The Voltage Sensor of Excitation-Contraction Coupling in Skeletal Muscle. Ion Dependence and Selectivity

Manifestations of excitation-contraction (EC) coupling of skeletal muscle were studied in the presence of metal ions of the alkaline and alkaline-earth groups in the extracellular medium. Single cut fibers of frog skeletal muscle were voltage clamped in a double Vaseline gap apparatus, and intramembrane charge movement and myoplasmic Ca2+ transients were simultaneously measured. In metal-free extracellular media both charge movement of the charge 1 type and Ca transients were suppressed. Under metal-free conditions the nonlinear charge distribution was the same in depolarized (holding potential of 0 mV) and normally polarized fibers (holding potentials between -80 and -90 mV). The manifestations of EC coupling recovered when ions of groups Ia and IIa of the periodic table were included in the extracellular solution; the extent of recovery depended on the ion species. These results are consistent with the idea that the voltage sensor of EC coupling has a binding site for metal cations--the priming site--that is essential for function. A state model of the voltage sensor in which metal ligands bind preferentially to the priming site when the sensor is in noninactivated states accounts for the results. This theory was used to derive the relative affinities of the various ions for the priming site from the magnitude of the EC coupling response. The selectivity sequence thus constructed is: Ca greater than Sr greater than Mg greater than Ba for group IIa cations and Li greater than Na greater than K greater than Rb greater than Cs for group Ia. Ca2+, the most effective of all ions tested, was 1,500-fold more effective than Na+. This selectivity sequence is qualitatively and quantitatively similar to that of the intrapore binding sites of the L-type cardiac Ca channel. This provides further evidence of molecular similarity between the voltage sensor and Ca channels

Essential ideal transforms

It is our intention in this research generalized some concept in local cohomology such as contravarint functor $ext$, covariant functor $Ext$, covarian functor $Tor$ and ideal transforms with $e$-exact sequences. The $e$-exact sequence was introduced by Akray and Zebari \cite{AZ} in 2020. We obtain for a torsion-free modules $B$, $_eext^n_R(P,B)=0$ while $_eExt^n_R(A,E)=0$ for every module $A$. Also for any torsion-free module $B$ we have an $e$-exact sequence $0\to \Gamma_{a}(B) \to B\to D_{a}(B)\to H^1_{a}(B)\to 0$ and an isomorphisms between $B$ and $r D_{a}(B)$. Finally we generalize Mayer-Vietories with $e$-exact sequences in essential local cohomology, we get a special $e$-exact sequences

Paths of Bridging the Gap Between Academic and Media Practice: The Professors’ Vision in Media Faculties

The article aims to explore paths for bridging the gap between academic qualification in media faculties, departments, and institutes, and media practice from the point of view of media professors in Jordanian universities. A descriptive approach has been adopted to achieve the articles aim, using a survey questionnaire of 50 practitioners of media institutions, and conducting 15 interviews with professors in media faculties and departments at Jordanian universities. The results indicated a gap between academic qualification and media practice. This gap had been due to the different requirements of the market, and the sufficiency of media institutions in terms of media professionals, besides the absence of criteria for accepting students in media faculties, and the academic plans focusing on theoretical aspects more than practical aspects. The results finally concluded that six paths might bridge the gap between the academic media path and media practice: applying the mechanism for accepting students in media majors, developing curricula and plans to keep pace with the requirements of the digital age and the needs of the labor market, recruiting experienced and competent professors and involving professionals in the teaching process, preparing advanced training programs for students; and developing training centers in media faculties

Алгоритм определения оптимального числа волокон используемых при внутритканевой фотодинамической терапии рака молочной железы на основании диффузионного уравнения

