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We explain and explore class-theoretic potentialism -- the view that one can always individuate more classes over a set-theoretic universe. We examine some motivations for class-theoretic potentialism, before proving some results concerning the relevant potentialist systems (in particular exhibiting failures of the .2 and .3 axioms). We then discuss the significance of these results for the different kinds of class-theoretic potentialist., (Updated after review.)

In the setting of ϵ -chainable metric spaces, we introduce ϵ − ρ − σ uniformly local weak contraction and obtain some results on the existence of fixed points. To show the veracity of the results, we also constructed some examples.

In this paper, we give an explicit realization of all irreducible modules in Chari’s category O ~ \widetilde {\mathcal O} for the affine Kac-Moody algebra A 1 ( 1 ) A_{1}^{(1)} by using the idea of free fields. We work on a much more general setting which also gives us explicit realizations of all simple weight modules for certain current algebra of s l 2 ( C ) \mathfrak {sl}_2(\mathbb {C}) with finite weight multiplicities, including the polynomial current algebra s l 2 ( C ) ⊗ C [ t ] \mathfrak {sl}_2(\mathbb {C})\otimes \mathbb {C}[t] , the loop algebra s l 2 ( C ) ⊗ C [ t , t − 1 ] \mathfrak {sl}_2(\mathbb {C})\otimes \mathbb {C}[t,t^{-1}] and the three-point Lie algebra s l 2 ( C ) ⊗ C [ t , t − 1 , ( t − 1 ) − 1 ] \mathfrak {sl}_2(\mathbb {C})\otimes \mathbb {C}[t,t^{-1},(t-1)^{-1}] arisen in the work by Kazhdan-Lusztig.

COVID-19 virus disease is an infectious disease caused by SARS-Cov-2 virus, as the diagnostic imaging department play a remarkable role in detecting and diagnosing of COVID-19 in early stages, therefore, medical imaging workers should be aware of infection control guidelines to prevent the transmission of the disease. A cross-sectional descriptive study survey design was conducted from July 15, 2020 to September 15, 2020, in diagnostic imaging departments in Palestine, aimed to evaluate the impact of COVID-19 pandemic on medical imaging workers; in terms of infection sources, awareness and commitment to relevant safety guidelines. From a 205 valid responses, there was 54.5% governmental, 27.2% private, and 18.3% from NGOs sector. Female were 26.8% and 81.9% holding BA degree, about 41.2% are less than five years of experience. 36.1% had a previous positive COVID-19 result, of them there was 61.6% due to nosocomial infection. Only 63.2% were confidence of their hospital preparedness for COVID-19, 65.1% felt that their department is capable of dealing with COVID-19 patients, 43.3% revealed that they had training on handling COVID-19 patients, 58.7% reported that selfreading was their source of information about COVID-19, inadequate training or knowledge about hand hygiene and proper use of PPE was noted. Our findings emphasize the vital need of expanded COVID-19 pandemic training for medical imaging workers, as well as related protective measures

The main aim of this study was to develop indirect enzyme linked immune sorbent assay based on the use of bacterial cloned SARS CoV-2 spike protein as a cheap and continuously available source of antigen. This test was proved to be useful for a quantitative measurement and evaluation of antibody immune response among SARS-CoV-2 infected individuals. Standard cloning procedures had been used in cloning two different segments of the spike gene and its expression. The size of the two cloned segments were of 700 base pair and of 500 base pair, which were named clone 8 and clone 105, respectively. These DNA segments were cloned in pET28a plasmid and then expressed in Bl21 E. coli. Different serum samples were tested from: current, previous infection, vaccinated and non-vaccinated patients using the amplified expressed proteins in enzyme linked immune sorbent assay. The expressed proteins from each clone were responded with varying degrees of sensitivity against COVID-19 positive human sera, and we attempted to validate which of the two recombinant proteins is the best to be used in Corona IgG and IgM antibody detection. Based on the results of indirect enzyme linked immunoassay, most of the tested samples had greater antibody titers with clone 8, which was found to have a higher similarity (99% resemblance) to the severe acute respiratory syndrome coronavirus 2 surface protein using BLAST search. We recommend clone 8 with high potential to be used for large-scale screening for COVID-19 outbreak; nevertheless, it requires greater sensitivity and specificity validation

An essential instrument for the operation of a power system is to monitor and analyze the data to find the fault and rectify it before the system collapses completely. This paper intents to utilize the idea to create a control system that will fulfill objectives like monitoring vital parameters controlling the power distribution, outage management by fault detection based on the variation of Voltage, Frequency, and Current & protection of the Circuit against any significant incidents by isolating the load from utility and flagging the information through feedback to the utility authority. The Project implements the high-end technology for IoT applications that will connect with the Microcontroller to receive the data at regular intervals and post the timestamped data in a cloud platform for remote monitoring and archiving. This innovation can reduce human dependency and overcome the whole outage situation by building a two-way communication that means electricity and information are traded between consumers and utilities to capitalize on the efficiency of a grid system. The proposed model offers intelligent monitoring of the timestamped data with remote access & historical data archiving for a better load profile. An outage management system is designed for the proposed system by intellectual fault detection through Voltage, Frequency & current variation, and isolation of the faulty part from the entire system, maintaining an auto circuit recloser application before the permanent isolation for reducing the human interaction & flagging the outage information & supply emergency backup during the shutdown period, and in the process, helping the power grid from total power outage or blackout.

