Miracle-dz/UniFAR-FTUs huggingface dataset:
Lateral and Longitudinal Driving Behavior Prediction Based on Improved Deep Belief Network

Accurately predicting driving behavior can help to avoid potential improper maneuvers of human drivers, thus guaranteeing safe driving for intelligent vehicles. In this paper, we propose a novel deep belief network (DBN), called MSR-DBN, by integrating a multi-target sigmoid regression (MSR) layer with DBN to predict the front wheel angle and speed of the ego vehicle. Precisely, the MSR-DBN consists of two sub-networks: one is for the front wheel angle, and the other one is for speed. This MSR-DBN model allows ones to optimize lateral and longitudinal behavior predictions through a systematic testing method. In addition, we consider the historical states of the ego vehicle and surrounding vehicles and the driver’s operations as inputs to predict driving behaviors in a real-world environment. Comparison of the prediction results of MSR-DBN with a general DBN model, back propagation (BP) neural network, support vector regression (SVR), and radical basis function (RBF) neural network, demonstrates that the proposed MSR-DBN outperforms the others in terms of accuracy and robustness.
System for Tool-Wear Condition Monitoring in CNC Machines under Variations of Cutting Parameter Based on Fusion Stray Flux-Current Processing

The computer numerical control (CNC) machine has recently taken a fundamental role in the manufacturing industry, which is essential for the economic development of many countries. Current high quality production standards, along with the requirement for maximum economic benefits, demand the use of tool condition monitoring (TCM) systems able to monitor and diagnose cutting tool wear. Current TCM methodologies mainly rely on vibration signals, cutting force signals, and acoustic emission (AE) signals, which have the common drawback of requiring the installation of sensors near the working area, a factor that limits their application in practical terms. Moreover, as machining processes require the optimal tuning of cutting parameters, novel methodologies must be able to perform the diagnosis under a variety of cutting parameters. This paper proposes a novel non-invasive method capable of automatically diagnosing cutting tool wear in CNC machines under the variation of cutting speed and feed rate cutting parameters. The proposal relies on the sensor information fusion of spindle-motor stray flux and current signals by means of statistical and non-statistical time-domain parameters, which are then reduced by means of a linear discriminant analysis (LDA); a feed-forward neural network is then used to automatically classify the level of wear on the cutting tool. The proposal is validated with a Fanuc Oi mate Computer Numeric Control (CNC) turning machine for three different cutting tool wear levels and different cutting speed and feed rate values.
Short-Term Supplemental Dietary Potassium from Potato and Potassium Gluconate: Effect on Calcium Retention and Urinary pH in Pre-Hypertensive-to-Hypertensive Adults

Potassium supplementation has been associated with reduced urinary calcium (Ca) excretion and increased Ca balance. Dietary interventions assessing the impact of potassium on bone are lacking. In this secondary analysis of a study designed primarily to determine blood pressure effects, we assessed the effects of potassium intake from potato sources and a potassium supplement on urinary Ca, urine pH, and Ca balance. Thirty men (n = 15) and women (n = 15) with a mean ± SD age and BMI of 48.2 ± 15 years and 31.4 ± 6.1 kg/m2, respectively, were enrolled in a cross-over, randomized control feeding trial. Participants were assigned to a random order of four 16-day dietary potassium interventions including a basal diet (control) of 2300 mg/day (~60 mmol/day) of potassium, and three phases of an additional 1000 mg/day (3300 mg/day(~85 mmol/day) total) of potassium in the form of potatoes (baked, boiled, or pan-heated), French fries (FF), or a potassium (K)-gluconate supplement. Calcium intake for all diets was approximately 700–800 mg/day. Using a mixed model ANOVA there was a significantly lower urinary Ca excretion in the K-gluconate phase (96 ± 10 mg/day) compared to the control (115 ± 10 mg/day; p = 0.027) and potato (114 ± 10 mg/day; p = 0.033). In addition, there was a significant difference in urinary pH between the supplement and control phases (6.54 ± 0.16 vs. 6.08 ± 0.18; p = 0.0036). There were no significant differences in Ca retention. An increased potassium intake via K-gluconate supplementation may favorably influence urinary Ca excretion and urine pH. This trial was registered at ClinicalTrials.gov as NCT02697708.
A Novel Role for Histatin 5 in Combination with Zinc to Promote Commensalism in C. albicans Survivor Cells

