Miracle-dz/UniFAR-FTUs huggingface dataset:
Home and school influences on the behavioral and academic outcomes of low-income children of color

ABSTRACT Framed within contextual systems model, this study examines how home and school operate together to shape behavioral and academic outcomes for 544 low-income African American (56%) and Latino/a (44%) elementary school-aged children (mean age = 7.88 years, SD = 1.46, 50% male). Using data from Welfare, Children, & Families Study: A Three City Study and multiple group path analysis, we found that for children in kindergarten through third grade, the adequacy of the home resources was positively related to applied problem scores (e.g. math literacy) and negatively associated with externalizing behavior. For fourth- to sixth-graders, the adequacy of classroom resources was negatively associated with applied problem scores. For both age groups positive teacher–child relational quality was also a positive predictor of externalizing behavior. Results revealed that barriers to parental involvement in school were a negative predictor of applied problem scores for low-income children in early and later elementary school. Implications for policy and practice aimed at strengthening opportunities for children and families from marginalized communities are discussed.
Does this App Really Need My Location?

The enormous popularity of smartphones, their rich sensing capabilities, and the data they have about their users have lead to millions of apps being developed and used. However, these capabilities have also led to numerous privacy concerns. Platform manufacturers, as well as researchers, have proposed numerous ways of mitigating these concerns, primarily by providing fine-grained visibility and privacy controls to the user on a per-app basis. In this paper, we show that this per-app permission approach is suboptimal for many apps, primarily because most data accesses occur due to a small set of popular third-party libraries which are common across multiple apps. To address this problem, we present the design and implementation of ProtectMyPrivacy (PmP) for Android, which can detect critical contextual information at runtime when privacy-sensitive data accesses occur. In particular, PmP infers the purpose of the data access, i.e. whether the data access is by a third-party library or by the app itself for its functionality. Based on crowdsourced data, we show that there are in fact a set of 30 libraries which are responsible for more than half of private data accesses. Controlling sensitive data accessed by these libraries can therefore be an effective mechanism for managing their privacy. We deployed our PmP app to 1,321 real users, showing that the number of privacy decisions that users have to make are significantly reduced. In addition, we show that our users are better protected against data leakage when using our new library-based blocking mechanism as compared to the traditional app-level permission mechanisms.
Clustering network-constrained uncertain trajectories

Low sampling-rate and uncertain features of trajectory data present new challenges to trajectories data mining. This paper proposed a relationship graph-based trajectory clustering algorithm for objects moving on road networks. By constructing an approximate minimum spanning tree of a trajectory, based on the spatial distance of candidate segments, a distance measurement scheme is presented to judge the degree of similarity. The relationship graphical model is adopted to represent the network-constrained trajectory data. A modified RepStream clustering algorithm is proposed to retain the stable relationship information. The experiments show that the clustering algorithm has superior accuracy in low sampling-rate and sampling error trajectories data.
Anodized Aluminum Oxide Thin Films for Room‐Temperature‐Processed, Flexible, Low‐Voltage Organic Non‐Volatile Memory Elements with Excellent Charge Retention

Despite considerable achievements in organic electronics, including examples of complex integrated circuits, [ 1 ] transistor matrix arrays for optical [ 2 ] and Braille displays, [ 3 ] image scanners, [ 4 ] and large-area electronic skin, [ 5 ] non-volatile organic memories remain underexploited. [ 6 ] Even at the lower end of the market, where potential applications are smart cards, wireless tags, and large-area sensors, no non-volatile memory that meets the minimum requirements in terms of access time, retention, and endurance is currently available. [ 6a ] Although there are several types of memory, such as electret, [ 7 ] ferroelectric polymer, [ 8 ] resistive, [ 9 ] and fl ash, [ 10 ] that may be considered suitable, none of them have reached maturity. Electret memories usually require high operating voltages and suffer from long programming times and low charge retention. [ 7 ] Ferroelectric polymer memories face problems known from their inorganic counterparts: interface charge trapping, fatigue, and imprint. [ 8 ] Resistive memories require currents to operate the memory. [ 9 ] Organic fl ash memories, based on fi eld-effect transistors with a fl oating gate architecture where charges stored in the fl oating gate change the threshold voltage of the transistor, currently suffer from either high voltage operation or low charge retention, typically on the order of a few hours or days. [ 10 ] In fl ash memories, the dielectric used to isolate the fl oating gate from the gate electrode and from the semiconductor is the main problem. The gate dielectric must be dense to achieve extremely low leakage currents, and it must provide very large dielectric breakdown strength. [ 11 ]
Identification of effective Pb resistant bacteria isolated from Lens culinaris growing in lead contaminated soils

