Miracle-dz/UniFAR-FTUs huggingface dataset:
INFLUENCE OF SOCIALIZATION ON ACADEMIC PERFORMANCE OF LEARNERS WITH HEARING IMPAIRMENT AT INCLUSIVE PRIMARY SCHOOLS IN KENYA: A CASE IN THAWABU PRIMARY OF NAIROBI CITY COUNTY

Purpose: This research aimed at determining the influence of socialization on performance of learners with hearing impairment at Thawabu Inclusive Public Primary School in Nairobi, Kenya. The objectives were to; establish modes of communication that promote socialization in an inclusive environment; establish strategies for boosting socialization to enhance academic performance; and establish challenges facing teachers in enhancing socialization to improve academic performance of learners with hearing impairment. Methodology: The research design was a case study design. Structured questionnaires and interviews were used to collect data. Purposive sampling was employed to select the school and learners with hearing impairment while hearing learners were randomly selected. Findings: The study found that: modes of communication among learners with hearing impairment, hearing learners and teachers create social and educational change for improvement of academic standards in the school and narrows the gap between those with hearing impairment and their hearing counterparts. Strategies like family support program (assisting children and families in language learning), family-infant-toddler program, and competent and consistent administration system promote learning. Socialization influences incidental learning of learners with hearing impairment to put them at par with their hearing peers on matters related to both academic performance and social advancement. Socialization makes learners with hearing impairment comfortable, self-esteemed, and self-actualized, hence improving educational performance. Unique contribution to theory, practice and policy: The study may help to promote attitudinal, psychological and educational change in all stakeholders for inclusive education to be a success and meaningful to learners with hearing impairment. The study recommends that the government should add specially qualified teachers of learners with hearing impairment in Thawabu among other inclusive public schools in Kenya to help promote socialization and to increase inclusivity of leaners with hearing impairment.
Early Holocene phytolith records for three shell midden sites, Yongjiang River, Guangxi Province, China

Phytolith records from three proximal freshwater shell midden sites document plant exploitation and local palaeoecological changes during the early Holocene in present-day Nanning City, Guangxi Province, China. Radiocarbon dating of freshwater gastropod shells indicates the midden sites formed sequentially, with variable chronological overlaps: Baozitou at 12,000-11,130 cal BP, Shichuantou at 11,250-10,500 cal BP and Nabeizui at 11,060-9560 cal BP. Palaeoecological data are inferred to show variable trends of forest reduction or recovery during the formation of each midden, suggesting different intensities of site use and impacts upon the local environment. Significantly, palms (Arecaceae) became more frequent during the middle period of formation at each site, which is interpreted to represent resource intensification and selective exploitation of palms by the communities who created each midden.
Drastic Vegetation Change in the Guajira Peninsula (Colombia) During the Neogene

Dry biomes occupy ~35% of the landscape in the Neotropics, but these are heavily human‐disturbed. In spite of their importance, we still do not fully understand their origins and how they are sustained. The Guajira Peninsula in northern Colombia is dominated by dry biomes and has a rich Neogene fossil record. Here, we have analyzed its changes in vegetation and precipitation during the Neogene using a fossil pollen and spore dataset of 20 samples taken from a well and we also dated the stratigraphic sequence using microfossils. In addition, we analyzed the pollen and spore contents of 10 Holocene samples to establish a modern baseline for comparison with the Neogene as well as a study of the modern vegetation to assess both its spatial distribution and anthropic disturbances during the initial stages of European colonization. The section was dated to span from the latest Oligocene to the early Miocene (~24.2 to 17.3 Ma), with the Oligocene/Miocene boundary being in the lower Uitpa Formation. The early Miocene vegetation is dominated by a rainforest biome with a mean annual precipitation of ~2,000 mm/yr, which strongly contrasts with Guajira's modern xerophytic vegetation and a precipitation of ~300 mm/yr. The shift to the dry modern vegetation probably occurred over the past three millions years, but the mechanism that led to this change is still uncertain. Global circulation models that include the vegetation could explain the ancient climate of Guajira, but further work is required to assess the feedbacks of vegetation, precipitation, and CO2.
Ecophysiological aspects of algal host–virus interactions in a changing ocean

