Miracle-dz/UniFAR-FTUs huggingface dataset:
CareCam: Concept of a new tool for Corporate Health Management

Corporate health management is an important tool for preventing work-related absenteeism, increasing overall employee satisfaction and reducing the costs of absenteeism or presenteeism in the long term. Today, corporate health management is even more important because many employees work from home. Often, there is a lack of workspace or even a workplace that meets minimum occupational health and safety guidelines. Overwork, noise pollution, incorrect sitting posture and unstructured work breaks contribute negatively to the daily work routine, as does the general problem of separating work and leisure. Under these conditions, daily work is made even more difficult, which can lead to increased mental and physical stress. A concept for unobtrusive monitoring to increase long-term health, improve working conditions or at least to show the necessary adjustments to the new work situation can help to solve these problems. This paper presents a concept that shows how a simple webcam can be used to record essential vital signs during working hours, evaluate them using machine learning, and offer intervention recommendations based on these data to reduce psychological and physical stress. Work on continuous stress measurement and the challenges associated with it will be presented. This work serves as a starting point for the development of a camera-based tool for mental and physical stress measurement in the workplace. Our approach demonstrates that the required parameters can be captured using a simple webcam and that interventions can be used to achieve long-term reductions in work-related mental and physical stress, provided that the proposed interventions are followed. The prototypical implementation shows that such a solution can work well in the workplace, but that data protection and technical limitations must be considered in the future in order to establish camera-based methods in the toolbox of workplace health management.
Parental Involvement in Computer Science Education and Computing Attitudes and Behaviours in the Home: Model and Scale Development

This work is situated in research on Parental Involvement (PI) in Computer Science (CS) Education. While the importance of PI in children's education is well established, most parents have little experience in CS and struggle to facilitate the learning of a child in the area. If PI in CS Education is to happen, then we argue that parents need support and that understanding the current behaviours and attitudes toward CS in the family context is important to discerning the form that support should take. This article therefore describes the development of an instrument to identify factors relating to parental attitudes toward and motivation for PI in CS education. Relevant variables situated in the context of parental computing behaviours and attitudes in the home were identified using a literature review and expert focus group. These include computing usage, availability, confidence, and experience. To measure these variables, a survey instrument was developed and administered to a large sample of parents (n = 1228). Results of exploratory and confirmatory factor analysis confirm that the instrument measures five constructs, namely “Confidence,” measuring parental confidence levels with computing; “Attitude to PI”; “Motivation for PI”; and two types of “Usage”: Creation and Consumption. Results of Pearson correlation revealed significant positive relationships between confidence and both positive attitudes toward, and motivation for, PI, with linear regressions confirming that confidence was a significant predictor of both. Regression analysis also identified that creative usage was a predictor of positive attitudes to PI, and that programming experience was a predictor of attitude to, and motivation for, PI. These findings were further validated through triangulation with qualitative data from focus groups with the target population. We conclude that this understanding of the predictors of PI attitudes and motivation should inform the design of initiatives to address parental engagement in CS Education.
CO2 Meter: A do-it-yourself carbon dioxide measuring device for the classroom

In this paper we report on CO2 Meter, a do-it-yourself carbon dioxide measuring device for the classroom. Part of the current measures for dealing with the SARS-CoV-2 pandemic is proper ventilation in indoor settings. This is especially important in schools with students coming back to the classroom even with high incidents rates. Static ventilation patterns do not consider the individual situation for a particular class. Influencing factors like the type of activity, the physical structure or the room occupancy are not incorporated. Also, existing devices are rather expensive and often provide only limited information and only locally without any networking. This leaves the potential of analysing the situation across different settings untapped. Carbon dioxide level can be used as an indicator of air quality, in general, and of aerosol load in particular. Since, according to the latest findings, SARS-CoV-2 can be transmitted primarily in the form of aerosols, carbon dioxide may be used as a proxy for the risk of a virus infection. Hence, schools could improve the indoor air quality and potentially reduce the infection risk if they actually had measuring devices available in the classroom. Our device supports schools in ventilation and it allows for collecting data over the Internet to enable a detailed data analysis and model generation. First deployments in schools at different levels were received very positively. A pilot installation with a larger data collection and analysis is underway.
Detection of physical strain and fatigue in industrial environments using visual and non-visual sensors

sustAGE is an ongoing project, developing an Internet of Things ecosystem, including smartphones, smartwatches, localization and environmental sensors and cameras to support ageing workers in industrial environments while performing assembly tasks, such a car manufacturing factory. In this context, we briefly describe a non-obtrusive method for assessing the physical strain of workers using visual data and a method for detecting worker fatigue using heart rate data acquired by smartwatches. The results of both methods are utilized by the recommendation system developed in sustAGE to support preventive actions towards work-related musculo-skeletal disorders and fatigue and to promote occupational safety.
Towards a Conceptual Model of Digital Innovation Success

