Miracle-dz/UniFAR-FTUs huggingface dataset:
Association between Lipid Profile and Apolipoproteins with Risk of Diabetic Foot Ulcer: A Systematic Review and Meta-Analysis

Background and Aims Biomarkers are necessary to stratify the risk of diabetic foot ulcers (DFUs). This systematic review and meta-analysis aimed to evaluate the association between the lipid profile and apolipoproteins with the risk of DFU. Methods A systematic search was conducted in PubMed, Scopus, Cochrane Library, and Web of Science among adult patients. Cohort and case-control studies were included. Random-effects models were used for meta-analyses, and the effects were expressed as odds ratio (OR) and their 95% confidence intervals (CIs). We evaluated publication bias through Egger's test and funnel plot. Results A total of 12 cohort studies and 26 case-control studies were included, with 17076 patients. We found that the higher values of total cholesterol (TC), low-density lipoprotein (LDL), triglycerides, and lipoprotein(a) (Lp(a)) were associated with a higher risk of developing DFU (OR: 1.47, OR: 1.47, OR: 1.5, OR: 1.85, respectively). Otherwise, the lower values of HDL were associated with a higher risk of developing DFU (OR: 0.49). Publication bias was not found for associations between TC, HDL, LDL, or TG and the risk of DFU. Conclusions The high values of LDL, TC, TG, and Lp(a) and low values of HDL are associated with a higher risk of developing DFU. Furthermore, we did not find a significant association for VLDL, ApoA1, ApoB, and ApoB/ApoA1 ratio.
ML-Based Performance Modeling in SDN-Enabled Data Center Networks

Traffic optimization and smart buffering are fundamental to achieve both great application performance and resource efficiency in data centers with heterogeneous workloads, including incast and elephant traffics. However, general performance models providing insights on how various factors affect traffic performance metrics needed by these management functions are missing. For the special case of incast, the existing models are analytical ones, either tightly coupled with a particular protocol version or specific to certain empirical data. Motivated by this observation, this paper proposes an SDN-enabled machine-learning-based performance modeling approach in data center networks that leverages random forest predictions. Evaluations based on datasets constructed through intensive NS-3 simulations show that we can achieve accurate predictions of incast and elephant performance metrics based on various features. With this performance modeling capability, smart buffering schemes or traffic optimization algorithms could anticipate and efficiently optimize system parameters adjustment to achieve optimal performance continuously in data centers.
PENERAPAN METODE CPM DAN PERT PADA PT. XYZ DALAM PEMBANGUNAN PROYEK APARTEMEN GARDEN DI TANGERANG

Growth property business in Indonesia since the last years has been growth significantly; it’s marked by the increase of property prices in Indonesia due to 2017. PT XYZ is one of company engaged in property business or real estate. At this time PT XYZ was currently conducting project development for Apartement located in Alam Sutera, Tangerang. The purpose of this research is to find out the application of the Critical Path Method and PERT method that can be applied to the apartment project, to compare the costs before and after using the Critical Path Method and PERT method, to determine the effectiveness and efficiency of using Crashing Program on the Apartment project. To optimize the development project, Therefore, they need a mature and structured Project Management to finish project to avoid delay. Hence, researchers tried to apply a method that approach optimization by using the Critical Path Method (CPM) and Project Evaluation and Review Technique (PERT) in Project Management, to be able to maximize profit and reduce the risk loss for the company and consumers.
Safety assessment of the process Amhil Europa, based on the Kreyenborg IR Clean+ technology, used to recycle post‐consumer PET into food contact materials

