Miracle-dz/UniFAR-FTUs huggingface dataset:
Lying through the eyes: detecting lies through eye movements

In this pilot study, we investigated if it is possible to detect lies through eye gaze behavior. Earlier research suggests that lying increases the cognitive load, resulting in less eye -movements and shorter saccade amplitudes. To investigate these findings further, a structured interview was conducted with three subjects. During the interview, subjects were supposed to lie in half of their answers. The subjects' eye gazes were tracked during the interview session. We hypothesized that people show shorter saccade amplitudes and tend to engage in less eye movements when lying. A significant difference could be observed for saccade amplitudes between the truth telling and lie telling situations. The overall results support the theory that cognitive load decreases the number of eye movements, but our analysis also revealed significant individual differences. This raised the question whether different individuals have different ways of handling deception and whether different viewing behavior patterns could be found for different groups of individuals.
Structures and Metal-Binding Properties of Helicobacter pylori Neutrophil-Activating Protein with a Di-Nuclear Ferroxidase Center

Helicobacter pylori causes severe diseases, such as chronic gastritis, peptic ulcers, and stomach cancers. H. pylori neutrophil-activating protein (HP-NAP) is an iron storage protein that forms a dodecameric shell, promotes the adhesion of neutrophils to endothelial cells, and induces the production of reactive oxygen radicals. HP-NAP belongs to the DNA-protecting proteins under starved conditions (Dps) family, which has significant structural similarities to the dodecameric ferritin family. The crystal structures of the apo form and metal-ion bound forms, such as iron, zinc, and cadmium, of HP-NAP have been determined. This review focused on the structures and metal-binding properties of HP-NAP. These metal ions bind at the di-nuclear ferroxidase center (FOC) by different coordinating patterns. In comparison with the apo structure, metal loading causes a series of conformational changes in conserved residues among HP-NAP and Dps proteins (Trp26, Asp52, and Glu56) at the FOC. HP-NAP forms a spherical dodecamer with 23 symmetry including two kinds of pores. Metal ions have been identified around one of the pores; therefore, the negatively-charged pore is suitable for the passage of metal ions.
Identifying Error Pathways during Elbow and Knee Replacements

The aim of our study was to identify errors and error pathways during joint replacements and to propose improvements. A time-action and error analysis method was adapted for use during surgery. The error analysis consisted of identifying all possible errors, determining error paths presented in an error chart, quantifying errors, and determining the impact of errors. This method was used to evaluate joint replacements. We evaluated five knee and 11 elbow replacements done by two experienced surgeons. The main error for elbow replacements was caused by inadequate instruments. The main error for knee replacements was caused by inexperienced nurses being unfamiliar with guiding instruments. The time-action analysis showed a large variation in procedure duration. The main surgical limitations for both procedures were waiting caused by the cementing process and waiting caused by inexperienced scrub nurses. Our study identified errors and surgical limitations during joint replacements by using time-action and error analysis. Placement of both prostheses will benefit from new fixation techniques, a more experienced nursing staff, and more organized instrument tables.
Causality in Hundreds of Narratives of the Same Events

Empirical research supporting computational models of narrative is often constrained by the lack of large-scale corpora with deep annotation. In this paper, we report on our annotation and analysis of a dataset of 283 individual narrations of the events in two short video clips. The utterances in the narrative transcripts were annotated to align with known events in the source videos, offering a unique opportunity to study the regularities and variations in the way that different people describe the exact same set of events. We identified the causal relationships between events in the two video clips, and investigated the role that causality plays in determining whether subjects will mention a particular story event and the likelihood that these events will be told in the order that they occurred in the original videos.
Venous Reconstruction in Surgery of Meningiomas Invading the Sagittal and Transverse Sinuses

