Miracle-dz/UniFAR-FTUs huggingface dataset:
EMAIL SPAM CLASSIFICATION USING HYBRID APPROACH OF RBF NEURAL NETWORK AND PARTICLE SWARM OPTIMIZATION

Email is one of the most popular communication media in the current century; it has become an effective and fast method to share and information exchangeall over the world. In recent years, emails users are facing problem which is spam emails. Spam emails are unsolicited, bulk emails are sent by spammers. It consumes storage of mail servers, waste of time and consumes network bandwidth.Many methods used for spam filtering to classify email messages into two groups spam and non-spam. In general, one of the most powerful tools used for data classification is Artificial Neural Networks (ANNs); it has the capability of dealing a huge amount of data with high dimensionality in better accuracy. One important type of ANNs is the Radial Basis Function Neural Networks (RBFNN) that will be used in this work to classify spam message. In this paper, we present a new approach of spam filtering technique which combinesRBFNN and Particles Swarm Optimization (PSO) algorithm (HC-RBFPSO). The proposed approach uses PSO algorithm to optimize the RBFNN parameters, depending on the evolutionary heuristic search process of PSO. PSO use to optimize the best position of the RBFNN centers c. The Radii r optimize using K-Nearest Neighbors algorithmand the weights w optimize using Singular Value Decomposition algorithm within each iterative process of PSO depending the fitness (error) function. The experiments are conducted on spam dataset namely SPAMBASE downloaded from UCI Machine Learning Repository. The experimental results show that our approach is performed in accuracy compared with other approaches that use the same dataset.
Child Bearing Decisions among Women Enrolled In PMTCT Programme: A Comparative Study of the Rural and Semi-Urban Setting of Malawi Chiradzulu District

Background: HIV and AIDS have caused untold harm and human suffering globally. Over 90% of people infected with this deadly virus live in sub-Saharan Africa including Malawi. In Malawi HIV disproportionally affects women in comparison with men. According to Demographic and Health Survey (2015-2016) key indicators, HIV prevalence among women aged 15-64 was 12.8% compared to men 8.2% public health. As per 2010 Malawi demographic and health survey, HIV prevalence in the southern region was twice as high as prevalence in the other regions (Southern 14.5%, Central 7.6% and northern region (6. 6%). Women and children are more affected than the rest of the general population. HIV infection in children below 15 years is largely due to mother-to-child transmission (MTCT). Worldwide, over two million children have been infected through MTCT. Type of Research Study: The study adopted a qualitative research design using the inductive research technique or grounded theory research in which the steps occur simultaneously, observing, collecting data and forming theory from the data at the same time. Problem Statement: HIV prevalence in Southern Region of Malawi is twice as high as Northern and Central regions, at 14.5% where fertility rate at 5.7% are also high. A combination of high fertility rate and high HIV prevalence have contributed to the undermining of an effective PMTCT continuum of prevention, care and treatment programme towards achieving virtual elimination of mother to child HIV transmission and keeping the mothers alive. Therefore, there is need to examine how and through what pathways learning about one’s HIV positive status could alter one’s childbearing decisions. Objectives: This study explored the decision-making process on pregnancy decisions among PMTCT participants and their family support systems; Examined factors that influence decision making process among PMTCT participants and their immediate family networks; Determined the gaps in the PMTCT service delivery; Explored the knowledge and attitudes of health providers PMTCT mothers; and analysed the gap between the PMTCT policy guidelines and their implementation This study revealed factors that influence fertility decisions among pregnant women with HIV attending ANC and ART clinic at Chiradzulu District Hospital. Some of participants became pregnant because they desired to have another child and others because their partners wanted a child. A proper understanding of factors associated with pregnancies among these women is essential to guide interventions and counselling strategies to better inform and support them. Religious doctrines, beliefs about having a healthy baby, personal desire and familial desires to have a baby, combined with the social stigma that accompanies HIV, puts women who are HIV-positive in a difficult situation. HIV-positive women must be appropriately counselled about the risks of childbearing rather than focusing only on issues related to mother-to-child transmission of HIV.
Bindings Are Functors

