Miracle-dz/UniFAR-FTUs huggingface dataset:
BACK ANALYSIS BY KALMAN FILTER-FINITE ELEMENTS AND A DETERMINATION OF OPTIMAL OBSERVED POINTS LOCATION

This paper focuses on the following two topics: one is a new back analysis method using Kalman Filter-Finite Elements; the other is a determination of optimal location of observed nodal points for back analysis. A formulation is shown on Finite Element Method in conjunction with Kalman filter for two dimensional and plane strain problem, where Lame's constants of non-homogeneous regions are solved. In the numerical procedure, the location of observed nodal points is determined taking into account the ‘sensitivity’ coefficients. These coefficients are defined as the derivatives of observed displacements by unknown parameters. The role and the meaning of ‘sensitivity’ coefficients in the Kalman Filter-Finite Elements are also discussed. The numerical performances for various problems in the field of geomechanics are described, and the applicability of the above procedure to some back analysis problems is examined on the comparison with the results by another algorithms.
Molecular basis of a high Hb A2/Hb Fβ-thalassemia trait: a retrospective analysis, genotype-phenotype interaction, diagnostic implication, and identification of a novel interaction with α-globin gene triplication

Background β0-thalassemia deletion removing 5´β-globin promoter usually presents phenotype with high hemoglobin (Hb) A2 and Hb F levels. We report the molecular characteristics and phenotype-genotype correlation in a large cohort of the β0-thalassemia with 3.4 kb deletion. Methods A total of 148 subjects, including 127 heterozygotes, 20 Hb E-β-thalassemia patients, and a double heterozygote with α-globin gene triplication, were recruited. Hb and DNA analysis were performed to identify thalassemia mutations and four high Hb F single nucleotide polymorphisms (SNPs) including four base pair deletion (-AGCA) at Aγ-globin promoter, rs5006884 on OR51B6 gene, −158 Gγ-XmnI, BCL11A binding motifs (TGGTCA) between 3´Aγ-globin gene and 5´δ-globin gene. Results It was found that heterozygous β0-thalassemia and Hb E-β0-thalassemia with 3.4 kb deletion had significantly higher Hb, hematocrit, mean corpuscular volume, mean corpuscular hemoglobin and Hb F values as compared with those with other mutations. Co-inheritance of heterozygous β0-thalassemia with 3.4 kb deletion and α-thalassemia was associated with even higher MCV and MCH values. The Hb E-β0-thalassemia patients carried a non-transfusion-dependent thalassemia phenotype with an average Hb of around 10 g/dL without blood transfusion. A hitherto undescribed double heterozygous β0-thalassemia with 3.4 kb deletion and α-globin gene triplication presented as a plain β-thalassemia trait. Most of the subjects had wild-type sequences for the four high Hb F SNPs examined. No significant difference in Hb F was observed between those of subjects with and without these SNPs. Removal of the 5´β-globin promoter may likely be responsible for this unusual phenotype. Conclusions The results indicate that β0-thalassemia with 3.4 kb deletion is a mild β-thalassemia allele. This information should be provided at genetic counseling and prenatal thalassemia diagnosis.
Time‐Variability of Flow Recession Dynamics: Application of Machine Learning and Learning From the Machine

Flow recession analysis, relating discharge Q and its time rate of change −dQ/dt, has been widely used to understand catchment scale flow dynamics. However, data points in the recession plot, the plot of −dQ/dt versus Q, typically form a wide point cloud due to noise and hysteresis in the storage‐discharge relationship, and it is still unclear what information we can extract from the plot and how to understand the information. There seem to be two contrasting approaches to interpret the plot. One emphasizes the importance of the ensemble characteristics of many recessions (i.e., the lower envelope or a measure of central tendency), and the other highlights the importance of the event scale analysis and questions the meaning of the ensemble characteristics. We examine if those approaches can be reconciled. We utilize a machine learning tool to capture the point cloud using the past trajectory of daily discharge. Our model results for a catchment show that most of the data points can be captured using 5 days of past discharge. We show that we can learn the catchment scale flow recession dynamics from what the machine learned. We analyze patterns learned by the machine and explain and hypothesize why the machine learned those characteristics. The hysteresis in the plot mainly occurs during the early time dynamics, and the flow recession dynamics eventually converge to an attractor in the plot, which represents the master recession curve. We also illustrate that a hysteretic storage‐discharge relationship can be estimated based on the attractor.
A psychometric evaluation of the Big Five Inventory (BFI) in an Eastern Africa population