SURGERY OF MENINGIOMAS INVOLVING MAJOR DURAL SINUSES LEAVES THE SURGEON CONFRONTED WITH A DIFFICULT DILEMMA: leave the fragment invading the sinus in place and have a higher risk of recurrence, or attempt a total removal with or without venous reconstruction and expose the patient to a potentially greater operative danger. The authors report a series of 47 meningiomas (41 of the sagittal sinus, 4 of the transverse sinus and 2 of the torcular) in whom gross total removal was achieved in all cases, and venous reconstruction (of various types) attempted in a majority. Thirty-nine patients had a good outcome and resumed their previous activities. There was a permanent neurological deficit in five due to infarction secondary to injury of central veins (all in the sagittal sinus midthird). Three patients died from brain swelling; all with meningioma totally occluding the sinus and in whom resection was achieved without sinus reconstruction. There were two recurrences in this series which has a mean follow-up of 7.5 years.The authors' surgical experience led them to favor whenever possible, total removal with sinus reconstruction, using a patch for meningiomas with partial sinus invasion and a venous bypass for those with total sinus occlusion.
Insights into the Fold Organization of TIM Barrel from Interaction Energy Based Structure Networks

There are many well-known examples of proteins with low sequence similarity, adopting the same structural fold. This aspect of sequence-structure relationship has been extensively studied both experimentally and theoretically, however with limited success. Most of the studies consider remote homology or “sequence conservation” as the basis for their understanding. Recently “interaction energy” based network formalism (Protein Energy Networks (PENs)) was developed to understand the determinants of protein structures. In this paper we have used these PENs to investigate the common non-covalent interactions and their collective features which stabilize the TIM barrel fold. We have also developed a method of aligning PENs in order to understand the spatial conservation of interactions in the fold. We have identified key common interactions responsible for the conservation of the TIM fold, despite high sequence dissimilarity. For instance, the central beta barrel of the TIM fold is stabilized by long-range high energy electrostatic interactions and low-energy contiguous vdW interactions in certain families. The other interfaces like the helix-sheet or the helix-helix seem to be devoid of any high energy conserved interactions. Conserved interactions in the loop regions around the catalytic site of the TIM fold have also been identified, pointing out their significance in both structural and functional evolution. Based on these investigations, we have developed a novel network based phylogenetic analysis for remote homologues, which can perform better than sequence based phylogeny. Such an analysis is more meaningful from both structural and functional evolutionary perspective. We believe that the information obtained through the “interaction conservation” viewpoint and the subsequently developed method of structure network alignment, can shed new light in the fields of fold organization and de novo computational protein design.
Metalloproteases with EGF, CUB, and thrombospondin-1 domains function in molting of Caenorhabditis elegans

Abstract Functional analysis using RNAi was performed on eleven genes for metalloproteases of the M12A family in Caenorhabditis elegans and the interference of the C17G1.6 gene (nas-37) was found to cause incomplete molting. The RNAi of the C26C6.3 gene (nas-36) also caused a similar molting defect but not so severely as that of the nas-37 gene. Both the genes encode an astacinlike metalloprotease with an epidermal growth factor (EGF) like domain, a CUB domain, and a thrombospondin-1 domain, in this order. The promoterdriven green fluorescent protein (GFP) expression analysis suggested that they are expressed in hypodermal cells throughout the larval stages and in the vulva of adult animals. In the genetic background of rde-1(ne219), where RNAi does not work, the molting defect caused by the nas-37 interference was observed when the transgenic wildtype rde-1 gene was expressed under the control of the dpy-7 promoter, known to be active in the hypodermal cells, but not under the control of the myo-3 promoter, active in the muscular cells. Therefore these proteases are thought to be secreted by the hypodermal cells and to participate in shedding of old cuticles.
The Neural Mechanisms Underlying the Acute Effect of Cigarette Smoking on Chronic Smokers