Generally, human epidermal growth factor 2 (HER2) breast cancer is more aggressive than other kinds of breast cancer. Currently, HER2 breast cancer is detected using variety of medical test which are most expensive. Therefore, the aim of this study was to develop a computational model named convoHER2 for detecting HER2 breast cancer with image data using convolution neural network (CNN). Hematoxylin and eosin (H&E) and immunohistochemical (IHC) stained images were used as raw data from the Bayesian information criterion (BIC) benchmark dataset. This dataset consists of 4873 images of H&E and IHC. Among all images of the dataset, 3896 and 977 images were applied to train and test the convoHER2 model, respectively. All images of this dataset are resized due to high resolution of the image for forming better detection performance of convoHER2 model. Moreover, the dataset is classified into four different labels (0+, 1+, 2+, 3+) for identifying the grade of detected HER2 breast cancer. The convoHER2 model is able to detect HER2 cancer and its grade with accuracy 85% and 88% using H&E images and IHC images, respectively. The outcomes of this study determined that the HER2 cancer detecting rates of the convoHER2 model are much enough to provide better diagnosis to the patient for recovering their HER2 breast cancer in future.

The Agile Methodology is a term which refers to a method of software development that is incremental and iterative in nature and is used to manage and incorporate constantly changing needs. This entails decomposing the entire development process cycle into a series of tasks. The process is further divided into a number of sub-tasks, each function is independently. The Agile Development technique, which is a popular and growth-oriented strategy, provides not only speedy project delivery, but also software responsiveness, which leads to total corporate growth and agility. The organization's project management capabilities and performance are improved through the adoption of Agile practices. In their business, the companies employ Agile methods. As a result, the goal of this study is to see how effective agile approaches are in Bangladeshi software organizations. A survey of established software companies in Bangladesh is being conducted to accomplish the objective. The Scrum and XP agile technique is the most widely used according to the findings. It is proposed that Scrum and the XP model be combined to achieve maximum effectiveness and overcome their respective limits.

Solar energy is a valuable resource on earth but the availability of solar resources relies on meteorological variables. In this paper, forecasting models using the artificial neural network are developed by changing the input meteorological variables from five to seven. The two years data are used to train the model whereas the testing is performed using one year data on different seasons following single step ahead. The input parameters are relative humidity, pressure, temperature, solar zenith angle, wind speed, wind direction and perceptible water. Three artificial neural network models (ANN-I5, ANN-I6, ANN-I7) are developed to estimate the global horizontal irradiation and performance of all models are measured on the basis of Mean Absolute Percentage Error (MAPE), Relative Root Mean Square Error (RRMSE) and Correlation Coefficient (R2). Result indicates that ANN-I7 shown better performance as comparison to other developed models. The average MAPE and RRMSE of ANN models such as ANN-I7, ANN-I6, ANN-I5 are 14.52%, 16.53%, 18.97% and 20.74%, 22.28%, 24.43% respectively. The ANN-I7 haiving an input meteorological parameters relative humidity, pressure, temperature, solar zenith angle, wind speed, wind direction and perceptible water showed good accuracy as comparison to other two developed models. This study indicates that accuracy of solar irradiation forecasting depends on meteorological parameters.

In this research paper, effects of fixing one barrier and varying another barrier have been analyzed and compared for a GaAs/Al0.3Ga0.7As based double barrier resonant tunnelling diode for two different models - Hartree Quantum Charge model and semi-classical Thomas Fermi model. VI characteristic graphs are studied to assess the overall performance of both models. The simulations are carried out in a nanoelectronics modelling tool suite – Nano electronic Modelling 5 (NEMO5) considering Non-Equilibrium Green’s Function (NEGF), at room temperature of 300K and biased voltage of 0 to 0.5 V. In this paper, it was demonstrated that a very larger amount of current is supplied by both models when the first barrier is varied and second barrier is fixed in comparison to the first barrier when kept fixed and second barrier is varied. But as quantum charge inside the quantum well is existed in the Hartree model, so overall Hartree model supplied a greater amount of current compared to the Thomas Fermi model. Quantum charge inside its quantum well is not present in the Thomas Fermi model. But a better NDR region is created by the Thomas Fermi model in both varied first barrier-fixed second barrier and fixed first barrier-varied second barrier cases compared to the Hartree model. This NDR region can be used for numerous digital applications. On the other hand, a vast range of analog applications can be used by the Hartree model that produced larger current per unit voltage.

