Miracle-dz/UniFAR-FTUs huggingface dataset:
Heart rate n-variability (HRnV) measures for prediction of mortality in sepsis patients presenting at the emergency department

Background: Sepsis is a potentially life threatening condition that requires prompt recognition and treatment for optimal outcomes. There is little consensus on an objective way to assess for sepsis severity and risk for mortality. In recent years, heart rate variability (HRV), a measure of the cardiac autonomic regulation derived from short electrocardiogram tracings, has been found to correlate with sepsis mortality, and its use as a prognostic variable and for risk stratification has been promising. In this paper, we present using novel heart rate n-variability (HRnV) measures for sepsis mortality risk prediction and compare against current mortality prediction scores. Methods: This study was a retrospective cohort study on a convenience sample of patients presenting to the emergency department (ED) of Singapore General Hospital between September 2014 to April 2017. Patients were included in the study if they were above 21 years old, were suspected to have sepsis by their attending physician, triaged as emergency or urgent cases, and if they met two or more of the Systemic Inflammatory Response Syndrome (SIRS) criteria. Demographic and clinical variables were obtained from the electronic medical records, and HRV and novel HRnV parameters were calculated from five minute ECG tracings. Univariable analysis was conducted on variables obtained, with the primary outcome being 30-day in-hospital mortality (IHM). Variables selected through univariable analysis and stepwise selection were included in a multivariable logistic regression model, the results of which were presented using receiver operating curve (ROC) analysis. Results: Of 342 patients included for final analysis, 66 (19%) met with the primary outcome. On univariable analysis, 85 out of 142 analysed HRV and HRnV parameters showed statistical difference between groups. The final multivariable logistic regression model comprised of 21 variables including four vital signs, two HRV parameters, and 15 HRnV parameters. The area under the curve (AUC) of the model was 0.86 (95% confidence interval 0.81-0.90), outperforming several established clinical scores. Conclusion: The use of novel HRnV measures can provide adequate power to predictive models in the risk stratification of patients presenting to the ED with sepsis. When included in a multivariable logistic regression model, the HRnV-based model outperformed traditional risk stratification scoring systems. The HRnV measures may have potential to allow for a rapid, objective, and accurate means of patient risk stratification for sepsis severity and mortality.
A renewal equation model to assess roles and limitations of contact tracing for disease outbreak control

We propose a deterministic model capturing essential features of contact tracing as part of public health non-pharmaceutical interventions to mitigate an outbreak of an infectious disease. By incorporating a mechanistic formulation of the processes at the individual level, we obtain an integral equation (delayed in calendar time and advanced in time since infection) for the probability that an infected individual is detected and isolated at any point in time. This is then coupled with a renewal equation for the total incidence to form a closed system describing the transmission dynamics involving contact tracing. We define and calculate basic and effective reproduction numbers in terms of pathogen characteristics and contact tracing implementation constraints. When applied to the case of SARS-CoV-2, our results show that only combinations of diagnosis of symptomatic infections and contact tracing that are almost perfect in terms of speed and coverage can attain control, unless additional measures to reduce overall community transmission are in place. Under constraints on the testing or tracing capacity, a temporary interruption of contact tracing may, depending on the overall growth rate and prevalence of the infection, lead to an irreversible loss of control even when the epidemic was previously contained.
From soil to plant: strengthening carrot defenses against Meloidogyne incognita with vermicompost and arbuscular mycorrhizal fungi biofertilizers

