Miracle-dz/UniFAR-FTUs huggingface dataset:
From strength to strength: An educational research journey using a Strengths Approach

Abstract Literature on the use of The Strengths Approach (McCashen, 2005) in social services, notes that this approach has potential for education that is still to be recognised. In this discussion paper, I explore that potential by both examining the literature about strengths based frameworks and by outlining an associated research project with Early Childhood pre-service teachers. I outline the context in which I used the literature to develop a strengths-approach module to teach students about child protection within a core Early Childhood education subject. I also discuss the research methodology developed using a strengths-approach to explore student responses to the issue of child protection. Preliminary findings from the literature and the associated development of the research project indicate a strengths-approach to pre-service child protection training could provide a positive alternative, or addition to, the traditionally used, adjunct, child protection workshop. I argue, that, to counter the anxiety reported by teachers when dealing with child protection issues, an extended Strengths Approach could assist by preparing pre-service teachers to connect with and understand protection issues. By examining their own and others’ perspectives of childprotection, pre-service teachers can examine their demanding child-protection roles in depth. The Strengths Approach allows developing practitioners to build on their understandings by identifying and using their strengths to formulate positive teaching strategies. Additionally, an unexpected finding of developing this research project was that it provided a unique opportunity to design and use collaborative, strengths-based techniques for working in a more authentic way with the research participants/pre-service teachers.
Maximum-Likelihood Estimation of Site-Specific Mutation Rates in Human Mitochondrial DNA From Partial Phylogenetic Classification

The mitochondrial DNA hypervariable segment I (HVS-I) is widely used in studies of human evolutionary genetics, and therefore accurate estimates of mutation rates among nucleotide sites in this region are essential. We have developed a novel maximum-likelihood methodology for estimating site-specific mutation rates from partial phylogenetic information, such as haplogroup association. The resulting estimation problem is a generalized linear model, with a nonstandard link function. We develop inference and bias correction tools for our estimates and a hypothesis-testing approach for site independence. We demonstrate our methodology using 16,609 HVS-I samples from the Genographic Project. Our results suggest that mutation rates among nucleotide sites in HVS-I are highly variable. The 16,400–16,500 region exhibits significantly lower rates compared to other regions, suggesting potential functional constraints. Several loci identified in the literature as possible termination-associated sequences (TAS) do not yield statistically slower rates than the rest of HVS-I, casting doubt on their functional importance. Our tests do not reject the null hypothesis of independent mutation rates among nucleotide sites, supporting the use of site-independence assumption for analyzing HVS-I. Potential extensions of our methodology include its application to estimation of mutation rates in other genetic regions, like Y chromosome short tandem repeats.
Associations between Schistosomiasis and the Use of Human Waste as an Agricultural Fertilizer in China

Background Human waste is used as an agricultural fertilizer in China and elsewhere. Because the eggs of many helminth species can survive in environmental media, reuse of untreated or partially treated human waste, commonly called night soil, may promote transmission of human helminthiases. Methodology/Principal Findings We conducted an open cohort study in 36 villages to evaluate the association between night soil use and schistosomiasis in a region of China where schistosomiasis has reemerged and persisted despite control activities. We tested 2,005 residents for Schistosoma japonicum infection in 2007 and 1,365 residents in 2010 and interviewed heads of household about agricultural practices each study year. We used an intervention attributable ratio framework to estimate the association between night soil use and S. japonicum infection. Night soil use was reported by half of households (56% in 2007 and 46% in 2010). Village night soil use was strongly associated with human S. japonicum infection in 2007. We estimate cessation of night soil use would lead to a 49% reduction in infection prevalence in 2007 (95% CI: 12%, 71%). However, no association between night soil and schistosomiasis was observed in 2010. These inconsistent findings may be due to unmeasured confounding or temporal shifts in the importance of different sources of S. japonicum eggs on the margins of disease elimination. Conclusions/Significance The use of untreated or partially treated human waste as an agricultural fertilizer may be a barrier to permanent reductions in human helminthiases. This practice warrants further attention by the public health community.
Robust localization against outliers in wireless sensor networks

In wireless sensor networks, a critical system service is the localization service that determines the locations of geographically distributed sensor nodes. The raw data used by this service are the distance measurements between neighboring nodes and the position knowledge of anchor nodes. However, these raw data may contain outliers that strongly deviate from their true values, which include both the outlier distances and the outlier anchors. These outliers can severely degrade the accuracy of the localization service. Therefore, we need a robust localization algorithm that can reject these outliers. Previous studies in this field mainly focus on enhancing multilateration with outlier rejection ability, since multilateration is a primitive operation used by localization service. But patch merging, a powerful operation for increasing the percentage of localizable nodes in sparse networks, is almost neglected. We thus propose a robust patch merging operation that can reject outliers for both multilateration and patch merging. Based on this operation, we further propose a robust network localization algorithm called RobustLoc. This algorithm makes two major contributions. (1) RobustLoc can achieve a high percentage of localizable nodes in both dense and sparse networks. In contrast, previous methods based on robust multilateration almost always fail in sparse networks with average degrees between 5 and 7. Our experiments show that RobustLoc can localize about 90% of nodes in a sparse network with 5.5 degrees. (2) As far as we know, RobustLoc is the first to uncover the differences between outlier distances and outlier anchors. Our simulations show that RobustLoc can reject colluding outlier anchors reliably in both convex and concave networks.
Employer-on-employee violence : type V workplace violence