Abstract The EFSA Panel on Food Contact Materials, Enzymes and Processing Aids (CEP) assessed the safety of the recycling process Amhil Europa (EU register number RECYC255), which uses the Kreyenborg IR Clean+ technology. The input material is hot caustic washed and dried poly(ethylene terephthalate) (PET) flakes originating from collected post‐consumer PET containers, including no more than 5% PET from non‐food consumer applications. The flakes are heated in a ■■■■■ IR dryer (step 2) before being processed by the finisher (step 3). Having examined the challenge test provided, the Panel concluded that step 2 and step 3 are critical in determining the decontamination efficiency of the process. The operating parameters to control the performance of this step are temperature, airflow and residence time. It was demonstrated that this recycling process is able to ensure a level of migration of potential unknown contaminants into food below the conservatively modelled migration of 0.10 and 0.15 μg/kg food, derived from the exposure scenario for infants and toddlers, respectively, when such recycled PET is used at up to 100%. Therefore, the Panel concluded that the recycled PET obtained from this process is not of safety concern when used at up to 100% for the manufacture of materials and articles for contact with all types of foodstuffs, including drinking water, for long‐term storage at room temperature, with or without hotfill. Articles made of this recycled PET are not intended to be used in microwave and conventional ovens and such uses are not covered by this evaluation.
Developing a Data Driven Strategy and Guideline to Increase Per Capita Open Space and Relative Accessibility in Chittagong City

The population density in Chittagong City Corporation (CCC) area was 242.28 per square meter in 2019, and Bulmer suggests that, due to the high birth rate in Asia, cities such as Chittagong can be considered high density. Contextually, this ‘high-density’ element is a determining factor that potentially allows one to address the city’s open space standard, which “should compensate and complement the physical and social context of the [urban] surrounding environment”. The research in this paper is focused on the urban setting, defined in the CCC area of 168 square kilometres. The literature review and case study analysis found that per capita open space in Chittagong is far lower than the WHO recommendation (nine square meters per person). Additionally, the UN stated that “47% of [the city’s] population live within 400 m walking distance to open public spaces”, whereas, according to the previous study, in Chittagong City only 19% of residents live within this distance. Observing these issues, the aim of the paper is to develop an innovative way to obtain per capita open space in Chittagong city. To achieve the aim, the researchers analysed the data from surveys and interviews conducted by using SPSS and NVivo. These tools produced data that were, for example, used to develop themes of open space in Chittagong. This investigation and analysis of material allowed for the generation of strategies and planning recommendations to improve the open space situation in the city. Beyond these strategies, the research team produced new insights to promote sustainability in this area.
Finite-Time Model Predictive Tracking Control of Position and Orientation for Redundant Manipulators

Most schemes of trajectory tracking control of redundant manipulators consider only the position of the end-effector with little regard for its orientation, and reduce the feasible region of decision variables when introducing multiple levels of joint limits. To remedy these weaknesses, this article constructs a model predictive tracking control of position and orientation (MPTCPO) scheme for redundant manipulators, which is able to achieve the simultaneous control of position and orientation of the end-effector. The proposed MPTCPO scheme simultaneously minimizes the tracking error, joint-velocity norm, and joint-acceleration norm. In the meantime, it directly handles three levels of joint limits of joint angle, joint velocity, and joint acceleration without reducing the feasible region of decision variables without conversion required. In addition, a finite-time convergent neural dynamics (FTCND) model is designed to find the optimal solution of the proposed scheme. Computer simulations and physical experiments confirm the feasibility and accuracy of the proposed MPTCPO scheme solved by the FTCND model.
A Translation-Based Approach to Contingent Planning

The problem of planning in the presence of sensing has been addressed in recent years as a nondeterministic search problem in belief space. In this work, we use ideas advanced recently for compiling conformant problems into classical ones for introducing a different approach where contingent problems P are mapped into non-deterministic problems X(P) in state space. We also identify a contingent width parameter, and show that for problems P with bounded contingent width, the translation is sound, polynomial, and complete. We then solve X(P) by using a relaxation X+(P) that is a classical planning problem. The formulation is tested experimentally over contingent benchmarks where it is shown to yield a planner that scales up better than existing contingent planners.
Intrusion Detection System: A hybrid approach for Cyber-Physical Environments