Although digital innovation ('DI') is a popular research field in these days, when it comes to innovation success, it has not yet been properly grounded in theory. Accordingly, there are prob-lems in identifying both generic and context-specific critical success factors (CSF) within the innovation process. Existing literature has focused mainly on the development of dynamic capabilities. We argue that to build digital innovation capabili-ties, an organization must first understand and support the ac-tions of those who are actively developing DI. To uncover spe-cific actions that constitute CSFs within every dimension of the digital innovation process, we follow a multiple case study de-sign with seven companies from different industries. Here, we build upon the 'digital innovation framework' which defines the process of creating DI across four dimensions (initiate, de-velop, implement, exploit). Based on these case studies, we build a conceptual model consisting of digital innovation actions, critical success factors and contingency factors. The proposed model serves as a starting point for future research, which should focus on a detailed quantitative investigation of the cause-effect relationships and the contingency factors to vali-date our propositions
Where Natural Protein Sequences Stand out From Randomness

Biological sequences are the product of natural selection, raising the expectation that they differ substantially from random sequences. We test this expectation by analyzing all fragments of a given length derived from either a natural dataset or different random models. For this, we compile all distances in sequence space between fragments within each dataset and compare the resulting distance distributions between sets. Even for 100mers, 95.4% of all distances between natural fragments are in accordance with those of a random model incorporating the natural residue composition. Hence, natural sequences are distributed almost randomly in global sequence space. When further accounting for the specific residue composition of domain-sized fragments, 99.2% of all distances between natural fragments can be modeled. Local residue composition, which might reflect biophysical constraints on protein structure, is thus the predominant feature characterizing distances between natural sequences globally, whereas homologous effects are only barely detectable.
Extreme hyperallometry of mammalian antibacterial defenses

Terrestrial mammals span 7 orders of magnitude in body size, ranging from the < 2 g pygmy shrew (Suncus etruscus) to the > 3900 kg African elephant (Loxodonta africana). Although body size has profound effects on the behavior, physiology, ecology, and evolution of animals, how body mass affects immune functions is unknown. Here, using data from >160 terrestrial species of mammals, we show that the size-scaling of antibacterial activity in serum exhibits extreme hyperallometry. Compared to small mammals, the serum of large mammals is remarkably inhospitable to bacteria. Such hypermetric scaling of immune defenses provides novel perspectives on the ecology of host-pathogen interactions, and on their co-evolutionary dynamics. These results also have implications for effectively modeling human immunity and for identifying reservoirs of zoonotic pathogens.
Cryptanalysis of An Encrypted Database in SIGMOD '14

Encrypted database is an innovative technology proposed to solve the data confidentiality issue in cloud-based DB systems. It allows a data owner to encrypt its database before uploading it to the service provider; and it allows the service provider to execute SQL queries over the encrypted data. Most of existing encrypted databases (e.g., CryptDB in SOSP '11) do not support data interoperability: unable to process complex queries that require piping the output of one operation to another. To the best of our knowledge, SDB (SIGMOD '14) is the only encrypted database that achieves data interoperability. Unfortunately, we found SDB is not secure! In this paper, we revisit the security of SDB and propose a ciphertext-only attack named co-prime attack. It successfully attacks the common operations supported by SDB, including addition, comparison, sum, equi-join and group-by. We evaluate our attack in three real-world benchmarks. For columns that support addition and comparison , we recover 84.9% -- 99.9% plaintexts. For columns that support sum, equi-join and group-by , we recover 100% plaintexts. Besides, we provide potential countermeasures that can prevent the attacks against sum, equi-join, group-by and addition. It is still an open problem to prevent the attack against comparison.
Interrelationship Between Obstructive Sleep Apnea Syndrome and Severe Asthma: From Endo-Phenotype to Clinical Aspects