The Big Five factor model is one of the most frequently used models in modern personality psychology. It captures personality in terms of five broad dimensions, namely Extraversion, Agreeableness, Conscientiousness, Emotional Stability/Neuroticism, and Intellect/Openness to experience, discovered through a series of psycho-lexical studies. We translated the Big Five Inventory (BFI), a metric developed to operationalize the Big Five personality structure, into the Swahili language and evaluated the psychometric properties of both the newly developed Swahili version and the original English version in a sample of 200 university students (114 women; 86 men; average age: 20.16) in Kenya. Principal Component Analysis with varimax rotation of the five factors was conducted for both raw and ipsatized scores, for both language versions of the BFI. Only two factors were fully replicated, Conscientiousness and Neuroticism. Conscientiousness factor was fully replicated using ipsatized scores of the English BFI, while Neuroticism was replicated with both the raw and ipsatized scores of the English BFI. The Swahili version of the BFI failed to unambiguously replicate any of the five factors with neither the raw nor the ipsatized scores. Results also showed poor-to-moderate scale reliabilities of both the English and the Swahili versions of the BFI.
Information ohne Redundanz — Von den Markoffschen Ketten zu vollständigen Beziehungsnetzen

Nouveau modele ou la sequence des symboles est interpretee comme un schema, c'est-a-dire ou la relation d'un element aux autres est prise en condideration. Creant des relations dependantes et independantes, une grande quantite de relations existantes peuvent etre eliminees, car elles peuvent etre substituees par une somme de quelques relations independantes. Les relations N log N representant le reseau de relation minimum complet
The Utility of Fluorescence Recovery after Photobleaching (FRAP) to Study the Plasma Membrane

The plasma membrane of mammalian cells is involved in a wide variety of cellular processes, including, but not limited to, endocytosis and exocytosis, adhesion and migration, and signaling. The regulation of these processes requires the plasma membrane to be highly organized and dynamic. Much of the plasma membrane organization exists at temporal and spatial scales that cannot be directly observed with fluorescence microscopy. Therefore, approaches that report on the membrane’s physical parameters must often be utilized to infer membrane organization. As discussed here, diffusion measurements are one such approach that has allowed researchers to understand the subresolution organization of the plasma membrane. Fluorescence recovery after photobleaching (or FRAP) is the most widely accessible method for measuring diffusion in a living cell and has proven to be a powerful tool in cell biology research. Here, we discuss the theoretical underpinnings that allow diffusion measurements to be used in elucidating the organization of the plasma membrane. We also discuss the basic FRAP methodology and the mathematical approaches for deriving quantitative measurements from FRAP recovery curves. FRAP is one of many methods used to measure diffusion in live cell membranes; thus, we compare FRAP with two other popular methods: fluorescence correlation microscopy and single-particle tracking. Lastly, we discuss various plasma membrane organization models developed and tested using diffusion measurements.
On affine group actions on Stein manifolds

Abstract. We consider actions of the complex affine group Aff()$\operatorname{Aff}({\mathbb {C}})$. For the case the action exhibits a regular dicritic singularity psing()$p\in \operatorname{sing}({\mathcal {F}_{\varphi }})$ and the ambient manifold is Stein we prove a linearization theorem. In dimension three we prove a (Reeb) stability theorem for a holomorphic foliations given by an affine group action on Stein 3-manifolds.
Depression and Different Brain Areas: Neural Activity and Potential Mechanisms