It is essential in interstitial Photodynamic therapy (iPDT) treatment planning to ensure a homogeneous distribution within a tumor volume using cylindrical diffusing fibers while keeping the surrounding tissue intact. Light distribution is simulated through two algorithms based on the diffusion equation assuming diffusers as light sources. The first algorithm analyzes the diffusion equation and studies the effects of different variables (optical properties, delivered power, diffuser length, and position). Next, optical properties of breast were applied to estimate the volume that receives accepted light dose from one diffuser. In the second algorithm, multiple diffusers were simulated in order to find the relation between the volume and the number of required diffusers which are needed to cover cubical or cylindrical volume with sufficient light dose. Throughout this study, real values of optical properties, clinical laser power, and treatment time were considered to evaluate sufficient light doses. This study is in agreement with previous works in that optical properties are the major factors influencing light distribution in iPDT. It is shown that for a homogeneous phantom mimicking breast cancer and cubical or cylindrical shape, the number of required fibers N equal W×L or D2 respectively.При планировании внутритканевой фотодинамической терапии (iPDT ) с использованием цилиндрических диффузных волокон важно обеспечить однородное распределение света по всему объему опухоли, сохранив при этом целостность окружающей ткани. Авторы данной статьи смоделировали распределение света с помощью двух алгоритмов, основанных на уравнении диффузии, в которых в качестве источников света используются цилиндрические диффузоры. Первый алгоритм анализирует уравнение диффузии и изучает влияние различных переменных (оптических свойств источника, применяемой мощности, длины диффузора и его положения). Затем были использованы параметры оптических свойств молочной железы для оценки объема, который рассчитывает световую дозу от одного диффузора. Во втором алгоритме было смоделировано несколько рассеивателей для нахожде ния соотношения между объемом и количеством рассеивателей, необходимых для покрытия кубического или цилиндрического объема достаточной световой дозой. На протяжении всего этого исследования рассматривались реальные значения оптических свойств, клинической мощности лазера и времени лечения для оценки достаточных световых доз. Это исследование согласуется с предыдущими работами в том, что оптические свойства являются основными факторами, влияющими на распределение света при iPDT. Показано, что, для однородного фантома, имитирующего рак молочной железы, кубической или цилиндрической формы, количество требуемых волокон N равно W×L или D2 , соответственно

Essential cohomology modules

In this article, we give a generalization to injective modules by using $e$-exact sequences introduced by Akray in [1] and name it $e$-injective modules and investigate their properties. We reprove both Baer criterion and comparison theorem of homology using $e$-injective modules and $e$-injective resolutions. Furthermore, we apply the notion $e$-injective modules into local cohomology to construct a new form of the cohomology modules call it essential cohomology modules (briefly $e$-cohomology modules). We show that the torsion functor $\Gamma_a ( - )$ is an $e$-exact functor on torsion-free modules. We seek about the relationship of $e$-cohomology within the classical cohomology. Finally, we conclude that they are different on the vanishing of their $i_{th}$ cohomology modules

Management of tomato damping-off using natural plant extracts, Trichoderma harzianum and selected fungicides in Penjween, Sulaimani Governorate, Kurdistan, Iraq

Tomato seedlings were found epidemically infected with damping-off disease at four locations (Kanimasyan, Kanishaban, Kanisev and Qzlja), in Penjween, Sulaimani Governorate, Kurdistan, Iraq during May 2011. The highest occurrence of disease incidence was observed in Kanimasyan (56%). Fusarium oxysporum (Schlecht), F. solani (Mart.) Sacc., F. acuminatum (Ell. and Ev.), F. equiseti (Corda) Sacc., F. compactum, Rhizoctonia solani (Kuhn), Macrophomina phaseolina (Tassi) Goid., Phoma lycopersici (Kleb), and Cephalosporium sp. were isolated from the infected plants and proved pathogenicity on tomato seeds (cv. Super Queen). Fusarium oxysporum and R. solani showed the highest level of seedling damping-off, with largest effect on decreasing the quality of seedling's vigor. Extracts of H. triquetrifolium, E. billardieri and C. rotundus at (20, 30, 40, 45 mg ml-¹) showed inhibitory effect on the mycelial growth of all pathogenic fungi. In vitro plant extract of C. rotundus revealed the highest inhibitory effects on fungal growth at 45 mg ml-¹. Fungicide of Keenol at 50 ppm proved to be chemostatic against all pathogens. T. harzianum appeared to be an important antagonistic agent against mycelial growth. Management of the disease was carried out in greenhouse using (H. triquetrifolium, Vitavax 200, T. harzianum and Keenol). It was found that the combination of (H. triquetrifolium + keenol) and (T. harzianum + H. triquetrifolium) showed impressive effects on plant height, dry and fresh weight when compared to the other treatments and control

