Miracle-dz/UniFAR-FTUs huggingface dataset:
The Role of Complex, Simultaneous Trunk Motions in the Risk of Occupation‐Related Low Back Disorders

Study Design. Simultaneous trunk kinematic variables of industrial workers performing jobs with varying degrees of low back disorder risk were quantified, by using a three‐dimensional electrogoniometer. Objectives. To assess the distinguishing patterns of simultaneous multidimensional (complex) motion parameters of workers performing manual material handling jobs with varying degrees of low back disorder risk. Summary of Background Data. There is significant epidemiologic and biomechanical evidence that implicates simultaneously occurring or combined motions and loading as important risk factors for low back disorder. However, the specific levels or magnitudes and patterns of these complex motions at which risk of low back disorder is increased are still unknown. Methods. An industrial database of 126 workers and jobs was used to quantify the complex trunk motions of groups with varying degrees of low back disorder risk. Three groups, low‐, medium‐, and high‐risk, were defined on the basis of retrospective injury records of the corresponding jobs. The jobs were further classified into five cells of weight‐lift rate combinations. Within each weight‐lift rate cell, the three‐dimensional trunk motion patterns of workers were analyzed. Bivariate distributions and cumulative distribution functions were used to compare the simultaneous occurrence of complex dynamic motions among risk groups. Results. High‐ and medium‐risk groups exhibited complex trunk motion patterns involving high magnitudes of combined velocities, especially at extreme sagittal flexion; whereas the low‐risk group did not. Postural trunk information alone did not provide a consistent pattern for distinguishing among risk groups. Conclusions. Elevated levels of complex simultaneous velocity patterns were unique to groups with increased low back disorder risk. Knowledge of these complex trunk velocity patterns in combination with key workplace factors provides a more sensitive means for identifying low back disorder occupational risk factors than does mere postural information.
Hydroxyurea‐induced senescent peripheral blood mesenchymal stromal cells inhibit bystander cell proliferation of JAK2V617F‐positive human erythroleukemia cells

Hydroxyurea (HU) is a nonalkylating antineoplastic agent used in the treatment of hematological malignancies. HU is a DNA replication stress inducer, and as such, it may induce a premature senescence‐like cell phenotype; however, its repercussion on bystander cell proliferation has not been revealed so far. Our results indicate that HU strongly inhibited peripheral blood mesenchymal stromal cells (PBMSC) proliferation by cell cycle arrest in S phase, and that, consequently, PBMSC acquire senescence‐related phenotypical changes. HU‐treated PBMSC display increased senescence‐associated β‐galactosidase levels and p16INK4 expression, as well as DNA damage response and genotoxic effects, evidenced by expression of γH2A. X and micronuclei. Moreover, HU‐induced PBMSC senescence is mediated by increased reactive oxygen species (ROS) levels, as demonstrated by the inhibition of senescence markers in the presence of ROS scavenger N‐acetylcysteine and NADPH oxidase inhibitor Apocynin. To determine the HU‐induced bystander effect, we used the JAK2V617F‐positive human erythroleukemia 92.1. 7 (HEL) cells. Co‐culture with HU‐induced senescent PBMSC (HU‐S‐PBMSC) strongly inhibited bystander HEL cell proliferation, and this effect is mediated by both ROS and transforming growth factor (TGF)‐β expression. Besides induction of premature senescence, HU educates PBMSC toward an inhibitory phenotype of HEL cell proliferation. Finally, our study contributes to the understanding of the role of HU‐induced PBMSC senescence as a potential adjuvant in hematological malignancy therapies.
Oxygen delivery, carbon dioxide removal, energy transfer to lungs and pulmonary hypertension behavior during venous-venous extracorporeal membrane oxygenation support: a mathematical modeling approach

Objective To describe (1) the energy transfer from the ventilator to the lungs, (2) the match between venous-venous extracorporeal membrane oxygenation (ECMO) oxygen transfer and patient oxygen consumption (VO2), (3) carbon dioxide removal with ECMO, and (4) the potential effect of systemic venous oxygenation on pulmonary artery pressure. Methods Mathematical modeling approach with hypothetical scenarios using computer simulation. Results The transition from protective ventilation to ultraprotective ventilation in a patient with severe acute respiratory distress syndrome and a static respiratory compliance of 20mL/cm H2O reduced the energy transfer from the ventilator to the lungs from 35.3 to 2.6 joules/minute. A hypothetical patient, hyperdynamic and slightly anemic with VO2 = 200mL/minute, can reach an arterial oxygen saturation of 80%, while maintaining the match between the oxygen transfer by ECMO and the VO2 of the patient. Carbon dioxide is easily removed, and normal PaCO2 is easily reached. Venous blood oxygenation through the ECMO circuit may drive the PO2 stimulus of pulmonary hypoxic vasoconstriction to normal values. Conclusion Ultraprotective ventilation largely reduces the energy transfer from the ventilator to the lungs. Severe hypoxemia on venous-venous-ECMO support may occur despite the matching between the oxygen transfer by ECMO and the VO2 of the patient. The normal range of PaCO2 is easy to reach. Venous-venous-ECMO support potentially relieves hypoxic pulmonary vasoconstriction.
Oxidative denitrification of N ω-hydroxyL-arginine by the superoxide radical anion