Candida albicans is maintained as a commensal by immune mechanisms at the oral epithelia. Oral antifungal peptide Histatin 5 (Hst 5) may function in innate immunity, but the specific role Hst 5 plays in C. albicans commensalism is unclear. Since Zn-binding potentiates the candidacidal activity of Hst 5, we hypothesized that Hst 5+Zn would elicit a unique fungal stress response to shape interactions between C. albicans and oral epithelial cells (OECs). We found that Hst 5+Zn but not Hst 5 alone resulted in the activation of cell wall integrity (CWI) signaling, and deletion mutants were then used to determine that CWI-mediated chitin synthesis was protective against killing. Using flow cytometry, we confirmed that Hst 5+Zn-treated cells had significantly elevated levels of cell-wall chitin, mannan and β-1,3 glucan compared to Hst 5-treated cells. We then tested the activation of host signaling components involved in C. albicans cell-wall recognition. The immunoblot assay of C. albicans-exposed oral epithelial cells showed increased activation of EphA2 and NF-κB but not EGFR. Interestingly, C. albicans treated with Hst 5+Zn induced the global suppression of pro-inflammatory cytokine release from OECs, but an increase in negative regulator IL-10. Hst 5+Zn-treated cells were more adherent but ultimately less invasive to OECs than control cells, thus indicating lowered virulence. Therefore, Hst 5+Zn-treated C. albicans cells are discerned by epithelial monolayers, but are less virulent and promote anti-inflammatory signaling, suggesting that Hst 5+Zn in combination could play a role in regulating commensalism of oral C. albicans through cell wall reorganization.
Quasispecies Composition of Small Ruminant Lentiviruses Found in Blood Leukocytes and Milk Epithelial Cells

Small ruminant lentiviruses (SRLVs) exist as populations of closely related genetic variants, known as quasispecies, within an individual host. The privileged way of SRLVs transmission in goats is through the ingestion of colostrum and milk of infected does. Thus, characterization of SRLV variants transmitted through the milk, including milk epithelial cells (MEC), may provide useful information about the transmission and evolution of SRLVs. Therefore, the aim of this study was to detect SRLVs in peripheral blood leukocytes (PBLs) and milk epithelial cells of goats naturally infected with SRLVs and perform single nucleotide variations analysis to characterize the extent of genetic heterogeneity of detected SRLVs through comparison of their gag gene sequences. Blood and milk samples from 24 seropositive goats were tested in this study. The double immunolabeling against p28 and cytokeratin demonstrated that milk epithelial cells originated from naturally infected goats were infected by SRLVs. Moreover, PCR confirmed the presence of the integrated SRLVs proviral genome indicating that MECs may have a role as a reservoir of SRLVs and can transmit the virus through milk. The blood and MEC derived sequences from 7 goats were successfully sequenced using NGS and revealed that these sequences were genetically similar. The MEC and blood-derived sequences contained from 3 to 30 (mean, 10.8) and from 1 to 10 (mean, 5.4) unique SNVs, respectively. In five out of seven goats, SNVs occurred more frequent in MEC derived sequences. Non-synonymous SNVs were found in both, PBLs and MEC-derived sequences of analyzed goats and their total number differed between animals. The results of this study add to our understanding of SRLVs genomic variability. Our data provides evidence for the existence of SRLVs quasispecies and to our knowledge, this is the first study that showed quasispecies composition and minority variants of SRLVs present milk epithelial cells.
Algorithmic component and system reliability analysis of truss structures