This paper presents the development of two IDSs (Intrusion Detection System), which, due to their easy learning and adaptability features, can be easily applied in a CPE (Cyber-Physical Environment). IDSs use two specific algorithms, the first is SOM (Self-Organizing Map) and the second is K-Means. For training and testing both IDSs, public data have been provided by DARPA (Defense Advanced Research Agency). The results have shown the algorithms' effectiveness considering the variety of attacks that could arise from a highly heterogeneous network, such as CPEs. The first IDS has reached a detection rate of 95.9%, considering an average of the experiments, with a false alarm rate of 4.26%. The second IDS has reached a detection rate of 85.03% in the average of the experiments, with a false alarm rate of 0.62%. The primary goal is to develop an IDS that facilitates the problems related to speed, accuracy, and adaptability, as well as the inherent aspects of these types of security mechanisms and that also achieves a greater impact as a result of new applications and CPEs heterogeneity.
Secondary electron yield characterization of high porosity surfaces for multipactor-free microwave components

We present secondary electron yield (SEY) characterization of high porosity surfaces for multipactor-free microwave components. We first calculate the SEYs of through porosity surfaces using Monte Carlo simulations. We demonstrate that these high porosity surfaces can be treated as homogeneous materials with low effective SEYs. We prove that a significant SEY reduction is attainable by high porosities, and above a certain porosity level, the entire effective SEY of the surface falls below unity, offering a multipactor free capability. We import the resultant SEYs into our semi-analytic approach to obtain multipactor susceptibility charts corresponding to different surface porosities. We predict the reduction of the multipactor-susceptible zone as the porosity increases and a total multipactor suppression with 0.66 through porosity level. The theoretical results were validated with multipactor experiments, and relatively good agreement was observed. Finally, we propose an alternative blind porosity approach that can offer the same multipactor suppression capabilities. The approach discussed herein can be adopted to design high-power multipactor-free microwave components.
Correlation of Cerebral Microdialysis with Non-Invasive Diffuse Optical Cerebral Hemodynamic Monitoring during Deep Hypothermic Cardiopulmonary Bypass

Neonates undergoing cardiac surgery involving aortic arch reconstruction are at an increased risk for hypoxic-ischemic brain injury. Deep hypothermia is utilized to help mitigate this risk when periods of circulatory arrest are needed for surgical repair. Here, we investigate correlations between non-invasive optical neuromonitoring of cerebral hemodynamics, which has recently shown promise for the prediction of postoperative white matter injury in this patient population, and invasive cerebral microdialysis biomarkers. We compared cerebral tissue oxygen saturation (StO2), relative total hemoglobin concentration (rTHC), and relative cerebral blood flow (rCBF) measured by optics against the microdialysis biomarkers of metabolic stress and injury (lactate–pyruvate ratio (LPR) and glycerol) in neonatal swine models of deep hypothermic cardiopulmonary bypass (DHCPB), selective antegrade cerebral perfusion (SACP), and deep hypothermic circulatory arrest (DHCA). All three optical parameters were negatively correlated with LPR and glycerol in DHCA animals. Elevation of LPR was found to precede the elevation of glycerol by 30–60 min. From these data, thresholds for the detection of hypoxic-ischemia-associated cerebral metabolic distress and neurological injury are suggested. In total, this work provides insight into the timing and mechanisms of neurological injury following hypoxic-ischemia and reports a quantitative relationship between hypoxic-ischemia severity and neurological injury that may inform DHCA management.
A 32-channel 840Msps TDC based on Altera Cyclone III FPGA

In this work we present a newly developed TDC (Time-to-Digital Converter) board in the VME-32 standard. The 32-channel TDC board is based on a single FPGA Altera Cyclone III chip. The main parameters of the TDC are as follows: a resolution of 1.19 ns, a dead time of 4.76 ns, and a maximal time interval of 19 504 ns.
Measuring Identification and Quantification Errors in Spectral CT Material Decomposition

