Miracle-dz/UniFAR-FTUs huggingface dataset:
Breathing as an Input Modality in a Gameful Breathing Training App (Breeze 2): Development and Evaluation Study

Background Slow-paced breathing training can have positive effects on physiological and psychological well-being. Unfortunately, use statistics indicate that adherence to breathing training apps is low. Recent work suggests that gameful breathing training may help overcome this challenge. Objective This study aimed to introduce and evaluate the gameful breathing training app Breeze 2 and its novel real-time breathing detection algorithm that enables the interactive components of the app. Methods We developed the breathing detection algorithm by using deep transfer learning to detect inhalation, exhalation, and nonbreathing sounds (including silence). An additional heuristic prolongs detected exhalations to stabilize the algorithm’s predictions. We evaluated Breeze 2 with 30 participants (women: n=14, 47%; age: mean 29.77, SD 7.33 years). Participants performed breathing training with Breeze 2 in 2 sessions with and without headphones. They answered questions regarding user engagement (User Engagement Scale Short Form [UES-SF]), perceived effectiveness (PE), perceived relaxation effectiveness, and perceived breathing detection accuracy. We used Wilcoxon signed-rank tests to compare the UES-SF, PE, and perceived relaxation effectiveness scores with neutral scores. Furthermore, we correlated perceived breathing detection accuracy with actual multi-class balanced accuracy to determine whether participants could perceive the actual breathing detection performance. We also conducted a repeated-measure ANOVA to investigate breathing detection differences in balanced accuracy with and without the heuristic and when classifying data captured from headphones and smartphone microphones. The analysis controlled for potential between-subject effects of the participants’ sex. Results Our results show scores that were significantly higher than neutral scores for the UES-SF (W=459; P<.001), PE (W=465; P<.001), and perceived relaxation effectiveness (W=358; P<.001). Perceived breathing detection accuracy correlated significantly with the actual multi-class balanced accuracy (r=0.51; P<.001). Furthermore, we found that the heuristic significantly improved the breathing detection balanced accuracy (F1,25=6.23; P=.02) and that detection performed better on data captured from smartphone microphones than than on data from headphones (F1,25=17.61; P<.001). We did not observe any significant between-subject effects of sex. Breathing detection without the heuristic reached a multi-class balanced accuracy of 74% on the collected audio recordings. Conclusions Most participants (28/30, 93%) perceived Breeze 2 as engaging and effective. Furthermore, breathing detection worked well for most participants, as indicated by the perceived detection accuracy and actual detection accuracy. In future work, we aim to use the collected breathing sounds to improve breathing detection with regard to its stability and performance. We also plan to use Breeze 2 as an intervention tool in various studies targeting the prevention and management of noncommunicable diseases.
Bayesian information fusion for probabilistic health index of power transformer

This study proposes a Bayesian information fusion approach for determining the probabilistic health index of power transformer. The proposed approach integrates a variety of data obtained from transformer measurements, maintenance records, and failure statistics. By making use of these data, an inference model is constructed using Bayesian belief network (BBN). In the inference model, the significance of each individual measurement on the corresponding component in the BBN is decided by both principal component analysis and expert's experience, and subsequently quantified with a score-probability transform. Finally, the inference model is used to derive a probabilistic health index. Case studies are provided to demonstrate the applicability of the proposed approach for evaluating transformer condition.
Adverse Childhood Experiences and Their Relationship with Poor Sexual Health Outcomes: Results from Four Cross-Sectional Surveys

Improving understanding of risk factors for risky sexual behaviour is fundamental to achieve better population sexual health. Exposure to adverse childhood experiences (ACEs) can increase the risk of poor sexual health outcomes, but most research is US-based. This study explored associations between ACEs and poor sexual health outcomes in the UK. Data from four cross-sectional ACE surveys with adult general populations in different regions of the UK from 2013–2015 (n = 12,788) were analysed. Data included participants’ demographics, ACE exposure, and four sexual health outcomes: having early sex (<16 years), having an accidental teenage pregnancy, becoming a teenage parent, or having a lifetime diagnosis of a sexually transmitted infection. ACE count was a consistent and significant predictor of all four sexual health outcomes for both males and females, with odds of these outcomes between three and seven times higher for those with 4+ ACEs compared to those with no ACEs. Increased risks of some, but not all, sexual health outcomes were also found with higher residential deprivation, younger age, being of white ethnicity, and being born to a teenage mother. Findings highlight the need for effective interventions to prevent and ameliorate the lifelong effects of ACEs. Trauma-informed relationships and sex education, sexual health services, and antenatal/postnatal services, particularly for teenagers and young parents, could provide opportunities to prevent ACEs and support those affected. Ensuring that those living in deprived areas have access to services and that barriers to uptake are addressed is also key.
Psychopathological analysis of several functional disorders and neurovegetative dysfunctions

