Miracle-dz/UniFAR-FTUs huggingface dataset:
RAAE 1/2020, Regular Article, Gwada and Mayaka

Feeding everyone in sub-Saharan African countries remains a challenge because of the high population growth rate, climate change effects and declining soil fertility, particularly affecting maize and legumes availability. In Kenya, maize and legumes are important staple crops and a recipe in most household dinner tables. However, smallholder farmers are still faced with low maize and legumes security. Understanding the factors that influence a given household to produce above or below the household annual requirements, is crucial and largely ignored in the literature. Therefore, this study was carried out to understand the factors influencing maize availability equivalent among smallholder maize-legume farmers in selected counties in Kenya. Panel data were collected from 613 randomly sampled households from five counties. A maize availability equivalent was then calculated and grouped into three categories, which included those households that produced maize equivalent below the average (deficient), along average (sufficient) and those above average (surplus). An ordered logistic regression model was then fitted to estimate the effect of social capital, socioeconomic and institutional factors on maize availability equivalent. The econometric results showed that only the network density as a measure of social capital positively and significantly influenced maize availability equivalent in the household. Other factors like gender, education, age, income of the household head and average plot di stance to nearest market were significant too. Policy recommendations must address gendered production, development of farmer education, participation on social institutions, creation of greater and stronger network density, as well as informing the correct age that will improve the maize equivalent in the households.
The impact of transurethral en bloc resection of bladder tumour on pathological and oncological outcomes

Transurethral resection of bladder tumour (TURBT) is the current gold standard in managing non-muscle invasive bladder cancer (NMIBC), but it is associated with suboptimal pathological and oncological outcomes. There are two main problems with TURBT. First, it is difficult to ascertain complete tumour removal upon piecemeal resection. Second, tumour fragmentation upon resection may lead to increased risk of tumour re-implantation. En bloc resection of bladder tumour (ERBT) has been proposed to tackle these problems. First, it allows full resection of the tumour in one piece including the underlying detrusor muscle, hence providing better evaluation of the resection margins and local staging. As tumours can be completely resected with clear margins, residual disease is less likely with this technique. Second, ERBT avoids manipulation and fragmentation of the bladder tumour, hence minimizing the amount of floating cells and reducing the risk of tumour re-implantation after the surgery. By upholding oncological principles as much as possible, oncological outcomes of NMIBC may be optimised. The future of ERBT is promising in providing better pathological and oncological outcomes, but larger randomised controlled trials are crucial in establishing solid evidence in clinically important outcomes and answering some technical uncertainties regarding ERBT.
A New Approach for Task Scheduling of Cloud Computing Using Fuzzy

 Abstract — Cloud Computing is the distributed computing on internet or delivery of computing services over the internet. Cloud computing involves deploying groups of remote servers and software networks that allow centralized data storage and online access to computer services or resources. Cloud Computing allows the customers to apply the application without set up and access their own files on any device with internet. The cloud service providers have developed the cloud enough to provide services to any number of users. Cloud is a set of virtualized resources that can be produced as demand of the user. In cloud computing basically there are three components: one is the host that represents a physical computing, second is the datacenter that is a collection of server for managing Virtual Machines during their life cycles. Here application is placed, which is accessed by internet. The last is the distributed servers that are in different places but acts as near to the next one. One important issue is the handling of requests from the various machines so that all the tasks can be completed in minimum waiting time. This paper presents and examine a new scheduling algorithm with the use of fuzzy control system for scheduling virtual machines between datacenters. The experimental results show the effectiveness of our algorithm by comparing it with the three scheduling techniques First Come First Serve (FCFS), Round Robin (RR) and Honeybee Foraging (HF) algorithm.
Population modeling and implications for Caribbean hawksbill sea turtle management

Population models provide a means to predict a population's likely response to a particular perturbation, and to evaluate the importance of data gaps with respect to the model's predictive capabilities. Current data are inadequate for development of a comprehensive, predictive model for hawksbill sea turtles (Eretmochelys imbricata). However, the growth, age to maturity, and fecundity data available suggest that inferences may be drawn, cautiously, from existing models for loggerhead ( Caretta caretta) and green ( Chelonia mydas) turtles. Endangered species such as the hawksbill turtle warrant protection at all life stages. Inferences from sea turtle population models point particularly to the need for maintaining unusually high annual survival rates for both benthic juveniles and adults for currently depleted Caribbean hawksbill populations. Reductions in benthic juvenile and adult mortality (both directed and incidental) are indicated wherever they occur.
Privacy, Economics, and Regulation: A Note