The superoxide radical anion (O # −d) produced during the catalytic activity of nitric oxide synthase (NOS) and cytochrome P-450 has been implicated in the oxidative denitrification of hydroxyguanidines ("C ̄NOH). The reactivity of the radiolytically generated O # −d radical with N-hydroxy--arginine (NHA) is pH dependent and appears to parallel the prototropic equilibrium of the hydroxyguanidino group ("C ̄NOHY"C ̄NO−­H+ ; pK ̄ 8). The N-hydroxyguanidino group is more reactive towards O # −d when deprotonated but exhibits negligible reactivity when protonated. Based on a model, the rate constant for the
Intrinsic electron trapping in amorphous oxide

We demonstrate that electron trapping at intrinsic precursor sites is endemic in non-glass-forming amorphous oxide films. The energy distributions of trapped electron states in ultra-pure prototype amorphous (a)-HfO2 insulator obtained from exhaustive photo-depopulation experiments demonstrate electron states in the energy range of 2–3 eV below the oxide conduction band. These energy distributions are compared to the results of density functional calculations of a-HfO2 models of realistic density. The experimental results can be explained by the presence of intrinsic charge trapping sites formed by under-coordinated Hf cations and elongated Hf–O bonds in a-HfO2. These charge trapping states can capture up to two electrons, forming polarons and bi-polarons. The corresponding trapping sites are different from the dangling-bond type defects responsible for trapping in glass-forming oxides, such as SiO2, in that the traps are formed without bonds being broken. Furthermore, introduction of hydrogen causes formation of somewhat energetically deeper electron traps when a proton is immobilized next to the trapped electron bi-polaron. The proposed novel mechanism of intrinsic charge trapping in a-HfO2 represents a new paradigm for charge trapping in a broad class of non-glass-forming amorphous insulators.
IMAGING STUDY: Prefrontal cortex morphometry in abstinent adolescent marijuana users: subtle gender effects

Adult human studies suggest frontal dysfunction associated with chronic marijuana (MJ) use, but due to continued neuromaturation, adult studies may not generalize to adolescents. This study characterized prefrontal cortex (PFC) morphometry in chronic MJ‐using adolescents following 1 month of monitored abstinence. Data were collected from MJ users (n = 16) and controls (n = 16) aged 16–18. Extensive exclusionary criteria included co‐morbid psychiatric and neurologic disorders. Substance use and anatomical measures were collected after 28 days of monitored abstinence. PFC volumes were ascertained from manual tracing by reliable raters on high‐resolution magnetic resonance images. After controlling for lifetime alcohol use, gender and intracranial volume, MJ users did not differ from controls in PFC volume. However, marginal group‐by‐gender interactions were observed (P < 0.09): female MJ users demonstrated comparatively larger PFC volumes while male MJ users had smaller volumes compared with same‐gender controls. Further, group status and total PFC volume interacted in predicting executive functioning (P < 0.05). Among MJ users, smaller PFC total volume was associated with better executive functioning while the opposite pattern was seen among the controls. These preliminary results indicate that gender may moderate the relationship between MJ use and PFC morphometry. Given the relationship between larger PFC total volumes and poorer executive functioning among MJ users, female MJ users may be at increased risk for neurocognitive consequences. Future research will measure PFC gray and white matter separately and follow boys and girls over adolescence to examine the influence of MJ use on neurodevelopment.
Are Your Classes Well-Encapsulated? Encapsulation Analysis for Java

Encapsulation is one of the basic characteristics of object-oriented programming. However, the access modifiers provided by common object-oriented languages do not help much because they only encapsulate the member references rather than the objects pointed to by them. Bad encapsulation makes object-oriented programs difficult to understand and reason about, thus concealing potential software vulnerabilities. We present in this paper the encapsulation analysis technique, which is an expression-based dataflow analysis, to statically compute the runtime memory layouts of object-oriented programs. The analysis results can help developers to master an intuitive comprehension on the code quality regarding encapsulation of classes. The results of experiments on various open-source Java projects and libraries show that our approach is both effective (25.76% of the classes are reported as not fully encapsulated) and efficient (2.15 KLOC/s and 27.35 classes/s) in finding potential encapsulation problems. We also give common guidance on how to achieve better encapsulation for object-oriented programs.
Modern Problems Require Modern Solutions: Hybrid Concepts for Industrial Intrusion Detection