Depression is a prevalent mental disorder that reduces the quality of life. It is associated with various psychological, behavioral, and physiological symptoms. A combination of genetic, epigenetic, and environmental factors could be traced in depression etiology. Depression affects various parts of the brain, becoming hypoactive and/or hyperactive. Various functions are impaired in depression due to the deregulated secretion of brain neurotransmitters, hormones, and growth factors. Moreover, it leads to immune system dysfunction and structural brain alterations. Therefore, administering proper and effective treatment for depression requires comprehensive knowledge of its underlying causes. All in all, the overview of the role of different brain areas and some of their influencing factors could be beneficial for the treatment of depression.
An Ultrasonic Target Identification System Based on Piezoelectric Micromachined Ultrasonic Transducers

In this paper, an ultrasonic target identification system based on Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) is proposed to improve the productivity efficiency of industrial production. The proposed system can accurately identify targets of different shapes. Two pieces of 3 × 3 PMUTs arrays with a resonant frequency of 115 kHz are used as the transmitter and receiver of the PMUTs-based ultrasonic sensor. The sensor is small in size and has high instability. In addition, the PMUTs based ultrasonic sensors have lower environmental requirements than vision sensors and are less expensive than laser sensors. Therefore, the sensors are suitable for large-scale use in industry. The characteristics of the proposed system are investigated in the shape experiments on the square, circle, frame, and ring targets. The four kinds of targets are acrylic plates with a thickness of 5mm. The experimental results show that the system can accurately identify the shapes of the four targets through the grid-based scheme. Besides, the identification process is automatically completed by the 3D mobile platform. The proposed system has demonstrated a cost-effective method to identify targets of different shapes, which can more efficiently guide the robotic manipulator’s grasping and other behaviors.
A dynamic failure mode and effect analysis (FMEA) method for CNC machine tool in service

To solve the problems such as uncertain evaluation information, high dependence on experts, and no consideration of the degradation of machine operating performance to failure risk in the practical application of FMEA in CNC machine tool operation and maintenance, a dynamic failure mode and effect analysis (FMEA) method for CNC machine tool in service is proposed, operation and maintenance data is introduced to the traditional failure risk analysis, which makes semantics criteria and data-driven method are systematically integrated, resulting in better performance of quantitative assessment and risk ranking of dynamic fault risk. Afterward, the fault classification and maintenance strategy of the CNC machine tool based on risk priority number (RPN) is proposed, which provides decision support for efficient operation and maintenance of the CNC machine tool. Finally, a machining center is taken as an example to verify the feasibility and effectiveness of the method.
A real-time dynamic simulation platform for 6R manipulators based on an explicit modeling method

Dynamic simulation is critical for robotic design and control. In this study, a modular simulation platform is developed using a novel explicit dynamic modeling method. Combined with a PD controller and a globally linearized compensator, the dynamic modeling method presents an explicit and canonical form for tree-chain and closed-chain multi-body systems. Paired with the new approach, the platform makes it convenient for modeling, and it performs well in real-time with a high update frequency. The platform also offers a thorough parameter setting and simulation scene presentation interface through the construction of several modules. A simulation experiment using a 6-DOF manipulator demonstrates the platform’s capacity for real-time, stable, and practical simulations, which is also applicable for high-DOF multi-body systems of future uses.
Aerodynamic parameter calculation and ballistic stability research of special projectile

Based on the aerodynamic layout of special projectiles, a targeted aerodynamic parameter solution algorithm is built by a mechanical analysis model. The simulation software is used to analyze the ballistic stability. The results show that the aerodynamic layout with the center of gravity moving down is helpful to overcome the rolling interference in uncontrolled flight.
Quantile regressions as a tool to evaluate how an exposure shifts and reshapes the outcome distribution: A primer for epidemiologists