Most of the parameters involved in the design and analysis of structures are of stochastic nature. This is, therefore, of paramount importance to be able to perform a fully stochastic analysis of structures both in component and system level to take into account the uncertainties involved in structural analysis and design. To the contrary, in practice, the (computerised) analysis of structures is based on a deterministic analysis which fails to address the randomness of design and analysis parameters. This means that an investigation on the algorithmic methodologies for a component and system reliability analysis can help pave the way towards the implementation of fully stochastic analysis of structures in a computer environment. This study is focused on algorithm development for component and system reliability analysis based on the various proposed methodologies. Truss structures were selected for this purpose due to their simplicity as well as their wide use in the industry. Nevertheless, the algorithms developed in this study can be used for other types of structures such as moment-resisting frames with some simple modifications. For a component level reliability analysis of structures different methods such as First Order Reliability Methods (FORM) and simulation methods are proposed. However, implementation of these methods for the statistically indeterminate structures is complex due to the implicit relation between the response of the structural system and the load effect. As a result, the algorithm developed for the purpose of component reliability analysis should be based on the concepts of Stochastic Finite Element Methods (SFEM) where a proper link between the finite element analysis of the structure and the reliability analysis methodology is ensured. In this study various algorithms are developed based on the FORM method, Monte Carlo simulation, and the Response Surface Method (RSM). Using the FORM method, two methodologies are considered: one is based on the development of a finite element code where required alterations are made to the FEM code and the other is based on the usage of a commercial FEM package. Different simulation methods are also implemented: Direct Monte Carlo Simulation (DMCS), Latin Hypercube Sampling Monte Carlo (LHCSMC), and Updated Latin Hypercube Sampling Monte Carlo (ULHCSMC). Moreover, RSM is used together with simulation methods. Throughout the thesis, the efficiency of these methods was investigated. A Fully Stochastic Finite Element Method (FSFEM) with alterations to the finite element code seems the fastest approach since the linking between the FEM package and reliability analysis is avoided. Simulaii Stellenbosch University http://scholar.sun.ac.za
Biomechanical analysis of stand-alone lumbar interbody cages versus 360° constructs: an in vitro and finite element investigation.

OBJECTIVE Low fusion rates and cage subsidence are limitations of lumbar fixation with stand-alone interbody cages. Various approaches to interbody cage placement exist, yet the need for supplemental posterior fixation is not clear from clinical studies. Therefore, as prospective clinical studies are lacking, a comparison of segmental kinematics, cage properties, and load sharing on vertebral endplates is needed. This laboratory investigation evaluates the mechanical stability and biomechanical properties of various interbody fixation techniques by performing cadaveric and finite element (FE) modeling studies. METHODS An in vitro experiment using 7 fresh-frozen human cadavers was designed to test intact spines with 1) stand-alone lateral interbody cage constructs (lateral interbody fusion, LIF) and 2) LIF supplemented with posterior pedicle screw-rod fixation (360° constructs). FE and kinematic data were used to validate a ligamentous FE model of the lumbopelvic spine. The validated model was then used to evaluate the stability of stand-alone LIF, transforaminal lumbar interbody fusion (TLIF), and anterior lumbar interbody fusion (ALIF) cages with and without supplemental posterior fixation at the L4-5 level. The FE models of intact and instrumented cases were subjected to a 400-N compressive preload followed by an 8-Nm bending moment to simulate physiological flexion, extension, bending, and axial rotation. Segmental kinematics and load sharing at the inferior endplate were compared. RESULTS The FE kinematic predictions were consistent with cadaveric data. The range of motion (ROM) in LIF was significantly lower than intact spines for both stand-alone and 360° constructs. The calculated reduction in motion with respect to intact spines for stand-alone constructs ranged from 43% to 66% for TLIF, 67%-82% for LIF, and 69%-86% for ALIF in flexion, extension, lateral bending, and axial rotation. In flexion and extension, the maximum reduction in motion was 70% for ALIF versus 81% in LIF for stand-alone cases. When supplemented with posterior fixation, the corresponding reduction in ROM was 76%-87% for TLIF, 86%-91% for LIF, and 90%-92% for ALIF. The addition of posterior instrumentation resulted in a significant reduction in peak stress at the superior endplate of the inferior segment in all scenarios. CONCLUSIONS Stand-alone ALIF and LIF cages are most effective in providing stability in lateral bending and axial rotation and less so in flexion and extension. Supplemental posterior instrumentation improves stability for all interbody techniques. Comparative clinical data are needed to further define the indications for stand-alone cages in lumbar fusion surgery.
Typing of alpha and beta coronaviruses by DNA barcoding of NSP12 gene

