Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of the Brief Confusion Assessment Method for Screening Delirium in Elderly Medical Patients in a German Emergency Department

BACKGROUND Delirium is frequent in elderly patients presenting in the emergency department (ED). Despite the severe prognosis, the majority of delirium cases remain undetected by emergency physicians (EPs). At the time of our study there was no valid delirium screening tool available for EDs in German-speaking regions. We aimed to evaluate the brief Confusion Assessment Method (bCAM) for a German ED during the daily work routine. METHODS We implemented the bCAM into practice in a German interdisciplinary high-volume ED and evaluated the bCAM's validity in a convenience sample of medical patients aged ≥ 70 years. The bCAM, which assesses four core features of delirium, was performed by EPs during their daily work routine and compared to a criterion standard based on the criteria for delirium as described in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. RESULTS Compared to the criterion standard, delirium was found to be present in 46 (16.0%) of the 288 nonsurgical patients enrolled. The bCAM showed 93.8% specificity (95% confidence interval [CI] = 90.0%-96.5%) and 65.2% sensitivity (95% CI = 49.8%-78.7%). Positive and negative likelihood ratios were 10.5 and 0.37, respectively, while the odds ratio was 28.4. Delirium was missed in 10 of 16 cases, since the bCAM did not indicate altered levels of consciousness and disorganized thinking. The level of agreement with the criterion standard increased for patients with low cognitive performance. CONCLUSION This was the first study evaluating the bCAM for a German ED and when performed by EPs during routine work. The bCAM showed good specificity, but only moderate sensitivity. Nevertheless, application of the bCAM most likely improves the delirium detection rate in German EDs. However, it should only be applied by trained physicians to maximize diagnostic accuracy and hence improve the bCAM's sensitivity. Future studies should refine the bCAM.
Polarization Reconfigurable Broadband Dielectric Resonator Antenna With a Lattice Structure

In this paper, a novel technique to design a broadband circularly polarized dielectric resonator antenna (DRA) with a lattice structure is proposed for the first time. Two resonant modes of TE111 and TE211 can be simultaneously excited through a cross-slot to constitute a wide operating bandwidth. On this basis, its reconfigurable version, which can operate in left-handed circular polarization (CP), right-handed CP, and linear polarization (LP) states, has been further presented. The latter possesses a simple design procedure to implement the reconfigurability since all the reconfigurable feeding circuits are isolated from the radiating DRA by the ground plane and only five p-i-n diodes are needed. Besides, a Teflon-based template is adopted to solve the problem of dielectric blocks’ critical placement and alignment tolerances. A backed cavity based on substrate integrated waveguide technology is introduced to reduce the unwanted radiation from the surface wave. Measured results indicate that the reconfigurable prototype can achieve a 3-dB axial ratio bandwidth of 20.7% for CP states, an impedance bandwidth of 29.6% for LP state with a cross-polarization level of better than −20 dB, and a peak gain over 7.3 dBi for all states. The proposed antenna can be used for polarization diversity applications of the modern wireless system.
Suppression of IKK, but not activation of p53 is responsible for cell death mediated by naturally occurring oxidized tetranortriterpenoid

Tetranortriterpenoids (limonoids) obtained from the neem tree (Azadirachta indica) have gained significant attention due to their anti‐proliferative properties. Here we are investigating the role of a highly oxidized tetranortriterpenoid, azadirachtin on induction of the cell death. Using various apoptotic assays, we show that azadirachtin induces cell death independent of cell types. Although azadirachtin‐treated cells show increased expression of p53, but no phosphorylation of p53 (at Ser15 and Ser46) is detected. In silico analysis reveals that azadirachtin interacts with Mdm2 in the p53 binding site, postulating the mutually exclusive interaction of p53 and azadirachtin with Mdm2. Surprisingly, azadirachtin potentiates cell death efficiently in both p53 wild‐type and p53 negative cells. In addition, we find azadirachtin suppresses nuclear transcription factor kappaB (NF‐κB) by inhibiting the phosphorylation of upstream inhibitory subunit of NF‐κB (IκB) kinase (IKK). Further, azadirachtin is unable to potentiate apoptosis in NF‐κB‐downregulated (IκB‐DN) cells, whereas ectopic expression of p65 rescues azadirachtin‐mediated apoptosis, regardless of their p53 status. Hence, our data suggest that azadirachtin mediates cell death through inhibition of NF‐κB, but not due to the activation of p53. In conclusion, this study proposes azadirachtin as a potential therapeutic agent where insensitivity toward chemotherapy occurs due to the inactivation or mutations in p53.
Gaussian fluctuations for the classical XY model