With this thesis I aimed to obtain a better understanding on how abiotic factors affect virus-phytoplankton interaction, alone and in combination with other relevant environmental variables. The main focus in this thesis is on phosphorus (P) limitation, for the primary reason that phytoplankton growth in many coastal and oceanic systems worldwide is (seasonally) limited in P, and the future (stratified) ocean is expected to become more P-limited than nitrogen (N) limited due to diazotroph N-fixation in the ocean surface. The studies in this thesis were carried out with axenic phytoplankton host-virus model systems under well-controlled experimental set-ups to obtain a mechanistic understanding and allow accurate quantification of virus growth characteristics, i.e., the viral latent period (time until first release of viruses), the viral burst size (number of viruses produced per host cell lysed) and the percentage of infective progeny viruses. Host cell physiology (e.g. photophysiology and lipid composition) was monitored to relate differences in results between treatments to host metabolism.
Evaluation of the Quality Supervision System for Construction Projects in China Considering the Quality Behavior Risk Transmission

In construction projects, improper quality behavior of a participant results in quality behavior risks, which can transmit to the downstream participants and may cause detrimental effects on the quality of the entity finally constructed. Controlling the transmission of quality behavior risks is the key to effectively supervising and ensuring the quality of construction projects. In this study, the effectiveness of the quality supervision system of construction projects in China was investigated by considering the transmission of quality behavior risks. A multi-player evolutionary game model consisting of the players of quality supervision of a government department, upstream participant (UP), and downstream participant (DP) was generated. By using the system dynamics theory, the game model was simulated to determine the stability of the evolutionary system and to evaluate the effectiveness of China’s current quality supervision system under different scenarios. The results showed that there is no evolutionary stable strategy (ESS) in the evolutionary system of the current quality supervision system in China and there are fluctuations in the evolution process. It revealed that high risk exists in the current quality supervision system in China. To resolve the problem of the low efficiency of the current Chinese supervision system, a dynamic penalty and incentive method is developed, which has been proven to be able to effectively control the quality behavior risks in construction projects and hence ensuring the quality of the entity finally constructed.
The development of preclinical strategies for facilitation of lead candidate selection

Kulczar, Christopher D. Ph.D., Purdue University, December 2016. The Development of Preclinical Strategies for Facilitation of Lead Candidate Selection. Major Professor: Gregory T. Knipp. Chapter 1 details a background of techniques used for modeling the blood-brain barrier (BBB). The BBB represents a diffusive barrier to both paracellular and transcellular movement of many compounds in and out of the brain. The main ratelimiting barriers of the BBB include exclusive tight junctions that prevent the movement of hydrophilic molecules through intercellular gaps, and efflux proteins in the membrane which pump many hydrophobic molecules back into the blood. In addition, the BBB contains metabolizing enzymes, including Cytochrome P450s. This barrier acts to protect the vulnerable tissues of the brain from harmful xenobiotics, but also can serve as a restrictive barrier for potential therapeutic compounds for the growing number of neurological diseases, including Alzheimer’s disease, Parkinson’s disease, stroke, depression, brain cancers, and many others. In fact, it is estimated that over 98% of pharmaceutical compounds are unable to cross into the brain. Due to this problem, many compounds must be screened in order to determine their BBB permeation and eventual druggability. While in vivo testing in pre-clinical animals and humans is ideal for testing, these methods aren’t suitable for early screening because of their high cost, low throughput, and ethical considerations, especially in humans.
Finite‐state model extraction and visualization from Java program execution

