Miracle-dz/UniFAR-FTUs huggingface dataset:
Two Decades of Generalizable Evidence on U.S. Instruction from National Surveys

Background Students’ instructional experiences—that is, their experiences working with subject matter during classroom instruction—are a major determinant of how they learn. Given the importance of classroom instruction, valid, generalizable evidence is needed by policymakers, researchers, and practitioners. Over the past two decades, a wealth of generalizable evidence on instruction has been generated by large-scale surveys administered to nationally-representative probability samples. But this vast body of research has not been systematically summarized. Purpose of the Study This article attempts to fill a gap in the research by describing evidence on instruction from all surveys conducted between 1987 and 2005 that measured instruction using nationally-representative samples. Our goal is to generate a portrait of the evidence from these surveys that identifies strengths and gaps in the literature and that summarizes what this research base says about the relationship between classroom instruction and student outcomes. Research Design Evidence on instruction was compiled and summarized in four steps: (1) all surveys conducted between 1987 and 2005 that measured instruction and were administered to nationally representative probability samples were identified, (2) manuscripts using data from these surveys were selected for review, (3) the dimensions of instruction addressed by each manuscript and other manuscript characteristics were coded, and (4) the methodology and findings of each manuscript were summarized. Findings More than half the studies used data more than a decade old; few studies examined instruction during important transition years such as sixth and ninth grade; and subject area emphasis was lopsided, with mathematics and science instruction receiving much greater attention than English/language arts and social studies. The summary also revealed a repeated finding of low-SES students receiving diminished learning opportunities than more affluent peers. We also found repeated evidence of a positive association with student achievement for six dimensions of instruction, and repeated evidence of a negative or null association with achievement for five dimensions of instruction. Conclusions More research is needed on disparities in the instructional experiences of low-and high-income students. More research is also needed on instruction at key transition points and on instruction in English/language arts and social studies. This review also suggests a need for studies that more rigorously test research questions about instruction using measures that more authentically reflect the complexities of instruction and that examine student achievement growth over longer periods of time.
Collaborative Filtering with a User-Item Matrix Reduction Technique

Collaborative filtering (CF) is regarded as one of the most popular recommendation methods. However, CF has some significant weaknesses, such as problems of sparsity and scalability. Sparsity causes inaccuracy in the formation of neighbors with similar interests, and scalability prevents CF from scaling up with increases in the number of users and/or items. To mitigate these problems, this study proposes a hybrid CF and genetic algorithm (GA) model. GAs are widely believed to be effective on NP-complete global optimization problems, and they can provide good suboptimal solutions in a reasonable amount of time. In this study, the GA searches for relevant users and items from a user-item matrix not only to condense the matrix but also to improve the prediction accuracy. The reduced user-item matrix may reduce the sparsity problem by increasing the likelihood that different customers rate common items. It also shrinks the search space for CF, which ameliorates the scalability problem. Experimental results show that the proposed model improves performance and speed compared to the typical CF model.
Performance Investigation and Comparison of Two Different Electrical Hybrid System Structures

Two different topologies of an electrical hybrid system composed of a fuel cell as main source and an ultracapacitor as auxiliary source are investigated in this paper. To control these hybrid systems, a flatness-based control method which eliminates algorithm commutation in different operating modes is employed and its operation is studied in each structure. After simulating model of the structures, system efficiency in steady states is calculated while all ohmic, switching and conduction losses are considered. The simulation results show well performance of the proposed control method in both topologies and allow comparing operation of the systems in different situations.
Network reconstruction based on compressive sensing

To identify the structure of networks is essential for analysis of complex networks. This paper transforms network reconstruction to be a signal recovery problem by means of compressive sensing. In the literature, the sensing matrix is determined by the network dynamic and measured states of nodes, which might violates the restriction on the coherence of the sensing matrix for exact recovery. This paper proposes random projection and zero component analysis to preprocess the sensing matrix in order to reduce the coherence of the sensing matrix. These two data whitening techniques are implemented in three different ways with different space complexity required, performing transformation on diagonal blocks, on multiple diagonal blocks and on the whole of the sensing matrix. Numerical simulations suggest that the latter method are effective to improve the quality of the reconstructed networks and comparisons are made among these methods and the ways they are implemented.
Gaze Assistant by Eye Tracking and Image Wrapping

The natural behavior of the eyes comprises a lot of useful information, like information of the focus of the user's attention or on the alertness of the user. In this paper, we introduce a system to catch the movement data of the eyes, and determine where the user is intended to view, and then provide a zoomed view of the local area of the scene. The view of the scene is changed dynamically in a multiple resolution way by eye tracking and image wrapping. The system is useful for a weak vision user.
Communications in Mathematical Physics On Classification of Modular Tensor Categories