Most regression models estimate an exposure's association with the mean value of the outcome, but quantifying how an exposure affects the entire outcome distribution is often important (e.g., when the outcome has non-linear relationships with risk of other adverse outcomes). Quantile regressions offer a powerful way of estimating an exposure's relationship with the outcome distribution but remain underused in epidemiology. We introduce quantile regressions and then present an empirical example in which we fit mean and quantile regressions to investigate the association of educational attainment with later-life systolic blood pressure (SBP). We use data on 8,875 US-born respondents aged 50+ years from the Health and Retirement Study. More education was negatively associated with mean SBP. Conditional and unconditional quantile regressions both suggested a negative association between education and SBP at all levels of SBP, but the absolute magnitudes of these associations were higher at higher SBP quantiles relative to lower quantiles. While all estimators showed more education was associated with a leftward shift of the SBP distribution, quantile regression results additionally revealed that education may have reshaped the SBP distribution through larger protective associations in the right tail, thus benefiting those at highest risk of cardiovascular diseases.
Population variability in thermal performance of pre-spawning adult Chinook salmon

Warming water temperatures threaten aquatic species and impact economies and cultures. Yet, vulnerability can vary within a species. We assessed the thermal performance of two populations of pre-spawning adult Chinook salmon and found that an interior summer-run population of Chinook salmon performed better at warmer temperatures than a coastal fall-run population. Current river temperatures already exceed the functional warming tolerances of both populations and highlight the value of physiological studies in supporting management decisions.
Endoplasmic Reticulum Stress Promotes Prostate Cancer Cells to Release Exosome and Up-regulate PD-L1 Expression via PI3K/Akt Signaling Pathway in Macrophages

Mounting evidence has demonstrated that endoplasmic reticulum stress (ERS) serves an important role in shaping the immunosuppressive microenvironment by modulating resident tumor-associated macrophages (TAMs). However, the communication between ER‑stressed tumor cells and TAMs is not fully understood. Exosomes have been reported to play a vital role in intercellular communication. Therefore, in order to investigate the role of ER stress‑related exosomes in prostate cancer cells promoting macrophage infiltration and polarization, laser scanning confocal microscope, RT-PCR, flow cytometric analysis, western‑blotting and cytokine bead array analyses were performed.The results demonstrated that TG-EXO downregulated the expression of PD-L1 on macrophages through flow cytometry analysis. In addition, Compared with CON-EXO, the expression of macrophage-associated inflammatory cytokines IL-12, TNF-α and IL-1βwas significantly decreased in TG-EXO treatment (P< 0.05). TG-EXO upregulated the expression levels of IL-6, IL-10 and TGF-β cytokinesin macrophages. Our research shows that TG-EXO increased PI3K/AKT signaling pathway compared to the CON-EXO group. In summary, we found exosomes from TG-treated prostate cancer cells altered the immunosupression status and affected macrophages polarization by up-regulating the expression of PD-L1 and inflammatory factors and PI3K/AKT pathway.
Targeting HSF1 for cancer treatment: mechanisms and inhibitor development

Heat Shock Factor 1 (HSF1) is a master regulator of heat shock responsive signaling. In addition to playing critical roles in cellular heat shock response, emerging evidence suggests that HSF1 also regulates a non-heat shock responsive transcriptional network to handle metabolic, chemical, and genetic stress. The function of HSF1 in cellular transformation and cancer development has been extensively studied in recent years. Due to important roles for HSF1 for coping with various stressful cellular states, research on HSF1 has been very active. New functions and molecular mechanisms underlying these functions have been continuously discovered, providing new targets for novel cancer treatment strategies. In this article, we review the essential roles and mechanisms of HSF1 action in cancer cells, focusing more on recently discovered functions and their underlying mechanisms to reflect the new advances in cancer biology. In addition, we emphasize new advances with regard to HSF1 inhibitors for cancer drug development.
High levels of indoor fine particulate matter during the cold season in Almaty prompt urgent public health action