Since the spread of the COVID‐19 pandemic, the world paid attention to coronaviruses (CoVs) evolution and their diverged lineages because many researches studies supposed that the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is evolutionarily developed from a lineage of bats CoVs. This is due to the ability of some mutant CoVs to transmit from a host to different hosts. For this reason, there are many fears about the pathogenicity of the upcoming variants of CoVs. Thus, it is important to get a rapid and economic technique for typing a wide range of human and animal CoVs species for following up their mutant transmission. Therefore, the present study aims at approaching a simple design of DNA barcoding of a wide range of mammals' CoVs (including alpha and beta CoVs), by universal amplification of a species‐specific sequence inside a conserved gene (NSP12) followed by amplicon sequencing. The in silico evaluation involved 96 nucleotide sequences of different CoVs (18 alpha CoVs and 78 beta CoVs), and was applied experimentally into the lab on 5 human CoVs isolates; 3 of them belong to beta CoVs (OC43, MERS, and SARS‐CoV‐2) and 2 are alpha CoVs (229E and NL63). The results indicated that the designed universal primers are able to amplify 332 bp of a taxonomic region inside the NSP12 coding sequence that facilitates the identification and classification of mammals' CoVs upon the resulting phylogenetic tree.
Assessing fatigue in childhood cancer survivors: Psychometric properties of the Checklist Individual Strength and the Short Fatigue Questionnaire––a DCCSS LATER study

Fatigue is often reported by patients with childhood cancer both during and after cancer treatment. Several instruments to measure fatigue exist, although none are specifically validated for use in childhood cancer survivors (CCS). The aim of the current study was to present norm values and psychometric properties of the Checklist Individual Strength (CIS) and Short Fatigue Questionnaire (SFQ) in a nationwide cohort of CCS.
Chemically induced senescence in human stem cell‐derived neurons promotes phenotypic presentation of neurodegeneration

Modeling age-related neurodegenerative disorders with human stem cells is difficult due to the embryonic nature of stem cell derived neurons. We developed a chemical cocktail to induce senescence of iPSC-derived neurons to address this challenge. We first screened small molecules that induce embryonic fibroblasts to exhibit features characteristic of aged fibroblasts. We then optimized a cocktail of small molecules that induced senescence in fibroblasts and cortical neurons without causing DNA damage. The utility of the “senescence cocktail” was validated in motor neurons derived from ALS patient iPSCs which exhibited protein aggregation and axonal degeneration substantially earlier than those without cocktail treatment. Our “senescence cocktail” will likely enhance the manifestation of disease-related phenotypes in neurons derived from iPSCs, enabling the generation of reliable drug discovery platforms.
Rapid processing and quantitative evaluation of structural brain scans for adaptive multimodal imaging