We classify all unitary modular tensor categories (UMTCs) of rank ≤ 4. There are a total of 35 UMTCs of rank ≤ 4 up to ribbon tensor equivalence. Since the distinction between the modular S-matrix S and −S has both topological and physical significance, so in our convention there are a total of 70 UMTCs of rank ≤ 4. In particular, there are two trivial UMTCs with S = (±1). Each such UMTC can be obtained from 10 non-trivial prime UMTCs by direct product, and some symmetry operations. Explicit data of the 10 non-trivial prime UMTCs are given in Sect. 5. Relevance of UMTCs to topological quantum computation and various conjectures are given in Sect. 6.
Sucrose-sweetened beverages increase fat storage in the liver, muscle, and visceral fat depot: a 6-mo randomized intervention study.

BACKGROUND The consumption of sucrose-sweetened soft drinks (SSSDs) has been associated with obesity, the metabolic syndrome, and cardiovascular disorders in observational and short-term intervention studies. Too few long-term intervention studies in humans have examined the effects of soft drinks. OBJECTIVE We compared the effects of SSSDs with those of isocaloric milk and a noncaloric soft drink on changes in total fat mass and ectopic fat deposition (in liver and muscle tissue). DESIGN Overweight subjects (n = 47) were randomly assigned to 4 different test drinks (1 L/d for 6 mo): SSSD (regular cola), isocaloric semiskim milk, aspartame-sweetened diet cola, and water. The amount of intrahepatic fat and intramyocellular fat was measured with (1)H-magnetic resonance spectroscopy. Other endpoints were fat mass, fat distribution (dual-energy X-ray absorptiometry and magnetic resonance imaging), and metabolic risk factors. RESULTS The relative changes between baseline and the end of 6-mo intervention were significantly higher in the regular cola group than in the 3 other groups for liver fat (132-143%, sex-adjusted mean; P < 0.01), skeletal muscle fat (117-221%; P < 0.05), visceral fat (24-31%; P < 0.05), blood triglycerides (32%; P < 0.01), and total cholesterol (11%; P < 0.01). Total fat mass was not significantly different between the 4 beverage groups. Milk and diet cola reduced systolic blood pressure by 10-15% compared with regular cola (P < 0.05). Otherwise, diet cola had effects similar to those of water. CONCLUSION Daily intake of SSSDs for 6 mo increases ectopic fat accumulation and lipids compared with milk, diet cola, and water. Thus, daily intake of SSSDs is likely to enhance the risk of cardiovascular and metabolic diseases. This trial is registered at clinicaltrials.gov as NCT00777647.
Securing OLSR and STAR Routing Protocols Against Packet Dropping by Malicious Nodes

Mobile Ad-hoc networks are those networks which has no physical links between the nodes. In MANET mobile nodes dynamically forming a network topology without the use of any existing network infrastructure or centralized administration. Routing in a MANET is challenging because of the dynamic topology and the lack of an existing fixed infrastructure. In most of their specifications it is assumed that all the nodes in the network are friendly. But in the open, collaborative MANET environment practically any node can maliciously or selfishly disrupt and deny communication of other nodes. Security in MANET is a very difficult problem to incorporate without degrading the performance of the protocol. There are various security issues associated with OLSR and STAR routing protocols among which one is packet dropping by malicious node. In this paper we have proposed one approach to minimize the packet dropping by malicious nodes in the network by applying IPSec in OLSR and STAR routing protocols and compared the results with existing without IPSec protocols. The simulation results demonstrate the success of the proposed approach and maximize the overall performance of MANET in presence of malicious nodes.
Effectiveness of Saliency-Based Methods in Optimization of Neural State Estimators of the Drive System With Elastic Couplings

This paper deals with the optimization problem of internal structure of neural-network (NN)-based state estimators of the drive system with elastic joints. Saliency-based optimization methods, developed in the NN theory, are tested in this paper to obtain the high-quality estimation of torsional torque and load-machine speed. The optimal brain damage and optimal brain surgeon methods are compared in this application. The state variables estimated by the optimized NN are used in feedback paths in the two-mass drive structure with a state controller. The simulation results show good accuracy of both presented neural estimators for a wide range of changes of the reference speed and the load torque. The simulation results are verified by laboratory experiments.
Hyperuricemia is independently associated with endothelial dysfunction in postmenopausal women but not in premenopausal women