Although previous research had related structural changes and impaired cognition to chronic cigarette smoking, recent neuroimaging studies have associated nicotine, which is a main chemical substance in cigarettes, with improvements in cognitive functions (e.g. improved attention performance). However, information about the alterations of whole-brain functional connectivity after acute cigarette smoking is limited. In this study, 22 smokers underwent resting-state functional magnetic resonance imaging (rs-fMRI) after abstaining from smoking for 12 hours (state of abstinence, SOA). Subsequently, the smokers were allowed to smoke two cigarettes (state of satisfaction, SOS) before they underwent a second rs-fMRI. Twenty non-smokers were also recruited to undergo rs-fMRI. In addition, high-resolution 3D T1-weighted images were acquired using the same magnetic resonance imaging(fMRI)scanner for all participants. The results showed that smokers had structural changes in insula, thalamus, medial frontal cortex and several regions of the default mode network (DMN) compared with non-smokers. Voxel-wise group comparisons of newly developed global brain connectivity (GBC) showed that smokers in the SOA condition had higher GBC in the insula and superior frontal gyrus compared with non-smokers. However, smokers in the SOS condition demonstrated significantly lower GBC in several regions of the DMN, as compared with smokers in the SOA condition. These results suggest that structural integrity combined with dysfunction of the DMN might be involved in relapses after a short period of time among smokers.
Lysis to Kill: Evaluation of the Lytic Abilities, and Genomics of Nine Bacteriophages Infective for Gordonia spp. and Their Potential Use in Activated Sludge Foam Biocontrol

Nine bacteriophages (phages) infective for members of the genus Gordonia were isolated from wastewater and other natural water environments using standard enrichment techniques. The majority were broad host range phages targeting more than one Gordonia species. When their genomes were sequenced, they all emerged as double stranded DNA Siphoviridae phages, ranging from 17,562 to 103,424 bp in size, and containing between 27 and 127 genes, many of which were detailed for the first time. Many of these phage genomes diverged from the expected modular genome architecture of other characterized Siphoviridae phages and contained unusual lysis gene arrangements. Whole genome sequencing also revealed that infection with lytic phages does not appear to prevent spontaneous prophage induction in Gordonia malaquae lysogen strain BEN700. TEM sample preparation techniques were developed to view both attachment and replication stages of phage infection.
A model to predict survival in patients with end‐stage liver disease

A recent mandate emphasizes severity of liver disease to determine priorities in allocating organs for liver transplantation and necessitates a disease severity index based on generalizable, verifiable, and easily obtained variables. The aim of the study was to examine the generalizability of a model previously created to estimate survival of patients undergoing the transjugular intrahepatic portosystemic shunt (TIPS) procedure in patient groups with a broader range of disease severity and etiology. The Model for End‐Stage Liver Disease (MELD) consists of serum bilirubin and creatinine levels, International Normalized Ratio (INR) for prothrombin time, and etiology of liver disease. The model's validity was tested in 4 independent data sets, including (1) patients hospitalized for hepatic decompensation (referred to as “hospitalized” patients), (2) ambulatory patients with noncholestatic cirrhosis, (3) patients with primary biliary cirrhosis (PBC), and (4) unselected patients from the 1980s with cirrhosis (referred to as “historical” patients). In these patients, the model's ability to classify patients according to their risk of death was examined using the concordance (c)‐statistic. The MELD scale performed well in predicting death within 3 months with a c‐statistic of (1) 0.87 for hospitalized patients, (2) 0.80 for noncholestatic ambulatory patients, (3) 0.87 for PBC patients, and (4) 0.78 for historical cirrhotic patients. Individual complications of portal hypertension had minimal impact on the model's prediction (range of improvement in c‐statistic: <.01 for spontaneous bacterial peritonitis and variceal hemorrhage to ascites: 0.01‐0.03). The MELD scale is a reliable measure of mortality risk in patients with end‐stage liver disease and suitable for use as a disease severity index to determine organ allocation priorities.
Spinal Cord Stimulation