The objective of this research is to present Type V workplace violence as an additional typology to the existing four types of workplace violence, namely Type I (stranger), Type II (client/customer), Type III (worker) and Type IV (relationship). This research focused on employers as perpetrators of Type V workplace violence. Type V workplace violence is defined as any form of soft or extreme physical or non-physical violence committed by an employer, which directly or indirectly affects his or her employee or employees in a negative way. Type V workplace violence occurs more often in workplaces that are private and far removed from public scrutiny. Farming and domestic workplaces in South Africa are cited in this research as typical examples of Type V workplace violence localities. The research concludes that Type V workplace violence is a reality that researchers cannot ignore.
Exemplar: EXEcutable exaMPLes ARchive

Searching for applications that are highly relevant to development tasks is challenging because the high-level intent reflected in the descriptions of these tasks doesn't usually match the low-level implementation details of applications. In this demo we show a novel code search engine called Exemplar (EXEcutable exaMPLes ARchive) to bridge this mismatch. Exemplar takes natural-language query that contains high-level concepts (e.g., MIME, data sets) as input, then uses information retrieval and program analysis techniques to retrieve applications that implement these concepts.
How to Best Name a Place? Facilitation and Inhibition of Route Learning Due to Descriptive and Arbitrary Location Labels

Establishing verbal memory traces for non-verbal stimuli was reported to facilitate or inhibit memory for the non-verbal stimuli. We show that these effects are also observed in a domain not indicated before—wayfinding. Fifty-three participants followed a guided route in a virtual environment. They were asked to remember half of the intersections by relying on the visual impression only. At the other 50% of the intersections, participants additionally heard a place name, which they were asked to memorize. For testing, participants were teleported to the intersections and were asked to indicate the subsequent direction of the learned route. In Experiment 1, intersections' names were arbitrary (i.e., not related to the visual impression). Here, participants performed more accurately at unnamed intersections. In Experiment 2, intersections' names were descriptive and participants' route memory was more accurate at named intersections. Results have implications for naming places in a city and for wayfinding aids.
Dielectric response of nanoscopic spherical colloids in alternating electric fields: a dissipative particle dynamics simulation

We study the response of single nanosized spherical colloids in electrolyte solution to an alternating electric field (AC field) by computer simulations. We use a coarse-grained mesoscopic simulation approach that accounts in full for hydrodynamic and electrostatic interactions as well as for thermal fluctuations. The solvent is modeled as a fluid of single dissipative particle dynamics (DPD) beads, and the colloidal particle is modeled as a rigid body made of DPD beads. We compute the mobility and the polarizability of a single colloid and investigate systematically the effect of amplitude and frequency of the AC fields. Even though the thickness of the Debye layer is not ‘thin’ compared to the radius of the colloid, and the thermal fluctuations are significant, the results are in good agreement with the theoretical prediction of the Maxwell–Wagner–O’Konski theory, especially for uncharged colloids.
Implementation Science, Professional Development, and Autism Spectrum Disorders

The increased prevalence of autism spectrum disorders (ASD) has intensified the need for high-quality special education services designed for children and youth with ASD and their families. Implementation science provides guidance for moving innovation, such as utilizing evidence-based practices for students with ASD, into regular practice in schools. The National Professional Development Center on ASD (NPDC) incorporated the principles of implementation science, the scientific knowledge about evidence-based practices, and the measurement of program quality into an intervention approach for students with ASD. This article presents the NPDC model as an example of using implementation science to build systems of professional development that increase the quality of services and promote teachers' use of evidence-based practices.
Design of adaptive block backstepping controllers for uncertain nonlinear dynamic systems with n blocks

Based on the Lyapunov stability theorem, a design methodology of adaptive block backstepping control is proposed in this article for a class of multi-input systems with matched and mismatched perturbations to solve regulation problems. The systems to be controlled contain n blocks' dynamic equations, hence n − 1 virtual input controllers are firstly designed so that the state variables of first n − 1 blocks are asymptotically stable if each virtual control input is equal to the state variable of next block. Then the control input is designed in the last nth block to ensure asymptotic stability for the whole state variables even if the perturbations exist. In addition, adaptive mechanisms are embedded in each virtual input function and control input, so that the upper bound of perturbations is not required to be known beforehand. Finally, a numerical example is given for demonstrating the feasibility of the proposed control scheme.
Cellular Binding Mechanism on Rat Macrophages for Sialylated Glycoconjugates, Inhibited by the Monoclonal Antibody ED3