Introduction Sustainable agricultural practices for controlling crop pests are urgently needed to reduce the reliance on chemical pesticides, which have long-term detrimental effects on ecosystems. In this study, we assessed the effectiveness of arbuscular mycorrhizal fungi (AMF) and vermicompost (Vc) supplementation, alone and in combination, in mitigating the negative impacts of Meloidogyne incognita infestation on carrot (Daucus carota L.) growth, development, and physiology. Methods We measured different plant growth parameters such as plant height and biomass accumulation, several plant physiological parameters such as the levels of photosynthetic pigments, phenolics, and the activity of defense enzymes such as peroxidases and polyphenol oxidases, and evaluated the severity of Meloidogyne incognita nematode infestation on plants treated or not treated with vermicompost (Vc) and/or arbuscular mycorrhizal fungi (AMF). Results Our findings show that M. incognita significantly affects plant growth, biomass accumulation, and photosynthetic pigment and carotenoid content. The incorporation of Vc and AMF into the soil, either individually or in combination, significantly alleviates the negative effects of nematode infestation on carrot plants. This was accompanied by the induction of phenolic compounds and defense enzymes such as peroxidases (+15.65%) and polyphenol oxidases (29.78%), and by a reduction in the severity of nematode infestation on Vc and AMF-treated plants compared to nematode-infested plants. Principal component analysis (PCA) shows significant correlations between various of the studied parameters. In particular, we observed negative correlations between the application of AMF and Vc alone and in combination and disease severity, and positive correlations between plant growth, photosynthetic pigments phenol content, and activity of defense enzymes. Discussion Our study highlights the relevance of cultural practices and beneficial microorganisms for the sustainable and environmentally friendly management of agricultural pests.
Intraoperative imaging of brain tumors with fluorescein: confocal laser endomicroscopy in neurosurgery. Clinical and user experience.

OBJECTIVE Confocal laser endomicroscopy (CLE) is an established tool in basic research for tissue imaging at the level of microstructures. Miniaturization and refinement of the technology have made this modality available for operative imaging with a handheld device. Sufficient image contrast is provided by the preoperative application of fluorescein sodium. The authors report their first experiences in a clinical case series using the new confocal laser endomicroscope. METHODS Handling, operative workflow, and visualization of the CLE were critically evaluated in 12 cases of different CNS tumors. Three different imaging positions in relation to the tumor were chosen: the tumor border (I), tumor center (II), and perilesional zone (III). Respective diagnostic sampling with H & E staining and matching intraoperative neuronavigation and microscope images are provided. RESULTS CLE was found to be beneficial in terms of high-quality visualization of fine structures and for displaying hidden anatomical details. The handling of the device was good, and the workflow was easy. CONCLUSIONS Handling ergonomics and image acquisition are intuitive. The endomicroscope allows excellent additional visualization of microstructures in the surgical field with a minimally invasive technique and could improve safety and clinical outcomes. The new confocal laser endomicroscope is an advanced tool with the potential to change intracranial tumor surgery. Imaging of these microstructures is novel, and research with comparative validation with traditional neuropathological assessments is needed.
The interaction between MtDELLA-MtGAF1 complex and MtARF3 mediates transcriptional control of MtGA3ox1 to elaborate leaf margin formation in Medicago truncatula.

The molecular mechanisms underlying diversity of leaf shapes have been of great interest to researchers. Leaf shape depends on the pattern of serrations and the degree of indentation of leaf margins. Multiple transcription factors and hormone signaling are involved in this process. In this study, we characterized the developmental roles of SMALL AND SERRATED LEAF (SSL) by analyzing a recessive mutant in the model legume Medicago truncatula. An ortholog of Arabidopsis thaliana GA3-oxidase 1 (GA3ox1), MtGA3ox1/SSL, is required for GA biosynthesis. Loss of function in MtGA3ox1 results in the small plant and lateral organs. The prominent phenotype of the mtga3ox1 mutant is the more pronounced leaf margin, indicating the critical role of GA level in leaf margin formation. Moreover, 35S: MtDELLA2 ΔDELLAand 35S: MtARF3 transgenic plants display leaves with the deeply wavy margin, which resembles those of mtga3ox1. Further investigations show that the MtGA3ox1 is under the control of MtDELLA1/2/3-MtGAF1 complexes-dependent feedback regulation. Meanwhile, MtARF3 behaves as a competitive inhibitor of MtDELLA2/3-MtGAF1 complexes to repress the expression of MtGA3ox1 indirectly. These findings suggest that GA feedback regulatory circuits play a fundamental role in leaf margin formation, in which the posttranslational interaction between transcription factors functions as an additional feature.
A High Sensitive TNT Sensor Based on Electrochemically Reduced Graphene Oxide‐Poly(amidoamine) Modified Electrode