We study the classical XY model in bounded domains of $\mathbb{Z}^{d}$ with Dirichlet boundary conditions. We prove that when the temperature goes to zero faster than a certain rate as the lattice spacing goes to zero, the fluctuation field converges to a standard Gaussian white noise. This and related results also apply to a large class of gradient field models.
Binned Kernels for Anomaly Detection in Multi-timescale Data using Gaussian Processes

Financial services and technology companies invest significantly in monitoring their complex technology infrastructures to allow for quick responses to technology failures. Because of the volume and velocity of signals monitored (e.g., customer transaction volume, API calls, server CPU utilization, etc.), they require sophisticated models of normal system behavior to determine when a component falls into an anomalous state. Gaussian processes (GPs) are flexible, Bayesian nonparametric models that have successfully been used for time series forecasting, interpolation, and anomaly detection in complex data sets. Despite the growing use of GPs for time series analysis in the literature, these methods scale poorly with the size of the data. In particular, data sets containing multiple timescales can pose a problem for GPs, as they can require a large number of points for training. We describe a novel method for including long and short timescale information without including an impractical number of data points through the use of a binned process, defined as the definite integral over a latent Gaussian process. This results in a binned covariance function for the time series, which we use to fit and forecast data at multiple resolutions. The resulting models achieve higher accuracy with fewer data points than their non-binned counterparts, and are more robust to long tailed noise, heteroskedasticity, and data artifacts.
Recommendations in Child Development Textbooks for Teachers’ Developmentally Appropriate Practices

Recommendations for teachers’ work with children were identified in eleven popular textbooks focused on child development. Coding yielded 2,200 recommendations. Recommendations emphasized cognition, behavioral learning, and social-emotional development; generally transcended a single age level; and typically did not refer to an underlying theory. Specific age levels were represented distinctively. Consensus practices found in six or more books concentrated on cognitive development, social-emotional development, family and community motivation, management, and self-regulation more so than on foundational principles, research and assessment, physical development, or language and literacy. Limitations and implications for future research and the preparation of teacher candidates are examined.
A Systematic Approach to the Selection of the Appropriate Avibactam Concentration for Use with Ceftazidime in Broth Microdilution Susceptibility Testing

ABSTRACT Selection of the avibactam concentration to combine with ceftazidime in susceptibility testing was determined using Gram-negative isolates with characterized β-lactamases predefined as susceptible or resistant, based on the known inhibition spectrum of avibactam. MIC values were determined by broth microdilution of ceftazidime with fixed concentrations and ratios of avibactam. A constant concentration of 4 μg/ml of avibactam was selected for susceptibility testing with ceftazidime because of its ability to correctly categorize susceptible and resistant isolates while minimizing categorical errors.
Improving Network Intrusion Detection Classifiers by Non-payload-Based Exploit-Independent Obfuscations: An Adversarial Approach

