Miracle-dz/UniFAR-FTUs huggingface dataset:
The Limpopo Non-Metropolitan Drinking Water Supplier Response to a Diagnostic Tool for Technical Compliance

Water services providers should supply water that is fit for human consumption, taking into account multi-barrier approaches and technical aspects such as design aspects, operation monitoring, final water quality compliance monitoring, plant monitoring practices, maintenance, and risk management practices. Against this background, this study focused on applying the diagnostic tool for technical compliance as well as assessing the compliance of water treatment plants with management norms. Six plants in the Vhembe District Municipality were selected; the Vondo, Malamulele, Mutshedzi, and Mutale plants (conventional), and the Dzingahe and Tshedza package plants. During the first assessment, four (Malamulele, Mutshedzi, Mutale and Dzingahe) plants scored between 44% and 49% and achieved Class 3 certification, revealing serious challenges requiring immediate intervention. Two water plants (Vondo and Tshedza, scoring 53% and 63%, respectively) were in the Class 2 category, revealing serious challenges requiring attention and improvement. During the second assessment, all plants scored between 63% and 87% (Class 2 category). The greatest improvement (30%) was noted for the Dzingahe and Tshedza plants, followed by the Malamulele plant, while the Mutale, Vondo, and Mutshedzi plants improved their scores by 20%, 17% and 14%, respectively. After corrective actions and re-measurement, no plant complied. It is recommended that Water Services Providers (WSPs) regularly apply the diagnostic tools and water safety plans as developed in order to comply with applicable standards.
Fast point cloud compression via reversible cellular automata block transform

Augmented and mixed reality applications require efficient tools permitting the compression and the visualization of 3D object at a limited computational cost. To this purpose, 3D point cloud representations have been widely used, together with an octree-based hierarchical organization of data that enables a multi-resolution visualization. This paper presents a voxel coding strategy based on a hierarchical Cellular Automata block reversible transform which permits obtaining a multi-resolution representation of the input volume and a higher compression gain with respect to the state-of-the-art octree strategies. The proposed solution also proves to be more flexible in defining multiple layers and more effective in preserving 3D volume quality when the stream is partially decoded.
Clinical Aspects of Dental Materials

Part 1 Fundamental perspectives: introduction materials science and dentistry physical and mechanical properties of dental materials adhesive materials direct polymeric restorative materials amalgam and other direct metallic restorative materials dental cements impression materials gypsum material, James Overberger materials for fixed indirect restorations and prostheses removable prostheses and acrylic resins radiographic appearance of dental tissues and materials, Joan Gibson-Howell polishing materials and abrasion clinical detection and management of dental restorative materials during scaling and polishing dental implants specialty materials tooth bleaching, William Howard oral appliances, Christine Nathe care and maintenance of instruments general rules for handling dental materials infection control and safety in the dental office, Carol Spear, Linda Bagby. Part 2 Laboratory and clinical applications: pit and fissure sealants amalgam finishing and polishing, Meg Zayan mixing liners, bases, and cements taking alginate impressions, Jacqueline Harper fabrication of a custom impression tray elastomeric impressions (addition silicones) fabrication and trimming of study models, Joan Gibson-Howell vital tooth bleaching - patient-applied, professionally supervised clinical and laboratory procedures, william Howard disinfection of impressions, dentures, and other appliances and materials, Carol Spear.
Assessment of an underwater biopsy probe for collecting teleost fish tissue samples

This study tested the efficiency of an underwater biopsy probe designed to remove tissue samples for molecular analysis from small- to medium-sized (15 to 70 cm) marine teleost fish in the field. The probe was fired at lower and higher power from a 76 cm rubber-propelled spear gun. Two species were targeted: Plectropomus maculatus and Lutjanus carponotatus. The results were highly successful for P. maculatus, with >80% of hits at lower and higher power resulting in sufficient tissue extraction for molecular analysis. The results were less consistent for L. carponotatus at lower power (45%) due to the relatively large scales of the fish. At higher power the success rate increased to 73%. In 97% of cases, fish swam away rapidly with only minor lesions and showing no signs of incapacitation. Furthermore, aquarium trials showed no post-impact mortality after a 2 wk period. Therefore, the biopsy probe tested in this study is considered successful when the spear gun is fired at the correct power for the target species. This will allow for easier tissue sample collection from small- to medium-sized teleost fish for population and phylogenetic studies than previous methods of killing or capturing individuals.
Deconvoluting heme biosynthesis to target blood-stage malaria parasites