Soil bacteria are a new phytoremediation system for the removal of heavy metals from soils. In this study, fifteen soil bacteria were isolated from root nodules of lentil growing in heavy metals contaminated soils, particularly by lead. Molecular characterization of the collection showed a large diversity, including Agrobacterium tumefaciens, Rahnella aquatilis, Pseudomonas, and Rhizobium sp. These soil bacteria had a wide range of tolerance to heavy metals. Among them, strains of A. tumefaciens and R. aquatilis tolerated up to 3.35 mM Pb; whereas Pseudomonas tolerated up to 3.24 mM Pb. The inoculation of lentil grown hydroponically with inoculums formed by these efficient and Pb resistant bacteria enhanced plant biomass. The treatment of this symbiosis by 1 mM Pb for 10 days or by 2 mM Pb for 3 days demonstrated that lentil had Pb accumulation capacity and can be considered a Pb accumulator plant, elsewhere, roots accumulated more Pb than shoots, and the inoculation decreased the Pb up take by the plants, suggesting that this symbiosis should be investigated for use in phytostabilization of Pb‐contaminated soils. At the same time, a modulation in the antioxidant enzyme activity and a specific duration was required for the induction of the superoxide dismutase (SOD), peroxidase (POX), and ascorbate peroxidase (APX) response and to adapt to Pb stress. These results suggested that these enzymes may be involved in the main mechanism of antioxidative defense in lentil exposed to Pb oxidative stress.
Subjective Outcome Evaluation Based on Secondary Data Analyses: The Project P.A.T.H.S. in Hong Kong

The intent of this study was to evaluate the program effectiveness of the Project P.A. T.H. S. (Positive Adolescent Training through Holistic Social Programmes) (Secondary 1 Curriculum) by analyzing 207 school-based program reports, in which program implementers were invited to write down five conclusions based on an integration of the subjective outcome evaluation data collected from the program participants and program implementers. Secondary data analyses were conducted and 1,855 meaningful units were extracted from 1,035 “aggregated” conclusions. Among them, about 27 and 18% were related to perceptions of the program and implementers, respectively, and most of them were positive in nature. About one-third was related to perceived effectiveness of the program, and most of them referred to enhancement of students' development in societal, familial, interpersonal, and personal aspects. However, difficulties encountered during program implementation (3.34%) and recommendations for improvement (18.11%) were also reported. The present study replicated the findings reported in previous studies and suggests that the Tier 1 Program of the Project P.A. T.H. S. is beneficial to the development of the program participants.
Data Intensive Computation in a Compute/storage Hierarchy

We are acquiring and storing ever-increasing volumes of data. Extracting useful information from these large datasets poses challenges throughout the memory/storage hierarchy. One solution is to reduce the amount of data movement between different level of memory. The two-level external memory (EM) model and its variants are used to design such algorithms. We show how application of EM techniques can yield significant performance improvement for a GIS application. We also show that the derived cache model does not adequately represent the memory system at the cache/register level. The other proposed solution to dealing with large datasets makes use of processing elements co-located with storage – active storage. Parallel processing has long been prescribed for increased performance. In many cases, it is much harder to develop a fully parallel solution. Active storage offers a more specific platform (at a lower projected cost). We hope that the heterogeneity inherent in active storage systems will allow us to develop an efficient, yet easy-to-use, programming model and interface library. EM-efficient algorithms provide a good starting point for our study. We will examine several EM solutions using the TPIE interface library, and propose a richer interface that will allow efficient active storage implementations. Because of the complexity of the complete system, we will favor an experimental evaluation strategy, but will also use theoretical analysis for the initial algorithm designs.
PSON: A Parallelized SON Algorithm with MapReduce for Mining Frequent Sets

Many algorithms have been proposed in past decades to efficiently mine frequent sets in transaction database, including the SON Algorithm proposed by Savasere, Omiecinski and Navathe. This paper introduces the SON algorithm, explains why SON is very suitable to be parallelized, and illustrates how to adapt SON to the MapReduce paradigm. Then we propose a parallelized SON algorithm, PSON, and implement it in Hadoop. Our study suggests that PSON can mine frequent item sets from a very large database with good performance. The experimental results show that when performing frequent sets mining, the time cost will increase almost linearly with the size of the datasets and decrease with approximately linear trend with the number of cluster nodes. Consequently, we conclude that PSON works well for solving the frequent set mining problem from massive datasets with a good performance in both scalability and speed-up.
Is IQ-Achievement Discrepancy Relevant in the Definition of Arithmetic Learning Disabilities?