A highly invasive form of electroanalgesia used to treat various chronic pain syndromes, which resist treatment by more common means. It is also used to treat peripheral ischemia, peripheral vascular disease, complex regional pain syndrome, intractable angina, chronic mesenteric ischemia, and diabetic peripheral arterial occlusive disease.
Dependable Data Repairing with Fixing Rules

One of the main challenges that data-cleaning systems face is to automatically identify and repair data errors in a dependable manner. Though data dependencies (also known as integrity constraints) have been widely studied to capture errors in data, automated and dependable data repairing on these errors has remained a notoriously difficult problem. In this work, we introduce an automated approach for dependably repairing data errors, based on a novel class of fixing rules. A fixing rule contains an evidence pattern, a set of negative patterns, and a fact value. The heart of fixing rules is deterministic: given a tuple, the evidence pattern and the negative patterns of a fixing rule are combined to precisely capture which attribute is wrong, and the fact indicates how to correct this error. We study several fundamental problems associated with fixing rules and establish their complexity. We develop efficient algorithms to check whether a set of fixing rules are consistent and discuss approaches to resolve inconsistent fixing rules. We also devise efficient algorithms for repairing data errors using fixing rules. Moreover, we discuss approaches on how to generate a large number of fixing rules from examples or available knowledge bases. We experimentally demonstrate that our techniques outperform other automated algorithms in terms of the accuracy of repairing data errors, using both real-life and synthetic data.
Classification of Medicinal Plant Leaves for Types and Diseases with Hybrid Deep Learning Methods

Leaf images are often used to detect plant diseases because most disease symptoms appear on the leaves. Analyzes performed by experts in the laboratory environment are expensive and time consuming. Therefore, there is a need for automated plant disease detection systems that are both economical and can help diagnose early symptoms more accurately. In this study, a deep learning-based methodology is presented for the classification of leaf diseases of plants, which are very similar in color, texture, vein and shape and cannot be noticed by non-experts, which are important for traditional medicine and pharmaceutical industry. In the model development process, 7 pre-learning deep learning algorithms and an image data set created from plant leaves in 10 categories were preferred. The proposed model classifies the plant type and diseased condition in the dataset. In the first step of training the model, different learning rates were tested with optimum hyperparameters. In the second part, a test accuracy rate of 98.69% was achieved with the DenseNet121 model, with increased data. At the last stage, after the edge detection processes, the test accuracy value of 67.92% was reached with the DenseNet 121 model.
Architecture of the Spectra 22 speech processor.

Cochlear Pty Limited's earliest speech processors relied heavily on formant extraction and presented the formant information on a small number of electrodes. In background noise, however, this is a disadvantage because there is no redundancy built in. In the presence of competing noise, for­ mantextractors cannot provide alternative information. Partly as a result of this, more parallel information was provided in the form ofamplitude data from fixed filters to supplement the formant extraction data. This was implemented in Multipeak (Mpeak) by using three fixed filters at frequencies around the top of the second formant frequency band.
On Monopolistic Licensing Strategies Under Asymmetric Information

Consider a research lab that owns a patent on a new technology but cannot develop a marketable final product based on the new technology. There are two downstream firms that might successfully develop the new product. If the downstream firms' benefits from being the sole supplier of the new product are private information, the research lab will sometimes sell two licences, even though under complete information it would have sold one exclusive licence. This is in contrast to the standard result that a monopolist will sometimes serve less, but never more buyers when there is private information.
Serine-Rich Repeat Adhesins Contribute to Streptococcus gordonii-Induced Maturation of Human Dendritic Cells