Heme metabolism is central to blood-stage infection by the malaria parasite Plasmodium falciparum. Parasites retain a heme biosynthesis pathway but do not require its activity during infection of heme-rich erythrocytes, where they can scavenge host heme to meet metabolic needs. Nevertheless, heme biosynthesis in parasite-infected erythrocytes can be potently stimulated by exogenous 5-aminolevulinic acid (ALA), resulting in accumulation of the phototoxic intermediate protoporphyrin IX (PPIX). Here we use photodynamic imaging, mass spectrometry, parasite gene disruption, and chemical probes to reveal that vestigial host enzymes in the cytoplasm of Plasmodium-infected erythrocytes contribute to ALA-stimulated heme biosynthesis and that ALA uptake depends on parasite-established permeability pathways. We show that PPIX accumulation in infected erythrocytes can be harnessed for antimalarial chemotherapy using luminol-based chemiluminescence and combinatorial stimulation by low-dose artemisinin to photoactivate PPIX to produce cytotoxic reactive oxygen. This photodynamic strategy has the advantage of exploiting host enzymes refractory to resistance-conferring mutations. DOI: http://dx.doi. org/10.7554/eLife.09143. 001
Estimating time series models by state space methods in Python-Statsmodels

This paper describes an object oriented approach to the estimation of time series models using state space methods and presents an implementation in the Python programming language. This approach at once allows for fast computation, a variety of out-of-the-box features, and easy extensibility. We show how to construct a custom state space model, retrieve filtered and smoothed estimates of the unobserved state, and perform parameter estimation using classical and Bayesian methods. The mapping from theory to implementation is presented explicitly and is illustrated at each step by the development of three example models: an ARMA(1,1) model, the local level model, and a simple real business cycle macroeconomic model. Finally, four fully implemented time series models are presented: SARIMAX, VARMAX, unobserved components, and dynamic factor models. These models can immediately be applied by users. * I thank Josef Perktold for many helpful discussions. Financial support from the Google Summer of Code program and the University of Oregon Kleinsorge Fellowship, Department of Economics, is gratefully acknowledged.
Tree patterns with full text search

Tree patterns with full text search form the core of both XQuery Full Text and the NEXI query language. On such queries, users expect a relevance-ranked list of XML elements as an answer. But this requirement may lead to undesirable behavior of XML retrieval systems: two queries which are intuitively (e.g., without ranking) equivalent return differently ordered lists of elements. We show that the best performing XML retrieval semantics has this behavior. We also show how minimization of tree patterns can efficiently solve this problem.
Earth Mover's Distance based Similarity Search at Scale

Earth Mover's Distance (EMD), as a similarity measure, has received a lot of attention in the fields of multimedia and probabilistic databases, computer vision, image retrieval, machine learning, etc. EMD on multidimensional histograms provides better distinguishability between the objects approximated by the histograms (e.g., images), compared to classic measures like Euclidean distance. Despite its usefulness, EMD has a high computational cost; therefore, a number of effective filtering methods have been proposed, to reduce the pairs of histograms for which the exact EMD has to be computed, during similarity search. Still, EMD calculations in the refinement step remain the bottleneck of the whole similarity search process. In this paper, we focus on optimizing the refinement phase of EMD-based similarity search by (i) adapting an efficient min-cost flow algorithm (SIA) for EMD computation, (ii) proposing a dynamic distance bound, which can be used to terminate an EMD refinement early, and (iii) proposing a dynamic refinement order for the candidates which, paired with a concurrent EMD refinement strategy, reduces the amount of needless computations. Our proposed techniques are orthogonal to and can be easily integrated with the state-of-the-art filtering techniques, reducing the cost of EMD-based similarity queries by orders of magnitude.
Properties and selection : irons, steels, and high-performance alloys

A comprehensive guide to compositions, properties, performance, and selection of cast irons, carbon and low-alloy steels, tool steels, stainless steels, and superalloys. Contains 1,328 illustrations (photographs, charts, and graphs). More than 500 tables provide extensive data for alloy designations, compositions, and mechanical and physical properties. This handbook is the best single-volume reference work on the properties and selection of ferrous metals and alloys. It features contributions from more than 200 technical experts.
Ethylene and Auxin Control the Arabidopsis Response to Decreased Light Intensity1