This study was designed to test whether the criterion based on the IQ-achievement discrepancy is useful in the definition of arithmetic learning disabilities (ALD). A sample of children with ALD, garden-variety (G-V) poor mathematics performance (i.e., the poor arithmetic performance of children of below-average intelligence is believed to be nondiscrepant, or in accordance with their lower cognitive capabilities) and normally achieving children were selected using the standard-score discrepancy method (i.e., the differences between IQ and achievement standard scores). All the groups were compared to determine whether there were differences in solving addition and subtraction word problems and in other cognitive abilities related to mathematics such as working memory. There were no significant differences between children with ALD and children with G-V poor mathematics performance in solving arithmetic word problems or on working memory tasks. The performance of both groups with arithmetic disabilities was significantly below that of normally achieving children. This means that the criterion based on the IQ-achievement discrepancy does not seem to be relevant for differentiating between children with ALD and children with G-V poor mathematics performance.
Self-Reported Property Crime Patterns in 30 Countries

In this article, we investigate the use of a multivariate exploratory data analysis technique, nonlinear principle components analysis (NPCA). The technique is presented as a means for thorough descriptive analysis in a multivariate setting and with data of varying levels of measurement. The technique includes a strong visualization component of the kind previously only available for only one- and two-variable situations. This multivariate technique makes possible more thorough pre-analysis examination of data, a step frequently overlooked in most quantitative research. The data examined are self-reported prevalence measures for property crime from the Second International Self-Report Delinquency Study (ISRD-2). Our examination suggested that: (a) the property variable seems to group around two underlying dimensions (“Simple Object Dimension” and the “Complex Object Dimension”); (b) hacking proved to be a potentially very interesting but yet problematic variable due to interpretation of the item by the youthful respondents; and (c) the groupings and subgroupings of variables do show distinct nonrandom relationships among the 30 country property crime profiles in the analysis as well as the Esping-Andersen/ISRD-2 clustering system widely used in ISRD-2 research efforts.
Gradient projection methods for quadratic programs and applications in training support vector machines

Gradient projection methods based on the Barzilai–Borwein spectral steplength choices are considered for quadratic programming (QP) problems with simple constraints. Well-known nonmonotone spectral projected gradient methods and variable projection methods are discussed. For both approaches, the behavior of different combinations of the two spectral steplengths is investigated. A new adaptive steplength alternating rule is proposed, which becomes the basis for a generalized version of the variable projection method (GVPM). Convergence results are given for the proposed approach and its effectiveness is shown by means of an extensive computational study on several test problems, including the special quadratic programs arising in training support vector machines (SVMs). Finally, the GVPM behavior as inner QP solver in decomposition techniques for large-scale SVMs is also evaluated.
Stories of loss and change : six mothers’ experiences of parenting an adult child with a mental illness

A qualitative narrative research method was used to explore and describe the experiences of personal growth and change of six mothers of adult children with schizophrenia or schizoaffective disorder who volunteered to participate in this study. A total of twenty-eight semi-structured interviews (average four per participant), were conducted over a period of two years. The research question was: How do parents of adult children with schizophrenia or schizoaffective disorder experience personal growth and change as they live with the challenges and uncertainties associated with their child's mental illness? Individual, co-constructed first person narratives of each participant's mothering experiences were written following an in-depth, holistic-content analysis of the interview data. A cross-narrative analysis was also conducted which resulted in four common themes (Enduring sadness and loss, Distress and struggle, Commitment to helping/action, Personal and relational change); four significant threads (What will happen when I am no longer able to care for my child? , Impact on siblings who are well, Fluctuations in hope, Regret/Guilt); and four broader dimensions (New normal mothering, Changes in mothering over time, Involvement in the mental health system, Adaptation and engagement with life in new and meaningful ways). These findings were found to be best understood through the conceptual lens of nonfinite loss – reflecting the ongoing challenges and lifetime implications of this mothering experience. Implications for theory, research and counselling psychology practice are addressed, based on
Transiently Chaotic Neural Networks for Channel Assignment in Cellular Mobile Communications

Recently, Chen and Aihara proposed the transiently chaotic neural network (TCNN) for solving combinatorial optimization problems, and the TCNN has shown a high solving ability for traveling salesman problem (TSP). In this paper, we are interested in the channel assignment problem (CAP) which is to assign the required number of frequency channels to each cell in a cellular mobile network in such a way that interference between channels is minimized and the demands are met. We used the TCNN to solve CAP, and simulation results show better performance than the results obtained by other algorithms.
Can Physiological Endpoints Improve the Sensitivity of Assays with Plants in the Risk Assessment of Contaminated Soils?