JASMIN CHRISTIAN BLANCHETTE, Vrije Universiteit Amsterdam, The Netherlands and Max-PlanckInstitut für Informatik, Germany LORENZO GHERI,Middlesex University London, UK ANDREI POPESCU,Middlesex University London, UK and Institute of Mathematics Simion Stoilow of the Romanian Academy, Romania DMITRIY TRAYTEL, ETH Zürich, Switzerland We present a general framework for specifying and reasoning about syntax with bindings. Abstract binder types are modeled using a universe of functors on sets, subject to a number of operations that can be used to construct complex binding patterns and binding-aware datatypes, including non-well-founded and infinitely branching types, in a modular fashion. Despite not committing to any syntactic format, the framework is “concrete” enough to provide definitions of the fundamental operators on terms (free variables, alpha-equivalence, and capture-avoiding substitution) and reasoning and definition principles. This work is compatible with classical higher-order logic and has been formalized in the proof assistant Isabelle/HOL. CCS Concepts: • Theory of computation → Logic and verification; Higher order logic; Type structures; Interactive proof systems; Additional
An Extensive Method for Maintenance of Sterility in Mammalian Cell Culture Laboratory Routine

Cell culture laboratories are designed to secure sterile environments for biological studies, and its susceptibility to biological contaminants is a major problem for researchers. Contamination can generally be overcome by frequently disposing of contaminated materials, cleaning and maintaining the sanitation of working areas, but in some cases, it is hard to eradicate the source(s) of contaminating agents completely. In particular, mold and fungal-based contaminants could be a devastating problem for any laboratory. Therefore, various contamination types can repeat over time and result in an increasing problem in the lab. To control and eliminate possible contaminations, a periodic cleaning treatment with disinfectant materials should be a routine procedure of every specialized laboratory, regardless of the existence of any contamination. The conventional method for maintaining hygiene in cell culture laboratories is to clean all surfaces with 70% ethanol; however, this may not be the complete solution. This paper presents a short and easy way to check whether any contamination source(s) are present in laboratories. After identification of the most contaminant-rich areas, without any distinction, each laboratory surface where the culturing samples were taken was comprehensively treated with suggested concentrations of ethanol, sodium hypochlorite and Virkon-S solutions. The method might be useful to regularly check and maintain the cleanliness and hygiene of entire cell culture laboratories to enable the control of possible contaminations in advance.
What do we gain from simplicity versus complexity in species distribution models

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.
Vertically Aligned MoS2/Mo2C hybrid Nanosheets Grown on Carbon Paper for Efficient Electrocatalytic Hydrogen Evolution

Maximizing and creating active sites has been a general strategy to increase the performance of a catalyst. Because of the high electrocatalytic hydrogen evolution reactivity (HER) of ultrafine Mo2C nanocrystals and edges of two-dimensional MoS2, an electrode with a synergistic integration of these two nanomaterials is expected to show a better HER performance. Here we report this hybrid nanostructure of vertically aligned MoS2/Mo2C nanosheets on conductive carbon paper. It was revealed that the original structure of MoS2 nanosheets remains intact after the carburization, but the surfaces are incorporated with either Mo2C nanodomains or a heteroatomic mixture of S and C. The hybrid catalyst exhibits a much lower HER overpotential in comparison to those of the corresponding Mo2C and MoS2 alone. Its high activity is congruent with DFT calculations, which show that multiple S and C coordinated Mo sites with near zero Gibbs free energy of hydrogen adsorption exist. Thus, the low overpotential of this binder-f.
Data-Intensive Grid Computing Based on Updatable Views