Dendritic cells (DCs) play a pivotal role in the induction of immunity by recognition, capture, process, and presentation of antigens from infectious microbes. Streptococcus gordonii is able to cause life-threatening systemic diseases such as infective endocarditis. Serine-rich repeat (SRR) glycoproteins of S. gordonii are sialic acid-binding adhesins mediating the bacterial adherence to the host and the development of infective endocarditis. Thus, the SRR adhesins are potentially involved in the bacterial adherence to DCs and the maturation and activation of DCs required for the induction of immunity to S. gordonii. Here, we investigated the phenotypic and functional changes of human monocyte-derived DCs treated with wild-type S. gordonii or the SRR adhesin-deficient mutant. The mutant poorly bound to DCs and only weakly increased the expression of CD83, CD86, MHC class II, and PD-L1 on DCs compared with the wild-type. In addition, the mutant induced lower levels of TNF-α, IL-6, and IL-12 than the wild-type in DCs. When DCs sensitized with the mutant were co-cultured with autologous T cells, they induced weaker proliferation and activation of T cells than DCs stimulated with the wild-type. Blockade of SRR adhesin with 3′-sialyllactose markedly reduced S. gordonii binding and internalization, causing attenuation of the bacterial immunostimulatory potency in DC maturation. Collectively, our results suggest that SRR adhesins of S. gordonii are important for maturation and activation of DCs.
Cross-media retrieval with semantics clustering and enhancement

Cross-media retrieval, which uses a text query to search for images and vice-versa, has attracted a wide attention in recent years. The mostly existing cross-media retrieval methods aim at finding a common subspace and maximizing different modalities correlations. But these approaches do not directly capture the underlying semantic information of different modalities. This paper proposes a novel cross-media retrieval by semantics clustering and enhancement, where a semantic-preserved mapping is learned from the original space to the target semantic space. Meanwhile, In order to improve the demarcation of semantic space, we enhance the semantic manifold by learning a dimension invariant matrix. Our approach not only maximizes the correlation between different modalities, but also increases the discriminative ability among different categories. Experiments show that our approach outperforms the popular methods on two real word datasets.
State Abstraction in Real-time Heuristic Search : The Director ’ s Cut

Real-time heuristic search methods are used by situated agents in applications that require the amount of planning per move to be independent of the problem size. Such agents plan only a few actions in a local search space and avoid getting trapped in local minima by improving their heuristic function over time. We extend a wide class of real-time search algorithms with automatically built state abstraction. We then prove completeness and convergence of the resulting novel family of algorithms. Finally, we analyze effects of abstraction in an extensive empirical study situated in the goal-directed navigation problem. In particular, we demonstrate the new algorithms are most efficient in trading pairs of antagonistic performance measures such as response time and overall convergence speed.
Versatile SQUID Susceptometer With Multiple Measurement Modes

We present a state of the art SQUID-based susceptometer which supports lock-in style vibrating sample magnetometer (VSM) measurements as well as traditional dc scans using a single motion control and detection circuit for both measurements. The dc scan fits the measured SQUID response as function of position to an expected response waveform and includes algorithm enhancements for better rejection of external magnetic signals. The VSM-style measurement uses a novel approach for its data acquisition, which is designed to minimize cross talk between the mechanical movement of the sample and the measured signal. In addition, the superconducting gradiometer of the detection circuit is optimized for best signal-to-noise performance in both types of measurements, achieving sensitivity in the range of 10-8 emu at fields up to 7 Tesla. This dual measurement capability allows a single instrument to measure a wide variety of samples by choosing the method most fitting to constraints imposed by the sample, e.g., limiting thermal and magnetic field variations or reducing forces the sample is exposed to during the measurement. Special consideration is given to a detailed analysis of the advantages of the different measurement methods, the influence of measurement parameters on the reported results, as well as the effect of sample properties and sample geometry on the reported moment.
Multimodal Content Adaptations for Heterogeneous Devices

We present Multiface, a multimodal dialog system that allows users to interact using different devices such as desktop computers, PDAs, and mobile phones. Users can request information and will receive multimodal responses, where the presented content and its modality are customized to individual and the device they are using. In addition, the system will attempt to assess the user's understanding and adapt its future responses accordingly. Multiface uses a plan-based approach to produce adaptive content and modalities from an annotated document and models of the user and device.