Site-specific risk assessment of contaminated areas indicates prior areas for intervention, and provides helpful information for risk managers. This study was conducted in the Ervedosa mine area (Bragança, Portugal), where both underground and open pit exploration of tin and arsenic minerals were performed for about one century (1857 – 1969). We aimed at obtaining ecotoxicological information with terrestrial and aquatic plant species to integrate in the risk assessment of this mine area. Further we also intended to evaluate if the assessment of other parameters, in standard assays with terrestrial plants, can improve the identification of phytotoxic soils. For this purpose, soil samples were collected on 16 sampling sites distributed along four transects, defined within the mine area, and in one reference site. General soil physical and chemical parameters, total and extractable metal contents were analyzed. Assays were performed for soil elutriates and for the whole soil matrix following standard guidelines for growth inhibition assay with Lemna minor and emergence and seedling growth assay with Zea mays. At the end of the Z. mays assay, relative water content, membrane permeability, leaf area, content of photosynthetic pigments (chlorophylls and carotenoids), malondialdehyde levels, proline content, and chlorophyll fluorescence (Fv/Fm and ΦPSII) parameters were evaluated. In general, the soils near the exploration area revealed high levels of Al, Mn, Fe and Cu. Almost all the soils from transepts C, D and F presented total concentrations of arsenic well above soils screening benchmark values available. Elutriates of several soils from sampling sites near the exploration and ore treatment areas were toxic to L. minor, suggesting that the retention function of these soils was seriously compromised. In Z. mays assay, plant performance parameters (other than those recommended by standard protocols), allowed the identification of more phytotoxic soils. The results suggest that these parameters could improve the sensitivity of the standard assays.
Analysis of blink rate patterns in normal subjects

The present study measured the normal blink rate (BR) variations in relation to behavioral tasks in 150 healthy volunteers (70 males and 80 females; aged 35.9 ± 17.9 years, range 5–87 years). The subjects were videotaped in a standard setting while performing three different tasks: resting quietly, reading a short passage, talking freely. The mean BR was computed during each task; the data were compared by means of analysis of variance and Student's t tests. Mean BR at rest was 17 blinks/min, during conversation it increased to 26, and it was as low as 4.5 while reading. As compared with rest, BR decreased by −55.08% while reading (p < 1 × 1015) and increased by 99.70% during conversation (p < 1 × 109). As compared with reading, BR increased during conversation by 577.8% (p < 1 × 10 17). The distribution curves were highly reproducible in each task. The best curve fit was represented by a long‐normal distribution, with the upper tail of each curve having a normal distribution. Eye color and eyeglass wearing did not influence BR. Women had higher BR than men just while reading. No age‐related differences were found. The most common BR pattern was conversation > rest > reading, which occurred in 101 subjects (67.3%); 34 subjects (22.7%) had the pattern rest > conversation > reading; 12 (8.0%) had the pattern conversation > reading > rest. This study identified three normal behavioral BR patterns and showed that BR is more influenced by cognitive processes than by age, eye color, or local factors. The present findings provide a normal reference for the analysis of BR in movement disorders such as dystonia or tics.
A framework for building collaborative applications.

The advent of the Internet has been driven by the relentless effort of decades of research to develop a digital environment that would facilitate collaborative work on a global scale. The popularity of the Internet soared when the world saw the potential of the World Wide Web (WWW) as an Internet-based tool for sharing digital media and communicating. The success of the WWW has been so tremendous that most of the effort invested in the development of Internet-based tools are focused on improving the WWW rather than investigating other forms of collaboration. Another explanation behind why there are so few collaborative applications is because it can be quite complicated to design and develop them. To this end, we propose in this thesis a framework written in Java that would facilitate the development of collaborative tools. It does so by providing readymade mechanisms such as, concurrency control which is common in every such applications. This study undertakes a constructive approach by identifying those features of Java such as, object serialization, that is exploited in our design of the framework. We also analyse several forms of socket-based communication which is essential for networked applications. Java’s Remote Method Invocation architecture is also investigated to get a sophisticated insight into how our collaborative model should operate. Finally, we conclude our analysis by studying the Java Messaging Service to obtain an alternative view on synchronous and asynchronous communication models. The scafolding of our collaboration model is based on the concept of an island which is essentially a star topology with a central coordinator and a number of satellite participants. It is demonstrated that this arrangement provide a robust concurrency control mechanism. Islands can be divided into smaller islands as a mean to counter the problem of overload which is peculiar to collaborative applications. The islands are interconnected via their coordinators to form a full-mesh topology and thus provide a very stable and scalable architecture. In order to gauge the effectiveness of our framework, we enhance a typical single user application to a collaborative one using the toolkit from our framework. It is shown that in extreme cases, when the applications generate large amount of data, our solution can easily withstand the creation islands of 11 users and after that it would be necessary to split the island. And under normal circumstances, islands can easily accomodate between 25 to 30 participants at a time before the load balancing mechanism has to be invoked.