The aim of the article is to present several conceptions on the functional disorders and neurovegetative (au-tonomic) dysfunctions. It was indicated that it is important to distinguish between these two concepts and to preserve this division in the newer classifications. The following syndromes were given as examples: neurocirculatory asthenia, Raynaud disease and bodily distress syndrome. The current reflections were based mostly on foreign literature. The cited works largely focused on the issue of clinical psychosomatics, which may be a potential area of interest in neuropsychiatry. The research carried out so far indicates that the concept of organ neuroses should be removed from the medical literature and rightly replaced with the concept of neurovegetative (autonomic) dysfunctions. Likewise, psychosomatic disorders begin to be understood as functional disorders. However, it becomes questionable to view these diseases as only one diagnostic unit, which is the bodily distress syndrome. They may have different health consequences and complications. The nature of functional disorders and neurovegetative dysfunctions is still not well known. Several theories have arisen to explain them, but in general assessment they do not seem sufficient to use them en masse in clinical practice. Especially the development of neurovegetative dysfunctions should be constantly monitored, because, through the neurasthenic period, they can transform into severe organic disease.
Automatic Flythrough Authoring in VR

The presentation of architectural models in virtual reality (VR) enables architects to evaluate their designs and present them to stakeholders, improving fidelity of architectural communication in architectural design. Virtual walkthroughs are a powerful tool to convey architectural concepts and unique features of the planned building. However, creating walkthroughs is a rather tedious process involving manual setting of keypoints at points of interest and in between, which are then interpolated to create the trajectory. This often results in awkward camera poses, sharp turns, intersection with geometry and clipping problems, all of which must be resolved by tweaking or adding new keypoints. Furthermore, the process requires constantly switching between an inside view, for local refinements, and an outside overview, for more global adjustments. To address this challenge, we present an interactive design tool for walkthroughs in VR. Our tool automatically provides a set of ideal keypoints, based on a customizable set of objectives, and instantly generates a complete and smooth trajectory that passes through them. It allows the user to tweak positions and update the walkthrough in real time, in VR. In addition, it allows the designer to have both an inside view and an overview simultaneously.
Cyber attack awareness and prevention in network security

This article aims to provide an overview of cyber attack awareness and prevention in network security. This article discussed the different types of cyber attacks, current trends of cyber attacks, how to prevent cyber attacks and uum students' awareness of cyber attacks. First, we will go over the different types of cyber attack, current trend, impact of cyber attack and the prevention. The approach entailed comparing and observing the outcomes of 13 different papers. The survey's findings would demonstrate the results obtained after analyzing the data collection which are the questionnaire filled out by respondents after watching the cyber attack awareness video to improve awareness of students through the cyber attack. Depending on the outcome of this survey, we will have a better understanding of current students' knowledge and awareness of cyber attacks, allowing us to improve students' understanding of cyber threats and the necessity of cyber security.
Characterizing and Improving Bug-Finders with Synthetic Bugs

Automated bug-finding tools such as KLEE have achieved mainstream success over the last decade, and have proved capable of finding deep bugs even in programs that have received significant manual testing. Some recent works have demonstrated techniques for finding bugs in these bug-finding tools themselves; however, it remains unclear whether these correctness issues have any practical impact on their ability to uncover serious bugs. In this paper, we study this issue by conducting experiments with KLEE 1.4 and 2.2 on several corpora of memory safety bugs. Using automated bug injection, we can automatically find false negatives (i.e., bugs missed by KLEE); moreover, because the bugs we inject come with triggering inputs, we can then use concolic execution to tell which bugs were missed due path explosion and which are caused by soundness issues in KLEE. Our evaluation uncovers several sources of unsoundness, including a limitation in how KLEE detects memory errors, mismatches in the modeling of the C standard library, lack of support for floating point and C++, and issues with calls to external functions. Our results suggest that bug injection and other synthetic corpora can help highlight implementation issues in current tools and illuminate directions for future research in automated software engineering.
Quantitative trait loci mapping reveals an oligogenic architecture of a rapidly adapting trait during the European invasion of common ragweed

Biological invasions offer a unique opportunity to investigate evolution over contemporary timescales. Rapid adaptation to local climates during range expansion can be a major determinant of invasion success, yet fundamental questions remain about its genetic basis. This study sought to investigate the genetic basis of climate adaptation in invasive common ragweed (Ambrosia artemisiifolia). Flowering time adaptation is key to this annual species' invasion success, so much so that it has evolved repeated latitudinal clines in size and phenology across its native and introduced ranges despite high gene flow among populations. Here, we produced a high‐density linkage map (4493 SNPs) and paired this with phenotypic data from an F2 mapping population (n = 336) to identify one major and two minor quantitative trait loci (QTL) underlying flowering time and height differentiation in this species. Within each QTL interval, several candidate flowering time genes were also identified. Notably, the major flowering time QTL detected in this study was found to overlap with a previously identified haploblock (putative inversion). Multiple genetic maps of this region identified evidence of suppressed recombination in specific genotypes, consistent with inversions. These discoveries support the expectation that a concentrated genetic architecture with fewer, larger, and more tightly linked alleles should underlie rapid local adaptation during invasion, particularly when divergently adapting populations experience high levels of gene flow.
Preliminary Study on Phytochemical Constituents and Biological Activities of Essential Oil from Myriactis nepalensis Less.

