Miracle-dz/UniFAR-FTUs huggingface dataset:
Glucose Estimation and Prediction through Meal Responses Using Ambulatory Subject Data for Advisory Mode Model Predictive Control

Background: A primary challenge for closed-loop glucose control in type 1 diabetes mellitus (T1DM) is the development of a control strategy that will be applicable during all daily activities, including meals, stress, and exercise. A model-based control algorithm requires a mathematical model that has the simplicity for online glucose prediction, yet retains the complexity necessary to cope with variations in insulin sensitivities and carbohydrate ingestion. Methods: A modified Bergman minimal model was linearized for Kalman filter (KF) state estimation on data from T1DM subjects, and multiple methods of parameter augmentation were developed for online adaptation. In addition, model deterioration for glucose prediction was assessed to determine an appropriate prediction horizon for model predictive control (MPC). Furthermore, MPC strategies were validated using advisory mode simulations. Results: Twenty days of continuous glucose data, which included 97 meals, were evaluated for three subjects. A constant parameter minimal model was used to predict glucose levels for normal days with meal announcement and with a maximum prediction horizon of approximately 45 minutes. In order to attain this prediction horizon in the absence of meal announcement, parameter adaptation was necessary to capture the glucose disturbance. Evaluation of advisory mode MPC permitted effective tuning for a moderately aggressive controller that responded well to meal disturbances. Conclusions: Estimation and prediction of glucose were accomplished using a KF based on a modified Bergman model. For a model with no meal announcement, parameter adaptation provided the means for closed-loop implementation. This state estimation and model validation scheme established the necessary framework for advisory mode MPC.
Religious/Spiritual Struggle in Young Adult Hematopoietic Cell Transplant Survivors.

PURPOSE This study describes the prevalence of religious and/or spiritual (R/S) struggle in long-term young adult (YA) survivors following hematopoietic cell transplantation (HCT) as well as existential concerns (EC), social support, and demographic, medical, and emotional correlates of R/S struggle. METHODS Data were collected as part of an annual survey of survivors of HCT aged 18-39 years at survey completion; age at HCT was 1-39 years. Study measures included measures of R/S struggle (defined as any non-zero response on the negative religious coping subscale from Brief RCOPE), quality of life (QOL), and depression. Factors associated with R/S struggle were identified using multivariable logistic regression models. RESULTS Fifty-two of the 172 respondents (30%), who ranged from less than a year to 33 years after HCT, had some R/S struggle. In bivariate analysis, depression was associated with R/S struggle. In a multivariable logistic regression model, individuals with greater EC were nearly five times more likely to report R/S struggle. R/S struggle was not associated with age at transplant, time since transplant, gender, race, R/S self-identification, or medical variables. CONCLUSION R/S struggle is common among YA HCT survivors, even many years after HCT. There is a strong correlation between EC and R/S struggle. Given the prevalence of R/S struggle and its associations with EC, survivors should be screened and referred to professionals with expertise in EC and R/S struggle as appropriate. Further study is needed to determine longitudinal trajectory, impact of struggle intensity, causal relationships, and effects of R/S struggle on health, mood, and QOL for YA HCT survivors.
Conditional independence testing based on a nearest-neighbor estimator of conditional mutual information

Conditional independence testing is a fundamental problem underlying causal discovery and a particularly challenging task in the presence of nonlinear and high-dimensional dependencies. Here a fully non-parametric test for continuous data based on conditional mutual information combined with a local permutation scheme is presented. Through a nearest neighbor approach, the test efficiently adapts also to non-smooth distributions due to strongly nonlinear dependencies. Numerical experiments demonstrate that the test reliably simulates the null distribution even for small sample sizes and with high-dimensional conditioning sets. The test is better calibrated than kernel-based tests utilizing an analytical approximation of the null distribution, especially for non-smooth densities, and reaches the same or higher power levels. Combining the local permutation scheme with the kernel tests leads to better calibration, but suffers in power. For smaller sample sizes and lower dimensions, the test is faster than random fourier feature-based kernel tests if the permutation scheme is (embarrassingly) parallelized, but the runtime increases more sharply with sample size and dimensionality. Thus, more theoretical research to analytically approximate the null distribution and speed up the estimation for larger sample sizes is desirable.
Adverse Events Following Cervical Disc Arthroplasty: A Systematic Review