Sleep-related breathing disorders (SBDs) are characterized by abnormal respiration during sleep. Obstructive sleep apnea (OSA), a common SBD increasingly recognized by physicians, is characterized by recurrent episodes of partial or complete closure of the upper airway resulting in disturbed breathing during sleep. OSA syndrome (OSAS) is associated with decreased patients' quality of life (QoL) and the presence of significant comorbidities, such as daytime sleepiness. Similarly to what seen for OSAS, the prevalence of asthma has been steadily rising in recent years. Interestingly, severe asthma (SA) patients are also affected by poor sleep quality—often attributed to nocturnal worsening of their asthma—and increased daytime sleepiness and snoring compared to the general population. The fact that such symptoms are also found in OSAS, and that these two conditions share common risk factors, such as obesity, rhinitis, and gastroesophageal reflux, has led many to postulate an association between these two conditions. Specifically, it has been proposed a bidirectional correlation between SA and OSAS, with a mutual negative effect in term of disease severity. According to this model, OSAS not only acts as an independent risk factor of asthma exacerbations, but its co-existence can also worsen asthma symptoms, and the same is true for asthma with respect to OSAS. In this comprehensive review, we summarize past and present studies on the interrelationship between OSAS and SA, from endo-phenotype to clinical aspects, highlighting possible implications for clinical practice and future research directions.
Symphony of Well-Being: Harmony Between Neural Variability and Self-Construal

Both neural activities and psychological processes vary over time. Individuals with interdependent self-construal tend to define themselves and adjust their behaviors to social contexts and others. The current research tested the hypothesis that the coordination between interdependent self-construal and neural variability could predict life satisfaction changes in university freshmen. We integrated resting-state functional magnetic resonance imaging scanning and self-construal assessment to estimate self-dependent neural variability (SDNV). In the whole-brain prediction, SDNV successfully predicted individuals’ life satisfaction changes over 2 years. Interdependent individuals with higher neural variability and independent individuals with lower neural variability became more satisfied with their lives. In the network-based prediction, the predictive effects were significant in the default mode, frontoparietal control, visual and salience networks. The important nodes that contributed to the predictive models were more related to psychological constructs associated with the social and self-oriented functions. The current research sheds light on the neural and psychological mechanisms of the subjective well-being of individuals from a dynamic perspective.
Effects of Matrix pH on Spontaneous Transient Depolarization and Reactive Oxygen Species Production in Mitochondria

Reactive oxygen species (ROS) oxidize surrounding molecules and thus impair their functions. Since mitochondria are a major source of ROS, suppression of ROS overproduction in the mitochondria is important for cells. Spontaneous transient depolarization of individual mitochondria is a physiological phenomenon widely observed from plants to mammals. Mitochondrial uncoupling can reduce ROS production; therefore, it is conceivable that transient depolarization could reduce ROS production. However, transient depolarization has been observed with increased ROS production. Therefore, the exact contribution of transient depolarization to ROS production has not been elucidated. In this study, we examined how the spontaneous transient depolarization occurring in individual mitochondria affected ROS production. When the matrix pH increased after the addition of malate or exposure of the isolated mitochondria to a high-pH buffer, transient depolarization was stimulated. Similar stimulation by an increased matrix pH was also observed in the mitochondria in intact H9c2 cells. Modifying the mitochondrial membrane potential and matrix pH by adding K+ in the presence of valinomycin, a K+ ionophore, clarified that an increase in the matrix pH is a major cause of ROS generation. When we added ADP in the presence of oligomycin to suppress the transient depolarization without decreasing the matrix pH, we observed the suppression of mitochondrial respiration, increased matrix pH, and enhanced ROS production. Based on these results, we propose a model where spontaneous transient depolarization occurs during increased proton influx through proton channels opened by increased matrix pH, leading to the suppression of ROS production. This study improves our understanding of mitochondrial behavior.
Randomized Cross Over Study Assessing the Efficacy of Non-invasive Stimulation of the Vagus Nerve in Patients With Axial Spondyloarthritis Resistant to Biotherapies: The ESNV-SPA Study Protocol

Axial spondyloarthritis (SpA), is a major cause of chronic pain and disability that profoundly alters the quality of life of patients. Nearly half of patients with SpA usually develop drug resistance. Non-pharmacological treatments targeting inflammation are an attractive alternative to drug administration. Vagus nerve stimulation (VNS), by promoting a cholinergic anti-inflammatory reflex holds promise for treating inflammatory disease. Inflammatory reflex signaling, which is enhanced by electrically stimulating the vagus nerve, significantly reduces cytokine production and attenuates disease severity in animal models of endotoxemia, sepsis, colitis, and other preclinical models of inflammatory diseases. It has been proposed that vagal efferent fibers release acetylcholine (Ach), which can interact with α7-subunit-containing nicotinic receptors expressed by tissue macrophages and other immune cells to rapidly inhibit the synthesis/release of pro-inflammatory cytokines such as TNFα, IL-1β, IL-6, and IL-18. External vagal nerve stimulation devices are now available that do not require surgery nor implantation to non-invasively stimulate the vagal nerve. This double-blind randomized cross-over clinical trial aims to study the change in SpA disease activity, according to Assessment in Ankylosing Spondylitis 20 (ASAS20) definition, after 12 weeks of non-invasive VNS treatment vs. non-specific dummy stimulation (control group). One hundred and twenty adult patients with drug resistant SpA, meeting the ASAS classification criteria, will be included in the study. Patients will be randomized into two parallel groups according to a cross over design: either active VNS for 12 weeks, then dummy stimulation for 12 weeks, or dummy stimulation for 12 weeks, then active VNS for 12 weeks. The two stimulation periods will be separated by a 4 weeks wash-out period. A transcutaneous auricular vagus nerve stimulator Tens Eco Plus SCHWA MEDICOTM France will be used in this study. The active VNS stimulation will be applied in the cymba conchae of the left ear upon the auricular branch of the vagus nerve, using low intensity (2–5 mA), once à week, during 1 h. Dummy stimulation will be performed under the same conditions and parameters as active VNS stimulation, but at an irrelevant anatomical site: the left ear lobule. This multicenter study was registered on ClinicalTrials.gov: NCT04286373.
Association Between Diabetic Retinopathy and Cognitive Impairment: A Systematic Review and Meta-Analysis