The mAb ED3 recognizes a subpopulation of rat macrophages, with a highly restricted tissue distribution. The tissue distribution as well as the in vitro expression of the ED3 antigen and of the sheep erythrocyte receptor (SER), binding unopsonized erythrocytes in the mouse, are very similar. This receptor has almost the same binding characteristics, although a different tissue distribution, as the sialic acid binding receptor (SAR), binding ganglioside‐coated erythrocytes in the rat In this study we summarize the available literature concerning these sialic acid binding receptors (SER and SAR). Furthermore we have identified ED3 as SER by inhibition studies of erythrocyte binding with mAb ED3, as well as by the newly developed equivalents ED16 and ED17. We also show that light trypsin treatment of alveolar macrophages, expressing SAR, results in SER‐like activity. This obtained SER‐like activity could not be blocked by the mAb ED3, indicating that SER and SAR are different receptors. It appears that rat macrophages can express two receptors for sialylated glycoconjugates, a high‐affinity receptor SER, recognized by mAb ED3, and a low‐affinity receptor SAR, not recognized by mAb ED3.
Longitudinal control strategy for a class of vehicles following systems based on random factor with delays

Considering time delays factors and random factors, the stability and control strategy for a class of stochastic vehicle following systems with delays are studied. By applying vector Lyapunov function method, sufficient conditions for exponential stability of the system are obtained. Based on the random vehicles longitudinal dynamics model, which is established by stochastic differential equation, the controller for the system is designed by sliding mode control method. According to the obtained results, the system stability is researched. Finally, simulation experiments are given to illustrate the obtained control strategy. Simulation results showed that in less than 5s, the accelerations and the speeds of the following vehicles converge to the leading vehicle, and the vehicle spacing errors approached to less than 0.05 m.
Yale University Department of Computer Science Similarity Detection via Random Subsets for Cyber War Protection in Big Data using Hadoop Framework

The increasing volume of Internet traffic to be analyzed imposes new challenges for anomaly detection systems. These systems should efficiently analyze a large amount of data to discover anomalous fragments within a reasonable response time. In this work, we propose a method for anomaly detection such as intrusion attacks in networking data, based on a parallel similarity detection algorithm that uses the MapReduce methodology implemented on an Hadoop platform. The proposed system processes large amount of data on a commodity hardware. The experimental results on the 2009 DARPA database demonstrate that the proposed system scales very well when data sizes increase. List of Abbreviations SDA Similarity Detection Algorithm IDS Intrusion Detection System MDP Multidimensional Data Point EMDP Embedded Multidimensional Data Point HDFS Hadoop Distributed File Systems DoS Denial of Service DDoS Distributed Denial of Service DM Diffusion Maps HTCondor High-Throughput Computing Condor DNS Domain Name System TCP Transmission Control Protocol UDP User Datagram Protocol IP Internet Protocol ICMP Internet Control Message Protocol LLC Logical Link Control ARP Address Resolution Protocol RM ResourceManager NM NodeManager AM ApplicationMaster
Intermittent Exposure to Xenon Protects against Gentamicin-Induced Nephrotoxicity

Aminoglycoside antibiotics, especially gentamicin, are widely used to treat Gram-negative infections due to their efficacy and low cost. Nevertheless the use of gentamicin is limited by its major side effect, nephrotoxicity. Xenon (Xe) provided substantial organoprotective effects in acute injury of the brain and the heart and protected against renal ischemic-reperfusion injury. In this study, we investigated whether xenon could protect against gentamicin-induced nephrotoxicity. Male Wistar rats were intermittently exposed to either 70% xenon or 70% nitrogen (N2) balanced with 30% oxygen before and during gentamicin administration at a dose of 100 mg/kg for 7 days to model gentamicin-induced kidney injury. We observed that intermittent exposure to Xe provided morphological and functional renoprotection, which was characterized by attenuation of renal tubular damage, apoptosis, and oxidative stress, but not a reduction in inflammation. We also found that Xe pretreatment upregulated hypoxia-inducible factor 2α (HIF-2α) and its downstream effector vascular endothelial growth factor, but not HIF-1α. With regard to the three HIF prolyl hydroxylases, Xe pretreatment upregulated prolyl hydroxylase domain-containing protein-2 (PHD2), suppressed PHD1, and had no influence on PHD3 in the rat kidneys. Pretreatment with Xe also increased the expression of miR-21, a microRNA known to have anti-apoptotic effects. These results support Xe renoprotection against gentamicin-induced nephrotoxicity.
Perceptions and impact of plain packaging of tobacco products in low and middle income countries, middle to upper income countries and low-income settings in high-income countries: a systematic review of the literature

