A Hint-Based Random Access Protocol for mMTC in 5G Mobile Network

With the increasing popularity of machine-type communication (MTC) devices, several new challenges are encountered by the legacy long term evolution (LTE) system. One critical issue is that a massive number of MTC devices trying to conduct random access procedures may cause significant collisions and long delays. In this work, we present a new random access mechanism by splitting the contention-based preambles in LTE into two logically disjoint parts, one for the user equipment (UE) being paged and the other for the UEs not being paged. Since the IDs of paged UEs are known by the base station, a novel hash-based random access, which we call hint, is possible. The main idea is to pre-allocate preambles to paged UEs in a contention-free manner and confines non-paged UEs to contend in a separate region. We further build a mathematical model to find the optimal ratio of pre-allocated preambles. Extensive simulations are conducted to validate our results

Parent–Child Cohesion, Basic Psychological Needs Satisfaction, and Emotional Adaptation in Left-Behind Children in China: An Indirect Effects Model

This study aimed to validate an indirect effects model of parent–child cohesion in emotional adaptation (i.e., loneliness and depression) via basic psychological needs satisfaction in Chinese left-behind children as well as the applicability of the model to both genders. A cross-sectional study was conducted and included 1,250 children aged between 9 and 12 years (635 left-behind children and 615 non-left-behind children) from rural primary schools. The results showed that: (1) relative to non-left-behind children, left-behind children exhibited significantly higher loneliness and depression scores and greater disadvantages involving father–child cohesion, mother–child cohesion, and psychological needs satisfaction. (2) Father– and mother–child cohesion were significantly negatively correlated with loneliness and depression and significantly positively correlated with psychological needs satisfaction in left-behind children. (3) Through structural equation modeling showed that psychological needs satisfaction partially mediated the relationship between parent–child cohesion and emotional outcomes in left-behind children. (4) Through multi-group analyses showed significant gender differences in structural weighting between parent–child cohesion and emotional adaptation, in that parent–child cohesion in left-behind boys was a stronger negative predictor of unfavorable emotional outcomes relative to that observed in left-behind girls, while psychological needs satisfaction in left-behind girls was a stronger negative predictor of unfavorable emotional outcomes relative to that observed in left-behind boys. The implications of these findings for interventions directed at Chinese left-behind children were discussed

Regulation of hepatic autophagy by stress‐sensing transcription factor CREBH

Autophagy, a lysosomal degradative pathway in response to nutrient limitation, plays an important regulatory role in lipid homeostasis upon energy demands. Here, we demonstrated that the endoplasmic reticulum–tethered, stress‐sensing transcription factor cAMP‐responsive element‐binding protein, hepatic‐specific (CREBH) functions as a major transcriptional regulator of hepatic autophagy and lysosomal biogenesis in response to nutritional or circadian signals. CREBH deficiency led to decreased hepatic autophagic activities and increased hepatic lipid accumulation upon starvation. Under unfed or during energy‐demanding phases of the circadian cycle, CREBH is activated to drive expression of the genes encoding the key enzymes or regulators in autophagosome formation or autophagic process, including microtubule‐associated protein IB‐light chain 3, autophagy‐related protein (ATG)7, ATG2b, and autophagosome formation Unc‐51 like kinase 1, and the genes encoding functions in lysosomal biogenesis and homeostasis. Upon nutrient starvation, CREBH regulates and interacts with peroxisome proliferator–activated receptor α (PPARα) and PPARγ coactivator 1α to synergistically drive expression of the key autophagy genes and transcription factor EB, a master regulator of lysosomal biogenesis. Furthermore, CREBH regulates rhythmic expression of the key autophagy genes in the liver in a circadian‐dependent manner. In summary, we identified CREBH as a key transcriptional regulator of hepatic autophagy and lysosomal biogenesis for the purpose of maintaining hepatic lipid homeostasis under nutritional stress or circadian oscillation.—Kim, H., Williams, D., Qiu, Y., Song, Z., Yang, Z., Kimler, V., Goldberg, A., Zhang, R., Yang, Z., Chen, X., Wang, L., Fang, D., Lin, J. D., Zhang, K. Regulation of hepatic autophagy by stress‐sensing transcription factor CREBH. FASEB J. 33, 7896–7914 (2019). www.fasebj.orgPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154423/1/fsb2fj201802528r-sup-0001.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154423/2/fsb2fj201802528r.pd

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Increasing interpretability in XAI: Addressing the design principles for interactive XUIs to increase interpretability in XAI for end-users