Material decomposition methods are used to identify and quantify multiple tissue components in spectral CT but there is no published method to quantify the misidentification of materials. This paper describes a new method for assessing misidentification and mis-quantification in spectral CT. We scanned a phantom containing gadolinium (1, 2, 4, 8 mg/mL), hydroxyapatite (54.3, 211.7, 808.5 mg/mL), water and vegetable oil using a MARS spectral scanner equipped with a poly-energetic X-ray source operated at 118 kVp and a CdTe Medipix3RX camera. Two imaging protocols were used; both with and without 0.375 mm external brass filter. A proprietary material decomposition method identified voxels as gadolinium, hydroxyapatite, lipid or water. Sensitivity and specificity information was used to evaluate material misidentification. Biological samples were also scanned. There were marked differences in identification and quantification between the two protocols even though spectral and linear correlation of gadolinium and hydroxyapatite in the reconstructed images was high and no qualitative segmentation differences in the material decomposed images were observed. At 8 mg/mL, gadolinium was correctly identified for both protocols, but concentration was underestimated by over half for the unfiltered protocol. At 1 mg/mL, gadolinium was misidentified in 38% of voxels for the filtered protocol and 58% of voxels for the unfiltered protocol. Hydroxyapatite was correctly identified at the two higher concentrations for both protocols, but mis-quantified for the unfiltered protocol. Gadolinium concentration as measured in the biological specimen showed a two-fold difference between protocols. In future, this methodology could be used to compare and optimize scanning protocols, image reconstruction methods, and methods for material differentiation in spectral CT.
Development and Evaluation of an Antimicrobial Formulation Containing Rosmarinus officinalis

Rosmarinus officinalis belongs to the Lamiaceae family, and its constituents show antioxidant, anti-inflammatory, antidepressant, antinociceptive, and antibacterial properties. The aim of this study was to develop a topical formulation with R. officinalis extract that had antimicrobial and antioxidant activity. Maceration, infusion, Soxhlet, and ultrasound were used to produce rosemary extracts, which were submitted to antioxidant, compound quantification, cell viability, and antimicrobial assays. Infusion and Soxhlet showed better results in the DPPH assay. During compound quantification, infusion showed promising metabolite extraction in phenolic compounds and tannins, although maceration was able to extract more flavonoids. The infusion and ultrasound extracts affected more strains of skin bacteria in the disk diffusion assays. In the minimum inhibitory concentration assay, the infusion extract showed results against S. aureus, S. oralis, and P. aeruginosa, while ultrasound showed effects against those three bacteria and E. coli. The infusion extract was chosen to be incorporated into a green emulsion. The infusion extract promoted lower spreadability and appropriated the texture, and the blank formulation showed high levels of acceptance among the volunteers. According to the results, the rosemary extract showed promising antioxidant and antimicrobial activity, and the developed formulations containing this extract were stable for over 90 days and had acceptable characteristics, suggesting its potential use as a phytocosmetic. This paper reports the first attempt to produce an oil-in-water emulsion using only natural excipients and rosemary extract, which is a promising novelty, as similar products cannot be found on the market or in the scientific literature.
A Novel Impervious Surface Extraction Method Based on Automatically Generating Training Samples From Multisource Remote Sensing Products: A Case Study of Wuhan City, China

Impervious surfaces caused by rapid urbanization affect the environment and increase the disaster risk. Currently, most articles have extracted impervious surfaces by manual participation for training samples with medium-and-high spatial resolution remote sensing images. Therefore, it is necessary to develop a new method for improving the efficiency of training sample acquisition and the accuracy of impervious surface extraction. In this article, a novel impervious surface extraction method is proposed based on automatically generating training samples from multisource remote sensing products. First, the preliminary sample area was constructed through the overlay analysis of the classification consistency area of three remote sensing products and homogeneous area detection based on Sentinel-2 images. Second, four spectral indices and digital surface model (DSM) elevation data were used for sample selection, and the pixels were further purified by variance purification calculation. Finally, by sample migration and random forest model training, impervious surfaces were extracted for other years with limited data. Wuhan city in China was selected as the study area due to a large number of interior objects for impervious surfaces. Sentinel-2 images from 2018 to 2020, three 30 m-resolution products, and DSM data in 2018 were used. The proposed method's extraction accuracies of impervious surfaces for Wuhan in 2018, 2019, and 2020 are 94.02%, 94.45%, and 93.87%, respectively. Additionally, with the resolution improved up to 10 m, the method is more conducive to distinguishing the boundary between impervious surfaces and pervious surfaces.
Improving of the working process of axial compressors of gas turbine engines by using an optimization method