The main goal of this paper is to make a multifunctional robot along with a database management system named “MEDBOT”. That will reduce the problem of spreading any viral or infectious disease by maintaining social distance. A robot is designed and implemented will replace the ordinary system in the medical sector in a digital way with fewer life risks. Being a multifunctional robot, it can perform as a receptionist, entertainer, nurse, cleaner, and deliveryman. As a nurse, it will check a patient’s temperature, Heart Rate, Oxygen Saturation, and Heart condition in a contactless way. Furthermore, these vitals are easily stored in its database system. These vitals are broadcast on the device’s display and server, where the doctor can quickly monitor them in real-time. A mobile application-based remote-control system is equipped in this robot to control it remotely. Moreover, a disinfecting system and UV-C light are used for sterilizing purposes. The previously invented medical robot can perform one or two tasks, but a revolutionary change will come into the medical sector by making this robot. At last, it can be said that the ‘Medbot’ can reduce infectious disease, save time moreover digitalize the medical industry by doing these works. Finally, building a digital Bangladesh, it will work along with the medical sector as a warrior.

Urban migration is becoming an increasing issue in the cities in Bangladesh. Since the migrants are mostly poverty affected, they have no other opportunity than to move to urban slums, where, there is no decent infrastructure. The high density of built-forms and lack of understanding about ventilation strategies and thermal insulation are some of the reasons for their sufferings during the summer and winter months. The constant need for health treatment, infrastructure repairing, increasing utility bills due to lack of daylight and ventilation are affecting their extremely marginal economic condition. This study investigates existing built-forms, socio-economic assets, and living conditions in a particular slum area, located in Dhaka, Bangladesh; and, suggests some adaptive solutions in the form of minor and affordable interventions to upgrade their infrastructure, mostly focusing on the inclusion of daylight and ventilation by retrofitting the existing condition.

A performance comparison of the conventional slip ring induction motor (SRIM) drive and the recently inducted variable frequency drive (VFD) in the sugar industry, for sugarcane preparation (chopping/ shredding of sugarcane), is carried out to assess their effectiveness and to explore better electric drives for the application. These high inertial machines demand high starting torque and mitigating means to reduce surge load due to the impact load imposed on them. Though, both the drives meet the requirement but the SRIM drives are subjected to huge slip power loss, low power factor, unequal load sharing problem for coupled motors and high drop in rpm, whereas VFDs are subjected to the problems of input current harmonics, high dV/dt stress and common-mode voltage (CMV). In this paper, along with the performance comparison a three/four-level multilevel inverter (MLI) fed open-end winding induction motor (OEWIM) drive is also proposed as an improvement over the existing ones.

Bangladesh is highly affected by climate change scenarios notably floods due to its location on the world map in the South Asian region. Besides due to monsoon rains and high upstream rainfall in several areas eventually turn into floods. Thus, early flood forecasting might save human lives as well as agriculture crops. In this paper, we have applied different machine learning classifier models (Decision tree, Naive bayes, k-NN and Random forest) with a view to predicting the occurrence of flood. RapidMiner tool has been used extensively to perform data preparation, decision tree model generation, cross-validation, model selection and optimization of the model parameters. It is seen that the decision tree model has performed well by achieving an accuracy of 94.23% which is further optimized to reach 94.68%. Feature Selection using ‘correlation matrix’ is also a good aspect of this work by which we have achieved a good accuracy.

In recent years, increasingly more soils are getting contaminated with organic and inorganic toxins globally due to waste emissions. Among inorganic pollutants, heavy metal like chromium (Cr) is alarming to our environment, even though its environmental management is also ignored. As a result, Cr accumulates in plant tissues at toxic concentrations end up in the food chain. Therefore, pot experiment was conducted to investigate the effects of biochar and modified biochar application on the properties of Cr polluted soils and interaction of Cr with other soil nutrients. Two different biochar viz. rice stubble and saw dust were slow pyrolyzed (450 ± 50ºC) and modified with1M KOH. All biochars were applied at a rate of 20 t ha-1 on soils artificially polluted with Cr at the levels of 0, 100, 200 and 300 µg g-1. The biochars and modified biochars had significant effects (P

The aim of this study is to develop a descriptive framework for teacher educators to assist teachers to plan and realize modelling implementations in their classrooms and for researchers to describe and analyse how modelling is implemented. The planning process and implementations of 12 middle and high school mathematics teachers who conducted modelling implementations were analysed by the researchers to achieve this aim. The data used in the study were lesson plans regarding each modelling implementation, the transcripts of the voice recordings of pre-implementation interviews with the teachers, transcriptions of the video recording of each implementation, and the observation notes of the researchers. The data were analysed within the framework of the grounded theory approach. All modelling implementations consisted of three main sections: planning, implementation, and assessment. The planning section includes identifying the goals, deciding the modelling task and making preparations. The implementation section consists of conducting warm up activities, sharing norms, sharing assessment criteria, presenting the modelling task and tracking students’ work. The assessment section involves presenting solutions, discussing solutions and necessary revisions, assessing competencies, and sharing assessment results and arriving at decisions.