Recent advancements in artificial intelligence (AI), particularly in deep learning, have significantly enhanced AI capabilities but have also led to more complex and less interpretable algorithms. This research addresses the challenge of Explainable AI (XAI) by focusing on enhancing the interpretability of AI decisions through the use of Explainable User Interfaces (XUI). The study identifies two primary knowledge gaps: the predominance of XAI research targeting technically skilled users, neglecting the end-user who often lacks technical expertise, and the insufficient exploration of user-centric design principles in real-world XUI applications.The research adopts the Design Science Research Method (DSRM) to develop an XUI tailored for the FOKUS project, which uses Electrocardiogram (ECG) data to detect myocardial infarctions. The study emphasises the strategic application of interactive design principles such as complementary naturalness, flexibility in explanation methods, and responsiveness through progressive disclosure to improve the system’s interpretability. Notably, sensitivity to context and mind, though not initially implemented, emerged as a critical design principle from the analysis and was subsequently positioned at the pinnacle of a restructured pyramid model of design principles.Key findings highlight the effectiveness of the selected design principles in enhancing interpretability and underscore the importance of involving stakeholders early in the development process to align the XAI and XUI with end-user needs. The research proposes a structured design approach framework for XUI, involving sequential phases from pre-XAI to XUI design, to systematically integrate user feedback and improve the design iteratively. The proposed framework restructured pyramid model of the design principles aim to guide future developments in XAI and XUI, enhancing their practical application and effectiveness in various contexts.Management of Technology (MoT

Novel Fractional Grey Prediction Model with the Change-Point Detection for Overseas Talent Mobility Prediction

Overseas students constitute the paramount talent resource for China, and, hence, overseas talent mobility prediction is crucial for the formulation of China’s talent strategy. This study proposes a new model for predicting the number of students studying abroad and returning students, based on the grey system theory, owing to the limited data and uncertainty of the influencing factors. The proposed model introduces change-point detection to determine the number of modeling time points, based on the fractional-order grey prediction model. We employed a change-point detection method to find the change points for determining the model length, based on the principle of new information priority, and used a fractional order accumulated generating operation to construct a grey prediction model. The two real data sets, the annual number of students studying abroad and returning students, were employed to verify the superiority of the proposed model. The results showed that the proposed model outperformed other benchmark models. Furthermore, the proposed model has been employed to predict the tendencies of overseas talent mobility in China by 2025. Further, certain policy recommendations for China’s talent strategy development have been proposed, based on the prediction results

Mixed Treatments Comparison of Oral Nutrition Interventions for Blood Immune Cell Parameters in Cancer Patients: Systematic Review and Network Meta-Analysis

Oral nutrition interventions are commonly applied as an assistant therapeutic approach, which could affect the balance of the immunological response but with mixed evidence. The objective of this study is to identify the potential of different oral nutrition interventions for blood immune cell parameters in cancer patients. Randomized controlled trials, which were published in peer-reviewed journals in the language of English, and which identified the effects of different oral nutrition interventions on cancer patients, were screened and included in the databases of PubMed, Medline, Embase, and Web of Science. White blood cell count (WBC), lymphocyte count, CD4/CD8, and neutrophil count were selected as outcome measures. For the result, 11 trials were included. The agreement between authors reached a kappa value of 0.78. Beta-carotene supplementation has a high potential in inducing a positive effect on blood immune cell parameters for cancer patients (first positive for WBC and CD4/CD8, second positive for lymphocyte count), as well as a combination of physical exercise and hypocaloric healthy eating intervention (first positive for lymphocyte and neutrophil count, second positive for WBC). Oral nutrition supplementations with a single substance have less potential to provide a positive effect on blood immune cell parameters for cancer patients (glutamine: 0.30 and 0.28 to be the last selection for WBCs and lymphocytes; Omega 3: 0.37 to be the last selection for WBCs; Protein: 0.44 to be the last selection for lymphocytes; Zinc: 0.60 to be the last selection for neutrophils). In conclusion, the programs of immunonutrition therapy for different cancer patients might be different. The past perception that mixed oral nutritional supplementations are superior to oral nutritional supplements with a single substance might be wrong and the selection of oral nutritional supplementation need cautiousness. A combination of physical exercise might have a positive effect but also needs a higher level of evidence. Registration Number: CRD42021286396

Novel Fractional Grey Prediction Model with the Change-Point Detection for Overseas Talent Mobility Prediction

Overseas students constitute the paramount talent resource for China, and, hence, overseas talent mobility prediction is crucial for the formulation of China’s talent strategy. This study proposes a new model for predicting the number of students studying abroad and returning students, based on the grey system theory, owing to the limited data and uncertainty of the influencing factors. The proposed model introduces change-point detection to determine the number of modeling time points, based on the fractional-order grey prediction model. We employed a change-point detection method to find the change points for determining the model length, based on the principle of new information priority, and used a fractional order accumulated generating operation to construct a grey prediction model. The two real data sets, the annual number of students studying abroad and returning students, were employed to verify the superiority of the proposed model. The results showed that the proposed model outperformed other benchmark models. Furthermore, the proposed model has been employed to predict the tendencies of overseas talent mobility in China by 2025. Further, certain policy recommendations for China’s talent strategy development have been proposed, based on the prediction results