The article presents one optimization method for improving of the working process of an axial compressor of gas turbine engine. Developed method allows to perform search for the best geometry of compressor blades automatically by using optimization software IOSO and CFD software NUMECA Fine/Turbo. Optimization was performed by changing the form of the middle line in the three sections of each blade and shifts of three sections of the guide vanes in the circumferential and axial directions. The calculation of the compressor parameters was performed for work and stall point of its performance map on each optimization step. Study was carried out for seven-stage high-pressure compressor and three-stage low-pressure compressors. As a result of optimization, improvement of efficiency was achieved for all investigated compressors.
Ruthenium(II) Polypyridyl Complexes for Antimicrobial Photodynamic Therapy: Prospects for Application in Cystic Fibrosis Lung Airways

Antimicrobial photodynamic therapy (aPDT) depends on a variety of parameters notably related to the photosensitizers used, the pathogens to target and the environment to operate. In a previous study using a series of Ruthenium(II) polypyridyl ([Ru(II)]) complexes, we reported the importance of the chemical structure on both their photo-physical/physico-chemical properties and their efficacy for aPDT. By employing standard in vitro conditions, effective [Ru(II)]-mediated aPDT was demonstrated against planktonic cultures of Pseudomonas aeruginosa and Staphylococcus aureus strains notably isolated from the airways of Cystic Fibrosis (CF) patients. CF lung disease is characterized with many pathophysiological disorders that can compromise the effectiveness of antimicrobials. Taking this into account, the present study is an extension of our previous work, with the aim of further investigating [Ru(II)]-mediated aPDT under in vitro experimental settings approaching the conditions of infected airways in CF patients. Thus, we herein studied the isolated influence of a series of parameters (including increased osmotic strength, acidic pH, lower oxygen availability, artificial sputum medium and biofilm formation) on the properties of two selected [Ru(II)] complexes. Furthermore, these compounds were used to evaluate the possibility to photoinactivate P. aeruginosa while preserving an underlying epithelium of human bronchial epithelial cells. Altogether, our results provide substantial evidence for the relevance of [Ru(II)]-based aPDT in CF lung airways. Besides optimized nano-complexes, this study also highlights the various needs for translating such a challenging perspective into clinical practice.
Multistacked Al2O3∕HfO2∕SiO2 tunnel layer for high-density nonvolatile memory application

A memory capacitor with a multistacked tunnel layer of Al2O3∕HfO2∕SiO2 (AHO) has been fabricated together with HfO2 charge trapping layer and Al2O3 control oxide layer. The resulting capacitor exhibits a memory window as large as 7.6V for ±12V sweep voltage range, a significant flatband voltage shift of 2.1V after 10V∕100μs programing as well as improved charge retention compared with a single SiO2 tunnel layer. The different memory effects in various sweep voltage ranges and enhanced retention characteristics have been explained based on the variable electrical thickness of the AHO stack under different electric fields.
The 1820s Marks a Shift to Hotter‐Drier Summers in Western Europe Since 1360

Recent soil moisture (SM) reconstructions revealed plunging trends and enhanced SM‐temperature couplings over the last two decades in dry regions. However, how SM changed and whether the land‐atmosphere interaction was intensified over time in humid regions remained unknown. Here we reported the first six‐century‐long regional summer SM reconstruction (1360–2000 CE) in western Europe (WE) using three individual tree‐ring δ18O chronologies in England and France. A sharp wet‐to‐dry change occurred around 1820, earlier than 1850–1900 CE, the commonly used historical baseline of anthropogenic climate changes. Enhanced coupling of SM‐temperature followed, with stronger summer sea level pressure anomalies in dry years after the 1820s. Our results reveal that the hotter‐drier regime has also become more frequent in humid WE under global warming.