Miracle-dz/UniFAR-FTUs huggingface dataset:
Detection of gaming in automated scoring of essays with the IEA

In addition to the standard test security issues, automated scoring provides new opportunities for students to deliberately misrepresent their ability. Gaming of essays can take many forms including repetition of words and sentences, incorporation of context irrelevant words, phrases, or sentences, plagiarism, and the insertion of “malicious” sequences of characters such as HTML web page markup language, which may be aimed at causing scoring failures. It can also involve a series of sophisticated words arranged in nonsensical ways that confuse a statistical language model into valuing the writing as sophisticated instead of as gibberish. Computer-based approaches to detecting gaming have advantages in that they can sometimes detect subtle statistical patterns in language and plagiarism, which are imperceptible to humans. However, computers may be less sensitive than human scorers to other aspects of writing, such as certain grammar patterns and language features. This talk will describe a general framework used to detect gaming within essays by the Intelligent Essay Assessor ™ . The development of features, by analyzing aspects of the topic content elaboration, language structure, coherence, and length and their use in detecting gaming, will be described. The talk will describe some of the tradeoffs between full transparency of scoring and detection methods versus obscuring some level of specificity in the algorithms to impede gaming.
CDI-Type I : Unsupervised and Weakly-Supervised Discovery of Facial Events 1

The face is one of the most powerful channels of nonverbal communication. Facial expression has been a focus of emotion research for over a hundred years [12]. It is central to several leading theories of emotion [18, 31, 54] and has been the focus of at times heated debate about issues in emotion science [19, 24, 50]. Facial expression figures prominently in research on almost every aspect of emotion, including psychophysiology [40], neural correlates [20], development [11], perception [4], addiction [26], social processes [30], depression [49] and other emotion disorders [55], to name a few. In general, facial expression provides cues about emotional response, regulates interpersonal behavior, and communicates aspects of psychopathology. Because of its importance to behavioral science and the emerging fields of computational behavior science, perceptual computing, and human-robot interaction, significant efforts have been applied toward developing algorithms that automatically detect facial expression. With few exceptions, previous work on facial expression relies on supervised approaches to learning (i.e. event categories are defined in advance in labeled training data). While supervised learning has important advantages, two critical limitations may be noted. One, because labeling facial expression is highly labor intensive, progress in automated facial expression recognition and analysis is slowed. For the most detailed and comprehensive labeling or coding systems, such as Facial Action Coding System (FACS), three to four months is typically required to train a coder (’coding’ refers to the labeling of video using behavioral descriptors). Once trained, each minute of video may require 1 hour or more to code [9]. No wonder relatively few databases are yet available, especially those of real-world rather than posed behavior [61]. Second, research has been limited to the perceptual categories used by human observers. Those categories were operationalized in large part based on technology available in the past [36]. While a worthy goal of computer vision and machine learning is to efficiently replicate human-based measurement, should that be our only goal? New measurement approaches make possible new scientific discoveries. Two in particular, unsupervised and weakly-supervised learning have the potential to inform new ways of perceiving and modeling human behavior, to impact the infrastructure of science, and contribute to the design of perceptual computing applications. We propose that unsupervised and weakly-supervised approaches to automatic facial expression analysis can increase the efficiency of current measurement approaches in behavioral science, demonstrate convergent validity with supervised approaches, and lead to new knowledge in clinical and developmental science. Specifically, we will:
High Precision Information Extraction

Most fully automatic information extraction systems achieve less than 100% extraction precision and recall. On real applications these parameters typically vary between 50% to 95%, depending on the extraction method and source data. We present an information extraction system designed for applications where little or no error can be tolerated. The system is not fully automatic. Instead, the extraction is guided by the intervention of a human expert. This \expert in the loop" approach greatly ampliies the amount of extraction an individual can accomplish, while insuring that the extraction process is nearly 100% accurate. We used a tool we created called HPIEW (for High Precision Information Extraction Workbench) to extract several different elds from the text remark elds of the Protein Data Bank (PDB). The workbench allowed us to extract each eld from more than 5,000 PDB les in an afternoon, with extraction precision and recall estimated to be greater than 99.9%. We believe this approach may be useful for other extraction problems where extreme accuracy is required.
P2P collaborative filtering with privacy