Study Design: Systematic review. Objectives: Cervical arthroplasty is an increasingly popular treatment of cervical radiculopathy and myelopathy. An understanding of the potential adverse events (AEs) is important to help both clinicians and patients. We sought to provide a comprehensive systematic review of the AEs reported in all randomized controlled trials (RCTs) of cervical disc arthroplasty in an attempt to characterize the quality of reporting. Methods: We conducted a systematic review of MEDLINE and Web of Science for RCTs of cervical disc arthroplasty reporting AEs. We reported the most frequently mentioned AEs, including dysphagia/dysphonia, vascular compromise, dural injury, and infections. We recorded the presence of industry funding and scored the quality of collection methods and reporting of AEs. Results: Of the 3734 identified articles, 29 articles met full inclusion criteria. The quality of AE reporting varied significantly between studies, and a combined meta-analysis was not feasible. The 29 articles covered separate 19 RCTs. Eight studies were US Food and Drug Administration (FDA) investigational device exemption (IDE) trials. Rates were recorded for the following AEs: dysphagia/dysphonia (range = 1.3% to 27.2%), vascular compromise (range = 1.1% to 2.4%), cervical wound infection (range = 1.2% to 22.5%), and cerebrospinal fluid leak (range = 0.8% to 7.1%). Conclusions: There is a lack of consistency in reporting of AEs among RCTs of cervical arthroplasty. FDA IDE trials scored better in AE event reporting compared to other studies. Standardized definitions for AEs and standardized data collection methodology are needed to improve future studies.
Proteases Underground: Analysis of the Maize Root Apoplast Identifies Organ Specific Papain-Like Cysteine Protease Activity

Plant proteases are key regulators of plant cell processes such as seed development, immune responses, senescence and programmed cell death (PCD). Apoplastic papain-like cysteine proteases (PL) are hubs in plant-microbe interactions and play an important role during abiotic stresses. The apoplast is a crucial interface for the interaction between plant and microbes. So far, apoplastic maize PL and their function have been mostly described for aerial parts. In this study, we focused on apoplastic PLCPs in the roots of maize plants. We have analyzed the phylogeny of maize PLCPs and investigated their protein abundance after salicylic acid (SA) treatment. Using activity-based protein profiling (ABPP) we have identified a novel root-specific PLCP belonging to the RD21-like subfamily, as well as three SA activated PLCPs. The root specific PLCP CP1C shares sequence and structural similarities to known CP1-like proteases. Biochemical analysis of recombinant CP1C revealed different substrate specificities and inhibitor affinities compared to the related proteases. This study characterized a root-specific PLCP and identifies differences between the SA-dependent activation of PLCPs in roots and leaves.
Transmission Electron Microscopy and X-ray Photoelectron Spectroscopy Studies of Soot Particles Emitted from a Domestic Cook-stove

Household air pollution due to the use of biomass fuels in domestic cook stoves is a serious public health problem. It is estimated that two billion people use biomass fuel (wood, dung and fiber residues) as their primary energy source for domestic needs such as heating and cooking [1]. People who use these tools for food preparation are exposed to different kind of emissions, mainly soot originated by the inefficient combustion. Inhalation of soot causing serious adverse health effects in women and children, for this reason it is important to learn more about the nature of these particles. [2], [3], [4].
Mangiferin Enhanced Autophagy via Inhibiting mTORC1 Pathway to Prevent High Glucose-Induced Cardiomyocyte Injury