In this report we propose a new approach to integration of distributed heterogeneous resources on the basis of a canonical object-oriented database model, a query language and updateable database views. Views are used as wrappers/mediators on top of local servers and as a data integration facility for global applications. Views support location, implementation and replication transparency. Because views are defined in a high-level query language, the mechanism is much more abstract and flexible in comparison to e.g. CORBA or Web Services. The report presents a short introduction to the query language SBQL and updateable views. It also presents the architecture of the grid network based on updateable views, and simple examples illustrating the mechanism. In the report we also show how the mechanism can be used in peer-to-peer networks. We shortly describe the process of grid design and development. Finally, we present some issues related to grid metadata. Słowa kluczowe: grid computing, podejście stosowe, aktualizowalne perspektywy 3 1. Introduction Grid computing is a new field concentrating on "flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources-what we refer to as virtual organizations" [Fost01]. Grid technology is presented as facilities that allow one to integrate many computers into one big virtual computer, which summarizes all the resources that particular computers possess: processing power, main memories, disc storages, data and services. A user of a grid can use idle computer resources of all the connected computers as a support of his/her individual desk-top computer. Sometimes computer resources are compared to electricity, which is supplied by many power stations to the global network and then distributed to many users according to their current needs. Essentially, grid technology addresses data-intensive applications, where distribution of massive data implies distribution and parallelization of computations. Practically all business applications are data-intensive. We can imagine a lot of new applications of a data-intensive grid, such as, for example, integrated information on bank services and loans, integrated on-line hotel information and reservations, integrated health services information, etc. New business quality concerns transparency of service providers: the user of a grid first is looking for the service that he/she requires, then makes some transaction, and at last (if any) is interested in the service provider. Many new businesses can be based on the transparency of service providers and with they may create new kind of the information society culture and new opportunities in society development. For …
Effect of in Ovo injection with Nano- Selenium or Nano- Zinc on Post-Hatch Growth Performance and Physiological Traits of Broiler Chicks

The current study was aimed to investigate the effect of in ovo injection with Nano-selenium or Nano-zinc on post-hatch growth performance and physiological traits of broiler chicks under heat stress. Four hundred fertile broiler eggs from cobb500™ flock were randomly divided into four treatments (100 eggs each). First was normally without injection (control), second was injected with 15 ppm Nano-Selenium (SENPs) /egg, third treatment was injected by 15 ppm Nano-Zinc (ZnNPs)/egg and fourth treatment was injected with phosphate buffered saline (PBs) 15 ppm /egg. To study the post-hatch performance, A total number of 240 one day-old chicks were randomly distributed into 4 equal experimental treatments of 60 chicks each. Every treatment was sub-divided into three replicates (20 chicks/ each), were at lasted 5weeks. Results obtained could be summarized as follows: Nano-selenium explained higher chick's weight at hatch, chick's weight to egg weight ratio and hatchability % than all other treatments. At first week of age, the body weight (BW) in the nano-selenium treatment increased than the untreated (control) treatment, although the gastrointestinal tract weight was 0.44 % and the intestine weight was 0.8 %, this is explained by an augmentation in the length of both the length of the small intestine and the gastrointestinal tract by 12 % at 7 day of age. The highest live body weight and body weight gain and the best-feed conversion ratio were recorded with Nano- selenium than all other treatments at 35 day of age. In conclusion, under semi-arid conditions, USAge the Nano-selenium are not harmful to the embryo (injected with 15 ppm) and can be used to improve the post-hatch performance of broiler under semi arid condition.
Cycle Factors and Renewal Theory

For which values of k does a uniformly chosen 3‐regular graph G on n vertices typically contain n/k vertex‐disjoint k‐cycles (a k‐cycle factor)? To date, this has been answered for k = n and for k ≪ log n; the former, the Hamiltonicity problem, was finally answered in the affirmative by Robinson and Wormald in 1992, while the answer in the latter case is negative since with high probability (w.h.p.) most vertices do not lie on k‐cycles.
Pre-Scleroderma State

Scleroderma is divided into localized and systemic. Localized Scleroderma is a cutaneous disease with only sclerosis of one or more skin area without Raynaud’s phenomenon and visceral involvement [1]. But, systemic Scleroderma [or systemic sclerosis] is a chronic autoimmune multisystem disorder with overproduction of collagen fibers; presented as a combination of thickened/sclerotic skin involvement and visceral organ fibrosis along with Raynaud’s phenomenon [2,3].
Short-Chain Fatty Acids Are Antineoplastic Agents

Human diet contains a mixture of saturated and unsaturated fatty acids. These are either long, medium or short chain fatty acids. As commonly believed, all fatty acids are not detrimental to human health. In addition to energy reserves, long chain fatty acids are known as acylating agents for many biomolecules such as cholesterol, terpenoids as well as steroid hormones. They are also involved in acylation of polyphenols such as flavonoids making them palatable for better absorption and biological activities. Polyunsaturated fatty acids (PUFAs) are known for their numerous beneficial health effects including cancer and inflammation. PUFA, particularly ω3 fatty acids, have attracted attention as anticancer agents and particularly for colorectal cancer. PUFAs exhibit immunomodula tory activities controlling inflammosome and are used as adjuvants together with stan - dard anticancer drugs. A reciprocal interaction of short chain fatty acids with PUFAs has been suggested for their anticancer activities. Thus, in colon cancer cells, sodium butyr ate (NaB) interacts with docosahexaenoic acid inducing cell differentiation or catalyze apoptosis. These results encouraged us to investigate NaB, a C4 acid, as an adjuvant to standard proteasome inhibitors. Our results show that NaB sensitizes colon cancer cell lines for treatment with proteasome inhibitors.
A Psychophysiologic Study of Weakening Traumatic Combat Memories with Post-Reactivation Propranolol

