The defining of additional conserved, accessible epitopes against which one can elicit antibodies will increase the probability that some may be the targets of broadly neutralizing antibodies.We postulate that additional cryptic epitopes of gp120 are present, against which neutralizing antibodies might be elicited even though these antibodies are not elicited by gp120, and that many of these epitopes may be accessible to antibodies should they be formed. We demonstrate a strategy for eliciting antibodies in mice against selected cryptic, conformationally dependent conserved epitopes of gp120 by immunizing with multiple identical copies of covalently linked peptides (MCPs). This has been achieved with MCPs representing 3 different domains of gp120. We show that some cryptic epitopes on gp120 are accessible to the elicited antibodies, and some epitopes in the CD4 binding region are not accessible. The antibodies bind to gp120 with relatively high affinity, and bind to oligomeric gp120 on the surface of infected cells.Immunization with MCPs comprised of selected peptides of HIV gp120 is able to elicit antibodies against conserved, conformationally dependent epitopes of gp120 that are not immunogenic when presented as gp120. Some of these cryptic epitopes are accessible to the elicited antibodies

Hierarchical orbital decompositions and extended decomposable distributions

Elliptically contoured distributions can be considered to be the distributions for which the contours of the density functions are proportional ellipsoids. Kamiya, Takemura and Kuriki (2006) generalized the elliptically contoured distributions to star-shaped distributions, for which the contours are allowed to be arbitrary proportional star-shaped sets. This was achieved by considering the so-called orbital decomposition of the sample space in the general framework of group invariance. In the present paper, we extend their results by conducting the orbital decompositions in steps and obtaining a further, hierarchical decomposition of the sample space. This allows us to construct probability models and distributions with further independence structures. The general results are applied to the star-shaped distributions with a certain symmetric structure, the distributions related to the two-sample Wishart problem and the distributions of preference rankings

Stochastic ordering of bivariate elliptical distributions

It is shown that for elliptically distributed bivariate random vectors, the riskiness and dependence strength of random portfolios, in the sense of the univariate convex and bivariate concordance stochastic orders respectively, can be simply characterised in terms of the vector's Σ-matrix

Letter from the American Labor Party, 13th Assembly District

Typed letter encouraging recipient to vote in the August 11, 1942 election. Additional signees: Blanche Lee; Florence Dillon. Student Publications: The Campus Newspaper Collectio

Structural and biophysical characterization of bacillus thuringiensis insecticidal proteins Cry34Ab1 and Cry35Ab1

Bacillus thuringiensis strains are well known for the production of insecticidal proteins upon sporulation and these proteins are deposited in parasporal crystalline inclusions. The majority of these insect-specific toxins exhibit three domains in the mature toxin sequence. However, other Cry toxins are structurally and evolutionarily unrelated to this three-domain family and little is known of their three dimensional structures, limiting our understanding of their mechanisms of action and our ability to engineer the proteins to enhance their function. Among the non-three domain Cry toxins, the Cry34Ab1 and Cry35Ab1 proteins from B. thuringiensis strain PS149B1 are required to act together to produce toxicity to the western corn rootworm (WCR) Diabrotica virgifera virgifera Le Conte via a pore forming mechanism of action. Cry34Ab1 is a protein of ∼14 kDa with features of the aegerolysin family (Pfam06355) of proteins that have known membrane disrupting activity, while Cry35Ab1 is a ∼44 kDa member of the toxin_10 family (Pfam05431) that includes other insecticidal proteins such as the binary toxin BinA/BinB. The Cry34Ab1/Cry35Ab1 proteins represent an important seed trait technology having been developed as insect resistance traits in commercialized corn hybrids for control of WCR. The structures of Cry34Ab1 and Cry35Ab1 have been elucidated to 2.15 Å and 1.80 Å resolution, respectively. The solution structures of the toxins were further studied by small angle X-ray scattering and native electrospray ion mobility mass spectrometry. We present here the first published structure from the aegerolysin protein domain family and the structural comparisons of Cry34Ab1 and Cry35Ab1 with other pore forming toxins