In the past two decades, far-reaching innovation in information technology has brought forward a lively scholarly and policy debate over the benefits accrued from the collection of consumer data and the costs and concerns associated with its possible misuse. Costs, benefits, and trade-offs are the domain of economists’ expertise and research. It is therefore not surprising that the academic field of privacy economics has experienced intense growth over the same period of time. Articles that employ economic methodologies to understand the diverse trade-offs associated with personal data have become common across a diverse set of outlets: traditional economic journals; marketing, law, and information systems venues; and computer science conference proceedings.
Efficient MPC with a Mixed Adversary

Over the past 20 years, the eﬃciency of secure multi-party protocols has been greatly improved. While the seminal protocols from the late 80’s require a communication of Ω( n 6 ) ﬁeld elements per multiplication among n parties, recent protocols oﬀer linear communication complexity. This means that each party needs to communicate a constant number of ﬁeld elements per multiplication, independent of n . However, these eﬃcient protocols only oﬀer active security, which implies that at most t < n/ 3 (perfect security), respectively t < n/ 2 (statistical or computational security) parties may be corrupted. Higher corruption thresholds (i.e., t ≥ n/ 2) can only be achieved with degraded security (unfair abort), where one single corrupted party can prevent honest parties from learning their outputs. The aforementioned upper bounds ( t < n/ 3 and t < n/ 2) have been circumvented by considering mixed adversaries (Fitzi et al., Crypto’ 98), i.e., adversaries that corrupt, at the same time, some parties actively, some parties passively, and some parties in the fail-stop manner. It is possible, for example, to achieve perfect security even if 2 / 3 of the parties are faulty (three quarters of which may abort in the middle of the protocol, and a quarter may even arbitrarily misbehave). This setting is much better suited to many applications, where the crash of a party is more likely than a coordinated active attack.
Enhancement of Academic Performance: Investigation of Prevailing Effects of Meditation and Yoga

The purpose of the study is to understand the impact of yoga and meditation on academic performance among students. One-way ANOVA had been used to know the difference between students who underwent yoga and students who have not been given any training. It is found from this study yoga and meditation helps students for enhancing their academic performance.
Modeling Support for Mass Collaboration in Open Innovation Initiatives—The Facilitation Process Model 2.0

Many governments and organizations recognize the potential of open innovation (OI) models to create value with large numbers of people beyond the organization. It can be challenging, however, to design an effective collaborative process for a massive group. Collaboration engineering (CE) is an approach for the design and deployment of repeatable collaborative work practices that can be executed by practitioners themselves without the ongoing support of external collaboration engineers. To manage the complexity of the design process, they use a modeling technique called facilitation process models (FPM) to capture high-level design decisions that serve different purposes, such as documenting and communicating a design, etc. FPM, however, was developed to support designs for groups of fewer than 100 people. It does not yet represent design elements that become important when designing for groups of hundreds or thousands of participants, which can be found in many OI settings. We use a design science approach to identify the limitations of the original FPM and derive requirements for extending FPM. This article contributes to the CE and to the OI literature by offering an FPM 2.0 that assists CE designers to design new OI processes, with a special focus on outside-in OI.
The Effectiveness of Attention Bias Modification with and without Trans Cranial Direct Current Stimulation in Chronic Low Back Pain

Objective: The present study aimed to compare the effect of ABM (attention bias modification) with and without tDCS (transcranial direct current stimulation) on attention bias, pain intensity, and disability due to pain and pain-related psychological consequences, such as depression, anxiety, and stress. Method : Using convenience sampling, 60 individuals who met the criteria for chronic low back pain (LBP) were selected and randomly assigned in to 2 experimental groups and 2 control and sham-tDCS groups. The experimental ABM group received 5 sessions of the dot-probe task, while the second experimental group received 5 sessions of dot-probe task combined with tDCS. Results: The findings indicated that ABM and ABM+tDCS could reduce attention bias and pain-related psychological consequences significantly, compared to the control and sham groups. Also, attention bias and pain outcomes (depression, anxiety, disability due to pain and pain intensity) remained in ABM+tDCS group than in ABM group in a 1-month follow-up. Conclusion: It was found that tDCS + ABM had no additional effects at the end of intervention, but led to more long-lasting effects in 1-month follow-up. Randomized clinical trial registry number: IRCT20171107037306N1.
S2045796019000386jra 1..7