Objectives The purpose of this study was to determine the relationships between uric acid, endothelial function and cardiovascular risk factors and to investigate whether menopausal status was associated with the relationship between uric acid and endothelial function in women. Design Cross-sectional study. Setting 3 general hospitals in Japan. Participants 749 Japanese women aged 30–74 years recruited from people who underwent health-screening examinations with agreement for measurement of vascular function. Measures We measured serum concentrations of uric acid and flow-mediated vasodilation (FMD). Percentage of FMD (peak diameter−baseline diameter/baseline diameter) was used for analysis. Endothelial dysfunction was defined as FMD ≤4.90%, division point for the lowest tertile and the middle tertile of FMD. Menopause women were defined as participants without menstruation for over 1 year or participants with a history of hysterectomy or bilateral oophorectomy. Results Of the 749 participants, 368 (49.1%) were premenopausal women and 381 (50.9%) were postmenopausal women. Age, body mass index, systolic blood pressure, total cholesterol, triglycerides, glucose, estimated glomerular filtration rate and Framingham risk score were significantly correlated with serum uric acid level. FMD showed a gradual decrease in accordance with the serum uric acid level in the entire study population (<4 mg/dL, 6.85±3.65%; 4 to <5 mg/dL, 6.79±3.60%; 5 to <6 mg/dL, 6.24±3.58%; ≥6 mg/dL, 5.27±3.18%; p=0.01). Multivariate analysis revealed that uric acid was a significantly independent risk factor for endothelial dysfunction in postmenopausal women (OR 1.23, 95% CI 1.01 to 1.50), but not in premenopausal women. Conclusions These findings suggest that uric acid can be used as a risk marker of endothelial dysfunction in a female population, and particularly as an independent risk factor in postmenopausal women but not in premenopausal women. Registration number of the study UMIN000003409.
Applied Vulnerability Detection System

In [1], we presented a Vulnerability Detection System (VDS) that can detect emergent vulnerabilities in complex Cyber Physical Systems (CPS). It used the attacker's point of view by collecting a target system's vulnerability information from varied sources, and populating a Attack Point (AP) database. From these APs, a Hierarchical Task Network generated the set of composite device-level attack scenarios. The VDS used Alloy [2] to reduce the cardinality of the generated space by evaluating the feasibility of each attack. This paper specializes prior research by submitting the generated prioritized list to an automotive-specific Attack Evaluation Process (AAEP). With a combination of simulation and vehicle instrumented real-time execution, the AAEP confirms each candidate attack. The AAEPs output is used as feedback to refine the Alloy model. VDS is designed to support short product release cycles. The AAEP separates domain-specific from domain-independent aspects so the VDS can be rapidly retargeted.
Emerging Role of Ubiquitination in Antiviral RIG-I Signaling

SUMMARY Detection of viruses by the innate immune system involves the action of specialized pattern recognition receptors. Intracellular RIG-I receptors sense the presence of viral nucleic acids in infected cells and trigger signaling pathways that lead to the production of proinflammatory and antiviral proteins. Over the past few years, posttranslational modification of RIG-I and downstream signaling proteins by different types of ubiquitination has been found to be a key event in the regulation of RIG-I-induced NF-κB and interferon regulatory factor 3 (IRF3) activation. Multiple ubiquitin ligases, deubiquitinases, and ubiquitin binding scaffold proteins contribute to both positive and negative regulation of the RIG-I-induced antiviral immune response. A better understanding of the function and activity of these proteins might eventually lead to the development of novel therapeutic approaches for management of viral diseases.
Configural learning without configural training.

Rats learned discriminations in which 2 familiar compound visual stimuli AB and CD were nonreinforced, whereas less-familiar compounds (EF, GH, IJ.) were reinforced (constant-negative paradigm). Such discriminations can in principle be acquired through elemental (nonconfigural) learning. Three different types of compound--object/object, object/position, and shape/fill-pattern--were used, and the number of familiar compounds extended to 3 or 4. In all cases, when rats were tested for the first time with previously unseen recombinations of the familiar elements--for example, AC, BD--they preferred these to the familiar compounds, implying that they had encoded configural information during the original training. Moreover, preference remained constant despite extended exposure to configural training in the test phase. The findings extend the evidence that configural representations are formed independently of explicit configural training.
Robust hashing learning via multi-view subspace learning

Hashing learning has attracted increasing attention these years with the explosive increase of data. The hashing learning can be divided into two steps. Firstly, obtain the low dimensional representation of the original data. Secondly, quantize the real number vector of the low dimensional representation of each data point and map them to binary codes. Most of the existing methods measure the original data only from one perspective. This paper introduces the multi-view methods to the hashing learning field, and proposes a hashing learning framework utilizing the multi-view methods. The experimental results illustrate that our algorithm outperforms several the other state-of-the-art methods.
Asymptotic entropy-constrained performance of tessellating and universal randomized lattice quantization