Mangiferin functions as a perfect anti-oxidative compound in the diabetic heart, however, the exact mechanism remains to be elucidated. Here, we show the cardioprotective effect of mangiferin under high glucose-induced cardiotoxic condition mainly contributed to enhanced autophagy via suppressing mTORC1 downstream signal transduction. Primary neonatal rat cardiomyocytes were cultured to detect myocytes injury, autophagy, and related signal transduction under different doses of glucose and mangiferin treatment. High glucose (30 mM) reduced autophagic flux, and increased myocyte apoptosis and death compared with normal glucose (5.5 mM) as determined by variation of autophagy markers LC3-II, p62, parkin, GFP-LC3, or mRFP-LC3 fluorescence puncta, cell viability, cleaved caspase 3, cleaved PARP apoptosis indices, reactive oxygen species (ROS), MAO, and PI death indices. Conversely, mangiferin inhibited hyperglycemia associated oxidative stress by reducing ROS, MAO, cleaved caspase 3, and cleaved PARP generation, reestablishing cell viability, mitochondrial membrane potential, and enhancing autophagic flux, thereby preventing myocytes from high glucose-induced toxicity. Furthermore, cardioprotection with mangiferin was potentially related to the decreased mTOR phosphorylation and suppression of mTORC1 downstream signaling pathway. These data indicated the valuable effects of mangiferin on regulation of cardiac autophagy and pointed to the promising utilization for hyperglycemia control.
Cinema comics: Cartoon generation from video stream

This paper presents CORVIS(COmics Rendering system on VIdeo Stream) which helps to create comic strips from video streams in semi-automated manner. For this, first we manually select a set of important featuring scenes in a cinema and transform them into simplified illustrations by Mean-Shift segmentation. Then we insert the stylized comic effects to each illustration by considering the before/after video images. We newly proposed some techniques for this cartoon rendering effects. These stylized effects include the speed line, rotational trajectory and the background effect. Finally CORVIS automatically places the word balloons to represent the dialogues of actors. And echoic words e.g., “BANG”, will be inserted in the comic cut to imitate the sound effects of the original film. We tested CORVIS with the well-known cinemas, “Spider Man II” and “I ROBOT”. The final results show that our technique is quite effective and efficient to create a comic booklet from video streams.
Optimizing Bloom Filter: Challenges, Solutions, and Comparisons

Bloom filter (BF) has been widely used to support membership query, i.e., to judge whether a given element ${x}$ is a member of a given set ${S}$ or not. Recent years have seen a flourish design explosion of BF due to its characteristic of space-efficiency and the functionality of constant-time membership query. The existing reviews or surveys mainly focus on the applications of BF, but fall short in covering the current trends, thereby lacking intrinsic understanding of their design philosophy. To this end, this survey provides an overview of BF and its variants, with an emphasis on the optimization techniques. Basically, we survey the existing variants from two dimensions, i.e., performance and generalization. To improve the performance, dozens of variants devote themselves to reducing the false positives and implementation costs. Besides, tens of variants generalize the BF framework in more scenarios by diversifying the input sets and enriching the output functionalities. To summarize the existing efforts, we conduct an in-depth study of the existing literature on BF optimization, covering more than 60 variants. We unearth the design philosophy of these variants and elaborate how the employed optimization techniques improve BF. Furthermore, comprehensive analysis and qualitative comparison are conducted from the perspectives of BF components. Lastly, we highlight the future trends of designing BFs. This is, to the best of our knowledge, the first survey that accomplishes such goals.
Machine Learning and Software Defined Networks for High-Density WLANs