A mobile agent navigating along edges of a simple connected unweighted graph, either finite or countably infinite, has to find an inert target (treasure) hidden in one of the nodes. This task is known as treasure hunt. The agent has no a priori knowledge of the graph, of the location of the treasure, or of the initial distance to it. The cost of a treasure hunt algorithm is the worst-case number of edge traversals performed by the agent until finding the treasure. Awerbuch et al. [ 3 ] considered graph exploration and treasure hunt for finite graphs in a restricted model where the agent has a fuel tank that can be replenished only at the starting node s . The size of the tank is B = 2 (1+α) r , for some positive real constant α, where r , called the radius of the graph, is the maximum distance from s to any other node. The tank of size B allows the agent to make at most ⌊ B ⌋ edge traversals between two consecutive visits at node s . Let e(d) be the number of edges whose at least one endpoint is at distance less than d from s . Awerbuch et al. [ 3 ] conjectured that it is impossible to find a treasure hidden in a node at distance at most d at cost nearly linear in e(d) . We first design a deterministic treasure hunt algorithm working in the model without any restrictions on the moves of the agent at cost 𝒪(e(d) log d ) and then show how to modify this algorithm to work in the model from Awerbuch et al. [ 3 ] with the same complexity. Thus, we refute the preceding 20-year-old conjecture. We observe that no treasure hunt algorithm can beat cost Θ ( e(d) ) for all graphs, and thus our algorithms are also almost optimal.

International literature is increasingly disclosing the relevance of cultural aspects within the processes of teaching and learning mathematics. Knowledge is inextricably linked to the activities in which the subjects engage, and must be considered in relation to the socio-cultural context wherein the activity takes place. Literature reveals the relationship between the background culture (e.g. language, nationality, etc.) of prospective elementary teachers and their beliefs about mathematics and its teaching. In this paper, we define culture with reference to the wider discussion from cross-cultural psychology literature about cultural values, and we investigate if and how differences in individuals’ cultural values are related to prospective teachers’ beliefs about being successful in mathematics and in its teaching. We adopt a questionnaire from the studies by Schwartz to measure participants’ values. We assign each prospective teacher of our sample to a cluster of beliefs and we analyse how the beliefs of prospective teachers are related to their values. Results show that cultural values and beliefs about mathematics are related, while this is not the case for beliefs about the teaching of this subject.

Emergent graphical shape thinking (EGST) involves interpreting or constructing a graph as dynamically generated, which is useful across science, technology, engineering, and mathematics fields. Although evidence suggests that students as young as middle school can engage in EGST with support, other research indicates most college students and U.S. teachers do not spontaneously engage in such reasoning when potentially productive. We describe a local instruction theory (LIT) to support middle school students developing EGST as part of their graphing meanings. We then present a case study to show how two students engaged with a task sequence designed with the LIT in mind to develop meanings for EGST. This article illustrates general principles researchers and educators could use to promote students’ graphing meanings.

We present findings from a study about obstacles that Black students who succeeded in developmental mathematics in community college reported having endured in those mathematics classrooms. To understand the types of obstacles that can arise for students in these classrooms, we analyze data using two frameworks: mathematics identity and dimensions of mathematics classrooms. Study participants faced obstacles in three categories: (a) impressions of faculty’s instructional practices for problem solving; (b) negative race-related perceptions they believed classmates had about them; and (c) perceptions about instructors’ expectations. These findings contribute to literature on Black students’ progress in mathematics by identifying obstacles experienced by students who achieve in these courses and can also inform professional development learning for mathematics faculty.

In this editorial, we suggest that writing and reviewing Research Commentaries for the Journal for Research in Mathematics Education (JRME) are avenues through which all researchers on mathematics education can serve as stewards of our field.

Mathematics education researchers concerned with justice and rehumanizing mathematics education are increasingly calling for research that takes seriously the values, commitments, and voices of the communities for which the research is most consequential. Exclusion of or superficial engagement with these perspectives and experiences in research and design processes have perpetuated deficit perspectives of minoritized communities, rendering them simply the object of reform efforts. Consequently, this Research Commentary conceptualizes a participatory turn in mathematics education research, offering a set of commitments that guide and examine the possibilities and tensions of such a turn.