With the evolution of the Internet and e-commerce, collaborative filtering (CF) and privacy-preserving collaborative filtering (PPCF) have become popular. The goal in CF is to generate predictions with decent accuracy, efficiently. The main issue in PPCF, however, is achieving such a goal while preserving users’ privacy. Many implementations of CF and PPCF techniques proposed so far are centralized. In centralized systems, data is collected and stored by a central server for CF purposes. Centralized storage poses several hazards to users because the central server controls users’ data.
Improvement of Decision Making Protocol for Duty Cycle Division Multiplexing (DCDM) System

Duty Cycle Division Multiplexing (DCDM) hasbeen shown to be able to improve utilization of the optical bandwidth. However, the challenge arises on its signal recoveryat the receiver ends. Decision making protocol plays an important role to determine the correctness of its regenerated data. Previous approach regenerate inaccurate data due to its assumption that all received signals are valid. Thus, the automatic mapping is used in their decision process with no consideration on invalid signals. Due to this motivation, we design a new signal recovery protocol for DCDM. In this protocol, the signal properties such as amplitude level, distance between slots, number of slot change and probabilities of occurrence are used in order to discriminate the received signal into an appropriate data. The simulation is established through OptiSystem simulator and Matlab programming. It is observed that an improvement of the BER by 16.2 percent can be achieved using the new proposed protocol.
Where does the time go? characterizing tail latency in memcached

To function correctly Online, Data-Intensive (OLDI) services require low and consistent service times. Maintaining predictable service times entails requiring 99th or higher percentile latency targets across hundreds to thousands of servers in the data-center. However, to maintain the 99th percentile targets servers are routinely run well below full utilization. The main difficulty in optimizing a server to run closer to peak utilization and maintain predictable 99th percentile response latencies is identifying and mitigating the causes of a request missing the target service time. In practice this analysis is challenging as requests and responses overlap their execution with respect to one another and traverse multiple layers of software, user/kernel protection boundaries, and the hardware/software divide. Traditional profiling methods that record the time being spent in each function usually yield few clues as to where a bottleneck may be present due to the many layers of software each consuming only a small fraction of time each. In this work we analyze the end-to-end sources of latency in a Memcached server from the wire through the kernel into the application and back again. To do so, we develop a tool that utilizes the Linux SystemTap infrastructure to measure latency throughout the many software layers that make up the complete request and response path for Memcached. While memory copies and the Linux networking stack are often suggested as major contributors to latency, we find that the main cause of missing response latency guarantees is the formation of standing queues and the application's inability to detect and remedy this situation.
Meeting Technology Challenges in Teacher Education: Responses from Schools and Colleges of Education.

Meeting Technology Challenges in Teacher Education: Responses from Schools and Colleges of Education The college level teachers is a critical variable in the shift toward acceptance of new technologies. Despite the recognized need for teacher to use and teach new technologies, and NCATE's new accreditation standards, there remains a large percentage of teachers unprepared to cope with technology in classrooms. While leading edge users of cyberspace are adjusting from a PC-centric environment to a netware-centric and digital environment, at the college level, we are still introducing word processing. Reengineering pedagogy in teacher education represents a profound paradigm shift which is well advance in our economy and our culture. We in teacher education have to overtake our colleagues in the other professional schools on campus as well as the corporate world. The data analyzed in this study were generated by a dean's task force of ACSESULGC/APU. Thirty-four cases were reported by twenty-three state and independent universities, geographically representative and varied in size and complexity. The data analysis focused on "successful strategies for technology-related faculty development" and included training, support, infrastructure, and funding. The article speaks to differential rates of change among colleges of education, the essential keys to successful strategies and the relative importance of infrastructure, budget, leadership and special incentives. We are reminded of Dewey's observation that all "knowledge is external", all "knowing is internal". Knowing is the process. The computer has become a powerful adjunct to the human mind and the "knowing" process. Colleges of education are under scrutiny not only by a university that is reengineering itself, but also by a larger society sorely disappointed by a public school system that is not performing to its expectations. If we fail to infuse and reform our curriculum and pedagogy with the most appropriate tools, we will put at risk the future of colleges of education. CAALLDOCTUBWACDEAB2.W131)
Generation and Characterization of Novel Magnetic Field-Responsive Biomaterials