Aims. Despite the frequency that refugees suffer bereavement, there is a dearth of research into the prevalence and predictors of problematic grief reactions in refugees. To address this gap, this study reports a nationally representative population-based study of refugees to determine the prevalence of probable prolonged grief disorder (PGD) and its associated problems. Methods. This study recruited participants from the Building a New Life in Australia (BNLA) prospective cohort study of refugees admitted to Australia between October 2013 and February 2014. The current data were collected in 2015–2016, and comprised 1767 adults, as well as 411 children of the adult respondents. Adult refugees were assessed for trauma history, post-migration difficulties, probable PGD, post-traumatic stress disorder (PTSD) and mental illness. Children were administered the Strengths and Difficulties Questionnaire. Results. In this cohort, 38.1% of refugees reported bereavement, of whom 15.8% reported probable PGD; this represents 6.0% of the entire cohort. Probable PGD was associated with a greater likelihood of mental illness, probable PTSD, severe mental illness, currently unemployed and reported disability. Children of refugees with probable PGD reported more psychological difficulties than those whose parents did not have probable PGD. Probable PGD was also associated with the history of imprisonment, torture and separation from family. Only 56.3% of refugees with probable PGD had received psychological assistance. Conclusions. Bereavement and probable PGD appear highly prevalent in refugees, and PGD seems to be associated with disability in the refugees and psychological problems in their children. The low rate of access to mental health assistance for these refugees highlights that there is a need to address this issue in refugee populations.
Techniques for Reducing the Connected-Standby Energy Consumption of Mobile Devices

Modern mobile devices, such as smartphones, tablets, and laptops, are idle most of the time but they remain connected to communication channels even when idle. This operation mode is called connected-standby. To increase battery life in the connected-standby mode, a mobile device enters the deepest-runtime-idle-power state (DRIPS), which minimizes power consumption and retains fast wake-up capability. In this work, we identify three sources of energy inefficiency in modern DRIPS designs and introduce three techniques to reduce the power consumption of mobile devices in connected-standby. To our knowledge, this is the first work to explicitly focus on and improve the connected-standby power management of high-performance mobile devices, with evaluations on a real system. We propose the optimized-deepest-runtime-idle-power state (ODRIPS), a mechanism that dynamically: 1) offloads the monitoring of wake-up events to low-power off-chip circuitry, which enables turning off all of the processor's clock sources, 2) offloads all of the processor's input/output functionality off-chip and power-gates the corresponding on-chip input/output functions, and 3) transfers the processor's context to a secure memory region inside DRAM, which eliminates the need to store the context using on-chip high-leakage SRAMs, thereby reducing leakage power. We implement ODRIPS in Intel's Skylake client processor and its associated Sunrise-Point chipset. An analysis of ODRIPS on a real system reveals that it reduces the platform average power consumption in connected-standby mode by 22%. We also identify an opportunity to further reduce ODRIPS power by using emerging low-power non-volatile memory (instead of DRAM) to store the processor context.
Laboratory experiments for diffusion transport processes in fractured chalk

Effective diffusivities of various artificial tracers of 0.59-2.78 E-6 cm2 s"1 for Maastrichtian chalk (Danish), and of 0.919-6.22 E-7 cm2 s"1 for Eocene (Israeli) chalk samples were obtained with the help of through-diffusion experiments. The variations can be explained by Archie's law with a distinct cementation factor for the chalk varieties tested. The Eocene chalk shows small relative diffusivity resulting in an extremely large m value of 3.3 due to its narrow and wide range of pore-throat sizes. The rock capacity factors obtained indicate retardation of pyranine in all chalk samples and batch experiments performed in parallel confirmed the sorptive behaviour of pyranine in chalk.
Development and multicenter validation of a CT-based radiomics signature for discriminating histological grades of pancreatic ductal adenocarcinoma.

Background The histological grade of pancreatic cancer is an important independent predictor of outcome. However, we lack a method for safely and accurately obtaining the pathological grade before surgery. Radiomics has been used to discriminate between histological grades in tumors. We aimed to develop and validate a radiomics signature for the preoperative prediction of histological grades of pancreatic ductal adenocarcinoma (PDAC) that was based on contrast-enhanced computed tomography (CE-CT). Methods This study comprised 301 patients with pathologically confirmed PDAC who were randomly divided into a training (n=151) and test group (n=150). Radiomics features were selected by a support vector machine (SVM) model, and a radiomics signature was generated by the least absolute shrinkage and selection operator (LASSO) model. An additional 100 patients from 2 other medical centers were used for external validation. Receiver operating characteristic (ROC) curve analysis was used to assess the model and to identify the optimal cutoff value. Results The radiomics signatures between high-grade and low-grade PDACs in the training and test groups were significantly different (P<0.05). The areas under the curve (AUCs) of the training and test datasets were 0.961 and 0.910, respectively. The optimal cutoff value of the radiomics score was 0.426. In the external validation dataset, the difference between the radiomics signatures of high-grade versus low-grade PDACs was also significant (P<0.05). The radiomics signature for the external validation data had an AUC of 0.770. Conclusions The CE-CT-based radiomics signature showed moderate predictive accuracy for differentiating low-grade from high-grade PDAC and should become a new noninvasive method for the preoperative prediction of histological grades of PDAC.
How Does Low for Long Impact Credit Risk Premiums?