Machine-learning based intrusion detection classifiers are able to detect unknown attacks, but at the same time, they may be susceptible to evasion by obfuscation techniques. An adversary intruder which possesses a crucial knowledge about a protection system can easily bypass the detection module. The main objective of our work is to improve the performance capabilities of intrusion detection classifiers against such adversaries. To this end, we firstly propose several obfuscation techniques of remote attacks that are based on the modification of various properties of network connections; then we conduct a set of comprehensive experiments to evaluate the effectiveness of intrusion detection classifiers against obfuscated attacks. We instantiate our approach by means of a tool, based on NetEm and Metasploit, which implements our obfuscation operators on any TCP communication. This allows us to generate modified network traffic for machine learning experiments employing features for assessing network statistics and behavior of TCP connections. We perform the evaluation of five classifiers: Gaussian Naive Bayes, Gaussian Naive Bayes with kernel density estimation, Logistic Regression, Decision Tree, and Support Vector Machines. Our experiments confirm the assumption that it is possible to evade the intrusion detection capability of all classifiers trained without prior knowledge about obfuscated attacks, causing an exacerbation of the TPR ranging from 7.8% to 66.8%. Further, when widening the training knowledge of the classifiers by a subset of obfuscated attacks, we achieve a significant improvement of the TPR by 4.21% - 73.3%, while the FPR is deteriorated only slightly (0.1% - 1.48%). Finally, we test the capability of an obfuscations-aware classifier to detect unknown obfuscated attacks, where we achieve over 90% detection rate on average for most of the obfuscations.
Spin‐Dependent Processes Measured without a Permanent Magnet

A novel Hall circuit design that can be incorporated into a working electrode, which is used to probe spin‐selective charge transfer and charge displacement processes, is reviewed herein. The general design of a Hall circuit based on a semiconductor heterostructure, which forms a shallow 2D electron gas and is used as an electrode, is described. Three different types of spin‐selective processes have been studied with this device in the past: i) photoinduced charge exchange between quantum dots and the working electrode through chiral molecules is associated with spin polarization that creates a local magnetization and generates a Hall voltage; ii) charge polarization of chiral molecules by an applied voltage is accompanied by a spin polarization that generates a Hall voltage; and iii) cyclic voltammetry (current–voltage) measurements of electrochemical redox reactions that can be spin‐analyzed by the Hall circuit to provide a third dimension (spin) in addition to the well‐known current and voltage dimensions. The three studies reviewed open new doors into understanding both the spin current and the charge current in electronic materials and electrochemical processes.
Ensembles for clinical entity extraction

Health records are a valuable source of clinical knowledge and Natural Language Processing techniques have previously been applied to the text in health records for a number of applications. Often, a first step in clinical text processing is clinical entity recognition; identifying, for example, drugs, disorders, and body parts in clinical text. However, most of this work has focused on records in English.Therefore, this work aims to improve clinical entity recognition for languages other than English by comparing the same methods on two different languages, specifically by employing ensemble methods. Models were created for Spanish and Swedish health records using SVM, Perceptron, and CRF and four different feature sets, including unsupervised features. Finally, the models were combined in ensembles. Weighted voting was applied according to the models individual F-scores. In conclusion, the ensembles improved the overall performance for Spanish and the precision for Swedish.
CodeMaster - Automatic Assessment and Grading of App Inventor and Snap! Programs

The development of computational thinking is a major topic in K-12 education. Many of these experiences focus on teaching programming using block-based languages. As part of these activities, it is important for students to receive feedback on their assignments. Yet, in practice it may be difficult to provide personalized, objective and consistent feedback. In this context, automatic assessment and grading has become important. While there exist diverse graders for text-based languages, support for block-based programming languages is still scarce. This article presents CodeMaster, a free web application that in a problem-based learning context allows to automatically assess and grade projects programmed with App Inventor and Snap! It uses a rubric measuring computational thinking based on a static code analysis. Students can use the tool to get feedback to encourage them to improve their programming competencies. It can also be used by teachers for assessing whole classes easing their workload.
An Empirical Analysis of Anonymity in Zcash

Among the now numerous alternative cryptocurrencies derived from Bitcoin, Zcash is often touted as the one with the strongest anonymity guarantees, due to its basis in well-regarded cryptographic research. In this paper, we examine the extent to which anonymity is achieved in the deployed version of Zcash. We investigate all facets of anonymity in Zcash's transactions, ranging from its transparent transactions to the interactions with and within its main privacy feature, a shielded pool that acts as the anonymity set for users wishing to spend coins privately. We conclude that while it is possible to use Zcash in a private way, it is also possible to shrink its anonymity set considerably by developing simple heuristics based on identifiable patterns of usage.
Mathematical Models Light Up Plant Signaling