Morphological responses of plants to shading have long been studied as a function of light quality, in particular the ratio of red to far red light that affects phytochrome activity. However, changes in light quantity are also expected to be important for the shading response because plants have to adapt to the reduction in overall energy input. Here, we present data on the involvement of auxin and ethylene in the response to low light intensities. Decreased light intensities coincided with increased ethylene production in Arabidopsis rosettes. This response was rapid because the plants reacted within minutes. In addition, ethylene- and auxin-insensitive mutants are impaired in their reaction to shading, which is reflected by a defect in leaf elevation and an aberrant leaf biomass allocation. On the molecular level, several auxin-inducible genes are up-regulated in wild-type Arabidopsis in response to a reduction in light intensity, including the primary auxin response gene IAA3 and a protein with similarity to AUX22 and the 1-aminocyclopropane-1-carboxylic acid synthase genes ACS6, ACS8, and ACS9 that are involved in ethylene biosynthesis. Taken together, the data show that ethylene and auxin signaling are required for the response to low light intensities.
Enhancing faecal sludge dewaterability and end-use by conditioning with sawdust and charcoal dust

ABSTRACT Faecal sludge (FS) treatment in urban slums of low-income countries of sub-Saharan Africa is poor or non-existent. FS contains over 90% water and therefore dewatering it within slums decreases transport costs, facilitates local treatment and end-use. This study was designed to enhance the dewatering efficiency of FS, using two locally available physical conditioners (sawdust and charcoal dust), each applied at dosages of 0%, 25%, 50%, 75%, 100% and 125% TS. The optimum dosage for both conditioners occurred at 50% and 75% for cake moisture content and capillary suction time, respectively. The dewatering rate improved by 14.3% and 15.8%, whereas dewatering extent (% cake solids) improved by 22.9% and 35.7%, for sawdust and charcoal dust, respectively. The dewatering in FS conditioned with sawdust and charcoal dust was mainly governed by absorption and permeation (porosity), respectively. The FS calorific value improved (from 11.4 MJ kg−1) by 42% and 49% with 50% TS dosage of sawdust and charcoal dust, respectively. The FS structure also became porous after dewatering which hastens the subsequent drying and/or composting processes. Due to comparable performance in dewatering, sawdust or charcoal dust, whichever is locally available, is recommended to treat FS in low-income urban slum settlements.
Pre-Processing of English-Hindi Corpus for Statistical Machine Translation

Corpus may be considered as fuel for the data driven approaches of machine translation. Parallel corpus building is a labour intensive task, which makes it a costly and scarce resource. Full potential of available data needs to be exploited and this can be ensured by removing different types of inconsistencies as being faced throughout the NLP domain. The paper presented here describes the experiments carried out on corpus text pre-processing for building the baseline Statistical Machine Translation (SMT) system. Text pre-processing performed here is classified in two stages – i. the first one relates to handling of orthographic representation of content and ii. the second stage relates to handling of non-lexical words. The first stage covers punctuation symbols, casing, word spellings and their normalization while second stage covers handling of numbers and named entities (NEs) applied on the best settings observed in first stage. The motivation behind performing these experiments was to derive a relationship and gauge the extent of pre-processing the corpus, thereby building a considerably optimized baseline SMT system. This baseline system would provide platform for performing further experiments with different syntactic and semantic factors in future. The findings presented here is for English-Hindi language pair, however, the concept of pre-processing is language neutral and can be transcended to any other language pair. The best performance is reported with retaining the punctuation symbols, lower-cased English corpus and spell normalized Hindi corpus for English to Hindi translation. Further to these, in the second stage of experiments, handling numbers and Named Entities have been described wherein these are mapped to unique class labels. The impact of these experiments have been explained with their appropriateness for the concerned language pair.
Polyaniline-stabilized electromagnetic wave absorption composites of reduced graphene oxide on magnetic carbon nanotube film

A multi-layered composite with exceptionally high electromagnetic wave-absorbing capacity and performance stability was fabricated via the facile electrophoresis of a reduced graphene oxide network on carbon nanotube (CNT)-Fe3O4-polyaniline (PANI) film. Minimum reflection loss (RL) of −53.2 dB and absorbing bandwidth of 5.87 GHz (< −10 dB) are achieved, surpassing most recently reported CNT- and graphene-based absorbers. In particular, comparing to the original composites, the minimum RL and bandwidth (< −10 dB) maintains 82.5% and 99.7%, respectively, after 20 h charge/discharge cycling, demonstrating high environmental suitability.
Loading of a Rb magneto-optic trap from a getter source

We study the properties of a Rb magneto-optic trap loaded from a commercial getter source. The source provides a large flux of atoms for the trap along with the capability of rapid turn off necessary for obtaining long trap lifetimes. We have studied the trap loading at two different values of background pressure to determine the cross section for Rb-N2 collisions to be 3.5(4)310214 cm2 and that for Rb-Rb collisions to be of order 3310213 cm2. At a background pressure of 1.331029 torr, we load more than 108 atoms into the trap with a time constant of 3.3 s. The 1/e lifetime of trapped atoms is 13 s limited only by background collisions.
EDGE2VEC: Edge Representations for Large-Scale Scalable Hierarchical Learning