Finite‐state models are extensively used for discrete systems and they have also been adopted for the analysis and verification of concurrent systems. Programs that have a repetitive cycle, such as event‐driven servers and controllers, lend themselves to finite‐state modeling. In this article, we use the term model extraction to refer to the construction of a finite‐state model from an execution trace of a Java program and a set of key attributes, that is, a subset of the fields of the objects in the program execution. By choosing different sets of attributes, different finite‐state models (or views) of the execution can be obtained. Such models aid program comprehension and they can also be used in debugging a program. We present algorithms for model extraction and also for model abstraction in order to reduce the size of the extracted models so that they are amenable to visualization. For long executions, we show how to minimize the overhead of execution trace collection through a bytecode instrumentation technique; and, for large models, which are not amenable to visualization, we show how key properties of the extracted model can be checked against declarative specifications. We have implemented our techniques in the context of JIVE, an Eclipse plugin that supports runtime visualization and analysis of Java program executions. We illustrate our techniques through a collection of case studies of varying size and complexity, from classic problems of concurrency control to a medium‐size protocol for authorization (OAuth2.0 protocol) to a large‐scale software that underlies web applications (Apache Tomcat server).
Habitat factors influencing the competitive ability of Calamagrostis epigejos (L.) Roth in mountain plant communities

The aim of this study was to assess how the expansion of Calamagrostis epigejos influences the species composition and diversity of forest, clearing, and meadow communities as well as how habitat factors influence biometric variability and features determining the potential of Calamagrostis epigejos for expansion in the studied communities. The study was conducted in the central part of the Sudetes Mountains (SW Poland). Four types of communities with C. epigejos occurrence were chosen: a beech forest (Luzulo luzuloidis-Fagetum), a Norway spruce monoculture, a clearing community belonging to the Epilobietea angustifolii class, and a mesic mountain meadow of the Arrhenatheretalia order. In each of the studied communities, randomized selection of 10 plots (1 x 1 m) was performed. On these plots releves were sampled, a biometric study was conducted, and soil samples were collected. The research revealed a significant influence of C. epigejos expansion on the species composition, diversity, and productivity in the herb layers of the studied communities. It also indicated a strong positive influence of sunlight availability and studied physicochemical properties of soil on the expansion ability of C. epigejos.
The Potential of Using Tree-Ring Chronology from the Southern Coast of Korea to Reconstruct the Climate of Subtropical Western North Pacific: A Pilot Study

Tree-ring width (TRW) chronologies have successfully been used as climate proxies to infer climate variabilities over the past hundreds to thousands of years worldwide beyond observational records. However, these data are scarce over parts of subtropical East Asia, and especially over the Korean Peninsula. In this pilot study, Korean red pine (Pinus densiflora Siebold and Zucc.) TRW chronologies from Mt. Mudeung and Mt. Wolchul, South Korea, were developed, and their local- to large-scale climatic responses were investigated. Mt. Mudeung TRW had a positive association with local temperature in the preceding December and April. Mt. Wolchul TRW had a positive association with local temperature in the preceding December and most of the early summer to autumn months, and with local precipitation in February and October. On a large scale, both TRWs retained meaningful temperature and monsoon precipitation signals over East Asia and sea surface temperature signals over the Western North Pacific. The results suggest that the subtropical trees from South Korea can be used to infer past long-term climate variability at both local and large scales over East Asia and the Western North Pacific, such as the East Asian summer monsoon, the Kuroshio Current, the Western North Pacific Subtropical High, and El Niño–Southern Oscillation.
Risk of vector tick exposure initially increases, then declines through time in response to wildfire in California