Plants respond to changes in the environment by triggering a suite of regulatory networks that control and synchronize molecular signaling in different tissues, organs, and the whole plant. Molecular studies through genetic and environmental perturbations, particularly in the model plant Arabidopsis thaliana, have revealed many of the mechanisms by which these responses are actuated. In recent years, mathematical modeling has become a complementary tool to the experimental approach that has furthered our understanding of biological mechanisms. In this review, we present modeling examples encompassing a range of different biological processes, in particular those regulated by light. Current issues and future directions in the modeling of plant systems are discussed.
Identification of Novel Acinetobacter baumannii Type VI Secretion System Antibacterial Effector and Immunity Pairs

ABSTRACT The type VI secretion system (T6SS) is a macromolecular machine that delivers protein effectors into host cells and/or competing bacteria. The effectors may be delivered as noncovalently bound cargo of T6SS needle proteins (VgrG/Hcp/PAAR) or as C-terminal extensions of these proteins. Many Acinetobacter baumannii strains produce a T6SS, but little is known about the specific effectors or how they are delivered. In this study, we show that A. baumannii AB307-0294 encodes three vgrG loci, each containing a vgrG gene, a T6SS toxic effector gene, and an antitoxin/immunity gene. Each of the T6SS toxic effectors could kill Escherichia coli when produced in trans unless the cognate immunity protein was coproduced. To determine the role of each VgrG in effector delivery, we performed interbacterial competitive killing assays using A. baumannii AB307-0294 vgrG mutants, together with Acinetobacter baylyi prey cells expressing pairs of immunity genes that protected against two toxic effectors but not a third. Using this approach, we showed that AB307-0294 produces only three T6SS toxic effectors capable of killing A. baylyi and that each VgrG protein is specific for the carriage of one effector. Finally, we analyzed a number of A. baumannii genomes and identified significant diversity in the range of encoded T6SS VgrG and effector proteins, with correlations between effector types and A. baumannii global clone lineages.
Evaluating verbal learning and memory in patients with an at-risk mental state or first episode psychosis using structural equation modelling

Background Verbal learning and memory are impaired not only in patients with a first episode of psychosis (FEP) but also–to a lower extent–in those with an at-risk mental state for psychosis (ARMS). However, little is known about the specific nature of these impairments. Hence, we aimed to study learning and memory processes in ARMS and FEP patients by making use of structural equation modelling. Methods Verbal learning was assessed with the California Verbal Learning Test (CVLT) in 98 FEP patients, 126 ARMS patients and 68 healthy controls (HC) as part of the Basel early detection of psychosis (FePsy) study. The four-factorial CFA model of Donders was used to estimate test performance on latent variables of the CVLT and growth curve analysis was used to model the learning curve. The latter allows disentangling initial recall, which is strongly determined by attentional processes, from the learning rate. Results The CFA model revealed that ARMS and FEP patients were impaired in Attention Span, Learning Efficiency and Delayed Memory and that FEP patients were additionally impaired in Inaccurate Memory. Additionally, ARMS-NT, but not ARMS-T, performed significantly worse than HC on Learning Efficiency. The growth curve model indicated that FEP patients were impaired in both initial recall and learning rate and that ARMS patients were only impaired in the learning rate. Conclusions Since impairments were more pronounced in the learning rate than the initial recall, our results suggest that the lower scores in the CVLT reported in previous studies are more strongly driven by impairments in the rate of learning than by attentional processes.
Downregulation of BRAF-activated non-protein coding RNA in patients with hepatitis B virus-associated hepatocellular carcinoma