Introduction Almaty is the largest city of Kazakhstan with extreme air pollution, mostly in the cold season, but little is known whether staying indoors could lessen the exposure. The aim was to quantitatively characterize indoor fine PM levels and to verify the contribution of ambient pollution to it in a polluted city like Almaty. Methods We collected forty-six 24-hour 15-min average samples of the ambient air and a similar number of paired indoor samples (total 92 samples). Predictors of both ambient and indoor PM2.5 mass concentrations in mg/m3, including ambient concentration, precipitation, minimal daily temperature and humidity, along with the indoor/outdoor (I/O) ratio were tested in the adjusted regression models at eight 15-min lags. Results Ambient air PM2.5 15-min average mass concentrations were highly variable and ranged from 0.001 to 0.694 mg/m3 (geometric mean (GM) 0.090, geometric standard deviation (GSD) 2.285). Snowing was the strongest predictor of lower ambient PM2.5 24-hour mass concentrations (median 0.053 vs 0.135 mg/m3 (p<0.001)). Indoor mean 15-min PM2.5 concentrations ranged from 0.002 to 0.228 mg/m3 (GM 0.034, GSD 2.254). In adjusted models, outdoor PM2.5 concentration explained 0.58 of all variability of the indoor concentration with a 75-min delay (R2 0.67 at lag8 on snowing days). Median I/O ranged from 0.386 (IQR 0.264 to 0.532) at lag0 to 0.442 (IQR 0.339 to 0.584) at lag8. Conclusion During the cold season when fossil fuel is burnt for heating, the population in Almaty is exposed to very high fine PM levels even indoors. Urgent public health action is needed.
Early changes of fecal short‐chain fatty acid levels in patients with mild cognitive impairments

To compare the fecal levels of short‐chain fatty acids (SCFAs) in patients with mild cognitive impairment (MCI) and normal controls (NCs) and to examine whether fecal SCFAs could be used as the biomarker for the identification of patients with MCI. To examine the relationship between fecal SCFAs and amyloid‐β (Aβ) deposition in the brain.
eIF4EHP promotes Ldh mRNA translation in and fruit fly adaptation to hypoxia

Hypoxia induces profound modifications in the gene expression program of eukaryotic cells due to lowered ATP supply resulting from the blockade of oxidative phosphorylation. One significant consequence of oxygen deprivation is the massive repression of protein synthesis, leaving a limited set of mRNAs to be translated. Drosophila melanogaster is strongly resistant to oxygen fluctuations; however, the mechanisms allowing specific mRNA to be translated into hypoxia are still unknown. Here, we show that Ldh mRNA encoding lactate dehydrogenase is highly translated into hypoxia by a mechanism involving a CA‐rich motif present in its 3′ untranslated region. Furthermore, we identified the cap‐binding protein eIF4EHP as a main factor involved in 3′UTR‐dependent translation under hypoxia. In accordance with this observation, we show that eIF4EHP is necessary for Drosophila development under low oxygen concentrations and contributes to Drosophila mobility after hypoxic challenge. Altogether, our data bring new insight into mechanisms contributing to LDH production and Drosophila adaptation to oxygen variations.
Weight stigma interventions as future avenues for stigma resistance: comment on Dubreucq et al.

Dubreucq et al. (2022) highlight the role stigma resistance in people with serious mental illness might play in people ’ s trajectories of personal recovery. They found that participants with elevated resistance to internalized mental health stigma – around half of their sample – were more likely to be in advanced stages of personal recovery. They also found correlations supporting that stigma resistance to mental health stigma was related to other positive outcomes such as wellbeing and life satisfaction. In their insightful conclusions, the authors propose interventions through which stigma resistance toward mental health stigma can be improved and its benefits reaped toward better recovery outcomes in serious mental illness. Dubreucq et al. ’ s (2022) line of work opens productive avenues through which we can improve outcomes for people with serious mental illnesses. One of these potential avenues is using stigma resistance interventions in dealing with weight stigma in people with serious mental illness. People with schizophrenia and other serious mental illnesses have higher weights and rates of obesity than the general population (Afzal et al., 2021). This has been associated with a higher risk of developing metabolic syndrome and years of life lost (De Hert, Schreurs, Vancampfort, & Van Winkel, 2009) as well as a decline in quality of life (Allison, Mackell, & McDonnell, 2003). Fortunately, these physical health issues have come to the