Identifying the effects of human-driven perturbations, such as species introductions or habitat fragmentation, on the ecology and dynamics of infectious disease has become a central focus of disease ecologists. Yet, comparatively little is known about how the ecology of zoonotic disease systems responds to catastrophic disturbance events such as wildfires or hurricanes. In California, wildfire disturbance is centrally important to the ecology of forests and oak woodlands and is projected to increase in severity and extent under future climate change. Here, taking advantage of a recent wildfire as a natural experiment, we investigate the effects of wildfire disturbance on the ecology of tick-borne disease in California oak woodlands. We find that wildfire leads to elevated abundance of questing adult and nymphal western blacklegged ticks (Ixodes pacificus) in the year following fire, relative to unburned control plots, but that vector tick abundance declines sharply in the following two years. We find that the abundance of non-competent hosts (western fence lizards) for the Lyme disease bacterium is unaffected by fire, but that the abundances of important reproductive hosts (deer) for ticks and reservoir hosts (dusky-footed woodrats) for tick-borne pathogens are significantly negatively affected by fire. We found ticks and hosts infected with Borrelia burgdorferi sensu lato only within the burn extent and only in the year following the wildfire, though rates of infection were exceedingly low representing little risk to humans. In aggregate, due to the differential effects of this catastrophic disturbance event on different key host species and vector tick life stages in the transmission of tick-borne pathogens, we conclude that wildfire may potentially increase risk of exposure to vector ticks in the first year following wildfire in California, but that risk is dampened substantially in following years due to tick population declines and loss of key reservoir hosts from the
Ammonia Emissions from Differing Manure Storage Facilities at Two Midwestern Free-Stall Dairies

Dairies contribute a major portion of agricultural ammonia emissions in the United States. Emissions were monitored over two years from an anaerobic lagoon receiving manure from cows in the milking parlor and holding area in Indiana (IN), USA and a storage basin receiving manure from cows in barns as well as the milking parlor and holding area in Wisconsin (WI), USA. Emissions were monitored using open-path tunable diode lasers, sonic anemometers, and two emission models. The mean annual daily emissions at the WI storage basins (30 µg m−2 s−1) was nearly equal to that at the IN lagoon (27 µg m−2 s−1). The mean annual daily ammonia (NH3) emissions on a per animal basis were greater at the WI basins (33 g NH3 hd−1 d−1; 26 g NH3 AU−1 d−1) (hd = animal; AU = 500 kg animal mass) than at the IN lagoon (9 g NH3 hd−1 d−1; 7 g NH3 AU−1 d−1). Emissions from both storage systems were highest in the summer, lowest in the winter, and similar during the spring and fall. Emissions were strongly correlated with air temperature and weakly correlated with wind conditions. Greater emissions at the WI basins appeared to be related primarily to the characteristics of the stored manure.
Making Data Reports Useful: From Descriptive to Predictive

The purpose of analyzing data is to transform it into useful knowledge. Descriptive analytics renders factual information about research and events that can be used to relate an organization’s environment to its activities. However, descriptive analytics alone is not enough to gain understanding and possibly predict the future. Minding only the output of such an analysis can mislead the researcher and decisionmaker. Because many factors influence results, it is essential to advance the prediction of future challenges through statistical analytics and factual patterns that dictate the environment with scientifically tested models. The data patterns, types of analysis, and attributes the prediction will be based on are all important. Data influenced by unforeseen variables make for poor predictions, such as the evening capacity report data in this study.
Response of benthic nitrogen cycling to estuarine hypoxia

The effects of bottom water oxygen concentration on sediment oxygen uptake, oxygen penetration depth, nitrate and ammonium fluxes, anammox, denitrification, dissimilatory nitrate reduction to ammonium, nitrification, and mineralization were investigated off the Changjiang estuary and its adjacent East China Sea, by combining a seasonal comparison with three artificially induced bottom water oxygen conditions (oxic, ambient, and severe hypoxia). A 50% decrease in in‐situ bottom water oxygen concentrations between May and August, led to decreases in the average sediment oxygen uptake and oxygen penetration depth by 23% and 29%, respectively. Anammox rates decreased by a factor of 2.5, and the relative contribution of anammox to the total benthic N‐loss decreased from 20% to 7.4%. However, denitrification rates increased, leading to an overall benthic N‐loss rate of 0.85 mmol N m−2 d−1. At the same time, an increasing contribution of dissimilatory nitrate reduction to ammonium to total nitrate reduction led to higher recycling of inorganic nitrogen during hypoxia in August. Under artificially induced conditions of severe hypoxia, there was a sharp decrease in both sediment oxygen uptake and benthic N‐loss rates by 88% and 38%, respectively. Nitrate and ammonium fluxes showed complex behavior at different sites which could be related to the repression of sedimentary nitrification below a bottom water oxygen threshold of 9.7 μM and increasing dissimilatory nitrate reduction to ammonium. Taken together, our results indicate that changes in benthic nutrient cycling under seasonal hypoxia enhance the retention of both organic and inorganic nitrogen, thereby exacerbating oxygen deficiency.
Titanium dioxide nanostructures as efficient photocatalyst: Progress, challenges and perspective