The concept of Industry 4.0 brings a disruption into the processing industry. It is characterised by a high degree of intercommunication, embedded computation, resulting in a decentralised and distributed handling of data. Additionally, cloud-storage and Software-as-a-Service (SaaS) approaches enhance a centralised storage and handling of data. This often takes place in third-party networks. Furthermore, Industry 4.0 is driven by novel business cases. Lot sizes of one, customer individual production, observation of process state and progress in real-time and remote maintenance, just to name a few. All of these new business cases make use of the novel technologies. However, cyber security has not been an issue in industry. Industrial networks have been considered physically separated from public networks. Additionally, the high level of uniqueness of any industrial network was said to prevent attackers from exploiting flaws. Those assumptions are inherently broken by the concept of Industry 4.0. As a result, an abundance of attack vectors is created. In the past, attackers have used those attack vectors in spectacular fashions. Especially Small and Mediumsized Enterprises (SMEs) in Germany struggle to adapt to these challenges. Reasons are the cost required for technical solutions and security professionals. In order to enable SMEs to cope with the growing threat in the cyberspace, the research project IUNO Insec aims at providing and improving security solutions that can be used without specialised security knowledge. The project IUNO Insec is briefly introduced in this work. Furthermore, contributions in the field of intrusion detection, especially machine learning-based solutions, for industrial environments provided by the authors are presented and set into context.
Synthetic defocus and look-ahead autofocus for casual videography

In cinema, large camera lenses create beautiful shallow depth of field (DOF), but make focusing difficult and expensive. Accurate cinema focus usually relies on a script and a person to control focus in realtime. Casual videographers often crave cinematic focus, but fail to achieve it. We either sacrifice shallow DOF, as in smartphone videos; or we struggle to deliver accurate focus, as in videos from larger cameras. This paper is about a new approach in the pursuit of cinematic focus for casual videography. We present a system that synthetically renders refocusable video from a deep DOF video shot with a smartphone, and analyzes future video frames to deliver context-aware autofocus for the current frame. To create refocusable video, we extend recent machine learning methods designed for still photography, contributing a new dataset for machine training, a rendering model better suited to cinema focus, and a filtering solution for temporal coherence. To choose focus accurately for each frame, we demonstrate autofocus that looks at upcoming video frames and applies AI-assist modules such as motion, face, audio and saliency detection. We also show that autofocus benefits from machine learning and a large-scale video dataset with focus annotation, where we use our RVR-LAAF GUI to create this sizable dataset efficiently. We deliver, for example, a shallow DOF video where the autofocus transitions onto each person before she begins to speak. This is impossible for conventional camera autofocus because it would require seeing into the future.
Model-Based Occupant Tracking Using Slab-Vibration Measurements

Sensor-based occupant tracking has the potential to enhance knowledge of the utilization of buildings. Occupancy-tracking strategies using footstep-induced floor vibrations may be beneficial for thermal-load prediction, security enhancement and care-giving without undermining privacy. Current floor-vibration-based occupant-tracking methodologies are based on data-driven techniques that do not include a physics-based model of the structural behavior of the floor slab. These techniques suffer from ambiguous interpretations when signals are affected by complex configurations of structural and non-structural elements such as beams and walls. Using a physics-based model for data-interpretation enables deployment of sparse number of sensors in contexts of non-uniform structural configurations. In this paper, an application of physics-based data interpretation using error-domain model falsification (EDMF) is presented to track an occupant within an office environment through footstep-induced floor vibrations. EDMF is a population-based approach that incorporates various sources of uncertainty, including bias, arising from measurements and modeling. EDMF involves the rejection of simulated model responses that contradict footstep-induced floor vibration measurements. Thus, EDMF provides a set of candidate locations from an initial population of possible occupant locations. A sequential analysis that accommodates information from previous footsteps is then used to enhance candidate locations and identify trajectories among candidates. In this way, incorporating structural behavior in interpreting vibration measurements induced by occupant footsteps has the potential to identify accurately the trajectory of an occupant in buildings with complex configurations, thereby providing tracking information without undermining privacy.
Relevance of Autophagy Induction by Gastrointestinal Hormones: Focus on the Incretin-Based Drug Target and Glucagon

The biology of autophagy in health and disease conditions has been intensively analyzed for decades. Several potential interventions can induce autophagy in preclinical research; however, none of these interventions are ready for translation to clinical practice yet. The topic of the current review is the molecular regulation of autophagy by glucagon, glucagon-like peptide (GLP)-1 and the GLP-1-degrading enzyme dipeptidyl peptidase-4 (DPP-4). Glucagon is a well-known polypeptide that induces autophagy. In contrast, GLP-1 has been shown to inhibit glucagon secretion; GLP-1 also has been related to the induction of autophagy. DPP-4 inhibitors can induce autophagy in a GLP-1–dependent manner, but other diverse effects could be relevant. Here, we analyze the distinct molecular regulation of autophagy by glucagon, GLP-1, and DPP-4 inhibitors. Additionally, the potential contribution to autophagy by glucagon and GLP-1 after bariatric surgery is discussed.
A Study on impacts of corporate internationalization speed on performance—Analyses on the listed Chinese manufacturers 2006–2010