Abstract : The objective of this project is to test whether the beta-adrenergic blocker propranolol, given following combat memory reactivation, results in a significantly greater weakening of traumatic memories than propranolol alone, supporting the proposition that this weakening is due to pharmacological blockade of memory reconsolidation, rather than nonspecific actions of propranolol. We hypothesize that subjects who undergo script preparation for the combat event(s) that caused their PTSD, followed by (post-reactivation) propranolol, will show significantly smaller psychophysiologic responses during script-driven imagery testing one week later -- indicative of weakening of the emotional memory -- compared to those who receive (nonreactivation) propranolol two days prior to combat script preparation. Subjects will be randomly assigned to one of two groups: post-reactivation propranolol or nonreactivation propranolol. Subjects randomized to the nonreactivation propranolol group will receive a "test" dose of propranolol, whereas subjects randomized to the post-reactivation propranolol group will receive placebo. Two days later, all subjects will return for an approximate 15-30 minute "script preparation" session, at which time they will describe the details of their traumatic combat event(s). Subjects randomized to the post-reactivation propranolol group will then receive propranolol, whereas subjects randomized to the nonreactivation propranolol group will receive placebo. Scripts will be composed using each subject's own words. Subjects will return to the psychophysiology laboratory 1 week and 6 months later. During each of these visits, heart rate, skin conductance, and corrugator electromyogram responses will be recorded during script-driven imagery of personal combat events. The hypothesis is that at each time period, the physiologic responses of the post-reactivation propranolol group will be significantly smaller than those of the nonreactivation propranolol group.
BEHAVIORAL PUBLIC CHOICE: THE BEHAVIORAL PARADOX OF GOVERNMENT POLICY

What are the economic justifications for government intervention in the economy? In a market economy, prices coordinate the activities of buyers and sellers and convey information about the strength of consumer demand for a good and the costs of supplying it. Because trade is voluntary, buyers and sellers only make exchanges when both parties benefit. Under ideal market conditions, this process leads to an efficient allocation of goods without government intervention. However, economics has long recognized instances in which markets can fail to lead to an efficient outcome. The long-standing view is that either market power or the nonexistence of markets causes market failures. Market power is present when some individuals or firms are price makers (for example, monopolists) rather than participants in a perfectly competitive environment. Such situations typically lead to the production of a less than efficient quantity of goods. The problem of market power is the purview of industrial organization economics and antitrust policy.1 The nonexistence of markets, or the failure of a robust market to arise, can occur for a number of reasons, such as asymmetric information (when one party in a transaction has information that is not available to another) and public goods (when a good is nonrival and nonexcludable in consumption and thus likely to be un-
Sparsity-aware affine projection adaptive algorithms for system identification

In this paper, we propose adaptive algorithms for system identification of sparse systems. We introduce a L1-norm penalty to improve the performance of affine projection algorithms. This strategy results in two new algorithms, the zero- attracting APA (ZA-APA) and the reweighted zero-attracting AP (RZA-APA). The ZA-APA is derived via the combination of a L1-norm penalty on the coefficients into a standard APA cost function, which generates a zero attractor in the update function. The zero attractor promotes sparsity in the filter coefficients during the update process, and therefore accelerates convergence when identifying sparse systems. We show that the ZA-APA can achieve a lower mean square error than the standard LMS and AP algorithms. To further improve the performance, the RZA-APA is developed using a reweighted zero attractor. The performance of the RZA-APA is superior to that of the ZA-APA numerically. Simulation results demonstrate the advantages of the proposed adaptive algorithms in both convergence rate and steady-state behavior under sparsity assumptions on the true coefficient vector. The RZA-APA is also shown to be robust when the number of non-zero taps increases. (5 pages)