In present front-line of Big Data, prediction tasks over the nodes and edges in complex deep architecture needs a careful representation of features by assigning hundreds of thousands, or even millions of labels and samples for information access system, especially for hierarchical extreme multi-label classiﬁcation. We introduce edge2vec, an edge representations framework for learning discrete and continuous features of edges in deep architecture. In edge2vec, we learn a mapping of edges associated with nodes where random samples are augmented by statistical and semantic representations of words and documents. We argue that infusing semantic representations of features for edges by exploiting word2vec and para2vec is the key to learningricherrepresentationsforexploringtargetnodes or labels in the hierarchy. Moreover, we design and implement a balanced stochastic dual coordinate ascent (DCA)-based support vector machine for speeding up training. We introduce a global decision-based top-down walks instead of random walks to predict the most likelihood labels in the deep architecture. We judge the efﬁciency of edge2vec over the existing state-of-the-art techniques on extreme multi-label hierarchical as well as ﬂat classiﬁcation tasks. The empirical results show that edge2vec is very promising and computationally very efﬁcient in fast learning and predicting tasks. In deep learning workbench, edge2vec represents a new direction for statistical and semantic representations of features in task-independent networks.
Dual role of BMP signaling in the regulation of Drosophila intestinal stem cell self-renewal

ABSTRACT Many adult organs including Drosophila adult midguts rely on resident stem cells to replenish damaged cells during tissue homeostasis and regeneration. Previous studies have shown that, upon injury, intestinal stem cells (ISCs) in the midguts can increase proliferation and lineage differentiation to meet the demand for tissue repair. Our recent study has demonstrated that, in response to certain injury, midguts can expand ISC population size as an additional regenerative mechanism. We found that injury elicited by bleomycin feeding or bacterial infection increased the production of two BMP ligands (Dpp and Gbb) in enterocytes (ECs), leading to elevated BMP signaling in progenitor cells that drove an expansion of ISCs by promoting their symmetric self-renewing division. Interestingly, we also found that BMP signaling in ECs inhibits the production of Dpp and Gbb, and that this negative feedback mechanism is required to reset ISC pool size to the homeostatic state. Our findings suggest that BMP signaling exerts two opposing influences on stem cell activity depending on where it acts: BMP signaling in progenitor cells promotes ISC self-renewal while BMP signaling in ECs restricts ISC self-renewal by preventing excessive production of BMP ligands. Our results further suggest that transient expansion of ISC population in conjunction with increasing ISC proliferation provides a more effective strategy for tissue regeneration.
The Impact of AP Computer Science Principles: Are You Ready to Change Your Undergraduate Courses?

1.SUMMARY In the last few years, there has been a groundswell of programs to support more and better computer science (CS) education in K-12. A large number of organizations and institutions including ACM, Code.org, CSTA and the National Science Foundation (NSF) have worked to make CS more available and engaging and in this way increase the CS into post-secondary CS programs. NSF's CS10K initiative, for example, aimed to “have rigorous, academic curricula incorporated into computing courses in 10,000 high schools, taught by 10,000 well-trained teachers” [3]. These initiatives have energized the education world and have resulted in sweeping changes in the way that computing is being taught at in K-12. Examples include the College Board’s CS Principles Course [1], the Beauty and Joy of Computing [2,4], UTeach CS Principles [5, 41], and Mobile CSP [6, 7].
Demonstrating sensemaking emergence in artificial agents: A method and an example

We propose an experimental method to study the possible emergence of sensemaking in artificial agents. This method involves analyzing the agent's behavior in a test bed environment that presents regularities in the possibilities of interaction afforded to the agent, while the agent has no presuppositions about the underlying functioning of the environment that explains such regularities. We propose a particular environment that permits such an experiment, called the Small Loop Problem. We argue that the agent's behavior demonstrates sensemaking if the agent learns to exploit regularities of interaction to fulfill its self-motivation as if it understood (at least partially) the underlying functioning of the environment. As a corollary, we argue that sensemaking and self-motivation come together. We propose a new method to generate self-motivation in an artificial agent called interactional motivation. An interactionally motivated agent seeks to perform interactions with predefined positive values and avoid interactions with predefined negative values. We applied the proposed sensemaking emergence demonstration method to an agent implemented previously, and produced example reports that suggest that this agent is capable of a rudimentary form of sensemaking.