Next generation of wireless local area networks (WLANs) will operate in dense and highly dynamic scenarios. In addition, chaotic deployments may cause an important degradation in terms of user's experience due to uncontrolled high interference levels. Flexible network architectures, such as the software-defined networking (SDN) paradigm, will provide to WLANs with new capabilities to deal with users' demands, while achieving greater levels of efficiency and flexibility in those dynamic and complex scenarios. Moreover, the use of machine learning (ML) techniques will improve network resource usage and management by identifying feasible configurations through learning. ML techniques can drive WLANs to reach optimal working points by means of parameter adjustment, in order to cope with different network requirements and policies, as well as with the dynamic conditions. In this paper we overview the work done in SDN for WLANs, as well as the pioneering works considering ML for WLAN optimization. Moreover, we validate the suitability of such an approach by developing a use-case in which we show the benefits of using ML, and how those techniques can be combined with SDN.
Genetic Diversity of Southeast African Bantus and African Americans using the PowerPlex Y23 System

The aim of this investigation is to determine the capacity of the newly available Y-STR multiplex system, PowerPlex ® Y23, to discriminate between populations of similar ancestry, specifically of African descent. Using network analysis, the parti - tioning of the 23-loci haplotypes was assessed in relation to Y-specific haplogroups. In the network projection, a number of Bantu haplogroups including E1b1a1a1a-M58, B2a1a-M109 and E2b-M98 as well as non-Bantu African haplogroups such as B2b2-M115 and A1b1b2b1-M118 segregate differentially based on Y-STR haplotypes. Further, we contrast population genetics parameters of the Bantu Southeast African and African American populations. Also, the genetic distance values il- lustrate the robust capacity of the PowerPlex ® Y23 system to discriminate among populations. Noteworthy, we demonstrate that the two populations of African ancestry are as genetically different from each other as the African American population is from the Caucasian, Hispanic and Native American groups. For the first time, allelic and genotypic frequencies for the 23 Y-STR loci included in the PowerPlex ® Y23 forensic system are provided for a continental Southeast African population, the Bantu from the Maputo Province.
Distribution Patterns of Three Molecularly Defined Classes of GABAergic Neurons Across Columnar Compartments in Mouse Barrel Cortex

The mouse somatosensory cortex is an excellent model to study the structural basis of cortical information processing, since it possesses anatomically recognizable domains that receive different thalamic inputs, which indicates spatial segregation of different processing tasks. In this work we examined three genetically labeled, non-overlapping subpopulations of GABAergic neurons: parvalbumin- (PV+), somatostatin- (SST+), and vasoactive intestinal polypeptide-expressing (VIP+) cells. Each of these subpopulations displayed a unique cellular distribution pattern across layers. In terms of columnar localization, the distribution of these three populations was not quantitatively different between barrel-related versus septal compartments in most layers. However, in layer IV (LIV), SST+, and VIP+, but not PV+ neurons preferred the septal compartment over barrels. The examined cell types showed a tendency toward differential distribution in supragranular and infragranular barrel-related versus septal compartments, too. Our data suggests that the location of GABAergic neuron cell bodies correlates with the spatial pattern of cortical domains receiving different kinds of thalamic input. Thus, at least in LIV, lemniscal inputs present a close spatial relation preferentially to PV+ cells whereas paralemniscal inputs target compartments in which more SST+ and VIP+ cells are localized. Our findings suggest pathway-specific roles for neocortical GABAergic neurons.
Identifying Trends in Technologies and Programming Languages Using Topic Modeling

Technology question and answer websites are a great source of technical knowledge. Users of these websites raise various types of technical questions, and answer them. These questions cover a wide range of domains in Computer Science like Networks, Data Mining, Multimedia, Multi-threading, Web Development, Mobile App Development, etc. Analyzing the actual textual content of these websites can help computer science and software engineering community better understand the needs of developers and learn about the current trends in technology. In this project, textual data from famous question and answer website called StackOverflow, is analyzed using Latent Dirichlet Allocation (LDA) topic modeling algorithm. The results show that this techniques help discover dominant topics in developer discussions. These topics are analyzed to find a number of interesting observations such as popular technology/language, impact of a technology, technology trends over time, relationship of a technology/language with other technologies and comparison of technologies addressing an area of computer science or software engineering.
Design Space Pruning and Computational Workload Splitting for Autotuning OpenCL Applications