In the growing energy consumption, the photocatalysis seems to be very helpful due to promising environmental applications. Several semiconducting nanostructures are reported as photocatalysts but still, the researchers are finding a way towards higher efficiency. The TiO2 nanostructures with different sizes, morphologies, synthesis methods and dopants have been reviewed to study their effect on photocatalysis. The TiO2 photocatalysts are presented to be widely used in energy and eco‐friendly applications including water purification, hydrogen production, phenol degradation, Cr(VI) and CO2 reduction. The photostability, accessibility and environmental harmlessness have been presented as a break through towards the global energy crisis due to potential application in photocatalytic hydrogen evolution. Besides variety of useful applications, the efficiency is limited due to wide bandgap, fast charge recombination, and many other factors. The progress of TiO2 photocatalyst along with the limitations underway and their possible solutions have been presented from reported literature. It is predicted that an approach towards highly efficient photocatalyst could be achieved in the form of nanostructured TiO2.
Examining the public's awareness of bee (Hymenoptera: Apoidae: Anthophila) conservation in Canada

Understanding the general public's knowledge and perceptions of an issue can help drive action on the part of decision‐makers. Such understanding is critical when decision‐makers are faced with multiple stakeholders, which is the case with biodiversity conservation issues. We surveyed the Canadian general public using a telephone questionnaire to assess the level of knowledge and perceptions of native wild bee (Hymenoptera: Apoidea: Anthophila) health and conservation. We found that the general level of bee knowledge among participants was low. Half of participants named the non‐native managed European honeybee (Apis mellifera Linnaeus 1758) as a wild bee, native to Canada. Over two‐thirds of participants stated the provisioning of ecosystem services (ES) is the most important reason to conserve bees. Half of participants thought the Canadian federal and provincial government should be principally responsible for bee conservation. One‐third of participants perceived no personal barriers to bee conservation and nearly one‐quarter stated they did not know how to help bee conservation efforts. Our results highlight that scientific researchers can play an important role in outreach and education and environmental non‐governmental organizations (ENGOs) can take an active lobbying role at the provincial and federal levels with respect to bee conservation.
Intelligent Fault Diagnosis Method Using Acoustic Emission Signals for Bearings under Complex Working Conditions

Recent convolutional neural network (CNN) models in image processing can be used as feature-extraction methods to achieve high accuracy as well as automatic processing in bearing fault diagnosis. The combination of deep learning methods with appropriate signal representation techniques has proven its efficiency compared with traditional algorithms. Vital electrical machines require a strict monitoring system, and the accuracy of these machines’ monitoring systems takes precedence over any other factors. In this paper, we propose a new method for diagnosing bearing faults under variable shaft speeds using acoustic emission (AE) signals. Our proposed method predicts not only bearing fault types but also the degradation level of bearings. In the proposed technique, AE signals acquired from bearings are represented by spectrograms to obtain as much information as possible in the time–frequency domain. Feature extraction and classification processes are performed by deep learning using EfficientNet and a stochastic line-search optimizer. According to our various experiments, the proposed method can provide high accuracy and robustness under noisy environments compared with existing AE-based bearing fault diagnosis methods.