With the analysis perspective of “time compression dis-economies” this paper uses panel data of listed Chinese manufacturing companies to empirically test the impact of internationalization speed upon corporate performance and the regulatory functions of governmental involvement and foreign capital participation to the relationship between the two ends. The empirical results show a U-shape curve between internationalization speed and corporate performance, marked negative regulatory function of governmental involvement to the relationship between the two, and no significant regulatory impact of foreign capital upon corporate performance. Corporate size and corporate age have significantly positive impacts on corporate internationalized performance. Based on the empirical findings, this paper argues that Chinese enterprises should attach more importance to the improvement of their international absorptive capacity and constantly accumulate international experience. They can become internationalized faster only when they cross the risk threshold.
Beyond Light: Insights Into the Role of Constitutively Photomorphogenic1 in Plant Hormonal Signaling

Light is an important environmental factor with profound effects in plant growth and development. Constitutively photomorphogenic1 (COP1) is a vital component of the light signaling pathway as a negative regulator of photomorphogenesis. Although the role of COP1 in light signaling has been firmly established for some time, recent studies have proven that COP1 is also a crucial part of multiple plant hormonal regulatory pathways. In this article, we review the available evidence involving COP1 in hormone signaling, its molecular mechanisms, and its contribution to the complicated regulatory network linking light and plant hormone signaling.
Functional Involvement of Interferon-Inducible Transmembrane Proteins in Antiviral Immunity

Interferons (IFNs) play crucial roles in host defense against viral infections by inducing the expression of numerous IFN-stimulated genes (ISGs) that can activate host antiviral immunity. Interferon-inducible transmembrane proteins (IFITMs), a family of small transmembrane proteins, are critical ISG products. Compelling evidence has implicated that IFITMs can establish an innate immune state to eliminate pathogens efficiently. IFITM proteins can impede broad-spectrum viral infection through various mechanisms. It is generally believed that IFITMs can block the viral entry by suppressing viral membrane fusion. However, some findings indicated that IFITMs might also inhibit viral gene expression and viral protein synthesis and thereby impair viral replication. IFITMs may incorporate into virions during viral assembly and thus reduce the infectivity of nascent virions. The precise inhibitory mechanism of IFITMs on viral infection and replication still requires further exploration. In this review, we highlight the recent findings regarding critical roles of IFITMs in host-virus interaction. We also discuss the molecular mechanisms underlying their functions in antiviral responses.
The Advantage of Low-Delta Electroencephalogram Phase Feature for Reconstructing the Center-Out Reaching Hand Movements

It is an emerging frontier of research on the use of neural signals for prosthesis control, in order to restore lost function to amputees and patients after spinal cord injury. Compared to the invasive neural signal based brain-machine interface (BMI), a non-invasive alternative, i.e., the electroencephalogram (EEG)-based BMI would be more widely accepted by the patients above. Ideally, a real-time continuous neuroprosthestic control is required for practical applications. However, conventional EEG-based BMIs mainly deal with the discrete brain activity classification. Until recently, the literature has reported several attempts for achieving the real-time continuous control by reconstructing the continuous movement parameters (e.g., speed, position, etc.) from the EEG recordings, and the low-frequency band EEG is consistently reported to encode the continuous motor control information. Previous studies with executed movement tasks have extensively relied on the amplitude representation of such slow oscillations of EEG signals for building models to decode kinematic parameters. Inspired by the recent successes of instantaneous phase of low-frequency invasive brain signals in the motor control and sensory processing domains, this study examines the extension of such a slow-oscillation phase representation to the reconstructing two-dimensional hand movements, with the non-invasive EEG signals for the first time. The data for analysis are collected on five healthy subjects performing 2D hand center-out reaching along four directions in two sessions. On representative channels over the cortices encoding the execution information of reaching movements, we show that the low-delta EEG phase representation is characterized by higher signal-to-noise ratio and stronger modulation by the movement tasks, compared to the low-delta EEG amplitude representation. Furthermore, we have tested the low-delta EEG phase representation with two commonly used linear decoding models. The results demonstrate that the low-delta EEG phase based decoders lead to superior performance for 2D executed movement reconstruction to its amplitude based counterparts, as well as the other-frequency band amplitude and power based features. Thus, our study contributes to improve the movement reconstruction from EEG by introducing a new feature set based on the low-delta EEG phase patterns, and demonstrates its potential for continuous fine motion control of neuroprostheses.