Recently, OpenCL standard reached much wider audiences due to the increasing number of devices supporting it. At the same time, we have observed an increase of differences among devices that support OpenCL. This situation offers to developers, who want to get high performance, a large spectrum of platforms. Given the additional OpenCL platform parameters alongside application specific parameters, the design space for exploration is seriously large. Furthermore, availability of more than one kind of device allows distribution of computation on the heterogeneous platform. Automatic design space exploration frameworks are one of the recent approaches to address these problems and to reduce the burden of programmers. In this work, we present our automatic and efficient technique to prune the design space before moving on to the exploration phase and we propose a new method for splitting the computational tasks to computing devices on heterogeneous platforms.
Toward a Bidirectional Communication Between Retinal Cells and a Prosthetic Device – A Proof of Concept

Background: Significant progress toward the recovery of useful vision in blind patients with severe degenerative retinal diseases caused by photoreceptor death has been achieved with the development of visual prostheses that stimulate the retina electrically. However, currently used prostheses do not provide feedback about the retinal activity before and upon stimulation and do not adjust to changes during the remodeling processes in the retina. Both features are desirable to improve the efficiency of the electrical stimulation (ES) therapy offered by these devices. Accordingly, devices that not only enable ES but at the same time provide information about the retinal activity are beneficial. Given the above, a bidirectional communication strategy, in which inner retinal cells are stimulated and the output neurons of the retina, the ganglion cells, are recorded using penetrating microelectrode arrays (MEAs) is proposed. Methods: Custom-made penetrating MEAs with four silicon-based shanks, each one with three or four iridium oxide electrodes specifically designed to match retinal dimensions were used to record the activity of light-adapted wildtype mice retinas and degenerated retinas from rd10 mice in vitro. In addition, responses to high potassium concentration and to light stimulation in wildtype retinas were examined. Furthermore, voltage-controlled ES was performed. Results: The spiking activity of retinal ganglion cells (RGCs) was recorded at different depths of penetration inside the retina. Physiological responses during an increase of the extracellular potassium concentration and phasic and tonic responses during light stimulation were captured. Moreover, pathologic rhythmic activity was recorded from degenerated retinas. Finally, ES of the inner retina and simultaneous recording of the activity of RGCs was accomplished. Conclusion: The access to different layers of the retina with penetrating electrodes while recording at the same time the spiking activity of RGCs broadens the use and the field of action of multi-shank and multi-site penetrating MEAs for retinal applications. It enables a bidirectional strategy to stimulate inner retinal cells electrically and to record from the spiking RGCs simultaneously (BiMEA). This opens the possibility of a feedback loop system to acknowledge the success of ES carried out by retinal prostheses.
Multicenter randomized evaluation of a nutritional education software in obese patients.

OBJECTIVE To study the efficacy of the nutritional education software, Nutri-Expert, in the management of obese adult patients. MATERIAL AND METHODS Two groups of obese patients were followed up over one year in a randomized study: the first group received close traditional management (seven nutritional visits over the year, with physicians and dietitians conjointly) and the second one also used at home by Minitel the Nutri-Expert system. 557 patients were enrolled in the study by 16 French centers of diabetology and nutrition. Body mass index (BMI), tests of dietetic knowledge, dietary records and centralized biological measurements were assessed at inclusion, 6 and 12 months. 341 patients were evaluable at the end of the year. RESULTS The group using Nutri-Expert scored significantly better in the tests of dietetic knowledge than the control group. For all patients, nutritional education led to a significant improvement in BMI, dietary records and biological measurements, without significant difference between the two groups. Five years after the end of the study, the weight of 148 patients was recorded; mean BMI was significantly lower than the initial value but there was no significant difference between the two groups. CONCLUSION In the management of obese patients, Nutri-Expert system has a role to play in reinforcing nutritional knowledge; if regular follow-up is not possible, or if a large series of obese patients is to be treated, Nutri-Expert could partly replace traditional management, for example between visits.