Directed Random Markets: Connectivity determines Money

Boltzmann-Gibbs distribution arises as the statistical equilibrium probability distribution of money among the agents of a closed economic system where random and undirected exchanges are allowed. When considering a model with uniform savings in the exchanges, the final distribution is close to the gamma family. In this work, we implement these exchange rules on networks and we find that these stationary probability distributions are robust and they are not affected by the topology of the underlying network. We introduce a new family of interactions: random but directed ones. In this case, it is found the topology to be determinant and the mean money per economic agent is related to the degree of the node representing the agent in the network. The relation between the mean money per economic agent and its degree is shown to be linear.Comment: 14 pages, 6 figure

Course Delivery: Online, Hybrid, Service and Experiential Learning Possibilities (New for 2018)

The leading barometers of online learning such as the Online Report Card (available at https://onlinelearningconsortium.org/read/online-report-card-tracking-online-education-united-states-2015/) indicate that over one in four higher education students now take distance courses and the increase in online enrollments is outpacing overall higher education enrollments. Busy life schedules, tight budgets, established career paths, advances in technology and the desire to reach ever wider, more diverse student bodies are some of the factors driving the growth. Students have differing needs and preferences and some disciplines’ training requirements cannot be met through online learning. In our Conflict Resolution Studies Department at Nova Southeastern University, we have been offering the whole range of course delivery modes; online, residential and hybrids driven by the desire to meet student needs in ever wider locations as well as capitalizing on the advances in class delivery modes. Our guiding philosophy of the scholarship of engagement, makes experiential learning and community engagement critical components of our curriculum. For our practice courses we find that hybrid courses give students online flexibility while providing the hands on, face to face interaction practice requires. In this chapter, we share from what we have learnt in three aspects of learning: online, hybrid and experiential studies.https://nsuworks.nova.edu/shss_facbooks/1095/thumbnail.jp

Route Discovery Development for Multiple Destination Using Artificial Ant Colony

Smart cities need a smart applications for the citizen, not just digital devices. Smart applications will provide a decision-making to users by using artificial intelligence. Many real-world services for online shopping and delivery systems were used and attracted customers, especially after the Covid-19 pandemics when people prefer to keep social distance and minimize social places visiting. These services need to discover the shortest path for the delivery driver to visit multiple destinations and serve the customers. The aim of this research is to develop the route discovery for multiple-destination by using ACO Algorithm for Multiple destination route planning. ACO Algorithm for Multiple destination route planning develops the Google MAP application to optimize the route when it is used for multiple destinations and when the route is updated with a new destination. The results show improvement in the multiple destination route discovery when the shortest path and the sequence order of cities are found. In conclusion, the ACO Algorithm for Multiple destination route planning simulation results could be used with the Google Map application and provide an artificial decision for the citizen of Erbil city.  Finally, we discuss our vision for future development

Enhanced the prediction approach of diabetes using an autoencoder with regularization and deep neural network

Diabetes mellitus is considered one of the foremost common and extreme diseases worldwide. A precise and early diagnosis of diabetes is essential to avoid complications and is of crucial importance to the medical care that patients get. To achieve that, we need to develop a model to predict diabetes. There are many prediction models, but they suffer from some problems such as the accuracy of prediction being poor and the time complexity. The prediction process is highly dependent on important features. So, in this paper, we proposed a new model called (CAER-DNN) that depends on an unsupervised technique for generating newly important features and a deep neural network for the prediction process. The unsupervised technique is called complete autoencoder with regularization techniques (CAER) that uses to reconstruct the original features (newly learned features). It is focused too much on training the most important learned features and misses out on less important features. Thus, improving the performance of the prediction process. These important features are used as input to the deep neural network for the prediction of diabetes. Our model is applied to two sets of data including Pima Indian and Mendeley diabetic datasets. Based on the 10-fold cross-validation technique Pima Indian dataset achieves high performance in evaluation measures (f1-score 97.38%, accuracy, recall 97.25%, specificity 97.59%, precision 97.53%,). While the Mendeley diabetes dataset achieved high performance in evaluation measures (f1-score 94.51%, accuracy 98.48, recall 91.74%, accuracy-balance 98.21%, precision 98.21%) based on the holdout technique. compared with other existing machine learning and deep learning techniques our model outperformed existing techniques