In response to the need for novel therapeutic strategies to combat the development of microbial resistance, plant essential oils may represent a promising alternative source. This study set out to characterize the chemical composition and assess the antibacterial potential of Myriactis nepalensis Less. essential oil (MNEO). Essential oil isolated from M. nepalensis by hydrodistillation was analyzed using a GC–MS technique. The antibacterial properties of MNEO alone and combined with antibiotics (chloramphenicol and streptomycin) were tested via the disc diffusion, microbroth dilution, and checkerboard methods. MNEO was represented by oxygenated sesquiterpenes (60.3%) and sesquiterpene hydrocarbons (28.6%), with caryophyllene oxide, spathulenol, humulene epoxide II, β-elemene, neointermedeol, and β-caryophyllene as the main compounds. MNEO exhibited a strong antibacterial effect against Gram-positive bacteria, with MIC and MBC values of 0.039 mg/mL and 0.039–0.156 mg/mL, respectively, and synergistic effects were observed in both combinations with chloramphenicol and streptomycin. Furthermore, the antibiofilm and cytotoxic activities of MNEO were also evaluated. The crystal violet assay was used for quantification of Staphylococcus aureus biofilm formation, and an MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide) assay was conducted to determine cell viability. The results revealed MNEO could dose-dependently inhibit Staphylococcus aureus biofilm formation and possessed potential cytotoxic on both normal and cancer cells (IC50 values from 13.13 ± 1.90 to 35.22 ± 8.36 μg/mL). Overall, the results indicate that MNEO may have promising applications in the field of bacterial infections.
Mass timber – the emergence of a modern construction material

Abstract In the move towards sustainable construction, timber and wood-based products are becoming increasingly important structural materials. The introduction of mass timber products with excellent load carrying characteristics allows timber to be used in larger, more complex structures. Cross-laminated timber (CLT) panel products have developed to the stage where they can be considered as economic and more sustainable alternatives to traditional materials. In this paper, the characteristics and design of CLT structures are described. Recent developments in mid- and high-rise CLT construction are reviewed and future opportunities identified. Current and future research needs are highlighted.
Fundamental signaling pathways for glioblastoma drug resistance and developing robust organoid models for drug discovery

This article presents a review of the current literature on the molecular mechanisms of treatment resistance in glioblastoma. As mounting research continues to explore novel methods of treating glioblastoma, from using organoid models for drug screening to developing novel cellular therapies, it is critical to understand the fundamental molecular landscape that makes glioblastoma difficult to treat. This review explores the means of chemoresistance to the conventional chemotherapy temozolomide. Consideration of DNA repair pathways, p53-mediated apoptosis and autophagy, convergent proliferation pathways, and epigenetic mechanisms demonstrate avenues for the development of sophisticated drug targets and combination treatments. Ultimately, this article highlights each of these mechanisms and presents referential material for future endeavors in organoid-based drug screening.
Robotic 3D Printing of Mineral Foam for a Lightweight Composite Concrete Slab

This paper presents the design and fabrication of a lightweight composite concrete slab prototype using 3D printing (3DP) of mineral foams. Conventionally, concrete slabs are standardized monolithic elements that are responsible for a large share of used materials and dead weight in concrete framed buildings. Optimized slab designs require less material at the expense of increasing the formwork complexity, required labour, and costs. To address these challenges, foam 3D printing (F3DP) can be used in construction as demonstrated in previous studies for lightweight facade elements. The work in this paper expands this research and uses F3DP to fabricate the freeform stay-in-place formwork components for a material-efficient lightweight ribbed concrete slab with a footprint of 2 x 1.3 m. For this advancement in scale, the robotic fabrication and material processing setup is refined and computational design strategies for the generation of advanced toolpaths developed. The presented composite of hardened mineral foam and fibre-reinforced ultra-high-performance concrete shows how custom geometries can be efficiently fabricated for geometrically complex formwork. The prototype demonstrates that optimized slabs could save up to 72% of total concrete volume and 70% weight. The discussion of results and challenges in this study provides a valuable outlook on the viability of this novel fabrication technique to foster a sustainable and resourceful future construction culture.
Organic Photoelectric Materials and Organic Photoelectric Devices Based on Smart Image Sensors