Objective To review the current literature around the potential impact, effectiveness and perceptions of plain packaging in low income settings. Method A systematic review of the literature. Data sources 9 databases (PubMed, Global Health, Social Policy and Practice, Applied Social Sciences Index and Abstracts (ASSIA), CINAHL, PsycINFO, British Library for Development Studies (BLDS), Global Health Library and Scopus) were searched. The terms used for searching combined terms for smoking and tobacco use with terms for plain packaging. Study selection Studies investigating the impact of plain packaging on the determinants of tobacco use, such as smoking behaviour, appeal, prominence, effectiveness of health warnings, response to plain packs, attitudes towards quitting or likelihood of smoking in low-income settings, were identified. Studies must have been published in English and be original research of any level of rigour. Data extraction Two independent reviewers assessed studies for inclusion and extracted data. Data synthesis The results were synthesised qualitatively, with themes grouped under four key headings: appeal and attractiveness; salience of health warnings and perceptions of harm; enjoyment and perceived taste ratings; and perceptions of the impact on tobacco usage behaviour. Results This review has identified four articles that met the inclusion criteria. Studies identified that tobacco products in plain packaging had less appeal than in branded packaging in low-income settings. Conclusions This review indicates that plain packaging appears to be successful in reducing appeal of smoking and packets, and supports the call for plain packaging to be widely implemented in conjunction with other tobacco control policies. However, there are considerable gaps in the amount of research conducted outside high-income countries.
A Design Support System for Kaga-Yuzen Kimono Pattern by Means of L-System

This paper proposes a support tool for designing kimono patterns. Kimono patterns are controlled by two rules, "flow" and "hierarchy"; the rule of "flow" controls the pattern arrangement, and the rule of "layered structure" manages the layer structure of pattern. The proposed system supports design of kimono patterns, considering these two rules. The system also applies L-System to express ornamental patterns of plants to appear in kimonos semi-automatically. It is possible for people who do not have good design skills to obtain an intended kimono pattern easily by using this system.
Unsupervised detection of non-stationary segments based on single-basis non-negative matrix factorization for effective annotation

We propose novel methods for automatically detecting non-stationary segments using non-negative matrix factorization (NMF) with aiming to effective sound annotation. For acoustic event detection or acoustic scene analysis, preparing a sufficient amount of training data is important. However, listening to all recorded signals and annotating them are very time-consuming. Assuming that the observed acoustic signal consists of a single stationary background sound and various short acoustic events, we apply NMF with single spectral basis for the spectrogram of the observed signal. Since it is expected that stationary background sound is well represented by NMF, the residual divergence is a good measure to detect non-stationary sound. Through experiments on nine real-world recordings of outside environmental sounds, we show that our methods effectively detect a variety of non-stationary sound segments.
Large-scale Multitask Learning for Machine Translation Quality Estimation

Multitask learning has been proven a useful technique in a number of Natural Language Processing applications where data is scarce and naturally diverse. Examples include learning from data of different domains and learning from labels provided by multiple annotators. Tasks in these scenarios would be the domains or the annotators. When faced with limited data for each task, a framework for the learning of tasks in parallel while using a shared representation is clearly helpful: what is learned for a given task can be transferred to other tasks while the peculiarities of each task are still modelled. Focusing on machine translation quality estimation as application, in this paper we show that multitask learning is also useful in cases where data is abundant. Based on two large-scale datasets, we explore models with multiple annotators and multiple languages and show that state-of-the-art multitask learning algorithms lead to improved re-sults in all settings.
Cardiac output during cardiopulmonary resuscitation at various compression rates and durations.

Cardiac output during cardiopulmonary resuscitation (CPR) was measured by a modified indicator-dilution technique in 20 anesthetized dogs (6-12 kg), during repeated 1- to 2-min episodes of electrically induced ventricular fibrillation, by a mechanical chest compressor and ventilator. With compression rates from 20 to 140/min and compression durations (duty cycles) from 10 to 90% of cycle time, cardiac output (CO) was predicted by the equation: CO = CR . SVmax . [DC/(k1 . CR + DC)] . [(1 -- DC)/k2 . CR + 1 - DC)], where CR is compression rate, DC is duty cycle, SVmax (19 ml) is the effective capacity of the pumping chamber, and k1 (0.00207 min) and k2 (0.00707 min) are ejection and filling constants. This expression predicts maximal CO for DC = 0.40 and cR = 126/min and 90-100% of maximal CO for 0.3 less than DC less than 0.5 and 70 less than CR less than 150/min. Such mathematical analysis may prove useful in the optimization of CPR.