We report the preparation of novel magnetic field-responsive tissue substitutes based on biocompatible multi-domain magnetic particles dispersed in a fibrin–agarose biopolymer scaffold. We characterized our biomaterials with several experimental techniques. First we analyzed their microstructure and found that it was strongly affected by the presence of magnetic particles, especially when a magnetic field was applied at the start of polymer gelation. In these samples we observed parallel stripes consisting of closely packed fibers, separated by more isotropic net-like spaces. We then studied the viability of oral mucosa fibroblasts in the magnetic scaffolds and found no significant differences compared to positive control samples. Finally, we analyzed the magnetic and mechanical properties of the tissue substitutes. Differences in microstructural patterns of the tissue substitutes correlated with their macroscopic mechanical properties. We also found that the mechanical properties of our magnetic tissue substitutes could be reversibly tuned by noncontact magnetic forces. This unique advantage with respect to other biomaterials could be used to match the mechanical properties of the tissue substitutes to those of potential target tissues in tissue engineering applications.
Controllability and motion algorithms for underactuated Lagrangian systems on Lie groups

We provide controllability tests and motion control algorithms for underactuated mechanical control systems on Lie groups with Lagrangian equal to kinetic energy. Examples include satellite and underwater vehicle control systems with the number of control inputs less than the dimension of the configuration space. Local controllability properties of these systems are characterized, and two algebraic tests are derived in terms of the symmetric product and the Lie bracket of the input vector fields. Perturbation theory is applied to compute approximate solutions for the system under small-amplitude forcing; in-phase signals play a crucial role in achieving motion along symmetric product directions. Motion control algorithms are then designed to solve problems of point-to-point reconfiguration, static interpolation and exponential stabilization. We illustrate the theoretical results and the algorithms with applications to models of planar rigid bodies, satellites and underwater vehicles.
Tunneling of the 3rd kind

We study a new kind of tunneling of particles through a barrier particular to quantum field theory. Here, the particles traverse the barrier by splitting into a virtual pair of particles of a different species which interacts only very weakly with the barrier and can therefore pass through it. Behind the barrier, the pair recombines into a particle of the original species. As an example, we discuss the case where photons split into a pair of minicharged particles. This process could be observed in experiments of the light-shining-through-a-wall type and may be used to search for minicharged particles in laboratory experiments.
Penetration of Salmonella through a polarized Madin-Darby canine kidney epithelial cell monolayer

Many intracellular parasites are capable of penetrating host epithelial barriers. To study this process in more detail we examined the interactions between the pathogenic bacteria Salmonella choleraesuis and polarized epithelial monolayers of Madin-Darby canine kidney (MDCK) cells grown on membrane filters. Association of bacteria with the MDCK cell apical surface was an active event, requiring bacterial RNA and protein synthesis, and was blocked by low temperatures. Salmonella were internalized within a membrane-bound vacuole and exhibited penetration through, but not between MDCK cells. A maximum of 14 Salmonella per MDCK cell crossed the monolayer per hour to the basolateral surface yet the monolayer remained viable and impermeable to Escherichia coli. Apical S. choleraesuis infection resulted in an increase in paracellular permeability but the MDCK intercellular contacts were not significantly disrupted. Basolateral S. choleraesuis infection was inefficient, and only small numbers of S. choleraesuis penetrated to the apical medium.
Myosin 1E localizes to actin polymerization sites in lamellipodia, affecting actin dynamics and adhesion formation

Summary Because the actin network in active lamellipodia is continuously assembling at the edge, moving inward and disassembling, there is a question as to how actin-binding proteins and other components are transported to the leading edge and how nascent adhesions are stabilized. Active transport could play a significant role in these functions but the components involved are unknown. We show here that Myosin 1E (a long tailed Myosin 1 isoform) rapidly moves to the tips of active lamellipodia and to actin-rich early adhesions, unlike Myosin 1G, 1B or 1C (short tailed isoforms). Myosin 1E co-localizes with CARMIL, FHOD1, Arp3 and &bgr;3-integrin in those early adhesions. But these structures precede stable paxillin-rich adhesions. Myosin 1E movement depends upon actin-binding domains and the presence of an SH3 oligomerization domain. Overexpression of a Myosin 1E deletion mutant without the extreme C-terminal interacting (SH3) domain (Myosin 1E&Dgr;SH3) increases edge fluctuations and decreases stable adhesion lifetimes. In contrast, overexpression of Myosin 1E full tail domain (TH1+TH2+TH3/SH3) decreases edge fluctuation. In Myosin 1E knockdown cells, and more prominently in cells treated with Myosin 1 inhibitor, cell–matrix adhesions are also short-lived and fail to mature. We suggest that, by moving to actin polymerization sites and early adhesion sites in active lamellipodia, Myosin 1E might play important roles in transporting not only important polymerizing proteins but also proteins involved in adhesion stabilization.
Polyclonal nature of diffuse proliferation of interstitial cells of Cajal in patients with familial and multiple gastrointestinal stromal tumours