In this paper, the electrochemically reduced graphene oxide-poly(amidoamine) hybrid (ErGO-PAMAM) have been used for fabrication of TNT electrochemical sensor. The prepared modified electrode is characterized with X-ray photoelectron spectroscopy (XPS), fourier transform infrared spectroscopy (FT-IR), electrochemical impedance spectroscopy (EIS), energy-dispersive X-ray (EDX) spectroscopy, scanning electron microscopy (SEM) and atomic force microscope (AFM). Based on obtained results, it is can be seen that the ErGO-PAMAM/GCE has high response to TNT than the other graphene based modified electrodes. The resulting electrochemical sensor exhibited good response to TNT with linear range from 0.05 to 1.2 ppm with a low detection limit of 0.0015 ppm.
On Convergence of Gradient Expected Sarsa(λ)

We study the convergence of Expected Sarsa(λ) with function approximation. We show that with off-line es- timate (multi-step bootstrapping) to ExpectedSarsa(λ) is unstable for off-policy learning. Furthermore, based on convex-concave saddle-point framework, we propose a con- vergent Gradient Expected Sarsa(λ) (GES(λ)) algorithm. The theoretical analysis shows that the proposed GES(λ) converges to the optimal solution at a linear convergence rate under true gradient setting. Furthermore, we develop a Lyapunov function technique to investigate how the step- size influences finite-time performance of GES(λ). Addition- ally, such a technique of Lyapunov function can be poten- tially generalized to other gradient temporal difference algo- rithms. Finally, our experiments verify the effectiveness of our GES(λ). For the details of proof, please refer to https: //arxiv.org/pdf/2012.07199. pdf.
A novel telencephalon‐opto‐hypothalamic morphogenetic domain coexpressing Foxg1 and Otp produces most of the glutamatergic neurons of the medial extended amygdala

Deficits in social cognition and behavior are a hallmark of many psychiatric disorders. The medial extended amygdala, including the medial amygdala and the medial bed nucleus of the stria terminalis, is a key component of functional networks involved in sociality. However, this nuclear complex is highly heterogeneous and contains numerous GABAergic and glutamatergic neuron subpopulations. Deciphering the connections of different neurons is essential in order to understand how this structure regulates different aspects of sociality, and it is necessary to evaluate their differential implication in distinct mental disorders. Developmental studies in different vertebrates are offering new venues to understand neuronal diversity of the medial extended amygdala and are helping to establish a relation between the embryonic origin and molecular signature of distinct neurons with the functional subcircuits in which they are engaged. These studies have provided many details on the distinct GABAergic neurons of the medial extended amygdala, but information on the glutamatergic neurons is still scarce. Using an Otp‐eGFP transgenic mouse and multiple fluorescent labeling, we show that most glutamatergic neurons of the medial extended amygdala originate in a distinct telencephalon‐opto‐hypothalamic embryonic domain (TOH), located at the transition between telencephalon and hypothalamus, which produces Otp‐lineage neurons expressing the telencephalic marker Foxg1 but not Nkx2.1 during development. These glutamatergic cells include a subpopulation of projection neurons of the medial amygdala, which activation has been previously shown to promote autistic‐like behavior. Our data open new venues for studying the implication of this neuron subtype in neurodevelopmental disorders producing social deficits.
Neurocognitive predictors of adaptive functioning trajectories among youth with spina bifida