Diabetic retinopathy (DR) is one of the most common microvascular complications associated with diabetes mellitus. However, its correlation with another diabetes-related disorder, cognitive impairment, has not been well studied. This systematic review and meta-analysis aimed to explore the association between DR and cognitive impairment. MEDLINE (PubMed), the Cochrane Library, and EMBASE databases were searched for observational studies that reported an association between DR and cognitive impairment. Data from selected studies were extracted, and a meta-analysis was conducted using fixed-effects modeling. Fifteen observational studies were included in the systematic review, and 10 studies were included in the meta-analysis. The odds ratio of the association between DR and cognitive impairment was 2.24 (95% confidence interval [CI], 1.89–2.66; I2 = 0.8%). The hazard ratio of the association between DR and cognitive impairment was significant in four studies, ranging from 1.09–1.32. Minimal or mild DR was not significantly associated with cognitive impairment (odds ratio [OR], 2.04; 95% CI, 0.87–4.77). However, the association between proliferative DR and cognitive impairment (OR, 3.57; 95% CI, 1.79–7.12; I2 = 16.6%) was not stronger than the association between moderate or worse DR and cognitive impairment (OR, 4.26; 95% CI, 2.01–9.07; I2 = 0.0%). DR is associated with cognitive impairment, and screening for DR will be helpful for the early identification of individuals with cognitive impairment. Further studies are needed to confirm the association between proliferative DR and cognitive impairment.
Causal Evidence for Induction of Pessimistic Decision-Making in Primates by the Network of Frontal Cortex and Striosomes

Clinical studies have shown that patients with anxiety disorders exhibited coactivation of limbic cortices and basal ganglia, which together form a large-scale brain network. The mechanisms by which such a large-scale network could induce or modulate anxiety-like states are largely unknown. This article reviews our experimental program in macaques demonstrating a causal involvement of local striatal and frontal cortical sites in inducing pessimistic decision-making that underlies anxiety. Where relevant, we related these findings to the wider literature. To identify such sites, we have made a series of methodologic advances, including the combination of causal evidence for behavioral modification of pessimistic decisions with viral tracing methods. Critically, we introduced a version of the classic approach-avoidance (Ap-Av) conflict task, modified for use in non-human primates. We performed microstimulation of limbic-related cortical regions and the striatum, focusing on the pregenual anterior cingulate cortex (pACC), the caudal orbitofrontal cortex (cOFC), and the caudate nucleus (CN). Microstimulation of localized sites within these regions induced pessimistic decision-making by the monkeys, supporting the idea that the focal activation of these regions could induce an anxiety-like state, which subsequently influences decision-making. We further performed combined microstimulation and tract-tracing experiments by injecting anterograde viral tracers into focal regions, at which microstimulation induced increased avoidance. We found that effective stimulation sites in both pACC and cOFC zones projected preferentially to striosomes in the anterior striatum. Experiments in rodents have shown that the striosomes in the anterior striatum project directly to the dopamine-containing cells in the substantia nigra, and we have found evidence for a functional connection between striosomes and the lateral habenular region in which responses to reward are inhibitory. We present here further evidence for network interactions: we show that the pACC and cOFC project to common structures, including not only the anterior parts of the striosome compartment but also the tail of the CN, the subgenual ACC, the amygdala, and the thalamus. Together, our findings suggest that networks having pACC and cOFC as nodes share similar features in their connectivity patterns. We here hypothesize, based on these results, that the brain sites related to pessimistic judgment are mediated by a large-scale brain network that regulates dopaminergic functions and includes striosomes and striosome-projecting cortical regions.