Current neuroimaging acquisition and processing approaches tend to be optimised for quality rather than speed. However, rapid acquisition and processing of neuroimaging data can lead to novel neuroimaging paradigms, such as adaptive acquisition, where rapidly processed data is used to inform subsequent image acquisition steps. Here we first evaluate the impact of several processing steps on the processing time and quality of registration of manually labelled T1‐weighted MRI scans. Subsequently, we apply the selected rapid processing pipeline both to rapidly acquired multicontrast EPImix scans of 95 participants (which include T1‐FLAIR, T2, T2*, T2‐FLAIR, DWI and ADC contrasts, acquired in ~1 min), as well as to slower, more standard single‐contrast T1‐weighted scans of a subset of 66 participants. We quantify the correspondence between EPImix T1‐FLAIR and single‐contrast T1‐weighted scans, using correlations between voxels and regions of interest across participants, measures of within‐ and between‐participant identifiability as well as regional structural covariance networks. Furthermore, we explore the use of EPImix for the rapid construction of morphometric similarity networks. Finally, we quantify the reliability of EPImix‐derived data using test–retest scans of 10 participants. Our results demonstrate that quantitative information can be derived from a neuroimaging scan acquired and processed within minutes, which could further be used to implement adaptive multimodal imaging and tailor neuroimaging examinations to individual patients.
Self-administered oral glucose tolerance test with capillary glucose measurements for the screening of diabetes mellitus in high-risk adults: a feasibility study

Introduction Early diagnosis of prediabetes based on blood sampling for the oral glucose tolerance test (OGTT) is crucial for intervention but multiple barriers hinder its uptake. This study aimed to assess the feasibility and precision of a self-administered capillary OGTT for type-2 diabetes mellitus (T2DM) in high-risk individuals. Research design and methods Participants with history of gestational diabetes or prediabetes were recruited in primary care. Due to their prediabetic status and previous diagnosis of gestational diabetes mellitus, a proportion of participants had previous experience doing OGTT. They self-administered the capillary OGTT and concurrently their venous glucose samples were obtained. They filled a questionnaire to collect their demographic information, views of their capillary OGTT, and their preferred site of the test. Results Among 30 participants enrolled in this feasibility study, 93.3% of them felt confident of performing the capillary OGTT themselves, and 70.0% preferred the test at home. Older, less educated participants found it less acceptable. Mean capillary glucose values were significantly higher than venous glucose values, with mean difference at 0.31 mmol/L (95% CI 0.13 to 0.49) at fasting, and 0.47 mmol/L (95% CI 0.12 to 0.92) 2 hours post-OGTT. Capillary and venous glucose measurements were correlated for fasting (r=0.95; p<0.001) and 2-hour-post-OGTT (r=0.95;p<0.001). The Fleiss-Kappa Score (0.79, p<0.0001) indicated fair agreement between the two methods. The capillary OGTT had excellent sensitivity (94.1%) and negative predictive value (NPV=91.7%) in identifying prediabetes or T2DM status, vis-a-vis to venous glucose samples. Conclusion Self-administered capillary OGTT is feasible and acceptable, especially among younger adults, with excellent sensitivity and NPV compared with plasma-based OGTT.
Use of power analysis to determine the number of samples needed to assess water quality in lakes and flowing waters

The Clean Water Act requires states to develop methods for assessing water quality. Assessment methods serve as decision‐making procedures for including waterbodies on the Section 303(d) List of Impaired Waters. We used 17 years of ambient water quality data to explore statistical analyses for assessment methods that represent New York's waterbodies. Power analyses were performed to determine how many samples are needed to evaluate exceedances of water quality criteria using one‐sample t‐tests in lakes and flowing waters. Results suggest six samples for lakes and eight samples for flowing waters are needed to obtain at least 80% power, which is fewer samples than most other types of statistical assessment methodologies. This smaller number was possible because the power analysis was applied to the actual variability found in monitoring data to calculate the effect size as opposed to more conservative statistical estimates based on random data. Water quality criteria can have different analysis requirements such as single samples or means above the threshold, so we compared how many impairments would occur in the dataset if the six or eight samples were assessed as two single exceedances or a mean above the water quality criteria. Because the power analysis gives no indication of the time frame of when samples should be collected, the intra‐ and interannual variability of the data was assessed to determine whether sampling over a growing season in one year or sampling over multiple years is more representative of the water quality status. Results demonstrated that data collected over the growing season captured more variability in water quality data than data collected over multiple years in both waterbody types. With the prevalence of regulatory agencies having large, historical datasets rising, it would be possible for other agencies to apply these types of analyses to their assessment methodologies. Integr Environ Assess Manag 2022;18:1621–1628. © 2021 SETAC