ABSTRACT Little is known about how youth with spina bifida (SB) acquire adaptive functioning skills across development. Therefore, the current study examined: (1) trajectories of adaptive functioning in youth with SB as they transitioned from childhood into adolescence, and (2) neuropsychological functioning as a potential risk factor for long-term adaptive functioning difficulties. Participants (n = 131 youth with SB) were recruited as part of a larger ongoing longitudinal study. Growth curves were used to examine changes over time across six adaptive functioning skills: communication, self-direction, functional academics, social, self-care, and home living skills. Additionally, youth’s attention and executive functioning (i.e., working memory, planning/organizational skills, cognitive flexibility, inhibition) were assessed via questionnaires and performance-based assessments, and entered as predictors in the models. Youth’s communication, self-direction, functional academics, self-care, and home living skills increased over time across age, whereas youth’s social skills did not. Scaled scores for youth’s social, communication, self-direction, and functional academics skills were generally within normal limits, whereas those for self-care and home living skills fell in the borderline range. Better attention and executive functioning predicted a higher intercept for many adaptive functioning abilities at 11.5 years old, above and beyond the influence of IQ. However, these variables did not predict growth in adaptive functioning. Results indicate that youth with SB acquire skills across development to better meet the demands of daily life. However, youth with poorer neurocognitive functioning may demonstrate adaptive functioning deficits in early childhood and benefit from timely intervention.
Unifying Compilers for SNARKs, SMT, and More

The programming languages community, the cryptography community, and others rely on translating programs in high-level source languages (e.g., C) to logical constraint representations. Unfortunately, building compilers for this task is difficult and time consuming. In this work, we show that all of these communities can build upon a shared compiler infrastructure, because they all share a common abstraction: stateless, non-deterministic computations that we call exis-tentially quantified circuits , or EQCs. To make our approach concrete we create CirC, an infrastructure for building compilers to EQCs. CirC makes it easy to add support for new EQCs: we build support for two, one used by the PL community and one used by the cryptography community, in ≈ 2000 LOC. It’s also easy to extend CirC to support new source languages: we build a feature-complete compiler for a cryptographic language in one week and ≈ 700 LOC, whereas the reference compiler for the same language took years to write, comprises ≈ 24000 LOC, and produces worse-performing output than our compiler. Finally, CirC enables novel applications that combine multiple EQCs. For example, we build the first pipeline that (1) automatically identifies bugs in programs, then (2) automatically constructs cryptographic proofs of the bugs’ existence.
Enzymatic Template Polymerization of Phenol in the Presence of Water-soluble Polymers in an Aqueous Medium

The enzymatic polymerization of phenol was investigated by using water-soluble polymers (WSPs) as template in an aqueous medium. The addition of PEG, one of WSPs, produced a miscible complex of polyphenol and PEG as precipitates in high yields. CD measurement verified the formation of a phenol–PEG complex by hydrogen bonding interaction. The presence of PEG in an aqueous medium greatly improved the regioselectivity of the polymerization, yielding a polyphenol with the phenylene unit content higher than 90%. The amount of PEG strongly affected the polyphenol yield. The unit molar ratio of polyphenol and PEG was ca. 1:1. The FT IR, DSC, and XRD analyses exhibited the formation of the miscible complex of polyphenol and PEG by hydrogen bonding interaction.
The Age of Testifying Wearable Devices: The Case of Intoxication Detection

Seven years ago, a famous case in which data from a Fitbit tracker was used in the courtroom in a personal injury case heralded a new age: the age of testifying wearable devices. Prior to that, data from wearable devices was used in various areas, including medicine, advertising, and scientific research, but the use of such data in the Fitbit case attracted the interest of a new sector: the legal sector. Since then, lawyers, investigators, detectives, and police officers have used data from pacemakers and smartwatches in order to prove/disprove allegations regarding wearable device owners in several wellknown cases (sexual assault, arson, personal injury, etc.). In this paper, we discuss testifying wearable devices. We explain the advantages of wearable devices over traditional IoT devices in the legal setting, the parties involved in cases in which a wearable device was used to testify against/for the device owner, and the information flow. We then focus on an interesting area of research: intoxication detection. We explain the motivation to detect whether a subject was intoxicated and explain the primary scientific gap in this area. In order to overcome this gap, we suggest a new method for detecting whether a subject was intoxicated based on free gait data obtained from a wearable device. We evaluate the performance of the proposed method in a user study involving 30 subjects and show that motion sensor data obtained from a smartphone and fitness tracker from eight seconds of free gait can indicate whether a subject is/was intoxicated (obtaining an AUC of 0.97) and thus be used as testimony. Finally, we analyze the current state and the near future of the age of testifying wearable devices and explain why we believe that (1) we are still at the beginning of this age despite the fact that seven years has passed since the original court case, and (2) the number of cases in which wearable device data is used to testify for/against the device owner is expected to increase significantly in the next few years.
Audio-Based Music Structure Analysis: Current Trends, Open Challenges, and Applications