Two results are given. First, using a result of Csiszar (1973) the asymptotic (i.e., high-resolution/low distortion) performance for entropy-constrained tessellating vector quantization, heuristically derived by Gersho (1979), is proven for all sources with finite differential entropy. This implies, using Gersho's conjecture and Zador's formula, that tessellating vector quantizers are asymptotically optimal for this broad class of sources, and generalizes a rigorous result of Gish and Pierce (1968) from the scalar to the vector case. Second, the asymptotic performance is established for Zamir and Feder's (1992) randomized lattice quantization. With the only assumption that the source has finite differential entropy, it is proven that the low-distortion performance of the Zamir-Feder universal vector quantizer is asympotically the same as that of the deterministic lattice quantizer. >
Effects of FP 2 and a Mercury Resistance Plasmid from Pseudomonas aeruginosa PA 103 on Exoenzyme Production

Plasmids encoding mercury resistance carried by Pseudomonas aeruginosa PAO1161 and PA103 were found to be involved in regulating the secretion of protease, phospholipase C, and alkaline phosphatase. Previously, mutations in Pseudomonas strains that caused pleiotropic effects on the production of extracellular enzymes were mapped to the bacterial chromosome. We show that pleiotropic changes in extracellular enzyme production can also be regulated by plasmids. In this study, the effects on secretion of exoenzymes by two mercury resistance plasmids, FP2 from PAO1161 and pRLW103 from PA103, were assayed in P. aeruginosa PA01 and PAO18. The introduction of either plasmid into PAO1 resulted in a significant decrease in exoprotease production. Additionally, pRLW103 significantly increased the production of alkaline phosphatase by both strains. Phospholipase C was produced only in strain PAO18 containing the pRLW103 plasmid. FP2 had no effect on alkaline phosphatase or phospholipase C production in either strain and was found to decrease exoprotease secretion only in strain PAO1. The results indicate the P. aeruginosa mercury resistance plasmids vary in their ability to modify exoenzyme expression, and this ability is influenced by the host strain.
Child abuse history and its effects on affect and social cognition as mediated by social support

This study examined retrospective reports of child abuse in 362 university students and assessed effects on positive and negative affect, locus of control, and maladaptive cognitive schema and affect (negative self view and viewing world as hostile) as mediated by social support. Behavior specific child abuse items and locus of control items were factor analyzed (principal factors iterated method). Child abuse was characterized by three factors (psychological/physical abuse, neglect/emotional neglect, and sexual abuse) with summary scores used for subsequent analyses. Internal, external, and victimization external locus of control emerged as locus of control factors. Relationships between child abuse history and dependent variables (affect, locus of control, and maladaptive cognitive schema/affect) were first explored through canonical correlation analysis, which found significant relationships between each abuse categorization and each dependent variable. Full fitted model regression followed for each dependent measure, with child abuse predictors alone and with demographics and social support included, to ascertain the unique and aggregate effects of predictor variables. Hierarchical regression was conducted to control for temporal priority of sets of variables. Additional results included: (1) psychological/physical abuse predicted negative affect, negative self view, hostile world view, and victimization locus of control; (2) neglect/emotional neglect predicted lower positive affect and internal locus of control and greater negative self view, hostile world view, and external locus of control; (3) effects of psychological/physical abuse and neglect/emotional neglect were indirectly expressed and/or mediated by other variables as they were not uniquely predictive when other predictors were included; (4) sexual abuse predicted negative affect, negative self view, hostile world view, and victimization locus of control; (5) positive affect and internal locus
Partial Delaunay triangulation and degree limited localized Bluetooth scatternet formation

We address the problem of localized scatternet formation for multihop Bluetooth-based personal area ad hoc networks. Nodes are assumed to know their positions and are able to establish connections with any of their neighboring nodes, located within their transmission radius, in the neighbor discovery phase. The next phase of the proposed formation algorithm is optional and can be applied to construct a sparse geometric structure in a localized manner. We propose here a new sparse planar structure, namely, partial Delaunay triangulation (PDT), which can be constructed locally and is denser than other known localized planar structures. In the next mandatory phase, the degree of each node is limited to seven by applying the Yao structure, and the master-slave relations in piconets are formed in created subgraphs. This phase consists of several iterations. In each iteration, undecided nodes with higher keys than any of their undecided neighbors apply the Yao structure to bound the degrees, decide master-slave relations on the remaining edges, and inform all neighbors about either deleting edges or master-slave decisions. To the best of our knowledge, our schemes are the first schemes that construct degree limited (a node has at most seven slaves) and connected piconets in multihop networks, without parking any node. The creation and maintenance require small overhead in addition to maintaining accurate location information for one-hop neighbors. The experiments confirm good functionality of created Bluetooth networks in addition to their fast creation and straightforward maintenance.