Background: Diffuse proliferation of interstitial cells of Cajal (ICCs) in the myenteric plexus layer of the intestine has been described in patients with familial and multiple gastrointestinal stromal tumours (GISTs). However, it is not fully understood whether proliferation is polyclonal or monoclonal. Aims: To evaluate the clonal nature of diffuse ICC proliferation in familial and multiple GIST cases, we carried out clonal analysis using inactivation at the human androgen receptor (HUMARA) locus. Materials and methods: Diffuse ICC proliferation tissues from three female patients were microdissected using a laser capture microdissection (LCM) system. Normal intestinal mucosal tissues were also microdissected for polyclonal controls and GIST tissues for monoclonal controls from the same patients, and genomic DNA was extracted. After digestion by restriction enzyme HhaI, the HUMARA locus was amplified by a fluorescent polymerase chain reaction (PCR) procedure and the PCR products were analysed. Results: One case was uninformative because it was homozygous at the HUMARA locus. In the two other cases, PCR products from the diffuse ICC proliferation showed two alleles as well as those from normal intestinal mucosal tissues, indicating that ICC proliferation was polyclonal. In contrast, PCR products from associated GIST tissues showed only one allele, indicating that GISTs were monoclonal. Conclusion: The results suggested that diffuse ICC proliferation in familial and multiple GIST cases was non-neoplastic hyperplasia.
Application of Feed-Forward Neural Networks Autoregressive Models in Gross DomesticProduct Prediction

In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression’s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.
T and B cell in hapten-specific carrier-determined tolerance

BDF1 mice were made tolerant by a single i.v. injection of 1 mg of DNAP- gamma1 or by weekly i.v. injections of 0.2 mg of DNP-gamma1 given for a month. In both instances, spleen cells of tolerant animals were fractionated to obtain pure populations of T cells (nonimmunoglobulin- bearing cells), referred to as tolerant T cells, and B cells (immunoglobulin-bearing cells) referred to as tolerant B cells (immunoglobulin-bearing cells) referred to as tolerant B cells. The control cells were similarly fractionated to obtain normal T and B cells. Mixtures of tolerant T cells and normal B cells, or conversely, normal T cells and tolerant B cells were used to repopulate lethally irradiated recipients. These recipients were then immunized with dinitrophenyl-keyhole limpet haemocyanin and in certain instances with other antigen horse red blood cells. The immune response to both antigens was measured using the direct hemolytic plaque assay. It was found that both T and B cells were tolerant and that tolerance was hapten specific at both T- and B-cell levels. While B-cell tolerance was demonstrated at a 1/1 T/B ratio, a 4/1 T/B ratio was necessary to show T-cell tolerance. Thus, the hapten-specific carrier-determined tolerance involves not only B cells but also T cells. The implication of this finding for the cellular mechanism of tolerance in an experimental model closely related to self tolerance is discussed.
How much energy is needed to run a wireless network?

In order to quantify the energy efficiency of a wireless network, the power consumption of the entire system needs to be captured. In this article, the necessary extensions with respect to existing performance evaluation frameworks are discussed. The most important addenda of the proposed energy efficiency evaluation framework (E3F) are a sophisticated power model for various base station types, as well as large-scale long-term traffic models. The BS power model maps the RF output power radiated at the antenna elements to the total supply power of a BS site. The proposed traffic model emulates the spatial distribution of the traffic demands over large geographical regions, including urban and rural areas, as well as temporal variations between peak and off-peak hours. Finally, the E3F is applied to quantify the energy efficiency of the downlink of a 3GPP LTE radio access network.
A multi-segment lane-switch algorithm for efficient real-time lane detection

Lane detection is an important aspect of intelligent transportation systems. In this study, we propose a fast real-time lane-detection algorithm based on an automated multi-segment lane-switch scheme which is integrated with the traditional Random Sample Consensus algorithm to improve the performance of the algorithm. To conduct our experiments, we used videos captured from urban roads and highways to show that our algorithm has higher efficiency than and comparable precision to other state-of-the-art algorithms.