The Federal Reserve’s experiments in monetary policy related to the Global Financial Crisis lasted longer than any previous easing cycle, giving rise to the question of how does a long-term, low-interest-rate environment affect the pricing of credit risk. We decompose credit default swap (CDS) rates into expected losses and credit risk premia, and show that the level of and firms’ exposure to systematic default risk, controls for mis-measuring expected losses and proxies for CDS market liquidity explain more than 80% of the variation in risk premia across firms and over time. We show that in the zero lower bound period, residual risk premia are lower for high-yield debt compared to investment-grade debt—consistent with a reaching for yield interpretation. Our findings are also consistent with investors demanding compensation for ambiguity aversion related to the end of the low-rate environment, a decrease in the supply of risk capital and higher costs of trading credit risky instruments due to regulatory changes. JEL Classifications: G12, G13, G22, G24
NATIVITY LANGUAGE PREDICTION USING A DOCUMENT WEIGHTED APPROACH

: The task of analyzing an interested text to find demographic characteristics such as gender, age, country and nativity language of an unknown author based on the writing style of the text called Author Profiling. The writing style differences are very important in Author Profiling research. Different researchers proposed several stylistic features to differentiate the writing style of the authors. In this work, the experimentation carried out with content based features like most frequent terms in the corpus to predict the nativity language of the authors. A Profile specific Document Weighted approach is used with most frequent terms as features. In this approach, the document weights are used to represent the document vectors. Various classification algorithms were used to generate the classification model and to predict the nativity language of the authors. The achieved results were good when compared with exiting techniques for nativity language prediction in Author Profiling research area.
Leveling the Playing Field: An Interprofessional Rural Preceptorship Pilot for Students of Nursing and Medicine

Despite the ubiquity of interprofessional education (IPE) in the health sciences, cultural barriers to collaboration and socialization across disciplines are pervasive and persistent. The Interprofessional Rural Preceptorship Pilot (IPRPP) was implemented over 18 months between 2014 and 2015, to deliver mutual, practice-based, collaborative experiences to students of nursing and medicine, and to capitalize on the multidisciplinary team ethos of rural settings in socializing these students into an interprofessional culture. Students; precepting nurses and physicians; unit managers; and faculty supplied qualitative research data through semistructured interviews and focus groups, to help determine the effectiveness of the IPRPP in achieving its ends. Thematic analysis of transcripts, field notes and memos revealed that the pilot: 1) induced all participants to reflect on cultural barriers to IPE, particularly in light of the more experienced, male physicians’ apparent reluctance to buy into the pilot or the research study; 2) sensitized medical students to the scope of practice, roles and knowledge base of registered nurses and nursing students, whom they came to value as collaborators and teachers; and 3) inspired nursing students to take the lead in arranging interprofessional experiences, and to assert their viewpoints as equals within the multidisciplinary team. It was found that liminal (transitional) spaces and the frontline relaxation of traditional hierarchies—both widely acknowledged features of rural health care settings—contributed to these outcomes. The findings show that clinical settings have a significant impact on the interprofessional socialization of nursing and medical students, with implications for the design of future IPE initiatives.
P2P Botnet Detection Based on Traffic Behavior Analysis and Classification

Nowadays, botnets are being considered as the most important security threats in the internet and it is important to find new ways for their detection. Peer to Peer (P2P) botnets are the most important kinds of botnets that use P2P communication protocols to control their bots remotely. Therefore, their detection is more difficult than other botnets. In this paper, we propose a new approach to detect P2P botnets in the command and control (C&C) phase of life cycle based on the analysis of traffic behavior. The proposed approach is able to detect C&C traffic of P2P botnets by using flow-based features and classification methods. The performance of the proposed approach is evaluated based on different parameters. The results of the evaluation show that the proposed approach is able to distinguish P2P botnet from normal network traffic with high detection rate.
Management of tracheal rupture in a pup with n-butyl cyanoacrylate glue - a case report.

A four months old Labrador pup with a dog bite wound on the neck was diagnosed to have rupture of trachea between 5 th and 6 th tracheal ring. The pup was stabilized immediately after its presentation followed by detection of tracheal opening and sealing with N-Butyl Cyanoacrylate (surgicloz). Treatment was followed by Antibiotic and supportive therapy which yielded a good recovery in the case without any complications. The clinical symptomology, management and clinical outcome of the case were discussed.