Long non-coding RNAs (lncRNAs) have been investigated as a novel class of regulators of cellular processes, including cell growth, apoptosis and carcinogenesis. lncRNA BRAF-activated non-protein coding RNA (BANCR) has recently been revealed to be involved in tumorigenesis of numerous types of cancer, including papillary thyroid carcinoma, melanoma, non-small cell lung cancer and colorectal cancer. However, the expression profiles and biological relevance of lncRNA BANCR in hepatocellular carcinoma (HCC) has not yet been reported. In the present study, the expression level of BANCR in tumor tissues and para-cancerous tissues was determined by reverse transcription-quantitative polymerase chain reaction in patients with hepatitis B virus (HBV)-associated HCC, and its association with clinicopathological characteristics of patients was analyzed. The results demonstrated that the expression level of BANCR was significantly reduced in tumor tissues in comparison with in para-cancerous tissues (P<0.001). Furthermore, the present study demonstrated that BANCR expression level was closely associated with serum α-fetoprotein levels (P<0.01) and HCC tumor number (P<0.05). To the best of our knowledge, these results revealed for the first time that BANCR downregulated in patients with HBV-associated HCC and BANCR expression level may be a potential valuable diagnosis and therapeutic biomarker in HCC.
Synthesis of Iron Oxide/Gold Composite Nanoparticles Using Polyethyleneimine as a Polymeric Active Stabilizer for Development of a Dual Imaging Probe

The combination of magnetic and plasmonic properties using iron oxide/gold nanocomposite particles is crucial for the development of multimodal molecular imaging probes. In this study, iron oxide/gold composite nanoparticles (NanoIOGs) were synthesized via the on-site reduction of an Au precursor salt by polyethyleneimine (PEI) molecules attached to iron oxide nanoparticles (IONPs), and they were employed in magnetic resonance and dark-field microscope imaging. PEI is considered as a polymeric active stabilizer (PAS), acting as a reducing agent for the synthesis of Au and a dispersant for nanoparticles. When the IONPs prepared at the PEI concentration of 0.02 wt. % were used for the NanoIOG synthesis, Au nanoseeds were formed around the IONPs. The alloy clusters of IONPs/Au crystals were produced with further reduction depending on PEI concentration. The NanoIOGs exhibited superparamagnetism in a magnetic field and plasmonic response in a dark-field (DF) microscope. The sizes, morphologies, magnetizations, and r2 relaxivities of NanoIOGs were affected significantly by the amount of PEI added during the NanoIOG synthesis. It is suggested that the PAS-mediated synthesis is simple and effective, and can be applied to various nanostructured Au-metal alloys.
The Belly of the World: A Note on Black Women’s Labors

The slave ship is a womb/abyss. The plantation is the belly of the world. Partus sequitur ventrem—the child follows the belly. The master dreams of future increase. The modern world follows the belly. Gestational language has been key to describing the world-making and world-breaking capacities of racial slavery. What it created and what it destroyed has been explicated by way of gendered figures of conception, birth, parturition, and severed or negated maternity. To be a slave is to be “excluded from the prerogatives of birth. ” The mother’s only claim—to transfer her dispossession to the child. The material relations of sexuality and reproduction defined black women’s historical experiences as laborers and shaped the character of their refusal of and resistance to slavery. The theft, regulation and destruction of black women’s sexual and reproductive capacities would also define the afterlife of slavery. Most often when the productive labor of the slave comes into view, it is as a category absent gender and sexual differentiation. In two of the greatest works of the black radical tradition, W.E. B. Du Bois’s Black Reconstruction and C.L. R. James’s Black Jacobins, the agency of the enslaved becomes legible as politics, rather than crime or destruction, at the moment slaves are transformed into black workers and revolutionary masses fashioned along the lines of the insurgent proletariat. However, representing the slave through the figure of the worker (albeit unwaged and unfree), obscures as much as it reveals, making it difficult to distinguish the constitutive elements of slavery as a mode of power, violence, dispossession and accumulation or to attend to the forms of gendered and sexual violence that enable these processes. In Black Reconstruction, women’s sexual and reproductive labor is critical in accounting for the violence and degradation of slavery, yet this labor falls outside of the heroic account of the black worker and the general strike.