With the development of the times in recent years, people’s requirements for vision are no longer limited to the original foundation. As the core of research in this field, organic electroluminescence has paid great attention to the research points in the application of organic optoelectronic materials and devices in the world. From the relevant scientific research results in recent years, for example, organic light-emitting diodes can be used in flat-panel displays and solid-state lighting, organic photovoltaic cells can be used as a clean and renewable energy source to effectively alleviate the current energy needs of society, and organic storage, sensors, and so on show great promise for application. It can be seen that the research of organic optoelectronic materials and their devices will be the core hot spot of future new energy research. In the past, traditional organic optoelectronic materials are updated through the regulation strategy of covalent modification of the molecular structure. In recent years, new effective methods have been obtained to regulate the properties of excited states through physical stimulation (such as mechanical force, temperature, electric field, and magnetic field). The type of research experiment in this paper is based on the current hot smart image sensor, with the addition of organic complexes of mononuclear metal platinum and iridium metal and the organic optoelectronic device in the form of host and guest doping. The experimental results show that using PVK without energy transfer, polyvinyl carbazole (PVK) had been widely used as blue luminescent material and hole transport layer in electroluminescent device research. Simple mononuclear platinum and iridium metal complexes cannot obtain white light. For OPV devices, by selecting the correct solvent to control the bulk heterojunction, it exhibits better photovoltaic performance. Solvents play an important role in phase separation. In organic solar cells (OPV) consisting of an electron donor (D) and an acceptor (A), optimizing the D-A interface produces efficient charge separation, effectively separating excitons at the D-A interface and forming continuous electron and hole transport channels, and effective charge transport between electrodes plays a positive role.
Diagnostic Values of Blood Urea Nitrogen (BUN), Creatinine (Cr), and the Ratio of BUN to Cr for Distinguishing Heart Failure from Asthma and Chronic Obstructive Pulmonary Disease

Background In clinical practise, it can be challenging to tell the difference between asthma and chronic obstructive pulmonary disease (COPD) and heart failure (HF), which share comparable dyspnea symptoms. We aimed to examine whether renal function indexes blood urea nitrogen (BUN), creatinine (Cr), and the ratio of BUN to Cr (BUN/Cr) can be used to distinguish HF from asthma and COPD. Methods A total of 170 patients were admitted for dyspnea symptoms in this retrospective study. There are 69 patients with HF (HF group), 50 patients with asthma (asthma group), and 51 patients diagnosed with COPD (COPD group). The levels of BUN, Cr, and the ratio of BUN/Cr in the three groups were compared. Student's t-test or the one-way analysis of variance (ANOVA) test was used to compare means. Using the area under the receiver operating characteristic curve, model differentiation was evaluated (AUC). Z-test comparisons of AUC were carried out. Results Compared with the asthma/COPD group (asthma group + COPD group) or the COPD group, the levels of BUN and Cr were raised in the HF group, while there was no significant difference of the BUN/Cr ratio. Compared with those in the asthma group, the levels of BUN, Cr, and BUN/Cr ratio were significantly increased in the HF group (all p < 0.05), whereas no significant differences of BUN, Cr, and BUN/Cr ratio were found between asthma and COPD. The AUC in distinguishing HF from asthma/COPD were 0.736 and 0.751 for BUN and Cr, respectively, and no significant difference was observed between BUN and Cr. The cutoff values (specificity, sensitivity, and Youden index) in distinguishing between HF and asthma/COPD were 20.45 mg/dL (79.21%, 56.52%, and 0.357) for BUN and 0.782 mg/dL (72.28%, 68.12%, and 0.404) for Cr, respectively. Conclusions BUN and Cr showed accurate and reliable diagnostic values which could be potential biomarkers for differentiating HF from asthma and/or COPD.
Design of an Intuitive Master for Improving Teleoperation Task Performance Using the Functional Separation of Actuators: Movement and Gravity Compensation

Teleoperation, in which humans and robots work together to improve work performance, is growing explosively. However, the work performance of teleoperation is not yet excellent. Master–slave systems with different kinematics and workspaces need space-transformation control techniques. These techniques cause psychological fatigue to an operator with poor manipulation skills. In this study, we propose an intuitive master design that focuses on fatigue. Large workspaces reduce mental fatigue; however, they lead to physical fatigue problems. To solve this problem, we reflect the role of actuators in the design, through functional separation using movement and gravity compensation. This study proposes the design and prototype fabrication of an intuitive master K-handler to improve remote-work performance. The K-handler features six degrees of freedom (DoF), an anthropomorphic structure, and a lightweight nature. It has a reach long enough to cover the workspace of the human arm to reduce mental fatigue. In addition, gravity compensation, which can reduce the operator’s physical fatigue during operation, is possible in all workspace areas.