With recent advances in the field of music informatics, approaches to audio-based music structural analysis have matured considerably, allowing researchers to reassess the challenges posed by the task, and reimagine potential applications. We review the latest breakthroughs on this topic and discuss the challenges that may arise when applying these techniques in real-world applications. Specifically, we argue that it could be beneficial for these systems to be application-dependent in order to increase their usability. Moreover, in certain scenarios, a user may wish to decide which version of a structure to use, calling for systems with multiple outputs, or where the output adapts in a user-dependent fashion. In reviewing the state of the art and discussing the current challenges on this timely topic, we highlight the subjectivity, ambiguity, and hierarchical nature of musical structure as essential factors to address in future work.
Batched Differentially Private Information Retrieval

Private Information Retrieval (PIR) allows several clients to query a database held by one or more servers, such that the contents of their queries remain private. Prior PIR schemes have achieved sublinear communication and computation by leveraging computational assumptions, federating trust among many servers, relaxing security to permit differentially private leakage, refactoring effort into an ofﬂine stage to reduce online costs, or amortizing costs over a large batch of queries. In this work, we present an efﬁcient PIR protocol that combines all of the above techniques to achieve constant amortized communication and computation complexity in the size of the database and constant client work. We leverage differentially private leakage in order to provide better trade-offs between privacy and efﬁciency. Our protocol achieves speed-ups up to and exceeding 10x in practical settings compared to state of the art PIR protocols, and can scale to batches with hundreds of millions of queries on cheap commodity AWS machines. Our protocol builds upon a new secret sharing scheme that is both incremental and non-malleable, which may be of interest to a wider audience. Our protocol provides security up to abort against malicious adversaries that can corrupt all but one party.
Mesoporous material-based manipulation of the enzyme-like activity of CoFe2O4 nanoparticles

Mesoporous material supported CoFe2O4 magnetic nanoparticles possess unique peroxidase/oxidase-like activity, and react with luminol to yield a novel chemiluminescence without the need of H2O2. Their oxidase-like activity shows pH and support dependence, and could be reversibly controlled by their pH. This offers a new method for manipulating the enzyme-like activity of nanoparticles.
Chemical upgrading of sedimentary Na-chabazite from Bowie, Arizona

Natural zeolites may represent one of the greatest under-utilized resources of the mineral world. Even with their unique character and properties, issues of consistency, homogeneity and purity preclude them from many premium applications. We report a simple method to upgrade mineral sedimentary Na-chabazite from the well known Bowie, Arizona, deposit to near synthetic purity and consistency. During this alkaline-silicate digestion process, initially soft chabazite ore granules gain substantial mechanical strength. This may allow direct employment in adsorption and purification processes without the need for binding and forming. These granules manifest significantly improved adsorption properties, including enhanced water and CO2 adsorptivity.
n‐type conductivity control of AlGaN with high Al mole fraction

Silicon doped AlxGa1–xN with high Al mole fraction was grown using epitaxial AlN as a underlying layer by low-pressure metalorganic vapor phase epitaxy. n-type conductivity control of high quality Si-doped AlxGa1–xN was achieved successfully. Structural, electrical and optical properties were investigated for various Al mole fractions, flow rates of silicon, and AlxGa1–xN thickness, respectively. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)